ObjectiveTo investigate the imaging features of calcium salt deposition and serological markers in patients with alveolar echinococcosis through a retrospective analysis， as well as independent risk factors for the degree of calcium salt deposition in lesions， and to provide a basis for assessing disease process. MethodsA retrospective analysis was performed for the imaging and clinical data of 107 patients with alveolar echinococcosis who were admitted to The First Affiliated Hospital of Shihezi University from December 2023 to June 2025， and according to the volume of calcium salt deposition， they were divided into non-deposition group with 16 patients， mild deposition group with 52 patients， moderate deposition group with 16 patients， and severe deposition group with 23 patients. A one-way analysis of variance or the Kruskal-Wallis H test was used for comparison of continuous data between groups， and the χ² test or Fisher’s exact test was used for comparison of categorical data between groups. The four groups were further combined into the low deposition group （no/mild deposition） and the high deposition group （moderate/severe deposition）. A binary logistic regression analysis was used to investigate the independent influencing factors for calcium salt deposition， and a predictive model was established. The receiver operating characteristic （ROC） curve was used to assess the predictive performance of the model， and the Bootstrap method was used for internal validation. ResultsThere were significant differences between the four groups in sex distribution， involvement of other sites， white blood cell count， lymphocyte percentage， fibrinogen， uric acid， sodium ion， chloride ion， and calcium ion （all P<0.05）. The univariate analysis showed that there were significant differences between the four groups in sex， involvement of other sites， white blood cell count， lymphocyte percentage， fibrinogen， alanine aminotransferase， albumin， creatinine， uric acid， sodium ion， chloride ion， and calcium ion （all P<0.1）. The multi-collinearity diagnosis showed that the VIF values for all continuous variables ranged from 1.104 to 1.760， suggesting that collinearity did not affect modeling. An ordinal logistic regression model was established based on sex， involvement of other sites， calcium ion， lymphocyte percentage， and uric acid. The multivariate analysis showed that lymphocyte percentage （odds ratio ［OR］=1.106， 95% confidence interval ［CI］： 1.041 — 1.174， P=0.001） and blood calcium level （OR=0.005， 95%CI： 0.000 —0.230， P=0.007） were independent influencing factors for the degree of calcium salt deposition. The regression equation was established as Logit（P）=8.231 + 0.100 × lymphocyte percentage -5.344 × calcium ion. The ROC curve analysis showed that the model had an area under the ROC curve of 0.716， with a Youden index of 0.353， a sensitivity of 1.000， and a specificity of 0.353. The Hosmer-Lemeshow test showed that the model had poor calibration （χ²=20.688， P=0.008）. The Bootstrap method with 1000 repeated samples showed that the estimated values of lymphocyte percentage （OR=1.106， 95%CI： 1.049 — 1.186， P=0.002） and calcium ion （OR=0.005， 95%CI： 0.000 — 0.214， P=0.010） were consistent with the original model， and the confidence intervals did not include 1， which further supported the reliability of the model. ConclusionBoth lymphocyte percentage and blood calcium level are independent influencing factors for calcium salt deposition in alveolar echinococcosis， and the degree of calcium salt deposition in alveolar echinococcosis lesions increases with the reduction in blood calcium level and the increase in lymphocyte percentage.

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.

ObjectiveTo study the changing law of appearance color and physicochemical properties of Angelicae Sinensis Radix Carbonisata（ASRC） during the processing by color space method combined with statistical analysis， so as to provide reference for determining the processing endpoint and evaluating the quality of the decoction pieces. MethodsTaking processing time（4， 8， 12， 16 min） and temperature（180， 200， 220， 240 ℃） as factors， ASRC decoction pieces with different processing degrees were prepared in a completely randomized design. Then， the brightness value（L^*）， red-green value（a^*）， yellow-blue value（b^*）， and total chromaticity value （E^*ab） of the decoction pieces were determined by spectrophotometer， the color difference value（ΔE） was calculated， and the data of colorimetric values were analyzed by discriminant analysis. At the same time， the pH， charcoal adsorption， and contents of tannins， 5-hydroxymethylfurfural（5-HMF）， tryptophan， chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H and ligustilide of ASRC with different processing degrees were determined by pH meter， ultraviolet and visible spectrophotometry and ultra-high performance liquid chromatography（UPLC）. Principal component analysis（PCA） was used to analyze the data of physicochemical indexes， after determining the processing technology of ASRC， the canonical discriminant function was established to distinguish the decoction pieces with different processing degrees， and leave-one-out cross validation was conducted. Finally， Pearson correlation analysis was used to explore the correlation between various physicochemical indexes and chromaticity values. ResultsWith the prolongation of the processing time， L^*， a^*， b^* and E^*ab all showed a decreasing trend， and the established discriminant model based on color parameters was able to distinguish ASRC with different processing degrees. The pH showed an increasing trend with the prolongation of processing time， and the charcoal adsorption， and the contents of tannins， 5-HMF， and tryptophan all showed an increasing and then decreasing trend. Among them， the charcoal adsorption， contents of tannin and 5-HMF reached their maximum values successively after processing for 8-12 min. While the contents of chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H and ligustilide decreased with the increase of processing time， with a decrease of 60%-80% at 8 min of processing. Therefore， the optimal processing time should be determined to be 8-12 min. PCA could clearly distinguish ASRC with different processing degrees， while temperature had no significant effect on the processing degree. The 12 batches of process validation results（10 min， 180-240 ℃） showed that except for 3 batches identified as class Ⅱ light charcoal， all other batches were identified as class Ⅲ standard charcoal， and the chromaticity values of each batch of ASRC were within the reference range of class Ⅱ-Ⅲ sample chromaticity values. The correlation analysis showed that the chromaticity values were negatively correlated with pH and charcoal adsorption， and positively correlated with contents of tryptophan， chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H， and ligustilide. And both pH and charcoal adsorption were negatively correlated with the contents of the above components， but the charcoal adsorption was positively correlated with the content of 5-HMF. ConclusionThe chromaticity values and the contents of various physicochemical indicators of ASRC undergo significant changes with the prolongation of processing time， and there is a general correlation between chromaticity values and various physicochemical indicators. Based on the changes in color and physicochemical indicators， the optimal processing time for ASRC is determined to be 8-12 min. This study reveals the dynamic changes of the relevant indexes in the processing of ASRC， which can provide a reference for the discrimination of the processing degree and the quantitative study of the processing endpoint.

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics.Similarities and variations of components present significant analytical challenges.A two-dimensional(2D)liquid chromatography-mass spectrometry(LC-MS)method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium(CMS).A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated.For efficient and high-accuracy screening of CMS,a targeted method based on a self-constructed high resolution(HR)mass spectrum database of CMS components was established.The database was built based on the commercial MassHunter Personal Compound Database and Library(PCDL)software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening.On this basis,the unknown peaks in the CMS chromatograms were deduced and assigned.The molecular formula,group composition,and origins of a total of 99 compounds,of which the combined area percentage accounted for more than 95％of CMS components,were deduced by this 2D-LC-MS method combined with the MassHunter PCDL.This profiling method was highly efficient and could distinguish hundreds of components within 3 h,providing reliable results for quality control of this kind of complex drugs.

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*

BACKGROUND: Hypertension is associated with an increased risk of calcific aortic valve stenosis (CAVS). However, the directionality of causation between blood pressure traits and aortic stenosis is unclear, as is the benefit of antihypertensive drugs for CAVS. METHODS: Using genome-wide association studies (GWAS) summary statistics, we performed bidirectional two-sample univariable mendelian randomization (UVMR) to assess the causal associations of systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) with CAVS. Multivariable mendelian randomization (MVMR) was conducted to evaluate the direct effect of hypertension on CAVS, adjusting for confounders. Drug target mendelian randomization (MR) and summary-level MR (SMR) were used to estimate the effects of 12 classes of antihypertensive drugs and their target genes on CAVS risk. Inverse variance weighting was the primary MR method, with sensitivity analyses to validate results. RESULTS: UVMR showed SBP, DBP, and PP have causal effects on CAVS, with no significant reverse causality. MVMR confirmed the causality between hypertension and CAVS after adjusting for confounders. Drug-target MR analyses indicated that calcium channel blockers (CCBs), loop diuretics, and thiazide diuretics via SBP lowering exerted protective effects on CAVS risk. SMR analysis showed that the CCBs target gene CACNA2D2 and ARBs target gene AGTR1 were positively associated with CAVS risk, while diuretics target genes SLC12A5 and SLC12A1 were negatively associated with aortic stenosis risk. CONCLUSIONS Hypertension has a causal relationship with CAVS. Managing SBP in hypertensive patients with CCBs may prevent CAVS. ARBs might exert protective effects on CAVS independent of blood pressure reduction. The relationship between diuretics and CAVS is complex, with opposite effects through different mechanisms.

Objective:To develop a predictive model for selecting patients with high-risk localized prostate cancer(HRLPC)who are suitable for preoperative maximum androgen blocking(MAB)therapy.Methods:This study was conducted among 96 patients with HRLPC who were diagnosed based on transrectal biopsy and underwent radical prostatectomy in Department of Urology,The First Af-filiated Hospital of Chongqing Medical University,from January 1,2021 to June 30,2024,and all patients received MAB therapy for 3 months before surgery and were followed up for 6 months after surgery.Related data were collected from all patients,including baseline demographic features,laboratory data,imaging findings,perioperative data,and follow-up information.At first,the association between prostate-specific antigen density(PSAD)stratification after MAB therapy and pathological and biochemical benefits was analyzed to determine the optimal PSAD group,then machine learning was used to identify important variables and establish a predictive model,and finally,the model was evaluated using the ROC curve,the calibration curve,and clinical applicability assessment.Results:The low PSAD group[PSAD<0.17 ng/(mL·cm3)]showed the best results of perioperative outcomes,pathological downgrading,the rate of undetectable PSA after-surgery,recovery from urinary incontinence,and PSA follow-up(P<0.05).The model was established based on prostate volume,low-density lipoprotein cholesterol,PSAD,smoking history,total cholesterol,PSA,and body mass index,and this predictive model had good performance(with an area under the ROC curve of 0.769)and showed a certain degree of clinical applica-bility.Conclusion:Patients in the low PSAD group tend to have better pathological and biochemical benefits.This study provides a re-liable predictive model to assist in the individualized treatment of patients with HRLPC.

Objective To analyze the lipid metabolism levels in patients with non-functional adrenal in-cidentalomas(NFAI)and the efficacy of different treatment approaches.Methods A retrospective analysis was conducted on the clinical data,including clinical manifestations,metabolism-related diseases,lipid metabo-lism levels,and hormone levels,of 114 patients diagnosed with NFAI who sought medical attention at this hospital from September 2021 to June 2024.The patients were divided into the surgical group(receiving surgi-cal treatment)and the non-surgical group(receiving conservative treatment).The surgical group was further categorized into the normal lipid group and the dyslipidemia group based on preoperative lipid levels.Changes in lipid metabolism levels before and after treatment were compared between the surgical and non-surgical groups,as well as between the normal lipid and dyslipidemia groups,to evaluate the impact of NFAI on lipid metabolism.Results Among the 114 patients,76 were divided into the surgical group and 38 into the non-sur-gical group.The surgical group was further divided into 36 patients in the normal lipid group and 40 in the dyslipidemia group.In the surgical group,triglycerides(TG)and low-density lipoprotein(LDL)levels de-creased significantly after treatment compared to pre-treatment levels(P=0.007,0.002).In contrast,no sta-tistically significant difference was observed in the non-surgical group between pre-and post-treatment TG and LDL levels(P＞0.05).Compared with the non-surgical group,the surgical group showed a greater reduc-tion in TG and LDL levels before and after treatment(P=0.049,0.002).In the dyslipidemia group,TG and LDL levels returned to normal levels after treatment and significantly decreased compared to those before treatment,with statistical significance(P=0.007,0.001).However,in the normal lipid group,there was no statistically significant difference in TG and LDL levels before and after treatment(P=0.640,0.499).Com-pared with the normal lipid group,the dyslipidemia group showed a greater reduction in TG and LDL levels before and after treatment(P＜0.001,P=0.022).The final pathological results of patients in the surgical group included 59 cases of cortical adenoma,6 cases of cyst,7 cases of myelolipoma,and 4 cases of nodular hy-perplasia.In patients with cortical adenoma,the postoperative TG and LDL levels significantly decreased com-pared to those before surgery(P=0.008,0.014),while there was no statistically significant difference in TG and LDL levels before and after treatment in patients with cysts,myelolipomas,and nodular hyperplasia(P＞0.05).Conclusion NFAI may adversely affect lipid metabolism and is associated with elevated TG and LDL-C levels.Compared with conservative treatment,surgical resection can significantly reduce the body's TG and LDL levels and effectively improve abnormal lipid metabolism.

OBJECTIVES: To construct a nomogram for predicting the efficacy of immune checkpoint inhibitors (ICIs) in advanced non-small cell lung cancer (aNSCLC) by integrating chest CT radiomics signature that reflects the tumor microenvironment (TME) and clinical parameters of the patients. METHODS: Transcriptomic and CT imaging data from TCGA, GEO and TCIA databases were integrated for weighted gene co-expression network analysis (WGCNA) of the GEO cohort to identify the immunotherapy-related genes (IRGs) associated with ICIs response. A prognostic model was built using these IRGs in the TCGA cohort to assess immune microenvironment features across different risk groups. Radiomics features were extracted from TCIA lung_3 cohort using PyRadiomics, and 94 features showing strong association with IRGs (|r|>0.4) were selected. A retrospective cohort consisting of 210 aNSCLC patients receiving first-line ICIs at Guangdong Provincial People's Hospital was analyzed and divided into training (n=147) and validation (n=63) groups. Least absolute shrinkage and selection operator was used for radiomic features selection, and logistic regression was applied to construct a combined clinical-radiomic model and nomogram for predicting ICIs therapy response. The performance of the model was evaluated using ROC curve, calibration curve, and decision curve analysis. RESULTS: WGCNA identified 84 IRGs enriched in immune activation pathways. The combined model outperformed individual models in both the training (AUC=0.725, 95% CI: 0.644-0.807) and validation cohorts (AUC=0.706, 95% CI: 0.577-0.836). Calibration curve and decision curve analyses confirmed the clinical efficacy of the nomogram for predicting ICIs therapy response in aNSCLC patients. CONCLUSIONS The genomic-radiomic-clinical multidimensional predictive framework established in this study provides an interpretable biomarker combination and clinical decision-making tool for evaluating ICIs efficacy in aNSCLC, potentially facilitating personalized immunotherapy decision-making.
Humans ; Carcinoma, Non-Small-Cell Lung/therapy* ; Tumor Microenvironment ; Lung Neoplasms/therapy* ; Immunotherapy ; Tomography, X-Ray Computed ; Nomograms ; Retrospective Studies ; Immune Checkpoint Inhibitors/therapeutic use* ; Prognosis ; Male ; Female ; Radiomics