Glucose Levels Research Articles

The Functional Role of microRNAs and mRNAs in Diabetic Kidney Disease: A Review.

Diabetes is a group of diseases marked by poor control of blood glucose levels. Diabetes mellitus (DM) occurs when pancreatic cells fail to make insulin, which is required to keep blood glucose levels stable, disorders, and so on. High glucose levels in the blood induce diabetic effects, which can cause catastrophic damage to bodily organs such as the eyes and lower extremities. Diabetes is classified into many forms, one of which is controlled by hyperglycemia or Diabetic Kidney Disease (DKD), and another that is not controlled by hyperglycemia (nondiabetic kidney disease or NDKD) and is caused by other factors such as hypertension, hereditary. DKD is associated with diabetic nephropathy (DN), a leading cause of chronic kidney disease (CKD) and end-stage renal failure. The disease is characterized by glomerular basement membrane thickening, glomerular sclerosis, and mesangial expansion, resulting in a progressive decrease in glomerular filtration rate, glomerular hypertension, and renal failure or nephrotic syndrome. It is also represented by some microvascular complications such as nerve ischemia produced by intracellular metabolic changes, microvascular illness, and the direct impact of excessive blood glucose on neuronal activity. Therefore, DKD-induced nephrotic failure is worse than NDKD. MicroRNAs (miRNAs) are important in the development and progression of several diseases, including diabetic kidney disease (DKD). These dysregulated miRNAs can impact various cellular processes, including inflammation, fibrosis, oxidative stress, and apoptosis, all of which are implicated during DKD. MiRNAs can alter the course of DKD by targeting several essential mechanisms. Understanding the miRNAs implicated in DKD and their involvement in disease development might lead to identifying possible therapeutic targets for DKD prevention and therapy. Therefore, this review focuses specifically on DKD-associated DN, as well as how in-silico approaches may aid in improving the management of the disease.

Effect of the Combined Treatment of Taoren Chengqi Decoction with Laser Photocoagulation on Diabetic Retinopathy

This study investigates the therapeutic effect of the combined treatment of Taoren Chengqi decoction with laser photocoagulation on DR. In animal experiments, A total of 18 rats were used and randomly divided into blank groups, model groups, and treatment groups. The rats in the model group and treatment group were intraperitoneally injected with 60 mg/kg streptozotocin. Moreover, the TCT group was gavaged with Tao-ren Cheng-qi decoction, while the other groups received an equivalent volume of normal saline once daily for 8 weeks. Fasting blood glucose (FBG) and serum interleukin (IL)-6 and IL-1β were determined. In the clinical trial, a total of 80 patients with DR were divided into a laser group (treated with laser photocoagulation) and a combination group (treated with laser photocoagulation+Taoren Chengqi decoction). The central macular thickness (CMT), best-corrected visual acuity (BCVA), and serum levels of high-density lipoprotein cholesterol, low-density-lipoprotein cholesterol, total cholesterol, triglycerides, glycated hemoglobin, and hypoxia-inducible factor 1α were measured in the patients. In animal experiments, we observe that Tao-ren Cheng-qi decoction can effectively reduce the levels of FBG, IL-6, and IL-1β in rats models with DR. Clinical studies revealed that the combination of Taoren Chengqi decoction with laser photocoagulation reduced the levels of blood glucose and lipid-related indices, and improved the inflammatory state, BCVA, and CMT. Therefore, this study suggests that the combined treatment of laser surgery and Taoren Chengqi decoction can be considered an optimal therapeutic approach for patients with DR.

Research-based Analytical Procedures to Evaluate Diabetic Biomarkers and Related Parameters: In Vitro and In Vivo Methods.

The degenerative tendency of diabetes leads to micro- and macrovascular complications due to abnormal levels of biochemicals, particularly in patients with poor diabetic control. Diabetes is supposed to be treated by reducing blood glucose levels, scavenging free radicals, and maintaining other relevant parameters close to normal ranges. In preclinical studies, numerous in vivo trials on animals as well as in vitro tests are used to assess the antidiabetic and antioxidant effects of the test substances. Since a substance that performs poorly in vitro won't perform better in vivo, the outcomes of in vitro studies can be utilized as a direct indicator of in vivo activities. The objective of the present study is to provide research scholars with a comprehensive overview of laboratory methods and procedures for a few selected diabetic biomarkers and related parameters. The search was conducted on scientific database portals such as ScienceDirect, PubMed, Google Scholar, BASE, DOAJ, etc. Conclusion: The development of new biomarkers is greatly facilitated by modern technology such as cell culture research, lipidomics study, microRNA biomarkers, machine learning techniques, and improved electron microscopies. These biomarkers do, however, have some usage restrictions. There is a critical need to find more accurate and sensitive biomarkers. With a few modifications, these biomarkers can be used with or even replace conventional markers of diabetes.

Burden and Coping Strategies of Hypoglycemia in People with Diabetes.

Hypoglycemia is a limiting adverse effect of glucose-lowering medications and particularly insulin replacement therapy. This review provides insights into the burden of hypoglycemia in the management of diabetes and outlines strategies available to reduce the risk of hypoglycemia and improve patients' well-being. People with type 1 diabetes are primarily affected by hypoglycemic episodes which are associated with direct physical harms like injuries and cardiac events as well as indirect psychosocial consequences including constant anxiety, absenteeism, increased healthcare costs and overall poorer quality of life. These complications are more prominent amongst individuals with hypoglycemia unawareness or overnight hypoglycemia and could even extend to caregivers such as parents of children with diabetes. Patients experiencing frequent or severe hypoglycemic events might also develop a pathological fear of hypoglycemia and adopt aberrant behaviors intending to maintain higher blood glucose levels. Modern pharmaceutical options with a safer profile in terms of hypoglycemia are available including novel basal insulins with lower rates of nocturnal hypoglycemia along with ultra-rapid-acting insulin analogs with a shorter duration of action that might avert late post-meal hypoglycemia. Continuous glucose monitoring and sensor-augmented insulin pump therapy with low glucose suspend technology can also prevent hypoglycemia, although concerns about cost and patient satisfaction remain. Advancements in insulin therapy and technological modalities should be coupled with ongoing education and support for patients to become co-managers of their disease and reduce the risk of hypoglycemia.

The Effect of City-Level Sugar-Sweetened Beverage Taxes on Longitudinal HbA1c and Incident Diabetes in Adults With Prediabetes.

Prediabetes, which is a condition characterized by higher-than-normal blood glucose levels that are under the threshold for diabetes, impacts over one-third of U.S. adults. Excise taxes on sugar-sweetened beverages (SSBs) are a proposed policy intervention to lower population consumption of SSBs and generate revenue to support health-related programs, thus potentially delaying or preventing the development of diabetes in individuals with prediabetes. We leveraged data from Kaiser Permanente in California to examine the impact of SSB taxes in California on individual-level mean HbA1c levels and rates of incident diabetes. We compared two outcomes, mean HbA1c levels and rates of incident diabetes, among a matched cohort of adults with prediabetes who lived and did not live in SSB excise tax cities, using outcomes collected in the 6 years prior and 4 years following SSB tax implementation. We used multivariable linear mixed effects models to analyze longitudinal mean HbA1c and discrete-time survival models for incident diabetes. We included 68,658 adults in the analysis. In adjusted models, longitudinal mean HbA1c was 0.007% (95% CI 0.002, 0.011) higher in the tax cities compared with control individuals; while the estimated difference was statistically significant, it was not clinically significant (HbA1c <0.5%). There was no significant difference in the risk of incident diabetes between individuals living in tax and control cities. We found no clinically significant association between SSB taxes and either longitudinal mean HbA1c or incident diabetes among adults with prediabetes in the 4 years following SSB tax implementation.

Enhancement of the Blood Glucose Level for Diabetic Patients Based on an Adaptive Auto-Tuned PID Controller via Meta-Heuristic Methods

Enhancement of the Blood Glucose Level for Diabetic Patients Based on an Adaptive Auto-Tuned PID Controller via Meta-Heuristic Methods

Impact of hospital-community diabetes management intervention in Central Region, Ghana: A retrospective study

ObjectiveEffective diabetes management remains suboptimal in low-resourced countries including Ghana. We determined the effectiveness of hospital-community link diabetes management intervention on glycaemic control and other outcomes. MethodsA retrospective study design, using secondary data from the Ghana-Netherlands for Health Foundation diabetes programme. The z-test was used for proportions, to compare parameters between baseline (2017) and endpoint (2022). The Friedman test was used to assess changes in blood glucose levels, and the multivariable Logistic regression to identify factors associated with blood glucose control. ResultsAnalyses of 251 clinical records showed decline in median blood glucose levels across six years from 8.8 mmol/L (7.2–12.9) in 2017 to 6.5 mmol/L (5.7–7.2) (p = 0.001) in 2022, recording 43 % increase in patients attaining glycaemic control in 2022 (p = 0.001). The Friedman test showed significant reduction in glucose levels (χ2 = 319.2, p = 0.001), with an effect size of 0.25 using the Kendall test. The logistic regression analyses revealed that patients on metformin and Glibenclamide combination were more likely to achieve glycaemic control than those on metformin monotherapy (adjusted OR = 7.30, 95 % CI 2.31–23.01, p = 0.001). ConclusionThe intervention achieved significant reduction in blood glucose levels. Patients with diabetes benefit from the hospital-community link diabetes management intervention regarding glycaemic control.

The role of accelerometer-derived sleep traits on glycated haemoglobin and glucose levels: a Mendelian randomization study

Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be ‘objective’ measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.

Adoption of Diabetes Technology in Denmark: Continuous Glucose Monitor as Time-Machine

ABSTRACT Health technologies to monitor glucose values are an important part of daily diabetes self-care. Based on 12 months of fieldwork in Denmark with 14 people with type 2 diabetes, I explore people’s experience of living with Continuous Glucose Monitoring. This new technology automatically measures glucose levels throughout the day but is not yet common in type 2 diabetes treatment in Denmark. In this article, I capture the social shaping of Continuous Glucose Monitoring, employing the concept of time. I show how adoption of the technology is embedded in a form of biographical time. This refers to people’s use of the technology linked to their stories about themselves. Drawing on a notion of habitus, people’s embodied past experiences and future prospects come to shape its use, I propose. My main claim is that while people with diabetes implement the technology into their lives in unique ways, adapting it to their circumstances and social conditions, practice of Continuous Glucose Monitoring reproduce social structures. This is evinced, I argue, in people’s tinkering with the technology and the frames of reference used to inform it. I introduce the term “tinkering in time”, highlighting the introduction of new health technology within the frame of lived human time.

Controlled synthesized of ternary Cu-Co-Ni-S sulfides nanoporous network structure on carbon fiber paper: a superior catalytic electrode for highly-sensitive glucose sensing

BackgroundEfficient monitoring of glucose concentration in the human body necessitates the utilization of electrochemically active sensing materials in nonenzymatic glucose sensors. However, prevailing limitations such as intricate fabrication processes, lower sensitivity, and instability impede their practical application. Herein, ternary Cu-Co-Ni-S sulfides nanoporous network structure was synthesized on carbon fiber paper (CP) by an ultrafast, facile, and controllable technique through on-step cyclic voltammetry, serving as a superior self-supporting catalytic electrode for the high-performance glucose sensor.ResultsThe direct growth of free-standing Cu-Co-Ni-S on the interconnected three-dimensional (3D) network of CP boosted the active site of the composites, improved ion diffusion kinetics, and significantly promoted the electron transfer rate. The multiple oxidation states and synergistic effects among Co, Ni, Cu, and S further promoted glucose electrooxidation. The well-architected Cu-Co-Ni-S/CP presented exceptional electrocatalytic properties for glucose with satisfied linearity of a broad range from 0.3 to 16,000 μM and high sensitivity of 6829 μA mM− 1 cm− 2. Furthermore, the novel sensor demonstrated excellent selectivity and storage stability, which could successfully evaluate the glucose levels in human serum. Notably, the novel Cu-Co-Ni-S/CP showed favorable biocompatibility, proving its potential for in vivo glucose monitoring.ConclusionThe proposed 3D hierarchical morphology self-supported electrode sensor, which demonstrates appealing analysis behavior for glucose electrooxidation, holds great promise for the next generation of high-performance glucose sensors.

Towards a better understanding of idiopathic epilepsy through metabolic fingerprinting of cerebrospinal fluid in dogs

Cerebrospinal fluid metabolomics is a promising research technology in the elucidation of nervous system disorders. Therefore, in this work, a cerebrospinal fluid (CSF) metabolomics method using liquid chromatography coupled to mass spectrometry was optimized and validated to cover a wide range of metabolites. An acceptable coefficient of variance regarding instrumental, within-lab and intra-assay precision was found for 95, 70 and 96 of 102 targeted metabolites, together with 1256, 676 and 976 untargeted compounds, respectively. Moreover, approximately 75% of targeted metabolites and 50% of untargeted compounds displayed good linearity across different dilution ranges. Consequently, metabolic alterations in CSF of dogs with idiopathic epilepsy (IE) were studied by comparing CSF of dogs diagnosed with IE (Tier II) to dogs with non-brain related disease. Targeted metabolome analysis revealed higher levels of cortisol, creatinine, glucose, hippuric acid, mannose, pantothenol, and 2-phenylethylamine (P values < 0.05) in CSF of dogs with IE, whereas CSF of dogs with IE showed lower levels of spermidine (P value = 0.02). Untargeted CSF metabolic fingerprints discriminated dogs with IE from dogs with non-brain related disease using Orthogonal Partial Least Squares Discriminant Analysis (R2(Y) = 0.997, Q2(Y) = 0.828), from which norepinephrine was putatively identified as an important discriminative metabolite.

Combined Sleeve Gastrectomy and Omentoplasty Improves Inflammation and Insulin Resistance in Obese Rats with Type II Diabetes Mellitus: A Randomized Controlled Trials

BACKGROUND: Diabetes mellitus (DM) is often associated with obesity, which can lead to chronic inflammation. Sleeve gastrectomy (SG) is a common treatment for obesity. Combining SG with omentoplasty, might help reducing inflammation in pancreatic beta cells. However, there is limited research regarding the combined effects of SG and omentoplasty in type 2 DM (T2DM). This study was conducted to fill this gap by evaluating the impact on body weight, insulin resistance, glucagon expression, and levels of interleukins (IL)-1, IL-6, and IL-10 in obese rats with type II DM.METHODS: An experimental study was conducted on 18 obese Wistar rats with DM that were randomized into: control, T1 (SG), and T2 (SG + omentoplasty). SG involved the surgical removal of a portion of the stomach to reduce its size, while omentoplasty utilized the omentum to target inflammation in pancreatic beta cells. Venous blood samples were taken from subjects one day before and ten days after the intervention to measure the biomedical parameters with various methods. Data was statistically analyzed using paired t-tests for pre-test and post-test differences, and Post Hoc tests or Mann-Whitney tests for hypothesis testing.RESULTS: All rats were confirmed to have obesity and DM according to the Lee index and blood glucose levels. T2 group exhibited a significant decrease in body weight, homeostatic model assessment of insulin resistance (HOMA-IR) values were lower, and glucagon expression, IL-1, IL-6, and IL-10 levels were significantly greater compared to both control and T1 groups.CONCLUSION: The combination of SG and omentoplasty significantly improves inflammation and insulin resistance in obese rats with T2DM.KEYWORDS: diabetes mellitus, sleeve gastrectomy, omentoplasty, inflammation, obesity

Adaptive selection at G6PD and disparities in diabetes complications.

Diabetes complications occur at higher rates in individuals of African ancestry. Glucose-6-phosphate dehydrogenase deficiency (G6PDdef), common in some African populations, confers malaria resistance, and reduces hemoglobin A1c (HbA1c) levels by shortening erythrocyte lifespan. In a combined-ancestry genome-wide association study of diabetic retinopathy, we identified nine loci including a G6PDdef causal variant, rs1050828 -T (Val98Met), which was also associated with increased risk of other diabetes complications. The effect of rs1050828 -T on retinopathy was fully mediated by glucose levels. In the years preceding diabetes diagnosis and insulin prescription, glucose levels were significantly higher and HbA1c significantly lower in those with versus without G6PDdef. In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, participants with G6PDdef had significantly higher hazards of incident retinopathy and neuropathy. At the same HbA1c levels, G6PDdef participants in both ACCORD and the Million Veteran Program had significantly increased risk of retinopathy. We estimate that 12% and 9% of diabetic retinopathy and neuropathy cases, respectively, in participants of African ancestry are due to this exposure. Across continentally defined ancestral populations, the differences in frequency of rs1050828 -T and other G6PDdef alleles contribute to disparities in diabetes complications. Diabetes management guided by glucose or potentially genotype-adjusted HbA1c levels could lead to more timely diagnoses and appropriate intensification of therapy, decreasing the risk of diabetes complications in patients with G6PDdef alleles.

Alpha-amylase Activity in Serum is Positively Associated with C-reactive Protein in Obesity and Diabetes

Alpha-amylase plays a critical job in metabolic homeostasis. Appraisal of alpha-amylase activity in metabolic disorders, for example, obesity and diabetes are important. The current investigation was meant to evaluate the relationship of alpha-amylase activity with C-reactive protein in obesity and diabetes. Alpha-amylase activity along with different biochemical markers like glucose level, triglyceride, total cholesterol, C-responsive protein, and creatinine level were analyzed in healthy, obese, and diabetes populations. In obese and diabetes, a significant deviation (p&lt;0.05) was seen in the degree of biochemical markers including blood glucose, lipid profile, C-reactive protein (CRP), creatinine, and alpha-amylase action when compared with healthy volunteers. The alpha-amylase activity was found to be strongly associated (p&lt; 0.01) with Body Mass Index (BMI), blood glucose level, and duration of diabetes Thus, it can be stated that alpha-amylase can initiate a cross-linking mechanism between BMI and blood glucose level facilitating the propensity of obesity and diabetes. Moreover, alpha-amylase indicated a positive correlation with CRP, a marker for inflammation, proposing a complex job in mediating inflammation in obesity (r= 0.486, p &lt; 0.01) and diabetes (r=0.507, p&lt;0.01). Serum creatinine was demonstrated as an insignificant positive correlation with alpha-amylase activity in obesity and type-2 diabetes. Alpha-amylase can be considered as a significant hazard factor in the pathogenesis of obesity and diabetes-related complications. Dhaka Univ. J. Pharm. Sci. 23(1): 7-12, 2024 (June)

Design and Implementation of a Low-Power Device for Non-Invasive Blood Glucose

Glucose is a simple sugar molecule. The chemical formula of this sugar molecule is C6H12O6. This means that the glucose molecule contains six carbon atoms (C), twelve hydrogen atoms (H), and six oxygen atoms (O). In human blood, the molecule glucose circulates as blood sugar. Normally, after eating or drinking, our bodies break down the sugars in food and use them to obtain energy for our cells. To execute this process, our pancreas produces insulin. Insulin “pulls” sugar from the blood and puts it into the cells for use. If someone has diabetes, their pancreas cannot produce enough insulin. As a result, the level of glucose in their blood rises. This can lead to many potential complications, including blindness, disease, nerve damage, amputation, stroke, heart attack, damage to blood vessels, etc. In this study, a non-invasive and therefore easily usable method for monitoring blood glucose was developed. With the experiment carried out, it was possible to measure glucose levels continuously, thus eliminating the disadvantages of invasive systems. Near-IR sensors (optical sensors) were used to estimate the concentration of glucose in blood; these sensors have a wavelength of 940 nm. The sensor was placed on a small black parallelepiped-shaped box on the tip of the finger and the output of the optical sensor was then connected to a microcontroller at the analogue input. Another sensor used, but only to provide more medical information, was the heartbeat sensor, inserted into an armband (along with the microprocessor). After processing and linear regression analysis, the glucose level was predicted, and data were sent via the Bluetooth network to a developed APP. The results of the implemented device were compared with available invasive methods (commercial products). The hardware consisted of a microcontroller, a near-IR optical sensor, a heartbeat sensor, and a Bluetooth module. Another objective of this experiment using low-cost and low-power hardware was to not carry out complex processing of data from the sensors. Our practical laboratory experiment resulted in an error of 2.86 per cent when compared to a commercial product, with a hardware cost of EUR 8 and a consumption of 50 mA.

MODY diabetes as an orphan disease: literature review

BACKGROUND. Maturity-onset diabetes of the young (MODY) is the most common form of monogenic diabetes, usually diagnosed before the age of 30 years in non-obese patients with a family history of diabetes mellitus (DM). MODY is relatively rare compared to type 1 and type 2 DM, with various literature estimates affecting only 1-2 % of people with diabetes, but because it is rare, clinicians may misdiagnose it as type 1 or type 2 DM, which happens in most cases. Unlike type 1 DM patients, patients with MODY have preserved pancreatic β-cell function, so lifestyle modification in combination with glucose-lowering therapy, which in some cases may include insulin, may be sufficient interventions as treatment. OBJECTIVE. With the help of literary sources, familiarize yourself with the classification, clinical manifestations, aspects of treatment and prognosis of the main forms of MODY diabetes. MATERIALS AND METHODS. Object: MODY diabetes as an orphan disease. Research method: a review of literary sources. RESULTS. MODY is most often an autosomal dominant disease and is divided into subtypes (MODY1 to MODY14) based on genetic mutation. Subtypes 1-3 are the most common, accounting for 95 % of cases. Treatment usually includes diet, exercise, and, in some cases, insulin or oral hypoglycemic drugs. In general, the prognosis can be quite favorable, provided that carbohydrate metabolism is compensated. CONCLUSIONS. MODY diabetes is a complex genetically determined pathology, and understanding the features of this disease, diagnosis and treatment are of great importance for patients and their families. The development of modern methods of treatment and monitoring of glucose, such as insulin pumps, 24-hour glycemic monitoring and other technologies, may improve the prognosis for patients with MODY. Each patient with MODY diabetes has individual characteristics, which leaves an imprint on the prognosis of the disease and approaches to treatment. The main goal is to maintain a normal level of glucose in the blood to avoid complications.

A nomogram for predicting the risk of cancer-related cognitive impairment in breast cancer patients based on a scientific symptom model

Cancer-related cognitive impairment is a significant clinical challenge observed in patients with breast cancer, manifesting during or after treatment. This impairment leads to deteriorations in memory, processing speed, attention, and executive functioning, which profoundly impact patients' occupational performance, daily living activities, and overall quality of life. Grounded in the Symptom Science Model 2.0, this study investigates the contributing factors to Cancer-related cognitive impairment in breast cancer patients and develops a predictive nomogram for this demographic. Employing both univariate and multivariate logistic regression analyses, this investigation delineates the predictive factors influencing outcomes in breast cancer patients. A nomogram was constructed leveraging these identified predictive factors, accompanied by internal validation through bootstrap resampling methodology (1000 bootstrap samples). The efficacy of the predictive model was assessed by employing the Hosmer–Lemeshow goodness-of-fit test and calibration curves. The prevalence of cognitive impairment in breast cancer patients was identified to be 45.83%.Multivariate logistic regression analysis identified the independent predictors of Cancer-related cognitive impairment in breast cancer patients as place of residence, educational level, chemotherapy, benefit finding, post-traumatic growth, anxiety, fear of cancer progression, and fasting blood glucose levels. these factors were integrated into the nomogram. The Hosmer–Lemeshow goodness-of-fit test demonstrated that the prediction model was appropriately calibrated (χ2 = 11.520, P = 0.174). Furthermore, the model exhibited an area under the curve of 0.955 (95% CI 0.939 to 0.971) and a sensitivity of 0.906, evidencing its robust discriminative capacity and accuracy. Utilizing the Symptom Science Model 2.0 as a framework, this study comprehensively examines the multifaceted factors influencing Cancer-related cognitive impairment in breast cancer patients, spanning five critical domains: complex symptoms, phenotypic characterization, biobehavioral factors, social determinants of health, and patient-centered experiences. A predictive nomogram model was established, demonstrating satisfactory predictive accuracy and capability. This model is capable of identifying breast cancer patients with cognitive impairments with high precision. The findings furnish empirical evidence in support of the early detection, diagnosis, and intervention strategies for high-risk breast cancer patients afflicted with Cancer-related cognitive impairment.

Incident diabetes in adolescents using antidepressant: a systematic review and meta-analysis.

The use of antidepressants has been on the rise among adolescents and young adults, populations also increasingly at risk for type 2 diabetes. However, the relationship between antidepressant uses and diabetes incidence in these age groups remains poorly understood. Adhering to PRISMA guidelines and the Cochrane Handbook, we conducted a comprehensive search in PubMed, Scopus, Embase, and Web of Science up to 21 February 2024, registering our protocol on PROSPERO (CRD42024516272). Six studies, ranging from 16, 470 to 1, 582, 914 participants and spanning 2010 to 2023 across North America, Europe, and Asia, were included. The meta-analysis revealed a significant association between antidepressant use and diabetes onset, with 10 cases per 1, 000 observations (p < 0.01; I2 = 100%). Adolescents using high doses of antidepressants showed a 62% increased risk of developing diabetes compared to non-users or those on low doses (Risk ratio = 1.67; 95% CI 1.19-2.35; I2 = 87%; p < 0.01). The overall quality of the studies was high, with an average Newcastle-Ottawa Scale score of 7.66. Sensitivity analysis highlighted the robustness of these findings, except when removing specific studies, indicating potential sources of heterogeneity. Antidepressant use in adolescents is associated with a significantly increased risk of diabetes onset, particularly at higher doses. This finding underscores the necessity for vigilant monitoring of glucose levels in this population and warrants further investigation into the underlying mechanisms and long-term outcomes.

Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers

Type II diabetes mellitus (T2DM) is a rising global health burden due to its rapidly increasing prevalence worldwide, and can result in serious complications. Therefore, it is of utmost importance to identify individuals at risk as early as possible to avoid long-term T2DM complications. In this study, we developed an interpretable machine learning model leveraging baseline levels of biomarkers of oxidative stress (OS), inflammation, and mitochondrial dysfunction (MD) for identifying individuals at risk of developing T2DM. In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. Two iForest models were trained and evaluated through ten-fold cross-validation, the first on traditional biomarkers (BMI, blood glucose levels (BGL) and triglycerides) alone and the second including the additional aforementioned biomarkers. The second model outperformed the first across all evaluation metrics, particularly for F1 score and recall, which were increased from 0.61 ± 0.05 to 0.81 ± 0.05 and 0.57 ± 0.06 to 0.81 ± 0.08, respectively. The feature importance scores identified a novel combination of biomarkers, including interleukin-10 (IL-10), 8-isoprostane, humanin (HN), and oxidized glutathione (GSSG), which were revealed to be more influential than the traditional biomarkers in the outcome prediction. These results reveal a promising method for simultaneously predicting and understanding the risk of T2DM development and suggest possible pharmacological intervention to address inflammation and OS early in disease progression.

Glyceraldehyde metabolism in mouse brain and the entry of blood‐borne glyceraldehyde into the brain

AbstractD‐Glyceraldehyde, a reactive aldehyde metabolite of fructose and glucose, is neurotoxic in vitro by forming advanced glycation end products (AGEs) with neuronal proteins. In Alzheimer's disease brains, glyceraldehyde‐containing AGEs have been detected intracellularly and in extracellular plaques. However, little information exists on how the brain handles D‐glyceraldehyde metabolically or if glyceraldehyde crosses the blood–brain barrier from the circulation into the brain. We injected [U‐13C]‐D‐glyceraldehyde intravenously into awake mice and analyzed extracts of serum and brain by 13C nuclear magnetic resonance spectroscopy. 13C‐Labeling of brain lactate and glutamate indicated passage of D‐glyceraldehyde from blood to brain and glycolytic and oxidative D‐glyceraldehyde metabolism in brain cells. 13C‐Labeling of serum glucose and lactate through hepatic metabolism of [U‐13C]‐D‐glyceraldehyde could not explain the formation of 13C‐labeled lactate and glutamate in the brain. Cerebral glyceraldehyde dehydrogenase and reductase activities, leading to the formation of D‐glycerate and glycerol, respectively, were 0.27–0.28 nmol/mg/min; triokinase, which phosphorylates D‐glyceraldehyde to D‐glyceraldehyde‐3‐phosphate, has been demonstrated previously at low levels. Thus, D‐glyceraldehyde metabolism toward glycolysis could proceed both through D‐glycerate, glycerol, and D‐glyceraldehyde‐3‐phosphate. The aldehyde group of D‐glyceraldehyde was overwhelmingly hydrated into a diol in aqueous solution, but the diol dehydration rate greatly exceeded glyceraldehyde metabolism and did not restrict it. We conclude that (1) D‐glyceraldehyde crosses the blood–brain barrier, and so blood‐borne glyceraldehyde could contribute to AGE formation in the brain, (2) glyceraldehyde is taken up and metabolized by brain cells. Metabolism thus constitutes a detoxification mechanism for this reactive aldehyde, a mechanism that may be compromised in disease states.image