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Simple Summary The study of cell features has historically been key for the progress of biological sciences and its relevance remains intact. In recent years, mass cytometry has emerged as a promising and powerful technology, capable of studying multiple parameters of cells in the same sample. Mass cytometry has been quickly applied to many research areas, particularly to the study of the immune system for different purposes, in which the simultaneous analysis of a large number of proteins is crucial. However, despite being a technique that is on the rise, its performance in scientific publications has not yet been evaluated. In this work, a bibliometric methodology known as H-Classics was applied to analyse the most relevant articles, known as highly cited papers (HCPs), and determine the main scientific producers (authors, institutions, and countries) and trends around mass cytometry research field. The results confirmed a high interest and application in immunological studies. The identified HCPs came from prestigious institutions and were published in high impact journals. These results may help researchers to expand their knowledge and to establish new valuable collaborative networks around mass cytometry. Abstract Mass cytometry (CyTOF) is a relatively novel technique for the multiparametric analysis of single-cell features with an increasing central role in cell biology, immunology, pharmacology, and biomedicine. This technique mixes the fundamentals of flow cytometry with mass spectrometry and is mainly used for in-depth studies of the immune system and diseases with a significant immune load, such as cancer, autoimmune diseases, and viral diseases like HIV or the recently emerged COVID-19, produced by the SARS-CoV-2 coronavirus. The objective of this study was to provide a useful insight into the evolution of the mass cytometry research field, revealing the knowledge structure (conceptual and social) and authors, countries, sources, documents, and organizations that have made the most significant contribution to its development. We retrieved 937 articles from the Web of Science (2010–2019), analysed 71 Highly Cited Papers (HCP) through the H-Classics methodology and computed the data by using Bibliometrix R package. HCP sources corresponded to high-impact journals, such as Nature Biotechnology and Cell, and its production was concentrated in the US, and specifically Stanford University, affiliation of the most relevant authors in the field. HCPs analysis confirmed great interest in the study of the immune system and complex data processing in the mass cytometry research field.

Significance: Real-time monitoring of the heart rate and blood flow is crucial for studying cardiovascular dysfunction, which leads to cardiovascular diseases. Aim: This study aims at in-depth understanding of high-speed cardiovascular dynamics in a zebrafish embryo model for various biomedical applications via frequency-comb-referenced quantitative phase imaging (FCR-QPI). Approach: Quantitative phase imaging (QPI) has emerged as a powerful technique in the field of biomedicine but has not been actively applied to the monitoring of circulatory/cardiovascular parameters, due to dynamic speckles and low frame rates. We demonstrate FCR-QPI to measure heart rate and blood flow in a zebrafish embryo. FCR-QPI utilizes a high-speed photodetector instead of a conventional camera, so it enables real-time monitoring of individual red blood cell (RBC) flow. Results: The average velocity of zebrafish’s RBCs was measured from 192.5 to 608.8 μm∕s at 24 to 28 hour-post-fertilization (hpf). In addition, the number of RBCs in a pulsatile blood flow was revealed to 16 cells/pulse at 48 hpf. The heart rates corresponded to 94 and 142 beats-per-minute at 24 and 48 hpf. Conclusions: This approach will newly enable in-depth understanding of the cardiovascular dynamics in the zebrafish model and possible usage for drug discovery applications in biomedicine. National Research Foundation (NRF) Published version Funding: National Research Foundation of the Republic of Korea (NRF-2012R1A3A1050386, NRF-2020R1A2C2102338, NRF-2020R1A2C210233811, and NRF-2021R1A4A1031660); KAIST UP Program; Singapore National Research Foundation (NRF-NRFF2015-02).

The biological status and biomedical significance of the concept of race as applied to humans continue to be contentious issues despite the use of advanced statistical and clustering methods to determine continental ancestry. It is thus imperative for researchers to understand the limitations as well as potential uses of the concept of race in biology and biomedicine. This paper deals with the theoretical assumptions behind cluster analysis in human population genomics. Adopting an interdisciplinary approach, it demonstrates that the hypothesis that attributes the clustering of human populations to “frictional” effects of landform barriers at continental boundaries is empirically incoherent. It then contrasts the scientific status of the “cluster” and “cline” constructs in human population genomics, and shows how cluster may be instrumentally produced. It also shows how statistical values of race vindicate Darwin's argument that race is evolutionarily meaningless. Finally, the paper explains why, due to spatiotemporal parameters, evolutionary forces, and socio-cultural factors influencing population structure, continental ancestry may be pragmatically relevant to global and public health genomics. Overall, this work demonstrates that, from a biological systematic and evolutionary taxonomical perspective, human races/continental groups or clusters have no natural meaning or objective biological reality. In fact, the utility of racial categorizations in research and in clinics can be explained by spatiotemporal parameters, socio-cultural factors, and evolutionary forces affecting disease causation and treatment response.

Impaired systemic redox homeostasis is implicated in the onset and development of various diseases, including skin diseases. Therefore, continuous search for natural products with antioxidant bioactivities applicable in biomedicine is attractive topic of general interest. Research efforts aiming to validate antioxidant potentials of natural products has led to the development of several assays based on various test principles. Hence, understanding the advantages and limitations of various assays is important for selection of assays useful to study antioxidant and related bioactivities of natural products of biomedical interest. This review paper gives a short overview on some chemical and cellular bioassays used to estimate the antioxidant activity of chosen natural products together with a brief overview on the use of natural products with antioxidant activities as adjuvant medicinal remedies in dermatology.

Despite COVID-19 turned into a pandemic, no approved drug for the treatment or globally available vaccine is out yet. In such a global emergency, drug repurposing approach that bypasses a costly and long-time demanding drug discovery process is an effective way in search of finding drugs for the COVID-19 treatment. Recent studies showed that SARS-CoV-2 uses neuropilin-1 (NRP1) for host entry. Here we took advantage of structural information of the NRP1 in complex with C-terminal of spike (S) protein of SARSCoV-2 to identify drugs that may inhibit NRP1 and S protein interaction. U.S. Food and Drug Administration (FDA) approved drugs were screened using docking simulations. Among top drugs, well-tolerated drugs were selected for further analysis. Molecular dynamics (MD) simulations of drugs-NRP1 complexes were run for 100 ns to assess the persistency of binding. MM/GBSA calculations from MD simulations showed that eltrombopag, glimepiride, sitagliptin, dutasteride, and ergotamine stably and strongly bind to NRP1. In silico Alanine scanning analysis revealed that Tyr(297), Trp(301), and Tyr(353) amino acids of NRP1 are critical for drug binding. Validating the effect of drugs analyzed in this paper by experimental studies and clinical trials will expedite the drug discovery process for COVID-19., NA

Background: D-Aspartic acid (D-Asp) is in invertebrate and vertebrate neuroendocrine tissues, where it carries out important physiological functions. Recently, it has been reported that D-Asp is involved in the synthesis and release of testosterone and is assumed can be used as a testosterone booster for infertile men, and by athletes to increase muscle mass and strength. Objective: The aim of this review is to summarize available evidence related to the effects of D-Asp on serum testosterone levels. Materials and Methods: We conducted a systematic review of all type studies, which evaluated the effect of the D-Asp on blood testosterone including published papers until October 2015, using PubMed, ISI Web of Science, ProQuest and Scopus database. Results: With 396 retrieved records, 23 animal studies and 4 human studies were included. In vivo and in vitro animal studies revealed the effect of D-Asp depending on species, sex and organ-specific. Our results showed that exogenous D-Asp enhances testosterone levels in male animal’s studies, whereas studies in human yielded inconsistent results. The evidence for this association in man is still sparse, mostly because of limited number and poor quality studies. Conclusion: There is an urgent need for more and well-designed human clinical trials with larger sample sizes and longer duration to investigate putative effects of D-Asp on testosterone concentrations.

Summary Digitalized fluorescence images contain numerical information such as color (wavelength), fluorescence intensity and spatial position. However, quantitative analyses of acquired data and their validation remained to be established. Our research group has applied quantitative fluorescence imaging on tissue sections and uncovered novel findings in skeletal biomedicine and biodentistry. This review paper includes a brief background of quantitative fluorescence imaging and discusses practical applications by introducing our previous research. Finally, the future perspectives of quantitative fluorescence imaging are discussed.

Modern medicine is often said to have originated with nineteenth century germ theory, which attributed diseases to bacterial contagions. The success of this theory is often associated with an underlying principle referred to as the “doctrine of specific etiology”. This doctrine refers to specificity at the level of disease causation or etiology. While the importance of this doctrine is frequently emphasized in the philosophical, historical, and medical literature, these sources lack a clear account of the types of specificity that it involves and why exactly they matter. This paper argues that nineteenth century germ theory involves two types of specificity at the level of etiology. One type receives significant attention in the literature, but its influence on modern medicine has been misunderstood. A second type is present in this model, but it has been completely overlooked in the extant literature. My analysis clarifies how these types of specificity led to a novel conception of etiology that continues to figure in medicine today.

Insight into the aberrant expression of microRNAs (miRNAs) and the genes that they regulate during the progression of cancer in general and prostate cancer (PCa) in particular is one of the most important issues in current molecular biomedicine and allows for the discovery of therapeutic or diagnostic miRNA targets. The present study aimed to analyze the available data regarding the direct or indirect effects of miRNAs on the expression of the mRNAs involved in carcinogenesis and to enable updating and optimizing the selection of the corresponding targets. The present review focuses on the data related to the genes with miRNA-dependent expression during the development of PCa. The data used in this review have been extracted from research papers and the databases STRING, PANTHER and TargetScan, with a special focus on the genes directly associated with cell transformation and the maintenance of the transformed genotype, as well as tumor invasion and spread. The search for miRNA markers of PCa and therapeutically active molecules should rely on bioinformatics resources, such as data from recent experimental studies, as well as meta-analysis and cross-analysis of the data on the state of the tumor, patient status, histological/immunohistological data and data on mRNA-miRNA coexpression.

Maternal colostrum is the primary post natal nutrient supply that affects the growth and development of newborns. The study of the fatty acid nutrition of colostrum based on biomedicine is of great significance. In this paper, the problem of fatty acid nutrition of colostrum in combination with biomedicine was analyzed. The study analyses the main contents of biomedicine as well as the variation of the content is analyzed through questionnaire method and big data analysis. The results showed that the nutritional level of colostrum fatty acid is related to the type and quantity of food consumed by pregnant women during pregnancy. And the level of fatty acids is related to the total amount of fat and protein ingested by the mother

Although the applications of Proteomics in Human Biomedicine have been explored for some time now, in animal and veterinary research, the potential of this resource has just started to be explored, especially when companion animal health is considered. In the last years, knowledge on the Canis lupus familiaris proteome has been accumulating in the literature and a resource compiling all this information and critically reviewing it was lacking. This article presents such a resource for the first time. CanisOme is a database of all proteins identified in Canis lupus familiaris tissues, either in health or in disease, annotated with information on the proteins present on the sample and on the donors. This database reunites information on 549 proteins, associated with 63 dog diseases and 33 dog breeds. Examples of how this information may be used to produce new hypothesis on disease mechanisms is presented both through the functional analysis of the proteins quantified in canine cutaneous mast cell tumors and through the study of the interactome of C. lupus familiaris and Leishmania infantum. Therefore, the usefulness of CanisOme for researchers looking for protein biomarkers in dogs and interested in a comprehensive analysis of disease mechanisms is demonstrated. Biological significance This paper presents CanisOme, a database of proteomic studies with relevant protein annotation, allowing the enlightenment of disease mechanisms and the discovery of novel disease biomarkers for C. lupus familiaris. This knowledge is important not only for the improvement of animal health but also for the use of dogs as models for human health studies.