Objective To study the effect of Compound Jinguanlan preparation on acne vulgaris through the p38MAPK signaling pathway.Methods New Zealand White Rabbits were randomly divided into high,medium,and low concentration groups of Jinguanlan,a positive control group,a model control group,and a blank control group.A rabbit ear acne model was constructed and each group was given the corresponding drug intervention.The gross changes in the skin tissue of the rabbit ears were observed.HE staining was used to observe pathological changes.ELISA was used to detect the levels of IL-6 and TNF-α in the serum.Western blot was used to detec the levels of p38MAPK protein expression.Results Jinguanlan significantly inhibited the inflammation of acne vulgaris,reducing swelling,erythema,hyperkeratosis,and inflammatory cell infiltration in the rabbit ears.ELISA results showed that compared with the model control group,the levels of IL-6 and TNF-α in the serum of each concentration of Jinguanlan group were significantly reduced,with the high concentration group showing a more pronounced decrease(P＜0.01).Western blot results indicated that compared with the model group,the relative expression of p38 MAPK protein in the Jinguanlan group was reduced.Conclusion Jinguanlan can inhibit the inflammatory response of acne vulgaris,and its effect may be achieved by regulating the p38MAPK signaling pathway and reducing the expression levels of IL-6 and TNF-α in the serum.

Objective To study the effect of Compound Jinguanlan preparation on acne vulgaris through the p38MAPK signaling pathway.Methods New Zealand White Rabbits were randomly divided into high,medium,and low concentration groups of Jinguanlan,a positive control group,a model control group,and a blank control group.A rabbit ear acne model was constructed and each group was given the corresponding drug intervention.The gross changes in the skin tissue of the rabbit ears were observed.HE staining was used to observe pathological changes.ELISA was used to detect the levels of IL-6 and TNF-α in the serum.Western blot was used to detec the levels of p38MAPK protein expression.Results Jinguanlan significantly inhibited the inflammation of acne vulgaris,reducing swelling,erythema,hyperkeratosis,and inflammatory cell infiltration in the rabbit ears.ELISA results showed that compared with the model control group,the levels of IL-6 and TNF-α in the serum of each concentration of Jinguanlan group were significantly reduced,with the high concentration group showing a more pronounced decrease(P＜0.01).Western blot results indicated that compared with the model group,the relative expression of p38 MAPK protein in the Jinguanlan group was reduced.Conclusion Jinguanlan can inhibit the inflammatory response of acne vulgaris,and its effect may be achieved by regulating the p38MAPK signaling pathway and reducing the expression levels of IL-6 and TNF-α in the serum.

Objective　To conduct an in-depth study of the molecular biological characteristics and evolutionary trends of H9N2 avian influenza virus (AIV) in live poultry markets in Yunnan Province in 2023, and to provide scientific evidence for the development of control strategies for H9N2 avian influenza in the region. Methods　Environmental samples were collected from live poultry markets in Yunnan Province in 2023 for H9N2 subtype nucleic acid detection. Positive samples were subjected to virus isolation using chicken embryos, and the genome of the 8 isolated strains was amplified, sequenced, and analyzed for genetic characteristics. Results　The eight avian influenza virus (AIV) isolates had the hemagglutinin (HA) cleavage site sequence PSRSSRGLF, which is a non-continuous basic amino acid sequence, consistent with the genetic characteristics of typical low-pathogenicity avian influenza viruses. Mutations Q234L and H191N were observed in the left arm of the HA protein, which enhanced the affinity for α-2,6 sialic acid receptors, suggesting that these viruses may have the potential to infect humans. The neuraminidase (NA) protein exhibited a deletion of three amino acids (TEI) at positions 62–64 in the stalk region, displaying characteristics of high pathogenicity at the molecular level. The increase or absence in potential glycosylation sites were observed in both HA and NA genes. The non-structural protein 1 (NS1) showed no D92E mutation, and had a C-terminal truncation of 13 amino acids, indicating that this virus is of low pathogenicity and poses a lower risk of human transmission. Mutations T37A, R95K, S224N, and K242N in the M1 protein of some isolates increased the risk of infection, while one isolate carried the V27A or S31N mutation in the M2 protein, conferring resistance to M2 ion channel inhibitors. Mutations M317I and S678N were identified in the PB1 protein, which may enhance pathogenicity in mice and increase the potential for mammalian infection. The PB2 protein carried the I292V mutation, which exhibited a stronger infectivity to mammals. Phylogenetic analysis revealed that the HA, NA, and PB2 gene segments belonged to the Y280 lineage, NP and PB1 gene segments were classified under the F98 lineage, the M gene segment of the NH013 isolate belonged to the F98 lineage, while M genes, as well as the NS and PA genes of other isolates belonged to the G1 lineage. Conclusions　These eight AIV isolates exhibited characteristics of low pathogenicity, but simultaneously carry the potential risk of infecting humans. Despite the HA cleavage site and NS1 protein mutations indicating low pathogenicity, the Q234L and H191N mutations in the HA protein enhanced its affinity for human receptors, suggesting the potential for human infection. The TEI deletion in the NA protein, mutations in the M1 protein, and resistance mutations in the M2 protein further increase the risk of human infection. Mutations in the PB1 and PB2 proteins increase the potential for these eight AIV strains to infect humans or mammals.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Background::Limited information exists regarding the impact of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection on psoriasis patients. The objective of this study was to identify clinical factors associated with the prognosis of psoriasis following SARS-CoV-2 infection.Methods::A retrospective, multicenter study was conducted between March and May 2023. Univariable and multivariable logistic regression analyses were employed to identify factors associated with coronavirus disease 2019 (COVID-19)-related psoriasis outcomes. The study included 2371 psoriasis patients from 12 clinical centers, with 2049 of them having been infected with SARS-CoV-2.Results::Among the infected groups, lower exacerbation rates were observed in individuals treated with biologics compared to those receiving traditional systemic or nonsystemic treatments (22.3% [236/1058] vs. 39.8% [92/231] vs. 37.5% [140/373], P <0.001). Psoriasis progression with lesions (adjusted odds ratio [OR] = 8.197, 95% confidence interval [95% CI] = 5.685–11.820, compared to no lesions), hypertension (adjusted OR = 1.582, 95% CI = 1.068–2.343), traditional systemic (adjusted OR = 1.887, 95% CI= 1.263–2.818), and nonsystemic treatment (adjusted OR= 1.602, 95% CI= 1.117–2.297) were found to be associated with exacerbation of psoriasis after SARS-CoV-2 infection, but not biologics (adjusted OR = 0.931, 95% CI = 0.680–1.274, compared to no treatment), according to multivariable logistic regression analysis. Conclusions::A reduced risk of psoriasis exacerbation after SARS-CoV-2 infection was observed with biologics compared to traditional systemic and nonsystemic treatments. Significant risk factors for exacerbation after infection were identified as existing psoriatic lesions and hypertension.

Objective:To explore the correlation of bone marrow polychonal plasma cell proportion (pPC% ) and clinical features in newly diagnosed multiple myeloma (NDMM) patients.Methods:A retrospective analysis of 317 patients with NDMM admitted to Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from January 2018 to January 2023 was performed. The results of the pPC% in all patients were clear. The relationship between the pPC% and clinical characteristics was analyzed.Results:A total of 317 patients were included, comprising 180 males and 137 females. The median age at diagnosis was 61 (26-91) years, and 55.8% were 60 years or older. The pPC% in the bone marrow of patients with NDMM was different in the DS, International Staging System (ISS), and revised ISS (R-ISS) stages ( P=0.002, 0.010, and 0.049, respectively), whereas no statistical difference in pPC% was observed among patients with different FISH risk stratigrams ( P=0.971). The correlation coefficient between pPC% and hemoglobin (HGB) at the first diagnosis in patients was 0.211 ( P<0.01). The correlation coefficients with serum calcium, serum creatinine, M protein level, and β 2-microglobulin were -0.141, -0.120, -0.181, and -0.207, respectively, and the results of the significance test were P=0.012, 0.033, 0.004, and 0.002, respectively, indicating a negative correlation. Compared with the patients with a pPC% of ≥2.5%, the group of patients with a pPC% of <2.5% had significantly higher levels of light chain, serum calcium, serum creatinine, M protein, and β 2-microglobulin at the initial diagnosis ( P<0.05) ; lower HGB level ( P<0.001) ; and a higher proportion of patients in ISS stage Ⅲ ( P=0.034) . Conclusion:In this study, the pPC% in patients with NDMM was associated with clinical features of good prognosis, including higher HGB, lower serum calcium, serum creatinine, M protein quantity, β 2-microglobulin, light chain involvement, lower proportion of advanced disease (DS stage and ISS stage Ⅲ), and clinical features showing lower tumor burden.

Objective:To investigate the relationship between body mass index(BMI) and osteoporosis using Mendelian randomization analysis.Methods:The genetic variation strongly related to BMI was selected as the instrumental variables in the collection data set of the genome-wide association study(GWAS). The MR-Egger regression, weighted median estimator(WME), inverse variance weighted(IVW), simple mode and weighted mode were used for Mendelian randomization(MR) analysis. The causal association between BMI and osteoporosis was evaluated by odds ratio and 95% confidence interval. The MR-APSS method was applied to make the causal inference results based on MR more reliable. The Linkage disequilibrium score regression was applied to evaluate the genetic correlation, and the horizontal pleiotropy test, heterogeneity test, and leave-one-out method were used to evaluate whether the results were reliable, The influence of heterogeneity and horizontal pleiotropy were reduced by the MR-PRESSO outlier test.Results:A total of 421 SNPs were included, with inverse variance-weighted method as the main analysis approach. The calculated OR value and 95% CI were 0.994(95% CI 0.992-0.997), indicating a protective effect of BMI on osteoporosis. The MR-APSS method showed that the effect of BMI on osteoporosis was statistically significant. Linkage disequilibrium score regression demonstrated a genetic correlation between BMI and osteoporosis. MR-Egger regression intercept showed no horizontal pleiotropy of instrumental variables, and the funnel plot showed no bias in instrumental variables. Leave-one-out analysis confirmed robust results. Conclusion:There may be a negative causal relationship between BMI and osteoporosis and BMI is a protective factor for osteoporosis.

Objective: To investigate the mechanism of action of Wuzi Yanzong pill (WYP) in rats with oligoasthenozoospermia (OAZ) via metabolomics and to provide a possible basis for improving this WYP-based treatment. Methods: A rat model of OAZ was established by treating male Sprague–Dawley rats with glucosides from Tripterygium wilfordii Hook. F. Seventy-two rats were randomly divided into six groups: control, L-carnitine (positive control), model, and low-, medium-, and high-dose WYP groups. Rats in the experimental groups were treated with WYP for 4 weeks. At the end of the treatment period, sperm cell quality (density, motility, and viability) was assessed using a semen analysis system, mitochondrial membrane potential (MMP) was assessed using flow cytometry, and testicular injury was assessed using hematoxylin and eosin staining to validate the therapeutic effect of WYP in OAZ. Further, serum metabolomics-based analysis was performed using high-performance liquid chromatography-mass spectrometry to identify differential metabolic pathways and possible mechanisms of action of WYP in OAZ treatment. Results: A rat model of OAZ was considered successfully-established after comparing the quality of spermatozoa in the model group to that in the control group. WYP-M and WYP-H treatments significantly improved sperm cell density, motility, and viability compared with those in the model group (all P < .05). Compared with the model group, both WYP-M and WYP-H treatments increased MMP values (P = .006 and P = .021 respectively), while there was no significant difference in the L-carnitine group. L-carnitine and WYP administration reversed damage to the testes to varying degrees compared with that in the model group. Further, 44 differential metabolites and four metabolic pathways, especially autophagy pathway, related to OAZ were identified via metabolomics. Conclusions WYP improves sperm cell quality and MMP in OAZ primarily via autophagy regulation. These findings can be employed to improve the efficacy of WYP in humans.

Objective:To investigate the differences in programmed death-ligand 1 (PD-L1) expression and immune cell infiltration characteristics in different molecular subtypes of endometrial cancer.Methods:A retrospective case series study was conducted. Ninety primary treated EC patients who underwent surgery without preoperative neoadjuvant therapy at the Second Hospital of Tianjin Medical University from November 2016 to May 2022 were collected. The surgical paraffin-embedded tissues were selected, and the molecular subtypes of endometrial cancer were classified according to 2020 World Health Organization (WHO) molecular subtypes using POLE gene Sanger sequencing and immunohistochemical staining. The expression of PD-L1, CD3, CD4, CD8, CD68, and CD20 proteins were detected by immunohistochemistry. Stained slides were digitally scanned for quantitative analysis of PD-L1 and immune cell infiltration density. The PD-L1-related scores were evaluated, including tumor cell score (TCS, the percentage of PD-L1 positive tumor cells among total tumor cells ≥1% was TCS positive, <1% was TCS negative), immune cell score (ICS, the percentage of PD-L1 positive tumor-associated lymphocytes and macrophages among total tumor-associated lymphocytes and macrophages ≥1% was ICS positive, <1% was ICS negative) and combined positive score [CPS, PD-L1 positive stained cells (including tumor cells, lymphocytes and macrophages)/total number of viable tumor cells ×100 ≥ 1 was CPS positive, < 1 was CPS negative]. Clinicopathological characteristics, PD-L1 scores and immune cell infiltration densities among different molecular subtypes were analyzed. Kaplan-Meier method was used to plot disease-free survival (DFS) curves for molecular subtypes, PD-L1 scores and immune cell infiltration densities, with subgroup comparisons using log-rank test. Cox proportional hazards models were used for univariate and multivariate analyses of poor DFS in endometrial cancer patients.Results:The median age of 90 patients was 58 years old (range: 33-72 years old); endometrioid carcinoma was present in 78 cases (86.7%), and non-endometrioid carcinoma was present in 12 cases (13.3%). Molecular subtyping identified POLE-mutated subtype in 6 cases (6.7%), mismatch repair deficient (MMRd) subtype in 23 cases (25.6%), p53 abnormal subtype in 14 cases (15.6%), and non-specific molecular profile (NSMP) subtype in 47 cases (52.2%). Significant differences were observed among the 4 molecular subtypes in International Federation of Gynecology and Obstetrics (FIGO) stage, histological grade, morphological subtype, tertiary lymphoid structures, estrogen receptor expression, and progesterone receptor expression (all P < 0.05). Among the 90 cases, 18 cases (20.0%) were positive for TCS, 31 cases (34.4%) were positive for ICS, and 39 cases (43.3%) were positive for CPS. Significant differences were found among the 4 molecular subtypes in PD-L1 + cell density, distribution of patients with ICS positivity, and distribution of patients with CPS positivity (all P < 0.01), but not in distribution of patients with TCS positivity ( P = 0.090); compared to NSMP subtype, the proportions of ICS-positive patients in POLE-mutated and MMRd subtypes were higher, the proportion of CPS-positive patients and PD-L1 + cell density in MMRd and p53 abnormal subtypes were higher, and the differences were statistically significant (all P < 0.05). Significant differences in immune cell densities were observed among the 4 molecular subtypes (all P < 0.01); compared to NSMP subtype, POLE-mutated, MMRd and p53 abnormal subtypes had higher densities of CD3 + and CD8 + cells, MMRd subtype had higher CD4 + cell density, and POLE-mutated and MMRd subtypes had higher CD68 + and CD20 + cell densities (all P < 0.05). The median follow-up was 43 months (range: 7-75 months). Among the molecular subtypes, p53 abnormal patients had the worst DFS, and POLE-mutated patients had the best DFS, and the difference in DFS among the 4 subtypes was statistically significant ( P = 0.046). Grouping according to the median density of immune cells in the entire group, patients with high CD8 + cell density (45 cases) had better DFS than those with low density (45 cases) ( P = 0.010), PD-L1 ICS-positive patients had worse DFS than negative patients ( P = 0.019), and NSMP subtype patients with high CD4 + cell density (24 cases) had better DFS than those with low density (23 cases) ( P < 0.001). There was no statistically significant difference in DFS among patients grouping with other PD-L1 scoring modes and other immune cell infiltration density (all P > 0.05). Cox regression analysis indicated that high CD8 + cell density ( HR = 0.335, 95% CI: 0.113-0.990, P = 0.048) was an independent protective factor for poor DFS in endometrial cancer patients, and high CD4 + cell density was an independent protective factor for poor DFS in NSMP subtype patients ( HR = 0.035, 95% CI: 0.003-0.345, P = 0.004). Conclusions:There are significant differences in PD-L1 expression and immune cell infiltration density among the different molecular subtypes of endometrial cancer, which are correlated with the prognosis of patients, and may provide reference for the selection of immunotherapy strategies and prognosis judgment.