Objective: To explore the latent profiles of psychological help seeking intentions among adolescents in Wuhan, and to investigate their association with non suicidal self injury (NSSI), in order to provide a theoretical basis for constructing an early intervention system for adolescents NSSI. Methods: From October to December 2022, a convenient sampling method was used to select 3 975 students from grades 7 to 12 in Wuhan. A self administered questionnaire assessed psychological help seeking intentions, followed by a post survey interview using the Ottawa Self injury Inventory to evaluate NSSI behaviors. Latent profile analysis(LPA) was used to explore the potential categories of help seeking intentions in adolescents. Multinomial Logistic regression was used to analyze factors associated with the latent profiles of help seeking intentions and multiple Logistic regression was used to analyze the association between latent profiles of help seeking intentions and NSSI. Results: Based on latent profile analysis, four latent profiles of help seeking intentions in adolescents were identified, namely overall low, moderate, and high help seeking group, as well as family/friendfocused help seeking group, accouting for 14.1%, 20.9%, 43.1% and 21.8%, respectively. Multinomial Logistic regression analysis showed that compared to senior high school students, junior high school students were more willing to seek help from family and friends ( OR =1.56); compared to males, females were more likely to exhibit moderate help seeking intentions( OR =1.37); students with extroverted or balanced personalities were more likely to exhibit high level help seeking intentions( OR =1.50, 1.49); students with average or good family economic status, better parental relationships, and adequate mental health knowledge were more likely to exhibit moderate and high level help seeking intentions( OR =1.59, 2.02; 1.80, 2.64; 1.44, 1.55; 1.34, 1.58) (all P <0.05). Students with moderate or severe family dysfunction were less likely to seek help from family and friends or to exhibit moderate and high level help seeking intentions( OR =0.51, 0.60, 0.25; 0.22, 0.27, 0.06, all P <0.01). Students whose parents exhibited stigma towards mental illness were less likely to show high level help seeking intentions( OR= 0.78 , P <0.05). Multivariable Logistic regression analysis results indicated that compared to the overall low help seeking intentions group, reduced risk of NSSI was observed among students in the overall moderate and overall high groups, as well as in the family/friend focused help seeking group( OR =0.73, 0.60, 0.70, all P <0.05). Conclusions Active psychological help seeking intentions can reduce NSSI behaviors in adolescents. Interventions should focus on improving family support environment to enhance adolescents intentions to seek psychological help.

Objective: To analyze the distribution characteristics of immunoglobulin A (IgA) concentration in Nanning Zhuang blood donors by measuring the concentration of plasma IgA. Methods: Enzyme-linked immunosorbent assay (ELISA) was performed to measure the absorbance of 2 000 plasma samples from Zhuang blood donors. The IgA concentration in samples was calculated using the ELISA Calc regression/fitting technology program. Results: The standard curve demonstrated that ELISA detection of plasma IgA concentration exhibited good precision. The frequency of IgA deficiency was 0/2 000. No statistically significant difference in the distribution of IgA concentration was observed between males and females (P>0.05). The distribution of IgA concentration varied significantly across age groups: younger individuals (18-39 years old) had lower plasma IgA levels (mg/dL) compared to older individuals (40-56 years old): 5-89.99 mg/dL group, 8.80% (176/2 000) vs 17.20% (344/2 000); 90-450 mg/dL group,20.65% (413/2 000) vs 51.20% (1 024/2 000); >450 mg/dL group, 0.45%, (9/2 000) vs 1.70% (34/2 000), P<0.05. No significant difference in IgA concentration was found among different ABO blood types in Zhuang blood donors (P>0.05). Spearman correlation analysis revealed a positive correlation between age and IgA concentration (R =0.114, P<0.05). Conclusion: No individuals with IgA deficiency were screened out among the Zhuang blood donors in Nanning area, and plasma IgA levels progressively increase with age.

OBJECTIVE To explore the potential mechanisms of astragalin （AG） in allevating ulcerative colitis （UC） in mice through modulation of the intestinal flora. METHODS Male C57BL/6 mice were randomly divided into normal group （CON group）， model group [dextran sodium sulfate （DSS） group]， 5-aminosalicylic acid group （5-ASA group）， AG low-dose group and high-dose group （AGL and AGH groups）， with 8 mice in each group. The mice UC model was established by drinking 3% DSS solution continuously for 7 days in all groups except the CON group. After that， 3% DSS solution was replaced by water， and the mice of each drug group were gavaged with the corresponding drug solution. Mice in the CON and DSS groups were gavaged with an equal volume of normal saline， once a day， for 7 days. After the last gavage， the body weight change index， disease activity index （DAI） score， colon length and spleen index， and levels of inflammatory factors （tumor necrosis factor-α， interleukin-1β， interleukin-6） were compared among the mice in each group； pathological changes in colonic tissues of the mice were observed in each group， and the pathological score and the percentage of goblet cells were compared； mRNA expressions of barrier-related factors [occludin and ZO-1] and inflammation-related factors [silencing information regulatory factor 1 （SIRT1）， c-Jun N-terminal kinase （JNK） and p38 mitogen-activated protein kinase （p38 MAPK）] were detected in each group of mice； the changes in the intestinal flora of mice in each group were analyzed and the contents of intestinal metabolites short-chain fatty acids （SCFAs） was determined. Using DSS and AG-treated fecal bacterial liquid as an intervention， the mechanism of anti-UC effect of AG was further verified by a fecal microbiota transplant experiment. RESULTS Compared with the CON group， the intestinal mucosal structure of mice in the DSS group was severely damaged， with obvious infiltration of inflammatory cells collapsing the wall； their body weight change index， colon length， the percentage of goblet cells， mRNA expressions of occludin， ZO-1 and SIRT1， Chao1 and Shannon indexes， and contents of acetic acid and butyric acid were significantly reduced， shortened or down-regulated （P＜0.05）； however， DAI score， spleen index， levels of inflammatory factors， pathological score， as well as mRNA expressions of p38 MAPK and JNK， were all significantly increased or up-regulated （P＜0.05）. Compared with the DSS group， colon tissue lesions of AG mice in all dose groups showed different degrees of improvement， and the above quantitative indexes were generally regressed （P＜0.05）， and the intervention effect of AG-treated fecal bacterial fluid was basically the same as that of AG. CONCLUSIONS AG can improve relevant symptoms in UC mice and reduce their inflammatory response and colonic histopathological changes. The above effects may be related to regulating the diversity of intestinal flora in mice， increasing the contents of butyric acid and propionic acid， and promoting the repair of the colonic mucosal barrier， thus regulating the expressions of genes related to the SIRT1/p38 MAPK inflammatory pathway.

OBJECTIVE To investigate the independent risk factors for carbapenem-resistant Klebsiella pneumoniae （CRKP） infection， develop a nomogram prediction model and validate it. METHODS Clinical data of hospitalized patients infected with CRKP between April 2020 and May 2023 at Kunming First People’s Hospital were retrospectively collected and matched 1∶1 with patients infected with carbapenem-susceptible Klebsiella pneumoniae （CSKP） during the same period as the modeling group. Using the same criteria， data from patients hospitalized and infected with CRKP and matched CSKP between June 2023 and June 2024 were collected as the validation group. Univariate analysis， LASSO regression and multivariate Logistic regression were conducted to identify independent risk factors for CRKP infection and to develop a nomogram prediction model. Internal validation of the model was performed using Bootstrap resampling， and external validation was carried out using the data of validation group. The predictive performance of the model was evaluated using receiver operating characteristic （ROC） curves and calibration plots. RESULTS A total of 530 patients were enrolled， with 372 in the modeling group and 158 in the validation group. Cerebrovascular disease， indwelling gastric tube， mechanical ventilation， exposure to carbapenem antibiotics， and exposure to β-lactamase inhibitor compound agents were identified as independent risk factors for CRKP infection （P＜0.05）. The nomogram predicting CRKP infection risk achieved an area under ROC of 0.729 and 0.803 in internal and external validations， respectively. Calibration curves indicated a high degree of consistency between predicted and observed probabilities. CONCLUSIONS Cerebrovascular disease， indwelling gastric tube， mechanical ventilation， exposure to carbapenem antibiotics， and exposure to β-lactamase inhibitor compound agent are independent risk factors for CRKP infection. The developed nomogram model for predicting CRKP infection risk demonstrates good predictive performance and can aid in the early identification of patients at high risk for CRKP infection.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Voice biomarkers， as an emerging smart medical technology， are now being used in applications such as assisting in the diagnosis and treatment of diseases， facilitating accurate and personalized medical services for patients. However， it also raises many ethical issues， including informed consent， privacy protection， accuracy and reliability， data security， legal risks， and other issues. This paper systematically sorted out the ethical issues in the applications of voice biomarkers in the medical field， summarized these issues， such as informed consent， privacy protection， accuracy and reliability， data security， and legal risks， as well as explored the corresponding coping strategies. These countermeasures encompassed utilizing new media platforms to raise public awareness of voice biomarkers， strengthening supervision and management to promote the privacy protection of voice biomarkers， reducing algorithm biases to promote the general benefits of voice biomarkers to the public， establishing multidisciplinary teams to protect the data security of voice biomarkers， and encouraging medical professionals and researchers to participate in policy research， with a view to providing references for promoting and regulating the applications of voice biomarkers in the medical field.

BACKGROUND: The sirtuin family is well recognized for its crucial involvement in various cellular processes. Nevertheless, studies on its role in the human endometrium are limited. This study aimed to explore the expression and localization of the sirtuin family in the human endometrium, focusing on sirtuin 3 (SIRT3) and its potential role in the oxidative imbalance of the endometrium in polycystic ovary syndrome (PCOS). METHODS: Endometrial specimens were collected from both patients with PCOS and controls undergoing hysteroscopy at the Center for Reproductive Medicine, Peking University Third Hospital, from July to August 2015 and used for cell culture. The protective effects of SIRT3 were investigated, and the mechanism of SIRT3 in improving endometrial receptivity of patients with PCOS was determined using various techniques, including cellular bioenergetic analysis, small interfering ribonucleic acid (siRNA) silencing, real-time quantitative polymerase chain reaction, Western blot, immunofluorescence, immunohistochemistry, and flow cytometry analysis. RESULTS: The sirtuin family was widely expressed in the human endometrium, with SIRT3 showing a significant increase in expression in patients with PCOS compared with controls ( P <0.05), as confirmed by protein and gene assays. Concurrently, endometrial antioxidant levels were elevated, while mitochondrial respiratory capacity was reduced, in patients with PCOS ( P <0.05). An endometrial oxidative stress (OS) model revealed that the downregulation of SIRT3 impaired the growth and proliferation status of endometrial cells and reduced their receptivity to day 4 mouse embryos. The results suggested that SIRT3 might be crucial in maintaining normal cellular state by regulating antioxidants, cell proliferation, and apoptosis, thereby contributing to enhanced endometrial receptivity. CONCLUSIONS Our findings proposed a significant role of SIRT3 in improving endometrial receptivity in patients with PCOS by alleviating OS and regulating the balance between cell proliferation and apoptosis. Therefore, SIRT3 could be a promising target for predicting and improving endometrial receptivity in this patient population.
Humans ; Female ; Polycystic Ovary Syndrome/metabolism* ; Endometrium/metabolism* ; Sirtuin 3/genetics* ; Oxidative Stress/genetics* ; Adult ; Animals ; Mice ; Apoptosis/physiology* ; Immunohistochemistry ; Cell Proliferation/physiology*

BACKGROUND: Temozolomide (TMZ) resistance is a significant challenge in treating glioblastoma (GBM). Collagen remodeling has been shown to be a critical factor for therapy resistance in other cancers. This study aimed to investigate the mechanism of TMZ chemoresistance by GBM cells reprogramming collagens. METHODS: Key extracellular matrix components, including collagens, were examined in paired primary and recurrent GBM samples as well as in TMZ-treated spontaneous and grafted GBM murine models. Human GBM cell lines (U251, TS667) and mouse primary GBM cells were used for in vitro studies. RNA-sequencing analysis, chromatin immunoprecipitation, immunoprecipitation-mass spectrometry, and co-immunoprecipitation assays were conducted to explore the mechanisms involved in collagen accumulation. A series of in vitro and in vivo experiments were designed to assess the role of the collagen regulators prolyl 4-hydroxylase subunit alpha 1 (P4HA1) and yes-associated protein (YAP) in sensitizing GBM cells to TMZ. RESULTS: This study revealed that TMZ exposure significantly elevated collagen type I (COL I) expression in both GBM patients and murine models. Collagen accumulation sustained GBM cell survival under TMZ-induced stress, contributing to enhanced TMZ resistance. Mechanistically, P4HA1 directly binded to and hydroxylated YAP, preventing ubiquitination-mediated YAP degradation. Stabilized YAP robustly drove collagen type I alpha 1 ( COL1A1) transcription, leading to increased collagen deposition. Disruption of the P4HA1-YAP axis effectively reduced COL I deposition, sensitized GBM cells to TMZ, and significantly improved mouse survival. CONCLUSION P4HA1 maintained YAP-mediated COL1A1 transcription, leading to collagen accumulation and promoting chemoresistance in GBM.
Temozolomide ; Humans ; Glioblastoma/drug therapy* ; Animals ; Mice ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics* ; YAP-Signaling Proteins ; Hydroxylation ; Dacarbazine/pharmacology* ; Adaptor Proteins, Signal Transducing/metabolism* ; Transcription Factors/metabolism* ; Collagen/biosynthesis* ; Collagen Type I/metabolism* ; Prolyl Hydroxylases/metabolism* ; Antineoplastic Agents, Alkylating/therapeutic use*

Alzheimer's disease (AD), a prototypical neurodegenerative disorder, encompasses multifaceted pathological processes. As pivotal cellular structures within the central nervous system, ion channels play critical roles in regulating neuronal excitability, synaptic transmission, and neurotransmitter release. Extensive research has revealed significant alterations in the expression and function of ion channels in AD, implicating an important role of ion channels in the pathogenesis of abnormal Aβ deposition, neuroinflammation, oxidative stress, and disruptions in calcium homeostasis and neural network functionality. This review systematically summarizes the crucial roles and underlying mechanisms of ion channels in the onset and progression of AD, highlighting how these channel abnormalities contribute to AD pathophysiology. We also discuss the therapeutic potential of ion channel modulation in AD treatment, emphasizing the importance of addressing multifactorial nature and heterogeneity of AD. The development of multi-target drugs and precision therapies is proposed as a future direction of scientific research.
Alzheimer Disease/therapy* ; Humans ; Ion Channels/physiology* ; Oxidative Stress ; Animals ; Amyloid beta-Peptides/metabolism* ; Synaptic Transmission ; Calcium/metabolism*

Dopamine, as a catecholamine neurotransmitter widely distributed in the central nervous system, is involved in physiological functions such as motivation, arousal, reinforcement, and movement through various dopamine signaling pathways. The hippocampus receives dopaminergic neuron projections from regions such as the ventral tegmental area, locus coeruleus, and substantia nigra. Through D1-like and D2-like receptors, dopamine exerts significant regulatory effects such as spatial navigation, episodic memory, fear, anxiety, and reward. This review mainly summarizes the research progress on the functions of dopamine in the hippocampus from aspects including the sources of dopamine, receptor distribution and function, and the association of hippocampal dopamine system dysregulation with neurodegenerative diseases. The aim is to provide insights into the involvement of the dopamine system in hippocampal functions and the diagnosis and treatment of related diseases.
Hippocampus/physiology* ; Dopamine/physiology* ; Humans ; Animals ; Receptors, Dopamine D2/physiology* ; Memory/physiology* ; Signal Transduction/physiology* ; Neurodegenerative Diseases/physiopathology*