Stroke is one of the leading causes of disability and mortality worldwide. Research into its mechanisms and the development of therapeutic strategies heavily rely on animal models that accurately replicate the pathological features of human disease. An ideal animal model for stroke should not only reproduce the neurological deficits and pathological changes observed in clinical patients but also demonstrate good reproducibility and translational value. This review focuses on the preparation and evaluation methods of ischemic stroke animal models. Firstly, it elaborates on the selection criteria, advantages, and disadvantages of experimental animals, including rodents (rats, mice) and non-rodents (non-human primates, miniature pigs, rabbits, zebrafish). Secondly, it provides a detailed overview of the modeling principles, key procedures, and application scopes for ischemic stroke models and hemorrhagic stroke models. Furthermore, the review summarizes advances in the applications of emerging technologies—including gene editing [e.g., clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene editing], multimodal imaging (e.g., two-photon microscopy, photoacoustic imaging), artificial intelligence, optogenetics, 3D bioprinting, organoid models, and multi-omics–in model optimization, precise assessment, and mechanistic investigation. Finally, based on a systematic analysis of relevant domestic and international literature from 2019 to 2024, this review discusses model selection strategies based on research objectives, a multidimensional evaluation system encompassing behavioral, imaging, and molecular pathological assessments, and envisions future directions involving technological integration to achieve model precision and individualization. This article aims to provide a comprehensive methodological reference to help researchers select appropriate animal models of stroke according to specific scientific questions.

Objective To evaluate the effectiveness of thermal tomography in breast cancer (BC) screening. Methods We conducted a general population-based BC screening in three regions of Hubei Province (Xiantao, Hongan, and Yangxin Districts). Participants underwent a questionnaire-based interview for baseline data collection. They then received a physical examination, thermal tomography, and ultrasound from doctors and technicians. We compared the efficacies, including sensitivity, specificity, and false-positive rates, of ultrasound and thermal tomography in BC screening. Results A total of 59 712 eligible women were included in this screening program. The BI-RADS 1, 2, 3, 4, and 5 accordance rates between the two screening methods were 0.9549, 0.8047, 0.9037, 0.3352, and 0, respectively. The overall accordance rate was 0.933 1. The kappa consistency results showed that the Cicchetti-Allison and Fleiss-Cohen kappa values were 0.7970 and 0.8583, respectively. Although the two methods had equal sensitivities, specificity was higher in thermal tomography than in ultrasound. The false-positive rate was lower in thermal tomography than in ultrasound. The area under the receiver operating characteristic (ROC) curve of thermal tomography was significantly larger than that of ultrasound. Conclusion The general consistency between thermal tomography and ultrasound in BC screening was high. Thermal tomography outperformed ultrasound in terms of specificity and diagnostic efficiency. Therefore, thermal tomography has a high application value for general population-based BC screening.

Viral infectious diseases, characterized by their intricate nature and wide-ranging diversity, pose substantial challenges in the domain of data management. The vast volume of data generated by these diseases, spanning from the molecular mechanisms within cells to large-scale epidemiological patterns, has surpassed the capabilities of traditional analytical methods. In the era of artificial intelligence (AI) and big data, there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information. Despite the rapid accumulation of data associated with viral infections, the lack of a comprehensive framework for integrating, selecting, and analyzing these datasets has left numerous researchers uncertain about which data to select, how to access it, and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels, from the molecular details of pathogens to broad epidemiological trends. The scope extends from the micro-scale to the macro-scale, encompassing pathogens, hosts, and vectors. In addition to data summarization, this review thoroughly investigates various dataset sources. It also traces the historical evolution of data collection in the field of viral infectious diseases, highlighting the progress achieved over time. Simultaneously, it evaluates the current limitations that impede data utilization.Furthermore, we propose strategies to surmount these challenges, focusing on the development and application of advanced computational techniques, AI-driven models, and enhanced data integration practices. By providing a comprehensive synthesis of existing knowledge, this review is designed to guide future research and contribute to more informed approaches in the surveillance, prevention, and control of viral infectious diseases, particularly within the context of the expanding big-data landscape.
Big Data ; Humans ; Virus Diseases/virology* ; Artificial Intelligence

OBJECTIVES: To report the development, validation, and findings of the Multi-dimensional Attention Rating Scale (MARS), a self-report tool crafted to evaluate six-dimension attention levels. METHODS: The MARS was developed based on Classical Test Theory (CTT). Totally 202 highly educated healthy adult participants were recruited for reliability and validity tests. Reliability was measured using Cronbach's alpha and test-retest reliability. Structural validity was explored using principal component analysis. Criterion validity was analyzed by correlating MARS scores with the Toronto Hospital Alertness Test (THAT), the Attentional Control Scale (ACS), and the Attention Network Test (ANT). RESULTS: The MARS comprises 12 items spanning six distinct dimensions of attention: focused attention, sustained attention, shifting attention, selective attention, divided attention, and response inhibition.As assessed by six experts, the content validation index (CVI) was 0.95, the Cronbach's alpha for the MARS was 0.78, and the test-retest reliability was 0.81. Four factors were identified (cumulative variance contribution rate 68.79%). The total score of MARS was correlated positively with THAT (r = 0.60, P < 0.01) and ACS (r = 0.78, P < 0.01) and negatively with ANT's reaction time for alerting (r = -0.31, P = 0.049). CONCLUSIONS The MARS can reliably and validly assess six-dimension attention levels in real-world settings and is expected to be a new tool for assessing multi-dimensional attention impairments in different mental disorders.
Humans ; Adult ; Male ; Attention/physiology* ; Female ; Middle Aged ; Reproducibility of Results ; Young Adult ; Psychometrics

OBJECTIVE: The aim of this study is to analyze the clinical features and genetic etiology of a patient with multiple morphological abnormalities of the sperm flagella (MMAF) retrospectively. METHODS: A severely oligospermic patient from the Reproductive Center of the First Affiliated Hospital of Ningbo University was selected as the study subject. Clinical data and examination results were collected. High-throughput sequencing and bioinformatics were used to analyze the genetic etiology. And Sanger sequencing was employed to validate findings in the family. Transmission electron microscopy (TEM) was used to observe the sperm ultrastructure, and immunofluorescence analysis was performed to examine the localization of FSIP2 protein in the sperm. RESULTS: The patient presented with severe oligospermia, and sperm morphology displayed MMAF. TEM revealed fibrous sheath and 9+2 microtubule structural disruptions in the sperm. Sequencing identified compound heterozygous variants in the FSIP2 gene (c.17798C > T, c.5927T > G), inherited from the father and mother, respectively. According to the guidelines of the American College of Medical Genetics and Genomics, the variants were classified as pathogenic. The patient's spouse underwent intracytoplasmic single sperm injection, resulting in one embryo, but no clinical pregnancy occurred after embryo transfer. CONCLUSION This study reported the mutation of FSIP2 gene c.17798C > T, c.5927T > G in a patient with MMAF. These findings expand the mutational spectrum of the FSIP2 gene and provide insights for genetic and assisted reproductive counseling for patients with MMAF.
Humans ; Male ; Sperm Tail/pathology* ; Heterozygote ; Oligospermia/genetics* ; Spermatozoa ; Mutation ; Infertility, Male/genetics* ; Adult ; Pedigree ; Retrospective Studies ; Sperm Injections, Intracytoplasmic

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

The pharmaceutical industry faces challenges in quality digitization for complex multi-stage processes, especially in small-sample systems. Here, an intelligent quality prediction and diagnostic (IQPD) framework was developed and applied to Tong Ren Tang's Niuhuang Qingxin Pills, utilizing four years of data collected from four production units, covering the entire process from raw materials to finished products. In this framework, a novel path-enhanced double ensemble quality prediction model (PeDGAT) is proposed, which combines a graph attention network and path information to encode inter-unit long-range and sequential dependencies. Additionally, the double ensemble strategy enhances model stability in small samples. Compared to global traditional models, PeDGAT achieves state-of-the-art results, with an average improvement of 13.18% and 87.67% in prediction accuracy and stability on three indicators. Additionally, a more in-depth diagnostic model leveraging grey correlation analysis and expert knowledge reduces reliance on large samples, offering a panoramic view of attribute relationships across units and improving process transparency. Finally, the IQPD framework integrates into a Human-Cyber-Physical system, enabling faster decision-making and real-time quality adjustments for Tong Ren Tang's Niuhuang Qingxin Pills, a product with annual sales exceeding 100 million CNY. This facilitates the transition from experience-driven to data-driven manufacturing.

Objective To establish an optimized diagnostic model for hepatocellular carcinoma(HCC),designated as G-GADA,in chronic hepatitis B(CHB)patients based on the parameters of age,sex,alpha-fetoprotein(AFP),des-γ-carboxy prothrombin(DCP),and Golgi protein 73(GP73),to address the problems of low sensitivity and specificity in the early diagnosis of hepatitis B virus(HBV)-related liver cancer,and to assess the value of this model in the diagnosis of HCC.Methods A retrospective analysis was performed for 201 CHB patients(CHB group),137 patients with HBV-related liver cirrhosis(LC group),and 111 treatment-na?ve patients with newly diagnosed HCC(HCC group)who were admitted to Mengchao Hepatobiliary Hospital of Fujian Medical University from June 2015 to June 2020.Serological markers(AFP,DCP,alpha-fetoprotein L3%[AFP-L3%],and GP73)were compared between groups and were analyzed in terms of their differences from the clinical and tumor characteristics of HCC patients,and the Spearman correlation analysis was used to assess the correlation between different markers.A Logistic regression analysis was used to establish a diagnostic model for liver cancer,and the receiver operating characteristic(ROC)curve was used to assess the diagnostic performance of each marker.Results Comparison of clinical features between CHB,LC,and HCC patients showed that HCC patients had significantly higher age,proportion of male patients,and serum levels of DCP,AFP,GP73,and AFP-L3%(all P<0.05).In HCC patients,DCP levels are associated with tumor size and microvascular invasion;AFP levels are related to patient age,tumor size,tumor number,distant metastasis,and microvascular invasion;AFP-L3%levels are associated with patient age,tumor size,tumor number,distant metastasis,Milan staging,and microvascular invasion;GP73 levels are linked to tumor number,distant metastasis,and microvascular invasion(all P<0.05).The correlation analysis of the serum markers showed a strong positive correlation between AFP and AFP-L3%(r=0.71,P<0.05)and a moderate positive correlation between AFP and GP73(r=0.33,P<0.05)and between AFP-L3%and GP73(r=0.41,P<0.05).Based on the features of age,sex,DCP,AFP,and GP73,the multivariate Logistic regression analysis was used to establish a G-GADA diagnostic model for HCC,and for all patients,the G-GADA model had an area under the ROC curve(AUC)of 0.915(95%confidence interval[CI]:0.875-0.945)in the derivation cohort and 0.913(95%CI:0.862-0.950)in the validation cohort for the diagnosis of HCC.In the AFP-negative patients,the G-GADA model achieved an AUC of 0.884(95%CI:0.833-0.924)in the derivation cohort and 0.851(95%CI:0.779-0.907)in the validation cohort,and in the patients with liver cirrhosis,the G-GADA model achieved an AUC of 0.901(95%CI:0.841-0.944)in the derivation cohort and 0.885(95%CI:0.806-0.940)in the validation cohort.Conclusion The G-GADA diagnostic model based on multiple variables significantly improves the detection rate of HCC,and demonstrates superior diagnostic performance in patients with low AFP expression and those with liver cirrhosis.The G-GADA model has a better clinical application value in the noninvasive diagnosis of HCC.

The nursing experience of buttonhole cannulation for an autogenous arteriovenous fistula with an Eluvia drug-eluting stent in a patient undergoing maintenance hemodialysis was summarized.Key nursing points included:developing a scientific and rational buttonhole cannulation plan for the autogenous arteriovenous fistula stent based on its characteristics post-stent implantation;conducting preoperative ultrasonic evaluations of the arteriovenous fistula and stent;establishing and maintaining a buttonhole tunnel at the stent site;regularly monitoring and following up on the cannulation site and the condition of the autogenous arteriovenous fistula;strengthening the observation and prevention of potential complications.Through rigorous and standardized assessments,procedures,and nursing care,the patient maintained good autogenous arteriovenous fistula function without stent-related complications such as fracture,stenosis,or infection over a 14-month follow-up period.

Objective To compare the differences of baseline characteristics of patients with myelodysplastic syndrome(MDS)who achieved platelet(PLT)response after arsenic-containing TCM compounds combined with Western medicine treatment.Methods Totally 72 MDS patients were selected from 12 outpatient departments and wards,such as Xiyuan Hospital,China Academy of Chinese Medical Sciences,Dongfang Hospital,Beijing University of Chinese Medicine from October 2021 to October 2024.Among them,45 patients received arsenic-containing TCM compounds combined with Western medicine treatment,27 patients received Western medicine treatment.The blood routine[white blood cell(WBC)count,hemoglobin,PLT,neutrophil count],TCM syndrome scores,safety indicators,and adverse events were observed before and after three courses of treatment.The efficacy of all patients was evaluated,and the baseline characteristics of patients who achieved PLT response in the arsenic-containing TCM compounds group and the Western medicine treatment group were compared.Results Comparing the differences of baseline characteristics of the two groups,it was found that the patients who achieved PLT response in the arsenic-containing TCM compounds group were compared with those in the Western medicine treatment group:Age<60 years old(P=0.038),longer disease duration(P=0.012),lower WBC(P=0.017),lower reticulocyte percentage(P=0.037),lower blood urea nitrogen(P=0.046),lower high-density lipoprotein cholesterol(P=0.014),and lower N-terminal pro-B-type natriuretic peptide(P=0.034),abnormal electrocardiogram(P=0.013),high blasts(P=0.009),grade 0 reticular fiber staining(P<0.01),normal chromosome karyotype(P<0.01),gene mutation(P<0.01)and high TCM syndrome scores(P=0.013)were found.Conclusion Arsenic-containing TCM compounds consisting of Qinghuang Powder and Bushen Jianpi Decoction combined with Western medicine is used to treat MDS.Patients with age<60 years old,long disease duration,low WBC count,low reticulocyte percentage,low blood urea nitrogen,low high-density lipoprotein cholesterol,low N-terminal pro-B-type natriuretic peptide,abnormal electrocardiogram,high blasts,grade 0 reticular fiber staining,normal chromosome karyotype,gene mutation and high TCM syndrome score are more likely to obtain PLT response.