A Novel Germline Mutation of BRCA1 and Integrated Analysis With Somatic Mutation in a Chinese Multi-Cancer Family.

The presence of mutations in the BRCA1 gene (MIM: 113705) is widely recognized as a significant genetic predisposition for ovarian cancer. This study investigated the genomic mutations in a Chinese family with a history of ovarian, breast, and rectal adenocarcinoma. A novel germline mutation (Phe1695Val) in BRCA1 was identified through whole-exome sequencing. Subsequently, we performed whole-genome sequencing to identify somatic mutations and analyze mutational signatures in individuals carrying the novel germline mutation. Our findings revealed a correlation between somatic mutational signatures and the BRCA1 germline mutation in the proband with ovarian cancer, while no such association was observed in the tumor tissue from the patient with breast cancer. Furthermore, distinct somatic driver mutations were identified, a truncated mutation in the TP53 gene in the ovarian tumor tissue, and a hotspot mutation in the PIK3CA gene in the breast cancer. According to our findings, the BRCA1 F1695V mutation is linked to ovarian cancer susceptibility in the family and causes specific somatic mutational profiles.

Short-term effects of air pollution exposure on the risk of preterm birth in Xi'an, China.

INTRODUCTION: Long-term exposure to air pollution is known to be harmful to preterm birth (PTB), but little is known about the short-term effects. This study aims to quantify the short-term effect of particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5), ≤10 µm (PM10) and nitrogen dioxide (NO2) on PTB. MATERIALS AND METHODS: A total of 18,826 singleton PTBs were collected during the study period. Poisson regression model combined with the distributed lag non-linear model was applied to evaluate the short-term effects of PTBs and air pollutants. RESULTS: Maternal exposure to NO2 was significantly associated increased risk of PTB at Lag1 (RR: 1.025, 95%CI: 1.003-1.047). In the moving average model, maternal exposure to NO2 significantly increased the risk of PTB at Lag01 (RR: 1.029, 95%CI: 1.004-1.054). In the cumulative model, maternal exposure to NO2 significant increased the risk of PTB at Cum01 (RR:1.026, 95%CI: 1.002-1.051), Cum02 (RR: 1.030, 95%CI: 1.003-1.059), and Cum03 (RR: 1.033, 95%CI: 1.002-1.066). The effects of PM2.5, PM10 and NO2 on PTB were significant and greater in the cold season than the warm season. CONCLUSIONS: Maternal exposure to NO2, PM2.5 and PM10 before delivery has a significant risk for PTB, particularly in the cold season.Key messagesMaternal exposure to NO2 was significant associated with an increased risk of preterm birth at the day 1 before delivery.Particle matter (PM2.5 and PM10) showed a significant short-term effect on preterm birth in the cold season.The effects of air pollutants on preterm birth was greater in the cold season compared with the warm season.

Association between noise exposure during pregnancy and pregnancy complications: A meta-analysis.

Background: Noise exposure has a significant impact on human health. However, the effect of occupational and residential noise on the risk of pregnancy complications was controversial in the literature. This study looked at previous research and performed a meta-analysis to determine how noise exposure during pregnancy affected the risk of pregnancy complications. Methods: Systematic searches were conducted in PubMed, Web of Science, Scopus, Embase, Ovid, and Cochrane, and all relevant studies were included. Two investigators independently evaluated the eligibility of these studies. The risk of bias in each study and the quality and strength of each outcome was evaluated by using the GRADE approach and Navigation Guide. Random effects meta-analysis model was used. Results: The meta-analysis retrieved 1,461 study records and finally included 11 studies. Occupational noise exposure during pregnancy was associated with preeclampsia (RR = 1.07, 95%CI: 1.04, 1.10). Neither occupational nor residential noise exposure was associated with hypertensive disorders of pregnancy (HDP) (RR = 1.10, 95%CI: 0.96, 1.25 and RR = 1.05, 95%CI: 0.98, 1.11) or gestational diabetes mellitus (GDM) (RR = 0.94, 95%CI: 0.88, 1.00 and RR = 1.06, 95%CI: 0.98, 1.16). Further bias analysis showed that the results were reliable. All outcomes were rated as low in quality and inadequate evidence of harmfulness in strength. Conclusions: Occupational noise exposure could increase the risk of preeclampsia, according to the findings. There was no clear evidence of a harmful effect of noise exposure during pregnancy on HDP or GDM.

Effects of Moss-Dominated Biocrusts on Soil Microbial Community Structure in an Ionic Rare Earth Tailings Area of Southern China.

Moss-dominated biocrusts are widespread in degraded mining ecosystems and play an important role in soil development and ecosystem primary succession. In this work, the soil microbial community structure under moss-dominated biocrusts in ionic rare earth tailings was investigated to reveal the relationship between different types of moss and taxonomy/function of microbiomes. The results showed that microbial community structure was significantly influenced by four moss species (Claopodium rugulosifolium, Orthotrichum courtoisii, Polytrichum formosum, and Taxiphyllum giraldii). The microbial assembly was more prominent in Claopodium rugulosifolium soil than in the other moss soils, which covers 482 bacterial genera (including 130 specific genera) and 338 fungal genera (including 72 specific genera), and the specific genus is 40% to 1300% higher than that of the other three mosses. Although only 141 and 140 operational taxonomic units (OTUs) rooted in bacterial and fungal clusters, respectively, were shared by all four mosses grown in ionic rare earth tailings, this core microbiome could represent a large fraction (28.2% and 38.7%, respectively) of all sequence reads. The bacterial population and representation are the most abundant, which mainly includes Sphingomonas, Clostridium_sensu_stricto_1, and unclassified filamentous bacteria and chloroplasts, while the fungi population is relatively singular. The results also show that biocrust dominated by moss has a positive effect on soil microbe activity and soil nutrient conditions. Overall, these findings emphasize the importance of developing moss-dominated biocrusts as hotspots of ecosystem functioning and precious microbial genetic resources in degraded rare-earth mining areas and promoting a better understanding of biocrust ecology in humid climates under global change scenarios.

Case report: A novel CASK mutation in a Chinese female child with microcephaly with pontine and cerebellar hypoplasia.

Objective: Microcephaly with pontine and cerebellar hypoplasia (MICPCH) is a rare X-linked dominant genetic disease, and most MICPCHs are ascribed to CASK mutations, while few are revealed in Chinese patients. This study aims to identify the pathogenic mutation in a Chinese proband with MICPCH. Methods: A 3-year-old female Chinese proband with MICPCH and her parents were included. Clinical data were collected from the medical records and recalled by the proband's mother. Whole genome sequencing and Sanger sequencing were used to find the pathogenic mutation of MICPCH. Results: The proband presented with postnatal progressive microcephaly, cerebellar hypoplasia, intellectual disability, motor and language development retardation and limb hypertonia. Genetic analysis indicated that there was a novel compound heterozygote nonsynonymous mutation, c.755T>C(p.Leu252Pro) in exon8 of CASK gene in the proband, but not in her parents. This CASK mutation has not been reported in other databases. Conclusion: This study broadens the mutation spectrum of the CASK gene and is of great value for precise prenatal diagnosis and genetic counseling.

Regularized Spectral Spike Response Model: A Neuron Model for Robust Parameter Reduction.

The modeling procedure of current biological neuron models is hindered by either hyperparameter optimization or overparameterization, which limits their application to a variety of biologically realistic tasks. This article proposes a novel neuron model called the Regularized Spectral Spike Response Model (RSSRM) to address these issues. The selection of hyperparameters is avoided by the model structure and fitting strategy, while the number of parameters is constrained by regularization techniques. Twenty firing simulation experiments indicate the superiority of RSSRM. In particular, after pruning more than 99% of its parameters, RSSRM with 100 parameters achieves an RMSE of 5.632 in membrane potential prediction, a VRD of 47.219, and an F1-score of 0.95 in spike train forecasting with correct timing (±1.4 ms), which are 25%, 99%, 55%, and 24% better than the average of other neuron models with the same number of parameters in RMSE, VRD, F1-score, and correct timing, respectively. Moreover, RSSRM with 100 parameters achieves a memory use of 10 KB and a runtime of 1 ms during inference, which is more efficient than the Izhikevich model.

Associations among prenatal PM2.5, birth weight, and renal function.

BACKGROUND: Low birth weight has long-term health effects, including neurodevelopmental delays, cardiovascular diseases, and type 2 diabetes, through epigenetic changes and modifications. Numerous studies have identified that PM2.5 is associated with low birth weight. However, the association between PM2.5 and renal function, as well as the mediated effect of renal function on the association between prenatal PM2.5 and birth weight are still under-recognized. METHODS: A total of 8969 singleton live births born in 2015-2019 were included in this study. The inverse distance weighting method was applied to interpolate and calculate the average exposure to PM2.5 during pregnancy for each pregnant woman. The multiple linear regression model was used to shed light on the associations among prenatal PM2.5, birth weight, and renal function. In addition, the mediation analysis was performed to figure out the mediated effect of renal function on the association between prenatal PM2.5 and birth weight, and the proportion of mediated effect = (indirect effect/total effect) × 100%. RESULTS: Per 10 µg/m3 increment of prenatal PM2.5 was associated with 8.98 g (95% CI: -16.94 to -1.02) decrease of birth weight, 0.49 (95% CI: -0.73 to -0.26) ml/min/1.73 m2 decrease of glomerular filtration rate (GFR), 0.03 (95% CI: 0.01-0.05) mmol/L increase of blood urea nitrogen (BUN), and 2.29 (95% CI: 0.86-3.72) µmol/L increase of uric acid (UA) after adjusting for the sociodemographic covariates, disease-related covariates and meteorological factors. Besides, the mediated effects of GFR and BUN on the association between prenatal PM2.5 and birth weight were 5.02% and 14.96%, but there was no significant mediated effect being identified in UA. CONCLUSION: Prenatal PM2.5 is related to reduced birth weight and impaired renal function. Renal function plays a partial role in the association between prenatal PM2.5 and birth weight. Appropriate guidelines should be formulated by the concerned authorities, and adequate efforts should be made to mitigate the detrimental health effects of PM2.5.

Maternal sleep during pregnancy and adverse pregnancy outcomes: A systematic review and meta-analysis.

AIMS/INTRODUCTION: Sleep problems are important public health concern worldwide. We carried out a meta-analysis to quantitatively evaluate whether sleep duration was associated with pregnancy outcomes, and the associations were modified by important characteristics of studies. MATERIALS AND METHODS: Based on PubMed, Embase and the Cochrane Central Register of Controlled Trials databases, we searched for published literature related to maternal sleep duration and adverse pregnancy outcomes before 30 June 2021. We carried out risk of bias assessment, subgroup analyses and sensitivity analysis. The relative risks or odds ratios with 95% confidence intervals (CI) were used to estimate the pooled effects. RESULTS: A total of 5,246 references were identified through a database search, and 41 studies were included in the study. Pregnant women with short sleep duration had 1.81-fold (95% CI 1.35-2.44, P < 0.001) the risk of developing gestational diabetes mellitus. The association between short sleep duration and the risk of gestational hypertension, cesarean section, low birthweight, preterm birth and small for gestational age were not significant (P > 0.05). Furthermore, long sleep duration was significantly correlated with gestational diabetes mellitus (odds ratio1.24. 95% CI 1.12-1.36, P < 0.001) and CS (odds ratio 1.13. 95% CI 1.04-1.22, P = 0.004), whereas long sleep duration was not linked with gestational hypertension, low birthweight, preterm birth and small for gestational age (P > 0.05). CONCLUSIONS: Short/long sleep duration appeared to be associated with adverse pregnancy outcomes, specifically with an increased risk of gestational diabetes mellitus. Sleep should be systematically screened in the obstetric population.

Effects of PM2.5 and its constituents on hemoglobin during the third trimester in pregnant women.

Anemia has been a public health issue evoking global concern, and the low hemoglobin (Hb) concentration links to adverse pregnancy outcomes. However, the associations of PM2.5 and its constituents with Hb and anemia in pregnant women remain unclear. In this retrospective birth cohort study, 7932 pregnant women who delivered in the First Affiliated Hospital of Xi'an Jiaotong University from 2015 to 2018 were included. The Hb during the third trimester in pregnant women was assessed before delivery. PM2.5 and its constituents (BC, NH4+, NO3-, OM, SO42-, and Dust) during pregnancy were retrieved from the V4.CH.03 product constructed by the Atmospheric Composition Analysis Group. Generalized linear regression model was applied to investigate the effects of PM2.5 and its constituents on Hb and anemia during the third trimester in pregnant women. The means and standard deviations of PM2.5, BC, NH4+, NO3-, OM, SO42-, and Dust were 69.56 (15.24), 10.02 (2.72), 8.11 (1.77), 14.96 (5.42), 15.36 (4.11), 10.08 (1.20), and 10.98 (1.85) µg/m3, respectively. Per IQR increase (µg/m3) of PM2.5, BC, NO3-, and OM linked to - 0.75 (- 1.50, - 0.01), - 0.85 (- 1.65, - 0.04), - 0.79 (- 1.56, - 0.03), and - 0.73 (- 1.44, - 0.03) g/L decrease of Hb during the third trimester in multiparous pregnant women, but not for NH4+, SO42-, Dust, and primiparous pregnant women. PM2.5 and its constituents had no significant association with anemia, except for Dust (OR: 0.90, 95% CI: 0.82, 0.99, per IQR increase) in primiparous pregnant women. Besides, SO42- was of lag effects on Hb and anemia in multiparous pregnant women. Moreover, non-linear associations were found among PM2.5 and its constituents, Hb, and anemia. Therefore, exposure to PM2.5 and some constituents of PM2.5 was associated with reduced Hb level during the third trimester in multiparous pregnant women. Related departments and pregnant women should take targeted actions to eliminate the detrimental effects of PM2.5 and its constituents on pregnancy outcomes.

Prenatal exposure to air pollution and the risk of macrosomia: Identifying windows of susceptibility.

This study explores the effects of prenatal exposure to air pollution on the risk of macrosomia and its window of susceptibility. We conducted a retrospective cohort study utilizing records of birth certificates for all full-term live newborns born in Xi'an city, China from January 1, 2015, to December 31, 2018.Weekly- and trimester-specific exposures of PM2.5, PM10, NO2, and O3 during pregnancy were calculated by inverse distance weighting (IDW) based on their residences. Cox proportional hazard model and distributed lag models (DLMs) were performed to estimate the effects of air pollution exposure during pregnancy on macrosomia risk and its window of susceptibility. In total, 318,323 full-term newborns were identified, including 24,996 (7.8%) cases of macrosomia. An IQR increase in PM2.5 exposure (45.46 µg/m3) from the 33rd until the 37th weeks of gestation was positively associated with an elevated risk of macrosomia, with the strongest effect in the 37th weeks (HR = 1.007, 95%CI: 1.002-1.013). The window of susceptibility for NO2 exposure on macrosomia risk was in the 29th-35th gestational weeks, with the strongest effect in the 34th weeks (IQR = 21.96 µg/m3, HR = 1.006, 95%CI:1.000-1.013). For prenatal exposure to O3, 5th-24th weeks of gestation was identified as susceptible windows for elevated risk of macrosomia, with the strongest associations observed in the 15th weeks (IQR = 80.53 µg/m3, HR = 1.022, 95%CI: 1.011-1.033). However, we did not observe any associations between weekly exposure of PM10 and macrosomia. Our findings imply that the windows of susceptibility to PM2.5 and NO2 exposure on macrosomia are mainly in late pregnancy, whereas the windows of susceptibility to O3 exposure are in early and middle pregnancy.

Socio-Economic Factors Affecting the Regional Spread and Outbreak of COVID-19 in China.

BACKGROUND: This study investigated the impact of socio-economic factors on the spread and outbreak of COVID-19 based on Chinese data. METHODS: Cumulative confirmed cases were collected and divided into the First-stage cases cluster dominated by imported cases, and the Second-stage cases cluster dominated by secondary cases, according to the time of emergency state and Wuhan city lockdown. The linear regression was used for data analysis. RESULTS: A total of 12,877 cases in 30 provinces were analyzed in the study. The First-stage cases cluster included 675 cases and Second-stage cases cluster included 12,202 cases. The socio-economic factors were significantly associated with the cases (P<0.05). The GDP and proportion of population moving out of Wuhan were associate with the First-stage dominated by imported cases (ß>0, P<0.05). The First-stage cases cluster, proportion of population moving out of Wuhan and urban population were associate with the Second-stage dominated by secondary cases (ß>0, P<0.05). CONCLUSION: Socio-economic factors had impacts on the spread and outbreak of COVID-19. The combination of different socio-economic indicators at different stages of the epidemic may help control the epidemic.

Maternal exposure to PM2.5 was linked to elevated risk of stillbirth.

BACKGROUND: More and more studies began to explore the hazardous health effects of PM2.5, but few reported its impacts on stillbirth. The sparse results were inconsistent and remained to be integrated. Therefore, we aimed to reveal the association between maternal exposure to PM2.5 and stillbirth. METHODS: In this meta-analysis, we searched PubMed, Web of Science, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases for related articles written in English and published before October 18, 2020. Study selection was conducted according to the predetermined criteria and data attraction was done with predesigned form. A new instrument was applied to conduct the risk of bias assessment. And random-effect models were used to pool the estimates. RESULTS: A total of 3655 records were identified from the databases, but only 7 studies were ultimately included in this study. Positive association was found between the maternal exposure to PM2.5 (per 10 µg/m3 increased) in the entire pregnancy (OR: 1.15, 95% CI: 1.07-1.25) and third trimester (OR: 1.09, 95% CI: 1.01-1.18) and stillbirth, but the association between the maternal exposure to PM2.5 (per 10 µg/m3 increased) in the first trimester (OR: 1.01, 95% CI: 0.90-1.13) and second trimester (OR: 1.06, 95% CI: 0.98-1.14) and stillbirth was not statistically significant. Besides, there was no publication bias. CONCLUSIONS: Maternal exposure to PM2.5 in the entire pregnancy and third trimester was associated with elevated risk of stillbirth. However, due to the high heterogeneity, further pathophysiological researches and high quality population studies were still warranted.

Local treatment for triple-negative breast cancer patients undergoing chemotherapy: breast-conserving surgery or total mastectomy?

BACKGROUND: Because there is no exact therapeutic target, the systemic treatment of triple-negative breast cancer (TNBC) still relies on chemotherapy. In terms of local treatment, based on the highly malignant characteristics of TNBC, it is still uncertain whether patients should be given more aggressive local treatment. METHODS: This study was based on the SEER database. 13,262 TNBC patients undergoing chemotherapy were included. According to local treatment methods, patients were divided into breast-conserving surgery with radiotherapy (BCS + RT), total mastectomy alone and total mastectomy with radiotherapy (Mastectomy+RT). Kaplan-Meier survival analysis drew the survival curves of Overall Survival (OS) and Breast Cancer Specific Survival (BCSS), and Cox proportional risk regression models were used to analyze the impact of different local treatments on OS and BCSS. RESULTS: After adjusting confounding factors, Mastectomy alone group (HR = 1.57; 95%CI: 1.40-1.77) and Mastectomy+RT group (HR = 1.28; 95%CI: 1.12-1.46) were worse in OS than BCS + RT group, and Mastectomy+RT group (HR = 0.81; 95%CI: 0.73-0.91) was better in OS than Mastectomy alone group. The effect of local treatment for BCSS was similar to that of OS. After stratification according to age, tumor size and lymph node status, when the age was less than 55 years old, at T4, N2 or N3 category, there was no statistical significance between the BCS + RT group and the Mastectomy+RT group in OS or BCSS (all P > 0.05). When the age was less than 65 years old, at T1, T2 or N0 category, there was no statistical significance between the Mastectomy alone group and the Mastectomy+RT group in OS or BCSS (all P > 0.05). The results of other stratified analyses were basically consistent with the results of total population analysis. CONCLUSION: The survival benefit of breast-conserving surgery with radiotherapy was higher than or similar to that of total mastectomy TNBC patients.

Competing risk nomogram predicting cancer-specific mortality for endometrial cancer patients treated with hysterectomy.

BACKGROUND: The incidence of endometrial cancer has tended to increase in recent years. However, competing risk nomogram combining comprehensive factors for endometrial cancer patients treated with hysterectomy is still scarce. Therefore, we aimed to build a competing risk nomogram predicting cancer-specific mortality for endometrial cancer patients treated with hysterectomy. METHODS: Patients diagnosed with endometrial cancer between 2010 and 2012 were abstracted from the Surveillance, Epidemiology, and End Results (SEER) database. Competing risk model was performed to select prognostic variables to build the competing risk nomogram to predict the cumulative 3- and 5-year incidences of endometrial cancer-specific mortality. Harrell's C-index, receiver operating characteristic (ROC) curve, and calibration plot were used in the internal validation. And decision curve analysis was applied to evaluate clinical utility. RESULTS: A total of 10,447 patients were selected for analysis. The competing risk nomogram identified eight prognostic variables, including age at diagnosis, race, marital status at diagnosis, grade, histology, tumor size, FIGO stage, and number of regional nodes positive. The C-index of the competing risk nomogram was 0.857 (95% confidence interval [CI]: 0.854-0.859), and the calibration plots were adequately fitted. When the threshold probabilities were between 1% and 57% for 3-year prediction and between 2% and 67% for 5-year prediction, the competing risk nomogram was of good clinical utility. CONCLUSIONS: A competing risk nomogram for endometrial cancer patients treated with hysterectomy was successfully built and internally validated. It was an accurately predicted and clinical useful tool, which could play an important role in consulting and health care management of endometrial cancer patients.

Maternal exposure to O3 and NO2 may increase the risk of newborn congenital hypothyroidism: a national data-based analysis in China.

Maternal exposure to air pollution during pregnancy is associated with adverse outcomes in the offspring, but limited studies focused on the impacts of gaseous air pollution on newborn congenital hypothyroidism (CH). Therefore, a national data-based analysis was conducted to explore the association between maternal exposure to gaseous air pollution and the incidence of CH in China. Annual average exposure levels of SO2, NO2, CO, and O3 from January 1, 2014, to December 30, 2014, were acquired from the Chinese Air Quality Online Monitoring and Analysis Platform. The annual incidence of newborn CH from October 1, 2014, to September 30, 2015, was collected from the Chinese Maternal and Child Health Surveillance Network. Temperature and toxic metal in wastewater in 2014 were also collected as covariates. Maternal exposure to O3 and NO2 in 1 µg/m3 level increment was positively associated with newborn CH, with an OR of 1.055 (95% CI 1.011, 1.102) and 1.097 (95% CI 1.019, 1.182) after adjusting for covariates completely. Compared with the lowest level of O3, maternal exposure to the 4th quartile of O3 was positively associated with newborn CH (OR 1.393, 95% CI 1.081, 1.794) after adjusting for covariates completely. And the 3rd and 4th quartiles of NO2 were associated positively with CH (OR 1.576, 95% CI 1.025, 2.424, and OR 1.553, 95% CI 0.999, 2.414, respectively) compared with the lowest level of NO2. By fitting the ROC curve, 93.688 µg/m3 in O3 might be used as cutoff to predict the incidence of newborn CH in China.

Development and validation of nomograms for epithelial ovarian cancer: a SEER population-based, real-world study.

Aim: To develop and internally validate nomograms to predict the overall survival (OS) and the cancer-specific survival (CSS) of patients with epithelial ovarian cancer (EOC). Methods: A total of 9001 EOC patients diagnosed between 2010 and 2013 were randomly divided into the training (n = 6301) and validation (n = 2700) cohorts. Nomogram and bootstrap validation were used to assess the predictive values of the models, including discrimination, calibration and clinical benefit. Results: In the validation cohort, the concordance statistic values were 0.733 for OS and 0.747 for CSS. Calibration plots and decision curve analyses demonstrated moderate accuracy and clinical applicability. Conclusion: Nomograms were user-friendly tools for guiding clinical treatment and estimating prognosis.

Impact of air pollution exposure during various periods of pregnancy on term birth weight: a large-sample, retrospective population-based cohort study.

Previous studies have suggested that maternal exposure to air pollution might affect term birth weight. However, the conclusions are controversial. Birth data of all term newborns born in Xi'an city of Shaanxi, China, from 2015 to 2018 and whose mother lived in Xi'an during pregnancy were selected form the Birth Registry Database. And the daily air quality data of Xi'an city was collected from Chinese Air Quality Online Monitoring and Analysis Platform. Generalized additive models (GAM) and 2-level binary logistic regression models were used to estimate the effects of air pollution exposure on term birth weight, the risk term low birth weight (TLBW), and macrosomia. Finally, 321521 term newborns were selected, including 4369(1.36%) TLBW infants and 24,960 (7.76%) macrosomia. The average pollution levels of PM2.5, PM10, and NO2 in Xi'an city from 2015 to 2018 were higher than national limits. During the whole pregnancy, maternal exposure to PM2.5, PM10, SO2, and CO all significantly reduced the term birth weight and increased the risk of TLBW. However, NO2 and O3 exposure have significantly increased the term birth weight, and O3 even increased the risk of macrosomia significantly. Those effects were also observed in the first and second trimesters of pregnancy. But during the third trimester, high level of air quality index (AQI) and maternal exposure to PM2.5, PM10, SO2, NO2, and CO increased the term birth weight and the risk of macrosomia, while O3 exposure was contrary to this effect. The findings suggested that prenatal exposure to air pollution might cause adverse impacts on term birth weight, and the effects varied with trimesters and pollutants, which provides further pieces of evidence for the adverse effects of air pollution exposure in heavy polluted-area on term birth weight.

Changing trends of birth weight with maternal age: a cross-sectional study in Xi'an city of Northwestern China.

BACKGROUND: Most studies have shown that maternal age is associated with birth weight. However, the specific relationship between each additional year of maternal age and birth weight remains unclear. The study aimed to analyze the specific association between maternal age and birth weight. METHODS: Raw data for all live births from 2015 to 2018 were obtained from the Medical Birth Registry of Xi'an, China. A total of 490,143 mother-child pairs with full-term singleton live births and the maternal age ranging from 20 to 40 years old were included in our study. Birth weight, gestational age, neonatal birth date, maternal birth date, residence and ethnicity were collected. Generalized additive model and two-piece wise linear regression model were used to analyze the specific relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia. RESULTS: The relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia were nonlinear. Birth weight increased 16.204 g per year when maternal age was less than 24 years old (95%CI: 14.323, 18.086), and increased 12.051 g per year when maternal age ranged from 24 to 34 years old (95%CI: 11.609, 12.493), then decreased 0.824 g per year (95% CI: -3.112, 1.464). The risk of low birth weight decreased with the increase of maternal age until 36 years old (OR = 0.917, 95%CI: 0.903, 0.932 when maternal age was younger than 27 years old; OR = 0.965, 95%CI: 0.955, 0.976 when maternal age ranged from 27 to 36 years old), then increased when maternal age was older than 36 years old (OR = 1.133, 95%CI: 1.026, 1.250). The risk of macrosomia increased with the increase of maternal age (OR = 1.102, 95%CI: 1.075, 1.129 when maternal age was younger than 24 years old; OR = 1.065, 95%CI: 1.060, 1.071 when maternal age ranged from 24 to 33 years old; OR = 1.029, 95%CI: 1.012, 1.046 when maternal age was older than 33 years old). CONCLUSIONS: For women of childbearing age (20-40 years old), the threshold of maternal age on low birth weight was 36 years old, and the risk of macrosomia increased with the increase of maternal age.

Calculating the overall survival probability in patients with cervical cancer: a nomogram and decision curve analysis-based study.

BACKGROUND: Cervical cancer has long been a common malignance troubling women. However, there are few studies developing nomogram with comprehensive factors for the prognosis of cervical cancer. Hence, we aimed to build a nomogram to calculate the overall survival (OS) probability in patients with cervical cancer. METHODS: Data of 9876 female patients in SEER database and diagnosed as cervical cancer during 2010-2015, was retrospectively analyzed. Univariate and multivariate Cox proportional hazard regression model were applied to select predicted factors and a nomogram was developed to visualize the prediction model. The nomogram was compared with the FIGO stage prediction model. Harrell's C-index, receiver operating curve, calibration plot and decision curve analysis were used to assess the discrimination, accuracy, calibration and clinical utility of the prediction models. RESULT: Eleven independent prognostic variables, including age at diagnosis, race, marital status at diagnosis, grade, histology, tumor size, FIGO stage, primary site surgery, regional lymph node surgery, radiotherapy and chemotherapy, were used to build the nomogram. The C-index of the nomogram was 0.826 (95% CI: 0.818 to 0.834), which was better than that of the FIGO stage prediction model (C-index: 0.785, 95% CI: 0.776 to 0.793). Calibration plot of the nomogram was well fitted in 3-year overall OS prediction, but overfitting in 5-year OS prediction. The net benefit of the nomogram was higher than the FIGO prediction model. CONCLUSION: A clinical useful nomogram for calculating the overall survival probability in cervical cancer patients was developed. It performed better than the FIGO stage prediction model and could help clinicians to choose optimal treatments and precisely predict prognosis in clinical care and research.

The association between prenatal exposure to polycyclic aromatic hydrocarbons and birth weight: A meta-analysis.

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are a kind of endocrine disruptors, which can enter human body by the inhalation of PAH-containing matter and the ingestion of PAH-containing foodstuffs. Studies showed that PAHs can cross the placental barrier and might cause adverse effects on the fetus. OBJECTIVES: This meta-analysis aimed to estimate the associations between prenatal exposure to PAHs and birth weight. METHODS: Articles published in English until May 8, 2020 and reported the effects of prenatal exposure to PAHs on birth weight were searched in multiple electronic databases including PubMed, the Web of Science, EMBASE and the Cochrane Library. The included studies were divided into three groups in accordance with the measurement of PAHs exposure. Then coefficient was extracted, conversed and synthesized by random-effects meta-analysis. And risk of bias was assessed for each study. RESULTS: A total of 3488 citations were searched and only 11 studies were included finally after double assessment. We found that there were no association between PAH-DNA adducts in cord blood (low/high) (OR: 1.0, 95%CI: 0.97, 1.03), 1-hydroxy pyrene (1-HP) concentration in maternal urine (OR: 1.0, 95%CI: 0.97, 1.03) and prenatal maternal airborne PAHs exposure (OR: 0.97, 95%CI: 0.93, 1.01) and birth weight. However, we observed ethnicity may change the effects of PAHs exposure on birth weight. CONCLUSIONS: There is no significant relationship between prenatal exposure to PAHs and birth weight in our meta-analysis. Further studies are still needed for determining the effects of prenatal PAHs exposure on birth weight.