BACKGROUND:Previous studies have found that neohesperidin can delay bone loss in ovariectomized mice and has the potential to treat osteoporosis,but its specific mechanism of action remains to be explored. OBJECTIVE:To explore the key targets and possible mechanisms of neohesperidin in the treatment of osteoporosis based on bioinformatics and cell experiments in vitro. METHODS:The gene expression dataset related to osteoporosis was obtained from GEO database,and the differentially expressed genes were screened and analyzed in R language.The osteoporosis-related targets were screened from GeneCards and DisGeNET databases,and the neohesperidin-related targets were screened from ChEMBL and PubChem databases,and the common targets were obtained by intersection of the three.The String database was used to construct the PPI network of intersection genes,and the key targets were screened.The DAVID database was used for GO and KEGG enrichment analysis.The AutoDock software was used to verify the molecular docking between the neohesperidin and the target protein.The effect of neohesperidin on osteogenic differentiation of C57 mouse bone marrow mesenchymal stem cells was detected.Complete medium was used as blank control group;osteogenic induction medium was used as the control group;and osteogenic induction medium containing different concentrations of neohesperidin(25,50 μmol/L)was used as experimental group.The expression of alkaline phosphatase,the degree of mineralization,the expression of osteogenic-related genes and target genes during osteogenic differentiation of cells were measured at corresponding time points. RESULTS AND CONCLUSION:(1)9 253 differentially expressed genes,2 161 osteoporosis-related targets,and 326 neohesperidin-related targets were screened.There were 53 common targets among the three.All 53 genes were up-regulated in osteoporosis samples.The PPI network screened the target gene PRKACA of research significance.GO function and KEGG pathway enrichment analysis showed that neohesperidin's treatment of osteoporosis through PRKACA target mainly depended on biological processes such as protein phosphorylation and protein autophosphorylation,acting on endocrine resistance,proteoglycan in cancer,and estrogen signaling pathway to play a therapeutic role.Molecular docking results showed that neohesperidin had a certain binding ability to the protein corresponding to the target PRKACA.(2)The results of alkaline phosphatase staining showed that neohesperidin could promote the expression of alkaline phosphatase in the early stage of osteogenic differentiation of mesenchymal stem cells.Alizarin red staining showed that neohesperidin could promote the mineralization of osteogenic differentiation of mesenchymal stem cells.RT-qPCR results showed that neohesperidin could increase the mRNA expression of alkaline phosphatase,PRKACA,and osteocalcin.(3)These results indicate that neohesperidin may promote osteogenic differentiation through PRKACA target on the estrogen signaling pathway to prevent and treat osteoporosis.

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.

Objective To investigate the epidemiological characteristics of dengue fever in Shenzhen City in 2024, so as to provide insights into formulation of the preventive and control measures for dengue fever. Methods The epidemiological data of dengue cases reported in Shenzhen City in 2024 were extracted from the China Disease Prevention and Control Information System and field epidemiological survey data of dengue fever in Shenzhen City, and the temporal, regional and population distributions of dengue fever cases, source of acquire dengue virus infections, disease diagnosis and treatment and outbreaks were analyzed. The dengue virus nucleic acid was tested and the serotypes of dengue virus were characterized using real-time quantitative reverse transcription PCR (RT-qPCR) assay, and the dengue virus gene was sequenced using next-generation sequencing (NGS). In addition, the surveillance on the density of Aedes albopictus was performed using Breteau index (BI) and mosquito oviposition index (MOI). Results A total of 1 735 dengue fever cases were reported in Shenzhen City in 2024, including 952 local cases and 783 imported cases. Most imported dengue fever cases acquired infections from eight cities of Foshan, Guangzhou, Zhongshan, Jiangmen, Dongguan, Zhaoqing, Huizhou, and Zhuhai in the Pearl River Delta region (664 cases, 84.8% of total imported cases) into Baoan, Longgang, and Nanshan districts. The epidemic exhibited an early onset and rapid progression, peaking during the period between September and November (1 632 cases, 94.1% of total cases), and dengue fever cases were distributed across 73 subdistricts in 10 districts, with most cases reported in densely populated central and western regions. The dengue fever cases had a male-to-female ratio of 1.9∶1.0, and a median age of 37 (21) years, with a higher median age among local cases than among imported cases [40 (20) years vs. 33(15) years; Z = -10.30, P < 0.05]. Housework, unemployment, workers, and business service were predominant occupations (1 405 cases, 81.0% of total cases), and there was a significant difference in the constituent ratio of occupations between local and imported cases (χ² = 92.30, P < 0.05). Among the 1 735 dengue fever cases, the median duration from onset to definitive diagnosis was 3.3 (2.9) days, and 1 686 cases (97.2%) were identified in healthcare facilities, with a low rate of hospitalization and isolation seen in 1 701 inpatients with available epidemiological data (485 cases, 28.5% of total inpatients). A total of 29 outbreaks of dengue fever occurred in Shenzhen City across 2024, which primarily in construction sites (27 outbreaks, 93.1% of total). Dengue virus type I was the dominant serotype causing dengue fever in Shenzhen City in 2024. Sequencing showed that the genomes of dengue virus from multiple dengue fever cases in Shenzhen City shared a high sequence homology with those from cities neighboring Shenzhen City, and there might be intra-city transmission of dengue virus among multiple construction sites in Shenzhen City. The Aedes albopictus density was significantly higher in Shenzhen City in 2024 than in 2023, peaking from May to September. The annual MOI values ranged from 0.9 to 14.0, and the BI values ranged from 0.6 to 6.0. Conclusions The overall epidemic of dengue fever was severe in Shenzhen City in 2024, which was greatly affected by case importation from neighboring cities, construction sites-centered local transmission, and the effectives of routine mosquito vector control was not satisfactory. Integrated dengue fever control measures should be implemented, focusing on regional joint prevention and control mechanisms, capacity building for mosquito vector control, addressing challenges in epidemic containment at construction sites, and strengthening case detection and management systems.

Aim To design and synthesize a series of phenylacetamide derivatives with different substituted phenylacetic acid as raw materials,and to investigate the protective effects of the compound on the damage of pancreatic β cells induced by palmitate acid(PA).Methods Min6 cells were cultured and divided into B blank control group,PA treatment group and PA+compounds group.The viability of Min6 cells was de-tected by CCK-8.The protein expressions of TXNIP and NLRP3 were observed by Western blot.MDA con-tent and SOD activity were detected by MDA and SOD kit.The insulin secretion of Min6 islet cells was meas-ured with insulin ELISA kit.Results A total of 10 phenylacetamide derivatives were designed and synthe-sized.Their structures were confirmed by 1H NMR and ESI-MS.Pharmacological activity study showed that most of the compounds had protective effects on islet βcells,among which LY-6 and LY-8 had stronger pro-tective effects than PA model group,with the cell via-bility of 61.4％,and LY-6 had the highest cell activi-ty,reaching to 104.9％.Compared with PA group,the protein expression of TXNIP and NLRP3 decreased in LY-6 and LY-8 groups,MDA content decreased and SOD activity increased,and insulin secretion of Min6 cell increased.Conclusions LY-6 and LY-8 inhibit TXNIP expression and decrease the activation of NL-RP3 inflammasome,and decrease the production of MDA and increase SOD activity,and thus reducing is-let β cells apoptosis and increasing insulin secretion.Therefore,the compound LY-6 could serve as a poten-tial anti-diabetic new chemical entity.

Objective To analyze the factors affecting the prognosis of patients with knee osteoarthritis,and to construct a nomogram prediction model in conjunction with multi-dimensional clinical indicators.Methods The clinical data of 234 pa-tients with knee osteoarthritis who were treated in our hospital from January 2015 to June 2021 were retrospectively analyzed,including 126 males and 108 females;age more than 60 years old for 135 cases,age less than 60 years old for 99 cases.Lysholm knee function score was used to evaluate the prognosis of the patients,and the patients were divided into good progno-sis group for 155 patients and poor prognosis group for 79 patients according to the prognosis.The clinical data of the subjects in the experimental cohort were analyzed by single factor and multiple factors.The patients were divided into experimental co-hort and verification cohort,the results of the multiple factor analysis were visualized to obtain a nomogram prediction model,the receiver operating characteristic curve(ROC),calibration curve and decision curve were used to evaluate the model's dis-crimination,accuracy and clinical benefit rate.Results The results of multivariate analysis showed that smoking,pre-treatment K-L grades of Ⅲto Ⅳ,and high levels of interleukin 6(IL-6)and matrix metallo proteinase-3(MMP-3)were risk factors for the prognosis of patients with knee osteoarthritis.ROC test results showed that the area under the curve of the nomogram model in the experimental cohort and validation cohort was 0.806[95％CI(0.742,0.866)]and 0.786[(95％CI(0.678,0.893)],re-spectively.The results of the calibration curve showed that the Brier values of the experimental cohort and verification cohort were 0.151 points and 0.134 points,respectively.When the threshold probability value in the decision curve was set to 31％,the clinical benefit rates of the experimental cohort and validation cohort were 51％and 56％,respectively.Conclusion The prognostic model of patients with knee osteoarthritis constructed based on multi-dimensional clinical data has both theoretical and practical significance,and can provide a reference for taking targeted measures to improve the prognosis of patients.

Objective To investigate the value of optical coherence tomography(OCT)in predicting the risk of major adverse cardiovascular events(MACE)in patients of acute coronary syndrome(ACS).Methods Four hundred and forth-eight ACS patients admitted to the First Affiliated Hospital of Xinjiang Medical University who underwent percutaneous coronary intervention(PCI)and OCT from February 2015 to February 2022 were selected as the study subjects.We found 749 non-culprit coronary lesions.And follow up the patients,median follow-up was 5 years[interquartile interval(IQR):3-7 years].Kaplan-meier was used to estimate the cumulative incidence of MACE,multivariate Cox regression was used to analyze the risk of MACE with OCT parameters non-culprit coronary lesions,and receiver operating characteristic(ROC)curve was used to evaluate the predictive value of OCT parameters for MACE in non-culprit coronary lesions.Results A total of 749 non-culprit coronary lesions were detected,and 41 MACE cases were caused by non-culprit coronary lesions imaged by OCT.Compared with plaques without thin-cap fibroatheroma(TCFA)and minimal lumen area(MLA)＜3.5 mm2,the incidence of MACE was significantly associated with vulnerable plaques with TCFA and MLA＜3.5 mm2(33％vs.3％,HR 13.62,95％CI 6.71-27.65,P＜0.001).Multivariate Cox regression analysis showed that larger maximum lipid arc(HR 1.02,95％CI 1.01-1.03,P＜0.001),smaller maximum lipid cap thickness(HR 0.97,95％CI 0.96-0.99,P＜0.001)and MLA(HR 0.31,95％CI 0.18-0.55,P＜0.001)were independent risk factors for MACE.The area under ROC curve(AUC)of the thinnest fiber cap thickness for predicting MACE occurrence was 0.858(95％CI 0.802-0.913),and the optimal cutoff value was 66.5 μm.The AUC of maximum lipid arc for predicting MACE occurrence was 0.853(95％CI 0.786-0.920),and the optimal cut-off value was 180.35°.The AUC of MLA for predicting MACE was 0.821(95％CI 0.766-0.876),and the optimal cutoff was 3.575 mm2.Conclusions The non-culprit coronary lesions with TCFA and MLA＜3.5 mm2 were significantly associated with an increased risk of subsequent MACE development at the lesion level,and OCT imaging helps early identification of the risk of MACE development in non-culprit coronary lesions in patients of ACS.

Critical care medicine-related treatment is an interdisciplinary and multi-professional process,often leading to secondary or concomitant mental disorders in clinical practice.Currently,there is no consensus on the pharmacological treatment of related mental illnesses in China.The Chinese Society of Psychosomatic Medicine collaborated with the Critical Care Medicine expert group to form a consensus writing expert group.After a systematic review of relevant literature,summarizing published domestic and foreign literature,and extensive discussions,the consensus was developed.The consensus elaborates on the principles and processes of the standardized use of psychotropic drugs in critical care medicine,as well as the clinical indications,precautions,and specific drug selection of various psychiatric medications,providing feasible suggestions and guidance for the clinical application of psychiatric medications in the intensive care unit.

Objective:To investigate the effect of CD8+CD28-T cells on acute graft-versus-host disease(aGVHD)after haploidentical hematopoietic stem cell transplantation(haplo-HSCT).Methods:The relationship between absolute count of CD8+CD28-T cells and aGVHD in 60 patients with malignant hematological diseases was retrospectively analyzed after haplo-HSCT,and the differences in the incidence rate of chronic graft-versus host disease(cGVHD),infection and prognosis between different CD8+CD28-T absolute cells count groups were compared.Results:aGVHD occurred in 40 of 60 patients after haplo-HSCT,with an incidence rate of 66.67％.The median occurrence time of aGVHD was 32.5(20-100)days.At 30 days after the transplantation,the absolute count of CD8+CD28-T cells of aGVHD group was significantly lower than that of non-aGVHD group(P=0.03).Thus the absolute count of CD8+CD28-T cells at 30 days after transplantation can be used to predict the occurrence of aGVHD to some extent.At 30 days after transplantation,the incidence rate of aGVHD in the low cell count group(CD8+CD28-T cells absolute count＜0.06/μl)was significantly higher than that in the high cell count group(CD8+CD28-T cells absolute count ≥0.06/μl,P=0.011).Multivariate Cox regression analysis further confirmed that the absolute count of CD8+CD28-T cells at 30 days after transplantation was an independent risk factor for aGVHD,and the risk of aGVHD in the low cell count group was 2.222 times higher than that in the high cell count group(P=0.015).The incidence of cGVHD,fungal infection,EBV infection and CMV infection were not significantly different between the two groups with different CD8+CD28-T cells absolute count.The overall survival,non-recurrent mortality and relapse rates were not significantly different between different CD8+CD28-T cells absolute count groups.Conclusion:Patients with delayed CD8+CD28-T cells reconstitution after haplo-HSCT are more likely to develop aGVHD,and the absolute count of CD8+CD28-T cells can be used to predict the incidence of aGVHD to some extent.The absolute count of CD8+CD28-T cells after haplo-HSCT was not associated with cGVHD,fungal infection,EBV infection,and CMV infection,and was also not significantly associated with the prognosis after transplantation.

Objective:This study evaluates the accessibility and equity of healthcare resources in deep mountain,shallow mountain,and plain suburban areas,taking Huairou,Mentougou,and Tongzhou districts of Beijing as examples,to identify factors contributing to the imbalance in resource allocation.Methods:Accessibility of healthcare services in the sample areas was measured using village-level health survey data and the Two-Step Floating Catchment Area(2SFCA)method.Equity of resource allocation was assessed using the Gini coefficient among other methods.Factors influencing imbalance were identified using the Geodetector and Spatial Lag Model.Results:The average accessibility scores for Huairou,Mentougou,and Tongzhou were 202.06,179.68,and 187.02,respectively.The Gini coefficients were 0.48,0.37,and 0.24,respectively.GDP,population density,and altitude were significant factors affecting accessibility.Conclusions and Suggestions:In Beijing,both plain and mountainous rural areas exhibited a spatial clustering of healthcare accessibility,higher near the city and lower in the suburbs,with plains performing better than mountains.Healthcare equity was ranked as plains>shallow mountains>deep mountains.Policies covering full healthcare services improved equity.It is recommended to strengthen the construction of village healthcare facilities and medical teams,improve the linkage of medical services at all rural levels,and enhance the willingness of villagers to seek primary care.Furthermore,gradual improvement of transportation and internet infrastructure is suggested to enhance the accessibility of online and offline medical services for villagers.

Objective:To evaluate the safety and efficiency of China-made Toumai Robot-assisted laparoscopic radical prosta-tectomy(LRP).Methods:This study included 40 cases of PCa treated from January 2023 to May 2023 by robot-assisted LRP with preservation of the bladder neck and maximal functional urethral length,15 cases with the assistance of Toumai Robot(the TMR group)and the other 25 with the assistance of da Vinci Robot as controls(the DVR group).We recorded the docking time,laparo-scopic surgery time,vesico-urethral anastomosis time,intraoperative blood loss and postoperative urinary continence,and compared them between the two groups.Results:Operations were successfully completed in all the cases.No statistically significant differ-ences were observed between the TMR and DVR groups in the docking time(6 min vs 5 min,P＞0.05)or intraoperative blood loss(200 ml vs 150 ml,P＞0.05).The TMR group,compared with the DVR group,showed a significantly longer median laparoscopic surgery time(146 min vs 130 min,P＜0.05)and median vesico-urethral anastomosis time(19 min vs 16 min,P＜0.05).There were no statistically significant differences between the TMR and DVR groups in the rates of urinary continence recovery immediately af-ter surgery(60.0％[9/15]vs 64.0％[16/25],P＞0.05)or at 1 month(80.0％[12/15])vs(76.0％[19/25],P＞0.05),3 months(93.3％[14/15])vs(92.0％[23/25],P＞0.05)and 6 months postoperatively(100％[15/15])vs(96％[24/25],P＞0.05).Conclusion:China-made Toumai? Robot surgical system is safe and reliable for laparoscopic radical prosta-tectomy,with satisfactory postoperative recovery of urinary continence.