Objective: To analyze the epidemiological characteristics of category C intestinal infectious diseases among children and adolescents in Shenzhen from 2012 to 2024 and the association with meteorological factors, so as to provide a scientific basis for the targeted prevention and control of infectious diseases for children and adolescents. Methods: Using data from the "Infectious Disease Reporting Information Management System" of the "China Disease Prevention and Control Information System" covering the period from January 1, 2012 to December 31, 2024, the study analyzed clinical and confirmed cases of hand, foot, and mouth disease, other infectious diarrhea, and acute hemorrhagic conjunctivitis among individuals aged 6-19 years old to describe demographic and temporal characteristics. It used Joinpoint regression to calculate the average annual percent change (AAPC) and annual percent change (APC) to analyze incidence trends, and Spearman s correlation was combined to generalize linear models so as to assess the association between category C intestinal infectious diseases and meteorological factors. Results: From 2012 to 2024, a cumulative total of 61 019 cases of hand, foot, and mouth disease among children and adolescents, 58 498 cases of other infectious diarrhea, and 6 377 cases of acute hemorrhagic conjunctivitis were reported. The AAPC in the incidence rates of these three diseases was 19.19%, 31.03% and 31.48 %, respectively(all P <0.05). Notably, the incidence of hand, foot, and mouth disease increased significantly after 2022 (APC= 133.66 %, P <0.01). The temporal distribution showed that hand,foot,and mouth disease was most prevalent in May,June and July (seasonal index of 2.39,3.64,1.97), other infectious diarrhea was most prevalent in February,March and December (seasonal index of 1.22,1.25,1.47), and acute hemorrhagic conjunctivitis peaked in September and October (seasonal index of 4.22,2.16). Monthly average temperature could increase the risk of hand,foot,and mouth disease( β = 0.18 ,95% CI =0.11-0.25); as monthly average wind speed increased, the incidence of other infectious diarrhea ( β =-0.86, 95% CI = -1.50 to -0.22) and acute hemorrhagic conjunctivitis ( β =-1.32, 95% CI =-2.60 to -0.05) both decreased (all P < 0.05 ). Conclusions Among children and adolescents in Shenzhen, category C intestinal infectious diseases remain prevalent throughout the year；the number of reported hand, foot, and mouth disease cases has shown an upward trend in recent years.Temperature and wind speed significantly affect the number of reported cases of three types with category C intestinal infectious diseases.

ObjectiveTo investigate the effects of modified Xiaoyaosan （JJXYS） on behavioral abnormalities and hippocampal mitochondrial quality control （MQC） in the rat model of post-myocardial infarction depression （PMD） and preliminarily explore its potential mechanism. MethodsA rat model of PMD was established by left anterior descending coronary artery ligation combined with chronic unpredictable mild stress （CUMS）. Rats were randomized into a control group， a model group， a fluoxetine （FLX， 10 mg·kg^-1） group， and low-， medium-， and high-dose JJXYS （JJXYS-L/M/H， 1.12， 2.24， 4.48 g·kg^-1， respectively） groups. Depressive-like behaviors were evaluated by body weight monitoring， sucrose preference test， open field test， and forced swimming test. Hematoxylin-eosin staining and Nissl staining were used to observe hippocampal histomorphology and neuronal changes. Enzyme-linked immunosorbent assay was conducted to determine the serum levels of 5-hydroxytryptamine （5-HT）， dopamine （DA）， interleukin-1 beta （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-alpha （TNF-α）. The mRNA levels of MQC-related genes including peroxisome proliferator-activated receptor-gamma coactivator-1 alpha （PGC-1α）， nuclear respiratory factor 1 （Nrf1）， and transcription factor A， mitochondrial （TFAM） in the hippocampal tissue were measured by real-time PCR. The expression of proteins related to the dynamin-related protein 1 （Drp1）/PTEN-induced putative kinase 1 （PINK1）/Parkin signaling pathway was determined by Western blot. ResultsCompared with the control group， the model group showed restricted body weight gain， aggravated depressive-like behaviors， declined serum 5-HT and DA levels， evident hippocampal neuronal damage and reduced Nissl bodies， as well as downregulated expression of MQC-related genes and proteins （P<0.05）. Compared with the model group， both FLX and JJXYS alleviated the above changes to varying degrees. Moreover， the JJXYS-M and JJXYS-H groups showed more pronounced effects， improving behavioral performance， restoring 5-HT and DA levels， alleviating hippocampal pathological injury， and upregulating the expression of PGC-1α/Nrf1/TFAM mRNA and Drp1/PINK1/Parkin signaling pathway-related proteins （P<0.05）. ConclusionJJXYS can significantly alleviate depressive-like behaviors and neurotransmitter imbalance in the rat model of PMD by regulating hippocampal MQC and upregulating the Drp1/PINK1/Parkin-related pathway. This study provides experimental evidence for the intervention of PMD with JJXYS.

ObjectiveStroke poses a heavy burden due to its high mortality and morbidity rates. Accurate and real-time detection of lesions is pivotal for prompt clinical intervention and favorable prognosis. Electrical impedance tomography (EIT) and microwave tomography (MWT) have emerged as compelling alternatives for stroke screening, owing to their non-ionizing, non-invasive and portable nature. EIT provides information on tissue conductivity, and MWT offers high sensitivity to changes in dielectric properties. However, single-modality imaging is inherently limited, EIT suffers from low sensitivity to deep-seated tissues and severe ill-posedness of inverse problems, whereas MWT is challenged by strong nonlinearity in inverse scattering and susceptibility to modeling errors. Consequently, the clinical utility of standalone EIT or MWT for stroke diagnosis remains constrained by poor spatial resolution and imaging artifacts. To improve the accuracy and robustness of stroke imaging, a dual-modality fusion conditional denoising diffusion probabilistic model (DM-DDPM) was proposed for high-precision dual-modality image reconstruction. MethodsA dual-encoder network with a symmetric architecture and independently trained parameters was constructed to extract heterogeneous features separately from EIT boundary voltage measurements and MWT scattered field signals. Attentional feature fusion (AFF) is employed to integrate complementary information from the two modalities adaptively, generating robust fused priors that suppress redundant noise while preserving key physical characteristics. Subsequently, the fused priors are embedded into a Transformer-based diffusion model via a cross attention mechanism to guide the reverse denoising process. This approach effectively reduces artifacts and enhances the stability of conductivity distribution reconstruction. Time step embedding is introduced to enable the network to perceive the diffusion stage and further improve the accuracy of noise prediction. ResultsSimulated experiments demonstrated that DM-DDPM significantly outperforms single-modality and multi-modality networks under various noise levels. A head model simulation dataset was constructed based on COMSOL Multiphysics, and tests were carried out under 50 dB, 40 dB and 30 dB signal-to-noise ratio levels. At 30 dB, the average relative error (RE) was below 0.20, while the structural similarity index measure (SSIM) and correlation coefficient (CC) remained above 0.90 and 0.89, respectively. Compared with single-modality and multi-modality networks, artifacts were significantly reduced, lesion edges were clearer, and localization was more accurate. The model maintains high reconstruction quality and strong robustness for single, double, and triple lesions simultaneously. Furthermore, physical experiments were conducted using a 16-electrode EIT system and a 16-antenna MWT system with asynchronous data acquisition. These experiments confirmed the feasibility of the method in real-world scenarios and demonstrated that it can robustly reconstruct simulated lesions despite environmental interference and measurement noise, validating its reliability for practical clinical applications. ConclusionThe proposed method effectively combines complementary dual-modality information with a conditional diffusion model. Low accuracy and poor noise resistance in single-modality imaging were effectively addressed, while the noise amplification issue caused by direct multimodal data fusion was avoided. The proposed algorithm exhibits strong anti-noise interference ability and high imaging stability in both simulation and physical experiments. Precise localization of stroke lesions with different quantities was achieved, providing a high-precision, and practical technical support for clinical stroke detection.

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 effect of liquid-liquid phase separation(LLPS)of YTH domain family protein 2(YTHDF2)on the sodium arsenite-induced malignant transformation of skin cells,providing a new intervention target for the prevention and control of sodium arsenite-induced carcinogenesis.Methods The HaCaT cell model of malignant transformation was constructed by continuous treatment with 1 μmol/L sodium arsenite for 22 weeks,including cells with normal YTHDF2 LLPS(YTHDF2-wt)and cells with inhibited YTHDF2 LLPS(YTHDF2-mut).Confocal microscopy was employed to observe and characterize the LLPS droplets formed by YTHDF2 during sodium arsenite-induced malignant transformation of skin cells.Cell proliferation,scratch healing,and colony formation assays were performed to detect malignant phenotypes.Western blotting,quantitative reverse transcription PCR,and immunofluorescence experiments were conducted to examine the effects of YTHDF2 LLPS on the mRNA and protein levels of phosphatase and tensin homolog deleted on chromosome ten(PTEN)during sodium arsenite-induced malignant transformation of skin cells.Results After 4 weeks of sodium arsenite treatment,LLPS droplets of YTHDF2 appeared in YTHDF2-wt cells,and the number of droplets gradually increased as the treatment time was prolonged(F=35.252,P<0.001),while no phase-separated droplets were observed in YTHDF2-mut cells.Compared with YTHDF2-mut cells,YTHDF2-wt cells showed enhanced proliferation at the time points of 48 h(t=3.654,P=0.006)and 72 h(t=5.458,P<0.001)after 22 weeks of sodium arsenite treatment.The scratch healing rate of YTHDF2-wt cells was increased at the 8th(t=12.137,P<0.001)and 22th(t=4.484,P=0.011)weeks of sodium arsenite treatment.The number of colonies formed by YTHDF2-wt cells was higher at the 4th(t=3.365,P=0.027),8th(t=5.580,P=0.005),and 22th(t=3.328,P=0.029)weeks of sodium arsenite treatment.Compared with YTHDF2-mut cells,YTHDF2-wt cells showed down-regulated protein(t=-3.119,P=0.036)and mRNA(t=4.051,P=0.015) levels of PTEN after 22 weeks of sodium arsenite treatment.Immunofluorescence results showed that after 4 weeks of sodium arsenite treatment,YTHDF2 LLPS droplets in YTHDF2-wt cells were localized to stress granules,translation-related membrane-less organelles.Conclusions During sodium arsenite-induced malignant transformation of skin cells,YTHDF2 undergoes LLPS and localizes to stress granules,translation-related membrane-less organelles.YTHDF2 LLPS participates in sodium arsenite-induced malignant transformation of skin cells by down-regulating the mRNA level of the key tumor suppressor PTEN.
Arsenites/toxicity* ; Sodium Compounds/toxicity* ; Humans ; Cell Transformation, Neoplastic/drug effects* ; PTEN Phosphohydrolase/metabolism* ; Cell Proliferation ; Skin/cytology* ; RNA-Binding Proteins ; Skin Neoplasms/chemically induced* ; Cell Line

Medical therapy and surgical intervention are the two primary approaches for treating myocardial bridge.However,there remains controversy regarding the use of coronary artery bypass grafting(CABG)and myocardial bridge unroofing.Here,we report a case of myocardial infarction following CABG in a patient with a myocardial bridge.The patient was admitted to Lanzhou First Peopie's Hospital with persistent chest pain,chest tightness,and shortness of breath lasting 2 hours.Physical examination revealed no significant abnormalities.Electrocardiography(ECG)indicated extensive anterior wall myocardial infarction.Laboratory findings showed myoglobin levels of 140.1 ng/ml and troponin Ⅰ levels of 2.59 ng/ml,with no other significant abnormalities.The initial diagnosis was acute extensive anterior wall myocardial infarction.Emergency coronary angiography revealed a myocardial bridge in the mid-segment of the left anterior descending artery(LAD).Emergency CABG using the left internal mammary artery to the LAD was performed,leading to symptomatic improvement,and the patient was discharged in stable condition.However,the patient experienced a recurrent myocardial infarction seven years post-surgery and received secondary preventive medical therapy.The patient is currently under ongoing follow-up care.CABG is an effective treatment for myocardial bridge.However,based on the case reported in this study,we recommend careful evaluation of whether a patient may benefit from CABG.

In the mid-20th century,internal mammary artery(IMA)ligation attracted attention for improving myocardial ischemia survival and relieving angina symptoms in animals,but was eliminated after sham-operation trials confirmed that its efficacy stemmed from a placebo effect.Recent advances in interventional techniques have led to the revival of distal IMA blockade,which has been shown to improve myocardial perfusion by modulating collateral circulation.Randomized controlled trials further showed that angina relief was significantly better in the blockade group than in the sham-operated group,especially in right coronary artery(RCA)and left anterior descending(LAD)lesions,but not in the ileocecal branch due to the lack of IMA collateral connections.Anatomy suggests that the internal mammary artery forms a natural collateral pathway to the RCA/LAD via the pericardial phrenic artery,which is the anatomic basis for its efficacy.Current technical limitations include incomplete occlusion,device-related complications,and insufficient evidence of long-term prognosis.Future studies are needed to optimize the design of occlusion devices,explore combined therapeutic strategies,and conduct controlled studies with conventional revascularization techniques.In this review,we systematically review the 100-year evolution of IMA occlusion,the paradigm shift from surgical ligation to precision intervention,analyze its anatomical and hemodynamic mechanisms,integrate evidence-based evidence and propose screening criteria for indications,and provide a new pathway for individualized treatment of high-risk patients who cannot tolerate coronary artery bypass grafting/percutaneous coronary intervention.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To analyze the risk factors of ultrasound-guided percutaneous transluminal angioplasty(PTA)for treating thrombotic occlusion of autogenous arteriovenous fistula(AVF).Methods A total of 144 patients with thrombotic occlusion of autologous AVF were retrospectively enrolled and divided into success group(n=114)and failure group(n=30)according to the success of treatment or not.Clinical data and ultrasonic parameters of AVF were compared between groups.A multivariate logistic regression model was constructed to analyze the risk factors of PTA for treating thrombotic occlusion of autologous AVF,and the results were visualized by nomogram.Then receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated to evaluate the predictive efficacy of this model.Results Patients'age,use years of AVF,degree of vascular calcification,the mean Young modulus(Emean),the maximum Young modulus(Emax)and the minimum Young modulus(Emin)were all higher,while the number of venous outflow tracts of AVF was less in failure group than those in success group(all P＜0.05).Moderate to severe calcification of vascular,high Emean of thrombus and 1 venous outflow tract of in AVF were all independent risk factors of ultrasound-guided PTA for treating thrombotic occlusion of autologous AVF(all P＜0.05),and AUC of the obtained model for predicting failure of treatment was 0.969.Conclusion Moderate to severe calcification of vascular,high Emean of thrombus and 1 venous outflow tract of AVF were all independent risk factors of ultrasound-guided PTA for treating thrombotic occlusion of autologous AVF.

[Objective]To investigate the effects of targeted inhibition of growth differentiation factor 3(GDF3)on choroidal neovascularization(CNV)and endothelial inflammatory response.[Methods]A laser-induced CNV mouse model was established,and differentially expressed genes were screened by RNA sequencing(RNA-seq).GDF3 expression was validated by real-time fluorescence quantitative PCR(RT-qPCR)and Western blot.GDF3 in endothelial cells was antagonized by siRNA and neutralizing antibodies.Functional assays including CCK8 assay,scratch assay,and tube formation assay were performed to assess endothelial cell proliferation,migration,and angiogenic capacity.The expression changes of inflammatory/adhesion molecules were measured,and immune cell adhesion and transendothelial migration were analyzed.In the CNV model,shRNA was intravitreally injected to suppress GDF3 expression,with CNV lesions and immune cell infiltration quantified by immunofluorescence staining.[Results]GDF3 expression was significantly upregulated in CNV tissues(P＜0.001).In vitro GDF3 intervention markedly suppressed endothelial cell proliferation(P＜0.001),migration(P＜0.001),and angiogenesis(P＜0.01),downregulated the expression of inflammatory/adhesion molecules(P＜0.001),and significantly reduced immune cell adhesion(P＜0.001)and transendothelial migration(P＜0.001).In vivo experiments confirmed that targeted inhibition of GDF3 significantly attenuated CNV formation(P＜0.001)and decreased immune cell infiltration(P＜0.001).[Conclusion]Targeted inhibition of GDF3 concurrently attenuates endothelial inflammatory response and pathological angiogenesis,potentially through modulating the inflammatory microenvironment.These findings provide novel insights for the treatment of wet age-related macular degeneration(wAMD).