Glucose Trends Research Articles

Trends in Intermittent Scanning Continuous Glucose Monitoring Usage in The Netherlands-An Opportunity for Elderly Individuals with Diabetes.

Background: Intermittent scanning continuous glucose monitoring (is-CGM) technology has gained widespread adoption and is known to improve glycemic control and quality of life for persons with diabetes. The elderly may lag behind in their adoption of the technology, which could be a potential avenue for improving quality of care. In this study, we investigated the adoption of is-CGM technology in the Dutch population, including effects of age. Methods: A retrospective observational study was performed using data from the Drug Information Project, a public database hosted by the Dutch National Health Care Institute. The database contained information concerning healthcare reimbursements from 2017 until 2022 and covered approximately 95% of the total population. Data concerning is-CGM and fast-acting insulin reimbursements were extracted, identifying actual and potential is-CGM users, who were subdivided into the categories 0-24, 25-44, 45-64, 65-74 and ≥75 years old. Results: From 2017 until 2022, is-CGM usage rapidly increased: from 38 to 82.050 actual users. The age categories 0-24 and 25-55 showed the highest is-CGM usage (62% and 84% of the potential population in 2022, respectively), and 65-74 and ≥75 the least (38% and 33%, respectively). However, the elderly had higher growth rates (+75% in the category ≥75 from 2021 to 2022) compared to the youngest (+54% in the category 0-24 in the same period). Conclusions: Data from this study demonstrate that the elderly lag behind in is-CGM adoption. Given the potential advantages of is-CGM for elderly persons with diabetes, we argue that strategies should be developed to address this (paradoxical) underutilization of is-CGM.

A new multivariate blood glucose prediction method with hybrid feature clustering and online transfer learning.

Accurate blood glucose (BG) prediction is greatly benefit for the treatment of diabetes. Generally, clinical physicians are required to comprehensively analyze various factors, such as patient's body temperature, meal, sleep, insulin injection, continuous glucose monitoring (CGM), and other information, to evaluate the fluctuation trend of blood glucose. To address this problem, this paper proposes a multivariate blood glucose prediction method based on mixed feature clustering. It clusters time series data with diverse or mixed features related to blood glucose, effectively leveraging correlations and distribution characteristics. By combining incremental clustering of multivariate time series with transfer learning, this method achieves online prediction of blood glucose levels. The experimental results indicate that the proposed method can decrease the prediction error RMSE by 4.2% (PH=30min) and 5.9% (PH=60min). Compared with other prediction methods, the training time of the multivariate prediction method is reduced by 5.2% (PH=30min) and 4.7% (PH=60min). It was also validated and compared with other methods in a real dataset. The proposed method in this study has lower prediction error and better prediction performance in the prediction horizon(PH) of PH=30, 45, 60, 75, and 90min, respectively. Compared with the traditional unitary and multivariate time series prediction method, the approach proposed in this paper significantly improves the accuracy and robustness of blood glucose prediction. According to the evaluation results on the data set from OhioT1DM and the Sixth People's Hospital of Shanghai, the proposed method has better generalization performance and clinical acceptability.

Validating the Use of Continuous Glucose Monitors With Nondiabetic Recreational Runners.

Continuous glucose monitors (CGMs) are becoming increasingly popular among endurance athletes despite unconfirmed accuracy. We assessed the concurrent validity of the FreeStyle Libre 2 worn on 2 different sites at rest, during steady-state running, and postprandial. Thirteen nondiabetic, well-trained recreational runners (age = 40 [8]y, maximal aerobic oxygen consumption = 46.1 [6.4]mL·kg-1·min-1) wore a CGM on the upper arm and chest while treadmill running for 30, 60, and 90minutes at intensities corresponding to 50%, 60%, and 70% of maximal aerobic oxygen consumption, respectively. Glucose was measured by manually scanning CGMs and obtaining a finger-prick capillary blood glucose sample. Mean absolute relative difference, time in range, and continuous glucose Clarke error grid analysis were used to compare paired CGM and blood glucose readings. Across all intensities of steady-state running, we found a mean absolute relative difference of 13.8 (10.9) for the arm and 11.4 (9.0) for the chest. The coefficient of variation exceeded 70%. Approximately 47% of arm and 50% of chest paired glucose measurements had an absolute difference ≤10%. Continuous glucose Clarke error grid analysis indicated 99.8% (arm) and 99.6% (chest) CGM data fell in clinically acceptable zones A and B. Time-in-range analysis showed reduced accuracy at lower glucose levels. However, CGMs accurately detected trends in mean glucose readings over time. CGMs are not valid for point glucose monitoring but appear to be valid for monitoring glucose trends during steady-state exercise. Accuracy is similar for arm and chest. Further research is needed to determine whether CGMs can detect important events such as hypoglycemia during exercise.

Assessment of Glucose and HbA1c Monitoring in a Pancreatic Cancer Surveillance Program for High-Risk Individuals.

Several studies suggest that new-onset diabetes mellitus is an early manifestation of pancreatic ductal adenocarcinoma (PDAC). Therefore, the International Cancer of the Pancreas Screening Consortium recommends glucose and hemoglobin A1c (HbA1c) monitoring in high-risk individuals (HRIs) undergoing surveillance. However, evidence that such monitoring improves PDAC detection is lacking. Our aim was to investigate the association between serum glucose and HbA1c values and the development of PDAC in HRIs undergoing surveillance. Participants were recruited from the familial pancreatic cancer surveillance cohort, which follows hereditary predisposed HRIs yearly by magnetic resonance imaging and/or endoscopic ultrasound and blood sampling. Those who underwent fasting glucose and/or HbA1c monitoring at least once were eligible candidates. Four hundred four HRIs met the inclusion criteria. During a median follow-up of 41 months (range 14-120), 9 individuals developed PDAC and 4 (without PDAC) were diagnosed with new-onset diabetes mellitus. Glucose levels ranged from 3.4 to 10.7 mmol/L (mean 5.6 ± 0.7) and HbA1c levels from 25 to 68 mmol/mol (mean 37.7 ± 4.1). The mean values did not differ significantly between PDAC cases and controls. The percentage of individuals with at least one elevated value were comparable between PDAC cases and controls for glucose (33% and 27%, P = 0.707) and HbA1c (22% and 14%, P = 0.623). No consistent glucose or HbA1c trends over time suggested a correlation with PDAC development. In this HRI surveillance cohort, measuring glucose and HbA1c values did not contribute to PDAC detection. Larger and longer-term studies are needed to determine the final role of glucose and HbA1c monitoring in PDAC surveillance.

Impact of Telemedicine Versus In-Person Pediatric Outpatient Type 1 Diabetes Visits on Immediate Glycemic Control: Retrospective Chart Review.

Children and adolescents with type 1 diabetes require frequent outpatient evaluation to assess glucose trends, modify insulin doses, and screen for comorbidities. Continuous glucose monitoring (CGM) provides a detailed glycemic control assessment. Telemedicine has been increasingly used since the COVID-19 pandemic. To investigate CGM profile parameter improvement immediately following pediatric outpatient diabetes visits and determine if visit modality impacted these metrics, completion of screening laboratory tests, or diabetic emergency occurrence. A dual-center retrospective review of medical records assessed the CGM metrics time in range and glucose management indicator for pediatric outpatient diabetes visits during 2021. Baseline values were compared with those at 2 and 4 weeks post visit. Rates of completion of screening laboratory tests and diabetic emergencies following visits were determined. A total of 269 outpatient visits (41.2% telemedicine) were included. Mean time in range increased by 1.63% and 1.35% at 2 and 4 weeks post visit (P=.003 and .01, respectively). Mean glucose management indicator decreased by 0.07% and 0.06% at 2 and 4 weeks post visit (P=.003 and .02, respectively). These improvements in time in range and glucose management indicator were seen across both telemedicine visits and in-person visits without a significant difference. However, patients seen in person were 2.69 times more likely to complete screening laboratory tests (P=.03). Diabetic emergencies occurred too infrequently to analyze. Our findings demonstrate an immediate improvement in CGM metrics following outpatient visits, regardless of modality. While statistically significant, the magnitude of these changes was small; hence, multiple visits over time would be required to achieve clinically relevant improvement. However, completion of screening laboratory tests was found to be more likely after visits occurring in person. Therefore, we suggest a hybrid approach that allows patient convenience with telemedicine but also incorporates periodic in-person assessment.

The measurement of plasma fructosamine as a diagnostic tool to improve the interpretation of plasma glucose and proteins in alpacas (Vicugna pacos).

This study assesses the use of fructosamine as a diagnostic tool for hyperglycemia in alpacas in view of their sensitivity to stress and susceptibility to conditions like lipid mobilization syndrome. Plasma fructosamine, like in diagnosing diabetes in cats and dogs, can reveal long-term blood glucose trends, differentiating stress-induced spikes from persistent diabetic hyperglycemia. In 125 alpacas presented as patients of a veterinary clinic, plasma glucose and fructosamine concentrations were compared for correlations with findings of the general clinical examination, laboratory parameters, demographic data, and a behavioral stress assessment processed by using principal component analysis. Hyperglycemia was observed on admission of 71% (89/125) of the animals. This was significantly associated with a higher concentration of serum cortisol and a higher behavioral stress scoring. Fructosamine above the reference limit was detected in only 15% (13/89) of the hyperglycemic individuals. In addition to a positive correlation of fructosamine to glucose concentration, positive relationships with different plasma proteins were detected. A relationship to stress parameters was not observed. These findings underscore stress as a significant trigger for hyperglycemia in alpacas and suggest fructosamine as a valuable parameter for distinguishing between stress-induced and diabetic hyperglycemia. However, the dependence of fructosamine formation on total plasma protein concentration should be considered to avoid misinterpretation.

336 Effects of feeding an immunomodulatory feed additive (NutraGen) on metabolite concentrations and cortisol production in calves following exposure to a combination bovine respiratory disease challenge

Abstract Two 89-d experiments (Exp 1 and Exp 2) evaluated the effects of feeding an immunomodulatory feed additive (NutraGen; NG) in calves following exposure to bovine viral diarrhea virus (BVDV) on d -3 and Mannheimia haemolytica (MH) infection on d 0. For each experiment, steers [body weight (BW) = 251 ± 38.2 kg)] were randomly allocated to 1 of 3 treatments. Treatments included a placebo (CON; Exp 1 n = 5; Exp 2 n = 5), a placebo fed from d -18 to d -3 followed by NG fed from d -3 to d 28 (CHLG; Exp 1 n = 5; Exp 2 n = 6), and NG fed from d -18 to d 28 (PREC; Exp 1 n = 6; Exp 2 n = 5). Data were analyzed using the GLIMMIX procedure of SAS Version 9.4 (SAS Institute, Cary, N.C.). Animal served as the experimental unit and time served as a repeated measure. Treatment, time, and the treatment × time interaction served as fixed effects. Block was included as a random effect. Multiple treatment × time interactions and time effects occurred for serum glucose, lactate, blood urea nitrogen, and non-esterified fatty acid concentrations (P ≤ 0.003) in both experiments. There was a general trend for serum glucose to decrease over time post-challenge, suggesting increased cellular utilization of glucose in response to the challenge. In Exp 1, treatment effects occurred for serum glucose (P ≤ 0.001) and serum lactate (P ≤ 0.01), where calves assigned to the CHLG treatment displayed the greatest concentrations of the metabolites. Blood urea nitrogen concentrations peaked at h 48 in Exp 1 and h 6 in Exp 2. There were no treatment effects or treatment × time interactions for serum cortisol, hair cortisol, or fecal corticosterone concentrations in either experiment (P ≥ 0.17). There were, however, multiple time effects for serum cortisol, hair cortisol, and fecal corticosterone concentrations in both experiments (P ≤ 0.02), indicating that the challenge directly impacted cortisol and corticosterone production. Serum cortisol steadily increased from h 96 to h 168 in both experiments. Trends in cortisol and corticosterone production were similar in both experiments; however, peak concentration times for these variables occurred later in Exp 2. These data suggest that feeding NG to calves may alter glucose availability and nutrient utilization in response to infection resulting from a bovine respiratory disease challenge.

Preserving insulin function in diabetes: a case report

BackgroundThis case report explores the long-term dynamics of insulin secretion and glycemic control in two patients with diabetes mellitus type 2 over 20 years. The observations underscore the impact of lifestyle interventions, including weight loss and calorie restriction, on insulin secretion patterns and glucose levels during 75 g oral glucose tolerance tests. Additionally, the role of hemoglobin A1c fluctuations, influenced by various factors such as body weight, exercise, and pharmacological interventions, is investigated.Case presentationCase 1 involves a Japanese woman now in her late 70s who successfully maintained her hemoglobin A1c below 7% for over two decades through sustained weight loss and lifestyle changes. Despite a gradual decline in the homeostasis model assessment of β cell function, the patient exhibited remarkable preservation of insulin secretion patterns over the 20-year follow-up. In case 2, a Japanese woman, now in her early 70s, experienced an improvement in hemoglobin A1c to 6.3% after a period of calorie limitation due to a wrist fracture in 2018. This incident seemed to trigger a temporary rescue of pancreatic β cell function, emphasizing the dynamic nature of insulin secretion. Both cases highlight the potential for pancreatic β cell rescue and underscore the persistence of insulin secretion over the 20-year follow-up. Additionally, we have briefly discussed three additional cases with follow-ups ranging from 10 to 17 years, demonstrating similar trends in glucose and insulin ratios.ConclusionsLong-term lifestyle interventions, such as weight loss and calorie restriction, can preserve pancreatic β cell function and maintain glycemic control in type 2 diabetes patients over 20 years. Two patients showed stable or improved insulin secretion and favorable hemoglobin A1c levels, challenging the traditional view of irreversible β cell decline. The findings highlight the importance of personalized, nonpharmacological approaches, suggesting that sustained lifestyle changes can significantly impact diabetes management and potentially rescue β cell function.

NOVEL ADAPTIVE AI-POWER INSULIN NAVIGATOR FOR DIABETES USING MACHINE LEARNING

Adaptive AI-powered insulin delivery systems represent a significant advancement in diabetes management, offering enhanced precision and safety for patients with diabetes. This paper examines the development and implementation of AI-driven insulin delivery systems that dynamically adjust insulin dosages based on real-time glucose monitoring and predictive analytics. The system integrates continuous glucose sensors with adaptive AI algorithms to analyze blood glucose trends, activity levels, and dietary inputs, enabling the automatic adjustment of insulin delivery to meet individual patient needs. The study evaluates the performance of these systems in optimizing glycemic control, reducing the incidence of hypoglycemia and hyperglycemia, and improving overall patient outcomes. Key features include the ability to learn from historical data to refine dosing algorithms and the incorporation of safety mechanisms to prevent adverse events. Additionally, the paper explores user experiences and feedback, highlighting the system’s potential to improve quality of life and provide more personalized diabetes management. The integration of adaptive AI in insulin delivery systems promises to revolutionize diabetes care by offering a more responsive, accurate, and user-centric approach to insulin therapy.

Exploring Symptom Management Experiences Among College Students With Type 1 Diabetes Mellitus Using a Theoretical Framework: A Qualitative Study.

The purpose of this study was to explore symptom management experiences among college students with type 1 diabetes mellitus (T1DM). Limited qualitative data using a theoretical framework exist that explore the self-care behavior processes for symptom management. A qualitative approach was used for this study. The middle-range theory of self care of chronic illness served as a framework for data collection and analysis procedures. Data collection included distributing a survey to collect participants' demographic and sociodemographic data and utilizing a semi-structured interview guide to conduct one-on-one interviews with 31 participants. Interviews occurred via Zoom (n = 28) and in person (n = 3). Interview transcripts were uploaded in NVivo for data management. The research team created a codebook using theoretical constructs to assist with thematic analysis. Data are representative of a sample whose characteristics include undergraduate students ages 18 to 23 living with T1DM for 2 years or more who attended large, public, 4-year universities located in the southeastern United States. Three main themes were created using theoretical constructs: symptom detection experiences, symptom interpretation experiences, and symptom response experiences. Two subthemes were identified for each theme. Participants engaged in symptom management for blood glucose regulation through detecting changes in their blood glucose physiologically and via technology. Additionally, symptom interpretation involved analyzing blood glucose trends and determining common causes of blood glucose changes. Symptom response included immediately addressing hypoglycemia but delayed responses addressing hyperglycemia. Challenges were present responding to hypoglycemia; therefore, additional research is warranted to improve symptom response skills.

Sugar Accumulation Patterns and Transcriptome Analysis during the Developmental Stage of Small-Fruit Watermelon (Citrullus lanatus L.)

The sugar content in watermelon significantly influences its flavor. To understand the sugar accumulation pattern in small-fruited watermelon and identify candidate genes involved in sugar synthesis and conversion, we measured the sugar content (sucrose, fructose, and glucose) at five developmental stages: 10d, 16d, 22d, 28d, and 34d post-pollination. Two watermelon varieties with the largest sugar content difference at 28d post-pollination (high-sugar G38-28 and low-sugar 482276-28) were selected for transcriptome sequencing. Differentially expressed genes (DEGs) were validated using RT-qPCR. Additionally, the sugar contents of three commercial varieties (‘Su Meng NO.5’, ‘Su Meng NO.6’, ‘Su Meng NO.7’) and their parents were compared at five stages. Results showed glucose and fructose levels peaked between 22d and 28d, followed by a decrease, while sucrose content continuously increased. F1 hybrids exhibited glucose and sucrose trends similar to their paternal parent and fructose trends similar to their maternal parent. Transcriptome sequencing identified 9337 DEGs (5072 upregulated and 4265 downregulated). Gene Ontology analysis highlighted overrepresentation in categories such as pectinase and oxidoreductase activity. KEGG analysis identified 12 DEGs involved in sugar synthesis and conversion pathways, including phenylpropanoid biosynthesis and pentose and glucuronate interconversions. RT-qPCR validation corroborated the transcriptome data. These findings explain the distinct sugar accumulation patterns in G38-28 and 482276-28 at the transcriptional level, offering insights for genetic breeding and regulation of key sugar-related genes in watermelon.

Prediction of personalised postprandial glycaemic response in type 1 diabetes mellitus.

Patients with type 1 diabetes (T1D) face unique challenges in glycaemic control due to the complexity and uniqueness of the dietary structure in China, especially in terms of postprandial glycaemic response (PPGR). This study aimed to establish a personalized model for predicting PPGR in patients with T1D. Data provided by the First People's Hospital of Yunnan Province, 13 patients with T1D, were recruited and provided with an intervention for at least two weeks. All patients were asked to wear a continuous glucose monitoring (CGM) device under free-living conditions during the study period. To tackle the challenge of incomplete data from wearable devices for CGM measurements, the GAIN method was used in this paper to achieve a more rational interpolation process. In this study, patients' PPGRs were calculated, and a LightGBM prediction model was constructed based on a Bayesian hyperparameter optimisation algorithm and a random search algorithm, which integrated glucose measurement, insulin dose, dietary nutrient content, blood measurement and anthropometry as inputs. The experimental outcomes revealed that the PPGR prediction model presented in this paper demonstrated superior accuracy (R=0.63) compared to both the carbohydrate content only model (R=0.14) and the baseline model emulating the standard of care for insulin administration (R=0.43). In addition, the interpretation of the model using the SHAP method showed that blood glucose levels at meals and blood glucose trends 30 minutes before meals were the most important features of the model. The proposed model offers a heightened precision in predicting PPGR in patients with T1D, so it can better guide the diet plan and insulin intake dose of patients with T1D.

Advancing elderly diabetes care: exploring the usability and acceptance of continuous glucose monitoring (CGM)

ObjectivesThis study aimed to evaluate the acceptability, usability, compliance, and satisfaction of Continuous Glucose Monitoring (CGM) among elderly diabetic patients. DesignUtilizing a mixed-methods approach, the study involved 30 participants, averaging 74.79 years in age. Participants wore two CGM devices, and their experiences, along with survey data, were comprehensively analyzed to gauge the effectiveness of CGM in managing diabetes. ResultsThe study demonstrated that -CGM- is highly usable and acceptable among elderly diabetic patients. Participants effectively utilized CGM to monitor and predict blood glucose trends, positively influencing their glucose control and lifestyle. The average adherence rate was found to be 81 %, indicating a substantial level of effective self-management and treatment decision-making. ConclusionThe study recommends developing CGM educational programs tailored for the elderly, educating healthcare professionals, expanding insurance coverage for CGM, and promoting real-time CGM technology to improve usability and acceptance among the elderly.

Japanese candlestick charts for diabetes.

Continuous glucose monitoring (CGM) is a popular technology among the diabetic population, especially in patients with type 1 diabetes and those with type 2 diabetes treated with insulin. The American Diabetes Association recommends standardization of CGM reports with visual cues, such as the ambulatory glucose profile. Nevertheless, interpreting this report requires training and time for CGM to be cost-efficient. In this work it has been proposed to incorporate Japanese candlestick charts in glucose monitoring. These graphs are used in price analysis in financial markets and are easier to view. Each candle provides extra information to make prudent decisions since it reports the opening, maximum, minimum and closing glucose levels of the chosen time frame, usually the daily one. The Japanese candlestick chart is an interesting tool to be considered in glucose control. This graphic representation allows identification of glucose trends easily through the colors of the candles and maximum and minimum glucose values.

Perfusion Measures and Outcomes (PERForm) registry: First annual report.

The Perfusion Measures and Outcomes (PERForm) registry was established in 2010 to advance cardiopulmonary bypass (CPB) practices and outcomes. The registry is maintained through the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative and is the official registry of the American Society of Extracorporeal Technology. This first annual PERForm registry report summarizes patient characteristics as well as CPB-related practice patterns in adult (≥18 years of age) patients between 2019 and 2022 from 42 participating hospitals. Data from PERForm are probabilistically matched to institutional surgical registry data. Trends in myocardial protection, glucose, anticoagulation, temperature, anemia (hematocrit), and fluid management are summarized. Additionally, trends in equipment (hardware/disposables) utilization and employed patient safety practices are reported. A total of 40,777 adult patients undergoing CPB were matched to institutional surgical registry data from 42 hospitals. Among these patients, 54.9% underwent a CABG procedure, 71.6% were male, and the median (IQR) age was 66.0 [58.0, 73.0] years. Overall, 33.1% of the CPB procedures utilized a roller pump for the arterial pump device, and a perfusion checklist was employed 99.6% of the time. The use of conventional ultrafiltration decreased over the study period (2019 vs. 2022; 27.1% vs. 24.9%) while the median (IQR) last hematocrit on CPB has remained stable [27.0 (24.0, 30.0) vs. 27.0 (24.0, 30.0)]. Pump sucker termination before protamine administration increased over the study period: (54.8% vs. 75.9%). Few robust clinical registries exist to collect data regarding the practice of CPB. Although data submitted to the PERForm registry demonstrate overall compliance with published perfusion evidence-based guidelines, noted opportunities to advance patient safety and outcomes remain.

Differences in glycemic trends due to reconstruction methods after proximal gastrectomy from the perspective of continuous glucose-monitoring.

In recent years, clinicians have focused on the importance of preventing hypoglycemia. We evaluated the impact of different reconstruction procedures after proximal gastrectomy on glycemic variability in non-diabetic patients with gastric cancer. This prospective observational study was conducted between April 2020 and March 2023. Flash continuous glucose-monitoring, a novel method for assessing glycemic control, was used to evaluate the glycemic profiles after gastrectomy. A flash continuous glucose-monitoring sensor was placed subcutaneously at the time of discharge, and glucose trends were evaluated for 2weeks. The anastomotic methods for proximal gastrectomy were esophagogastrostomy in 10 patients and double-tract reconstruction in 10 patients. The time below this range (glucose levels < 70mg/dL) was significantly higher in the double-tract reconstruction group than in the esophagogastrostomy group (p = 0.049). A higher nocturnal time below this range was significantly correlated with an older age and double-tract reconstruction (p = 0.025 and p = 0.025, respectively). These findings provide new insights into reconstruction methods after proximal gastrectomy by assessing postoperative hypoglycemia in non-diabetic patients with gastric cancer.

Galactonate bio-preparation from cheese whey waste and its application as a novel bio-retarder

Cheese whey, as the major byproduct in cheese making, contains significant amounts of lactose, which can be efficiently hydrolyzed to glucose and galactose. Therefore, it is a potential resource for producing gluconic acid (GA) and galactonic acid (GalA) by Gluconobacter oxydans (G. oxydans). The glucose can be preferentially and rapidly bio-oxidized into GA by G. oxydans, however, the preserved GA and galactose would be simultaneously metabolized, meaning that the GA and GalA cannot be co-produced. Therefore, based on the kinetics of biphasic trend for glucose and galactose metabolism, a novel approach involving the integration of bio-oxidation and electrodialysis techniques was developed to sequentially convert glucose and galactose into GA and GalA, correspondingly. As a result, 79.2 g/L GA and 75.1 g/L GalA could be co-produced step by step from the enzymatic hydrolysate that contain approximately 80 g/L glucose and 80 g/L galactose. Furthermore, in this study, the evaluation experiment of GalA as cement additive suggested that it could be used as a novel bio-retarder with an excellent retarding effect, providing a new idea for cheese whey waste utilization.

Perioperative changes of serum orphanin in diabetic patients and its relationship with sympathetic nervous system

The occurrence of cardiovascular events in diabetic patients during the perioperative period is related to the activation of sympathetic nerves. Basic research shows that serum nociceptin/orphanin FQ (N/OFQ) levels in diabetic neuropathy rats increased, and N/OFQ reduces the release of norepinephrine (NE). We hypothesize that N/OFQ will affect the sympathetic nervous system during perioperative myocardium of diabetic patients. 66 patients with unilateral knee arthroplasty were divided into diabetes group (D group) and non-diabetes group (N group). Measured blood glucose, serum NE, N/OFQ concentrations at the 30 min before anesthesia (T0), 1 h after surgery (T1), 24 h after surgery (T2) and the cardiac troponinI (cTnI) concentration at T0 and T2. Compared with N group, the concentration of blood glucose, N/OFQ and cTnI in D group was higher and the NE was lower at T0 (P < 0.05). At T1, the blood glucose, N/OFQ, NE concentrations of D group increased, only the blood glucose increased in N group (P < 0.05). Serum N/OFQ of D group from T0 to T1 was correlated with the change trend of blood glucose, NE concentration from T0 to T1 and cTnI from T0 to T2(r = 0.386, P = 0.027; r = 0.350, P = 0.046; r = 0.363, P = 0.038). The outcomes demonstrated that the preoperative serum N/OFQ concentration in diabetic patients was increased, and the increase in N/OFQ concentration during the operation was related to the increase in NE and cTnI concentrations, perioperative N/OFQ may mediate myocardial injury through sympathetic nervous system.

Patterns and Trends in Continuous Glucose Monitoring Utilization Among Commercially Insured Individuals With Type 1 Diabetes: 2010-2013 to 2016-2019.

Prior studies suggest that only ∼30% of patients with type 1 diabetes use continuous glucose monitoring (CGM), but most studies to date focused on children and young adults seen by endocrinologists or in academic centers. This study examined national trends in CGM utilization among commercially insured children and adults with type 1 diabetes. Overall, CGM utilization was 20.12% in 2010-2013 and 49.78% in 2016-2019, reflecting a 2.5-fold increase in utilization within a period of <10 years. Identifying populations with low CGM use is a necessary first step in developing targeted interventions to increase CGM uptake.

Feasibility and acceptability of the use of flash glucose monitoring encountered by Indigenous Australians with type 2 diabetes mellitus: initial experiences from a pilot study

BackgroundType 2 diabetes mellitus (T2DM) is highly prevalent within the Indigenous Australian community. Novel glucose monitoring technology offers an accurate approach to glycaemic management, providing real-time information on glucose levels and trends. The acceptability and feasibilility of this technology in Indigenous Australians with T2DM has not been investigated.ObjectiveThis feasibility phenomenological study aims to understand the experiences of Indigenous Australians with T2DM using flash glucose monitoring (FGM).MethodsIndigenous Australians with T2DM receiving injectable therapy (n = 8) who used FGM (Abbott Freestyle Libre) for 6-months, as part of a clinical trial, participated in semi-structured interviews. Thematic analysis of the interviews was performed using NVivo12 Plus qualitative data analysis software (QSR International).ResultsSix major themes emerged: 1) FGM was highly acceptable to the individual; 2) FGM’s convenience was its biggest benefit; 3) data from FGM was a tool to modify lifestyle choices; 4) FGM needed to be complemented with health professional support; 5) FGM can be a tool to engage communities in diabetes management; and 6) cost of the device is a barrier to future use.ConclusionsIndigenous Australians with T2DM had positive experiences with FGM. This study highlights future steps to ensure likelihood of FGM is acceptable and effective within the wider Indigenous Australian community.