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

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

Vitamin D in the general population of young adults with autism in the Faroe Islands

Vitamin D deficiency has been proposed as a possible risk factor for developing autism spectrum disorder (ASD). 25-Hydroxyvitamin D3 (25(OH)D3) levels were examined in a cross-sectional population-based study in the Faroe Islands. The case group consisting of a total population cohort of 40 individuals with ASD (aged 15–24 years) had significantly lower 25(OH)D3 than their 62 typically-developing siblings and their 77 parents, and also significantly lower than 40 healthy age and gender matched comparisons. There was a trend for males having lower 25(OH)D3 than females. Effects of age, month/season of birth, IQ, various subcategories of ASD and Autism Diagnostic Observation Schedule score were also investigated, however, no association was found. The very low 25(OH)D3 in the ASD group suggests some underlying pathogenic mechanism

Can computational efficiency alone drive the evolution of modularity in neural networks?

Some biologists have abandoned the idea that computational efficiency in processing multipart tasks or input sets alone drives the evolution of modularity in biological networks. A recent study confirmed that small modular (neural) networks are relatively computationally-inefficient but large modular networks are slightly more efficient than non-modular ones. The present study determines whether these efficiency advantages with network size can drive the evolution of modularity in networks whose connective architecture can evolve. The answer is no, but the reason why is interesting. All simulations (run in a wide variety of parameter states) involving gradualistic connective evolution end in non-modular local attractors. Thus while a high performance modular attractor exists, such regions cannot be reached by gradualistic evolution. Non-gradualistic evolutionary simulations in which multi-modularity is obtained through duplication of existing architecture appear viable. Fundamentally, this study indicates that computational efficiency alone does not drive the evolution of modularity, even in large biological networks, but it may still be a viable mechanism when networks evolve by non-gradualistic means

Health care systems in Sweden and China: Legal and formal organisational aspects

<p>Abstract</p> <p>Background</p> <p>Sharing knowledge and experience internationally can provide valuable information, and comparative research can make an important contribution to knowledge about health care and cost-effective use of resources. Descriptions of the organisation of health care in different countries can be found, but no studies have specifically compared the legal and formal organisational systems in Sweden and China.</p> <p>Aim</p> <p>To describe and compare health care in Sweden and China with regard to legislation, organisation, and finance.</p> <p>Methods</p> <p>Literature reviews were carried out in Sweden and China to identify literature published from 1985 to 2008 using the same keywords. References in recent studies were scrutinized, national legislation and regulations and government reports were searched, and textbooks were searched manually.</p> <p>Results</p> <p>The health care systems in Sweden and China show dissimilarities in legislation, organisation, and finance. In Sweden there is one national law concerning health care while in China the law includes the "Hygienic Common Law" and the "Fundamental Health Law" which is under development. There is a tendency towards market-orientated solutions in both countries. Sweden has a well-developed primary health care system while the primary health care system in China is still under development and relies predominantly on hospital-based care concentrated in cities.</p> <p>Conclusion</p> <p>Despite dissimilarities in health care systems, Sweden and China have similar basic assumptions, i.e. to combine managerial-organisational efficiency with the humanitarian-egalitarian goals of health care, and both strive to provide better care for all.</p

Prevalence of treated autism spectrum disorders in Aruba

To study autism outside of a narrow range of settings previously studied, and in a particularly distinctive setting in the Caribbean. The aim of the Aruba Autism Project was to determine the prevalence of autism spectrum disorders (ASDs) in birth years 1990–1999 in Aruba. A record review study was conducted; cases were ascertained from children treated at the Child & Adolescent Psychiatry Clinic of Aruba, the first and only child psychiatry service on the island. In these 10 birth years we found a prevalence for autistic disorder (AD) of 1.9 per 1,000 (95% CI 1.2–2.8) and for autism spectrum disorders of 5.3 per 1,000 (95% CI 4.1–6.7). Comparison analysis with a cumulative incidence report from the UK, showed a similar cumulative incidence to age five in Aruba. Prevalence of ASDs in birth years 1990–1999 and cumulative incidence to age five in Aruba are similar to recent reports from the United Kingdom and the United States

The implications of autonomy: Viewed in the light of efforts to uphold patients dignity and integrity

This article focuses on Danish patients’ experience of autonomy and its interplay with dignity and integrity in their meeting with health professionals. The aim is to chart the meanings and implications of autonomy for persons whose illness places them in a vulnerable life situation. The interplay between autonomy and personal dignity in the meeting with health care staff are central concepts in the framework. Data collection and findings are based on eight qualitative semi-structured interviews with patients. Patients with acute, chronic, and life threatening diseases were represented including surgical as well as medical patients. The values associated with autonomy are in many ways vitalising, but may become so dominant, autonomy seeking, and pervasive that the patient's dignity is affected. Three types of patient behaviour were identified. (1) The proactive patient: Patients feel that they assume responsibility for their own situation, but it may be a responsibility that they find hard to bear. (2) The rejected patient: proactive patients take responsibility on many occasions but very active patients are at risk of being rejected with consequences for their dignity. (3) The knowledgeable patient: when patients are health care professionals, the patient's right of self-determination was managed in a variety of ways, sometimes the patient's right of autonomy was treated in a dignified way but the opposite was also evident. In one way, patients are active and willing to take responsibility for themselves, and at the same time they are “forced” to do so by health care staff. Patients would like health professionals to be more attentive and proactive