Dissecting the Genetic Basis of Yield Traits and Validation of a Novel Quantitative Trait Locus for Grain Width and Weight in Rice.

Grain yield in rice is a complex trait and it is controlled by a number of quantitative trait loci (QTL). To dissect the genetic basis of rice yield, QTL analysis for nine yield traits was performed using an F2 population containing 190 plants, which was developed from a cross between Youyidao (YYD) and Sanfenhe (SFH), and each plant in the population evaluated with respect to nine yield traits. In this study, the correlations among the nine yield traits were analyzed. The grain yield per plant positively correlated with six yield traits, except for grain length and grain width, and showed the highest correlation coefficient of 0.98 with the number of filled grains per plant. A genetic map containing 133 DNA markers was constructed and it spanned 1831.7 cM throughout 12 chromosomes. A total of 36 QTLs for the yield traits were detected on nine chromosomes, except for the remaining chromosomes 5, 8, and 9. The phenotypic variation was explained by a single QTL that ranged from 6.19% to 36.01%. Furthermore, a major QTL for grain width and weight, qGW2-1, was confirmed to be newly identified and was narrowed down to a relatively smaller interval of about ~2.94-Mb. Collectively, we detected a total of 36 QTLs for yield traits and a major QTL, qGW2-1, was confirmed to control grain weight and width, which laid the foundation for further map-based cloning and molecular design breeding in rice.

Endosymbiotic Fungal Diversity and Dynamics of the Brown Planthopper across Developmental Stages, Tissues, and Sexes Revealed Using Circular Consensus Sequencing.

Endosymbiotic fungi play an important role in the growth and development of insects. Understanding the endosymbiont communities hosted by the brown planthopper (BPH; Nilaparvata lugens Stål), the most destructive pest in rice, is a prerequisite for controlling BPH rice infestations. However, the endosymbiont diversity and dynamics of the BPH remain poorly studied. Here, we used circular consensus sequencing (CCS) to obtain 87,131 OTUs (operational taxonomic units), which annotated 730 species of endosymbiotic fungi in the various developmental stages and tissues. We found that three yeast-like symbionts (YLSs), Polycephalomyces prolificus, Ophiocordyceps heteropoda, and Hirsutella proturicola, were dominant in almost all samples, which was especially pronounced in instar nymphs 4-5, female adults, and the fat bodies of female and male adult BPH. Interestingly, honeydew as the only in vitro sample had a unique community structure. Various diversity indices might indicate the different activity of endosymbionts in these stages and tissues. The biomarkers analyzed using LEfSe suggested some special functions of samples at different developmental stages of growth and the active functions of specific tissues in different sexes. Finally, we found that the incidence of occurrence of three species of Malassezia and Fusarium sp. was higher in males than in females in all comparison groups. In summary, our study provides a comprehensive survey of symbiotic fungi in the BPH, which complements the previous research on YLSs. These results offer new theoretical insights and practical implications for novel pest management strategies to understand the BPH-microbe symbiosis and devise effective pest control strategies.

Effects of heat-killed Lactiplantibacillus plantarum TWK10 on exercise performance, fatigue, and muscle growth in healthy male adults.

Consumption of Lactiplantibacillus plantarum TWK10 (TWK10) has beneficial probiotic effects, improves exercise endurance performance, regulates body composition, and mitigates aging-related problems in mice and humans. Here, we investigated the effects of heat-killed TWK10 on exercise endurance performance, muscle weight and strength, fatigue, and body composition in a double-blind, placebo-controlled clinical trial. Thirty healthy males aged 20-40 years were assigned to the Control group or heat-killed TWK10 group (TWK10-HK) in a balanced order according to each individual's initial maximal oxygen uptake. After 6-week administration, the exercise endurance time in the TWK10-HK was significantly increased (p = 0.0028) compared with that in the Control group. The grip strength on the right and left hands of the subjects was significantly increased (p = 0.0002 and p = 0.0140, respectively) in the TWK10-HK compared with that in the Control group. Administration of heat-killed TWK10 resulted in a significant increase (p = 0.0275) in muscle weight. After 6-week administration, serum lactate, and ammonia levels were significantly lower in the TWK10-HK group than in the Control group during the exercise and recovery periods. These findings demonstrate that heat-killed TWK10 has significant potential to be used as a postbiotic for humans.

Determinants of outpatient substance use disorder treatment length-of-stay and completion: the case of a treatment program in the southeast U.S.

Successful outcomes of outpatient substance use disorder treatment result from many factors for clients-including intersections between individual characteristics, choices made, and social determinants. However, prioritizing which of these and in what combination, to address and provide support for remains an open and complex question. Therefore, we ask: What factors are associated with outpatient substance use disorder clients remaining in treatment for > 90 days and successfully completing treatment? To answer this question, we apply a virtual twins machine learning (ML) model to de-identified data for a census of clients who received outpatient substance use disorder treatment services from 2018 to 2021 from one treatment program in the Southeast U.S. We find that primary predictors of outcome success are: (1) attending self-help groups while in treatment, and (2) setting goals for treatment. Secondary predictors are: (1) being linked to a primary care provider (PCP) during treatment, (2) being linked to supplemental nutrition assistance program (SNAP), and (3) attending 6 or more self-help group sessions during treatment. These findings can help treatment programs guide client choice making and help set priorities for social determinant support. Further, the ML method applied can explain intersections between individual and social predictors, as well as outcome heterogeneity associated with subgroup differences.

Bayesian multitask learning for medicine recommendation based on online patient reviews.

MOTIVATION: We propose a drug recommendation model that integrates information from both structured data (patient demographic information) and unstructured texts (patient reviews). It is based on multitask learning to predict review ratings of several satisfaction-related measures for a given medicine, where related tasks can learn from each other for prediction. The learned models can then be applied to new patients for drug recommendation. This is fundamentally different from most recommender systems in e-commerce, which do not work well for new customers (referred to as the cold-start problem). To extract information from review texts, we employ both topic modeling and sentiment analysis. We further incorporate variable selection into the model via Bayesian LASSO, which aims to filter out irrelevant features. To our best knowledge, this is the first Bayesian multitask learning method for ordinal responses. We are also the first to apply multitask learning to medicine recommendation. The sample code and data are made available at GitHub: https://github.com/thrushcyc-github/BMull. RESULTS: We evaluate the proposed method on two sets of drug reviews involving 17 depression/high blood pressure-related drugs. Overall, our method performs better than existing benchmark methods in terms of accuracy and AUC (area under the receiver operating characteristic curve). It is effective even with a small sample size and only a few available features, and more robust to possible noninformative covariates. Due to our model explainability, insights generated from our model may work as a useful reference for doctors. In practice, however, a final decision should be carefully made by combining the information from the proposed recommender with doctors' domain knowledge and past experience. AVAILABILITY AND IMPLEMENTATION: The sample code and data are publicly available at GitHub: https://github.com/thrushcyc-github/BMull.

Examining Physical Wellness as the Fundamental Element for Achieving Holistic Well-Being in Older Persons: Review of Literature and Practical Application in Daily Life.

This review examines the impact of physical activity, nutrition, and sleep evaluations on the physical wellness (PW) and overall well-being of older individuals. A comprehensive search was conducted in databases like PubMed, Google Scholar, and EBSCO Information Services. The search spanned from January 2000 to December 2022, resulting in 19,400 articles, out of which 98 review articles met the inclusion criteria. Through the analysis of these articles, key characteristics of the literature were summarized, and opportunities to enhance the practical application of physical activity (PA), nutrition, and sleep evaluations in the daily lives of older persons were identified. Regular physical activity is crucial for older persons to maintain their physical, mental, and emotional well-being and prevent age-related health issues. Older persons have specific nutritional needs, including increased protein, vitamin D, calcium, and vitamin B12 intake. Poor sleep quality in older persons is associated with negative health outcomes such as cognitive decline, physical disability, and mortality. This review emphasizes the significance of considering physical wellness as a fundamental element for achieving holistic well-being in older persons and highlights the importance of physical activity, nutrition, and sleep evaluations in improving their overall health and well-being. By understanding and implementing these findings, we can enhance the quality of life and promote healthy aging in older persons.

Different Impacts of Heat-Killed and Viable Lactiplantibacillus plantarum TWK10 on Exercise Performance, Fatigue, Body Composition, and Gut Microbiota in Humans.

Lactiplantibacillus plantarum TWK10, a probiotic strain, has been demonstrated to improve exercise performance, regulate body composition, and ameliorate age-related declines. Here, we performed a comparative analysis of viable and heat-killed TWK10 in the regulation of exercise performance, body composition, and gut microbiota in humans. Healthy adults (n = 53) were randomly divided into three groups: Control, TWK10 (viable TWK10, 3 × 1011 colony forming units/day), and TWK10-hk (heat-killed TWK10, 3 × 1011 cells/day) groups. After six-week administration, both the TWK10 and TWK10-hk groups had significantly improved exercise performance and fatigue-associated features and reduced exercise-induced inflammation, compared with controls. Viable TWK10 significantly promoted improved body composition, by increasing muscle mass proportion and reducing fat mass. Gut microbiota analysis demonstrated significantly increasing trends in the relative abundances of Akkermansiaceae and Prevotellaceae in subjects receiving viable TWK10. Predictive metagenomic profiling revealed that heat-killed TWK10 administration significantly enhanced the signaling pathways involved in amino acid metabolisms, while glutathione metabolism, and ubiquinone and other terpenoid-quinone biosynthesis pathways were enriched by viable TWK10. In conclusion, viable and heat-killed TWK10 had similar effects in improving exercise performance and attenuating exercise-induced inflammatory responses as probiotics and postbiotics, respectively. Viable TWK10 was also highly effective in regulating body composition. The differences in efficacy between viable and heat-killed TWK10 may be due to differential impacts in shaping gut microbiota.

Use of machine learning to examine disparities in completion of substance use disorder treatment.

The objective of this work is to examine disparities in the completion of substance use disorder treatment in the U.S. Our data is from the Treatment Episode Dataset Discharge (TEDS-D) datasets from the U.S. Substance Abuse and Mental Health Services Administration (SAMHSA) for 2017-2019. We apply a two-stage virtual twins model (random forest + decision tree) where, in the first stage (random forest), we determine differences in treatment completion probability associated with race/ethnicity, income source, no co-occurrence of mental health disorders, gender (biological), no health insurance, veteran status, age, and primary substance (alcohol or opioid). In the second stage (decision tree), we identify subgroups associated with probability differences, where such subgroups are more or less likely to complete treatment. We find the subgroups most likely to complete substance use disorder treatment, when the subgroup represents more than 1% of the sample, are those with no mental health condition co-occurrence (4.8% more likely when discharged from an ambulatory outpatient treatment program, representing 62% of the sample; and 10% more likely for one of the more specifically defined subgroups representing 10% of the sample), an income source of job-related wages/salary (4.3% more likely when not having used in the 30 days primary to discharge and when primary substance is not alcohol only, representing 28% of the sample), and white non-Hispanics (2.7% more likely when discharged from residential long-term treatment, representing 9% of the sample). Important implications are that: 1) those without a co-occurring mental health condition are the most likely to complete treatment, 2) those with job related wages or income are more likely to complete treatment, and 3) racial/ethnicity disparities persist in favor of white non-Hispanic individuals seeking to complete treatment. Thus, additional resources may be needed to combat such disparities.

Persistent TLR4 Activation Promotes Hepatocellular Carcinoma Growth through Positive Feedback Regulation by LIN28A/Let-7g miRNA.

Chronic inflammation caused by liver damage or infection plays an important role in the development and progression of hepatocellular carcinoma (HCC). The activation of Toll-like receptors 4 (TLR4) is involved in HCC tumorigenesis. Moreover, high TLR4 expression in HCC has been linked to poor prognosis. Although the expression of TLR4 in HCC is relatively low compared to hematopoietic cells, it is important to explore the molecular mechanism leading to the elevation of TLR4 in HCC. In this study, we aimed to investigate the positive regulating loop for TLR4 expression in HCC in response to chronic inflammation. Our results confirm that the mRNA expression of TLR4 and proinflammatory cytokines, including interleukin 6 (IL6) and C-C motif chemokine ligand 2 (CCL2), positively correlate in human HCC samples. High TLR4 expression in HCC is more susceptible to lipopolysaccharide (LPS); TLR4 activation in HCC provides growth and survival advantages and thus promotes tumorigenesis. It has been shown that the LIN28/let-7 microRNA (miRNA) axis is a downstream effector of the TLR4 signal pathway, and let-7 miRNA is a potential post-transcriptional regulator for TLR4. Thus, we investigated the correlation between TLR4 and LIN28A mRNA and let-7g miRNA in HCC clinical samples and found that the expression of TLR4 was positively correlated with LIN28A and negatively correlated with let-7g miRNA. Moreover, by culturing PLC/PRF5 (PLC5) HCC cells in low-dose LPS-containing medium to mimic chronic inflammation for persistent TLR4 activation, the mRNA and protein levels of TLR4 and LIN28A were elevated, and let-7g miRNA was decreased. Furthermore, the 3' untranslated region (3'UTR) of TLR4 mRNA was shown to be the target of let-7g miRNA, suggesting that inhibition of let-7g miRNA is able to increase TLR4 mRNA. While parental PLC5 cells have a low susceptibility to LPS-induced cell growth, long-term LPS exposure for PLC5 cells leads to increased proliferation, cytokine expression and stemness properties. In conclusion, our studies demonstrate positive feedback regulation for chronic TLR4 activation in the modulation of TLR4 expression level through the LIN28A/let-7g pathway in HCC and suggest a connection between chronic inflammation and TLR4 expression level in HCC for promoting tumorigenesis.

Intrinsic antiviral immunity of barrier cells revealed by an iPSC-derived blood-brain barrier cellular model.

Physiological blood-tissue barriers play a critical role in separating the circulation from immune-privileged sites and denying access to blood-borne viruses. The mechanism of virus restriction by these barriers is poorly understood. We utilize induced pluripotent stem cell (iPSC)-derived human brain microvascular endothelial cells (iBMECs) to study virus-blood-brain barrier (BBB) interactions. These iPSC-derived cells faithfully recapitulate a striking difference in in vivo neuroinvasion by two alphavirus isolates and are selectively permissive to neurotropic flaviviruses. A model of cocultured iBMECs and astrocytes exhibits high transendothelial electrical resistance and blocks non-neurotropic flaviviruses from getting across the barrier. We find that iBMECs constitutively express an interferon-induced gene, IFITM1, which preferentially restricts the replication of non-neurotropic flaviviruses. Barrier cells from blood-testis and blood-retinal barriers also constitutively express IFITMs that contribute to the viral resistance. Our application of a renewable human iPSC-based model for studying virus-BBB interactions reveals that intrinsic immunity at the barriers contributes to virus exclusion.

Consumer perceptions of telehealth for mental health or substance abuse: a Twitter-based topic modeling analysis.

Objective: The objective of this study is to understand the primary topics of consumer discussion on Twitter associated with telehealth for mental health or substance abuse for prepandemic versus during-pandemic time-periods, using a state-of-the-art machine learning (ML) natural language processing (NLP) method. Materials and Methods: The primary methodological phases of this project were: (1) collecting, cleaning, and filtering data (tweets) from January 2014 to June 2021, (2) describing the final corpus, (3) running and optimizing Bidirectional Encoder Representations from Transformers (BERT; using BERTopic in Python) models, and (4) human refinement of topic model results and thematic classification of topics. Results: The number of tweets in this context increased by 4 times during the pandemic (2017 tweets prepandemic vs 8672 tweets during the pandemic). During the pandemic topics were more frequently mental health related than substance abuse related. Top during-pandemic topics were therapy, suicide, pain (associated with burnout and drinking), and mental health diagnoses such as ADHD and autism. Anxiety was a key topic of discussion both pre- and during the pandemic. Discussion: Telehealth for mental health and substance abuse is being discussed more frequently online, which implies growing demand. Given the topics extracted as proxies for demand, the most demand is currently for telehealth for mental health primarily, especially for children, parents, and therapy for those with anxiety or depression, and substance abuse secondarily. Conclusions: Scarce telehealth resources can be allocated more efficiently if topics of consumer discussion are included in resource allocation decision- and policy-making processes.

Transcriptome and Metabolome Profiling Reveal the Resistance Mechanisms of Rice against Brown Planthopper.

Brown planthopper (Nilaparvata lugens Stål, BPH) is one of the most destructive insects affecting rice production. To better understand the physiological mechanisms of how rice responds to BPH feeding, we analyzed BPH-induced transcriptomic and metabolic changes in leaf sheaths of both BPH-susceptible and -resistant rice varieties. Our results demonstrated that the resistant rice reduced the settling, feeding and growth of BPH. Metabolic analyses indicated that BPH infestation caused more drastic overall metabolic changes in the susceptible variety than the resistant rice. Differently accumulated metabolites (DAMs) belonging to flavonoids were downregulated in the susceptible rice but upregulated in resistant variety. Transcriptomic analyses revealed more differentially expressed genes (DEGs) in susceptible rice than resistant rice, and DEGs related to stimulus were significantly upregulated in resistant rice but downregulated in susceptible rice. Combined analyses of transcriptome and metabolome showed that many DEGs and DAMs were enriched in phenylpropane biosynthesis, flavonoid biosynthesis, and plant hormone signal transduction. We conducted correlation analyses of DEGs and DAMs in these pathways and found a high correlation between DEGs and DAMs. Then, we found that the contents of endogenous indole 3-acetic acid (IAA) in resistant rice was lower than that of susceptible rice after BPH feeding, while the salicylic acid (SA) content was the opposite. For functional analysis, an exogenous application of IAA decreased rice resistance to BPH, but the exogenous application of SA increased resistance. In addition, biochemical assessment and quantitative PCR analysis showed that the lignin content of resistant accession was constitutively higher than in susceptible accession. By adding epigallocatechin, the substrate of anthocyanidin reductase (ANR), to the artificial diet decreased the performance of BPH. We first combined a transcriptome-metabolome-wide association study (TMWAS) on rice resistance to BPH in this study. We demonstrated that rice promoted resistance to BPH by inducing epigallocatechin and decreasing IAA. These findings provided useful transcriptomic and metabolic information for understanding the rice-BPH interactions.

Telehealth Adoption and Discontinuation by US Hospitals: Results From 2 Quasi-Natural Experiments.

BACKGROUND: Prior US hospital telehealth (video visit) studies have focused on describing factors that influence telehealth adoption or performance effects for specific patient segments, hospital systems, or geographic regions. To our knowledge, a larger-scale, national-level (US) study has yet to be conducted on the causal impacts of hospital telehealth adoption as well as discontinuation. OBJECTIVE: The aim of this study is to understand the causal impact of US hospital telehealth adoption or discontinuation on hospital performance from 2016 to 2018. METHODS: We analyzed impacts of telehealth adoption or discontinuation by US hospitals on emergency department visits, total ambulatory visits (minus emergency department visits), outpatient services revenue, total facility expenses, and total hospital revenue for the 2016-2018 period. We specifically focused on performance effects for hospitals that switched from not having telehealth to adopting telehealth, or vice versa, during the 2016-2018 period, thus exploiting 2 quasi-natural experiments. We applied a difference-in-differences research design to each of the 2 main analyses. We compared hospitals that have made a telehealth change to groups of hospitals with similar characteristics that did not make a telehealth change, which established a counterfactual. To appropriately match hospitals between treatment and control groups, we applied propensity score matching. Our primary data were from the American Hospital Association Annual Survey and the Healthcare Cost Report Information System data. Several control variables were obtained from additional sources, including the Area Health Resource File and the Federal Communications Commission. RESULTS: We found that telehealth adoption by US hospitals during the 2016-2018 period resulted in, on average, an increased number of total ambulatory visits (P=.008), increased total facility expenses (P<.001), and increased hospital revenue (P=.004) compared with the control group. We found that telehealth discontinuation during the same period resulted in, on average, decreased outpatient services revenue (P=.02) compared with the control group. CONCLUSIONS: Our findings suggest that telehealth adoption increases use but has mixed impacts on performance, given that cost and revenue increase. However, once telehealth is offered, removing it can have a negative impact on performance, implying that returning to prior performance levels, if telehealth is removed, may be challenging.

Detection of QTLs for panicle-related traits using an indica × japonica recombinant inbred line population in rice.

BACKGROUND: The panicle is the most important organ in rice, and all the panicle-related traits are correlated with rice grain yield. Understanding the underlying genetic mechanisms controlling panicle development is very important for improving rice production. METHODS: Nine panicle-related traits including heading date, panicle length, number of primary branches, number of secondary branches, number of grains per panicle, number of panicles per plant, number of filled grains per plant, seed-setting rate, and grain yield per plant were investigated. To map the quantitative trait loci (QTLs) for the nine panicle-related traits, a PCR-based genetic map with 208 markers (including 121 simple sequence repeats and 87 InDels) and a high-density linkage map with 18,194 single nucleotide polymorphism (SNP) markers were both used. RESULTS: Using a recombinant inbred line population derived from an indica variety Huanghuazhan and a japonica line Jizi 1560, a total of 110 and 112 QTLs were detected for panicle-related traits by PCR-based genetic map and by high-density linkage map, respectively. Most of the QTLs were clustered on chromosomes 1, 2, 3, 6, and 7 while no QTLs were detected on chromosome 10. Almost all the QTLs with LOD values of more than 5.0 were repeatedly detected, indicating the accuracy of the two methods and the stability of the QTL effects. No genes for panicle-related traits have been previously reported in most of these regions. QTLs found in JD1006-JD1007 and RM1148-RM5556 with high LOD and additive values deserved further research. The results of this study are beneficial for marker-assisted breeding and provide research foundation for further fine-mapping and cloning of these QTLs for panicle-related traits.

Coordination of Zika Virus Infection and Viroplasm Organization by Microtubules and Microtubule-Organizing Centers.

Zika virus (ZIKV) became a global health concern in 2016 due to its links to congenital microcephaly and other birth defects. Flaviviruses, including ZIKV, reorganize the endoplasmic reticulum (ER) to form a viroplasm, a compartment where virus particles are assembled. Microtubules (MTs) and microtubule-organizing centers (MTOCs) coordinate structural and trafficking functions in the cell, and MTs also support replication of flaviviruses. Here we investigated the roles of MTs and the cell's MTOCs on ZIKV viroplasm organization and virus production. We show that a toroidal-shaped viroplasm forms upon ZIKV infection, and MTs are organized at the viroplasm core and surrounding the viroplasm. We show that MTs are necessary for viroplasm organization and impact infectious virus production. In addition, the centrosome and the Golgi MTOC are closely associated with the viroplasm, and the centrosome coordinates the organization of the ZIKV viroplasm toroidal structure. Surprisingly, viroplasm formation and virus production are not significantly impaired when infected cells have no centrosomes and impaired Golgi MTOC, and we show that MTs are anchored to the viroplasm surface in these cells. We propose that the viroplasm is a site of MT organization, and the MTs organized at the viroplasm are sufficient for efficient virus production.

Exercise Dosage in Reducing the Risk of Dementia Development: Mode, Duration, and Intensity-A Narrative Review.

Senile dementia, also known as dementia, is the mental deterioration which is associated with aging. It is characterized by a decrease in cognitive abilities, inability to concentrate, and especially the loss of higher cerebral cortex function, including memory, judgment, abstract thinking, and other loss of personality, even behavior changes. As a matter of fact, dementia is the deterioration of mental and intellectual functions caused by brain diseases in adults when they are mature, which affects the comprehensive performance of life and work ability. Most dementia cases are caused by Alzheimer's disease (AD) and multiple infarct dementia (vascular dementia, multi-infarct dementia). Alzheimer's disease is characterized by atrophy, shedding, and degenerative alterations in brain cells, and its occurrence is linked to age. The fraction of the population with dementia is smaller before the age of 65, and it increases after the age of 65. Since women live longer than men, the proportion of women with Alzheimer's disease is higher. Multiple infarct dementia is caused by a cerebral infarction, which disrupts blood supply in multiple locations and impairs cerebral cortex function. Researchers worldwide are investigating ways to prevent Alzheimer's disease; however, currently, there are no definitive answers for Alzheimer's prevention. Even so, research has shown that we can take steps to reduce the risk of developing it. Prospective studies have found that even light to moderate physical activity can lower the risk of dementia and Alzheimer's disease. Exercise has been proposed as a potential lifestyle intervention to help reduce the occurrence of dementia and Alzheimer's disease. Various workout modes will be introduced based on various physical conditions. In general, frequent exercise for 6-8 weeks lessens the risk of dementia development.

Verification and dissection of one quantitative trait locus for grain size and weight on chromosome 1 in rice.

Grain size and weight are the key traits determining rice quality and yield and are mainly controlled by quantitative trait loci (QTL). In this study, one minor QTL that was previously mapped in the marker interval of JD1009-JD1019 using the Huanghuazhan/Jizi1560 (HHZ/JZ1560) recombinant inbred line (RIL) population, qTGW1-2, was validated to regulate grain size and weight across four rice-growing seasons using twenty-one near isogenic line (NIL)-F2 populations. The twenty-one populations were in two types of genetic background that were derived from the same parents HHZ and JZ1560. Twelve F9, F10 or F11 NIL-F2 populations with the sequential residual heterozygous regions covering JD1009-RM6840 were developed from one residual heterozygote (RH) in the HHZ/JZ1560 RIL population, and the remaining nine BC3F3, BC3F4 or BC3F5 NIL-F2 populations with the sequential residual heterozygous regions covering JD1009-RM6840 were constructed through consecutive backcrosses to the recurrent parent HHZ followed with marker assistant selection in each generation. Based on the QTL analysis of these genetic populations, qTGW1-2 was successfully confirmed to control grain length, width and weight and further dissected into two QTLs, qTGW1-2a and qTGW1-2b, which were respectively narrowed down to the marker intervals of JD1139-JD1127 (~ 978.2-kb) and JD1121-JD1102 (~ 54.8-kb). Furthermore, the two types of NIL-F2 populations were proved to be able to decrease the genetic background noise and increase the detection power of minor QTL. These results provided an important basis for further map-based cloning and molecular design breeding with the two QTLs in rice.

Supervised t-distributed stochastic neighbor embedding for data visualization and classification.

We propose a novel supervised dimension reduction method, called supervised t-distributed stochastic neighbor embedding (St-SNE), which achieves dimension reduction by preserving the similarities of data points in both feature and outcome spaces. The proposed method can be used for both prediction and visualization tasks, with the ability to handle high-dimensional data. We show through a variety of datasets that when compared with a comprehensive list of existing methods, St-SNE has superior prediction performance in the ultra-high dimensional setting where the number of features p exceeds the sample size n, and has competitive performance in the p ≤ n setting. We also show that St-SNE is a competitive visualization tool that is capable of capturing within cluster variations. In addition, we propose a penalized Kullback-Leibler divergence criterion to automatically select the reduced dimension size k for St-SNE.

Posttranslational Modification of Waxy to Genetically Improve Starch Quality in Rice Grain.

The waxy (Wx) gene, encoding the granule-bound starch synthase (GBSS), is responsible for amylose biosynthesis and plays a crucial role in defining eating and cooking quality. The waxy locus controls both the non-waxy and waxy rice phenotypes. Rice starch can be altered into various forms by either reducing or increasing the amylose content, depending on consumer preference and region. Low-amylose rice is preferred by consumers because of its softness and sticky appearance. A better way of improving crops other than downregulation and overexpression of a gene or genes may be achieved through the posttranslational modification of sites or regulatory enzymes that regulate them because of their significance. The impact of posttranslational GBSSI modifications on extra-long unit chains (ELCs) remains largely unknown. Numerous studies have been reported on different crops, such as wheat, maize, and barley, but the rice starch granule proteome remains largely unknown. There is a need to improve the yield of low-amylose rice by employing posttranslational modification of Wx, since the market demand is increasing every day in order to meet the market demand for low-amylose rice in the regional area that prefers low-amylose rice, particularly in China. In this review, we have conducted an in-depth review of waxy rice, starch properties, starch biosynthesis, and posttranslational modification of waxy protein to genetically improve starch quality in rice grains.