Background Air pollution is a major environmental factor threatening respiratory health. Different pollutants exhibit varying degrees of lag effects on respiratory diseases, and synergistic effects may exist among multiple pollutants. There is an urgent need to identify the key air pollutants influencing respiratory diseases and their interactive effects at specific lags. Objective To identify key pollutants affecting hospital admissions for respiratory diseases, to analyze their lag effect characteristics, and to quantify the impact of multi-pollutant synergistic effects on respiratory disease admissions. Methods Daily air pollution data, meteorological data, and respiratory disease hospitalization records were collected from multiple national monitoring stations in Hefei City from 2019 to 2024. A two-stage analytical framework was employed. First, a distributed lag model (DLM) was used to construct pollutant lag matrices, followed by least absolute shrinkage and selection operator (LASSO) regression to select key variables among fine particulate matter (PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃). Second, a generalized additive model (GAM) was established, incorporating product interaction terms and excess relative risk (ERI) to quantitatively assess synergistic effects among the selected pollutants. Results Through LASSO regression, 24 pollutant lag terms with non-zero coefficients were identified, among which NO₂, PM_2.5, and SO₂ accounted for 66.7% of the total positive effects and exhibited distinct lag patterns. Exposure to NO₂ showed acute risk, with a relative risk of 1.040 (95%CI: 1.023, 1.057) at lag0. Conversely, PM_2.5 and SO₂ exhibited delayed effects, with peak impacts observed at lag7 (RR=1.012, 95%CI: 1.0002, 1.024) and lag3 (RR=1.015, 95%CI: 1.0004, 1.03), respectively. Short-term NO₂ exposure (lag0–1) exhibited a significant positive interaction with medium-term PM_2.5 exposure (lag4–7). When both pollutants coexisted at high exposure levels, the combined health risk exceeded the sum of their independent effects by 4.40%. Stratified analysis showed that the interaction effects of pollutants were higher in females (ERI=5.00%), children (<18 years, ERI=5.50%), and older adults (≥65 years, ERI=3.90%)Conclusion There are significant lag heterogeneity and synergistic mechanisms in the health effects of air pollution in Hefei. It is recommended to implement real-time early warning responses for NO₂, prioritize medium-to-long-term management for PM_2.5 and SO₂, and adopt coordinated emission reduction measures when NO₂ and PM_2.5 concentrations rise simultaneously. Concurrently, enhanced health protection should be provided for sensitive populations such as women, children, and the elderly.

ObjectiveTo investigate the impact of hepatocellular carcinoma （HCC） on the prognosis of patients with liver cirrhosis undergoing emergency endoscopic therapy for esophagogastric variceal bleeding， as well as independent influencing factors for the prognosis of liver cirrhosis patients without HCC after emergency endoscopic therapy for esophagogastric variceal bleeding. MethodsA total of 117 liver cirrhosis patients without HCC and 119 liver cirrhosis patients with HCC who underwent emergency endoscopic therapy for esophagogastric variceal bleeding in Renmin Hospital of Wuhan University from January 2017 to July 2023 were enrolled. Basic information including age and sex was collected from all patients， as well as the presence or absence of chronic diseases such as hypertension， diabetes， and coronary heart disease， the time of emergency endoscopy after admission， and liver function parameters including international normalized ratio， albumin， creatinine， sodium， total bilirubin， alanine aminotransferase， and aspartate aminotransferase （AST）. The independent-samples t test was used for comparison of normally distributed continuous variables between two groups， and the Wilcoxon rank-sum test was used for comparison of non-normally distributed continuous variables between two groups； the chi-square test was used for comparison of categorical variables between groups. The covariance analysis and the multivariate logistic regression analysis were used for comparison of outcome variables after control of baseline variables， and the Kaplan-Meier survival curve was plotted for each group. The univariate and multivariate Cox regression analyses were performed for survival time in the non-HCC group to investigate the independent influencing factors for survival time， and then the Kaplan-Meier curve analysis and the log-rank test were performed to validate such independent influencing factors and analyze the independent influencing factors for secondary outcomes. ResultsCompared with the non-HCC group， the HCC group had significantly higher red blood cell transfusion units （6.00［2.00～9.00］ vs 4.00［1.75～7.00］， Z=-2.050， P=0.040， F=4.869， adjusted P=0.028）， a significantly shorter survival time （29.77±16.01 days vs 38.07±11.43 days， t=4.574， P<0.001， F=17.294， adjusted P<0.001）， and a significantly higher 5-day rebleeding rate （22.69% vs 6.84%， χ²=11.736， P<0.001， adjusted P=0.021）. The Kaplan-Meier curve analysis showed that the risk of 42-day mortality in the HCC group was 3.897 （95% confidence interval ［CI］： 2.338 ‍— 6.495， P<0.001） times that in the non-HCC group. The multivariate Cox regression analysis of the non-HCC group showed that the total length of hospital stay （hazard ratio ［HR］=0.793， 95%CI： 0.644 ‍— ‍0.976， P=0.029） was an independent protective factor for 42-day survival. The Kaplan-Meier curve analysis showed that a length of hospital stay of >9 days was beneficial for the prognosis of patients （HR=4.302， 95%CI： 1.439 — 12.870， P=0.037）. Blood sodium level （odds ratio ［OR］=0.523， 95%CI： 0.289 ‍— ‍0.945， P=0.032） and MELD-Na score （OR=0.495， 95%CI： 0.257 ‍— ‍0.954， P=0.036） were independent protective factors against 5-day rebleeding， while AST level was an independent risk factor for 5-day rebleeding （OR=1.023， 95%CI： 1.002 ‍— ‍1.043， P=0.028） and in-hospital death （OR=1.036， 95%CI： 1.001‍— ‍1.073， P=0.045）. ConclusionLiver cirrhosis patients with variceal bleeding and HCC tend to have a worse prognosis， and for the non-HCC group， in-hospital mortality rate increases with the increase in AST level. The total length of hospital stay is an independent protective factor for survival time in the non-HCC group， and it is recommended to appropriately prolong the length of hospital stay for such patients.

Objective To summarize the clinical and genetic characteristics of end-stage renal disease caused by PLCE1 gene mutations.Methods A retrospective analysis of the clinical and genetic features of three children from a family with PLCE1 gene mutations was conducted,along with a literature review of hereditary kidney disease cases caused by PLCE1 gene mutations.Results The proband was an 8-year-old male presenting with nephrotic syndrome stage 4 chronic kidney disease.Renal biopsy showed focal segmental glomerulosclerosis.Two years and five months after kidney transplantation,the patient had persistent negative proteinuria and normal renal function.Whole-exome sequencing identified two pathogenic heterozygous variants:c.961C>T and c.3255_3256delinsT,with c.3255_3256delinsT being a novel mutation.Family screening revealed no renal involvement in the parents,but among five siblings,one brother died at age of 4 years from end-stage renal disease.A 7-year-old sister presented with proteinuria and bilateral medullary sponge kidney,with proteinuria resolving after one year of follow-up.A 3-year-old brother died after kidney transplantation due to severe pneumonia.The literature review included 45 patients with hereditary kidney disease caused by PLCE1 gene mutations.The main clinical phenotype was nephrotic syndrome(87%,39/45),and renal pathology predominantly showed focal segmental glomerulosclerosis(57%,16/28).No mutation hotspots were identified.Conclusions Compound heterozygous mutations in the PLCE1 gene can lead to rapid progression of the disease to end-stage renal disease,with favorable outcomes following kidney transplantation.Family screening is crucial for early diagnosis,and medullary sponge kidney may be a novel phenotype associated with these gene mutations.Citaion:[Chinese Journal of Contemporary Pediatrics,2025,27(5):580-587]

Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the"therapeutic module"of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Objective:To investigate the effect and mechanism of injectable photopolymerizable porous gelatin methacrylate anhydride (Porous GelMA)/methacrylated silk fibroin (SilMA) composite hydrogel (PSE) loaded with human umbilical cord mesenchymal stem cell-derived exosomes (hUCMSC-Exos) in promoting knee joint cartilage regeneration.Methods:The porous GelMA solution (60 g/L) was mixed with SilMA solution (200 g/L) at a volume ratio of 6∶1 . The mixture was ultraviolet-irradiated for 30 seconds to form a cured Porous GelMA/SilMA hydrogel (P/S6). The hUCMSC-Exos was isolated via differential centrifugation coupled with ultrafiltration and then was incorporated into the Porous GelMA/SilMA composite solution at 200 μg/ml, followed by ultraviolet irradiation for 30 seconds to generate Exos-loaded PSE. Primary rat chondrocytes (P1) were divided into control group, P/S6 group, and PSE group to characterize the porosity, compressive strength, and sustained exosome release kinetics of PSE hydrogel. Chondrocytes were allocated to control group, interleukin-1β (IL-1β) group, P/S6 group, and PSE group, among which the last three groups were preconditioned with 10 ng/ml IL-1β for 24 hours, and then cultured in complete medium, P/S6 extract and PSE extract for 3 days, respectively, to establish in vitro cartilage defect models, while the control group remained untreated. Western blot and qRT-PCR analysis were conducted to quantify the expression levels of antibody to aggrecan core protein (ACAN), sex-determining region Y-box transcription factor 9 (SOX9), matrix metalloproteinase-13 (MMP13) and collagen type II (COL II). Murine monocyte-macrophage leukemia cells (RAW264.7) were divided into control group, P/S6 group, and PSE group, which were then cultured in complete medium, PSE extract, and PSE extract medium for 3 days, respectively. qRT-PCR was employed to detect the expression levels of recombinant arginase-1 protein (ARG1), mannose receptor (CD206), and inducible nitric oxide synthase (iNOS). Transcriptomic sequencing was used to identify differentially expressed genes during PSE-mediated chondrocyte regeneration, followed by functional enrichment analysis of key signaling pathways. Twenty-four SD rats were selected to establish cartilage defect models and assigned to injury control group, P/S6 group, and PSE group according to the random number table (8 rats per group). The right knee joints of the rats were surgically exposed, and cylindrical osteochondral defects (a diameter of 2.0 mm× a depth of 1.0 mm) were surgically created in the center of the femoral trochlear groove using a drill bit. The injury control group received phosphate-buffered saline, while the P/S6 group and PSE group were injected with corresponding hydrogels followed by photo-crosslinking. Incisions then were closed in layers. At 6 and 10 weeks after injury, specimens were harvested for HE staining and safranin O-fast green staining to evaluate cartilage regeneration and immunohistochemistry staining to quantify the positive area fractions for COL II, MMP13, ARG1, and CD206 in the defect areas. Results:PSE hydrogel exhibited compressive strength matching native cartilage (0.41 MPa), high porosity (85%), and sustained exosome release capacity (cumulative release rate of approximately 85% over 14 days). In chondrocyte repair experiments, compared to the IL-1β group, the PSE group demonstrated significantly upregulated expression of anabolic markers of cartilage (COL II expression increased by 2.1-fold, ACAN by 1.8-fold, and SOX9 by 1.5-fold) ( P<0.01) as well as significantly suppressed expression of catabolic markers (MMP13 expression decreased by 52%) ( P<0.01). In macrophage polarization assays, the PSE group exhibited ARG1 expression increased by 68% when compared to the control group ( P<0.01), thus promoting M2 polarization of macrophages. Transcriptomic analysis revealed that PSE enhanced extracellular matrix (ECM) synthesis by activating the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway and ECM-receptor interaction pathway, as well as by suppressing inflammation-related gene expression. Histological evaluation in animal experiments revealed regeneration of hyaline cartilage with smooth, continuous surfaces in the defect areas in the PSE group. At 10 weeks after surgery, the neocartilage-positive area in the PSE group was (9.94±0.26)%, significantly larger than (1.67±0.11)% in the injury control group ( P<0.01). Besides, the CD206? M2 macrophage-positive area reached (14.44±0.23)% in the PSE group, significantly larger than (3.41±0.36)% in the injury control group ( P<0.01). Conclusions:The PSE hydrogel successfully engineered in the study can significantly promote regenerative repair of knee cartilage defects through a dual mechanism of enhanced ECM anabolism and remodeled inflammatory microenvironment. The core mechanisms involve specific activation of the PI3K/Akt pathway (boosting chondrocyte proliferation and survival) and ECM-receptor interaction pathway (driving ECM synthesis and assembly) by exosome-loaded PSE, while effectively polarizing macrophages toward an anti-inflammatory M2 phenotype so as to coordinately regulate cartilage ECM metabolism and suppress inflammatory responses.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Purpose To investigate the sex differences of white matter damage in Alzheimer's disease(AD)and their association with cognitive impairment.Materials and Methods This retrospective study included 88 AD patients(48 females),71 amnestic mild cognitive impairment(aMCI)patients(39 females),and 95 healthy controls(63 females)recruited from the Memory Disorder Clinic at the First Affiliated Hospital of Anhui Medical University from September 2017 to July 2024.High-resolution three-dimensional T1 structure images and diffusion tensor imaging images were all obtained from each participant.The mean diffusivity(MD)and fractional anisotropy(FA)values of each white matter region were obtained,and the two-way ANOVA analysis was conducted to investigate brain regions with interaction effects between groups and sexes,those brain regions were then chosen as regions of interest for further correlation analysis with a series of cognitive scale scores.Results In terms of FA values,the right posterior corona radiata,right anterior limb of the internal capsule and left corticospinal tract showed interaction between sexes and cognitive groups(F=4.764,3.812,5.937,all P<0.05).The FA value of AD group was significantly lower than that of healthy control and aMCI group(all P<0.05),but there was no significant difference between healthy control and aMCI group(except the right anterior limb of the internal capsule,P=0.018).In AD group,FA values were significantly higher in women than in men in the previously described brain regions(all P<0.05),while there was no significant difference in FA values between male and female in healthy control and aMCI groups(except the left corticospinal tract,P<0.001).In terms of MD values,the right anterior limb of the internal capsule,right superior corona radiata and left external capsule showed interaction effect between sexes and cognitive groups(F=8.581,3.680,7.218,all P<0.05).The MD value of AD group was significantly higher than that of aMCI group(P<0.001),and aMCI group was higher than that of healthy control group(all P<0.05).In AD group,the MD values in the above brain regions were significantly higher in males than those in females(all P<0.01),while no significant difference was found between males and females in healthy control and aMCI groups(except for the left external capsule,P<0.05).For correlation analysis,the AD group was dimidiated into two groups by sex,the scores of the Montreal cognitive assessment,the Mini Mental state examination and the verbal fluency test of the female patient group were positively correlated with the FA values of the right posterior corona radiate(r=0.372,P=0.009;r=0.345,P=0.016;r=0.383,P=0.007),while the Mini Mental state examination and the verbal fluency test scores of female AD patient group were negatively correlated with the MD values of the right superior corona radiata(r=-0.360,P=0.012;r=-0.360,P=0.003).Conclusion Compared to the healthy control and MCI groups,white matter damage in AD patients shows sex differences and is associated with general cognitive and language functions impairment in female AD patients.

Objective:To establish a stable rat model of sequelae of pelvic inflammatory disease(SPID)with clinical characteristics,and to provide a reliable experimental model for the study of the pharmcological effect and mechanism of SPID.Methods:Twenty-four 7-week-old SD rats were divided into sham operation group,model-A(108 cfu/mL mixed bacterial solution,0.2 mL),model-B(109 cfu/mL mixed bacterial solution 0.2 mL),and model-C(108 cfu/mL E.coli 0.2 mL).The weight of the rat's uterine was weighed and the uterine index was calculated.The automatic hematology analyzer was used to detect the blood routine;hematoxylin-eosin staining(HE)and masson staining were used to detect uterine pathlogical changes in rats.Enzyme-linked immunosorbent assay(ELISA)was used to detect interleukin-1β(IL-1β),interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)in rat uterine tissue homogenates.Western blot was used to detect the expression of proteins related to NF-κB signaling pathway.Results:Compared with the sham operation group,the uterine index of model-A,model-B,and model-C were significantly increased(P＜0.05,P＜0.01).The levels of WBC and NE in the model-A increased significantly(P＜0.01).The level of LY in model-B decreased significantly(P＜0.01).The levels of IL-1β,TNF-α in model-A,model-B,and model-C were significantly increased(P＜0.01).The levels of IL-6 in model-A and model-B were significantly increased(P＜0.05,P＜0.01).The collagen volume fraction of model-A and model-B were significantly increased(P＜0.01).Mechanism study indicates that the expression levels of p-IKKβ/IKKβ,p-IκBα/IκBα and p-p65/p65 in model-A were significantly increased(P＜0.01),and the expression levels of IκBα/β-actin were significantly decreased(P＜0.01).The expression level of p-IKKβ/IKKβ in model-B was significantly increased(P＜0.01).Conclusions:A stable rat model of SPID that conforms to clinical characteristics can be successfully constructed by combining 0.2 mL of mixed bacterial solution with a concentration of 108 cfu/mL and mechanical injury.This modeling method intervened in the expression of the NF-κB inflammatory signaling pathway.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

An assay was established for detection of toxigenic Clostridioides difficile by combining microfluidic chip analysis with immunochromatography,and its performance was evaluated and compared with those of the Xpert C.difficile/Epi and VIDAS CD AB tests.Primer pairs were designed according to the tcdB and tpi genes in C.difficile.The specificity,limit of detection,reproducibility,and stability were evaluated.A total of 215 stool samples from patients with diarrhea were collected and tested in parallel with the Xpert C.difficile/Epi,VIDAS CDAB,and our assay.C.difficile was isolated from samples,and the tcdB gene was identified when discrepant results were obtained from the three above assays.Our assay showed no cross-reaction with other diarrhea-associated pathogens.Its reproducibility was 100％in testing of two standard plasmids containing tcdB and tpi genes at two concentrations(105 and 102 copies/μL).Two standard plasmids were detected after the PCR and immunochromatography reagents had been stored for 3,6,9,and 12 months,and all the results were posi-tive.The limit of detection was 10 copies/μL for toxigenic C.difficile.Testing of 33 samples positive for C.difficile with our assay(33/215,15.3％)yielded findings statistically coherent with those of the Xpert C.difficile/Epi test(kappa value=0.965).The sensitivity,specificity,positive predictive value,and negative predictive value of our assay,with respect to Xpert C.difficile/Epi as the standard,were 94.3％,100.0％,100.0％,and 98.9％;these values were significantly higher than those of VIDAS CDAB(60.0％,98.9％,91.3％,and 92.7％)(Kappa=0.714,OR=157.50,95％CI:62.03-847.28,P=0.013).In conclusion,our newly developed assay is specific,stable,and reproducible,and may be used for rapid and accu-rate detection of toxigenic C.difficile.The assay could be used for C.difficile infection screening in outpatient and emergen-cy,community medical service center,and epidemiological settings.