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Abstract Background Sodium-glucose cotransporter 2 (SGLT2) inhibition is recognized for its evident renoprotective benefits in diabetic renal disease. Recent data suggest that SGLT2 inhibition also slows down kidney disease progression and reduces the risk of acute kidney injury, regardless of whether the patient has diabetes or not, but the mechanism behind these observed effects remains elusive. The objective of this study is to utilize a mendelian randomization (MR) methodology to comprehensively examine the influence of metabolites in circulation regarding the impact of SGLT2 inhibition on kidney function. Methods We used a MR study to obtain associations between genetic proxies for SGLT2 inhibition and kidney function. We retrieved the most recent and comprehensive summary statistics from genome-wide association studies (GWAS) that have been previously published and involved kidney function parameters such as estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (UACR), and albuminuria. Additionally, we included blood metabolite data from 249 biomarkers in the UK Biobank for a more comprehensive analysis. We performed MR analyses to explore the causal relationships between SGLT2 inhibition and kidney function and two-step MR to discover potential mediating metabolites. Results The study found that a decrease in HbA1c levels by one standard deviation, which is genetically expected to result in SGLT2 inhibition, was linked to a decreased likelihood of developing type 2 diabetes mellitus (T2DM) (odds ratio [OR] = 0.55 [95% CI 0.35, 0.85], P = 0.007). Meanwhile, SGLT2 inhibition also protects eGFR (β = 0.05 [95% CI 0.03, 0.08], P = 2.45 × 10− 5) and decreased UACR (-0.18 [95% CI -0.33, -0.02], P = 0.025) and albuminuria (-1.07 [95% CI -1.58, -0.57], P = 3.60 × 10− 5). Furthermore, the study found that of the 249 metabolites present in the blood, only one metabolite, specifically the concentration of small high-density lipoprotein (HDL) particles, was significantly correlated with both SGLT2 inhibition and kidney function. This metabolite was found to play a crucial role in mediating the improvement of renal function through the use of SGLT2 inhibition (β = 0.01 [95% CI 0.005, 0.018], P = 0.001), with a mediated proportion of 13.33% (95% CI [5.71%, 26.67%], P = 0.020). Conclusions The findings of this investigation provide evidence in favor of a genetically anticipated biological linkage between the inhibition of SGLT2, the presence of circulating metabolites, and renal function. The findings demonstrate that the protective effect of SGLT2 inhibition on renal function is mostly mediated by HDL particle concentrations in circulating metabolites. These results offer significant theoretical support for both the preservation of renal function and a better comprehension of the mechanisms underlying SGLT2 inhibition.

Background The objective of this study was to develop and validate a machine learning (ML) model for predict in-hospital mortality among critically ill patients with congestive heart failure (CHF) combined with chronic kidney disease (CKD).Methods After employing least absolute shrinkage and selection operator regression for feature selection, six distinct methodologies were employed in the construction of the model. The selection of the optimal model was based on the area under the curve (AUC). Furthermore, the interpretation of the chosen model was facilitated through the utilization of SHapley Additive exPlanation (SHAP) values and the Local Interpretable Model-Agnostic Explanations (LIME) algorithm.Results This study collected data and enrolled 5041 patients on CHF combined with CKD from 2008 to 2019, utilizing the Medical Information Mart for Intensive Care Unit. After selection, 22 of the 47 variables collected post-intensive care unit admission were identified as mortality-associated and subsequently utilized in the development of ML models. Among the six models generated, the eXtreme Gradient Boosting (XGBoost) model demonstrated the highest AUC at 0.837. Notably, the SHAP values highlighted the sequential organ failure assessment score, age, simplified acute physiology score II, and urine output as the four most influential variables in the XGBoost model. In addition, the LIME algorithm explains the individualized predictions.Conclusions In conclusion, our study accomplished the successful development and validation of ML models for predicting in-hospital mortality in critically ill patients with CHF combined with CKD. Notably, the XGBoost model emerged as the most efficacious among all the ML models employed.

Tert-butylhydroquinone (TBHQ) is a phenolic substance that is commonly employed to prevent food oxidation. Excessive or improper utilization of this antioxidant can not only impact food quality but may also pose potential risks to human health. In this study, an ultrasensitive, stable, and easily operable ratiometric electrochemical sensor was successfully fabricated by combining the tubular (3,4-ethylenedioxythiophene) (T-PEDOT) with single-wall carbon nanohorns (SWCNHs) for the detection of TBHQ antioxidants in food. The SWCNHs/T-PEDOT nanocomposite fabricated through ultrasound-assisted and template approaches was employed as the modified substrate for the electrode interface. The synergistic effect of SWCNHs and T-PEDOT, which possess excellent electrical conductivity and catalytic properties, enabled the modified electrode to showcase remarkable electrocatalytic performance towards TBHQ, with the redox signal of methylene blue serving as an internal reference. Under optimized conditions, the SWCNHs/T-PEDOT-modified electrode demonstrated good linearity within the TBHQ concentration range of 0.01–200.0 μg mL−1, featuring a low limit of detection (LOD) of 0.005 μg mL−1. The proposed ratiometric electrochemical sensor displayed favorable reproducibility, stability, and anti-interference capacity, thereby offering a promising strategy for monitoring the levels of TBHQ in oil-rich food products.

Nitrogen (N) is an essential macronutrient for plant growth and productivity. Leguminous plants establish symbiotic relationships with nitrogen-fixing rhizobial bacteria to use atmospheric dinitrogen gas to meet high N demand under low-N conditions. Nodule formation and N fixation are energy-consuming processes and are inhibited by nitrate present in the environment. Previous studies in model leguminous plants characterized NIN-LIKE PROTEIN (NLP) proteins that mediate nitrate control of root nodule symbiosis, but the mechanism by which nitrate regulates soybean root nodules via NLP remains unclear. In the soybean genome we found four homologs of AtNLP7, named GmNLP7a–GmNLP7d. We showed that the expression of GmNLP7s is responsive to nitrate but not to rhizobial infection and localized GmNLP7a to the nucleus. Downregulation of GmNLP7s increased nodule number, and overexpression of GmNLP7a (GmNLP7aOE) reduced nodule number regardless of nitrate availability, suggesting a negative role for GmNLP7s in nodulation. Nitrogenase activity in the GmNLP7aOE line was comparable to that of the wild type, indicating that GmNLP7a does not affect mature nodule activity. Overexpression of GmNLP7a downregulated the expression of GmNIN1a and GmENOD40-1. GmNLP7a interacted with GmNIN1a via the PB1 domain. Our results reveal a new regulator of GmNLP7 in nodulation and a molecular mechanism by which nitrate affects nodule number in soybean.

Introduction: Observational studies have shown that obesity is a risk factor for various autoimmune diseases. However, the causal relationship between obesity and autoimmune diseases is unclear. Mendelian randomization (MR) was used to investigate the causal effects of obesity on 15 autoimmune diseases. Methods: MR analysis employed instrumental variables, specifically single-nucleotide polymorphisms associated with obesity measures such as body mass index (BMI), waist circumference, hip circumference, and waist-to-hip ratio. The study utilized UK Biobank and FinnGen data to estimate the causal relationship between obesity and autoimmune diseases. Results: Genetically predicted BMI was associated with risk for five autoimmune diseases. The odds ratio per 1-SD increase in genetically predicted BMI, the OR was 1.28 (95% CI, 1.18–1.09; p < 0.001) for asthma, 1.37 (95% CI, 1.24–1.51; p < 0.001) for hypothyroidism, 1.52 (95% CI, 1.27–1.83; p < 0.001) for psoriasis, 1.22 (95% CI, 1.06–1.40; p = 0.005) for rheumatoid arthritis, and 1.55 (95% CI, 1.32–1.83; p < 0.001) for type 1 diabetes. However, after adjusting for genetic susceptibility to drinking and smoking, the correlation between BMI and rheumatoid arthritis was not statistically significant. Genetically predicted waist circumference, hip circumference, and waist and hip circumference were associated with 6, 6, and 1 autoimmune disease, respectively. Conclusion: This study suggests that obesity may be associated with an increased risk of several autoimmune diseases, such as asthma, hypothyroidism, psoriasis, rheumatoid arthritis, and type 1 diabetes.

When using transformer insulation oil as a liquid dielectric, the oil is easily polluted by the solid particles generated in the operation of the transformer, and these metallic impurity particles have a significant impact on the insulation performance inside the power transformer. The force of the metal particles suspended in the flow insulation oil is multidimensional, which will lead to a change in the movement characteristics of the metal particles. Based on this, this study explored the motion rules of suspended metallic impurity particles in mobile insulating oil in different electric field environments and the influencing factors. A multiphysical field model of the solid–liquid two-phase flow of single-particle metallic impurity particles in mobile insulating oil was constructed using the dynamic analysis method, and the particles’ motion characteristics in the oil in different electric field environments were simulated. The motion characteristics of metallic impurity particles under conditions of different particle sizes, oil flow velocities, and insulation oil qualities and influencing factors were analyzed to provide theoretical support for the detection of impurity particles in transformer insulation oil and enable accurate estimations of the location of equipment faults. Our results show that there are obvious differences in the trajectory of metallic impurity particles under different electric field distributions. The particles will move towards the region of high field intensity under an electric field, and the metallic impurity particles will not collide with the electrode under an AC field. When the electric field intensity and particle size increase, the trajectory of the metallic impurity particles between electrodes becomes denser, and the number of collisions between particles and electrodes and the motion speed both increase. Under the condition of a higher oil flow velocity, the number of collisions between metal particles and electrodes is reduced, which reduces the possibility of particle agglomeration. When the temperature of the insulation oil changes and the quality deteriorates, its dynamic viscosity changes. With a decrease in the dynamic viscosity of the insulation oil, the movement of the metallic impurity particles between the electrodes becomes denser, the collision times between the particles and electrodes increase, and the maximum motion speed of the particles increases.

In this study, a pH-responsive polycaprolactone (PCL)–copper peroxide (CuO2) composite antibacterial coating was developed by suspension flame spraying. The successful synthesis of CuO2 nanoparticles and fabrication of the PCL-CuO2 composite coatings were confirmed by microstructural and chemical analysis. The composite coatings were structurally homogeneous, with the chemical properties of PCL well maintained. The acidic environment was found to effectively accelerate the dissociation of CuO2, allowing the simultaneous release of Cu2+ and H2O2. Antimicrobial tests clearly revealed the enhanced antibacterial properties of the PCL-CuO2 composite coating against both Escherichia coli and Staphylococcus aureus under acidic conditions, with a bactericidal effect of over 99.99%. This study presents a promising approach for constructing pH-responsive antimicrobial coatings for biomedical applications.

AbstractBackground This study aimed to establish and validate a machine learning (ML) model for predicting in-hospital mortality in critically ill patients with chronic kidney disease (CKD).Methods This study collected data on CKD patients from 2008 to 2019 using the Medical Information Mart for Intensive Care IV. Six ML approaches were used to build the model. Accuracy and area under the curve (AUC) were used to choose the best model. In addition, the best model was interpreted using SHapley Additive exPlanations (SHAP) values.Results There were 8527 CKD patients eligible for participation; the median age was 75.1 (interquartile range: 65.0–83.5) years, and 61.7% (5259/8527) were male. We developed six ML models with clinical variables as input factors. Among the six models developed, the eXtreme Gradient Boosting (XGBoost) model had the highest AUC, at 0.860. According to the SHAP values, the sequential organ failure assessment score, urine output, respiratory rate, and simplified acute physiology score II were the four most influential variables in the XGBoost model.Conclusions In conclusion, we successfully developed and validated ML models for predicting mortality in critically ill patients with CKD. Among all ML models, the XGBoost model is the most effective ML model that can help clinicians accurately manage and implement early interventions, which may reduce mortality in critically ill CKD patients with a high risk of death.

Abstract This study aimed to establish and validate a machine learning (ML) model for predicting in-hospital mortality in patients with sepsis-associated acute kidney injury (SA-AKI). This study collected data on SA-AKI patients from 2008 to 2019 using the Medical Information Mart for Intensive Care IV. After employing Lasso regression for feature selection, six ML approaches were used to build the model. The optimal model was chosen based on precision and area under curve (AUC). In addition, the best model was interpreted using SHapley Additive exPlanations (SHAP) values and Local Interpretable Model-Agnostic Explanations (LIME) algorithms. There were 8129 sepsis patients eligible for participation; the median age was 68.7 (interquartile range: 57.2–79.6) years, and 57.9% (4708/8129) were male. After selection, 24 of the 44 clinical characteristics gathered after intensive care unit admission remained linked with prognosis and were utilized developing ML models. Among the six models developed, the eXtreme Gradient Boosting (XGBoost) model had the highest AUC, at 0.794. According to the SHAP values, the sequential organ failure assessment score, respiration, simplified acute physiology score II, and age were the four most influential variables in the XGBoost model. Individualized forecasts were clarified using the LIME algorithm. We built and verified ML models that excel in early mortality risk prediction in SA-AKI and the XGBoost model performed best.

Abstract Background Taurine performs multiple physiological functions, and the maintenance of taurine level for most mammals relies on active uptake from diet and endogenous taurine synthesis through its synthesis enzymes, including cysteine dioxygenase (CDO). In addition, uterus tissue and uterus fluid are rich in taurine, and taurine synthesis is regulated by estrogen (E2) and progesterone (P4), the key hormones priming embryo-uterine crosstalk during embryo implantation, but the functional interactions and mechanisms among which are largely unknown. The present study was thus proposed to identify the effects of CDO and taurine on embryo implantation and related mechanisms by using Cdo knockout (KO) and ovariectomy (OVX) mouse models. Results The uterine CDO expression was assayed from the first day of plugging (d 1) to d 8 and the results showed that CDO expression level increased from d 1 to d 4, followed by a significant decline on d 5 and persisted to d 8, which was highly correlated with serum and uterine taurine levels, and serum P4 concentration. Next, Cdo KO mouse was established by CRISPER/Cas9. It was showed that Cdo deletion sharply decreased the taurine levels both in serum and uterus tissue, causing implantation defects and severe subfertility. However, the implantation defects in Cdo KO mice were partly rescued by the taurine supplementation. In addition, Cdo deletion led to a sharp decrease in the expressions of P4 receptor (PR) and its responsive genes Ihh, Hoxa10 and Hand2. Although the expression of uterine estrogen receptor (ERα) had no significant change, the levels of ERα induced genes (Muc1, Ltf) during the implantation window were upregulated after Cdo deletion. These accompanied by the suppression of stroma cell proliferation. Meanwhile, E2 inhibited CDO expression through ERα and P4 upregulated CDO expression through PR. Conclusion The present study firstly demonstrates that taurine and CDO play prominent roles in uterine receptivity and embryo implantation by involving in E2-ERα and P4-PR signaling. These are crucial for our understanding the mechanism of embryo implantation, and infer that taurine is a potential agent for improving reproductive efficiency of livestock industry and reproductive medicine.

Cytokinin is essential for regulation of nodulation. Here, the authors identified a B-type response regulator GmRR11d that governs a transcriptional program associated with nodulation and cytokinin activation essential for systemic regulation of nodulation.

Oocyte-dependent and cumulus cell-derived transforming growth factor-β promotes natriuretic peptide type C expression in mouse ampullary epithelial cells, which promotes sperm migration into the ampulla for fertilization.

Abstract Germ cell division and differentiation require intimate contact and interaction with the surrounding somatic cells. Luteinizing hormone (LH) triggers epidermal growth factor (EGF)-like growth factors to promote oocyte maturation and developmental competence by activating EGF receptor (EGFR) in somatic cells. Here, we showed that LH-EGFR signaling-activated sphingosine kinases (SphK) in somatic cells. The activation of EGFR by EGF increased S1P and calcium levels in cumulus-oocyte complexes (COCs), and decreased the binding affinity of natriuretic peptide receptor 2 (NPR2) for natriuretic peptide type C (NPPC) to release the cGMP-mediated meiotic arrest. These functions of EGF were blocked by the SphK inhibitor SKI-II, which could be reversed by the addition of S1P. S1P also activated the Akt/mTOR cascade reaction in oocytes and promoted targeting protein for Xklp2 (TPX2) accumulation and oocyte developmental competence. Specifically depleting Sphk1/2 in somatic cells reduced S1P levels and impaired oocyte meiotic maturation and developmental competence, resulting in complete female infertility. Collectively, SphK-produced S1P in somatic cells serves as a functional transmitter of LH-EGFR signaling from somatic cells to oocytes: acting on somatic cells to induce oocyte meiotic maturation, and acting on oocytes to improve oocyte developmental competence.

Background: This study aimed to develop a nomogram for predicting gram-negative bacterial (GNB) infections in patients with peritoneal dialysis-associated peritonitis (PDAP) to identify patients at high risk for GNB infections. Methods: In this investigation, hospitalization information was gathered retrospectively for patients with PDAP from January 2016 to December 2021. The concatenation of potential biomarkers obtained by univariate logistic regression, LASSO analysis, and RF algorithms into multivariate logistic regression was used to identify confounding factors related to GNB infections, which were then integrated into the nomogram. The concordance index (C-Index) was utilized to assess the precision of the model's predictions. The area under the curve (AUC) and decision curve analysis (DCA) was used to assess the predictive performance and clinical utility of the nomogram. Results: The final study population included 217 patients with PDAP, and 37 (17.1%) patients had gram-negative bacteria due to dialysate effluent culture. After multivariate logistic regression, age, procalcitonin, and hemoglobin were predictive factors of GNB infections. The C-index and bootstrap-corrected index of the nomogram for estimating GNB infections in patients were 0.821 and 0.814, respectively. The calibration plots showed good agreement between the predictions of the nomogram and the actual observation of GNB infections. The AUC of the receiver operating characteristic curve was 0.821, 95% CI: 0.747–0.896, which indicates that the model has good predictive accuracy. In addition, the DCA curve showed that the nomogram had a high clinical value in the range of 1%–94%, which further demonstrated that the nomogram could accurately predict GNB infection in patients with PDAP. Conclusions: We have created a new nomogram for predicting GNB infections in patients with PDAP. The nomogram model may improve the identification of GNB infections in patients with PDAP and contribute to timely intervention to improve patient prognosis.

With styrene and acrylonitrile in ABS plastic toys as examples, this paper introduces to the development of a systematic strategy for studying the chemical migration risk in toys. The approach, included the detection method, establishment of migration model, model verification, and the practical application of the model in risk assessment. First, simple and sensitive methods for detecting analyte residues and migration were developed by headspace GC-MS. Then, the migration models were established based on the migration data from 5 min to 168 h and verified using 11 ABS samples. The results showed that the predicted values of the models and the experimental values had a good fit (RMSE=0.10–8.72 %). Subsequently, the migration of analytes in 94 ABS toys was predicted with these models at specific migration times. The daily average exposure level to styrene and acrylonitrile were estimated for children (3 months to 3 years). At last, the migration models reasonably predicted that the cancer risk of styrene and acrylonitrile in ABS toys were 1.6 × 10−8–1.4 × 10−6 and 3.1 × 10−8–1.6 × 10−6, respectively. This research contributes to promote toy safety and child health by enriching migration models and risk assessments.

Abstract In mammals, nonrenewable primordial follicles are activated in an orderly manner to maintain the longevity of reproductive life. Mammalian target of rapamycin (mTOR)-KIT ligand (KITL) signaling in pre-granulosa cells and phosphatidylinositol 3-kinase (PI3K)-protein kinase B (Akt)-forkhead Box O3a (FOXO3a) signaling in oocytes are important for primordial follicle activation. The activation process is accompanied by the enhancement of energy metabolism, but the causal relationship is unclear. In the present study, the levels of glycolysis-related proteins GLUT4, HK1, PFKL, and PKM2 were significantly increased in granulosa cells but were decreased in oocytes during the mouse primordial-to-primary follicle transition. Both short-term pyruvate deprivation in vitro and acute fasting in vivo increased the glycolysis-related gene and protein levels, decreased AMPK activity, and increased mTOR activity in mouse ovaries. The downstream pathways Akt and FOXO3a were phosphorylated, resulting in mouse primordial follicle activation. The blockade of glycolysis by 2-deoxyglucose (2-DG), but not the blockade of the communication network between pre-granulosa cells and oocyte by KIT inhibitor ISCK03, decreased short-term pyruvate deprivation-promoted mTOR activity. Glycolysis was also increased in human granulosa cells during the primordial-to-primary follicle transition, and short-term pyruvate deprivation promoted the activation of human primordial follicles by increasing the glycolysis-related protein levels and mTOR activity in ovarian tissues. Taken together, the enhanced glycolysis in granulosa cells promotes the activation of primordial follicles through mTOR signaling. These findings provide new insight into the relationship between glycolytic disorders and POI/PCOS.

Abstract Sphingosine phosphate lyase 1 (SGPL1) is a highly conserved enzyme that irreversibly degrades sphingosine-1-phosphate (S1P). Sgpl1-knockout mice fail to develop germ cells, resulting in infertility. However, the molecular mechanism remains unclear. The results of the present study showed that SGPL1 was expressed mainly in granulosa cells, Leydig cells, spermatocytes, and round spermatids. Sgpl1 deletion led to S1P accumulation in the gonads. In the ovary, S1P decreased natriuretic peptide receptor 2 (NPR2) activity in granulosa cells and inhibited early follicle growth. In the testis, S1P increased the levels of cyclin-dependent kinase inhibitor 1A (p21) and apoptosis in Leydig cells, thus resulting in spermatogenesis arrest. These results indicate that Sgpl1 deletion increases intracellular S1P levels, resulting in the arrest of female and male germ cell development via different signaling pathways.

Abstract Background Abscisic acid (ABA) plays an important role in plant growth and adaptation through the ABA signaling pathway. The ABA-responsive element binding (AREB/ABF) family transcriptional factors are central regulators that integrate ABA signaling with various signaling pathways. It has long been known that ABA inhibits rhizobial infection and nodule formation in legumes, but the underlying molecular mechanisms remain elusive. Results Here, we show that nodulation is very sensitive to ABA and exogenous ABA dramatically inhibits rhizobial infection and nodule formation in soybean. In addition, we proved that GmbZIP1, an AREB/ABF transcription factor, is a major regulator in both nodulation and plant response to ABA in soybean. GmbZIP1 was specifically expressed during nodule formation and development. Overexpression of GmbZIP1 resulted in reduced rhizobial infection and decreased nodule number. Furthermore, GmbZIP1 is responsive to ABA, and ectopic overexpression of GmbZIP1 increased sensitivity of Arabidopsis plants to ABA during seed germination and postgerminative growth, and conferred enhanced drought tolerance of plants. Remarkably, we found that GmbZIP1 directly binds to the promoter of GmENOD40–1, a marker gene for nodule formation, to repress its expression. Conclusion Our results identified GmbZIP1 as a node regulator that integrates ABA signaling with nodulation signaling to negatively regulate nodule formation.

This paper reports the non-targeted analysis of unknown volatile chemicals in medical masks through headspace gas chromatography-Orbitrap high-resolution mass spectrometry. In view of the difficulties that may be encountered in the qualitative analysis of unknown substances, several typical cases and the corresponding reliable solutions are given from the perspective of comprehensive score and retention index, chemical ionization identification molecular formula, fragment ion detail comparison for distinguishing isomers, and identification of alkanes. With this method, 69 volatile substances were identified in 60 masks. The identified substances were divided into nine categories. Alkanes, esters, benzenes, and alcohols were the top four groups of substances identified in masks and accounted for 34.8%, 15.9%, 10.1%, and 7.2% of the total substances, respectively. In addition, ketones, ethers, phenolics, amides, and other substances were identified. Ethanol, 1,4-dichlorobenzene, toluene, m-xylene, dimethyl glutarate, and N,N-dimethylacetamide had high detection rates. The identified substances were further filtered and screened according to their detection rate, toxicity, and response intensity. Finally, 12 high-risk volatile chemicals in medical masks were listed. This study could serve as a reference for identifying unknown substances and a guide for monitoring volatile chemicals in masks and promoting chemical safety improvements in products.

Porcine spermatozoa are stored in the oviductal isthmus after natural mating, and the number of spermatozoa is increased in the oviductal ampulla when the mature cumulus-oocyte complexes (COCs) are transferred into the ampulla. However, the mechanism is unclear. Herein, natriuretic peptide type C (NPPC) was mainly expressed in porcine ampullary epithelial cells, whereas its cognate receptor natriuretic peptide receptor 2 (NPR2) was located on the neck and the midpiece of porcine spermatozoa. NPPC increased sperm motility and intracellular Ca2+ levels, and induced sperm release from oviduct isthmic cell aggregates. These actions of NPPC were blocked by the cyclic guanosine monophosphate (cGMP)-sensitive cyclic nucleotide-gated (CNG) channel inhibitor l-cis-Diltiazem. Moreover, porcine COCs acquired the ability to promote NPPC expression in the ampullary epithelial cells when the immature COCs were induced to maturation by epidermal growth factor (EGF). Simultaneously, transforming growth factor-β ligand 1 (TGFB1) levels were dramatically increased in the cumulus cells of the mature COCs. The addition of TGFB1 promoted NPPC expression in the ampullary epithelial cells, and the mature COC-induced NPPC was blocked by the transforming growth factor-β type 1 receptor (TGFBR1) inhibitor SD208. Taken together, the mature COCs promote NPPC expression in the ampullae via TGF-β signaling, and NPPC is required for the release of porcine spermatozoa from the oviduct isthmic cells.

A total of 90 wooden toys were collected, and six wood preservatives (chlorophenols and lindane) were analyzed by using gas chromatography–tandem mass spectrometry to assess the exposure risk of children to wood preservatives through oral contact with wooden toys. The detection rates of six preservatives ranged from 2.2% to 22.2%. The contents of the preservatives ranged from 0.6 µg/kg to 9.6 µg/kg. 2,4-Dichlorophenol (2,4-DCP) and 2,4,6-trichlorophenol (2,4,6-TCP) had higher detection rates and contents than other preservatives. Thus, their migration behaviors from toys to saliva were further investigated. In 11 positive samples, the max migration ratios of 2,4-DCP and 2,4,6-TCP ranged from 7.1% to 20.3% and from 11.1% to 24.8%, respectively. For children aged 3–36 months, the daily average 2,4-DCP exposure level associated with wooden toys ranged from 2.7 pg/(kg day) to 46.9 pg/(kg day), and the daily average 2,4,6-TCP exposure ranged from 3.6 pg/(kg day) to 69.4 pg/(kg day). The contribution to exposure provided by the saliva mobilization pathway was more than that provided by the ingestion of scraped-off toys, and the exposure level of 2,4,6-TCP was greater than that of 2,4-DCP. The max hazard quotient for 2,4-DCP was 1.9 × 10−4, and the max cancer risk for 2,4,6-TCP was 1.2 × 10−9. The above results indicated that although wood preservatives were distributed in wooden toys, exposure arising from directly mouthing these materials currently does not pose unacceptable risks to children.

Drought is a major threat to plant growth and crop productivity. Reduced level of the gibberellin would result in increased drought tolerance, but the underlying mechanism is still unclear. In Brassica napus, there are four BnaRGA genes that code for DELLA proteins, negative regulators of GA signaling. Among them, expression of BnaA6.RGA was greatly induced by drought and abscisic acid (ABA). Previously, we created the gain-of-function mutant of BnaA6.RGA, bnaa6.rga-D, and the loss-of-function quadruple mutant, bnarga by CRISPR/Cas9, respectively. Here we show that bnaa6.rga-D displayed enhanced drought tolerance, and its stomatal closure was hypersensitive to ABA treatment. By contrast, bnarga displayed reduced drought tolerance and was less sensitive to ABA treatment, but there is no difference in drought tolerance between single BnaRGA mutant and WT, suggesting a functional redundancy between the BnaRGA genes in this process. Furthermore, we found that BnaRGAs were able to interact physically with BnaA10.ABF2, an essential transcription factor in ABA signaling. The BnaA10.ABF2-BnaA6.RGA protein complex greatly increased the expression level of the drought responsive gene BnaC9.RAB18. Taken together, this work highlighted the fundamental roles of DELLA proteins in drought tolerance in B. napus, and provide desirable germplasm for further breeding of drought tolerance in rapeseed.

Legumes control nodule number through nodulation and autoregulation of nodulation (AON) pathways. Nodule Inception (NIN) is essential for rhizobial infection and nodule organogenesis in legumes. The GmNINa-miR172c-NNC1 (NMN) module, which consists of two positive regulators, GmNINa and miR172c, and a suppressor, NNC1, integrates both pathways. GmNINa activates miR172c to downregulate NNC1, leading to nodulation, while NNC1 inhibits miR172c expression, forming a negative feedback loop. GmNINa and NNC1 interact with each other and antagonistically fine-tune GmRIC1/RIC2 expression, turning AON on and off. Conversely, activation of AON inhibits GmNINa and miR172c expression, thereby reducing their inhibitory effects on NNC1 to attenuate both nodulation signaling and AON. The NMN module functions not only as an “accelerator” of the nodulation signal to promote nodulation but also as a “brake” on the signal by activating AON to orchestrate nodule number. : Plant Biology; Interaction of Plants with Organisms; Plant Genetics Subject Areas: Plant Biology, Interaction of Plants with Organisms, Plant Genetics

A MoS2-nanosheet-decorated C-N/Co4S3 (C-N/Co4S3@MoS2) nanorod with multi-defects was synthesized by using a core-shell zeolitic imidazole framework (ZIF-8@ZIF-67) as the precursor. The C-N/Co4S3@MoS2 hybrid showed high activity towards the hydrogen evolution reaction and the oxygen evolution reaction. This work provides a new strategy to find MoS2-based bifunctional electrocatalysts through MOF precursors. Keywords: MoS2 nanosheet, Hydrogen evolution reaction, Oxygen evolution reaction, Bifunctional electrocatalyst

DELLA (GAI/RGA/RGL1/RGL2/RGL3) proteins are key negative regulators in GA (gibberellin) signaling and are involved in regulating plant growth as a response to environmental stresses. It has been shown that the DELLA protein PROCERA (PRO) in tomato promotes drought tolerance, but its molecular mechanism remains unknown. Here, we showed that the gai-1 (gibberellin insensitive 1) mutant (generated from the gai-1 (Ler) allele (with a 17 amino acid deletion within the DELLA domain of GAI) by backcrossing gai-1 (Ler) with Col-0 three times), the gain-of-function mutant of GAI (GA INSENSITIVE) in Arabidopsis, increases drought tolerance. The stomatal density of the gai-1 mutant was increased but its stomatal aperture was decreased under abscisic acid (ABA) treatment conditions, suggesting that the drought tolerance of the gai-1 mutant is a complex trait. We further tested the interactions between DELLA proteins and ABF2 (abscisic acid (ABA)-responsive element (ABRE)-binding transcription factors) and found that there was a strong interaction between DELLA proteins and ABF2. Our results provide new insight into DELLA proteins and their role in drought stress tolerance.

The phytohormone abscisic acid (ABA) is an essential part of the plant response to abiotic stressors such as drought. Upon the perception of ABA, pyrabactin resistance (PYR)/PYR1-like (PYL)/regulatory components of ABA receptor (RCAR) proteins interact with co-receptor protein phosphatase type 2Cs to permit activation Snf1-related protein kinase2 (SnRK2) kinases, which switch on ABA signaling by phosphorylating various target proteins. Thus, SnRK2 kinases are central regulators of ABA signaling. However, the mechanisms that regulate SnRK2 degradation remain elusive. Here, we show that SnRK2.3 is degradated by 26S proteasome system and ABA promotes its degradation. We found that SnRK2.3 interacts with AtPP2-B11 directly. AtPP2-B11 is an F-box protein that is part of a SKP1/Cullin/F-box E3 ubiquitin ligase complex that negatively regulates plant responses to ABA by specifically promoting the degradation of SnRK2.3. AtPP2-B11 was induced by ABA, and the knockdown of AtPP2-B11 expression markedly increased the ABA sensitivity of plants during seed germination and postgerminative development. Overexpression of AtPP2-B11 does not affect ABA sensitivity, but inhibits the ABA hypersensitive phenotypes of SnRK2.3 overexpression lines. These results reveal a novel mechanism through which AtPP2-B11 specifically degrades SnRK2.3 to attenuate ABA signaling and the abiotic stress response in Arabidopsis.

Arrays of aligned multi-walled carbon nanotube-ionic liquid (MIL) were assembled on silicon wafers (Si-MIL). Formation of Si-MIL was confirmed by ATR-FTIR, AFM and Raman techniques. The electrochemical measurements indicated that Si-MIL showed good electrocatalysis towards oxygen reduction compared with MIL drop-cast on a glassy carbon electrode.