Evolutionary divergence of duplicated genomes in newly described allotetraploid cottons.

Allotetraploid cotton (Gossypium) species represents a model system for the study of plant polyploidy, molecular evolution, and domestication. Here, chromosome-scale genome sequences were obtained and assembled for two recently described wild species of tetraploid cotton, Gossypium ekmanianum [(AD)6, Ge] and Gossypium stephensii [(AD)7, Gs], and one early form of domesticated Gossypium hirsutum, race punctatum [(AD)1, Ghp]. Based on phylogenomic analysis, we provide a dated whole-genome level perspective for the evolution of the tetraploid Gossypium clade and resolved the evolutionary relationships of Gs, Ge, and domesticated G. hirsutum. We describe genomic structural variation that arose during Gossypium evolution and describe its correlates-including phenotypic differentiation, genetic isolation, and genetic convergence-that contributed to cotton biodiversity and cotton domestication. Presence/absence variation is prominent in causing cotton genomic structural variations. A presence/absence variation-derived gene encoding a phosphopeptide-binding protein is implicated in increasing fiber length during cotton domestication. The relatively unimproved Ghp offers the potential for gene discovery related to adaptation to environmental challenges. Expanded gene families enoyl-CoA δ isomerase 3 and RAP2-7 may have contributed to abiotic stress tolerance, possibly by targeting plant hormone-associated biochemical pathways. Our results generate a genomic context for a better understanding of cotton evolution and for agriculture.

CsMYBL2 homologs modulate the light and temperature stress-regulated anthocyanin and catechins biosynthesis in tea plants (Camellia sinensis).

Anthocyanin and catechin production in tea (Camellia sinensis) leaves can positively affect tea quality; however, their regulatory mechanisms are not fully understood. Here we report that, while the CsMYB75- or CsMYB86-directed MYB-bHLH-WD40 (MBW) complexes differentially activate anthocyanin or catechin biosynthesis in tea leaves, respectively, CsMYBL2a and CsMYBL2b homologs negatively modified the light- and temperature-induced anthocyanin and catechin production in both Arabidopsis and tea plants. The MBW complexes activated both anthocyanin synthesis genes and the downstream repressor genes CsMYBL2a and CsMYBL2b. Overexpression of CsMYBL2b, but not CsMYBL2a, repressed Arabidopsis leaf anthocyanin accumulation and seed coat proanthocyanin production. CsMYBL2b strongly and CsMYBL2a weakly repressed the activating effects of CsMYB75/CsMYB86 on CsDFR and CsANS, due to their different EAR and TLLLFR domains and interactions with CsTT8/CsGL3, interfering with the functions of activating MBW complexes. CsMYBL2b and CsMYBL2a in tea leaves play different roles in fine-tuning CsMYB75/CsMYB86-MBW activation of biosynthesis of anthocyanins and catechins, respectively. The CsbZIP1-CsmiR858a-CsMYBL2 module mediated the UV-B- or cold-activated CsMYB75/CsMYB86 regulation of anthocyanin/catechin biosynthesis by repressing CsMYBL2a and CsMYBL2b. Similarly, the CsCOP1-CsbZIP1-CsPIF3 module, and BR signaling as well, mediated the high temperature repression of anthocyanin and catechin biosynthesis through differentially upregulating CsMYBL2b and CsMYBL2a, respectively. The present study provides new insights into the complex regulatory networks in environmental stress-modified flavonoid production in tea plant leaves.

Hospital-Level Variation in COVID-19 Treatment Among Hospitalized Adults in the United States: A Retrospective Cohort Study.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: To characterize variation in dexamethasone and remdesivir use over time among hospitals. BACKGROUND: Little is known about hospital-level variation in COVID-19 drug treatments in a large and diverse network in the United States. METHODS: We selected individuals hospitalized with COVID-19 across 163 hospitals between February 23, 2020 and October 31, 2021 from using the HCA CHARGE, an electronic health record repository from a network of community health care facilities in the United States. We quantified receipt of dexamethasone, remdesivir, and combined use of dexamethasone and remdesivir during the hospital stay. We used 2-level logistic regression models to determine the intraclass correlation coefficient (ICC) at the hospital level, adjusting for patient and hospital characteristics. The ICC shows the proportion of total variation in drug use accounted for by hospitals. RESULTS: Among 161,667 individuals hospitalized with COVID-19, 73.0% were treated with dexamethasone, 49.1% with remdesivir, and 45.0% with both dexamethasone and remdesivir. The proportion of variation in dexamethasone use was 12.7% (adjusted ICC: 0.127), 8.5% for remdesivir, and 11.3% for combined drug use, indicating low interhospital variation. In the fully adjusted models, between-facility variation in dexamethasone use declined from 34.1% in February-March 2020 to 11.3% in January-March 2021 and then increased to 17.3% in July-October 2021. The variation in remdesivir use remained relatively stable during the study period. CONCLUSIONS: During the first 2 years of the pandemic, there was relatively consistent use of dexamethasone and remdesivir across the hospitals examined. Consistent adoption and implementation of treatment guidelines across the hospitals examined may have led to a decrease in variation in drug usage over time.

A Bayesian semi-parametric model for learning biomarker trajectories and changepoints in the preclinical phase of Alzheimer's disease.

It has become consensus that mild cognitive impairment (MCI), one of the early symptoms onset of Alzheimer's disease (AD), may appear 10 or more years after the emergence of neuropathological abnormalities. Therefore, understanding the progression of AD biomarkers and uncovering when brain alterations begin in the preclinical stage, while patients are still cognitively normal, are crucial for effective early detection and therapeutic development. In this paper, we develop a Bayesian semiparametric framework that jointly models the longitudinal trajectory of the AD biomarker with a changepoint relative to the occurrence of symptoms onset, which is subject to left truncation and right censoring, in a heterogeneous population. Furthermore, unlike most existing methods assuming that everyone in the considered population will eventually develop the disease, our approach accounts for the possibility that some individuals may never experience MCI or AD, even after a long follow-up time. We evaluate the proposed model through simulation studies and demonstrate its clinical utility by examining an important AD biomarker, ptau181, using a dataset from the Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD) study.

Genetic Analysis of Cotton Fiber Traits in Gossypium Hybrid Lines.

Cotton plays a crucial role in the progress of the textile industry and the betterment of human life by providing natural fibers. In our study, we explored the genetic determinants of cotton architecture and fiber yield and quality by crossbreeding Gossypium hirsutum and Gossypium barbadense, creating a recombinant inbred line (RIL) population. Utilizing SNP markers, we constructed an extensive genetic map encompassing 7,730 markers over 2,784.2 cM. We appraised two architectural and seven fiber traits within six environments, identifying 58 QTLs, of which 49 demonstrated stability across these environments. These encompassed QTLs for traits such as lint percentage (LP), boll weight (BW), fiber strength (STRENGTH), seed index (SI), and micronaire (MIC), primarily located on chromosomes chr-A07, chr-D06, and chr-D07. Notably, chr-D07 houses a QTL region affecting SI, corroborated by multiple studies. Within this region, the genes BZIP043 and SEP2 were identified as pivotal, with SEP2 particularly showing augmented expression in developing ovules. These discoveries contribute significantly to marker-assisted selection, potentially elevating both the yield and quality of cotton fiber production. These findings provide valuable insights into marker-assisted breeding strategies, offering crucial information to enhance fiber yield and quality in cotton production.

Evaluation of three prediction formulas of 24-hour urinary sodium excretion in Chinese residents: a systematic review and meta-analysis.

OBJECTIVE: To determine the appropriateness of three widely used formulas estimating 24-h urinary Na (24hUNa) from spot urine samples in the Chinese population. DESIGN: Systematic review and meta-analysis. SETTING: Literature review was conducted to identify studies for estimating 24hUNa using the Kawasaki, Tanaka and INTERSALT formulas simultaneously in PubMed, Embase and the Cochrane library databases. The mean difference (MD) and correlation coefficients (r) between measures and estimates from different formulas were assessed. PARTICIPANTS: Information extraction and quality assessment were performed in thirteen studies involving 8369 subjects. RESULTS: Two studies which affected the overall robustness were excluded in the 'leave-one-out' sensitivity analyses. Within the final meta-analysis included eleven studies and 7197 participants, 36·07 mmol/d (95 %CI 16·89, 55·25) of MD was observed in the Kawasaki formula, and -19·62 mmol/d (95 %CI -37·37, -1·87) in the Tanaka formula and -35·78 mmol/d (95 %CI -50·76, -20·80) in the INTERSALT formula; a pooled r-Fisher's Z of 0·39 (95 %CI 0·32, 0·45) in the Kawasaki formula, 0·43 (95 %CI 0·37, 0·49) in the Tanaka formula and 0·36 (95 %CI 0·31, 0·42) in the INTERSALT formula. Subgroup analyses were conducted to explore the possible factors affecting the accuracy of the formula estimation from three mainly aspects: population types, Na intake levels and urine specimen types. CONCLUSIONS: The meta-analysis suggested that the Tanaka formula performed a more accurate estimate in Chinese population. Time of collecting spot urine specimens and Na intake level of the sample population might be the main factors affecting the accuracy of the formula estimation.

Genome-wide chromatin accessibility landscape and dynamics of transcription factor networks during ovule and fiber development in cotton.

BACKGROUND: The development of cotton fiber is regulated by the orchestrated binding of regulatory proteins to cis-regulatory elements associated with developmental genes. The cis-trans regulatory dynamics occurred throughout the course of cotton fiber development are elusive. Here we generated genome-wide high-resolution DNase I hypersensitive sites (DHSs) maps to understand the regulatory mechanisms of cotton ovule and fiber development. RESULTS: We generated DNase I hypersensitive site (DHS) profiles from cotton ovules at 0 and 3 days post anthesis (DPA) and fibers at 8, 12, 15, and 18 DPA. We obtained a total of 1185 million reads and identified a total of 199,351 DHSs through ~ 30% unique mapping reads. It should be noted that more than half of DNase-seq reads mapped multiple genome locations and were not analyzed in order to achieve a high specificity of peak profile and to avoid bias from repetitive genomic regions. Distinct chromatin accessibilities were observed in the ovules (0 and 3 DPA) compared to the fiber elongation stages (8, 12, 15, and 18 DPA). Besides, the chromatin accessibility during ovules was particularly elevated in genomic regions enriched with transposable elements (TEs) and genes in TE-enriched regions were involved in ovule cell division. We analyzed cis-regulatory modules and revealed the influence of hormones on fiber development from the regulatory divergence of transcription factor (TF) motifs. Finally, we constructed a reliable regulatory network of TFs related to ovule and fiber development based on chromatin accessibility and gene co-expression network. From this network, we discovered a novel TF, WRKY46, which may shape fiber development by regulating the lignin content. CONCLUSIONS: Our results not only reveal the contribution of TEs in fiber development, but also predict and validate the TFs related to fiber development, which will benefit the research of cotton fiber molecular breeding.

Blended Tea Ameliorates T2DM via Modulation of Gut Microflora.

Increasing evidences suggest that type 2 diabetes mellitus (T2DM) is closely related to gut microflora dysbiosis, which can be improved by dietary intervention. Four natural plant products, including Cyclocarya paliurus, Fu brick tea, Ampelopsis grossedentata, and Lithocarpus litseifolius, were blended to form a blended tea product for obtaining the better flavor. The blended tea was also expected to have excellent pharmacological activity. Therefore, the ameliorative effect of blended tea on T2DM and underlying mechanisms were studied in this study. The results showed that the blended tea extract effectively attenuated the symptoms of glucose and lipid metabolism-related disorders in T2DM mice fed by high-fat and high-sucrose diet. Furthermore, blended tea extract intervention significantly attenuated gut microbiota dysbiosis, the abundance of bacteria such as Bacteroidetes and Firmicutes, which aid in the hydrolysis and utilization of carbohydrates, significantly increased, while the abundance of pathogenic bacteria such as Proteobacteria significantly decreased. Certain core microorganisms involved in energy metabolism, including Ruminococcaceae_UCG-005, Butyricimonas, Roseburia, Oscillibacter, [Eubacterium]_nodatum_group, Muribaculaceae, Prevotellaceae UCG 001, were also found to be improved by blended tea extract. Collectively, our results demonstrated that the blended tea may ameliorate T2DM through modulation of gut microflora. The blended tea may serve as novel functional drink for the treatment of T2DM and dysbiosis of gut microbiota.

Functional Bayesian networks for discovering causality from multivariate functional data.

Multivariate functional data arise in a wide range of applications. One fundamental task is to understand the causal relationships among these functional objects of interest. In this paper, we develop a novel Bayesian network (BN) model for multivariate functional data where conditional independencies and causal structure are encoded by a directed acyclic graph. Specifically, we allow the functional objects to deviate from Gaussian processes, which is the key to unique causal structure identification even when the functions are measured with noises. A fully Bayesian framework is designed to infer the functional BN model with natural uncertainty quantification through posterior summaries. Simulation studies and real data examples demonstrate the practical utility of the proposed model.

Abdominal obesity and digestive system cancer: a systematic review and meta-analysis of prospective studies.

BACKGROUND: The diagnostic criteria for abdominal obesity are usually waist circumference or waist-to-hip ratio. The magnitude of the risks for cancers of the digestive system and abdominal obesity is unknown. To assess whether abdominal obesity increases the risk of digestive cancer, we conducted a systematic review and meta-analysis of prospective cohort studies in a database. METHODS: PubMed, Embase, and Web of Science databases were searched from their inception to December 2022. The 9-star Newcastle Ottawa Scale was used to assess  study quality. Pooled relative risks and 95% confidence intervals were calculated using fixed or random effect models respectively. The stability of the results was explored by one-by-one exclusion. Subgroup analysis was conducted to explore sources of heterogeneity. Publication bias was evaluated by Begg's and Egger's tests. RESULTS: A total of 43 cohort studies were included. There were 42 and 31 studies in the meta-analysis of waist circumference and waist-to-hip ratio on digestive system cancer, respectively. The results of the meta-analysis revealed that the greater waist circumference and waist-to-hip ratio were correlated with increased incidence of digestive system cancers: waist circumference: RR 1.48, 95% CI 1.38-1.59, p < 0.001; waist-to-hip ratio: RR 1.33, 95% CI 1.28-1.38, p = 0.001. Subgroup analysis by cancer type showed that higher WC and WHR would increase the prevalence of LC, PC, GC, EC, and CRC. The sensitivity analysis was conducted by a one-by-one elimination method, and the results of the meta-analysis remained stable. It is proved that the results were robust by the trim-and-fill method. CONCLUSIONS: There was evidence to suggest that abdominal obesity increased the incidence of digestive cancer, it is necessary to take appropriate measures to reduce abdominal obesity. Waist circumference and waist-to-hip ratio may be better predictors of digestive system cancers. However, the association between waist circumference and digestive system cancer was greater, so more attention should be paid to measuring abdominal obesity with waist circumference.

Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races.

Lint percentage is one of the most essential yield components and an important economic index for cotton planting. Improving lint percentage is an effective way to achieve high-yield in cotton breeding worldwide, especially upland cotton (Gossypium hirsutum L.). However, the genetic basis controlling lint percentage has not yet been systematically understood. Here, we performed a genome-wide association mapping for lint percentage using a natural population consisting of 189 G. hirsutum accessions (188 accessions of G. hirsutum races and one cultivar TM-1). The results showed that 274 single-nucleotide polymorphisms (SNPs) significantly associated with lint percentage were detected, and they were distributed on 24 chromosomes. Forty-five SNPs were detected at least by two models or at least in two environments, and their 5 Mb up- and downstream regions included 584 makers related to lint percentage identified in previous studies. In total, 11 out of 45 SNPs were detected at least in two environments, and their 550 Kb up- and downstream region contained 335 genes. Through RNA sequencing, gene annotation, qRT-PCR, protein-protein interaction analysis, the cis-elements of the promotor region, and related miRNA prediction, Gh_D12G0934 and Gh_A08G0526 were selected as key candidate genes for fiber initiation and elongation, respectively. These excavated SNPs and candidate genes could supplement marker and gene information for deciphering the genetic basis of lint percentage and facilitate high-yield breeding programs of G. hirsutum ultimately.

Real-World Effectiveness of Remdesivir in Adults Hospitalized With Coronavirus Disease 2019 (COVID-19): A Retrospective, Multicenter Comparative Effectiveness Study.

BACKGROUND: There is an urgent need to understand the real-world effectiveness of remdesivir in the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: This was a retrospective comparative effectiveness study. Individuals hospitalized in a large private healthcare network in the United States from 23 February 2020 through 11 February 2021 with a positive test for SARS-CoV-2 and ICD-10 diagnosis codes consistent with symptomatic coronavirus disease 2019 (COVID-19) were included. Remdesivir recipients were matched to controls using time-dependent propensity scores. The primary outcome was time to improvement with a secondary outcome of time to death. RESULTS: Of 96 859 COVID-19 patients, 42 473 (43.9%) received at least 1 remdesivir dose. The median age of remdesivir recipients was 65 years, 23 701 (55.8%) were male, and 22 819 (53.7%) were non-White. Matches were found for 18 328 patients (43.2%). Remdesivir recipients were significantly more likely to achieve clinical improvement by 28 days (adjusted hazard ratio [aHR] 1.19, 95% confidence interval [CI], 1.16-1.22). Remdesivir patients on no oxygen (aHR 1.30, 95% CI, 1.22-1.38) or low-flow oxygen (aHR 1.23, 95% CI, 1.19-1.27) were significantly more likely to achieve clinical improvement by 28 days. There was no significant impact on the likelihood of mortality overall (aHR 1.02, 95% CI, .97-1.08). Remdesivir recipients on low-flow oxygen were significantly less likely to die than controls (aHR 0.85, 95% CI, .77-.92; 28-day mortality 8.4% [865 deaths] for remdesivir patients, 12.5% [1334 deaths] for controls). CONCLUSIONS: These results support the use of remdesivir for hospitalized COVID-19 patients on no or low-flow oxygen. Routine initiation of remdesivir in more severely ill patients is unlikely to be beneficial.

Comparative Genome Analyses Highlight Transposon-Mediated Genome Expansion and the Evolutionary Architecture of 3D Genomic Folding in Cotton.

Transposable element (TE) amplification has been recognized as a driving force mediating genome size expansion and evolution, but the consequences for shaping 3D genomic architecture remains largely unknown in plants. Here, we report reference-grade genome assemblies for three species of cotton ranging 3-fold in genome size, namely Gossypium rotundifolium (K2), G. arboreum (A2), and G. raimondii (D5), using Oxford Nanopore Technologies. Comparative genome analyses document the details of lineage-specific TE amplification contributing to the large genome size differences (K2, 2.44 Gb; A2, 1.62 Gb; D5, 750.19 Mb) and indicate relatively conserved gene content and synteny relationships among genomes. We found that approximately 17% of syntenic genes exhibit chromatin status change between active ("A") and inactive ("B") compartments, and TE amplification was associated with the increase of the proportion of A compartment in gene regions (∼7,000 genes) in K2 and A2 relative to D5. Only 42% of topologically associating domain (TAD) boundaries were conserved among the three genomes. Our data implicate recent amplification of TEs following the formation of lineage-specific TAD boundaries. This study sheds light on the role of transposon-mediated genome expansion in the evolution of higher-order chromatin structure in plants.

The Effectiveness of High-Flow Nasal Cannula in Coronavirus Disease 2019 Pneumonia: A Retrospective Cohort Study.

OBJECTIVES: High-flow nasal cannula is widely used in acute hypoxemic respiratory failure due to coronavirus disease 2019, yet data regarding its effectiveness is lacking. More evidence is needed to guide patient selection, timing of high-flow nasal cannula initiation, and resource allocation. We aimed to assess time to discharge and time to death in severe coronavirus disease 2019 in patients treated with high-flow nasal cannula compared with matched controls. We also evaluated the ability of the respiratory rate-oxygenation ratio to predict progression to invasive mechanical ventilation. DESIGN: Time-dependent propensity score matching was used to create pairs of individuals who were then analyzed in a Cox proportional-hazards regression model to estimate high-flow nasal cannula's effect on time to discharge and time to death. A secondary analysis excluded high-flow nasal cannula patients intubated within 6 hours of admission. A Cox proportional-hazards regression model was used to assess risk of invasive mechanical ventilation among high-flow nasal cannula patients stratified by respiratory rate-oxygenation. SETTING: The five hospitals of the Johns Hopkins Health System. PATIENTS: All patients who were admitted with a laboratory-confirmed diagnosis of coronavirus disease 2019 were eligible for inclusion. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: High-flow nasal cannula was associated with longer median time to discharge: 10.6 days (interquartile range, 7.1-15.8 d) versus 7.8 days (interquartile range, 4.9-12.1 d). Respiratory rate-oxygenation index performed poorly in predicting ventilation or death. In the primary analysis, there was no significant association between high-flow nasal cannula and hazard of death (adjusted hazard ratio, 0.79; 95% CI, 0.57-1.09). Excluding patients intubated within 6 hours of admission, high-flow nasal cannula was associated with reduced hazard of death (adjusted hazard ratio, 0.67; 95% CI, 0.45-0.99). CONCLUSIONS: Among unselected patients with severe coronavirus disease 2019 pneumonia, high-flow nasal cannula was not associated with a statistically significant reduction in hazard of death. However, in patients not mechanically ventilated within 6 hours of admission, high-flow nasal cannula was associated with a significantly reduced hazard of death.

Transcriptomics for Drought Stress Mediated by Biological Processes in-relation to Key Regulated Pathways in Gossypium darwinii.

BACKGROUND: Wild cotton Gossypium darwinii, an allotetraploid harbours important traits useful for tolerating abiotic stress, i.e., drought, salt and good genetic stability, hence these characteristics can be transferred to cultivated cotton for genetic improvement. MATERIALS AND METHODS: In this study, we analyzed the RNA-seq transcriptomes from leaves of G. darwinii seedlings with and without drought stress. A total of 86.7 million valid reads with an average length of 95.79 bp were generated from the two samples and 58,960 transcripts with a length of more than 500 bp were assembled. We searched the known proteins on the strength of sequence similarity; these transcripts were annotated with COG, KEGG and GO functional categories. According to gene expression abundance RPKM value, we carried out RT-qPCR analysis to determine the expression pattern of the obtained transcription factors. RESULTS: A total of 58,960 genes was differentially expressed (DEG), with 32,693 and 25,919 genes found to be upregulated and downregulated, respectively. Through gene ontology and KEGG pathways, the upregulated genes were found to associate with all the GO terms, molecular functions (MF), biological process (BP) and cellular components (CC), which are highly linked to enhancing drought stress tolerance. CONCLUSION: The study provides an in-depth knowledge of regulation of pathways and genes involved in photosynthesis during drought stress in G. darwinii. These pathways and genes were found to be significantly downregulated and this information could be further utilized by cotton breeders in developing a more drought tolerant cotton germplasm.

Development of Severe COVID-19 Adaptive Risk Predictor (SCARP), a Calculator to Predict Severe Disease or Death in Hospitalized Patients With COVID-19.

BACKGROUND: Predicting the clinical trajectory of individual patients hospitalized with coronavirus disease 2019 (COVID-19) is challenging but necessary to inform clinical care. The majority of COVID-19 prognostic tools use only data present upon admission and do not incorporate changes occurring after admission. OBJECTIVE: To develop the Severe COVID-19 Adaptive Risk Predictor (SCARP) (https://rsconnect.biostat.jhsph.edu/covid_trajectory/), a novel tool that can provide dynamic risk predictions for progression from moderate disease to severe illness or death in patients with COVID-19 at any time within the first 14 days of their hospitalization. DESIGN: Retrospective observational cohort study. SETTINGS: Five hospitals in Maryland and Washington, D.C. PATIENTS: Patients who were hospitalized between 5 March and 4 December 2020 with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) confirmed by nucleic acid test and symptomatic disease. MEASUREMENTS: A clinical registry for patients hospitalized with COVID-19 was the primary data source; data included demographic characteristics, admission source, comorbid conditions, time-varying vital signs, laboratory measurements, and clinical severity. Random forest for survival, longitudinal, and multivariate (RF-SLAM) data analysis was applied to predict the 1-day and 7-day risks for progression to severe disease or death for any given day during the first 14 days of hospitalization. RESULTS: Among 3163 patients admitted with moderate COVID-19, 228 (7%) became severely ill or died in the next 24 hours; an additional 355 (11%) became severely ill or died in the next 7 days. The area under the receiver-operating characteristic curve (AUC) for 1-day risk predictions for progression to severe disease or death was 0.89 (95% CI, 0.88 to 0.90) and 0.89 (CI, 0.87 to 0.91) during the first and second weeks of hospitalization, respectively. The AUC for 7-day risk predictions for progression to severe disease or death was 0.83 (CI, 0.83 to 0.84) and 0.87 (CI, 0.86 to 0.89) during the first and second weeks of hospitalization, respectively. LIMITATION: The SCARP tool was developed by using data from a single health system. CONCLUSION: Using the predictive power of RF-SLAM and longitudinal data from more than 3000 patients hospitalized with COVID-19, an interactive tool was developed that rapidly and accurately provides the probability of an individual patient's progression to severe illness or death on the basis of readily available clinical information. PRIMARY FUNDING SOURCE: Hopkins inHealth and COVID-19 Administrative Supplement for the HHS Region 3 Treatment Center from the Office of the Assistant Secretary for Preparedness and Response.

Starting or Switching to an Integrase Inhibitor-Based Regimen Affects PTSD Symptoms in Women with HIV.

As the use of Integrase inhibitor (INSTI)-class antiretroviral medications becomes more common to maintain long-term viral suppression, early reports suggest the potential for CNS side-effects when starting or switching to an INSTI-based regimen. In a population already at higher risk for developing mood and anxiety disorders, these drugs may have significant effects on PTSD scale symptom scores, particularly in women with HIV (WWH). A total of 551 participants were included after completing ≥ 1 WIHS study visits before and after starting/switching to an INSTI-based ART regimen. Of these, 14% were ART naïve, the remainder switched from primarily a protease inhibitor (PI) or non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen. Using multivariable linear mixed effects models, we compared PTSD Civilian Checklist subscale scores before and after a "start/switch" to dolutegravir (DTG), raltegravir (RAL), or elvitegravir (EVG). Start/switch to EVG improved re-experiencing subscale symptoms (P's < 0.05). Switching to EVG improved symptoms of avoidance (P = 0.01). Starting RAL improved arousal subscale symptoms (P = 0.03); however, switching to RAL worsened re-experiencing subscale symptoms (P < 0.005). Starting DTG worsened avoidance subscale symptoms (P = 0.03), whereas switching to DTG did not change subscale or overall PTSD symptoms (P's > 0.08). In WWH, an EVG-based ART regimen is associated with improved PTSD symptoms, in both treatment naïve patients and those switching from other ART. While a RAL-based regimen was associated with better PTSD symptoms than in treatment naïve patients, switching onto a RAL-based regimen was associated with worse PTSD symptoms. DTG-based regimens either did not affect, or worsened symptoms, in both naïve and switch patients. Further studies are needed to determine mechanisms underlying differential effects of EVG, RAL and DTG on stress symptoms in WWH.

Knockdown of Gh_A05G1554 (GhDHN_03) and Gh_D05G1729 (GhDHN_04) Dehydrin genes, Reveals their potential role in enhancing osmotic and salt tolerance in cotton.

In this investigation, whole-genome identification and functional characterization of the cotton dehydrin genes was carried out. A total of 16, 7, and 7 dehydrin proteins were identified in G. hirsutum, G. arboreum and G. raimondii, respectively. Through RNA sequence data and RT-qPCR validation, Gh_A05G1554 (GhDHN_03) and Gh_D05G1729 (GhDHN_04) were highly upregulated, and knockdown of the two genes, significantly reduced the ability of the plants to tolerate the effects of osmotic and salt stress. The VIGS-plants recorded significantly higher concentration levels of oxidants, hydrogen peroxide (H2O2) and malondialdehyde (MDA), furthermore, the four stress responsive genes GhLEA2, Gh_D12G2017 (CDKF4), Gh_A07G0747 (GPCR) and a transcription factor, trihelix, Gh_A05G2067, were significantly downregulated in VIGS-plants, but upregulated in wild types under osmotic and salt stress condition. The result indicated that dehydrin proteins are vital for plants and can be exploited in developing a more osmotic and salt stress-resilient germplasm to boost and improve cotton production.

Identification, Molecular Characteristic, and Expression Analysis of PIFs Related to Chlorophyll Metabolism in Tea Plant (Camellia sinensis).

The phytochrome-interacting factors (PIFs) proteins belong to the subfamily of basic helix-loop-helix (bHLH) transcription factors and play important roles in chloroplast development and chlorophyll biosynthesis. Currently, knowledge about the PIF gene family in Camellia sinensis remains very limited. In this study, seven PIF members were identified in the C. sinensis genome and named based on homology with AtPIF genes in Arabidopsis thaliana. All C. sinensis PIF (CsPIF) proteins have both the conserved active PHYB binding (APB) and bHLH domains. Phylogenetic analysis revealed that CsPIFs were clustered into four groups-PIF1, PIF3, PIF7, and PIF8-and most CsPIFs were clustered in pairs with their corresponding orthologs in Populus tremula. CsPIF members in the same group tended to display uniform or similar exon-intron distribution patterns and motif compositions. CsPIF genes were differentially expressed in C. sinensis with various leaf colors and strongly correlated with the expression of genes involved in the chlorophyll metabolism pathway. Promoter analysis of structural genes related to chlorophyll metabolism found DNA-binding sites of PIFs were abundant in the promoter regions. Protein-protein interaction networks of CsPIFs demonstrated a close association with phytochrome, PIF4, HY5, TOC1, COP1, and PTAC12 proteins. Additionally, subcellular localization and transcriptional activity analysis suggested that CsPIF3b was nuclear localized protein and possessed transcriptional activity. We also found that CsPIF3b could activate the transcription of CsHEMA and CsPOR in Nicotiana benthamiana leaves. This work provides comprehensive research of CsPIFs and would be helpful to further promote the regulation mechanism of PIF on chlorophyll metabolism in C. sinensis.

Genetic regulatory networks for salt-alkali stress in Gossypium hirsutum with differing morphological characteristics.

BACKGROUND: Cotton grows in altering environments that are often unfavorable or stressful for its growth and development. Consequently, the plant must cope with abiotic stresses such as soil salinity, drought, and excessive temperatures. Alkali-salt stress response remains a cumbersome biological process and is regulated via a multifaceted transcriptional regulatory network in cotton. RESULTS: To discover the molecular mechanisms of alkali-salt stress response in cotton, a comprehensive transcriptome analysis was carried out after alkali-salt stress treatment in three accessions of Gossypium hirsutum with contrasting phenotype. Expression level analysis proved that alkali-salt stress response presented significant stage-specific and tissue-specific. GO enrichment analysis typically suggested that signal transduction process involved in salt-alkali stress response at SS3 and SS12 stages in leaf; carbohydrate metabolic process and oxidation-reduction process involved in SS48 stages in leaf; the oxidation-reduction process involved at all three phases in the root. The Co-expression analysis suggested a potential GhSOS3/GhCBL10-SOS2 network was involved in salt-alkali stress response. Furthermore, Salt-alkali sensitivity was increased in GhSOS3 and GhCBL10 Virus-induced Gene Silencing (VIGS) plants. CONCLUSION: The findings may facilitate to elucidate the underlying mechanisms of alkali-salt stress response and provide an available resource to scrutinize the role of candidate genes and signaling pathway governing alkali-salt stress response.