1.Analysis and prediction of global burden due to cystic echinococcosis from 1990 to 2035
Zhen LAI ; Gang LIU ; Haili ZHAO ; Miaomiao QIU ; Jian CHEN ; En LUO ; Junguo XIN ; Xiaohong YANG
Chinese Journal of Schistosomiasis Control 2025;37(3):255-267
Objective To investigate the trends in the global burden due to cystic echinococcosis from 1990 to 2021, and to predict the global burden of cystic echinococcosis from 2022 to 2035, so as to provide insights into formulation of the cystic echinococcosis control strategy. Methods The global age-standardized prevalence, mortality, disability-adjusted life years (DALYs) rates and their 95% uncertainty intervals (UI) of cystic echinococcosis from 1990 to 2021 were captured from the Global Burden of Disease Study 2021 (GBD 2021) database, and the trends in the global burden of cystic echinococcosis from 1990 to 2021 were analyzed using the Joinpoint regression model. The associations between the global burden of cystic echinococcosis and socio-demographic index (SDI) were examined using a smoothing spline model and frontier analysis, and the global burden of cystic echinococcosis was projected from 2022 to 2035 using the Bayesian age-period-cohort (BAPC) model. Results The global agestandardized prevalence, mortality and DALYs rates of cystic echinococcosis were 7.69/105 [95% UI: (6.27/105, 9.51/105)], 0.02/105 [95% UI: (0.01/105, 0.02/105)], and 1.32/105 [95% UI: (0.99/105, 1.69/105)] in 2021. The global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a rise by 0.14% per year from 1990 to 2021, and the global age-standardized mortality and DALYs rates of cystic echinococcosis appeared a tendency towards a decline by 4.68% and 4.01% per year from 1990 to 2021, respectively. Joinpoint regression analysis showed that global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a decline from 1990 to 2000 [annual percent change (APC) = −0.66%, 95% confidence interval (CI): (−0.70%, −0.61%)] and from 2005 to 2015 [APC = −0.88%, 95% CI: (−0.93%, −0.82%)], and towards a rise from 2000 to 2005 [APC = 3.68%, 95% CI: (3.49%, 3.87%)] and from 2015 to 2021 [APC=0.30%, 95%CI: (0.19%, 0.40%)].Theagestandardized prevalence (r = −0.17, P < 0.05), mortality (r = −0.67, P < 0.05) and DALYs rates of cystic echinococcosis (r = −0.60, P < 0.05) all correlated negatively with SDI across 21 geographical regions from 1990 to 2021, and the age-standardized mortality (r = −0.61, P < 0.05) and DALYs rates (r = −0.44, P < 0.05) both correlated negatively with SDI across 204 countries and territories in 2021. Frontier analysis revealed that the age-standardized DALYs rate of cystic echinococcosis was still not in line with the frontier in some high-SDI countries or territories. In addition, the global age-standardized prevalence was projected with the BAPC model to appear a tendency towards a rise among both men [estimated annual percent change (EAPC) = 0.18%, 95% CI: (0.13%, 0.23%)] and women [EAPC = 0.29%, 95% CI: (0.24%, 0.34%)] from 2022 to 2035, and the global age-standardized mortality [men: EAPC = −4.71%, 95% CI: (−4.71%, −4.37%); women: EAPC = −4.74%, 95% CI: (−4.74%, −4.74%)] and DALYs rates [men: EAPC = −3.35%, 95% CI: (−3.36%, −3.34%); women: EAPC = −3.17%, 95% CI: (−3.18%, −3.16%)] were projected to appear a tendency towards a decline among both men and women. Conclusions The global burden of cystic echinococcosis appeared an overall tendency towards a decline from 1990 to 2021; however, the global prevalence of cystic echinococcosis is projected to appear a tendency towards a rise from 2022 to 2035. Intensified cystic echinococcosis control programmes are recommended.
2.tRF Prospect: tRNA-derived Fragment Target Prediction Based on Neural Network Learning
Dai-Xi REN ; Jian-Yong YI ; Yong-Zhen MO ; Mei YANG ; Wei XIONG ; Zhao-Yang ZENG ; Lei SHI
Progress in Biochemistry and Biophysics 2025;52(9):2428-2438
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.
3.Mechanisms and intervention strategies of aging based on epigenetics
Li-yuan ZHANG ; Hao-nan SHI ; Wen-feng ZHANG ; Ming-qian ZHANG ; Zi-yang ZHAO ; Zhen-zhen CHENG ; Ti ZHANG ; Zhen-teng YAN ; Jian-ning SUN ; Shi-fen DONG
Chinese Pharmacological Bulletin 2025;41(12):2230-2235
Aging is comprehensively influenced by multiple fac-tors such as internal genes,cellular metabolism,external envi-ronment,and lifestyle habits.Among them,epigenetic regula-tion plays a core role.Epigenetic modifications,including DNA methylation,histone modification,heterochromatin remodeling,and non-coding RNA regulation,act in concert with the three-di-mensional genome architecture to precisely regulate gene expres-sion.This review elaborates on the factors influencing epigenetic regulation,as well as the mechanisms of how epigenetics affects the occurrence of organismal aging and the corresponding inter-vention strategies,providing relevant insights for uncovering the mechanisms of aging and preventing/treating aging-related disea-ses.
4.Comprehensive evaluation of application effect of personalized narrative nursing in elderly patients with stroke hemiplegia
Mei-qin DING ; Zhen YANG ; Jian-guo TANG ; Fang LIU
Fudan University Journal of Medical Sciences 2025;52(5):743-746
We aimed to explore the value of personalized narrative intervention in the nursing care of elderly patients with stroke hemiplegia(SH).A total of 68 elderly patients with SH were selected and divided into two groups using the ball-rolling method,with 34 cases in each group.The control group received routine nursing care,while the observation group received routine care and personalized narrative nursing.The nursing outcomes of the two groups were compared.Compared with the control group,the observation group had lower scores in anxiety and depression(P<0.05),and higher scores in the Functional Evaluation of Cognitive State-Short Screening(FECS-SS)(P<0.05).The rehabilitation effects of normal rate in the observation group was higher than that in the control group(P<0.05).Personalized narrative nursing for SH patients can effectively relieve the patients'negative emotions,enhance their compliance with rehabilitation,and improve the outcomes of rehabilitation.
5.Expression characteristics and diagnostic value of PD-1 and PD-L1 in patients with acute exacerbation of chronic obstructive pulmonary disease
Yuexin SHI ; Li LI ; Jun YAN ; Caijun WU ; Zhi YAO ; Yuan-zhen JIAN ; Ziqing LI ; Fang LI ; Lulu YANG
The Journal of Practical Medicine 2025;41(11):1655-1662
Objective To investigate the expression characteristics and clinical diagnostic value of programmed death receptor 1(PD-1)and its corresponding ligand(PD-L1)in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD).Methods One hundred and sixty COPD patients who visited Dongzhimen Hospital of Beijing University of Chinese Medicine from April 2024 to November 2024 were included and divided into an acute exacerbation group of 100 cases and a stable group of 60 cases according to the severity of the disease.Additionally,40 healthy volunteers during the same period were recruited as the control group.The general clinical data of the patients were collected.Chronic Obstructive Pulmonary Disease Assessment Test(CAT)and Modified Medical Research Council Dyspnea Questionnaire(mMRC)Scale were used to test the severity of the disease;respiratory function testing was performed and fasting venous blood was collected for serum PD-1 and PD-L1 testing.Pearson correlation was used to analyze the correlation between serum PD-1,PD-L1,CAT,and mMRC,and multiple logistic regression analysis to identify the influencing factors of AECOPD.Receiver operating characteristic(ROC)curve was drawn to evaluate the diagnostic value of serum PD-1 and PD-L1 level for AECOPD.Results Serum PD-1 level in the stable COPD group and AECOPD group was significantly increased compared with that in the control group,while serum PD-L1 level was significantly decreased,showing statistical significance(P<0.05);The level of PD-1 gradually increased with the grading of lung function and the deterioration of AECOPD,with statistical significance(P<0.05);Pearson correlation showed that serum PD-1 level was positively correlated with CAT scores in COPD patients,while negatively with CAT scores,showing statistical significance(P<0.05);Multiple logistic regression analysis showed that elevated levels of serum inter-leukin-6(IL-6),neutrophil to lymphocyte ratio(NLR),and PD-1 were risk factors for AECOPD,while elevated level of PD-L1 was protective factor for AECOPD(P<0.05);ROC curve showed that the levels of PD-1,PD-L1,IL-6,NLR,and the area under the ROC curve(AUC)for their combined prediction of AECOPD diagnosis were 0.884,0.867,0.868,0.802,and 0.995,respectively.Conclusion Serum PD-1 and PD-L1 in AECOPD patients have presented certain expression characteristics,with elevated PD-1 level while decreased PD-L1 level.Both have good clinical diagnostic value for AECOPD.
6.Expert consensus on peri-implant keratinized mucosa augmentation at second-stage surgery.
Shiwen ZHANG ; Rui SHENG ; Zhen FAN ; Fang WANG ; Ping DI ; Junyu SHI ; Duohong ZOU ; Dehua LI ; Yufeng ZHANG ; Zhuofan CHEN ; Guoli YANG ; Wei GENG ; Lin WANG ; Jian ZHANG ; Yuanding HUANG ; Baohong ZHAO ; Chunbo TANG ; Dong WU ; Shulan XU ; Cheng YANG ; Yongbin MOU ; Jiacai HE ; Xingmei YANG ; Zhen TAN ; Xiaoxiao CAI ; Jiang CHEN ; Hongchang LAI ; Zuolin WANG ; Quan YUAN
International Journal of Oral Science 2025;17(1):51-51
Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans
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Consensus
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Dental Implants
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Mouth Mucosa/surgery*
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Keratins
7.Effects of Japan Tallow on Alleviating Liver Injury and Modulating Gut Microbiota in Type 2 Diabetic Mice
Kai-ya XIE ; Xin YU ; En-ya LI ; Li-ping HUA ; Xiao-man LI ; Ying-zhen SU ; Meng-chun SHU ; Yi-jian YANG
Progress in Modern Biomedicine 2025;25(19):3041-3047
Objective:To investigate the effects of Japan tallow(JT)on liver injury and gut microbiota regulation in type 2 diabetes mellitus(T2DM)mice,thereby providing a theoretical basis for developing therapeutic edible oils for diabetes treatment.Methods:T2DM animal model was established through a combined approach of nutritional intervention and chemical induction.Experimental animals were first fed a high-fat diet(HFD)for 6 weeks,followed by intraperitoneal injection of freshly prepared streptozotocin(STZ).After successful model establishment,the mice were divided into five groups(n=6 per group):control group without any intervention;T2DM group;HFD reversion to standard chow group;metformin group;and JT intervention group,which received respective treatments for 4 weeks.At the endpoint,fresh fecal samples were collected from all groups,and the gut microbiota composition was analyzed using 16s rDNA high-throughput sequencing.Liver histopathological changes were examined using histological methods.Results:Compared with the normal control(ND),T2DM mice showed significantly increased fasting blood glucose(FBG)levels,with evident hepatocyte lipid accumulation,steatosis,inflammatory cell infiltration,and widespread vacuolar and fatty degeneration.After Japan tallow(JT)intervention,FBG levels decreased significantly,liver color approximated normal appearance,and pathological morphology improved noticeably.16s rDNA sequencing analysis demonstrated that JT treatment could effectively regulate the intestinal microbiota structure in T2DM mice.Increased microbial α-diversity indices(Chao1,observed_species,Faith_pd,Simpson);At the phylum level,increased Verrucomicrobia abundance while decreased Proteobacteria were detected;At the family level,elevated Bifidobacteriaceae and reduced Porphyromonadaceae were seen;At the genus level,Bifidobacterium was promoted and Akkermansia proliferat while Escherichia and Klebsiella were downregulated.Conclusions:Japan tallow exhibits significant effects in alleviating liver tissue damage and regulating intestinal microbiota disorders in T2DM mice,our study indicated new theoretical basis for the research and development of potential strategy for diabetes.
8.International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025).
Sheng-Sheng ZHANG ; Lu-Qing ZHAO ; Xiao-Hua HOU ; Zhao-Xiang BIAN ; Jian-Hua ZHENG ; Hai-He TIAN ; Guan-Hu YANG ; Won-Sook HONG ; Yu-Ying HE ; Li LIU ; Hong SHEN ; Yan-Ping LI ; Sheng XIE ; Jin SHU ; Bin-Fang ZENG ; Jun-Xiang LI ; Zhen LIU ; Zheng-Hua XIAO ; Jing-Dong XIAO ; Pei-Yong ZHENG ; Shao-Gang HUANG ; Sheng-Liang CHEN ; Gui-Jun FEI
Journal of Integrative Medicine 2025;23(5):502-518
Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy*
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Humans
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Medicine, Chinese Traditional/methods*
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Practice Guidelines as Topic
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Drugs, Chinese Herbal/therapeutic use*
9.Laboratory Diagnosis and Molecular Epidemiological Characterization of the First Imported Case of Lassa Fever in China.
Yu Liang FENG ; Wei LI ; Ming Feng JIANG ; Hong Rong ZHONG ; Wei WU ; Lyu Bo TIAN ; Guo CHEN ; Zhen Hua CHEN ; Can LUO ; Rong Mei YUAN ; Xing Yu ZHOU ; Jian Dong LI ; Xiao Rong YANG ; Ming PAN
Biomedical and Environmental Sciences 2025;38(3):279-289
OBJECTIVE:
This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF.
METHODS:
Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus.
RESULTS:
LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response.
CONCLUSION
The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans
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China/epidemiology*
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Genome, Viral
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Lassa Fever/virology*
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Lassa virus/classification*
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Molecular Epidemiology
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Phylogeny
10.Construction and evaluation of a deep learning-based intelligent diagnosis model for temporomandibular joint osteoarthritis imaging
Dandan WU ; Pei WANG ; Yang JING ; Zhen JIA ; Jian YANG
Journal of Practical Stomatology 2025;41(4):519-524
Objective:To develop an automatic diagnostic model for temporomandibular joint osteoarthritis(TMJOA)imaging based on deep learning technology,and to assist clinical diagnosis and improve the efficiency and accuracy of TMJOA diagnosis.Methods:CBCT data of 220 patients were collected,and 2 052 sagittal images were exported.Regions of interest were delineated according to the imaging analysis criteria for temporomandibular joint disorders,and the images were classified into TMJOA-free,TMJOA-uncer-tain and TMJOA.The data were randomly divided into a training set and a validation set according to 8∶2 ratio,and the training set data were used to train a TMJOA detection model based on three lightweight YOLOV5 deep learning frameworks,and the models' performance was evaluated on the validation set.Results:The Yolov5N model demonstrated the best performance,achieving a de-tection accuracy,recall,and precision of 92.5%,90.1%and 85.7%on the validation set,respectively.Conclusion:The auto-matic detection model for TMJOA imaging developed in this study can effectively identify arthritic lesions.Artificial intelligence tools are expected to become a powerful auxiliary tool for the clinical diagnosis of TMJOA.

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