High-throughput UAV-based rice panicle detection and genetic mapping of heading-date-related traits.

Introduction: Rice (Oryza sativa) serves as a vital staple crop that feeds over half the world's population. Optimizing rice breeding for increasing grain yield is critical for global food security. Heading-date-related or Flowering-time-related traits, is a key factor determining yield potential. However, traditional manual phenotyping methods for these traits are time-consuming and labor-intensive. Method: Here we show that aerial imagery from unmanned aerial vehicles (UAVs), when combined with deep learning-based panicle detection, enables high-throughput phenotyping of heading-date-related traits. We systematically evaluated various state-of-the-art object detectors on rice panicle counting and identified YOLOv8-X as the optimal detector. Results: Applying YOLOv8-X to UAV time-series images of 294 rice recombinant inbred lines (RILs) allowed accurate quantification of six heading-date-related traits. Utilizing these phenotypes, we identified quantitative trait loci (QTL), including verified loci and novel loci, associated with heading date. Discussion: Our optimized UAV phenotyping and computer vision pipeline may facilitate scalable molecular identification of heading-date-related genes and guide enhancements in rice yield and adaptation.

Mitofilin in cardiovascular diseases: Insights into the pathogenesis and potential pharmacological interventions.

The impact of mitochondrial dysfunction on the pathogenesis of cardiovascular disease is increasing. However, the precise underlying mechanism remains unclear. Mitochondria produce cellular energy through oxidative phosphorylation while regulating calcium homeostasis, cellular respiration, and the production of biosynthetic chemicals. Nevertheless, problems related to cardiac energy metabolism, defective mitochondrial proteins, mitophagy, and structural changes in mitochondrial membranes can cause cardiovascular diseases via mitochondrial dysfunction. Mitofilin is a critical inner mitochondrial membrane protein that maintains cristae structure and facilitates protein transport while linking the inner mitochondrial membrane, outer mitochondrial membrane, and mitochondrial DNA transcription. Researchers believe that mitofilin may be a therapeutic target for treating cardiovascular diseases, particularly cardiac mitochondrial dysfunctions. In this review, we highlight current findings regarding the role of mitofilin in the pathogenesis of cardiovascular diseases and potential therapeutic compounds targeting mitofilin.

Core-Shell Gold Nanoparticles@Pd-Loaded Covalent Organic Framework for In Situ Surface-Enhanced Raman Spectroscopy Monitoring of Catalytic Reactions.

A core-shell nanostructure of gold nanoparticles@covalent organic framework (COF) loaded with palladium nanoparticles (AuNPs@COF-PdNPs) was designed for the rapid monitoring of catalytic reactions with surface-enhanced Raman spectroscopy (SERS). The nanostructure was prepared by coating the COF layer on AuNPs and then in situ synthesizing PdNPs within the COF shell. With the respective SERS activity and catalytic performance of the AuNP core and COF-PdNPs shell, the nanostructure can be directly used in the SERS study of the catalytic reaction processes. It was shown that the confinement effect of COF resulted in the high dispersity of PdNPs and outstanding catalytic activity of AuNPs@COF-PdNPs, thus improving the reaction rate constant of the AuNPs@COF-PdNPs-catalyzed hydrogenation reduction by 10 times higher than that obtained with Au/Pd NPs. In addition, the COF layer can serve as a protective shell to make AuNPs@COF-PdNPs possess excellent reusability. Moreover, the loading of PdNPs within the COF layer was found to be in favor of avoiding intermediate products to achieve a high total conversion rate. AuNPs@COF-PdNPs also showed great catalytic activities toward the Suzuki-Miyaura coupling reaction. Taken together, the proposed core-shell nanostructure has great potential in monitoring and exploring catalytic processes and interfacial reactions.

Efficacy of Personalized Postoperative Epilepsy Management in Patients with Glioblastoma Utilizing IDH1 Gene Assessment.

Objective: We explored the correlation between the presence of isocitrate dehydrogenase-1 (IDH1) mutations and the incidence of postoperative epilepsy in patients with glioblastoma, as well as assessed the efficacy of preemptive administration of antiepileptic medications in mitigating the occurrence of postoperative epilepsy. Methods: Fifty-three patients who received a postoperative pathological diagnosis of glioblastoma, were enrolled in this study. Tumor specimens were subjected to IDH1 gene analysis. The patient cohort was stratified based on their IDH1 mutation status and the administration of prophylactic antiepileptic drugs during the postoperative phase. We subsequently conducted a comparative analysis of postoperative epileptic complications within each patient subgroup. Results: In the cohort of 53 patients under study, the occurrence of epilepsy was observed in 10 out of 21 patients carrying IDH1 mutations, while 5 out of 32 patients with wild-type IDH1 also experienced epilepsy, revealing a statistically significant difference (P < 0.05). Among the 27 patients who received prophylactic antiepileptic drugs, 6 of them developed epilepsy, whereas 9 out of 26 patients who did not receive prophylactic antiepileptic drugs exhibited concurrent epilepsy, with no statistically significant difference (P > 0.05). However, when performing a subgroup analysis, it was found that 3 out of 12 patients with IDH1 mutations who received prophylactic antiepileptic drugs experienced epilepsy, whereas 7 out of 9 patients who did not receive prophylactic antiepileptic drugs developed epilepsy, demonstrating a statistically significant difference (P < 0.05). Furthermore, within the group of 15 patients with wild-type IDH1, 3 patients who received prophylactic antiepileptic drugs developed epilepsy, while 2 cases of epilepsy occurred among the 17 patients who did not receive prophylactic antiepileptic drugs, with no statistically significant difference (P > 0.05). Conclusion: In individuals with IDH1 mutant glioblastoma who have undergone surgical resection, the implementation of preventive antiepileptic therapy demonstrates a potential to diminish the occurrence of postoperative epilepsy.

Using Machine Learning to Construct the Blood-Follicle Distribution Models of Various Trace Elements and Explore the Transport-Related Pathways with Multiomics Data.

Permeabilities of various trace elements (TEs) through the blood-follicle barrier (BFB) play an important role in oocyte development. However, it has not been comprehensively described as well as its involved biological pathways. Our study aimed to construct a blood-follicle distribution model of the concerned TEs and explore their related biological pathways. We finally included a total of 168 women from a cohort of in vitro fertilization-embryo transfer conducted in two reproductive centers in Beijing City and Shandong Province, China. The concentrations of 35 TEs in both serum and follicular fluid (FF) samples from the 168 women were measured, as well as the multiomics features of the metabolome, lipidome, and proteome in both plasma and FF samples. Multiomics features associated with the transfer efficiencies of TEs through the BFB were selected by using an elastic net model and further utilized for pathway analysis. Various machine learning (ML) models were built to predict the concentrations of TEs in FF. Overall, there are 21 TEs that exhibited three types of consistent BFB distribution characteristics between Beijing and Shandong centers. Among them, the concentrations of arsenic, manganese, nickel, tin, and bismuth in FF were higher than those in the serum with transfer efficiencies of 1.19-4.38, while a reverse trend was observed for the 15 TEs with transfer efficiencies of 0.076-0.905, e.g., mercury, germanium, selenium, antimony, and titanium. Lastly, cadmium was evenly distributed in the two compartments with transfer efficiencies of 0.998-1.056. Multiomics analysis showed that the enrichment of TEs was associated with the synthesis and action of steroid hormones and the glucose metabolism. Random forest model can provide the most accurate predictions of the concentrations of TEs in FF among the concerned ML models. In conclusion, the selective permeability through the BFB for various TEs may be significantly regulated by the steroid hormones and the glucose metabolism. Also, the concentrations of some TEs in FF can be well predicted by their serum levels with a random forest model.

Reducing Indoor Particulate Air Pollution Improves Student Test Scores: A Randomized Double-Blind Crossover Study.

Short-term exposure to air pollution is associated with a decline in cognitive function. Standardized test scores have been employed to evaluate the effects of air pollution exposure on cognitive performance. Few studies aimed to prove whether air pollution is responsible for reduced test scores; none have implemented a "gold-standard" method for assessing the association such as a randomized, double-blind intervention. This study used a "gold-standard" method─randomized, double-blind crossover─to assess whether reducing short-term indoor particle concentrations results in improved test scores in college students in Tianjin, China. Participants (n = 162) were randomly assigned to one of two similar classrooms and completed a standardized English test on two consecutive weekends. Air purifiers with active or sham (i.e., filter removed) particle filtration were placed in each classroom. The filtration mode was switched between the two test days. Linear mixed-effect models were used to evaluate the effect of the intervention mode on the test scores. The results show that air purification (i.e., reducing PM) was significantly associated with increases in the z score for combined (0.11 [95%CI: 0.02, 0.21]) and reading (0.11 [95%CI: 0.00, 0.22]) components. In conclusion, a short-term reduction in indoor particle concentration led to improved test scores in students, suggesting an improvement in cognitive function.

Li Promoting Long Afterglow Organic Light-Emitting Transistor for Memory Optocoupler Module.

The artificial brain is conceived as advanced intelligence technology, capable to emulate in-memory processes occurring in the human brain by integrating synaptic devices. Within this context, improving the functionality of synaptic transistors to increase information processing density in neuromorphic chips is a major challenge in this field. In this article, Li-ion migration promoting long afterglow organic light-emitting transistors, which display exceptional postsynaptic brightness of 7000 cd m-2 under low operational voltages of 10 V is presented. The postsynaptic current of 0.1 mA operating as a built-in threshold switch is implemented as a firing point in these devices. The setting-condition-triggered long afterglow is employed to drive the photoisomerization process of photochromic molecules that mimic neurotransmitter transfer in the human brain for realizing a key memory rule, that is, the transition from long-term memory to permanent memory. The combination of setting-condition-triggered long afterglow with photodiode amplifiers is also processed to emulate the human responding action after the setting-training process. Overall, the successful integration in neuromorphic computing comprising stimulus judgment, photon emission, transition, and encoding,  to emulate the complicated decision tree of the human brain is demonstrated.

Model fusion for predicting unconventional proteins secreted by exosomes using deep learning.

Unconventional secretory proteins (USPs) are vital for cell-to-cell communication and are necessary for proper physiological processes. Unlike classical proteins that follow the conventional secretory pathway via the Golgi apparatus, these proteins are released using unconventional pathways. The primary modes of secretion for USPs are exosomes and ectosomes, which originate from the endoplasmic reticulum. Accurate and rapid identification of exosome-mediated secretory proteins is crucial for gaining valuable insights into the regulation of non-classical protein secretion and intercellular communication, as well as for the advancement of novel therapeutic approaches. Although computational methods based on amino acid sequence prediction exist for predicting unconventional proteins secreted by exosomes (UPSEs), they suffer from significant limitations in terms of algorithmic accuracy. In this study, we propose a novel approach to predict UPSEs by combining multiple deep learning models that incorporate both protein sequences and evolutionary information. Our approach utilizes a convolutional neural network (CNN) to extract protein sequence information, while various densely connected neural networks (DNNs) are employed to capture evolutionary conservation patterns.By combining six distinct deep learning models, we have created a superior framework that surpasses previous approaches, achieving an ACC score of 77.46% and an MCC score of 0.5406 on an independent test dataset.

Linker-Preserved Iron Metal-Organic Framework-Based Lateral Flow Assay for Sensitive Transglutaminase 2 Detection in Urine Through Machine Learning-Assisted Colorimetric Analysis.

A groundbreaking demonstration of the utilization of the metal-organic framework MIL-101(Fe) as an exceptionally perceptive visual label in colorimetric lateral flow assays (LFA) is described. This pioneering approach enables the precise identification of transglutaminase 2 (TGM2), a recognized biomarker for chronic kidney disease (CKD), in urine specimens, which offers a remarkably sensitive naked-eye detection mechanism. The surface of MIL-101(Fe) was modified with oxalyl chloride, adipoyl chloride, and poly(acrylic) acid (PAA); these not only improved the labeling material stability in a complex matrix but also achieved a systematic control in the detection limit of the TGM2 concentration using our LFA platform. The advanced LFA with the MIL-101(Fe)-PAA label can detect TGM2 concentrations down to 0.012, 0.009, and 0.010 nM in Tris-HCl buffer, urine, and desalted urine, respectively, which are approximately 55-fold lower than those for a conventional AuNP-based LFAs. Aside from rapid TGM2 detection (i.e., within 20 min), the performance of the MIL-101(Fe)-PAA-based LFA on reproducibility [coefficients of variation (CV) < 2.9%] and recovery (95.9-103.2%) along with storage stability within 25 days of observation (CV < 6.0%) shows an acceptable parameter range for quantitative analysis. A sophisticated sensing method grounded in machine learning principles was also developed, specifically aimed at precisely deducing the TGM2 concentration by analyzing immunoreaction sites. More importantly, our developed LFA offers potential for clinical measurement of TGM2 concentration in normal human urine and CKD patients' samples.

Identification and Analysis of the MIR399 Gene Family in Grapevine Reveal Their Potential Functions in Abiotic Stress.

MiR399 plays an important role in plant growth and development. The objective of the present study was to elucidate the evolutionary characteristics of the MIR399 gene family in grapevine and investigate its role in stress response. To comprehensively investigate the functions of miR399 in grapevine, nine members of the Vvi-MIR399 family were identified based on the genome, using a miRBase database search, located on four chromosomes (Chr 2, Chr 10, Chr 15, and Chr 16). The lengths of the Vvi-miR399 precursor sequences ranged from 82 to 122 nt and they formed stable stem-loop structures, indicating that they could produce microRNAs (miRNAs). Furthermore, our results suggested that the 2 to 20 nt region of miR399 mature sequences were relatively conserved among family members. Phylogenetic analysis revealed that the Vvi-MIR399 members of dicots (Arabidopsis, tomato, and sweet orange) and monocots (rice and grapevine) could be divided into three clades, and most of the Vvi-MIR399s were closely related to sweet orange in dicots. Promoter analysis of Vvi-MIR399s showed that the majority of the predicted cis-elements were related to stress response. A total of 66.7% (6/9) of the Vvi-MIR399 promoters harbored drought, GA, and SA response elements, and 44.4% (4/9) of the Vvi-MIRR399 promoters also presented elements involved in ABA and MeJA response. The expression trend of Vvi-MIR399s was consistent in different tissues, with the lowest expression level in mature and young fruits and the highest expression level in stems and young leaves. However, nine Vvi-MIR399s and four target genes showed different expression patterns when exposed to low light, high light, heat, cold, drought, and salt stress. Interestingly, a putative target of Vvi-MIR399 targeted multiple genes; for example, seven Vvi-MIR399s simultaneously targeted VIT_213s0067g03280.1. Furthermore, overexpression of Vvi_MIR399e and Vvi_MIR399f in Arabidopsis enhanced tolerance to drought compared with wild-type (WT). In contrast, the survival rate of Vvi_MIR399d-overexpressed plants were zero after drought stress. In conclusion, Vvi-MIR399e and Vvi-MIR399f, which are related to drought tolerance in grapevine, provide candidate genes for future drought resistance breeding.

Modeling competitive biosorption for methylene blue removal on rape straw powders using response surface methodology in a ternary dye aqueous solution.

The improvement of biosorption efficiency for selective dye removal in a multi-dye aqueous system has become an increasingly significant research topic. However, the competitive effects of coexisting dyes and the target dye in such systems remain uncertain due to complex interactions between adsorbent and coexisting dyes. Therefore, in this research, response surface methodology (RSM) model was effectively employed to investigate the competitive effects of allura red (AR) and malachite green (MG) on methylene blue (MB) removal in a ternary dye aqueous system using three different parts of rape straw powders. In the current design of RSM, the initial concentrations of AR and MG dyes ranging from 0 mg·L-1 to 500 mg·L-1 were considered as influencing factors, while the removal rates of MB on adsorbents at an initial concentration of 500 mg·L-1 were established as response values. The RSM models exhibited high correlation coefficients with adjusted R2 values of 0.9908 (pith core), 0.9870 (seedpods), and 0.9902 (shells), respectively, indicating a close fitted between predicted and actual values. The proposed models indicated that the perturbation effects of initial AR and MG concentrations were observed on the removal rates of MB by three types of rape straw powders in a ternary dye aqueous system, resulting in a decrease in MB removal rates, particularly at higher initial AR concentration due to stronger competitive effects compared to initial MG concentration. The structures of rape straw powders, including pith core, seedpods and shell, were analyzed using scanning eletron microscoe (SEM), energy dispersive spectroscopy (EDS), N2 physisorption isotherm, frourier transform infared spectroscopy (FTIR), Zeta potential classes and fluorescence spectrum before and after adsorption of MB in various dye aqueous systems. The characteristics of rape straw powders suggested that similar adsorption mechanisms, such as electrostatic attraction, pore diffusion, and group complex formation for MB, AR, and MG, respectively, occurred on the surfaces of adsorbents during their respective adsorption processes. This leads to significant competitive effects on the removal rates of MB in a ternary dye aqueous system, which are particularly influenced by initial AR concentrations as confirmed through fluorescence spectrum analysis.

Impact of AR and MG on MB removal was analyzed using simple methodologies.Competitive behaviors between AR, MG and MB were understood through RSM.Intense restrain effects on MB removal were revealed by AR concentration.

Comparison of Population-Weighted Exposure Estimates of Air Pollutants Based on Multiple Geostatistical Models in Beijing, China.

Various geostatistical models have been used in epidemiological research to evaluate ambient air pollutant exposures at a fine spatial scale. Few studies have investigated the performance of different exposure models on population-weighted exposure estimates and the resulting potential misclassification across various modeling approaches. This study developed spatial models for NO2 and PM2.5 and conducted exposure assessment in Beijing, China. It explored three spatial modeling approaches: variable dimension reduction, machine learning, and conventional linear regression. It compared their model performance by cross-validation (CV) and population-weighted exposure estimates. Specifically, partial least square (PLS) regression, random forests (RF), and supervised linear regression (SLR) models were developed based on an ordinary kriging (OK) framework for NO2 and PM2.5 in Beijing, China. The mean squared error-based R2 (R2mse) and root mean squared error (RMSE) in leave-one site-out cross-validation (LOOCV) were used to evaluate model performance. These models were used to predict the ambient exposure levels in the urban area and to estimate the misclassification of population-weighted exposure estimates in quartiles between them. The results showed that the PLS-OK models for NO2 and PM2.5, with the LOOCV R2mse of 0.82 and 0.81, respectively, outperformed the other models. The population-weighted exposure to NO2 estimated by the PLS-OK and RF-OK models exhibited the lowest misclassification in quartiles. For PM2.5, the estimates of potential misclassification were comparable across the three models. It indicated that the exposure misclassification made by choosing different modeling approaches should be carefully considered, and the resulting bias needs to be evaluated in epidemiological studies.

Chuanzhitongluo capsule improves cognitive impairment in mice with chronic cerebral hypoperfusion via the cholinergic anti-inflammatory pathway.

Vascular cognitive impairment (VCI) has become a common disease-causing cognitive deficit in humans, second only to Alzheimer's Disease (AD). Chuanzhitongluo capsule (CZTL) is a Traditional Chinese Medicine (TCM) preparation known for its effective protection against cerebral ischemia. However, its potential to ameliorate VCI remains unclear. This study aimed to investigate the cognitive improvement effects of CZTL in a mouse model of VCI. Chronic cerebral hypoperfusion (CCH) was induced in mice by bilateral common carotid artery stenosis (BCAS) to simulate the pathological changes associated with VCI. Spatial learning and memory abilities were assessed using the Morris Water Maze (MWM). RNA sequencing (RNA-Seq) was employed to identify differentially expressed genes (DEGs) in the hippocampus. Levels of inflammatory factors were measured through enzyme-linked immunosorbent assay (ELISA), while immunofluorescence (IF) determined the expression intensity of target proteins. Western Blot (WB) confirmed the final action pathway. Results indicated that CZTL significantly improved the spatial learning and memory abilities of CCH mice, along with alterations in gene expression profiles in the hippocampus. It also reduced neuroinflammation in the hippocampus and upregulated the choline acetyltransferase (ChAT) and α7 subunit-containing nicotinic acetylcholine receptor (α7nAChR), which are in synaptic plasticity and neuronal development. Moreover, CZTL inhibited the NF-κB signaling pathway. In conclusion, CZTL may alleviate neuroinflammation induced by CCH and improve cognitive impairment in CCH mice by regulating the cholinergic anti-inflammatory pathway (CAIP) involving ChAT/α7nAChR/NF-κB.

Bovine parainfluenza virus type 3 infections induce ER stress-mediated autophagy to facilitate virus replication.

Bovine Parainfluenza Virus Type 3 (BPIV3) serves as a crucial pathogen in cattle, adept at triggering severe respiratory symptoms. This investigation explores the intricate interplay of endoplasmic reticulum stress (ER stress), unfolded protein response (UPR), and autophagy upon BPIV3 infection. In this study, we initially confirm a substantial increase in glucose regulatory protein 78 (GRP78) expression, accompanied by noticeable morphological changes and significant expansion of the ER lumen observed through transmission electron microscopy upon BPIV3 infection. Our findings indicate that ER Stress is induced during BPIV3 infection in vitro. Subsequently, we illustrate that BPIV3 triggers ER Stress to facilitate viral replication through heightened autophagy through treatment with the ER stress inhibitor 4-phenylbutyrate (4-PBA) and utilizing small interfering RNA (siRNA) technology to knock down GRP78. Additionally, we observe that the activation of ER stress initiates the UPR via PERK and ATF6 pathways, with the IRE1 pathway not contributing to the regulation of ER stress-mediated autophagy. Moreover, intervention with the PERK inhibitor GSK2606414, ATF6 inhibitor Ceapin-A7, and siRNA technology successfully reverses BPIV3-induced autophagy. In summary, these findings propose that BPIV3 induces ER stress to enhance viral replication through increased autophagy, with the PERK and ATF6 pathways playing a significant role in ER stress-mediated autophagy.

Ascertaining sensitive exposure biomarkers of various metal(loid)s to embryo implantation.

Close relationships exist between metal(loid)s exposure and embryo implantation failure (EIF) from animal and epidemiological studies. However, there are still inconsistent results and lacking of sensitive metal(loid) exposure biomarkers associated with EIF risk. We aimed to ascertain sensitive metal(loid) biomarkers to EIF and provide potential biological explanations. Candidate metal(loid) biomarkers were measured in the female hair (FH), female serum (FS), and follicular fluid (FF) with various exposure time periods. An analytical framework was established by integrating epidemiological association results, comprehensive literature searching, and knowledge-based adverse outcome pathway (AOP) networks. The sensitive biomarkers of metal(loid)s along with potential biological pathways to EIF were identified in this framework. Among the concerned 272 candidates, 45 metal(loid)s biomarkers across six time periods and three biomatrix were initially identified by single-metal(loid) analyses. Two biomarkers with counterfactual results according to literature summary results were excluded, and a total of five biomarkers were further determined from 43 remained candidates in mixture models. Finally, four sensitive metal(loid) biomarkers were eventually assessed by overlapping AOP networks information, including Se and Co in FH, and Fe and Zn in FS. AOP networks also identified key GO pathways and proteins involved in regulation of oxygen species biosynthetic, cell proliferation, and inflammatory response. Partial dependence results revealed Fe in FS and Co in FH at their low levels might be potential sensitive exposure levels for EIF. Our study provided a typical framework to screen the crucial metal(loid) biomarkers and ascertain that Se and Co in FH, and Fe and Zn in FS played an important role in embryo implantation.

Recent Advances of CeO2-Based Composite Materials for Photocatalytic Applications.

Photocatalysis has the advantages of practical, sustainable and environmental protection, so it plays a significant role in energy transformation and environmental utilization. CeO2 has attracted widespread attention for its unique 4 f electrons, rich defect structures, high oxygen storage capacity and great chemical stability. In this paper, we review the structure of CeO2 and the common methods for the preparation of CeO2-based composites in the first part. In particular, we highlight the co-precipitation method, template method, and sol-gel method methods. Then, in the second part, we introduce the application of CeO2-based composites in photocatalysis, including photocatalytic CO2 reduction, hydrogen production, degradation, selective organic reaction, and photocatalytic nitrogen fixation. In addition, we discuss several modification techniques to improve the photocatalytic performance of CeO2-based composites, such as elemental doping, defect engineering, constructing heterojunction and morphology regulation. Finally, the challenges faced by CeO2-based composites are analyzed and their development prospects are prospected. This review provides a systematic summary of the recent advance of CeO2-based composites in the field of photocatalysis, which can provide useful references for the rational design of efficient CeO2-based composite photocatalysts for sustainable development.

Co-exposure to phthalates and polycyclic aromatic hydrocarbons and the risk of gestational hypertension in Chinese women.

Phthalates (PAEs) and polycyclic aromatic hydrocarbons (PAHs) are frequently detected in females of reproductive age. Many studies have found that environmental PAE and PAH levels are independent risk factors for gestational hypertension. However, exposure to both components is a more realistic scenario. To better assess the health effects of PAEs and PAHs in pregnant women, we explored the associations of exposure to both individual and combined PAEs and PAHs with gestational hypertension. This nested case-control study was a component of a prospective cohort study conducted in Beijing, China. We included 206 women with gestational hypertension and 214 pregnant controls. We used gas chromatography/tandem mass spectrometry (GC-MS/MS) to detect 8 PAEs and 13 PAHs in > 80 % of all collected hair samples. Multiple linear regression models were employed to test the individual associations between each component and gestational hypertension. A quantile-based g-computation (qgcomp) model and a weighted quantile sum (WQS) regression model were used to estimate whether exposure to both PAEs and PAHs increased the risk of gestational hypertension. The individual exposure analyses revealed that diethyl phthalate (DEP), diisobutyl phthalate (DIBP) (both PAEs), benzo(k)fluoranthene (BKF), anthracene, (ANT), and benzo(a)pyrene (BAP) (all PAHs) were positively associated with increased risk of gestational hypertension. In mixed-effect analyses, the qgcomp model indicated that co-exposure to PAEs and PAHs increased the risk of gestational hypertension (odds ratio = 2.01; 95 % confidence interval: 1.02, 3.94); this finding was verified by the WQS regression model. Our findings support earlier evidence that both PAEs and PAHs increase the risk of gestational hypertension, both individually and in combination. This suggests that reductions in exposure to endocrine system-disrupting chemicals such as PAEs and PAHs might reduce the risk of gestational hypertension.

Association between multipollutant exposure and thyroid hormones in elderly people: A cross-sectional study in China.

Environmental chemicals have been indicated to cause disruption of thyroid homeostasis in human populations. However, previous studies mostly focused on single group of chemicals. Herein, we investigate the independent and combined effects of multiple pollutants on thyroid homeostasis, including thyroid-stimulating hormone (TSH), total and free thyroxine (tT4 and fT4) and total and free triiodothyronine (tT3 and fT3) in elderly people. These environmental pollutants (n = 144) are from ten categories, including phenols, parabens, perfluoroalkyl substances (PFASs), polychlorinated biphenyls (PCBs), phthalate esters (PAEs), polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides (OCPs), organophosphate pesticides (OPPs), synthetic pyrethroids (SPs), herbicides, and metals. Few studies have evaluated the health risks of these 144 chemicals, especially their joint effects. In single-pollutant evaluations, multiple linear regression (MLR) models were used to estimate the independent associations between multiple exposures and thyroid biomarkers. In multi-pollutant evaluations, elastic net regression and Bayesian kernel machine regression (BKMR) models were used to estimate the combined associations. The MLR models showed that 41 chemicals were significantly related to THs levels. BKMR models revealed the most important chemical groups: metals for TSH, PAHs, SPs and PCBs for tT4, herbicides and SPs for tT3. This study will contribute to the understanding of multipollutant exposure and help prioritize specific chemical groups related to thyroid hormone disruption.

HNF1A induces glioblastoma by upregulating EPS8 and activating PI3K/AKT signaling pathway.

Despite the exact biological role of HNF1 homolog A (HNF1A) in the regulatory mechanism of glioblastoma (GBM), the molecular mechanism, especially the downstream regulation as a transcription factor, remains to be further elucidated. Immunohistochemistry was used to detect the expression and clinical relevance of HNF1A in GBM patients. CCK8, TUNEL, and subcutaneous tumor formation in nude mice were used to evaluate the effect of HNF1A on GBM in vitro and in vivo. The correction between HNF1A and epidermal growth factor receptor pathway substrate 8 (EPS8) was illustrated by bioinformatics analysis and luciferase assay. Further mechanism was explored that the transcription factor HNF1A regulated the expression of EPS8 and downstream signaling pathways by directly binding to the promoter region of EPS8. Our comprehensive analysis of clinical samples in this study showed that upregulated expression of HNF1A was associated with poor survival in GBM patients. Further, we found that knockdown of HNF1A markedly suppressed the malignant phenotype of GBM cells in vivo and in vitro as well as promoted apoptosis of tumor cells, which was reversed by upregulation of HNF1A. Mechanistically, HNF1A could significantly activate PI3K/AKT signaling pathway by specifically binding to the promoter regions of EPS8. Moreover, overexpression of EPS8 was able to reverse the apoptosis of tumor cells caused by HNF1A knockdown, thereby exacerbating the GBM progression. Correctively, our study has clarified the explicit mechanism by which HNF1A promotes GBM malignancy and provides a new therapeutic target for further clinical application.

A higher-yield hybrid rice is achieved by assimilating a dominant heterotic gene in inbred parental lines.

The exploitation of heterosis to integrate parental advantages is one of the fastest and most efficient ways of rice breeding. The genomic architecture of heterosis suggests that the grain yield is strongly correlated with the accumulation of numerous rare superior alleles with positive dominance. However, the improvements in yield of hybrid rice have shown a slowdown or even plateaued due to the limited availability of complementary superior alleles. In this study, we achieved a considerable increase in grain yield of restorer lines by inducing an alternative splicing event in a heterosis gene OsMADS1 through CRISPR-Cas9, which accounted for approximately 34.1%-47.5% of yield advantage over their corresponding inbred rice cultivars. To achieve a higher yield in hybrid rice, we crossed the gene-edited restorer parents harbouring OsMADS1GW3p6 with the sterile lines to develop new rice hybrids. In two-line hybrid rice Guang-liang-you 676 (GLY676), the yield of modified hybrids carrying the homozygous heterosis gene OsMADS1GW3p6 significantly exceeded that of the original hybrids with heterozygous OsMADS1. Similarly, the gene-modified F1 hybrids with heterozygous OsMADS1GW3p6 increased grain yield by over 3.4% compared to the three-line hybrid rice Quan-you-si-miao (QYSM) with the homozygous genotype of OsMADS1. Our study highlighted the great potential in increasing the grain yield of hybrid rice by pyramiding a single heterosis gene via CRISPR-Cas9. Furthermore, these results demonstrated that the incomplete dominance of heterosis genes played a major role in yield-related heterosis and provided a promising strategy for breeding higher-yielding rice varieties above what is currently achievable.