Dual Engine Boosts Organic Photoelectrochemical Transistor for Enhanced Modulation and Bioanalysis.

Organic photoelectrochemical transistor (OPECT) has shown substantial potential in the development of next-generation bioanalysis yet is limited by the either-or situation between the photoelectrode types and the channel types. Inspired by the dual-photoelectrode systems, we propose a new architecture of dual-engine OPECT for enhanced signal modulation and its biosensing application. Exemplified by incorporating the CdS/Bi2S3 photoanode and Cu2O photocathode within the gate-source circuit of Ag/AgCl-gated poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) channel, the device shows enhanced modulation capability and larger transconductance (gm) against the single-photoelectrode ones. Moreover, the light irritation upon the device effectively shifts the peak value of gm to zero gate voltage without degradation and generates larger current steps that are advantageous for the sensitive bioanalysis. Based on the as-developed dual-photoelectrode OPECT, target-mediated recycling and etching reactions are designed upon the CdS/Bi2S3, which could result in dual signal amplification and realize the sensitive microRNA-155 biodetection with a linear range from 1 fM to 100 pM and a lower detection limit of 0.12 fM.

Single-nucleus RNA transcriptome profiling reveals murine adipose tissue endothelial cell proliferation gene networks involved in obesity development.

Endothelial cells play an important role in the metabolism of adipose tissue (AT). This study aimed to analyze the changes that adipose tissue in AT endothelial cells undergo during the development of obesity, using single-nucleus RNA sequence (snRNA-seq). Mouse paraepididymal AT cells were subjected to snRNA-seq with the 10X Genomics platform. The cell types were then clustered using t-distributed stochastic neighbor embedding and unbiased computational informatics analyses. Protein-protein interactions network was established using the STRING database and visualized using Cytoscape. The dataset was subjected to differential gene enrichment analysis. In total, 21,333 cells acquired from 24 mouse paraepididymal AT samples were analyzed using snRNA-seq. This study identified 18 distinct clusters and annotated macrophages, fibroblasts, epithelial cells, T cells, endothelial cells, stem cells, neutrophil cells, and neutrophil cell types based on representative markers. Cluster 12 was defined as endothelial cells. The proportion of endothelial cells decreased with the development of obesity. Inflammatory factors, such as Vegfa and Prdm16 were upregulated in the medium obesity group but downregulated in the obesity group. Genes, such as Prox1, Erg, Flt4, Kdr, Flt1, and Pecam1 promoted the proliferation of AT endothelial cells and maintained the internal environment of AT. This study established a reference model and general framework for studying the mechanisms, biomarkers, and therapeutic targets of endothelial cell dysfunction-related diseases at the single-cell level.

Multilevel Screening Strategy to Identify the Hydrophobic Organic Components of Ambient PM2.5 Associated with Hepatocellular Steatosis.

Hepatic steatosis is the first step in a series of events that drives hepatic disease and has been considerably associated with exposure to fine particulate matter (PM2.5). Although the chemical constituents of particles matter in the negative health effects, the specific components of PM2.5 that trigger hepatic steatosis remain unclear. New strategies prioritizing the identification of the key components with the highest potential to cause adverse effects among the numerous components of PM2.5 are needed. Herein, we established a high-resolution mass spectrometry (MS) data set comprising the hydrophobic organic components corresponding to 67 PM2.5 samples in total from Taiyuan and Guangzhou, two representative cities in North and South China, respectively. The lipid accumulation bioeffect profiles of the above samples were also obtained. Considerable hepatocyte lipid accumulation was observed in most PM2.5 extracts. Subsequently, 40 of 695 components were initially screened through machine learning-assisted data filtering based on an integrated bioassay with MS data. Next, nine compounds were further selected as candidates contributing to hepatocellular steatosis based on absorption, distribution, metabolism, and excretion evaluation and molecular dockingin silico. Finally, seven components were confirmed in vitro. This study provided a multilevel screening strategy for key active components in PM2.5 and provided insight into the hydrophobic PM2.5 components that induce hepatocellular steatosis.

Supramolecular prodrug of SN38 based on endogenous albumin and SN38 prodrug modified with semaglutide side chain to improve the tumor distribution.

To improve the biodistribution of the drug in the tumor, a supramolecular prodrug of SN38 was fabricated in situ between endogenous albumin and SN38 prodrug modified with semaglutide side chain. Firstly, SN38 was conjugated with semaglutide side chain and octadecanedioic acid via glycine linkers to obtain SI-Gly-SN38 and OA-Gly-SN38 prodrugs, respectively. Both SI-Gly-SN38 and OA-Gly-SN38 exhibited excellent stability in PBS for over 24 h. Due to the strong binding affinity of the semaglutide side chain with albumin, the plasma half-life of SI-Gly-SN38 was 2.7 times higher than that of OA-Gly-SN38. Furthermore, with addition of HSA, the fluorescence intensity of SI-Gly-SN38 was 4 times higher than that of OA-Gly-SN38, confirming its strong binding capability with HSA. MTT assay showed that the cytotoxicity of SI-Gly-SN38 and OA-Gly-SN38 was higher than that of Irinotecan. Even incubated with HSA, the SI-Gly-SN38 and OA-Gly-SN38 still maintained high cytotoxicity, indicating minimal influence of HSA on their cytotoxicity. In vivo pharmacokinetic studies demonstrated that the circulation half-life of SI-Gly-SN38 was twice that of OA-Gly-SN38. SI-Gly-SN38 exhibited significantly reduced accumulation in the lungs, being only 0.23 times that of OA-Gly-SN38. The release of free SN38 in the lungs from SI-Gly-SN38 was only 0.4 times that from OA-Gly-SN38 and Irinotecan. The SI-Gly-SN38 showed the highest accumulation in tumors. The tumor inhibition rate of SI-Gly-SN38 was 6.42% higher than that of OA-Gly-SN38, and 8.67% higher than that of Irinotecan, respectively. These results indicate that the supramolecular prodrug delivery system can be constructed between SI-Gly-SN38 and endogenous albumin, which improves drug biodistribution in vivo, enhances tumor accumulation, and plays a crucial role in tumor growth inhibition.

Factors associated with the level of self-management in elderly patients with chronic diseases: a pathway analysis.

BACKGROUND: To analyze the effects and pathways of factors such as psychological capital, family functioning, and sources of meaning in life on the level of self-management in elderly patients with chronic diseases and to provide a basis for the development of relevant nursing interventions in the future. METHODS: Convenience sampling was used to select elderly patients with chronic diseases who underwent medical checkups and consultations at three community hospitals in Jinzhou city from March 2023 to October 2023, and the self-designed General Information Questionnaire (GIS), Psychological Capital of the Elderly Scale (PCE), Family Functioning Index Questionnaire (APGAR), Sources of Meaning of Life Scale for Older Adults(SMSE), and Self-Management Behavior of Chronic Patients Scale (SMCS) were used. SPSS 26.0 was used for data entry, one-way analysis, Pearson correlation analysis, and multiple linear regression were used to analyze the data, and Amos 17.0 was used to construct the structural equation model. RESULTS: A total of 355 elderly patients with chronic diseases were included, and their self-management score was 74.75 ± 12.93, which was moderate. The results of the influencing factor analysis showed that the influencing factors of the self-management level of elderly chronic disease patients were age, years of illness, psychological capital, family functioning, and sources of meaning in life (p < 0.05). Path analysis revealed that sources of meaning in life were a partial mediator of the relationship between psychological capital and self-management, with an effect value of 0.166 (95% CI: 0.042,0.391), accounting for 37.6% of the total effect; life meaning was a partial mediator of family functioning and self-management level, with an effect value of 0.231 (95% CI: 0.040,0.452), accounting for 54.0% of the total effect. accounting for 54.0% of the total effect. CONCLUSION: The self-management of elderly patients with chronic diseases is intermediate. Healthcare professionals should actively implement holistic healthcare management measures from the family aspect to help patients understand the meaning of life and improve the level of patients' psychological capital to improve the self-management level of elderly patients with chronic diseases.

An inducible CRISPRi circuit for tunable dynamic regulation of gene expression in Saccharopolyspora erythraea.

Actinomyces are gram-positive bacteria known for their valuable secondary metabolites. Redirecting metabolic flux towards desired products in actinomycetes requires precise and dynamic regulation of gene expression. In this study, we integrated the CRISPR interference (CRISPRi) system with a cumate-inducible promoter to develop an inducible gene downregulation method in Saccharopolyspora erythraea, a prominent erythromycin-producing actinobacterium. The functionality of the cumate-inducible promoter was validated using the gusA gene as a reporter, and the successful inducible expression of the dCas9 gene was confirmed. The developed inducible CRISPRi strategy was then employed to downregulate the expression of target genes rppA in the wild-type strain NRRL2338 and sucC in the high erythromycin-producing strain E3. Through dynamic control of sucC expression, a significant enhancement in erythromycin production was achieved in strain E3. This study demonstrated the effectiveness of an inducible gene downregulation approach using CRISPRi and a cumate-inducible promoter, providing valuable insights for optimizing natural product production in actinomyces.

YOLOv8-MU: An Improved YOLOv8 Underwater Detector Based on a Large Kernel Block and a Multi-Branch Reparameterization Module.

Underwater visual detection technology is crucial for marine exploration and monitoring. Given the growing demand for accurate underwater target recognition, this study introduces an innovative architecture, YOLOv8-MU, which significantly enhances the detection accuracy. This model incorporates the large kernel block (LarK block) from UniRepLKNet to optimize the backbone network, achieving a broader receptive field without increasing the model's depth. Additionally, the integration of C2fSTR, which combines the Swin transformer with the C2f module, and the SPPFCSPC_EMA module, which blends Cross-Stage Partial Fast Spatial Pyramid Pooling (SPPFCSPC) with attention mechanisms, notably improves the detection accuracy and robustness for various biological targets. A fusion block from DAMO-YOLO further enhances the multi-scale feature extraction capabilities in the model's neck. Moreover, the adoption of the MPDIoU loss function, designed around the vertex distance, effectively addresses the challenges of localization accuracy and boundary clarity in underwater organism detection. The experimental results on the URPC2019 dataset indicate that YOLOv8-MU achieves an mAP@0.5 of 78.4%, showing an improvement of 4.0% over the original YOLOv8 model. Additionally, on the URPC2020 dataset, it achieves 80.9%, and, on the Aquarium dataset, it reaches 75.5%, surpassing other models, including YOLOv5 and YOLOv8n, thus confirming the wide applicability and generalization capabilities of our proposed improved model architecture. Furthermore, an evaluation on the improved URPC2019 dataset demonstrates leading performance (SOTA), with an mAP@0.5 of 88.1%, further verifying its superiority on this dataset. These results highlight the model's broad applicability and generalization capabilities across various underwater datasets.

Development and validation of a risk prediction model for mild cognitive impairment in elderly patients with type 2 diabetes mellitus.

BACKGROUND: The prevalence of mild cognitive impairment (MCI) is steadily increasing among elderly people with type 2 diabetes (T2DM). This study aimed to create and validate a predictive model based on a nomogram. METHODS: This cross-sectional study collected sociodemographic characteristics, T2DM-related factors, depression, and levels of social support from 530 older adults with T2DM. We used LASSO regression and multifactorial logistic regression to determine the predictors of the model. The performance of the nomogram was evaluated using calibration curves, receiver operating characteristics (ROC), and decision curve analysis (DCA). RESULTS: The nomogram comprised age, smoking, physical activity, social support, depression, living alone, and glycosylated hemoglobin. The AUC for the training and validation sets were 0.914 and 0.859. The DCA showed good clinical applicability. CONCLUSIONS: This predictive nomogram has satisfactory accuracy and discrimination. Therefore, the nomogram can be intuitively and easily used to detect MCI in elderly adults with T2DM.

Network Pharmacology Study on Herb Pair Bletilla striata-Galla chinensis in the Treatment of Chronic Skin Ulcers.

BACKGROUND: Herb pair Bletilla striata-Galla chinensis (BS-GC) is a classic combination of topical traditional Chinese medicine formulae in the treatment of chronic skin ulcers (CSUs). OBJECTIVE: The aim of this study is to explore the effective active ingredients of BS-GC, as well as the core targets and signal transduction pathways of its action on CSUs. METHODS: The ingredients of BS-GC were obtained from TCMSP and HERB databases. The targets of all active ingredients were retrieved from the SwissTargetPrediction database. The targets of CSUs were obtained from OMIM, GeneCards, Drugbank, and DisGeNET databases. A drug-disease target protein-protein interaction (PPI) network was constructed to select the most core targets, and an herb-ingredient-target network was built by utilizing Cytoscape 3.7.2. Furthermore, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes database (KEGG) analysis and verified the results of network pharmacology through molecular docking. RESULTS: A total of 40 active ingredients from the herb pair BS-GC were initially screened, and a total of 528 targets were retrieved. Meanwhile, the total number of CSU targets was 1032. Then, the number of common targets between BS-GC and CSUs was 107. The 13 core targets of herb pair BS-GC with CSUs were filtered out according to the PPI network, including AKT1, TNF, EGFR, BCL2, HIF1A, MMP-9, etc. The 5 main core active ingredients were 1-(4-Hydroxybenzyl)-2-methoxy-9,10-dihydrophenanthrene-4,7-diol, 1-(4- Hydroxybenzyl)-4-methoxy-9,10-dihydrophenanthrene-2,7-diol, physcion, dihydromyricetin, and myricetin. The main biological processes were inflammation, oxidative stress, and immune response, involving the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, NF-κB signaling pathway, and calcium signaling pathway. Molecular docking results showed good binding activity between the 5 main core active ingredients and 13 core targets. CONCLUSION: This study predicted the core targets and signal transduction pathways in the treatment of CSUs to provide a reference for further molecular mechanism research.

Fatigue, Physical Activity, and Quality of Life in Patients with Inflammatory Bowel Disease: A Cross-Sectional Study.

Purpose: The benefits of physical activity (PA) are widely recognized, but the intensity of PA in inflammatory bowel disease (IBD) patients with varying disease activity levels remains controversial. We aimed to investigate the relationship between PA levels, fatigue, and other health-related quality of life (QoL) in Chinese IBD patients. Patients and Methods: The study is a cross-sectional investigation conducted at a comprehensive IBD diagnosis and treatment facility in East China, spanning from August 2022 to February 2023. A total of 245 participants were initially enrolled, and after excluding individuals with incomplete data about crucial exposure and outcome variables, the final sample size amounted to 237. Participants were provided with a questionnaire encompassing sociodemographic factors, clinical information, the International Physical Activity Questionnaire (IPAQ), the Multidimensional Fatigue Inventory (MFI-20), and the Inflammatory Bowel Disease Questionnaire (IBDQ). Correlation analysis was employed to assess the relationship between variables. Results: A majority of participants (144) exhibited low levels of PA. Furthermore, 40.5% of all participants reported experiencing fatigue. Individuals with low levels of PA had an average MIF-20 score of 62.9±16.0. Correlation analysis showed that PA was significantly and negatively associated with fatigue (r = -0.224, p < 0.001). Additionally, PA was also negatively correlated with anxiety (r = -0.150, p < 0.05) and depression (r = -0.242, p < 0.001). On the other hand, PA was positively correlated with quality of life (QoL) (r = 0.171, p < 0.01). Furthermore, our analysis indicated that sleep disorders were positively associated with both anxiety (r = 0.349, p < 0.01) and depression (r = 0.354, p < 0.001). Conclusion: The levels of PA are significantly low, and there is a high prevalence of fatigue among individuals with IBD. PA in IBD showed a strong negative correlation with fatigue and a strong positive correlation with quality of life.

Deliberate self-harm among pediatric psychiatric inpatients in China: A single-center retrospective study.

BACKGROUND: For children and adolescents, deliberate self-harm (DSH) is becoming a mental health problem of concern. Despite several studies on the prevalence and factors of DSH in the world, there is little information on DSH among children and adolescents in China. This study explores the prevalence, types, associated risk factors and tendency of DSH in pediatric psychiatric inpatients in China. AIM: To understand the situation of DSH among hospitalized children and adolescents and its related factors. METHODS: In this study, we retrospectively studied 1414 hospitalized children and adolescents with mental illness at Xiamen Mental Health Center from 2014 to 2019, extracted the demographic and clinical data of all patients, and analyzed clinical risk factors of DSH. RESULTS: A total of 239 (16.90%) patients engaged in at least one type of DSH in our study. Cutting (n = 115, 48.12%) was the most common type of DSH. Females (n = 171, 71.55%) were more likely to engage in DSH than males (n = 68, 28.45%). DSH was positively associated with depressive disorders [OR = 3.845 (2.196-6.732); P < 0.01], female [OR = 2.536 (1.815-3.542); P < 0.01], parental marital status [OR = 5.387 (2.254-12.875); P < 0.01] and negative family history of psychiatric illness [OR = 7.767 (2.952-20.433); P < 0.01], but not with occupation, substance use and history of physical abuse. CONCLUSION: Our findings suggest that for patients with depression, females, an abnormal marriage of parents, and no history of mental illness, attention should be paid to the occurrence of DSH.

Enhancing SN38 prodrug delivery using a self-immolative linker and endogenous albumin transport.

Enhancing the delivery and release efficiency of hydroxyl agents, constrained by high pKa values and issues of release rate or unstable linkage, is a critical challenge. To address this, a self-immolative linker, composed of a modifiable p-hydroxybenzyl ether and a fast cyclization adapter (N-(ortho-hydroxyphenyl)-N-methylcarbamate) was strategically designed, for the synthesis of prodrugs. The innovative linker not only provides a side chain modification but also facilitates the rapid release of the active payloads, thereby enabling precise drug delivery. Particularly, five prodrug model compounds (J1, J2, J3, J5 and J6) were synthesized to evaluate the release rates by using ß-glucuronic acid as trigger and five hydroxyl compounds as model payloads. Significantly, all prodrug model compounds could efficiently release the hydroxyl payloads under the action of ß-glucuronidase, validating the robustness of the linker. And then, to assess the drug delivery and release efficiency using endogenous albumin as a transport vehicle, J1148, a SN38 prodrug modified with maleimide side chain was synthesized. Results demonstrated that J1148 covalently bound to plasma albumin through in situ Michael addition, effectively targeting the tumor microenvironment. Activated by ß-glucuronidase, J1148 underwent a classical 1, 6-elimination, followed by rapid cyclization of the adapter, thereby releasing SN38. Impressively, J1148 showed excellent therapeutic efficacy against human colonic cancer xenograft model, leading to a significant reduction or even disappearance of tumors (3/6 of mice cured). These findings underscore the potential of the designed linker in the delivery system of hydroxyl agents, positioning it at the forefront of advancements in drug delivery technology.

The evolution of simulation-based medical education research: From traditional to virtual simulations.

Background: Simulation-based medical education (SBME) is a widely used method in medical education. This study aims to analyze publications on SBME in terms of countries, institutions, journals, authors, and keyword co-occurrence, as well as to identify trends in SBME research. Methods: We retrieved the Publications on SBME from the Web of Science Core Collection (WoSCC) database from its inception to January 27, 2024. Microsoft Excel 2019, CiteSpace, and VOSviewer were used to identify the distribution of countries, journals, and authors, as well as to determine the research hotspots. Results: We retrieved a total of 11272 publications from WoSCC. The number of documents published in 2022 was the highest in the last few decades. The USA, the UK, and Canada were three key contributors to this field. The University of Toronto, Stanford University, and Harvard Medical School were the top major institutions with a larger number of publications. Konge, Lars was the most productive author, while McGaghie, William C was the highest cited author. BMC Medical Education has the highest number of publications among journals. The foundational themes of SBME are "Patient simulation," "extending reality," and "surgical skills." Conclusions: SBME has attracted considerable attention in medical education. The research hotspot is gradually shifting from traditional simulations with real people or mannequins to virtual, digitally-based simulations and online education. Further studies will be conducted to elucidate the mechanisms of SBME. The utilization of SBME will be more rationalized.

Prevalence and Outcomes of Cognitive Frailty Among Community-Dwelling Older Adults: A Systematic Review and Meta-Analysis.

PURPOSE: To systematically review the available evidence regarding the prevalence and outcomes of cognitive frailty-a clinical syndrome characterized by the combination of physical frailty and cognitive impairment, without dementia-in community-dwelling older adults. METHOD: The following databases were searched: PubMed, Web of Science, Embase, EBSCO, Cochrane Central Register of Controlled Trials, ProQuest, CNKI, Wanfang, VIP, and CBMdisc (inception to October 2, 2023). RESULTS: Twenty-four studies were included (N = 62,169) reporting a median prevalence of cognitive frailty among community-dwelling older adults of 12.2%. Frailty with cognitive impairment was independently associated with increased all-cause mortality (adjusted 8-year hazard ratio [HR] = 2.6, 95% confidence interval [CI] [2.05, 3.30]). There was evidence of increased risk of 3-year mortality for frailty (adjusted HR = 1.92, 95% CI [1.26, 2.93]) and prefrailty (adjusted HR = 1.79, 95% CI [1.33, 2.41]) with cognitive impairment. There was also evidence of increased risk of dementia for frailty (adjusted 24-month HR = 6.19, 95% CI [2.74, 13.99]; adjusted 4-year HR = 4.98, 95% CI [2.17, 11.41]) and prefrailty (adjusted 4-year HR = 5.21, 95% CI [2.95, 9.20]; adjusted 5-year HR = 14.5, 95% CI [1.68, 125.1]) with cognitive impairment. Activities of daily living (ADL) dependence was more frequent in individuals with cognitive impairment and frailty (adjusted 4-year odds ratio = 5.6, 95% CI [2.13, 14.72]). CONCLUSION: Of community-dwelling older adults, 12.2% have cognitive frailty as well as increased risk of all-cause mortality, dementia, and ADL dependence. Further studies on prevention and treatment of cognitive frailty is warranted. Health care providers should formulate specific interventions to decrease the impact of cognitive frailty. [Research in Gerontological Nursing, 17(4), 202-212.].

Alteration of the health effects of bioaerosols by chemical modification in the atmosphere: A review.

Bioaerosols are a subset of important airborne particulates that present a substantial human health hazard due to their allergenicity and infectivity. Chemical reactions in atmospheric processes can significantly influence the health hazard presented by bioaerosols; however, few studies have summarized such alterations to bioaerosols and the mechanisms involved. In this paper, we systematically review the chemical modifications of bioaerosols and the impact on their health effects, mainly focusing on the exacerbation of allergic diseases such as asthma, rhinitis, and bronchitis. Oxidation, nitration, and oligomerization induced by hydroxyl radicals, ozone, and nitrogen dioxide are the major chemical modifications affecting bioaerosols, all of which can aggravate allergenicity mainly through immunoglobulin E pathways. Such processes can even interact with climate change including the greenhouse effect, suggesting the importance of bioaerosols in the future implementation of carbon neutralization strategies. In summary, the chemical modification of bioaerosols and the subsequent impact on health hazards indicate that the combined management of both chemical and biological components is required to mitigate the health hazards of particulate air pollution.

Chemical Logic Gates on Active Colloids.

Recent studies have shown that active colloidal motors using enzymatic reactions for propulsion hold special promise for applications in fields ranging from biology to material science. It will be desirable to have active colloids with capability of computation so that they can act autonomously to sense their surroundings and alter their own dynamics. It is shown how small chemical networks that make use of enzymatic chemical reactions on the colloid surface can be used to construct motor-based chemical logic gates. The basic features of coupled enzymatic reactions that are responsible for propulsion and underlie the construction and function of chemical gates are described using continuum theory and molecular simulation. Examples are given that show how colloids with specific chemical logic gates, can perform simple sensing tasks. Due to the diverse functions of different enzyme gates, operating alone or in circuits, the work presented here supports the suggestion that synthetic motors using such gates could be designed to operate in an autonomous way in order to complete complicated tasks.

HSG-MGAF Net: Heterogeneous subgraph-guided multiscale graph attention fusion network for interpretable prediction of whole-slide image.

BACKGROUND AND OBJECTIVE: Pathological whole slide image (WSI) prediction and region of interest (ROI) localization are important issues in computer-aided diagnosis and postoperative analysis in clinical applications. Existing computer-aided methods for predicting WSI are mainly based on multiple instance learning (MIL) and its variants. However, most of the methods are based on instance independence and identical distribution assumption and performed at a single scale, which not fully exploit the hierarchical multiscale heterogeneous information contained in WSI. METHODS: Heterogeneous Subgraph-Guided Multiscale Graph Attention Fusion Network (HSG-MGAF Net) is proposed to build the topology of critical image patches at two scales for adaptive WSI prediction and lesion localization. The HSG-MGAF Net simulates the hierarchical heterogeneous information of WSI through graph and hypergraph at two scales, respectively. This framework not only fully exploits the low-order and potential high-order correlations of image patches at each scale, but also leverages the heterogeneous information of the two scales for adaptive WSI prediction. RESULTS: We validate the superiority of the proposed method on the CAMELYON16 and the TCGA- NSCLC, and the results show that HSG-MGAF Net outperforms the state-of-the-art method on both datasets. The average ACC, AUC and F1 score of HSG-MGAF Net can reach 92.7 %/0.951/0.892 and 92.2 %/0.957/0.919, respectively. The obtained heatmaps can also localize the positive regions more accurately, which have great consistency with the pixel-level labels. CONCLUSIONS: The results demonstrate that HSG-MGAF Net outperforms existing weakly supervised learning methods by introducing critical heterogeneous information between the two scales. This approach paves the way for further research on light weighted heterogeneous graph-based WSI prediction and ROI localization.

Establishment and validation of a prediction model for nonrecovery of left ventricular ejection fraction in acute myocardial infarction patients combined with decreased left ventricular ejection fraction.

BACKGROUND: This study aimed to investigate the risk factors for nonrecovery of left ventricular ejection fraction (LVEF) during follow-up in patients with acute myocardial infarction (AMI) who underwent percutaneous coronary intervention (PCI) combined with reduced LVEF, and establish and verify a risk prediction model based on these factors. METHODS: In this study, patients with AMI who underwent PCI in a high-volume PCI center between December 2018 and December 2021 were consecutively enrolled, screened, and randomly assigned to the model establishment and validation cohorts. A predictive model method based on least absolute shrinkage and selection operator regression was used for establishment and validation. RESULTS: Cardiac troponin I, myoglobin, left ventricular end-diastolic dimension, multivessel disease, and no-reflow were identified as potential predictors of LVEF recovery failure. The areas under the curve were 0.703 and 0.665 in the model establishment and validation cohorts, respectively, proving that the prediction model had some predictive ability. The calibration curves of the two cohorts showed good agreement with those of the nomogram model. In addition, the decision curve analysis showed that the model had a net clinical benefit. CONCLUSION: This prediction model can assess the risk of nonrecovery of LVEF in patients with AMI undergoing PCI combined with LVEF reduction during follow-up, and conveniently screen high-risk patients with nonrecoverable LVEF early.

Propane-2-sulfonic acid octadec-9-enyl-amide, a novel PPARα/γ dual agonist, attenuates molecular pathological alterations in learning memory in AD mice.

OBJECTIVE: Previous studies have revealed that Propane-2-sulfonic acid octadec-9-enyl-amide(N15) exerts a protective role in the inflammatory response after ischemic stroke and in neuronal damage. However, little is known about N15 in Alzheimer's disease (AD). The aim of this study was to investigate the effects of N15 on AD and explore the underlying molecular mechanism. METHODS: AD mice model was established by lateral ventricular injection with Aß25-35. N15 was daily intraperitoneal administered for 28 days. Morris Water Maze was used to evaluate the neurocognitive function of the mice. The expression of PPARα/γ, brain-derived neurotrophic factor (BDNF), Neurotrophin-3 (NT3), ADAM10, PS1 and BACE1 were measured by qPCR. Aß amyloid in the hippocampus was measured by Congo red assay. Toluidine blue staining was used to detect the neuronal apoptosis. Protein levels of ADAM10, PS1 and BACE1 were determined using immunoblotting. RESULTS: N15 treatment significantly reduced neurocognitive dysfunction, which also significantly activated the expression of PPARα/γ at an optimal dose of 200 mg/kg. Administration of N15 alleviated the formation of Aß amyloid in the hippocampus of AD mice, enhanced the BDNF mRNA expression, decreased the mRNA and protein levels of PS1 and BACE1, upregulated ADAM10 mRNA and protein levels. CONCLUSION: N15 exerts its neuroprotective effects through the activation of PPARα/γ and may be a potential drug for the treatment of AD.

SOCS modulates JAK-STAT pathway as a novel target to mediate the occurrence of neuroinflammation: Molecular details and treatment options.

SOCS (Suppressor of Cytokine Signalling) proteins are intracellular negative regulators that primarily modulate and inhibit cytokine-mediated signal transduction, playing a crucial role in immune homeostasis and related inflammatory diseases. SOCS act as inhibitors by regulating the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway, thereby intervening in the pathogenesis of inflammation and autoimmune diseases. Recent studies have also demonstrated their involvement in central immunity and neuroinflammation, showing a dual functionality. However, the specific mechanisms of SOCS in the central nervous system remain unclear. This review thoroughly elucidates the specific mechanisms linking the SOCS-JAK-STAT pathway with the inflammatory manifestations of neurodegenerative diseases. Based on this, it proposes the theory that SOCS proteins can regulate the JAK-STAT pathway and inhibit the occurrence of neuroinflammation. Additionally, this review explores in detail the current therapeutic landscape and potential of targeting SOCS in the brain via the JAK-STAT pathway for neuroinflammation, offering insights into potential targets for the treatment of neurodegenerative diseases.