To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

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: CRISPR-Cas protects bacteria from exogenous DNA invasion and is associated with bacterial biofilm formation and pathogenicity. METHODS: We analyzed the type I-F CRISPR-Cas system of Legionella pneumophila WX48, including Cas1, Cas2-Cas3, Csy1, Csy2, Csy3, and Cas6f, along with downstream CRISPR arrays. We explored the effects of the CRISPR-Cas system on the in vitro growth, biofilm-forming ability, and pathogenicity of L. pneumophila through constructing gene deletion mutants. RESULTS: The type I-F CRISPR-Cas system did not affect the in vitro growth of wild-type or mutant strains. The biofilm formation and intracellular proliferation of the mutant strains were weaker than those of the wild type owing to the regulation of type IV pili and Dot/Icm type IV secretion systems. In particular, Cas6f deletion strongly inhibited these processes. CONCLUSION The type I-F CRISPR-Cas system may reduce biofilm formation and intracellular proliferation in L. pneumophila.
Legionella pneumophila/pathogenicity* ; CRISPR-Cas Systems ; Biofilms/growth & development* ; Phenotype ; Bacterial Proteins/metabolism* ; Gene Deletion

Objective:To construct the sphingosine kinase 1(SPHK1)overexpression lentiviral vector,and to establish the SKOV3 lentiviral stable transfection cell line.Methods:According to the SPHK1 data information provided by the National Center for Biotechnology Information(NCBI)database,the primers were designed and synthesized,the target gene was amplified,and connected to the GV492 plasmid treated with Bam HⅠ and AgeⅠ restriction enzymes to construct the SPHK1 overexpression lentiviral vector;the positive clones were selected for PCR and sequencing identification;the lentiviral plasmid and the lentiviral packaging auxiliary plasmid were co-transfected into the HEK-293T cells for packaging and titer determination;according to the measured optimal multiplicity of infection(MOI)of 10,the corresponding lentiviral amounts in various groups were transfected into the SKOV3 cells,and the SKOV3 cells were divided into blank group(without treatment),GV492 control group(GV492 control lentivirus infected SKOV3 cells),and GV492-SPHK1 overexpression group(GV492-SPHK1 overexpression lentivirus infected SKOV3 cells,ov-SPHK1 group);the optimal concentration of 2 mg·L-1 puromycin was used to screen the stably transfected SKOV3 cell line;after 48 h,the medium was changed and replaced with 1 mg·L-1 puromycin for screening for 14 d;the morphology and fluorescence expression of the cells were observed under fluorescence microscope;real-time fluorescence quantitative PCR(RT-qPCR)method was used to detect the expression levels of SPHK1 mRNA in the SKOV3 cells in various groups;Western blotting method was used to detect the expression level of SPHK1 protein in the SKOV3 cells in various groups.Results:The PCR sequencing results showed that the gene sequence of the SPHK1 overexpression lentiviral vector was completely consistent with the target sequence,and the SPHK1 overexpression lentiviral vector was successfully constructed;the titer determination results showed that the lentiviral titers in GV492 control group and ov-SPHK1 group were 5×1011 and 8×1011 TU·L?1,respectively;the SKOV3 cells in GV492 control group and ov-SPHK1 group were in good state and showed strong fluorescence expression,suggesting that the SKOV3 stable transfection cell line overexpressing SPHK1 was successfully established;the RT-qPCR results showed that compared with blank group and GV492 control group,the expression level of SPHK1 mRNA in the SKOV3 cells in ov-SPHK1 group was significantly increased(P<0.01);the Western blotting results showed that compared with blank group and GV492 control group,the expression level of SPHK1 protein in the SKOV3 cells in ov-SPHK1 group was significantly increased(P<0.01).Conclusion:The SPHK1 overexpression lentiviral vector is successfully constructed,and the SKOV3 stable transfection cell line is established.

Objective To explore the efficacy and safety of pegylated doxorubicin liposome(PLD)in neoadjuvant chemotherapy(NAC)for breast cancer.Methods A total of 126 breast cancer patients treated with the NAC regimen containing PLD in the Third Xiangya Hospital of Central South University from Janu-ary 2018 to December 2022 were selected as the research subjects.The clinical efficacy,pathological efficacy and occurrence of adverse reactions of the patients were observed,and total pathological complete response(tpCR)rates of different molecular subtypes were analyzed.The changes in left ventricular ejection fraction(LVEF)were compared between before and after treatment.Results Among 126 patients,the clinical efficacy of NAC in 119 cases was evaluated,and the objective response rate(ORR)was 67.2％(80/119).A total of 123 patients were evaluated for the pathological efficacy,breast cancer pathological complete response(bpCR)rate was 13.8％(17/123);tpCR rate was 12.2％(15/123),in which the the human epidermal growth factor receptor 2(HER2)positive[hormone receptor(HR)negative]type had the highest rate(33.3％),followed by triple-negative(21.7％).There was no hand-foot syndrome occurred,and only one case developed the grade 2 oral mucositis.LVEF showed no statistically significant difference between before and after treatment[69.9％(51.0％,87.0％)vs.69.0％(57.0％,85.0％)](P＞0.05).Conclusion The NAC regimen containing PLD has a better effect on HER2—positive and triple-negative breast cancer.

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*

Transcranial temporal interference stimulation (tTIS) is a novel non-invasive neuromodulation technique with the potential to precisely target deep brain structures. This study explores the neural and behavioral effects of tTIS on the superior colliculus (SC), a region involved in eye movement control, in mice. Computational modeling revealed that tTIS delivers more focused stimulation to the SC than traditional transcranial alternating current stimulation. In vivo experiments, including Ca²⁺ signal recordings and eye movement tracking, showed that tTIS effectively modulates SC neural activity and induces eye movements. A significant correlation was found between stimulation frequency and saccade frequency, suggesting direct tTIS-induced modulation of SC activity. These results demonstrate the precision of tTIS in targeting deep brain regions and regulating eye movements, highlighting its potential for neuroscientific research and therapeutic applications.
Animals ; Superior Colliculi/physiology* ; Transcranial Direct Current Stimulation/methods* ; Eye Movements/physiology* ; Male ; Mice ; Mice, Inbred C57BL

Objective:To carry out carrier screening among people of childbearing age, detect the pathogenic genes of monogenic genetic diseases and analyze the carrier status of pathogenic variants, so as to provide fertility guidance and intervention measures for high-risk families.Methods:From August 2022 to August 2023, 1 533 families of childbearing age who met the criteria were recruited in the Chinese PLA General Hospital, including a total of 3 044 subjects. According to the standard enrollment procedure, 223 genes (197 autosomal recessive genes and 26 X-linked genes) of the subjects were tested. According to the screening results, genetic counseling and fertility guidance were provided to the subjects. Invasive prenatal diagnosis was performed for high-risk couples (both couples being carriers of the same autosomal recessive disease gene or the woman was a carrier of X-linked disease gene), and their pregnancy pattern, outcome and offspring phenotype were followed up.Results:(1) A total of 3 044 cases from 1 511 couples and women of childbearing age from 22 families were included for carrier screening. Totally 1 503 families chose simultaneous screening and 30 families chose sequential screening out of the 1 533 families. Among the 3 044 subjects, 1 603 individuals carried at least one pathogenic or likely pathogenic variant, and the overall carrier rate was 52.66% (1 603/3 044). A total of 2 292 pathogenic or likely pathogenic variants were detected, and 0.75 variants (2 292/3 044) were detected per capita. (2) The three genes with the highest carrier rates were GJB2 (8.67%, 264/3 044), CYP21A2 (3.19%, 97/3 044) and PAH (3.09%, 94/3 044). There were 32 genes with a carrier rate ≥1/200, 17 genes with a carrier rate ≥1/100, and 7 genes with a carrier rate ≥1/50. (3) Thirty-eight high-risk families were identified. After excluding G6PD gene mutation, there were 33 high-risk families, of which 25 couples were carriers of the same autosomal recessive gene, 9 women were carriers of X-linked gene, and 1 family was double high-risk couple with both autosomal recessive and X-linked gene. After further excluding the GJB2 c.109G>A mutation, 21 high-risk families were identified. Preimplantation genetic testing for monogenic disease was performed in 12 families after genetic counseling. Prenatal diagnosis was completed in 4 out of 5 high-risk families who conceived naturally. Two fetuses carried the parental variants and terminated the pregnancy, one fetus did not carry the parental variants but was induced due to trisomy 21 syndrome, and one fetus was a carrier of congenital disorders of glycosylation type 1a.Conclusions:Carrier screening effectively identifies high-risk genetic disease families and provides reproductive guidance to prevent the birth of affected children. However, establishing multidisciplinary team is essential for managing complex cases. Implementation should prioritize prenatal institutions with genetic counseling or diagnostic expertise for monogenic disorders or established referral networks.

Objective:To investigate the correlation between carotid-femoral pulse wave velocity(cfPWV)and carotid artery structural,hemodynamic,and cardiac functional parameters.Methods:A total of 420 healthy volunteers who underwent neck ultrasound,cardiac ultrasound,and cfPWV examination at Kailuan General Hospital from June 2022 to February 2023 were selected,and they were divided into two groups based on the atherosclerosis threshold value of cfPWV>10 m/s,which included high cfPWV group(140 cases,cfPWV>10 m/s)and low cfPWV group(280 cases,cfPWV≤10 m/s).The demographic data(age,sex)of 420 persons were collected,and the common carotid artery diameter(CCAD),common carotid artery intima-media thickness(CIMT),plaque status,peak systolic velocity(PSV),end-diastolic velocity(EDV)and mean flow velocity(MFV)were compared between two groups.Then,the differences of interventricular septal thickness(IVST)of heart,left ventricular posterior wall thickness(LVPWT),the ratio of blood flow velocity at early stage to that at advanced stage in mitral valve(E/A)and stroke volume(SV)were analyzed.Multivariate logistic regression was adopted to analyze the independent influence factors of cfPWV enhancement.Results:The average age of high cfPWV group was(61.31±9.66)years old,which was significantly higher than(51.06±10.47)years old of low cfPWV group,and the difference of that was significant(t=-9.56,P<0.01).In the parameters of common carotid artery,63 persons(45.0%)occurred plaque in 140 persons of high cfPWV group,which was significantly lower than 50 persons(17.86%)in 280 persons of low cfPWV group,and the difference of that between two groups was significant(x2=34.97,P<0.05).The differences of CCAD,CIMT,PSV,EDV and MV of common carotid artery at right side of persons between two groups were significant(t=-2.16,-5.40,4.52,5.59,5.04,P<0.05),respectively.The parameters of heart showed that the LVPWT thickness increased(9.35±1.13)mm,and the ratio of E/A<1 increased 77.86%in high cfPWV group,which were significantly related to the increase of cfPWV(r=0.27,0.38,P<0.01).Multivariate logistic regression analysis indicated that age(OR=1.05,95%CI:1.02-1.08),CCAD(OR=1.63,95%CI:1.22-2.16),plaque presence(OR=1.84,95%CI:1.07-3.17),LVPWT(OR=1.35,95%CI:1.05-1.72),and the ratio of E/A<1(OR=2.37,95%CI:1.32-4.26)were independent predictors of cfPWV enhancement.Conclusion:The enhancement of cfPWV is closely related to high age,the reconstruction of common carotid artery(widening of inside diameter,and plaque formation),left ventricular hypertrophy,and diastolic abnormality,which indicates it is possible that atherosclerosis process accompanies by the change of interaction mechanism of blood vessels-heart.

Objective To observe the value of machine learning model based on MR T2WI and diffusion weighted imaging(DWI)radiomics for predicting perineural invasion(PNI)of rectal cancer.Methods Totally 343 patients with rectal cancer were retrospectively collected and divided into training set(n=275,92 PNI[+]and 183 PNI[-])and test set(n=68,23 PNI[+]and 45 PNI[-])at the ratio of 8∶2.Univariate and multivariate logistic regression(LR)were used to analyze clinical data and screen the independent predictors of PNI in rectal cancer,so as to construct a clinical model.The best radiomics features were extracted and screened based on preoperative T2WI and DWI.Then extremely randomized trees,multilayer perceptron,light gradient boosting machine,extreme gradient boosting,support vector machine(SVM),LR,K-nearest neighbor and random forest algorithms were used to construct ML models,respectively,and the optimal ML model was selected to establish a clinical-radiomics ML model combined with clinical relevant independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Patients' age was the independent predictor of PNI of rectal cancer(OR=0.988,P＜0.001),and the area under the curve(AUC)of the clinical model constructed based on it was 0.435 and 0.458 in training and test sets,respectively.SVM model was the best one among 8 ML models,with AUC in training and test set of 0.887 and 0.854,respectively.The AUC of clinical-radiomics ML model in training and test sets was 0.887 and 0.860,respectively,not different with AUC of SVM model(both P＞0.05).Decision curve analysis showed that when the threshold value was 0.20-0.45,clinical net benefit of SVM model was higher than that of other models.Conclusion SVM model based on T2WI and DWI radiomics could effectively predict PNI of rectal cancer.