Pumpkin Pancake Recipe | My Bizzy Kitchen

By electricdiet / September 15, 2021

Sneaking vegetables into your diet is easy with this pumpkin pancake recipe!

zucchini pumpkin pancakes with canned apples

Recently I met with a nutritionist.  First, she wanted me to track my grams of sugar each day, which was around 20 grams per day (a little higher if I ate more fruit).  Secondly she suggested that I eat more vegetables.  I know I am not alone in this problem, so I’ve been trying to think of creative ways to sneak them in as if I am a toddler.  This pumpkin pancake recipes is a great example.

What is the secret to fluffy pancakes?

The key to fluffy pancakes is allowing the baking powder a chance to do it’s magic.  Simply let the batter sit at room temperature for 30 minutes before cooking.  That’s it!

pumpkin pancake recipe batter

How do you know when to flip pancakes?

After you let the batter sit for 30 minutes, using a 1/3 cup measure per pancake, place the batter in a non-stick skillet.  As soon as you see bubbles start to form on the top of the pancake, it’s ready to flip.

this is a photo of a pancake that is ready to flip

How to add more vegetables to your diet?

Recently I asked that same question to my followers on Instagram and love all the ideas!

  1.  Adding a salad to one meal a day.
  2.  Vegetable stirfry.
  3.  Using cauliflower rice in place of brown/white rice.
  4.  Adding frozen spinach to smoothies.
  5.  Using sauteed veggies like mushrooms, carrots and celery to pasta sauce – once blended, you’ll never know!
  6.  Roasting vegetables at the beginning of the week to add to omelets or a quick side dish.
  7.  Making vegetable soup with veggies you have on hand.

Ingredients you’ll need for these pancakes:

  • flour (I used self-rising but regular flour works!)
  • salt
  • baking powder – the key to fully pancakes!
  • baking soda
  • cinnamon
  • ginger (I used a tablespoon of fresh ginger, but 1 teaspoon of ground ginger works)
  • canned pumpkin (not to be confused with canned pumpkin pie filling)
  • zucchini
  • almond milk (any milk works)
  • eggs
  • non-calorie sweetener (I used Truvia)


  • 1.5 cups self-rising flour (regular flour is fine too!)
  • 1/2 teaspoon salt
  • 1 teaspoon baking soda
  • 1 teaspoon baking powder
  • 1 teaspoon ground cinnamon
  • 1 tablespoon fresh ginger, finely chopped (or 1 teaspoon ground ginger)
  • 1 cup canned pumpkin puree
  • 2 cups shredded zucchini
  • 3/4 cup unsweetened almond milk (or your favorite milk)
  • 2 large eggs
  • 1/3 cup Truvia no calorie sweetener (or any non-calorie sweetener of choice)


  1. Mix everything together. Don’t overmix.
  2. Let the batter sit 30 minutes to let the baking powder do it’s magic.
  3. Cook over medium low heat, using 1/3 cup measure per pancake, and cook 2-3 minutes a side.
  4. I only use one skillet so it takes me about 20-30 minutes to make a batch.
  5. These keep in the fridge for up to a week. They can also be frozen. Freeze the pancakes on a cookie sheet for 30 minutes. Store in a ziptop bag. You can go straight from freezer to a toaster to reheat.


On all WW plans, these pancakes are 2 points each no matter how many you have. If you count calories or macros, each one is 94 calories, 1.5 fat, 16.5 carbs, 1.3 fiber and 3.6 protein.

Did you make this recipe?

Please leave a comment on the blog or share a photo on Instagram

These pancakes are light, fluffy and delicious.  For the topping I heated 1/4 cup sugar free pancake syrup with 1/3 cup no sugar added apple pie filling.  This is the perfect breakfast after apple picking – it screams fall!

this is a stack of pumpkin pancakes recipe

Can pancakes be frozen and reheated?

Absolutely!  This pumpkin pancake recipe will stay fresh in the fridge for up to five days.  To freeze, lay the pancakes on a cookie sheet in a single layer and freeze for 30 minutes.  Next, place the frozen pancakes in a ziptop bag – that way they won’t stick together and you can pull out as many as you want.  Simply go from freezer to toaster and run the toaster twice to thaw and reheat.  They will literally taste like they were freshly made.

If pancakes are your jam, check out some of my other pancake recipes!

What’s your favorite pancake?



I am a widowed 52 year old trying to figure out my life after losing my husband after a long illness.

Cooking and being in the kitchen feeds my soul!

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Ketosis Vs. Ketoacidosis: The Differences Explained

By electricdiet / September 13, 2021

If you live with diabetes, you are probably well aware of the dangers of letting your blood sugar go too high and slipping into diabetic ketoacidosis, or DKA. 

This dangerous condition can become fatal if left untreated. 

What a lot of people (with and without diabetes) may not be aware of, however, is that there is a similar biological condition known as ketosis, that has nothing to do with dangerously high blood sugars and generally feeling awful. 

This article will explain in greater depth what ketoacidosis is, what ketosis is, and how the two conditions are different. 

What is ketoacidosis? 

Diabetic ketoacidosis, or DKA, is a serious short-term complication of diabetes that develops when the blood turns acidic from too many ketones in the body, from extremely high blood sugar levels.

Ketoacidosis happens when the body cannot metabolize any glucose ingested because there is no insulin available in the body. This results in a rapid deterioration and requires immediate emergency medical attention.

Ketoacidosis can happen quickly from a complete lack of insulin (due to an insulin pump failure or forgetting to take an injection before a meal), or develop more slowly, due to regular sickness and stubborn high blood sugars over the course of several days. 

Ketoacidosis occurs in people with type 1 diabetes much more often than people living with type 2 diabetes. In fact, about 25% of patients are in DKA at diagnosis with type 1 diabetes. 

Although rare, some people who don’t have diabetes can get ketoacidosis too. It can be caused by chronic alcoholism, starvation, or an overactive thyroid. 

What are the symptoms of ketoacidosis? 

Some common symptoms of ketoacidosis are the following. Please seek immediate emergency medical attention if you suspect you have ketoacidosis.

  • Bodyache and headache 
  • Extreme thirst and dry mouth 
  • Frequent urination 
  • High blood sugar
  • Ketones in the urine 
  • Nausea 
  • Vomiting 
  • Blurry vision
  • Fruity-smelling breath
  • Extreme fatigue 
  • Confusion 
  • Weight loss (rapid and dangerous) 
  • Flushed face 

How dangerous is ketoacidosis? 

Ketoacidosis is extremely dangerous and must be addressed immediately by a medical professional. 

Call 911 or go to your local emergency department if you think you are in DKA and/or have a blood sugar of 250 mg/dL or higher and moderate to high ketones for several hours and cannot get your blood sugar down. 

If left untreated, ketoacidosis can lead to diabetic coma and death. 

Everyone with diabetes should have at-home ketone strips to test (via blood or urine) for ketones in their system and to help prevent the development of DKA. 

What is ketosis? 

Ketosis, on the other hand, is a harmless biological condition that occurs when the body starts to rely on fat for energy instead of glucose. 

Once the body burns this fat, it creates ketones that the body can then use for fuel. This can cause rapid and sustained weight loss (similar to the weight loss seen at the diagnosis of diabetes, but this weight loss is harmless). 

This usually occurs when people eat an extremely low carbohydrate diet, such as the ketogenic diet, intermittent fasting, or (occasionally) the Paleo diet. 

Ketosis can be achieved after about 3-4 days of eating 50 or fewer carbohydrates per day. 

Symptoms of ketosis

Although the only way to be sure that the body is in ketosis is to take a ketone test, there are some symptoms that you may be experiencing the “keto flu”, or experiencing the initial side effects of sugar and carbohydrate withdrawal. 

These will pass within a few days but include: 

  • Brain fog 
  • Insomnia
  • Irritability 
  • Headache
  • Constipation (and sometimes diarrhea) 
  • Sugar cravings
  • Muscle aches
  • Elevated heart rate
  • Dehydration 
  • Nausea 
  • Cramping
  • Bad breath (known as “ketosis” breath

Drinking plenty of water can help alleviate the symptoms of ketosis, and most of them should completely go away after a few days. 

One severe side effect that some people see from long-term ketosis is the increased incidence of kidney stones. Supplementing your diet with a potassium citrate tablet can help prevent this. 

Is ketosis dangerous?

For people without any chronic conditions and who are not pregnant, ketosis is not dangerous. 

A person can be in ketosis and not have dangerously high blood sugars, nor be in any grave danger.

Ketosis is not recommended for women who are pregnant, are trying to become pregnant, and those who are breastfeeding, as ketosis can affect breast milk supply. 

Eating for a state of ketosis is also not recommended for people who are experiencing: 

  • Pancreatitis
  • Liver failure
  • Carnitine deficiency
  • Porphyria
  • Disorders that affect the metabolism of dietary fat 

Some people who stay in ketosis long-term may experience low blood sugar, fatigue, fatty liver, chronic constipation, raised cholesterol levels, and increased incidence of kidney stones, but this is not guaranteed. 

Always check with your doctor before beginning any new eating plan. 

Can someone with diabetes be in ketosis without being in ketoacidosis?

Yes! While you should always talk with your doctor before beginning any new eating regimen, there are plenty of people with diabetes who adhere to a ketogenic diet and stay in ketosis, while maintaining a normal blood sugar range

In fact, several studies attest to the health benefits of being on a ketogenic diet/staying in ketosis if you have diabetes. A two-year study found that people with diabetes following the ketogenic diet lost an average of 26 pounds.

A different study found that the ketogenic diet helped improve people’s insulin sensitivity by 75%.

If followed for 3 months or longer, staying in ketosis via an extremely low carbohydrate diet has even been found to lower hba1c levels in people with diabetes.

Be aware that being on a ketogenic diet and/or achieving ketosis will affect the amount of insulin and/or diabetes medication you require, so always check with your doctor before making any changes to your eating habits or medications. 

You can learn more about the ketogenic diet here: The Ketogenic Diet and Diabetes: The Definitive Guide

The key difference between ketosis and ketoacidosis 

While both conditions result in the development of ketones in the body, the difference between ketosis and ketoacidosis is the mechanism behind the development of ketones. 

Ketones along with high blood sugar (ketoacidosis) is an extremely dangerous condition that can lead to diabetic coma or death, if left untreated. 

It usually only happens to people with type 1 diabetes, although people with type 2 diabetes can develop the condition as well, along with people who are suffering from an overactive thyroid, starvation, or alcoholism. 

The ketones formed from the body being in a state of ketosis, on the other hand, result from the body using fat instead of carbohydrates for fuel, oftentimes from eating a very low carbohydrate diet or fasting. 

Both conditions lead to weight loss, but for very different reasons. 

If you’re interested in exploring ways to achieve ketosis and you live with diabetes, check with your doctor first before making any changes to your dietary and/or medication regimens. 

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When I Dip, You Dip, We Dip – Corn Dip!

By electricdiet / September 11, 2021

Weekend Entertaining with Corn Dip

There seems to always be a reason to have friends hang out – a weekend grill-out, rooting on your team, or just good old-fashioned game night. Whatever the gathering – this Corn Dip from Holly Clegg’s trim&TERRIFIC KITCHEN 101: Secrets to Cooking Confidence cookbook, is the perfect appetizer to whip together. This dip is the epitome of fresh + convenience = homemade: you probably have these easy pantry-friendly ingredients already stocked. When entertaining, make it easy on yourself by making ahead of time, refrigerate and reheat in the microwave until heated through. Diabetic-friendly, and definitely a people-pleaser, this creamy dip with a kick is a sure-fire hit!

Corn Dip
A quick and easy, economical dip that’s creamy, crunchy, and spicy in each bite.

    Servings10 (1/4 cup) servings


    • 1tablespoon

      olive oil

    • 2cups

      frozen cornthawed

    • 1/2cup

      chopped onion

    • 1/3cup

      chopped red bell pepper

    • 1/2cup

      chopped green onions

    • 2tablespoons

      chopped jalapenofound in jar

    • 2tablespoons

      light mayonnaise

    • 1/3cup

      nonfat sour cream

    • 2/3cup

      shredded reduced-fat sharp Cheddar cheese

    • salt and pepper to taste

    1. In large nonstick skillet, heat oil and add corn cooking over medium heat, stirring until golden brown, about 5 minutes.

    2. Add onion and pepper, sauté until tender, 3-4 minutes.

    3. Add green onions, jalapeño, mayonnaise, sour cream and cheese, stirring until heated and bubbly; cheese is melted. Season to taste.

    Recipe Notes

    Calories 89, Calories from Fat 39%, Fat 4g, Saturated Fat 1g, Cholesterol 7mg, Sodium 108mg, Carbohydrates 11g, Dietary Fiber 1g, Total Sugars 3g, Protein 4g, Dietary Exchanges: 1/2 starch, 1 fat

    Terrific Tip: If making ahead of time, refrigerate and reheat in microwave until heated.

    Serve Up Your Favorite Dips

    3 Tier Oval Bowl Set3 Tier Oval Bowl Set3 Tier Oval Bowl SetChip and Dip Serving Bowl SetChip and Dip Serving Bowl SetChip and Dip Serving Bowl SetMud Pie Circa Chip N Dip Set, WhiteMud Pie Circa Chip N Dip Set, WhiteMud Pie Circa Chip N Dip Set, White

    Cajun Red Beans rice Red beans recipe Mardi Gras Theme party

    Dig Into Louisiana Red Bean Dip

    Whether you are watching football at home or tuning in to the latest reality tv show, dig into Louisiana Red Bean Dip recipe. The most delicious way to start your menu! A dip that has the savory flavors reminiscent of Cajun red beans rice dish celebrating the festivities of Mardi Gras. Plus, this speedy appetizer, Red Beans recipe is full of heart healthy fiber.


    tailgating recipes

    You will love Holly’s 25 Favorite Football Tailgating Recipes available for only $1.99! Included are dips, pick-ups, hearty food and the best of Holly’s sweet treats.  Best of all, it comes with a SHOPPING LIST so all the work is done for you from your menu to your grocery run.

    Healthier and EASY-TO-MAKE recipes with the nutritional information.  If you have health concerns, gluten-free and diabetic-recipes are highlighted.  DOWNLOAD  this great menu of party option.

    Get All of Holly’s Healthy Easy Cookbooks

    The post When I Dip, You Dip, We Dip – Corn Dip! appeared first on The Healthy Cooking Blog.

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    Elevated First-Trimester Neutrophil Count Is Closely Associated With the Development of Maternal Gestational Diabetes Mellitus and Adverse Pregnancy Outcomes

    By electricdiet / September 9, 2021


    Chronic low-grade inflammation plays a central role in the pathophysiology of gestational diabetes mellitus (GDM). To investigate the ability of different inflammatory blood cell parameters in predicting the development of GDM and pregnancy outcomes, 258 women with GDM and 1,154 women without were included in this retrospective study. First-trimester neutrophil count outperformed white blood cell count and the neutrophil-to-lymphocyte ratio in the predictability for GDM. Subjects were grouped based on tertiles of neutrophil count during their first-trimester pregnancy. The results showed that as the neutrophil count increased, there was a stepwise increase in GDM incidence as well as in glucose and glycosylated hemoglobin levels, HOMA for insulin resistance (HOMA-IR), macrosomia incidence, and newborn weight. Neutrophil count was positively associated with prepregnancy BMI, HOMA-IR, and newborn weight. Additionally, neutrophil count was an independent risk factor for the development of GDM, regardless of the history of GDM. Spline regression showed that there was a significant linear association between GDM incidence and the continuous neutrophil count when it was >5.0 × 109/L. This work suggested that the first-trimester neutrophil count is closely associated with the development of GDM and adverse pregnancy outcomes.


    Gestational diabetes mellitus (GDM), one of the most common metabolic disorders in pregnant women, is defined as any degree of glucose intolerance with onset or first diagnosis during pregnancy (1). Over the past few decades, the prevalence of GDM has increased, coinciding with rising rates of obesity and type 2 diabetes (T2DM). In 2010, GDM prevalence in the U.S. was estimated to be 4.6–9.2% (2). In China, GDM prevalence has been reported to be 9.3–18.9% (3). The presence of GDM is associated with higher risk of adverse consequences for both the mother (preeclampsia, cesarean section, development of T2DM after delivery) and infant (macrosomia with consequent shoulder dystocia and birth injury, neonatal hypoglycemia, and childhood obesity) (48). Several traditional factors, including a family or personal history of diabetes, previous adverse pregnancy outcome, glycosuria, and obesity, are associated with GDM, but the exact pathophysiology of GDM remains elusive.

    Previous studies have shown that low-grade chronic inflammation plays a crucial role in the pathophysiology of GDM and T2DM (914). The abnormal increase of the inflammatory blood cell parameters, such as white blood cell (WBC) and neutrophil count, neutrophil-to-lymphocyte ratio (NLR), and platelet count, usually serve as simple markers of inflammation, and all have been investigated for their ability to predict GDM in a previous study with a small sample size, but results were inconsistent (1519).

    This study investigated the potential correlation of inflammatory blood cell parameters with GDM and adverse pregnancy outcomes. First, we found that the first-trimester neutrophil count outperformed WBC count and NLR as a risk factor and showed better diagnostic predictability for GDM. In addition, our cohort study showed that as the first-trimester neutrophil count increased, the incidence of GDM, blood glucose level, HOMA for insulin resistance (HOMA-IR), and adverse pregnancy outcomes increased in a stepwise manner. The first-trimester neutrophil count was closely associated with prepregnancy BMI, HOMA-IR, and newborn weight and was also an independent risk factor for development of GDM. Finally, a significant linear association between continuous neutrophil count and the incidence of GDM was analyzed by spline regression.

    Research Design and Methods

    Study Population

    From May 2015 to July 2018, 1,781 pregnant women were retrospectively screened at the GDM Care Center of Shanghai Fifth People’s Hospital, Fudan University. The retrospective analysis process followed the procedure described in Fig. 1. Women were excluded from the study for any of the following: 1) any infectious disease 2 weeks before the blood cell test; 2) abnormal liver or renal function; 3) presence of viral infection or positive carrier status (hepatitis B virus, syphilis, and HIV); 4) preexisting diabetes; 5) chronic hypertension; or 6) multiple gestation. Finally, 1,412 women (1,154 without GDM and 258 with GDM) were collected for the analysis.

    Figure 1
    Figure 1

    Flowchart of this study. DM, diabetes.

    Data Collection and Laboratory Assessments During Pregnancy

    At the first visit, gestational age was calculated based on the date of last menstruation or first-trimester ultrasonography. After an overnight fast for 12 h, blood samples were collected for counts of blood cells (XN9000 Automatic Blood Cell Analyzer; Sysmex, Kobe, Japan) and biochemical parameters tests (Cobas 8000 Automatic Biochemical Analyzer; Roche, Basel, Switzerland). Blood pressure and anthropometric parameters were measured, and a questionnaire was also completed. The patient questionnaire obtained information of last menstruation, method of conception, parity, obstetric history, family history of diabetes, previous history of GDM, and prepregnancy weight. Prepregnancy BMI was calculated as the prepregnancy weight in kilograms divided by the square of height in meters. After delivery, details including gestational age at delivery, mode of delivery, newborn weight, and sex of the neonate were recorded by medical staff.

    Oral Glucose Tolerance Test

    All subjects, with the exception of those diagnosed with overt diabetes or GDM in early pregnancy, underwent routine screening for GDM at 24–28 weeks’ gestation according to a 75-g oral glucose tolerance test (OGTT) (1). OGTT was performed in the morning after an overnight fast of at least 8 h. Diagnosis of GDM was made when fasting blood glucose (FBG) was ≥5.1 mmol/L, the 1-h level was ≥10.0 mmol/L, or the 2-h level was ≥8.5 mmol/L, respectively.

    Intervention for GDM

    Therapeutic regimen started as soon as the individual was diagnosed with GDM. At first, lifestyle intervention was initiated, and insulin was then supplemented in addition to lifestyle intervention if the goals of glycemic control were not reached (fasting glucose <5.3 mmol/L, 1-h postprandial glucose <7.8 mmol/L, or 2-h postprandial glucose <6.7 mmol/L).

    Calculation of HOMA-IR, HOMA of β-Cell Function, and QUICKI

    The values for HOMA-IR, HOMA of β-cell function (HOMA-β), and QUICKI were determined from FBG and insulin concentration using the following formula (20): HOMA-IR = (I0 [µIU/mL] × G0 [mmol/L])/22.5; HOMA-β = 20 × (I0 [µIU/mL]/[G0 (mmol/L]) − 3.5; QUICKI = 1/(logI0 [µIU/mL] + logG0 [mg/dL]). I0 is the level of fasting insulin, and G0 is the level of FBG.

    Statistical Analysis

    To avoid the potential bias due to uneven distribution of covariates between women with or without GDM, a case-control matching method was used to match variables that included prepregnancy BMI, age, and parity. Matching tolerance was 0.5, 2, and 0, respectively. To compare the predictability for GDM among the inflammatory blood cell parameters, logistic regression analysis and receiver operating characteristic curves were performed.

    To further validate the association of neutrophil count with GDM and pregnancy outcomes, a cohort including the same subjects as the case-control study was established in which patients were divided into three groups by tertiles of neutrophil count: lowest group (<5.30 × 109/L), middle group (5.30–6.80 × 109/L), and highest group (>6.80 × 109/L). Descriptive statistics for the studied variables are presented as means ± SD for normally distributed variables, median (interquartile range [IQR]) for nonnormally distributed variables, and frequency (percentage) for categorical variables. ANOVA and the Student t test were used to identify the difference in the mean between groups. Bonferroni correction was applied in multiple comparisons. Nonnormally distributed variables were analyzed by Kruskal-Wallis one-way ANOVA or Wilcoxon tests. HOMA-IR, HOMA-β, and QUICKI were log-transformed previously for t tests or ANOVA. Linear correlation between neutrophil count and HOMA-IR and prepregnancy BMI and newborn weight were assessed by simple and multivariate linear regression analysis. Continuous association of neutrophil count with GDM incidence was determined by spline regression analysis. To determine whether neutrophil count was an independent risk factor, logistic regression analysis was performed with GDM classified in a binary manner (presence/absence) as the dependent variable. Neutrophil count and traditional risk factors, including age, previous GDM history, prepregnancy BMI, triglyceride (TG) level, and weight gain before GDM was diagnosed as the possible risk factors, were entered into logistic regression analysis in all mothers, and the same analyses were repeated in the subgroup of mothers with no previous GDM (women without GDM history and nulliparous). All data were analyzed using SPSS 24.0 software (IBM, Armonk, NY). A two-tailed P < 0.05 was considered to indicate statistical significance.

    Data and Resource Availability

    The data sets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.


    Characteristics of Women With and Without GDM in All Subjects and Matched Case-Control Study

    GDM developed in 258 women (18.27%) among the 1,412 subjects, and women with older age, previous GDM history, or GDM family history were more likely to develop GDM (Table 1). Compared with women without GDM, patients with GDM had a much higher level of prepregnancy BMI (P < 0.001), first-trimester WBC count (9.37 ± 2.07 vs. 8.57 ± 2.00 × 109/L, P < 0.001), neutrophil count (7.06 ± 1.76 vs. 6.03 ± 1.70 × 109/L, P < 0.001), and NLR (3.93 ± 1.32 vs. 3.36 ± 1.13, P < 0.001), whereas the difference in lymphocyte count or platelet count was not significant. In addition, patients with GDM had much higher second-trimester TG (P = 0.010), HDL (P = 0.011), FBG (P < 0.001), 1-h blood glucose (BG) (P < 0.001), 2-h BG (P < 0.001), HbA1c (P < 0.001), HOMA-IR (P < 0.001), and weight gain before GDM screening (P = 0.022) and lower QUICKI (P < 0.001) and HOMA-β (P < 0.001) than women without GDM. Unexpectedly, patients with GDM had lower LDL than women without GDM (2.81 ± 1.07 vs. 3.11 ± 0.88 mmol/L, P = 0.001). There was no difference in weight gain during the whole pregnancy between women with and without GDM, and we found most patients with GDM (86.8%) simply needed lifestyle intervention, while only 34 women (13.2%) with GDM required insulin treatment. Obviously, mothers with GDM tended to deliver heavier newborns (3,527.2 ± 562.7 vs. 3,361.6 ± 476.5 g, P < 0.001) and had a higher rate of delivering macrosomic infants than mothers without GDM (21.4% vs. 7.7%, P < 0.001) (Table 1).

    Table 1

    Characteristics of women with and without GDM in all subjects and in the matched case-control study

    A 1:1 case-control matching procedure was performed to avoid the potential bias of covariates that were not evenly distributed between women with and without GDM. After matching for age, pregnancy BMI, and parity, there were no differences in TG and weight gain before GDM screening between women with and without GDM. There remained a significantly higher WBC count (9.27 ± 2.04 vs. 8.57 ± 1.92 × 109/L, P < 0.001), neutrophil count (7.00 ± 1.74 vs. 6.05 ± 1.61 × 109/L, P < 0.001), and NLR (3.93 ± 1.34 vs. 3.45 ± 1.21, P = 0.001) as well as higher glucose level (P < 0.001) and HOMA-IR (P = 0.001) and lower HOMA-β (P < 0.001) and QUICKI (P < 0.001) in women with GDM compared with control subjects (Table 1).

    Higher Neutrophil Count Outperformed WBC Count and NLR as an Independent Risk Factor and Diagnostic Predictive Factor for GDM Development and Incidence of Macrosomia

    To compare the predictive capability of metric WBC count, neutrophil count, and NLR as risk factors for GDM development, logistic regression analysis with enter selection was performed separately in a matched case-control study. We found neutrophil count had the highest odds ratio (OR) value as an independent risk factor for the development of GDM (OR 3.60; 95% CI 2.02–6.41 in the highest tertile vs. the lowest tertile; P < 0.001), regardless of GDM history (OR 3.70; 95% CI 2.05–6.66; P < 0.001) compared with WBC count (OR 2.40; 95% CI 1.38–4.17; P = 0.002 in all mothers; OR 2.75; 95% CI 1.56–4.86; P < 0.001 in mothers without GDM history) and NLR (OR 2.77; 95% CI 1.58–4.88; P < 0.001 in all mothers; OR 2.45; 95% CI 1.40–4.30; P = 0.002 in mothers without GDM history) (Table 2). Furthermore, we also found neutrophil count and combined basal factors (age, previous GDM history, prepregnancy BMI, and TG) had the highest area under receiver operating characteristic curve for predicting GDM compared with WBC count and NLR (0.787, 0.776, and 0.774, respectively) (Supplementary Fig. 1).

    Table 2

    Logistic regression analysis to determine the risk factors for development of GDM in matched case-control study

    Besides, neutrophil count was also an independent risk factor for the incidence of macrosomia (OR 4.09; 95% CI 1.04–16.13 in the highest tertile vs. the lowest tertile; P = 0.044) corrected by prepregnancy BMI and weight gain during the whole pregnancy, rather than WBC count and NLR (Supplementary Table 1).

    Comparison of Parameters in the First Trimester, the Second Trimester, and at Delivery Among Three Groups Categorized by Tertiles of Neutrophil Count in the Cohort Study

    Subjects were divided into three groups according to tertiles of neutrophil count in the first trimester: lowest group (<5.30 × 109/L), middle group (5.30–6.80 × 109/L), and highest group (>6.80 × 109/L). There was a step-wise increase in the incidence of GDM (9.1%, 14.7%, and 28.2%; P < 0.001), level of prepregnancy BMI, alanine aminotransferase, 1-h BG (6.68 ± 1.60 vs. 6.99 ± 1.77 vs. 7.60 ± 2.29 mmol/L; P < 0.001), 2-h BG (6.07 ± 1.29 vs. 6.39 ± 1.45 vs. 6.87 ± 1.81 mmol/L; P < 0.001), HbA1c (4.9 ± 0.3 vs. 5.0 ± 0.3 vs. 5.1 ± 0.5%; P < 0.001), and HOMA-IR (P < 0.001) across the lowest, middle, and highest groups, respectively (Table 3). Likewise, macrosomia, neonatal weight, placental weight, and the incidence of cesarean delivery increased as neutrophil count increased (Table 4).

    Table 3

    Comparison of parameters in the first trimester and the second trimester among three groups categorized by tertiles of neutrophil count in the cohort study

    Table 4

    Comparison of parameters at delivery among three groups categorized by tertile of neutrophil count in the cohort study

    First-Trimester Neutrophil Count Was Closely Associated With Prepregnancy BMI, HOMA-IR, and Newborn Weight

    To investigate the correlation between neutrophil count and insulin resistance or newborn weight, correlation analysis was performed. Simple linear regression analyses were performed to determine the association of neutrophil count during the first trimester with prepregnancy BMI, HOMA-IR, and newborn weight. There was a significant and linear correlation for neutrophil count with prepregnancy BMI [β = 0.29; F(1, 1,085) = 27.51; adjusted R2 = 0.02; P < 0.001] (Fig. 2A), HOMA-IR [β = 0.07; F(1, 426) = 19.88; adjusted R2 = 0.04; P < 0.001] (Fig. 2B), and newborn weight [β = 0.03; F(1, 1,039) = 10.27; adjusted R2 = 0.01; P = 0.001] (Fig. 2C). Multiple linear regression analysis adjusting for confounding factors was performed to analyze the association between neutrophil count and prepregnancy BMI, HOMA-IR, and newborn weight. There was a significant linear association of neutrophil count with prepregnancy BMI (P < 0.001) and HOMA-IR (P = 0.045) (Supplementary Table 2).

    Figure 2
    Figure 2

    Simple linear regression analysis between the first-trimester neutrophil (N) count and prepregnancy BMI, HOMA-IR, and newborn weight. The neutrophil count showed a significant and moderate linear correlation with prepregnancy BMI [β = 0.29; F(1, 1,085) = 27.51; adjusted R2 = 0.02; P < 0.001] (A), HOMA-IR [β = 0.07; F(1, 426) = 19.88; adjusted R2 = 0.04; P < 0.001] (B), and newborn weight [β = 0.03; F(1, 1,039) = 10.27; adjusted R2 = 0.01; P = 0.001] (C).

    Neutrophil Count Was an Independent Risk Factor for the Development of GDM

    To determine independent risk factors for the development of GDM, tertiles of neutrophil count, GDM history (divided into no previous GDM, previous GDM, and nulliparous), prepregnancy BMI, age, TG, and weight gain before GDM was diagnosed were entered into logistic regression analysis with enter selection. The risk of developing GDM in the highest tertile neutrophil count increased 3.71-fold compared with the lowest tertile neutrophil count (P < 0.001). Risk of developing GDM in women with a previous history of GDM was significantly higher than in those without (OR 58.16; 95% CI 18.60–181.86; P < 0.001), and women with a higher prepregnancy BMI (OR 1.12; 95% CI 1.04–1.20; P = 0.004), age (OR 1.16; 95% CI 1.09–1.23; P < 0.001), and TG level (OR 1.19; 95% CI 1.03–1.37; P = 0.020) also had a tendency to develop GDM. Furthermore, the independent risk factors in women without a history of GDM (including those with no previous GDM and nulliparous) were also determined, and neutrophil count (OR 3.66; 95% CI 1.78–7.56 in highest tertile vs. in lowest tertile; P < 0.001) remained a risk factor for development of GDM independent of prepregnancy BMI, age, and TG level (Table 5).

    Table 5

    Logistic regression analysis to determine the risk factors for development of GDM in the cohort study

    Continuous Neutrophil Count in the First Trimester Was Closely Associated With the Incidence of GDM

    After adjusting for GDM history, prepregnancy BMI, age, and TG, a spline model showed a significant relationship between continuous neutrophil count during the first trimester and GDM incidence. The risk of developing GDM increased when the neutrophil count was >5.0 × 109/L (Fig. 3).

    Figure 3
    Figure 3

    Continuous association of the neutrophil count in the first trimester with the incidence of GDM. Adjusted for GDM history, prepregnancy BMI, age, and TG.


    This retrospective case-control and cohort study is the first one to confirm the closest association of neutrophil count with development of GDM in a large sample size. Many studies have demonstrated increased inflammatory markers during pregnancy compared with a nonpregnant state characterized by elevated WBC count and neutrophil count (19,21). Nevertheless, pregnant women generally have a steady state of pro- and anti-inflammatory cytokines, although this balance is disturbed in some pathological states, including obesity and insulin resistance (2224). A growing number of studies have described the central role of inflammation in GDM. In their 2004 cohort study, Wolf et al. (17) showed that women who developed GDM had a much higher leukocyte count than those who did not.

    Neutrophils, which constitute the largest fraction of WBCs, have been found to be involved in chronic metainflammatory states such as diabetes, nonalcoholic fatty liver disease, and atherosclerosis (2527). Although previous studies have produced inconsistent results, Yilmaz et al. (15) showed that NLR was significantly higher in patients with GDM compared with pregnant women with normal glycemic levels and was a powerful predictor of GDM, whereas Sargın et al. (16) showed no predictive ability of NLR. In our case-control study, after matching the possible confounder factors, we found that neutrophils, WBCs, and NLR were all associated with the development of GDM but that the neutrophil count had the highest OR and possessed the most predictive value. As we know, the WBC count is largely equal to the sum of the neutrophil count and the lymphocyte count, NLR is the ratio of neutrophil count to lymphocyte count. Because there is no difference of lymphocytes, which may dilute the impact of neutrophils on GDM, the WBC count and NLR were inferior to the neutrophil count in the role of GDM development and its outcomes. These results support the important pathological role of innate immune cells in the development of diabetes (28,29). Further analyses of the relationship between neutrophil count and GDM were performed in the cohort study. We found the incidence of GDM increased progressively with the increase of the neutrophil count, which was also an independent factor for GDM development. Moreover, fully adjusted spline regression showed a significant correlation of continuous neutrophil count with GDM incidence, and the risk abruptly increased when the neutrophil count was >5.0 × 109/L. All of these demonstrated a close association of the first-trimester neutrophil count with GDM development.

    From a functional perspective, Talukdar et al. (30) and Mansuy-Aubert et al. (31) both revealed that neutrophils contribute to the etiology of chronic inflammation and insulin resistance via secreted neutrophil elastase (NE) by the degradation of insulin receptor substrate 1 (IRS1). Recently, Stoikou et al. (32) reported that patients with GDM had increased neutrophil activity with elevated neutrophil extracellular traps (NETs) and NE levels in vitro. Lou et al. (33) found that high levels of neutrophil gelatinase-associated lipocalin (NGAL) in plasma and subcutaneous adipose tissue were associated with insulin resistance in GDM. Our study showed a significant positive association between neutrophil count and HOMA-IR, supporting the crucial role of neutrophils in insulin resistance. All of these results demonstrate that neutrophils may contribute to GDM development by mediating insulin resistance and that neutrophil-derived NE, NETs, and NGAL may serve as the potential targets.

    Another important finding in our study was that an increased neutrophil count was also associated with adverse pregnancy outcomes. A higher neutrophil count was an independent risk factor for macrosomia corrected by prepregnancy BMI and weight gain during the whole pregnancy in the case-control study. Women with the highest tertile of neutrophil count had the highest risk for macrosomia and cesarean delivery in the cohort study. The developmental overnutrition hypothesis suggests that maternal hyperglycemia and obesity predispose offspring to obesity and metabolic dysfunction and may have been transferred from the mother through the placenta (34,35), although the underlying mechanism is elusive. An increased neutrophil count may lead to a rise in NE and NETs in the placenta, as suggested in the Stoikou et al. (32) study; therefore, we hypothesize that neutrophil count may play a crucial role in this programming process via NE and NETs.

    Moreover, our study found that patients with GDM had much higher levels of TG and lower levels of LDL, consistent with previous studies (3640). The precise mechanism of lower LDL in women with GDM was unclear. This might be attributed to higher concentration of estrogen and insulin resistance in women with GDM.

    There were some limitations of this study. First, all subjects were derived from one center, which may have led to biased results. We also acknowledge that a mechanistic insight into the potentially pathophysiological role of neutrophils in GDM development and offspring metabolic dysfunction is lacking in this clinical study. Further studies using reliable rodent GDM models to delineate the function of neutrophils, especially NE, NETs, and NGAL, are warranted.


    This study demonstrated that the first-trimester neutrophil count was closely associated with GDM development and adverse pregnancy outcomes, especially macrosomia. The neutrophil count was an independent risk factor for GDM development when it was >5.0 × 109/L.

    Article Information

    Funding. This study received support from the Natural Science Foundation of China (81700510), the Medical Key Faculty Foundation of Shanghai (ZK2019B15), Health Profession Clinical Funds of the Shanghai Municipal Health Commission (201940295), the Science Foundation of the Fifth People’s Hospital of Shanghai (2019WYZD02, 2018WYZD04), and the Science and Technology Planning Project of Hangzhou City (20170533B43).

    Duality of Interest. No potential conflicts of interest relevant to this article were reported.

    Author Contributions. T.S. wrote the manuscript and researched data. F.M. and H.D. contributed to discussion and reviewed and edited manuscript. H.Z. contributed to data collection. M.Y., R.Z., Z.Y., and X.H. contributed to data collection and database establishment. J.L. and S.Z. reviewed and edited the manuscript. S.Z. researched data. S.Z. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Prior Presentation. Parts of this study were presented in abstract form at the 79th Scientific Sessions of the American Diabetes Association, San Francisco, CA, 7–11 June 2019.

    • Received September 30, 2019.
    • Accepted April 16, 2020.

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    Apple Spiced Overnight Oats – Diabetic Foodie

    By electricdiet / September 7, 2021

    Diabetes-friendly meal-prepping doesn’t get any easier (or more delicious) than apple spiced overnight oats! Perfect for a nutritious grab-and-go breakfast that will energize your morning.

    Close-up of a white bowl of oats topped with pecans with a second bowl in the background

    Overnight oats are such an easy way to meal-prep for breakfast. On top of that, oatmeal is a great option for people living with diabetes!

    That’s why I love making these apple spiced overnight oats with hemp hearts, chia seeds, and Greek yogurt. Combined with the shredded apple and cinnamon, it’s such a delicious way to energize your morning.

    In all honesty, the trickiest part about making this recipe is remembering to soak the oats. Pro tip: put a sticky note on your cabinet to remind you before bed.

    Besides that, this make-ahead breakfast truly couldn’t be easier! Just mix the ingredients, let it sit in the refrigerator for at least two hours, and enjoy.

    If you’ve been looking for a way to simplify your morning, give these overnight-soaked oats a try. The irresistible flavor and power-packed ingredients may turn it into your new favorite way to start the day.

    How to make apple spiced overnight oats

    Who can resist a nutritious and tasty recipe that only takes five minutes to prep? Let’s see how it’s done!

    Ingredients for recipe in separate bowls and ramekins, as seen from above

    Step 1: In a 2-cup mason jar or similar sized container, stir together the hemp hearts, oats, chia seeds, and cinnamon.

    Hemp hearts, oats, chia seeds, and cinnamon in a jar with a spoon, as seen from above

    Step 2: Mix in the Greek yogurt and shredded apple.

    Shredded apple and greek yogurt added to the jar, as seen from above

    Step 3: Add the milk and stir until the mixture is well combined.

    Ingredients for overnight oats mixed together in a glass jar, as seen from above

    Step 4: Place the oats in the refrigerator and allow to chill for at least 2 hours or overnight.

    Step 5: Top with pecans before serving.

    That’s it! Just throw everything together the night before and you’ll have this amazing breakfast waiting for you in the morning.

    Finished oats in two white bowls topped with pecans on a white serving tray

    Variations for your oats

    There are so, so, SO many ways to make this recipe. Don’t hesitate to get creative with your add-ins or toppings!

    Prefer chia seeds over hemp hearts, or vice versa? You can adjust the ratio to your liking, or completely omit one and add more of the other if you want.

    Want to have some fun with the toppings? Instead of pecans, you could try chopped walnuts, slivered almonds, or even pumpkin seeds. Some chopped apple or pear would be great on top as well.

    Looking for some sweetness? Try vanilla Greek yogurt instead of plain for a yummy alternative.

    A spoonful of oats with two bowls of oats topped with pecans, an empty glass jar, and two apples in the background


    This recipe is ready in as little as two hours, but you can store it in the refrigerator for up to three days. Just make sure you use a jar with a screw-top lid or other airtight container.

    Want to have this meal on-the-go? After you mix all the ingredients, divide everything into two or three containers. That way, you can easily grab a serving on your way out the door.

    Finished oats topped with pecans in two white bowls on a white serving tray

    Other healthy make-ahead breakfast recipes

    Looking for more nutritious breakfasts that you can make ahead of time? Meal-prepping is such a great way to simplify your morning! Here are a few of my favorite recipes I know you’ll enjoy:

    You can also check out this round-up of my favorite 10 Diabetic Smoothie Recipes for even more healthy ways to start your day!

    When you’ve tried this recipe, please don’t forget to let me know how you liked it and rate the recipe in the comments below!

    Recipe Card

    Apple spiced overnight oats in a white bowl topped with pecans on a white serving tray, as seen from above

    Apple Spiced Overnight Oats

    Meal-prepping doesn’t get any easier (or more delicious) than apple spiced overnight oats! Perfect for a nutritious grab-and-go breakfast that will energize your morning.

    Prep Time:5 minutes

    Chill Time:2 hours

    Total Time:2 hours 5 minutes

    Author:Diabetic Foodie

    Servings:2 servings


    • In a 2-cup mason jar or similar sized container, stir together the hemp hearts, oats, chia seeds, and cinnamon.

    • Mix in the Greek yogurt and shredded apple.

    • Add the milk and stir until the mixture is well combined.

    • Place the oats in the refrigerator and allow to chill for at least 2 hours or overnight.

    • Top with pecans before serving.

    Recipe Notes

    This recipe is for two servings of overnight oats.
    Make sure to let your oats chill in the refrigerator for at least 2 hours, but you can store them for up to 3 days in an airtight container.
    For a grab-and-go breakfast, mix together the ingredients, then separate into 2 or 3 containers before storing.

    Nutrition Info Per Serving

    Nutrition Facts

    Apple Spiced Overnight Oats

    Amount Per Serving

    Calories 278
    Calories from Fat 143

    % Daily Value*

    Fat 15.9g24%

    Saturated Fat 3.4g21%

    Trans Fat 0g

    Polyunsaturated Fat 9.9g

    Monounsaturated Fat 1.7g

    Cholesterol 3.8mg1%

    Sodium 13.6mg1%

    Potassium 308.2mg9%

    Carbohydrates 19.2g6%

    Fiber 5.3g22%

    Sugar 7.1g8%

    Protein 15.3g31%

    Vitamin A 0IU0%

    Vitamin C 0mg0%

    Calcium 0mg0%

    Iron 0mg0%

    Net carbs 13.9g

    * Percent Daily Values are based on a 2000 calorie diet.

    Course: Breakfast

    Cuisine: American

    Diet: Diabetic, Gluten Free

    Keyword: apple overnight oats, easy breakfast recipes, gluten-free, spiced overnight oats

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    Black Bean Chili with Sweet Potatoes

    By electricdiet / September 5, 2021

    Use sweet potatoes as the meat!  This vegetarian black bean chili is so hearty and filling, I promise you won’t miss the beef.

    How do you make black bean chili from scratch?

    You can make black bean chili from dried beans, but I prefer using canned beans.  My favorite grocery store Mariano’s sells canned beans 2 cans for $1 every three weeks and I stock up.  If you don’t like black beans, any canned beans would work: garbanzo beans, kidney beans, etc.

    This chili tastes as if it’s been simmering for hours.  The secret is the canned chipotle peppers – just one gives such a depth of flavor.  Beware though – some chipotle peppers are hotter than others.  I’d start with half a chili and add more after tasting.

    Black Bean Chili with Sweet Potatoes


    • avocado oil spray
    • 2 medium sweet potatoes
    • 4 tsp minced garlic
    • 2 Tbsp chili powder
    • 4 tsp ground cumin
    • 1 tsp. ground chipotle pepper
    • 1/4 tsp table salt
    • 3 cup(s) water
    • 28 oz canned black beans, rinsed
    • 2 cup(s) canned tomatoes
    • 2 tsp fresh lime juice
    • 1 Tbsp cilantro, chopped
    • 2 Tbsp canned chipotle peppers, (one whole pepper)


      1. Heat avocado oil in a large stock pot and bring to medium-high heat. Add diced sweet potato and cook, stirring often, about 4 minutes.Add garlic, chili powder, chipotle and salt and cook, stirring constantly, until fragrant, about 30 seconds.
      2. Add water, bring to a simmer, cover, reduce heat to maintain a gentle simmer and cook until potato is tender, 10 to 12 minutes. Add canned tomatoes. (If you don’t like chunks like I do, puree at this point). Add beans, tomatoes and lime juice and return to a simmer. Cook for an additional 45 minutes.
      3. Garnish with nonfat Greek yogurt and shredded cheddar cheese


    On #wwteampurple this is zero points, on #wwteamblue it’s 3 points and on #wwteamgreen its 5 points.

    Nutrition Information:

    Yield: 4

    Serving Size: 1

    Amount Per Serving:

    Calories: 307Total Fat: 6gSaturated Fat: 1gTrans Fat: 0gUnsaturated Fat: 4gCholesterol: 0mgSodium: 1069mgCarbohydrates: 53gFiber: 19gSugar: 7gProtein: 15g

    Did you make this recipe?

    Please leave a comment on the blog or share a photo on Instagram

    There are so many chili recipes on my blog – check out it!

    Best Buffalo Chicken Chili (this won $10,000 in a nationwide recipe contest in 2013)

    No Cook Chili!  Just add pantry ingredients are heat in the microwave before eating.

    Pumpkin Chicken Chili – this one screams fall!

    Beef and Chipotle Chili – so good!

    What is your favorite kind of chili?


    I am a widowed 52 year old trying to figure out my life after losing my husband after a long illness.

    Cooking and being in the kitchen feeds my soul!

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    How to Prepare for Very Low Blood Sugar

    By electricdiet / September 3, 2021

    Do you have a low blood sugar plan?

    If you live with insulin-dependent diabetes, low blood sugar is an unavoidable part of life and something to prepare for by always having carbohydrates like glucose tablets or juice with you.

    But low blood sugar can sometimes creep dangerously low, which is why we should also prepare for severe low blood sugars or situations where we simply cannot eat more carbohydrates.

    Historically, we’ve had very limited options when it comes to treating those scary severe lows, but once Gvoke® (glucagon injection), the first pre-filled glucagon became available, we finally had a ready-to-use option.

    I had a chance to sit down with Paloma Guerrero (aka GlitterGlucose), who has been living with type 1 diabetes since 2013, to discuss her experiences with severe lows and how to properly prepare for a very low blood sugar emergency.

    This post is sponsored by Xeris Pharmaceuticals, Inc. the manufacturer of Gvoke HypoPen® (glucagon injection).

    How to Prepare for Very Low Blood Sugar

    What is low blood sugar and why is it scary?

    Low blood sugar (Hypoglycemia) can feel different for different people, both when it comes to when we feel low and how the symptoms manifest.

    In a non-diabetic body, blood sugar levels rarely dip below 70 mg/dL, but if you manage your diabetes with insulin (or other blood sugar-lowering drugs) and if too much insulin is present in the body, blood sugars start to drop below normal levels.

    Without enough glucose (a form of sugar) in your bloodstream, your brain and entire body will struggle to function and most people will start feeling the symptoms of low blood sugar.

    If not treated with glucose, blood sugar can continue to drop, which can lead to a severe low blood sugar. A severe low blood sugar is defined as a situation where your blood sugar is so low that you need help from someone else to get your blood sugar back into a safe range.

    Paloma’s story

    Using a glucagon kit wasn’t something that was top of mind for Paloma until she experienced two very bad low blood sugars only a week apart. In one situation she was prepared and in one she was not.

    The first time, she was on a road trip with a friend. She had brought all of her diabetes supplies including Gvoke. Her friend knew where it was and how to use it should she need it.

    As they arrived at their hotel, Paloma checked her CGM and saw that she was 179 mg/dL (9.9 mmol/L), but within the next hour, she started to feel low. She felt sweaty and was shaking. She checked her CGM again and now her blood sugar was 52 mg/dL (2.9 mmol/L) and her CGM was showing an arrow pointing down, indicating her blood sugar was dropping.

    She started to eat her emergency low snacks, but this low felt different, and as her blood sugar continued to drop, she began to fear that she would pass out. At that point, her friend got the Gvoke for her.  Paloma injected it into her thigh and felt a sense of relief knowing she had taken a medicine proven to bring blood sugar up and that she was going to be OK.

    Her blood sugar steadily went up and topped out at 237 mg/dL (13.2 mmol/L) before settling at 180 mg/dL (10 mmol/L).

    Gvoke was the right tool for that situation and it corrected her low without putting her on a 24-hour blood sugar roller coaster.  

    Box of Gvoke prefilled syringes

    What can happen when we don’t prepare for a low blood sugar

    The week after, Paloma and her friend were on the road again. This time she didn’t bring Gvoke (didn’t think she’d need it two weeks in a row) and as she was trending low during the trip, she ate all of her low snacks before they arrived at their hotel.

    That night, she woke up and checked her CGM to find that her blood sugar had dropped to 40 mg/dL (2.2 mmol/L), and that’s when her low symptoms intensified, and she started feeling poorly. But she was out of snacks and didn’t have her glucagon with her, so there was no way of treating the low.

    Her friend ran to the vending machine in the hallway, but it was malfunctioning. As time was ticking, her friend ended up punching through the glass of the machine to get to the snacks.

    At this point, they were both panicking and once her friend returned with the snacks, Paloma ate as much as she could. This experience left them both emotionally drained and she had to fight resistant high blood sugars throughout the following day.

    How these experiences have changed how she prepares for a low blood sugar

    Both severe low situations were scary, but even though her blood sugar dropped most aggressively during the first episode, it felt more controlled and less emotionally exhausting, as she knew she had the right treatment with her, which was Gvoke.

    Because it’s pre-mixed and ready to go with no visible needle, she wasn’t nervous about whether her friend would be able to use it should she need assistance.

    She has made some changes to her care after the two low episodes, and now wears a newer CGM model that will alert her if her blood sugars are dropping below range. She also carries Gvoke HypoPen with her at all times, tells those around her where it is, and is confident that those around her will be able to use it if needed.

    I asked if she had any words of advice for others living with diabetes and this is what she said:

    Emergencies happen. Even if we think it will never happen to us, sometimes it does, so to be prepared for such situations is incredibly important. And the thing is, we don’t have to be scared of low blood sugars if we’re prepared and have the right solutions with us. For me, knowing that Gvoke works, it’s ready to use, and that it doesn’t wreck my blood sugars has meant a world of difference, and now I don’t go anywhere without.”

    What is Gvoke HypoPen and how to get it

    Gvoke HypoPen can be used to treat a severe low blood sugar if you or someone around you experience one or more of the following:

    • have repeatedly tried correcting with food or drink and it isn’t working
    • are unable to swallow safely
    • feel like you/they might pass out
    • experience loss of consciousness or a seizure

    Gvoke is the only premixed glucagon approved for children 2 years and up and you don’t have to worry about measuring out the glucagon dose as Gvoke comes in 2 pre-measured doses – one dose for adolescents and adults (1.0 mg) and one for kids age 2 and above (0.5 mg).

    Kids younger than 12 who weigh at least 100 pounds may be prescribed the 1.0 mg dose.

    Gvoke is a prescription drug so you need to reach out to your doctor and request a prescription. If you have commercial insurance, you can also go directly through GvokeGlucagon.com and request a prescription to be delivered directly at your door.

    For a limited time, Xeris Pharmaceuticals is offering a $0 copay for commercially eligible patients to help ensure as many people as possible can access Gvoke HypoPen.


    Important Safety Information

    Gvoke is a prescription medicine used to treat very low blood sugar (severe hypoglycemia) in adults and kids with diabetes ages 2 year and above. It is not known if Gvoke is safe and effective in children under 2 years of age.

    Do not use Gvoke if you have a tumor in the gland on top of your kidneys (adrenal gland), called a pheochromocytoma; you have a tumor in your pancreas, called either insulinoma or glucagonoma; you are allergic to glucagon or any other inactive ingredient in Gvoke.

    Gvoke may cause serious side effects, including high blood pressure: Gvoke can cause high blood pressure in certain people with tumors in their adrenal glands. Low blood sugar: Gvoke can cause low blood sugar in certain people with tumors in their pancreas. Serious skin rash: Gvoke can cause a serious skin rash in certain people with a tumor in their pancreas called glucagonoma. Serious allergic reaction: Call your doctor or get medical help right away if you have a serious allergic reaction including rash, difficulty breathing, low blood pressure. US-SM-GVKHP-21-00081

    See Important Safety Information: http://bit.ly/2lJdBjY

    See Full Prescribing Information: http://bit.ly/2lRtk07

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    Berberine, a Natural Plant Product, Activates AMP-Activated Protein Kinase With Beneficial Metabolic Effects in Diabetic and Insulin-Resistant States

    By electricdiet / September 1, 2021


    Berberine has been shown to have antidiabetic properties, although its mode of action is not known. Here, we have investigated the metabolic effects of berberine in two animal models of insulin resistance and in insulin-responsive cell lines. Berberine reduced body weight and caused a significant improvement in glucose tolerance without altering food intake in db/db mice. Similarly, berberine reduced body weight and plasma triglycerides and improved insulin action in high-fat–fed Wistar rats. Berberine downregulated the expression of genes involved in lipogenesis and upregulated those involved in energy expenditure in adipose tissue and muscle. Berberine treatment resulted in increased AMP-activated protein kinase (AMPK) activity in 3T3-L1 adipocytes and L6 myotubes, increased GLUT4 translocation in L6 cells in a phosphatidylinositol 3′ kinase–independent manner, and reduced lipid accumulation in 3T3-L1 adipocytes. These findings suggest that berberine displays beneficial effects in the treatment of diabetes and obesity at least in part via stimulation of AMPK activity.

    Obesity poses a serious health risk contributing to the increased prevalence of a host of other diseases including type 2 diabetes, hyperlipidemia, hypercholesterolemia, and hypertension (1,2). Peripheral insulin resistance, which is often associated with obesity, is one of the earliest detectable defects identified in individuals at risk of type 2 diabetes. For this reason, pharmacologic agents that overcome insulin resistance, so-called insulin-sensitizing agents, have received considerable attention. In recent years, several major insulin-sensitizing agents have been developed, including the thiazolidinediones (TZDs) (3) and metformin (4). Both of these agents are thought to have beneficial effects, at least in part, by activating the stress-activated kinase AMP-activated protein kinase (AMPK) (5,6). AMPK is activated under a variety of conditions that signify cellular stress, usually in response to a change in the intracellular ATP-to-AMP ratio. Active AMPK orchestrates a variety of metabolic processes, most of which lead to reduced energy storage and increased energy production. TZDs and metformin are thought to activate AMPK via discrete mechanisms; TZDs stimulate the proliferation of small adipocytes that secrete adipokines such as adiponectin, which have been shown to stimulate AMPK activity in muscle and liver cells (7). Conversely, it appears that metformin activates AMPK directly via an ill-defined mechanism (8). These studies emphasize the potential utility of targeting the AMPK pathway in the treatment of type 2 diabetes and obesity.

    The use of natural products for the treatment of metabolic diseases has not been explored in depth despite the fact that a number of modern oral hypoglycemic agents such as metformin are derivatives of natural plant products (9,10). Although several traditional medicines have been reported to have antidiabetic effects (10), the molecular targets of such compounds have not been revealed, and a careful analysis of their mode of action in animal models has not been undertaken. In the present study, we have focused on berberine because this natural product has been reported in the Chinese literature and several recent studies (1114) to have beneficial effects in human type 2 diabetes, although its mechanism of action is not known. Here, we show that in vivo administration of berberine has insulin sensitizing as well as weight- and lipid-lowering properties in both db/db mice and in high-fat–fed rats. Strikingly, berberine acutely stimulated AMPK activity in both myotubes and adipocytes in vitro, contributing to enhanced GLUT4 translocation in myotubes and reduced lipid mass in adipocytes. Based on these studies, we propose that berberine may have a major application as a new treatment for obesity and/or insulin resistance in humans.


    Mouse experiments.

    All experiments were approved by the Seoul National University Animal Experiment Ethics Committee. Obese and diabetic C57BLKS/J-Leprdb/Leprdb male mice were housed at 22 ± 2°C, 55 ± 5% relative humidity, with a light/dark cycle of 12 h. Food (Purina Mills) and water were given ad libitum. From 12 weeks of age, berberine (Wako, Osaka, Japan) was injected intraperitoneally (5 mg · kg body wt−1 · day−1) into the mice for 26 days between 1400 and 1600. Thereafter, the brain, liver, right subcutaneous fat, epididymal fat tissues, interscapular brown adipose tissue, and skeletal muscle were dissected. After the dissection, the specimens were immediately frozen in liquid nitrogen and stored at −80°C.

    Rat experiments.

    Wistar rats (250 g) supplied by the Animal Resources Center (Perth, Australia) were acclimatized in communal cages at 22°C, with a 12-h light 12-h dark cycle (lights on at 0600) for 1 week and had access to a standard chow diet (Gordon’s Specialty Stock Feed, Sydney, Australia) and water ad libitum. Rats were then randomly assigned to receive either the standard chow diet as the control group (CH group) or a high-fat (60% calories as saturated fat) diet for 4 weeks (15). After 2 weeks of feeding, rats were randomly assigned to receive oral administration of either vehicle (0.5% methylcellulose) or berberine (380 mg · kg−1 · day−1) by gavage for the last 2 weeks. Body weight and food intake were recorded daily. For euglycemic-hyperinsulinemic clamps (insulin infusion 0.25 units · kg−1 · h−1), jugular and carotid cannulae were implanted 7 days previously, and animals were studied over 2 h in the conscious state after 5–7 h fasting, as previously described (16). All experimental procedures were approved by the Garvan Institute Animal Experimentation Ethics Committee and were in accordance with the National Health and Medical Research Council of Australia Guidelines on Animal Experimentation.

    Cell culture and GLUT4 translocation assay.

    3T3-L1 cells were cultured at 37°C in Dulbecco’s modified Eagle’s medium (DMEM) containing 10% bovine calf serum in an atmosphere of 10% CO2. The differentiation of 3T3-L1 cells was induced as described previously (17). L6 myoblasts up to passage 15 were cultured in α-minimal essential medium supplemented with 10% heat-inactivated fetal calf serum (FCS) at 37°C in 10% CO2. For differentiation into myotubes, cells were cultured in α-minimal essential medium supplemented with 2% heat-inactivated FCS at 37°C in 10% CO2 and were maintained in this medium postdifferentiation. Myotubes were used for experiments 5–7 days after differentiation. To express HA-GLUT4 in L6 cells, myoblasts were infected with retrovirus as previously described (18) and differentiated as described above. The GLUT4 translocation assay was performed essentially as previously described (19).

    RNA preparation and Northern blot analysis.

    Total RNA was prepared with TRIzol (Life Technologies-BRL) according to the manufacturer’s instructions. Northern blot analyses were conducted in a previously described manner (17).

    Measurement of triglycerides, free fatty acids, and cholesterol.

    Adipocytes were lysed, and the levels of intracellular triglycerides and free fatty acids were determined with commercial kits as described by the manufacturer (Sigma-Aldrich, St. Louis, MO). Blood samples were also collected from both rats and mice for the measurement of plasma levels of cholesterol and triglycerides. Liver samples from rats were used for the measurement of triglyceride content as previously described (15).

    Histological analysis and morphometry.

    The adipose tissues from the vehicle-treated controls or the berberine-treated db/db mice were embedded in a tissue-freezing medium (Leica) and frozen in liquid nitrogen immediately after decapitation and stored at −80°C. Tissue sections (50 μm) were prepared with a cryostat microtome and mounted on gelatin-coated glass slides. After paraformaldehyde fixation, they were stained with hematoxylin and eosin and photographed at ×100 magnification. The sectional areas of white adipose tissue (WAT) were analyzed for the purpose of quantifying the number and size of adipocytes.

    Western blot analysis.

    Protein samples denatured in SDS sample buffer (125 mmol/l Tris-HCl, pH 6.8, 50% glycerol, 2% SDS, 5% β-mercaptoethanol, and 0.01% bromophenol blue) were subjected to SDS-PAGE and blotted onto polyvinylidene difluoride (Millipore) membranes. Blotted membranes were blocked with 5% skim milk in Tris-buffered saline containing 0.1% Tween 20 for 1 h and then incubated with primary antibodies against AMPK (Cell Signaling Technology), phosphoAMPK (Thr172) (Cell Signaling Technology), acetyl-CoA carboxylase (Upstate), and phosphoACC (Upstate) for 16 h at 4°C. After three washes in Tris-buffered saline containing 0.1% Tween 20, the membranes were incubated with anti-mouse or anti-rabbit IgG and horseradish peroxidase–linked antibodies for 2 h. Immunoreactive signals were detected with the WEST-1 Western blot detection system (Intron, Kyungki-Do, Korea) and quantified with a LuminoImager (LAS-3000) and Science Lab 2001 Image Gauge software (Fuji Photo Film).

    Luciferase reporter assay.

    HEK293 cells were transfected 1 day before confluence by the calcium phosphate method described previously (20). All the transfection experiments were performed in duplicate and repeated independently at least three times.

    Statistical comparisons.

    Data were compared using paired Student’s t tests or ANOVA as appropriate and are presented as means ± SE.


    Effects of berberine in db/db mice.

    To investigate the in vivo metabolic properties of berberine, we initially examined its effects when administered to db/db mice because these animals exhibit marked obesity as well as impaired glucose tolerance. Berberine was administered daily (5 mg · kg−1 · day−1) intraperitoneally for 3 weeks to 12-week-old db/db mice. Body weight was significantly reduced in berberine-treated animals (Fig. 1A). Whereas the vehicle-treated mice showed normal body weight gain during the experimental period (Fig. 1B), berberine treatment resulted in a gradual loss (∼13%) of body weight over the same period (Fig. 1B). Importantly, food intake was not significantly different between vehicle and berberine-treated animals. Consistent with this, the expression of several hypothalamic neuropeptides, known to be involved in regulating food intake, were not significantly affected by berberine treatment (Figs. 1C–E). Gross inspection of berberine-treated mice indicated a clear reduction in adipose tissue mass (Fig. 1A). Quantification of this effect revealed that epididymal fat mass was reduced by ∼10% when normalized for body weight (Figs. 2A and B). Computer tomography revealed that both visceral and subcutaneous fat depots were similarly reduced by berberine (Fig. 2C). Histological studies indicated that the reduction in fat mass by berberine treatment was principally due to reduced adipocyte size (Fig. 2D). The average diameter of the white fat cells in control and berberine-treated db/db mice was 54.13 ± 9.74 and 31.96 ± 7.28 μm, respectively (Figs. 2E and F). These results suggest that berberine reduces fat mass primarily by decreasing the size of fat cells rather than fat cell number.

    To assess glucose homeostasis and insulin sensitivity in db/db mice treated with berberine, we next performed glucose tolerance tests. Berberine administration resulted in a significant reduction in fasting blood glucose levels combined with a significant improvement in glucose tolerance (Fig. 3). There was no significant effect on basal glucose or glucose tolerance in normal wild-type mice.

    Effects of berberine in high-fat–fed rats.

    Another animal model that is frequently used to study insulin resistance is the high-fat–fed rat. Berberine was administered orally to chow-fed and high-fat–fed rats for 2 weeks. Consistent with the data in db/db mice, we observed a significant reduction in body weight gain following berberine treatment (Fig. 3). This reduction in body weight was observed in both chow- and high-fat–fed animals, without a concomitant change in food intake (Figs. 3C and D). Importantly, berberine was well tolerated in the animals, as indicated by the fact that food intake was unaltered by the drug, and necropsy and histological analysis of major organs such as the liver and kidney revealed no adverse pathology or inflammation (data not shown).

    We next performed hyperinsulinemic-euglycemic clamp studies in control and high-fat–fed rats administered either vehicle or berberine (380 mg/day) by daily gavage for 2 weeks. Plasma triglycerides, measured in the basal state before the clamp, were significantly lowered in the high-fat–fed group treated with berberine (Fig. 3E). The untreated high-fat–fed group had a significantly lower clamp glucose infusion rate compared with the chow-fed group, demonstrating whole-body insulin resistance (Fig. 3F). Berberine treatment significantly lessened this insulin resistance in high-fat–fed rats, as indicated by an increased clamp glucose infusion rate (Fig. 3F). Plasma triglyceride and clamp glucose infusion rate were not altered by berberine treatment in normal chow-fed rats (Figs. 3E and F). We have also obtained preliminary data to show that insulin stimulated suppression of hepatic glucose output was enhanced following 2 weeks of treatment with berberine in rats (data not shown).

    Berberine alters the expression of metabolic genes in fat and muscle in vivo.

    To investigate the mechanism of berberine action on insulin action and body weight, we next assessed the effects of berberine on the expression of certain genes that are known to play a critical role in energy balance. As shown in Fig. 4A, the expression of a number of adipocyte-specific genes including fatty acid synthase (FAS), ADD1/SREBP1c (adipocyte determination and differentiation–dependent factor 1/sterol regulatory element–binding protein 1c), peroxisome proliferator–activated receptor (PPAR)γ, 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1), and aP2 was reduced in various WAT depots of berberine-treated mice. In contrast, the level of cyclin D kinase 5 mRNA was not significantly altered, indicating that the inhibitory effect of berberine on gene expression was restricted to adipogenic and lipogenic genes. Conversely, in skeletal muscle, the expression of uncoupling protein (UCP) 2 mRNA was significantly increased by berberine, while that of UCP3 was unchanged (Fig. 4B). In brown adipose tissue, the expression of PPARα mRNA also increased dramatically, while the mRNA of lipogenic genes such as FAS was reduced as in the case of WAT (Fig. 4C). Additionally, expression of PPARγ coactivator-1, a key regulator of several mitochondrial genes involved in adaptive thermogenesis, was substantially increased (Fig. 4C).

    To further investigate the effects of berberine on overall gene expression, we compared genome-wide expression profiles in the WAT of berberine-treated mice and control mice using DNA microarrays. The genes that responded reproducibly to berberine were categorized by their fold induction (>1.5-fold, 996 genes) or repression (<0.8-fold, 1,483 genes) (online appendix Table 1 [available at http://diabetes.diabetesjournals.org]). Most genes involved in lipogenesis were downregulated by berberine treatment; for example, FAS and fatty acid desaturase 3, which control the final step of triglyceride synthesis from malonyl-CoA to palmitate and from phosphatidic acid to triglycerides, respectively, decreased 0.59- and 0.27-fold, respectively. Interestingly, 11β-HSD1, a key enzyme linked to visceral obesity and metabolic syndrome, decreased 0.63-fold, and expression of most genes involved in carbohydrate metabolism was also reduced (online appendix Table 1). In contrast, the transcript level of enzymes related to energy dissipation, including glycerol kinase and acyl-CoA dehydrogenase, increased 4.0- and 2.2-fold, respectively. These results imply that berberine treatment in vivo results in an altered gene expression profile that would promote catabolism of high energy intermediates (online appendix Fig. 1).

    Berberine activates AMPK in adipocytes, myotubes, and liver.

    AMPK has previously been shown to play a key role as an energy sensor in metabolic tissues by coordinating both short- and long-term metabolic changes that lead to improved energy production and reduced energy storage (21). In view of the changes in gene expression observed with berberine treatment (Fig. 4), we hypothesized that this might be facilitated via activation of AMPK. To determine whether the effects of berberine that we have observed in animals could be mediated by activation of AMPK, we examined the effects of berberine on AMPK phosphorylation in adipocytes and myoblasts in vitro, since this has been shown to correlate with kinase activity. Furthermore, we also examined phosphorylation of ACC, as this is a major substrate of AMPK (2224). Intriguingly, the effects of berberine on AMPK activity in adipocytes were more pronounced than that of 5-aminoimidazole-4-carboxamide riboside (AICAR), a known AMPK agonist (Fig. 5A). As shown in Fig. 5A–C, AMPK phosphorylation and ACC phosphorylation were increased in myoblasts and adipocytes in vitro after short-term treatment with berberine and in liver after long-term berberine treatment of db/db mice.

    Berberine stimulates GLUT4 translocation in L6 myotubes.

    One of the major acute actions of AMPK is to stimulate GLUT4 translocation in muscle (25). As shown in Fig. 5D, insulin and the AMPK agonist AICAR increased the cell surface levels of GLUT4 by four- and threefold, respectively. In agreement with previous studies (26,27), the phosphatidylinositol (PI) 3′ kinase inhibitor wortmannin blocked insulin-stimulated GLUT4 translocation but had no effect on AICAR stimulation (Fig. 5D). Strikingly, berberine also stimulated GLUT4 translocation in L6 myotubes by more than threefold, and, like AICAR, this effect was unaffected by wortmannin (Fig. 5D). Consistently, we could not observe additive effects of berberine and insulin on GLUT4 translocation over periods of ≥2 h exposure to berberine (Fig. 5D).

    Effects of berberine on adipocytes.

    AMPK activation has been shown to lead to lipid lowering consistent with our in vivo data (28) (Fig. 3E). To further test this in vitro, we next treated 3T3-L1 cells with or without berberine during adipocyte differentiation and found that triglyceride accumulation was strongly inhibited (Fig. 6). Vehicle-treated adipocytes displayed normal differentiation, as indicated by the appearance of numerous intracellular lipid droplets. However, berberine caused a dramatic reduction in lipid droplet accumulation and adipogenic gene expression (Figs. 6A and B), implying that berberine would indeed attenuate adipocyte differentiation.

    We next investigated the effects of berberine on lipid metabolism in fully differentiated adipocytes. Berberine-treated 3T3-L1 adipocytes had significantly reduced levels of intracellular triglycerides and free fatty acids compared with vehicle-treated cells (Figs. 6C and D). To determine the molecular mechanism for the lipid-lowering properties of berberine in 3T3-L1 adipocytes, we measured the transcript levels of a number of adipocyte-specific genes. Consistent with the in vivo gene expression data (Fig. 4), the levels of most lipogenic transcripts, including FAS, ADD1/SREBP1c, PPARγ, C/EBPα, 11β-HSD1, and aP2, were decreased by berberine (Fig. 6E), whereas the expression of nonadipogenic genes, such as cyclin D kinase 5, was not affected. Berberine did not cause a significant loss of cell viability or affect the growth rate of NIH-3T3 fibroblasts (online appendix Fig. 2). Furthermore, we observed that berberine (15 μmol/l) significantly reduced GLUT4 mRNA expression as well as several lipogenic and adipogenic genes in 3T3-L1 adipocytes, suggesting that chronic administration of berberine could provoke dedifferentiation of adipocytes in vitro (online appendix Fig. 3).

    Berberine stimulates phosphorylation of p38 and PPARγ.

    Many of the genes that undergo a reduction in expression in response to berberine treatment are PPARγ-responsive genes. Thus, it is possible that berberine may inhibit the activity of PPARγ. It has previously been described that PPARγ transcriptional activity is regulated by phosphorylation and that the upstream kinase for this effect is p38 mitogen-activated protein kinase (MAPK) (2934). We also observed that phosphorylation of both p38 MAPK and PPARγ were increased by berberine in adipocytes (Fig. 7A). To confirm that berberine inhibits PPARγ activity, we next examined its effects in luciferase reporter assays. These studies demonstrated that berberine inhibited the transcriptional activity of PPARγ in a dose-dependent manner (Fig. 7B). The effect of berberine to inhibit PPARγ activity was quantitatively similar to that observed with bisphenal A diglycidyl ether, a known PPARγ antagonist (35).


    Berberine has been used as a therapeutic to treat a variety of human diseases in Korea, China, and possibly other Asian countries that practice the use of traditional medicines. Although its most common use is in the treatment of diarrhea and as an antitumor and antimicrobial agent (3639), there are some reports of its potential use for the treatment of human diabetes (13,40,41). In one clinical study, 60 patients with type 2 diabetes were treated with berberine for 1–3 months, and 90% of patients showed improvement in their clinical symptoms (11). Very recently, Kong et al. (42) described the cholesterol-lowering properties of berberine. In the present study, we have extended these previous investigations and provide evidence that berberine reduces body weight and lipid levels and improves insulin action in two separate animal models of insulin resistance. Most importantly, we show that berberine acutely activates AMPK activity in both adipocytes and myocytes, and within these cell types berberine induces a variety of metabolic effects consistent with AMPK activation. These include activation of GLUT4 translocation; increased phosphorylation of AMPK, ACC, and p38 MAPK; reduced lipid content in adipocytes; increased expression of genes involved in lipid oxidation; and decreased expression of genes involved in lipid synthesis.

    The present data indicate that AMPK is a major intermediate in facilitating the beneficial effects of berberine. These effects are likely manifest both as short- and long-term effects. The acute effects probably involve increased GLUT4 translocation in muscle cells and increased trafficking of free fatty acids into mitochondria via increased ACC phosphorylation, both of which contribute to glucose and lipid lowering. We could not observe acute effects of berberine on blood glucose, while AICAR was successful to reduce blood glucose acutely. However, acute administration of other AMPK agonists, such as metformin, also had no effect on blood glucose, suggesting that blood glucose–lowering action is not essential for AMPK agonist. The chronic effects involve changes in gene expression, which likely contribute to reduced fat cell differentiation and increased mitochondrial biogenesis, again contributing to lipid lowering, reduced fat mass, and improved insulin sensitivity. We have observed a significant reduction in the expression of lipogenic genes in adipose tissue following treatment with berberine either in vitro or in vivo. Moreover, our in vitro studies in 3T3-L1 cells showed that berberine inhibited adipocyte differentiation probably by inhibiting PPARγ activity. It is now well established that PPARγ is an important transcriptional regulator of adipogenesis (43,44). In addition, the activity of PPARγ can be regulated by a variety of mechanisms, including phosphorylation by members of the MAPK family (2931,33,34). In particular, p38 MAPK has been shown to enhance PPARγ phosphorylation, which leads to inhibition of its transcriptional activity, resulting in a blockade in fat cell differentiation (29,31). AMPK has been implicated as an upstream regulator of p38 MAPK (45), thus providing a link between the activation of AMPK and fat cell differentiation and control of lipogenic gene expression. Our data are consistent with such a mechanism because we have observed that berberine treatment increases the phosphorylation of AMPK, p38, and PPARγ in adipocytes, suggesting that this may be a major regulatory pathway by which this compound mediates its actions. It is also conceivable that this pathway plays an important role in lipogenesis in other tissues such as the liver because we also observed increased phosphorylation of AMPK and p38 in berberine-treated FAO rat hepatoma cells (W.S.K., Y.S.L., J.B.K., unpublished data). A further prediction from our work is that berberine leads to increased whole-body energy expenditure. Indeed, we observed that berberine-treated animals exhibited increased oxygen consumption and core body temperature (data not shown) with concurrent increase in the expression of genes involved in the control of energy expenditure, such as UCP2 (46,47). Similar metabolic adaptations to those described above have been ascribed to AMPK in other contexts (48,49), again supporting the conclusion that berberine mediates many of its metabolic actions via AMPK.

    It is intriguing to compare the metabolic effects of berberine with other insulin-sensitizing agents such as the TZDs or metformin. Based on the data presented here, berberine and metformin share a number of features in common. Metformin causes weight reduction, improved insulin sensitivity, and lipid lowering in both human and animal models of insulin resistance (50). A major mode of action of metformin is activation of AMPK, particularly in liver (51), although it has also been shown to stimulate AMPK activity in adipose tissue (52). The latter effect is particularly germane to the present studies because one of the major disadvantages of TZDs is that while they lead to improved insulin sensitivity and lipid lowering, they also lead to increased adiposity due to their stimulatory effects on adipocyte differentiation (53). In contrast, berberine and metformin have the opposite effects on adiposity. This may reflect the fact that berberine and metformin have a direct effect on AMPK activity in a variety of tissues, whereas TZDs principally activate AMPK in the liver indirectly via increased adiponectin secretion, while at the same time sequestering fatty acids in adipose tissue via the “lipid steal” effect (54).

    Collectively, these data are consistent with a model whereby berberine activates AMPK in multiple tissues, including adipose tissue and muscle (Fig. 7C). This increase blocks adipose tissue differentiation presumably via p38 MAPK–mediated phosphorylation of PPARγ and increases free fatty acid oxidation either directly by reducing ACC activity, thus allowing for increased trafficking of nutrients into the mitochondria, or indirectly via upregulation of genes that regulate energy expenditure. A major question arising from these studies concerns the mechanism by which berberine activates AMPK. It is highly unlikely that these effects are mediated indirectly via increased secretion of some cellular factor because we have observed rapid activation of AMPK in several cell lines in vitro. One possibility is that berberine directly effects the integrity of the mitochondria, perhaps via a similar mechanism to metformin, and this mechanism is currently under investigation.

    In conclusion, berberine, a purified component from a traditional oriental medicine, reduces whole-body adiposity and improves insulin sensitivity in two separate animal models of insulin resistance, at least in part, by activating AMPK in multiple cell types. Collectively, these effects lead to changes in biochemical processes and gene expression that lead to a net switch in the metabolic program of the organism to catabolism of fuel stores, an adaptation that may be of some benefit in the face of disorders characterized by insulin resistance.

    FIG. 1.
    FIG. 1.

    Effects of berberine on body weight and food intake. A: Gross appearance of whole body and abdomen of vehicle (DMSO, Control, left)-treated or berberine (BBR, right; 5 mg · kg−1 · day−1)-treated db/db mice. B: Changes of body weight with or without berberine. db/db mice were treated with vehicle (□; n = 16) or berberine (•; n = 17) for 26 days. **P < 0.001. C: Effects of berberine on food intake. db/db mice were treated with vehicle (□) or berberine (•). D: Quantitative RT-PCR analyses of NPY and POMC genes in the presence or absence of berberine from whole brain. E: Relative amounts of each mRNA were normalized with amounts of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA and are indicated as fold changes. NS, not significant.

    FIG. 2.
    FIG. 2.

    Effect of berberine on white adipose tissue mass. A: The weights of all tissues from vehicle-treated mice (□; male, n = 10) and berberine-treated mice (□; male, n = 15) normalized by total body weight. Data are mean ratios of the weight of each organ to total body weight (±SE). *P < 0.002. B: Appearance of epididymal WATs from vehicle- or berberine-treated mice. C: Computed tomography images of abdominal and thoracic regions of control (left) or berberine-treated (BBR) mice (right). Diamonds and triangles indicate subcutaneous fat and visceral fat, respectively. D: Histological analysis of subcutaneous WATs from control and berberine-treated mice. Samples were stained with hematoxylin and eosin and are photographed at ×100 magnification (bar = 50 μm). E: Distribution of fat cell sizes in WATs from control and berberine-treated mice. F: Average fat cell size. Values are means ± SE. **P < 0.001.

    FIG. 3.
    FIG. 3.

    Effects of berberine on in vivo metabolism in two animal models of insulin resistance. Wild-type and db/db mice were treated with berberine, and basal blood glucose (A) and glucose tolerance (B) were measured. db/db mice spontaneously develop basal hyperglycemia as shown in the control (db/db-Con) versus wild-type groups. A: Basal hyperglycemia was significantly reduced in db/db mice gavaged with berberine (BBR; 560 mg · kg−1 · day−1) for 7 days, compared with controls (vehicle-only gavage). B: Glucose tolerance test. Intraperitoneal bolus glucose (1 g/kg) was given to wild-type (Wt) mice, and glucose loads to db/db mice were then matched to the lean wild-type littermates. C–F: Berberine was also administered to chow-fed and high-fat–fed rats followed by measurement of body weight gain (C), food intake (D), basal plasma triglyceride (E), and whole-body insulin sensitivity as determined by hyperinsulinemic euglycemic clamp (F). Rats were gavaged with vehicle (Veh) or berberine (380 mg · kg−1 · day−1) for 2 weeks before (but not including) the acute clamp study. For clamp studies (insulin infusion 0.25 units · kg−1 · h−1), jugular and carotid cannulae were implanted 7 days previously and animals were studied over 2 h in the conscious state after 5–7 h fasting. Group sizes were 4–5 mice for A–B, >10 rats for C–E, and >6 for F. *P < 0.05; **P < 0.01 vs. corresponding control group.

    FIG. 4.
    FIG. 4.

    Effects of berberine (BBR) on expression of metabolic genes in fat and muscle. A: Northern blot analysis of gene expression in subcutaneous (S.C Fat), epididymal (Epi Fat), and perirenal fat (Peri Fat) tissues. B: Northern blot analyses of UCP2 and UCP3 mRNA in skeletal muscle (quadricopes). C: Northern blot analyses of FAS, PPARα, and PPARγ coactivator-1 (PGC1) mRNA in brown adipose tissue.

    FIG. 5.
    FIG. 5.

    Activation of AMPK and GLUT4 translocation by berberine. A: 3T3-L1 adipocytes were treated with DMSO, berberine (BBR; 5 μg/ml), or AICAR (0.5 mmol/l) after 16 h serum starvation with DMEM supplemented with 0.1% BSA for different time periods as indicated. AICAR was used as a positive control for activating AMPK. B: L6 myotubes were incubated under basal conditions or in the presence of berberine (BBR) or AICAR for 30 min. Total cell lysates were subjected to Western blot analysis using antibodies specific for phosphoAMPK, phosphoACC, and total AMPK. Representative blots are shown. C: AMPK activation by administration of berberine (BBR) in vivo. Berberine or vehicle (controls) was injected intraperitoneally (5 mg/kg) into 9-week-old db/db obese and diabetic mice every day for 3 weeks. Livers were removed, lysed, and immunoblotted with antibodies specific for phosphoAMPK, phosphoACC, total AMPK, and total ACC. Quantitative data represents the means ± SE for n = 6 in each group. D: L6 myotubes were incubated under basal conditions or in the presence of insulin for 15 min, berberine (BBR) for 30 min, or AICAR for 30 min. Wortmannin (100 nmol/l) was added 5 min before the addition of the different agonists. The cell surface levels of the HA-GLUT4 reporter were measured in myotubes using a fluorescence assay, and data are expressed as the amount of HA-GLUT4 at the surface as a percent of the total expression. Data shown are the means ± SE of four to five separate experiments.

    FIG. 6.
    FIG. 6.

    Effects of berberine on adipogenic gene expression and lipid metabolites. A: Microscopic views of 3T3-L1 cells. 3T3-L1 cells were differentiated into adipocytes in the absence or presence of berberine (BBR; 3 μmol/l). B: Northern blot analysis. Total RNA was isolated from 3T3-L1 adipocytes treated with DMSO (lane 1) or berberine (lane 2, 0.3 μmol/l; lane 3, 3 μm; and lane 4, 15 μmol/l) for 9 days. Blots were hybridized with adipocyte-specific gene probes. Expression of 36B4 was used as a loading control. C: Microscopic views of differentiated adipocytes treated without or with berberine (BBR; 15 μmol/l) for 72 h. D: Intracellular lipid content of adipocytes in the absence or presence of berberine (BBR; 15 μmol/l). E: Alteration of adipocyte gene expression by berberine (BBR). Total RNA was isolated from 3T3-L1 adipocytes treated with DMSO (lane 1) and berberine (15 μmol/l; lane 2 for 48 h and lane 3 for 72 h). Northern blots were analyzed with cDNA probes.

    FIG. 7.
    FIG. 7.

    Activation of AMPK and p38 MAPK and inhibition of PPARγ activity in adipocytes by berberine. A: Western blot analysis of AMPK, p38 MAPK, and PPARγ phosphorylation by berberine (BBR). Mouse primary adipocytes were isolated and treated with DMSO, berberine, or insulin for 20 min in DMEM supplemented with 0.1% BSA. B: h293 cells were transfected with DR-1-luciferase reporter construct along with PPARγ and RXRα expression vectors, as indicated. After 12 h serum starvation with DMEM media supplemented with 0.1% BSA, cells were treated with DMSO, rosiglitazone (100 nmol/l), bisphenol A diglycidyl ether (50 μmol/l), or berberine for an additional 12 h. C: Schematic model of berberine (BBR) in control of energy metabolism. Berberine stimulates fatty acid oxidation by activating AMPK and p38 and increasing PPARα, UCP2, and PPARγ coactivator-1 (PGC-1) in peripheral tissues. It also inhibits adipogenesis by suppressing the transcriptional activity PPARγ by increasing inhibitory phosphorylation of PPARγ.


    This work was supported in part by grants from the Molecular and Cellular Biodiscovery Research Program, the Stem Cell Research Center of the 21st Century Frontier Research Program, and the National Research Laboratory Program of Korea Science and Engineering Foundation. Y.S.L., W.S.K., K.H.K., and J.B.K. are supported by the BK21 Research Fellowship from the Ministry of Education and Human Resources Development. D.E.J. and E.W.K. are Senior Principal Research Fellows of the Australian National Health and Medical Research Council. A.G. is supported by a Young Garvan postdoctoral fellowship, and we are indebted to the Bill Ferris Foundation for generous support.

    We thank Dr. Kee Up Lee for help with computer tomography imaging.


    • Y.S.L. and W.S.K. contributed equally to this study.

      Additional information on this article can be found in an online appendix at http://diabetes.diabetesjournals.org.

    • The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

      • Accepted May 22, 2006.
      • Received January 4, 2006.


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    Smoked Salmon Spread – Diabetic Foodie

    By electricdiet / August 30, 2021

    This rich and creamy smoked salmon spread is always a crowd-pleaser! They’ll never know it only requires five main ingredients and three steps to make.

    Bowl of smoked salmon spread with crackers and cucumbers

    Don’t you love when you bring a dish to a party or get-together and suddenly everyone is asking you for the recipe?

    That’s what always happens with this smoked salmon spread… I even had a friend try to give me $50 once for a container to take home! That’s how you know you have a winner.

    The best part is that no one realizes how easy it is to make. You only need five ingredients plus freshly ground pepper, and everything comes together right in the food processor!

    The next time you want to impress friends and family or just enjoy a tasty spread all to yourself, this recipe is the one to try.

    How to make smoked salmon spread

    Would you believe this creamy spread comes together in just three simple steps?

    Ingredients for the recipe laid out on a cutting board

    Step 1: Place the cream cheese in a food processor and pulse until smooth.

    Step 2: Add the chopped smoked salmon, lemon juice, dill, chopped green onions, and pepper. Pulse until everything is incorporated.

    Ingredients in a food processor seen from above

    Step 3: Transfer the dip to a small bowl, cover, and refrigerate for at least an hour to allow the flavors to develop.

    That’s it! And after one bite, this might become your new go-to recipe.

    What to eat with this spread

    So what should you serve with this amazing little dish? it’s wonderful with keto cheese crackers, a good low-carb bread, or even some regular store-bought crackers (if you don’t mind the carbs)!

    For some lower-carb options, try cucumber rounds or celery sticks. Fresh veggies add a delicious crunch.

    I will also admit that I’m guilty of eating it right off a spoon.

    Knife gathering up some salmon spread from a bowl


    I will warn you that when shared with others, this salmon spread goes quickly!

    If you’re fortunate enough to have any leftover, store it covered in the refrigerator and enjoy within 3 days… if it lasts that long.

    Knife putting salmon spread on a cracker

    Other spread and dip recipes

    Who doesn’t love a tasty dip or spread to serve as an appetizer or a snack? They’re easy to make and can be served alongside almost any dish. Here are a few of my favorites that I know you’ll love:

    When you’ve tried this spread, please don’t forget to let me know how you liked it and rate the recipe in the comments below!

    Recipe Card

    Smoked Salmon Spread

    Smoked Salmon Spread

    This rich and creamy smoked salmon spread is always a crowd-pleaser! They’ll never know it only requires five main ingredients and three steps to make.

    Prep Time:2 minutes

    Cook Time:3 minutes

    Chill:1 hour

    Total Time:1 hour 5 minutes

    Author:Diabetic Foodie



    • Place the cream cheese in a food processor and pulse until smooth.

    • Add the chopped smoked salmon, lemon juice, dill, chopped green onions, and pepper. Pulse until everything is incorporated.

    • Transfer the dip to a small bowl, cover, and refrigerate for at least an hour to allow the flavors to develop.

    Recipe Notes

    This recipe is for 8 servings. Each serving is 2 tablespoons of spread.
    I recommend serving with crackers or veggies.
    Any extra can be stored covered in the refrigerator for up to 3 days.

    Nutrition Info Per Serving

    Nutrition Facts

    Smoked Salmon Spread

    Amount Per Serving (2 tablespoons)

    Calories 47
    Calories from Fat 28

    % Daily Value*

    Fat 3.1g5%

    Saturated Fat 1.7g11%

    Trans Fat 0g

    Polyunsaturated Fat 0g

    Monounsaturated Fat 0g

    Cholesterol 10.7mg4%

    Sodium 140.3mg6%

    Potassium 1.6mg0%

    Carbohydrates 1.2g0%

    Fiber 0.3g1%

    Sugar 1.1g1%

    Protein 3.1g6%

    Vitamin A 0IU0%

    Vitamin C 0mg0%

    Calcium 0mg0%

    Iron 0mg0%

    Net carbs 0.9g

    * Percent Daily Values are based on a 2000 calorie diet.

    Course: Appetizer, Breakfast, Snack

    Cuisine: American

    Diet: Diabetic

    Keyword: easy breakfast recipes, salmon, smoked salmon spread

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    Simple Marinara Sauce | My Bizzy Kitchen

    By electricdiet / August 28, 2021

    This simple marinara sauce takes only 20 minutes to make, yet is rich and tastes like it’s been simmering all day.  Tomato paste gives this a depth of flavor that is delicious.

    this is a photo of simple marinara sauce

    A few months ago I bought a Vitamix on sale for $249.  I am kicking myself for not buying one sooner – it’s amazing.  Costco sometimes has Vitamix’s on sale too.

    this is a photo of a Vitamix blending simple marinara sauce

    What is the secret to a simple marinara?

    Good canned tomatoes.  My late husband introduced me to peeled Italian tomatoes and they are so delicious and readily available in any grocery store.  The cans cost between $1.49 and $2.00 not on sale, but about every three weeks they are on sale for $.99 so I stock up.

    What can you do with leftover marinara sauce?

    I live alone, but I still make this full batch to use throughout the week.  Here are some recipes that use marinara sauce:

    You can use some of this marinara sauce to make my chicken meatball dish.

    this is a photo of chicken meatballs with marinara

    Zucchini Lasagna with Pork Ragu:

    this is a photo of zucchini lasagna

    Quick Tomato Soup:

    this is a photo of quick tomato soup


    Or my quick chicken parmesan.  

    4 ounces chicken breast tossed in 1 tablespoon of flour, salt and pepper.  Pan fried over medium heat for 4 minutes a side.  On the last minute, top with 1 tablespoon shredded Parmesan cheese and put that side down in the pan so it gets nice and crispy.  Serve over whole wheat pasta and some of the marinara.  Garnish with fresh basil.

    This is a photo of crispy chicken parmesan over whole wheat pasta


    • 1 28 ounce can Italian peeled plum tomatoes
    • 2 tablespoons minced garlic
    • 2 tablespoons tomato paste
    • 1 tablespoon oregano
    • 1 tablespoon Italian seasoning
    • 1/2 teaspoon crushed red pepper
    • 1/2 teaspoon salt
    • 1/2 teaspoon pepper


    1. Spray a skillet with avocado oil spray. Add the garlic and cook for five minutes. Add the tomato paste and cook for two minutes. Add the remaining ingredients and simmer for 10 minutes.
    2. Use a blender or stick blender, puree sauce.


    This is ZERO points on all WW plans. If your sauce is a bit acidic, add a pinch of sugar to balance it out. A teaspoon of sugar is only 10 calories, so I wouldn’t count that. 😂

    Nutrition Information:

    Yield: 4

    Serving Size: 1

    Amount Per Serving:

    Calories: 55Total Fat: 1gSaturated Fat: 0gTrans Fat: 0gUnsaturated Fat: 0gCholesterol: 0mgSodium: 281mgCarbohydrates: 12gFiber: 4gSugar: 6gProtein: 3g

    Did you make this recipe?

    Please leave a comment on the blog or share a photo on Instagram

    Let me know if you make this – I’d love to hear what you think!

    This homemade marinara sauce takes only 20 minutes to make, yet it is rich and tastes like it’s been simmering all day. Tomato paste gives this a depth of flavor that is delicious. You can use some of this marinara sauce to make my chicken meatball recipe, my zucchini lasagna, my quick tomato soup, and my chicken parmesan. This is ZERO points on all WW plans. If your sauce is a bit acidic, add a pinch of sugar to balance it out. #ww #weightwatchers #pasta #marinara #sauce


    I am a widowed 52 year old trying to figure out my life after losing my husband after a long illness.

    Cooking and being in the kitchen feeds my soul!

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