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Introduction The prevalence of type 2 diabetes (T2D) has increased dramatically in recent decades, and there are increasing indications that dementia is related to T2D. Previous attempts to analyze such relationships principally relied on traditional multiple linear regression (MLR). However, recently developed machine learning methods (Mach-L) outperform MLR in capturing non-linear relationships. The present study applied four different Mach-L methods to analyze the relationships between risk factors and cognitive function in older T2D patients, seeking to compare the accuracy between MLR and Mach-L in predicting cognitive function and to rank the importance of risks factors for impaired cognitive function in T2D. Methods We recruited older T2D between 60–95 years old without other major comorbidities. Demographic factors and biochemistry data were used as independent variables and cognitive function assessment (CFA) was conducted using the Montreal Cognitive Assessment as an independent variable. In addition to traditional MLR, we applied random forest (RF), stochastic gradient boosting (SGB), Naïve Byer’s classifier (NB) and eXtreme gradient boosting (XGBoost). Results Totally, the test cohort consisted of 197 T2D (98 men and 99 women). Results showed that all ML methods outperformed MLR, with symmetric mean absolute percentage errors for MLR, RF, SGB, NB and XGBoost respectively of 0.61, 0.599, 0.606, 0.599 and 0.2139. Education level, age, frailty score, fasting plasma glucose and body mass index were identified as key factors in descending order of importance. Conclusion In conclusion, our study demonstrated that RF, SGB, NB and XGBoost are more accurate than MLR for predicting CFA score, and identify education level, age, frailty score, fasting plasma glucose, body fat and body mass index as important risk factors in an older Chinese T2D cohort.

PTEN is frequently mutated in prostate cancer. The tumor suppressor function of PTEN is attributed to its lipid phosphatase activity that counters PI3K action. Here, we report a PTEN-ARID4B-PI3K axis in which PTEN inhibits expression of ARID4B , while ARID4B is a transcriptional activator of the PI3K subunit genes PIK3CA and PIK3R2 that are crucial for activation of the PI3K/AKT pathway. Reciprocal binding of ARID4B and histone H1 to the PIK3CA and PIK3R2 promoters modulates chromatin condensation, suggesting a mechanism by which ARID4B activates these promoters. Functional analyses reveals that ARID4B is required for prostate tumorigenesis when PTEN is deficient. The biological significance is further substantiated by the existence of a PTEN / ARID4B / PIK3CA three-gene signature that improves the predictive power for prostate cancer recurrence in patients. In summary, we identify ARID4B as a master regulator in the PTEN-PI3K pathway, thus providing a potential therapeutic target for prostate cancer carrying PTEN mutations. The identification of synthetic essential genes of PTEN is of therapeutic potential for PTEN-deficient prostate cancers. Here, the authors show that ARID4B is a synthetic essential gene in these cancers in which deficiency of PTEN prompts the AKT-ARID4B feedback loop required for activation of the PI3K-AKT signaling pathway.

Apolipoprotein C3 (APOC3) plays a critical role in regulating triglyceride levels and serves as a key predictor of cardiovascular disease (CVD) risk, particularly in patients with diabetes. While APOC3 is known to inhibit lipoprotein lipase, recent findings reveal its broader influence across lipoprotein metabolism, where it modulates the structure and function of various lipoproteins. Therefore, this review examines the complex metabolic cycle of APOC3, emphasizing the impact of APOC3-containing lipoproteins on human metabolism, particularly in patients with diabetes. Notably, APOC3 affects triglyceride-rich lipoproteins and causes structural changes in high-, very low-, intermediate-, and low-density lipoproteins, thereby increasing CVD risk. Evidence suggests that elevated APOC3 levels—above the proposed safe range of 10–15 mg/dL—correlate with clinically significant CVD outcomes. Recognizing APOC3 as a promising biomarker for CVD, this review underscores the urgent need for high-throughput, clinically feasible methods to further investigate its role in lipoprotein physiology in both animal models and human studies. Additionally, we analyze the relationship between APOC3-related genes and lipoproteins, reinforcing the value of large-population studies to understand the impact of APOC3 on metabolic diseases. Ultimately, this review supports the development of therapeutic strategies targeting APOC3 reduction as a preventive approach for diabetes-related CVD.

Peripheral neuropathy is a common neurological issue that leads to sensory and motor disorders. Over time, the treatment for peripheral neuropathy has primarily focused on medications for specific symptoms and surgical techniques. Despite the different advantages of these treatments, functional recovery remains less than ideal. Schwann cells, as the primary glial cells in the peripheral nervous system, play crucial roles in physiological and pathological conditions by maintaining nerve structure and functions and secreting various signaling molecules and neurotrophic factors to support both axonal growth and myelination. In addition, stem cells, including mesenchymal stromal cells, skin precursor cells and neural stem cells, have the potential to differentiate into Schwann-like cells to perform similar functions as Schwann cells. Therefore, accumulating evidence indicates that Schwann cell transplantation plays a crucial role in the resolution of peripheral neuropathy. In this review, we summarize the literature regarding the use of Schwann cell/Schwann cell-like cell transplantation for different peripheral neuropathies and the potential role of promoting nerve repair and functional recovery. Finally, we discuss the limitations and challenges of Schwann cell/Schwann cell-like cell transplantation in future clinical applications. Together, these studies provide insights into the effect of Schwann cells/Schwann cell-like cells on cell therapy and uncover prospective therapeutic strategies for peripheral neuropathy.

The condensing effect of cholesterol on phospholipid bilayers was systematically investigated for saturated and unsaturated chains, as a function of cholesterol concentration. X-ray lamellar diffraction was used to measure the phosphate-to-phosphate distances, PtP, across the bilayers. The measured PtP increases nonlinearly with the cholesterol concentration until it reaches a maximum. With further increase of cholesterol concentration, the PtP remains at the maximum level until the cholesterol content reaches the solubility limit. The data in all cases can be quantitatively explained with a simple model that cholesterol forms complexes with phospholipids in the bilayers. The phospholipid molecules complexed with cholesterol are lengthened and this lengthening effect extends into the uncomplexed phospholipids surrounding the cholesterol complexes. This long-range thickening effect is similar to the effect of gramicidin on the thickness of lipid bilayers due to hydrophobic matching.

Traditional Chinese courtyard theaters in Taiwan possess a unique architectural and performative identity, distinct from Western-style proscenium theaters that dominate contemporary performance venues. These Western configurations often impose spatial and acoustic constraints that hinder the authentic expression of traditional Chinese opera. In contrast, courtyard-style theaters—characterized by open-air layouts and architectural enclosures—offer inherent acoustic advantages rooted in structural coupling and boundary reflections. This study focuses on the Da-Hua Hall at the Wu-Feng Lin Family Mansion, employing on site acoustic measurements to characterize its sound environment not only distribute sound energy and calibrate a sound tracing and a wave-based simulation model. The finite element method framework enables precise modeling of low-frequency acoustic phenomena, including modal behavior and resonance, which were conducted to assess the impact of stage permeability, vessel geometry, and wall-mounted resonators on acoustic parameters. The results demonstrate that the interaction between sub-stage resonators and architectural elements, specifically the width of stage floorboard joints and the presence of embedded jars, significantly influences acoustic performance, notably affecting the distribution of sound waves. These findings underscore the acoustically responsive architectural design in preserving the sonic integrity of traditional Chinese opera and highlight the value of simulation-based approaches in heritage research.

Neurodegeneration and neuroinflammation are key components in the pathogenesis of Japanese Encephalitis caused by Japanese Encephalitis Virus (JEV) infection. The N-methyl-D-aspartate (NMDA)-type glutamate receptor displays excitatory neurotoxic and pro-inflammatory properties in a cell context-dependent manner. Herein, potential roles of the NMDA receptor in excitatory neurotoxicity and neuroinflammation and effects of NMDA receptor blockade against JEV pathogenesis were investigated in rat microglia, neuron/glia, neuron cultures, and C57BL/6 mice. In microglia, JEV infection induced glutamate release and activated post-receptor NMDA signaling, leading to activation of Ca 2+ mobilization and Calcium/Calmodulin-dependent Protein Kinase II (CaMKII), accompanied by pro-inflammatory NF-κB and AP-1 activation and cytokine expression. Additionally, increased Dynamin-Related Protein-1 protein phosphorylation, NAPDH Oxidase-2/4 expression, free radical generation, and Endoplasmic Reticulum stress paralleled with the reactive changes of microglia after JEV infection. JEV infection-induced biochemical and molecular changes contributed to microglia reactivity and pro-inflammatory cytokine expression. NMDA receptor antagonists MK801 and memantine alleviated intracellular signaling and pro-inflammatory cytokine expression in JEV-infected microglia. JEV infection induced neuronal cell death in neuron/glia culture associated with the concurrent production of pro-inflammatory cytokines. Conditioned media of JEV-infected microglia compromised neuron viability in neuron culture. JEV infection-associated neuronal cell death was alleviated by MK801 and memantine. Activation of NMDA receptor-related inflammatory changes, microglia activation, and neurodegeneration as well as reversal effects of memantine were revealed in the brains of JEV-infected mice. The current findings highlight a crucial role of the glutamate/NMDA receptor axis in linking excitotoxicity and neuroinflammation during the course of JEV pathogenesis, and proposes the anti-inflammatory and neuroprotective potential of NMDA receptor blockade.

The prevalence of osteoporosis has drastically increased recently. It is not only the most frequent but is also a major global public health problem due to its high morbidity. There are many risk factors associated with osteoporosis were identified. However, most studies have used the traditional multiple linear regression (MLR) to explore their relationships. Recently, machine learning (Mach-L) has become a new modality for data analysis because it enables machine to learn from past data or experiences without being explicitly programmed and could capture nonlinear relationships better. These methods have the potential to outperform conventional MLR in disease prediction. In the present study, we enrolled a Chinese post-menopause cohort followed up for 4 years. The difference of T-score (δ-T score) was the dependent variable. Information such as demographic, biochemistry and life styles were the independent variables. Our goals were: (1) Compare the prediction accuracy between Mach-L and traditional MLR for δ-T score. (2) Rank the importance of risk factors (independent variables) for prediction of δ T-score. Totally, there were 1698 postmenopausal women were enrolled from MJ Health Database. Four different Mach-L methods namely, Random forest (RF), eXtreme Gradient Boosting (XGBoost), Naïve Bayes (NB), and stochastic gradient boosting (SGB), to construct predictive models for predicting δ-BMD after four years follow-up. The dataset was then randomly divided into an 80% training dataset for model building and a 20% testing dataset for model testing. A 10-fold cross-validation technique for hyperparameter tuning was used. The model with the lowest root mean square error for the validation dataset was viewed as the best model for each ML method. The averaged metrics of the RF, SGB, NB, and XGBoost models were used to compare the model performance of the benchmark MLR model that used the same training and testing dataset as the Mach-L methods. We defined that the priority demonstrated in each model ranked 1 as the most critical risk factor and 22 as the last selected risk factor. For Pearson correlation, age, education, BMI, HDL-C, and TSH were positively and plasma calcium level, and baseline T-score were negatively correlated with δ-T score. All four Mach-L methods yielded lower prediction errors than the MLR method and were all convincing Mach-L models. From our results, it could be noted that education level is the most important factor for δ-T Score, followed by DBP, smoking, SBP, UA, age, and LDL-C. All four Mach-L outperformed traditional MLR. By using Mach-L, the most important six risk factors were selected which are, from the most important to the least: DBP, SBP, UA, education level, TG and sleeping hour. δ T score was positively related to SBP, education level, UA and TG and negatively related to DBP and sleeping hour in postmenopausal Chinese women.

How antimicrobial peptides form pores in membranes is of interest as a fundamental membrane process. However, the underlying molecular mechanism, which has potential applications in therapeutics, nonviral gene transfer, and drug delivery, has been in dispute. We have resolved this mechanism by observing the time-dependent process of pore formation in individual giant unilamellar vesicles (GUVs) exposed to a melittin solution. An individual GUV first expanded its surface area at constant volume and then suddenly reversed to expanding its volume at constant area. The area expansion, the volume expansion, and the point of reversal all match the results of equilibrium measurements performed on peptide-lipid mixtures. The mechanism includes a negative feedback that makes peptide-induced pores stable with a well defined size, contrary to the suggestion that peptides disintegrate the membrane in a detergent-like manner.

Reactive oxygen species (ROS)-induced vascular endothelial cell apoptosis is strongly associated with atherosclerosis progression. Herein, we aimed to examine whether Kansuinine A (KA), extracted from Euphorbia kansui L., prevents atherosclerosis development in a mouse model and inhibits cell apoptosis through oxidative stress reduction. Atherosclerosis development was analyzed in apolipoprotein E-deficient (ApoE−/−) mice fed a high-fat diet (HFD) using Oil Red O staining and H&E staining. Human aortic endothelial cells (HAECs) were treated with KA, followed by hydrogen peroxide (H2O2), to investigate the KA-mediated inhibition of ROS-induced oxidative stress and cell apoptosis. Oil Red O staining and H&E staining showed that atherosclerotic lesion size was significantly smaller in the aortic arch of ApoE−/− mice in the HFD+KA group than that in the aortic arch of those in the HFD group. Further, KA (0.1–1.0 μM) blocked the H2O2-induced death of HAECs and ROS generation. The H2O2-mediated upregulation of phosphorylated IKKβ, phosphorylated IκBα, and phosphorylated NF-κB was suppressed by KA. KA also reduced the Bax/Bcl-2 ratio and cleaved caspase-3 expression, preventing H2O2-induced vascular endothelial cell apoptosis. Our results indicate that KA may protect against ROS-induced endothelial cell apoptosis and has considerable clinical potential in the prevention of atherosclerosis and cardiovascular diseases.