QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology.

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber cross-sectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the "patchy" distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigator-specific needs and provides novel analytical approaches for quantifying muscle morphology

Effective public involvement in the HoST-D Programme for dementia home care support: From proposal and design to methods of data collection (innovative practice)

Public involvement is an important element in health and social care research. However, it is little evaluated in research. This paper discusses the utility and impact of public involvement of carers and people with dementia in a five-year programme on effective home support in dementia, from proposal and design to methods of data collection, and provides a useful guide for future research on how to effectively involve the public. The Home SupporT in Dementia (HoST-D) Programme comprises two elements of public involvement, a small reference group and a virtual lay advisory group. Involving carers and people with dementia is based on the six key values of involvement – respect, support, transparency, responsiveness, fairness of opportunity, and accountability. Carers and people with dementia gave opinions on study information, methods of data collection, an economic model, case vignettes, and a memory aid booklet, which were all taken into account. Public involvement has provided benefits to the programme whilst being considerate of the time constraints and geographical locations of members

Aircraft and ground-based measurements of hydroperoxides during the 2006 MILAGRO field campaign

International audienceMixing ratios of hydrogen peroxide and hydroxymethyl hydroperoxide were determined aboard the US Department of Energy G-1 Research Aircraft during the March 2006 MILAGRO field campaign in Mexico. Ground measurements of total hydroperoxide were made at the T1 site at Universidad Technologica de Tecámac, about 35 km NW of Mexico City. In the air and on the ground, peroxide mixing ratios near the source region were generally near 1 ppbv, much lower than had been predicted from photochemical models based on the 2003 Mexico City study. Strong southerly flow resulted in transport of pollutants from the T0 to T1 and T2 surface sites on several flight days. On these days, it was observed that peroxide concentrations slightly decreased as the G-1 flew progressively downwind. This observation is consistent with low or negative net peroxide production rates calculated for the source region and is due to the very high NOx concentrations above the Mexico City plateau. However, relatively high values of peroxide were observed at takeoff and landing near Veracruz, a site with much higher humidity and lower NOx concentrations

Odd Frequency Pairing in the Kondo Lattice

We discuss the possibility that heavy fermion superconductors involve odd-frequency pairing of the kind first considered by Berezinskii. Using a toy model for odd frequency triplet pairing in the Kondo lattice we are able to examine key properties of this new type of paired state. To make progress treating the strong $n_f=1$ constraint in the Kondo lattice model we use the technical trick of a Majorana representation of the local moments, which permits variational treatments of the model without a Gutzwiller approximation. The simplest mean field theory involves the development of bound states between the local moments and conduction electrons, characterized by a spinor order parameter. We show that this state is a stable realization of odd frequency triplet superconductivity with surfaces of gapless excitations whose spin and charge coherence factors vanish linearly in the quasiparticle energy. A $T^3$ NMR relaxation rate coexists with a linear specific heat. We discuss possible extensions of our toy model to describe heavy fermion superconductivity.Comment: 67 page

Donor genetic determinant of thymopoiesis, rs2204985, and stem cell transplantation outcome in a multipopulation cohort

\ua9 2024 The Author(s)Background: A genetic polymorphism, rs2204985, has been reported to be associated with the diversity of T-cell antigen receptor repertoire and TREC levels, reflecting the function of the thymus. As the thymus function can be assumed to be an important factor regulating the outcome of stem cell transplantation (SCT), it was of great interest that rs2204985 showed a genetic association to disease-free and overall survival in a German SCT donor cohort. Tools to predict the outcome of SCT more accurately would help in risk assessment and patient safety. Objective: To evaluate the general validity of the original genetic association found in the German cohort, we determined genetic associations between rs2204985 and the outcome of SCT in 1,473 SCT donors from four different populations. Study design: Genetic associations between rs2204985 genotype AA versus AG/GG and overall survival (OS) and disease-free survival (DFS) in 1,473 adult, allogeneic SCT from Finland, the United Kingdom, Spain, and Poland were performed using the Kaplan-Meier analysis and log-rank tests. We adjusted the survival models with covariates using Cox regression. Results: In unrelated SCT donors (N = 425), the OS of genotype AA versus AG/GG had a trend for a similar association (p = 0.049, log-rank test) as previously reported in the German cohort. The trend did not remain significant in the Cox regression analysis with covariates. No other associations were found. Conclusion: Weak support for the genetic association between rs2204985, previously also associated with thymus function, and the outcome of SCT could be found in a cohort from four populations

Preface to the special issue of the Division Energy, Resources and the Environment at the EGU General Assembly EGU22

The European Geosciences Union (EGU) is one of the leading global bottom-up societies that promotes earth, planetary and space sciences. In its annual general assemblies, EGU brings together experts from all over the world to discuss cutting-edge research and implementation of findings in their respective disciplines and beyond via its inter-and transdisciplinary sessions, and thus offers a unique forum for scientific exchange, science-policy interaction, and joint development of strategies for future research endeavours. Within that framework the Energy, Resources and the Environment (ERE) Programme Group provides the platform for discussion about adequate and reliable supplies of affordable energy and other georesources in environmentally sustainable ways. This special issue in Advances in Geosciences comprises a collection of contributions from the ERE Programme Group, which were presented at the General Assembly 2022. It was held in hybrid mode for the first time from 23–27 May 2022, after two virtual assemblies in 2020 and 2021.</p

QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber crosssectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the “patchy” distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigatorspecific needs and provides novel analytical approaches for quantifying muscle morphology

Non-Coding Changes Cause Sex-Specific Wing Size Differences between Closely Related Species of Nasonia

The genetic basis of morphological differences among species is still poorly understood. We investigated the genetic basis of sex-specific differences in wing size between two closely related species of Nasonia by positional cloning a major male-specific locus, wing-size1 (ws1). Male wing size increases by 45% through cell size and cell number changes when the ws1 allele from N. giraulti is backcrossed into a N. vitripennis genetic background. A positional cloning approach was used to fine-scale map the ws1 locus to a 13.5 kilobase region. This region falls between prospero (a transcription factor involved in neurogenesis) and the master sex-determining gene doublesex. It contains the 5′-UTR and cis-regulatory domain of doublesex, and no coding sequence. Wing size reduction correlates with an increase in doublesex expression level that is specific to developing male wings. Our results indicate that non-coding changes are responsible for recent divergence in sex-specific morphology between two closely related species. We have not yet resolved whether wing size evolution at the ws1 locus is caused by regulatory alterations of dsx or prospero, or by another mechanism. This study demonstrates the feasibility of efficient positional cloning of quantitative trait loci (QTL) involved in a broad array of phenotypic differences among Nasonia species

Expert Elicitation on Wind Farm Control

Wind farm control is an active and growing field of research in which the control actions of individual turbines in a farm are coordinated, accounting for inter-turbine aerodynamic interaction, to improve the overall performance of the wind farm and to reduce costs. The primary objectives of wind farm control include increasing power production, reducing turbine loads, and providing electricity grid support services. Additional objectives include improving reliability or reducing external impacts to the environment and communities. In 2019, a European research project (FarmConners) was started with the main goal of providing an overview of the state-of-the-art in wind farm control, identifying consensus of research findings, data sets, and best practices, providing a summary of the main research challenges, and establishing a roadmap on how to address these challenges. Complementary to the FarmConners project, an IEA Wind Topical Expert Meeting (TEM) and two rounds of surveys among experts were performed. From these events we can clearly identify an interest in more public validation campaigns. Additionally, a deeper understanding of the mechanical loads and the uncertainties concerning the effectiveness of wind farm control are considered two major research gaps