Bayesian tensor-on-tensor regression with efficient computation.

We propose a Bayesian tensor-on-tensor regression approach to predict a multidimensional array (tensor) of arbitrary dimensions from another tensor of arbitrary dimensions, building upon the Tucker decomposition of the regression coefficient tensor. Traditional tensor regression methods making use of the Tucker decomposition either assume the dimension of the core tensor to be known or estimate it via cross-validation or some model selection criteria. However, no existing method can simultaneously estimate the model dimension (the dimension of the core tensor) and other model parameters. To fill this gap, we develop an efficient Markov Chain Monte Carlo (MCMC) algorithm to estimate both the model dimension and parameters for posterior inference. Besides the MCMC sampler, we also develop an ultra-fast optimization-based computing algorithm wherein the maximum a posteriori estimators for parameters are computed, and the model dimension is optimized via a simulated annealing algorithm. The proposed Bayesian framework provides a natural way for uncertainty quantification. Through extensive simulation studies, we evaluate the proposed Bayesian tensor-on-tensor regression model and show its superior performance compared to alternative methods. We also demonstrate its practical effectiveness by applying it to two real-world datasets, including facial imaging data and 3D motion data.

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.

Integration of non-targeted/targeted metabolomics and electronic sensor technology reveals the chemical and sensor variation in 12 representative yellow teas.

Yellow tea is a lightly fermented tea with unique sensory qualities and health benefits. However, chemical composition and sensory quality of yellow tea products have rarely been studied. 12 representative yellow teas, which were basically covered the main products of yellow tea, were chosen in this study. Combined analysis of non-targeted/targeted metabolomics and electronic sensor technologies (E-eye, E-nose, E-tongue) revealed the chemical and sensor variation. The results showed that yellow big tea differed greatly from yellow bud teas and yellow little teas, but yellow bud teas could not be effectively distinguished from yellow little teas based on chemical constituents and electronic sensory characteristics. Sensor variation of yellow teas might be attributed to some compounds related to bitterness and aftertaste-bitterness (4'-dehydroxylated gallocatechin-3-O-gallate, dehydrotheasinensin C, myricitin 3-O-galactoside, phloroglucinol), aftertaste-astringency (methyl gallate, 1,5-digalloylglucose, 2,6-digalloylglucose), and sweetness (maltotriose). This study provided a comprehensive understanding of yellow tea on chemical composition and sensory quality.

Insight into the chemical compositions of Anhua dark teas derived from identical tea materials: A multi-omics, electronic sensory, and microbial sequencing analysis.

Anhua dark teas (DTs), including Tianjian tea, Qianliang tea, Hei brick tea, and Fu brick tea, are unique fermented teas from China's Anhua County; yet their chemical composition differences remain unclear. Herein, metabolomics, volatolomics, and electronic sensory assessments were employed to analyze and compare chemical compositions and sensory characteristics of five types of Anhua DTs. All of these teas were derived from identical tea materials. Chemical compositions differed significantly among Anhua DTs, with Tianjian tea remarkable. Long-lasting fermentation and complex processing methods led to transformation of multiple compounds, particularly catechins. Eighteen volatile compounds with OVA > 1 were key aroma contributors in Anhua DTs. Internal transcribed spacer and 16S ribosomal DNA sequencing showed that Eurotium, Pseudomonas, and Bacillus are dominant microorganisms in Anhua DTs. Furthermore, this study unveiled notable differences in chemical compositions between Anhua DTs and five other traditional types of tea. This research enhances our understanding of Anhua DTs processing.

Widespread incomplete lineage sorting and introgression shaped adaptive radiation in the Gossypium genus.

Cotton (Gossypium) stands as a crucial economic crop, serving as the primary source of natural fiber for the textile sector. However, the evolutionary mechanisms driving speciation within the Gossypium genus remain unresolved. In this investigation, we leveraged 25 Gossypium genomes and introduced four novel assemblies-G. harknessii, G. gossypioides, G. trilobum, and G. klotzschianum (Gklo)-to delve into the speciation history of this genus. Notably, we encountered intricate phylogenies potentially stemming from introgression. These complexities are further compounded by incomplete lineage sorting (ILS), a factor likely to have been instrumental in shaping the swift diversification of cotton. Our focus subsequently shifted to the rapid radiation episode during a concise period in Gossypium evolution. For a recently diverged lineage comprising G. davidsonii, Gklo, and G. raimondii, we constructed a finely detailed ILS map. Intriguingly, this analysis revealed the non-random distribution of ILS regions across the reference Gklo genome. Moreover, we identified signs of robust natural selection influencing specific ILS regions. Noteworthy variations pertaining to speciation emerged between the closely related sister species Gklo and G. davidsonii. Approximately 15.74% of speciation structural variation genes and 12.04% of speciation-associated genes were estimated to intersect with ILS signatures. These findings enrich our understanding of the role of ILS in adaptive radiation, shedding fresh light on the intricate speciation history of the Gossypium genus.

Secondary Metabolites from the Genus Eurotium and Their Biological Activities.

Eurotium is the teleomorph genus associated with the section Aspergillus. Eurotium comprises approximately 20 species, which are widely distributed in nature and human environments. Eurotium is usually the key microorganism for the fermentation of traditional food, such as Fuzhuan brick tea, Liupao tea, Meju, and Karebushi; thus, Eurotium is an important fungus in the food industry. Eurotium has been extensively studied because it contains a series of interesting, structurally diverse, and biologically important secondary metabolites, including anthraquinones, benzaldehyde derivatives, and indol diketopiperazine alkaloids. These secondary metabolites have shown multiple biological activities, including antioxidative, antimicrobial, cytotoxic, antitumor, insecticidal, antimalarial, and anti-inflammatory activities. This study presents an up-to-date review of the phytochemistry and biological activities of all Eurotium species. This review will provide recent advances on the secondary metabolites and their bioactivities in the genus Eurotium for the first time and serve as a database for future research and drug development from the genus Eurotium.

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.

Clinical Outcomes Associated With Overestimation of Oxygen Saturation by Pulse Oximetry in Patients Hospitalized With COVID-19.

Importance: Many pulse oximeters have been shown to overestimate oxygen saturation in persons of color, and this phenomenon has potential clinical implications. The relationship between overestimation of oxygen saturation with timing of COVID-19 medication delivery and clinical outcomes remains unknown. Objective: To investigate the association between overestimation of oxygen saturation by pulse oximetry and delay in administration of COVID-19 therapy, hospital length of stay, risk of hospital readmission, and in-hospital mortality. Design, Setting, and Participants: This cohort study included patients hospitalized for COVID-19 at 186 acute care facilities in the US with at least 1 functional arterial oxygen saturation (SaO2) measurement between March 2020 and October 2021. A subset of patients were admitted after July 1, 2020, without immediate need for COVID-19 therapy based on pulse oximeter saturation (SpO2 levels of 94% or higher without supplemental oxygen). Exposures: Self-reported race and ethnicity, difference between concurrent SaO2 and pulse oximeter saturation (SpO2) within 10 minutes, and initially unrecognized need for COVID-19 therapy (first SaO2 reading below 94% despite SpO2 levels of 94% or above). Main Outcome and Measures: The association of race and ethnicity with degree of pulse oximeter measurement error (SpO2 - SaO2) and odds of unrecognized need for COVID-19 therapy were determined using linear mixed-effects models. Associations of initially unrecognized need for treatment with time to receipt of therapy (remdesivir or dexamethasone), in-hospital mortality, 30-day hospital readmission, and length of stay were evaluated using mixed-effects models. All models accounted for demographics, clinical characteristics, and hospital site. Effect modification by race and ethnicity was evaluated using interaction terms. Results: Among 24 504 patients with concurrent SpO2 and SaO2 measurements (mean [SD] age, 63.9 [15.8] years; 10 263 female [41.9%]; 3922 Black [16.0%], 7895 Hispanic [32.2%], 2554 Asian, Native American or Alaskan Native, Hawaiian or Pacific Islander, or another race or ethnicity [10.4%], and 10 133 White [41.4%]), pulse oximetry overestimated SaO2 for Black (adjusted mean difference, 0.93 [95% CI, 0.74-1.12] percentage points), Hispanic (0.49 [95% CI, 0.34-0.63] percentage points), and other (0.53 [95% CI, 0.35-0.72] percentage points) patients compared with White patients. In a subset of 8635 patients with a concurrent SpO2 - SaO2 pair without immediate need for COVID-19 therapy, Black patients were significantly more likely to have pulse oximetry values that masked an indication for COVID-19 therapy compared with White patients (adjusted odds ratio [aOR], 1.65; 95% CI, 1.33-2.03). Patients with an unrecognized need for COVID-19 therapy were 10% less likely to receive COVID-19 therapy (adjusted hazard ratio, 0.90; 95% CI, 0.83-0.97) and higher odds of readmission (aOR, 2.41; 95% CI, 1.39-4.18) regardless of race (P for interaction = .45 and P = .14, respectively). There was no association of unrecognized need for COVID-19 therapy with in-hospital mortality (aOR, 0.84; 95% CI, 0.71-1.01) or length of stay (mean difference, -1.4 days; 95% CI, -3.1 to 0.2 days). Conclusions and Relevance: In this cohort study, overestimation of oxygen saturation by pulse oximetry led to delayed delivery of COVID-19 therapy and higher probability of readmission regardless of race. Black patients were more likely to have unrecognized need for therapy with potential implications for population-level health disparities.

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.

The R2R3-MYB transcription factor CsMYB42 regulates theanine biosynthesis in albino tea leaves.

Theanine is a unique secondary metabolite in tea plants and contributes to the umami taste and health benefits of tea. However, theanine biosynthesis in tea plants is not fully understood, and its mechanism of transcriptional regulation remains poorly reported. Theanine content was significantly correlated with the expression of theanine biosynthesis-related gene CsGS1c and transcription factor CsMYB42 in different leaf positions and picking times, but there was no significant correlation in different tissues of albino tea plant 'Anjibaicha'. This suggests that CsMYB42 may regulate CsGS1c to synthesize theanine in albino tea leaves, and the regulation is tissue specific. CsMYB42 is a nuclear-localized R2R3-MYB transcription factor gene with transcriptional activation activity. Yeast one-hybrid assay and electrophoretic mobility shift assay confirmed the direct binding of CsMYB42 to the promoter of CsGS1c. Luciferase assay showed that CsMYB42 activates the CsGS1c expression. Furthermore, the inhibition of CsMYB42 using an antisense oligonucleotide in tea leaves decreased CsGS1c expression and theanine content. These results indicate that CsMYB42 plays a crucial role in activating the expression of CsGS1c and may be involved in the biosynthesis of theanine in albino tea leaves. This study provides fresh insights into the tissue-specific regulation of theanine biosynthesis, which laid a foundation for breeding high-theanine tea plants.

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.

Identification of salt stress-tolerant candidate genes in the BC2F2 population at the seedling stages of G. hirsutum and G. darwinii using NGS-based bulked segregant analysis.

Salinity is a major threat to the yield and productivity of cotton seedlings. In the present study, we developed a BC2F2 population of cotton plants from Gossypium darwinii (5-7) and Gossypium hirsutum (CCRI 12-4) salt-susceptible parents to identify salt-resistant candidate genes. The Illumina HiSeq™ strategy was used with bulked segregant analysis. Salt-resistant and salt-susceptible DNA bulks were pooled by using 30 plants from a BC2F2 population. Next-generation sequencing (NGS) technology was used for the sequencing of parents and both bulks. Four significant genomic regions were identified: the first genomic region was located on chromosome 18 (1.86 Mb), the second and third genomic regions were on chromosome 25 (1.06 Mb and 1.94 Mb, respectively), and the fourth was on chromosome 8 (1.41 Mb). The reads of bulk1 and bulk2 were aligned to the G. darwinii and G. hirsutum genomes, respectively, leading to the identification of 20,664,007 single-nucleotide polymorphisms (SNPs) and insertions/deletions (indels). After the screening, 6,573 polymorphic markers were obtained after filtration of the candidate regions. The SNP indices in resistant and susceptible bulks and Δ(SNP-index) values of resistant and susceptible bulks were measured. Based on the higher Δ(SNP-index) value, six effective polymorphic SNPs were selected in a different chromosome. Six effective SNPs were linked to five candidate genes in four genomic regions. Further validation of these five candidate genes was carried out using reverse transcription-quantitative polymerase chain reaction (RT-qPCR), resulting in an expression profile that showed two highly upregulated genes in the salt-tolerant species G. darwinii, i.e., Gohir.D05G367800 and Gohir.D12G239100; however, the opposite was shown in G. hirsutum, for which all genes, except one, showed partial expression. The results indicated that Gohir.D05G367800 and Gohir.D12G239100 may be salt-tolerant genes. We are confident that this study could be helpful for the cloning, transformation, and development of salt-resistant cotton varieties.

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.

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.

Polysaccharides from Fu brick tea ameliorate obesity by modulating gut microbiota and gut microbiota-related short chain fatty acid and amino acid metabolism.

Fu brick tea (FBT) is a traditional tea manufactured by solid-state fermentation of tea leaves (Camellia sinensis). Although anti-obesity effects have been reported for FBT, the associated role of FBT polysaccharides (PSs) and the underlying mechanisms remain unknown. In this study, we found that FBTPSs inhibited obesity, hyperlipidemia, and inflammation; improved intestinal barrier function; and alleviated gut microbiota dysbiosis in high-fat diet-fed rats. Akkermansia muciniphila, Bacteroides, Parasutterella, Desulfovibrio, and Blautia were the core microbes regulated by FBTPSs. FBTPSs regulated the production of gut microbiota-related metabolites, including short-chain fatty acids (SCFAs), branched-chain amino acids, and aromatic amino acids throughout the development of obesity, and regulated the SCFA-GPR signaling pathway. FBTPS-treated fecal microbiota transplant ameliorated obesity, alleviated gut microbiota dysbiosis, and improved gut microbiota-associated metabolites, suggesting that the anti-obesity effect of FBTPSs was gut microbiota-dependent. FBTPSs may serve as novel prebiotic agents for the treatment of obesity and dysbiosis of gut microbiota.

Variations of stomata development in tea plant (Camellia sinensis) leaves in different light and temperature environments and genetic backgrounds.

Stomata perform important functions in plant photosynthesis, respiration, gas exchange, and interactions with environments. However, tea plant stomata development and functions are not known. Here, we show morphological changes during stomata development and genetic dissection of stomata lineage genes regulating stomata formation in tea developing leaves. Different tea plant cultivars displayed clear variations in the stomata development rate, density and size, which are closely related to their tolerance against dehydration capabilities. Whole sets of stomata lineage genes were identified to display predicted functions in regulating stomatal development and formation. The stomata development and lineage genes were tightly regulated by light intensities and high or low temperature stresses, which affected stomata density and function. Furthermore, lower stomatal density and larger size were observed in triploid tea varieties as compared to those in diploid plant. Key stomata lineage genes such as CsSPCHs, CsSCRM, and CsFAMA showed much lower expression levels, whereas negative regulators CsEPF1 and CsYODAs had higher expression levels in triploid than in diploid tea varieties. Our study provides new insight into tea plant stomatal morphological development and the genetic regulatory mechanisms on stomata development under abiotic stresses and genetic backgrounds. The study lays a foundation for future exploring of the genetic improvement of water use efficiency in tea plants for living up to the challenge of global climate change.

Federated Learning for Sparse Bayesian Models with Applications to Electronic Health Records and Genomics.

Federated learning is becoming increasingly more popular as the concern of privacy breaches rises across disciplines including the biological and biomedical fields. The main idea is to train models locally on each server using data that are only available to that server and aggregate the model (not data) information at the global level. While federated learning has made significant advancements for machine learning methods such as deep neural networks, to the best of our knowledge, its development in sparse Bayesian models is still lacking. Sparse Bayesian models are highly interpretable with natural uncertain quantification, a desirable property for many scientific problems. However, without a federated learning algorithm, their applicability to sensitive biological/biomedical data from multiple sources is limited. Therefore, to fill this gap in the literature, we propose a new Bayesian federated learning framework that is capable of pooling information from different data sources without breaching privacy. The proposed method is conceptually simple to understand and implement, accommodates sampling heterogeneity (i.e., non-iid observations) across data sources, and allows for principled uncertainty quantification. We illustrate the proposed framework with three concrete sparse Bayesian models, namely, sparse regression, Markov random field, and directed graphical models. The application of these three models is demonstrated through three real data examples including a multi-hospital COVID-19 study, breast cancer protein-protein interaction networks, and gene regulatory networks.

Efficacy of prophylactic human papillomavirus vaccines on cervical cancer among the Asian population: A meta-analysis.

Objective: We conducted a meta-analysis to assess the efficacy of prophylactic human papillomavirus (HPV) vaccines against cervical cancer precursors and HPV persistent infection among Asian populations. Methods: Randomized controlled clinical trials conducted in Asian countries were identified from three electronic databases (PubMed, EMBASE and the Cochrane Library). Publication retrieval was performed on September 1, 2022 and only those written in English were included. The data were analyzed with Cochrane Review Manager (version 5.3) and Stata/SE (15.1). Effect sizes were presented as risk ratios (RRs) and 95% confidence intervals (CIs). Results: Ten articles were considered in the meta-analysis, without significant heterogeneity among them. The fixed-effect RRs and 95% CIs for cervical intraepithelial neoplasia grade 1 (CIN1+) and CIN2+ were 0.10 (0.05-0.21) and 0.11 (0.04-0.27), respectively. Positive effect of HPV vaccination on 6- and 12-month persistent infection were observed, with the respective pooled RRs of 0.05 (95% CI: 0.03-0.09) and 0.09 (95% CI: 0.05-0.15). HPV vaccination has a positive effect on the incidence of cytological abnormalities associated with HPV 16/18 (RR, 0.13; 95% CI (0.09-0.20)). Positive effects of HPV vaccination were also observed for HPV 16- and 18-specific immunogenicity (RR, 235.02; 95% CI (82.77-667.31) and RR, 98.24; 95% CI (50.36-191.67), respectively). Females receiving an initial vaccination showed significant decreased incidences of cervical intraepithelial neoplasia, HPV persistent infection and cytological abnormalities and a significantly higher antibody positive conversion rate compared with non-vaccination counterparts. Conclusion: Prophylactic HPV vaccines are highly efficacious in preventing cervical cancer in Asian females. The government should accelerate the processes of vaccine introduction and vaccination implementation by prioritizing them in public health policies, which should be helpful to enhance Asian females' awareness of receiving HPV vaccination volitionally.

Distribution pattern of endophytic bacteria and fungi in tea plants.

Endophytes are critical for plant growth and health. Tea is an economically important crop in China. However, little is known about the distribution pattern and potential functions of endophytic communities in tea trees. In this study, two genotypes (BXZ and MF) cultivated under the same conditions were selected, and endophytic bacteria and fungi were analyzed through 16S rRNA and ITS high-throughput sequencing technologies, respectively. For endophytic bacteria, root tissues harbored the most diverse endophytes, followed by stems and old leaves, and new leaves possessed the lowest diversity. In contrast, old leave tissues harbored more diverse endophytic fungi than did root and stem tissues. Most of the dominant endophytes showed obvious cultivar and tissue preferences. Tissue type played a more important role in shaping community structure than did cultivar. Nevertheless, some endophytic bacterial groups, which mainly affiliated to Chryseobacterium, Sphingomonas, Rhizobium, Morganella, Methylobacterium and Comamonadaceae, could parasitize different tissues, and the average relative abundance of endophytic bacteria was as high as 72.57%. Some endophytic fungal populations, such as Colletotrichum, Uwebraunia, Cladosporium, and Devriesia, could also parasitize tea, and the relative abundance accounted for approximately 25.70-97.26%. The cooperative relationship between endophytic bacteria and fungi in the new leaves was stronger than that in the old leaves, which can better participate in the metabolism of tea material.

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.