LncRNA DANA1 promotes drought tolerance and histone deacetylation of drought responsive genes in Arabidopsis.

Although many long noncoding RNAs have been discovered in plants, little is known about their biological function and mode of action. Here we show that the drought-induced long intergenic noncoding RNA DANA1 interacts with the L1p/L10e family member protein DANA1-INTERACTING PROTEIN 1 (DIP1) in the cell nucleus of Arabidopsis, and both DANA1 and DIP1 promote plant drought resistance. DANA1 and DIP1 increase histone deacetylase HDA9 binding to the CYP707A1 and CYP707A2 loci. DIP1 further interacts with PWWP3, a member of the PEAT complex that associates with HDA9 and has histone deacetylase activity. Mutation of DANA1 enhances CYP707A1 and CYP707A2 acetylation and expression resulting in impaired drought tolerance, in agreement with dip1 and pwwp3 mutant phenotypes. Our results demonstrate that DANA1 is a positive regulator of drought response and that DANA1 works jointly with the novel chromatin-related factor DIP1 on epigenetic reprogramming of the plant transcriptome during the response to drought.

Electrochemical CO2 Reduction on Cu-Based Monatomic Alloys: A DFT Study.

In recent years, single-atom alloy catalysts (SAAs) have received much attention due to the combination of structural features of both single-atom and alloy catalysts, as well as their efficient catalytic activity, high selectivity, and high stability in various chemical reactions. In this work, we designed a series of Cu-based SAAs by doping isolated 3d transition metal (TM1) atoms on the surface of Cu(111) (TM1 = Fe, Co, Ru, Rh, Os and Ir), in which Ir1/Cu(111) SAAs are considered to be the most stable among 3d-series SAAs due to their optimal binding energy (Eb). The density of states of SAAs have been systematically investigated to further discuss structural properties. Based on density functional theory calculations, the activity and selectivity of Ir1/Cu(111) SAAs are investigated for electrocatalytic CO2 reduction reaction (CO2RR). The initial hydrogenation of CO2 on Ir1/Cu(111) SAAs can form *CO intermediates, which will be further to CH4 production by the pathway of *CO → *CHO → *CHOH → *CH2OH → *CH2 → *CH3 → CH4. This study provides theoretical insights for the rational design of selective Cu-based monatomic alloy catalysts.

Quantifying the Importance of Non-Suicidal Self-Injury Characteristics in Predicting Different Clinical Outcomes: Using Random Forest Model.

Existing research on non-suicidal self-injury (NSSI) among adolescents has primarily concentrated on general risk factors, leaving a significant gap in understanding the specific NSSI characteristics that predict diverse psychopathological outcomes. This study aims to address this gap by using Random Forests to discern the significant predictors of different clinical outcomes. The study tracked 348 adolescents (64.7% girls; mean age = 13.31, SD = 0.91) over 6 months. Initially, 46 characteristics of NSSI were evaluated for their potential to predict the repetition of NSSI, as well as depression, anxiety, and suicidal risks at a follow-up (T2). The findings revealed distinct predictors for each psychopathology. Specifically, psychological pain was identified as a significant predictor for depression, anxiety, and suicidal risks, while the perceived effectiveness of NSSI was crucial in forecasting its repetition. These findings imply that it is feasible to identify high-risk individuals by assessing key NSSI characteristics, and also highlight the importance of considering diverse NSSI characteristics when working with self-injurers.

Elastic priors to dynamically borrow information from historical data in clinical trials.

Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is to effectively borrow information from historical data while maintaining a reasonable type I error and minimal bias. We propose the elastic prior approach to address this challenge. Unlike existing approaches, this approach proactively controls the behavior of information borrowing and type I errors by incorporating a well-known concept of clinically significant difference through an elastic function, defined as a monotonic function of a congruence measure between historical data and trial data. The elastic function is constructed to satisfy a set of prespecified criteria such that the resulting prior will strongly borrow information when historical and trial data are congruent, but refrain from information borrowing when historical and trial data are incongruent. The elastic prior approach has a desirable property of being information borrowing consistent, that is, asymptotically controls type I error at the nominal value, no matter that historical data are congruent or not to the trial data. Our simulation study that evaluates the finite sample characteristic confirms that, compared to existing methods, the elastic prior has better type I error control and yields competitive or higher power. The proposed approach is applicable to binary, continuous, and survival endpoints.

IBIS: identify biomarker-based subgroups with a Bayesian enrichment design for targeted combination therapy.

BACKGROUND: Combination therapies directed at multiple targets have potentially improved treatment effects for cancer patients. Compared to monotherapy, targeted combination therapy leads to an increasing number of subgroups and complicated biomarker-based efficacy profiles, making it more difficult for efficacy evaluation in clinical trials. Therefore, it is necessary to develop innovative clinical trial designs to explore the efficacy of targeted combination therapy in different subgroups and identify patients who are more likely to benefit from the investigational combination therapy. METHODS: We propose a statistical tool called 'IBIS' to Identify BIomarker-based Subgroups and apply it to the enrichment design framework. The IBIS contains three main elements: subgroup division, efficacy evaluation and subgroup identification. We first enumerate all possible subgroup divisions based on biomarker levels. Then, Jensen-Shannon divergence is used to distinguish high-efficacy and low-efficacy subgroups, and Bayesian hierarchical model (BHM) is employed to borrow information within these two subsets for efficacy evaluation. Regarding subgroup identification, a hypothesis testing framework based on Bayes factors is constructed. This framework also plays a key role in go/no-go decisions and enriching specific population. Simulation studies are conducted to evaluate the proposed method. RESULTS: The accuracy and precision of IBIS could reach a desired level in terms of estimation performance. In regard to subgroup identification and population enrichment, the proposed IBIS has superior and robust characteristics compared with traditional methods. An example of how to obtain design parameters for an adaptive enrichment design under the IBIS framework is also provided. CONCLUSIONS: IBIS has the potential to be a useful tool for biomarker-based subgroup identification and population enrichment in clinical trials of targeted combination therapy.

BASIC: A Bayesian adaptive synthetic-control design for phase II clinical trials.

BACKGROUND: Randomized controlled trials are considered the gold standard for evaluating experimental treatments but often require large sample sizes. Single-arm trials require smaller sample sizes but are subject to bias when using historical control data for comparative inferences. This article presents a Bayesian adaptive synthetic-control design that exploits historical control data to create a hybrid of a single-arm trial and a randomized controlled trial. METHODS: The Bayesian adaptive synthetic control design has two stages. In stage 1, a prespecified number of patients are enrolled in a single arm given the experimental treatment. Based on the stage 1 data, applying propensity score matching and Bayesian posterior prediction methods, the usefulness of the historical control data for identifying a pseudo sample of matched synthetic-control patients for making comparative inferences is evaluated. If a sufficient number of synthetic controls can be identified, the single-arm trial is continued. If not, the trial is switched to a randomized controlled trial. The performance of The Bayesian adaptive synthetic control design is evaluated by computer simulation. RESULTS: The Bayesian adaptive synthetic control design achieves power and unbiasedness similar to a randomized controlled trial but on average requires a much smaller sample size, provided that the historical control data patients are sufficiently comparable to the trial patients so that a good number of matched controls can be identified in the historical control data. Compared to a single-arm trial, The Bayesian adaptive synthetic control design yields much higher power and much smaller bias. CONCLUSION: The Bayesian adaptive synthetic-control design provides a useful tool for exploiting historical control data to improve the efficiency of single-arm phase II clinical trials, while addressing the problem of bias when comparing trial results to historical control data. The proposed design achieves power similar to a randomized controlled trial but may require a substantially smaller sample size.

Phylosymbiosis: The Eco-Evolutionary Pattern of Insect-Symbiont Interactions.

Insects harbor diverse assemblages of bacterial and fungal symbionts, which play crucial roles in host life history. Insects and their various symbionts represent a good model for studying host-microbe interactions. Phylosymbiosis is used to describe an eco-evolutionary pattern, providing a new cross-system trend in the research of host-associated microbiota. The phylosymbiosis pattern is characterized by a significant positive correlation between the host phylogeny and microbial community dissimilarities. Although host-symbiont interactions have been demonstrated in many insect groups, our knowledge of the prevalence and mechanisms of phylosymbiosis in insects is still limited. Here, we provide an order-by-order summary of the phylosymbiosis patterns in insects, including Blattodea, Coleoptera, Diptera, Hemiptera, Hymenoptera, and Lepidoptera. Then, we highlight the potential contributions of stochastic effects, evolutionary processes, and ecological filtering in shaping phylosymbiotic microbiota. Phylosymbiosis in insects can arise from a combination of stochastic and deterministic mechanisms, such as the dispersal limitations of microbes, codiversification between symbionts and hosts, and the filtering of phylogenetically conserved host traits (incl., host immune system, diet, and physiological characteristics).

FoxO3a cooperates with RUNX1 to promote chondrogenesis and terminal hypertrophic of the chondrogenic progenitor cells.

FoxO transcription factors (FoxOs) have recently been shown to protect against chondrocyte dysfunction and modulate cartilage homeostasis in osteoarthritis. The mechanism underlying of FoxOs regulate chondrocyte differentiation remains unknown. Runt related transcription factor 1 (RUNX1) mediated both chondrocyte and osteoblast differentiation. Our data showed that FoxO3a and RUNX1 are co-expressed in ATDC5 cells and undifferentiated mesenchyme cells and have similar high levels in chondrocytes undergoing transition from proliferation to hypertrophy. Overexpression of FoxO3a in ATDC5 cells or mouse mesenchymal cells resulted in a potent induction of the chondrocyte differentiation markers. Knockdown FoxO3a or RUNX1 potently inhibits the expressions of chondrocyte differentiation markers, including Sox9, Aggrecan, Col2, and hypertrophic chondrocyte markers including RUNX2, ColX, MMP13 and ADAMTs-5 in ATDC5 cells. Co-immunoprecipitation showed that FoxO3a binds the transcriptional regulator RUNX1. Immunohistochemistry showed that FoxO3a and RUNX1 are highly co-expressed in the proliferative chondrocytes of the growth plates in the hind limbs of newborn mice. Collectively, we revealed that FoxO3a cooperated with RUNX1 promoted chondrocyte differentiation through enhancing both early chondrogenesis and terminal hypertrophic of the chondrogenic progenitor cells, indicating FoxO3a interacting with RUNX1 may be a therapeutic target for the treatment of osteoarthritis and other bone diseases.

MOVICS: an R package for multi-omics integration and visualization in cancer subtyping.

SUMMARY: Stratification of cancer patients into distinct molecular subgroups based on multi-omics data is an important issue in the context of precision medicine. Here, we present MOVICS, an R package for multi-omics integration and visualization in cancer subtyping. MOVICS provides a unified interface for 10 state-of-the-art multi-omics integrative clustering algorithms, and incorporates the most commonly used downstream analyses in cancer subtyping researches, including characterization and comparison of identified subtypes from multiple perspectives, and verification of subtypes in external cohort using two model-free approaches for multiclass prediction. MOVICS also creates feature rich customizable visualizations with minimal effort. By analysing two published breast cancer cohort, we signifies that MOVICS can serve a wide range of users and assist cancer therapy by moving away from the 'one-size-fits-all' approach to patient care. AVAILABILITY AND IMPLEMENTATION: MOVICS package and online tutorial are freely available at https://github.com/xlucpu/MOVICS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The APETALA2-Like Transcription Factor SUPERNUMERARY BRACT Controls Rice Seed Shattering and Seed Size.

The elimination of seed shattering was a crucial event during crop domestication. Improving and fine-tuning the regulation of this process will further enhance grain yield by avoiding seed losses during crop production. In this work, we identified the loss-of-shattering mutant suppression of shattering1 (ssh1) through a screen of mutagenized wild rice (Oryza rufipogon) introgression lines with naturally high shattering. Using the MutMap approach and transformation experiments, we isolated a genetic factor for seed shattering, SSH1, which is an allele of SUPERNUMERARY BRACT (SNB), a gene encoding a plant-specific APETALA2-like transcription factor. A C-to-A point mutation in the ninth intron of SNB altered the splicing of its messenger RNA, causing the reduced shattering of the ssh1 mutant by altering the development of the abscission layer and vascular bundle at the junction between the seed and the pedicel. Our data suggest that SNB positively regulates the expression of two rice REPLUMLESS orthologs, qSH1 and SH5 In addition, the ssh1 mutant had larger seeds and a higher grain weight, resulting from its increased elongation of the glume longitudinal cells. The further identification of favorable SNB alleles will be valuable for improving rice seed shattering and grain yield using molecular breeding strategies.

Circulation of genotypes of dengue virus serotype 2 in Guangzhou over a period of 20 years.

BACKGROUND: The dengue epidemic in Guangzhou has imposed a rising burden on society and health infrastructure. Here, we present the genotype data for dengue virus serotype 2 (DENV-2) to improve understanding of this dengue epidemic. METHODS: We sequenced the envelope gene of DENV-2 obtained from patient serum samples and subsequently performed maximum-likelihood phylogenetic analysis using PhyMLv3.1, maximum clade credibility analysis using BEAST v.1.10.4, and selection pressure analysis using Datamonkey 2.0. RESULTS: The prevalent DENV-2 strains identified in Guangzhou region are related to those in Southeast Asian countries. In particular, the Malaysia/Indian subcontinent genotype is prevailing in Guangzhou with no apparent genotype shift having occurred over the past 20 years. However, episodic positive selection was detected at one site. CONCLUSIONS: Local control of the DENV-2 epidemic in Guangzhou requires effective measures to prevent and monitor imported cases. Moreover, the shift between the Malaysia/Indian subcontinent genotype lineages, which originated at different time points, may account for the rise in DENV-2 cases in Guangzhou. Meanwhile, the low rate of dengue haemorrhagic fever in Guangzhou may be explained by the dominance of the less virulent Malaysia/Indian subcontinent genotype.

Phylosymbiotic Structures of the Microbiota in Mollitrichosiphum tenuicorpus (Hemiptera: Aphididae: Greenideinae).

Aphids harbor an array of symbionts that provide hosts with ecological benefits. Microbial community assembly generally varies with respect to aphid species, geography, and host plants. However, the influence of host genetics and ecological factors on shaping intraspecific microbial community structures has not been fully understood. In the present study, using Illumina sequencing of the V3 - V4 hypervariable region of the 16S rRNA gene, we characterized the microbial compositions associated with Mollitrichosiphum tenuicorpus from different regions and plants in China. The primary symbiont Buchnera aphidicola and the secondary symbiont Arsenophonus dominated the microbial flora in M. tenuicorpus. Ordination analyses and statistical tests suggested that geography and aphid genetics primarily contributed to the variation in the microbiota of M. tenuicorpus. We further confirmed the combined effect of aphid genetics and geography on shaping the structures of symbiont and secondary symbiont communities. Moreover, the significant correlation between aphid genetic divergence and symbiont community dissimilarity provides evidence for intraspecific phylosymbiosis in natural systems. Our study helped to elucidate the eco-evolutionary relationship between symbiont communities and aphids within one given species.

Multiomics data reveals the influences of myasthenia gravis on thymoma and its precision treatment.

Thymoma is a rare characterized by a unique association with autoimmune diseases, especially myasthenia gravis (MG). However, little is known about the molecular characteristics of MG-associated thymoma individuals. We aim to examine the influences of MG on thymoma by analyzing multiomics data. A total of 105 samples with thymoma was analyzed from TCGA and these samples were divided into subgroups with MG (MGT) or without MG (MGF) according to clinical information. We then characterized the differential gene expression, pathway activity, somatic mutation frequency, and likelihood of responding to chemotherapies and immunotherapies of the two identified subgroups. MGT subgroup was characterized by elevated inflammatory responses and metabolically related pathways, whereas the MGF subgroup was predicted to be more sensitive to chemotherapy and presented with mesenchymal characteristics. More copy number amplifications and deletions were observed in MGT, whereas GTF2I mutations occur at significantly higher frequencies in MGF. Two molecular subtypes were further identified within MGF samples by unsupervised clustering where one subtype was enriched in TGF-ß and WNT pathways with higher sensitivity to relevant targeted drugs but hardly respond to immunotherapy. For another subtype, a higher recurrence rate of thymoma and more likelihood of responding to immunotherapy were observed. Our findings presented a comprehensive molecular characterization of thymoma patients given the status of MG, and provided potential strategies to help individualized management and treatment.

Microbiota associated with Mollitrichosiphum aphids (Hemiptera: Aphididae: Greenideinae): diversity, host species specificity and phylosymbiosis.

Symbiotic association is universal in nature, and an array of symbionts play a crucial part in host life history. Aphids and their diverse symbionts have become a good model system to study insect-symbiont interactions. Previous symbiotic diversity surveys have mainly focused on a few aphid clades, and the relative importance of different factors regulating microbial community structure is not well understood. In this study, we collected 65 colonies representing eight species of the aphid genus Mollitrichosiphum from different regions and plants in southern China and Nepal and characterized their microbial compositions using Illumina sequencing of the V3 - V4 hypervariable region of the 16S rRNA gene. We evaluated how microbiota varied across aphid species, geography and host plants and the correlation between microbial community structure and host aphid phylogeny. Heritable symbionts dominated the microbiota associated with Mollitrichosiphum, and multiple infections of secondary symbionts were prevalent. Ordination analyses and statistical tests highlighted the contribution of aphid species in shaping the structures of bacterial, symbiont and secondary symbiont communities. Moreover, we observed a significant correlation between Mollitrichosiphum aphid phylogeny and microbial community composition, providing evidence for a pattern of phylosymbiosis between natural aphid populations and their microbial associates.

Diversity of bacterial symbionts associated with Myzus persicae (Sulzer) (Hemiptera: Aphididae: Aphidinae) revealed by 16S rRNA Illumina sequencing.

Aphids are known to be associated with a variety of symbiotic bacteria. To improve our knowledge of the bacterial diversity of polyphagous aphids, in the present study, we investigated the microbiota of the cosmopolitan agricultural pest Myzus persicae (Sulzer). Ninety-two aphid samples collected from different host plants in various regions of China were examined using high-throughput amplicon sequencing. We comprehensively characterized the symbiont diversity of M. persicae and assessed the variations in aphid-associated symbiont communities. We detected a higher diversity of symbionts than has been previously observed. M. persicae hosted the primary endosymbiont Buchnera aphidicola and seven secondary symbionts, among which Wolbachia was the most prevalent and Rickettsia, Arsenophonus, and Spiroplasma were reported for the first time. Ordination analyses and statistical tests revealed that the symbiont flora associated with M. persicae did not change with respect to host plant or geography, which may be due to frequent migrations between different aphid populations. These findings will advance our knowledge of the microbiota of polyphagous insects and will enrich our understanding of assembly of host-microbiome systems.

Continuously available ratio of SpO2/FiO2 serves as a noninvasive prognostic marker for intensive care patients with COVID-19.

RATIONALE: Oxygen saturation to fraction of inspired oxygen ratio (SpO2/FiO2) has been described as potential predictor of poor outcome for COVID-19, without considering its time-varying behavior though. METHODS: Prognostic value of SpO2/FiO2 was evaluated by jointly modeling the longitudinal responses of SpO2/FiO2 and time-to-event data retrieved from 280 severe and critically ill (intensive care) patients with COVID-19. RESULTS: A sharply decrease of SpO2/FiO2 from the first to second measurement for non-survivors was observed, and a strong association between square root SpO2/FiO2 and mortality risk was demonstrated, with a unit decrease in the marker corresponding to 1.82-fold increase in mortality risk (95% CI: 1.56-2.13). CONCLUSIONS: The current study suggested that SpO2/FiO2 could serve as a non-invasive prognostic marker to facilitate early adjustment for treatment, thus improving overall survival.

The Bacterial Flora Associated with the Polyphagous Aphid Aphis gossypii Glover (Hemiptera: Aphididae) Is Strongly Affected by Host Plants.

Aphids live in symbiosis with a variety of bacteria, including the obligate symbiont Buchnera aphidicola and diverse facultative symbionts. The symbiotic associations for one aphid species, especially for polyphagous species, often differ across populations. In the present study, by using high-throughput 16S rRNA sequencing, we surveyed in detail the microbiota in natural populations of the cotton aphid Aphis gossypii in China and assessed differences in bacterial diversity with respect to host plant and geography. The microbial community of A. gossypii was dominated by a few heritable symbionts. Arsenophonus was the most dominant secondary symbiont, and Spiroplasma was detected for the first time. Statistical tests and ordination analyses showed that host plants rather than geography seemed to have shaped the associated symbiont composition. Special symbiont communities inhabited the Cucurbitaceae-feeding populations, which supported the ecological specialization of A. gossypii on cucurbits from the viewpoint of symbiotic bacteria. Correlation analysis suggested antagonistic interactions between Buchnera and coexisting secondary symbionts and more complicated interactions between different secondary symbionts. Our findings lend further support to an important role of the host plant in structuring symbiont communities of polyphagous aphids and will improve our understanding of the interactions among phytophagous insects, symbionts, and environments.

Comparing Bayesian early stopping boundaries for phase II clinical trials.

When designing phase II clinical trials, it is important to construct interim monitoring rules that achieve a balance between reliable early stopping for futility or safety and maintaining a high true positive probability (TPP), which is the probability of not stopping if the new treatment is truly safe and effective. We define and compare several methods for specifying early stopping boundaries as functions of interim sample size, rather than as fixed cut-offs, using Bayesian posterior probabilities as decision criteria. We consider boundaries with constant, linear, or exponential shapes. For design optimization criteria, we use the TPP and mean number of patients enrolled in the trial. Simulations to evaluate and compare the designs' operating characteristics under a range of scenarios show that, while there is no uniformly optimal boundary, an appropriately calibrated exponential shape maintains high TPP while limiting the number of patients assigned to a treatment with an inferior response rate or an excessive toxicity rate.

The increasing menace of dengue in Guangzhou, 2001-2016: the most important epicenter in mainland China.

BACKGROUND: Dengue is the most prevalent mosquito-borne disease in the world, with China affected seriously in recent years. 65.8% of dengue cases identified in mainland China since 2005 were reported from the city of Guangzhou. METHODS: In this study, we described the incidence rate and distribution of dengue cases using data collected form National Notifiable Infectious Disease Reporting Information System data in Guangzhou for 2001 to 2016. All dengue cases were investigated using standardized questionnaire. RESULTS: A total of 42,469 dengue cases were reported, with an average annual incidence rate of 20.99 per 100,000 resident population. Over this time period, the incidence rate of indigenous cases increased. Dengue affected areas also expanded sharply geographically from 58.1% of communities affected during 2001-2005 to 96.4% of communities affected in 2011-2016. Overall 95.30% of the overseas imported cases were reported during March and December, while 99.79% of indigenous cases were reported during July and November. All four dengue virus serotypes were identified both in imported cases and indigenous cases. The Aedes albopictus mosquito was the only vector for dengue transmission in the area. CONCLUSIONS: Guangzhou has become the dengue epicenter in mainland China. Control strategies for dengue should be adjusted to the epidemiological characteristics above and intensive study need to be conducted to explore the factors that driving the rapid increase of dengue.

Design and inference for 3-stage bioequivalence testing with serial sampling data.

A bioequivalence test is to compare bioavailability parameters, such as the maximum observed concentration (Cmax ) or the area under the concentration-time curve, for a test drug and a reference drug. During the planning of a bioequivalence test, it requires an assumption about the variance of Cmax or area under the concentration-time curve for the estimation of sample size. Since the variance is unknown, current 2-stage designs use variance estimated from stage 1 data to determine the sample size for stage 2. However, the estimation of variance with the stage 1 data is unstable and may result in too large or too small sample size for stage 2. This problem is magnified in bioequivalence tests with a serial sampling schedule, by which only one sample is collected from each individual and thus the correct assumption of variance becomes even more difficult. To solve this problem, we propose 3-stage designs. Our designs increase sample sizes over stages gradually, so that extremely large sample sizes will not happen. With one more stage of data, the power is increased. Moreover, the variance estimated using data from both stages 1 and 2 is more stable than that using data from stage 1 only in a 2-stage design. These features of the proposed designs are demonstrated by simulations. Testing significance levels are adjusted to control the overall type I errors at the same level for all the multistage designs.