Serine/glycine-one-carbon (SGOC) metabolism is frequently altered in lung adenocarcinoma (LUAD), but its relationship to tumor behavior and predicted immunotherapy responsiveness remains incompletely defined. Metabolomic profiling of 23 paired LUAD and adjacent normal lung tissues was performed using internal extractive electrospray ionization mass spectrometry. Transcriptomic and clinical data from The Cancer Genome Atlas LUAD cohort (TCGA-LUAD) were analyzed to assess SHMT2 expression, prognosis, differentially expressed genes, and immune-related features. Predicted response to immune checkpoint blockade was evaluated using Tumor Immune Dysfunction and Exclusion (TIDE) and The Cancer Immunome Atlas (TCIA), and drug sensitivity was inferred using oncoPredict. Single-cell RNA-seq data were used to examine the cellular distribution of SHMT2. Experimental validation included quantitative reverse-transcription PCR (RT-qPCR), western blotting, Human Protein Atlas (HPA) immunohistochemistry, and short hairpin RNA (shRNA)-mediated SHMT2 knockdown followed by proliferation, wound-healing and colony formation assays. Metabolomic analysis identified glycine, serine, and threonine metabolism as a prominently altered pathway in LUAD. SHMT2 was upregulated in LUAD and associated with worse overall survival and adverse clinicopathological features. SHMT2-high tumors displayed enrichment of cell-cycle and SGOC-related transcriptional programs, lower immune and stromal scores, and reduced predicted responsiveness to immunotherapy. Single-cell analysis showed relative enrichment of SHMT2 expression in B cell populations. In vitro, SHMT2 was overexpressed in LUAD cells, and its knockdown suppressed proliferation, migration, and clonogenic growth. Collectively, SHMT2 is associated with SGOC metabolic reprogramming, aggressive tumor phenotypes, and an immune-disadvantaged state in LUAD, supporting its potential relevance as a biomarker; therapeutic targeting requires additional pharmacologic and in vivo validation.

Background The gut microbiome is closely associated with malignant tumors; however the specific mechanisms by which it contributes to the development of lung adenocarcinoma remain unclear. In this study, we performed a two-sample bidirectional Mendelian randomization (MR) analysis to assess the causal relationship between the gut microbiome and lung adenocarcinoma. By identifying single nucleotide polymorphism markers linked to gut microbiome species, we aimed to discover potential biomarkers for lung adenocarcinoma. These findings may offer new insights into the role of the gut microbiome in the prevention and treatment of lung adenocarcinoma. Methods We used genome-wide association study (GWAS) summary statistics to assess the association between the gut microbiome and lung adenocarcinoma through two-sample MR analysis. Sensitivity analyses were performed to confirm the robustness of the findings. Reverse MR analysis and GWAS data integration were employed to identify potential genetic and therapeutic targets. Bioinformatics analysis and quantitative Real-Time PCR (qRT-PCR) were utilized to validate gene expression and explore the underlying mechanisms of key genes. Results Our analysis identified two bacterial taxa, Prevotella9 and Parabacteroides, as being causally associated with lung adenocarcinoma, both showing positive causal relationships. Sensitivity analyses confirmed the robustness of these associations. The reverse MR analysis revealed no evidence of reverse causality. GWAS data identified 15 genes (DNAH1, PDE10A, DOCK2, INSYN2B, DNAI3, SUOX, LINC01505, SULT4A1, NT5ELP, LINC02895, calcium/calmodulin dependent protein kinase 1D (CAMK1D), ENSG00000253557, BCAS3, C18orf63, MYO18B) that passed the summary-data-based MR test. The transcriptomic data revealed that five genes (CAMK1D, BCAS3, DNAH1, PDE10A, and C18orf63) were differentially expressed between lung adenocarcinoma patients and healthy individuals. Through qRT-PCR validation, the CAMK1D gene was markedly upregulated in lung adenocarcinoma cell lines, whereas BCAS3, DNAH1, PDE10A, and C18orf63 genes exhibit ed substantially reduced expression. Conclusion Our study identified specific gut microbial taxa as risk factors for lung adenocarcinoma and proposes CAMK1D as a microbiota-related candidate biomarker and potential therapeutic target that may inform personalized treatment and drug development strategies in the future.

Background:Lung adenocarcinoma (LUAD) is characterized by marked prognostic heterogeneity. Although lactylation has been implicated in tumor progression and immune regulation, the clinical relevance of lactylation-related transcriptional programs in LUAD remains insufficiently defined. This study aimed to develop and externally validate a lactylation-related gene signature for overall survival prediction in LUAD and to prioritize candidate genes for further biological investigation. Methods:We conducted a retrospective prediction model development and external validation study by integrating single-cell and bulk transcriptomic data. The Cancer Genome Atlas (TCGA)-LUAD was used as the model development cohort, whereas GSE31210 and GSE72094 were used as independent external validation cohorts, including 503, 226, and 398 patients, respectively. Overall survival was defined as the primary outcome. An optimized lactylation-related gene signature (LRGS) was constructed using machine learning strategies, and its predictive performance was evaluated using the concordance index, Kaplan-Meier survival analysis, and time-dependent receiver operating characteristic (ROC) analysis. In addition, pathway enrichment, tumor microenvironment, genomic alteration, and intercellular communication analyses were performed. Immunohistochemistry and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were further used to validate TUBA1C expression in LUAD tissues and cell lines. Results:The optimal model [StepCox (forward) + random survival forest (RSF)] achieved C-index values of 0.935, 0.668, and 0.637 in the TCGA-LUAD, GSE31210, and GSE72094 cohorts, respectively. The final LRGS consisted of 15 genes and stratified patients into high- and low-risk groups with significantly different overall survival across all cohorts (all P<0.001). Time-dependent ROC analysis demonstrated favorable predictive performance, with areas under the curve (AUCs) of 0.96, 0.98, and 0.99 at 1, 2, and 3 years in TCGA-LUAD. Multivariate Cox analysis confirmed that LRGS was an independent prognostic factor. High-risk tumors were associated with enhanced glycolysis, hypoxia, and PI3K-AKT-mTOR signaling, as well as a less immune-active tumor microenvironment. Single-cell ligand-receptor analysis further inferred relatively increased transforming growth factor-beta (TGF-β), vascular endothelial growth factor (VEGF), and C-X-C motif chemokine ligand (CXCL) communication patterns in the high-risk group. TUBA1C was prioritized as a candidate gene, and showed higher expression in LUAD tissues and NSCLC cell lines in preliminary validation assays. Conclusions:LRGS may support prognostic stratification of LUAD based on lactylation-related transcriptional features. In addition, TUBA1C may be a potential biomarker worthy of further functional investigation.

Esophageal cancer is biologically heterogeneous, and conventional clinicopathological staging incompletely captures variation in patient outcomes. This study aimed to determine whether histopathology-derived features associated with phosphoinositide metabolism could support exploratory prognostic stratification and identify biologically interpretable epithelial states. Diagnostic whole-slide images and bulk transcriptomic data from The Cancer Genome Atlas Esophageal Carcinoma (TCGA-ESCA) cohort were integrated with single-cell RNA-sequencing data. Tissue-rich image tiles underwent manual quality control, deep features were extracted using an ImageNet-pretrained ResNet-50 model, and phosphoinositide metabolism activity was quantified by single-sample gene set enrichment analysis (ssGSEA). Associated image features were evaluated using machine-learning survival models, followed by clinicopathological adjustment and multimodal molecular characterization. The selected random survival forest plus gradient boosting machine model stratified overall survival in the training and internal validation cohorts, with concordance indices of 0.762 and 0.723, respectively. The standardized pathology-derived risk score remained associated with overall survival after adjustment for age, sex, histological subtype, and pathological stage (hazard ratio, 2.37; 95% confidence interval, 1.60–3.50). However, calibration was imperfect, and performance estimates may be optimistic because the internal validation cohort informed model selection. Most initial pathology–phosphoinositide metabolism associations were attenuated after adjustment for histological subtype. Multimodal analyses prioritized PLEKHA6 as a candidate pathology-associated epithelial-state marker rather than a subtype-independent prognostic biomarker. PLEKHA6-positive epithelial cells exhibited inflammatory and microenvironment-related transcriptional programs, predicted midkine- and macrophage migration inhibitory factor-related communication features, and stronger inferred copy-number variation-like signals. Higher tumor-level PLEKHA6 expression was also associated with distinct inferred immune, metabolic, and predicted drug-response profiles, although malignant-cell identity was not established. Because the analyzed tiles were not derived from pathologist-annotated malignant regions, the image signal represents composite diagnostic-slide tissue context. These findings identify an exploratory pathology-derived prognostic signal and a PLEKHA6-associated epithelial state in esophageal cancer that require independent, subtype-specific, pathological, and experimental validation.

The rising incidence of lung cancer in never-smokers (LCINS) warrants investigation into novel etiological factors. Gut microbiota-associated metabolic pathways (e.g., glycolysis, glyoxylate degradation) and immune traits, such as the proportion of memory B cells, have been implicated in various diseases, but their causal roles in LCINS remain unclear. Using summary-level data from IEU OpenGWAS, we performed 2-sample Mendelian randomization (MR) to assess causal relationships of 412 gut microbiota features and 731 immune cell traits with LCINS. Mediation MR quantified immune cells' role in linking microbiota to LCINS. Twelve gut microbial taxa and 15 metabolic pathways (including glycolysis and glyoxylate degradation) demonstrated causal associations with LCINS (PIVW < .05). Separately, 36 peripheral immune cell traits showed causal links to LCINS. Mediation analysis further revealed that memory B cell ratio attenuated the effect of microbiota-derived metabolic pathways on LCINS by 7.53% (95% confidence interval: -2.63% to 17.70%; βmediation = -0.017, 95% confidence interval: -0.041 to 0.006). The ratio of memory B cells partially mediates the effect of gut microbiota-driven glycolysis/glyoxylate degradation on LCINS pathogenesis. These findings suggest the gut-immune-lung axis may inform preventive strategies for LCINS.

BackgroundThe triglyceride-glucose index (TyG index) is one of the surrogate markers of insulin resistance, and high-sensitivity C-reactive protein (hsCRP) reflects systemic inflammation. Existing studies suggest that insulin resistance or systemic inflammation may be indicative of cardiometabolic disease, but few of the existing studies have combined the TyG index and inflammation levels before assessing cardiometabolic multimorbidity. Our study data came from the China Health and Retirement Longitudinal Study (CHARLS). Participants in this data were followed for 9 years, and we used these data to conduct a long-term analysis to assess the combined effects of the TyG index and hsCRP on cardiometabolic multimorbidity in Chinese adults over 45 years of age.PurposeTo study the combined effect of TyG index and hsCRP on cardiometabolic multimorbidity in middle-aged as well as elderly Chinese.MethodThe study data came from the China Health and Retirement Longitudinal Study (CHARLS), which included a total of 4,483 middle-aged and elderly participants who did not have cardiovascular metabolic diseases at baseline, which was from CHARLS 2011, and the last survey was in 2020. A total of five cardiometabolic diseases were considered in this study: diabetes, hypertension, hyperlipidemia, heart disease and stroke. A person was defined as having cardiometabolic multimorbidity when he/she had two or more cardiometabolic diseases at the same time. TyG index (median as cut-off) and hsCRP (1mg/L as cut-off) were each divided into two groups and combined into four groups (Group L-L: TyG index=median & hsCRP<1mg/L; Group L-H: TyG index=1mg/L; Group H-H: TyG index>=median & hsCRP>=1mg/L). Multiple regression equations were fitted to analyse the combined influence of TyG index and hsCRP on cardiometabolic multimorbidity.ResultsTyG index increases the risk of CMM events independently of hsCRP, as does the reverse. When the TyG index is elevated and hsCRP is also elevated, this condition significantly increases the danger of cardiometabolic multimorbidity in middle-aged and elderly Chinese.ConclusionHigh levels of TyG index and hsCRP can enhance the danger of cardiometabolic multimorbidity in Chinese middle-aged and elderly people, and the joint use of hsCRP and TyG index assessment may be a better way to achieve primary prevention of cardiometabolic multimorbidity in Chinese middle-aged and elderly people.

Background:The optimal surgical approach for treating stage I second primary lung cancer (SPLC) in elderly patients with a history of lobar resection remains uncertain. To address this knowledge gap, we conducted a comparative analysis of lobar resection versus sublobar resection outcomes in elderly patients diagnosed with contralateral stage I SPLC, utilizing population-based databases. Methods:We identified elderly patients diagnosed with T1-2N0M0 SPLC from the Surveillance, Epidemiology, and End Results (SEER) database (2008-2015) who had undergone prior lobar resection for their first primary lung cancer. To ensure accurate classification of SPLC, we applied the Martini and Melamed criteria, which distinguish multiple primary lung cancers based on histologic and anatomic features. Survival outcomes were compared using Kaplan-Meier analysis and multivariable Cox proportional hazards regression. To mitigate potential confounding factors, we constructed a matched cohort through propensity score matching (PSM), balancing baseline characteristics between the lobar and sublobar resection groups. Results:A total of 373 patients met the inclusion criteria, comprising 253 in the sublobar resection group and 120 in the lobar resection group. Following PSM, 297 patients were retained for analysis. The analysis revealed that sublobar resection was associated with significantly improved overall survival (OS) compared to lobar resection in elderly patients with contralateral SPLC, with 5-year OS rates of 43.4% versus 34.3% (P=0.03). Conclusions:For elderly patients with contralateral SPLC, sublobar resection is better than lobar resection.

Accurate determination of lung cancer margins at the molecular level is of great significance to determine the optimal extent of resection during surgical operation and reduce the risk of postoperative recurrence. In this study, internal extractive electrospray ionization mass spectrometry (iEESI-MS) was used to trace potential molecular tumor margins in lung cancer tissue. Molecular differential model for the determination of lung cancer tumor margin was established via partial least-squares discriminant analysis (PLS-DA) of iEESI-MS data collected from lung tissue pieces within cancer tumor area and iEESI-MS data collected from lung tissue pieces outside cancer tumor area. Proof-of-concept data demonstrate that the developed molecular differential model yields ca. 1-2 mm wider potential molecular tumor margin of a lung cancer compared to the conventional histological analysis, showing promising potential of iEESI-MS to increase the accuracy of tumor margins determination and lower risk of lung cancer postoperative recurrence. Furthermore, our results revealed that creatine and taurine showed positive correlations with lung cancer.

INTRODUCTIONResearch on somatic and germline mutations in Chinese individuals with early-onset Alzheimer's disease (EOAD) has been limited. METHODSWe conducted whole-genome sequencing of blood DNA from 108 patients with EOAD and 116 controls. The analysis included somatic and germline mutations across coding and non-coding regions, mutational signature determination, pathway enrichment identification, and predictive model. RESULTSThe mutational burden was significantly higher in the EOAD group compared to the control group. The prevalence of single-base substitution signature 5, which is strongly associated with aging, was much higher in patients with EOAD than in controls. EOAD-specific somatic mutations were identified in genes such as MIR31HG, TUBB4B, and APP. Germline mutations in DOCK3, PCSK5, and PDE4D were significantly associated with age of dementia onset. Furthermore, a predictive model comprising 15 mutations demonstrated an area under the curve of 0.78. DISCUSSIONThe accumulation of senescence-related somatic mutations may increase the risk of developing EOAD. Highlights Whole genome sequencing was used to find somatic and germline mutations in Chinese individuals with early-onset Alzheimer's disease (EOAD). Total number and burden of blood somatic mutations were significantly higher. The prevalence of single-base substitution signature 5 was notably elevated in EOAD. EOAD-specific somatic mutations were identified in MIR31HG, TUBB4B, and APP. DOCK3, PCSK5, and PDE4D germline mutations were associated with the age of EOAD onset.

BACKGROUND:The use of nomograms in predicting the prognosis of early-stage non-small cell lung cancer (NSCLC), particularly in elderly patients, is not widespread. A validated prognostic model specifically for NSCLC patients over 80 years old holds promising potential for clinical application in forecasting patient outcomes. METHODS:The prognostic value of various factors for NSCLC patients aged 80 and above was evaluated using data from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2017). Kaplan-Meier (KM) curves, Cox proportional hazards regression models, and nomogram were utilized to evaluate the impact of each factor on cancer-specific survival (CSS). RESULTS:A cohort comprising 7045 individuals was selected for inclusion in the analysis. Through rigorous statistical analysis, 10 independent prognostic factors were identified and incorporated into the nomogram. The nomogram's receiver operating characteristic (ROC) curve area under the curve (AUC) was higher than that of the AJCC 7th edition TNM staging system's predicted CSS (0.744 versus 0.602), establishing the superior prognostic value of the nomogram. CONCLUSIONS:We have successfully created a highly accurate and discriminative nomogram that enables oncologists to predict the survival outcome of each individual patient with I/II NSCLC who is 80 years or older.

BackgroundAs lung squamous cell carcinoma (LUSC) patients are at increased risk of developing a second primary cancer, this complicates the patient’s condition and thus makes prognostic assessment more difficult, posing a significant prognostic challenge for clinicians. Our goal was to assess the prognosis of LUSC patients with a second primary tumor, and provide insights into appropriate therapy and monitoring strategies.MethodsData was obtained for LUSC patients from the Surveillance, Epidemiology, and End Results (SEER) database. The LUSC patients were divided into three groups (LS-SPM, OT-LUSC and LUSC-only). Univariate and stratified analyses were performed for the baseline and clinical characteristics of the participants. Multiple regression and Kaplan-Meier survival analyses were also performed, followed by a final life table analysis.ResultsIn our sample of 101,626 patients, the HR for OS in the LS-SPM group was 0.40 in univariate analysis. Kaplan-Meier survival curves showed that LS-SPM patients had considerably longer lifespans compared to the other groups. The LS-SPM patients had median and mean survival times of 64 months and 89.11 months. Unadjusted and adjusted multiple regression analyses showed that LS-SPM patients had a superior survival compared to LUSC-only and OT-LUSC groups.ConclusionLS-SPM patients have a good prognosis with aggressive therapy and immune monitoring. The present study offers novel insights into the pathophysiological causes and treatments for LS-SPM.

Background:Spontaneous pneumothorax (SP) is a common pleural disease in adolescents and adults. However, the role of immunological characteristics in the pathogenesis of SP remains unclear. This study aims to clarify the causal associations between circulating immune cells, lymphocyte subgroups, and SP susceptibility. Methods:Employing Mendelian randomization (MR), the causal association between circulating immune blood cells and lymphocyte subgroups on SP susceptibility have been assessed. Reverse MR analysis was used to further explore the causal relationship. The MR analysis ensured the reliability of the study results through the deletion of confounding single nucleotide polymorphisms (SNPs), heterogeneity testing, sensitivity analysis. Results:Seven immune cells and SP risk under stringent and lenient threshold conditions were identified. Eosinophils absolute count (AC) [odds ratio (OR) =1.0014, 95% confidence interval (CI): 1.0001-1.0014, P=0.02], memory B cell %B cell ratio (OR =1.008, 95% CI: 1.0002-1.0015, P=0.01), CD4+ T cell AC (OR =1.0014, 95% CI: 1.0003-1.0025, P=0.009), effector memory CD4+ T cell %T cell ratio (OR =1.0028, 95% CI: 1.0010-1.0046, P=0.003), and HLA-DR+CD8+ T cell %T cell ratio (OR =1.0019, 95% CI: 1.0004-1.0035, P=0.01) were identified as risk factors for increased susceptibility to SP. Conversely, CD8dim T cell AC (OR =0.9983, 95% CI: 0.9967-0.9999, P=0.03) and CD8dim natural killer T (NKT) %T cell ratio (OR =0.9982, 95% CI: 0.9965-0.9999, P=0.04) exhibited protective effects on SP. In natural killer (NK) cell subgroups and reverse MR analysis, no significance was found. Conclusions:This study establishes a close causal relationship between immune cells and SP through genetic methods, providing a new perspective for understanding the pathophysiological mechanisms of SP.

In recent years, twin pregnancies have become increasingly common. The aim of our study was to analyze the exposure to risk factors for postpartum pulmonary edema in twin pregnancies. We get all our data from the “DATADRYAD” database, which is available directly. We used a variety of statistical methods, including multivariate logistic regression analysis and smoothed curve fitting. The aim was to critically assess the relationship between height and the occurrence of postpartum pulmonary edema in pregnant women with twin pregnancies. Among pregnant women whose height was <154 cm, the risk of postpartum development of pulmonary edema gradually decreased with increasing height (OR = 0.65, P = .0104). There was no relationship between maternal height and postpartum development of pulmonary edema among pregnant women with height higher than 154 cm (P = .9142). Pregnant women who were taller than 154 cm had a 76% lower risk of developing pulmonary edema postpartum compared to pregnant women whose height was lower than 154 cm (P = .0005). Our study suggests that pregnant women with twin pregnancies whose height is <154 cm are more likely to suffer from postpartum pulmonary edema. Therefore, healthcare professionals and caregivers should pay closer attention to twin pregnancies with heights below 154 cm, be alert to the occurrence of pulmonary edema, and take preventive and therapeutic measures as early as possible. This will help prevent the development of pulmonary edema.

Background The incidence and mortality rates of cancer are the highest globally. Developing novel methodologies that precisely, safely, and economically differentiate between benign and malignant lung conditions holds immense clinical importance. This research seeks to construct a predictive model utilizing a combination of diverse biomarkers to effectively discriminate between benign and malignant lung diseases.Methods This retrospective study included patients admitted to the two general hospitals in Shanghai from 2014 to 2015. This study was developed using five tumor markers: carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), cytokeratin fragment 21-1 (CA211), squamous cell carcinoma antigen (SCC), and neuron specific enolase (NSE). The entire sample was divided into two groups according to the hospital: 1033 cases were included in the development cohort and 300 cases in the validation cohort. Logistic regression analysis was used for univariate analysis to explore individual correlations between each selected clinical variable and lung cancer diagnostic outcome. Diagnostic prediction models were constructed and validated based on independent prognostic factors identified using multifactorial analysis. A nomogram was created using these tumor markers (age and sex were additionally included) and validated using the concordance index and calibration curves. Clinical prediction models were evaluated using decision curve analysis.Results Fully adjusted multivariate analysis showed that the risk of lung cancer was 2.38 times higher in men than in women. CEA positivity was associated with an 13.41-fold increased risk in lung cancer. The area under the curve (AUC) values for the development cohort and validation cohort models were 0.907 and 0.954, respectively. In the established nomogram, the AUC for the receiver operating characteristic curve was 0.907 (95% CI, 0.889-0.925). The validation model confirmed the strong discriminative power of the nomogram (AUC = 0.954). The described calibration curves demonstrated good fit predictions and observation probabilities. In addition, decision curve analysis concluded that the newly established nomogram has important implications for clinical decision making.Conclusions Combined prediction models based on CEA, CA199, CA211, SCC, and NSE biomarkers could significantly the differentiation between benign and malignant lung diseases, thus facilitating better clinical decision making.

Background There are various therapeutic methods for treating stage IA (T1N0M0) non-small cell lung cancer (NSCLC), but no studies have systematically assessed multiple treatments to determine the most effective therapy. Methods Stage IA NSCLC patient data collected between 2004 and 2018 were gathered from the Surveillance, Epidemiology, and End Results (SEER) database. Treatment modalities included observation, chemotherapy alone (CA), radiation alone (RA), radiation+chemotherapy (RC), surgery alone (SA), surgery+chemotherapy (SC), surgery+radiation (SR) and surgery+radiation+chemotherapy (SRC). Comparisons were made of overall survival (OS) and lung cancer-specific survival (LCSS) among patients based on different therapeutic methods by survival analysis. Results Ultimately, 89147 patients with stage IA NSCLC between 2004 and 2018 were enrolled in this study. The order of multiple treatment modalities based on the hazard ratio (HR) for OS for the entire cohort revealed the following results: SA (HR: 0.20), SC (HR: 0.25), SR (HR: 0.42), SRC (HR: 0.46), RA (HR: 0.56), RC (HR: 0.72), CA (HR: 0.91) (P<0.001), and observation (HR: Ref). The SA group had the best OS and LCSS, and similar results were found in most subgroup analyses (all P<0.001). The order of surgical modalities based on the HR for OS for the entire cohort revealed the following results: lobectomy (HR: 0.32), segmentectomy (HR: 0.41), wedge resection (HR: 0.52) and local tumor destruction (HR: Ref). Lobectomy had the best effects on OS and LCSS, and similar results were found in all subgroup analyses (all P<0.001). Conclusion SA appeared to be the optimal treatment modality for patients with stage IA NSCLC, and lobectomy was associated with the best prognosis. There may be some indication and selection bias in our study, and the results of this study should be confirmed in a prospective study.

There are numerous causes of abdominal aortic calcification (AAC), among which the relationship between serum uric acid and AAC still needs to be investigated further. The aim of this research was to ascertain whether serum uric acid is correlated with AAC. Our study included 3007 participants. We described the study population characteristics and utilized univariate analysis, stratified analysis, multiple equation regression analysis, smoothed curve fitting, and threshold effects analysis. AAC Total 24 score is used to reflect the range of aortic calcification at each vertebral level. As serum uric acid increased, the AAC Total 24 score first decreased and then increased. The fold point is located when serum uric is at 3.5 mg/dL. After adjusting for 16 covariates, the beta values for the groups with moderate and high serum uric acid levels were 0.34 and 0.53, respectively, compared with the low serum uric acid tertile group (P < .05). Our research indicates a negative correlation between serum acid level and AAC when serum uric acid <3.5 mg/dl, but it is positively correlated with the formation of AAC when serum uric acid >3.5 mg/dl.

BACKGROUND:Surgical aortic valve replacement (SAVR) currently stands as a primary surgical intervention for addressing aortic valve disease in patients. This retrospective study focused on the role of the red blood cell distribution width (RDW) in predicting adverse outcomes among SAVR patients. METHODS:The subjects for this study were exclusively derived from the Medical Information Mart for Intensive Care database (MIMIC IV 2.0). Kaplan‒Meier (K-M) curves and Cox proportional hazards regression models were employed to assess the correlation between RDW, one-year mortality, and postoperative atrial fibrillation (POAF). The smooth-fitting curves were used to observe the relative risk (RR) of RDW in one-year mortality and POAF. Furthermore, time-dependent receiver operating characteristic (ROC) curves, the continuous-net reclassification index (NRI), and integrated discrimination improvement (IDI) were employed for comprehensive assessment of the prognostic value of RDW. RESULTS:Analysis of RDW revealed a distinctive inverted U-shaped relationship with one-year mortality, while its association with POAF appeared nearly linear. Cox multiple regression models showed that RDW > 14.35%, along with preoperative potassium concentration and perioperative red blood cell transfusion, were significantly linked to one-year mortality (K-M curves, log-rank P < 0.01). Additionally, RDW was associated with both POAF and prolonged hospital stays (P < 0.05). There was no significant difference in length of stay in ICU. Notably, the inclusion of RDW in the predictive models substantially enhanced its performance. This was evidenced by the time-dependent ROC curve (AUC = 0.829), NRI (P< 0.05), IDI (P< 0.05), and K-M curves (log-rank P< 0.01). CONCLUSIONS:RDW serves as a robust prognostic indicator for SAVR patients, offering a novel means of anticipating adverse postoperative events.

BACKGROUND Few studies have investigated the association between gestational age, birth weight, and esophageal cancer risk; however, causality remains debated. We aimed to establish causal links between genetic gestational age and birth weight traits and gastroesophageal reflux disease (GERD), Barrett’s esophagus (BE), and esophageal adenocarcinoma (EA). Additionally, we explored if known risk factors mediate these links. AIM To analyze of the relationship between gestational age, birth weight and GERD, BE, and EA. METHODS Genetic data on gestational age and birth weight (n = 84689 and 143677) from the Early Growth Genetics Consortium and outcomes for GERD (n = 467253), BE (n = 56429), and EA (n = 21271) from genome-wide association study served as instrumental variables. Mendelian randomization (MR) and mediation analyses were conducted using MR-Egger, weighted median, and inverse variance weighted methods. Robustness was ensured through heterogeneity, pleiotropy tests, and sensitivity analyses. RESULTS Birth weight was negatively correlated with GERD and BE risk [odds ratio (OR) = 0.78; 95% confidence interval (CI): 0.69-0.8] and (OR = 0.75; 95%CI: 0.60-0.9), respectively, with no significant association with EA. No causal link was found between gestational age and outcomes. Birth weight was positively correlated with five risk factors: Educational attainment (OR = 1.15; 95%CI: 1.01-1.31), body mass index (OR = 1.06; 95%CI: 1.02-1.1), height (OR = 1.12; 95%CI: 1.06-1.19), weight (OR = 1.13; 95%CI: 1.10-1.1), and alcoholic drinks per week (OR = 1.03; 95%CI: 1.00-1.06). Mediation analysis showed educational attainment and height mediated the birth weight-BE link by 13.99% and 5.46%. CONCLUSION Our study supports the protective role of genetically predicted birth weight against GERD, BE, and EA, independent of gestational age and partially mediated by educational attainment and height.

Abstract Objective: To investigate the effect of LCP2 expression in lung adenocarcinoma on the prognosis and microenvironment of patients. Methods: The expression of LCP2 in lung adenocarcinoma tissues and normal tissue samples were analyzed by the TCGA database. Kaplan–Meier survival analysis was used to evaluate the relationship between expression level and prognosis of patients. The effect of differential expression of LCP2 on tumor cells was verified by Colony formation, CCK-8, wound healing, Transwell, and apoptosis. To analyze the relationship between LCP2 expression and immune infiltration in lung adenocarcinoma cells. The expression level of LCP2 was significantly correlated with tumor immune cell infiltration and immune checkpoint expression Results: LCP2 expression was downregulated in lung adenocarcinoma, and patients with a low expression level of lung adenocarcinoma had a poor prognosis. LCP2 overexpression significantly inhibited the proliferation, migration, invasion, and tumor sphere formation potential. LCP2 overexpression enhanced apoptosis. The expression level of LCP2 was significantly correlated with tumor immune cell infiltration and immune checkpoint expression. Conclusion: The expression of LCP2 is low in lung adenocarcinoma, which is related to the prognosis and tumor immunity of lung adenocarcinoma patients, and can be used as a potential target for the treatment of lung adenocarcinoma patients

In patients with stage IA non-small cell lung cancer (NSCLC), uniportal video-assisted thoracic surgery (U-VATS) anatomical segmentectomy removes the lung tumor while preserving lung function as much as possible, and it is therefore an alternative to lobectomy. Patients with stage IA NSCLC receiving U-VATS segmental resection at our institution from September 2017 to June 2019 were compared with patients receiving U-VATS lobectomy. A total of 47 patients received segmentectomy and 209 patients received U-VATS lobectomy in the same period. Propensity score matching was conducted to diminish bias. The final study cohort included 42 patients who received segmentectomy and 42 propensity score matching-matched patients who received lobectomy. Perioperative parameters and postoperative complications, length of hospital stay, postoperative forced expiratory volume in 1 s (FEV1), and forced vital capacity (FVC) were compared between the 2 groups. Surgery was successfully completed in all patients. The mean follow-up was for 8.2 months. The postoperative complication rate was comparable between the 2 groups: 31.0% in segmentectomy patients versus 35.7% in lobectomy patients (P = .643). At 1 month after surgery, FEV1% and FVC% were not significantly different between the 2 groups (P > .05). At 3 months after surgery, FEV1 and FVC were higher in segmentectomy patients than in lobectomy patients (FEV1, 82.79% ± 6.36% vs 78.55% ± 5.42%; FVC, 81.66% ± 6.09% vs 78.90% ± 5.58%, P < .05). Patients receiving segmentectomy suffer less pain and have better postoperative lung function and higher quality of life.