Building on an improved theoretical understanding, we analysed the robustness of 489 E. coli, Shigella, Salmonella, and fungal genome-scale metabolic models (GSMMs). In contrast to the popular "congruence theory", which explains the origin of genetic robustness as a byproduct of selection for environmental flexibility, we found no correlation between network robustness and the diversity of growth-supporting environments.  https://www.selleckchem.com/products/Decitabine.html  On the contrary, our analysis indicates that amino acid synthesis rather than carbon metabolism dominates metabolic robustness.Biofilm growth is a widespread mechanism that protects bacteria against harsh environments, antimicrobials, and immune responses. These types of conditions challenge chronic colonizers such as Helicobacter pylori but it is not fully understood how H. pylori biofilm growth is defined and its impact on H. pylori survival. To provide insights into H. pylori biofilm growth properties, we characterized biofilm formation on abiotic and biotic surfaces, identified genes required for biofilm formation, and defined the biofilm-associated gene expression of the laboratory model H. pylori strain G27. We report that H. pylori G27 forms biofilms with a high biomass and complex flagella-filled 3D structures on both plastic and gastric epithelial cells. Using a screen for biofilm-defective mutants and transcriptomics, we discovered that biofilm cells demonstrated lower transcripts for TCA cycle enzymes but higher ones for flagellar formation, two type four secretion systems, hydrogenase, and acetone metabolism. We confirmed that biofilm formation requires flagella, hydrogenase, and acetone metabolism on both abiotic and biotic surfaces. Altogether, these data suggest that H. pylori is capable of adjusting its phenotype when grown as biofilm, changing its metabolism, and re-shaping flagella, typically locomotion organelles, into adhesive structures.
  Canine mammary carcinoma (CMC) has been used as a model to investigate the pathogenesis of human breast cancer and the same grading scheme is commonly used to assess tumor malignancy in both. One key component of this grading scheme is the density of mitotic figures (MF). Current publicly available datasets on human breast cancer only provide annotations for small subsets of whole slide images (WSIs). We present a novel dataset of 21 WSIs of CMC completely annotated for MF. For this, a pathologist screened all WSIs for potential MF and structures with a similar appearance. A second expert blindly assigned labels, and for non-matching labels, a third expert assigned the final labels. Additionally, we used machine learning to identify previously undetected MF. Finally, we performed representation learning and two-dimensional projection to further increase the consistency of the annotations. Our dataset consists of 13,907 MF and 36,379 hard negatives. We achieved a mean F1-score of 0.791 on the test set and ofmean F1-score of 0.791 on the test set and of up to 0.696 on a human breast cancer dataset.MicroRNAs (miRNAs) are short (19-24 nt) non-coding RNAs that suppress the expression of protein coding genes at the post-transcriptional level. Differential expression profiles of miRNAs across a range of diseases have emerged as powerful biomarkers, making a reliable yet rapid profiling technique for miRNAs potentially essential in clinics. Here, we report an amplification-free multi-color single-molecule imaging technique that can profile purified endogenous miRNAs with high sensitivity, specificity, and reliability. Compared to previously reported techniques, our technique can discriminate single base mismatches and single-nucleotide 3'-tailing with low false positive rates regardless of their positions on miRNA. By preloading probes in Thermus thermophilus Argonaute (TtAgo), miRNAs detection speed is accelerated by more than 20 times. Finally, by utilizing the well-conserved linearity between single-molecule spot numbers and the target miRNA concentrations, the absolute average copy numbers of endogenous miRNA species in a single cell can be estimated. Thus our technique, Ago-FISH (Argonaute-based Fluorescence In Situ Hybridization), provides a reliable way to accurately profile various endogenous miRNAs on a single miRNA sensing chip.Conducting biomedical research using smartphones is a novel approach to studying health and disease that is only beginning to be meaningfully explored. Gathering large-scale, real-world data to track disease manifestation and long-term trajectory in this manner is quite practical and largely untapped. Researchers can assess large study cohorts using surveys and sensor-based activities that can be interspersed with participants' daily routines. In addition, this approach offers a medium for researchers to collect contextual and environmental data via device-based sensors, data aggregator frameworks, and connected wearable devices. The main aim of the SleepHealth Mobile App Study (SHMAS) was to gain a better understanding of the relationship between sleep habits and daytime functioning utilizing a novel digital health approach. Secondary goals included assessing the feasibility of a fully-remote approach to obtaining clinical characteristics of participants, evaluating data validity, and examining user retention patterns and data-sharing preferences. Here, we provide a description of data collected from 7,250 participants living in the United States who chose to share their data broadly with the study team and qualified researchers worldwide.The evolutionary trajectories of early lung adenocarcinoma (LUAD) have not been fully elucidated. We hypothesize that genomic analysis between pre-invasive and invasive components will facilitate the description of LUAD evolutionary patterns. We micro-dissect malignant pulmonary nodules (MPNs) into paired pre-invasive and invasive components for panel-genomic sequencing and recognize three evolutionary trajectories. Evolutionary mode 1 (EM1) demonstrates none of the common driver events between paired components, but another two modes, EM2A and EM2B, exhibit critical private alterations restricted to pre-invasive and invasive components, respectively. When ancestral clones harbor EGFR mutations, truncal mutation abundance significantly decrease after the acquisition of invasiveness, which may be associated with the intratumoral accumulation of infiltrated B cells. Harboring EGFR mutations is critical to the selective pressure and further impacts the prognosis. Our findings extend the understanding of evolutionary trajectories during invasiveness acquisition in early LUAD.