Low-dose aspirin for the prevention of preterm birth in nulliparous women: systematic review and meta-analysis.

OBJECTIVE: The objective was to assess the efficacy and safety of low-dose aspirin for the prevention of preterm birth in nulliparous women. DATA SOURCES: We searched PubMed, Embase and the Cochrane Central Register of Controlled Trials (CENTRAL) from inception to June 2022. STUDY ELIGIBILITY CRITERIA: Randomized controlled trials that compared aspirin to placebo in nulliparous women were eligible. METHODS: This study was reported in accordance with the PRISMA 2020 checklist. The primary outcomes of this study were the rates of preterm birth at less than 37 weeks and less than 34 weeks of gestation. The secondary outcomes included postpartum hemorrhage, placental abruption, cesarean section, any hypertensive disorder of pregnancy and small for gestational age. Relative risks with their 95% confidence intervals were calculated for analysis. Heterogeneity was assessed by Cochran's Q test and Higgins's I2. A random-effects model was used when I2 was > 50% to generate the RR and 95% CI; otherwise, a fixed-effects model was used. The risk of publication bias was assessed by funnel plots. We performed sensitivity analysis by sequentially omitting each included study to confirm the robustness of the analysis. RESULTS: Seven studies with a total of 29,029 participants were included in this review. Six studies were assessed as having a low risk of bias or an unclear risk of bias, and one study was judged as having a high risk of bias. In nulliparous women, low-dose aspirin was associated with a significant reduction in the rate of preterm birth at less than 34 weeks of gestational age (RR 0.84,95% CI: 0.71-0.99; I2 = 0%; P = 0.04), but we did not observe a significant difference in the rate of preterm birth at less than 37 weeks of gestation (RR 0.96,95% CI: 0.90-1.02; I2 = 31%; P = 0.18). Low-dose aspirin was associated with a significant increase in the rates of postpartum hemorrhage (RR 1.32,95% CI: 1.14-1.54; I2 = 0%; P = 0.0003), placental abruption (RR 2.18,95% CI: 1.10-4.32; I2 = 16%; P = 0.02) and cesarean section (RR 1.053, 95% CI: 1.001-1.108; I2 = 0%; P = 0.05) in nulliparous women. We also did not observe a significant effect of low-dose aspirin on the rates of any hypertensive disorder of pregnancy (RR 1.05, 95% CI: 0.96-1.14; I2 = 9%; P = 0.28) or small for gestational age (RR 0.96, 95% CI: 0.91-1.02; I2 = 0%; P = 0.16) in nulliparous women. Funnel plots indicated that no significant publication bias existed in this meta-analysis. Except for preterm birth at less than 34 weeks of gestation, placental abruption and cesarean section, the sensitivity analysis showed similar results, which confirmed the robustness of this meta-analysis. CONCLUSIONS: Low-dose aspirin might reduce the risk of preterm birth at less than 34 weeks of gestation in nulliparous women. The use of low-dose aspirin in nulliparous women increased the risk of postpartum hemorrhage and might increase the risk of placental abruption and cesarean section.

The quality evaluation of 30 Asparagus officinalis L. varieties.

Asparagus, a vital economic contributor, is a well-liked vegetable grown around the globe, and some secondary metabolites in its spear are beneficial to human health. Asparagus spears possess a significant quantity of nutrients and phytochemicals; however, the difference in these chemical compositions among various varieties has not been sufficiently studied. This work aimed to detect the chemical compositions of 30 varieties of asparagus and to assess them by principal component analysis (PCA). The results showed that the contents of these chemical compositions varied in varieties. Selenium (Se, 1.12-2.9 µg/100 g dry-weight [DW]) was abundant in asparagus, with an average dry matter content of 8.25%. Free amino acids (5.60-9.98 g/100 g DW) and polyphenols (6.34-8.67 mg/g DW) were both present in high amounts, along with flavonoids (4.218-8.22 mg/g DW) and protodioscin (0.44-1.96 mg/g DW). Correlation analysis, PCA, and hierarchical cluster analysis were used to conduct a comprehensive evaluation of asparagus. Atlas, Appolo, Jinggang 111, Jingke 2, and WS-1 were the top five varieties with comprehensive scores. This study provided valuable data for the breeding, quality improvement, processing, and utilization of asparagus varieties in the future.

Gestational weight gain and pregnancy outcomes in Chinese women with type 2 diabetes mellitus: evidence from a tertiary hospital in Beijing.

Objective: To examine the effects of gestational weight gain on pregnancy outcomes and determine the optimal range of weight gain during pregnancy for Chinese women with type 2 diabetes mellitus. Methods: This retrospective cohort study included 691 Chinese women with type 2 diabetes mellitus from 2012 to 2020. The study utilized a statistical-based approach to determine the optimal range of gestational weight gain. Additionally, multivariate logistic regression analysis was conducted to assess the impact of gestational weight gain on pregnancy outcomes. Results: (1) In the obese subgroup, gestational weight gain below the recommendations was associated with decreased risks of large for gestational age (adjusted odds ratio [aOR] 0.19; 95% confidence interval [CI] 0.06-0.60) and macrosomia (aOR 0.18; 95% CI 0.05-0.69). In the normal weight subgroup, gestational weight gain below the recommendations of the Institute of Medicine was associated with decreased risks of preeclampsia (aOR 0.18; 95% CI 0.04-0.82) and neonatal hypoglycemia (aOR 0.38; 95% CI 0.15-0.97). (2) In the normal weight subgroup, gestational weight gain above the recommendations of the Institute of Medicine was associated with an increased risk of large for gestational age (aOR 4.56; 95% CI 1.54-13.46). In the obese subgroup, gestational weight gain above the recommendations was associated with an increased risk of preeclampsia (aOR 2.74; 95% CI 1.02, 7.38). (3) The optimal ranges of gestational weight gain, based on our study, were 9-16 kg for underweight women, 9.5-14 kg for normal weight women, 6.5-12 kg for overweight women, and 3-10 kg for obese women. (4) Using the optimal range of gestational weight gain identified in our study seemed to provide better prediction of adverse pregnancy outcomes. Conclusion: For Chinese women with type 2 diabetes, inappropriate gestational weight gain is associated with adverse pregnancy outcomes, and the optimal range of gestational weight gain may differ from the Institute of Medicine recommendations.

Phospholipid Type Regulates Protein Corona Composition and In Vivo Performance of Lipid Nanodiscs.

Over the years, there has been significant interest in PEGylated lipid-based nanocarriers within the drug delivery field. The inevitable interplay between the nanocarriers and plasma protein plays a pivotal role in their in vivo biological fate. Understanding the factors influencing lipid-based nanocarrier and protein corona interactions is of paramount importance in the design and clinical translation of these nanocarriers. Herein, discoid-shaped lipid nanodiscs (sNDs) composed of different phospholipids with varied lipid tails and head groups were fabricated. We investigated the impact of phospholipid components on the interaction between sNDs and serum proteins, particle stability, and biodistribution. The results showed that all of these lipid nanodiscs remained stable over a 15 day storage period, while their stability in the blood serum demonstrated significant differences. The sND composed of POPG exhibited the least stability due to its potent complement activation capability, resulting in rapid blood clearance. Furthermore, a negative correlation between the complement activation capability and serum stability was identified. Pharmacokinetic and biodistribution experiments indicated that phospholipid composition did not influence the capability of sNDs to evade the accelerated blood clearance phenomenon. Complement deposition on the sND was inversely associated with the area under the curve. Additionally, all lipid nanodiscs exhibited dominant adsorption of apolipoprotein. Remarkably, the POPC-based lipid nanodisc displayed a significantly higher deposition of apolipoprotein E, contributing to an obvious brain distribution, which provides a promising tool for brain-targeted drug delivery.

Molybdenum Concentration and the Risk of Spontaneous Preterm Birth: A Nested Case-Control Study - Beijing Municipality, China, 2018-2020.

What is already known about this topic?: The level of molybdenum (Mo) in a mother's urine has been linked to the growth rate of the fetus and the blood pressure levels in children. What is added by this report?: We evaluated the variations in maternal plasma Mo concentrations throughout pregnancy and their potential association with the risk of spontaneous preterm birth (SPB). What are the implications for public health practice?: Future research must determine the Mo levels in pregnant women across various regions in China. Moreover, particular attention needs to be given to the potential increase in Mo concentration throughout pregnancy and its possible adverse impacts on the health of both the mother and the fetus.

Butyrate and iso-butyrate: a new perspective on nutrition prevention of gestational diabetes mellitus.

BACKGROUND: Dietary imbalance, such as a lower proportion of complex carbohydrates and a higher protein diet, may contribute to gestational diabetes mellitus (GDM) risks through their metabolisms. However, there is a lack of knowledge regarding the association between butyrate, iso-butyrate, and GDM, which are metabolisms of the two primary nutrients above. This study aimed to clarify the association of butyrate and iso-butyrate with GDM. METHODS: A nested case-control study was conducted based on the Beijing Birth Cohort Study (BBCS) from 2017 to 2018. Totally, 99 singleton women were involved (GDM: n = 49, control: n = 50). All participants provided blood samples twice (in their first and second trimesters). Gas chromatography-mass spectrometry (GC-MS) was used for butyrate and iso-butyrate detection. Unconditional logistic regression and receiver operating characteristic (ROC) curve analysis were used for statistical analysis. RESULTS: The results showed that butyrate in the first trimester was negatively correlated with GDM (odds ratio (OR): 0.00, 95% confidential interval (CI): 0.00-0.21, P = 0.008), and iso-butyrate in the second trimester was positively related to GDM (OR: 627.68, 95% CI: 40.51-9724.56, P < 0.001). The ratio (butyrate/iso-butyrate) was negatively associated with GDM, both in the first trimester (OR: 0.00, 95%CI: 0.00-0.05, P < 0.001) and in the second trimester (OR: 0.52, 95% CI: 0.34-0.80, P = 0.003). The area under the curve (AUC) using the ratio in the first trimester combined with clinical risk factors achieved 0.89 (95% CI: 0.83-0.95). Iso-butyrate in the second trimester combined with clinical risk factors achieved an AUC of 0.97 (95% CI: 0.92-1.00). CONCLUSIONS: High iso-butyrate and low butyrate levels may be associated with an increased risk of GDM. As they are produced through dietary nutrient formation by gut microbiota, further studies on the association of dietary intake and butyrate or iso-butyrate concentration in plasma may help find a novel approach to nutritional intervention for GDM.

The influence of maternal prepregnancy weight and gestational weight gain on the umbilical cord blood metabolome: a case-control study.

BACKGROUND: Maternal overweight/obesity and excessive gestational weight gain (GWG) are frequently reported to be risk factors for obesity and other metabolic disorders in offspring. Cord blood metabolites provide information on fetal nutritional and metabolic health and could provide an early window of detection of potential health issues among newborns. The aim of the study was to explore the impact of maternal prepregnancy overweight/obesity and excessive GWG on cord blood metabolic profiles. METHODS: A case control study including 33 pairs of mothers with prepregnancy overweight/obesity and their neonates, 30 pairs of mothers with excessive GWG and their neonates, and 32 control mother-neonate pairs. Untargeted metabolomic profiling of umbilical cord blood samples were performed using UHPLC‒MS/MS. RESULTS: Forty-six metabolites exhibited a significant increase and 60 metabolites exhibited a significant reduction in umbilical cord blood from overweight and obese mothers compared with mothers with normal body weight. Steroid hormone biosynthesis and neuroactive ligand‒receptor interactions were the two top-ranking pathways enriched with these metabolites (P = 0.01 and 0.03, respectively). Compared with mothers with normal GWG, in mothers with excessive GWG, the levels of 63 metabolites were increased and those of 46 metabolites were decreased in umbilical cord blood. Biosynthesis of unsaturated fatty acids was the most altered pathway enriched with these metabolites (P < 0.01). CONCLUSIONS: Prepregnancy overweight and obesity affected the fetal steroid hormone biosynthesis pathway, while excessive GWG affected fetal fatty acid metabolism. This emphasizes the importance of preconception weight loss and maintaining an appropriate GWG, which are beneficial for the long-term metabolic health of offspring.

HSPA4 upregulation induces immune evasion via ALKBH5/CD58 axis in gastric cancer.

INTRODUCTION: Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide. Recently, targeted therapies including PD1 (programmed cell death 1) antibodies have been used in advanced GC patients. However, identifying new biomarker for immunotherapy is still urgently needed. The objective of this study is to unveil the immune evasion mechanism of GC cells and identify new biomarkers for immune checkpoint blockade therapy in patients with GC. METHODS: Coimmunoprecipitation and meRIP were performed to investigate the mechanism of immune evasion of GC cells. Cocuture system was established to evaluate the cytotoxicity of cocultured CD8+ T cells. The clinical significance of HSPA4 upregulation was analyzed by multiplex fluorescent immunohistochemistry staining in GC tumor tissues. RESULTS: Histone acetylation causes HSPA4 upregulation in GC tumor tissues. HSPA4 upregulation increases the protein stability of m6A demethylase ALKBH5. ALKBH5 decreases CD58 in GC cells through m6A methylation regulation. The cytotoxicity of CD8+ T cells are impaired and PD1/PDL1 axis is activated when CD8+ T cells are cocultured with HSPA4 overexpressed GC cells. HSPA4 upregulation is associated with worse 5-year overall survival of GC patients receiving only surgery. It is an independent prognosis factor for worse survival of GC patients. In GC patients receiving the combined chemotherapy with anti-PD1 immunotherapy, HSPA4 upregulation is observed in responders compared with non-responders. CONCLUSION: HSPA4 upregulation causes the decrease of CD58 in GC cells via HSPA4/ALKBH5/CD58 axis, followed by PD1/PDL1 activation and impairment of CD8+ T cell's cytotoxicity, finally induces immune evasion of GC cells. HSPA4 upregulation is associated with worse overall survival of GC patients with only surgery. Meanwhile, HSPA4 upregulation predicts for better response in GC patients receiving the combined immunotherapy.

Physiological and biochemical mechanisms underlying the role of anthocyanin in acquired tolerance to salt stress in peanut (Arachis hypogaea L.).

Anthocyanin is an important pigment that prevents oxidative stress and mediates adaptation of plants to salt stress. Peanuts with dark red and black testa are rich in anthocyanin. However, correlation between salt tolerance and anthocyanin content in black and dark red testa peanuts is unknown. In this study, three peanut cultivars namely YZ9102 (pink testa), JHR1 (red testa) and JHB1 (black testa) were subjected to sodium chloride (NaCl) stress. The plant growth, ion uptake, anthocyanin accumulation, oxidation resistance and photosynthetic traits were comparatively analyzed. We observed that the plant height, leaf area and biomass under salt stress was highly inhibited in pink color testa (YZ9102) as compare to black color testa (JHB1). JHB1, a black testa colored peanut was identified as the most salt-tolerance cultivar, followed by red (JHR1) and pink(YZ9102). During salt stress, JHB1 exhibited significantly higher levels of anthocyanin and flavonoid accumulation compared to JHR1 and YZ9102, along with increased relative activities of antioxidant protection and photosynthetic efficiency. However, the K+/Na+ and Ca2+/Na+ were consistently decreased among three cultivars under salt stress, suggesting that the salt tolerance of black testa peanut may not be related to ion absorption. Therefore, we predicted that salt tolerance of JHB1 may be attributed to the accumulation of the anthocyanin and flavonoids, which activated antioxidant protection against the oxidative damage to maintain the higher photosynthetic efficiency and plant growth. These findings will be useful for improving salt tolerance of peanuts.

Identifying virulence factors using graph transformer autoencoder with ESMFold-predicted structures.

With the increasing resistance of bacterial pathogens to conventional antibiotics, antivirulence strategies targeting virulence factors (VFs) have become an effective new therapy for the treatment of pathogenic bacterial infections. Therefore, the identification and prediction of VFs can provide ideal candidate targets for the implementation of antivirulence strategies in treating infections caused by pathogenic bacteria. Currently, the existing computational models predominantly rely on the amino acid sequences of virulence proteins while overlooking structural information. Here, we propose a novel graph transformer autoencoder for VF identification (GTAE-VF), which utilizes ESMFold-predicted 3D structures and converts the VF identification problem into a graph-level prediction task. In an encoder-decoder framework, GTAE-VF adaptively learns both local and global information by integrating a graph convolutional network and a transformer to implement all-pair message passing, which can better capture long-range correlations and potential relationships. Extensive experiments on an independent test dataset demonstrate that GTAE-VF achieves reliable and robust prediction accuracy with an AUC of 0.963, which is consistently better than that of other structure-based and sequence-based approaches. We believe that GTAE-VF has the potential to emerge as a valuable tool for assessing VFs and devising antivirulence strategies.

DDX27 regulates oral squamous cell carcinoma development through targeting CSE1L.

THE HEADINGS AIMS: DEAD-box helicase 27 (DDX27), a member of the DEAD-Box nucleic acid helicase family, holds an elusive role in oral squamous cell carcinoma (OSCC). This study aims to unravel the regulatory functions of DDX27 in OSCC and explore its downstream targets. MATERIALS AND METHODS: A commercial oral squamous cell carcinoma (OSCC) tissue microarray (TMA) was utilized. We analyzed differentially expressed genes in OSCC through the GEO database. Target gene silencing was achieved using the shRNA-mediated lentivirus method. Coexpedia analysis identified co-expressed genes associated with DDX27. Additionally, a Co-Immunoprecipitation (Co-IP) experiment confirmed the protein interaction between DDX27 and CSE1L. Xenograft tumor models were employed to evaluate DDX27's role in OSCC tumor formation. KEY FINDINGS: Elevated DDX27 expression in OSCC correlated with a higher pathological grade. DDX27 knockdown resulted in decreased cell proliferation, increased apoptosis, inhibited cell migration, and induced G2/M phase cell cycle arrest, as well as impaired tumor outgrowth. Coexpedia analysis identified STAU1, NELFCD, and CSE1L as top co-expressed genes. Lentiviral vectors targeting STAU1, NELFCD, and CSE1L revealed that silencing CSE1L significantly impaired cell growth, indicating it as a downstream target of DDX27. Cell rescue experiments demonstrated that increased DDX27 levels ameliorated cell proliferation, attenuated apoptosis, and CSE1L depletion blocked cell development induced by DDX27 overexpression. SIGNIFICANCES: This study highlighted DDX27 as a potential therapeutic target for OSCC treatment, shedding light on its crucial role in OSCC development. Targeting DDX27 or its downstream effector, CSE1L, holds promise for innovative OSCC therapies.

High-speed flexible near-infrared organic photodiode for optical communication.

Optical communication is a particularly compelling technology for tackling the speed and capacity bottlenecks in data communication in modern society. Currently, the silicon photodetector plays a dominant role in high-speed optical communication across the visible-near-infrared spectrum. However, its intrinsic rigid structure, high working bias and low responsivity essentially limit its application in next-generation flexible optoelectronic devices. Herein, we report a narrow-bandgap non-fullerene acceptor (NFA) with a remarkable π-extension in the direction of both central and end units (CH17) with respect to the Y6 series, which demonstrates a more effective and compact 3D molecular packing, leading to lower trap states and energetic disorders in the photoactive film. Consequently, the optimized solution-processed organic photodetector (OPD) with CH17 exhibits a remarkable response time of 91 ns (λ = 880 nm) due to the high charge mobility and low parasitic capacitance, exceeding the values of most commercial Si photodiodes and all NFA-based OPDs operating in self-powered mode. More significantly, the flexible OPD exhibits negligible performance attenuation (<1%) after bending for 500 cycles, and maintains 96% of its initial performance even after 550 h of indoor exposure. Furthermore, the high-speed OPD demonstrates a high data transmission rate of 80 MHz with a bit error rate of 3.5 [Formula: see text] 10-4, meaning it has great potential in next-generation high-speed flexible optical communication systems.

Maternal cobalt concentration and risk of spontaneous preterm birth: the role of fasting blood glucose and lipid profiles.

Introduction: Spontaneous preterm birth (SPB) is a significant cause of neonatal mortality, yet its etiology remains unclear. Cobalt, an essential trace element, might be a risk factor for SPB. This study aims to investigate the relationship between maternal serum cobalt concentration and SPB, and to clarify the role of blood lipids and fasting blood glucose (FBG) in this relationship. Methods: We conducted a nested case-control study within the Beijing Birth Cohort Study. Serum samples were obtained from 222 pregnant women with SPB and 224 controls during the first (7-13 weeks of pregnancy) and third trimesters (32-42 weeks of pregnancy). Serum cobalt concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). Fasting blood glucose and lipids levels were detected using a fully automated biochemical immunoassay instrument. Logistic regression models and linear regression models were established to explore the association between serum cobalt concentration and the risk of SPB in pregnant women, and to test the mediating effect of fasting blood glucose (FBG) and lipids. Results: We found that the serum cobalt concentration in mothers with SPB and controls was similar in the first trimester, with values of 0.79 (0.58-1.10) ng/mL and 0.75 (0.51-1.07) ng/mL, respectively. However, in the third trimester, the cobalt concentration increased to 0.88 (0.59-1.14) ng/mL and 0.84 (0.52-1.19) ng/mL, respectively. In the logistic regression model, when considering the third trimester of pregnancy, after adjusting for ethnicity, pre-pregnancy body mass index (BMI), maternal age, education, income, and parity, it was observed that the medium level of cobalt concentration (0.63-1.07 ng/ml) had a negative correlation with the risk of SPB. The odds ratio (OR) was 0.56, with a 95% confidence interval of 0.34-0.90 ng/mL and a p-value of 0.02. This suggests that cobalt in this concentration range played a protective role against SPB. Additionally, it was found that FBG in the third trimester of pregnancy had a partial intermediary role, accounting for 9.12% of the association. However, no relationship between cobalt and SPB risk was found in the first trimester. Conclusion: During the third trimester, intermediate levels of maternal cobalt appear to offer protection against SPB, with FBG playing a partial mediating role. To further clarify the optimal cobalt concentrations during pregnancy for different populations, a multi-center study with a larger sample size is necessary. Additionally, exploring the specific mechanism of FBG's mediating role could provide valuable insights for improving the prevention of SPB.

The incidence, prevalence, and health burden of hip fractures in China: Data from the global burden of disease study 2019.

Background: Hip fracture is commonly in the elderly as a consequence of osteoporsis. Currently, China is entering an aging society and there is a lack of studies about the epidemiology and health burden of hip fracturs there. Methods: We used data from the Global Burden of Disease study 2019 (GBD 2019) to estimate the incidence, prevalence and disease burden of hip fractures in China and the temporal trends from 1990 to 2019. These estimates were produced by DisMod-MR 2.1, a Bayesian meta-regression tool. Estimated annual percentage change (EAPC) was used to represent the temporal trends. Results: In 2019, there was estimated to be 2.0 million incident and 2.6 million prevalent hip fracture cases in China. The age standardized incidence and prevalence rate were estimated to be 117.8 (95 % UI, 83.8 to 161.6) per 100,000 and 139.8 (95 % UI, 125.7 to 154.7) per 100,000, respectively. From 1990 to 2019, the incidence (EAPC, 1.06; 95 % CI, 0.6 to 1.52) and prevalence (EAPC, 1.41; 95 % CI, 1.02 to 1.8) rates have increased, while the age standardized DALY decreased (95 %CI, -1.8; 95 % CI, -2.3 to -1.2). The incidence and DALY rates of hip fractures increased with age, and female people have higher incidence rate and disease burden. Falls were the leading cause for hip fractures, followed by road injuries. Conclusion: Due to population growth and ageing, the challenges from hip fractures are expected to increase in the future, and related measures are in need to reduce the related health and economic burden.

Predicting Drug-Protein Interactions through Branch-Chain Mining and multi-dimensional attention network.

Identifying drug-protein interactions (DPIs) is crucial in drug discovery and repurposing. Computational methods for precise DPI identification can expedite development timelines and reduce expenses compared with conventional experimental methods. Lately, deep learning techniques have been employed for predicting DPIs, enhancing these processes. Nevertheless, the limitations observed in prior studies, where many extract features from complete drug and protein entities, overlooking the crucial theoretical foundation that pharmacological responses are often correlated with specific substructures, can lead to poor predictive performance. Furthermore, certain substructure-focused research confines its exploration to a solitary fragment category, such as a functional group. In this study, addressing these constraints, we present an end-to-end framework termed BCMMDA for predicting DPIs. The framework considers various substructure types, including branch chains, common substructures, and specific fragments. We designed a specific feature learning module by combining our proposed multi-dimensional attention mechanism with convolutional neural networks (CNNs). Deep CNNs assist in capturing the synergistic effects among these fragment sets, enabling the extraction of relevant features of drugs and proteins. Meanwhile, the multi-dimensional attention mechanism refines the relationship between drug and protein features by assigning attention vectors to each drug compound and amino acid. This mechanism empowers the model to further concentrate on pivotal substructures and elements, thereby improving its ability to identify essential interactions in DPI prediction. We evaluated the performance of BCMMDA on four well-known benchmark datasets. The results indicated that BCMMDA outperformed state-of-the-art baseline models, demonstrating significant improvement in performance.

Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction.

BACKGROUND: Long noncoding RNAs (lncRNAs) are integral to a plethora of critical cellular biological processes, including the regulation of gene expression, cell differentiation, and the development of tumors and cancers. Predicting the relationships between lncRNAs and diseases can contribute to a better understanding of the pathogenic mechanisms of disease and provide strong support for the development of advanced treatment methods. RESULTS: Therefore, we present an innovative Node-Adaptive Graph Transformer model for predicting unknown LncRNA-Disease Associations, named NAGTLDA. First, we utilize the node-adaptive feature smoothing (NAFS) method to learn the local feature information of nodes and encode the structural information of the fusion similarity network of diseases and lncRNAs using Structural Deep Network Embedding (SDNE). Next, the Transformer module is used to capture potential association information between the network nodes. Finally, we employ a Transformer module with two multi-headed attention layers for learning global-level embedding fusion. Network structure coding is added as the structural inductive bias of the network to compensate for the missing message-passing mechanism in Transformer. NAGTLDA achieved an average AUC of 0.9531 and AUPR of 0.9537 significantly higher than state-of-the-art methods in 5-fold cross validation. We perform case studies on 4 diseases; 55 out of 60 associations between lncRNAs and diseases have been validated in the literatures. The results demonstrate the enormous potential of the graph Transformer structure to incorporate graph structural information for uncovering lncRNA-disease unknown correlations. CONCLUSIONS: Our proposed NAGTLDA model can serve as a highly efficient computational method for predicting biological information associations.

The association between gestational weight trajectories in women with gestational diabetes and their offspring's weight from birth to 40 months.

AIMS: To identify the gestational weight gain (GWG) patterns in women with gestational diabetes mellitus (GDM) and evaluate their association with offspring weight status from birth to 40 months. MATERIALS AND METHODS: This study included 2,723 GDM-mother-child pairs from the Beijing Birth Cohort Study. The association between GWG trajectories identified by the latent class model and offspring weight outcomes from birth to 40 months were evaluated, after adjustment for maternal age, parity, pre-pregnancy body mass index, maternal height, and blood glucose levels. RESULTS: Three GWG rate groups, including the non-excessive GWG group (1,994/2,732), excessive GWG group (598 /2,732), and excessive early GWG group (140/2,732), were identified in women with GDM, respectively. Compared to the non-excessive GWG group, the adjusted OR (aOR) and 95% CI were 1.83 (1.35-2.47) and 1.79 (1.06-3.01) for macrosomia, 1.33 (1.07-1.66) and 1.48 (1.01-2.17) for large for gestational age (LGA) in the excessive GWG group and excessive early GWG group. Excessive GWG was also associated with an increased risk of BMI-for-age at 40 months (aOR = 1.66, 95% CI 1.14-2.42). CONCLUSIONS: Both excessive GWG and excessive early GWG increased the risk of macrosomia and LGA in women with GDM, but only the excessive GWG was associated with childhood overweight/obesity. The results suggest the long-term impact of GWG on offspring weight status in women with GDM and the potential benefits of GWG restriction after GDM diagnosis.

Nitrogen application in pod zone improves yield and quality of two peanut cultivars by modulating nitrogen accumulation and metabolism.

Cultivated peanut (Arachis hypogaea L.) represents one of the most important oil and cash crops world-widely. Unlike many other legumes, peanuts absorb nitrogen through their underground pods. Despite this unique feature, the relationship between yield and nitrogen uptake within the pod zone remains poorly understood. In our pot experiment, we divided the underground peanut part into two zones-pod and root-and investigated the physiological and agronomic traits of two peanut cultivars, SH11 (large seeds, LS) and HY23 (small seeds, SS), at 10 (S1), 20 (S2), and 30 (S3) days after gynophores penetrated the soil, with nitrogen application in the pod zone. Results indicated that nitrogen application increased pod yield, kernel protein content, and nitrogen accumulation in plants. For both LS and SS peanut cultivars, optimal nitrogen content was 60 kg·hm- 2, leading to maximum yield. LS cultivar exhibited higher yield and nitrogen accumulation increases than SS cultivar. Nitrogen application up-regulated the expression of nitrogen metabolism-related genes in the pod, including nitrate reductase (NR), nitrite reductase (NIR), glutamine synthetase (GS), glutamate synthase (NADH-GOGAT), ATP binding cassette (ABC), and nitrate transporter (NRT2). Additionally, nitrogen application increased enzyme activity in the pod, including NR, GS, and GOGAT, consistent with gene expression levels. These nitrogen metabolism traits exhibited higher up-regulations in the large-seeded cultivar than in the small-seeded one and showed a significant correlation with yield in the large-seeded cultivar at S2 and S3. Our findings offer a scientific basis for the judicious application and efficient utilization of nitrogen fertilization in peanuts, laying the groundwork for further elucidating the molecular mechanisms of peanut nitrogen utilization.