Large-scale annotated dataset for cochlear hair cell detection and classification

Our sense of hearing is mediated by cochlear hair cells, of which there are two types organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains 5-15 thousand terminally differentiated hair cells, and their survival is essential for hearing as they do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. Machine learning can be used to automate the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, rat, guinea pig, pig, primate, and human cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 107,000 hair cells which have been identified and annotated as either inner or outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair-cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to give other hearing research groups the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease

Lake Michigan’s suitability for bigheaded carp: The importance of diet flexibility and subsurface habitat

As bighead (Hypophthalmichthys nobilis) and silver carp (Hypophthalmichthys molitrix)—collectively bigheaded carp (BHC)—arrive at Lake Michigan’s doorstep, questions remain as to whether there is sufficient food to support these invasive filter‐feeding fishes in the upper Laurentian Great Lakes. Previous studies suggest that suitable BHC habitat is limited to a few productive, nearshore areas. However, those studies did not consider the influence of BHC’s diet plasticity or the presence of spatially‐discrete subsurface prey resources. This study aimed to characterise Lake Michigan’s suitability for BHC and evaluate the importance of these considerations in habitat suitability assessments.We used simulated outputs of prey biomass (phytoplankton, zooplankton, and detritus) and water temperature from a three‐dimensional biophysical model of Lake Michigan to evaluate growth rate potential (GRP, quantitative index of habitat suitability) of adult BHC throughout the entire volume of the lake. Our GRP model applied a foraging model and a bioenergetics model to translate prey concentrations and water temperatures into habitat quality indexed by individual fish growth rate. We defined suitable habitat as habitats that can support GRP ≥ 0 g g−1 day−1. We developed six feeding scenarios to evaluate the impact of diet flexibility and subsurface prey resources on suitable habitat quantity. Scenarios were defined by the number of prey types the fish could consume and the depths at which they could feed (surface or whole water column).Consistent with previous studies, we found that habitats with the highest quality were concentrated near river mouths and in eutrophic areas of Green Bay. However, in contrast to previous studies, we found suitable offshore habitat for bighead carp owing to our added considerations of diet plasticity and subsurface prey resources. For silver carp, these considerations extended suitable habitat within Green Bay and in some tributary‐influenced nearshore areas, but offshore areas remained predominantly unsuitable in all feeding scenarios. Differences in simulated habitat suitability between these two species probably reflect differences in energy density and mass of the specific fishes we used in our model. However, reports of these two species in environments where they coexist indicate that bighead carp grow at faster rates than silver carp, as our model simulated.Our vertical analysis at Muskegon, MI, U.S.A. indicates that subsurface temperature and prey biomass are not only sufficient to support bighead carp growth but provide maximum habitat quality during late summer stratification.Overall, our study demonstrates that BHC are capable of surviving and growing in much larger areas of Lake Michigan than predicted by previous studies, and thus suggests that the risk of establishment is not sufficiently reduced by low plankton concentrations. Maps generated by our model identified the potential for cross‐lake migration corridors that may facilitate and accelerate lake‐wide movements. We believe these maps could be used to prioritise surveillance protocols by identifying areas to which BHC might spread upon entering the lake. More broadly, this research demonstrates how the physiology and trophic ecology of BHC contributes to their high invasive capacity and can permit their survival in novel environments.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151968/1/fwb13382_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151968/2/fwb13382.pd

PomBase 2015: updates to the fission yeast database.

PomBase (http://www.pombase.org) is the model organism database for the fission yeast Schizosaccharomyces pombe. PomBase provides a central hub for the fission yeast community, supporting both exploratory and hypothesis-driven research. It provides users easy access to data ranging from the sequence level, to molecular and phenotypic annotations, through to the display of genome-wide high-throughput studies. Recent improvements to the site extend annotation specificity, improve usability and allow for monthly data updates. Both in-house curators and community researchers provide manually curated data to PomBase. The genome browser provides access to published high-throughput data sets and the genomes of three additional Schizosaccharomyces species (Schizosaccharomyces cryophilus, Schizosaccharomyces japonicus and Schizosaccharomyces octosporus)

A Randomized Controlled Trial of the Effect of Allopurinol on Left Ventricular Mass Index in Hemodialysis Patients

Introduction: Increased left ventricular mass index (LVMI) is associated with mortality in end-stage renal disease. LVMI regression may improve outcomes. Allopurinol has reduced LVMI in randomized controlled trials in chronic kidney disease, diabetes, and ischemic heart disease. This study investigated whether allopurinol would regress LVMI in hemodialysis patients. Methods: This was a randomized placebo-controlled double-blind multicenter trial. A total of 80 patients undergoing regular maintenance hemodialysis were recruited from NHS Tayside, NHS Greater Glasgow and Clyde and NHS Ayrshire and Arran in Scotland, UK. Participants were randomly assigned on a 1:1 ratio to 12 months of therapy with allopurinol 300 mg or placebo after each dialysis session. The primary outcome was change in LVMI, as assessed by cardiac magnetic resonance imaging (MRI) at baseline and 12 months. Secondary outcomes were change in BP, flow-mediated dilation (FMD), augmentation indices (AIx), and pulse wave velocity (PWV). Results: A total of 53 patients, with a mean age of 58 years, completed the study and had MRI follow-up data for analysis. Allopurinol did not regress LVMI (change in LVMI: placebo +3.6 ± 10.4 g/m2; allopurinol: +1.6 ± 11 g/m2; P = 0.49). Allopurinol had no demonstrable effect on BP, FMD, AIx, or PWV. Conclusion: Compared with placebo, treatment with allopurinol did not regress LVMI in this trial

Modeling the multi‐state natural history of rare diseases with heterogeneous individual patient data : a simulation study

Multi‐state survival models are used to represent the natural history of a disease, forming the basis of a health technology assessment comparing a novel treatment to current practice. Constructing such models for rare diseases is problematic, since evidence sources are typically much sparser and more heterogeneous. This simulation study investigated different one‐stage and two‐stage approaches to meta‐analyzing individual patient data (IPD) in a multi‐state survival setting when the number and size of studies being meta‐analyzed are small. The objective was to assess methods of different complexity to see when they are accurate, when they are inaccurate and when they struggle to converge due to the sparsity of data. Biologically plausible multi‐state IPD were simulated from study‐ and transition‐specific hazard functions. One‐stage frailty and two‐stage stratified models were estimated, and compared to a base case model that did not account for study heterogeneity. Convergence and the bias/coverage of population‐level transition probabilities to, and lengths of stay in, each state were used to assess model performance. A real‐world application to Duchenne Muscular Dystrophy, a neuromuscular rare disease, was conducted, and a software demonstration is provided. Models not accounting for study heterogeneity were consistently out‐performed by two‐stage models. Frailty models struggled to converge, particularly in scenarios of low heterogeneity, and predictions from models that did converge were also subject to bias. Stratified models may be better suited to meta‐analyzing disparate sources of IPD in rare disease natural history/economic modeling, as they converge more consistently and produce less biased predictions of lengths of stay

Hsp90 depletion goes wild

Hsp90 reveals phenotypic variation in the laboratory, but is Hsp90 depletion important in the wild? Recent work from Chen and Wagner in BMC Evolutionary Biology has discovered a naturally occurring Drosophila allele that downregulates Hsp90, creating sensitivity to cryptic genetic variation. Laboratory studies suggest that the exact magnitude of Hsp90 downregulation is important. Extreme Hsp90 depletion might reactivate transposable elements and/or induce aneuploidy, in addition to revealing cryptic genetic variation

PomBase: a comprehensive online resource for fission yeast.

PomBase (www.pombase.org) is a new model organism database established to provide access to comprehensive, accurate, and up-to-date molecular data and biological information for the fission yeast Schizosaccharomyces pombe to effectively support both exploratory and hypothesis-driven research. PomBase encompasses annotation of genomic sequence and features, comprehensive manual literature curation and genome-wide data sets, and supports sophisticated user-defined queries. The implementation of PomBase integrates a Chado relational database that houses manually curated data with Ensembl software that supports sequence-based annotation and web access. PomBase will provide user-friendly tools to promote curation by experts within the fission yeast community. This will make a key contribution to shaping its content and ensuring its comprehensiveness and long-term relevance

Left ventricular dysfunction with preserved ejection fraction: the most common left ventricular disorder in chronic kidney disease patients

Chronic kidney disease (CKD) is a risk factor for premature cardiovascular disease. As kidney function declines, the presence of left ventricular abnormalities increases such that by the time kidney replacement therapy is required with dialysis or kidney transplantation, more than two-thirds of patients have left ventricular hypertrophy. Historically, much research in nephrology has focussed on the structural and functional aspects of cardiac disease in CKD, particularly using echocardiography to describe these abnormalities. There is a need to translate knowledge around these imaging findings to clinical outcomes such as unplanned hospital admission with heart failure and premature cardiovascular death. Left ventricular hypertrophy and cardiac fibrosis, which are common in CKD, predispose to the clinical syndrome of heart failure with preserved left ventricular ejection fraction (HFpEF). There is a bidirectional relationship between CKD and HFpEF, whereby CKD is a risk factor for HFpEF and CKD impacts outcomes for patients with HFpEF. There have been major improvements in outcomes for patients with heart failure and reduced left ventricular ejection fraction as a result of several large randomized controlled trials. Finding therapy for HFpEF has been more elusive, although recent data suggest that sodium-glucose cotransporter 2 inhibition offers a novel evidence-based class of therapy that improves outcomes in HFpEF. These observations have emerged as this class of drugs has also become the standard of care for many patients with proteinuric CKD, suggesting that there is now hope for addressing the combination of HFpEF and CKD in parallel. In this review we summarize the epidemiology, pathophysiology, diagnostic strategies and treatment of HFpEF with a focus on patients with CKD