Combined transcriptome and metabolome analyses reveal the mechanism of abundant bioactive compounds and high antioxidant activity in germinated weedy rice.

Germinated brown rice has recently garnered widespread attention due to its high nutritional value. Previous research demonstrated that the bioactive components and functional properties of germinated brown rice varieties exhibit significant differences. Three germinated rice cultivars weedy rice WR04-6 (WR) and two cultivated rice cultivars with superior eating quality, Koshihikari (YG) and Daohuaxiang (DHX), were analyzed using metabolites and transcriptome profiling. Widely targeted metabolomics results showed that 85.9% and 71.2% of differential metabolites for WR vs. YG and WR vs. DHX were enriched in WR, respectively. The substances mainly included amino acids and derivatives, carbohydrates and its derivatives, organic acids and its derivatives, and flavonoids. Higher antioxidant activity was detected in WR compared to cultivated rice in metabolome analysis. Transcriptome analyses indicated that 18 responsive genes played pivotal roles in the conversion of key metabolites. These findings will provide theoretical underpinnings for the development of rice germplasm resources and the formulation of functional germinated grain foods.

Predicting rice phenology across China by integrating crop phenology model and machine learning.

This study explores the integration of crop phenology models and machine learning (ML) approaches for predicting rice phenology across China, to gain a deeper understanding of rice phenology prediction. Multiple approaches were used to predict heading and maturity dates at 337 locations across the main rice growing regions of China from 1981 to 2020, including crop phenology model, machine learning and hybrid model that integrate both approaches. Furthermore, an interpretable machine learning (IML) using SHapley Additive exPlanation (SHAP) was employed to elucidate influence of climatic and varietal factors on uncertainty in crop phenology model predictions. Overall, the hybrid model demonstrated a high accuracy in predicting rice phenology, followed by machine learning and crop phenology models. The best hybrid model, based on a serial structure and the eXtreme Gradient Boosting (XGBoost) algorithm, achieved a root mean square error (RMSE) of 4.65 and 5.72 days and coefficient of determination (R2) values of 0.93 and 0.9 for heading and maturity predictions, respectively. SHAP analysis revealed temperature to be the most influential climate variable affecting phenology predictions, particularly under extreme temperature conditions, while rainfall and solar radiation were found to be less influential. The analysis also highlighted the variable importance of climate across different phenological stages, rice cultivation patterns, and geographic regions, underscoring the notable regionality. The study proposed that a hybrid model using an IML approach would not only improve the accuracy of prediction but also offer a robust framework for leveraging data-driven in crop modeling, providing a valuable tool for refining and advancing the modeling process in rice.

A bridge dynamic response analysis and load recognition method using traffic imaging.

As the primary variable load of bridges, vehicle load is an important parameter for bridge health monitoring. However, traditional Weigh-in-Motion (WIM) systems and the commonly used method of placing sensors on the bridge are challenging to apply in load monitoring for many small and medium-sized bridges. Therefore, this paper proposes a bridge vehicle load identification method based on traffic surveillance video data. Leveraging the surveillance video data on the bridge, without introducing additional hardware devices, the displacement of target points is detected through sub-pixel level image detection algorithms, enabling non-contact measurement of bridge structural response through imaging. A spatiotemporal relationship model of structural displacement, vehicle load, and load distribution is established to solve for vehicle load. Finally, model bridge tests under various loading conditions and engineering practice experiments are conducted to validate the feasibility of the method. The results of the model bridge tests show that the structural displacement measured using traffic video measurement has a deviation of less than 10% compared to the measurements obtained using contact displacement sensors (LVDT), and it can accurately reflect the displacement characteristics of the structure. The results of the field tests demonstrate that the average estimation deviation for heavy vehicle loads ranging from 12 to 18 tons is approximately 18%, meeting the engineering requirements. The proposed method can provide load statistical information for the extensive health monitoring of small and medium-sized bridges and offer a new technical pathway for obtaining bridge load information.

The impact of anxiety on the risk of kidney stone disease: Insights into eGFR-mediated effects.

BACKGROUND: Previous studies have linked kidney stone disease (KSD) with depression, but there are no reports on the relationship between anxiety and KSD, and the mechanism underlying the potential relationship remains unclear. METHODS: Associations of anxiety and incident KSD were assessed in the National Health and Nutrition Examination Survey (NHENES) using multivariate logistic regression. Two-sample bidirectional Mendelian randomization studies and a two-step two-sample MR was used to estimate the mediating factors that influence KSD risk. RESULTS: Examinations of NHANES data revealed that a rise in the frequency and intensity of anxiety were independently associated with incident KSD. In MR analysis, anxiety (uk-a-51 and uk-b-6519) were from the UK Biobank, with sample sizes of 328,717 and 450,765 respectively. KSD data were from the FinnGen, including 8597 cases and 333,128 controls. In the IVW analysis, genetically predicted anxieties (ukb-a-51 and ukb-b-6519) were found to be causally associated with a higher risk of KSD, with odds ratios of 6.18 (95 % CI 2.54-15.04) and 3.44 (95 % CI 1.67-7.08), respectively. There were no reverse causal effects. Further mediation analysis indicated that anxiety increases the risk of KSD by raising eGFR, through which 11.8 % of the effect of anxiety on KSD risk was mediated. LIMITATIONS: The research was confined to individuals of European heritage, and there could be specific genetic variances among diverse ethnicities. CONCLUSION: The current study suggests anxiety as an independent causal risk factor for KSD and unveils a new pathogenic mechanism, showing that anxiety raises eGFR, thereby increasing the risk of KSD.

Exploring the pathogen diagnosis and prognostic factors of severe COVID-19 using metagenomic next-generation sequencing: A retrospective study.

Background: This study aimed to identify pathogens and factors that predict the outcome of severe COVID-19 by utilizing metagenomic next-generation sequencing (mNGS) technology. Methods: We retrospectively analyzed data from 56 severe COVID-19 patients admitted to our hospital between December 2022 and March 2023. We analyzed the pathogen types and strains detected through mNGS and conventional microbiological testing and collected general patient information. Results: In this study, 42 pathogens were detected using mNGS and conventional microbiological testing. mNGS had a significantly higher detection rate of 90.48% compared to 71.43% for conventional testing (P=0.026). A total of 196 strains were detected using both methods, with a significantly higher detection rate of 70.92% for mNGS compared to 49.49% for conventional testing (P=0.000). The 56 patients were divided into a survival group (33 cases) and a death group (23 cases) based on clinical outcomes. The survival group had significantly lower age, number of pathogens detected by mNGS, number of pathogens detected by conventional testing, APACHE-II score, SOFA score, high-sensitivity troponin, creatine kinase-MB subtype, and lactate dehydrogenase compared to the death group (P<0.05). Multivariate logistic regression analysis showed that these factors were risk factors for mortality in severe COVID-19 patients (P<0.05). In contrast, ROC curve analysis revealed that these factors had diagnostic values for mortality, with AUC values ranging from 0.657 to 0.963. The combined diagnosis of these indicators had an AUC of 0.924. Conclusions: The use of mNGS technology can significantly enhance the detection of pathogens in severe cases of COVID-19 and also has a solid ability to predict clinical outcomes.

A prognostic model constructed by ferroptosis-associated genes (FAGs) in papillary renal cell carcinoma (PRCC) and its association with tumor mutation burden (TMB) and immune infiltration.

BACKGROUND: This study aimed to identify the prognostic-related differentially expressed ferroptosis-associated genes (DEFAGs) in papillary renal cell carcinoma (PRCC). METHODS: Data encompassing simple nucleotide variation, transcriptome profiles, and relevant clinical information of PRCC patients were sourced from The Cancer Genome Atlas (TCGA) database. The expression matrix of ferroptosis-associated genes (FAGs) was analyzed using the "limma" package in R to identify differentially expressed DEFAGs. Lasso regression analysis, along with univariate and multivariate Cox proportional hazards regressions, was employed to identify independent prognostic-related DEFAGs and formulate a nomogram. Additionally, we examined potential independent survival-related clinical risk factors and compared immune cell infiltration and tumor mutation burden (TMB) differences between high- and low-risk patient groups. RESULTS: A cohort of 321 patients were analyzed, revealing twelve FAGs significantly influencing the overall survival (OS) of PRCC patients. Among them, two mRNAs (GCLC, HSBP1) emerged as independent prognostic-related DEFAGs. Smoking status, tumor stage, and risk score were identified as independent clinical risk factors for PRCC. Furthermore, notable disparities in immune cell infiltration and function were observed between high- and low-risk groups. GCLC and HSBP1 were associated with various immune cells and functions, TMB, and immune evasion. CONCLUSION: This finding revealed two independent prognostic-related DEFAGs in PRCC and established a robust prognostic model, offering potential therapeutic targets and promising insights for the management of this disease.

Anti-CTLA-4 m2a Antibody Exacerbates Cardiac Injury in Experimental Autoimmune Myocarditis Mice By Promoting Ccl5-Neutrophil Infiltration.

The risk for suffering immune checkpoint inhibitors (ICIs)-associated myocarditis increases in patients with pre-existing conditions and the mechanisms remain to be clarified. Spatial transcriptomics, single-cell RNA sequencing, and flow cytometry are used to decipher how anti-cytotoxic T lymphocyte antigen-4 m2a antibody (anti-CTLA-4 m2a antibody) aggravated cardiac injury in experimental autoimmune myocarditis (EAM) mice. It is found that anti-CTLA-4 m2a antibody increases cardiac fibroblast-derived C-X-C motif chemokine ligand 1 (Cxcl1), which promots neutrophil infiltration to the myocarditic zones (MZs) of EAM mice via enhanced Cxcl1-Cxcr2 chemotaxis. It is identified that the C-C motif chemokine ligand 5 (Ccl5)-neutrophil subpopulation is responsible for high activity of cytokine production, adaptive immune response, NF-κB signaling, and cellular response to interferon-gamma and that the Ccl5-neutrophil subpopulation and its-associated proinflammatory cytokines/chemokines promoted macrophage (Mφ) polarization to M1 Mφ. These altered infiltrating landscape and phenotypic switch of immune cells, and proinflammatory factors synergistically aggravated anti-CTLA-4 m2a antibody-induced cardiac injury in EAM mice. Neutralizing neutrophils, Cxcl1, and applying Cxcr2 antagonist dramatically alleviates anti-CTLA-4 m2a antibody-induced leukocyte infiltration, cardiac fibrosis, and dysfunction. It is suggested that Ccl5-neutrophil subpopulation plays a critical role in aggravating anti-CTLA-4 m2a antibody-induced cardiac injury in EAM mice. This data may provide a strategic rational for preventing/curing ICIs-associated myocarditis.

Expression of ITPR2 regulated by lncRNA-NONMMUT020270.2 in LPS-stimulated HT22 cells.

Background: Long non-coding RNA (lncRNA)-NONMMUT020270.2 is downregulated and co-expressed with inositol 1,4,5-trisphosphate receptor type 2 (ITPR2) in the hippocampus of Alzheimer's disease (AD) mice. However, whether the expression of ITPR2 was regulated by lncRNA-NONMMUT020270.2 remains unclear. we aimed to investigate regulating relationship of lncRNA-NONMMUT020270.2 and ITPR2. Methods: HT22 cells were firstly transfected with the pcDNA3.1-lncRNA-NONMMUT020270.2 overexpression plasmid or with the lncRNA-NONMMUT020270.2 smart silencer, and then were stimulated with lipopolysaccharide (LPS) for 24h. The mRNA expression levels of lncRNA-NONMMUT020270.2 and ITPR2 were measured by reverse transcription-quantitative PCR. Cell viability was assessed using a Cell Counting Kit 8 assay. The expression of Aß1-42 was detected by ELISA. The expression levels of p-tau, caspase-1, and inositol trisphosphate receptor (IP3R) proteins were detected by western-blotting. Nuclear morphological changes were detected by Hoechst staining. Flow cytometry and Fluo-3/AM were carried out to determine cell apoptosis and the intracellular Ca2+. Results: LPS significantly decreased cell viability, and ITPR2 mRNA and IP3R protein expression levels. While it markedly enhanced the expression levels of p-tau and Aß1-42, cell apoptosis rate, as well as intracellular Ca2+ concentration (P < 0.05). In addition, lncRNA-NONMMUT020270.2 overexpression significantly increased the expressions levels of ITPR2 mRNA and IP3R protein (P < 0.05), and inhibited expression of p-tau and Aß1-42, cell apoptosis rate, and reduced intracellular Ca2+ concentration (P < 0.05). By contrast, lncRNA-NONMMUT020270.2 silencing notably downregulated expressions levels of ITPR2 mRNA and IP3R protein (P < 0.05), and elevated expression levels of p-tau and Aß1-42, cell apoptosis rate, and intracellular Ca2+ concentration (P < 0.05). Conclusion: lncRNA-NONMMUT020270.2 was positively correlated with ITPR2 expression in LPS-induced cell. Downregulating the lncRNA-NONMMUT020270.2 and ITPR2 may promote cell apoptosis and increase intracellular Ca2+ concentration.

Fast-track surgery with three-port versus conventional perioperative management of bladder cancer associated laparoscopic radical cystectomy and Ileal conduit diversion: Chinese experience.

OBJECTIVE: This study seeks to explore the impact of fast track surgery (FTS) with three-port in patients treated with laparoscopic radical cystectomy and ileal conduit on postoperative recovery, hospital stay and the complications. METHODS: This retrospective study analyzed 230 patients with invasive bladder cancer who underwent laparoscopic radical cystectomy at the Second Hospital of Anhui Medical University between December 2011 to January 2023. 50 patients received conventional surgery (CS) and 180 patients received FTS with three-port. Patients were assessed for time to normal diet consumption, time to passing first flatus, number of postoperative recovery days and complications. Trends of serum C-reactive protein levels were monitored preoperatively and on postoperative days 1, 3 and 7. RESULTS: Patients who underwent FTS with three-port had a shorter duration to first flatus (P < 0.05). And number of postoperative hospital days and the length of hospital stay were notably shorter in contrast to the CS group (P < 0.05). Serum CRP levels on postoperative day 7 were markedly reduced in those of the FTS group compared to the CS group (P < 0.05). Those of the CS group experienced more frequent rates of complications compared to those of the FTS with three-port group (P < 0.05). CONCLUSION: Our findings demonstrate that the FTS with three-port program hastens postoperative recovery and reduces duration of hospital stay. It is safer and more effective than the CS program in the Chinese population undergoing laparoscopic radical cystectomy.

Animal healer for refractory diseases: Myth or reality?

A vast amount of knowledge has been acquired through human activities such as farming, hunting, and fishing. Throughout history, humans have utilized living creatures for disease treatment, relying on the natural world's healing powers. The special "healers" may be able to treat patients via the power of nature. However, there was no systematic introduction or summary of these treatments. Therefore, we conducted a literature review based on PubMed, Google Scholar, Web of Science, Scopus, CNKI and WanFang DATA. Here, we defined this unique method as "animal healer" and six common kinds of animal healers were reviewed. These are fish therapy, pet therapy, worm therapy, leech therapy, maggot therapy, and bee therapy. According to the different characteristics of healers, treatment methods mainly included bite, parasitism, contact and communication. With the advantages of green and effectiveness, animal healers have great therapy potential against a variety of refractory diseases. The main purpose of this review is to draw people's attention to animal healer, promote it to become a possible clinical treatment strategy, and make further exploration in species cultivation, mechanism research, animal welfare, standard setting, safety evaluation and other aspects. In the future, animal healers will play an increasingly important role in medicine and hopefully solve more medical problems and dilemmas.

Chromosome-level genome assembly and sex chromosome identification of the pink stem borer, Sesamia inferens (Lepidoptera: Noctuidae).

The pink stem borer, Sesamia inferens Walker (Lepidoptera: Noctuidae), is one of the most notorious pest insects of rice and maize crops in the world. Here, we generated a high-quality chromosome-level genome assembly of S. inferens, using a combination of Illumina, PacBio HiFi and Hi-C technologies. The total assembly size was 973.18 Mb with a contig N50 of 33.39 Mb, anchored to 31 chromosomes, revealing a karyotype of 30 + Z. The BUSCO analysis indicated a high completeness of 98.90% (n = 5286), including 5172 (97.8%) single-copy BUSCOs and 58 (1.1%) duplicated BUSCOs. The genome contains 58.59% (564.58 Mb) repeat elements and 26628 predicted protein-coding genes. The chromosome-level genome assembly of S. inferens provides in-depth knowledge and will be a helpful resource for the Lepidoptera and pest control research communities.

Understanding the role of atmospheric deposition on the environmental load of per- and polyfluoroalkyl substances: A case study in Three Gorges Reservoir, China.

Sixty-nine total suspended particle (TSP) samples, paired with forty-eight surface soil samples, covering four seasons from January 2021 to November 2021, were collected from the Three Gorges Reservoir Region (TGRR). Twenty per- and poly-fluoroalkyl substances (PFASs) were analyzed to evaluate their contamination characteristics and understand the role of atmospheric deposition on the environmental loads in TGRR. The annual average concentrations of PFASs in TSP and soil were 37.2 ± 1.22 pg·m-3 and 0.798 ± 0.134 ng·g-1, respectively. For TSP, concentrations were highest in spring and lowest in summer. For soil, it was in autumn and winter, respectively. The seasonality was more influenced by anthropogenic activities than by meteorological conditions or physicochemical parameters of the soil. Positive matrix fractionation (PMF) indicated that, based on annual averages, PFOA-based products (40.2 %) were the major sources of PFASs in TSP, followed by PFOS-based products (25.2 %) and precursor degradation (34.6 %). The highest source contributor for PFASs in spring was precursor degradation (40.9 %), while in other three seasons, it was PFOA-based products (39.9 %, 40.9 % and 52.0 %, respectively). The mean atmospheric dry and wet deposition fluxes of PFASs were estimated at 4.38 ng·m-2·day-1 and 23.5 ng·m-2·day-1, respectively. The contribution of atmospheric deposition to the inventory mass of PFASs in the surface soil was 22.3 %. These findings fill a gap in knowledge regarding the processes and mechanisms of the occurrence, sources and atmospheric deposition of PFASs in the TGRR.

RAC1 inhibition ameliorates IBSP-induced bone metastasis in lung adenocarcinoma.

Macrophage-to-osteoclast differentiation (osteoclastogenesis) plays an essential role in tumor osteolytic bone metastasis (BM), while its specific mechanisms remain largely uncertain in lung adenocarcinoma BM. In this study, we demonstrate that integrin-binding sialoprotein (IBSP), which is highly expressed in the cancer cells from bone metastatic and primary lesions of patients with lung adenocarcinoma, can facilitate BM and directly promote macrophage-to-osteoclast differentiation independent of RANKL/M-CSF. In vivo results further suggest that osteolytic BM in lung cancer specifically relies on IBSP-induced macrophage-to-osteoclast differentiation. Mechanistically, IBSP regulates the Rac family small GTPase 1 (Rac1)-NFAT signaling pathway and mediates the forward shift of macrophage-to-osteoclast differentiation, thereby leading to early osteolysis. Moreover, inhibition of Rac1 by EHT-1864 or azathioprine in mice models can remarkably alleviate IBSP-induced BM of lung cancer. Overall, our study suggests that tumor-secreted IBSP promotes BM by inducing macrophage-to-osteoclast differentiation, with potential as an early diagnostic maker for BM, and Rac1 can be the therapeutic target for IBSP-promoted BM in lung cancer.

The Effects of Hydroxypropyl Methyl Cellulose and Metakaolin on the Properties of Self-Compacting Solidified Soil Based on Abandoned Slurry.

As a new type of backfill material, Self-compacting solidified soil (SCSS) takes the abandoned slurry of cast-in-place piles after dewatering and reduction as the main raw material, which brings a problem of coordinating the working performance with the mechanical property under the condition of high mobility. In this paper, hydroxypropyl methyl cellulose (HPMC) and metakaolin were introduced as additives to solve this problem. First, the workability and mechanical properties of SCSS were regulated and optimized by means of the water seepage rate test, the flowability test, and the unconfined compressive strength test. Second, this study also used X-ray diffraction (XRD) and scanning electron microscopy (SEM) to investigate the effects of HPMC and metakaolin on the physical phase and microstructure of SCSS. In this way, the results showed that there was a significant impact on the flowability of SCSS, that is, when the dosage reached 0.3%, the water seepage rate of SCSS was reduced to less than 1%, and the compressive strength at 7 days reached its peak. At the same time, HPMC weakened the strength growth of SCSS in the age period of 7 days to 14 days. However, the addition of metakaolin promoted its compressive strength. XRD analysis showed that the additives had no significant effects on the physical phases. And, from the SEM results, it can be seen that although the water-retaining effect of HPMC makes hydration of cement more exhaustive, more ettringite (AFt) can be observed in the microstructure. In addition, it can be observed that the addition of metakaolin can generate more hydrated calcium silicate (C-S-H) due to the strong surface energy possessed by metakaolin. As a result of the above factors, SCSS filled the voids between particles and improved the interface structure between particles, thus enhanced the compressive strength.

Effects of different observed datasets on the calibration of crop model parameters with GLUE: A case study using the CROPGRO-Soybean phenological model.

Suitable combinations of observed datasets for estimating crop model parameters can reduce the computational cost while ensuring accuracy. This study aims to explore the quantitative influence of different combinations of the observed phenological stages on estimation of cultivar-specific parameters (CPSs). We used the CROPGRO-Soybean phenological model (CSPM) as a case study in combination with the Generalized Likelihood Uncertainty Estimation (GLUE) method. Different combinations of four observed phenological stages, including initial flowering, initial pod, initial grain, and initial maturity stages for five soybean cultivars from Exp. 1 and Exp. 3 described in Table 2 are respectively used to calibrate the CSPs. The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in Table 2. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R2), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. The evaluation results suggest that RMSE and MAE decrease, and R2 and NSE increase with the increase in the number of observed phenological stages used for parameter calibration. However, there is no significant reduction in the RMSEs (MAEs, NSEs) using two, three, and four observed stages. Relatively reliable optimized CSPs for CSMP are obtained by using at least two observed phenological stages balancing calibration effect and computational cost. These findings provide new insight into parameter estimation of crop models.

Current development of severe acute respiratory syndrome coronavirus 2 neutralizing antibodies (Review).

The coronavirus disease 2019 pandemic due to severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) seriously affected global public health security. Studies on vaccines, neutralizing antibodies (NAbs) and small molecule antiviral drugs are currently ongoing. In particular, NAbs have emerged as promising therapeutic agents due to their well­defined mechanism, high specificity, superior safety profile, ease of large­scale production and simultaneous application for both prevention and treatment of viral infection. Numerous NAb therapeutics have entered the clinical research stages, demonstrating promising therapeutic and preventive effects. These agents have been used for outbreak prevention and control under urgent authorization processes. The present review summarizes the molecular targets of SARS­CoV­2­associated NAbs and screening and identification techniques for NAb development. Moreover, the current shortcomings and challenges that persist with the use of NAbs are discussed. The aim of the present review is to offer a reference for the development of NAbs for any future emergent infectious diseases, including SARS­CoV­2.

Associations of blood pressure in the third trimester and risk of venous thromboembolism postpartum.

Studies on the associations of blood pressure (BP) and the risk of venous thromboembolism (VTE) had been performed neither among pregnant women nor in Chinese population. This study included participants of pregnant women from a retrospective multicenter cohort, between May 2020 and April 2023. Systolic BP (SBP) and diastolic BP (DBP) of the participants were measured in the third trimester. The incidences of VTE (including deep venous thrombosis and/or pulmonary embolism) at 42 days postpartum were followed. With regards to SBP, pregnant women in the Q1 (≤114 mmHg), Q2 (115-122 mmHg), and Q4 group (≥131 mmHg) had increased risk of VTE than those in Q3 group (123-130 mmHg), with ORs 4.48 [1.69, 11.85], 3.52 [1.30, 9.59], and 3.17 [1.12, 8.99], respectively. Compared with pregnant women with the Q4 of DBP (≥85 mmHg), women of Q1 (≤71 mmHg) were found to have elevated risk of VTE (OR 2.73 [1.25, 5.96]). A one standard deviation decrease of DBP (9 mmHg) was related with 37% elevated risk of VTE (OR 1.37 [1.05, 1.79]). This study demonstrated a U-shaped association of SBP in the third trimester and VTE postpartum and inverse association of DBP in the third trimester and VTE postpartum.

Recent Advances in Ferroelectret Fabrication, Performance Optimization, and Applications.

The growing demand for wearable devices has sparked a significant interest in ferroelectret films. They possess flexibility and exceptional piezoelectric properties due to strong macroscopic dipoles formed by charges trapped at the interface of their internal cavities. This review of ferroelectrets focuses on the latest progress in fabrication techniques for high temperature resistant ferroelectrets with regular and engineered cavities, strategies for optimizing their piezoelectric performance, and novel applications. The charging mechanisms of bipolar and unipolar ferroelectrets with closed and open-cavity structures are explained first. Next, the preparation and piezoelectric behavior of ferroelectret films with closed, open, and regular cavity structures using various materials are discussed. Three widely used models for predicting the piezoelectric coefficients (d33) are outlined. Methods for enhancing the piezoelectric performance such as optimized cavity design, utilization of fabric electrodes, injection of additional ions, application of DC bias voltage, and synergy of foam structure and ferroelectric effect are illustrated. A variety of applications of ferroelectret films in acoustic devices, wearable monitors, pressure sensors, and energy harvesters are presented. Finally, the future development trends of ferroelectrets toward fabrication and performance optimization are summarized along with its potential for integration with intelligent systems and large-scale preparation.

Acute toxicity of binary mixtures for quorum sensing inhibitors and sulfonamides against Aliivibrio fischeri: QSAR investigations and joint toxic actions.

Quorum sensing inhibitors (QSIs), as a kind of ideal antibiotic substitutes, have been recommended to be used in combination with traditional antibiotics in medical and aquaculture fields. Due to the co-existence of QSIs and antibiotics in environmental media, it is necessary to evaluate their joint risk. However, there is little information about the acute toxicity of mixtures for QSIs and antibiotics. In this study, 10 QSIs and 3 sulfonamides (SAs, as the representatives for traditional antibiotics) were selected as the test chemicals, and their acute toxic effects were determined using the bioluminescence of Aliivibrio fischeri (A. fischeri) as the endpoint. The results indicated that SAs and QSIs all induced S-shaped dose-responses in A. fischeri bioluminescence. Furthermore, SAs possessed greater acute toxicity than QSIs, and luciferase (Luc) might be the target protein of test chemicals. Based on the median effective concentration (EC50) for each test chemical, QSI-SA mixtures were designed according to equitoxic (EC50(QSI):EC50(SA) = 1:1) and non-equitoxic ratios (EC50(QSI):EC50(SA) = 1:10, 1:5, 1:0.2, and 1:0.1). It could be observed that with the increase of QSI proportion, the acute toxicity of QSI-SA mixtures enhanced while the corresponding TU values decreased. Furthermore, QSIs contributed more to the acute toxicity of test binary mixtures. The joint toxic actions of QSIs and SAs were synergism for 23 mixtures, antagonism for 12 mixtures, and addition for 1 mixture. Quantitative structure-activity relationship (QSAR) models for the acute toxicity QSIs, SAs, and their binary mixtures were then constructed based on the lowest CDOCKER interaction energy (Ebind-Luc) between Luc and each chemical and the component proportion in the mixture. These models exhibited good robustness and predictive ability in evaluating the toxicity data and joint toxic actions of QSIs and SAs. This study provides reference data and applicable QSAR models for the environmental risk assessment of QSIs, and gives a new perspective for exploring the joint effects of QSI-antibiotic mixtures.

Quantum computing for several AGV scheduling models.

Due to the high degree of automation, automated guided vehicles (AGVs) have been widely used in many scenarios for transportation, and traditional computing power is stretched in large-scale AGV scheduling. In recent years, quantum computing has shown incomparable performance advantages in solving specific problems, especially Combinatorial optimization problem. In this paper, quantum computing technology is introduced into the study of the AGV scheduling problem. Additionally two types of quadratic unconstrained binary optimisation (QUBO) models suitable for different scheduling objectives are constructed, and the scheduling scheme is coded into the ground state of Hamiltonian operator, and the problem is solved by using optical coherent Ising machine (CIM). The experimental results show that compared with the traditional calculation method, the optical quantum computer can save 92% computation time on average. It has great application potential.