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Protein ubiquitination is common and crucial in cellular functions, however, little is known about how deubiquitinating enzymes (DUBs) reverse regulate the ubiquitination signaling process. PPPDE family proteins are a novel class of deubiquitinating peptidases with demonstrated deubiquitination/deSUMOylating activities. In this study, we identified 10 PPPDE genes from the rice (Oryza sativa L.) genome unevenly distributed on five chromosomes, where most of these members have not been reported to date. Based on the gene structure, the OsPPPDE family consists of three distinct subgroups within the phylogenetic tree. Cis-element analysis identified light/phytohormone-responsive, development, and abiotic stress-related elements in the promoters of OsPPPDE. Furthermore, we conducted and analyzed the transcript abundance of OsPPPDE under various tissues and stresses using the transcriptome data of 352 samples from the Rice Expression Database and GEO datasets. Moreover, OsPPPDE5 showed differential regulation of its transcript abundance during Cd and drought stress. Collinearity and syntenic analysis of 101 PPPDEs and PPPDE-like proteins in 10 plant genomes indicated that this family is evolutionarily conserved. Domestication analysis suggests that OsPPPDEs may contribute to indica–japonica divergence using the data from the 3K Rice Genome Project. Our study provides a foundation for further study on the function and molecular mechanism of the OsPPPDE gene family. [ABSTRACT FROM AUTHOR]

Developing a confidence interval for the ratio of two quantities is an important task in statistics because of its omnipresence in real world applications. For such a problem, the MOVER-R (method of variance recovery for the ratio) technique, which is based on the recovery of variance estimates from confidence limits of the numerator and the denominator separately, was proposed as a useful and efficient approach. However, this method implicitly assumes that the confidence interval for the denominator never includes zero, which might be violated in practice. In this article, we first use a new framework to derive the MOVER-R confidence interval, which does not require the above assumption and covers the whole parameter space. We find that MOVER-R can produce an unbounded confidence interval, just like the well-known Fieller method. To overcome this issue, we further propose the penalized MOVER-R. We prove that the new method differs from MOVER-R only at the second order. It, however, always gives a bounded and analytic confidence interval. Through simulation studies and a real data application, we show that the penalized MOVER-R generally provides a better confidence interval than MOVER-R in terms of controlling the coverage probability and the median width. [ABSTRACT FROM AUTHOR]

Background: Group format weight loss interventions have benefits over individual format, but privacy concerns may limit their uptake. Method: In this study, adults with obesity and interest in losing weight were recruited nationally online and randomly assigned to view one of eight videos describing a hypothetical, group behavioral weight loss intervention. Based on three fully crossed factors, the videos varied on privacy features of intervention (present or not); matching participants to group based on weight loss barriers (matched or not); and intervention format (online or in-person). Participants rated their willingness to join, privacy concerns, and perceived effectiveness of these interventions. They further reported preference for individual or group format interventions and reason for preferences. Results: Description of privacy features, matching of participants, and format did not affect willingness to join, privacy concerns, or perceived effectiveness of the intervention. Privacy concerns were associated with lower willingness to join and lower perceived intervention effectiveness, and greater social anxiety and weight stigma. More participants preferred individual over group format (40.1% vs 33.9%; 26% selected neither) and preference for individual format was associated with greater privacy concerns. Conclusion: Strategies to address privacy concerns in group-based interventions warrant further attention. [ABSTRACT FROM AUTHOR]

Genome-wide association study (GWAS) is the most popular approach to dissecting complex traits in plants, humans, and animals. Numerous methods and tools have been proposed to discover the causal variants for GWAS data analysis. Among them, linear mixed models (LMMs) are widely used statistical methods for regulating confounding factors, including population structure, resulting in increased computational proficiency and statistical power in GWAS studies. Recently more attention has been paid to pleiotropy, multi-trait, gene–gene interaction, gene–environment interaction, and multi-locus methods with the growing availability of large-scale GWAS data and relevant phenotype samples. In this review, we have demonstrated all possible LMMs-based methods available in the literature for GWAS. We briefly discuss the different LMM methods, software packages, and available open-source applications in GWAS. Then, we include the advantages and weaknesses of the LMMs in GWAS. Finally, we discuss the future perspective and conclusion. The present review paper would be helpful to the researchers for selecting appropriate LMM models and methods quickly for GWAS data analysis and would benefit the scientific society. [ABSTRACT FROM AUTHOR]

Mitogen-activated protein kinase (MAPK) cascades play central roles in response to biotic and abiotic stresses. However, the mechanisms by which various MAPK members regulate the plant immune response in rice remain elusive. In this article, to characterize the mechanisms, the knock-out and overexpression mutants of OsMPK15 were constructed and the disease resistance was investigated under the various fungal and bacterial inoculations. The knock-out mutant of OsMPK15 resulted in the constitutive expression of pathogenesis-related (PR) genes, increased accumulation of reactive oxygen species (ROS) triggered by the pathogen-associated molecular pattern (PAMP) elicitor chitin, and significantly enhanced the disease resistance to different races of Magnaporthe oryzae and Xanthomonas oryzae pv. oryzae (Xoo), which cause the rice blast and bacterial blight diseases, respectively. On contrary, the expression of PR genes and ROS were down-regulated in the OsMPK15 -overexpressing (OsMPK15-OE) lines. Meanwhile, phytohormones such as salicylic acid (SA) and jasmonic acid (JA) were accumulated in the mpk15 mutant lines but decreased in the OsMPK15-OE lines. The expression of SA- and JA-pathway associated genes were significantly upregulated in the mpk15 mutant, whereas it was down regulated in the OsMPK15-OE lines. We conclude that OsMPK15 may negatively regulate the disease resistance through modulating SA- and JA-mediated signaling pathway. [ABSTRACT FROM AUTHOR]

With development of sequencing technology, dense single nucleotide polymorphisms (SNPs) have been available, enabling uncovering genetic architecture of complex traits by genome-wide association study (GWAS). However, the current GWAS strategy usually ignores epistatic and gene-environment interactions due to absence of appropriate methodology and heavy computational burden. This study proposed a new GWAS strategy by combining the graphics processing unit- (GPU-) based generalized multifactor dimensionality reduction (GMDR) algorithm with mixed linear model approach. The reliability and efficiency of the analytical methods were verified through Monte Carlo simulations, suggesting that a population size of nearly 150 recombinant inbred lines (RILs) had a reasonable resolution for the scenarios considered. Further, a GWAS was conducted with the above two-step strategy to investigate the additive, epistatic, and gene-environment associations between 701,867 SNPs and three important quality traits, gelatinization temperature, amylose content, and gel consistency, in a RIL population with 138 individuals derived from super-hybrid rice Xieyou9308 in two environments. Four significant SNPs were identified with additive, epistatic, and gene-environment interaction effects. Our study showed that the mixed linear model approach combining with the GPU-based GMDR algorithm is a feasible strategy for implementing GWAS to uncover genetic architecture of crop complex traits. [ABSTRACT FROM AUTHOR]

The generalizability of study findings may be influenced by pre-enrollment trial procedures, including the use of behavioral run-in periods. The study goals were to determine whether behavioral run-in periods and other pre-enrollment processes affect outcomes in randomized trials of behavioral weight loss interventions that have contributed to clinical guidelines. The sample was behavioral weight loss intervention trials included in the 2018 U.S. Preventive Services Task Force systematic review. Information on pre-enrollment processes (total steps, in-person steps, behavioral run-in) was abstracted, and meta-regressions were conducted in 2022 to test whether pre-enrollment processes were associated with weight loss at 6 or 12 months and trial retention at 12 months. Across 80 trials, the median number of total pre-enrollment steps was 2 (range=1–5), and that of in-person pre-enrollment steps was 1 (range=0–4). Almost one-third of the trials (k =24; 30%) used a behavioral run-in. The most common run-in tasks were self-monitoring physical activity (k =9) or both physical activity and diet (k =6). Greater weight loss was observed in trials with behavioral run-ins at 6 months (−2.33 kg; 95% CI= −3.72, −0.93) and, to an attenuated extent, at 12 months (−0.86 kg; 95% CI= −1.72, 0.01) compared to those without run-ins. The total number of pre-enrollment steps was also associated with greater 6-month weight loss (−0.85 kg; 95% CI= −1.59, −0.11). Higher retention was associated with total number of pre-enrollment steps and in-person steps and marginally with the presence of run-ins. The use of more pre-enrollment processes is associated with greater weight loss in behavioral weight loss trials and may impact the generalizability of outcomes. [ABSTRACT FROM AUTHOR]

Tobacco ( Nicotiana tabacum L.) use is the leading cause of preventable death, due to deleterious chemical components and smoke from tobacco products, and therefore reducing harmful chemical components in tobacco is one of the crucial tobacco breeding targets. However, due to complexity of tobacco smoke and unavailability of high-density genetic maps, the genetic architecture of representative hazardous smoke has not been fully dissected. The present study aimed to explore the genetic architecture of nine hazardous component traits of mainstream smoke through QTL mapping using 271 recombinant inbred lines (RILs) derived from K326 and Y3 in multiple environments. The analysis of genotype and genotype by environment interaction ( GE ) revealed substantially greater heritability over 95% contributed mostly by GE interaction effects. We also observed strong genetic correlations among most studied hazardous smoke traits, with the highest correlation coefficient of 0.84 between carbon monoxide and crotonaldehyde. Based on a published high-density genetic map, a total of 19 novel QTLs were detected for eight traits using a full QTL model, of which 17 QTLs showed significant additive effects, six showed significant additive-by-environment interaction effects, and one pair showed significant epistasis-by-environment interaction effect. Bioinformatics analysis of sequence in QTL region predicted six genes as candidates for four traits, of which Nt21g04598.1 , Nt21g04600.1 , and Nt21g04601.1 had pleiotropic effects on PHE and TAR., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. This study received funding from China National Tobacco Company, the Yunnan Academy of Tobacco Agricultural Sciences and the NSFC. The funders had the following involvement with the study: performed field trials and provided data including genotypic and phenotypic data., (Copyright © 2024 Xu, Tong, Jin, Zhang, Lin, Fang, Chen, Zhu, Lou, Xiao and Xu.)

Introduction: We describe the development and validation of a mixed-reality prostate biopsy (PBx) simulator with built-in guidance aids and real-time 3-dimensional visualization., Methods: We evaluated our simulator during one-on-one training sessions with urology residents and attendings from 2018 to 2022. Participants performed freehand, side-fire, double-sextant transrectal ultrasound-guided systematic prostate biopsy (sPBx). After a baseline assessment (first set of 12 biopsy cores), participants trained for 25 minutes with visualization and cognitive aids activated. Training was followed by an exit set of 12 biopsy cores without visualization or cognitive aids and afterward, subjective assessment by trainees of the simulator. Deviation is the shortest distance of the center of a core from its intended template location., Results: Baseline deviations (mean ± SD) for residents (n = 24) and attendings (n = 4) were 13.4 ± 8.9 mm and 8.5 ± 3.6 mm ( P < 0.001), respectively. Posttraining deviations were 8.7 ± 6.6 mm and 7.6 ± 3.7 mm ( P = 0.271), respectively. Deviations between baseline and exit were decreased significantly for residents ( P < 0.001) but not for attendings ( P = 0.093). Overall feedback from participants was positive. Confidence in performing a PBx increased in novices after training ( P = 0.011) and did not change among attendings ( P = 0.180)., Conclusions: A new PBx simulator can quantify and improve accuracy during simulated freehand sPBx while providing visualization and graphical feedback. Improved simulated sPBx accuracy could lead to more even distribution of biopsy cores within the prostate when performed in clinical settings, possibly reducing the high risk of missing an existing lesion and thus decreasing the time to initiating treatment, if indicated., Competing Interests: The authors declare no conflict of interest., (Copyright © 2023 Society for Simulation in Healthcare.)

Gene therapy is a potential treatment for Friedreich ataxia, with multiple programs on the horizon. The purpose of this study was to collect opinions about gene therapy from individuals 14 years or older with Friedreich ataxia or parents/caregivers of Friedreich ataxia patients who were diagnosed as children 17 or younger. Participants were asked to complete a survey after reading brief educational materials regarding gene therapy. Most of the patients captured in this survey have an early-onset (classical) presentation of the disease. Participants expressed urgency in participating in gene therapy clinical trials despite the associated risks. About half of the respondents believed that gene therapy would cease progression or minimize symptoms, whereas nearly one-fourth expected to be cured. The survey also revealed how participants perceive their symptom burden, because a substantial majority reported that balance/walking issues most interfere with their quality of life and would be the symptom they would prioritize treating. Although not statistically significant, more caregivers prioritized treating cardiomyopathy than patients. This study provides valuable information on priorities, beliefs, and expectations regarding gene therapy and serves to guide future gene therapy opinion studies and gene therapy trial design., Competing Interests: M.C. and B.J.B. are co-founders of AavantiBio, which supported the employee at ClinicalMind who provided graphical support for the educational material written by the study team. The survey was completed before the acquisition of AavantiBio by Solid Biosciences. None of the authors have any financial, commercial, legal, or professional relationship with Solid Biosciences. There was no commercial support for this study. The study was developed and conducted by the academic team at the University of Florida. Thus, the authors declare that they have no competing interests., (© 2023 The Author(s).)

Introduction: The management of low-risk febrile infants presents a model population for exploring how implicit racial bias promotes inequitable emergency care for children who belong to racial, ethnic and language minority groups. Although widely used clinical standards guide the clinical care of febrile infants, there remains substantial variability in management strategies. Deviations from recommended care may be informed by the physician's assessment of the family's values, risk tolerance and access to supportive resources. However, in the fast-paced emergency setting, such assessments may be influenced by implicit racial bias. Despite significant research to inform the clinical care of febrile infants, there is a dearth of knowledge regarding health disparities and clinical guideline implementation. The proposed mixed methods approach will (1) quantify the extent of disparities by race, ethnicity and language proficiency and (2) explore the role of implicit bias in physician-patient communication when caring for this population., Methods and Analysis: With 42 participating sites from the Pediatric Emergency Medicine Collaborative Research Committee, we will conduct a multicenter, cross-sectional study of low-risk febrile infants treated in the emergency department (ED) and apply multivariable logistic regression to assess the association between (1) race and ethnicity and (2) limited English proficiency with the primary outcome, discharge to home without lumbar puncture or antibiotics. We will concurrently perform an interpretive study using purposive sampling to conduct individual semistructured interviews with (1) minority parents of febrile infants and (2) paediatric ED physicians. We will triangulate or compare perspectives to better elucidate disparities and bias in communication and medical decision-making., Ethics and Dissemination: This study has been approved by the University of Florida Institutional Review Board. All participating sites in the multicenter analysis will obtain local institutional review board approval. The results of this study will be presented at academic conferences and in peer-reviewed publications., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Soil organic matter contains more carbon than global vegetation and the atmosphere combined. Gaining access to this source of organic carbon is challenging and requires at least partial removal of polyphenolic and/or soil mineral protections, followed by subsequent enzymatic or chemical cleavage of diverse plant polysaccharides. Soil-feeding animals make significant contributions to the recycling of terrestrial organic matter. Some humivorous earthworms, beetles, and termites, among others, have evolved the ability to mineralize recalcitrant soil organic matter, thereby leading to their tremendous ecological success in the (sub)tropical areas. This ability largely relies on their symbiotic associations with a diverse community of gut microbes. Recent integrative omics studies, including genomics, metagenomics, and proteomics, provide deeper insights into the functions of gut symbionts. In reviewing this literature, we emphasized that understanding how these soil-feeding fauna catabolize soil organic substrates not only reveals the key microbes in the intestinal processes but also uncovers the potential novel enzymes with considerable biotechnological interests., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lou, Zhao, Lou, Xia, Feng and Li.)

Background It is well known that white matter injuries observed at birth are associated with adverse neurodevelopmental outcomes later in life. Whether white matter developmental variations in healthy newborns are also associated with changes in later neurodevelopment remains to be established. Purpose To evaluate whether developmental variations of white matter microstructures identified by MRI correlate with neurodevelopmental outcomes in healthy full-term infants. Materials and Methods In this prospective study, pregnant women were recruited and their healthy full-term newborns underwent a brain MRI including diffusion tensor imaging at approximately 2 weeks of age. These infants were tested at approximately 2 years of age with the Bayley Scales of Infant Development (BSID). Voxel-wise correlation analyses of fractional anisotropy (FA), measured with diffusion tensor MRI, and neurodevelopmental test scores, measured by using BSID, were performed by using tract-based spatial statistics (TBSS), followed by region-of-interest (ROI) analyses of correlations between mean FA in selected white matter ROIs and each BSID subscale score. Results Thirty-eight full-term infants (20 boys, 18 girls) underwent MRI examination at 2 weeks of age (14.3 days ± 1.6) and BSID measurement at 2 years of age (732 days ± 6). TBSS analyses showed widespread clusters in major white matter tracts, with positive correlations ( P ≤ .05, corrected for the voxel-wise multiple comparisons) between FA values and multiple BSID subscale scores. These correlations were largely independent of several demographic parameters as well as family environment. Gestational age at birth appeared to be a confounding factor as TBSS-observed correlations weakened when it was included as a covariate; however, after controlling for gestational age at birth, ROI analyses still showed positive correlations ( P ≤ .05, R = 0.35 to 0.48) between mean FA in many white matter ROIs and BSID cognitive, language, and motor scores. Conclusion There were significant associations between white matter microstructure developmental variations in healthy full-term newborns and their neurodevelopmental outcomes. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Hu and McAllister in this issue.

With the development and application of super rice breeding, elite rice hybrids with super high-yielding potential have been widely developed in last decades in China. Xieyou9308 is one of the most famous super hybrid rice varieties. To uncover the genetic mechanism of Xieyou9308's high yield potential, a recombinant inbred line (RIL) population derived from cross of XieqingzaoB and Zhonghui9308 was re-sequenced and investigated on the grain yield (GYD) and its three component traits, number of panicles per plant (NP), number of filled grains per panicle (NFGP), and grain weight (GW). Unconditional and conditional genome-wide association analysis, based on a linear mixed model with epistasis and gene-environment interaction effects, were conducted, using ~0.7 million identified SNPs. There were six, four, seven, and seven QTSs identified for GYD, NP, NFGP, and GW, respectively, with accumulated explanatory heritability varying from 43.06% to 48.36%; additive by environment interactions were detected for GYD, some minor epistases were detected for NP and NFGP. Further, conditional genetic mapping analysis for GYD given its three components revealed several novel QTSs associated with yield than that were suppressed in our unconditional mapping analysis.

The seeds of flowering plants develop from double fertilization and play a vital role in reproduction and supplying human and animal food. The genetic variation of seed traits is influenced by multiple genetic systems, e.g., maternal, embryo, and/or endosperm genomes. Understanding the genetic architecture of seed traits is a major challenge because of this complex mechanism of multiple genetic systems, especially the epistasis within or between different genomes and their interactions with the environment. In this study, a statistical model was proposed for mapping QTL with epistasis and QTL-by-environment (QE) interactions underlying endosperm and embryo traits. Our model integrates the maternal and the offspring genomes into one mapping framework and can accurately analyze maternal additive and dominant effects, endosperm/embryo additive and dominant effects, and epistatic effects of two loci in the same or two different genomes, as well as interaction effects of each genetic component of QTL with environment. Intensive simulations under different sampling strategies, heritabilities, and model parameters were performed to investigate the statistical properties of the model. A set of real cottonseed data was analyzed to demonstrate our methods. A software package, QTLNetwork-Seed-1.0.exe, was developed for QTL analysis of seed traits., (Copyright © 2015 by the Genetics Society of America.)