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Ideal plant architecture is essential for enhancing crop yields. Ideal soybean (Glycine max) architecture encompasses an appropriate plant height, increased node number, moderate seed weight, and compact architecture with smaller branch angles for growth under high-density planting. However, the functional genes regulating plant architecture are far not fully understood in soybean. In this study, we investigated the genetic basis of 12 agronomic traits in a panel of 496 soybean accessions with a wide geographical distribution in China. Analysis of phenotypic changes in 148 historical elite soybean varieties indicated that seed-related traits have mainly been improved over the past 60 years, with targeting plant architecture traits having the potential to further improve yields in future soybean breeding programs. In a genome-wide association study (GWAS) of 12 traits, we detected 169 significantly associated loci, of which 61 overlapped with previously reported loci and 108 new loci. By integrating the GWAS loci for different traits, we constructed a genetic association network and identified 90 loci that were associated with a single trait and 79 loci with pleiotropic effects. Of these 79 loci, 7 hub-nodes were strongly linked to at least three related agronomic traits. qHub_5, containing the previously characterized Determinate 1 (Dt1) locus, was associated not only with plant height and node number (as determined previously), but also with internode length and pod range. Furthermore, we identified qHub_7, which controls three branch angle-related traits; the candidate genes in this locus may be beneficial for breeding soybean with compact architecture. These findings provide insights into the genetic relationships among 12 important agronomic traits in soybean. In addition, these studies uncover valuable loci for further functional gene studies and will facilitate molecular design breeding of soybean architecture.

BackgroundChild sexual abuse is a major public health problem with adverse consequences for victims’ physical, mental, and reproductive health. This cross-sectional study aimed to determine the prevalence of child sexual abuse and its associated factors among 15- to 17-year-old adolescents in mainland China.MethodsFrom September 8, 2019 to January 17, 2020, a total of 48,660 participants were recruited by 58 colleges and universities across the whole country to complete the self-administered, structured, online questionnaire. This analysis was restricted to 3,215 adolescents aged between 15 and 17 years in mainland China. Chi-square tests and multivariate Logistic regression analyses were performed to identify individual, relationship, and community factors associated with child sexual abuse.ResultsThe overall prevalence of child sexual abuse was 12.0%. More specifically, 13.0% of girls and 10.6% of boys reported that they were sexually abused prior to 18 years of age. At the individual level, being female, sexual minority identity, younger age, and higher levels of knowledge, skills and self-efficacy regarding condom use were significantly related to increased odds of reporting sexual abuse. At the relationship and community level, adolescents from disrupted families and those entering into a marriage, having casual sexual partners, and having first intercourse at a younger age were more likely to report sexual abuse. On the contrary, those who had never discussed sex-related topics with their family members at home and were offered school-based sexuality education later (vs. earlier) were less likely to report sexual abuse.ConclusionMultilevel prevention programs and strategies, including targeting adolescents with high-risk characteristics, educating young children and their parents about child sexual abuse prevention and optimizing the involvement of parents, school, community, society and government in comprehensive sexuality education, should be taken to reduce child sexual abuse among 15- to 17-year-old adolescents.

BackgroundThe acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a common respiratory disease among older adults, which imposes a significant burden on individuals and society and poses a major challenge to the global public health system due to its high morbidity and mortality. Acupuncture is effective for AECOPD, but its efficacy has been questioned due to the limited methodological quality. Thus, we aim to investigate the efficacy of acupuncture as adjunctive therapy for AECOPD and determine whether the efficacy of acupuncture differs with the type of acupoint combinations.Methods and analysisThis study proposes a prospective, multicenter randomized controlled trial that will comprise four groups, including two acupuncture treatment groups, one sham acupuncture group, and one basic treatment group. The acupuncture treatment groups will be distinguished by their focus on different patterns of acupoint combination, namely the Xi-cleft and He-sea acupoint combination and the Eight Confluence points acupoint combination, which may vary in clinical efficacy based on traditional acupuncture theories. The study aims to randomize 556 patients in a 1:1:1:1 ratio across the four groups. Each patient in acupuncture group or sham acupuncture group will receive routine drug therapy and 7 sessions of acupuncture treatment over 1 week. Participants in the basic treatment group will only receive routine drug therapy. The trial will be conducted in seven hospitals located in China. The primary outcomes in this trial will include differences in the Breathlessness, Cough, and Sputum Scale (BCSS) before randomization, 7 days after randomization, 5 and 9 weeks after randomization.Ethics and disseminationEthical approval was obtained from the Sichuan Regional Ethics Review of Committee on Traditional Chinese Medicine (Approval ID: 2022KL-068). The results of this study will be distributed through peer-reviewed journals.Clinical Trial Registration: ClinicalTrials.gov, identifier ChiCTR2200064484.

Seed coat color is a typical morphological trait that can be used to reveal the evolution of soybean. The study of seed coat color-related traits in soybeans is of great significance for both evolutionary theory and breeding practices. In this study, 180 F10 recombinant inbred lines (RILs) derived from the cross between the yellow-seed coat cultivar Jidou12 (ZDD23040, JD12) and the wild black-seed coat accession Y9 (ZYD02739) were used as materials. Three methods, single-marker analysis (SMA), interval mapping (IM), and inclusive composite interval mapping (ICIM), were used to identify quantitative trait loci (QTLs) controlling seed coat color and seed hilum color. Simultaneously, two genome-wide association study (GWAS) models, the generalized linear model (GLM) and mixed linear model (MLM), were used to jointly identify seed coat color and seed hilum color QTLs in 250 natural populations. By integrating the results from QTL mapping and GWAS analysis, we identified two stable QTLs (qSCC02 and qSCC08) associated with seed coat color and one stable QTL (qSHC08) related to seed hilum color. By combining the results of linkage analysis and association analysis, two stable QTLs (qSCC02, qSCC08) for seed coat color and one stable QTL (qSHC08) for seed hilum color were identified. Upon further investigation using Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we validated the previous findings that two candidate genes (CHS3C and CHS4A) reside within the qSCC08 region and identified a new QTL, qSCC02. There were a total of 28 candidate genes in the interval, among which Glyma.02G024600, Glyma.02G024700, and Glyma.02G024800 were mapped to the glutathione metabolic pathway, which is related to the transport or accumulation of anthocyanin. We considered the three genes as potential candidate genes for soybean seed coat-related traits. The QTLs and candidate genes detected in this study provide a foundation for further understanding the genetic mechanisms underlying soybean seed coat color and seed hilum color and are of significant value in marker-assisted breeding.

ATP-dependent SWI/SNF chromatin remodeling complexes (CRCs) are evolutionarily conserved multi-component machines that regulate transcription, replication, and genome stability in eukaryotes. SWI/SNF components play pivotal roles in development and various stress responses in plants. However, the compositions and biological functions of SWI/SNF complex subunits remain poorly understood in soybean. In this study, we used bioinformatics to identify 39 genes encoding SWI/SNF subunit distributed on the 19 chromosomes of soybean. The promoter regions of the genes were enriched with several cis-regulatory elements that are responsive to various hormones and stresses. Digital expression profiling and qRT-PCR revealed that most of the SWI/SNF subunit genes were expressed in multiple tissues of soybean and were sensitive to drought stress. Phenotypical, physiological, and molecular genetic analyses revealed that GmLFR1 (Leaf and Flower-Related1) plays a negative role in drought tolerance in soybean and Arabidopsis thaliana. Together, our findings characterize putative components of soybean SWI/SNF complex and indicate possible roles for GmLFR1 in plants under drought stress. This study offers a foundation for comprehensive analyses of soybean SWI/SNF subunit and provides mechanistic insight into the epigenetic regulation of drought tolerance in soybean.

IntroductionGenomic selection (GS) is a potential breeding approach for soybean improvement.MethodsIn this study, GS was performed on soybean protein and oil content using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) based on 1,007 soybean accessions. The SoySNP50K SNP dataset of the accessions was obtained from the USDA-ARS, Beltsville, MD lab, and the protein and oil content of the accessions were obtained from GRIN.ResultsOur results showed that the prediction accuracy of oil content was higher than that of protein content. When the training population size was 100, the prediction accuracies for protein content and oil content were 0.60 and 0.79, respectively. The prediction accuracy increased with the size of the training population. Training populations with similar phenotype or with close genetic relationships to the prediction population exhibited better prediction accuracy. A greatest prediction accuracy for both protein and oil content was observed when approximately 3,000 markers with -log10(P) greater than 1 were included.DiscussionThis information will help improve GS efficiency and facilitate the application of GS.

High-density planting is a major way to improve crop yields. However, shade-avoidance syndrome (SAS) is a major factor limiting increased planting density. First Green Revolution addressed grass lodging problem by using dwarf/semi-dwarf genes. However, it is not suitable for soybean, which bear seeds on stalk and whose seed yield depends on plant height. Hence, mining shade-tolerant germplasms and elucidating the underlying mechanism could provide meaningful resources and information for high-yield breeding. Here, we report a high-plant density-tolerant soybean cultivar, JiDou 17, which exhibited an inactive SAS (iSAS) phenotype under high-plant density or low-light conditions at the seedling stage. A quantitative trait locus (QTL) mapping analysis using a recombinant inbred line (RIL) population showed that this iSAS phenotype is related to a major QTL, named shade-avoidance response 1 (qSAR1), which was detected. The mapping region was narrowed by a haplotype analysis into a 554 kb interval harboring 44 genes, including 4 known to be key regulators of the SAS network and 4 with a variance response to low-light conditions between near isogenic line (NIL) stems. Via RNA-seq, we identified iSAS-specific genes based on one pair of near isogenic lines (NILs) and their parents. The iSAS-specific genes expressed in the stems were significantly enriched in the “proteasomal protein catabolic” process and the proteasome pathway, which were recently suggested to promote the shade-avoidance response by enhancing PIF7 stability. Most iSAS-specific proteasome-related genes were downregulated under low-light conditions. The expression of genes related to ABA, CK, and GA significantly varied between the low- and normal-light conditions. This finding is meaningful for the cloning of genes that harbor beneficial variation(s) conferring the iSAS phenotype fixed in domestication and breeding practice.

Heterophylly, the existence of different leaf shapes and sizes on the same plant, has been observed in many flowering plant species. Yet, the genetic characteristics and genetic basis of heterophylly in soybean remain unknown. Here, two populations of recombinant inbred lines (RILs) with distinctly different leaf shapes were used to identify loci controlling heterophylly in two environments. The ratio of apical leaf shape (LSUP) to basal leaf shape (LSDOWN) at the reproductive growth stage (RLS) was used as a parameter for classifying heterophylly. A total of eight QTL were detected for RLS between the two populations and four of them were stably identified in both environments. Among them, qRLS20 had the largest effect in the JS population, with a maximum LOD value of 46.9 explaining up to 47.2% of phenotypic variance. This locus was located in the same genomic region as the basal leaf shape QTL qLSDOWN20 on chromosome 20. The locus qRLS19 had the largest effect in the JJ population, with a maximum LOD value of 15.2 explaining up to 27.0% of phenotypic variance. This locus was located in the same genomic region as the apical leaf shape QTL qLSUP19 on chromosome 19. Four candidate genes for heterophylly were identified based on sequence differences among the three parents of the two mapping populations, RT-qPCR analysis, and gene functional annotation analysis. The QTL and candidate genes detected in this study lay a foundation for further understanding the genetic mechanism of heterophylly and are invaluable in marker-assisted breeding.

Soybean is a primary meal protein for human consumption, poultry, and livestock feed. In this study, quantitative trait locus (QTL) controlling protein content was explored via genome-wide association studies (GWAS) and linkage mapping approaches based on 284 soybean accessions and 180 recombinant inbred lines (RILs), respectively, which were evaluated for protein content for 4 years. A total of 22 single nucleotide polymorphisms (SNPs) associated with protein content were detected using mixed linear model (MLM) and general linear model (GLM) methods in Tassel and 5 QTLs using Bayesian interval mapping (IM), single-trait multiple interval mapping (SMIM), single-trait composite interval mapping maximum likelihood estimation (SMLE), and single marker regression (SMR) models in Q-Gene and IciMapping. Major QTLs were detected on chromosomes 6 and 20 in both populations. The new QTL genomic region on chromosome 6 (Chr6_18844283–19315351) included 7 candidate genes and the Hap.XAA at the Chr6_19172961 position was associated with high protein content. Genomic selection (GS) of protein content was performed using Bayesian Lasso (BL) and ridge regression best linear unbiased prediction (rrBULP) based on all the SNPs and the SNPs significantly associated with protein content resulted from GWAS. The results showed that BL and rrBLUP performed similarly; GS accuracy was dependent on the SNP set and training population size. GS efficiency was higher for the SNPs derived from GWAS than random SNPs and reached a plateau when the number of markers was >2,000. The SNP markers identified in this study and other information were essential in establishing an efficient marker-assisted selection (MAS) and GS pipelines for improving soybean protein content.

Smart grids, the next generation of electricity systems, would be intelligent and self-aware of physical and cyber activity in the control area. As a cyber-embedded infrastructure, it must be capable of detecting cyberattacks and responding appropriately in a timely and effective manner. This article tries to introduce an advanced and unique intrusion detection model capable of classifying binary-class, trinary-class, and multiple-class CDs and electrical network incidents for smart grids. It makes use of the gray wolf algorithm (GWA) for evolving training of artificial neural networks (ANNs) as a successful machine learning model for intrusion detection. In this way, the intrusion detection model’s weight vectors are initialized and adjusted using the GWA in order to reach the smallest mean square error possible. With the suggested evolving machine learning model, the issues of cyberattacks, failure forecast, and failure diagnosing would be addressed in the smart grid energy sector properly. Using a real dataset from the Mississippi State Laboratory in the United States, the proposed model is illustrated and the experimental results are explained. The proposed model is compared to some of the most widely used classifiers in the area. The results show that the suggested intrusion detection model outperforms other well-known models in this field.

In order to solve the problem of the time offset between the supervisory control and data acquisition system and phasor measurement unit and the unknown distribution of non-Gauss noise, this paper proposes a robust state estimation method for power systems based on the Maximum Exponential Square and data fusion. Firstly, the robust Mahalanobis distance is used to detect system outliers and assign appropriate weights to the selected PMU buffer measurement. Then, the MES-based estimator uses these weights to filter out non-Gauss PMU measurement noise to generate a set of state estimation results. At the same time, the MES estimator is used to process the received SCADA measurement with unknown measurement noise, thereby generating another set of state estimation results. Finally, the two sets of estimation results from two independent MES estimators are fused by using data fusion theory to obtain the final optimal state estimation results. Based on IEEE-14 and 30-buses standard system, the simulation results prove the effectiveness and robustness of the method proposed in this paper.

Although elastic properties of hydrating cement paste are crucial in concrete engineering practice, there are only a few widely available models for engineers to predict the elastic behavior of hydrating cement paste. Therefore, in this paper, we derive an analytical model to efficiently predict the elastic properties (e.g., Young’s modulus) of hydrating cement paste. Notably, the proposed model provides the prediction of hydration, percolation, and homogenization of the cement paste, enabling the study of the early age elasticity evolution in cement paste. A hydration model considering the mineral composition and the initial w/c ratio was used, while the percolation threshold was calculated adopting a phenomenological semi-empirical method describing the effects of the solid volume fraction and the w/c ratio. An efficient mixing rule based on the degree of solid connectivity was then adopted to calculate the elastic properties of the hydrating cement paste. Moreover, for ordinary Portland cement, a simplified model was built using Powers’ hydration model. The obtained modeling results are following experimental data and other numerical results available in the literature.

Background and Purpose: Anger has been recognized as a commonly experienced emotion among caregivers of elderly people with dementia. While several cognitive behavioral therapy (CBT)-based intervening methods have been developed, limited research has systematically examined the associations between dementia-related cognition and caregiving anger. Currently, we focused on three representative and well-studied cognitive constructs, person-centered attitude (PCA), dementia representation (DR), and empathy, exploring how they related to caregiving anger.Methods & Results: In total, 327 caregivers (239 female) participated in the study and finished online questionnaires. Multi-variable regression analyzes showed that PCA (βPCA = −0.22**) and empathy (βempathy = −0.18**) could negatively predict caregiving anger. However, all DR dimensions had no influence on caregiving anger except coherence (βcoherence = −0.24**) in the current study.Conclusion: Generally, lower caregiving anger was associated with: (1) being more empathic; (2) having a person-centered attitude; and (3) having a comprehensive understanding of dementia. The results of this study provide detailed suggestions for the development of anger management programs for caregivers of people with dementia.

Developing high yielding cultivars with outstanding quality traits are perpetual objectives throughout crop breeding operations. Confoundingly, both of these breeding objectives typically involve working with complex quantitative traits that can be affected by genetic and environmental factors. Establishing correlations of these complex traits with more easily identifiable and highly heritable traits can simplify breeding processes. In this study, two parental soybean genotypes contrasting in seed hilum size, yield, and seed quality, as well as 175 F9 recombinant inbred lines (RILs) derived from these parents, were grown in 3 years. The h2b of four hilum size, two quality and two yield traits, ranged from 0.72 to 0.87. The four observed hilum size traits exhibited significant correlation (P < 0.05) with most of seed yield and quality traits, as indicated by correlation coefficients varying from -0.35 to 0.42, which suggests that hilum size could be considered as a proxy trait for soybean yield and quality. Interestingly, among 53 significant quantitative trait loci (QTLs) with logarithm of odds (LOD) values ranging from 2.51 to 6.69 and accounting for 6.40–16.10% of genetic variation, three loci encoding hilum size, qSH6.2, qSH8, and qSH10, colocated with QTLs for seed yield and quality traits, demonstrating that genes impacting seed hilum size colocalize in part with genes acting on soybean yield and quality. As a result of the breeding efforts and field observations described in this work, it is reasonable to conclude that optimizing hilum size through selection focused on a few QTLs may be useful for breeding new high yielding soybean varieties with favorable quality characteristics.

Vertical transmission of Toxoplasma gondii (T. gondii) infection during gestation can result in severe complications such as abortion, congenital malformation, fetal teratogenesis, etc. Immune inhibitory molecule Tim-3 was discovered to be expressed on some decidual immune cells and participates in the maintenance of maternal-fetal tolerance. Dysregulation of Tim-3 expression on decidual NK (dNK) cells was observed in several cases of pregnancy complications, whereas the role of Tim-3 on dNK cells during T. gondii infection remains unclear. In the present study, T. gondii infected Tim-3-/- pregnant mice, and anti-Tim-3 neutralizing antibody treated and infected human dNK cells were successfully established to explore the role of Tim-3 in dysfunction of dNK cells during abnormal pregnancy. Our results illustrated that Tim-3-/- pregnant mice displayed more worse pregnancy outcomes with T. gondii infection compared to infected WT pregnant mice. Also, it demonstrated that Tim-3 expression on dNK cells was significantly down-regulated following T. gondii infection. Data suggested a remarkable activation of dNK cells in Tim-3-/- mice and anti-Tim-3 neutralizing antibody treated and infected groups, with higher ratios of activating receptor NKG2D to inhibitory receptor NKG2A or KIR2DL4, IFN-γ/IL-10, and increased granule production compared with that of the infected group. Mechanism analysis proved that T. gondii-induced Tim-3 down-regulation significantly activated the phosphatidylinositol-3-kinase (PI3K)-AKT and JAK-STAT signaling pathway, by which the GranzymeB, Perforin, IFN-γ, and IL-10 production were further up-regulated. Our research demonstrated that the decrease of Tim-3 on dNK cells caused by T. gondii infection further led to dNK cells function disorder, which finally contributed to the development of abnormal pregnancy outcomes.

Direct conversion of fibroblasts into induced cardiomyocytes (iCMs) holds promising potential to generate functional cardiomyocytes for drug development and clinical applications, especially for direct in situ heart regeneration by delivery of reprogramming genes into adult cardiac fibroblasts in injured hearts. For a decade, many cocktails of transcription factors have been developed to generate iCMs from fibroblasts of different tissues in vitro and some were applied in vivo. Here, we aimed to develop genetic cocktails that induce cardiac reprogramming directly in cultured cardiac fibroblasts isolated from adult mice with myocardial infarction (MICFs), which could be more relevant to heart diseases. We found that the widely used genetic cocktail, Gata4, Mef2c, and Tbx5 (GMT) were inefficient in reprogramming cardiomyocytes from MICFs. In a whole well of a 12-well plate, less than 10 mCherry+ cells (

Soluble epoxide hydrolase (sEH) is responsible for rapid degradation of 14, 15-EET, which is one of the isomers of EETs and plays an important role in cardiovascular diseases. In this study, we investigated the mechanism by which sEH inhibitor AUDA played an anti-inflammatory effect in HCAECs. Our results indicated that AUDA treatment promoted PPARγ expression, while knockdown of PPARγ blocked the cell growth and STAT1 expression inhibition induced by 100 μmol/L AUDA in HCAECs. AUDA also inhibited the overexpression of TNF-α, IL-1 β, and MMP-9 induced by KD sera in HCAECs. Moreover, 30 blood samples from children with Kawasaki disease (KD) were collected with 30 healthy children as the control group. QPCR and ELISA assays were used to detect the level of 14, 15-EET, TNF-α, IL-1β, and MMP-9. We found that the level of 14, 15-EET was higher in peripheral blood of children with KD compared with healthy controls (P < 0.05). In comparison to KD children with non-coronary artery lesion (nCAL), the level of 14, 15-EET was higher in peripheral blood of KD children with coronary artery lesion (CAL) (P < 0.05). Compared with healthy control group, the expression levels of TNF-α, IL-1β, and MMP-9 in patients with KD were significantly up-regulated. Compared with nCAL KD children, the expression levels of TNF-α, IL-1β, and MMP-9 in CAL children were abnormally high (P < 0.05). Our study indicated that AUDA played an anti-inflammatory effect in HCAECs through PPARγ/STAT1 signaling pathway, and 14, 15-EET is up-regulated in children with KD, suggesting that 14, 15-EET involved in the progression of KD.

Infections caused by antibiotic-resistant bacteria have become one of the most serious global public health crises. Early detection and effective treatment can effectively prevent deterioration and further spreading of the bacterial infections. Therefore, there is an urgent need for time-saving diagnosis as well as therapeutically potent therapy approaches. Development of nanomedicine has provided more choices for detection and therapy of bacterial infections. Ultrasmall gold nanoclusters (Au NCs) are emerging as potential antibacterial agents and have drawn intense attention in the biomedical fields owing to their excellent biocompatibility and unusual physicochemical properties. Recent significant efforts have shown that these versatile Au NCs also have great application potential in the selective detection of bacteria and infection treatment. In this review, we will provide an overview of research progress on the development of versatile Au NCs for bacterial detection and infection treatment, and the mechanisms of action of designed diagnostic and therapeutic agents will be highlighted. Based on these cases, we have briefly discussed the current issues and perspective of Au NCs for bacterial detection and infection treatment applications.

Soybean is a major source of protein for human consumption and animal feed. Releasing new cultivars with high nutritional value is one of the major goals in soybean breeding. To achieve this goal, genome-wide association studies of seed amino acid contents were conducted based on 249 soybean accessions from China, US, Japan, and South Korea. The accessions were evaluated for 15 amino acids and genotyped by sequencing. Significant genetic variation was observed for amino acids among the accessions. Among the 231 single nucleotide polymorphisms (SNPs) significantly associated with variations in amino acid contents, fifteen SNPs localized near 14 candidate genes involving in amino acid metabolism. The amino acids were classified into two groups with five in one group and seven amino acids in the other. Correlation coefficients among the amino acids within each group were high and positive, but the correlation coefficients of amino acids between the two groups were negative. Twenty-five SNP markers associated with multiple amino acids can be used to simultaneously improve multi-amino acid concentration in soybean. Genomic selection analysis of amino acid concentration showed that selection efficiency of amino acids based on the markers significantly associated with all 15 amino acids was higher than that based on random markers or markers only associated with individual amino acid. The identified markers could facilitate selection of soybean varieties with improved seed quality.

Vertical transmission of the intracellular parasite Toxoplasma gondii (T. gondii) can lead to devastating consequences during gestation. Tim-3, a negative immune regulator, is constitutively expressed on decidual macrophages, but its specific role during T. gondii infection has not yet been explored. In the present study, we discovered that Tim-3 plays an important role in the abnormal pregnancy due to T. gondii infection using Tim-3−/− pregnant mice and anti-Tim-3 neutralizing antibody treated human decidual macrophages. The results showed that abnormal pregnancy outcomes were more prevalent in Tim-3−/− infected pregnant mice than in wild-type infected pregnant mice. Tim-3 expression in decidual macrophages was significantly down-regulated after T. gondii infection both in vitro and in vivo. Tim-3 down-regulation by T.gondii infection could strengthen M1 activation and weaken M2 tolerance by changing the M1 and M2 membrane molecule expression, arginine metabolic enzymes synthesis, and cytokine secretion profiles of decidual macrophages. Moreover, Tim-3 down-regulation by T.gondii infection led to PI3K-AKT phosphorylation inhibition, downstream transcription factor C/EBPβ expression, and SOCS1 activation, which resulted in enzymes synthesis regulation and cytokines secretion. Our study demonstrates that Tim-3 plays an indispensable role in the adverse pregnancy outcomes caused by T. gondii infection.

The use of sterility is common in plants and multiple loci for hybrid sterility have been identified in crops such as rice. In soybean, fine-mapping and research on the molecular mechanism of male sterility is limited. Here, we identified a male-sterile soybean line, which produces larger, abnormal pollen grains that stain poorly with I2-KI. In an inheritance test, all F1 plants were fertile and the F2 and F2:3 populations conformed with the expected segregation ratio of 3:1 (fertility:sterility) (p = 0.82) and showed a 1:2:0 ratio of homozygous fertile: heterozygous fertile: homozygous sterile genotypes (p = 0.73), suggesting that the sterility was controlled by a single recessive gene (designated “mst-M”). Bulked segregant analysis showed that almost all single-nucleotide polymorphisms (SNPs; 95.92%) were distributed on chromosome 13 and 868 SNPs (95.81%) were distributed in the physical region of Chromosome 13.21877872 to Chromosome 13.22862641. Genetic mapping revealed that mst-M was flanked by W1 and dCAPS-1 with genetic distances of 0.6 and 1.8 cM, respectively. The order of the consensus markers and known sterility genes was: Satt146 – (5.0 cM) – st5 – (2.5 cM) – Satt030 – (15.3 cM) – ms6 – (5.0 cM) – Satt149 – (39.5 cM) – W1 – (0.6 cM) – mst-M – (14.1 cM) – Satt516 (7.5 cM) – ms1 – (16.3 cM) – Satt595. These results suggest that mst-M is a newly identified male-sterility gene, which represents an alternative genetic resource for developing a hybrid seed production system for soybean.

Background: Early postmenopausal women frequently suffer from cognitive impairments and emotional disorders, such as lack of attention, poor memory, deficits in executive function and depression. However, the underlying mechanisms of these impairments remain unclear.Method: Forty-three early postmenopausal women and forty-four age-matched premenopausal controls underwent serum sex hormone analysis, neuropsychological testing and resting-state functional magnetic resonance imaging (rs-fMRI). Degree centrality (DC) analysis was performed to confirm the peak points of the functionally abnormal brain areas as the centers of the seeds. Subsequently, the functional connectivity (FC) between these abnormal seeds and other voxels across the whole brain was calculated. Finally, the sex hormone levels, neuroimaging indices and neuropsychological data were combined to detect potential correlations.Results: Compared with the premenopausal controls, the early postmenopausal women exhibited significantly higher serum follicle-stimulating hormone (FSH) levels, more severe climacteric and depressive symptoms, worse sleep quality and more extensive cognitive impairments. Concurrently, the neuroimaging results showed elevated DC values in the left amygdala (AMYG.L), reduced DC values in the left middle occipital gyrus (MOG.L) and right middle occipital gyrus (MOG.R). When we used the AMYG.L as the seed point, FC with the left insula (INS.L), bilateral prefrontal cortex (PFC) and right superior frontal gyrus (SFG.R) was increased; these regions are related to depressive states, poor sleep quality and decreased executive function. When bilateral MOG were used as the seed points, FC with left inferior parietal gyrus (IPG.L), this area closely associated with impaired memory, was decreased.Conclusion: These results illuminated the regional and network-level brain dysfunction in early postmenopausal women, which might provide information on the underlying mechanisms of the different cognitive impairments and emotional alterations observed in this group.

Toxoplasma gondii (T. gondii) infection in early pregnancy can result in miscarriage, dead fetus, and other abnormalities. The LILRB4 is a central inhibitory receptor in uterine dendritic cells (uDCs) that plays essential immune-regulatory roles at the maternal–fetal interface. In this study, T. gondii-infected human primary uDCs and T. gondii-infected LILRB4-/- pregnant mice were utilized. The immune mechanisms underlying the role of LILRB4 on uDCs were explored in the development of abnormal pregnancy outcomes following T. gondii infection in vitro and in vivo. Our results showed that the expression levels of LILRB4 on uDCs from normal pregnant mice were obviously higher than non-pregnant mice, and peaked in mid-gestation. The LILRB4 expression on uDC subsets, especially tolerogenic subsets, from mid-gestation was obviously down-regulated after T. gondii infection and LILRB4 decrease could further regulate the expression of functional molecules (CD80, CD86, and HLA-DR or MHC II) on uDCs, contributing to abnormal pregnancy outcomes. Our results will shed light on the molecular immune mechanisms of uDCs in abnormal pregnancy outcomes by T. gondii infection.

Soybean [Glycine max (L.) Merr] is an important legume crop and its yield largely depends on root architecture (RA) and biological nitrogen fixation (BNF). However, the relationship between RA and BNF, and its genetics behind remain unclear. Here, two soybean genotypes contrasting in RA and their 175 F9:11 recombinant inbred lines (RILs) were evaluated in field. The shallow-root parent, JD12, had better nodulation and higher yield than the deep-root parent, NF58. Strong correlations between shoot dry weight (SDW) and RA or BNF traits existed in the RILs, and the shallow-root group had more and heavier nodules, as well as higher SDW. After inoculating with rhizobia, roots became shallower and bigger, showing strong synergistic interactions between RA and BNF. In total, 70 QTLs were identified for the 21 tested traits. Among them, qBNF-RA-C2, qBNF-RA-O, and qBNF-RA-B1, were newly identified QTLs for BNF and/or RA traits in soybean, which co-located with the QTLs for SDW detected presently, and with the QTLs for yield identified previously. The results together suggest that there are synergistic interactions between RA and BNF, and the QTLs identified here could be used for breeding new soybean varieties with higher yields through optimization of RA traits and BNF capacity.

Temperature, nutrients, and salinity are among the important factors constraining the distribution and abundance of microorganisms in the ocean. Marine Group II (MGII) belonging to Euryarchaeota commonly dominates the planktonic archaeal community in shallow water and Marine Group I (MGI, now is called Thaumarchaeota) in deeper water in global oceans. Results of quantitative PCR (qPCR) and 454 sequencing in our study, however, showed the dominance of MGII in planktonic archaea throughout the water column of the northeastern South China Sea (SCS) that is characterized by strong water mixing. The abundance of ammonia-oxidizing archaea (AOA) representing the main group of Thaumarchaeota in deeper water in the northeastern SCS was significantly lower than in other oceanic regions. Phylogenetic analysis showed that the top operational taxonomic units (OTUs) of the MGII occurring predominantly below 200 m depth may be unique in the northeastern SCS based on the observation that they are distantly related to known sequences (identity ranging from 90–94%). The abundance of MGII was also significantly correlated with total bacteria in the whole column, which may indicate that MGII and bacteria may have similar physiological or biochemical properties or responses to environmental variation. This study provides valuable information about the dominance of MGII over AOA in both shallow and deep water in the northeastern SCS and highlights the need for comprehensive studies integrating physical, chemical, and microbial oceanography.

Introduction: Genomic selection (GS) is a potential breeding approach for soybean improvement. Methods: In this study, GS was performed on soybean protein and oil content using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) based on 1,007 soybean accessions. The SoySNP50K SNP dataset of the accessions was obtained from the USDA-ARS, Beltsville, MD lab, and the protein and oil content of the accessions were obtained from GRIN. Results: Our results showed that the prediction accuracy of oil content was higher than that of protein content. When the training population size was 100, the prediction accuracies for protein content and oil content were 0.60 and 0.79, respectively. The prediction accuracy increased with the size of the training population. Training populations with similar phenotype or with close genetic relationships to the prediction population exhibited better prediction accuracy. A greatest prediction accuracy for both protein and oil content was observed when approximately 3,000 markers with -log10(P) greater than 1 were included. Discussion: This information will help improve GS efficiency and facilitate the application of GS. [ABSTRACT FROM AUTHOR]