Image Quality Ranking Method for Microscopy

Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics

Automated cell tracking using StarDist and TrackMate [version 1; peer review: awaiting peer review]

The ability of cells to migrate is a fundamental physiological process involved in embryonic development, tissue homeostasis, immune surveillance, and wound healing. Therefore, the mechanisms governing cellular locomotion have been under intense scrutiny over the last 50 years. One of the main tools of this scrutiny is live-cell quantitative imaging, where researchers image cells over time to study their migration and quantitatively analyze their dynamics by tracking them using the recorded images. Despite the availability of computational tools, manual tracking remains widely used among researchers due to the difficulty setting up robust automated cell tracking and large-scale analysis. Here we provide a detailed analysis pipeline illustrating how the deep learning network StarDist can be combined with the popular tracking software TrackMate to perform 2D automated cell tracking and provide fully quantitative readouts. Our proposed protocol is compatible with both fluorescent and widefield images. It only requires freely available and open-source software (ZeroCostDL4Mic and Fiji), and does not require any coding knowledge from the users, making it a versatile and powerful tool for the field. We demonstrate this pipeline's usability by automatically tracking cancer cells and T cells using fluorescent and brightfield images. Importantly, we provide, as supplementary information, a detailed step-by-step protocol to allow researchers to implement it with their images

ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data

<p>Abstract</p> <p>Background</p> <p>With next-generation sequencing technologies, experiments that were considered prohibitive only a few years ago are now possible. However, while these technologies have the ability to produce enormous volumes of data, the sequence reads are prone to error. This poses fundamental hurdles when genetic diversity is investigated.</p> <p>Results</p> <p>We developed ShoRAH, a computational method for quantifying genetic diversity in a mixed sample and for identifying the individual clones in the population, while accounting for sequencing errors. The software was run on simulated data and on real data obtained in wet lab experiments to assess its reliability.</p> <p>Conclusions</p> <p>ShoRAH is implemented in C++, Python, and Perl and has been tested under Linux and Mac OS X. Source code is available under the GNU General Public License at <url>http://www.cbg.ethz.ch/software/shorah</url>.</p

Meaning behind measurement : self-comparisons affect responses to health related quality of life questionnaires

Purpose The subjective nature of quality of life is particularly pertinent to the domain of health-related quality of life (HRQOL) research. The extent to which participants’ responses are affected by subjective information and personal reference frames is unknown. This study investigated how an elderly population living with a chronic metabolic bone disorder evaluated self-reported quality of life. Methods Participants (n = 1,331) in a multi-centre randomised controlled trial for the treatment of Paget’s disease completed annual HRQOL questionnaires, including the SF-36, EQ-5D and HAQ. Supplementary questions were added to reveal implicit reference frames used when making HRQOL evaluations. Twenty-one participants (11 male, 10 female, aged 59–91 years) were interviewed retrospectively about their responses to the supplementary questions, using cognitive interviewing techniques and semi-structured topic guides. Results The interviews revealed that participants used complex and interconnected reference frames to promote response shift when making quality of life evaluations. The choice of reference frame often reflected external factors unrelated to individual health. Many participants also stated that they were unclear whether to report general or disease-related HRQOL. Conclusions It is important, especially in clinical trials, to provide instructions clarifying whether ‘quality of life’ refers to disease-related HRQOL. Information on selfcomparison reference frames is necessary for the interpretation of responses to questions about HRQOL.The Chief Scientist Office of the Scottish Government Health Directorates, The PRISM funding bodies (the Arthritis Research Campaign, the National Association for the Relief of Paget’s disease and the Alliance for Better Bone Health)Peer reviewedAuthor final versio

Transfer Functions for Protein Signal Transduction: Application to a Model of Striatal Neural Plasticity

We present a novel formulation for biochemical reaction networks in the context of signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of 'source' species, which receive input signals. Signals are transmitted to all other species in the system (the 'target' species) with a specific delay and transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and recalled to build discrete dynamical models. By separating reaction time and concentration we can greatly simplify the model, circumventing typical problems of complex dynamical systems. The transfer function transformation can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant insight, while remaining an executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modules that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. We also found that overall interconnectedness depends on the magnitude of input, with high connectivity at low input and less connectivity at moderate to high input. This general result, which directly follows from the properties of individual transfer functions, contradicts notions of ubiquitous complexity by showing input-dependent signal transmission inactivation.Comment: 13 pages, 5 tables, 15 figure

Nestin contributes to skeletal muscle homeostasis and regeneration

Nestin, a member of the cytoskeletal family of intermediate filaments, regulates the onset of myogenic differentiation through bidirectional signaling with the kinase Cdk5. Here, we show that these effects are also reflected at the organism level, as there is a loss of skeletal muscle mass in nestin(-/-) (NesKO) mice, reflected as reduced lean (muscle) mass in the mice. Further examination of muscles in male mice revealed that these effects stemmed from nestin- deficient muscles being more prone to spontaneous regeneration. When the regeneration capacity of the compromised NesKO muscle was tested by muscle injury experiments, a significant healing delay was observed. NesKO satellite cells showed delayed proliferation kinetics in conjunction with an elevation in p35 (encoded by Cdk5r1) levels and Cdk5 activity. These results reveal that nestin deficiency generates a spontaneous regenerative phenotype in skeletal muscle that relates to a disturbed proliferation cycle that is associated with uncontrolled Cdk5 activity

Novel associations for hypothyroidism include known autoimmune risk loci

Hypothyroidism is the most common thyroid disorder, affecting about 5% of the general population. Here we present the first large genome-wide association study of hypothyroidism, in 2,564 cases and 24,448 controls from the customer base of 23andMe, Inc., a personal genetics company. We identify four genome-wide significant associations, two of which are well known to be involved with a large spectrum of autoimmune diseases: rs6679677 near _PTPN22_ and rs3184504 in _SH2B3_ (p-values 3.5e-13 and 3.0e-11, respectively). We also report associations with rs4915077 near _VAV3_ (p-value 8.3e-11), another gene involved in immune function, and rs965513 near _FOXE1_ (p-value 3.1e-14). Of these, the association with _PTPN22_ confirms a recent small candidate gene study, and _FOXE1_ was previously known to be associated with thyroid-stimulating hormone (TSH) levels. Although _SH2B3_ has been previously linked with a number of autoimmune diseases, this is the first report of its association with thyroid disease. The _VAV3_ association is novel. These results suggest heterogeneity in the genetic etiology of hypothyroidism, implicating genes involved in both autoimmune disorders and thyroid function. Using a genetic risk profile score based on the top association from each of the four genome-wide significant regions in our study, the relative risk between the highest and lowest deciles of genetic risk is 2.1

Psychometric Evaluation of the HIV Stigma Scale in a Swedish Context

Background HIV-related stigma has negative consequences for infected people's lives and is a barrier to HIV prevention. Therefore valid and reliable instruments to measure stigma are needed to enable mapping of HIV stigma. This study aimed to evaluate the psychometric properties of the HIV stigma scale in a Swedish context with regard to construct validity, data quality, and reliability. Methods The HIV stigma scale, developed by Berger, Ferrans, and Lashley (2001), was distributed to a cross-sectional sample of people living with HIV in Sweden (n = 194). The psychometric evaluation included exploratory factor analysis together with an analysis of the distribution of scores, convergent validity by correlations between the HIV stigma scale and measures of emotional well-being, and an analysis of missing items and floor and ceiling effects. Reliability was assessed using Cronbach's α. Results The exploratory factor analysis suggested a four-factor solution, similar to the original scale, with the dimensions personalised stigma, disclosure concerns, negative self-image, and concerns with public attitudes. One item had unacceptably low loadings and was excluded. Correlations between stigma dimensions and emotional well-being were all in the expected direction and ranged between −0.494 and −0.210. The instrument generated data of acceptable quality except for participants who had not disclosed their HIV status to anybody. In line with the original scale, all subscales demonstrated acceptable internal consistency with Cronbach's α 0.87–0.96. Conclusion A 39-item version of the HIV stigma scale used in a Swedish context showed satisfactory construct validity and reliability. Response alternatives are suggested to be slightly revised for items assuming the disclosure of diagnosis to another person. We recommend that people that have not disclosed should skip all questions belonging to the dimension personalised stigma. Our analysis confirmed construct validity of the instrument even without this dimension

Pleosporales

One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae