Advancing Drug-Target Interaction prediction with BERT and subsequence embedding.

Exploring the relationship between proteins and drugs plays a significant role in discovering new synthetic drugs. The Drug-Target Interaction (DTI) prediction is a fundamental task in the relationship between proteins and drugs. Unlike encoding proteins by amino acids, we use amino acid subsequence to encode proteins, which simulates the biological process of DTI better. For this research purpose, we proposed a novel deep learning framework based on Bidirectional Encoder Representation from Transformers (BERT), which integrates high-frequency subsequence embedding and transfer learning methods to complete the DTI prediction task. As the first key module, subsequence embedding allows to explore the functional interaction units from drug and protein sequences and then contribute to finding DTI modules. As the second key module, transfer learning promotes the model learn the common DTI features from protein and drug sequences in a large dataset. Overall, the BERT-based model can learn two kinds features through the multi-head self-attention mechanism: internal features of sequence and interaction features of both proteins and drugs, respectively. Compared with other methods, BERT-based methods enable more DTI-related features to be discovered by means of attention scores which associated with tokenized protein/drug subsequences. We conducted extensive experiments for the DTI prediction task on three different benchmark datasets. The experimental results show that the model achieves an average prediction metrics higher than most baseline methods. In order to verify the importance of transfer learning, we conducted an ablation study on datasets, and the results show the superiority of transfer learning. In addition, we test the scalability of the model on the dataset in unseen drugs and proteins, and the results of the experiments show that it is acceptable in scalability.

Impact of frailty on short-term postoperative outcomes in patients undergoing colorectal cancer surgery: A systematic review and meta-analysis.

BACKGROUND: Colorectal cancer is a major global health challenge that predominantly affects older people. Surgical management, despite advancements, requires careful consideration of preoperative patient status for optimal outcomes. AIM: To summarize existing evidence on the association of frailty with short-term postoperative outcomes in patients undergoing colorectal cancer surgery. METHODS: A literature search was conducted using PubMed, EMBASE and Scopus databases for observational studies in adult patients aged ≥ 18 years undergoing planned or elective colorectal surgery for primary carcinoma and/or secondary metastasis. Only studies that conducted frailty assessment using recognized frailty assessment tools and had a comparator group, comprising nonfrail patients, were included. Pooled effect sizes were reported as weighted mean difference or relative risk (RR) with 95% confidence intervals (CIs). RESULTS: A total of 24 studies were included. Compared with nonfrail patients, frailty was associated with an increased risk of mortality at 30 d (RR: 1.99, 95%CI: 1.47-2.69), at 90 d (RR: 4.76, 95%CI: 1.56-14.6) and at 1 year (RR: 5.73, 95%CI: 2.74-12.0) of follow up. Frail patients had an increased risk of any complications (RR: 1.81, 95%CI: 1.57-2.10) as well as major complications (Clavien-Dindo classification grade ≥ III) (RR: 2.87, 95%CI: 1.65-4.99) compared with the control group. The risk of reoperation (RR: 1.18, 95%CI: 1.07-1.31), readmission (RR: 1.70, 95%CI: 1.36-2.12), need for blood transfusion (RR: 1.67, 95%CI: 1.52-1.85), wound complications (RR: 1.49, 95%CI: 1.11-1.99), delirium (RR: 4.60, 95%CI: 2.31-9.16), risk of prolonged hospitalization (RR: 2.09, 95%CI: 1.22-3.60) and discharge to a skilled nursing facility or rehabilitation center (RR: 3.19, 95%CI: 2.0-5.08) was all higher in frail patients. CONCLUSION: Frailty in colorectal cancer surgery patients was associated with more complications, longer hospital stays, higher reoperation risk, and increased mortality. Integrating frailty assessment appears crucial for tailored surgical management.

The CXCR4 might be a potential biomarker for esophageal squamous cell carcinoma: A meta-analysis.

OBJECTIVE: To evaluate the relationship between CXCL12/CXCR4 and the progress, prognosis of esophageal squamous cell carcinoma (ESCC), providing evidence for potential early diagnosis, clinical treatment, prognosis evaluation, and therapeutic target of ESCC. METHODS: Databases of PubMed, the Cochrane Library, Embase, and Web of Science were searched for the relationship between CXCL12/CXCR4 and clinicopathological characteristics and survival time of ESCC. Stata16.0 software was used to conduct meta-analysis. RESULTS: A total of 10 studies involving 1216 cases of patients with ESCC were included in our study. The results indicated that high-level expression of CXCR4 was significantly correlated with tumor differentiation [OR = 0.69, 95% confidence interval (CI): (0.50, 0.97)], tumor infiltration [OR = 0.39, 95% CI: (0.25, 0.61)], lymph node metastasis [OR = 0.36, 95% CI: (0.21, 0.61)], clinical stage [OR = 0.33, 95% CI: (0.24, 0.45)] of ESCC. The expression of CXCR4 was also significantly correlated with OS [HR = 2.00, 95% CI: (1.63, 2.45)] and disease-free survival [HR = 1.76, 95% CI: (1.44, 2.15)] in patients of ESCC after surgical resection. No significant relationship was observed between the expression of CXCL12 and the clinicopathological characteristics of ESCC. CONCLUSION: CXCR4 might be a potential biomarker for the progress and prognosis evaluation, and therapeutic target for ESCC.

Diagnostic and prognostic performance of artificial intelligence-based fully-automated on-site CT-FFR in patients with CAD.

Currently, clinically available coronary CT angiography (CCTA) derived fractional flow reserve (CT-FFR) is time-consuming and complex. We propose a novel artificial intelligence-based fully-automated, on-site CT-FFR technology, which combines the automated coronary plaque segmentation and luminal extraction model with reduced order 3 dimentional (3D) computational fluid dynamics. A total of 463 consecutive patients with 600 vessels from the updated China CT-FFR study in Cohort 1 undergoing both CCTA and invasive fractional flow reserve (FFR) within 90 d were collected for diagnostic performance evaluation. For Cohort 2, a total of 901 chronic coronary syndromes patients with index CT-FFR and clinical outcomes at 3-year follow-up were retrospectively analyzed. In Cohort 3, the association between index CT-FFR from triple-rule-out CTA and major adverse cardiac events in patients with acute chest pain from the emergency department was further evaluated. The diagnostic accuracy of this CT-FFR in Cohort 1 was 0.82 with an area under the curve of 0.82 on a per-patient level. Compared with the manually dependent CT-FFR techniques, the operation time of this technique was substantially shortened by 3 times and the number of clicks from about 60 to 1. This CT-FFR technique has a highly successful (> 99%) calculation rate and also provides superior prediction value for major adverse cardiac events than CCTA alone both in patients with chronic coronary syndromes and acute chest pain. Thus, the novel artificial intelligence-based fully automated, on-site CT-FFR technique can function as an objective and convenient tool for coronary stenosis functional evaluation in the real-world clinical setting.

Nondestructive detection of SSC in multiple pear (Pyrus pyrifolia Nakai) cultivars using Vis-NIR spectroscopy coupled with the Grad-CAM method.

Vis-NIR spectroscopy coupled with chemometric models is frequently used for pear soluble solid content (SSC) prediction. However, the model robustness is challenged by the variations in pear cultivars. This study explored the feasibility of developing universal models for predicting SSC of multiple pear varieties to improve the model's generalizability. The mature fruits of 6 pear cultivars with green skin (Pyrus pyrifolia Nakai cv. 'Cuiyu', 'Sucui No.1' and 'Cuiguan') and brown skin (Pyrus pyrifolia Nakai cv. 'Hosui','Syusui' and 'Wakahikari') were used to establish single-cultivar models and multi-cultivar universal models using convolutional neural network (CNN), partial least square (PLS), and support vector regression (SVR) approaches. Multi-cultivar universal models were built using full spectra and important variables extracted by gradient-weighted class activation mapping (Grad-CAM), respectively. The universal models based on important variables obtained satisfactory performances with RMSEPs of 0.76, 0.59, 0.80, 1.64, 0.98, and 1.03°Brix on 6 cultivars, respectively.

Deciphering the role of non-coding RNAs involved in sorafenib resistance.

Sorafenib is an important treatment strategy for advanced hepatocellular carcinoma (HCC). Unfortunately, drug resistance has become a major obstacle in sorafenib application. In this study, whole transcriptome sequencing (WTS) was conducted to compare the paired differences between non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and mRNAs, in sorafenib-resistant and parental cells. The overlap of differentially expressed ncRNAs (DENs) between the SMMC7721/S and Huh7/S cells and their parental cells was determined. 2 upregulated and 3 downregulated lncRNAs, 2 upregulated and 1 downregulated circRNAs, as well as 10 upregulated and 2 downregulated miRNAs, in both SMMC7721/S and Huh7/S cells, attracted more attention. The target genes of these DENs were then identified as the overlaps between the differentially expressed mRNAs achieved using the WTS analysis and the predicted genes of DENs obtained using the "co-localization" or "co-expression," miRanda, and RNAhybrid analysis. Consequently, the potential regulatory network between overlapping DENs and their target genes in both SMMC7721/S and Huh7/S cells was explored. The "lncRNA-miRNA-mRNA" and "circRNA-miRNA-mRNA" networks were constructed based on the competitive endogenous RNA (ceRNA) theory using the Cytoscape software. In particular, lncRNA MED17-203-miRNA (miR-193a-5p, miR-197-3p, miR-27a-5p, miR-320b, miR-767-3p, miR-767-5p, miR-92a-3p, let-7c-5p)-mRNA," "circ_0002874-miR-27a-5p-mRNA" and "circ_0078607-miR-320b-mRNA" networks were first introduced in sorafenib-resistant HCC. Furthermore, these networks were most probably connected to the process of metabolic reprogramming, where the activation of the PPAR, HIF-1, Hippo, and TGF-ß signaling pathways is governed. Alternatively, the network "circ_0002874-miR-27a-5p-mRNA" was also involved in the regulation of the activation of TGF-ß signaling pathways, thus advancing Epithelial-mesenchymal transition (EMT). These findings provide a theoretical basis for exploring the mechanisms underlying sorafenib resistance mediated by metabolic reprogramming and EMT in HCC.

Novel STAT3 oligonucleotide compounds suppress tumor growth and overcome the acquired resistance to sorafenib in hepatocellular carcinoma.

Signal transducer and activator of transcription 3 (STAT3) plays an important role in the occurrence and progression of tumors, leading to resistance and poor prognosis. Activation of STAT3 signaling is frequently detected in hepatocellular carcinoma (HCC), but potent and less toxic STAT3 inhibitors have not been discovered. Here, based on antisense technology, we designed a series of stabilized modified antisense oligonucleotides targeting STAT3 mRNA (STAT3 ASOs). Treatment with STAT3 ASOs decreased the STAT3 mRNA and protein levels in HCC cells. STAT3 ASOs significantly inhibited the proliferation, survival, migration, and invasion of cancer cells by specifically perturbing STAT3 signaling. Treatment with STAT3 ASOs decreased the tumor burden in an HCC xenograft model. Moreover, aberrant STAT3 signaling activation is one of multiple signaling pathways involved in sorafenib resistance in HCC. STAT3 ASOs effectively sensitized resistant HCC cell lines to sorafenib in vitro and improved the inhibitory potency of sorafenib in a resistant HCC xenograft model. The developed STAT3 ASOs enrich the tools capable of targeting STAT3 and modulating STAT3 activity, serve as a promising strategy for treating HCC and other STAT3-addicted tumors, and alleviate the acquired resistance to sorafenib in HCC patients. A series of novel STAT3 antisense oligonucleotide were designed and showed potent anti-cancer efficacy in hepatocellular carcinoma in vitro and in vivo by targeting STAT3 signaling. Moreover, the selected STAT3 ASOs enhance sorafenib sensitivity in resistant cell model and xenograft model.

Recovery of biochar particles laden with lead in saturated porous media by DC electric field.

The co-transport behavior of environmental pollutants with biochar particles has aroused great interests from researchers due to the concerns about pollutant diffusion and environmental exposure after biochar is applied to soil. In this work, the recovery and co-transport behavior of biochar micron-/nano-particles (BCMP and BCNP) and lead (Pb2+) in saturated porous media were investigated under different ionic strength conditions (IS = 1, 5 and 10 mM) under a direct current electric field. The results showed that the electric field could significantly enhance the mobility of Pb adsorbed biochar particles, particularly BCNP. The recovery of Pb laden biochar particles was improved by 1.8 folds, reaching 78.8% at maximum under favorable condition at +0.5 V cm-1. According to the CDE (Convection-Dispersion-Equation) model and DLVO (Derjaguin-Landau-Verwey-Overbeek) theory analysis, the electric field facilitated the transport of Pb carried biochar mainly by increasing the negative charges on biochar surface and improving the repulsive force between biochar and porous media. High IS was favorable for biochar transport under the electric field, but inhibited desorbing Pb2+ from biochar (18% by maximum at IS = 10 mM). By switching the electric field power, a two-stage strategy was established to maximize the recovery of both biochar particles and Pb, where BCNP and Pb recovery were higher than electric field free case by 90% and 35%, respectively. The findings of this study can help build a biochar recovery approach to prevent potential risks from biochar application in heavy metal contaminated soil remediation.

Passivation of 2D Cs2PbI2Cl2 Nanosheets for Efficient and Stable CsPbI3 Quantum Dot Solar Cells.

Inorganic CsPbI3 perovskite quantum dots (PQDs) possess remarkable optical properties, making them highly promising for photovoltaic applications. However, the inadequate stability resulting from internal structural instability and the complex external surface chemical environment of CsPbI3 PQDs has hindered the development of CsPbI3 PQD solar cells (PQDSCs). In this work, the capping layer composed of inorganic two-dimensional (2D) Ruddlesden-Popper (RP) phase Cs2PbI2Cl2 nanosheets (NSs) is introduced, which may be effectively treated to improve the surface properties of the CsPbI3 PQD film. This modification serves to passivate defects by filling cesium and iodine vacancies while optimizing the energy band arrangement and preventing humidity intrusion, leading to the meliorative stability and photovoltaic performance. The optimized CsPbI3 PQDSCs achieve an enhanced power conversion efficiency (PCE) of 14.73%, with the superb stability of only a 16% efficiency loss after being exposed to ambient conditions (30 ± 5% RH) for 432 h.

The manufacturing process provides green teas with differentiated nonvolatile profiles and influences the deterioration of flavor during storage at room temperature.

Hundreds of green tea products are available on the tea market and exhibit different characteristics. In the present study, seven types of green tea were processed, and their nonvolatile profiles were analyzed by liquid chromatography-mass spectrometry. Non-spreading green tea contained higher concentrations of catechins and flavonoid glycosides, but lower concentrations of amino acids, caffeine, and theaflavins. Non-rolling green teas with a straight appearance contained higher concentrations of flavonoid glycosides and theaflavins. In contrast, leaf-rolling green teas contained much lower concentrations of flavonoid glycosides and catechins. These seven green tea qualities all decreased following prolonged storage, concurrent with increasing concentrations of proanthocyanidins, catechins dimers, theaflavins, and organic acids. The leaf-rolling green teas exhibited reduced levels of deterioration during storage in terms of their nonvolatile profile and sensory quality. Findings show that moderate destruction on tea leaves during green tea processing is beneficial to both tea flavor and quality maintenance during storage.

Metabolism pathway-based subtyping in endometrial cancer: An integrated study by multi-omics analysis and machine learning algorithms.

Endometrial cancer (EC), the second most common malignancy in the female reproductive system, has garnered increasing attention for its genomic heterogeneity, but understanding of its metabolic characteristics is still poor. We explored metabolic dysfunctions in EC through a comprehensive multi-omics analysis (RNA-seq datasets from The Cancer Genome Atlas [TCGA], Cancer Cell Line Encyclopedia [CCLE], and GEO datasets; the Clinical Proteomic Tumor Analysis Consortium [CPTAC] proteomics; CCLE metabolomics) to develop useful molecular targets for precision therapy. Unsupervised consensus clustering was performed to categorize EC patients into three metabolism-pathway-based subgroups (MPSs). These MPS subgroups had distinct clinical prognoses, transcriptomic and genomic alterations, immune microenvironment landscape, and unique patterns of chemotherapy sensitivity. Moreover, the MPS2 subgroup had a better response to immunotherapy. Finally, three machine learning algorithms (LASSO, random forest, and stepwise multivariate Cox regression) were used for developing a prognostic metagene signature based on metabolic molecules. Thus, a 13-hub gene-based classifier was constructed to predict patients' MPS subtypes, offering a more accessible and practical approach. This metabolism-based classification system can enhance prognostic predictions and guide clinical strategies for immunotherapy and metabolism-targeted therapy in EC.

Assessing the wastewater reclaim system consisted of wastewater plant - hybrid constructed wetland - ultra filtration and reverse osmosis in a chemical industrial park, a multi-criteria decision-making analysis.

Wastewater reclaim in industrial parks can effectively reduce the dependence on external water resources, few literatures evaluated the reclaim system from perspectives of economy, technology, and environmental impact. It is very popular across China that a constructed wetland is linked with a wastewater plant and then discharged the tailwater into surface waters, based on current situation, pilot experiment, and other available techniques, six scenarios for wastewater reclaim system were designed for Shanghai Chemical Industrial Park. Using life cycle assessment, it was found that in scenario of pilot experiment, most environmental impact was derived from wastewater plant and ultra filtration - reverse osmosis, in which ultra filtration - reverse osmosis accounted >20 % for POCP, AP, and EP, Wastewater plant accounted >86 % for ADP, ODP. It was showed that electricity and sludge were most important parameters affecting LCA, when electricity consumption was reduced by 20 %, total standardized environmental impact would be changed in the range of 1.40 %-1.65 %, the most significant change was HTP (6.12 %-6.32 %) when 20 % up and downward change in sludge amount, followed by MAETP (5.27 %-5.36 %). A multi-criteria decision-making analysis was conducted on all the scenarios based on environmental impact, life cycle cost, technical efficiency, it was showed that the scenario designed for pilot experiment was the best available technique, which was consisted of wastewater plant, hybrid constructed wetland, ultra-filtration and reverse osmosis, and reused as desalted water. A wastewater reclaim plant is suggested from the result of this paper. It was believed that this study could provide references for construction of wastewater reclaim system in industrial parks of the world.

Aging and mitigation of microplastics during sewage sludge treatments: An overview.

Wastewater treatment plants (WWTPs) receive large quantities of microplastics (MPs) from raw wastewater, but many MPs are trapped in the sludge. Land application of sludge is a significant source of MP pollution. Existing reviews have summarized the analysis methods of MPs in sludge and the effect of MPs on sludge treatments. However, MP aging and mitigation during sludge treatment processes are not fully reviewed. Treatment processes used to remove water, pathogenic microorganisms, and other pollutants in sewage sludge also cause surface changes and degradation in the sludge MPs, affecting the potential risk of MPs. This study integrates MP abundance and distribution in sludge and their aging and mitigation characteristics during sludge treatment processes. The abundance, composition, and distribution of sludge MPs vary significantly with WWTPs. Furthermore, MPs exhibit variable degrees of aging, including rough surfaces, enhanced adsorption potentials for pollutants, and increased leaching behavior. Various sludge treatment processes further intensify these aging characteristics. Some sludge treatments, such as hydrothermal treatment, have efficiently removed MPs from sewage sludge. It is crucial to understand the potential risk of MP aging in sludge and the degradation properties of the MP-derived products from MP degradation in-depth and develop novel MP mitigation strategies in sludge, such as combining hydrothermal treatment and biological processes.

Quantitative differentiation of toxicity contributions and predicted global risk of fipronil and its transformation products to aquatic invertebrates.

Biotransformation often alters chemical toxicity, yet its impacts on risk assessment are hardly quantified due to the challenges in acquiring internal exposure-based thresholds for chemicals that are readily metabolizable. Here, we integrated toxic unit and toxicokinetics to quantitatively assess toxicity contributions and potential risk of both parent compound and transformation products (TPs) to aquatic organisms, using fipronil (FIP) as a representative toxicant. In aquatic invertebrates Chironomus dilutus and Hyalella azteca, approximately 90 % of FIP was transformed to fipronil sulfone (SUL). FIP and SUL exhibited similar intrinsic toxicity to these organisms, which was contrary to conventional perception that SUL was more toxic than FIP. However, biotransformation was still important in risk assessment because the TP had 10-fold slower depuration rate than FIP. The amphipod H. azteca was found to be as sensitive to FIPs as the insect C. dilutus, which was previously considered ten times more sensitive based on external thresholds. This discrepancy has led to overlooking the toxicity of FIP to H. azteca in regional risk assessments. Lastly, we predicted the lethal risk of FIPs in global surface water. When using external thresholds for prediction, FIPs in 3.4 % of the water samples were lethally toxic to H. azteca, and the percentage of water samples at risk increased to 14 % when internal thresholds were used and SUF dominated the risk. This study presents an improved method for quantifying aquatic risk of readily metabolized toxicants. Our findings underscore the urgency of considering TPs in water quality assessments, especially for sensitive species that are at risk in the environment.

Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.

OBJECTIVE: The preoperative prediction of the overall survival (OS) status of patients with head and neck cancer (HNC) is significant value for their individualized treatment and prognosis. This study aims to evaluate the impact of adding 3D deep learning features to radiomics models for predicting 5-year OS status. METHODS: Two hundred twenty cases from The Cancer Imaging Archive public dataset were included in this study; 2212 radiomics features and 304 deep features were extracted from each case. The features were selected by univariate analysis and the least absolute shrinkage and selection operator, and then grouped into a radiomics model containing Positron Emission Tomography /Computed Tomography (PET/CT) radiomics features score, a deep model containing deep features score, and a combined model containing PET/CT radiomics features score +3D deep features score. TumorStage model was also constructed using initial patient tumor node metastasis stage to compare the performance of the combined model. A nomogram was constructed to analyze the influence of deep features on the performance of the model. The 10-fold cross-validation of the average area under the receiver operating characteristic curve and calibration curve were used to evaluate performance, and Shapley Additive exPlanations (SHAP) was developed for interpretation. RESULTS: The TumorStage model, radiomics model, deep model, and the combined model achieved areas under the receiver operating characteristic curve of 0.604, 0.851, 0.840, and 0.895 on the train set and 0.571, 0.849, 0.832, and 0.900 on the test set. The combined model showed better performance of predicting the 5-year OS status of HNC patients than the radiomics model and deep model. The combined model was shown to provide a favorable fit in calibration curves and be clinically useful in decision curve analysis. SHAP summary plot and SHAP The SHAP summary plot and SHAP force plot visually interpreted the influence of deep features and radiomics features on the model results. CONCLUSIONS: In predicting 5-year OS status in patients with HNC, 3D deep features could provide richer features for combined model, which showed outperformance compared with the radiomics model and deep model.

Mediating Effect of Tobacco Dependence on the Association Between Maternal Smoking During Pregnancy and Chronic Obstructive Pulmonary Disease: Case-Control Study.

BACKGROUND: Maternal smoking during pregnancy (MSDP) is a known risk factor for offspring developing chronic obstructive pulmonary disease (COPD), but the underlying mechanism remains unclear. OBJECTIVE: This study aimed to explore whether the increased COPD risk associated with MSDP could be attributed to tobacco dependence (TD). METHODS: This case-control study used data from the nationwide cross-sectional China Pulmonary Health study, with controls matched for age, sex, and smoking status. TD was defined as smoking within 30 minutes of waking, and the severity of TD was assessed using the Fagerstrom Test for Nicotine Dependence. COPD was diagnosed when the ratio of forced expiratory volume in 1 second to forced vital capacity was <0.7 in a postbronchodilator pulmonary function test according to the 2017 Global Initiative for Chronic Obstructive Lung Disease criteria. Logistic regression was used to examine the correlation between MSDP and COPD, adjusting for age, sex, BMI, educational attainment, place of residence, ethnic background, occupation, childhood passive smoking, residential fine particulate matter, history of childhood pneumonia or bronchitis, average annual household income, and medical history (coronary heart disease, hypertension, and diabetes). Mediation analysis examined TD as a potential mediator in the link between MSDP and COPD risk. The significance of the indirect effect was assessed through 1000 iterations of the "bootstrap" method. RESULTS: The study included 5943 participants (2991 with COPD and 2952 controls). Mothers of the COPD group had higher pregnancy smoking rates (COPD: n=305, 10.20%; controls: n=211, 7.10%; P<.001). TD was more prevalent in the COPD group (COPD: n=582, 40.40%; controls: n=478, 33.90%; P<.001). After adjusting for covariates, MSDP had a significant effect on COPD (ß=.097; P<.001). There was an association between MSDP and TD (ß=.074; P<.001) as well as between TD and COPD (ß=.048; P=.007). Mediation analysis of TD in the MSDP-COPD association showed significant direct and indirect effects (direct: ß=.094; P<.001 and indirect: ß=.004; P=.03). The indirect effect remains present in the smoking population (direct: ß=.120; P<.001 and indirect: ß=.002; P=.03). CONCLUSIONS: This study highlighted the potential association between MSDP and the risk of COPD in offspring, revealing the mediating role of TD in this association. These findings contribute to a deeper understanding of the impact of prenatal tobacco exposure on lung health, laying the groundwork for the development of relevant prevention and treatment strategies.

STAT4 targets KISS1 to inhibit the oxidative damage, inflammation and neuronal apoptosis in experimental PD models by inactivating the MAPK pathway.

BACKGROUND: Oxidative stress and neuroinflammation are proven to play critical roles in the pathogenesis of Parkinson's disease (PD). As reported, patients with PD have lower level of STAT4 compared with healthy subjects. However, the biological functions and mechanisms of STAT4 in PD pathogenesis remain uncertain. This study aimed to investigate the roles and related mechanisms of STAT4 in PD development. METHODS: The intraperitoneal injection of MPTP (20 mg/kg) dissolved in physiological saline was performed to mimic PD-like conditions in vivo. MPP + solution was prepared for cell model of PD. Cell viability was measured by CCK-8. Griess reaction was conducted to measure NO concentrations. The mRNA and protein levels were evaluated by RT-qPCR and western blotting. ROS generation was assessed by DCFH-DA. The levels of inflammatory cytokines were measured by ELISA. Cell apoptosis was examined by flow cytometry and western blotting. Moreover, the SH-SY5Y cells were treated with conditioned medium from LPS-stimulated microglia and subjected to CCK-8 assays and ELISA. Mechanistically, CHIP assays and luciferase reporter assays were performed to verify the binding relationship between KISS1 and STAT4. For in vivo analysis, the histological changes of midbrain tissues of mice were determined by hematoxylin and eosin staining. The expression of tyrosine hydroxylase (TH) was detected by immunohistochemistry staining. Iba-1 positive microglial cells in the striatum were assessed by immunofluorescence staining. RESULTS: For in vitro analysis, STAT4 level was downregulated after MPP+ treatment, and STAT4 upregulation inhibited the oxidative damage, inflammation and apoptosis in SH-SY5Y cells. STAT4 bound at +215-228 region of KISS1, and KISS1 upregulation counteracted the protection of STAT4 upregulation against cell damage. Moreover, STAT4 upregulation inhibited cell viability loss and inflammation induced by conditioned medium from LPS-treated microglia, whereas KISS1 upregulation had the opposite effect. For in vivo analysis, the protective effects of STAT4 upregulation against inflammatory response, oxidative stress, dopaminergic neuronal loss and microglia activation were attenuated by KISS1 upregulation. Moreover, the inactivation of MAPK pathway caused by STAT4 upregulation was reversed by KISS1 upregulation, and MAPK inhibition attenuated the MPP+-induced inflammation, oxidative stress and apoptosis in SH-SY5Y cells. CONCLUSION: STAT4 inhibits KISS1 to attenuate the oxidative damage, inflammation and neuronal apoptosis in PD by inactivating the MAPK pathway.

Association of the Verbal Rating Scale-Measured Dysmenorrhea with Nausea and Vomiting in Pregnancy: A Retrospective Cohort Study.

OBJECTIVES: Nausea and vomiting in pregnancy (NVP) is a common condition that reduces the quality of life by negatively affecting work and family life, physical and mental health, and economic well-being. However, its risk factors remain unclear. This study aimed to explore the association between NVP and verbal rating scale (VRS)-measured dysmenorrhea and to explore potential protective factors. METHODS: This retrospective cohort study was conducted from June 2018 to December 2020 at Tongji Hospital in Wuhan. Information on baseline characteristics, pregnancy-related history, periconceptional micronutrient supplementation, and obstetric outcomes were collected. The severity of dysmenorrhea was assessed using VRS. RESULTS: A total of 443 pregnant women were recruited and divided into the NVP group (n = 76) and the control group (n = 367). A significant association was observed between NVP and VRS-measured dysmenorrhea (c2=10.038, P = 0.007). After adjusting for covariates, the association between moderate/severe dysmenorrhea and NVP remained significant (OR 2.384; 95% CI 1.104-5.148, P = 0.004). First-trimester docosahexaenoic acid supplement (OR 0.443; 95% CI 0.205-0.960, P = 0.039) may be beneficial in reducing the risk of NVP. CONCLUSIONS: Women with moderate to severe dysmenorrhea have a higher risk of experiencing NVP during the first trimester. Periconceptional docosahexaenoic acid supplementation may play a protective role.

Characteristics of Serum Lipid Metabolism among Women Complicated with Hypertensive Disorders in Pregnancy: A Retrospective Cohort Study in Mainland China.

Background: Altered maternal serum lipid metabolism is associated with hypertensive disorders in pregnancy (HDP). However, its range in pregnancy and characteristic among different subgroups of HDPs are unclear. Methods: Pregnant women with HDP who underwent antenatal care and delivered in Obstetrics and Gynecology Hospital of Fudan University during January 2018 to August 2022 were enrolled. The levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), apolipoprotein (Apo)-A, B, and E, free fatty acids (FFA), and small and dense low-density lipoprotein cholesterol (sdLDL) were measured during 4-16 weeks and 28-42 weeks of pregnancy. Results: A total of 2648 pregnant women were diagnosed with HDP, 1,880 of whom were enrolled for final analysis, including 983 (52.3%) preeclampsia (PE), 676 (36.0%) gestational hypertension (GH), and 221 (11.7%) chronic hypertension (CH). For all HDPs, serum TC, TG, LDLC, HDLC, Apo-A, Apo-B, Apo-E, and sdLDL increased significantly during pregnancy, while FFA decreased significantly. Notably, the levels of TC, LDLC, Apo-B, and sdLDL in PE group were equal to or lower than those in CH group at 4-16 weeks of pregnancy, but increased greatly during pregnancy (P < 0.05). Conclusions: Maternal serum lipid levels changed through pregnancy among women with HDPs. Women complicated with PE seem to have undergone a more significant serum lipid change compared to those with GH or CH.