Design and validation of dual-point time-differentiated photoplethysmogram (2PPG) wearable for cuffless blood pressure estimation.

BACKGROUND & OBJECTIVES: Measurement of blood pressure (BP) in ambulatory patients is crucial for at high-risk cardiovascular patients. A non-obtrusive, non-occluding device that continuously measures BP via photoplethysmography will enable long-term ambulatory assessment of BP. The aim of this study is to validate the metasense 2PPG cuffless wearable design for continuous BP estimation without ECG. METHODS: A customized high-speed electronic optical sensor architecture with laterally spaced reflectance pulse oximetry was designed into a simple unobtrusive low-power wearable in the form of a watch. 78 volunteers with a mean age of 32.72 ± 7.4 years (21 to 64), 51% male, 49% female were recruited with ECG-2PPG signals acquired. The fiducial features of the 2PPG morphologies were then attributed to the estimator. A 9-1 K-fold cross-validation was applied in the ML. RESULTS: The correlation for PTT-SBP was 0.971 and for PTT-DBP was 0.954. The mean absolute error was 3.167±1.636 mmHg for SBP and 6.4 ± 3.9 mm Hg for DBP. The ambulatory estimate for SBP and DBP for an individual over 3 days with 8-hour recordings was 0.70-0.81 for SBP and 0.42-0.51 for DBP with a ± 2.65 mmHg for SBP and ±2.02 mmHg for DBP. For SBP, 98% of metasense measurements were within 15 mm Hg and for DBP, 91% of metasense measurements were within 10 mmHg CONCLUSIONS: The metasense device provides continuous, non-invasive BP estimations that are comparable to ambulatory BP meters. The portability and unobtrusiveness of this device, as well as the ability to continuously measure BP could one day enable long-term ambulatory BP measurement for precision cardiovascular therapeutic regimens.

Point-of-care AI-enhanced novice echocardiography for screening heart failure (PANES-HF).

The increasing prevalence of heart failure (HF) in ageing populations drives demand for echocardiography (echo). There is a worldwide shortage of trained sonographers and long waiting times for expert echo. We hypothesised that artificial intelligence (AI)-enhanced point-of-care echo can enable HF screening by novices. The primary endpoint was the accuracy of AI-enhanced novice pathway in detecting reduced LV ejection fraction (LVEF) < 50%. Symptomatic patients with suspected HF (N = 100, mean age 61 ± 15 years, 56% men) were prospectively recruited. Novices with no prior echo experience underwent 2-weeks' training to acquire echo images with AI guidance using the EchoNous Kosmos handheld echo, with AI-automated reporting by Us2.ai (AI-enhanced novice pathway). All patients also had standard echo by trained sonographers interpreted by cardiologists (reference standard). LVEF < 50% by reference standard was present in 27 patients. AI-enhanced novice pathway yielded interpretable results in 96 patients and took a mean of 12 min 51 s per study. The area under the curve (AUC) of the AI novice pathway was 0.880 (95% CI 0.802, 0.958). The sensitivity, specificity, positive predictive and negative predictive values of the AI-enhanced novice pathway in detecting LVEF < 50% were 84.6%, 91.4%, 78.5% and 94.1% respectively. The median absolute deviation of the AI-novice pathway LVEF from the reference standard LVEF was 6.03%. AI-enhanced novice pathway holds potential to task shift echo beyond tertiary centres and improve the HF diagnostic workflow.

Blocking of amino acid transporter OsAAP7 promoted tillering and yield by determining basic and neutral amino acids accumulation in rice.

BACKGROUND: Amino acids are not only the main form of N in rice, but also are vital for its growth and development. These processes are facilitated by amino acid transporters within the plant. Despite their significance, only a few AAP amino acid transporters have been reported. RESULTS: In this study, we observed that there were differences in the expression of amino acid transporter OsAAP7 among 521 wild cultivated rice varieties, and it directly negatively correlated with tillering and grain yield per plant. We revealed that OsAAP7 protein was localized to the endoplasmic reticulum and had absorption and transport affinity for amino acids such as phenylalanine (Phe), lysine (Lys), leucine (Leu), and arginine (Arg) using subcellular localization, yeast substrate testing, fluorescent amino acid uptake, and amino acid content determination. Further hydroponic studies showed that exogenous application of amino acids Phe, Lys and Arg inhibited the growth of axillary buds in the overexpression lines, and promoted the elongation of axillary buds in the mutant lines. Finally, RNA-seq analysis showed that the expression patterns of genes related to nitrogen, auxin and cytokinin pathways were changed in axillary buds of OsAAP7 transgenic plants. CONCLUSIONS: This study revealed the gene function of OsAAP7, and found that blocking of amino acid transporter OsAAP7 with CRISPR/Cas9 technology promoted tillering and yield by determining basic and neutral amino acids accumulation in rice.

Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.

BACKGROUND: Increasing patient loads, healthcare inflation and ageing population have put pressure on the healthcare system. Artificial intelligence and machine learning innovations can aid in task shifting to help healthcare systems remain efficient and cost effective. To gain an understanding of patients' acceptance toward such task shifting with the aid of AI, this study adapted the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), looking at performance and effort expectancy, facilitating conditions, social influence, hedonic motivation and behavioural intention. METHODS: This was a cross-sectional study which took place between September 2021 to June 2022 at the National Heart Centre, Singapore. One hundred patients, aged ≥ 21 years with at least one heart failure symptom (pedal oedema, New York Heart Association II-III effort limitation, orthopnoea, breathlessness), who presented to the cardiac imaging laboratory for physician-ordered clinical echocardiogram, underwent both echocardiogram by skilled sonographers and the experience of echocardiogram by a novice guided by AI technologies. They were then given a survey which looked at the above-mentioned constructs using the UTAUT2 framework. RESULTS: Significant, direct, and positive effects of all constructs on the behavioral intention of accepting the AI-novice combination were found. Facilitating conditions, hedonic motivation and performance expectancy were the top 3 constructs. The analysis of the moderating variables, age, gender and education levels, found no impact on behavioral intention. CONCLUSIONS: These results are important for stakeholders and changemakers such as policymakers, governments, physicians, and insurance companies, as they design adoption strategies to ensure successful patient engagement by focusing on factors affecting the facilitating conditions, hedonic motivation and performance expectancy for AI technologies used in healthcare task shifting.

Blocking of awn development-related gene OsGAD1 coordinately boosts yield and quality of Kam Sweet Rice.

Kam Sweet Rice is a high-quality local variety of Guizhou province in China, but most varieties have awns on lemma. In this study, we aimed to obtain awnless varieties of Kam Sweet Rice by blocking the awn development-related gene OsGAD1 using CRISPR/Cas9 technology. We determined that natural variations of the OsGAD1 triggered different lengths of awns of Kam Sweet Rice. We found that the awning rate of the CRISPR lines of OsGAD1 in Guxiangnuo, Goujingao and Gouhuanggang decreased by over 65%, and the number of grains per panicle and yield per plant increased by more than 17% and 20% compared to the wild-types. Furthermore, we indicated that blocking OsGAD1 resulted in an increase of over 2% in the brown rice rate and milled rice rate in these varieties. In addition, the analysis of the transcriptome revealed that the regulation of awn development and yield formation in CRISPR lines of OsGAD1 may involve genes associated with phytohormone and nitrogen pathways. These results suggest that blocking OsGAD1 in Kam Sweet Rice using CRISPR/Cas9 technology can be used for breeding programs seeking high yield and grain quality of Kam Sweet Rice.

Anti-citrullinated α-enolase peptide as a highly sensitive autoantigen in patients with rheumatoid arthritis.

Rheumatoid arthritis (RA) is the most common autoimmune rheumatic disease in Taiwan. Anti-cyclic citrullinated peptide (anti-CCP) assay is widely used for RA diagnosis; however, not all anti-CCPs are detectable in RA-joint lesions. Citrullinated α-enolase peptide (CEP), which has a unique immunodominant epitope, can be detected in synovial fluid. Here, we aimed to evaluate the potential of anti-CEP as a serologic marker for the early diagnosis of RA and a prognostic predictor of joint destruction. We also determined the association of single-nucleotide polymorphisms (SNPs) in genes with the serological status and clinical characteristics of RA. Clinical records of 30 patients with RA were collected, and their serum and DNA samples were evaluated using enzyme-linked immunosorbent assay (ELISA) and SNP cross-reaction analysis. A considerable amount of anti-CEP was detected in patients with RA, a trend similar to that of anti-CCP. Moreover, anti-CEP was considerably associated with the protein-arginine deiminase type-2 SNP rs1005753.

A Higher Estimated Glomerular Filtration Rate Is Associated with Better Survival in Subjects with Coronary Artery Disease and Heart Failure with a Mildly Reduced Ejection Fraction.

Subjects with coronary artery disease (CAD) have myocardial ischemia and associated abnormal left ventricular ejection fraction (EF). Heart failure with mildly reduced EF (41-49%) (HFmrEF) is a new subgroup of EF for heart failure. Although prognostic factors for CAD and HF with reduced EF are well known, fewer studies have been conducted on factors related to the survival of CAD and HFmrEF. We recruited study subjects with significant CAD and HFmrEF from our cardiac catheterization data bank. Data were recorded from traceable chart records from our hospital. All-cause and cardiovascular mortality were recorded until December 2019 and served as a follow-up outcome. A total of 348 subjects with CAD and HFmrEF were analyzed. The median duration of follow-up was 37 months. Seventy-eight subjects died during the follow-up period and 30 of them were due to cardiovascular causes. In univariate analyses, those who died were of older ages, and with a lower estimated glomerular filtration rate (eGFR) (47 ± 30 versus 71 ± 30 mL/minute/1.73 m2, P < 0.001), and lower usage of percutaneous coronary intervention (PCI) and beta blockers. In the Cox survival regression analysis, a higher eGFR (hazard ratio 0.980, P < 0.001) was protective, while older age and a higher serum total cholesterol (hazard ratio 1.006, P = 0.048) were related to all-cause mortality for CAD with HFmrEF. Furthermore, a higher eGFR was also associated with less cardiovascular mortality. In conclusion, for subjects with CAD and HFmrEF, a higher eGFR was protective and associated with a lower all-cause and cardiovascular mortality.

A critical review of enzymes immobilized on chitosan composites: characterization and applications.

Enzymes with industrial significance are typically used in biological processes. However, instability, high sensitivity, and impractical recovery are the major drawbacks of enzymes in practical applications. In recent years, the immobilization technology has attracted wide attention to overcoming these restrictions and improving the efficiency of enzyme applications. Chitosan (CS) is a unique functional substance with biocompatibility, biodegradability, non-toxicity, and antibacterial properties. Chitosan composites are anticipated to be widely used in the near future for a variety of purposes, including as supports for enzyme immobilization, because of their advantages. Therefor this review explores the effects of the chitosan's structure, molecular weight, degree of deacetylation on the enzyme immobilized, effect of key factors, and the enzymes immobilized on chitosan based composites for numerous applications, including the fields of biosensor, biomedical science, food industry, environmental protection, and industrial production. Moreover, this study carefully investigates the advantages and disadvantages of using these composites as well as their potential in the future.

A natural polymer-based hydrogel with shape controllability and high toughness and its application to efficient osteochondral regeneration.

Hydrogels prepared from sustainable natural polymers have broad prospects in the biological field. However, their poor mechanical properties and challenges in achieving shape control have limited their application. Herein, a novel preforming dual-effect post-enhancing method is proposed to address these issues. The method utilizes the hydrogen bonding of agar to obtain a shape-controllable preformed hydrogel at low polymer concentrations using casting, injection, or 3D printing techniques. Subsequently, the preformed hydrogel was subjected to a permeation process to form a post-enhanced multi-network (PEMN) hydrogel with hierarchical chain entanglements to ensure its high toughness, which exhibits tensile and compressive strengths of up to 0.51 MPa and 1.26 MPa with solely physically crosslinking networks. The excellent biocompatibility of the PEMN hydrogel prepared without the need for additional initiator agents under mild conditions was confirmed by both in vitro and in vivo experiments. Furthermore, the adaptability for irregular defects, suitable toughness, adhesive properties, and degradability of PEMN hydrogels are beneficial to provide mechanical support, induce endogenous cell mineralization, and accelerate the regeneration of cartilage and subchondral bone with more than 40% bone regeneration in 12 weeks. Our work has provided a novel solution to simultaneously achieve shape controllability and high toughness based on natural polymers among the already well-explored strategies for osteochondral regeneration.

Astrocyte-associated fibronectin promotes the proinflammatory phenotype of astrocytes through ß1 integrin activation.

Astrocytes are key players in neuroinflammation. In response to central nervous system (CNS) injury or disease, astrocytes undergo reactive astrogliosis, which is characterized by increased proliferation, migration, and glial fibrillary acidic protein (GFAP) expression. Activation of the transcription factor nuclear factor-κB (NF-κB) and upregulation of downstream proinflammatory mediators in reactive astrocytes induce a proinflammatory phenotype in astrocytes, thereby exacerbating neuroinflammation by establishing an inflammatory loop. In this study, we hypothesized that excessive fibronectin (FN) derived from reactive astrocytes would induce this proinflammatory phenotype in astrocytes in an autocrine manner. We exogenously treated astrocytes with monomer FN, which can be incorporated into the extracellular matrix (ECM), to mimic plasma FN extravasated through a compromised blood-brain barrier in neuroinflammation. We also induced de novo synthesis and accumulation of astrocyte-derived FN through tumor necrosis factor-α (TNF-α) stimulation. The excessive FN deposition resulting from both treatments initiated reactive astrogliosis and triggered NF-κB signaling in the cultured astrocytes. In addition, inhibition of FN accumulation in the ECM by the FN inhibitor pUR4 strongly attenuated the FN- and TNF-α-induced GFAP expression, NF-κB activation, and proinflammatory mediator production of astrocytes by interrupting FN-ß1 integrin coupling and thus the inflammatory loop. In an in vivo experiment, intrathecal injection of pUR4 considerably ameliorated FN deposition, GFAP expression, and NF-κB activation in inflamed spinal cord, suggesting the therapeutic potential of pUR4 for attenuating neuroinflammation and promoting neuronal function restoration.

Comparing the pooled cohort equations and coronary artery calcium scores in a symptomatic mixed Asian cohort.

Background: The value of pooled cohort equations (PCE) as a predictor of major adverse cardiovascular events (MACE) is poorly established among symptomatic patients. Coronary artery calcium (CAC) assessment further improves risk prediction, but non-Western studies are lacking. This study aims to compare PCE and CAC scores within a symptomatic mixed Asian cohort, and to evaluate the incremental value of CAC in predicting MACE, as well as in subgroups based on statin use. Methods: Consecutive patients with stable chest pain who underwent cardiac computed tomography were recruited. Logistic regression was performed to determine the association between risk factors and MACE. Cohort and statin-use subgroup comparisons were done for PCE against Agatston score in predicting MACE. Results: Of 501 patients included, mean (SD) age was 53.7 (10.8) years, mean follow-up period was 4.64 (0.66) years, 43.5% were female, 48.3% used statins, and 50.0% had no CAC. MI occurred in 8 subjects while 9 subjects underwent revascularization. In the general cohort, age, presence of CAC, and ln(Volume) (OR = 1.05, 7.95, and 1.44, respectively) as well as age and PCE score for the CAC = 0 subgroup (OR = 1.16 and 2.24, respectively), were significantly associated with MACE. None of the risk factors were significantly associated with MACE in the CAC > 0 subgroup. Overall, the PCE, Agatston, and their combination obtained an area under the receiver operating characteristic curve (AUC) of 0.501, 0.662, and 0.661, respectively. Separately, the AUC of PCE, Agatston, and their combination for statin non-users were 0.679, 0.753, and 0.734, while that for statin-users were 0.585, 0.615, and 0.631, respectively. Only the performance of PCE alone was statistically significant (p = 0.025) when compared between statin-users (0.507) and non-users (0.783). Conclusion: In a symptomatic mixed Asian cohort, age, presence of CAC, and ln(Volume) were independently associated with MACE for the overall subgroup, age and PCE score for the CAC = 0 subgroup, and no risk factor for the CAC > 0 subgroup. Whilst the PCE performance deteriorated in statin versus non-statin users, the Agatston score performed consistently in both groups.

OsAAP15, an amino acid transporter in response to nitrogen concentration, mediates panicle branching and grain yield in rice.

N is essential for plant architecture, particularly tillering. However, whether and how N mediates panicle branching and influences rice grain yield remains unclear. In order to identify genes and pathways associated with N-regulated panicle branching, we treated rice with different concentrations of N to determine the key genes by transcriptomic analysis and function verification. We measured panicle growth in response to N, and found that panicle branching benefits from 2 mM exogenous N, and 2-5 mM N is essential for vascular bundle, phloem, and xylem development in these branches. Interestingly, total N concentrations increased continuously with N 0-2 mM and decreased continuously with N 5-15 mM, whereas the concentrations of amino acids Tyr and Val increased continuously with N 0-15 mM in the panicle. Furthermore, N metabolism, phytohormone signal transduction, stress response, and photosynthesis pathways play important roles in response to nitrogen of regulating panicle branching. Altered expression of key N-response amino acid transporter gene OsAAP15 positively regulated panicle branching at low N concentrations, however, OsAAP15 negatively influenced it at high N concentrations. Overexpression of OsAAP15 in the field significantly increased primary and secondary branches, filled grain number, and grain yield by regulating the concentrations of amino acids Tyr and Val in the panicle. Taken together, OsAAP15, an amino acid transporter in response to nitrogen concentration, could mediate panicle branching and grain yield, and it may have applications in rice breeding to improve grain yield under extreme N concentrations.

Patient-Reported Versus Physician-Assessed Health Status in Heart Failure With Reduced and Preserved Ejection Fraction From ASIAN-HF Registry.

BACKGROUND: We aimed to assess if discordance between patient-reported Kansas City Cardiomyopathy Questionnaire (KCCQ)-overall summary (os) score and physician-assessed New York Heart Association (NYHA) class is common among patients with heart failure (HF) with reduced or preserved ejection fraction, and determine its association with outcomes. METHODS: A total of 4818 patients with HF were classified according to KCCQ-os score (range 0-100, dichotomized by median value 71.9 into high [good] versus low [bad]) and NYHA class (I/II [good] or III/IV [bad]) as concordant good (low NYHA class, high KCCQ-os score), concordant bad (high NYHA class, low KCCQ-os score), discordant worse NYHA class (high NYHA class, high KCCQ-os score), and discordant worse KCCQ-os score (low NYHA class, low-KCCQ-os score). The composite of HF hospitalization or death at 1 year was compared across groups. RESULTS: There were 2070 (43.0%) concordant good, 1099 (22.8%) concordant bad, 331 (6.9%) discordant worse NYHA class, and 1318 (27.4%) discordant worse KCCQ-os score patients. Compared with concordant good, adverse outcomes were the highest in concordant bad (HR, 2.7 [95% CI, 2.2-3.5]) followed by discordant worse KCCQ-os score (HR, 1.8 [95% CI, 1.4-2.2]) and discordant worse NYHA class (HR, 1.5 [95% CI, 1.0-2.3]); with no modification by HF phenotype (preserved versus reduced ejection fraction, Pinteraction=0.52). At 6 months, 1403 (48%) experienced clinically significant improvement in KCCQ-os score (≥5 points increase over 6 months). Patients with improved KCCQ-os at 6 months (HR, 0.65 [95% CI, 0.47-0.92]) had better outcomes and the association was not modified by HF phenotype (Pinteraction=0.40). CONCLUSIONS: One-third of patients with HF had discordance between patient-reported and clinician-assessed health status, largely attributable to worse patient-reported outcomes. Such discordance, particularly in those with discordantly worse KCCQ, should alert physicians to an increased risk of HF hospitalization and death, and prompt further assessment for potential drivers of worse patient-reported outcomes relative to physicians' assessment.

Noninvasive Classification of Glioma Subtypes Using Multiparametric MRI to Improve Deep Learning.

Background: Deep learning (DL) methods can noninvasively predict glioma subtypes; however, there is no set paradigm for the selection of network structures and input data, including the image combination method, image processing strategy, type of numeric data, and others. Purpose: To compare different combinations of DL frameworks (ResNet, ConvNext, and vision transformer (VIT)), image preprocessing strategies, magnetic resonance imaging (MRI) sequences, and numerical data for increasing the accuracy of DL models for differentiating glioma subtypes prior to surgery. Methods: Our dataset consisted of 211 patients with newly diagnosed gliomas who underwent preoperative MRI with standard and diffusion-weighted imaging methods. Different data combinations were used as input for the three different DL classifiers. Results: The accuracy of the image preprocessing strategies, including skull stripping, segment addition, and individual treatment of slices, was 5%, 10%, and 12.5% higher, respectively, than that of the other strategies. The accuracy increased by 7.5% and 10% following the addition of ADC and numeric data, respectively. ResNet34 exhibited the best performance, which was 5% and 17.5% higher than that of ConvNext tiny and VIT-base, respectively. Data Conclusions: The findings demonstrated that the addition of quantitatively numeric data, ADC images, and effective image preprocessing strategies improved model accuracy for datasets of similar size. The performance of ResNet was superior for small or medium datasets.

Prediction of subclinical atherosclerosis in low Framingham risk score individuals by using the metabolic syndrome criteria and insulin sensitivity index.

Background: Subclinical atherosclerosis can be present in individuals with an optimal cardiovascular risk factor profile. Traditional risk scores such as the Framingham risk score do not adequately capture risk stratification in low-risk individuals. The aim of this study was to determine if markers of metabolic syndrome and insulin resistance can better stratify low-risk individuals. Methods: A cross-sectional study of 101 healthy participants with a low Framingham risk score and no prior morbidities was performed to assess prevalence of subclinical atherosclerosis using computed tomography (CT) and ultrasound. Participants were compared between groups based on Metabolic Syndrome (MetS) and Insulin-Sensitivity Index (ISI-cal) scores. Results: Twenty three individuals (23%) had subclinical atherosclerosis with elevated CT Agatston score ≥1. Presence of both insulin resistance (ISI-cal <9.23) and fulfillment of at least one metabolic syndrome criterion denoted high risk, resulting in significantly improved AUC (0.706 95%CI 0.588-0.822) over the Framingham risk score in predicting elevated CT Agatston score ≥1, with net reclassification index of 50.9 ± 23.7%. High-risk patients by the new classification also exhibited significantly increased carotid intima thickness. Conclusions: The overlap of insulin resistance and presence of ≥1 criterion for metabolic syndrome may play an instrumental role in identifying traditionally low-risk individuals predisposed to future risk of atherosclerosis and its sequelae.

Gender differences in fasting and postprandial metabolic traits predictive of subclinical atherosclerosis in an asymptomatic Chinese population.

The prediction utility of Framingham Risk Score in populations with low conventional cardiovascular risk burden is limited, particularly among women. Gender-specific markers to predict cardiovascular risk in overtly healthy people are lacking. In this study we hypothesize that postprandial responses triggered by a high-calorie meal test differ by gender in their ability to triage asymptomatic subjects into those with and without subclinical atherosclerosis. A total of 101 healthy Chinese subjects (46 females, 55 males) at low risk of coronary heart disease completed the study. Subjects underwent cardiovascular imaging and postprandial blood phenotyping after consuming a standardized macronutrient meal. Prediction models were developed using logistic regression and subsequently subjected to cross-validation to obtain a de-optimized receiver operating characteristic (ROC) curve. Distinctive gender differences in postprandial trajectories of glucose, lipids and inflammatory markers were observed. We used gender-specific association with different combinations of postprandial predictors to develop 2 models for predicting risk of subclinical atherosclerosis in males (ROC AUC = 0.7867, 95% CI 0.6567, 0.9166) and females (ROC AUC = 0.9161, 95% CI 0.8340, 0.9982) respectively. We report novel postprandial models for predicting subclinical atherosclerosis in apparently healthy Asian subjects using a gender-specific approach, complementing the conventional Framingham Risk Score.Clinical Trial Registration: The trial was registered at clinicaltrials.gov as NCT03531879.

High-Resolution Digital Phenotypes From Consumer Wearables and Their Applications in Machine Learning of Cardiometabolic Risk Markers: Cohort Study.

BACKGROUND: Consumer-grade wearable devices enable detailed recordings of heart rate and step counts in free-living conditions. Recent studies have shown that summary statistics from these wearable recordings have potential uses for longitudinal monitoring of health and disease states. However, the relationship between higher resolution physiological dynamics from wearables and known markers of health and disease remains largely uncharacterized. OBJECTIVE: We aimed to derive high-resolution digital phenotypes from observational wearable recordings and to examine their associations with modifiable and inherent markers of cardiometabolic disease risk. METHODS: We introduced a principled framework to extract interpretable high-resolution phenotypes from wearable data recorded in free-living conditions. The proposed framework standardizes the handling of data irregularities; encodes contextual information regarding the underlying physiological state at any given time; and generates a set of 66 minimally redundant features across active, sedentary, and sleep states. We applied our approach to a multimodal data set, from the SingHEART study (NCT02791152), which comprises heart rate and step count time series from wearables, clinical screening profiles, and whole genome sequences from 692 healthy volunteers. We used machine learning to model nonlinear relationships between the high-resolution phenotypes on the one hand and clinical or genomic risk markers for blood pressure, lipid, weight and sugar abnormalities on the other. For each risk type, we performed model comparisons based on Brier scores to assess the predictive value of high-resolution features over and beyond typical baselines. We also qualitatively characterized the wearable phenotypes for participants who had actualized clinical events. RESULTS: We found that the high-resolution features have higher predictive value than typical baselines for clinical markers of cardiometabolic disease risk: the best models based on high-resolution features had 17.9% and 7.36% improvement in Brier score over baselines based on age and gender and resting heart rate, respectively (P<.001 in each case). Furthermore, heart rate dynamics from different activity states contain distinct information (maximum absolute correlation coefficient of 0.15). Heart rate dynamics in sedentary states are most predictive of lipid abnormalities and obesity, whereas patterns in active states are most predictive of blood pressure abnormalities (P<.001). Moreover, in comparison with standard measures, higher resolution patterns in wearable heart rate recordings are better able to represent subtle physiological dynamics related to genomic risk for cardiometabolic disease (improvement of 11.9%-22.0% in Brier scores; P<.001). Finally, illustrative case studies reveal connections between these high-resolution phenotypes and actualized clinical events, even for borderline profiles lacking apparent cardiometabolic risk markers. CONCLUSIONS: High-resolution digital phenotypes recorded by consumer wearables in free-living states have the potential to enhance the prediction of cardiometabolic disease risk and could enable more proactive and personalized health management.

The GzMYB-7D1 gene of Guizimai No.1 wheat is essential for seed anthocyanins accumulation and yield regulation.

Anthocyanins are antioxidants with important benefits for human health. Therefore, they have caught the interest of plant breeding programs. In this study, GzMYB-7D1, the key gene responsible for anthocyanin synthesis regulation in the purple Guizimai No.1 wheat, was transferred into Zhonghua 11 (ZH11) rice. Compared to wild-type ZH11, anthocyanin accumulated in the seeds of GzMYB-7D1 overexpressing lines. Furthermore, anthocyanin content kept increasing in the growing panicle of GzMYB-7D1 overexpressing lines, accumulating mostly in the rice glumes and grains during maturation, along with a concomitant steady decrease in chlorophyll. Genes related to anthocyanin synthesis, including OsPAL4, Os4CL3, OsCHS, OsDFR, OsANS, and Os3GT, exhibited much higher expression in the panicles of GzMYB-7D1 overexpressing lines than in those of wild-type ZH11. Interestingly, the grain yield per plant was significantly improved in GzMYB-7D1 overexpressing lines, as indicated by a higher tiller number per plant and branching of the secondary panicle, together with a significantly higher content of total amino acids. In conclusion, the GzMYB-7D1 gene of Guizimai No.1 wheat is essential for regulating seed anthocyanin levels and grain yield in rice, and could be applied to attain rice varieties with better nutritional value and improved yields.

BARD1 is an ATPase activating protein for OLA1.

OLA1 is a P-loop ATPase, implicated in centrosome duplication through the interactions with tumor suppressors BRCA1 and BARD1. Disruption of the interaction of OLA1 with BARD1 results in centrosome amplification. However, the molecular interplay and mechanism of the OLA1-BARD1 complex remain elusive. Here, we use a battery of biophysical, biochemical, and structural analyses to elucidate the molecular basis of the OLA1-BARD1 interaction. Our structural and enzyme kinetics analyses show this nucleotide-dependent interaction enhances the ATPase activity of OLA1 by increasing the turnover number (kcat). Unlike canonical GTPase activating proteins that act directly on the catalytic G domain, the BARD1 BRCT domain binds to the OLA1 TGS domain via a highly conserved BUDR motif. A cancer related mutation V695L on BARD1 is known to associate with centrosome abnormality. The V695L mutation reduces the BARD1 BRCT-mediated activation of OLA1. Crystallographic snapshot of the BRCT V695L mutant at 1.88 Å reveals this mutation perturbs the OLA1 binding site, resulting in reduced interaction. Altogether, our findings suggest the BARD1 BRCT domain serves as an ATPase activating protein to control OLA1 allosterically.