JAZ2 Negatively Regulates Drought Tolerance in Barley by Modulating PLT2 Expression.

Drought is an important abiotic factor constricting crop production globally. Although the roles of JAZ proteins in regulating jasmonic acid signalling and plant responses to environmental stress are well documented, their specific functions and underlying mechanisms remain little known. In this study, JAZ proteins in barley were thoroughly analyzed, revealing a total of 11 members classified into three phylogenetic subgroups. HvJAZ2, based on its distinct expression patterns, is considered a key candidate gene for regulating drought tolerance in barley. Using the HvJAZ2 knockout mutants, we revealed that the gene negatively regulates drought tolerance by inhibiting barley root growth. Notably, the jaz2 mutants upregulated the expression of root development genes, including SHR1, PLT1, PLT2 and PLT6. plt2 and plt1/plt2 mutants exhibited suppressed root development and reduced drought tolerance. Analysis of interactions between HvJAZ2 and other proteins showed that HvJAZ2 does not directly interact with HvPLT1/2/6, but interacts with some other proteins. BIFC and LCA assays further confirmed the nuclear interaction between HvJAZ2 and HvMYC2. Y1H and Dual-Luciferase experiments demonstrated that HvMYC2 can bind to and activate the HvPLT2 promoter. In summary, HvJAZ2 negatively regulates root development and drought tolerance in barley by suppressing HvPLT2 expression through interacting with HvMYC2.

OsCaM1-1 Is Responsible for Salt Tolerance by Regulating Na+/K+ Homoeostasis in Rice.

Calmodulin, a highly conserved calcium-binding protein, plays a crucial role in response to salt stress. Previous studies investigated sequence and function of calmodulin members in some plants, but their roles in rice have not been fully elucidated. Three OsCaM1 genes namely OsCaM1-1/2/3 encode the same OsCaM1 protein. Here, we found that OsCaM1-1 had significantly higher expression than the other two genes under salt stress. After 4 weeks of exposure to 75 mM NaCl, OsCaM1-1 overexpressed mutants showed higher salt tolerance, while knocked-out mutants exhibited lower salt tolerance, compared to the wild type. Moreover, the oscam1-1 mutants had higher Na+ concentration and Na+/K+ ratio in both shoots and roots, less instantaneous K+ and Ca2+ fluxes in roots, compared to wild type under salt stress, indicating the involvement of OsCaM1-1 in regulation of Na+ and K+ homoeostasis via Ca2+ signal. RNA-seq analysis identified 452 differentially expressed genes (DEGs) regulated by OsCaM1-1 and salt stress, and they were mainly enriched in nucleus DNA-binding activities, including ABI5, WRKY76, WRKY48 and bHLH120 transcription factors. Knockout of OsCaM1-1 also modulated the expression of Na+ transporters, including HKT1;1, HKT1;5, SOS1, NHX1 and NHX4. In conclusion, OsCaM1-1 positively regulates salt tolerance in rice through mediating ion homoeostasis.

Prediction of heterosis in the recent rapeseed (Brassica napus) polyploid by pairing parental nucleotide sequences.

The utilization of heterosis is a successful strategy in increasing yield for many crops. However, it consumes tremendous manpower to test the combining ability of the parents in fields. Here, we applied the genomic-selection (GS) strategy and developed models that significantly increase the predictability of heterosis by introducing the concept of a regional parental genetic-similarity index (PGSI) and reducing dimension in the calculation matrix in a machine-learning approach. Overall, PGSI negatively affected grain yield and several other traits but positively influenced the thousand-seed weight of the hybrids. It was found that the C subgenome of rapeseed had a greater impact on heterosis than the A subgenome. We drew maps with overviews of quantitative-trait loci that were responsible for the heterosis (h-QTLs) of various agronomic traits. Identifications and annotations of genes underlying high impacting h-QTLs were provided. Using models that we elaborated, combining abilities between an Ogu-CMS-pool member and a potential restorer can be simulated in silico, sidestepping laborious work, such as testing crosses in fields. The achievements here provide a case of heterosis prediction in polyploid genomes with relatively large genome sizes.

Uncovering the Complexity of Perinatal Polysubstance Use Disclosure Patterns on X: Mixed Methods Study.

BACKGROUND: According to the Morbidity and Mortality Weekly Report, polysubstance use among pregnant women is prevalent, with 38.2% of those who consume alcohol also engaging in the use of one or more additional substances. However, the underlying mechanisms, contexts, and experiences of polysubstance use are unclear. Organic information is abundant on social media such as X (formerly Twitter). Traditional quantitative and qualitative methods, as well as natural language processing techniques, can be jointly used to derive insights into public opinions, sentiments, and clinical and public health policy implications. OBJECTIVE: Based on perinatal polysubstance use (PPU) data that we extracted on X from May 1, 2019, to October 31, 2021, we proposed two primary research questions: (1) What is the overall trend and sentiment of PPU discussions on X? (2) Are there any distinct patterns in the discussion trends of PPU-related tweets? If so, what are the implications for perinatal care and associated public health policies? METHODS: We used X's application programming interface to extract >6 million raw tweets worldwide containing ≥2 prenatal health- and substance-related keywords provided by our clinical team. After removing all non-English-language tweets, non-US tweets, and US tweets without disclosed geolocations, we obtained 4848 PPU-related US tweets. We then evaluated them using a mixed methods approach. The quantitative analysis applied frequency, trend analysis, and several natural language processing techniques such as sentiment analysis to derive statistics to preview the corpus. To further understand semantics and clinical insights among these tweets, we conducted an in-depth thematic content analysis with a random sample of 500 PPU-related tweets with a satisfying κ score of 0.7748 for intercoder reliability. RESULTS: Our quantitative analysis indicates the overall trends, bigram and trigram patterns, and negative sentiments were more dominant in PPU tweets (2490/4848, 51.36%) than in the non-PPU sample (1323/4848, 27.29%). Paired polysubstance use (4134/4848, 85.27%) was the most common, with the combination alcohol and drugs identified as the most mentioned. From the qualitative analysis, we identified 3 main themes: nonsubstance, single substance, and polysubstance, and 4 subthemes to contextualize the rationale of underlying PPU behaviors: lifestyle, perceptions of others' drug use, legal implications, and public health. CONCLUSIONS: This study identified underexplored, emerging, and important topics related to perinatal PPU, with significant stigmas and legal ramifications discussed on X. Overall, public sentiments on PPU were mixed, encompassing negative (2490/4848, 51.36%), positive (1884/4848, 38.86%), and neutral (474/4848, 9.78%) sentiments. The leading substances in PPU were alcohol and drugs, and the normalization of PPU discussed on X is becoming more prevalent. Thus, this study provides valuable insights to further understand the complexity of PPU and its implications for public health practitioners and policy makers to provide proper access and support to individuals with PPU.

Population-level transcriptomes reveal gene expression and splicing underlying cadmium accumulation in barley.

Genetic variation is an important determinant of gene transcription, which in turn contributes to functional and phenotypic diversity. Identification of the genetic variants controlling gene expression and alternative splicing in crops responding to cadmium (Cd), an important issue for food safety and human health, is of great value to improve our understanding of Cd accumulation-related genes. Here we report an in-depth survey of population-level transcriptome variation of barley (Hordeum vulgare) core accessions under Cd exposure. We reveal marked transcriptomic changes in response to Cd exposure, and these are largely independent of tissues. A genome-wide association study (GWAS) revealed 59 498 expression quantitative trait loci (eQTLs) and 23 854 splicing quantitative trait loci (sQTLs), leading to a complex network that covers 66.6% of the expressed genes, including 68 metal transporter genes. On average, 41.0% of sQTLs overlapped with eQTLs across different tissues, indicating that these two dimensions of transcript variation are largely independent. Moreover, we found that 34.5% of GWAS QTLs that underlie 10 Cd accumulation traits in barley are co-localized with eQTLs and sQTLs, which could imply a mechanistic role of different genetic variants affecting gene expression and alternative splicing in these traits. This study highlights the role of distal and proximal genetic effects on gene expression, splicing, and phenotypic plasticity. We anticipate that our results on the genetic control of expression and splicing underlying Cd accumulation provide a bridge to better understand genetic variation and phenotypic diversity to elucidate the mechanisms underlying Cd accumulation in plants.

Molecular evidence for adaptive evolution of drought tolerance in wild cereals.

The considerable drought tolerance of wild cereal crop progenitors has diminished during domestication in the pursuit of higher productivity. Regaining this trait in cereal crops is essential for global food security but requires novel genetic insight. Here, we assessed the molecular evidence for natural variation of drought tolerance in wild barley (Hordeum spontaneum), wild emmer wheat (Triticum dicoccoides), and Brachypodium species collected from dry and moist habitats at Evolution Canyon, Israel (ECI). We report that prevailing moist vs dry conditions have differentially shaped the stomatal and photosynthetic traits of these wild cereals in their respective habitats. We present the genomic and transcriptomic evidence accounting for differences, including co-expression gene modules, correlated with physiological traits, and selective sweeps, driven by the xeric site conditions on the African Slope (AS) at ECI. Co-expression gene module 'circadian rhythm' was linked to significant drought-induced delay in flowering time in Brachypodium stacei genotypes. African Slope-specific differentially expressed genes are important in barley drought tolerance, verified by silencing Disease-Related Nonspecific Lipid Transfer 1 (DRN1), Nonphotochemical Quenching 4 (NPQ4), and Brassinosteroid-Responsive Ring-H1 (BRH1). Our results provide new genetic information for the breeding of resilient wheat and barley in a changing global climate with increasingly frequent drought events.

Vacuolar H+-pyrophosphatase HVP10 enhances salt tolerance via promoting Na+ translocation into root vacuoles.

Vacuolar H+-pumping pyrophosphatases (VPs) provide a proton gradient for Na+ sequestration in the tonoplast; however, the regulatory mechanisms of VPs in developing salt tolerance have not been fully elucidated. Here, we cloned a barley (Hordeum vulgare) VP gene (HVP10) that was identified previously as the HvNax3 gene. Homology analysis showed VP10 in plants had conserved structure and sequence and likely originated from the ancestors of the Ceramiales order of Rhodophyta (Cyanidioschyzon merolae). HVP10 was mainly expressed in roots and upregulated in response to salt stress. After salt treatment for 3 weeks, HVP10 knockdown (RNA interference) and knockout (CRISPR/Cas9 gene editing) barley plants showed greatly inhibited growth and higher shoot Na+ concentration, Na+ transportation rate and xylem Na+ loading relative to wild-type (WT) plants. Reverse transcription quantitative polymerase chain reaction and microelectronic Ion Flux Estimation results indicated that HVP10 likely modulates Na+ sequestration into the root vacuole by acting synergistically with Na+/H+ antiporters (HvNHX1 and HvNHX4) to enhance H+ efflux and K+ maintenance in roots. Moreover, transgenic rice (Oryza sativa) lines overexpressing HVP10 also showed higher salt tolerance than the WT at both seedling and adult stages with less Na+ translocation to shoots and higher grain yields under salt stress. This study reveals the molecular mechanism of HVP10 underlying salt tolerance and highlights its potential in improving crop salt tolerance.

Structural variations and environmental specificities of flowering time-related genes in Brassica napus.

KEY MESSAGE: We found that the flowering time order of accessions in a genetic population considerably varied across environments, and homolog copies of essential flowering time genes played different roles in different locations. Flowering time plays a critical role in determining the life cycle length, yield, and quality of a crop. However, the allelic polymorphism of flowering time-related genes (FTRGs) in Brassica napus, an important oil crop, remains unclear. Here, we provide high-resolution graphics of FTRGs in B. napus on a pangenome-wide scale based on single nucleotide polymorphism (SNP) and structural variation (SV) analyses. A total of 1337 FTRGs in B. napus were identified by aligning their coding sequences with Arabidopsis orthologs. Overall, 46.07% of FTRGs were core genes and 53.93% were variable genes. Moreover, 1.94%, 0.74%, and 4.49% FTRGs had significant presence-frequency differences (PFDs) between the spring and semi-winter, spring and winter, and winter and semi-winter ecotypes, respectively. SNPs and SVs across 1626 accessions of 39 FTRGs underlying numerous published qualitative trait loci were analyzed. Additionally, to identify FTRGs specific to an eco-condition, genome-wide association studies (GWASs) based on SNP, presence/absence variation (PAV), and SV were performed after growing and observing the flowering time order (FTO) of plants in a collection of 292 accessions at three locations in two successive years. It was discovered that the FTO of plants in a genetic population changed a lot across various environments, and homolog copies of some key FTRGs played different roles in different locations. This study revealed the molecular basis of the genotype-by-environment (G × E) effect on flowering and recommended a pool of candidate genes specific to locations for breeding selection.

One-step fabrication of high-performance graphene composites from graphite solution for bio-scaffolds and flexible strain sensors.

Graphene composites possess great application potential in various fields including flexible electrodes, wearable sensors and biomedical devices owing to their excellent mechanical and electrical properties. However, it remains challenging to fabricate graphene composites-based devices with high consistency due to the gradual aggression effect of graphene during fabrication process. Herein, we propose a method for one-step fabricating graphene/polymer composite-based devices from graphite/polymer solution by using electrohydrodynamic (EHD) printing with the Weissenberg effect (EPWE). Taylor-Couette flows with high shearing speed were generated to exfoliate high-quality graphene with a rotating steel microneedle coaxially set in a spinneret tube. The effects of the rotating speed of the needle, spinneret size and precursor ingredients on the graphene concentration were discussed. As a proof of concept, EPWE was used to successfully fabricate graphene/polycaprolactone (PCL) bio-scaffolds with good biocompatibility and graphene/thermoplastic polyurethane strain sensor for detecting human motions with a maximum gauge factor more than 2400 from 40% to 50% strain. As such, this method sheds a new light on one-stepin situfabrication of graphene/polymer composite-based devices from graphite solution with low cost.

Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review.

BACKGROUND: Artificial intelligence (AI)-based chatbots can offer personalized, engaging, and on-demand health promotion interventions. OBJECTIVE: The aim of this systematic review was to evaluate the feasibility, efficacy, and intervention characteristics of AI chatbots for promoting health behavior change. METHODS: A comprehensive search was conducted in 7 bibliographic databases (PubMed, IEEE Xplore, ACM Digital Library, PsycINFO, Web of Science, Embase, and JMIR publications) for empirical articles published from 1980 to 2022 that evaluated the feasibility or efficacy of AI chatbots for behavior change. The screening, extraction, and analysis of the identified articles were performed by following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. RESULTS: Of the 15 included studies, several demonstrated the high efficacy of AI chatbots in promoting healthy lifestyles (n=6, 40%), smoking cessation (n=4, 27%), treatment or medication adherence (n=2, 13%), and reduction in substance misuse (n=1, 7%). However, there were mixed results regarding feasibility, acceptability, and usability. Selected behavior change theories and expert consultation were used to develop the behavior change strategies of AI chatbots, including goal setting, monitoring, real-time reinforcement or feedback, and on-demand support. Real-time user-chatbot interaction data, such as user preferences and behavioral performance, were collected on the chatbot platform to identify ways of providing personalized services. The AI chatbots demonstrated potential for scalability by deployment through accessible devices and platforms (eg, smartphones and Facebook Messenger). The participants also reported that AI chatbots offered a nonjudgmental space for communicating sensitive information. However, the reported results need to be interpreted with caution because of the moderate to high risk of internal validity, insufficient description of AI techniques, and limitation for generalizability. CONCLUSIONS: AI chatbots have demonstrated the efficacy of health behavior change interventions among large and diverse populations; however, future studies need to adopt robust randomized control trials to establish definitive conclusions.

Issue of Data Imbalance on Low Birthweight Baby Outcomes Prediction and Associated Risk Factors Identification: Establishment of Benchmarking Key Machine Learning Models With Data Rebalancing Strategies.

BACKGROUND: Low birthweight (LBW) is a leading cause of neonatal mortality in the United States and a major causative factor of adverse health effects in newborns. Identifying high-risk patients early in prenatal care is crucial to preventing adverse outcomes. Previous studies have proposed various machine learning (ML) models for LBW prediction task, but they were limited by small and imbalanced data sets. Some authors attempted to address this through different data rebalancing methods. However, most of their reported performances did not reflect the models' actual performance in real-life scenarios. To date, few studies have successfully benchmarked the performance of ML models in maternal health; thus, it is critical to establish benchmarks to advance ML use to subsequently improve birth outcomes. OBJECTIVE: This study aimed to establish several key benchmarking ML models to predict LBW and systematically apply different rebalancing optimization methods to a large-scale and extremely imbalanced all-payer hospital record data set that connects mother and baby data at a state level in the United States. We also performed feature importance analysis to identify the most contributing features in the LBW classification task, which can aid in targeted intervention. METHODS: Our large data set consisted of 266,687 birth records across 6 years, and 8.63% (n=23,019) of records were labeled as LBW. To set up benchmarking ML models to predict LBW, we applied 7 classic ML models (ie, logistic regression, naive Bayes, random forest, extreme gradient boosting, adaptive boosting, multilayer perceptron, and sequential artificial neural network) while using 4 different data rebalancing methods: random undersampling, random oversampling, synthetic minority oversampling technique, and weight rebalancing. Owing to ethical considerations, in addition to ML evaluation metrics, we primarily used recall to evaluate model performance, indicating the number of correctly predicted LBW cases out of all actual LBW cases, as false negative health care outcomes could be fatal. We further analyzed feature importance to explore the degree to which each feature contributed to ML model prediction among our best-performing models. RESULTS: We found that extreme gradient boosting achieved the highest recall score-0.70-using the weight rebalancing method. Our results showed that various data rebalancing methods improved the prediction performance of the LBW group substantially. From the feature importance analysis, maternal race, age, payment source, sum of predelivery emergency department and inpatient hospitalizations, predelivery disease profile, and different social vulnerability index components were important risk factors associated with LBW. CONCLUSIONS: Our findings establish useful ML benchmarks to improve birth outcomes in the maternal health domain. They are informative to identify the minority class (ie, LBW) based on an extremely imbalanced data set, which may guide the development of personalized LBW early prevention, clinical interventions, and statewide maternal and infant health policy changes.

Stomatal morphological variation contributes to global ecological adaptation and diversification of Brassica napus.

MAIN CONCLUSION: Stomatal density and guard cell length of 274 global core germplasms of rapeseed reveal that the stomatal morphological variation contributes to global ecological adaptation and diversification of Brassica napus. Stomata are microscopic structures of plants for the regulation of CO2 assimilation and transpiration. Stomatal morphology has changed substantially in the adaptation to the external environment during land plant evolution. Brassica napus is a major crop to produce oil, livestock feed and biofuel in the world. However, there are few studies on the regulatory genes controlling stomatal development and their interaction with environmental factors as well as the genetic mechanism of adaptive variation in B. napus. Here, we characterized stomatal density (SD) and guard cell length (GL) of 274 global core germplasms at seedling stage. It was found that among the significant phenotypic variation, European germplasms are mostly winter rapeseed with high stomatal density and small guard cell length. However, the germplasms from Asia (especially China) are semi-winter rapeseed, which is characterized by low stomatal density and large guard cell length. Through selective sweep analysis and homology comparison, we identified several candidate genes related to stomatal density and guard cell length, including Epidermal Patterning Factor2 (EPF2; BnaA09g23140D), Epidermal Patterning Factor Like4 (EPFL4; BnaC01g22890D) and Suppressor of LLP1 (SOL1 BnaC01g22810D). Haplotype and phylogenetic analysis showed that natural variation in EPF2, EPFL4 and SOL1 is closely associated with the winter, spring, and semi-winter rapeseed ecotypes. In summary, this study demonstrated for the first time the relation between stomatal phenotypic variation and ecological adaptation in rapeseed, which is useful for future molecular breeding of rapeseed in the context of evolution and domestication of key stomatal traits and global climate change.

Design, fabrication and application of magnetically actuated micro/nanorobots: a review.

Magnetically actuated micro/nanorobots are typical micro- and nanoscale artificial devices with favorable attributes of quick response, remote and contactless control, harmless human-machine interaction and high economic efficiency. Under external magnetic actuation strategies, they are capable of achieving elaborate manipulation and navigation in extreme biomedical environments. This review focuses on state-of-the-art progresses in design strategies, fabrication techniques and applications of magnetically actuated micro/nanorobots. Firstly, recent advances of various robot designs, including helical robots, surface walkers, ciliary robots, scaffold robots and biohybrid robots, are discussed separately. Secondly, the main progresses of common fabrication techniques are respectively introduced, and application achievements on these robots in targeted drug delivery, minimally invasive surgery and cell manipulation are also presented. Finally, a short summary is made, and the current challenges and future work for magnetically actuated micro/nanorobots are discussed.

A flexible tactile sensor that uses polyimide/graphene oxide nanofiber as dielectric membrane for vertical and lateral force detection.

Flexible force sensors are of great interest in the fields of healthcare, physiological signals, and aircraft smart skin applications because of their compatibility with curved surfaces. However, the simultaneous detection of multidirectional forces remains an engineering challenge, despite the great progress made in recent years. Herein, we present the development of a flexible capacitive force sensor capable of efficiently distinguishing normal and sliding shear forces. A two-layer electrospun polyimide/graphene oxide (PI/GO) nanofiber membrane is used as the dielectric layer, which is sandwiched between one top electrode and four symmetrically distributed bottom electrodes. This composite membrane has an improved dielectric constant, a reduced friction coefficient, and good compressibility, leading to superior performance that includes high sensitivity over a wide operational range with measured results of 3 MPa-1for 0-242 kPa (0-2.2 N) and 0.92 MPa-1for 242-550 kPa (2.2-5 N) in the normal direction; and better than 1 N-1for 0-3 N in thex- andy-axis directions. The system also has a low detection limit of 10 Pa, fast response and recovery times of 39 ms and 13 ms, respectively, a good cyclic stability of 10,000 cycles at a pressure of 176 kPa, and promising potential for use in high-temperature environments (200 °C). Moreover, a prototype 4 × 4 sensor array has been fabricated and successfully used in a robotic system to grasp objects and operate a wireless toy car. As such, the proposed system could offer superior capabilities in simultaneous multidirectional force sensing for applications such as intelligent robots, human-machine interaction, and smart skin.

Patient Trust in Physicians Matters-Understanding the Role of a Mobile Patient Education System and Patient-Physician Communication in Improving Patient Adherence Behavior: Field Study.

BACKGROUND: The ultimate goal of any prescribed medical therapy is to achieve desired outcomes of patient care. However, patient nonadherence has long been a major problem detrimental to patient health and, thus, is a concern for all health care providers. Moreover, nonadherence is extremely costly for global medical systems because of unnecessary complications and expenses. Traditional patient education programs often serve as an intervention tool to increase patients' self-care awareness, disease knowledge, and motivation to change patient behaviors for better adherence. Patient trust in physicians, patient-physician relationships, and quality of communication have also been identified as critical factors influencing patient adherence. However, little is known about how mobile patient education technologies help foster patient adherence. OBJECTIVE: This study aimed to empirically investigate whether and how a mobile patient education system (MPES) juxtaposed with patient trust can increase patient adherence to prescribed medical therapies. METHODS: This study was conducted based on a field survey of 125 patients in multiple states in the United States who have used an innovative mobile health care system for their health care education and information seeking. Partial least squares techniques were used to analyze the collected data. RESULTS: The results revealed that patient-physician communication and the use of an MPES significantly increase patients' trust in their physicians. Furthermore, patient trust has a prominent effect on patient attitude toward treatment adherence, which in turn influences patients' behavioral intention and actual adherence behavior. Based on the theory of planned behavior, the results also indicated that behavioral intention, response efficacy, and self-efficacy positively influenced patients' actual treatment adherence behavior, whereas descriptive norms and subjective norms do not play a role in this process. CONCLUSIONS: Our study is one of the first that examines the relationship between patients who actively use an MPES and their trust in their physicians. This study contributes to this context by enriching the trust literature, addressing the call to identify key patient-centered technology determinants of trust, advancing the understanding of patient adherence mechanisms, adding a new explanation of the influence of education mechanisms delivered via mobile devices on patient adherence, and confirming that the theory of planned behavior holds in this patient adherence context.

Impact of Hospital Characteristics and Governance Structure on the Adoption of Tracking Technologies for Clinical and Supply Chain Use: Longitudinal Study of US Hospitals.

BACKGROUND: Despite the increasing adoption rate of tracking technologies in hospitals in the United States, few empirical studies have examined the factors involved in such adoption within different use contexts (eg, clinical and supply chain use contexts). To date, no study has systematically examined how governance structures impact technology adoption in different use contexts in hospitals. Given that the hospital governance structure fundamentally governs health care workflows and operations, understanding its critical role provides a solid foundation from which to explore factors involved in the adoption of tracking technologies in hospitals. OBJECTIVE: This study aims to compare critical factors associated with the adoption of tracking technologies for clinical and supply chain uses and examine how governance structure types affect the adoption of tracking technologies in hospitals. METHODS: This study was conducted based on a comprehensive and longitudinal national census data set comprising 3623 unique hospitals across 50 states in the United States from 2012 to 2015. Using mixed effects population logistic regression models to account for the effects within and between hospitals, we captured and examined the effects of hospital characteristics, locations, and governance structure on adjustments to the innate development of tracking technology over time. RESULTS: From 2012 to 2015, we discovered that the proportion of hospitals in which tracking technologies were fully implemented for clinical use increased from 36.34% (782/2152) to 54.63% (1316/2409), and that for supply chain use increased from 28.58% (615/2152) to 41.3% (995/2409). We also discovered that adoption factors impact the clinical and supply chain use contexts differently. In the clinical use context, compared with hospitals located in urban areas, hospitals in rural areas (odds ratio [OR] 0.68, 95% CI 0.56-0.80) are less likely to fully adopt tracking technologies. In the context of supply chain use, the type of governance structure influences tracking technology adoption. Compared with hospitals not affiliated with a health system, implementation rates increased as hospitals affiliated with a more centralized health system-1.9-fold increase (OR 1.87, 95% CI 1.60-2.13) for decentralized or independent hospitals, 2.4-fold increase (OR 2.40, 95% CI 2.07-2.80) for moderately centralized health systems, and 3.1-fold increase for centralized health systems (OR 3.07, 95% CI 2.67-3.53). CONCLUSIONS: As the first of such type of studies, we provided a longitudinal overview of how hospital characteristics and governance structure jointly affect adoption rates of tracking technology in both clinical and supply chain use contexts, which is essential for developing intelligent infrastructure for smart hospital systems. This study informs researchers, health care providers, and policy makers that hospital characteristics, locations, and governance structures have different impacts on the adoption of tracking technologies for clinical and supply chain use and on health resource disparities among hospitals of different sizes, locations, and governance structures.

Topics and Sentiment Surrounding Vaping on Twitter and Reddit During the 2019 e-Cigarette and Vaping Use-Associated Lung Injury Outbreak: Comparative Study.

BACKGROUND: Vaping or e-cigarette use has become dramatically more popular in the United States in recent years. e-Cigarette and vaping use-associated lung injury (EVALI) cases caused an increase in hospitalizations and deaths in 2019, and many instances were later linked to unregulated products. Previous literature has leveraged social media data for surveillance of health topics. Individuals are willing to share mental health experiences and other personal stories on social media platforms where they feel a sense of community, reduced stigma, and empowerment. OBJECTIVE: This study aimed to compare vaping-related content on 2 popular social media platforms (ie, Twitter and Reddit) to explore the context surrounding vaping during the 2019 EVALI outbreak and to support the feasibility of using data from both social platforms to develop in-depth and intelligent vaping detection models on social media. METHODS: Data were extracted from both Twitter (316,620 tweets) and Reddit (17,320 posts) from July 2019 to September 2019 at the peak of the EVALI crisis. High-throughput computational analyses (sentiment analysis and topic analysis) were conducted. In addition, in-depth manual content analyses were performed and compared with computational analyses of content on both platforms (577 tweets and 613 posts). RESULTS: Vaping-related posts and unique users on Twitter and Reddit increased from July 2019 to September 2019, with the average post per user increasing from 1.68 to 1.81 on Twitter and 1.19 to 1.21 on Reddit. Computational analyses found the number of positive sentiment posts to be higher on Reddit (P<.001, 95% CI 0.4305-0.4475) and the number of negative posts to be higher on Twitter (P<.001, 95% CI -0.4289 to -0.4111). These results were consistent with the clinical content analyses results indicating that negative sentiment posts were higher on Twitter (273/577, 47.3%) than Reddit (184/613, 30%). Furthermore, topics prevalent on both platforms by keywords and based on manual post reviews included mentions of youth, marketing or regulation, marijuana, and interest in quitting. CONCLUSIONS: Post content and trending topics overlapped on both Twitter and Reddit during the EVALI period in 2019. However, crucial differences in user type and content keywords were also found, including more frequent mentions of health-related keywords on Twitter and more negative health outcomes from vaping mentioned on both Reddit and Twitter. Use of both computational and clinical content analyses is critical to not only identify signals of public health trends among vaping-related social media content but also to provide context for vaping risks and behaviors. By leveraging the strengths of both Twitter and Reddit as publicly available data sources, this research may provide technical and clinical insights to inform automatic detection of social media users who are vaping and may benefit from digital intervention and proactive outreach strategies on these platforms.

BnaGVD: A genomic variation database of rapeseed (Brassica napus).

Rapeseed (Brassica napus L.) is a typical polyploid crop and one of the most important oilseed crops worldwide. With the rapid progress on high-throughput sequencing technologies and the reduction of sequencing cost, large-scale genomic data of a specific crop have become available. However, raw sequence data are mostly deposited in the sequence read archive of the National Center of Biotechnology Information (NCBI) and the European Nucleotide Archive (ENA), which is freely accessible to all researchers. Extensive tools for practical purposes should be developed to efficiently utilize these large raw data. Here, we report a web-based rapeseed genomic variation database (BnaGVD, http://rapeseed.biocloud.net/home) from which genomic variations, such as single nucleotide polymorphisms (SNPs) and insertions/deletions (InDels) across a world-wide collection of rapeseed accessions, can be referred. The current release of the BnaGVD contains 34,591,899 high-quality SNPs and 12,281,923 high-quality InDels and provides search tools to retrieve genomic variations and gene annotations across 1,007 accessions of worldwide rapeseed germplasm. We implement a variety of built-in tools (e.g., BnaGWAS, BnaPCA, and BnaStructure) to help users perform in-depth analyses. We recommend this web resource for accelerating studies on the functional genomics and screening of molecular markers for rapeseed breeding.

Genome-wide association study reveals a patatin-like lipase relating to the reduction of seed oil content in Brassica napus.

BACKGROUND: Rapeseed (Brassica napus L.) is an important oil crop world-widely cultivated, and seed oil content (SOC) is one of the most important traits for rapeseed. To increase SOC, many efforts for promoting the function of genes on lipid biosynthesis pathway have been previously made. However, seed oil formation is a dynamic balance between lipid synthesis and breakdown. It is, therefore, also reasonable to weaken or eliminate the function of genes involved in lipid degradation for a higher final SOC. RESULTS: We applied a genome-wide association study (GWAS) on SOC in a collection of 290 core germplasm accessions. A total of 2,705,480 high-quality SNPs were used in the GWAS, and we identified BnaC07g30920D, a patatin-like lipase (PTL) gene, that was associated with SOC. In particular, six single-nucleotide-polymorphisms (SNPs) in the promoter region of BnaC07g30920D were associated with the significant reduction of SOC, leading to a 4.7-6.2% reduction of SOCs. We performed in silico analysis to show a total of 40 PTLs, which were divided into four clades, evenly distributed on the A and C subgenomes of Brassica napus. RNA-seq analysis unveiled that BnPTLs were preferentially expressed in reproductive tissues especially maturing seeds. CONCLUSIONS: We identified BnaC07g30920D, a BnPTL gene, that was associated with SOC using GWAS and performed in silico analysis of 40 PTLs in Brassica napus. The results enrich our knowledge about the SOC formation in rapeseed and facilitate the future study in functional characterization of BnPTL genes.

Creation of male-sterile lines that can be restored to fertility by exogenous methyl jasmonate for the establishment of a two-line system for the hybrid production of rice (Oryza sativa L.).

Male sterility is widely used in the production of hybrid seeds in rice, but the use of genic male sterility is limited because of the high labour cost for maintaining male-sterile lines. Previous studies using T-DNA insertional mutagenesis demonstrated that disrupting the expression of oxophytodienoic acid reductase 3 (OPR3), which is involved in the jasmonate biosynthesis pathway, results in a kind of male sterility that can be restored to fertility by exogenous jasmonate in Arabidopsis. Here, we created male-sterile mutations by editing the second and fourth exons of OsOPR7 in rice through clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated system 9. The induced mutagenesis at these exons resulted in 31.8% and 23.9% male-sterile plants in the T0 generation, respectively. We screened male-sterile lines that can be restored to fertility by exogenous methyl jasmonate in the T0, T1 and T2 rice populations and characterized the anther and agronomic traits of the transgenic plants. Results showed the successful generation of male-sterile lines through the silencing of OsOPR7, the orthologous gene of Arabidopsis OPR3, in a field crop, paving the way for the establishment of a two-line system for rice hybrid production. The system consists of a male-sterile line that can be maintained by spraying methyl jasmonate and a restoring line that confers pollen.