Biomedical Research Practice Research Articles

Negligence in biomedical research: an anti-racist approach for substance use researchers.

Racism is embedded in the fabric of society at structural, disciplinary, hegemonic, and interpersonal levels, working as a mechanism that drives health disparities. In particular, stigmatized views of substance use get entangled with racialization, serving as a tool to uphold oppressive systems. While national health institutions have made commitments to dismantle these systems in the United States, anti-racism has not been integrated into biomedical research practice. The ways in which substance use researchers use and interpret race data-without engaging in structural racism as a mechanism of health inequity-can only be described as inadequate. Drawing upon concepts from the Public Health Critical Race praxis, QuantCrit, and an anti-racism research framework, we recommend a set of guidelines to help biomedical researchers conceptualize and engage with race more responsibly in substance use research.

ВЛИЯНИЕ ЛЕКТИНА Paenibacillus polymyxa 1460 (ЛII) НА ЛИПИДНЫЙ СПЕКТР КРОВИ САМЦОВ КРЫС ПРИ АНТИБИОТИКО-АССОЦИИРОВАННОМ ДИСБАКТЕРИОЗЕ

Paenibacillus polymyxa 1460 lectin (LII) isolated from the surface of soil nitrogen-fixing bacteria were shown to, contributes to the optimization of lipid metabolism in the organism of male albino rats with antibiotic-associated dysbacteriosis leading to the normal are important biochemical parameters in blood such as total cholesterol (TC), high density lipoproteins (HDL-C), low density lipoprotein (TC-LDL), lipoprotein very low density (XC-VLDL). The study of the effect of Paenibacillus polymyxa 1460 (LII) lectin on animal metabolism is important for understanding the mechanisms underlying the metabolic activity of these substances, and reveals the possibilities of its application in the practice of biomedical research with the prospect of its use as biologically active substances.

Human and animal intestinal commensals and probiotics vs modern challenges of biosafety: problems and prospects.

The appearance of an array of data on the study of the intestinal microbiota in Metazoa has significantly expanded our understanding of the role of commensals in the control of a wide range of physiological functions in higher organisms in norm and pathology. In the intestine, where the microbial load significantly exceeds the number of microorganisms of other ecosystems, the components of the intestinal microbiota are a constant source of stimuli that induce activation of the host immune system. The introduction into practice of biomedical research of innovative high-resolution methods, includingmulti-omics technologies, has brought data that change our understanding of intestinal commensals, including probiotics with GRAS status, widely used in medicine, agriculture and biotechnology. The ability of these bacteria to induce negative processes in the host body that are beneficial for bacterial proliferation and expansion revealed a clear lack of our knowledge about the logic of their life and the mechanisms of interaction with eukaryotic cells. This determines the urgent need for comprehensive research of probiotics and the development of standardization of their safety assessment. Apriori's confidence in the exceptional benefit of the bacteria widely used in medicine, agriculture and biotechnology has determined the seriously omission in our control system today - the lack of standardization of studies for the safety assessment of bacteria with GRAS status . The moment has come when it became clear that this gap should be promptly filled and that only exact understanding the molecular base of interacting the microbes with eukaryotic cells can provide the foundation for effective practical developments in controlling the evolution of bacterial virulence and probiotic safety strategy, as well as the competent use of genetic technologies for monitoring the environment and managing infectious processes, thus avoiding the dramatic consequences of large-scale interventions in the micro and macro worlds.

Considering hormones as sex- and gender-related factors in biomedical research: Challenging false dichotomies and embracing complexity

The inclusion of sex and gender considerations in biomedicine has been increasing in light of calls from research and funding agencies, governmental bodies, and advocacy groups to direct research attention to these issues. Although the inclusion of both female and male participants is often an important element, overreliance on a female-male binary tends to oversimplify the interactions between sex- and gender-related factors and health, and runs a risk of being influenced by cultural stereotypes about sex and gender. When biomedical researchers are examining how hormones associated with gender and sex may influence pathways of interest, it is of crucial importance to approach this work with a critical lens on the rhetoric used, and in ways that acknowledge the complexity of hormone physiology. Here, we document the ways in which discourses around sex, gender and hormones shape our scientific thinking and practice in biomedical research, and review how the existing scientific knowledge about hormones reflects a complex and dynamic reality that is often not reflected outside of specialist niches of hormone biology. Where biomedical scientists take up sex- and gender-associated hormones as a way of addressing sex and gender considerations, it is valuable for us to bring a critical lens to the rhetoric and discourses used, to employ a sex contextualist approach in designing experimentation, and be rigorous and reflexive about the approaches used in analysis and interpretation of data. These strategies will allow us to design experimentation that goes beyond binaries, and grapples more directly with the material intricacies of sex, gender, and hormones.

Practice on Biomedical Research and Barriers Experienced by The Post-Graduate Medical Students in Bangladesh

Background: Research experience in medical education is strongly related to post graduate course curriculum and is also highly associated with future career achievements but conducting research is a difficult task at student level. Many hurdles are faced by post-graduate medical students during conducting biomedical research in Bangladesh. Previously doctors were either clinicians or researchers but now it is realized that a good clinician is a good researcher and able to be a competent physician & scientist. This study was conducted to find out practice on biomedical research and barriers experienced by the post-graduate medical students during conducting it in Bangladesh. Methods: This cross-sectional type of descriptive study was carried out in the different medical colleges and Universities all over the Bangladesh over a period of 12 months from January to December 2020 among the postgraduate students of different medical colleges. Approval from the Ethical Review Committee (ERC) of Rajshahi Medical College was obtained prior to the commencement of the study and convenient sampling technique was used. Pre-designed, validated, structured questionnaire was used to collect data from 325 respondents on practice of biomedical research and 5-point Likert scale was used for assessment of barriers to its practice. Results: Regarding practice on research, 35.10% respondents had satisfactory practice on biomedical research and only 13.20% had published their research report in journals. Lack of research training & necessary skills (73.80%), lack of fund (68.80%), lack of interest & motivation (66.20%) and lack of appropriate knowledge (65.50%) were commonly faced barrier by the post-graduate medical students. Students who were in Ph. D (100%) and MPH course (68.20%) had more practice on biomedical research than those who were in MD/MS (35.80%), M. Phil (32.40%), FCPS (39.20%) and Diploma (4.90%) courses (p < 0.05). Thesis part (39.50%) and dissertation part (39.20%) post-graduate students had also more practice on biomedical research than those who were in Diploma (4.90%) courses (p < 0.05). But relationship of practice on biomedical research of the respondents was not statistically significant with age, gender, religion, type of medical college of MBBS passing, marital status, parental and spouse educational status (p > 0.05). Conclusion: The study revealed that the post-graduate medical students faced various types of difficulties during conducting research. So, respective higher authorities must be careful to solve their problems during conducting biomedical research. JOPSOM 2021; 41(1):25-34

How should communities be meaningfully engaged (if at all) when setting priorities for biomedical research? Perspectives from the biomedical research community

BackgroundThere is now rising consensus that community engagement is ethically and scientifically essential for all types of health research. Yet debate continues about the moral aims, methods and appropriate timing in the research cycle for community engagement to occur, and whether the answer should vary between different types of health research. Co-design and collaborative partnership approaches that involve engagement during priority-setting, for example, are common in many forms of applied health research but are not regular practice in biomedical research. In this study, we empirically examine the normative question: should communities be engaged when setting priorities for biomedical research projects, and, if so, how and for what purpose?MethodsWe conducted in-depth interviews with 31 members of the biomedical research community from the UK, Australia, and African countries who had engaged communities in their work. Interview data were thematically analysed.ResultsOur study shows that biomedical researchers and community engagement experts strongly support engagement in biomedical research priority-setting, except under certain circumstances where it may be harmful to communities. However, they gave two distinct responses on what ethical purpose it should serve—either empowerment or instrumental goals—and their perspectives on how it should achieve those goals also varied. Three engagement approaches were suggested: community-initiated, synergistic, and consultative. Pre-engagement essentials and barriers to meaningful engagement in biomedical research priority-setting are also reported.ConclusionsThis study offers initial evidence that meaningful engagement in priority-setting should potentially be defined slightly differently for biomedical research relative to certain types of applied health research and that engagement practice in biomedical research should not be dominated by instrumental goals and approaches, as is presently the case.

Modeling issues in experimental toxicology and medicine. Zero-order biomodels

Introduction. The creation of adequate models for studying the processes of human interaction with the environment is a key problem of modern experimental biology and medicine. This is due to the fact that both the results of the conducted studies and the recommendations developed on their basis depend on the choice of the biological object and the characteristics of the factor directly affecting it. It should be noted that errors related to both the discrepancy between the developed experimental pathology and the simulated conditions for humans, and the choice of a method for assessing the safety of xenobiotics are critical and can lead to serious consequences. The study aims to determine the existing trends in biomodeling and extrapolation of the results currently being implemented in experimental toxicology and medicine based on the analysis of literature data. Materials and methods. We have used forty five domestic and foreign scientific publications as materials. The research method was the analysis and generalization of the materials presented in scientific publications. Results. The scientists considered such components of extrapolation modeling as the creation of an adequate model, compliance with the principles of proper laboratory, as well as extrapolation of the obtained data to humans. We have given the definition of an experimental model of the disease as a condition developing in a laboratory animal under the influence of an etiological factor, which most fully reflects the main manifestations of the disease that arose on the basis of a common human and used biomodel of pathogenesis. We introduced the term "zero-order biomodels" and defined it as an object used for biomodeling and also presented a classification of zero-order biomodels. Conclusion. Currently, issues related to their standardization are of increasing importance in conducting biomedical research, which is reflected in the appearance of a large number of regulatory documents regulating not only the procedure for conducting them, but also the requirements for biological models used for these studies. However, despite the existing trends, the key point in conducting all studies was and still is the issues related to the extrapolation of the data obtained to humans. The conducted analysis suggests that new biological models (of the zero-order) are being actively introduced into the practice of biomedical research according to their characteristics fully corresponding to the prototype - human biological material obtained from various sources. A distinctive feature of these models is the absence of the need to extrapolate the results obtained to humans. The analysis shows that at present there are all prerequisites for conducting preclinical studies using almost the entire spectrum of biological models of the zero-order specified in this publication within the existing legal framework.

Do German university medical centres promote robust and transparent research? A cross-sectional study of institutional policies

BackgroundIn light of replication and translational failures, biomedical research practices have recently come under scrutiny. Experts have pointed out that the current incentive structures at research institutions do not sufficiently incentivise researchers to invest in robustness and transparency and instead incentivise them to optimize their fitness in the struggle for publications and grants. This cross-sectional study aimed to describe whether and how relevant policies of university medical centres in Germany support the robust and transparent conduct of research and how prevalent traditional metrics are.MethodsFor 38 German university medical centres, we searched for institutional policies for academic degrees and academic appointments as well as websites for their core facilities and research in general between December 2020 and February 2021. We screened the documents for mentions of indicators of robust and transparent research (study registration; reporting of results; sharing of research data, code and protocols; open access; and measures to increase robustness) and for mentions of more traditional metrics of career progression (number of publications; number and value of awarded grants; impact factors; and authorship order).ResultsWhile open access was mentioned in 16% of PhD regulations, other indicators of robust and transparent research were mentioned in less than 10% of institutional policies for academic degrees and academic appointments. These indicators were more frequently mentioned on the core facility and general research websites. Institutional policies for academic degrees and academic appointments had frequent mentions of traditional metrics.ConclusionsReferences to robust and transparent research practices are, with a few exceptions, generally uncommon in institutional policies at German university medical centres, while traditional criteria for academic promotion and tenure still prevail.

Best Practices in the Study of Gender.

Integrating sex- and gender-related aspects into research and innovation content has become an urgent requirement of major science funding bodies as f.e. the European Commission, the Canadian Institutes of Health Research and the US NIH/Office of Women's Health Research.It was the only right response in reaction to the documented failure of the 'one size fits all' approach in traditional biomedical research practices. Attention to sex differences seems to be taken up by researchers quite well, however integrating a gender analysis has met with difficulties. Of prime importance here is to consider gender as a multidimensional concept, covering gender norms, gender identities and gender relations. A research design should clarify from the outset whether gender norms, identities or relations are of relevance to the research question at hand. This chapter provides an overview of international policies insisting on integrating a sex, gender and intersectional analysis into research and innovation with a focus on the the gender equality policy of the European Union. Next, more in depth, a collection of best practices, to be understood as a coherent set of processes and activities, corresponding to the starting points, theories and evidence of the field concerned of which it can be expected to contribute to the intended results in a particular context is described. Finally some challenges ahead are identified.

A New Bayesian Two-Sample t Test and Solution to the Behrens–Fisher Problem Based on Gaussian Mixture Modelling with Known Allocations

Testing differences between a treatment and control group is common practice in biomedical research like randomized controlled trials (RCT). The standard two-sample t test relies on null hypothesis significance testing (NHST) via p values, which has several drawbacks. Bayesian alternatives were recently introduced using the Bayes factor, which has its own limitations. This paper introduces an alternative to current Bayesian two-sample t tests by interpreting the underlying model as a two-component Gaussian mixture in which the effect size is the quantity of interest, which is most relevant in clinical research. Unlike p values or the Bayes factor, the proposed method focusses on estimation under uncertainty instead of explicit hypothesis testing. Therefore, via a Gibbs sampler, the posterior of the effect size is produced, which is used subsequently for either estimation under uncertainty or explicit hypothesis testing based on the region of practical equivalence (ROPE). An illustrative example, theoretical results and a simulation study show the usefulness of the proposed method, and the test is made available in the R package bayest. In sum, the new Bayesian two-sample t test provides a solution to the Behrens–Fisher problem based on Gaussian mixture modelling.

LitSuggest: a web-based system for literature recommendation and curation using machine learning.

Searching and reading relevant literature is a routine practice in biomedical research. However, it is challenging for a user to design optimal search queries using all the keywords related to a given topic. As such, existing search systems such as PubMed often return suboptimal results. Several computational methods have been proposed as an effective alternative to keyword-based query methods for literature recommendation. However, those methods require specialized knowledge in machine learning and natural language processing, which can make them difficult for biologists to utilize. In this paper, we propose LitSuggest, a web server that provides an all-in-one literature recommendation and curation service to help biomedical researchers stay up to date with scientific literature. LitSuggest combines advanced machine learning techniques for suggesting relevant PubMed articles with high accuracy. In addition to innovative text-processing methods, LitSuggest offers multiple advantages over existing tools. First, LitSuggest allows users to curate, organize, and download classification results in a single interface. Second, users can easily fine-tune LitSuggest results by updating the training corpus. Third, results can be readily shared, enabling collaborative analysis and curation of scientific literature. Finally, LitSuggest provides an automated personalized weekly digest of newly published articles for each user's project. LitSuggest is publicly available at https://www.ncbi.nlm.nih.gov/research/litsuggest.

From Mice to Monkeys? Beyond Orthodox Approaches to the Ethics of Animal Model Choice.

Simple SummaryNew tools, allowing scientists to make precise changes to mammal genomes, have made possible future increased use of larger mammals in biomedical research, such as primates, pigs, and dogs. This paper addresses ethical issues that are raised by using larger mammals instead of smaller ones in this research. Because scientists who use animals in research follow strict guidelines, we first examine what those guidelines suggest for using larger mammals. We then consider what philosophers, who write about the ethics of animal use, consider as the important questions in evaluating which (if any) animals are acceptable to use in research. We find that philosophical perspectives have typically been interested in the question of when or if animal use is justified, while biomedical research guidance has assumed that animal use is justified but defined specific limits to that use. To address directly the ethical questions that arise in the practice of biomedical research in selecting which animals to use, we consider an approach to ethics that is focused on character and living well (or flourishing). This paper is valuable to society in drawing attention to the ethical questions, rather than merely the scientific issues, that are important in selecting which animals to use in biomedical research.Recent developments in genome editing tools, along with limits in the translational potential of rodent models of human disease, have spurred renewed biomedical research interest in large mammals like nonhuman primates, pigs, and dogs. Such scientific developments raise ethical issues about the use of these animals in comparison with smaller mammals, such as mice and rats. To examine these ethical questions, we first consider standard (or “orthodox”) approaches, including ethics oversight within biomedical research communities, and critical theoretical reflections on animal research, including rights-based and utilitarian approaches. We argue that oversight of biomedical research offers guidance on the profession’s permitted uses of animals within a research setting and orthodox approaches to animal ethics questions when and whether animals should be used in biomedicine; however, neither approach sufficiently investigates the nuances of ethical practices within the research setting. To fill this lacuna, we consider a virtue ethical approach to the use of specific animal models in biomedicine. From this perspective, we argued that limitations on flourishing for large mammals in a research setting, as well as potential human-animal bonds, are two sources of likely ethical tensions in animal care and use in the context of larger mammals.

Monitoring long-term DNA storage via absolute copy number quantification by ddPCR

Long-term storage of DNA is a routine practice in biomedical research, diagnostics and drug discovery. Periodic monitoring is important for early detection of changes in DNA quality and quantity. Existing methods include agarose gel, ultraviolet (UV) absorbance, fluorometric reading and qPCR. However, these methods are either limited by sensitivity or depend on DNA standards, which face the same storage challenges. In this paper, we tested the state-of-the-art droplet digital PCR (ddPCR) technology that can quantify the absolute DNA copy number with no need of a standard curve. We found that ddPCR was very accurate in determining the level of a plasmid DNA standard and was sensitive to DNA loss due to degradation or adsorption. With the ddPCR technology, we found a gradual process of DNA adsorption to several types of low binding tubes, which was unnoticed before. Although modest, adsorption significantly affected recovery of highly diluted DNA (<0.2 μg/mL), which could be rescued by addition of carrier DNA. In conclusion, this paper not only demonstrated that ddPCR is an ideal method for monitoring DNA storage, but also provided an effective approach to improving recovery of highly diluted DNA, which may have broad implications in assay development, diagnostics and forensic sciences.

A two-tiered curriculum to improve data management practices for researchers.

BackgroundBetter research data management (RDM) provides the means to analyze data in new ways, effectively build on another researcher’s results, and reproduce the results of an experiment. Librarians are recognized by many as a potential resource for assisting researchers in this area, however this potential has not been fully realized in the biomedical research community. While librarians possess the broad skill set needed to support RDM, they often lack specific knowledge and time to develop an appropriate curriculum for their research community. The goal of this project was to develop and pilot educational modules for librarians to learn RDM and a curriculum for them to subsequently use to train their own research communities.Materials and methodsWe created online modules for librarians that address RDM best practices, resources and regulations, as well as the culture and practice of biomedical research. Data was collected from librarians through questions embedded in the online modules on their self-reported changes in understanding of and comfort level with RDM using a retrospective pre-post design. We also developed a Teaching Toolkit which consists of slides, a script, and an evaluation form for librarians to use to teach an introductory RDM class to researchers at their own institutions. Researchers’ satisfaction with the class and intent to use the material they had learned was collected. Actual changes in RDM practices by researchers who attended was assessed with a follow-up survey administered seven months after the class.Results and discussionThe online curriculum increased librarians’ self-reported understanding of and comfort level with RDM. The Teaching Toolkit, when employed by librarians to teach researchers in person, resulted in improved RDM practices. This two-tiered curriculum provides concise training and a ready-made curriculum that allows working librarians to quickly gain an understanding of RDM, and translate this knowledge to researchers through training at their own institutions.

Electronic Module for Photoplethysmography аnd Pulse Oximetry

Methods of pulse oximetry and photoplethysmography are widely used in clinical medicine and practice of biomedical research outside the clinic. The advantages of the method are high efficiency of preparation for the diagnostic procedure, non-invasive, complete safety for health. The method provides the possibility of unlimited long - term monitoring of the dynamics of saturation and desaturation of hemoglobin. In combination with the above, subject to the qualitative registration of photoplethysmograms, the method allows the calculation and analysis of a number of indicators of peripheral blood circulation: the total pulse blood flow to the study region, the tone of arterial vessels of different diameters, the state of capillary blood flow. Most modern foreign models of pulse oximeters are integrated devices that provide measurement of a very limited set of physiological parameters: the percentage of hemoglobin oxygen saturation and pulse rate. The range of pulse oximeters containing the interface with the personal computer and providing operational calculation of indicators of peripheral photoplethysmograms is small. Such devices have a fairlyhigh cost and are not portable. The development of domestic integrated electronic devices is extremely relevant, allowing along with obtaining information about blood oxygenation to perform continuous monitoring of peripheral blood circulation. The authors developed an electronic module that provides long-term registration of photoplethysmograms in the infrared and red areas of the light spectrum. The electronic module is made exclusively with the use of domestic active radio elements – discrete semiconductor devices and integrated circuits. The device was developed in full compliance with the import substitution policy pursued by the President and the Government of the Russian Federation. The advantage of the device is the "open architecture" of the electronic circuit, which provides four analog signals suitable for further digitization. The signals contain information about pulsating and non-pulsating components of the optical density of biological tissue in the infrared and red ranges of the spectrum. The device has an electronic filter of mains interference. Tests of the device demonstrated high quality of photoplethysmograms. This makes it possible tosuccessfullyuse the device for studies of hemoglobin oxygenation and peripheral hemodynamics.

Joint significance tests for mediation effects of socioeconomic adversity on adiposity via epigenetics

Mediation analysis has become a popular practice in biomedical research. We conduct mediation analyses to investigate whether epigenetic variations mediate the effect of socioeconomic disadvantage on adiposity. Mediation effects can be expressed as a product of two parameters: one for the exposure-mediator association and the other for the mediator-outcome association conditional on the exposure. Under multi-mediator models, we study joint significance tests which examine the two parameters separately and compare with the widely used product significance tests which focus on the product of two parameters. Normal approximation of product significance tests depends on both effect size and sample size. We show that joint significance tests are intersection-union tests with size $\alpha$ and asymptotically more powerful than the normality-based product significance tests. Based on the theoretical results, we construct powerful testing procedures for gene-based mediation analyses and path-specific analyses. Advantage of joint significance tests is supported by simulation as well as the results of locus-based and gene-based mediation analyses of chromosome 17. Our analyses suggest that methylation of FASN gene mediates the effect of socioeconomic adversity on adiposity.

Johns Hopkins Science Policy Group: Training scientists to be effective advocates and communicators

Legislative and regulatory affairs in science policy play a central role in shaping the practice of biomedical research. However, there are limited opportunities allowing scientists to practice techniques in effective policy advocacy. Since its inception in 2016, the Johns Hopkins Science Policy Group has provided trainees in the biological and health sciences with immersive training and professional development opportunities in advocacy, policy analysis, and strategic communications. Our student‐led initiatives, such as our flagship “Eat and Advocate” program, trains researchers to engage their Congressional representatives with targeted advocacy messages promoting pro‐science legislation. Trainees attending our advocacy training seminars learn how to communicate the value of federally‐funded research to policy‐makers, honing their science outreach and communication skills. Further, our members develop educational content, including fact sheets, infographics, message templates, and call‐to‐action memos, to incentive fellow researchers to engage in civic action supporting pro‐research legislative agendas. Past student‐led projects have provided training and professional development opportunities through advocacy initiatives on NIH appropriations, the Affordable Care Act, 21st Century Cures, the Paris Climate Accord, prescription drug pricing regulation, and the Clean Water Act of 2015. The Johns Hopkins Science Policy Group is a model of a highly effective trainee‐led program that is capable of training researchers in 1) organizational leadership by leading grassroots advocacy initiatives 2) strategic communications in advocacy, policy analysis, and science communication 3) civic engagement and public outreach.Support or Funding InformationJohns Hopkins Graduate Student Association, Johns Hopkins School of Public Health Student Assembly, and the Johns Hopkins University Alumni AssociationThis abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Cancer researcher looks to artists for inspiration

By day, Dhruba Deb studies lung cancer. A postdoctoral researcher at the UT Southwestern Medical Center in Dallas, Deb puzzles over disease-causing genes and the scores of signaling pathways in which they act. Searching through this sea of data, he often has trouble deciding where to focus or how to push forward. In the evenings, Deb leaves the microscope and pipettes and enters a different world—his home studio—where canvas and paint brushes await. Talking with artist friends, Deb sees the different ways they tackle challenges. Researchers in many fields tend to be reductionist in their approaches, whereas artists “look at the problem from a 30,000-foot view,” Deb says. “They try to encapsulate all the complexity in the system. They say, ‘I don’t know what I am doing, but it’s going to lead me somewhere.’” Working with cancer biologist Dhruba Deb, artist Caroline Ometz explored cancer’s effects on cells, including in this painting, Order to Chaos , which depicts a healthy cell (center) being attacked by a yellow cancer-shaped cell. Image courtesy of Caroline Shaw Ometz. Deb’s dual pursuits prompted him to figure out how to bring the more open-ended, intuitive thinking of artists into the practice of biomedical research. In 2014 he launched Cancer ART-SCI Network to connect individuals who, like him, want to probe the complexity of cancer using science and art in parallel. Today this online community has nearly 200 members—artists, researchers, and scientist–artists like Deb—from 20 countries. Inspired by art–science collaborations in other fields, such as astronomy …

Neuroinflammation - using big data to inform clinical practice.

Neuroinflammation is emerging as a central process in many neurological conditions, either as a causative factor or as a secondary response to nervous system insult. Understanding the causes and consequences of neuroinflammation could, therefore, provide insight that is needed to improve therapeutic interventions across many diseases. However, the complexity of the pathways involved necessitates the use of high-throughput approaches to extensively interrogate the process, and appropriate strategies to translate the data generated into clinical benefit. Use of 'big data' aims to generate, integrate and analyse large, heterogeneous datasets to provide in-depth insights into complex processes, and has the potential to unravel the complexities of neuroinflammation. Limitations in data analysis approaches currently prevent the full potential of big data being reached, but some aspects of big data are already yielding results. The implementation of 'omics' analyses in particular is becoming routine practice in biomedical research, and neuroimaging is producing large sets of complex data. In this Review, we evaluate the impact of the drive to collect and analyse big data on our understanding of neuroinflammation in disease. We describe the breadth of big data that are leading to an evolution in our understanding of this field, exemplify how these data are beginning to be of use in a clinical setting, and consider possible future directions.

Generation of a Functional Human Neural Network by NDM29 Overexpression in Neuroblastoma Cancer Cells.

Recent advances in life sciences suggest that human and rodent cell responses to stimuli might differ significantly. In this context, the results achieved in neurotoxicology and biomedical research practices using neural networks obtained from mouse or rat primary culture of neurons would benefit of the parallel evaluation of the same parameters using fully differentiated neurons with a human genetic background, thus emphasizing the current need of neuronal cells with human origin. In this work, we developed a human functionally active neural network derived by human neuroblastoma cancer cells genetically engineered to overexpress NDM29, a non-coding RNA whose increased synthesis causes the differentiation toward a neuronal phenotype. These cells are here analyzed accurately showing functional and morphological traits of neurons such as the expression of neuron-specific proteins and the possibility to generate the expected neuronal current traces and action potentials. Their morphometrical analysis is carried out by quantitative phase microscopy showing soma and axon sizes compatible with those of functional neurons. The ability of these cells to connect autonomously forming physical junctions recapitulates that of hippocampal neurons, as resulting by connect-ability test. Lastly, these cells self-organize in neural networks able to produce spontaneous firing, in which spikes can be clustered in bursts. Altogether, these results show that the neural network obtained by NDM29-dependent differentiation of neuroblastoma cells is a suitable tool for biomedical research practices.