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Context: Computational drug repurposing methods have been continuously developed in recent years to alleviate the high costs associated with drug development. As drug targets or the products of disease-related genes, proteins play an important role in drug repurposing. Although the potential has been demonstrated, heterogeneous graphs with proteins as independent nodes have yet to be studied, where extracting high-quality protein features from heterogeneous graphs poses a significant challenge. A novel drug repurposing model based on the feature construction of multi-layer ensemble (DRML-Ensemble) is proposed in this study. The performance of DRML-Ensemble, as evaluated on publicly available datasets, achieves an AUPR value of 0.93 and an AUROC value of 0.92, surpassing those of existing state-of-the-art methods. Additionally, DRML-Ensemble demonstrates its notable ability for drug repurposing in Alzheimer's disease. Methods: DRML-Ensemble is primarily composed of multiple layers of heterogeneous graph feature construction (HGFC). Each HGFC can extract protein features by leveraging the relationships between drugs, diseases, and proteins. These protein features are then utilized in subsequent layers to build drug and disease features, facilitating drug repurposing. By stacking multiple layers, optimal protein features can be obtained from the heterogeneous graph, consequently improving the accuracy of drug repurposing. However, an excessive· stacking of layers usually affect the model's training process, for example, causing problems such as overfitting; a multi-layer ensemble prediction module is designed to further improve the model's performance. [ABSTRACT FROM AUTHOR]

Straw returning has gradually been adopted as an effective approach to address the serious degradation of farmland. However, the carbon/nitrogen (C/N) ratio of rice straw is generally too high for microorganisms to decompose the organic materials and release nutrients, which may minimize the benefits of straw returning to the agricultural production system. This study aimed to investigate the effects of straw returning on rice production and propose optimum nitrogen (N) management for early rice production under a straw returning system. The total N fertilizer that was evaluated was 165 kg N ha-1, urea (46% N), applied in different proportions in three stages of rice cultivation: basal, tillering, and panicle. Using no straw returning with the N fertilizer ratio of basal:tillering:panicle = 5:2:3 treatment (T1) as the control, four different N fertilizer ratios of basal:tillering:panicle, including 5:2:3 (T2), 5:2:2 (T3), 5:4:1 (T4), and 5:5:0 (T5) were set under straw returning. The return of straw decreased the available N in the soil at the tillering stage, and impeded root growth and the crop canopy from establishing, which decreased the effective panicles by 10.1% compared with that of T1, limiting the increases in rice grain yield. Increasing the N fertilizer ratio 10–20% (T3 and T4) at the tillering stage effectively increased the content of soil ammonium and nitrate nitrogen, improved the root growth, and increased the root activities by 16.0–40.5% at the tillering stage. As a result, the effective panicle number increased by 5.1–16.2%. Among these, T4 treatment maximized the benefits of straw returning the most. Additionally, increasing the N fertilizer ratio at the tillering stage increased the shoot uptake across the early rice growing season and synchronized crop N uptake with the accumulation of carbon assimilates, which enhanced the crop growth rate and increased the rice yield by 13.5–25.1%. It is concluded that increasing the N fertilizer ratio by 20% at the tillering stage is a promising strategy to increase the availability of N in the phases of high demand for this nutrient. [ABSTRACT FROM AUTHOR]

The rupture of unstable plaques is a major cause of acute cardiovascular events. The early assessment of carotid plaques can significantly reduce the cardiovascular risks, so developing evaluation models suitable for data from different centers is of great clinical importance. This study leverages plaque datasets from multiple centers to develop a Weighted multi-source carotid artery plaque Unsupervised Classification Framework (WUCF). The multi-source domain adaptation module of the WUCF focuses on maintaining feature consistency between each independent source and target center, while also integrating a specialized domain discriminator expert. This ensures that the knowledge from each source center is effectively learned and combined for accurate predictions in the target domain. The experimental evaluation of WUCF, using datasets from three centers, has demonstrated the method's superiority and robustness. [ABSTRACT FROM AUTHOR]

Accurately predicting drug–target interactions is a critical yet challenging task in drug discovery. Traditionally, pocket detection and drug–target affinity prediction have been treated as separate aspects of drug–target interaction, with few methods combining these tasks within a unified deep learning system to accelerate drug development. In this study, we propose EMPDTA, an end-to-end framework that integrates protein pocket prediction and drug–target affinity prediction to provide a comprehensive understanding of drug–target interactions. The EMPDTA framework consists of three main modules: pocket online detection, multimodal representation learning for affinity prediction, and multi-task joint training. The performance and potential of the proposed framework have been validated across diverse benchmark datasets, achieving robust results in both tasks. Furthermore, the visualization results of the predicted pockets demonstrate accurate pocket detection, confirming the effectiveness of our framework. [ABSTRACT FROM AUTHOR]

Although our knowledge of autism spectrum disorder (ASD) has been deepened, the accurate diagnosis of ASD from normal individuals is still left behind. In this study, we proposed to apply the spatial pattern of the network topology (SPN) to identify children with ASD from normal ones. Based on two independent batches of electroencephalogram datasets collected separately, the accurate recognition of ASD from normal children was achieved by applying the proposed SPN features. Since decreased long-range connectivity was identified for children with ASD, the SPN features extracted from the distinctive topological architecture between two groups in the first dataset were used to validate the capacity of SPN in classifying ASD, and the SPN features achieved the highest accuracy of 92.31%, which outperformed the other features e.g., power spectrum density (84.62%), network properties (76.92%), and sample entropy (73.08%). Moreover, within the second dataset, by using the model trained in the first dataset, the SPN also acquired the highest sensitivity in recognizing ASD, when compared to the other features. These results consistently illustrated that the functional brain network, especially the intrinsic spatial network topology, might be the potential biomarker for the diagnosis of ASD. [ABSTRACT FROM AUTHOR]

Purpose: Sleep apnea-specific hypoxic burden (SASHB) is a polysomnographic metric that comprehensively measures the degree of nocturnal desaturation caused by obstructive sleep apnea. This research was conducted to elucidate the relationship between SASHB and coronary artery disease (CAD) severity. Methods: We carried out a prospective study of hospitalized patients with CAD of unstable angina who were expected to undergo invasive coronary angiography at Beijing Anzhen Hospital from February to September 2023. SASHB values were calculated using a self-programmed C + + program. Multivariable logistic regression analysis was applied to identify the association between SASHB and the prevalence of severe CAD, documented by the Gensini Score, and the SYNTAX (Synergy between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery) Score. Results: This study enrolled 137 patients with a median age of 59 years, 96 (70.1%) of whom were male. A total of 125 (91.2%) patients had coronary stenosis of ≥ 50% in at least one location. Patients with a high SASHB of ≥ 18% min/h had a significantly higher Gensini Score (32.0 vs. 18.5, P = 0.002) and SYNTAX Score (14.0 vs. 7.0, P = 0.002) than those with a low SASHB. After adjusting for multiple covariates, a high SASHB was significantly associated with the prevalence of severe CAD, determined by a Gensini Score ≥ 21 (OR 2.67, P = 0.008) or a SYNTAX Score > 22 (OR 4.03, P = 0.016). Conclusion: Our findings revealed a robust and independent association between SASHB and CAD severity in patients with unstable angina, highlighting the potential value of SASHB as a predictor of risk and a target for interventions aimed at preventing cardiovascular diseases. Trial registration: Chinese Clinical Trial Registry No. ChiCTR2300067991 on February 2, 2023. [ABSTRACT FROM AUTHOR]

The multiple intersecting stiffeners on the chemical milling stiffened panel (CMSP) limit the application of active health monitoring methods on it. An imaging algorithm based on electromechanical impedance (EMI) and probability-weighting is proposed to achieve quantitative evaluation and localization of the damage on CMSP. The proposed algorithm compensates for the difference in sensor performance with coefficients and there is no need to determine the key parameters of the algorithm through prior experiments. In the paper, the applicability of ultrasonic guided wave (GW) and EMI on CMSP was first studied through the finite element method. Based on EMI and the mean absolute percentage deviation (MAPD), the selected damage indicator (DI), a probability-weighted damage imaging algorithm are proposed and experimentally verified. The results indicate that due to the reflection and attenuation effects of stiffeners on GW, the signal characteristics of damage scattering waves are contaminated, making it difficult to quantitatively characterize the damage from GW signals through DIs. MAPD is positively correlated with the damage degree and has consistency in characterizing the signal of different PZTs under the same working condition. The feasibility and accuracy of the proposed algorithm are verified through experiments which show a strong engineering application capability. [ABSTRACT FROM AUTHOR]

Background: The study aimed to establish a link between blood ethylene oxide (EO) levels and periodontitis, given the growing concern about EO’s detrimental health effects. Materials and methods: The study included 1006 adults from the 2013–2014 National Health and Nutrition Examination Survey (NHANES) dataset. We assessed periodontitis prevalence across groups, used weighted binary logistic regression and restricted cubic spline fitting for HbEO-periodontitis association, and employed Receiver Operating Characteristic (ROC) curves for prediction. Results: In the periodontitis group, HbEO levels were significantly higher (40.57 vs. 28.87 pmol/g Hb, P < 0.001). The highest HbEO quartile showed increased periodontitis risk (OR = 2.88, 95% CI: 1.31, 6.31, P = 0.01). A “J”-shaped nonlinear HbEO-periodontitis relationship existed (NL-P value = 0.0116), with an inflection point at ln-HbEO = 2.96 (EO = 19.30 pmol/g Hb). Beyond this, ln-HbEO correlated with higher periodontitis risk. A predictive model incorporating sex, age, education, poverty income ratio, alcohol consumption, and HbEO had 69.9% sensitivity and 69.2% specificity. The model achieved an area under the ROC curve of 0.761. Conclusions: These findings suggest a correlation between HbEO levels and an increased susceptibility to periodontitis. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OS) is the most common malignancy in children and adolescents and has a high probability of recurrence and metastasis. A growing number of studies have shown that neutrophil extracellular traps (NETs) are strongly associated with cancer metastasis, but in osteosarcoma, genes associated with NETs that promote osteosarcoma recurrence and metastasis remain to be explored. We systematically investigated the gene expression patterns of NETs in OS samples from the GEO database. NETs molecular typing was evaluated based on NETs expression profiles, and the association between NETs molecular subtypes and immune microenvironment and metastatic features were explored. Ultimately, we constructed a signature model and column line graph associated with metastasis prediction and screened possible potential drugs for metastatic osteosarcoma. We established two different molecular subtypes of NETs, which showed significant differences in metastatic status, metastasis time, tumor immune microenvironment, and biological effects. We also constructed a NETs-related gene metastasis signature(NRGMS) to assess the expression pattern of NETs in patients to predict metastatic recurrence in osteosarcoma patients. We screened for TOMM40 and FH associated with metastatic recurrence in osteosarcoma patients. Overall, this study constructs a predictive model for osteosarcoma metastasis of NETs-related genes, which is expected to provide new insights into the metastasis of osteosarcoma. [ABSTRACT FROM AUTHOR]

Three new hetisine type C20-diterpenoid alkaloids, named as trichophorines A–C (1–3), were isolated from Delphinium trichophorum, together with nine known alkaloids (4–12). Their structures were elucidated on the basis of spectroscopic data (1D, 2D NMR, single-crystal X-ray, and HR-ESI-MS). All compounds were evaluated for the inhibitory activities against LPS induced NO production in RAW 264.7 macrophage cells, and none of them showed considerable inhibitory activity. [ABSTRACT FROM AUTHOR]

Carbon fiber-reinforced epoxy resin composites have poor high temperature resistance and are prone to thermal damage during service in the aerospace field. The purpose of this study was to evaluate the thermal decomposition (pyrolysis) characteristics of carbon fiber-reinforced epoxy composites and reasonably predict their thermal decomposition under arbitrary temperature conditions. The kinetic analysis was conducted on the thermal decomposition of carbon fiber-reinforced epoxy resin composites (USN15000/9A16/RC33, supplied by Weihai GuangWei Composites Co., Ltd. Weihai City, Shandong Province, China) under a nitrogen environment, and an improved model of pyrolysis prediction suitable for the arbitrary temperature program was developed in this work. The results showed that the carbon fiber-reinforced epoxy composites begin to degrade at about 500 K, and the peak value of the weight loss rate at the respective heating rate appears in the range of 650 K to 750 K. A single-step reaction can characterize the thermal decomposition of carbon fiber-reinforced epoxy composites in a nitrogen atmosphere, and a wide variety of isoconversional approaches can be used for the calculation of the kinetic parameters. The proposed model of pyrolysis prediction can avoid numerous limitations of temperature integration, and it shows good prediction accuracy by reducing the temperature rise between sampling points. This study provides a reference for the kinetic analysis and pyrolysis prediction of carbon fiber-reinforced epoxy composites. [ABSTRACT FROM AUTHOR]

In this study, the intact Nanning stiff clay were subjected to cyclic wetting–drying under different axial constrain conditions. Experimental results showed that specimen presented vertical stress-dependent axial strain under one-dimensional condition, and gave varying axial stress responses under limited-axial swelling condition. At the first wetting stage, the swelling pressure extrapolated from the swelling strain–vertical stress relationship was found well comparable to that measured on the intact specimen hydrated under constant-volume condition. The proceeding wetting–drying cycles caused structural deterioration of the intact specimens, which differed under different constraint conditions, thus giving rise to different swelling behaviour of the soil. Under one-dimensional condition, the swelling deformation directly destroyed the diagenetic structure of the natural expansive stiff clay. Increasing the vertical stress helps prohibiting such destructive effect. While under limited-axial swelling condition, the specimen swelled to develop varying axial stress in response to hydration during each wetting–drying cycle. More interestingly, the developed axial stress presented a considerable decrease after it remained comparatively stable over three-consecutive wetting–drying cycles. By further analysing such evolving trend of the axial stress from the perspective of structural degradation, the de-structuration of expansive stiff clay under limited-axial swelling condition could evolve in forms of the desiccation- and hydration-induced cracks growth, diagenetic bonds breakdown and crack sealing during cyclic wetting–drying. Such degradation mechanism needs further verification and quantification by microstructural observations. [ABSTRACT FROM AUTHOR]

A surgical site infection (SSI) is one of the most common complications of spinal surgery. Malnutrition has also been linked to SSI after other surgical procedures. However, whether malnutrition is a risk factor for SSI after spinal surgery remains controversial. Therefore, we performed a meta‐analysis to comprehensively evaluate the relationship between malnutrition and SSI. Relevant studies of the correlation between malnutrition and SSI were retrieved from the Cochrane Library, EMBASE, PubMed, Web of Science, China National Knowledge Infrastructure and Wanfang Data from database inception to 21 May 2023. Two reviewers independently assessed the included studies, and a meta‐analysis was performed using STATA 17.0 software. A total of 24 articles with 179 388 patients were included: 3919 and 175 469 cases comprised the SSI and control groups, respectively. The meta‐analysis results showed that malnutrition significantly increased the SSI incidence (odds ratio, 1.811; 95% confidence interval, 1.512–2.111; p < 0.001). These results suggest that patients with malnutrition are at higher risk for SSI after surgery. However, because of significant differences in sample sizes among studies, and because some studies had limitations to their methodological quality, further validation of these results by additional high‐quality studies with larger sample sizes is necessary. [ABSTRACT FROM AUTHOR]

Length-weight relationships (LWRs) were described for four fish species inhabiting the tributaries of the Dongting Lake, China. Fish were sampled using stationary gillnets (50 m long × 2.0 m high and mesh size: 2, 6, 10, and 14 cm) and lobster pots (18 m long × 0.33 m high × 0.45 m width and mesh size: 1 cm) twice a year from May 2021 to July 2023. All fishes were measured in the field immediately after collection for total length (L) to the nearest 0.1 cm and body weight (W) to the nearest 0.1 g. There was a strong correlation between total length and weight in all four species (r2 > 0.98). The values of parameter b in LWR ranged from 2.9709 to 3.4373. The LWR of Sinilabeo tungting, Acrossocheilus jishouensis, Onychostoma rara, and Onychostoma barbata provide new data for https://Fishbase.org and can be useful for establishing conservation measures of fish resources after fishing closure in the Dongting Lake basin, China. [ABSTRACT FROM AUTHOR]

Aim: The study aimed to provide evidence of the relationship between probiotics consumption and periodontitis. Materials and Methods: A total of 4577 adults who participated in the National Health and Nutrition Examination Survey (NHANES) during 2009–2014 were included in the study. The weighted prevalence of periodontitis was compared among different groups, and a weighted binary logistic regression analysis was conducted to explore the relationship between probiotic consumption and periodontitis. Receiver operating characteristic (ROC) curves were used to assess the role of probiotic consumption in the periodontitis prediction model. Results: Participants who consumed probiotics had a significantly lower prevalence of periodontitis than those who did not (41.08% vs. 27.83%, p <.001). After fully adjusting for all factors, the odds ratio associated with periodontitis for consuming probiotics was 0.70 (95% confidence interval 0.54–0.92, p =.01) when compared with those who did not consume probiotics. A predictive model including age, sex, ethnicity, poverty income ratio, smoking status and probiotics had 77.0% sensitivity and 60.3% specificity in detecting periodontitis in US adults and achieved an area under the ROC curve of 0.749. Conclusions: These results indicate that consuming probiotics is associated with a reduced risk of periodontitis. [ABSTRACT FROM AUTHOR]

Seventeen compounds were isolated and identified from the ethyl acetate part of Zanthoxylum bungeanum Maxim., including one new compound 18-acetyloxyneocryptotanshinone (1) and 16 known compounds (2–17). Their structures were elucidated by extensive spectroscopy. The absolute configuration of 1 was confirmed by electronic circular dichroism (ECD). All compounds were evaluated for the inhibition of LPS-induced nitric oxide (NO) production in RAW264.7 macrophages, of which 1 and 10 exhibited the most significant inhibitory effect, with IC50 of 17.29 and 10.27 μM, respectively. [ABSTRACT FROM AUTHOR]

Phishing attacks are evolving with more sophisticated techniques, posing significant threats. Considering the potential of machine-learning-based approaches, our research presents a similar modern approach for web phishing detection by applying powerful machine learning algorithms. An efficient layered classification model is proposed to detect websites based on their URL structure, text, and image features. Previously, similar studies have used machine learning techniques for URL features with a limited dataset. In our research, we have used a large dataset of 20,000 website URLs, and 22 salient features from each URL are extracted to prepare a comprehensive dataset. Along with this, another dataset containing website text is also prepared for NLP-based text evaluation. It is seen that many phishing websites contain text as images, and to handle this, the text from images is extracted to classify it as spam or legitimate. The experimental evaluation demonstrated efficient and accurate phishing detection. Our layered classification model uses support vector machine (SVM), XGBoost, random forest, multilayer perceptron, linear regression, decision tree, naïve Bayes, and SVC algorithms. The performance evaluation revealed that the XGBoost algorithm outperformed other applied models with maximum accuracy and precision of 94% in the training phase and 91% in the testing phase. Multilayer perceptron also worked well with an accuracy of 91% in the testing phase. The accuracy results for random forest and decision tree were 91% and 90%, respectively. Logistic regression and SVM algorithms were used in the text-based classification, and the accuracy was found to be 87% and 88%, respectively. With these precision values, the models classified phishing and legitimate websites very well, based on URL, text, and image features. This research contributes to early detection of sophisticated phishing attacks, enhancing internet user security. [ABSTRACT FROM AUTHOR]

Loss of Smad3 and the consequent activation of myocardin-related transcription factor (MRTF) are associated with vascular pathologies. This study aimed to examine the impact of persistent hypoxia with intermittent aggravation (PI hypoxia) on cellular senescence and pulmonary arterial remodeling mediated by the Smad3/MRTF imbalance. We examined the effects of PI hypoxia on the Smad3/MRTF pathway and cellular senescence using human pulmonary artery endothelial cells (HPAECs) and in vivo studies in rats. The senescent degree was evaluated using β-galactosidase staining, p16 quantitation and the measurement of senescence-associated secretory phenotype. Structural data in the pathological analysis of pulmonary artery remodeling were collected. Compared to the control, HPAECs and pulmonary tissue from rats exposed to PI hypoxia showed a significantly higher senescent degree, lower expression of Smad3, and higher MRTF levels. The overexpression of Smad3 significantly mitigated HPAECs senescence in vitro. Further, treatment with CCG-203971, which inhibits MRTF, increased Smad3 levels and reduced β-galactosidase positive cells in rat lung tissue. This intervention also alleviated PI hypoxia-induced pathological changes, including remodeling indices of pulmonary arterial thickening, muscularization, and collagen formation. In conclusion, imbalanced Smad3/MRTF signaling is linked to PI hypoxia-induced senescence and pulmonary arterial remodeling, making it a potential therapeutic target for patients with sleep apnea and chronic obstructive pulmonary disease. [ABSTRACT FROM AUTHOR]

Four new compounds (1–4) were isolated from the whole plants of two species of Delphinium, including two C20-diterpenoid alkaloids, umbrodines A and B (1 and 2), and a dibenzoxazepinone, umbrolide A (3) from Delphinium umbrosum Hand.-Mazz. and a C20-diterpenoid alkaloid, kingiadine (4) from Delphinium kingianum Bruhl. ex Huth. Ten known diterpenoid alkaloids were also isolated. Their structures were elucidated via HR-ESIMS, IR, and NMR data. Lycoctonine (11) and delectinine (12) exhibited appreciable cardiac activity. Furthermore, 11 and 12 showed cardioprotective effects against doxorubicin-induced toxicity in H9c2 cells, with the maximum protection rates of 61.63% and 51.18%, respectively. [ABSTRACT FROM AUTHOR]

Introduction: Allergic rhinitis (AR) is identified as a multifactorial disease caused by the interaction of genes and surroundings, which is difficult to cure. MicroRNAs were reported to be engaged in AR development. Here, we aimed to seek the anti-inflammatory effects and regulatory mechanism of miR-193b-3p in AR. Methods: Mucosal tissues from AR patients and healthy volunteers were collected, and human nasal epithelial cells (HNECs) were treated with IL-13 to establish a cell model of AR. The gene expression of miR-193b-3p, ETS1, TLR4, GM-CSF, eotaxin, and MUC5AC was determined by RT-qPCR. The protein levels of ETS1 and TLR4 were examined using Western blot. Enzyme-linked immunosorbent assay was performed to measure protein concentration of GM-CSF, eotaxin, and MUC5AC in cell supernatant. Dual luciferase assay was applied to verify the interaction among miR-193b-3p, ETS1, and TLR4. Results: The expression of miR-193b-3p was declined in clinical samples from AR patients and in IL-13-induced HNECs, while the mRNA and protein levels of ETS1 and TLR4 were elevated. MiR-193b-3p overexpression or ETS1 silencing notably decreased the mRNA and protein levels of GM-CSF, eotaxin, and MUC5AC in IL-13-treated HNECs. Mechanistically, miR-193b-3p directly combined with ETS1 to silence ETS1 expression. ETS1 promoted the transcriptional activity of TLR4 through interacting with TLR4 promoter. Furthermore, rescue experiments revealed that ETS1 overexpression abolished miR-193b-3p sufficiency-mediated suppression of the mRNA and protein levels of GM-CSF, eotaxin, and MUC5AC in IL-13-treated HNECs. Similarly, TLR4 overexpression compromised the inhibitory impacts of ETS1 downregulation on the mRNA and protein levels of GM-CSF, eotaxin, and MUC5AC in IL-13-induced HNECs. Discussion:MiR-193b-3p repressed IL-13-induced inflammatory response in HNECs by suppressing ETS1/TLR4 axis, which indicated that miR-193b-3p might be a therapeutic target for AR treatment. [ABSTRACT FROM AUTHOR]

The construction of cell differentiation trajectories from single-cell transcriptomic data or proteomic data by single-cell trajectory inference methods can help to understand the developmental process of normal tissues or provide pathologically relevant information. However, the accuracy and robustness of current single-cell trajectory inference algorithms are still a challenge, one of the reasons is the noise caused by the detection of a large number of unrelated genes in single-cell sequencing. In order to solve this problem, a trajectory inference method iterTIPD (iterative trajectory inference based on probability distribution) based on iterative feature selection is proposed. Its innovation lies in iteratively applying feature selection methods widely used for screening differentially expressed genes to linear or branching single-cell RNA sequencing data, and improving the accuracy and robustness of cell pseudotime ordering by selecting the gene subset that contributes the most to the constructed differentiation trajectory. Experimental results on four scRNA-seq datasets show that iterTIPD can effectively improve the accuracy and robustness of the single-cell trajectory inference algorithm. IterTIPD also improves the performance of other trajectory inference algorithms, proving generalization of iterTIPD. The differentiation trajectory of neural stem cells is reconstructed by iterTIPD algorithm, and the comparison shows that the differentiation trajectory is highly consistent with the known neural stem cell differentiation trajectory. Meanwhile, Top2a and Gja1 may be novel markers defining activated neural stem cell subpopulations. [ABSTRACT FROM AUTHOR]

Organophosphate insecticides have been widely used in agriculture to control insect pests and raised growing problems including insecticide resistance. According to recent studies, microbial symbionts play important roles in developing insecticide resistance. The bean bug Riptortus pedestris is a notorious pest of leguminous crops, harbouring diverse microorganisms in their insect midguts. However, the potential biological roles of many gut‐associated bacteria are largely unknown. In this study, we isolated a bacterial strain from the midgut of R. pedestris and identified it as Serratia marcescens based on its morphological characteristics and the phylogenetic analysis of the 16S rRNA gene sequence. A halo of phosphorus‐solubilizing bacteria was observed on a medium containing lecithin and an organophosphorus insecticide dimethoate. Subsequently, the microbial degradation of dimethoate was determined using Gas Chromatography with Mass Spectroscopy (GC–MS). Further analysis indicated that the S. marcescens contained organophosphorus‐degrading MBL‐fold metallo‐hydrolase gene. Additionally, we discovered that the bacterium could colonize the insect midgut stably and enhance the host survivorship when exposed to dimethoate. Our results revealed that an insect gut‐associated bacterium could degrade organophosphorus compounds, thereby reducing related insecticide toxicity to the insect hosts. These findings provided further insights into the host‐microbiota interactions underpinning the development of insecticide resistance. [ABSTRACT FROM AUTHOR]

During the postconstruction operation period, the engineering structure and operation safety of a pipe-jacking tunnel are more likely to be threatened by the surrounding environment and groundwater when it is located in a soft clay stratum. Surface settlement data related to the construction of 24 rectangular pipe-jacking tunnels in a soft clay stratum in China were collected and analyzed to determine the effect of pipe-jacking tunnel engineering on its deformation based on factors such as structural section form, geotechnical condition, groundwater condition, and buried depth. The postmaximum surface settlement and postformation loss rate were obtained, the correlation coefficients between the postsurface deformation of soft clay strata and various influencing factors were calculated using a software for correlation analysis, and the variation rules for each influencing factor were explored in depth. Subsequently, multiple linear regression methods were used to predict the maximum surface deformation of the pipe-jacking tunnel project in soft clay strata during the postoperation period, and actual engineering cases were verified and analyzed. The results show that the relative buried depth of the pipe-jacking tunnel in soft clay stratum has the greatest influence on the postmaximum ground settlement, followed by the section area of the pipe-jacking tunnel, and the relative height coefficient of groundwater level has the least influence. Under the reduction coefficient of 0.937 − 0.846, a new prediction formula for surface settlement deformation after the construction of the soft clay layer was derived. The error between the formula and the measured data was 9.05%, which can be used as a reference for controlling design parameters to predict the settlement after construction of pipe-jacking engineering. [ABSTRACT FROM AUTHOR]

The disturbance of disruptive passengers in the cabin seriously affects aviation security in China. Reducing the occurrence of disturbances in the cabin is an inevitable choice to strengthen the security of civil aviation in China and improve the emergency disposal of airlines. Therefore, this paper investigates the strength of government support, the benefits of cooperation and the punishment of disposers, and uses the event tree method to analyze the relevant subjects affecting the consequences of cabin disruptions. To this end, a cabin disturbance emergency management game model comprised of regulatory authority, airline security and disruptive passengers was then established. The results of the game playing and simulation highlight the inherent relationships in emergency management in China's civil aviation. First, the choice of behavior of the regulatory authority and disruptive passengers are mainly influenced by the strategy of airline security. Second, the strength of support from the regulatory authority determines whether the airline security can dispose of the passengers successfully. Third, the disruptive inclination of disruptive passengers is directly influenced by the intensity of punishment by airport police. Finally, an empirical analysis and simulation is conducted with the example of using an open flame or smoking in the cabin. This study provides new ideas for enhancing aviation security and improving emergency management. [ABSTRACT FROM AUTHOR]

Background: The Chinese population is aging, and chronic non-communicable diseases (NCDs) prevalence is correspondingly increasing, along with associated disability and healthcare costs. Although self-management has been associated with social support and is a recognized priority, its mediating variables have not been studied in detail, particularly among old people with chronic diseases. Purpose: To examine the mediating role of e-health literacy and general self-efficacy in the relationship between social support and self-management of chronic NCDs in Chinese community home-based aging institution residents. Patients and Methods: A random sample of 289 community home-based aging institution elders (≥ 60 years) with chronic NCDs in China was recruited. Questionnaire data were recorded on self-reported socio-demographics, self-management, social support, e-health literacy, and general self-efficacy. Pearson's correlation analysis identified the relationship between these factors and self-management. Serial multiple mediation model was used to test the hypothesized relationships. Results: The self-management mean (±SD) score was 29.39 ± 9.60, and the level of self-management was medium. Social support (r = 0.283; P < 0.001), e-health literacy (r = 0.566; P < 0.001), and general self-efficacy (r = 0.477; P < 0.001) were positively associated with self-management. Furthermore, social support indirectly influenced self-management through three pathways: independent mediation of e-health literacy (effect = 0.234, P < 0.001), independent mediation of general self-efficacy (effect = 0.515, P < 0.001), and chain mediation of e-health literacy and general self-efficacy (effect = 0.075, P < 0.001). Conclusion: In Chinese community home-based aging institution elders, the relationship between self-reported self-management and social support is positively affected by the independent mediating effect of e-health literacy and general self-efficacy and the serial mediating effect of e-health literacy and general self-efficacy. Targeted self-management programs for elders with chronic NCDs have theoretical support, which could improve the health status and quality of life in this population. [ABSTRACT FROM AUTHOR]

Purpose: To determine the independent predictive role of nasal obstruction in resistant hypertension (RH) in uncontrolled hypertensive patients with obstructive sleep apnea (OSA). Methods: This prospective cohort study comprised of 236 OSA patients with uncontrolled blood pressure (BP) using 1 or 2 classes of antihypertensive drugs visiting Sleep Medicine Center from April 2021 to March 2022. Information on demographic characteristics, comorbidities, BP control and classes of antihypertensive medication, sleep-related symptoms, Nasal Obstruction Symptom Evaluation (NOSE) Scale and sleep parameters was collected. RH incidence according to the BP control and classes of antihypertensive drugs data during the 5 month follow-up was collected. Results: After 5 month follow-up, 217 participants were included for final data analysis. Ninety-five subjects had nocturnal nasal obstruction with a higher proportion of RH (36.8% vs. 17.2%, p = 0.001) compared to those without nocturnal nasal obstruction. After adjustment for demographic characteristics, sleep-related symptoms and OSA severity, multinomial logistic regression models showed that nocturnal nasal obstruction (all ORs > 2.5, p < 0.05) or NOSE ≥ 8 (all ORs > 4.5, p < 0.05) was independently associated with a higher odds of RH. Nasal obstruction treatment improved NOSE score significantly, but did not reduce the incidence of RH significantly. Effective nasal obstruction treatment was associated with antihypertensive drugs reduction (OR 4.43; 95% CI 1.20–16.27). Conclusions: Nasal obstruction is an independent predictor of RH in uncontrolled hypertensive patients with OSA. In addition to the treatment of OSA, assessment and treatment of nasal obstruction should be considered in the management of uncontrolled hypertensive patients with OSA. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorders (ASD) is a neurodevelopmental disorder with high incidence rate and difficult diagnosis. The purpose of this study was to explore whether salivary cortisol, dehydroepiandrosterone (DHEA) and pregnenolone can be used as biomarkers of ASD children. Methods: The saliva samples of 55 boys with ASD were collected as the experimental group, and the saliva samples of 24 neurotypical boys were collected as the control group. The Child Behavior Checklist (CBCL), Autism Behavior Checklist (ABC), Social Responsiveness Scale (SRS), Repetitive Behavior Scale (RBS) were used to assess the severity of symptoms in boys with ASD. Cortisol, DHEA and pregnenolone concentrations in saliva were measured using an ABSSCIEX QTRAP® 6500 + LC/MS/MS system. SPSS 23.0 was used for statistical analysis. Comparisons between the two groups which conform to normal distribution were performed by T-test, and those which don’t conform to normal distribution were performed by Mann–Whitney U test. Correlation analysis between two variables was performed using Spearman's correlation analysis. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the discriminatory sensitivity of each hormone between ASD and normal control groups. Logistic regression models were used to analyze whether DHEA and salivary pregnenolone can be used as a biomarker of ASD. Results: There were no significant differences in age, and weight between the ASD group and the normal control group. The ABC, SRS, RBS and CBCL scale scores in the ASD group were significantly higher than those in the normal control group. The salivary DHEA and pregnenolone concentrations in the ASD group were significantly higher than those in the normal control group, but there was no significant difference in cortisol. Spearman's correlation analysis showed that only pregnenolone associated with ABC. Logistic regression model analysis suggested that pregnenolone in saliva was an independent predictor of ASD. ROC analysis found that pregnenolone had good discrimination sensitivity between ASD and normal controls. Conclusion: Gave salivary preoperative a space for utilization as biomarker as number of cases are limited to this high expectation. [ABSTRACT FROM AUTHOR]

Long-term intensive use of mineral fertilizers in double rice-cropping systems has led to soil acidification and soil degradation. Manure fertilization was suggested as an alternative strategy to mitigate soil degradation. However, the effects of long-term mineral and manure fertilization on rice grain yield, yield stability, soil organic carbon (SOC) content, soil total nitrogen (TN) content, and the underlying mechanisms are unclear. Based on a long-term experiment established in 1981 in southern China, we compared four treatments: no fertilizer application (Control); application of nitrogen–phosphorus–potassium (NPK); NPK plus green manure in early rice (M1); and M1 plus farmyard manure in late rice and rice straw return in winter (M2). Our results showed that 37 years of NPK, M1, and M2 significantly increased rice grain yield by 54%, 46%, and 72%, and yield stability by 22%, 17%, and 9%, respectively. M1 and M2 significantly increased SOC content by 39% and 23% compared to Control, respectively, whereas there was no difference between Control and NPK. Regarding soil TN content, it was significantly increased by 8%, 46%, and 20% by NPK, M1, and M2, respectively. In addition, M2 significantly increased bacterial OTU richness by 68%, Chao1 index by 79%, and altered the bacterial community composition. Changes in soil nutrient availability and bacterial Simpson index were positively correlated with the changes in grain yield, while shifts in bacterial community were closely related to yield stability. This study provides pioneer comprehensive assessments of the simultaneous responses of grain yield, yield stability, SOC and TN content, nutrient availability, and bacterial community composition to long-term mineral and manure fertilization in a double rice-cropping system. Altogether, this study spanning nearly four decades provides new perspectives for developing sustainable yet intensive rice cultivation to meet growing global demands. [ABSTRACT FROM AUTHOR]

Background: Drug–drug interactions (DDIs) occur when two or more drugs are taken simultaneously or successively. Early detection of adverse drug interactions can be essential in preventing medical errors and reducing healthcare costs. Many computational methods already predict interactions between small molecule drugs (SMDs). As the number of biotechnology drugs (BioDs) increases, so makes the threat of interactions between SMDs and BioDs. However, few computational methods are available to predict their interactions. Results: Considering the structural specificity and relational complexity of SMDs and BioDs, a novel multi-modal representation learning method called Multi-SBI is proposed to predict their interactions. First, multi-modal features are used to adequately represent the heterogeneous structure and complex relationships of SMDs and BioDs. Second, an undersampling method based on Positive-unlabeled learning (PU-sampling) is introduced to obtain negative samples with high confidence from the unlabeled data set. Finally, both learned representations of SMD and BioD are fed into DNN classifiers to predict their interaction events. In addition, we also conduct a retrospective analysis. Conclusions: Our proposed multi-modal representation learning method can extract drug features more comprehensively in heterogeneous drugs. In addition, PU-sampling can effectively reduce the noise in the sampling procedure. Our proposed method significantly outperforms other state-of-the-art drug interaction prediction methods. In a retrospective analysis of DrugBank 5.1.0, 14 out of the 20 predictions with the highest confidence were validated in the latest version of DrugBank 5.1.8, demonstrating that Multi-SBI is a valuable tool for predicting new drug interactions through effectively extracting and learning heterogeneous drug features. [ABSTRACT FROM AUTHOR]

Adverse drug–drug interactions (DDIs) can severely damage the body. Thus, it is essential to accurately predict DDIs. DDIs are complex processes in which many factors can cause interactions. Rather than merely considering one or two of the factors, we design a two-pathway drug–drug interaction framework named TP-DDI that uses multimodal data for DDI prediction. TP-DDI effectively explores the combined effect of a topological structure-based pathway and a biomedical object similarity-based pathway to obtain multimodal drug representations. For the topology-based pathway, we focus on drug chemistry structures through the self-attention mechanism, which can capture hidden critical relationships, especially between pairs of atoms at remote topological distances. For the similarity-based pathway, our model can emphasize useful biomedical objects according to the channel weights. Finally, the fusion of multimodal data provides a holistic view of DDIs by learning the complementary features. On a real-world dataset, experiments show that TP-DDI can achieve better performance than the state-of-the-art models. Moreover, we can find the most critical substructures with certain interpretability in the newly predicted DDIs. [ABSTRACT FROM AUTHOR]

Background: Female reproductive tract infection (RTI) is the common source of varied diseases, especially as an important risk factor for pregnancy outcomes, therefore the rapid, accurate and simultaneous detection of multiple pathogens is in urgent need for assisting the diagnosis and treatment of RTI in pregnant women. Streptococcus agalactiae (S. agalactiae), Enterococcus faecalis (E. faecalis), Gardnerella vaginalis (G. vaginalis), Candida albicans (C. albicans) and Chlamydia trachomatis (C. trachomatis) are five main pathogens in lower genital tract with high risk, serious consequences and clinical demands. The combination of loop-mediated isothermal amplification (LAMP) and microfluidic technology was used to develop the LAMP-microfluidic chip for rapid, simple, sensitive and simultaneous detection of the five target pathogens above. Results: Standard strains and clinical isolates were used for the establishment of the novel LAMP method in tube and LAMP-microfluidic chip, followed by the chip detection on 103 clinical samples and PCR verification partially. The sensitivities of LAMP of S. agalactiae, E. faecalis, G. vaginalis, and C. albicans in tube were 22.0, 76.0, 13.2, 1.11 CFU/μL, respectively, and C. trachomatis was 41.3 copies/μL; on LAMP-microfluidic chip they were 260, 154, 3.9 and 7.53 CFU/μL, respectively, and C. trachomatis was 120 copies/μL. The positive coincidence rates of clinical stains in tube and on chip experiments were 100%. Compared with the classic culture method performed in hospitals, the positive coincidence rate of the 103 clinical samples detected by LAMP-microfluidic chip were 100%. For the six inconsistent ones, including four G. vaginalis and two C. albicans positive samples tested by LAMP-microfluidic chip and verified by PCR were negative by culturing method in hospitals, indicating the lack of efficient detection by the classic culturing method. Conclusion: Our study suggested that the LAMP-microfluidic chips could simultaneously, efficiently, and accurately detect multiple main pathogens, including S. agalactiae, E. faecalis, G. vaginalis, C. albicans and C. trachomatis, in clinical samples of female RTI to give a great clinical value. Accordingly, this novel method has the potential to provide a valuable reference for female RTI screening and early diagnosis during pregnancy. [ABSTRACT FROM AUTHOR]

Purpose: It has been established that obstructive sleep apnea (OSA) is an independent risk factor for atherosclerosis. Chronic intermittent hypoxia (CIH) activates sympathoadrenal system and upregulates β3 adrenergic receptor (β3 AR). However, the effect of selective β3 AR agonist mirabegron in CIH-induced atherosclerosis remains unknown. Methods: We generated a CIH-induced atherosclerosis model through exposing ApoE−/− mice to CIH (8 h per day, cyclic inspiratory oxygen fraction 5–21%, 60-s cycle) for 6 weeks after 4-week high-fat dieting and investigated the effects of mirabegron, a selective β3 AR agonist, on CIH-induced atherosclerosis. The coronary endarterectomy (CE) specimens from coronary artery disease patients with OSA and without OSA were collected. Results: The expression of β3 AR was significantly elevated in CIH-induced atherosclerosis model. Furthermore, treatment with mirabegron (10mg/kg per day by oral administration for 6 weeks) ameliorated atherosclerosis in ApoE−/− mice in CIH but not in normoxia. Mechanistically, mirabegron activated β3 AR and ameliorated intraplaque oxidative stress by suppressing p22phox expression and reactive oxygen species (ROS) level. In addition, in human CE specimens, β3 AR was also upregulated associated with increased p22phox expression and ROS level both in the lumen and in the plaque of coronary artery in OSA subjects. Conclusion: This study first demonstrated that mirabegron impeded the progression of CIH-induced atherosclerosis, at least in part, via β3 AR–mediated oxidative stress, suggesting a promising therapeutic strategy for protecting against atherosclerosis induced by CIH. [ABSTRACT FROM AUTHOR]

Compared to arid regions, forests in humid regions can be more vulnerable to drought as they are not used to, and thus not adapted to, water stress. Therefore, it is vital to understand the drought responses of woodland species in humid areas. Xylem structures and functions of species growing in the humid regions are the key to their drought responses. Two Cupressaceae species (including three taxa: Sequoia sempervirens, Taxodium distichum and its variety Taxodium distichum var. imbricatum) grown in a mesic common garden were targeted, and their xylem hydraulic function (hydraulic conductivity, Ks; cavitation resistance, P50), anatomical structure (tracheid and pit structure), and mechanical support (wood density, WD; tracheid thickness-to-span ratio, Ttob) were measured. Likewise, we analyzed the differences in hydraulic function and anatomical structure of xylem in branches and roots, and the quantitative relationship between xylem water transport, anatomical structure, and mechanical support. Our results showed that roots had a higher hydraulic conductivity and a weaker cavitation resistance than branches. There was no safety–efficiency trade-off in the branches and roots within species. Tracheid mechanical support had a trade-off relationship with Ks or P50 (negative correlation appeared in branch Ks ~ WD and root Ks ~ Ttob of S. sempervirens, root P50 ~ Ttob of T. distichum var. imbricatum, and branch P50 ~ WD). There was no trade-off in anatomical structure, which led to no safety–efficiency trade-off in xylem function. Our results suggest that the two species exhibit both low efficiency and low safety in xylem, and that there is no safety–efficiency trade-off in branches and roots. The reason behind this is that the structural demand for high safety and high efficiency differs (i.e., the root Ks of S. sempervirens was strongly controlled by Dh; in contrast, the root P50 of S. sempervirens was strongly determined by tracheid density, N). Namely, the structural basis for a safety–efficiency trade-off does not exist and therefore trade-offs cannot be achieved. [ABSTRACT FROM AUTHOR]

Leaf veins are the continuation of twigs, and the hydraulic system of a leaf is part of, and the continuation of, the hydraulic architecture of a tree. Previous studies have demonstrated that the vessel diameter of the widest part at the tree base is tightly related to the total stem length of a tree. Here, we demonstrate that: the vessel diameter of the narrowest part at the distal end of the tree (the terminal twigs) is closely correlated to the leaf size for an angiosperm tree. Consequently, the basic feature of the hydraulic system of an angiosperm tree may be predicted by two simple parameters: the stem length (or tree height) and the leaf size, with the tree height predicting the size of the widest vessel at the tree base and the leaf size predicting the size of the narrowest vessel at the terminal trig. Namely, there is an inherent coordination between the leaf size and the hydraulic architecture of the angiosperm tree. As leaves are replacing themselves every year, their responses to climate are direct and immediate, while the woody part of a tree is there for years and more, and thus can only respond passively to climate change. This may cause a mismatch between the woody part and leaf part of the hydraulic system, and thus endanger the hydraulic coordination between leaves and the woody part. [ABSTRACT FROM AUTHOR]

Apnea of prematurity (AOP) is onc of the common diseases in preterm infants. The main cause of AOP is immature development of the respiratory control center. If AOP is not treated timely and effectively, it will lead to respiratory failure, hypoxic brain injury, and even death in severe cases. Caffeine is the first choice for the treatment of AOP, but its effectiveness varies in preterm infants. With the deepening of AOP research, more and more genetic factors have been confirmed to play important roles in the pathogenesis and treatment of AOP; in particular, the influence of single nucleotide polymorphism on the efficacy of caffeine has become a research hotspot in recent years. This article reviews the gene polymorphisms that affect the efficacy of caffeine, in order to provide a reference for individualized caffeine therapy. [ABSTRACT FROM AUTHOR]

Acute respiratory distress syndrome (ARDS) is a leading cause of death in critically ill patients due to hypoxemic respiratory failure. The specific pathogenesis underlying ARDS has not been fully elucidated. In this study, we constructed a triple regulatory network involving competing endogenous RNA (ceRNA) to investigate the potential mechanism of ARDS and evaluated the immune cell infiltration patterns in ARDS patients. Overall, we downloaded three microarray datasets that included 60 patients with sepsis-induced ARDS and 79 patients with sepsis alone from the public Gene Expression Omnibus (GEO) database and identified differentially expressed genes (DEGs, including 9 DElncRNAs, 9 DEmiRNAs, and 269 DEmRNAs) by R software. The DEGs were subjected to the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional enrichment analysis, and a protein–protein interaction (PPI) network was generated for uncovering interactive relationships among DEmRNAs. Then, a ceRNA network that contained 5 DElncRNAs, 7 DEmiRNAs, and 71 DEmRNAs was established according to the overlapping genes in both DEGs and predicted genes by public databases. Finally, we identified the TUG1/miR-140-5p/NFE2L2 pathway as the hub pathway in the whole network through Cytoscape. In addition, we evaluated the distribution of 22 subtypes of immune cells and recognized three differentially expressed immune cells in patients with sepsis-induced ARDS by "Cell Type Identification by Estimating Relative Subsets of Known RNA Transcripts (CIBERSORT)" algorithm, namely, naive B cells, regulatory T cells, and eosinophils. Correlations between differentially expressed immune cells and hub genes in the ceRNA network were also performed. In conclusion, we demonstrated a new potential regulatory mechanism underlying ARDS (the TUG1/miR-140-5p/NFE2L2 ceRNA regulatory pathway), which may help in further exploring the pathogenesis of ARDS. [ABSTRACT FROM AUTHOR]

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The treatment of autism spectrum disorder (ASD) is one of the most difficult challenges in neurodevelopmental diseases, because of the unclear pathogenesis research and low brain-lesion targeting efficiency. Besides, maternal immune activation has been reported as the most mature and widely used model of ASD and aspirin-triggered lipoxin A4 is a potent anti-inflammatory mediator being involved in the resolution of neuroinflammation in ASD. Therefore, an aspirin encapsulated cascade drug delivery system (Asp@TMNPs) is established, which can successively target the blood-brain barrier (BBB) and microglial cells and response to the acid microenvironment in lysosome. As a result, the mitochondrial oxidative stress, DNA damage, and inflammation of microglial cells are prominently alleviated. After the treatment of Asp@TMNPs, the social interaction, stereotype behavior, and anxious condition of ASD mice are notably improved and the activation of microglial cells is inhibited. Overall, this system successively penetrates the BBB and targets microglial cells, therefore, it significantly enhances the intracephalic drug accumulation and improves anti-neuroinflammatory efficacy of aspirin, providing a promising strategy for ASD treatment. [ABSTRACT FROM AUTHOR]

The early prediction of a patient's response to neoadjuvant chemotherapy (NAC) in breast cancer treatment is crucial for guiding therapy decisions. We aimed to develop a novel approach, named the dual-branch convolutional neural network (DBNN), based on deep learning that uses ultrasound (US) images for the early prediction of NAC response in patients with locally advanced breast cancer (LABC). This retrospective study included 114 women who were monitored with US during pretreatment (NAC pre) and after one cycle of NAC (NAC1). Pathologic complete response (pCR) was defined as no residual invasive carcinoma in the breast. For predicting pCR, the data were randomly split into a training set and test set (4:1). DBNN with US images was proposed to predict pCR early in breast cancer patients who received NAC. The connection between pretreatment data and data obtained after the first cycle of NAC was considered through the feature sharing of different branches. Moreover, the importance of data in various stages was emphasized by changing the weight of the two paths to classify those with pCR. The optimal model architecture of DBNN was determined by two ablation experiments. The diagnostic performance of DBNN for predicting pCR was compared with that of four methods from the latest research. To further validate the potential of DBNN in the early prediction of NAC response, the data from NAC pre and NAC1 were separately assessed. In the prediction of pCR, the highest diagnostic performance was obtained when combining the US image information of NAC pre and NAC1 (area under the receiver operating characteristic curve (AUC): 0.939; 95% confidence interval (CI): 0.907, 0.972; F1-score: 0.850; overall accuracy: 87.5%; sensitivity: 90.67%; and specificity: 85.67%), and the diagnostic performance with the combined data was superior to the performance when only NAC pre (AUC: 0.730; 95% CI: 0.657, 0.802; F1-score: 0.675; sensitivity: 76.00%; and specificity: 68.38%) or NAC1 (AUC: 0.739; 95% CI: 0.664, 0.813; F1-score: 0.611; sensitivity: 53.33%; and specificity: 86.32%) (p<0.01) was used. As a noninvasive prediction tool, DBNN can achieve outstanding results in the early prediction of NAC response in patients with LABC when combining the US data of NAC pre and NAC1. [ABSTRACT FROM AUTHOR]

In global climate researches, marine ecosystem researches, and ocean-related applications, it is of considerable significance to accurately observe and predict sea surface temperature (SST). However, various physical and environmental factors affect the changes in SST, making it highly random and uncertain. Therefore, it is still a challenge to propose a highly accurate SST prediction method. SST prediction methods based on the temporal information usually focus on capturing the temporal influence of the historical SST but ignore the spatial influence in the sea area, so these methods meet the performance bottlenecks. To fuse the multidimensional spatiotemporal influence and further improve the accuracy of the SST prediction, this letter proposed the convolutional gated recurrent unit (GRU) with multilayer perceptron (CGMP) to predict SST in the Bohai Sea and the South China Sea. The convolutional layer of CGMP can capture the neighbor influence effectively in the spatial dimension, making up for the shortcomings of methods that are based on the temporal information and do not consider the spatial information. The GRU layer and the MLP layer of CGMP can process historical information effectively in the temporal dimension. Experiments showed that the prediction performance of CGMP was better than those of other comparison methods in different sea areas, different schemas, and different prediction scales. Besides, the error distribution law in the Bohai Sea daily mean SST prediction was explored. [ABSTRACT FROM AUTHOR]

Autism spectrum disorders (ASD) represent a complex group of neurodevelopmental disorders that are characterized by impaired social behavior and communication as well as repetitive behavior and restricted interests. Prenatal exposure to high levels of testosterone and preeclampsia are thought to be risk factors of ASD. We had previously reported that overexpression of the mitochondrial cholesterol side-chain cleavage enzyme (CYP11A1) could lead to both preeclampsia-like symptoms and increased testosterone levels in pregnant rats. In this study, we investigated the association between high CYP11A1 levels in pregnant rats and autism-like behavior in their offspring. Timed-pregnant Sprague-Dawley (SD) rats were injected with CYP11A1 gene-carrying adenoviruses on gestational day 8.5, and their offspring were then compared with those from timed-pregnant control SD rats. Compared with their control counterparts, the offspring of the CYP11A1 -ovexpressing dams displayed more symptoms of anxiety and spent less time in social interactions and more time in self-grooming and rearing, all indicators of autism-like behavior. Sequencing of the transcriptome in primary microglia from the offspring of CYP11A1 -overexpressing dams revealed that immune pathways were highly activated, and the gamma-aminobutyric acid type A (GABAA) receptor genes were among the top differentially expressed genes. Using primary microglia cultures generated from neonatal rats, tumor necrosis factor-alpha expression was found to be elevated in the cells transfected with CYP11A1 -carrying adenoviruses. Additionally, the offspring of CYP11A1 -overexpressing dams displayed dysregulated GABAA receptor expression. Taken together, these results suggest that abnormal CYP11A1 gene expression in pregnant rats could lead to microglial immune activation and dysregulated GABAA receptor expression in their offspring and thereby anxiety and autism-related behavior. Our study suggests that the pathways regulated by CYP11A1 could be promising preventative and therapeutic targets for ASD. [ABSTRACT FROM AUTHOR]

Single-cell RNA-seq technology provides an unprecedented opportunity to allow researchers to study the biological heterogeneity during cell differentiation and development with higher resolution. Although many computational methods have been proposed to infer cell lineages from single-cell RNA-seq data, constructing accurate cell trajectories remains a challenge. We develop a novel trajectory inference method-based probability distribution (TIPD) to describe the heterogeneity of cell population. TIPD combines signalling entropy and clustering results of the gene expression profile to describe the probability distributions of heterogeneous states in a cell population. It does not require external knowledge to determine the direction of the differentiation trajectories, so its application is not limited by the annotations of the data set. We also propose a new distance metric to measure the distance of the probability distributions of the identified heterogeneous states. On this distance matrix, a minimum spanning tree (MST) is built to reorganize the order of cell clusters. The constructed MST is calculated based on systems-level information, so it is consistent with the real biological process. We validated our method on four previously published single-cell RNA-seq data sets including the linear structure and branch structure. The results showed that TIPD successfully reconstructed the differentiation trajectories that are highly consistent with the known differentiation trajectories and outperformed the other four state-of-the-art methods under different assessment criteria. [ABSTRACT FROM AUTHOR]

With the feedback rotor speed outer-loop PI control, the mechanism analysis of SMES-based power oscillation damping is derived by the small signal and classical electric torque method in this research. Theoretical analysis shows that adjusting the proportional and integral can equivalently dominate the damping ability and synchronization level. However, the conventional PI may cause the deep charging-discharging so that the power oscillation damping failure. To this end, the proportional integral controller with integral alleviation (PI-IA) controller is designed to address this issue, which not only ensures energy deviation-free of SMES, but also holds the advantage of PI controller. Moreover, the effectiveness of the proposed controller and the validity of the mechanism analysis are performed by the time-domain simulation. [ABSTRACT FROM AUTHOR]

Soldier pile support is an important tool for supporting deep foundation pits in the sand-gravel layer. However, since the sand-gravel layer itself is an aggregate of particles, its noncontinuity will cause extremely complex changes in the properties of the surrounding soils during pile supporting, and the changes in the mechanical properties of the soil behind the piles can also affect the safety and stability of the pit. To study the changing pattern of the surrounding soil in the course of pile supporting, we used the numerical method to simulate an excavation in the sand-gravel layer, followed by an analysis of the movement and stress distribution of the surrounding rocks. A photoelastic experiment was carried out to simulate the excavation process and study the force chain network of the surrounding soil as well as its changing characteristics. As shown by the results, (1) during the excavation of a deep foundation pit supported by soldier piles, on the same horizontal plane, the force chain changed most dramatically at the position that was 13.8 m (depth of the foundation pit) away from the edge of the foundation pit; (2) during the excavation, the force chain structure of the surrounding soil changed from vertical development to both vertical and horizontal developments; when there was a hard rock layer at the bottom of the soldier piles, the supporting effect of the piles was mainly provided by the hard rock layer; (3) the free face should be reinforced, and the excavation face should be adjusted based on the underground conditions of surrounding buildings (structures). [ABSTRACT FROM AUTHOR]

Based on the lattice Boltzmann Method (LBM), a new moving boundary treatment is proposed by studying the influence of the moving boundary in a low-speed incompressible fluid. Simulating flow past a static cylinder, flow past a moving cylinder, and flow in a curved moving pipe shows that the LBM has high reliability and stability with moving boundary conditions. In order to reduce parallel computing time and take full advantage of the characteristics of the model, the solid grids are allocated according to the number of computing cores. Two parallel speedup ratios were tested, keeping the overall task volume unchanged to increase the number of cores and keeping the single-core task volume unchanged. In the first speedup ratio, the efficiency of the flow field calculation at 112 cores reached more than 80%. The second speedup ratio indicated that the proportion of communication in the program was tiny and suitable for large-scale parallel computing. The study of the moving boundary problem can effectively help solve the fluid-structure coupling problem. Due to the particularity of the model, it can be used to simulate the fluid-structure coupling problem of blood vessel flow effectively. [ABSTRACT FROM AUTHOR]