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It has long been believed that most female mammalian species lose the ability to generate oocytes in postnatal ovaries. Recent evidence has demonstrated the isolation and culture of female germline stem cells (FGSCs) from adult mice and humans. However, the process and mechanisms of FGSC differentiation in vivo following transplantation have not yet been studied. Here, we isolated and characterized FGSCs from a single EGFP-transgenic mouse, and traced the development and behavior of transplanted FGSCs (F-TFs) in vivo. Comparisons of folliculogenesis between recipients with FGSC transplantation and wild-type (WT) mice were performed by single follicle RNA-sequencing (RNA-seq). Results showed that FGSCs exhibited a homing ability and began to differentiate into early-stage oocytes only when they reached the edge of the ovarian cortex. The F-TFs restored function of premature ovarian failure (gdf9iCre; PtenloxP/loxP genotype) and generated offspring. Furthermore, results demonstrated that the developmental mechanisms of follicles derived from F-TFs were similar to that of WT follicles. Weighted gene co-expression network analysis identified two potential sub-networks and core genes that played a critical role in follicular development. These findings provide a theoretical basis and lay a technology platform for specific or personalized medical treatment of ovarian failure or other ovarian diseases. Wu et al. isolated and characterized female germline stem cells (FGSCs) from a single EGFP-transgenic mouse and traced the development and behavior of transplanted FGSCs (F-TFs) in vivo. The F-TFs exhibited homing and began to differentiate into early-stage oocytes when they reached the edge of the ovarian cortex. The F-TFs restored function of mouse ovaries exhibiting premature ovarian failure and generated offspring, suggesting a possible strategy to treat ovarian failure or other ovarian diseases.

Tea aroma is a key indicator for evaluating tea quality. Although notable success in tea aroma improvement has been achieved with heterosis breeding technology, the molecular basis underlying heterosis remains largely unexplored. Thus, the present report studies the tea plant volatile heterosis using a high-throughput next-generation RNA-seq strategy and gas chromatography–mass spectrometry. Phenotypically, we found higher terpenoid volatile and green leaf volatile contents by gas chromatography–mass spectrometry in the F1 hybrids than in their parental lines. Volatile heterosis was obvious in both F1 hybrids. At the molecular level, the comparative transcriptomics analysis revealed that approximately 41% (9027 of 21,995) of the genes showed non-additive expression, whereas only 7.83% (1723 of 21,995) showed additive expression. Among the non-additive genes, 42.1% showed high parental dominance and 17.6% showed over-dominance. Among different expression genes with high parental dominance and over-dominance expression patterns, KEGG and GO analyses found that plant hormone signal transduction, tea plant physiological process related pathways and most pathways associated with tea tree volatiles were enriched. In addition, we identified multiple genes (CsDXS, CsAATC2, CsSPLA2, etc.) and transcription factors (CsMYB1, CsbHLH79, CsWRKY40, etc.) that played important roles in tea volatile heterosis. Based on transcriptome and metabolite profiling, we conclude that non-additive action plays a major role in tea volatile heterosis. Genes and transcription factors involved in tea volatiles showing over-dominance expression patterns can be considered candidate genes and provide novel clues for breeding high-volatile tea varieties.

Garlic has the charisma of a potent remedy and holds its repute of a therapeutic panacea since the dawn of civilization. An integrated approach was adopted to evaluate the genetic diversity among Chinese garlic cultivars for their antifungal potency as well as allicin content distribution and, furthermore; a bioassay was performed to study the bio-stimulation mechanism of aqueous garlic extracts (AGE) in the growth and physiology of cucumber (Cucumis sativus). Initially, 28 garlic cultivars were evaluated against four kinds of phytopathogenic fungi; Fusarium oxysporum, Botrytis cinerea, Verticillium dahliae and Phytophthora capsici, respectively. A capricious antifungal potential among the selected garlic cultivars was observed. HPLC fingerprinting and quantification confirmed diversity in allicin abundance among the selected cultivars. Cultivar G025, G064, and G074 had the highest allicin content of 3.98, 3.7, and 3.66 mg g(-1), respectively, whereas G110 was found to have lowest allicin content of 0.66 mg g(-1). Cluster analysis revealed three groups on the basis of antifungal activity and allicin content among the garlic cultivars. Cultivar G025, G2011-4, and G110 were further evaluated to authenticate the findings through different solvents and shelf life duration and G025 had the strongest antifungal activity in all conditions. minimum inhibitory concentration and minimum fungicidal concentration of Allicin aqueous standard (AAS) and AGE showed significant role of allicin as primary antifungal substance of AGE. Leaf disk bioassay against P. capsici and V. dahliae to comparatively study direct action of AGE and AAS during infection process employing eggplant and pepper leaves showed a significant reduction in infection percentage. To study the bioactivity of AGE, a bioassay was performed using cucumber seedlings and results revealed that AGE is biologically active inside cucumber seedlings and alters the defense mechanism of the plant probably activating reactive oxygen species at mild concentrations. However, at higher concentrations, it might cause lipid peroxidation and membrane damage which temper the growth of cucumber seedlings. At the outcome of the study, an argument is advanced that current research findings provide bases for cultivar selection in antifungal effectivity as well as genetic variability of the cultivars. Allicin containing AGE can be used in specialized horticultural situations such as plastic tunnel and organic farming as a bio-stimulant to enhance cucumber growth and attenuate fungal degradation of agricultural produce.

Tea plants (Camellia sinensis) are commercially cultivated in >60 countries, and their fresh leaves are processed into tea, which is the most widely consumed beverage in the world. Although several chromosome-level tea plant genomes have been published, they collapsed the two haplotypes and ignored a large number of allelic variations that may underlie important biological functions in this species. Here, we present a phased chromosome-scale assembly for an elite oolong tea cultivar, “Huangdan”, that is well known for its high levels of aroma. Based on the two sets of haplotype genome data, we identified numerous genetic variations and a substantial proportion of allelic imbalance related to important traits, including aroma- and stress-related alleles. Comparative genomics revealed extensive structural variations as well as expansion of some gene families, such as terpene synthases (TPSs), that likely contribute to the high-aroma characteristics of the backbone parent, underlying the molecular basis for the biosynthesis of aroma-related chemicals in oolong tea. Our results uncovered the genetic basis of special features of this oolong tea cultivar, providing fundamental genomic resources to study evolution and domestication for the economically important tea crop.

Coronary heart disease (CHD) and type 2 diabetes mellitus (T2DM) frequently coexist, significantly elevating the risk of adverse cardiovascular outcomes and mortality. The C-reactive protein-triglyceride-glucose index (CTI), a novel composite marker reflecting both inflammation and insulin resistance, has been associated with poor prognosis in various populations. However, its relationship with all-cause and cardiovascular mortality in patients with coexisting CHD and T2DM remains unclear. Data were obtained from 759 adults with both CHD and T2DM enrolled in the National Health and Nutrition Examination Survey (NHANES) 1999–2010 cycles, with mortality follow-up through December 31, 2019. CTI was calculated and categorized into quartiles. Kaplan-Meier survival analysis, multivariable Cox proportional hazards models, and restricted cubic spline (RCS) analyses were performed to assess the association between CTI levels and risks of all-cause and cardiovascular mortality. Pearson correlation analyses were conducted to evaluate the associations between CTI and key metabolic and inflammatory markers. Subgroup analyses were performed to assess the robustness and consistency of the associations across different clinical strata. During a median follow-up of 109 months, 520 all-cause deaths and 213 cardiovascular deaths were recorded. Higher CTI levels were independently associated with increased risks of both all-cause (HR: 1.68; 95%CI: 1.47–1.92) and cardiovascular mortality (HR: 1.70; 95%CI: 1.38–2.10) after full adjustment ( P for trend < 0.001). RCS analysis confirmed a linear dose-response relationship. The association was consistent across subgroups, with stronger effects observed in patients with HbA1c < 7%. CTI also showed significant correlations with multiple metabolic and inflammatory markers.nteraction analyses further revealed that the association between CTI and all-cause mortality was more pronounced in younger individuals ( P for interaction = 0.012), while no significant effect modification was observed across cardiovascular-kidney-metabolic stages or frailty status. Findings remained robust in survey-weighted analyses, and CTI also showed strong correlations with a range of metabolic and inflammatory biomarkers, supporting its integrative prognostic utility. Elevated CTI is independently associated with higher all-cause and cardiovascular mortality risks in patients with CHD and T2DM. CTI may serve as a valuable biomarker for risk stratification in this high-risk population. Further studies are warranted to validate its clinical utility.

Reconstruction of man-made scenes from multi-view images is an important problem in computer vision and computer graphics. Observing that man-made scenes are usually composed of planar surfaces, we encode plane shape prior in reconstructing man-made scenes. Recent approaches for single-view reconstruction employ multi-branch neural networks to simultaneously segment planes and recover 3D plane parameters. However, the scale of available annotated data heavily limits the generalizability and accuracy of these supervised methods. In this paper, we propose multi-view regularization to enhance the capability of piecewise planar reconstruction during the training phase, without demanding extra annotated data. Our multi-view regularization enables the consistency among multiple views by making the feature embedding more robust against view change and lighting variations. Thus, the neural network trained by multi-view regularization performs better on a wide range of views and lightings in the test phase. Based on more consistent prediction results, we merge the recovered models from multiple views to reconstruct scenes. Our approach achieves state-of-the-art reconstruction performance compared to previous approaches on the public ScanNet dataset.

Mitotic anaphase onset is a key cellular process tightly regulated by multiple kinases. The involvement of mitogen-activated protein kinases (MAPKs) in this process has been established in Xenopus egg extracts. However, the detailed regulatory cascade remains elusive, and it is also unknown whether the MAPK-dependent mitotic regulation is evolutionarily conserved in the single-cell eukaryotic organisms such as fission yeast ( Schizosaccharomyces pombe ). Here, we show that two MAPKs in S. pombe indeed act in concert to restrain anaphase-promoting complex/cyclosome (APC/C) activity upon activation of the spindle assembly checkpoint (SAC). One MAPK, Pmk1, binds to and phosphorylates Slp1 Cdc20 , the co-activator of APC/C. Phosphorylation of Slp1 Cdc20 by Pmk1, but not by Cdk1, promotes its subsequent ubiquitylation and degradation. Intriguingly, Pmk1-mediated phosphorylation event is also required to sustain SAC under environmental stress. Thus, our study establishes a new underlying molecular mechanism of negative regulation of APC/C by MAPK upon stress stimuli, and provides a previously unappreciated framework for regulation of anaphase entry in eukaryotic cells.

Plants have evolved regulatory mechanisms at multiple levels to regulate gene expression in order to improve their cold adaptability. However, limited information is available regarding the stress response at the chromatin and translational levels. Here, we characterize the chromatin accessibility, transcriptional, and translational landscapes of tea plants in vivo under chilling stress for the first time. Chilling stress significantly affected both the transcription and translation levels as well as the translation efficiency of tea plants. A total of 3010 genes that underwent rapid and independent translation under chilling stress were observed, and they were significantly enriched in the photosynthesis-antenna protein and phenylpropanoid biosynthesis pathways. A set of genes that were significantly responsive to cold at the transcription and translation levels, including four (+)-neomenthol dehydrogenases (MNDs) and two (E)-nerolidol synthases (NESs) arranged in tandem on the chromosomes, were also found. We detected potential upstream open reading frames (uORFs) on 3082 genes and found that tea plants may inhibit the overall expression of genes by enhancing the translation of uORFs under chilling stress. In addition, we identified distal transposase hypersensitive sites (THSs) and proximal THSs and constructed a transcriptional regulatory network for tea plants under chilling stress. We also identified 13 high-confidence transcription factors (TFs) that may play a crucial role in cold regulation. These results provide valuable information regarding the potential transcriptional regulatory network in plants and help to clarify how plants exhibit flexible responses to chilling stress.

Alzheimer’s disease (AD) is a great challenge for the world and hardly to be cured, partly because of the lack of animal models that fully mimic pathological progress. Recently, a rat model exhibiting the most pathological symptoms of AD has been reported. However, high-resolution imaging and accurate quantification of beta-amyloid (Aβ) plaques in the whole rat brain have not been fulfilled due to substantial technical challenges. In this paper, a high-efficiency data analysis pipeline is proposed to quantify Aβ plaques in whole rat brain through several terabytes of image data acquired by a high-speed volumetric imaging approach we have developed previously. A novel segmentation framework applying a high-performance weakly supervised learning method which can dramatically reduce the human labeling consumption is described in this study. The effectiveness of our segmentation framework is validated with different metrics. The segmented Aβ plaques were mapped to a standard rat brain atlas for quantitative analysis of the Aβ distribution in each brain area. This pipeline may also be applied to the segmentation and accurate quantification of other non-specific morphology objects.