Ability of smooth muscles to contract in response to distension plays a crucial role in motor function of intestine. Qualitative analysis of dynamical models using myogenic active property of smooth muscles has shown well agreement with physiologic d
ata. Considered as a self-regulatory unit, function of gastrointestinal (GI) segment is assumed to be regulated by integration of basis patterns providing accumulation and propagation of intestinal content. By implementing external, depending on neural system, variable to the previous model, and considering two attaches to one another reservoirs as a physical analogue of the segmental partition of intestine, a system of six ODE equations, three for each reservoir, describes coordinated wall motions and propagation of the content from one reservoir to another. It was shown that besides negative feedback (NFB), other functional patterns, namely positive feedback (PFB) and reciprocal links (RL) are involved in regulations of filling-emptying cycle. Being integrated in a whole functional system these three patterns expressed in a matrix form represent basis elements of imaginary part of coquaternion which with identity basis component is an algebraically closed structure under addition and multiplication of its elements. A coquaternion ring may be considered as a model of inner self-regulatory functional structure providing coordinated wall motions of GI tract portions.
Quantitative methods and mathematical modeling are playing an increasingly important role across disciplines. As a result, interdisciplinary mathematics courses are increasing in popularity. However, teaching such courses at an advanced level can be
challenging. Students often arrive with different mathematical backgrounds, different interests, and divergent reasons for wanting to learn the material. Here we describe a course on stochastic processes in biology, delivered between September and December 2020 to a mixed audience of mathematicians and biologists. In addition to traditional lectures and homeworks, we incorporated a series of weekly computational challenges into the course. These challenges served to familiarize students with the main modeling concepts, and provide them with an introduction on how to implement them in a research-like setting. In order to account for the different academic backgrounds of the students, they worked on the challenges in small groups, and presented their results and code in a dedicated discussion class each week. We discuss our experience designing and implementing an element of problem-based learning in an applied mathematics course through computational challenges. We also discuss feedback from students, and describe the content of the challenges presented in the course. We provide all materials, along with example code for a number of challenges.
Despite the significant advances in life science, it still takes decades to translate a basic drug discovery into a cure for human disease. To accelerate the process from bench to bedside, interdisciplinary research (especially research involving bot
h basic research and clinical research) has been strongly recommend by many previous studies. However, the patterns and the roles of the interdisciplinary characteristics in drug research have not been deeply examined in extant studies. The purpose of this study was to characterize interdisciplinary characteristics in drug research from the perspective of translational science, and to examine the role of different kinds of interdisciplinary characteristics in translational research for drugs.
The imminent release of atlases combining highly multiplexed tissue imaging with single cell sequencing and other omics data from human tissues and tumors creates an urgent need for data and metadata standards compliant with emerging and traditional
approaches to histology. We describe the development of a Minimum Information about highly multiplexed Tissue Imaging (MITI) standard that draws on best practices from genomics and microscopy of cultured cells and model organisms.
The ways in which race, ethnicity, and ancestry are used and reported in human genomics research has wide-ranging implications for how research is translated into clinical care, incorporated into public understanding, and implemented in public policy
. Genetics researchers play an essential role in proactively dismantling genetic conceptions of race and in recognizing the social and structural factors that drive health disparities. Here, we offer commentary and concrete recommendations on the use and reporting of race, ethnicity, and ancestry across the arc of genetic research, including terminology, data harmonization, analysis, and reporting. While informed by our experiences as researchers in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, the recommendations are broadly applicable to basic and translational genomic research in diverse populations. To fully realize the benefit of diversifying genetics research beyond primarily European ancestry populations, we as genetics researchers need to make structural changes to the research process and within the research community. Considerable collaborative effort and ongoing reflection will be required to root out elements of racism from the field and generate scientific knowledge that yields broad and equitable benefit.
Modern tools for biological research, especially microscopy, have rapidly advanced in recent years, which has led to the generation of increasingly large amounts of data on a regular basis. The result is that scientists desperately need state-of-the-
art technical infrastructure for raw data storage, transfer, and processing. These scientists currently rely on outdated ways to move and store data, costing valuable time and risking loss of valuable data. While the community is aware of modern approaches to data management and high-level principles (including FAIR), highly-trained and highly-paid scientists are forced to spend time dealing with technical problems, which can ultimately costs more than providing storage and a fast network on campus. Here we provide concise arguments for better infrastructure, blueprints of possible solutions, and advice in navigating the political process of solving this issue. We suggest, as a broad solution, separate NIH-managed fund for supporting universities and institutes in deployment of data storage and long-term data sharing for all funded projects. This position statement is open for more contributors from imaging, life sciences, and other disciplines. Please contact us with your experience and perspective.
Objectives: A conflicting body of evidence suggests localized periodontal inflammation to spread systemically during pregnancy inducing adverse pregnancy outcomes. This systematic review and meta-analysis aimed to specifically evaluate the relationsh
ip between periodontitis and preeclampsia. Methods: Electronic searches were carried out in Medline, Pubmed, Cochrane Controlled Clinical Trial Register to identify and select observational case-control and cohort studies that analyzed the association between periodontal disease and preeclampsia. Prisma guidelines and Moose checklist were followed. Results: Thirty studies including six cohorts and twenty-four case-control studies were selected. Periodontitis was significantly associated with increased risk for preeclampsia, especially in a subgroup analysis including cohort studies and subgroup analysis with lower-middle-income countries. Conclusion: Periodontitis appears as a significant risk factor for preeclampsia, which might be even more pronounced in lower-middle-income countries.
The aim of this work was to study the effect of volatile suspended solid (VSS) and pH on volatile fatty acids (VFA) production from waste activated sludge (WAS) fermentation by means of batch tests. The final goal was to gain insights to enhance VFA
stream quality, with the novelty of using WAS with high sludge retention time. Results revealed that the optimum conditions to maximize VFAs and minimize nutrients and non-VFA sCOD are a VSS concentration of 5.9 g/L and initial pH adjustment to pH 10. The WAS bacterial community structures were analysed according to Next Generation Sequencing (NGS) of 16S rDNA amplicons. The results revealed changes of bacterial phyla abundance in comparison with the batch test starting condition.
Providing computational infrastructure for handling diverse intensive care unit (ICU) datasets, the R package ricu enables writing dataset-agnostic analysis code, thereby facilitating multi-center training and validation of machine learning models. T
he package is designed with an emphasis on extensibility both to new datasets as well as clinical data concepts, and currently supports the loading of around 100 patient variables corresponding to a total of 319,402 ICU admissions from 4 data sources collected in Europe and the United States. By allowing for the addition of user-specified medical concepts and data sources the aim of ricu is to foster robust, data-based intensive care research, allowing the user to externally validate their method or conclusion with relative ease, and in turn facilitating reproducible and therefore transparent work in this field.
The received wisdom on how activity affects energy expenditure is that the more activity is undertaken, the more calories will have been burned by the end of the day. Yet traditional hunter-gatherers, who lead physically hard lives, burn no more calo
ries each day than western populations living in labour-saving environments. Indeed, there is now a wealth of data, both for humans and other animals, demonstrating that long-term lifestyle changes involving increases in exercise or other physical activities do not result in commensurate increases in daily energy expenditure (DEE). This is because humans and other animals exhibit a degree of energy compensation at the organismal level, ameliorating some of the increases in DEE that would occur from the increased activity by decreasing the energy expended on other biological processes. And energy compensation can be sizable, reaching many hundreds of calories in humans. But the processes that are downregulated in the long-term to achieve energy compensation are far from clear, particularly in humans. We do not know how energy compensation is achieved. My review here of the literature on relevant exercise intervention studies, for both humans and other species, indicates conflict regarding the role that basal metabolic rate (BMR) or low level activity such as fidgeting play, if any, particularly once changes in body composition are factored out. In situations where BMR and low-level activity are not major components of energy compensation, what then drives it? I discuss how changes in mitochondrial efficiency and changes in circadian fluctuations in BMR may contribute to our understanding of energy management. Currently unexplored, these mechanisms and others may provide important insights into the mystery of how energy compensation is achieved.
