Increasing transparency and reproducibility in stroke-microbiota research: A toolbox for microbiota analysis

Homeostasis of gut microbiota is crucial in maintaining human health. Alterations, or “dysbiosis”, are increasingly implicated in human diseases, such as cancer, inflammatory bowel diseases and more recently neurological disorders. In ischemic stroke patients, gut microbial profiles are markedly different compared to healthy controls, while manipulation of microbiota in animal models of stroke, modulates outcome, further implicating microbiota in stroke pathobiology. Despite this, evidence for the involvement of specific microbes or microbial products and microbial signatures have yet to be identified, likely due to differences in methodology, data analysis and confounding variables between different studies. Here, we provide a set of guidelines to enable researchers to conduct high quality, reproducible and transparent microbiota studies, focusing on 16S rRNA sequencing in the emerging subfield of the stroke-microbiota. In doing so, we aim to facilitate novel and reproducible associations between the microbiota and brain diseases including stroke, and translation into clinical practice

Rapid Microwave Synthesis, Characterization and Reactivity of Lithium Nitride Hydride, Li4NH

Lithium nitride hydride, Li4NH, was synthesised from lithium nitride and lithium hydride over minute timescales, using microwave synthesis methods in the solid state for the first time. The structure of the microwave-synthesised powders was confirmed by powder X-ray diffraction [tetragonal space group I41/a; a = 4.8864(1) Å, c = 9.9183(2) Å] and the nitride hydride reacts with moist air under ambient conditions to produce lithium hydroxide and subsequently lithium carbonate. Li4NH undergoes no dehydrogenation or decomposition [under Ar(g)] below 773 K. A tetragonal–cubic phase transition, however, occurs for the compound at ca. 770 K. The new high temperature (HT) phase adopts an anti-fluorite structure (space group Fm 3̅ m; a = 4.9462(3) Å) with N3− and H− ions disordered on the 4a sites. Thermal treatment of Li4NH under nitrogen yields a stoichiometric mixture of lithium nitride and lithium imide (Li3N and Li2NH respectively)

Activated ATF6 Induces Intestinal Dysbiosis and Innate Immune Response to Promote Colorectal Tumorigenesis

BACKGROUND & AIMS Activating transcription factor 6 (ATF6) regulates endoplasmic reticulum stress. We studied whether ATF6 contributes to the development of colorectal cancer (CRC) using tissue from patients and transgenic mice. METHODS We analyzed data from 541 patients with CRC in The Cancer Genome Atlas database for genetic variants and aberrant expression levels of unfolded protein response genes. Findings were validated in a cohort of 83 patients with CRC in Germany. We generated mice with intestinal epithelial cell-specific expression of the active form of Atf6 (nATF6IEC) from 2 alleles (homozygous), mice with expression of nATF6IEC from 1 allele (heterozygous), and nATF6IECfl/fl mice (controls). All nATF6IEC mice were housed under either specific-pathogen-free or germ-free conditions. Cecal microbiota from homozygous nATF6IEC mice or control mice was transferred into homozygous nATF6IEC mice or control mice. nATF6IEC mice were crossed with mice with disruptions in the myeloid differentiation primary response gene 88 and toll-like receptor adaptor molecule 1 gene (Myd88/Trif-knockout mice). Intestinal tissues were collected from mice and analyzed by histology, immunohistochemistry, immunoblots, gene expression profiling of unfolded protein response and inflammatory genes, array-based comparative genome hybridization, and 16S ribosomal RNA gene sequencing. RESULTS Increased expression of ATF6 was associated with reduced disease-free survival times of patients with CRC. Homozygous nATF6IEC mice developed spontaneous colon adenomas at 12 weeks of age. Compared with controls, homozygous nATF6IEC mice had changes in the profile of their cecal microbiota, increased proliferation of intestinal epithelial cells, and loss of the mucus barrier-all preceding tumor formation. These mice had increased penetration of bacteria into the inner mucus layer and activation of signal transducer and activator of transcription 3, yet inflammation was not observed at the pretumor or tumor stages. Administration of antibiotics to homozygous nATF6IEC mice greatly reduced tumor incidence, and germ-free housing completely prevented tumorigenesis. Analysis of nATF6IEC MyD88/TRIF-knockout mice showed that tumor initiation and growth required MyD88/TRIF-dependent activation of signal transducer and activator of transcription 3. Transplantation of cecal microbiota from nATF6IEC mice and control mice, collected before tumor formation, caused tumor formation in ex-germ-free nATF6IEC mice. CONCLUSIONS In patients with CRC, ATF6 was associated with reduced time of disease-free survival. In studies of nATF6IEC mice, we found sustained intestinal activation of ATF6 in the colon to promote dysbiosis and microbiota-dependent tumorigenesis

Validity of machine learning in biology and medicine increased through collaborations across fields of expertise

Machine learning (ML) has become an essential asset for the life sciences and medicine. We selected 250 articles describing ML applications from 17 journals sampling 26 different fields between 2011 and 2016. Independent evaluation by two readers highlighted three results. First, only half of the articles shared software, 64% shared data and 81% applied any kind of evaluation. Although crucial for ensuring the validity of ML applications, these aspects were met more by publications in lower-ranked journals. Second, the authors’ scientific backgrounds highly influenced how technical aspects were addressed: reproducibility and computational evaluation methods were more prominent with computational co-authors; experimental proofs more with experimentalists. Third, 73% of the ML applications resulted from interdisciplinary collaborations comprising authors from at least two of the three disciplines: computational sciences, biology, and medicine. The results suggested collaborations between computational and experimental scientists to generate more scientifically sound and impactful work integrating knowledge from both domains. Although scientifically more valid solutions and collaborations involving diverse expertise did not correlate with impact factors, such collaborations provide opportunities to both sides: computational scientists are given access to novel and challenging real-world biological data, increasing the scientific impact of their research, and experimentalists benefit from more in-depth computational analyses improving the technical correctness of work