ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.

Objective To introduce the calculation of the DISO index in multi-dimensional data ranking for disease surveillance, and evaluate its applicability. Methods Using the data from the quality supervision and inspection of infectious disease reporting in Jingzhou City in a certain year as an example, the DISO index was used to rank 16 investigated medical institutions and compared with the TOPSIS method. The consistency between the two evaluation results was analyzed using Spearman correlation. Then, The DISO index from different medical institutions was used to evaluate the ranking of 8 counties (cities, districts). The evaluation indicators for the supervision and inspection included six items: report rate, timely report rate, completeness of report card filling, accuracy of report card filling, consistency rate with network information report, and completeness of valid ID number filling. Results Among the 16 medical institutions, 8 institutions had all six evaluation indicators at 100%. Using the two methods to rank the 16 medical institutions, the two methods showed that the 8 medical institutions with all six evaluation indicators at 100% were ranked first. There was a strong correlation between the rankings of the 16 medical institutions using the two methods (r_s=0.992, P=0.000). The three counties (cities, districts) with all six evaluation indicators at 100% were all ranked first, while country G was ranked seventh and country E was ranked eighth. Conclusion The results of the DISO index and the TOPSIS method were similar in one-dimensional ranking. DISO can be used for multi-dimensional ranking of disease surveillance data and deserves to be promoted and applied.

Objective: To explore the relative importance of different food attributes and levels in food decision making of school aged children, and to understand their meal preferences, so as to provide the evidence for formulating precise intervention strategies for dietary behaviours of school aged children. Methods: From May to June 2024, a total of 854 children aged 11 to 15 years old were selected from 2 middle schools (each school in urban and rural areas) in both Hubei Province and Anhui Province by stratified cluster random sampling method to conduct a D-optimal discrete choice experiment. The mixed Logit model was used to analyze children s preference for meal attributes and different levels, and to calculate the relative importance (RI) of attributes and willingness to pay (WTP) in meal choices. Results: The included five food attributes had statistical significance on meal choice of school aged children ( P <0.05). The relative importance of food attributes affecting the meal choices of school aged children in descending order were dining mode ( RI =31.26%), food varieties ( RI =30.56%), cooking method( RI =23.84%), taste( RI =8.06%) and price ( RI =6.27%). Among them, school aged children preferred home cooked meals ( β =0.74) (WTP=86.3 yuan),varied foods(grain/tubers+vegetables+fish, meat, eggs and beans) ( β =0.61) (WTP=71.9 yuan), fried/roasted cooking ( β =0.51) and spicy taste ( β =0.33).Price was negatively correlated with meal choices( β =-0.01) ( P <0.05). Based on residential area and body mass index (BMI), the stratified analysis showed that dining mode was highest in the relative importance for rural children with overweight and obese children ( RI =31.28%,34.17%), both of whom preferred home cooked meals ( β =0.76, 0.91), and meals containing fish, meat, eggs and beans with grain/tubers or grain/tubers and vegetables in terms of food choice (area: β =0.53, 0.53 ; BMI: β =0.55, 0.56) ( P <0.05). Conclusions School aged children have different preferences for different attributes of meals. The quality of school meals should be improved,the cost of buying healthy meals should be reduced,targeted family health education should be carried out,and healthy cooking methods should be advocated.

The amino acid sequences of the OmpA protein isolated from Escherichia coli QML2206-1(E.coli QML2206-1)in our laboratory were analyzed for homology with different strains of OmpA proteins using bioinformatics software,and the OmpA protein was analyzed for its physicochemical properties,transmembrane structure and signal peptide prediction,B-cell anti-genic epitope prediction,secondary and tertiary structure prediction.The OmpA gene fragment was ligated with pET-32a vector to construct a prokaryotic expression vector,which was purified by a nickel column affinity purification system after prokaryotic expression and optimization of ex-pression conditions in BL21(DE3).The purified recombinant protein was fully mixed with Freund's adjuvant to immunize mice,and the levels of mouse-specific IgG antibody and the expression levels of cytokines CD4,CD8 and IL-4 in mouse serum were detected by ELISA,and the immuno-protective effect was evaluated by mouse attack protection test.OmpA protein is a hydrophilic protein with no transmembrane structural domains and a secondary structure consisting mainly of irregular coils(47.98％)and α-helices(29.77％),with 12 antigenic epitopes that can bind to anti-bodies produced by B cells.The recombinant protein OmpA with a relative molecular mass of a-bout 55 kDa was successfully obtained by prokaryotic expression,and the highest expression was induced by IPTG concentration of 0.000 4 mmol/L for 6 h at 37 ℃.The serum-specific IgG anti-body potency of recombinant protein immunized mice was up to 1∶32 000;the expression levels of CD4,CD8 and IL-4 in the serum of immunized mice were elevated compared with those of the con-trol group.The survival rate of mice was 80％and 40％after attack with minimum lethal dose(MLD)and 2 times minimum lethal dose(2MLD),respectively.OmpA recombinant protein has good antigenicity and certain immunoprotective effects,and this study provides a technical basis for the next step in the development of a genetically engineered subunit vaccine against yak-appli-cable E.coli based on OmpA protein.

Porcine deltacoronavirus(PDCoV)is the main pathogen of porcine deltacoronavirus dis-ease.After infection,pigsmanifest a series of main symptoms,such as persistent vomiting,watery diarrhea and severe dehydration.Pigs at almost all growth stages are likely to be infected with the virus,especially suckling piglets are much sensitive to the virus.Once PDCoV infects the host,it u-sually causes significant immunosuppression.In recent years,studies on the immunosuppressive mechanism of PDCoV have gradually attracted widespread attention.The results showed that mul-tiple proteins of PDCoV were involved in the regulation of host innate immunity,revealing the mechanism of these proteins in regulating host innate immunity.In this paper,the interaction mechanism between PDCoV protein and host innate immunity were rsummarized,which will pro-vide a theoretical basis for further understanding the pathogenesis of PDCoV and effective preven-tion and control of porcine delta coronavirus disease.

To establish a TaqMan-based multiplex RT-qPCR method for the identification of Japa-nese encephalitis virus(JEV),Porcine reproductive and respiratory syndrome virus(PRRSV),and Classical swine fever virus(CSFV),this study designed and synthesized three pairs of specific primers and probes based on the conserved sequences of JEV E,PRRSV ORF6,and CSFV E2 a-vailable in the NCBI GenBank.By optimizing the reaction system and protocol,a multiplex RT-qPCR method for detecting these three viruses was developed and applied to the detection of clini-cal samples.The results showed that the established TaqMan multiplex RT-qPCR specifically am-plified the gene fragments of JEV,PRRSV,and CSFV,and did not amplify other non-target genes,indicating good specificity of the method.Intra-assay and inter-assay repeatability tests showed that the coefficient of variation(Cv)values were all below 3％,demonstrating that the method has ex-cellent repeatability.Sensitivity tests revealed that the minimum detectable amount for the recom-binant plasmids of the three viruses was 100 copies/pL.Using the established method,a total of 969 samples,including blood,aborted fetuses,semen,and deceased pigs,from 26 pig farms in Guizhou Province were tested.The detection rates were 34.3％(332/969)for JEV,28.3％(274/969)for PRRSV,and 19.8％(192/969)for CSFV.The co-infection rates were 10.1％(98/969)for JEV and PRRSV,12.1％(117/969)for JEV and CSFV,and 14.6％(141/969)for CSFV and PRRSV.Additionally,the triple co-infection rate of JEV,PRRSV,and CSFV was 7.9％(77/969).These results indicate that the TaqMan multiplex RT-qPCR method developed in this study is ef-fective for detecting these three viruses in pig farms,providing technical support for identifying vi-ral causes of reproductive disorders.

Japanese encephalitis virus(JEV)belongs to the genus Flavivirus and the family Flavi-viridae,and is classified as a single-stranded,positive-sense RNA virus.The disease known as Japa-nese encephalitis(JE),which results from JEV infection,is a viral zoonosis that is prevalent worldwide and poses a significant public health concern.JEV infection activates a variety of signa-ling pathways,leading to a series of changes that are crucial to the virus's pathogenesis.Among these pathways,Toll-like receptors(TLRs)are particularly significant,and their diverse range and complex signal transduction mechanisms present substantial challenges for the prevention and con-trol of JEV.Currently,there is no specific treatment for JEV.Although some vaccines have been developed to prevent JE,eradicating JEV remains difficult due to its zoonotic transmission cycle and the limited efficacy of the available vaccines.This article reviews the alterations in various TLR signaling pathways induced by JEV infection in the host,aiming to provide insights into the patho-genic mechanisms of JEV and to identify potential new antiviral targets.

Porcine reproductive and respiratory syndrome virus(PRRSV)is the pathogen of porcine reproductive and respiratory syndrome(PRRS),and its infection mainly causes abortion,stillbirth in sows and piglet respiratory infections,which are widely prevalent in the world and seriously jeopardize the development of the world's animal husbandry industry.PRRSV infection of the host is capable of inducing significant immunosuppression,and in recent years,the study of the mecha-nism of PRRSV immunosuppression has become a hot topic,with studies showing that numerous PRRSV proteins are involved in the regulation of host innate immunity and elucidating the mecha-nism by which PRRSV proteins modulate host innate immunity.In this paper,we reviewed the progress of research on the interaction mechanism between PRRSV proteins and host innate im-munity to provide a theoretical basis for a comprehensive understanding of the pathogenesis of PRRSV and the prevention and control of PRRS.

Atopic dermatitis (AD) is a prevalent inflammatory skin disorder in which patients experience recurrent eczematous lesions and intense itching. The colonization of Staphylococcus aureus (S. aureus) is correlated with the severity of the disease, but its role in AD development remains elusive. Using single-cell RNA sequencing, we uncovered that keratinocytes activate a distinct immune response characterized by induction of Il24 when exposed to methicillin-resistant S. aureus (MRSA). Further experiments using animal models showed that the administration of recombinant IL-24 protein worsened AD-like pathology. Genetic ablation of Il24 or the receptor Il20rb in keratinocytes alleviated allergic inflammation and atopic march. Mechanistically, IL-24 acted through its heterodimeric receptors on keratinocytes and augmented the production of IL-33, which in turn aggravated type 2 immunity and AD-like skin conditions. Overall, these findings establish IL-24 as a critical factor for onset and progression of AD and a compelling therapeutic target.
Dermatitis, Atopic/genetics* ; Interleukins/metabolism* ; Animals ; Methicillin-Resistant Staphylococcus aureus/immunology* ; Mice ; Keratinocytes/microbiology* ; Humans ; Interleukin-33/immunology* ; Inflammation/microbiology* ; Staphylococcal Infections/microbiology* ; Disease Models, Animal ; Hypersensitivity/microbiology* ; Mice, Inbred C57BL

Objective To explore the application of serum signal transducer and activator of transcription 3(STAT3),histone deacetylase 2(HDAC2),and developmental endothelial locus-1(Del-1)levels in the evaluation of disease severity and prognosis of children with respiratory syncytial virus pneumonia(RSVP).Methods A total of 109 children with RSVP admitted to Jiamusi Central Hospital from November 2023 to March 2025 were enrolled as the RSVP group.Based on disease severity,RSVP patients were categorized into a low-risk group(n=31),a medium-risk group(n=42),and a high-risk group(n=36).According to the prognosis after 7 days of treatment,they were divided into a favorable prognosis group(n=78)and a poor prognosis group(n=31).Additionally,109 healthy children undergoing physical examination at the same hospital during the same period were selected as the normal control group(NC group).ELISA method was used to detect serum levels of STAT3,HDAC2,and Del-1.Pearson correlation analysis was used to explore the correlations between serum STAT3,HDAC2,Del-1 levels and pulmonary function indices.Multivariate logistic regression analysis was used to explore the factors affecting the prognosis of children with RSVP.Moreover,ROC curve was used to explore the predictive value of serum STAT3,HDAC2,and Del-1 levels for the prognosis of children with RSV.Results Compared with the NC group,the RSVP group had higher serum STAT3 and HDAC2 levels,and lower serum Del-1 levels(P<0.05).Serum STAT3 and HDAC2 levels progressively increased from the low-risk group,medium risk group,to high-risk group,while the time to peak ratio(time to peak tidal expiratory flow to total expiratory time ratio,TPTEF/TE),peak volume ratio(volume to peak expiratory flow to total expired volume ratio,VPEF/VE),and serum Del-1 levels progressively decreased(P<0.05).TPTEF/TE and VPEF/VE were prominently negatively correlated with serum STAT3 and HDAC2 levels,and prominently positively correlated with Del-1 levels(P<0.05).Compared with the favorable prognosis group,the poor prognosis group had significantly lower initial blood oxygen saturation,serum Del-1 levels,and significantly higher serum STAT3 and HDAC2 levels(P<0.05).High expression levels of STAT3 and HDAC2 were independent risk factors affecting the prognosis of children with RSVP,while high expression of Del-1 was an independent protective factor(P<0.05).The AUC values of serum STAT3,HDAC2,and Del-1 levels alone in predicting the prognosis of children with RSV were 0.824,0.818,and 0.842,respectively.The combined prediction AUC was 0.947,which was superior to individual predictions(ZSTAT3-joint=2.436,ZHDAC2-joint=2.570,ZDel-1-joint=2.611,all P<0.05).Conclusion Serum expression of STAT3 and HDAC2 is upregulated,while the expression of Del-1 is down-regulated in children with RSVP.The three markers are closely related to the disease severity and pulmonary function indices,and are important factors affecting the prognosis of children with RSVP.Combined detection of these markers demonstrates high efficacy for prognosis evaluation.