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Objective: Hypertension (HTN) is a prevalent global health concern. From the standpoint of preventive and personalized medicine (PPPM/3PM), early detection of HTN offers a crucial opportunity for targeted prevention and personalized treatment. This study aimed to evaluate the association between the weight-adjusted waist index (WWI) and HTN risk. Methods: A case-control study using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 was conducted. Logistic regression models assessed the association between WWI and HTN. Subgroup analyses explored differences in age, sex, ethnicity, and diabetes status. Restricted cubic spline (RCS) analyses examined potential nonlinear relationships. Results: A total of 32,116 participants, with an average age of 49.28 ± 17.56 years, were included in the study. A significant positive association between WWI and the risk of HTN was identified (odds ratio [OR], 2.49; 95% CI, 2.39-2.59; P < 0.001). When WWI was categorized into quartiles (Q1-Q4), the highest quartile (Q4) exhibited a stronger association compared to Q1 (OR, 2.94; 95% CI, 2.65-3.27; P < 0.001). Subgroup analyses indicated that WWI was a risk factor for HTN across different populations, although variations in the magnitude of effect were observed. Furthermore, the findings from the RCS elucidated a nonlinear positive correlation between WWI and HTN. Conclusion: WWI is independently associated with HTN risk, highlighting its potential as a risk assessment tool in clinical practice. Incorporating WWI into early detection strategies enhances targeted prevention and personalized management of HTN. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00375-3.

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BACKGROUND: Placental histological chorioamnionitis (HCA) is recognised as a significant risk factor for various adverse neonatal outcomes. This study aims to explore if the inflammatory protein levels in neonates were associated with HCA. METHODS: All women with singleton births from February 2020 to November 2022 were selected and divided into three groups based on maternal placental pathology results: the HCA-stage 1 group (n=24), the HCA-stage 2 group (n=16) and the control group (n=17). Olink Target 96 Inflammation Panel was used to detect the levels of 92 inflammation-related proteins in the plasma of newborns from all three groups within 24 hours after birth. We compared the protein profiles through differential protein expression analysis. RESULTS: A total of six inflammation-related proteins exhibited significant differences between the HCA-stage 1 and the control group. Specifically, TRANCE and CST5 were significantly upregulated (p=0.006, p=0.025, respectively), whereas the expression of IFN-gamma, CXCL9, CXCL10 and CCL19 was significantly downregulated (p=0.040, p=0.046, p=0.007, p=0.006, respectively). HCA-stage 2 newborns had significantly elevated levels of CD5 and CD6 and decreased IFN-gamma, CXCL10 and CCL19 in comparison to controls. These differential proteins were significantly enriched in positive regulation of cytokine activity, leucocyte chemotaxis and positive regulation of T-cell activation pathway-related Gene Ontology terms. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that viral protein interaction with cytokine and cytokine receptor, interleukin-17/NF-kappa B/toll-like receptor/chemokine signalling pathway, and cytokine-cytokine receptor interaction exhibited significant differences. Spearman analysis demonstrated a significant positive connection between the levels of CD6 and CD5 proteins, not only in neonatal leucocytes but also in maternal leucocytes. Additionally, CD6 was found to be associated with neonatal birth weight. CONCLUSIONS: In conclusion, placental histological changes associated with chorioamnionitis appear to influence the expression of inflammatory proteins in offspring. Notably, CD6 and CD5 proteins may potentially contribute to the pathogenesis of HCA-related neonatal diseases.

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Aim: We investigate the genome-wide DNA methylation (DNAm) patterns of term low birth weight (TLBW) neonates.Methods: In the discovery phase, we assayed 32 samples (TLBW/control:16/16) using the EPIC 850k BeadChip Array. Targeted pyrosequencing of in 60 samples (TLBW/control:28/32) using targeted pyrosequencing during the replication phase.Results: The 850K array identified TLBW-associated 144 differentially methylated positions (DMPs) and 149 DMRs. Nearly 77% DMPs exhibited hypomethylation, located in the opensea and gene body regions. The most significantly enriched pathway in KEGG is sphingolipid metabolism (hsa00600), and the genes GALC and SGMS1 related to this pathway both show hypomethylation.Conclusion: Our analysis provides evidence of genome-wide DNAm alterations in TLBW. Further investigations are needed to elucidate the functional significance of these DNAm changes.

This study looked at the DNA of babies born after 37 weeks of pregnancy but weighing less than 2500 grams. We found that these babies had lower levels of DNA methylation, which might change how their bodies handle fats.

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Background: Esophageal squamous cell carcinoma (ESCC) has a poor early detection rate, prognosis, and survival rate. Effective prognostic markers are urgently needed to assist in the prediction of ESCC treatment outcomes. There is accumulating evidence of a strong relationship between cancer cell growth and amino acid metabolism. This study aims to determine the relationship between amino acid metabolism and ESCC prognosis. Methods: This study comprehensively evaluates the association between amino acid metabolism-related gene (AAMRG) expression profiles and the prognosis of ESCC patients based on data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to verify the expression of prognosis-related genes. Results: A univariate Cox regression analysis of TCGA data identified 18 prognosis-related AAMRGs. The gene expression profiles of 90 ESCC tumor and normal tissues were obtained from the GSE20347 and GSE67269 datasets. Two differently expressed genes (DEGs) were considered as ESCC prognosis-related genes; and they were branched-chain amino acid transaminase 1 (BCAT1) and methylmalonic aciduria and homocystinuria type C protein (MMACHC). These two AAMRGs were used to develop a novel AAMRG-related gene signature to predict 1- and 2-year prognostic risk in ESCC patients. Both BCAT1 and MMACHC expression were verified by RT-qPCR. A prognostic nomogram that incorporated clinical factors and BCAT1 and MMACHC gene expression was constructed, and the calibration plots showed that it had good prognostic performance. Conclusions: The AAMRG signature established in our study is efficient and could be used in clinical settings to predict the early prognosis of ESCC patients.

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BACKGROUND AND OBJECTIVES: This study aimed to identify predictors of sepsis-associated in-hospital mortality from readily available laboratory biomarkers at onset of illness that include haematological, coagulation, liver and kidney function, blood lipid, cardiac enzymes and arterial blood gas. METHODS: Children with sepsis were enrolled consecutively in a prospective observational study involving paediatric intensive care units (PICUs) of two hospitals in Beijing, between November 2016 and January 2020. The data on demographics, laboratory examinations during the first 24 hours after PICU admission, complications and outcomes were collected. We screened baseline laboratory indicators using the Least Absolute Shrinkage and Selection Operator (LASSO) analysis, then we constructed a mortality risk model using Cox proportional hazards regression analysis. The ability of risk factors to predict in-hospital mortality was evaluated by receiver operating characteristic (ROC) curves. RESULTS: A total of 266 subjects were enrolled including 44 (16.5%) deaths and 222 (83.5%) survivors. Those who died showed a shorter length of hospitalisation, and a higher proportion of mechanical ventilation, complications and organ failure (p<0.05). LASSO analysis identified 13 clinical parameters related to prognosis, which were included in the final Cox model. An elevated triglyceride (TG) remained the most significant risk factor of death (HR=1.469, 95% CI: 1.010 to 2.136, p=0.044), followed by base excess (BE) (HR=1.131, 95% CI: 1.046 to 1.223, p=0.002) and pH (HR=0.95, 95% CI: 0.93 to 0.97, p<0.001). The results of the ROC curve showed that combined diagnosis of the three indicators-TG+BE+pH-has the best area under the curve (AUC) (AUC=0.77, 95% CI: 0.69 to 0.85, p<0.001), with a 68% sensitivity and 80% specificity. CONCLUSION: Laboratory factors of TG, BE and pH during the first 24 hours after intensive care unit admission are associated with in-hospital mortality in PICU patients with sepsis. The combination of the three indices has high diagnostic value.

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Objective: This study aims to explore the association between outdoor artificial light at night (ALAN) exposure and gestational diabetes mellitus (GDM). Methods: This study is a retrospective case-control study. According with quantiles, ALAN has been classified into three categories (Q1-Q3). GDM was diagnosed through oral glucose tolerance tests. Conditional logistic regression models were used to evaluate the association between ALAN exposure and GDM risk. The odds ratio (OR) with 95% confidence interval (CI) was used to assess the association. Restricted cubic spline analysis (RCS) was utilized to investigate the no liner association between ALAN and GDM. Results: A total of 5,720 participants were included, comprising 1,430 individuals with GDM and 4,290 matched controls. Pregnant women exposed to higher levels of ALAN during the first trimester exhibited an elevated risk of GDM compared to those with lower exposure levels (Q2 OR = 1.39, 95% CI 1.20-1.63, p < 0.001); (Q3 OR = 1.70, 95% CI 1.44-2.00, p < 0.001). Similarly, elevated ALAN exposure during the second trimester also conferred an increased risk of GDM (second trimester: Q2 OR = 1.70, 95% CI 1.45-1.98, p < 0.001; Q3 OR = 2.08, 95% CI 1.77-2.44, p < 0.001). RCS showed a nonlinear association between ALAN exposure and GDM risk in second trimester pregnancy, with a threshold value of 4.235. Conclusion: Outdoor ALAN exposure during pregnancy is associated with an increased risk of GDM.

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Lung cancer has become the leading cause of cancer-related deaths globally. However, early detection of lung cancer remains challenging, resulting in poor outcomes for the patients. Herein, we developed an optical biosensor integrating surface-enhanced Raman spectroscopy (SERS) with a catalyzed hairpin assembly (CHA) to detect circular RNA (circRNA) associated with tumor formation and progression (circSATB2). The signals of the Raman reporter were considerably enhanced by generating abundant SERS "hot spots" with a core-shell nanoprobe and 2D SERS substrate with calibration capabilities. This approach enabled the sensitive (limit of detection: 0.766 fM) and reliable quantitative detection of the target circRNA. Further, we used the developed biosensor to detect the circRNA in human serum samples, revealing that patients with lung cancer had higher circRNA concentrations than healthy subjects. Moreover, we characterized the unique circRNA concentration profiles of the early stages (IA and IB) and subtypes (IA1, IA2, and IA3) of lung cancer. These results demonstrate the potential of the proposed optical sensing nanoplatform as a liquid biopsy and prognostic tool for the early screening of lung cancer.

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BACKGROUND: Adverse childhood experiences (ACEs) are associated with asthma, but the role of depressive symptoms (DS) in this is poorly studied. OBJECTIVE: The aim of this study was to investigate the mediating effect of DS on ACEs and asthma. PARTICIPANTS AND SETTING: This study was a retrospective cohort study of participants from the China Longitudinal Study of Health and Retirement from 2011 to 2018. A total of 12,277 participants including 5942 males and 6335 females were involved in the study. METHODS: DS were assessed using the 10-item short form of the Center for Epidemiological Research Depression Scale. Logistic regression adjusted for confounders was used to explore the relationship between ACEs with asthma. Mediating effect analysis was used to assess the role of DS in the relationship between ACEs and asthma. RESULTS: The results of logistic regression showed that there were an association between ACEs and asthma. Mediating effect analysis revealed that among the 15 ACEs examined, DS had partial mediating effects on the association between asthma and 5 specific ACEs (feeling alone, peer bullied, self-reported health status, health limitation, and death of parents), and fully mediated the relationship between asthma and another 5 ACEs (death of siblings, childhood neighborhood safety, childhood neighborhood quality, physical abuse, and parents' mental health) (all p < .05). CONCLUSION: ACEs are significantly associated with an increased risk of asthma, and DS play a mediating role in the relationship between ACEs and asthma.

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Surface-enhanced Raman spectroscopy (SERS) has shown promising potential in cancer screening. In practical applications, Raman spectra are often affected by deviations from the spectrometer, changes in measurement environments, and anomalies in spectrum characteristic peak intensities due to improper sample storage. Previous research has overlooked the presence of outliers in categorical data, leading to significant impacts on model learning outcomes. In this study, we propose a novel method, called Principal Component Analysis and Density Based Spatial Clustering of Applications with Noise (PCA-DBSCAN) to effectively remove outliers. This method employs dimensionality reduction and spectral data clustering to identify and remove outliers. The PCA-DBSCAN method introduces adjustable parameters (Eps and MinPts) to control the clustering effect. The effectiveness of the proposed PCA-DBSCAN method is verified through modeling on outlier-removed datasets. Further refinement of the machine learning model and PCA-DBSCAN parameters resulted in the best cancer screening model, achieving 97.41% macro-average recall and 97.74% macro-average F1-score. This paper introduces a new outlier removal method that significantly improves the performance of the SERS cancer screening model. Moreover, the proposed method serves as inspiration for outlier detection in other fields, such as biomedical research, environmental monitoring, manufacturing, quality control, and hazard prediction.

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The association between residential land cover (RLC) and wheezing remains poorly understood. This study aimed to investigate the association between RLC and wheezing in childhood and adolescence. A cross-sectional survey was conducted among children and adolescents in five provinces of China. Land cover data were obtained from the Cross-Resolution Land-Cover mapping framework based on noisy label learning, classifying land cover into five categories: cropland, forest, grass/shrubland, wetland, and impervious. Generalized linear mixed models were employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of wheezing. Mediation analysis was employed to investigate whether ambient particulate matter (PM2.5) acts as a mediator in the association between RLC and wheezing. A total of 12,875 participants were included in the study, comprising 318 patients and 12,557 controls. Cropland500m was significantly associated with decreased odds of wheezing (OR: 0.929, 95% CI: 0.879-0.982), while impervious surfaces500m significantly was associated with increased odds of wheezing (OR: 1.056, 95% CI: 1.019-1.096) in all participants. In the stratified analysis, significant differences were found in the main outcomes between the adolescence group (age ≥10 years) and the childhood group (age <10 years) (Pinteraction < 0.05), while no significant differences were observed between the southern and northern regions, or between male and female respondents. Mediation analysis revealed that PM2.5 partially mediated the association between cropland500m and impervious surfaces500m with wheezing. RLC plays a significant role in wheezing during childhood and adolescence, with cropland offering protection and impervious surfaces posing a heightened risk.

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Esophageal squamous cell carcinoma (ESCC) is a highly lethal form of cancer. Cuproptosis is a recently discovered form of regulated cell death. However, its significance in ESCC remains largely unknown. In this study, we observed significant expression differences in most of the 12 cuproptosis-related genes (CRGs) in the TCGA-ESCC dataset, which was validated using GSE20347, GSE38129, and individual ESCC datasets. We were able to divide patients in the TCGA-ESCC cohort into two subgroups based on disease, and found significant differences in survivor outcomes and biological functions between these subgroups. Additionally, we identified 11 prognosis-related genes from the 12 CRGs using LASSO COX regression analysis and constructed a CRGs signature for ESCC. Patients were categorized into high- and low-risk subgroups based on their median risk score, with those in the high-risk subgroup having significantly worse overall survival than those in the low-risk subgroup. The CRGs signature was also highly accurate in predicting prognosis and survival outcomes. Univariate and multivariate Cox regression analyses revealed that 8 of the 11 CRGs were independent prognostic factors for predicting survival in ESCC patients. Furthermore, our nomogram performed well and could serve as a useful tool for predicting prognosis. Finally, our risk model was found to be relevant to the sensitivity of targeted agents and immune infiltration. Functional enrichment analysis demonstrated that the risk model was associated with biological pathways of tumor migration and invasion. In summary, our study may provide a promising prognostic signature based on CRGs and offers potential targets for personalized therapy.

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BACKGROUND: Limited research has been conducted on the association between preconception exposure to ambient particulate matter (PM) and hypothyroidism. This study aimed to investigate the relationship between preconception PM exposure and hypothyroidism. METHODS: A retrospective case-control study at China-Japan Friendship Hospital was performed. Fine particulate matter (PM2.5) and inhalable particulate matter (PM10) were obtained from the China High Air Pollution Dataset. Buffer analysis methods were used to calculate the exposure of pregnant women to PM in a circular area of 250, 500, and 750 m in diameter at preconception and in early pregnancy. Logistic regression models were used to assess the relationship between PM and hypothyroidism. Odd ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the effect of PM on the risk of hypothyroidism. RESULTS: A total of 3,180 participants were studied, and they comprised 795 hypothyroid patients and 2,385 matched controls. The mean age was 31.01 years (standard deviation: 3.66) in the control group and 31.16 years (standard deviation: 3.71) in the case group. Logistic regression analysis showed that exposure to PM2.5 and PM10 in the 60-day period before the last menstrual period month (LMPM), 30-day period before the LMPM, and LMP, across all distance buffers, was associated with an increased risk of hypothyroidism (all P < 0.05). The most pronounced effect was observed during the LMPM, with PM2.5 (OR: 1.137, 95% CI: 1.096-1.180) and PM10 (OR: 1.098, 95% CI: 1.067-1.130) in the 250-m buffer. Subgroup analysis in the Changping District yielded consistent results with the main analysis. CONCLUSION: Our study shows that preconception PM2.5 and PM10 exposure increases the risk of hypothyroidism during pregnancy.

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Rapid identification of cancer cells is crucial for clinical treatment guidance. Laser tweezer Raman spectroscopy (LTRS) that provides biochemical characteristics of cells can be used to identify cell phenotypes through classification models in a non-invasive and label-free manner. However, traditional classification methods require extensive reference databases and clinical experience, which is challenging when sampling at inaccessible locations. Here, we describe a classification method combing LTRS with deep neural network (DNN) for differential and discriminative analysis of multiple liver cancer (LC) cells. By using LTRS, we obtained high-quality single-cell Raman spectra of normal hepatocytes (HL-7702) and liver cancer cell lines (SMMC-7721, Hep3B, HepG2, SK-Hep1 and Huh7). The tentative assignment of Raman peaks indicated that arginine content was elevated and phenylalanine, glutathione and glutamate content was decreased in liver cancer cells. Subsequently, we randomly selected 300 spectra from each cell line for DNN model analysis, achieving a mean accuracy of 99.2%, a mean sensitivity of 99.2% and a mean specificity of 99.8% for the identification and classification of multiple LC cells and hepatocyte cells. These results demonstrate the combination of LTRS and DNN is a promising method for rapid and accurate cancer cell identification at single cell level.

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Background: The study purpose was to characterize the mycobiome and its associations with the expression of pathogenic genes in esophageal squamous cell carcinoma (ESCC). Methods: Patients with primary ESCC were recruited from two central hospitals. We performed internal transcribed spacer 1 (ITS1) ribosomal DNA sequencing analysis. We compared differential fungi and explored the ecology of fungi and the interaction of bacteria and fungi. Results: The mycobiota diversity was significantly different between tumors and tumor-adjacent samples. We further analysed the differences between the two groups, at the species level, confirming that Rhodotorula toruloides, Malassezia dermatis, Hanseniaspora lachancei, and Spegazzinia tessarthra were excessively colonized in the tumor samples, whereas Preussia persica, Fusarium solani, Nigrospora oryzae, Acremonium furcatum, Golovinomyces artemisiae, and Tausonia pullulans were significantly more abundant in tumor-adjacent samples. The fungal co-occurrence network in tumor-adjacent samples was larger and denser than that in tumors. Similarly, the more complex bacterial-fungal interactions in tumor-adjacent samples were also detected. The expression of mechanistic target of rapamycin kinase was positively correlated with the abundance of N. oryzae and T. pullulans in tumor-adjacent samples. In tumors, the expression of MET proto-oncogene, receptor tyrosine kinase (MET) had a negative correlation and a positive correlation with the abundance of R. toruloides and S. tessarthra, respectively. Conclusion: This study revealed the landscape of the esophageal mycobiome characterized by an altered fungal composition and bacterial and fungal ecology in ESCC.

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Background: The study aimed to develop a nomogram model to predict overall survival (OS) and construct a risk stratification system of upper thoracic esophageal squamous cell carcinoma (ESCC). Methods: Newly diagnosed 568 patients with upper ESCC at Fujian Medical University Cancer Hospital were taken as a training cohort, and additional 155 patients with upper ESCC from Sichuan Cancer Hospital Institute were used as a validation cohort. A nomogram was established using Cox proportional hazard regression to identify prognostic factors for OS. The predictive power of nomogram model was evaluated by using 4 indices: concordance statistics (C-index), time-dependent ROC (ROCt) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI). Results: In this study, multivariate analysis revealed that gender, clinical T stage, clinical N stage and primary gross tumor volume were independent prognostic factors for OS in the training cohort. The nomogram based on these factors presented favorable prognostic efficacy in the both training and validation cohorts, with concordance statistics (C-index) of 0.622, 0.713, and area under the curve (AUC) value of 0.709, 0.739, respectively, which appeared superior to those of the American Joint Committee on Cancer (AJCC) staging system. Additionally, net reclassification index (NRI) and integrated discrimination improvement (IDI) of the nomogram presented better discrimination ability to predict survival than those of AJCC staging. Furthermore, decision curve analysis (DCA) of the nomogram exhibited greater clinical performance than that of AJCC staging. Finally, the nomogram fairly distinguished the OS rates among low, moderate, and high risk groups, whereas the OS curves of clinical stage could not be well separated among clinical AJCC stage. Conclusion: We built an effective nomogram model for predicting OS of upper ESCC, which may improve clinicians' abilities to predict individualized survival and facilitate to further stratify the management of patients at risk.

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Background: This retrospective review of patients with upper thoracic esophageal squamous cell carcinoma (ESCC) analyzed the prognostic value of age, as a continuous variable, and offered insight into treatment options. Methods: 568 upper ESCC patients underwent radical therapy between 2004 and 2016. Age as a continuous variable was entered into the Cox regression model with penalized spline (P-spline) analysis to investigate a correlation between age and survival outcomes. Results: Before adjustment, P-spline regression revealed U-shaped survival curves. Sixty years was the optimal cut-off age for differences in overall and progression-free survival (OS, PFS). The cohort was divided into age groups ≤ 50, 51-69, and ≥ 70 years. Multivariate analyses showed no significant differences in either PFS or OS for patients aged ≤ 50 and 51-69 years. After adjusting for covariates, P-spline regression showed that the risk of mortality and disease progression increased with age, and ≥ 70 years was an unfavorable independent prognostic factor. For age ≥ 70 years, the OS and PFS associated with non-surgery was comparable to that of surgery. For patients younger, the OS and PFS of patients given surgery was significantly better than that of patients given non-surgery. Conclusion: Age was an independent prognostic factor for upper ESCC. Patients ≥ 70 years achieved no significant survival benefit from surgery, but for those younger than 70 years surgery was the preferred treatment option.

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Background: Esophageal squamous cell cancer (ESCC) is an aggressive cancer with high incidence and mortality. It is crucial to predict prognosis of these patients individually. Neutrophil-to-lymphocyte ratio (NLR) has been reported as a prognostic indicator in several tumors, including esophageal cancer. Besides inflammatory factors, nutritional status can impact survival of cancer patients. Albumin (Alb) concentration is an easily obtained indicator to reflect nutritional status. Methods: In this study, we retrospectively collected the data of patients with ESCC and used univariate and multivariate analysis to investigate the relationship between combination of NLR and Alb (NLR-Alb) and survival. Meanwhile, we compared clinical features among NLR-Alb cohorts. Results: Univariate analysis showed that age (P=0.013), gender (P=0.021), surgical type (P=0.031), preoperative therapy (P=0.007), NLR-Alb (P=0.001), and tumor-node-metastasis (TNM) status (P<0.001) were associated with 5-year overall survival (OS). In multivariate analysis, NLR-Alb [hazard ratio (HR) =2.53, 95% confidence interval (95% CI): 1.38-4.63, P=0.003] and TNM status (HR =4.76, 95% CI: 3.09-7.33, P<0.001) were independent predictive factors for 5-year OS. The 5-year OS rates were 83%, 62%, and 55% for NLR-Alb 1, NLR-Alb 2, and NLR-Alb 3, respectively (P=0.001). Conclusions: In summary, pre-operative NLR-Alb is a favorable and cost-effective index to predict prognosis of patients with ESCC individually.

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To evaluate the relationships between maternal particulate matter exposure and offspring birth weight. Studies were categorized into three subgroups: term low birth weight (TLBW) among full-term births and all births (regardless of gestational age) and low birth weight (LBW) among all births, based on the search results of MEDLINE and the Web of Science from the inception of the database to April 2022. Subgroup analyses were conducted based on the economic status, region, exposure assessment, risk of bias, and adjustment. Sixty-one studies involving 34,506,975 singleton live births in 15 countries were analyzed. Overall, the risk of bias for most studies (75%) was low. In 39 of 47 term birth studies, the pooled odds ratio of TLBW among term births for per interquartile range (IQR) increases throughout the entire pregnancy was 1.02 (1.01 to 1.03) for PM2.5 and 1.03 (1.01 to 1.05) for PM10 after adjustment for covariates. No significant relevance was detected across each trimester period for PM2.5. A stronger effect was observed during the second trimester (1.03, 1.01 to 1.06) for PM10. There was no increased risk of TLBW in all births associated with IQR increases in PM2.5 and PM10. LBW was associated with PM2.5 exposure in 4 of 7 studies, but statistical heterogeneity was considerable. In the TLBW subgroup analysis, the effects of PM2.5 and PM10 were both greater in studies conducted in advanced countries, studies with low bias, and studies that adjusted for maternal age, infant sex, and parity. Stronger effects were present for PM2.5 exposure collected from monitoring stations and PM10 exposure interpolated from the inverse distance weighting model. TLBW may be associated with prenatal exposure to particulate matter, but no critical windows were identified. Stronger associations were observed in advanced countries. Future original study designs need to consider the impact of different exposure assessment modalities and all possible confounding factors.

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OBJECTIVE: This study aimed to investigate the effect of preoperative albumin-to-globulin ratio (AGR) on overall survival (OS) and health-related quality of life in patients with esophageal cell squamous carcinoma (ESCC). METHODS: Serum albumin and globulin were measured within one week before surgery. Multiple follow-ups were conducted among patients with ESCC in the study in order to assess their life quality. The method used in the study was a telephone interview. Quality of life was measured using the EORTC Quality of Life Questionnaire-Core Questionnaire (EORTC QLQ-C30, version 3.0) and Esophageal Cancer Module (EORTC QLQ- OES18). RESULTS: A total of 571 ESCC patients were included in the study. The results illustrated that 5-year OS of high AGR group (74.3%) was better than the low one (62.3%) (P = 0.0068). Univariate and multivariate Cox regression analysis found that preoperative AGR (HR = 0.642, 95%CI: 0.444-0.927) are prognostic factor for patients with ESCC after surgery. In terms of quality of life, found that low AGR associated with increased postoperative time to deterioration (TTD) events in ESCC patients, and compared to low AGR, high AGR could delay the deterioration of emotional functioning(P = 0.001), dysphagia(P = 0.033), trouble with taste(P = 0.043) and speech problems(P = 0.043). After using the multivariate Cox regression analysis showed that high AGR could improve patients' emotional function (HR = 0.657, 95% CI: 0.507-0.852) and trouble with taste (HR = 0.706, 95% CI: 0.514-0.971). CONCLUSIONS: Preoperative AGR in patients with ESCC after esophagectomy was positively correlated with overall survival rate and quality of life after operation.

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Immunotherapy is an effective treatment for esophageal cancer (ESCA) patients. However, there are no dependable markers for predicting prognosis and immunotherapy responses in ESCA. Our study aims to explore immune gene prognostic models and markers in ESCA as well as predictors for immunotherapy. The expression profiles of ESCA were obtained from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and International Cancer Genome Consortium (ICGC) databases. Cox regression analysis was performed to construct an immune gene prognostic model. ESCA was grouped into three immune cell infiltration (ICI) clusters by CIBERSORT algorithm. The immunotherapy response of patients in different ICI score clusters was also compared. The copy number variations, somatic mutations, and single nucleotide polymorphisms were analyzed. Enrichment analyses were also performed. An immune gene prognostic model was successfully constructed. The ICI score may be used as a predictor independent of tumor mutation burden. Enrichment analyses showed that the differentially expressed genes were mostly enriched in microvillus and the KRAS and IL6/JAK/STAT3 pathways. The top eight genes with the highest mutation frequencies in ESCA were identified and all related to the prognosis of ESCA patients. Our study established an effective immune gene prognostic model and identified markers for predicting the prognosis and immunotherapy response of ESCA patients.

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