ObjectiveUlcerative colitis is a prevalent immunoinflammatory disease. Th17/Treg cell imbalance and gut microbiota dysregulation are key factors in ulcerative colitis pathogenesis. The actin cytoskeleton contributes to regulating the proliferation, differentiation, and migration of Th17 and Treg cells. Wdr63, a gene containing the WD repeat domain, participates in the structure and functional modulation of actin cytoskeleton. Recent research indicates that WDR63 may serve as a regulator of cell migration and metastasis via actin polymerization inhibition. This article aims to explore the effect of Wdr63 deletion on Th17/Treg cells and ulcerative colitis. MethodsWe constructed Wdr63^-/- mice, induced colitis in mice using dextran sulfate sodium salt, collected colon tissue for histopathological staining, collected mesenteric lymph nodes for flow cytometry analysis, and collected healthy mouse feces for microbial diversity detection. ResultsCompared with wild-type colitis mice, Wdr63^-/- colitis mice had a more pronounced shortening of colonic tissue, higher scores on disease activity index and histological damage index, Treg cells decreased and Th17 cells increased in colonic tissue and mesenteric lymph nodes, a lower level of anti-inflammatory cytokine IL-10, and a higher level of pro-inflammatory cytokine IL-17A. In addition, WDR63 has shown positive effects on maintaining intestinal microbiota homeostasis. It maintains the balance of Bacteroidota and Firmicutes, promoting the formation of beneficial intestinal bacteria linked to immune inflammation. ConclusionWdr63 deletion aggravates ulcerative colitis in mice, WDR63 inhibits colonic inflammation likely by regulating Th17/Treg balance and maintains intestinal microbiota homeostasis.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

BACKGROUND: Our understanding of the correlation between postdischarge cancer and mortality in patients with coronary artery disease (CAD) remains incomplete. The aim of this study was to investigate the relationships between postdischarge cancers and all-cause mortality and cardiovascular mortality in CAD patients. METHODS: In this retrospective cohort study, 25% of CAD patients without prior cancer history who underwent coronary artery angiography between January 1, 2011 and December 31, 2015, were randomly enrolled using SPSS 26.0. Patients were monitored for the incidence of postdischarge cancer, which was defined as cancer diagnosed after the index hospitalization, survival status and cause of death. Cox regression analysis was used to explore the association between postdischarge cancer and all-cause mortality and cardiovascular mortality in CAD patients. RESULTS: A total of 4085 patients were included in the final analysis. During a median follow-up period of 8 years, 174 patients (4.3%) developed postdischarge cancer, and 343 patients (8.4%) died. A total of 173 patients died from cardiovascular diseases. Postdischarge cancer was associated with increased all-cause mortality risk (HR = 2.653, 95% CI: 1.727-4.076, P < 0.001) and cardiovascular mortality risk (HR = 2.756, 95% CI: 1.470-5.167, P = 0.002). Postdischarge lung cancer (HR = 5.497, 95% CI: 2.922-10.343, P < 0.001) and gastrointestinal cancer (HR = 1.984, 95% CI: 1.049-3.750, P = 0.035) were associated with all-cause mortality in CAD patients. Postdischarge lung cancer was significantly associated with cardiovascular death in CAD patients (HR = 4.979, 95% CI: 2.114-11.728, P < 0.001), and cardiovascular death was not significantly correlated with gastrointestinal cancer or other types of cancer. CONCLUSIONS Postdischarge cancer was associated with all-cause mortality and cardiovascular mortality in CAD patients. Compared with other cancers, postdischarge lung cancer had a more significant effect on all-cause mortality and cardiovascular mortality in CAD patients.

Objective To explore the mechanism by which cancer-associated fibroblasts(CAFs)regulate CD13-high expression neutrophil-like myeloid-derived suppressor cell(CD13hi-nMDSC)migration in pancreatic ductal adenocarcinoma(PDAC),so as to provide potential molecular targets and experimental evidences for immunotherapy in patients.Methods CAFs were isolated and purified from pancreatic cancer tissues of 5 PDAC patients.The phenotype and purity of CAFs were identified by immunofluorescence and flow cytometry.The expression of related factors in CAF was detected by quantitative polymerase chain reaction(qPCR)and enzyme-linked immunosorbent assay(ELISA).CAF conditioned medium and myeloid-derived suppressor cell(MDSC)migration system were constructed by Transwell to observe the migration of MDSCs and to study the specific mechanisms by which the aforementioned cytokines participate in regulating the migration of MDSCs.Results The isolated primary CAFs expressed activation biomarkers fibroblast activation protein(FAP)and α-smooth muscle actin(α-SMA),while the human foreskin fibroblasts(HFFs)of control cells did not express FAP and α-SMA.qPCR results showed that the mRNA expression levels of interleukin 6(IL-6),monocyte chemotactic protein 1(MCP-1),and stromal cell-derived factor 1(SDF-1)in CAFs were higher than those in HFFs(all P＜0.01).The contents of IL-6,MCP-1,and SDF-1 in the CAF culture supernatant were significantly higher than those in the HFF culture supernatant(all P＜0.01),and the secretion content increased with the prolongation of culture time.Compared with HFF conditioned medium and regular medium(RPMI 1640),CAF conditioned medium could recruit more total MDSCs and CD13hi-nMDSCs(all P＜0.01).The addition of SDF-1 recombinant protein alone in the culture system could induce the migration of total MDSCs and CD13hi-nMDSCs,and the addition of SDF-1 neutralizing antibodies or C-X-C motif chemokine receptor 4(CXCR4)blocking antibodies could significantly reduce the migration of CD13hi-nMDSCs induced by CAF conditioned medium(all P＜0.01).Although MCP-1 alone could also induce the migration of total MDSCs and CD13hi-nMDSCs,the number of CD13hi-nMDSCs migrating was significantly less than that of the SDF-1 experimental group.The IL-6 recombinant protein did not induce the migration of total MDSCs or CD13hi-nMDSCs.Conclusion CAFs can mediate the migration of total MDSCs and CD13hi-nMDSCs in PDAC through SDF-1/CXCR4 pathway.

Foodborne illnesses caused by Salmonella pose significant threats to worldwide public health safety.In this study,a rapid method for screening viable Salmonella in oyster sauce and milk was developed by utilizing an electronic microbial growth analyzer(EMGA).Target food samples were diluted 10-fold with RVS broth and loaded into test tubes.Test tubes were positioned in the EMGA to determine the bacterial growth curves and the time required to reach the maximum growth rate(Tmgr).Using Salmonella typhimurium(S.typhimurium)asan model species,there was linear relationship between the logarithmic value of viable bacterial concentration(lgC)and Tmgr over the range of 5×101-5×106 CFU/mL,with a detection limit of 10 CFU/mL.For oyster sauce,the regression equation was Tmgr(min)=-80.775lg[C/(CFU/mL)]+754.96(R2=0.9907),and the recovery rates of S.typhimurium ranged from 95.2%to 119.8%,with relative standard deviations(RSD)ranging from 3.5%to 16.3%.For milk,the regression equation was Tmgr(min)=-71.922 lg[C/(CFU/mL)]+618.65(R2=0.9985),with recovery rates ranging from 98.4%to 110.6%and RSD ranging from 6.4%to 12.8%.The EMGA method required only one portable instrument,and involving only three manual steps,i.e.,dilution,transfer,and insertion.When S.typhimurium contamination reached 106 CFU/mL,the total time consumption,from the unwrapping of samples to the readout of bacterial concentration,was no more than 7 h.When applied to detection of actual oyster sauce and milk samples,the new method demonstrated strong consistency with plate counting results in positive detection rates.This method was superior to the plate counting method,which was generally considered as a gold standard,in terms of accuracy,precision,simplicity and efficiency,representing a promising alternative for the on-site screening and quantification of viable Salmonella in oyster sauce and milk products.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective To assess the effectiveness of the evaluation of military physical function(EMPF)system in predicting the occurrence of military training injuries among new recruits to provide scientific guidance and methodological choice for military training.Methods A total of 527 new recruits from 5 grassroots units from July 2016 to February 2018 were selected for the study.The recruits underwent EMPF testing,and their military training injuries were monitored over a 2-year follow-up period.Those who sustained injuries during training were divided into injury group(n=163),while the remaining recruits were placed in healthy group(n=364).The predictive ability of the total EMPF score for training injuries was assessed using the receiver operating characteristic curve(ROC),and the correlation between the total EMPF score,individual test scores,and military training injuries were analyzed using binary logistic regression.Results The total EMPF score of new recruits in injury group(19.52±1.97)was significantly lower than that of healthy group(24.31±1.54)(P<0.001),which also demonstrated a high diagnostic value in predicting the risk of military training injuries,with an area under the curve(AUC)of ROC of 0.971(P<0.001).A cut-off value of 22 scores was found to have the highest accuracy in predicting future training injuries,with an odds ratio(OR)of 25.63,sensitivity of 0.939,specificity of 0.879,positive likelihood ratio of 7.76,and a post-test probability of 0.67.Binary logistic regression analysis revealed that 6 EMPF tests,including holding the ball over and leaning back,bending forward and touching the ground with the ball,lunge squat and twist,swallow balance with holding the ball afterward,vertical jump,and respiratory pattern assessment,were negatively associated with the risk of military training injuries(P<0.0001).Conclusion The EMPF system can effectively predict the risk of military training injuries,with military personnel whose total EMPF score is less than 22 being at higher risk of sustaining such injuries.

Objective This study aimed to investigate whether Trichinella spiralis Ts87 protein can facilitate immune evasion by degrading the mouse neutrophil extracellular traps(NETs).Methods First,we used bioinformatics tools to analyze the physicochemical properties of Ts87 and,through sequence homology alignment,confirmed its classification within the nuclease family.Molecular cloning and protein purification techniques were then employed to obtain high-purity Ts87 protein,and its nuclease activity was confirmed.Additionally,we compared the primary sequence of Ts87 with known active sites from human lysosomal DNase IIα and the structurally characterized Burkholderia thailandensis DNase II.This enabled us to predict potential active sites.Ts87 enzymatic mutants were generated using site-directed mutagenesis,and their functions were confirmed through enzymatic activity experiments.The extracellular nucleic acid content of mouse bone marrow neutrophils and the immunofluorescence staining of mouse NETs were assessed in vitro to verify whether the Ts87 protease mutants exhibited a decreased ability to degrade NETs.Finally,after immunizing mice with Ts87,calculated larvae burden and the degradation of NETs in vivo were observed by immunostaining the MPO and CitH3 expression in the intestinal NETs of the mice.Results High-purity Ts87 protein was successfully obtained and confirmed to possess nuclease activity,capable of degrading NETs in vitro.The Ts87 mutants exhibited reduced capacity in degrading NETs.In vivo experiments in mice demonstrated that the production of anti-Ts87 antibodies in immunized mice reduced the degradation of NETs,facilitating NET-mediated attack on the parasites and resulting in decreased larvae burden in the mice.Conclusions Trichinella spiralis can utilize Ts87 nuclease to evade capture by NETs,providing potential vaccine and drug targets for the prevention and treatment of trichinellosis.

Intermittent theta burst stimulation (iTBS), a time-saving and cost-effective repetitive transcranial magnetic stimulation regime, has been shown to improve cognition in patients with Alzheimer's disease (AD). However, the specific mechanism underlying iTBS-induced cognitive enhancement remains unknown. Previous studies suggested that mitochondrial functions are modulated by magnetic stimulation. Here, we showed that iTBS upregulates the expression of iron-sulfur cluster assembly 1 (ISCA1, an essential regulatory factor for mitochondrial respiration) in the brain of APP/PS1 mice. In vivo and in vitro studies revealed that iTBS modulates mitochondrial iron-sulfur cluster assembly to facilitate mitochondrial respiration and function, which is required for ISCA1. Moreover, iTBS rescues cognitive decline and attenuates AD-type pathologies in APP/PS1 mice. The present study uncovers a novel mechanism by which iTBS modulates mitochondrial respiration and function via ISCA1-mediated iron-sulfur cluster assembly to alleviate cognitive impairments and pathologies in AD. We provide the mechanistic target of iTBS that warrants its therapeutic potential for AD patients.
Humans ; Mice ; Animals ; Transcranial Magnetic Stimulation ; Alzheimer Disease/therapy* ; Cognitive Dysfunction/therapy* ; Cognition ; Sulfur ; Iron ; Iron-Sulfur Proteins ; Mitochondrial Proteins