Type 2 diabetes mellitus (T2DM) is a globally prevalent metabolic disorder characterized by insulin resistance and dysfunction of islet cells. Endoplasmic reticulum (ER) stress plays a crucial role in the pathogenesis and progression of T2DM, especially in the function and survival of β-cells. β-cells are particularly sensitive to ER stress because they require substantial insulin synthesis and secretion energy. In the early stages of T2DM, the increased demand for insulin exacerbates β-cell ER stress. Although the unfolded protein response (UPR) can temporarily alleviate this stress, prolonged or excessive stress leads to pancreatic cell dysfunction and apoptosis, resulting in insufficient insulin secretion. This review explores the mechanisms of ER stress in T2DM, particularly its impact on islet cells. We discuss how ER stress activates UPR signaling pathways to regulate protein folding and degradation, but when stress becomes excessive, these pathways may contribute to β-cell death. A deeper understanding of how ER stress impacts islet cells could lead to the development of novel T2DM treatment strategies aimed at improving islet function and slowing disease progression.

Integral feedback control strategies have proven effective in regulating protein expression in unpredictable cellular environments. These strategies, grounded in model-based designs and control theory, have advanced synthetic biology applications. Autocatalytic integral feedback controllers, utilizing positive autoregulation for integral action, are one class of simplest architectures to design integrators. This class of controllers offers unique features, such as robustness against dilution effects and cellular growth, as well as the potential for synthetic realizations across different biological scales, owing to their similarity to self-regenerative behaviors widely observed in nature. Despite this, their potential has not yet been fully exploited. One key reason, we discuss, is that their effectiveness is often hindered by resource competition and context-dependent couplings. This study addresses these challenges using a multilayer feedback strategy. Our designs enabled population-level integral feedback and multicellular integrators, where the control function emerges as a property of coordinated interactions distributed across different cell populations coexisting in a multicellular consortium. We provide a generalized mathematical framework for modeling resource competition in complex genetic networks, supporting the design of intracellular control circuits. The use of our proposed multilayer autocatalytic controllers is examined in two typical control tasks that pose significant relevance to synthetic biology applications: concentration regulation and ratiometric control. We define a ratiometric control task and solve it using a variant of our controller. The effectiveness of our controller motifs is demonstrated through a range of application examples, from precise regulation of gene expression and gene ratios in embedded designs to population growth and coculture composition control in multicellular designs within engineered microbial ecosystems. These findings offer a versatile approach to achieving robust adaptation and homeostasis from subcellular to multicellular scales.

The increasing need for point-of-care (POC) testing has prompted a rise in the popularity of affordable biosensors that are eco-friendly, especially paper-based electrochemical sensors. This research introduces a biodegradable paper-based enzymatic biosensor for detecting glucose levels in intricate biological samples, such as cell lysates. This biosensor uses Prussian Blue (PB) as a mediator and glucose oxidase to detect glucose with excellent accuracy using direct electrochemical signals. Screen printing using Whatman filter paper produced a better biosensor than other substrates. The PB concentration of 12.5 mmol L-1 was found to be optimal and resulted in an operating potential of -0.1 V, which helped decrease interference from other active substances and improved its selectivity. Calibration was found to be linear up to a concentration of 2 mmol L-1 with a detection limit of 40 μmol L-1 and a limit of quantification of 120 μmol L-1. Moreover, experiments performed on cell lysates obtained from peripheral blood mononuclear cells (PBMCs) suggest the possible application of biosensors to measure glucose levels in vitro in both stimulated and unstimulated cells. This feature underscores its promise for use in monitoring metabolism and conducting diagnostic applications. The paper-based biosensor is an alternative to the current platform for the development of an eco-friendly, portable glucose-sensitive biosensor for point-of-care monitoring of glucose. Its flexibility and efficiency make it a strong candidate for use in the field of POC diagnostics, especially in areas of limited resources and in conditions where there is a problem with glucose dysregulation including diabetes and other related metabolic disorders.

The element fluorine, which is never found in nature in a free state, is the source of the fluoride ion. When fluoride intake is excessive, it can cause various impairments in living organism. This review aims to assess the relationship between fluoride exposure and glucose metabolism, considering positive, negative, and null findings, with a focus on its potential role in insulin resistance and diabetes-related complications.

Numerous studies that have demonstrated changes in blood glucose and insulin variations due to fluoride are included in our analysis on the bases of their relevance. Twenty significant research papers from Pubmed, Google Scholar, and Research Gate are included up to January 2025 using search terms such as "Fluoride," "Toxicity," "Diabetes," "Insulin resistance," "fluoride and diabetes," "fluoride and insulin," "fluoride and blood glucose" in this review. Of the 20 research papers, 14 involve normal organisms unaffected by diabetes or complications connected to the disease, serving as standard animal models, while 5 involve animals exposed to diabetes and 1 is a human population study.

The findings suggest a negative association between fluoride exposure and diabetes, as studies indicate fluoride's potential role in impairing glucose homeostasis and increasing insulin resistance. These research studies showed how fluoride affected the participants' blood sugar and diabetes-related complications.

This study highlights how important it is to comprehend how fluoride may contribute to diabetes or diabetes-related complications, and it makes recommendations for future research directions that might lead to the discovery of efficient treatment measures to avoid them.

GABA (γ-Aminobutyric Acid), a well-established inhibitory neurotransmitter in the central nervous system, has garnered considerable interest for its potential role in diabetes management, particularly due to its presence in pancreatic islets. This review aims to explore the therapeutic role of GABA in diabetes management and its potential mechanisms for antidiabetic effects. Relevant studies were searched across databases such as PubMed and ScienceDirect, applying strict eligibility criteria focused on GABA administration methods and diabetic models. The collective results showed that the administration of GABA in diabetic models resulted in remarkable enhancements in glucose and insulin homeostasis, favorable modifications in lipid profiles, and amelioration of dysfunctions across neural, hepatic, renal, and cardiac systems. The findings from the literature demonstrated that GABAergic signaling within pancreatic tissues can significantly contribute to the stimulation of β cell proliferation through the facilitation of a sustained trans-differentiation process, wherein glucagon-secreting α cells are converted into insulin-secreting β-like cells. In addition, activated GABAergic signaling can trigger the initiation of the PI3K/AKT signaling pathway within pancreatic tissues, leading to improved insulin signaling and maintained glucose homeostasis. GABAergic signaling can further function within hepatic tissues, promoting inhibitory effects on the expression of genes related to gluconeogenesis and lipogenesis. Moreover, GABA may enhance gut microbiota diversity by attenuating gut inflammation, attributable to its anti-inflammatory and immunomodulatory properties. Furthermore, the neuroprotective effects of GABA play a significant role in ameliorating neural disorders associated with diabetes by facilitating a substantial reduction in neuronal apoptosis. In conclusion, GABA emerges as a promising candidate for an antidiabetic agent; however, further research is highly encouraged to develop a rigorously designed framework that comprehensively identifies and optimizes the appropriate dosages and intervention methods for effectively managing and combating diabetes.

The identification of disease-specific subtypes can provide valuable insights into disease progression and potential individualized therapies, important aspects of precision medicine given the complex nature of disease heterogeneity. The advent of high-throughput technologies has enabled the generation and analysis of various molecular data types, such as single-cell RNA-seq, proteomic, and imaging datasets, on a large scale. While these datasets offer opportunities for subtype discovery, they also pose challenges in finding subtype signatures due to their high dimensionality. Feature selection, a key step in the machine learning pipeline, involves selecting signatures that reduce feature size for more efficient downstream computational analysis. Although many existing methods focus on selecting features that differentiate known diseases or cell states, they often struggle to identify features that both preserve heterogeneity and reveal subtypes. To address this, we utilized deep metric learning-based feature embedding to explore the statistical properties of features crucial for preserving heterogeneity. Our analysis indicated that features with a notable difference in interquartile range (IQR) between classes hold important subtype information. Guided by this insight, we developed a statistical method called PHet (Preserving Heterogeneity), which employs iterative subsampling and differential analysis of IQR combined with Fisher's method to identify a small set of features that preserve heterogeneity and enhance subtype clustering quality. Validation on public single-cell RNA-seq and microarray datasets demonstrated PHet's ability to maintain sample heterogeneity while distinguishing known disease/cell states, with a tendency to outperform previous differential expression and outlier-based methods. Furthermore, an analysis of a single-cell RNA-seq dataset from mouse tracheal epithelial cells identified two distinct basal cell subtypes differentiating towards a luminal secretory phenotype using PHet-based features, demonstrating promising results in a real-data application. These results highlight PHet's potential to enhance our understanding of disease mechanisms and cell differentiation, contributing significantly to the field of personalized medicine.

Lactate is among the highest flux circulating metabolites. It is made by glycolysis and cleared by both tricarboxylic acid (TCA) cycle oxidation and gluconeogenesis. Severe lactate elevations are life-threatening, and modest elevations predict future diabetes. How lactate homeostasis is maintained, however, remains poorly understood. Here, we identify, in mice, homeostatic circuits regulating lactate production and consumption. Insulin induces lactate production by upregulating glycolysis. We find that hyperlactatemia inhibits insulin-induced glycolysis, thereby suppressing excess lactate production. Unexpectedly, insulin also promotes lactate TCA cycle oxidation. The mechanism involves lowering circulating fatty acids, which compete with lactate for mitochondrial oxidation. Similarly, lactate can promote its own consumption by lowering circulating fatty acids via the adipocyte-expressed G-protein-coupled receptor hydroxycarboxylic acid receptor 1 (HCAR1). Quantitative modeling suggests that these mechanisms suffice to produce lactate homeostasis, with robustness to noise and perturbation of individual regulatory mechanisms. Thus, through regulation of glycolysis and lipolysis, lactate homeostasis is maintained.

The clinical application of cellular immunotherapy in hepatocellular carcinoma (HCC) is impeded by the lack of a cell surface target frequently expressed in HCC cells and with minimal presence in normal tissues to reduce on-target, off-tumor toxicity. To address this, an in silico multomics analysis was conducted to identify an optimal therapeutic target in HCC. A longlist of genes (n = 12,948) expressed in HCCs according to The Human Protein Atlas database were examined. Eight genes were shortlisted to identify one with the highest expression in HCCs, without being shed into circulation, and with restrictive expression profile in other normal human tissues. A total of eight genes were shortlisted and subsequently ranked according to the combination of their transcript and protein expression levels in HCC cases (n = 791) derived from four independent datasets. TM4SF4 was the top-ranked target with the highest expression in HCCs. TM4SF4 showed more favorable expression profile with significantly lower expression in normal human tissues but more highly expressed in HCC compared with seven other common HCC therapeutic targets. Furthermore, scRNA-seq and immunohistochemistry datasets showed that TM4SF4 was absent in immune cell populations but highly expressed in the bile duct canaliculi of hepatocytes, regions inaccessible to immune cells. In scRNA-seq dataset of HCCs, TM4SF4 expression was positively associated with mitochondrial components and oxidative phosphorylation Gene Ontologies in HCC cells (n = 15,787 cells), suggesting its potential roles in mitochondrial-mediated oncogenic effects in HCC. Taken together, TM4SF4 is proposed as a promising cell surface target in HCC due to its high expression in HCC cells with restricted expression profile in non-cancerous tissues, and association with HCC oncogenic pathways.

The pancreas, an organ with dual functions, regulates blood glucose levels through the endocrine system by secreting hormones such as insulin and glucagon. It also aids digestion through the exocrine system by secreting digestive enzymes. Complex interactions and signaling mechanisms between the endocrine and exocrine functions of the pancreas play a crucial role in maintaining metabolic homeostasis and overall health. Compelling evidence indicates direct and indirect crosstalk between the endocrine and exocrine parts, influencing the development of diseases affecting both. From a developmental perspective, the exocrine and endocrine parts share the same origin-the "tip-trunk" domain. In certain circumstances, pancreatic exocrine cells may transdifferentiate into endocrine-like cells, such as insulin-secreting cells. Additionally, several pancreatic diseases, including pancreatic cancer, pancreatitis, and diabetes, exhibit potential relevance to both endocrine and exocrine functions. Endocrine cells may communicate with exocrine cells directly through cytokines or indirectly by regulating the immune microenvironment. This crosstalk affects the onset and progression of these diseases. This review summarizes the history and milestones of findings related to the exocrine and endocrine pancreas, their embryonic development, phenotypic transformations, signaling roles in health and disease, the endocrine-exocrine crosstalk from the perspective of diseases, and potential therapeutic targets. Elucidating the regulatory mechanisms of pancreatic endocrine and exocrine signaling and provide novel insights for the understanding and treatment of diseases.

Lysosome, a highly dynamic organelle, is an important nutrient sensing center. They utilize different ion channels and transporters to complete the mission in degradation, trafficking, nutrient sensing and integration of various metabolic pathways to maintain cellular homeostasis. Glucose homeostasis relies on tightly regulated insulin secretion by pancreatic β cells, and their dysfunction is a hallmark of type 2 diabetes. Glucagon also plays an important role in hyperglycemia in diabetic patients. Currently, lysosome has been recognized as a nutrient hub to regulate the homeostasis of insulin and other hormones. In this review, we will discuss recent advances in understanding lysosome-mediated autophagy and lysosomal proteins involved in maintaining insulin and glucagon homeostasis, as well as their contributions to the etiology of diabetes.

Developing effective drug screening methods for type 2 diabetes requires physiologically relevant models. Traditional 2D cell cultures have limitations in replicating in vivo conditions, leading to challenges in assessing drug efficacy. To overcome these issues, we developed a 3D artificial muscle model that induces insulin resistance, a hallmark of type 2 diabetes. Using C2C12 myoblasts cultured in a scaffold of 1% alginate and 1 mg/mL collagen type 1, we optimized conditions for differentiation and structural stability. Insulin resistance was induced using palmitic acid (PA), and glucose uptake was assessed using the fluorescent glucose analog 2-NBDG. The 3D model demonstrated superior glucose uptake responses compared with 2D cultures, with a threefold increase in insulin-stimulated glucose uptake on days 4 and 8 of differentiation. Induced insulin resistance was observed with 0.1 mM PA, which maintained cell viability and differentiation capacity. The model was validated through comparative drug screening using rosiglitazone and metformin, as well as 165 candidate compounds provided by Korea Chemical Bank. Drug screening revealed that three out of five hit compounds identified in both 2D and 3D models exhibited greater efficacy in 3D cultures, with results consistent with ex vivo assays using mouse soleus muscle. This model closely mimics in vivo conditions, offering a robust platform for type 2 diabetes drug discovery while supporting ethical research practices.

Type 1 diabetes is a unique autoimmune attack on the β cell of the pancreatic islet resulting in progressive destruction of these cells and as a result the ability of the body to maintain insulin production. The consequences of insulin deficiency are very severe, and the disease was fatal prior to the ability to extract insulin from animal pancreas in 1921. We review progress in the treatment of childhood type 1 diabetes over the past 100 years.

We used PubMed and standard search engines to search for the evolution of diagnosis and treatment of type 1 diabetes.

Insulin replacement proved lifesaving for children afflicted with type 1 diabetes. However, it was observed that these children suffered from microvascular and large vessel disease. The Diabetes Control and Complications Trial (DCCT) with its extension Epidemiology of Diabetes Interventions and Complications Trial (EDIC) proved that control of blood glucose as close to normal as possible could prevent these diabetes-related conditions. Many formuations of insulin with varying onset and duration of action have been developed; yet normalization of glucose levels is difficult due to hypoglycemic events. There is continued progress toward that goal.

The pancreas plays a crucial role in digestion and blood glucose regulation. Current animal models, primarily mice and zebrafish, have limited the exploration of pancreatic biology from an evolutionary-developmental perspective. Tetrapod vertebrate axolotl (Ambystoma mexicanum) serves as a valuable model in developmental, regenerative, and evolutionary biology. However, the fundamental biology of the axolotl pancreas remains underexplored. This study aims to characterize the unique developmental, functional, and evolutionary features of the axolotl pancreas to expand the understanding of pancreatic biology.

We conducted morphological, histological, and transcriptomic analyses to investigate the axolotl pancreas. Pancreatic development was observed using in situ hybridization and immunostaining for key pancreatic markers. RNA sequencing was performed to profile global gene expression during larva and adult stages. And differential gene expression analysis was used to characterize the conserved and unique gene patterns in the axolotl pancreas. Functional assays, including glucose tolerance tests and insulin tolerance tests, were optimized for individual axolotls. To assess pancreatic gene function, Pdx1 mutants were generated using CRISPR/Cas9-mediated gene editing, and their effects on pancreatic morphology, endocrine cell populations, and glucose homeostasis were analyzed.

The axolotl pancreas contains all known pancreatic cell types and develops from dorsal and ventral buds. Both of buds contribute to exocrine and endocrine glands. The dorsal bud produces the major endocrine cell types, while the ventral bud generates α and δ cells, but not β cells. Differential gene expression analysis indicated a transition in global gene expression from pancreatic cell fate commitment and the cell cycle to glucose response, hormone synthesis, and secretion, following the development progression. Notably, the adult axolotl pancreas exhibits slower metabolic activity compared to mammals, as evidenced by the results of GTT and ITT. The mutation of Pdx1 resulted in hyperglycemia and a significant reduction in pancreatic cell mass, including a complete loss of endocrine cells, although it did not lead to a lethal phenotype.

This study examines the axolotl pancreas, highlighting the conservation of pancreatic development. Our study highlights the unique features of the axolotl pancreas and broadens the scope of animal models available for pancreatic evolution and disease research.

Metabolic reprogramming is increasingly recognized as a crucial factor influencing the development, progression, and prognosis of pancreatic ductal adenocarcinoma (PDAC). Despite this, the potential association of specific metabolic characteristics and PDAC remains ambiguous due to the variability introduced by individual patient differences. In this study, we aimed to find out metabolic pathways that may be associated with the overall survival (OS) of PDAC patients.

We utilized Mendelian randomization (MR) to assess the associations between 1400 metabolites and metabolite ratios and PDAC. We performed functional annotation and pathway enrichment analysis on both significant metabolites and the shared proteins corresponding to the significant metabolite ratios. Additionally, we analyzed peripheral blood metabolites from 32 PDAC patients to correlate metabolites with clinicopathological features and OS. Functional enrichment analysis was also conducted on the significant metabolites.

Our MR analysis revealed 55 metabolites/metabolite ratios associated with PDAC. Among the top 20 enriched metabolic pathways involving proteins related to significant metabolite ratios, seven were associated with amino acid metabolism, three with carbohydrate metabolism, and two with lipid metabolism. Serum metabolomics of PDAC patients highlighted significant upregulation in pathways related to primary bile acid biosynthesis, as well as taurine and hypotaurine metabolism, which correlated negatively with OS. Conversely, pathways involved in arginine biosynthesis, arginine and proline metabolism, and aminoacyl-tRNA biosynthesis were notably downregulated and positively associated with OS. Both upregulated and downregulated differential metabolites were notably enriched in the pyrimidine metabolism pathway, which was linked to poorer OS. These associations were corroborated by MR analysis.

The study provides valuable insights into the metabolic characteristics associated with PDAC, offering a reference point for improving diagnosis and treatment for PDAC.

The immune system shapes body metabolism, while interactions between peripheral neurons and immune cells control tissue homeostasis and immunity. However, whether peripheral neuroimmune interactions orchestrate endocrine system functions remains unexplored. After fasting, mice lacking type 2 innate lymphoid cells (ILC2s) displayed disrupted glucose homeostasis, impaired pancreatic glucagon secretion, and inefficient hepatic gluconeogenesis. Additionally, intestinal ILC2s were found in the pancreas, which was dependent on their expression of the adrenergic beta 2 receptor. Targeted activation of catecholaminergic intestinal neurons promoted the accumulation of ILC2s in the pancreas. Our work provides evidence that immune cells can be regulated by neuronal signals in response to fasting, activating an inter-organ communication route that promotes pancreatic endocrine function and regulation of blood glucose levels.

Advancing our understanding of pancreatic toxicity and metabolic disorders caused by environmental exposures requires innovative approaches. The pancreas, a vital organ for glucose regulation, is increasingly recognized as a target of harm from environmental chemicals and dietary factors. Traditional toxicological methods, while foundational, often fail to address the mechanistic complexities of pancreatic dysfunction, particularly under real-world conditions involving multiple exposures. New Approach Methodologies (NAMs)-including high-throughput screening (HTS), OMICS technologies, computational modeling, and advanced in vitro systems-offer transformative tools to tackle these challenges. NAMs enable the identification of mechanistic pathways, improve testing efficiency, and reduce reliance on animal testing. This commentary explores the integration of NAMs into pancreatic toxicity screening, addresses critical gaps in evaluating the cumulative risks of chemical and dietary exposures, and proposes solutions for integrating the pancreas into toxicity screening through NAMs. By highlighting recent advancements and emphasizing their adoption in environmental toxicity assessment frameworks, this work demonstrates the potential of NAMs to revolutionize environmental health research, inspire interdisciplinary collaboration, and protect public health.

Type 2 diabetes mellitus (T2DM) is one of the most widespread chronic diseases globally, with its prevalence expected to rise significantly in the years ahead. Previous studies on risk stratification for T2DM identify certain biomarkers, including glycated hemoglobin (HbA1c), oral glucose tolerance testing (OGTT), fructosamine, and glycated albumin, as key indicators for predicting the onset and progression of T2DM. However, these traditional markers have been shown to lack sensitivity and specificity and their results are difficult to analyze due to non-standardized interpretation criteria, posing significant challenges to an accurate and definitive diagnosis. The strict measures of these traditional markers may not catch gradual increases in blood sugar levels during the early stages of diabetes evolution, as these might still fall within acceptable glycemic parameters. Recent advancements in research have suggested novel micro ribonucleic acid (miRNA) as circulatory molecules that can facilitate the early detection of prediabetic conditions in high-risk groups and potentially enable prevention of the progression to T2DM. This capability makes them a very powerful tool for potentially improving population health, enhancing outcomes for many patients, and reducing the overall burden of T2DM. These promising biomarkers are small, noncoding RNA involved in the regulation of many cellular functions that have a hand in the metabolic activities of cells, making them a very useful and relevant biomarker to explore for the diagnosis and risk stratification of T2DM. This review analyzes the current literature, outlining the occurrence of miRNAs in prediabetic and diabetic individuals and their implications in predicting dysglycemic disorders.

Environmental exposure to arsenic is associated with significant health risks, including diabetogenic effects linked to pancreatic dysfunction. The NOD-like receptor protein 3 (NLRP3) inflammasome has been implicated in various metabolic abnormalities; however, its specific role in arsenic-induced pancreatic dysfunction remains insufficiently understood. This study aimed to elucidate the involvement and underlying mechanisms of the NLRP3 inflammasome in arsenic-induced pancreatic beta cells dysfunction through in vivo and in vitro models. In rat models, arsenic exposure was found to activate the NLRP3 inflammasome, as evidenced by pathomorphological changes and the expression of inflammasome activation markers. These pathological changes were accompanied by disruptions in the insulin signaling pathway, characterized by increased phosphorylation of insulin receptor substrate 1 (IRS-1) at Ser616, reduced expression of phosphatidylinositol 3-kinase (PI3K) and phosphorylated protein kinase B (AKT) at Ser473, and significant decreases in downstream targets, including the nuclear translocation of PDX-1, membrane translocation of glucose transporter 2 (GLUT2), and glucokinase (GCK) expression. In vitro, NaAsO2-treated INS-1 cells exhibited a dose-dependent reduction in glucose-stimulated insulin secretion. Furthermore, arsenic exposure in these cells activated the NLRP3 inflammasome, suppressed the IRS-1/PI3K/AKT signaling pathway, and downregulated insulin secretion regulatory molecules (PDX-1, GLUT2, and GCK). Notably, these arsenic-induced effects were reversed by MCC950, an NLRP3 inflammasome inhibitor, and Extendin-4, an agonist of the IRS-1/PI3K/AKT signaling pathway. Collectively, these findings demonstrate that NLRP3 inflammasome activation disrupts the IRS-1/PI3K/AKT signaling pathway, contributing to arsenic-induced pancreatic beta cells dysfunction in rats.

The aim of this work was to understand the role of non-beta cells in pancreatic islets at early stages of type 2 diabetes pathogenesis.

Specific clustering was employed to single-cell transcriptome data from islet cells of obese mouse strains differing in their diabetes susceptibility (diabetes-resistant B6.V.Lepob/ob [OB] and diabetes-susceptible New Zealand Obese [NZO] mice) on a diabetogenic diet.

Refined clustering analysis revealed several heterogeneous subpopulations for alpha cells, delta cells and macrophages, of which 133 mapped to human diabetes genes identified by genome-wide association studies. Importantly, a similar non-beta cell heterogeneity was found in a dataset of human islets from donors at different stages of type 2 diabetes. The predominant alpha cell cluster in NZO mice displayed signs of cellular stress and lower mitochondrial capacity (97 differentially expressed genes [DEGs]), whereas delta cells from these mice exhibited higher expression levels of maturation marker genes (Hhex and Sst) but lower somatostatin secretion than OB mice (184 DEGs). Furthermore, a cluster of macrophages was almost twice as abundant in islets of OB mice, and displayed extensive cell-cell communication with beta cells of OB mice. Treatment of beta cells with IL-15, predicted to be released by macrophages, activated signal transducer and activator of transcription (STAT3), which may mediate anti-apoptotic effects. Similar to mice, humans without diabetes possess a greater number of macrophages than those with prediabetes (39 mmol/mol [5.7%] < HbA1c < 46 mmol/mol [6.4%]) and diabetes.

Our study indicates that the transcriptional heterogeneity of non-beta cells has an impact on intra-islet crosstalk and participates in beta cell (dys)function.

scRNA-seq data from the previous study are available in gene expression omnibus under gene accession number GSE159211 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159211 ).

Precise blood glucose control continues to be a critical challenge in the treatment and management of type 1 diabetes in order to mitigate both acute and chronic complications. This study investigates the development of a supramolecular peptide amphiphile (PA) material functionalized with phenylboronic acid (PBA) for glucose-responsive glucagon delivery. The PA-PBA system self-assembles into nanofibrillar hydrogels in the presence of physiological glucose levels, resulting in stable hydrogels capable of releasing glucagon under hypoglycemic conditions. Glucose responsiveness is driven by reversible binding between PBA and glucose, which modulates the electrostatic interactions necessary for hydrogel formation and dissolution. Through comprehensive in vitro characterization, including circular dichroism, zeta potential measurements, and rheological assessments, the PA-PBA system is found to exhibit glucose-dependent assembly, enabling controlled glucagon release that is inversely related to glucose concentration. Glucagon release is accelerated under low glucose conditions, simulating a hypoglycemic state, with a reduced rate seen at higher glucose levels. Evaluation of the platform in vivo using a type 1 diabetic mouse model demonstrates the efficacy in protecting against insulin-induced hypoglycemia by restoring blood glucose levels following an insulin overdose. The ability to tailor glucagon release in response to fluctuating glucose concentrations underscores the potential of this platform for improving glycemic control. These findings suggest that glucose-stabilized supramolecular peptide hydrogels hold significant promise for responsive drug delivery applications, offering an approach to manage glucose levels in diabetes and other metabolic disorders.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decline and memory impairment. The pathophysiology of AD may involve aggregated amyloid β (Aβ) accumulation, which may underlie the disease mechanism. Patients with diabetes exhibit an elevated risk of developing AD, indicating potential therapeutic implications upon elucidating the underlying mechanisms. We hypothesized that pancreatic β cell-secreted factors could protect neurons from Aβ-induced toxicity. Therefore, we established an experimental model to elucidate the communication between pancreatic β cells and neuronal cells. Notably, our findings demonstrate that pancreatic β cell culture supernatant effectively inhibits Aβ-induced neuronal cell death. Transcriptomic analysis showed significant up-regulation of multiple ribosomal protein genes in neuronal cells treated with pancreatic β cell culture supernatant. Fibroblast growth factor 23, a secreted factor from pancreatic β cells, significantly suppressed Aβ-induced neuronal cell death. Our findings suggest that pancreatic β cells may secrete previously unrecognized neuroprotective factors, thereby attenuating neuronal cell death in AD.

Objective: This study aims to investigate the continuum of glucose control from normoglycemia to dysglycemia (HbA1c ≥ 5.7%/39 mmol/mol) using metrics derived from continuous glucose monitoring (CGM). In addition, we aim to develop a machine learning-based classification model to classify dysglycemia based on observed patterns. Methods: Data from five distinct studies, each featuring at least two days of CGM, were pooled. Participants included individuals classified as healthy, with prediabetes, or with type 2 diabetes mellitus (T2DM). Various CGM indices were extracted and compared across groups. The data set was split 70/30 for training and testing two classification models (XGBoost/Logistic Regression) to differentiate between prediabetes or dysglycemia and the healthy group. Results: The analysis included 836 participants (healthy: n = 282; prediabetes: n = 133; T2DM: n = 432). Across all CGM indices, a progressive shift was observed from the healthy group to those with diabetes (P < 0.001). Statistically significant differences (P < 0.01) were noted in mean glucose, time below range, time above 140 mg/dl, mobility, multiscale complexity index, and glycemic risk index when transitioning from health to prediabetes. The XGBoost models achieved the highest receiver operating characteristic area under the curve values on the test data set ranging from 0.91 [confidence interval (CI): 0.87-0.95] (prediabetes identification) to 0.97 [CI: 0.95-0.98] (dysglycemia identification). Conclusion: Our findings demonstrate a gradual deterioration of glucose homeostasis and increased glycemic variability across the spectrum from normo- to dysglycemia, as evidenced by CGM metrics. The performance of CGM-based indices in classifying healthy individuals and those with prediabetes and diabetes is promising.

Pancreatic diseases pose considerable health challenges due to their complex etiology and limited therapeutic options. Mitochondrial uncoupling protein 2 (UCP2), highly expressed in pancreatic tissue, participates in numerous physiological processes and signaling pathways, indicating its potential relevance in these diseases. Despite this, UCP2's role in acute pancreatitis (AP) remains underexplored, and its functions in chronic pancreatitis (CP) and pancreatic steatosis are largely unknown. Additionally, the mechanisms connecting various pancreatic diseases are intricate and not yet fully elucidated. Given UCP2's diverse functionality, broad expression in pancreatic tissue, and the distinct pathophysiological features of pancreatic diseases, this review offers a comprehensive analysis of current findings on UCP2's involvement in these conditions. We discuss recent insights into UCP2's complex regulatory mechanisms, propose that UCP2 may serve as a central regulatory factor in pancreatic disease progression, and hypothesize that UCP2 dysfunction could significantly contribute to disease pathogenesis. Understanding UCP2's role and mechanisms in pancreatic diseases may pave the way for innovative therapeutic and diagnostic approaches.

Pancreatic cancer remains one of the most lethal forms of cancer. Currently, there is a lack of effective drug treatments for pancreatic cancer. However, as a newly discovered form of non-apoptotic cell death, ferroptosis has garnered increasing attention in relation to pancreatic cancer. Understanding the role of ferroptosis in the tumorigenesis and treatment of pancreatic cancer may enable more effective clinical trials and treatments for pancreatic cancer and may minimize side effects or restrict the emergence of drug resistance. In this review, we summarize the current knowledge regarding the process and underlying mechanisms of ferroptosis, as well as its dual role in both promoting tumorigenesis and facilitating treatment strategies for pancreatic cancer. Additionally, how ferroptosis is implicated in the development of pancreatitis and insulin resistance, indicating that ferroptosis may play an important role in the risk of pancreatitis- and insulin-resistance-related pancreatic cancers, is also addressed.

Over the past decades, the global prevalence of Type 2 diabetes mellitus (T2D) and impaired glucose tolerance (IGT) has been increasing at an epidemic rate, yet the exact cause remains unknown. It is widely accepted that glucose metabolism can be impaired by circadian rhythms and sleep disturbances. Concurrently, exposures to light at night have been closely linked to circadian and sleep disturbances. However, there is no direct experiment on primates to demonstrate the precise extent of how serious light pollution impairs glucose metabolism, whether people will eventually become accustomed to this environment, and whether the pollution has synergistic impairing effects with aging and weight on glucose metabolism. To quantitatively address these questions, 137 cynomolgus were exposed to three distinct nocturnal light intensities for consecutive 10 months. Monthly glucose metabolism assessments were conducted. Data pertaining to the mortality rate of preexisting diabetes, incidence of light-induced diabetes and IGT, and alterations in insulin secretion were collected and analyzed. The results show that nocturnal light (1) caused premature deaths in individuals with preexisting diabetes; (2) intensity-dependently induced diabetes and IGT in previous healthy monkeys; (3) intensity-dependently reduced melatonin secretion; (4) had a synergistic impairing effect on glucose metabolism with aging and weight; and (5) although monkeys would eventually adapt to the environment, the disrupted glucose metabolism would not fully recover in most individuals. In conclusion, nocturnal light is associated with the global high prevalence of T2D and IGT. The harmful effects of light pollution on glucose metabolism are synergistic with age and weight.

Pancreatic diseases, typically including pancreatic cancer, pancreatitis, and diabetes, pose enormous threats to people's lives and health. To date, therapeutics with high therapeutic efficacy and low side effects are still challenging. With the development of nanotechnology, nanomaterials have successfully been applied in pancretic disease treatment. Here, we first introduce the diversity of nanomaterials and the effects of their different physicochemical properties on pancreatic function. Following this, we analyze the potential of nanomaterials to enhance pancreatic targeting by overcoming the challenges of traditional delivery methods through surface modifications, structural adjustments, and optimized drug loading. Then, we introduce the application of structurally optimized nanomaterials to pancreatic-related diseases. For instance, on pancreatic cancer (as drug delivery platforms, for the promotion of radiation therapy, and as multifunctional tools), pancreatitis (as drug delivery systems, anti-inflammatory and anti-fibrotic agents), and diabetes (as insulin delivery carriers, for protecting pancreatic β cells, and for improving insulin resistance). Through analysis of the progress of current research, we summarize how nanomaterials can enhance treatment efficacy while minimizing side effects. Finally, we look forward to the prospects of nanomaterials in pancreatic disease treatment.

This article focuses on homeostasis and offers a pathophysiological perspective. The dynamic mechanisms responsible for maintaining internal balance and disruptive processes will be analysed through the lens of key systems including the nervous, endocrine and renal systems. The environmental factors and their potential impact on homeostasis have been considered. A clinical case study will contextualise homeostasis in clinical practice.

To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).

This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s-40 s, 60 s-70 s, and 150 s-180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.

A total of 562 participants (median age 58 years [interquartile range: 47-67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = -0.240, p = 0.001), and type-II diabetes (β = -0.449, p < 0.001); NICPP by VFA (β = -0.301, p = 0.017) and smoking (β = -0.291, p < 0.001); and NICEP by smoking (β = -0.154, p = 0.10) and alcohol consumption (β = -0.350, p < 0.001) with statistical power values over 0.81.

NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.

This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.

Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies. Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake. Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.

Animal models are an important tool for studying noncommunicable diseases (NCDs) as they provide a unique opportunity to investigate real-time changes that occur in the onset of, and during, the diseased state. This is of particular importance given that the global prevalence of NCDs, such as type 2 diabetes mellitus (T2DM), is rising at an alarming rate. In South Africa, which has one of the highest levels of HIV in the world, the incidence of T2DM is thought to be associated, in part, with exposure to combination antiretrovirals. We report on the establishment of both nonobese and obese zebrafish models of T2DM, as well as associated changes in mRNA expression of preproinsulin and phosphoenolpyruvate carboxykinase (pck) 1 and 2. The diabetic state was achieved by either immersing adult zebrafish in a 2% glucose solution for 40 days or by overfeeding adult zebrafish for 10 weeks. Glucose immersion resulted in significantly elevated fasting blood glucose levels twice as high as control, whereas bodyweight did not change significantly (nonobese model). Overfeeding led to both significantly elevated fasting blood glucose and bodyweight compared with control (obese model). Both models were characterized by significantly increased preproinsulin mRNA expression indicating insulin resistance; mRNA expression of metabolic enzymes PCK 1 and 2 was also significantly upregulated, as seen in diabetic patients. These candidate gene expression changes, similar in both zebrafish models, establish a baseline that can be utilized to investigate the underlying mechanisms driving the increased T2DM incidence, using an excellent alternative to traditional rodent models.

Insulin secretion is a highly regulated process critical for maintaining glucose homeostasis. This abstract explores the intricate interplay between three essential pathways: The Triggering Pathway, The Metabolic Amplifying Pathway, and Cellular Transduction, in orchestrating glucose-dependent biphasic insulin secretion.

During the triggering pathway, glucose metabolism in pancreatic beta-cells leads to ATP production, closing ATP-sensitive potassium channels and initiating insulin exocytosis. The metabolic amplifying pathway enhances insulin secretion via key metabolites like NADH and glutamate, enhancing calcium influx and insulin granule exocytosis. Additionally, the cellular transduction pathway involves G-protein coupled receptors and cyclic AMP, modulating insulin secretion.

These interconnected pathways ensure a dynamic insulin response to fluctuating glucose levels, with the initial rapid phase and the subsequent sustained phase. Understanding these pathways' complexities provides crucial insights into insulin dysregulation in diabetes and highlights potential therapeutic targets to restore glucose-dependent insulin secretion.

While glucose-responsive insulin delivery systems are in widespread clinical use to treat insulin insufficiency, the on-demand supplementation of glucagon for acute hypoglycemia treatment remains understudied. A self-regulated glucagon release material is highly desired to mitigate the potential risks of severe insulin-induced hypoglycemia. Here, we describe a glucose-responsive polymeric nanosystem with glucagon covalently grafted to the end-group. Under normoglycemic conditions, phenylboronic acid units in the polymer chain reversibly bind glucose, triggering self-assembly of the conjugate into micelles. During hypoglycemia, however, the micelle disassembles into its original, unimeric state, revealing the active glucagon conjugate. The formulation showed a 5-fold increase in activity compared to native glucagon when tested in vitro. Glucagon-loaded micelles injected into mice prevented or reversed deep hypoglycemia when administered prior to or during an insulin challenge. Glucagon release was only observed at or below the counterregulatory threshold and not during normoglycemia or moderate hypoglycemia. The in vivo acute and chronic toxicity analysis, along with μPET/μCT imaging, established the biosafety profile of this formulation and demonstrated no organ accumulation. This proof-of-concept work is the first step toward development of a translational, stimuli-responsive glucagon delivery platform to control glycemia.

Type 1 diabetes (T1D) is a chronic condition in which the body produces too little insulin, a hormone needed to regulate blood glucose. Various factors such as carbohydrates, exercise, and hormones impact insulin needs. Beyond carbohydrates, most factors remain underexplored. Regulating insulin is a complex control task that can go wrong and cause blood glucose levels to fall outside a range that protects people from adverse health effects. Automated insulin delivery (AID) has been shown to maintain blood glucose levels within a narrow range. Beyond clinical outcomes, data from AID systems are little researched; such systems can provide data-driven insights to improve the understanding and treatment of T1D.

The aim is to discover unexpected temporal patterns in insulin needs and to analyze how frequently these occur. Unexpected patterns are situations where increased insulin does not result in lower glucose or where increased carbohydrate intake does not raise glucose levels. Such situations suggest that factors beyond carbohydrates influence insulin needs.

We analyzed time series data on insulin on board (IOB), carbohydrates on board (COB), and interstitial glucose (IG) from 29 participants using the OpenAPS AID system. Pattern frequency in hours, days (grouped via k-means clustering), weekdays, and months were determined by comparing the 95% CI of the mean differences between temporal units. Associations between pattern frequency and demographic variables were examined. Significant differences in IOB, COB, and IG across temporal dichotomies were assessed using Mann-Whitney U tests. Effect sizes and Euclidean distances between variables were calculated. Finally, the forecastability of IOB, COB, and IG for the clustered days was analyzed using Granger causality.

On average, 13.5 participants had unexpected patterns and 9.9 had expected patterns. The patterns were more pronounced (d>0.94) when comparing hours of the day and similar days than when comparing days of the week or months (0.3

Conclusions

Our study shows that unexpected patterns in the insulin needs of people with T1D are as common as expected patterns. Unexpected patterns cannot be explained by carbohydrates alone. Our results highlight the complexity of glucose regulation and emphasize the need for personalized treatment approaches. Further research is needed to identify and quantify the factors that cause these patterns.

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Chemical modification of proteins is of growing importance to generate new molecular probes for chemical biology and for the development of new biopharmaceuticals. For example, two approved, long-acting insulin variants are lipidated at the LysB29 side-chain. Acylations of proteins have so far been performed in batch-mode. Here we describe the use of flow chemistry for site-selective acylation of a small protein, insulin. To the best of our knowledge this is the first report on flow chemistry for chemical modification of insulin. The first step was to develop reaction conditions for acylation of Lys B29 that gave a soluble mixture and thus was compatible with flow chemistry in a microreactor; this included selection of a soluble base. Secondly, the conditions, such as reagent ratios and flow rate were optimized. Third, the use of these conditions for the acylation with a wide range of acids was demonstrated. Finally, Boc-protected insulins were synthesized. Insulin remained stable towards these flow chemistry conditions. This use of flow chemistry for the chemical modification of insulin opens the prospect of producing chemically modified biopharmaceuticals by flow chemistry with fewer byproducts.

Homeostasis can be described as the dynamic process within an organism designed to maintain a relatively constant internal environment that is conducive to the optimal functioning of cells, enzymes and organs. To regulate physiological variables, homeostasis relies on mechanisms called negative and positive feedback loops. However, certain factors can disrupt homeostatic processes, leading to dysregulation and disease. This article provides an overview of homeostasis, including negative and positive feedback loops and dysregulation. The authors use a fictional case study - an adolescent girl with type 1 diabetes who develops diabetic ketoacidosis - to illustrate the adverse effects of homeostatic dysregulation and demonstrate the relevance of understanding homeostasis in children's nursing.

A strategy to reduce starch digestibility is to limit its accessibility to α-amylase by preserving the integrity of cells where starch is encapsulated. Coarse flour is rich in intact cells and can be used for this purpose. However, making bread with coarse flour negatively affects crumb cohesiveness, which may increase the gastric disintegration rate, and enhance starch accessibility. Therefore, this study aimed to assess the combined effect of coarse semolina and its 20% gluten substitution in bread in healthy volunteers on glycemic and insulinemic responses, oral processing and bolus characteristics.

Apparently, healthy volunteers (n = 16) randomly consumed bread made with coarse semolina and 20% gluten substitution (80CS_20G), its counterpart with fine semolina (80FS_20G), and bread with fine semolina and 5% gluten (95FS_5G). The glycemic and insulinemic responses were measured over 2 h after bread consumption. Mastication behaviour, bolus properties and reducing sugar were also evaluated.

No differences in glycemic responses and mastication were observed among the samples. 80CS_20G and 80FS_20G exhibited similar textural properties but 80CS_20G released less reducing sugars and elicited a lower insulin response at 30 min than 80FS_20G, probably due to intact cells that limit starch accessibility. Also, 95FS_5G released lower reducing sugars and had lower insulin peak than 80FS_20G. The compact structure of 95FS_5G may have delayed starch hydrolysis by restricting α-amylase accessibility.

Combining gluten and coarse semolina resulted in bread with a lower release of reducing sugars, a reduced insulinemic peak and textural properties similar to the counterpart with fine semolina.

The trial is registered at ClinicalTrials.gov: NCT06152874.

We investigated the effect of individual, joint and fluctuating exposure to air pollution (PM2.5, BC, NO3-, NH4+, OM, SO42-, PM10, NO2, SO2, O3) on glucose metabolisms among prediabetes, and simultaneously explored the modifying effect of lifestyle. We conducted a longitudinal study among prediabetes during 2018-2022. Exposure windows within 60-days moving averages and their variabilities were calculated. FBG, insulin, HOMA-IR, HOMA-B, triglyceride glucose index (TyG), glucose insulin ratio (GI) and allostatic load of glucose homeostasis system (AL-GHS) was included. Linear mixed-effects model and BKMR were adopted to investigate the individual and overall effects, respectively. We also explored the preventive role of lifestyle. Individual air pollutant was associated with increased FBG, insulin, HOMA-IR, HOMA-B, TyG, and decreased GI. People with FBG ≥6.1 mmol/L were more susceptible. Air pollutants mixture were only associated with increased HOMA-B, and constituents have the highest group-PIP. Air pollutants variation also exert harmful effect. We observed similar diabetic effect on AL-GHS. Finally, the diabetic effect of air pollutants disappeared if participants adopt a favorable lifestyle. Our findings highlighted the importance of comprehensively assessing multiple air pollutants and their variations, focusing on metabolic health status in the early prevention of T2D, and adopting healthy lifestyle to mitigate such harmful effect.

The microbiota in humans consists of trillions of microorganisms that are involved in the regulation of the gastrointestinal tract and immune and metabolic homeostasis. The gut microbiota (GM) has a prominent impact on the pathogenesis of metabolic syndrome (MetS). This process is reciprocal, constituting a crosstalk process between the GM and MetS. In this review, GM directly or indirectly inducing MetS via the host-microbial metabolic axis has been systematically reviewed. Additionally, the specifically altered GM in MetS are detailed in this review. Moreover, short-chain fatty acids (SCFAs), as unique gut microbial metabolites, have a remarkable effect on MetS, and the role of SCFAs in MetS-related diseases is highlighted to supplement the gaps in this area. Finally, the existing therapeutics are outlined, and the superiority and shortcomings of different therapeutic approaches are discussed, in hopes that this review can contribute to the development of potential treatment strategies.

The number of people suffering from type 2 diabetes has rapidly increased. Taking into account, that elevated intracellular lipid concentrations, as well as their metabolism, are correlated with diminished insulin sensitivity, in this study we would like to show lipids spectroscopy markers of diabetes. For this purpose, serum collected from rats (animal model of diabetes) was analyzed using Fourier Transformed Infrared-Attenuated Total Reflection (FTIR-ATR) spectroscopy. Analyzed spectra showed that rats with diabetes presented higher concentration of phospholipids and cholesterol in comparison with non-diabetic rats. Moreover, the analysis of second (IInd) derivative spectra showed no structural changes in lipids. Machine learning methods showed higher accuracy for IInd derivative spectra (from 65 % to 89 %) than for absorbance FTIR spectra (53-65 %). Moreover, it was possible to identify significant wavelength intervals from IInd derivative spectra using random forest-based feature selection algorithm, which further increased the accuracy of the classification (up to 92 % for phospholipid region). Moreover decision tree based on the selected features showed, that peaks at 1016 cm-1 and 2936 cm-1 can be good candidates of lipids marker of diabetes.

Since it was inspired by Bernard and developed and named by Cannon, the concept of homeostasis has been invoked by many as the central theoretical framework for physiology. It has also been the target of numerous criticisms that have elicited the introduction of a plethora of alternative concepts. We argue that many of the criticisms actually target the more restrictive account of homeostasis advanced by the cyberneticists. What was crucial to Bernard and Cannon was a focus on the maintenance of the organism as the goal of physiological regulation. We analyse how Bernard's and Cannon's broad conception of what was required to maintain the organism was narrowed to negative feedback, characterized in terms of setpoints, by the cyberneticists and demonstrate how many of the alternative concepts challenge the role of setpoints - treating them as variable in light of circumstances or in anticipation of future circumstances, or as dispensable altogether. To support our analysis, we draw on the experimental and theoretical work on thermoregulation, a phenomenon that has been considered as a paradigmatic example of homeostasis and has been a common focus of those advancing alternative concepts. To integrate the insights advanced by the original proponents of homeostasis and the theorists proposing replacement notions we advance a framework in which regulation is viewed from the perspective of maintaining the organism.

Nine cyclists (age: 26 ± 5 years, height: 168 ± 5 cm and mass 58.5 ± 4.5 kg) were observed using continuous glucose monitoring devices throughout a training camp. Interstitial glucose [iG] data were captured via the Abbott libre sense biosensor (Abbott Laboratories) and paired with the Supersapiens software (TT1 Products Inc.). [iG] data were split into time ranges, that is, overall (24-hourly), day-time (06:00-23:59), night-time (00:00-05:59) and exercise. [iG] data were stratified into percentage of time, below range ([TBR] < 70 mg/dl), in range ([TIR] 70-140 mg/dl) and above range ([TAR] ≥ 141 mg/dl). Differences in diurnal and nocturnal data were analysed via repeated measures analysis of variance and paired t-tests where appropriate. p-value of ≤0.05 was accepted as significant. Riders spent an average of 3 ± 1% TAR, 93 ± 2% TIR and 8 ± 3% TBR. Mean 24 h [iG] was 93 ± 2 mg/dl with a coefficient of variation (CV) of 18 ± 1%. Mean (day: 95 ± 3 vs. night: 86 ± 3 mg/dl and p < 0.001) and CV (day: 18 ± 1 vs. night: 9 ± 1% and p < 0.001) in [iG] were higher during the day-time hours. TAR was greater during the day (day: 3 ± 1 vs. night: 0 ± 0% and p < 0.001) but TBR and TIR were similar. Glucose levels below the clinical range may have implications for those without diabetes and warrants further investigation.

Sericin-derived oligopeptides (SDOs) from yellow silk cocoons exhibit antihypertensive and hypoglycemic properties in both in vitro and in vivo studies. This study investigated the acute toxicity of SDOs as a novel food for human consumption using female ICR mice and Wistar rats, as well as the chronic toxicity test on both sexes of Wistar rats. Clinical chemistry, hematology, and histopathological studies revealed that SDOs were safe for a single dose of 2000 mg kg-1 body weight (BW) and daily oral administration of 50, 100, and 200 mg kg-1 BW for six months. The chronic toxicity study additionally measured the rats' systolic blood pressure (SBP) and blood sugar monthly as they slowly aged. In the 2nd month for male rats and the 4th month for both sexes, SDOs had a significant hypotensive effect on Wistar rats' blood pressure, lowering it from 130 mmHg to a plateau at 110-115 mmHg. In contrast, the blood pressure of the control rats exceeded 140 mmHg after five months. Nonetheless, the hypoglycemic effect was not observed. Measurements of SBP and blood glucose in aged rats during chronic toxicity tests yielded insights beyond ordinary toxicity, including the health and fitness of the lab rats, perhaps resulting in novel discoveries or areas of study that justify the sacrifice of the animals' lives.

The SWItch3-related gene (SRG3) is a core component of ATP-dependent SWI/SNF complexes, which are crucial for regulating immune cell development and function (e.g., macrophages and CD4+ T cells), embryonic development, and non-immune cell differentiation. Notably, SRG3 overexpression has been shown to polarize macrophages in the central nervous system toward an anti-inflammatory M2 phenotype, thereby protecting against the development of experimental autoimmune encephalomyelitis in mice. However, the effect of SRG3 on immune responses in adipose tissues remains unclear. To address this issue, we examined the cellularity and inflammatory status of adipose tissue in B10.PL mice overexpressing the SRG3 gene under the ubiquitous β-actin promoter (SRG3β-actin). Interestingly, SRG3 overexpression significantly reduced adipocyte size in both white and brown adipose tissues, without affecting the overall adipose tissue weight. Such phenotypic effects might be associated with the improved glucose tolerance observed in SRG3β-actin B10.PL mice. Moreover, we found that SRG3 overexpression down-regulates IL1β-expressing M1 macrophages, leading to a significant decrease in the M1/M2 macrophage ratio. Additionally, SRG3β-actin B10.PL mice showed a dramatic reduction in neutrophils as well as IL1β- and IL17-producing T cells in adipose tissues. Taken together, our results indicate that SRG3 plays a vital role in maintaining immune homeostasis within adipose tissues.