Biological Entities Research Articles

Gestational breast cancer: distinctive molecular and clinico-epidemiological features

Gestational breast cancer (GBC), defined as breast cancer (BC) diagnosed during pregnancy or the first-year post-partum, accounts for 6–15% of BC cases in women aged 20–44 years. GBC has worse prognosis than non-GBC, but reasons behind are not clear. The GEICAM/2012–03 Study (Molecular Characterization of Gestational Breast Cancer) is a multicenter prospective/retrospective observational registry of patients diagnosed with GBC. From November 2014 to June 2015 seventy patients diagnosed with GBC were included in the study, 30 diagnosed during pregnancy and 40 after delivery. Our current study was aimed to explore differences in epidemiological, clinico-pathological and gene expression features of GBC tumors, from the GEICAM/2012–03 Study, compared to non-GBC tumors from patients of similar age (< 43 years) from six different GEICAM studies, used as non- GBC control population. As per the main objective, the study found multiple differences showing GBC tumors as a different biological entity. GBC showed a more aggressive biology, with higher Ki67 levels, higher incidence of breast and/or ovarian cancer family history, and germline deleterious BRCA1/2 mutations, and are enriched in basal-like intrinsic subtype. GBC patients showed a lower number of tumor infiltrating lymphocytes, while specific genetic signatures highlight differences in GBC´s distinctive transcriptome. Our study shows that GBC is potentially a clinically and molecularly different entity, with specific epidemiological, clinical, and histological features, as well as a distinctive altered immune state and genetic signature. Nevertheless, further studies are needed to better understand the biology of GBC and to identify new targets against which develop new, more effective, targeted therapies.

The Socialization of Children from Vietnamese - Korean Multicultural Families: A Case Study of Korean International Schools in Hanoi and Ho Chi Minh City

From the moment of birth, an individual exists as a biological entity. However, true integration into human society necessitates the acquisition of cultural norms, values, knowledge, and beliefs specific to their given community. This process involves adapting to social roles and cultural practices, ultimately enabling effective communication and fulfillment of societal responsibilities. Notably, language assumes a pivotal role in this intricate web of socialization and stands as arguably the most influential factor in the overall process. To delve into the current state of socialization among children from Vietnamese-Korean multicultural families residing in Vietnam and attending a Korean International School, this research employs socialization theory, descriptive statistical methods via questionnaires, and interdisciplinary research techniques.

Orphan genes are not a distinct biological entity.

The genome sequencing revolution has revealed that all species possess a large number of unique genes critical for trait variation, adaptation, and evolutionary innovation. One widely used approach to identify such genes consists of detecting protein-coding sequences with no homology in other genomes, termed orphan genes. These genes have been extensively studied, under the assumption that they represent valid proxies for species-specific genes. Here, we critically evaluate taxonomic, phylogenetic, and sequence evolution evidence showing that orphan genes belong to a range of evolutionary ages and thus cannot be assigned to a single lineage. Furthermore, we show that the processes generating orphan genes are substantially more diverse than generally thought and include horizontal gene transfer, transposable element domestication, and overprinting. Thus, orphan genes represent a heterogeneous collection of genes rather than a single biological entity, making them unsuitable as a subject for meaningful investigation of gene evolution and phenotypic innovation.

Target Fisher: a Consensus Structure-Based Target Prediction Tool, and its Application in the Discovery of Selective MAO-B Inhibitors.

In this work we introduce Target Fisher, a consensus structure-based target prediction tool that integrates molecular docking and machine learning with the aim to aid in the identification of potential biological targets and the optimization of the use of bioassays. Target Fisher uses per-residue energy decomposition profiles extracted from docking poses as fingerprints to train target-specific machine learning models. It provides predictions for a curated set of 37 protein targets, covering a diverse range of biological entities, and offers a user-friendly interface accessible via a web server (https://gqc.quimica.unlp.edu.ar/targetfisher/). In this sense, Target Fisher is a valuable tool to aid organic and medicinal chemistry groups in target identification, drug discovery and drug repurposing. As a case study, we demonstrate the efficacy of Target Fisher by screening a small library of assorted natural products for targets relevant to neurodegenerative diseases, which resulted in the identification and experimental validation of selective inhibitors of monoamine oxidase B (MAO-B).

A Review on Green Synthesized Metal Nanoparticles Applications

Nanotechnology pertains to the manipulation of materials at exceedingly small scales, specifically between 1 and 100 nanometers. Materials at this scale exhibit significantly different properties compared to the same materials at larger scales. An emerging trend is the utilization of nanoparticles (NPs) to address environmental issues. Metallic nanoparticles are among the several nanoparticles that are extensively utilized in environmentally sustainable endeavors. A sustainable, economical, and enduring approach is to synthesize nanoparticles through a more ecologically friendly procedure instead of a physical or chemical method. Plant components primarily function as reducing and capping agents in eco-friendly synthesis. Diverse metallic nanoparticles of various sizes and shapes have been created utilizing extracts from plant materials, including leaves, bark, fruits, and flowers. The synthesis of Nobel laureate metal nanoparticles is essential to the medical sector. A diverse array of glycosides and phenolic compounds constitutes numerous organic constituents in plants, facilitating the synthesis of metal nanoparticles. The absence of detrimental by-products in metal nanoparticle synthesis is the primary significance of green synthesis. The nanoparticles generated by an eco-friendly approach demonstrate several significant biological activity. A substantial body of literature demonstrates that the synthesized nanoparticles are efficacious against both gram-positive and gram-negative bacteria, including E. coli, Bacillus subtilis, Klebsiella pneumoniae, and Pseudomonas fluorescens. The synthesized nanoparticles not only display antifungal efficacy against several cancer cell lines, including those of breast cancer, but also demonstrate antifungal activity against Trichophyton simii, Trichophyton mentagrophytes, and Trichophyton rubrum. Moreover, they exhibit potent antioxidant properties. The dimensions and morphology of these metal nanoparticles substantially influence their functionalities. Particles characterized by a large surface area and diminutive size provide significant potential for medical applications. This paper aims to provide a comprehensive summary of current advancements in the synthesis of nanoparticles utilizing biological entities and their numerous potential applications.

The mechanism underlying B-cell developmental dysfunction in Kawasaki disease based on single-cell transcriptomic sequencing.

Kawasaki disease (KD) is an acute systemic vasculitis that can lead to acquired heart disease in children mostly from in developed countries. The previous research showed that B cells in KD patients underwent a profound change in both the cell numbers and types after intravenous immunoglobulin (IVIG) therapy. We performed the single-cell RNA-sequencing for the peripheral blood mononuclear cells (PBMCs) from three febrile patients and three KD patients to investigate the possible mechanism underlying B cell developmental dysfunction in KD. The pseudo-time analysis was employed to study the developmental trajectories of the PBMCs in febrile control and KD patients. Overall single-cell expression profiles show that the biological processes of immunity, B cell activation pathway and their related biological entities are repressed in KD patients before IVIG treatment compared to febrile patient and KD patients after IVIG treatment. The differentially expressed gene analyses further demonstrate that B cell signaling pathway is downregulated in B cells and plasma blast cells of KD patients before treatment while cell cycle genes and MYC gene are upregulated in dendritic cells (DCs) and hematopoietic stem and progenitor cells (HSPCs) of KD patients before treatment. The biological process of immune response is upregulated in the HSPCs of KD patients before treatment in our dataset while the biological process of inflammatory response is upregulated in the HSPCs of KD patients before treatment in GSE168732 dataset. Single-cell trajectory analyses demonstrate that KD patients before treatment have a shortened developmental path in which B cells and T cells are failed to differentiate into separate lineages. HSPD1 and HSPE1 genes show an elevated expression level in the early cell development stage of KD patients before treatment accompanied with the repression of MYC, SPI1, MT2A and UBE2C genes. Our analyses of all B cells from KD patients before treatment show most of B cells are arrested in a transitional state with an ill developmental path compared with febrile patients and KD patients after treatment. Our results indicate that the immune premature HSPCs accompanied with the abnormal expression dynamics of cell cycle and SPI1 genes are the mechanism underlying B cell developmental dysfunction in KD patients.

An Update on Theoretical and Metrological Aspects of the Surface Hydrophobicity of Virus and Virus-Like Particles.

Viruses are biological entities embodied in protein-based nanoparticles devoid of metabolic activity. Hence, the colloidal, interfacial, and chemical reactivity of virus particles (VPs) profoundly affects the fate of natural and artificial viruses in biotic or abiotic aqueous systems. These rely on the physical chemistry at the outer surface of VPs. In other words, whether wild or synthetic VPs and regardless of the scientific fields involved, taming viruses implies thus managing the physical chemistry at the VP external surface. The surface hydrophobicity (SH) of VPs is a critical feature that must be looked at. Still, the literature dealing with nanoscale hydrophobic domains at the proteinaceous surface of VPs underlying their global SH is like a fragmented puzzle. This article provides an overview of the topic from the perspective of modern protein biophysics for updating the classic physicochemical picture of outer VP/water interfaces hitherto accepted. Patterns of non-polar and "false-polar" patches, expressing variable hydrophobic degrees according to neighboring polar patches, are now drawn. The extensive discussion of reviewed data generates such fresh ideas to explore in the coming years for better modeling the SH of wild virions or engineered virus-based nanoparticles, paving the way for new directions in fundamental virology and virus-based chemistry.

Is metadata of articles about COVID-19 enough for multilabel topic classification task?

The ever-increasing volume of COVID-19-related articles presents a significant challenge for the manual curation and multilabel topic classification of LitCovid. For this purpose, a novel multilabel topic classification framework is developed in this study, which considers both the correlation and imbalance of topic labels, while empowering the pretrained model. With the help of this framework, this study devotes to answering the following question: Do full texts, MeSH (Medical Subject Heading), and biological entities of articles about COVID-19 encode more discriminative information than metadata (title, abstract, keyword, and journal name)? From extensive experiments on our enriched version of the BC7-LitCovid corpus and Hallmarks of Cancer corpus, the following conclusions can be drawn. Our framework demonstrates superior performance and robustness. The metadata of scientific publications about COVID-19 carries valuable information for multilabel topic classification. Compared to biological entities, full texts and MeSH can further enhance the performance of our framework for multilabel topic classification, but the improved performance is very limited. Database URL: https://github.com/pzczxs/Enriched-BC7-LitCovid.

Multi-level processing of emotions in life motion signals revealed through pupil responses

Perceiving emotions from the movements of other biological entities is critical for human survival and interpersonal interactions. Here, we report that emotional information conveyed by point-light biological motion (BM) triggered automatic physiological responses as reflected in pupil size. Specifically, happy BM evoked larger pupil size than neutral and sad BM, while sad BM induced a smaller pupil response than neutral BM. Moreover, this happy over sad pupil dilation effect is negatively correlated with individual autistic traits. Notably, emotional BM with only local motion features retained could also exert modulations on pupils. Compared with intact BM, both happy and sad local BM evoked stronger pupil responses than neutral local BM starting from an earlier time point, with no difference between the happy and sad conditions. These results revealed a fine-grained pupil-related emotional modulation induced by intact BM and a coarse but rapid modulation by local BM, demonstrating multi-level processing of emotions in life motion signals. Taken together, our findings shed new light on BM emotion processing, and highlight the potential of utilizing the emotion-modulated pupil response to facilitate the diagnosis of social cognitive disorders.

Multi-level processing of emotions in life motion signals revealed through pupil responses.

Perceiving emotions from the movements of other biological entities is critical for human survival and interpersonal interactions. Here, we report that emotional information conveyed by point-light biological motion (BM) triggered automatic physiological responses as reflected in pupil size. Specifically, happy BM evoked larger pupil size than neutral and sad BM, while sad BM induced a smaller pupil response than neutral BM. Moreover, this happy over sad pupil dilation effect is negatively correlated with individual autistic traits. Notably, emotional BM with only local motion features retained could also exert modulations on pupils. Compared with intact BM, both happy and sad local BM evoked stronger pupil responses than neutral local BM starting from an earlier time point, with no difference between the happy and sad conditions. These results revealed a fine-grained pupil-related emotional modulation induced by intact BM and a coarse but rapid modulation by local BM, demonstrating multi-level processing of emotions in life motion signals. Taken together, our findings shed new light on BM emotion processing, and highlight the potential of utilizing the emotion-modulated pupil response to facilitate the diagnosis of social cognitive disorders.

A novel avenue to explore in the treatment of dementia

A novel avenue to explore in the treatment of dementia A collaborative project between the University of South Florida and The Healthy Aging Company is exploring how a new biological entity called ALF5755 could be a candidate drug for the treatment of dementia and Alzheimer’s disease. Aging is the major common risk factor for death from all adult diseases. Death rates increase logarithmically with advancing age for all diseases associated with aging, including heart disease, cancer, stroke, type 2 diabetes mellitus (T2DM), and Alzheimer’s disease. In this context, Alzheimer’s disease has emerged as a major health concern. Despite some improvement in the therapy, the overall prognosis of AD is still poor. With the current lack of treatments, any type of symptom alleviation will have a beneficial impact on the lives of patients and their caregivers.

Viromes vs. mixed community metagenomes: choice of method dictates interpretation of viral community ecology

BackgroundViruses, the majority of which are uncultivated, are among the most abundant biological entities on Earth. From altering microbial physiology to driving community dynamics, viruses are fundamental members of microbiomes. While the number of studies leveraging viral metagenomics (viromics) for studying uncultivated viruses is growing, standards for viromics research are lacking. Viromics can utilize computational discovery of viruses from total metagenomes of all community members (hereafter metagenomes) or use physical separation of virus-specific fractions (hereafter viromes). However, differences in the recovery and interpretation of viruses from metagenomes and viromes obtained from the same samples remain understudied.ResultsHere, we compare viral communities from paired viromes and metagenomes obtained from 60 diverse samples across human gut, soil, freshwater, and marine ecosystems. Overall, viral communities obtained from viromes had greater species richness and total viral genome abundances than those obtained from metagenomes, although there were some exceptions. Despite this, metagenomes still contained many viral genomes not detected in viromes. We also found notable differences in the predicted lytic state of viruses detected in viromes vs metagenomes at the time of sequencing. Other forms of variation observed include genome presence/absence, genome quality, and encoded protein content between viromes and metagenomes, but the magnitude of these differences varied by environment.ConclusionsOverall, our results show that the choice of method can lead to differing interpretations of viral community ecology. We suggest that the choice of whether to target a metagenome or virome to study viral communities should be dependent on the environmental context and ecological questions being asked. However, our overall recommendation to researchers investigating viral ecology and evolution is to pair both approaches to maximize their respective benefits.ADm-mTTAXM3aVZwCyoroCBVideo

Recent Developments and Prospects of Electromagnetically Active Metamaterials in Biosensing

This paper provides an overview of the progress of research on electromagnetically active metamaterials in the field of biosensing, especially the potential of terahertz metamaterials for biosensor applications. Electromagnetically active metamaterials exhibit a negative refractive index and perfect absorption through their special structure, and their electromagnetic behavior is affected by their structure and geometry, which is different from traditional materials. The article reviews the application of terahertz technology for the bio-detection of cancer cells and apoptotic processes using periodic metal arrays by terahertz biosensors, demonstrating the advantages of terahertz biosensors, such as high sensitivity and detection without labeling. This paper presents a comprehensive overview of the advancements in research concerning electromagnetically active metamaterials within the domain of biosensing, with a particular emphasis on the potential applications of terahertz metamaterials in biosensor technology. Electromagnetically active metamaterials are characterized by their negative refractive index and perfect absorption, which arise from their distinctive structural properties. The electromagnetic behavior of these materials is significantly influenced by their design and geometry, setting them apart from conventional materials. The article examines the utilization of terahertz technology for the bio-detection of cancer cells and apoptotic processes tunability, employing periodic metal arrays in terahertz biosensors. It underscores the advantages of terahertz biosensors, which include high sensitivity and the capability to detect biological entities without the necessity for labeling. Terahertz metamaterial biosensors are promising for protein, virus, and cancer cell detection. This paper also explores the design and application of chiral metamaterials, especially indium tin oxide-based mid-infrared chiral metamaterials, to solve the problem of the large size of traditional materials and investigates their circular dichroism. Looking ahead, electromagnetically active metamaterials, especially terahertz metamaterials, are expected to improve resolving power and sensitivity, reduce costs, and expand the applications of biosensors in the biomedical field. The applications and research of these sensors will continue to advance with the advancement of micro and nanoprocessing technologies.

A paradigm for natural eutectic solvents based on fatty acids: Molecular interactions and toxicological considerations

In this work, we present experimental and molecular modeling results on archetypal hydrophobic natural deep eutectic solvents (NADES) based on fatty acids (octanoic and dodecanoic acid) and menthol, a representative monoterpenoid. Our goal is to provide a multiscale characterization to enhance the understanding of this field by studying these selected archetypical mixtures. We examine their liquid state properties, intermolecular forces, nanoscopic arrangements, toxicity, and environmental impact.The computational study integrates quantum chemistry, molecular dynamics (both all-atom and coarse-grained approaches), and thermodynamic modeling (COSMO-RS approach) to analyze the fluids and their interactions with biological entities, such as proteins and plasma membranes. The experimental characterization focuses on elucidating intermolecular interactions and liquid phase dynamics using NMR spectroscopy, visible and UV Resonance Raman spectroscopy (UVRR). Notably, this is the first report of UVRR data on NADES.Additionally, we simulate the effect of the molecular moieties forming the solvents on biological targets—specifically, protein and cell membrane models –. This in silico analysis aims to rationalize and predict their potential toxicity.Overall, our experimental findings and in silico simulations contribute to a deeper understanding of these novel solvents in terms of their network of interactions. Additionally, they highlight the potential impact on biological targets, providing new data to accurately define the eco-friendliness of type V DES and their suitability as sustainable alternatives to traditional molecular solvents.

Biodiversity of mudflat intertidal viromes along the Chinese coasts

Viruses constitute the most diverse and abundant biological entities on Earth. However, our understanding of this tiniest life form in complex ecosystems remains limited. Here, we recover 20,102 viral OTUs from twelve intertidal zones along the Chinese coasts. Our analysis demonstrates high viral diversity and functional potential in intertidal zones, encoding important functional genes that can be potentially transferred to microbial hosts and mediate elemental biogeochemical cycles, especially carbon, phosphate and sulfur. Virus-host abundance dynamics vary among different microbial lineages. Viral community composition is closely associated with environmental conditions, including dissolved organic matter. Concordant biogeographic patterns are observed for viruses and microbes. Viral communities are generally habitat specific with low overlaps between intertidal and other habitats. Environmental factors and geographic distance dominate the compositional variation of intertidal viromes. Overall, these findings expand our understanding of intertidal viromes within an ecological framework, providing insights into the virus-host coevolutionary arms race.

Towards generative digital twins in biomedical research

Digital twins in biomedical research, i.e. virtual replicas of biological entities such as cells, organs, or entire organisms, hold great potential to advance personalized healthcare. As all biological processes happen in space, there is a growing interest in modeling biological entities within their native context. Leveraging generative artificial intelligence (AI) and high-volume biomedical data profiled with spatial technologies, researchers can recreate spatially-resolved digital representations of a physical entity with high fidelity. In application to biomedical fields such as computational pathology, oncology, and cardiology, these generative digital twins (GDT) thus enable compelling in silico modeling for simulated interventions, facilitating the exploration of ‘what if’ causal scenarios for clinical diagnostics and treatments tailored to individual patients. Here, we outline recent advancements in this novel field and discuss the challenges and future research directions.

Physicochemical and biological characterization of the lipid particles with bovine serum albumin corona

Diacylglycerol–based nanoparticles are promising bioactive delivery systems. However, limited understanding of their interaction with biological entities restricts their clinical use. This study investigated the protein corona formed on medium and long chain diacylglycerol (MLCD)-based solid lipid nanoparticles (NPs) modified by Polyoxethylene stearate (PEG) and compared to glyceryl tristearate (TG) and cetyl palmitate (CP) nanoparticles. Bovine serum albumin (BSA) formed corona with MLCD NPs through hydrophobic interactions and hydrogen bonding, contributing to a decrease in α–helix, an increase in β–sheet and a change in the microenvironment of Tyr residues. Owing to higher lipid hydrophilicity, MLCD NPs showed a much lower affinity for BSA than TG and CP NPs, and the binding constant with BSA was increased for larger NPs. PEG modification and the protein corona reduced the uptake of NPs by macrophages but exerted little influence on B16 cell. Among the NPs with different lipid core, the MLCD NPs showed a lower macrophages cell uptake but higher B16 cell uptake, suggesting a longer circulation time in blood but higher cancer cell internalization. This work shed light on the interactions between MLCD NPs and proteins, which is significant for application as nanocarriers with improved biological efficacy.

High-frequency episodic migraine: Time for its recognition as a migraine subtype?

High-frequency episodic migraine (HFEM) has gained attention in the field of headache research and clinical practice. In this narrative review, we analyzed the available literature to assess the evidence that could help decide whether HFEM may represent a distinct clinical and/or biological entity within the migraine spectrum. The output of the literature search included 61 papers that were allocated to one of the following topics: (i) socio-demographic features and burden; (ii) clinical and therapeutic aspects; (iii) pathophysiology; and (iv) classification. Multiple features differentiate subjects with HFEM from low-frequency episodic migraine and from chronic migraine: education, employment rates, quality of life, disability and psychiatric comorbidities load. Some evidence also suggests that HFEM bears a specific profile of activation of cortical and spinal pain-related pathways, possibly related to maladaptive plasticity. Subjects with HFEM bear a distinctive clinical and socio-demographic profile within the episodic migraine group, with a higher disease burden and an increased risk of transitioning to chronic migraine. Recognizing HFEM as a distinct entity is an opportunity for the better understanding of migraine and the spectrum of frequency with which it can manifest, as well as for stimulating further research and more adequate public health approaches.

Predictability and evolutionary determinism — the search for quantitative explanation

Physics describes reality through the understanding and elucidation of physical laws. From these laws, the universe is predictable. It has indeed been suggested that explanation of observable phenomena comes from our ability to predict these events, through our understanding of physical laws and causal processes. Biological entities operate, of course, through physical and chemical laws. But there exist biological processes that have emergent properties, notably the evolution of adaptation through natural selection, which add an extra dimension to the concept of the understanding of biological phenotypes. The population genetic theory of evolution is mathematically formulated, and contains elements of determinism, typified by the action of natural selection, and elements of randomness, typified by the action of genetic drift and by the randomness of mutation. But is the goal-directed property of natural selection sufficient to conclude that the deterministic elements of the evolutionary process make evolutionary change predictable? And to what extent can we expect 'adaptation' to function as an explanation of biological phenotypes?

Cyanobacterial Silver Nanoparticles and Their Potential Utility-Recent Progress and Prospects: A Review.

The current situation involves an increase in interest in nanotechnology, in particular the ways in which it can be applied in the commercial and medical fields. However, traditional methods of synthesizing nanoparticles have some drawbacks, including the generation of harmful byproducts, high energy consumption, and cost. As a result, researchers have shifted their focus to "green" nanoparticle synthesis to circumvent these drawbacks. Because of their exceptional physiochemical properties, silver nanoparticles (Ag Nps) are the noble metal nanoparticles that are used most frequently. The green approach to Ag NP synthesis is environmentally friendly, non-toxic, and cost-effective, and it makes use of a variety of biological entities. Cyanobacteria, in particular, have garnered the most attention because of the abundance of bioactive substances that they contain, which serve both as reducing agents and as stabilizing agents during the process of biosynthesis. This review article discusses the current state of cyanobacteria-mediated Ag NP synthesis, the potential mechanisms that are involved, nanoparticle characterization, the various applications of Ag NP in different fields, and their prospects.