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Background Monitoring vital signs such as oximetry, blood pressure, and heart rate is important to follow the evolution of patients. Smartwatches are a revolution in medicine allowing the collection of such data in a continuous and organic way. However, it is still a challenge to make this information available to health care professionals to make decisions during clinical follow-up. Objective This study aims to build a digital solution that displays vital sign data from smartwatches, collected remotely, continuously, reliably, and from multiple users, with trigger warnings when abnormal results are identified. Methods This is a single-center prospective study following the guidelines “Evaluating digital health products” from the UK Health Security Agency. A digital platform with 3 different applications was created to capture and display data from the mobile phones of volunteers with smartwatches. We selected 80 volunteers who were followed for 24 weeks each, and the synchronization interval between the smartwatch and digital solution was recorded for each vital sign collected. Results In 14 weeks of project progress, we managed to recruit 80 volunteers, with 68 already registered in the digital solution. More than 2.8 million records have already been collected, without system downtime. Less than 5% of continuous heart rate measurements (bpm) were synchronized within 2 hours. However, approximately 70% were synchronized in less than 24 hours, and 90% were synchronized in less than 119 hours. Conclusions The digital solution is working properly in its role of displaying data collected from smartwatches. Vital sign values are being monitored by the research team as part of the monitoring of volunteers. Although the digital solution proved unsuitable for monitoring urgent events, it is more than suitable for use in outpatient clinical use. This digital solution, which is based on cloud technology, can be applied in the future for telemonitoring in regions lacking health care professionals. Accuracy and reliability studies still need to be performed at the end of the 24-week follow-up.

Background Composting is an important technique for environment-friendly degradation of organic material, and is a microbe-driven process. Previous metagenomic studies of composting have presented a general description of the taxonomic and functional diversity of its microbial populations, but they have lacked more specific information on the key organisms that are active during the process. Results Here we present and analyze 60 mostly high-quality metagenome-assembled genomes (MAGs) recovered from time-series samples of two thermophilic composting cells, of which 47 are potentially new bacterial species; 24 of those did not have any hits in two public MAG datasets at the 95% average nucleotide identity level. Analyses of gene content and expressed functions based on metatranscriptome data for one of the cells grouped the MAGs in three clusters along the 99-day composting process. By applying metabolic modeling methods, we were able to predict metabolic dependencies between MAGs. These models indicate the importance of coadjuvant bacteria that do not carry out lignocellulose degradation but may contribute to the management of reactive oxygen species and with enzymes that increase bioenergetic efficiency in composting, such as hydrogenases and N2O reductase. Strong metabolic dependencies predicted between MAGs revealed key interactions relying on exchange of H+, NH3, O2 and CO2, as well as glucose, glutamate, succinate, fumarate and others, highlighting the importance of functional stratification and syntrophic interactions during biomass conversion. Our model includes 22 out of 49 MAGs recovered from one composting cell data. Based on this model we highlight that Rhodothermus marinus, Thermobispora bispora and a novel Gammaproteobacterium are dominant players in chemolithotrophic metabolism and cross-feeding interactions. Conclusions The results obtained expand our knowledge of the taxonomic and functional diversity of composting bacteria and provide a model of their dynamic metabolic interactions.

Background: Thermophilic composting is a semi-engineered process carried out by diverse microbial communities. Composting is an environment friendly way of degrading biomass; its study may help uncover important biomass-degrading organisms and key enzymes. DNA sequence-based previous studies have presented a general description of the microbial-molecular features of composting, but they have lacked more specific information on the key organisms that are active during the process and their genomes. Methods: We present an analysis of metagenome-assembled genomes (MAGs) obtained from time-series samples of a thermophilic composting process in the São Paulo Zoological Park (Brazil). Our results are based on a careful analysis of MAG gene content and on metabolic modeling of their interactions. Results: We recovered 60 MAGs from sequencing datasets from two separate composting cells. Phylogenetic analysis shows that 47 of these MAGs represent novel taxa at the genus or higher levels. We have analyzed the gene repertoire of these MAGs in terms of lignocellulose degradation, secondary metabolite production, antibiotic resistance genes, denitrification genes, sulfur metabolism, hydrogen metabolism, and oxygen metabolism. For one of the composting cells we also had metatranscriptome data, which allowed a deeper analysis of 49 MAGs. This analysis showed the presence of three distinct clusters of MAGs with varying activity during the 99-day composting process. The interaction model pointed to Sphaerobacter thermophilus and Thermobispora bispora as key players in the process, as well as other bacteria that are novel. Our results also show the importance of coadjuvant bacteria and of microbial functions related to efficient bioenergetic processes during biomass conversion, such as N2O reduction and hydrogenases. A novel acidobacteria MAG encodes N2O reductase hallmark genes (nosZD). Strong metabolic dependencies predicted between MAGs revealed that cross-feeding in composting can be determined by complementary functions found in the genomes of producers and consumers, supporting the Black Queen hypothesis for co-evolutionary interactions. Conclusions: This study reveals for the first time the key bacterial players in thermophilic composting and provides a model of their dynamic metabolic interactions. These findings pave the way for more rational composting procedures and provide information that could help the development of novel biomass-degrading technologies.