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It is well known that lifestyle changes can alter several physiological functions in the human body. For exercise and diet, these effects are used sensibly in basic therapies, as in cardiovascular diseases. However, the physiological changes induced by exercise and a modified diet also have the capacity to influence the efficacy and toxicity of several drugs, mainly by affecting different pharmacokinetic mechanisms. This pharmacological plasticity is not clinically relevant in all cases but might play an important role in altering the effects of very common drugs, particularly drugs with a narrow therapeutic window. Therefore, with this review, we provide insights into possible food–drug and exercise–drug interactions to sharpen awareness of the potential occurrence of such effects.
Objective: The NADPH oxidase Nox4 is an important source of H2O2. Nox4-derived H2O2 limits vascular inflammation and promotes smooth muscle differentiation. On this basis, the role of Nox4 for restenosis development was determined in the mouse carotid artery injury model. Methods and results: Genetic deletion of Nox4 by a tamoxifen-activated Cre-Lox-system did not impact on neointima formation in the carotid artery wire injury model. To understand this unexpected finding, time-resolved single-cell RNA-sequencing (scRNAseq) from injured carotid arteries of control mice and massive-analysis-of-cDNA-ends (MACE)-RNAseq from the neointima harvested by laser capture microdissection of control and Nox4 knockout mice was performed. This revealed that resting smooth muscle cells (SMCs) and fibroblasts exhibit high Nox4 expression, but that the proliferating de-differentiated SMCs, which give rise to the neointima, have low Nox4 expression. In line with this, the first weeks after injury, gene expression was unchanged between the carotid artery neointimas of control and Nox4 knockout mice. Conclusion: Upon vascular injury, Nox4 expression is transiently lost in the cells which comprise the neointima. NADPH oxidase 4 therefore does not interfere with restenosis development after wire-induced vascular injury.
Diabetes results from a decline in functional pancreatic β-cells, but the molecular mechanisms underlying the pathological β-cell failure are poorly understood. Here we report that large-tumor suppressor 2 (LATS2), a core component of the Hippo signaling pathway, is activated under diabetic conditions and induces β-cell apoptosis and impaired function. LATS2 deficiency in β-cells and primary isolated human islets as well as β-cell specific LATS2 ablation in mice improves β-cell viability, insulin secretion and β-cell mass and ameliorates diabetes development. LATS2 activates mechanistic target of rapamycin complex 1 (mTORC1), a physiological suppressor of autophagy, in β-cells and genetic and pharmacological inhibition of mTORC1 counteracts the pro-apoptotic action of activated LATS2. We further show a direct interplay between Hippo and autophagy, in which LATS2 is an autophagy substrate. On the other hand, LATS2 regulates β-cell apoptosis triggered by impaired autophagy suggesting an existence of a stress-sensitive multicomponent cellular loop coordinating β-cell compensation and survival. Our data reveal an important role for LATS2 in pancreatic β-cell turnover and suggest LATS2 as a potential therapeutic target to improve pancreatic β-cell survival and function in diabetes.
Objective: Nationwide data on the epidemiology, treatment characteristics, and long-term outcome of severe traumatic brain injury (TBI) in Germany is not yet existing. Neurosurgeons from the German Neurosurgery Society (DGNC) and traumatologists from the German Trauma Society (DGU), therefore, joined forces in 2016 to conceptualize a TBI module for the well-established Trauma Register of the DGU (TR-DGU). Here, we report how this “German National TBI registry (GNTR)” has been developed, implemented, and tested in a recently completed pilot period.
Methods: The conception and implementation process of the GNTR from August 2016 to February 2019 is described, and results of its 23-months long pilot period from February 2019 to December 2020 are presented. For the pilot period, TBI patients were prospectively enrolled at nine neurosurgical and traumatological hospitals across Germany. Inclusion criteria were treatment on the ICU ≥ 24h, or an ISS score ≥ 16. A variety of clinical, imaging, and laboratory parameters were collected, and the GOSE score was used to assess the outcome at discharge and 6- and 12 months follow-up.
Results: Details on the structure and dataset of the GNTR as well as milestones and pitfalls during its conception and implementation, are outlined. During the pilot period, a total of 264 TBI patients were enrolled. Their demographic characteristics, clinical, imaging, and radiological findings, and their early mortality and functional outcome are described. Furthermore, factors associated with an unfavorable outcome (GOSE 1-4) are assessed using uni- and multivariate regression analyses. Finally, problems and future directions of the GNTR are discussed.
Conclusion: The pilot period of the GNTR offers a first glance at the current epidemiology and treatment characteristics of TBI patients in Germany. More importantly, they show how a national TBI registry yielding high-quality prospective data can be developed, implemented, and tested within four years
Background: The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing fragmentation of information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the “German Corona Consensus Dataset” (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data, in particular for university medicine.
Methods: Based on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats.
Results: A core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, medical history, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined.
Conclusion: GECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.
Background: The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing segmentation of information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the “German Corona Consensus Dataset” (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data.
Methods: Based on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats.
Results: A core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, anamnesis, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined.
Conclusion: GECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.
Besides transcription, RNA decay accounts for a large proportion of regulated gene expression and is paramount for cellular functions. Classical RNA surveillance pathways, like nonsense-mediated decay (NMD), are also implicated in the turnover of non-mutant transcripts. Whereas numerous protein factors have been assigned to distinct RNA decay pathways, the contribution of long non-coding RNAs (lncRNAs) to RNA turnover remains unknown. Here we identify the lncRNA CALA as a potent regulator of RNA turnover in endothelial cells. We demonstrate that CALA forms cytoplasmic ribonucleoprotein complexes with G3BP1 and regulates endothelial cell functions. A detailed characterization of these G3BP1-positive complexes by mass spectrometry identifies UPF1 and numerous other NMD factors having cytoplasmic G3BP1-association that is CALA-dependent. Importantly, CALA silencing impairs degradation of NMD target transcripts, establishing CALA as a non-coding regulator of RNA steady-state levels in the endothelium.
Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E–P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure (“stressor reactivity,” SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.
Simple Summary: Forensic entomologists are most often tasked with determining when arthropods colonized living or deceased vertebrates. In most cases, this estimation involves humans; however, pets, livestock, and other domesticated animals can also be illegally killed or victims of neglect. Globally, there is no standard format for the case report, and much of the content is based on the personal preferences of the analyst or standards set within a country. The article below proposes a general overview of sections to be considered when drafting a case report.
Abstract: Forensic practitioners analyzing entomological evidence are faced with numerous challenges when presenting their findings to law practitioners, particularly in terms of terminology used to describe insect age, what this means for colonization time of remains, and the limitations to estimates made. Due to varying legal requirements in different countries, there is no standard format for the entomological case report prepared, nor any guidelines as to the sections that are required, optional or unnecessary in a case report. The authors herein propose sections that should be considered when drafting an entomological case report. The criteria under which entomological evidence is analyzed are discussed, as well as the limitations for each criterion. The concept of a global, standardized entomological case report is impossible to achieve due to national legislative differences, but the authors here propose a basic template which can be adapted and changed according to the needs of the practitioner. Furthermore, while the discussion is fairly detailed, capturing all differences between nations could not be accomplished, and those initiating casework for the first time are encouraged to engage other practicing forensic entomologists or professional associations within their own nation or region, to ensure a complete report is generated that meets lab or national requirements, prior to generating a finalized report.