Postprandial glucose metabolism in children and adolescents with type 1 diabetes mellitus: potential targets for improvement

The main goal of therapeutic management of type 1 Diabetes Mellitus (T1DM) is to maintain optimal glycemic control to prevent acute and long-term diabetes complications and to enable a good quality of life. Postprandial glycemia makes a substantial contribution to overall glycemic control and variability in diabetes and, despite technological advancements in insulin treatments, optimal postprandial glycemia is difficult to achieve. Several factors influence postprandial blood glucose levels in children and adolescents with T1DM, including nutritional habits and adjustment of insulin doses according to meal composition. Additionally, hormone secretion, enteroendocrine axis dysfunction, altered gastrointestinal digestion and absorption, and physical activity play important roles. Meal-time routines, intake of appropriate ratios of macronutrients, and correct adjustment of the insulin dose for the meal composition have positive impacts on postprandial glycemic variability and long-term cardiometabolic health of the individual with T1DM. Further knowledge in the field is necessary for management of all these factors to be part of routine pediatric diabetes education and clinical practice. Thus, the aim of this report is to review the main factors that influence postprandial blood glucose levels and metabolism, focusing on macronutrients and other nutritional and lifestyle factors, to suggest potential targets for improving postprandial glycemia in the management of children and adolescents with T1DM.

Carbohydrate Counting, Empowerment and Glycemic Outcomes in Adolescents and Young Adults with Long Duration of Type 1 Diabetes

The complex treatment for diabetes type 1 (T1D) includes insulin dosing for every meal, which requires education and experience to achieve optimal outcomes. Advanced carbohydrate counting (ACC) is the recommended method. We studied ACC as part of a standard treatment with the aim to explore its associations with glycemic control and empowerment in adolescents and young adults. We used national registry data on glycemic outcomes, a study-specific questionnaire regarding the use of ACC and the Gothenburg Young Persons Empowerment Scale (GYPES) to measure empowerment. A total of 111 participants (10-28 years of age, diabetes duration >9 years, mean HbA1c of 55.4 mmol/mol) answered the questionnaire. We found that most participants (79.3%) who learn ACC, at onset or later, continue to use the method. A higher level of empowerment was associated with lower HbA1c (p = 0.021), making patient empowerment an important factor in achieving optimal glycemic outcomes. No associations were found between ACC and empowerment or glycemic outcomes. A mixed strategy, only using ACC sometimes when insulin dosing for meals, was associated with the lowest empowerment score and highest HbA1c and should warrant extra education and support from the diabetes team to reinforce a dosing strategy.

Healthy weight and overweight adolescents with type 1 diabetes mellitus do not meet recommendations for daily physical activity and sleep

AIMS

Physical activity (PA) plays an important role in the prevention of cardiovascular disease (CVD), particularly in individuals with type 1 diabetes mellitus (T1DM) who are at increased risk. Our aim was to determine levels of moderate-to-vigorous physical activity (MVPA), sedentary behaviour and sleep in adolescents with T1DM, and identify barriers to PA.

METHODS

Participants aged 12-18 with T1DM wore an accelerometer and continuous glucose monitor for 24 h over 7-days. Data was processed into PA metrics and sleep. Pearson correlations were used to test associations between MVPA and metabolic measures. Barriers to PA were measured using a questionnaire.

RESULTS

Thirty-seven adolescents provided valid accelerometer data. Mean daily MVPA was 44.0 min [SD 17.6] with 16.2% achieving the guideline of ≥ 60 min/day. Participants had 11 h [SD 1.2] of sedentary behaviour and 7.6 h [SD 1.5] of sleep/day. There was no difference in MVPA in overweight or obese (53.8%) vs. healthy weight (44.2%) adolescents (45.0 min [SD 16.6] vs. 43.1 min [SD 18.8]). Only 39.6% reported one or more diabetes specific barrier to PA.

CONCLUSION

Adolescents with T1DM engage in insufficient MVPA and sleep, irrespective of body weight status, suggesting the need for targeted interventions.

Medical nutrition therapy for gestational diabetes mellitus in Australia: What has changed in 10 years and how does current practice compare with best practice?

BACKGROUND

The present study aimed to report Australian dietetic practice regarding management of gestational diabetes mellitus (GDM) and to make comparisons with the findings from a 2009 survey of dietitians and with the Academy of Nutrition and Dietetics Evidence-Based Nutrition Practice Guidelines (NPG).

METHODS

Cross-sectional surveys were conducted in 2019 and 2009 of dietitians providing medical nutrition therapy (MNT) to women with GDM in Australia. The present study compares responses on demographics, dietetic assessment and interventions, and guideline use in 2019 vs. 2009.

RESULTS

In total, 149 dietitians (2019) and 220 (2009) met survey inclusion criteria. In both surveys >60% of respondents reported dietary interventions aiming for >45% energy from carbohydrate, 15%-25% energy from protein and 15%-30% energy from fat. Many variations in MNT found in 2009 continued to be evident in 2019, including the percentage of energy from carbohydrate aimed for (30%-65% in 2019 vs. 20%-75% in 2009) and the wide range in the recommended minimum daily carbohydrate intake (40-220 and 60-300 g). Few dietitians reported aiming for the NPG minimum of 175 g of carbohydrate daily in both surveys (32% in 2019 vs. 26% in 2009). There were, however, some significant increases in MNT consistent with NPG recommendations in 2019 vs. 2009, including the minimum frequency of visits provided (49%, n = 61 vs. 33%, n = 69; p < 0.001) and provision of gestational weight gain advice (59%, n = 95 vs. 40%, n = 195; p < 0.05).

CONCLUSIONS

Although many dietitians continue to provide MNT consistent with existing NPG, there is a need to support greater uptake, especially for recommendations regarding carbohydrate intake.

Insulin delivery patterns required to maintain postprandial euglycemia in type 1 diabetes following consumption of traditional Egyptian Ramadan Iftar meal using insulin pump therapy: A randomized crossover trial

OBJECTIVES

During Ramadan, traditional Egyptian Iftar meals have large amounts of high-glycemic index carbohydrate and fat. The efficacy of different bolus regimens on optimizing post prandial glucose (PPG) excursion following this Iftar meal was assessed.

METHODS

A randomized controlled trial evaluating 4-h PPG measured by continuous glucose-monitoring was conducted. A total of 25 youth with T1DM using insulin pumps were given the same Iftar meal (fat [45 g], protein [28 g], CHO [95 g]) on seven consecutive days. Insulin to carbohydrate ratio (ICR) was individualized, and all boluses were given upfront 20 min before Iftar. Participants were randomized to receive a standard bolus and six different split boluses delivered over 4 h in the following splits: dual wave (DW) 50/50; DW 50/50 with 20% increment (120% ICR); DW60/40; DW 60/40 with 20% increment; DW 70/30 and DW 70/30 with 20% increment.

RESULTS

Standard bolus and split 70/30 with 20% increment resulted in significantly lower early glucose excursions (120 min) with mean excursions of less than 40 mg/dL (2.2 mmol/L) compared to other conditions (p < 0.01). The split 70/30 with 20% increment significantly optimized late PPG excursion (240 min) in comparison to standard bolus (p < 0.01), as well as resulting in a significantly lower post meal glucose area under the curve compared with all other conditions (p < 0.01), with no late hypoglycemia.

CONCLUSION

To achieve physiologic PPG profile in traditional Iftar meal, a DW bolus with 20% increment given 20 min preprandial as split bolus 70/30 over 4 h, optimized both early and delayed PPG excursions.

Adolescents with type 1 diabetes can achieve glycemic targets on intensive insulin therapy without excessive weight gain

Introduction

The aim of this study was to compare glycemic control and body mass index standard deviation score (BMI‐SDS) before and after implementation of intensive insulin therapy using multiple daily injection (MDI) or continuous subcutaneous insulin infusion (CSII) in adolescents with type 1 diabetes (T1D) attending a large multidisciplinary paediatric diabetes clinic in Australia.

Methods

Prospective data were collected for cross‐sectional comparison of youth aged 10.0–17.9 years (n = 669) from routine follow‐up visits to the diabetes clinic in 2004, 2010, and 2016. Outcome measures included HbA1c; BMI‐SDS; and insulin regimen.

Results

BMI‐SDS remained stable between 2004 to 2016 in the 10–13 and 14–17 year age group (0.7 vs. 0.5, p = .12 and 0.7 vs. 0.7, p = .93, respectively). BMI‐SDS was not different across HbA1c groups; <53 mmol/mol (7.0%), 53 to <75 mmol/mol (<7.0 to <9.0%) and >75 mmol/mol (>9.0%) in 2004 (p = .873), 2010 (p = .10) or 2016 (p = .630). Mean HbA1c decreased from 2004 to 2016 in the 10–13 year (69 mmol/mol (8.4%) vs. 57 mmol/mol (7.4%), p = <.001) and 14–17 year group (72 mmol/mol (8.7%) vs. 63 mmol/mol (7.9%), p = <.001). Prior to the implementation of MDI and CSII in 2004 only 10% of 10–13 year olds and 8% of 14–17 year olds achieved the international target for glycemic control (HbA_1c 53 mmol/mol [<7.0%]). In 2016, this increased to 31% of 10–13 year olds and 21% of 14–17 year olds.

Conclusions

BMI‐SDS did not increase with the change to intensive insulin therapy despite a doubling in the number of adolescents achieving the recommended glycemic target of <7.0% (53 mmol/mol). HbA1c was not associated with weight gain.

Proposal for a New Pathologic Prognostic Index After Neoadjuvant Chemotherapy in Pancreatic Ductal Adenocarcinoma (PINC)

BACKGROUND

Limited information is available on the relevant prognostic variables after surgery for patients with pancreatic ductal adenocarcinoma (PDAC) subjected to neoadjuvant chemotherapy (NACT). NACT is known to induce a spectrum of histological changes in PDAC. Different grading regression systems are currently available; unfortunately, they lack precision and accuracy. We aimed to identify a new quantitative prognostic index based on tumor morphology.

PATIENTS AND METHODS

The study population was composed of 69 patients with resectable or borderline resectable PDAC treated with preoperative NACT (neoadjuvant group) and 36 patients submitted to upfront surgery (upfront-surgery group). A comprehensive histological assessment on hematoxylin and eosin (H&E) stained sections evaluated 20 morphological parameters. The association between patient survival and morphological variables was evaluated to generate a prognostic index.

RESULTS

The distribution of morphological parameters evaluated was significantly different between upfront-surgery and neoadjuvant groups, demonstrating the effect of NACT on tumor morphology. On multivariate analysis for patients that received NACT, the predictors of shorter overall survival (OS) and disease-free survival (DFS) were perineural invasion and lymph node ratio. Conversely, high stroma to neoplasia ratio predicted longer OS and DFS. These variables were combined to generate a semiquantitative prognostic index based on both OS and DFS, which significantly distinguished patients with poor outcomes from those with a good outcome. Bootstrap analysis confirmed the reproducibility of the model.

CONCLUSIONS

The pathologic prognostic index proposed is mostly quantitative in nature, easy to use, and may represent a reliable tumor regression grading system to predict patient outcomes after NACT followed by surgery for PDAC.

Does weight management after gestational diabetes mellitus diagnosis improve pregnancy outcomes? A multi-ethnic cohort study

AIMS

To assess the impact of achieving an Institute of Medicine based personalised weight target in addition to conventional glycaemic management after gestational diabetes mellitus diagnosis on maternal and neonatal outcomes.

METHODS

A retrospective audit of clinical data (2016-2019) for singleton gestational diabetes pregnancies was conducted in a multi-ethnic cohort. Logistic regression analyses assessed relationships between achieving, exceeding and gaining less than a personalised weight target provided after gestational diabetes diagnosis and rates of large for gestational age, small for gestational age infants, insulin therapy initiation and neonatal outcomes. Adjusted odds ratios (aOR) were adjusted for glucose 2-h post-glucose load value, family history of type 2 diabetes, previous gestational diabetes, macrosomia in a previous pregnancy, and East and South-East Asian ethnicity.

RESULTS

Of 1034 women, 44% (n = 449) achieved their personalised weight target. Women who exceeded their personalised weight target had significantly and higher mean insulin doses (28.8 ± 21.5 units vs. 22.7 ± 18.7, p = 0.006) and higher rates of large for gestational age infants (19% vs. 9.8%, p < 0.001), with aOR of 1.99 [95% CI 1.25-3.15] p = 0.004, but no difference in rates of small for gestational age infants (5.3% vs. 8.0%) (aOR 0.77 [0.41-1.44] p = 0.41). Lower rates of large for gestational age infants occurred in those who gained below their personalised weight target (aOR 0.48 [0.25-0.95] p = 0.034), but rates of small for gestational age infants concurrently increased (aOR 1.9 [1.19-3.12] p = 0.008).

CONCLUSIONS

Weight management after gestational diabetes diagnosis does not appear to be too late to confer additional benefits to glucose-lowering treatment, resulting in lower mean insulin doses, and lower rates of large for gestational age infants without increasing the risk of small for gestational age infants.

Does dietary fat cause a dose dependent glycemic response in youth with type 1 diabetes?

OBJECTIVE

To determine the glycemic impact of dietary fat alone consumed without prandial insulin in individuals with T1D.

RESEARCH DESIGN AND METHODS

Thirty participants with T1D (aged 8-18 years) consumed a test drink with either 20 g glucose or 1, 13, 26, 39, 51 g of fat with negligible carbohydrate/protein on 6 consecutive evenings, in a randomized order without insulin. Continuous glucose monitoring was used to measure glucose levels for 8 h postprandially. Primary outcome was mean glycemic excursion at each 30 min interval for each test condition. Generalized linear mixed models with a random effect for people with diabetes were used to test for an increase in blood glucose excursion with increasing quantity of fat.

RESULTS

Glycemic excursions after 20 g glucose were higher than after fat drinks over the first 2 h (p < 0.05). Glycemic excursion for the fat drinks demonstrated a dose response, statistically significant from 4 h (p = 0.026), such that increasing loads of fat caused a proportionally larger increase in glycemic excursion, remaining statistically significant until 8 h (p < 0.05). Overall, for every 10 g fat added to the drink, glucose concentrations rose by a mean of 0.28 mmol L^-1 from 330 min (95% CI 0.15 to 0.39, p < 0.001).

CONCLUSIONS

Fat ingested without other macronutrients increases glucose excursions from 4 to 8 h after ingestion, in a dose dependent manner. These observations may impact on insulin dosing for high-fat foods in individuals with T1D.

Association of the use of diabetes technology with HbA1c and BMI-SDS in an international cohort of children and adolescents with type 1 diabetes: The SWEET project experience

OBJECTIVE

To examine the association between the use of diabetes technology (insulin pump [CSII], glucose sensor [CGM] or both) and metabolic control (HbA1c) as well as body adiposity (BMI-SDS) over-time in a cohort of children and adolescents with type 1 diabetes (T1D), that have never used these technologies before.

SUBJECTS AND METHODS

Four thousand six hundred forty three T1D patients (2-18 years, T1D ≥1 year, without celiac disease, no CSII and/or CGM before 2016) participating in the SWEET prospective multicenter diabetes registry, were enrolled. Data were collected at two points (2016; 2019). Metabolic control was assessed by glycated hemoglobin (HbA1c) and body adiposity by BMI-SDS (WHO). Patients were categorized by treatment modality (multiple daily injections [MDI] or CSII) and the use or not of CGM. Linear regression models, adjusted for age, gender, duration of diabetes and region, were applied to assess differences in HbA1c and BMI-SDS among patient groups.

RESULTS

The proportion of patients using MDI with CGM and CSII with CGM significantly increased from 2016 to 2019 (7.2%-25.7%, 7.8%-27.8% respectively; p < 0.001). Linear regression models showed a significantly lower HbA1c in groups that switched from MDI to CSII with or without CGM (p < 0.001), but a higher BMI-SDS (from MDI without CGM to CSII with CGM p < 0.05; from MDI without CGM to CSII without CGM p < 0.01).

CONCLUSIONS

Switching from MDI to CSII is significantly associated with improvement in glycemic control but increased BMI-SDS over-time. Diabetes technology may improve glucose control in youths with T1D although further strategies to prevent excess fat accumulation are needed.

Insulin strategies for dietary fat and protein in type 1 diabetes: A systematic review

AIM

To identify and report the efficacy of insulin strategies used to manage glycaemia following fat and/or fat and protein meals in type 1 diabetes.

METHODS

A systematic literature search of medical databases from 1995 to 2021 was undertaken. Inclusion criteria were randomised controlled trials that reported at least one of the following glycaemic outcomes: mean glucose, area under the curve, time in range or hypoglycaemic episodes.

RESULTS

Eighteen studies were included. Thirteen studies gave additional insulin. Five studies gave an additional 30%-43% of the insulin-to-carbohydrate ratio (ICR) for 32-50 g of fat and 31%-51% ICR for 7-35 g of fat with 12-27 g of protein added to control meals. A further eight studies gave -28% to +75% ICR using algorithms based on fat and protein for meals with 19-50 g of carbohydrate, 2-79 g of fat and 10-60 g of protein, only one study reported a glycaemic benefit of giving less than an additional 24% ICR. Eight studies evaluated insulin delivery patterns. Four of six studies in pump therapy, and one of two studies in multiple daily injections showed the combination of bolus and split dose, respectively, were superior. Five studies examined the insulin dose split, four demonstrated 60%-125% ICR upfront was necessary. Two studies investigated the timing of insulin delivery, both reported administration 15 min before the meal lowered postprandial glycaemia.

CONCLUSIONS

Findings highlight the glycaemic benefit of an additional 24%-75% ICR for fat and fat and protein meals. For these meals, there is supportive evidence for insulin delivery in a combination bolus with a minimum upfront dose of 60% ICR, 15 min before the meal.

In children and young people with type 1 diabetes using Pump therapy, an additional 40% of the insulin dose for a high-fat, high-protein breakfast improves postprandial glycaemic excursions: A cross-over trial

AIM

To determine the insulin requirement for a high-fat, high-protein breakfast to optimise postprandial glycaemic excursions in children and young people with type 1 diabetes using insulin pumps.

METHODS

In all, 27 participants aged 10-23 years, BMI <95^th percentile (2-18 years) or BMI <30 kg/m² (19-25 years) and HbA_1c ≤64 mmol/mol (≤8.0%) consumed a high-fat, high-protein breakfast (carbohydrate: 30 g, fat: 40 g and protein: 50 g) for 4 days. In this cross-over trial, insulin was administered, based on the insulin-to-carbohydrate ratio (ICR) of 100% (control), 120%, 140% and 160%, in an order defined by a randomisation sequence and delivered in a combination bolus, 60% ¼ hr pre-meal and 40% over 3 hr. Postprandial sensor glucose was assessed for 6 hr.

RESULTS

Comparing 100% ICR, 140% ICR and 160% ICR resulted in significantly lower 6-hr areas under the glucose curves: mean (95%CI) (822 mmol/L.min [605,1039] and 567 [350,784] vs 1249 [1042,1457], p ≤ 0.001) and peak glucose excursions (4.0 mmol/L [3.0,4.9] and 2.7 [1.7,3.6] vs 6.0 [5.0,6.9],p < 0.001). Rates of hypoglycaemia for 100%-160% ICR were 7.7%, 7.7%, 12% and 19% respectively (p ≥ 0.139). With increasing insulin dose, a step-wise reduction in mean glucose excursion was observed from 1 to 6 hr (p = 0.008).

CONCLUSIONS

Incrementally increasing the insulin dose for a high-fat, high-protein breakfast resulted in a predictable, dose-dependent reduction in postprandial glycaemia: 140% ICR improved postprandial glycaemic excursions without a statistically significant increase in hypoglycaemia. These findings support a safe, practical method for insulin adjustment for high-fat, high-protein meals that can be readily implemented in practice to improve postprandial glycaemia.

For a high fat, high protein breakfast, preprandial administration of 125% of the insulin dose improves postprandial glycaemic excursions in people with type 1 diabetes using multiple daily injections: A cross-over trial

AIM

To determine the glycaemic impact of an increased insulin dose, split insulin dose and regular insulin for a high fat, high protein breakfast in people with type 1 diabetes using multiple daily injections (≥4/day).

METHODS

In this cross-over trial, participants received the same high fat, high protein breakfast (carbohydrate:30 g, fat:40 g, protein:50 g) for 4 days. Four different insulin strategies were randomly allocated and tested; 100% of the insulin-to-carbohydrate ratio (ICR) given in a single dose using aspart insulin (100Asp), 125% ICR given in a single dose using aspart (125Asp) or regular insulin (125Reg) and 125% ICR given in a split dose using aspart insulin (100:25Asp). Insulin was given 0.25 hr pre-meal and for 100:25Asp, also 1 hr post-meal. Postprandial sensor glucose was measured for 5 hr.

RESULTS

In all, 24 children and adults were participated. The 5-hr incremental area under the curves for 100Asp, 125Asp, 125Reg and 100:25Asp were 620 mmol/L.min [95% CI: 451,788], 341 mmol/L.min [169,512], 675 mmol/L.min [504,847] and 434 mmol/L.min [259,608], respectively. The 5-hr incremental area under the curve for 125Asp was significantly lower than for 100Asp (p = 0.016) and for 125Reg (p = 0.002). There was one episode of hypoglycaemia in 125Reg.

CONCLUSIONS

For a high fat, high protein breakfast, giving 125% ICR preprandially, using aspart insulin significantly improved postprandial glycaemia without hypoglycaemia. There was no additional glycaemic benefit from giving insulin in a split dose (100:25%) or replacing aspart with regular insulin.

Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA)

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (i.e. before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes. Graphical abstract.

Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA)

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (ie, before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.

Screening and identification of disordered eating in people with type 1 diabetes: A systematic review

People with Type 1 diabetes (T1D) have been shown to be an at-risk group for the development of disordered eating behaviours, however, the validity of tools used to assess disordered eating behaviours in T1D is unclear. This review aimed to identify tools used to screen or identify disordered eating behaviours and eating disorders in people with T1D, and evaluate the validity and reliability of these tools. A systematic search strategy was conducted to October 2019 according to the PRISMA guidelines. The search strategy retrieved 2714 articles, with 100 articles describing 90 studies included in the review. Studies were predominantly conducted in adolescent females in clinical settings. Forty-eight individual tools were used across retrieved studies. Overall, the quality of tools reported in included articles was poor, with high risk of bias due to the use of non-validated tools (n = 44 articles) and few studies comparing to the reference standard (n = 10 articles) of a diagnostic interview. This review shows that a variety of tools have been used to screen and identify disordered eating behaviours and eating disorders in people with T1D. Future research including comparison to a gold standard diagnostic interview is warranted to further evaluate the validity and reliability of available tools.

Excessive Weight Gain Before and During Gestational Diabetes Mellitus Management: What Is the Impact?

OBJECTIVE

Conventional gestational diabetes mellitus (GDM) management focuses on managing blood glucose in order to prevent adverse outcomes. We hypothesized that excessive weight gain at first presentation with GDM (excessive gestational weight gain [EGWG]) and continued EGWG (cEGWG) after commencing GDM management would increase the risk of adverse outcomes, despite treatment to optimize glycemia.

RESEARCH DESIGN AND METHODS

Data collected prospectively from pregnant women with GDM at a single institution were analyzed. GDM was diagnosed on the basis of Australasian Diabetes in Pregnancy Society 1998 guidelines (1992-2015). EGWG means having exceeded the upper limit of the Institute of Medicine-recommended target ranges for the entire pregnancy, by GDM presentation. The relationship between EGWG and antenatal 75-g oral glucose tolerance test (oGTT) values and adverse outcomes was evaluated. Relationships were examined between cEGWG, insulin requirements, and large-for-gestational-age (LGA) infants.

RESULTS

Of 3,281 pregnant women, 776 (23.6%) had EGWG. Women with EGWG had higher mean fasting plasma glucose (FPG) on oGTT (5.2 mmol/L [95% CI 5.1-5.3] vs. 5.0 mmol/L [95% CI 4.9-5.0]; P < 0.01), after adjusting for confounders, and more often received insulin therapy (47.0% vs. 33.6%; P < 0.0001), with an adjusted odds ratio (aOR) of 1.4 (95% CI 1.1-1.7; P < 0.01). aORs for each 2-kg increment of cEGWG were a 1.3-fold higher use of insulin therapy (95% CI 1.1-1.5; P < 0.001), an 8-unit increase in final daily insulin dose (95% CI 5.4-11.0; P < 0.0001), and a 1.4-fold increase in the rate of delivery of LGA infants (95% CI 1.2-1.7; P < 0.0001).

CONCLUSIONS

The absence of EGWG and restricting cEGWG in GDM have a mitigating effect on oGTT-based FPG, the risk of having an LGA infant, and insulin requirements.

Young children, adolescent girls and women with type 1 diabetes are more overweight and obese than reference populations, and this is associated with increased cardiovascular risk factors

AIM

Overweight and obesity are frequently reported in young persons with type 1 diabetes, however its relative magnitude in comparison to the general population is not well understood. This study compared the prevalence of overweight and obesity in young persons with type 1 diabetes to a reference population and explored possible associated factors, including gender, age, HbA_1c , insulin regimen, age at diagnosis, diabetes duration, socio-economic status and cardiovascular disease risk factors.

METHODS

A cross-sectional review was undertaken of data collected from youth (3-17 years) in 2016 and young adults (18-30 years) in 2015 with a diagnosis of type 1 diabetes for > 3 months attending diabetes centres in Newcastle, Australia. Rates of overweight and obesity were compared with matched population survey results.

RESULTS

Data from 308 youth and 283 young adults were included. In girls, significantly higher prevalence of overweight and obesity were seen in the 5-8 (43% vs. 18%), 13-16 (41% vs. 27%), 18-24 (46% vs. 34%) and 25-30 (60% vs. 43%) years age groups; whereas in boys increased prevalence was observed in the 5-8 years age group only (41% vs. 18%). Rates of overweight and obesity increased with age across sexes. In youth, BMI standard deviation score was correlated with socio-economic status, insulin regimen, blood pressure and blood lipids (P < 0.05). In adults, BMI was positively associated with blood pressure, and longer diabetes duration (P < 0.02).

CONCLUSIONS

Overweight and obesity are over-represented in young persons with type 1 diabetes, particularly girls. As overweight is associated with other cardiovascular disease markers early intervention is paramount.

The ups and downs of low-carbohydrate diets in the management of Type 1 diabetes: a review of clinical outcomes

Dietary management has been a mainstay of care in Type 1 diabetes since before the discovery of insulin when severe carbohydrate restriction was advocated. The use of insulin facilitated re-introduction of carbohydrate into the diet. Current management guidelines focus on a healthy and varied diet with consideration of glycaemic load, protein and fat. As a result of frustration with glycaemic outcomes, low-carbohydrate diets have seen a resurgence in popularity. To date, low-carbohydrate diets have not been well studied in the management of Type 1 diabetes. Studies looking at glycaemic outcomes from low-carbohydrate diets have largely been cross-sectional, without validated dietary data and with a lack of control groups. The participants have been highly motivated self-selected individuals who follow intensive insulin management practices, including frequent blood glucose monitoring and additional insulin corrections with tight glycaemic targets. These confounders limit the ability to determine the extent of the impact of dietary carbohydrate restriction on glycaemic outcomes. Carbohydrate-containing foods including grains, fruit and milk are important sources of nutrients. Hence, low-carbohydrate diets require attention to vitamin and energy intake to avoid micronutrient deficiencies and growth issues. Adherence to restricted diets is challenging and can have an impact on social normalcy. In individuals with Type 1 diabetes, adverse health risks such as diabetic ketoacidosis, hypoglycaemia, dyslipidaemia and glycogen depletion remain clinical concerns. In the present paper, we review studies published to date and provide clinical recommendations for ongoing monitoring and support for individuals who choose to adopt a low-carbohydrate diet. Strategies to optimize postprandial glycaemia without carbohydrate restriction are presented.

Dietary intake and eating patterns of young children with type 1 diabetes achieving glycemic targets

INTRODUCTION

Young children with type 1 diabetes (T1D) consume more saturated fat and less fruit and vegetables than recommended. A common challenge in this age group is unpredictable appetite potentially impacting the way parents manage diabetes cares at mealtimes. This small study aimed to assess nutritional intake and mealtime routines of young children with T1D in a clinic where the majority of children were achieving glycemic targets. A secondary aim was to explore association of eating pattern with HbA1c.

METHODS

A retrospective, cross-sectional review of children aged less than 7.0 years with T1D attending a pediatric diabetes service in Australia was performed (n=24). Baseline characteristics, glycated hemoglobin (HbA1c), a 3-day weighed food diary and a mealtime management survey were collected.

RESULTS

Twenty-two children (55% male) were included aged 4.9±1.3 years (mean±SD), HbA1c 47±10 mmol/mol (6.4%±0.9%), body mass index Z-score 0.8±0.9 and diabetes duration 1.7±1.1 years. Preprandial insulin use was reported in 95% of children. Macronutrient distribution (% energy intake) was carbohydrate (48%±4%), protein (16%±2%) and fat (33%±5%) with saturated fat (15%±3%). The majority of children did not meet vegetable and lean meat/protein intake recommendations (0% and 28%, respectively). HbA1c was not correlated with daily total carbohydrate, protein or fat intake (p>0.05). HbA1c was significantly higher in children offered food in a grazing pattern compared with those offered regular meals (mean 61 mmol/mol vs 43 mmol/mol (7.7% vs 6.1%), p=0.01).

CONCLUSIONS

Dietary quality is a concern in young children with T1D with excessive saturated fat and inadequate vegetable intake. Our results suggest that young children meeting glycemic targets give insulin before meals and follow a routine eating pattern.

A randomized comparison of three prandial insulin dosing algorithms for children and adolescents with Type 1 diabetes

AIM

To compare systematically the impact of two novel insulin-dosing algorithms (the Pankowska Equation and the Food Insulin Index) with carbohydrate counting on postprandial glucose excursions following a high fat and a high protein meal.

METHODS

A randomized, crossover trial at two Paediatric Diabetes centres was conducted. On each day, participants consumed a high protein or high fat meal with similar carbohydrate amounts. Insulin was delivered according to carbohydrate counting, the Pankowska Equation or the Food Insulin Index. Subjects fasted for 5 h following the test meal and physical activity was standardized. Postprandial glycaemia was measured for 300 min using continuous glucose monitoring.

RESULTS

33 children participated in the study. When compared to carbohydrate counting, the Pankowska Equation resulted in lower glycaemic excursion for 90-240 min after the high protein meal (p < 0.05) and lower peak glycaemic excursion (p < 0.05). The risk of hypoglycaemia was significantly lower for carbohydrate counting and the Food Insulin Index compared to the Pankowska Equation (OR 0.76 carbohydrate counting vs. the Pankowska Equation and 0.81 the Food Insulin Index vs. the Pankowska Equation). There was no significant difference in glycaemic excursions when carbohydrate counting was compared to the Food Insulin Index.

CONCLUSION

The Pankowska Equation resulted in reduced postprandial hyperglycaemia at the expense of an increase in hypoglycaemia. There were no significant differences when carbohydrate counting was compared to the Food Insulin Index. Further research is required to optimize prandial insulin dosing.

Optimizing the combination insulin bolus split for a high-fat, high-protein meal in children and adolescents using insulin pump therapy

AIMS

To determine the optimum combination bolus split to maintain postprandial glycaemia with a high-fat and high-protein meal in young people with Type 1 diabetes.

METHODS

A total of 19 young people (mean age 12.9 ± 6.7 years) participated in a randomized, repeated-measures trial comparing postprandial glycaemic control across six study conditions after a high-fat and high-protein meal. A standard bolus and five different combination boluses were delivered over 2 h in the following splits: 70/30 = 70% standard /30% extended bolus; 60/40=60% standard/40% extended bolus; 50/50=50% standard/50% extended bolus; 40/60=40% standard/60% extended bolus; and 30/70=30% standard/70% extended bolus. Insulin dose was determined using the participant's optimized insulin:carbohydrate ratio. Continuous glucose monitoring was used to assess glucose excursions for 6 h after the test meal.

RESULTS

Standard bolus and combination boluses 70/30 and 60/40 controlled the glucose excursion up to 120 min. From 240 to 300 min after the meal, the glucose area under the curve was significantly lower for combination bolus 30/70 compared with standard bolus (P=0.004).

CONCLUSIONS

High-fat and high-protein meals require a ≥60% insulin:carbohydrate ratio as a standard bolus to control the initial postprandial rise. Additional insulin at an insulin:carbohydrate ratio of up to 70% is needed in the extended bolus for a high fat and protein meal to prevent delayed hyperglycaemia.

Exercise management in type 1 diabetes: a consensus statement

Type 1 diabetes is a challenging condition to manage for various physiological and behavioural reasons. Regular exercise is important, but management of different forms of physical activity is particularly difficult for both the individual with type 1 diabetes and the health-care provider. People with type 1 diabetes tend to be at least as inactive as the general population, with a large percentage of individuals not maintaining a healthy body mass nor achieving the minimum amount of moderate to vigorous aerobic activity per week. Regular exercise can improve health and wellbeing, and can help individuals to achieve their target lipid profile, body composition, and fitness and glycaemic goals. However, several additional barriers to exercise can exist for a person with diabetes, including fear of hypoglycaemia, loss of glycaemic control, and inadequate knowledge around exercise management. This Review provides an up-to-date consensus on exercise management for individuals with type 1 diabetes who exercise regularly, including glucose targets for safe and effective exercise, and nutritional and insulin dose adjustments to protect against exercise-related glucose excursions.

A novel validated model for the prediction of insulin therapy initiation and adverse perinatal outcomes in women with gestational diabetes mellitus

AIMS/HYPOTHESIS

Identifying women with gestational diabetes mellitus who are more likely to require insulin therapy vs medical nutrition therapy (MNT) alone would allow risk stratification and early triage to be incorporated into risk-based models of care. The aim of this study was to develop and validate a model to predict therapy type (MNT or MNT plus insulin [MNT+I]) for women with gestational diabetes mellitus (GDM).

METHODS

Analysis was performed of de-identified prospectively collected data (1992-2015) from women diagnosed with GDM by criteria in place since 1991 and formally adopted and promulgated as part of the more detailed 1998 Australasian Diabetes in Pregnancy Society management guidelines. Clinically relevant variables predictive of insulin therapy by univariate analysis were dichotomised and included in a multivariable regression model. The model was tested in a separate clinic population.

RESULTS

In 3317 women, seven dichotomised significant independent predictors of insulin therapy were maternal age >30 years, family history of diabetes, pre-pregnancy obesity (BMI ≥30 kg/m(2)), prior GDM, early diagnosis of GDM (<24 weeks gestation), fasting venous blood glucose level (≥5.3 mmol/l) and HbA1c at GDM diagnosis ≥5.5% (≥37 mmol/mol). The requirement for MNT+I could be estimated according to the number of predictors present: 85.7-93.1% of women with 6-7 predictors required MNT+I compared with 9.3-14.7% of women with 0-1 predictors. This model predicted the likelihood of several adverse outcomes, including Caesarean delivery, early delivery, large for gestational age and an abnormal postpartum OGTT. The model was validated in a separate clinic population.

CONCLUSIONS/INTERPRETATION

This validated model has been shown to predict therapy type and the likelihood of several adverse perinatal outcomes in women with GDM.

The relationship between carbohydrate and the mealtime insulin dose in type 1 diabetes

A primary focus of the nutritional management of type 1 diabetes has been on matching prandial insulin therapy with carbohydrate amount consumed. Different methods exist to quantify carbohydrate including counting in one gram increments, 10g portions or 15g exchanges. Clinicians have assumed that counting in one gram increments is necessary to precisely dose insulin and optimize postprandial control. Carbohydrate estimations in portions or exchanges have been thought of as inadequate because they may result in less precise matching of insulin dose to carbohydrate amount. However, studies examining the impact of errors in carbohydrate quantification on postprandial glycemia challenge this commonly held view. In addition it has been found that a single mealtime bolus of insulin can cover a range of carbohydrate intake without deterioration in postprandial control. Furthermore, limitations exist in the accuracy of the nutrition information panel on a food label. This article reviews the relationship between carbohydrate quantity and insulin dose, highlighting limitations in the evidence for a linear association. These insights have significant implications for patient education and mealtime insulin dose calculations.

The Role of Dietary Protein and Fat in Glycaemic Control in Type 1 Diabetes: Implications for Intensive Diabetes Management

A primary focus of the management of type 1 diabetes has been on matching prandial insulin therapy with carbohydrate amount consumed. However, even with the introduction of more flexible intensive insulin regimes, people with type 1 diabetes still struggle to achieve optimal glycaemic control. More recently, dietary fat and protein have been recognised as having a significant impact on postprandial blood glucose levels. Fat and protein independently increase the postprandial glucose excursions and together their effect is additive. This article reviews how the fat and protein in a meal impact the postprandial glycaemic response and discusses practical approaches to managing this in clinical practice. These insights have significant implications for patient education, mealtime insulin dose calculations and dosing strategies.

Impact of fat, protein, and glycemic index on postprandial glucose control in type 1 diabetes: implications for intensive diabetes management in the continuous glucose monitoring era

BACKGROUND

Continuous glucose monitoring highlights the complexity of postprandial glucose patterns present in type 1 diabetes and points to the limitations of current approaches to mealtime insulin dosing based primarily on carbohydrate counting.

METHODS

A systematic review of all relevant biomedical databases, including MEDLINE, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials, was conducted to identify research on the effects of dietary fat, protein, and glycemic index (GI) on acute postprandial glucose control in type 1 diabetes and prandial insulin dosing strategies for these dietary factors.

RESULTS

All studies examining the effect of fat (n = 7), protein (n = 7), and GI (n = 7) indicated that these dietary factors modify postprandial glycemia. Late postprandial hyperglycemia was the predominant effect of dietary fat; however, in some studies, glucose concentrations were reduced in the first 2-3 h, possibly due to delayed gastric emptying. Ten studies examining insulin bolus dose and delivery patterns required for high-fat and/or high-protein meals were identified. Because of methodological differences and limitations in experimental design, study findings were inconsistent regarding optimal bolus delivery pattern; however, the studies indicated that high-fat/protein meals require more insulin than lower-fat/protein meals with identical carbohydrate content.

CONCLUSIONS

These studies have important implications for clinical practice and patient education and point to the need for research focused on the development of new insulin dosing algorithms based on meal composition rather than on carbohydrate content alone.

In children using intensive insulin therapy, a 20-g variation in carbohydrate amount significantly impacts on postprandial glycaemia

AIM

To determine if an insulin dose calculated for a meal containing 60 g carbohydrate maintains postprandial glycaemic control for meals containing 40, 50, 70 or 80 g carbohydrate.

METHODS

Thirty-four young people (age range 8.5-17.7 years) using intensive insulin therapy consumed five test breakfasts with equivalent fat, protein and fibre contents but differing carbohydrate quantities (40, 50, 60, 70 and 80 g of carbohydrate). The preprandial insulin dose was the same for each meal, based on the subject's usual insulin:carbohydrate ratio for 60 g carbohydrate. Continuous glucose monitoring was used to monitor postprandial glucose over 180 min.

RESULTS

The 40-g carbohydrate meal resulted in significantly more hypoglycaemia than the other meals (P = 0.003). There was a one in three chance of hypoglycaemia between 120 and 180 min if an insulin dose for 60 g carbohydrate was given for 40 g carbohydrate. The glucose levels of subjects on the 80-g meal were significantly higher than the 60- and 70-g carbohydrate meals at all time points between 150 and 180 min (P < 0.01). Subjects consuming the 80-g meal were more likely to have significant hyperglycaemia (blood glucose levels ≥ 12 mmol/l) compared with the other meals (P < 0.001).

CONCLUSIONS

In patients using intensive insulin therapy, an individually calculated insulin dose for 60 g carbohydrate results in postprandial hypoglycaemia or hyperglycaemia for meals containing 40 and 80 g carbohydrate. To calculate mealtime insulin in order to maintain postprandial control, carbohydrate estimations should be within 10 g of the actual meal carbohydrate.

Can children with Type 1 diabetes and their caregivers estimate the carbohydrate content of meals and snacks?

AIMS

Carbohydrate (CHO) counting allows children with Type 1 diabetes to adjust mealtime insulin dose to carbohydrate intake. Little is known about the ability of children to count CHO and whether a particular method for assessing CHO quantity is better than others. We investigated how accurately children and their caregivers estimate carbohydrate, and whether counting in gram increments improves accuracy compared with CHO portions or exchanges.

METHODS

One hundred and two children and adolescents (age range 8.3-18.1 years) on intensive insulin therapy and 110 caregivers independently estimated the CHO content of 17 standardized meals (containing 8-90 g CHO), using whichever method of carbohydrate quantification they had been taught (gram increments, 10-g portions or 15-g exchanges).

RESULTS

Seventy-three per cent (n = 2530) of all estimates were within 10-15 g of actual CHO content. There was no relationship between the mean percentage error and method of carbohydrate counting or glycated haemoglobin (HbA(1c)) (P > 0.05). Mean gram error and meal size were negatively correlated (r = -0.70, P < 0.0001). The longer children had been CHO counting the greater the mean percentage error (r = 0.173, P = 0.014). Core foods in non-standard quantities were most frequently inaccurately estimated, while individually labelled foods were most often accurately estimated.

CONCLUSIONS

Children with Type 1 diabetes and their caregivers can estimate the carbohydrate content of meals with reasonable accuracy. Teaching CHO counting in gram increments did not improve accuracy compared with CHO portions or exchanges. Large meals tended to be underestimated and snacks overestimated. Repeated age-appropriate education appears necessary to maintain accuracy in carbohydrate estimations.

Children and adolescents on intensive insulin therapy maintain postprandial glycaemic control without precise carbohydrate counting

AIMS

Carbohydrate (CHO) quantification is used to adjust pre-meal insulin in intensive insulin regimens. However, the precision in CHO quantification required to maintain postprandial glycaemic control is unknown. We determined the effect of a +/-10-g variation in CHO amount, with an individually calculated insulin dose for 60 g CHO, on postprandial glycaemic control.

METHODS

Thirty-one children and adolescents (age range 9.5-16.8 years), 17 using continuous subcutaneous insulin infusion (CSII) and 14 using multiple daily injections (MDI), participated. Each subject consumed test lunches of equal macronutrient content, differing only in carbohydrate quantity (50, 60, 70 g CHO), in random order on three consecutive days. For each participant, the insulin dose was the same for each meal, based on their usual insulin : CHO ratio for 60 g CHO. Activity was standardized. Continuous glucose monitoring was used.

RESULTS

The CSII and MDI subjects demonstrated no difference in postprandial blood glucose levels (BGLs) for comparable carbohydrate loads (P > 0.05). The 10-g variations in CHO quantity resulted in no differences in BGLs or area under the glucose curves for 2.5 h (P > 0.05). Hypoglycaemic episodes were not significantly different (P = 0.32). The 70-g meal produced higher glucose excursions after 2.5 h, with a maximum difference of 1.9 mmol/l at 3 h (P = 0.01), but the BGLs remained within international postprandial targets.

CONCLUSIONS

In patients using intensive insulin therapy, an individually calculated insulin dose for 60 g of carbohydrate maintains postprandial BGLs for meals containing between 50 and 70 g of carbohydrate. A single mealtime insulin dose will cover a range in carbohydrate amounts without deterioration in postprandial control.

Influence of and optimal insulin therapy for a low-glycemic index meal in children with type 1 diabetes receiving intensive insulin therapy

OBJECTIVE

The purpose of this study was to quantify the effects of glycemic index on postprandial glucose excursion (PPGE) in children with type 1 diabetes receiving multiple daily injections and to determine optimal insulin therapy for a low-glycemic index meal.

RESEARCH DESIGN AND METHODS

Twenty subjects consumed test breakfasts with equal macronutrient contents on 4 consecutive days; high-and low-glycemic index meals (glycemic index 84 vs. 48) were consumed with preprandial ultra-short-acting insulin, and the low-glycemic index meal was also consumed with preprandial regular insulin and postprandial ultra-short-acting insulin. Each child's insulin dose was standardized. Continuous glucose monitoring was used.

RESULTS

The PPGE was significantly lower for the low-glycemic index meal compared with the high-glycemic index meal at 30-180 min (P < 0.02) when preprandial ultra-short-acting insulin was administered. The maximum difference occurred at 60 min (4.2 mmol/l, P < 0.0001). Regular insulin produced a 1.1 mmol/l higher PPGE at 30 min compared with ultra-short-acting insulin (P = 0.015) when the low-glycemic index meal was consumed. Postprandial ultra-short-acting insulin produced a higher PPGE at 30 and 60 min compared with preprandial administration when the low-glycemic index meal was consumed. The maximum difference was 2.5 mmol/l at 60 min (P < 0.0001).

CONCLUSIONS

Low-glycemic index meals produce a lower PPGE than high-glycemic index meals. Preprandial ultra-short-acting insulin is the optimal therapy for a low-glycemic index meal.

Nutritional management of children and adolescents on insulin pump therapy - a survey of Australian Practice

OBJECTIVE

The aims of the survey were to review nutritional care provided to children on insulin pump therapy (IPT) and to identify areas of consensus in medical nutrition therapy. Interventions were compared with existing evidence for best practice.

METHOD

A questionnaire was sent to Dieticians in tertiary pediatric diabetes centers in Australia. Data were gathered on clinic demographics, reasons for commencement of pump therapy, and time spent in medical nutrition therapy. Details of nutrition education strategies were identified. Outcomes from nutrition interventions were reported.

RESULTS

A 100% response rate was achieved (n = 12). A number of nutrition therapy interventions were provided to children on IPT. These included carbohydrate counting, glycemic index (GI), and carbohydrate exchanges. At most centers, nutrition education involved teaching dose adjustment for meals based on the carbohydrate content of the meal with estimations to within 5 g. All centers taught GI. The format of nutrition education, including number and length of consults, varied greatly between centers. Only one center had developed nutrition guidelines for managing insulin pump patients.

CONCLUSIONS

Most pediatric diabetes centers in Australia did not follow nutrition guidelines for the management of children on IPT. There were inconsistencies in the number and length of nutrition consultations provided. Some strategies employed in nutrition education were not supported by existing guidelines for best practice. Differences between centers highlighted gaps in the evidence for nutrition therapy interventions in children on pumps.

The proliferative and migratory activities of breast cancer cells can be differentially regulated by heparan sulfates

To explore how heparan sulfate (HS) controls the responsiveness of the breast cancer cell lines MCF-7 and MDA-MB-231 to fibroblast growth factors (FGFs), we have exposed them to HS preparations known to have specificity for FGF-1 (HS glycosaminoglycan (HSGAG A)) or FGF-2 (HSGAGB). Proliferation assays confirmed that MCF-7 cells were highly responsive to FGF-2 complexed with GAGB, whereas migration assays indicated that FGF-1/HSGAGA combinations were stimulatory for the highly invasive MDA-MB-231 cells. Quantitative polymerase chain reaction for the levels of FGF receptor (FGFR) isoforms revealed that MCF-7 cells have greater levels of FGFR1 and that MDA-MB-231 cells have greater relative levels of FGFR2. Cross-linking demonstrated that FGF-2/HSGAGB primarily activated FGFR1, which in turn up-regulated the activity of mitogen-activated protein kinase; in contrast, FGF-1/HSGAGA led to the phosphorylation of equal proportions of both FGFR1 and FGFR2, which in turn led to the up-regulation of Src and p125(FAK). MDA-MB-231 cells were particularly responsive to vitronectin substrates in the presence of FGF-1/HSGAGA, and blocking antibodies established that they used the alpha(v)beta(3) integrin to bind to it. These results suggest that the clustering of particular FGFR configurations on breast cancer cells induced by different HS chains leads to distinct phenotypic behaviors.

The mitogenic signaling pathway for fibroblast growth factor-2 involves the tyrosine phosphorylation of cyclin D2 in MCF-7 human breast cancer cells

Fibroblast growth factor-2 (FGF-2) is mitogenic for the human breast cancer cell line MCF-7; here we investigate some of the signaling pathways subserving this activity. FGF-2 stimulation of MCF-7 cells resulted in a global increase of intracellular tyrosine phosphorylation of proteins, particularly FGF receptor substrate-2, the protooncogene product Src and the mitogen-activated protein kinase (MAP kinase) cascade. A major increase in the tyrosine phosphorylation of a 30-kDa protein species was also found. This protein was identified as cyclin D2 by mass spectrometry after trypsin digestion. Immunoprecipitation of cyclin D2 and immunoblotting with anti-phosphotyrosine antibodies confirmed that the tyrosine phosphorylation of cyclin D2 was indeed induced by FGF-2 stimulation. In addition, pharmacological inhibition of Src (with herbimycin A and PP2), and of the MAP kinase cascade (with PD98059), confirmed that Src activity is required for the FGF-2-induced phosphorylation of cyclin D2 whereas MAP kinase activity is not. Thus, tyrosine phosphorylation of cyclin D2 may be a key regulatory target for FGF-2 signaling.

Lysosomotropic agents and inhibitors of cellular transglutaminase stimulate dome formation, a differentiated characteristic of MDCK kidney epithelial cell cultures

Dome formation is a manifestation of transepithelial fluid transport in cell culture, a differentiated characteristic of transporting epithelia. A dramatic increase in numbers of domes in confluent MDCK kidney epithelial cell cultures was noted after addition of Friend cell inducers such as hexamethylane bisacetamide (HMBA) (Lever, 1979b). In the present study, we show that primary amines such as methylamine, ethylamine, and dansyl cadaverine also stimulate dome formation. These compounds largely prevented the marked decrease in numbers of spontaneously occurring domes which occurred when cultures were switched from medium containing 10% serum to medium containing serum concentrations below 0.2%. Many of these primary amines are not only lysosomotropic agents but also potent inhibitors of transglutaminase activity when assayed in MDCK cell extracts, at concentrations correlating with those effective in stimulation of dome formation. Other lysosomotropic agents such as chloroquine and secondary and tertiary amines stimulated dome formation yet did not inhibit transglutaminase. Induction of domes by HMBA differed in several properties from that stimulated by amines and did not involve fluctuations in transglutaminase activity. These findings suggest that lysosomal functions modulate serum stimulation of dome formation in epithelial cells by a pathway distinct from that triggered by HMBA.

Rubber solvent: a clastogenic agent that fails to induce sister-chromatid exchanges

Rubber solvent was tested for its ability to induce chromosome aberrations and sister-chromatid exchanges in human whole blood cultures. Following exposure to relatively low rubber solvent concentrations (0.0125% and greater) significant increases in the frequencies of chromatid gaps and breaks were observed. At higher rubber-solvent concentrations (0.05% and greater) there were also significant increases in the frequency of chromosome breaks. In contrast to the increase in chromosome aberrations following rubber-solvent exposure, rubber-solvent concentrations up to the toxic level failed to produce increases in the sister-chromatid exchange frequency.