Race in the Life Sciences: An Empirical Assessment, 1950-2000

The mainstream narrative regarding the evolution of race as an idea in the scientific community is that biological understandings of race dominated throughout the nineteenth and twentieth centuries up until World War II, after which a social constructionist approach is thought to have taken hold. Many believe that the horrific outcomes of the most notorious applications of biological race—eugenics and the Holocaust—moved scientists away from thinking that race reflects inherent differences and toward an understanding that race is a largely social, cultural, and political phenomenon. This understanding of the evolution of race as a scientific idea informed the way that many areas of law conceptualize human equality, including civil rights, human rights, and constitutional law. This Article provides one of the first large-scale empirical assessments of publications in peer-reviewed biomedical and life science journals to examine whether biological theories of race actually lost credibility in the life sciences after World War II. We find that biological theories of race transformed yet persisted in the dominant academic discourse up through modern times—a finding that contradicts the central narrative that the life sciences became “color-blind” or “post-racial” several decades ago. The continued salience of biological race in the life sciences suggests that more attention needs to be paid to the questionable assumptions driving this research on biological race and its potential spillover effects, i.e., how persisting claims of biological race in the scientific literature might reconstitute its significance in law and society in a manner that may be harmful to racial minorities

Discovery of molecular associations among aging, stem cells, and cancer based on gene expression profiling.

The emergence of a huge volume of omics data enables a computational approach to the investigation of the biology of cancer. The cancer informatics approach is a useful supplement to the traditional experimental approach. I reviewed several reports that used a bioinformatics approach to analyze the associations among aging, stem cells, and cancer by microarray gene expression profiling. The high expression of aging- or human embryonic stem cell-related molecules in cancer suggests that certain important mechanisms are commonly underlying aging, stem cells, and cancer. These mechanisms are involved in cell cycle regulation, metabolic process, DNA damage response, apoptosis, p53 signaling pathway, immune/inflammatory response, and other processes, suggesting that cancer is a developmental and evolutional disease that is strongly related to aging. Moreover, these mechanisms demonstrate that the initiation, proliferation, and metastasis of cancer are associated with the deregulation of stem cells. These findings provide insights into the biology of cancer. Certainly, the findings that are obtained by the informatics approach should be justified by experimental validation. This review also noted that next-generation sequencing data provide enriched sources for cancer informatics study

Citation count distributions for large monodisciplinary journals

Many different citation-based indicators are used by researchers and research evaluators to help evaluate the impact of scholarly outputs. Although the appropriateness of individual citation indicators depends in part on the statistical properties of citation counts, there is no universally agreed best-fitting statistical distribution against which to check them. The two current leading candidates are the discretised lognormal and the hooked or shifted power law. These have been mainly tested on sets of articles from a single field and year but these collections can include multiple specialisms that might dilute their properties. This article fits statistical distributions to 50 large subject-specific journals in the belief that individual journals can be purer than subject categories and may therefore give clearer findings. The results show that in most cases the discretised lognormal fits significantly better than the hooked power law, reversing previous findings for entire subcategories. This suggests that the discretised lognormal is the more appropriate distribution for modelling pure citation data. Thus, future analytical investigations of the properties of citation indicators can use the lognormal distribution to analyse their basic properties. This article also includes improved software for fitting the hooked power law

Epigenetics applied to child and adolescent mental health: Progress, challenges and opportunities

BACKGROUND: Epigenetic processes are fast emerging as a promising molecular system in the search for both biomarkers and mechanisms underlying human health and disease risk, including psychopathology. METHODS: In this review, we discuss the application of epigenetics (specifically DNA methylation) to research in child and adolescent mental health, with a focus on the use of developmentally sensitive datasets, such as prospective, population-based cohorts. We look back at lessons learned to date, highlight current developments in the field and areas of priority for future research. We also reflect on why epigenetic research on child and adolescent mental health currently lags behind other areas of epigenetic research and what we can do to overcome existing barriers. RESULTS: To move the field forward, we advocate for the need of large-scale, harmonized, collaborative efforts that explicitly account for the time-varying nature of epigenetic and mental health data across development. CONCLUSION: We conclude with a perspective on what the future may hold in terms of translational applications as more robust signals emerge from epigenetic research on child and adolescent mental health

Epigenetics applied to child and adolescent mental health: Progress, challenges and opportunities

BackgroundEpigenetic processes are fast emerging as a promising molecular system in the search for both biomarkers and mechanisms underlying human health and disease risk, including psychopathology.MethodsIn this review, we discuss the application of epigenetics (specifically DNA methylation) to research in child and adolescent mental health, with a focus on the use of developmentally sensitive datasets, such as prospective, population-based cohorts. We look back at lessons learned to date, highlight current developments in the field and areas of priority for future research. We also reflect on why epigenetic research on child and adolescent mental health currently lags behind other areas of epigenetic research and what we can do to overcome existing barriers.ResultsTo move the field forward, we advocate for the need of large-scale, harmonized, collaborative efforts that explicitly account for the time-varying nature of epigenetic and mental health data across development.ConclusionWe conclude with a perspective on what the future may hold in terms of translational applications as more robust signals emerge from epigenetic research on child and adolescent mental health

Recurrent Tissue-Specific Mtdna Mutations are Common in Humans

Mitochondrial DNA (mtDNA) variation can affect phenotypic variation; therefore, knowing its distribution within and among individuals is of importance to understanding many human diseases. Intra-individual mtDNA variation (heteroplasmy) has been generally assumed to be random. We used massively parallel sequencing to assess heteroplasmy across ten tissues and demonstrate that in unrelated individuals there are tissue-specific, recurrent mutations. Certain tissues, notably kidney, liver and skeletal muscle, displayed the identical recurrent mutations that were undetectable in other tissues in the same individuals. Using RFLP analyses we validated one of the tissue-specific mutations in the two sequenced individuals and replicated the patterns in two additional individuals. These recurrent mutations all occur within or in very close proximity to sites that regulate mtDNA replication, strongly implying that these variations alter the replication dynamics of the mutated mtDNA genome. These recurrent variants are all independent of each other and do not occur in the mtDNA coding regions. The most parsimonious explanation of the data is that these frequently repeated mutations experience tissue-specific positive selection, probably through replication advantage

Journal Productivity in Fishery Science an informetric analysis

Knowledge is a human resource which has the ability to consolidate the valuable results of human thinking and civilization through different times. It is the totality of understanding of nature and its features for improved quality of life of human society. Because of this, knowledge has been increasing in volume, dimension and directions. The term ‘information’ and 'knowledge' are often used as if they are interchangeable. Information is ‘potential knowledge‘ which is converted into knowledge by the integration of memory of human beings. In modern times there is a confusion on knowledge usage. Therefore an understanding of the concept ‘knowledge’ is needed for formulation of strategies in information science

Evidence-Based Genetics and Identification of Key Human Alzheimer’s Disease Alleles with Co-morbidities

Advancements in biomedical research have contributed to increasing the life expectancy of humans, but we now observe an increase in age-related diseases such as Alzheimer’s disease. Genome-Wide Association Studies (GWAS) and linkage studies have identified human genes associated with Alzheimer’s disease (referred to as AD genes). A previous study by Vahdati in 2017 has revealed the human AD genes and counterparts in model species [1]. Thus, we further investigate the co-morbidity genes and alleles. Using ontology analysis combined with cluster analysis, the study identified functional pathways enriched among the human AD genes, including 179 genes out of 695 human AD genes (26%) that were associated with one or more of the four neurological diseases including Amyotrophic lateral sclerosis, Multiple sclerosis, Parkinson’s disease, and Schizophrenia [1]. More importantly, the results indicate co-morbidities with Late-Onset Alzheimer’s Disease (LOAD) and other neurological conditions, implying the complexity of the phenotypes in the human AD. The co-morbidity genes may account for mixed symptoms for human AD as well as age-related risks of infections. Of them, the three genes are well conserved (Angiotensin I Converting Enzyme gene, ACE; Methylenetetrahydrofolate Reductase gene, MTHFR; and tumor necrosis factor gene, TNF). In this study, we confirmed the comorbidity of the three genes associated with AD. We further identified the comorbidity of two alleles in the MTHFR gene, C677T and A222V, significantly associated with Alzheimer’s disease. This study provides an example of evidencebased analysis that is cost-effective and may be an effective approach to develop cure-alls for multiple diseases

Caveats for the Use of Citation Indicators in Research and Journal Evaluations

Ageing of publications, percentage of self-citations, and impact vary from journal to journal within fields of science. The assumption that citation and publication practices are homogenous within specialties and fields of science is invalid. Furthermore, the delineation of fields and among specialties is fuzzy. Institutional units of analysis and persons may move between fields or span different specialties. The match between the citation index and institutional profiles varies among institutional units and nations. The respective matches may heavily affect the representation of the units. Non-ISI journals are increasingly cornered into "transdisciplinary" Mode-2 functions with the exception of specialist journals publishing in languages other than English. An "externally cited impact factor" can be calculated for these journals. The citation impact of non-ISI journals will be demonstrated using Science and Public Policy as the example

Age-Related Macular Degeneration: A Scientometric Analysis

Age-related macular degeneration (ARMD) is a major cause of central blindness among working aged adults across the world. Systematic research planning on any subject, including ARMD is in need of solid data regarding previous efforts in this field and to identify the gaps in the research. This study aimed to elucidate the most important trends, directions, and gap in this subject. The data extracted from the Institute for Scientific Information were used to perform a bibliometric analysis of the scientific productions (1993–2013) about ARMD. Specific parameters related to ARMD were analyzed to obtain a view of the topic’s structure, history, and document relationships. Additionally, the trends and authors in the most influential publications were analyzed. The number of articles in this field was found constantly increasing. Most highly cited articles addressed genetic epidemiology and clinical research topics in this field.  During the past 3 years, there has been a trend toward biomarker research. Through performing the first scientometric survey on ARMD research, we analyzed the characteristics of papers and the trends in scientific production.  We also identified some of the critical gaps in the current research efforts that would help in large-scale research strategic planning