Interindividual Variability in Self-Monitoring of Blood Pressure Using Consumer-Purchased Wireless Devices.

BACKGROUND: Engagement with self-monitoring of blood pressure (BP) declines, on average, over time but may vary substantially by individual. OBJECTIVES: We aimed to describe different 1-year patterns (groups) of self-monitoring of BP behaviors, identify predictors of those groups, and examine the association of self-monitoring of BP groups with BP levels over time. METHODS: We analyzed device-recorded BP measurements collected by the Health eHeart Study-an ongoing prospective eCohort study-from participants with a wireless consumer-purchased device that transmitted date- and time-stamped BP data to the study through a full 12 months of observation starting from the first day they used the device. Participants received no instruction on device use. We applied clustering analysis to identify 1-year self-monitoring, of BP patterns. RESULTS: Participants had a mean age of 52 years and were male and White. Using clustering algorithms, we found that a model with three groups fit the data well: persistent daily use (9.1% of participants), persistent weekly use (21.2%), and sporadic use only (69.7%). Persistent daily use was more common among older participants who had higher Week 1 self-monitoring of BP frequency and was associated with lower BP levels than the persistent weekly use or sporadic use groups throughout the year. CONCLUSION: We identified three distinct self-monitoring of BP groups, with nearly 10% sustaining a daily use pattern associated with lower BP levels.

BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data.

Droplet-based single cell transcriptome sequencing (scRNA-seq) technology, largely represented by the 10× Genomics Chromium system, is able to measure the gene expression from tens of thousands of single cells simultaneously. More recently, coupled with the cutting-edge Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), the droplet-based system has allowed for immunophenotyping of single cells based on cell surface expression of specific proteins together with simultaneous transcriptome profiling in the same cell. Despite the rapid advances in technologies, novel statistical methods and computational tools for analyzing multi-modal CITE-Seq data are lacking. In this study, we developed BREM-SC, a novel Bayesian Random Effects Mixture model that jointly clusters paired single cell transcriptomic and proteomic data. Through simulation studies and analysis of public and in-house real data sets, we successfully demonstrated the validity and advantages of this method in fully utilizing both types of data to accurately identify cell clusters. In addition, as a probabilistic model-based approach, BREM-SC is able to quantify the clustering uncertainty for each single cell. This new method will greatly facilitate researchers to jointly study transcriptome and surface proteins at the single cell level to make new biological discoveries, particularly in the area of immunology.

[Classification, distribution and change of Uighur medicinal materials resources].

With the development and change of Uygur medicine, The sources,medicinal parts and producing area of some Uygur Medicine have changed. It is more important to master the classification, distribution and change of Uygur medicinal materials. These were more than 1 200 kinds Uygur medicine in history were resaerched by field investigation, philological research, and textual research, which main source of original plant were 140 families, 510 genera, 840 species; and source of original animal were 76 families, 107 genera, the original animal 141 species; 55 kinds of original mineral, which main producer were Xinjiang and Central Asia, West Asia, the Mediterranean, and North Africa, Southeast Asia and other provinces in China, there are individual medicinal materials from the Americas, Europe and other places. Through this study the classification, distribution, source and evolution of specific families and genera of Uygur medicine resources have mastered.It is hoped to provide theoretical basis for further research and development of Uygur medicinal materials.

Characteristics of multi-channel intermuscular directional coupling based on time-varying partial directional coherence analysis.

The human body transmits directional information between muscles during upper limb movements, and this will be particularly evident when the dominant muscle changes during movement transitions. By capturing the electromyography (EMG) signals of wrist flexion and extension continuous transition movements, we investigated the characteristics of multichannel intermuscular directional coupling and directional information transmission, and consequently explored the control mechanism of Central nervous system (CNS) and the coordination mechanism of motor muscles. Multi-channel EMG was collected from 12 healthy subjects under continuous translational movements of wrist flexion and extension, and the time-varying biased directional coherence analysis (TVPDC) model was constructed using partial directional coherence analysis (PDC) frequency domain directionality to study the directional information transfer characteristics in the time-frequency domain, screen closely related muscle pairs and perform directional coupling significance analysis. Palmaris longus (PL) played a dominant role under wrist flexion movements(WF), Extensor Carpi Radialis (ECR) played a dominant role under wrist extension movements(WE), and the remaining muscles responded to them with information and Biceps Brachii (BB) played a responsive role throughout the movement; flexor pairs had the highest positive coupling values in the beta band during Conversion action1 (MC1) and WF phases, and extensor pairs had the highest positive coupling values in the gamma band during Conversion action2(MC2) phase and the highest coupling values in the beta band during WE phase. TVPDC can effectively analyze the multichannel intermuscular directional coupling and information transmission relationship of surface electromyography under wrist flexion and extension transition movements, providing a reference for exploring the control mechanism of CNS and abnormal control mechanism in patients with motor dysfunction in a new perspective.

SECANT: a biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics.

The recent advance of single cell sequencing (scRNA-seq) technology such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) allows researchers to quantify cell surface protein abundance and RNA expression simultaneously at single cell resolution. Although CITE-seq and other similar technologies have gained enormous popularity, novel methods for analyzing this type of single cell multi-omics data are in urgent need. A limited number of available tools utilize data-driven approach, which may undermine the biological importance of surface protein data. In this study, we developed SECANT, a biology-guided SEmi-supervised method for Clustering, classification, and ANnoTation of single-cell multi-omics. SECANT is used to analyze CITE-seq data, or jointly analyze CITE-seq and scRNA-seq data. The novelties of SECANT include (1) using confident cell type label identified from surface protein data as guidance for cell clustering, (2) providing general annotation of confident cell types for each cell cluster, (3) utilizing cells with uncertain or missing cell type label to increase performance, and (4) accurate prediction of confident cell types for scRNA-seq data. Besides, as a model-based approach, SECANT can quantify the uncertainty of the results through easily interpretable posterior probability, and our framework can be potentially extended to handle other types of multi-omics data. We successfully demonstrated the validity and advantages of SECANT via simulation studies and analysis of public and in-house datasets from multiple tissues. We believe this new method will be complementary to existing tools for characterizing novel cell types and make new biological discoveries using single-cell multi-omics data.

Disentangled and Proportional Representation Learning for Multi-View Brain Connectomes.

Diffusion MRI-derived brain structural connectomes or brain networks are widely used in the brain research. However, constructing brain networks is highly dependent on various tractography algorithms, which leads to difficulties in deciding the optimal view concerning the downstream analysis. In this paper, we propose to learn a unified representation from multi-view brain networks. Particularly, we expect the learned representations to convey the information from different views fairly and in a disentangled sense. We achieve the disentanglement via an approach using unsupervised variational graph auto-encoders. We achieve the view-wise fairness, i.e. proportionality, via an alternative training routine. More specifically, we construct an analogy between training the deep network and the network flow problem. Based on the analogy, the fair representations learning is attained via a network scheduling algorithm aware of proportionality. The experimental results demonstrate that the learned representations fit various downstream tasks well. They also show that the proposed approach effectively preserves the proportionality.

Application of Simplicillium chinense for Cd and Pb biosorption and enhancing heavy metal phytoremediation of soils.

Phytoremediation is an effective approach to control soil heavy metal pollution. This study isolated a fungus strain from soils contaminated by cadmium (Cd) and lead (Pb) in Zhalong Wetland (China), which was identified as Simplicillium chinense QD10 via both genotypic and phenotypic analysis. The performance and mechanism of S. chinense QD10 in Cd and Pb adsorption was unraveled by morphological analysis and biosorption test, and its roles in ameliorating phytoremediation by Phragmites communis were tested in pot-experiments. Cd biosorption was attributed to the formation of Cd-chelate, whereas Pb was predominantly adsorbed by extracellular polymeric substances. Metal biosorption followed Langmuir isotherm, and the maximum biosorption capacity was 88.5 and 57.8 g/kg for Cd and Pb, respectively. Colonized in soils, such biosorption behavior of S. chinense QD10 can generate gradients of available Cr or Pb and drive their enrichment. Accordingly, S. chinense QD10 amendment significantly enhanced the phytoextraction of Cd and Pb by P. communis, possibly attributing to rhizospheric enrichment of Cd or Pb and defending effects on plants, explained by the significant removal of acid-extractable and reducible metals in soils and the increase of Cd and Pb content in P. communis tissues. The present study explored the mechanisms of S. chinense QD10 in Cd and Pb biosorption and proved its potential in ameliorating the phytoremediation performance at metal contaminated sites.

Molecular characterisation of a DREB gene from Sophora moorcroftiana, an endemic species of plateau.

Various plant species in the Qinghai-Tibet Plateau exposed to harsh conditions, such as low oxygen, drought, extremely low temperatures and salinity, have evolved both molecular and physiological adaptation strategies to deal with these multiple stresses. Sophora moorcroftiana (Benth.) Baker (Fabaceae) is a highly drought-resistant endemic Sophora shrub species in the Qinghai-Tibet Plateau. In our previous study, a drought-induced DREB transcription factor gene was identified and was designated as SmDREB1. SmDREB1-GFP fusion construct was introduced into Arabidopsis protoplast to characterise the function of SmDREB1 in drought resistance. The results showed that SmDREB1 targets the nucleus of Arabidopsis protoplast. Ectopic expression of SmDREB1 in model plant species Arabidopsis was performed. The transgenic lines showed increasing expressions of drought marker genes including AtDHN, AtLEA, AtPIP2 ;2, AtPIP2;3 and AtRD29, increasing activities of antioxidant enzymes and proline contents and increasing light-use efficiency under drought stress as compared with the wild-type plants; SmDREB1 transgenic lines are more resistant to drought than wild-type plants. Therefore, the SmDREB1 is a drought-resistant transcription factor gene of S. moorcroftiana and could be a candidate in genetic engineering to improve drought resistance of plateau plant species.

Transcriptomic analyses reveal biosynthetic genes related to rosmarinic acid in Dracocephalum tanguticum.

Dracocephalum tanguticum Maxim, a Lamiaceae species endemic to the Qinghai-Tibetan Plateau and adjacent regions, is an important ornamental, medicinal and aromatic herb. In this study, a comprehensive transcriptome of 18 libraries from six organs namely, roots, stems, leaves, sepals, flowers and seeds of D. tanguticum were generated. More than 100 Gb of sequence data were obtained and assembled de novo into 187,447 transcripts, including 151,463 unigenes, among which the six organs shared 17.7% (26,841). In addition, all unigenes were assigned to 362 pathways, in which 'biosynthesis of secondary metabolites' is the second enriched pathway. Furthermore, rosmarinic acid (RA) is one of the multifunctional phenolic bioactive compounds produced in some Lamiaceae species. The six organs of D. tanguticum were confirmed to produce RA. A total of 22 predicted biosynthetic genes related to RA from the transcriptome were further isolated. Two of these genes were identified as candidates by evaluating the correlation coefficient between the RA contents and the expression of the predicted biosynthetic genes in the six organs. The new sequence information will improve the knowledge of D. tanguticum, as well as provide a reference tool for future studies of biosynthetic genes related to RA in this species.