With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Ischemic stroke (IS) ranks as a leading cause of death and disability globally. The blood-brain barrier (BBB) poses significant challenges for effective drug delivery to brain tissues. Recent decades have seen the development of targeted nanomedicine and biomimetic technologies, sparking substantial interest in biomimetic drug delivery systems for treating IS. These systems are devised by utilizing or replicating natural cells and their derivatives, offering promising new pathways for detection and transport across the BBB. Their multifunctionality and high biocompatibility make them effective treatment options for IS. In addition, the incorporation of engineering techniques has provided these biomimetic drug delivery systems with active targeting capabilities, enhancing the accumulation of therapeutic agents in ischemic tissues and specific cell types. This improvement boosts drug transport and therapeutic efficacy. However, it is crucial to thoroughly understand the advantages and limitations of various engineering strategies employed in constructing biomimetic delivery systems. Selecting appropriate construction methods based on the characteristics of the disease is vital to achieving optimal treatment outcomes. This review summarizes recent advancements in three types of engineered biomimetic drug delivery systems, developed from natural cells and their derivatives, for treating IS. It also discusses their effectiveness in application and potential challenges in future clinical translation.
Humans ; Drug Delivery Systems/methods* ; Ischemic Stroke/drug therapy* ; Animals ; Blood-Brain Barrier/metabolism* ; Stroke/drug therapy*

Objective: To investigate the molecular mechanisms and pathways of action of total flavonoids of Dracocephalum moldavica L.(TFDM) in treating vascular cognitive impairment(VCI) based on network pharmacology and in vivo animal experiments. Methods : The swiss target prediction database, literature, and PubChem were used to screen the active components and action targets of TFDM. The online mendelian inheritance in man(OMIM) and GeneCards databases were utilized to screen for possible VCI targets. Venny software was used to obtain the intersection target of TFDM and VCI. The search tool for recurring instances of neighbouring genes(String) database and Cytoscape software was used to construct the PPI network. The database for annotation, visualization and integrated discovery(DAVID) database was utilized to screen for the kyoto encyclopedia of genes and genomes(KEGG) pathway and gene ontology(GO) enrichment analyses to explore the molecular mechanism and signaling pathway of TFDM for VCI. 24 rats were divided into Sham, Model, Donepezil, and TFDM groups. Except for the Sham group, the VCI model was created using modified bilateral common carotid artery ligation. After continuous gavage for 21 days, the Morris water maze test was used to evaluate the spatial learning and memory ability of rats. Hematoxy-lineosin(HE) staining was used to observe the pathological changes in the hippocampal CA1 and cortex region of the animals and immunohistochemistry detection of zonula occludens-1(ZO-1) content in the brains of the rats. Western blot was used to detect nuclear factor kappa-B p65(NF-κB p65) and tumor necrosis factor-α(TNF-α) in rat brains. Results : A total of 39 active ingredients of TFDM were screened, 209 corresponding targets, 10 417 gene targets of VCI, and 193 intersecting targets. According to the results of the GO enrichment of function analysis, TFDM could improve the response of reactive oxygen species and metabolic processes of reactive oxygen species, etc. KEGG pathway enrichment analysis suggested that TFDM might regulate TNF, IL-17 signing pathway, etc. The results of animal experiments showed that TFDM improved learning and memory while reduced pathological damage in the brains of VCI rats. In addition, TFDM upregulated the positive expression of ZO-1 and downregulated the protein levels of TNF-α and NF-κB p65(P<0.05). Conclusion TFDM can improve the cognitive function of VCI through multi-components and multi-targets, and its key mechanism may be related to inhibiting TNF-α/NF-κB p65 signaling pathway,reducing neuroinflammation,and improvement of blood-brain barrier permeability.

The aim of this investigation was to determine the optimal storage medium for testicular hypothermic transportation and identify the ideal concentration for the application of the protective agent 5-aminolevulinic acid (5-ALA). Furthermore, this study aimed to explore the underlying mechanism of the protective effects of 5-ALA. First, we collected and stored mouse testicular fragments in different media, including Hank's balanced salt solution (HBSS; n = 5), Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F12; n = 5), and alpha-minimum essential medium (αMEM; n = 5). Storage of testicular tissue in HBSS preserved the integrity of testicular morphology better than that in the DMEM/F12 group ( P < 0.05) and the αMEM group ( P < 0.01). Testicular fragments were subsequently placed in HBSS with various concentrations of 5-ALA (0 [control], 1 mmol l -1 , 2 mmol l -1 , and 5 mmol l -1 ) to determine the most effective concentration of 5-ALA. The 2 mmol l -1 5-ALA group ( n = 3) presented the highest positive rate of spermatogonial stem cells compared with those in the control, 1 mmol l -1 , and 5 mmol l -1 5-ALA groups. Finally, the tissue fragments were preserved in HBSS with control ( n = 3) and 2 mmol l -1 5-ALA ( n = 3) under low-temperature conditions. A comparative analysis was performed against fresh testes ( n = 3) to elucidate the underlying mechanism of 5-ALA. Gene set enrichment analysis (GSEA) for WikiPathways revealed that the p38 mitogen-activated protein kinase (MAPK) signaling pathway was downregulated in the 2 mmol l -1 5-ALA group compared with that in the control group (normalized enrichment score [NES] = -1.57, false discovery rate [FDR] = 0.229, and P = 0.019). In conclusion, these data suggest that using 2 mmol l -1 5-ALA in HBSS effectively protected the viability of spermatogonial stem cells upon hypothermic transportation.
Male ; Animals ; Testis/cytology* ; Aminolevulinic Acid/pharmacology* ; Mice ; Organ Preservation/methods* ; Organ Preservation Solutions/pharmacology* ; Cryopreservation/methods*

Periodontitis is a common oral disease caused by bacteria coupled with an excessive host immune response. Stem cell therapy can be a promising treatment strategy for periodontitis, but the relevant mechanism is complicated. This study aimed to explore the therapeutic potential of mitochondria from human embryonic stem cell-derived mesenchymal stem cells (hESC-MSCs) for the treatment of periodontitis. The gingival tissues of periodontitis patients are characterized by abnormal mitochondrial structure. Human gingival fibroblasts (HGFs) were exposed to 5 μg/mL lipopolysaccharide (LPS) for 24 h to establish a cell injury model. When treated with hESC-MSCs or mitochondria derived from hESC-MSCs, HGFs showed reduced expression of inflammatory genes, increased adenosine triphosphate (ATP) level, decreased reactive oxygen species (ROS) production, and enhanced mitochondrial function compared to the control. The average efficiency of isolated mitochondrial transfer by hESC-MSCs was determined to be 8.93%. Besides, a therapy of local mitochondrial injection in mice with LPS-induced periodontitis showed a reduction in inflammatory gene expression, as well as an increase in both the mitochondrial number and the aspect ratio in gingival tissues. In conclusion, our results indicate that mitochondria derived from hESC-MSCs can reduce the inflammatory response and improve mitochondrial function in HGFs, suggesting that the transfer of mitochondria between hESC-MSCs and HGFs serves as a potential mechanism underlying the therapeutic effect of stem cells.
Humans ; Gingiva/cytology* ; Fibroblasts/metabolism* ; Mitochondria/physiology* ; Mesenchymal Stem Cells/cytology* ; Animals ; Periodontitis/therapy* ; Mice ; Reactive Oxygen Species/metabolism* ; Inflammation ; Lipopolysaccharides ; Human Embryonic Stem Cells/cytology* ; Cells, Cultured ; Adenosine Triphosphate/metabolism* ; Male

Ischemic stroke is the leading cause of disability and mortality worldwide. The blood‒brain barrier (BBB) is the first line of defense after ischemic stroke. Disruption of the BBB induced by brain microvascular endothelial cells (BMECs) dysfunction is a key event that triggers secondary damage to the central nervous system, where blood-borne fluids and immune cells penetrate the brain parenchyma, causing cerebral edema and inflammatory response and further aggravating brain damage. Here, we develop a novel artificial mesenchymal stem cell (MSC) extracellular vesicles by integrating MSC membrane proteins into liposomal bilayers, which encapsulated miR-132-3p with protective effects on BMECs. The artificial extracellular vesicles (MSCo/miR-132-3p) had low immunogenicity to reduce non-specific clearance by the mononuclear phagocytosis system (MPS) and could target ischemia-injured BMECs. After internalization into the damaged BMECs, MSCo/miR-132-3p escaped the lysosomes via the H_II phase transition of 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) and decreased cellular reactive oxygen species (ROS) and apoptosis levels by regulating the RASA1/RAS/PI3K/AKT signaling pathway. In the transient middle cerebral artery occlusion (tMCAO) models, MSCo/miR-132-3p targeted impaired brain regions (approximately 9 times the accumulation of plain liposomes at 12 h), reduced cerebral vascular disruption, protected BBB integrity, and decreased infarct volume (from 44.95% to 6.99%).

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective This study aims to analyze the factors influencing per capita current health expenditure in Guizhou Province from 2016 to 2022 using the gray correlation analysis method.Methods Based on the"SHA2011"accounting results of current health expenditure in Guizhou Province,as well as data from the"Guizhou Statistical Yearbook"and"Guizhou Health Statistical Yearbook",the gray correlation analysis method was used to analyze the factors influencing per capita current health expenditure in Guizhou Province from 2016 to 2022.Results The factors with the highest correlation to per capita current health expenditure in Guizhou Province were health expenditure(0.829),followed by the number of health technical personnel per thousand people(0.715),the number of practicing(assistant)physicians per thousand people(0.705),and per capita GDP(0.704).The factor with the lowest correlation was the proportion of the tertiary industry to GDP(0.543).Conclusion Health expenditure investment has the strongest correlation with per capita current health expenditure in Guizhou Province.Health re-source investment and health service capacity are the main influencing factors of per capita current health expenditure in Guizhou Province.At the same time,the impact of economic and social factors on current health expenditure should be fully recognized.