To analyze the correlation of cholecystectomy and changes in intestinal microbiota composition and function by observing functional characteristics of differential microbial communities.

A cross-sectional study was conducted on the patients (PC group, n=73) undergoing cholecystectomy in our hospital from 2020 to 2021. Another 56 healthy age- and gender-matched individuals (HC group) without a history of cholecystectomy were subjected and served as the control group. Fecal specimens were collected from the 2 groups. 16S rRNA sequencing analysis was performed to examine the changes in composition and function of intestinal microbiota.

There were no statistical differences between the 2 groups in baseline indicators, such as gender, age, BMI, smoking and drinking history, blood pressure, heart rate, and comorbidities, but significant difference was observed in total bilirubin (TBIL) between them (P<0.01). Alpha diversity analysis showed no significant difference in Chao1, Shannon, and Simpson indices between the 2 groups. Beta diversity analysis using the Bray-Curtis distance algorithm revealed a significant difference between the 2 groups at the class and genus levels (P<0.05). The analysis of microbiota relative abundance using LEFSE showed that Enterobacteriaceae, Lactobacillales, Citrobacter, Megasphaera, Lactobacillus, Enterococcus, Akkermansia, Streptococcus, Klebsiella, and Ruminococcus_gnavus were up-regulated in the PC group, and Lachnospiraceae, Sutterellaceae, Lachnospirales, Lachnospira, and Sutterella were down-regulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional prediction analysis indicated that significant differences were seen between the 2 groups in metabolic pathways, including ascorbic acid (vitamin C) metabolism and aldonic acid metabolism (P<0.05), tricarboxylic acid cycle (TCA cycle) (P<0.05), glutathione metabolism (P<0.05), glutamic acid metabolism (P<0.05), secondary bile acid metabolism (P<0.05), and pentose phosphate pathway (P<0.01).

Cholecystectomy is closely associated with the structural alterations in the composition of intestinal microbiota. Variations in microbiota composition and function may induce perturbations in TCA cycle and glutathione metabolism, glutamate metabolism, secondary bile acid metabolism, and pentose phosphate pathways.

To investigate the diversity and composition of gut fungi microbiota in patients with polycystic kidney disease (PKD) and its correlation with clinical indicators.

A total of 44 PKD patients, 44 patients with non-polycystic chronic kidney disease (NPCKD) and 22 healthy controls (HC) admitted to our hospital from February 2023 to February 2024 were recruited. ITS1 DNA sequencing was applied to analyze the gut fungal composition. Bioinformatics analysis was used to compare the diversity and structural differences of fungi among the 3 groups. Pearson correlation analysis was performed to analyze the relationship between gut fungi and clinical indicators.

There were no significant differences in baseline characteristics (gender, age, body mass index, etc.) among the 3 groups, but statistical differences were seen in terms of serum indicators (such as serum creatinine, blood urea nitrogen, uric acid, estimated glomerular filtration rate, etc.) (P<0.01). Alpha diversity analysis showed no significant difference was seen between the PKD and HC groups, but the PKD group had significant differences to the NPCKD group (P<0.01). Beta diversity analysis revealed significant differences among the 3 groups and in pairwise comparisons (P=0.001). Fungi composition analysis found that the abundance of Candida was significantly higher in the PKD group than the other 2 groups (P<0.01), while the abundances of Aspergillus and Cladosporium were significantly lower in the PKD group than the HC group (P<0.05). Linear discriminant analysis (LEFSe) indicated that Candida was significantly enriched, while Aspergillus and Cladosporium were significantly reduced in the PKD group. Correlation analysis revealed that the abundance of Cladosporium was negatively correlated with cyst diameter and immunoglobulin light chain Kappa/Lambda ratio in the PKD group (P<0.05), while the abundance of Candida was positively correlated with liver/kidney cyst diameter (P<0.01).

PKD patients exhibit characteristic changes in gut fungi diversity and composition. The abundances of Cladosporium and Candida are closely associated with clinical indicators of PKD patients.

To investigate the predictive value of combined radiomic features derived from chest CT scans with clinical characteristics for epidermal growth factor receptor (EGFR) gene mutations in non-small cell lung cancer (NSCLC).

A multi-center case-control study was conducted on the clinical data and CT images of 1 070 NSCLC patients from the radiology departments of the 3 medical institutions between January 2013 and October 2023. The 719 NSCLC patients from the First Affiliated Hospital of Army Medical University were randomly divided into a training set and an internal validation set in a ratio of 7∶3; The 173 patients in the Eastern Theatre General Hospital and the 178 patients in Army Medical Centre of PLA were assigned into the external validation set 1 and 2, respectively. Least absolute shrinkage and selection operator (LASSO) regression was employed to identify the optimal radiomic features, which were subsequently used to construct a radiomics model. Univariate and multivariate logistic regression analyses were applied to identify clinical features associated with EGFR mutation, thereby developing a clinical model. The radiomic and clinical features were subsequently combined to develop a comprehensive model. All the 3 classification models were built using random forest (RF) machine learning. The area under curve (AUC), accuracy, sensitivity and specificity were utilized to evaluate the predictive performance of the models. Calibration curve was plotted to assess the goodness of fit of the comprehensive model, while decision curve analysis was performed to assess the clinical utility of the model.

The AUC value of the radiomics model was 0.762 4 (95%CI: 0.692 4~0.825 1), 0.745 4 (95%CI: 0.671 1~0.814 3), and 0.724 7 (95%CI: 0.639 7~0.801 6), respectively, in the internal validation set, external validation set 1, and external validation set 2; The AUC value of the clinical prediction model was 0.691 7 (95%CI: 0.627 9~0.757 6), 0.652 5 (95%CI: 0.576 7~0.729 1), and 0.779 2 (95%CI: 0.712 5~0.847 3), respectively in the above sets in turn; The comprehensive model constructed based on clinical features and radiomic features showed the best predictive efficacy, with an AUC value of 0.818 0 (95%CI: 0.757 7~0.874 3), 0.782 4 (95%CI: 0.703 1~0.848 2), and 0.796 6 (95%CI: 0.718 1~0.868 6), respectively in the above sets. Calibration curve analysis indicated that the comprehensive model had a good fit, while decision curve analysis revealed that the model provided a favorable net benefit.

Our comprehensive model constructed based on chest CT radiomic features and clinical characteristics shows superior predictive performance for EGFR gene mutations in NSCLC across multiple center datasets, which may be helpful for clinical decision-making for treatment strategies.

To compare the gut fungal composition between gout patients and healthy individuals through high-throughput sequencing of ribosomal DNA internal transcribed spacer 1 (ITS1).

Gout patients and healthy volunteers who visited our hospital from January 2023 to December 2024 were enrolled in this study. Then based on established medical guidelines, the gout patients were categorized into 3 groups: Group H (asymptomatic hyperuricemia, n=14), Group G (acute gouty arthritis, n=14), and Group I (intercritical period of gouty arthritis, n=15), and the healthy individuals were assigned into Group N (n=9). Fecal samples were collected from all the participants to undergo ITS1 sequencing analysis. The differences in diversity and composition of gut mycobiome, and FunGuild-derived fungal functions and nutritional status were compared among the 4 groups, and the correlation between the gut mycobiome and clinical indicators was analyzed.

There were no significant differences in baseline features such as gender, age, glomerular filtration rate (GFR), and levels of serum creatinine (SCr) and serum urea among Group N and other gout groups, but obvious differences were observed in body mass index (BMI), erythrocyte sedimentation rate, and levels of C-reactive protein (CRP), serum uric acid (SUA), and IL-1β and IL-6 (P<0.05). In terms of gut fungal diversity, ITS1 analysis showed there were no statistical differences in α-diversity or the principal coordinate analysis (PCoA) of β-diversity among the groups. However, as gout progressed, significant changes were observed in β-diversity indices, indicating a shift in the gut fungal community composition with disease advancement (P<0.05). The phyla Ascomycota, Basidiomycota, and Mucoromycotina were the dominant fungal phyla in all groups. Compared with the other 3 gout groups, the abundance of Pichia was significantly increased in Group N (P<0.05), that of Saccharomyces was in Group H (P<0.05), and that of Starmerella was in Group G (P<0.05). Correlation analysis between the gut mycobiome and clinical indices indicated that the relative abundance of Starmerella was significantly positively correlated with IL-1β (P<0.01) and IL-6 (P<0.05).The relative abundance of Pichia was significantly positively correlated with IL-1β and IL-6 levels (P<0.05), and negatively correlated with serum urea level (P<0.05), and the relative abundance of Saccharomyces was negatively correlated with IL-1β and IL-6 levels (P<0.05).

There exist significant alterations in both the diversity and composition of gut fungi among patients with gout at various stages. Notably, the fluctuations in the relative abundance of Starmerella, Pichia and Saccharomyces appear to correlate with key clinical indicators.

To explore the value of preoperative ultrasound examination in the prediction of restenosis of arteriovenous fistula (AVF) after percutaneous transluminal angioplasty (PTA) in hemodialysis patients.

A case-control trial was conducted on 225 hemodialysis patients who undergoing PTA due to AVF in our hospital January 2023 to May 2024. After 3 months of follow-up, they were divided into a patency group (n=204) and a restenosis group (n=21) according to the occurrence of postoperative restenosis. The preoperative clinical data and ultrasound parameters were compared between the groups. Binary logistic regression analysis was used to identify the independent factors for AVF restenosis after PTA. Receiver operating characteristic (ROC) curve was drawn to evaluate the value of preoperative stenosis length in the prediction of the restenosis after PTA.

There were significant differences in preoperative internal diameter at the site of stenosis, stenosis length, stenosis number, intimal thickness, and brachial artery flow between the 2 groups (P<0.05). Preoperative stenosis length (OR=1.856, 95%CI: 1.350~2.552, P<0.001) was an independent factor of AVF restenosis in hemodialysis patients after PTA. ROC curve analysis showed that the area under the curve of preoperative stenosis length in predicting restenosis after PTA was 0.868 (95%CI: 0.784~0.953, P<0.001), with a sensibility and specificity of 85.7% and 80.4%, respectively.

Preoperative stenosis length may be an independent factor for AVF restenosis after PTA in hemodialysis patients.

To develop a new biological age model based on the National Health and Nutrition Examination Survey (NHANES) database and evaluate its predictive performance for mortality outcomes.

After excluding pregnant women and those with incomplete clinical data, a total of 8 234 participants aged 20~79 years from NHANES 2007-2010 were included and assigned into a testing set, and another 17 522 non-pregnant participants （17~79 years old） subjected from NHANESⅢ were enrolled and served as a training set to construct the new biological age (new Bioage) model. Multiple linear regression was used to construct models for new Bioage and age-adjusted biological age (new-agefixed Bioage), and other types of biological ages were calculated. Pearson correlation analysis was performed to assess the correlation between biological age and chronological age. Based on new-agefixed Bioage, biological age acceleration was calculated, and then according to the results, the participants were divided into accelerated biological aging group (biological age acceleration ≥0, n=3 884) and decelerated biological aging group (biological age acceleration <0, n=4 350). Weighted data comparisons were conducted using the survey package in R, and Cox regression analysis was used to assess the impact of biological age acceleration on the mortality of the participants. Receiver operating characteristic (ROC) curve was plotted to determine the effect of new-agefixed Bioage and biological age acceleration on the area under the curve (AUC) for the mortality.

The new-agefixed Bioage model, composed of 9 variables, had the highest AUC value (AUC=0.889 2, P<0.001) in predicting mortality outcomes and showed high correlation with chronological age and other biological ages. The decelerated biological aging group had significantly larger proportions of males, whites, education level of high school or higher, middle to high household income, married (or with a partner), engaging in physical activity, having private insurance, and cancer (P<0.05), lower BMI, slower biological age acceleration level, and less proportions of smokers, hypertension, diabetes, cardiovascular disease, and chronic obstructive pulmonary disease when compared with the accelerated biological aging group (P<0.05). Cox regression analysis indicated that, compared to the decelerated biological aging group, the accelerated biological aging group had a significantly increased risk of mortality in Model3 [adjust for age group, gender, race, BMI, education level, household income, married (or with a partner), smoking status, heavy alcohol consumption, insurance status, physical activity, hypertension, diabetes, cardiovascular disease, chronic obstructive pulmonary disease, and cancer](HR=1.62, 95% CI: 1.28-2.06, P<0.001). ROC curve analysis revealed that new-agefixed Bioage significantly increased the AUC values (AUC=0.781, P<0.001; AUC=0.731, P<0.001) for middle-aged and elderly populations, while biological age acceleration significantly improved the AUC values (AUC=0.756, P<0.001) for the middle-aged population.

The new-agefixed Bioage model demonstrates high correlation with chronological age and other biological ages, and has good predictive performance for mortality outcomes, particularly in middle-aged and elderly populations.

To revise the Inventory of Alienation Toward Parents (IAP) and test its reliability and validity in a military population in order to provide a scientific tool for assessing the level and grade of parent-child alienation among military personnel.

Whole-cluster stratified random sampling was used to subject 8 641 service members from 8 Army units. Then all participants were surveyed with 18-item adolescent IAP, Beck Depression Inventory-Ⅱ, and Generalized Anxiety Disorder-7. SPSS 27.0 and AMOS 26.0 were used to perform item analysis, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA) to assess reliability and validity. Subsequently, our revised 16-item version of IAP was employed to develop means, percentiles, cut-off scores, and category norms.

①Items 3 and 12 were deleted in item analysis. ②EFA extracted the original communication and emotional distance factors; CFA indicated that the two-factor model had good fitness, with the mother-child alienation scale: χ²/df=4.248, comparative fit index (CFI)=0.962, Tucker-Lewis index (TLI)= 0.929, root mean square error of approximation(RMSEA)= 0.028, standardized root mean squared residual (SRMR)=0.023; while the father-child alienation scale: χ²/df=5.41, CFI=0.939, TLI=0.901, RMSEA=0.032, SRMR=0.044. ③The internal consistency reliability of the total IAP was good (0.744~0.888). ④The total IAP score and scores of the mother-child and father-child subscales were positively correlated with depression and anxiety (r=0.395~0.493, P<0.01). ⑤ The average total IAP score for military personnel was 17.27±4.21, and the scores of mother-child alienation and father-child alienation were 8.64±2.26 and 8.62±2.43, respectively. With percentiles of P₇₅ and P₉₀ as the cut-off points, the total IAP score can be stratified into 3 levels, that is, normal (≤16), moderate (17~19), and severe (≥20). Then, additional category norms were developed based on demographic characteristics.

Our revised 16-item military version of IAP shows good reliability and validity. A preliminary and representative norm is developed primarily, and can be used to assess the level and grade of military parental alienation.

To investigate the protective effect and mechanism of heat acclimation (HA) on electromagnetic field (EMF) induced hippocampus neuron injury in mice.

Forty healthy BALB/c male mice (18~22 g, 7 weeks old) were randomly divided into 4 groups (n=10): Control group (Con), HA group (34 ℃, 30 d), EMF group (2 450 MHz, 20 min/d, 4 weeks) and HA+EMF group (HA preconditioning+EMF). Sucrose preference test was performed to evaluate sucrose preference levels of mice in each group. Tail suspension test and forced swimming test were utilized to observe the immobility time. Morris water maze test was conducted to determine the learning and memory capabilities. Pathological changes in the hippocampus were observed with HE staining. Immunohistochemical assay for Iba1 (marker of microglia), CD68 (marker of pro-inflammatory phenotype) and CD206 (marker of anti-inflammatory phenotype) were used to detect the number and activation phenotype of microglia in the hippocampus. ELISA was applied to measure the levels of TNF-α, IL-1β, TGF-β and IL-10 in the hippocampus of each group. Western blotting was performed to determine the protein levels of HSP70 in the hippocampus.

As compared with the Con group, the EMF group showed a decreased preference for sucrose (P<0.05), prolonged immobile time in the tail suspension test (P<0.01) as well as in the forced swimming test (P<0.01), extented escape latency on the 7th day (P<0.01), and a decreased time of crossing the platform (P<0.05). EMF exposure resulted in that the hippocampal neurons were in disordered arrangement, loose structure and irregular morphology, with swollen cytoplasm and condensed nuclei, swollen and more microglial cells in the hippocampus (P<0.01), and enhanced relative fluorescence intensity of CD68 (P<0.01), but not in CD206 fluorescence intensity (P=0.885). All these findings suggested that activated microglia predominantly exhibited a pro-inflammatory M1 phenotype during this phase. In the hippocampus, the levels of TNF-α and IL-1β were significantly increased, while the levels of IL-10 and TGF-β were significantly decreased (P<0.01).HA treatment reversed the conditions induced by EMF exposure, including better preference for sucrose (P<0.01), shorten immobile time in tail suspension test (P<0.05) and forced swimming test (P<0.01), less escape latency on the 7th day (P<0.01), and improved hippocampal cell injuries. Compared with the Con group, there were more microglial cells in the hippocampus in the HA+EMF group, with increased relative fluorescence intensity of M2 phenotype marker CD206 (P<0.01) and decreased CD68 fluorescence intensity (P<0.01). HA treatment also significantly decreased the expression of TNF-α and IL-1β levels (P<0.01), increased the expression of IL-10 and TGF-β (P<0.01), and elevated the protein level of HSP70 (P<0.01) when compared with the EMF group.

HA may ameliorate EMF-induced hippocampus neurons injury in mice by altering the phenotype of activated microglia and inhibiting inflammatory responses.

To investigate the role and underlying mechanism of spermidine (SPD) in intracerebral hemorrhage (ICH).

Male C57BL/6 mice were subjected to establish a collagenase-induced ICH model. The 108 mice were randomly divided into Sham group, ICH group and ICH+SPD group (intraperitoneal injection of 15 mg/kg SPD for 3 consecutive days after modeling), with 36 mice in each group. On the 3rd day after ICH, neurological deficits were evaluated using modified Garcia scoring and forelimb placing test; brain pathological damage was assessed with HE staining; activation of microglia/macrophages (Iba-1) and astrocytes (GFAP) was detected by immunofluorescence assay; expression of autophagy markers (Beclin-1, P62) and inflammatory factors (MMP-9, NLRP3, COX-2) was measured with Western blotting. In in vitro experiments, hemin was used to stimulate HT-22 cells to mimic ICH. The HT-22 cells were randomly divided into Control group, Hemin group, Hemin+SPD group, and Hemin+SPD+3-methyladenine (3-MA, an autophagy inhibitor) group (n=7). After 24 h of hemin treatment, cell viability was detected with CCK-8 assay, the expression of autophagy-related proteins (LC3-II and P62) were detected with Western blotting, and oxidative stress was determined by measuring superoxide dismutase (SOD) activity and malondialdehyde (MDA) content.

On day 3 post-ICH, SPD significantly reduced the area of brain damage (P<0.05), improved neurological recovery (P<0.05), activated autophagy with up-regulation of Beclin-1 while down-regulation of P62 (P<0.05), suppressed the activation of microglia/macrophage and astrocytes (P<0.01), reduced the expression of MMP-9, NLRP3 and COX-2, and enhanced SOD activity and decreased MDA content (P<0.05) when compared with the ICH group. SPD increased the viability of HT-22 cells (P<0.05), improved SOD activity and reduced MDA content (P<0.01). Autophagy inhibitor 3-MA effectively blocked the down-regulation of LC3-II and up-regulation of P62, and completely reversed above protective effects caused by SPD (P<0.05).

SPD activates autophagy after ICH and improves post-ICH brain injury by suppressing neuroinflammation and oxidative stress.

To investigate the change in choroid plexus (CP) volume in Parkinson’s disease (PD) patients with different cognitive states and its correlation with structural volumes of other brain regions.

A cross-sectional study was conducted on 48 PD patients admitted in Department of Neurosurgery of the First Affiliated Hospital of Army Medical University between May 2023 and April 2024, and on 35 healthy controls (HC) recruited through a physical exam center. According to the results of Mini-Mental State Examination (MMSE), the patients were divided into PD with cognitive impairment (PD-CI) group (n=27) and PD with normal cognitive function (PD-NC) group (n=21). 3.0T magnetic resonance imaging (MRI) was performed using MPRAGE sequences, and CP volume and volumes of other brain regions were obtained using FreeSurfer 6.0 software. The CP volume was adjusted by calculating the ratio of its volume to estimated total intracranial volume (eTIV). After controlling for confounders, partial correlation analysis was used to assess the relationship between the CPV/eTIV ratio and the volumes of other brain regions as well as cognitive scale scores. Additionally, multiple linear regression analysis was performed to further explore the relationship between CPV and cognitive function in the PD-CI group.

Compared to the HC group, the CPV in the PD-CI group was significantly larger (P=0.029). In the PD-CI group, the CPV/eTIV ratio showed significant positive correlations with the volume of the lateral ventricles (r=0.689, P=0.001), the volume of the third ventricle (r=0.592, P=0.006), the volume of cerebrospinal fluid (CSF) (r=0.508, P=0.022), and white matter hyperintensities (WMH) (r=0.486, P=0.030), but was negatively correlated with the volume of the caudate nucleus (r=-0.530, P=0.016), the volume of the thalamus (r=-0.477, P=0.033), and the MMSE scores (r=-0.483, P=0.031). But in the PD-NC group, the CPV/eTIV ratio was only positively correlated with CSF volume (r=0.571, P=0.021). Multiple linear regression analysis indicated that the CPV/eTIV ratio and MMSE scores remained significantly negatively correlated in the PD-CI group (β=-0.388, P=0.046).

Cognitive impairment in PD patients may be closely associated with the change in CP volume, suggesting that the volume can serve as a potential imaging marker in assessment of cognitive impairment in PD patients.