Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

Behavioral and Neuroimaging Research on Developmental Coordination Disorder (DCD): A Combined Systematic Review and Meta-Analysis of Recent Findings

Data Availability Statement: The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s. Supplementary Material: The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2022.809455/full#supplementary-materialAim: The neurocognitive basis of Developmental Coordination Disorder (DCD; or motor clumsiness) remains an issue of continued debate. This combined systematic review and meta-analysis provides a synthesis of recent experimental studies on the motor control, cognitive, and neural underpinnings of DCD. Methods: The review included all published work conducted since September 2016 and up to April 2021. One-hundred papers with a DCD-Control comparison were included, with 1,374 effect sizes entered into a multi-level meta-analysis. Results: The most profound deficits were shown in: voluntary gaze control during movement; cognitive-motor integration; practice-/context-dependent motor learning; internal modeling; more variable movement kinematics/kinetics; larger safety margins when locomoting, and atypical neural structure and function across sensori-motor and prefrontal regions. Interpretation: Taken together, these results on DCD suggest fundamental deficits in visual-motor mapping and cognitive-motor integration, and abnormal maturation of motor networks, but also areas of pragmatic compensation for motor control deficits. Implications for current theory, future research, and evidence-based practice are discussed. Systematic Review Registration: PROSPERO, identifier: CRD42020185444.Australian Government Research Training Program Scholarship; Research Centre scheme, Australian Catholic University; Czech Science Foundation (GACR EXPRO scheme: 21-15728X); Knut and Alice Wallenberg Foundation (KAW 2020.0200).https://www.frontiersin.org/articles/10.3389/fpsyg.2022.809455/full#supplementary-materia

Prognostic Factors of Long Term Disability Due to Mental Disorders: A Systematic Review

Introduction In the past few decades, mental health problems have increasingly contributed to sickness absence and long-term disability. However, little is known about prognostic factors of return to work (RTW) and disability of persons already on sick leave due to mental health problems. Understanding these factors may help to develop effective prevention and intervention strategies to shorten the duration of disability and facilitate RTW. Method We reviewed systematically current scientific evidence about prognostic factors for mental health related long term disability, RTW and symptom recovery. Searching PubMed, PsycINFO, Embase, Cinahl and Business Source Premier, we selected articles with a publication date from January 1990 to March 2009, describing longitudinal cohort studies with a follow-up period of at least 1 year. Participants were persons on sick leave or receiving disability benefit at baseline. We assessed the methodological quality of included studies using an established criteria list. Consistent findings in at least two high quality studies were defined as strong evidence and positive findings in one high quality study were defined as limited evidence. Results Out of 796 studies, we included seven articles, all of high methodological quality describing a range of prognostic factors, according to the ICF-model categorized as health-related, personal and external factors. We found strong evidence that older age (>50 years) is associated with continuing disability and longer time to RTW. There is limited evidence for the association of other personal factors (gender, education, history of previous sickness absence, negative recovery expectation, socio-economic status), health related (stress-related and shoulder/back pain, depression/anxiety disorder) and external i.e., job-related factors (unemployment, quality and continuity of occupational care, supervisor behavior) with disability and RTW. We found limited evidence for the association of personal/external factors (education, sole breadwinner, partial/full RTW, changing work tasks) with symptom recovery. Conclusion This systematic review identifies a number of prognostic factors, some more or less consistent with findings in related literature (mental health factors, age, history of previous sickness absence, negative recovery expectation, socio-economic status, unemployment, quality and continuity of occupational care), while other prognostic factors (gender, level of education, sole breadwinner, supervisor support) conflict with existing evidence. There is still great need for research on modifiable prognostic factors of continuing disability and RTW among benefit claimants with mental health problems. Recommendations are made as to directions and methodological quality of further research, i.e., prognostic cohort studies

Targeted therapies in colorectal cancer: an integrative view by PPPM

In developed countries, colorectal cancer (CRC) is the third most common malignancy, but it is the second most frequent cause of cancer-related death. Clinicians are still faced with numerous challenges in the treatment of this disease, and future approaches which target the molecular features of the disorder will be critical for success in this disease setting. Genetic analyses of many solid tumours have shown that up to 100 protein-encoding genes are mutated. Within CRC, numerous genetic alterations have been identified in a number of pathways. Therefore, understanding the molecular pathology of CRC may present information on potential routes for treatment and may also provide valuable prognostic information. This will be particularly pertinent for molecularly targeted treatments, such as anti-vascular endothelial growth factor therapies and anti-epidermal growth factor receptor (EGFR) monoclonal antibody therapy. KRAS and BRAF mutations have been shown to predict response to anti-EGFR therapy. As EGFR can also signal via the phosphatidylinositol 3-kinase (PI3K) kinase pathway, there is considerable interest in the potential roles of members of this pathway (such as PI3K and PTEN) in predicting treatment response. Therefore, a combined approach of new techniques that allow identification of these biomarkers alongside interdisciplinary approaches to the treatment of advanced CRC will aid in the treatment decision-making process and may also serve to guide future therapeutic approaches

Valid and reliable instruments for arm-hand assessment at ICF activity level in persons with hemiplegia: a systematic review

Contains fulltext : 110141.pdf (publisher's version ) (Open Access)BACKGROUND: Loss of arm-hand performance due to a hemiparesis as a result of stroke or cerebral palsy (CP), leads to large problems in daily life of these patients. Assessment of arm-hand performance is important in both clinical practice and research. To gain more insight in e.g. effectiveness of common therapies for different patient populations with similar clinical characteristics, consensus regarding the choice and use of outcome measures is paramount. To guide this choice, an overview of available instruments is necessary. The aim of this systematic review is to identify, evaluate and categorize instruments, reported to be valid and reliable, assessing arm-hand performance at the ICF activity level in patients with stroke or cerebral palsy. METHODS: A systematic literature search was performed to identify articles containing instruments assessing arm-hand skilled performance in patients with stroke or cerebral palsy. Instruments were identified and divided into the categories capacity, perceived performance and actual performance. A second search was performed to obtain information on their content and psychometrics. RESULTS: Regarding capacity, perceived performance and actual performance, 18, 9 and 3 instruments were included respectively. Only 3 of all included instruments were used and tested in both patient populations. The content of the instruments differed widely regarding the ICF levels measured, assessment of the amount of use versus the quality of use, the inclusion of unimanual and/or bimanual tasks and the inclusion of basic and/or extended tasks. CONCLUSIONS: Although many instruments assess capacity and perceived performance, a dearth exists of instruments assessing actual performance. In addition, instruments appropriate for more than one patient population are sparse. For actual performance, new instruments have to be developed, with specific focus on the usability in different patient populations and the assessment of quality of use as well as amount of use. Also, consensus about the choice and use of instruments within and across populations is needed

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases