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Copyright of Veterinarska Stanica is the property of Croatian Veterinary Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Veterinarska Stanica is the property of Croatian Veterinary Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The exponential growth of genomic data in biomedical informatics has necessitated efficient computational methods to process and analyze vast datasets. Traditional computational systems often fall short in handling the scale and complexity of genomic data. This study investigates the implementation of grid computing as a scalable and cost-effective solution for genomic data processing in biomedical informatics. The research aims to evaluate the feasibility and performance of grid computing in enhancing data throughput, reducing computational latency, and improving resource utilization in genomic data workflows. The study adopts a methodological approach that integrates grid computing frameworks, such as Globus Toolkit and Apache Hadoop, into genomic data processing pipelines. Simulated genomic datasets and real-world case studies were employed to benchmark the grid computing system against conventional computational environments. The results demonstrate significant improvements in processing speed, with an average reduction of 40% in computational time, and a 25% increase in resource efficiency. Additionally, the system showcased robust scalability, handling up to 10 times larger datasets without compromising accuracy or reliability. In conclusion, the findings underscore the potential of grid computing to revolutionize genomic data processing, making it a pivotal technology in biomedical informatics. This study highlights the importance of adopting distributed computing paradigms to address the challenges posed by modern bioinformatics demands. [ABSTRACT FROM AUTHOR]

The rapid growth of biomedical research has generated massive volumes of data, creating significant computational challenges. Traditional high-performance computing systems struggle to efficiently process, analyze, and manage such large-scale datasets. Grid computing, with its distributed architecture, offers a promising solution by enabling scalable and cost-effective data processing. This study explores the optimization of grid computing frameworks for big data processing in biomedical research, focusing on enhancing computational efficiency, scalability, and fault tolerance. The research aimed to evaluate the performance of optimized grid computing systems in processing diverse biomedical datasets, including genomic, proteomic, and imaging data. A combination of experimental and comparative approaches was employed, integrating grid computing frameworks such as Apache Hadoop and Globus Toolkit with biomedical data pipelines. Key metrics, including processing time, resource utilization, and error rates, were analyzed to assess the system's performance. The findings demonstrated that optimized grid computing systems reduced processing time by an average of 35% compared to traditional methods while maintaining high accuracy. Scalability tests confirmed the framework's ability to handle datasets up to 15 times larger without significant performance degradation. Fault tolerance improved through adaptive resource allocation, minimizing workflow interruptions. The study concludes that optimized grid computing is a transformative approach for big data processing in biomedical research. Its ability to enhance computational efficiency and scalability positions it as a crucial tool for addressing the growing data demands of modern biomedical science. [ABSTRACT FROM AUTHOR]

Most Americans, even those that consider themselves vegan, are implicated in the morally deplorable practice of harvesting and bleeding horseshoe crabs. In the U.S., the biomedical industry collects the distinctive blue blood of horseshoe crabs to test the safety of most injectable medicines, vaccines, and implantable medical devices. In 2022, the industry harvested more than 900,000 horseshoe crabs from the Atlantic coast and bled them for biomedical purposes. While most are returned to the sea afterwards, an estimated 20-35% of horseshoe crabs perish from the bleeding process, and the released survivors often suffer lasting health consequences after the removal of up to half of their blood. Currently, there is only a patchwork of federal, state, and interstate regulation addressing the taking, treatment, and use of horseshoe crabs collected for biomedical purposes. These anthropocentric regulations fall drastically short of protecting horseshoe crabs' interest in living free from human exploitation. Fortunately, recent developments may soon encourage an industry shift to a non-animal-derived alternative toxicity test. This paper argues the replacement of the horseshoe crab-dependent test, rather than improved welfare regulations, would best protect the interests of horseshoe crabs. The latter only further entrenches the exploitative biomedical horseshoe crab industry. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing (scRNA-seq) is one of the most advanced sequencing technologies for studying transcriptome landscape at the single-cell revolution. It provides numerous advantages over traditional RNA-seq. Since it was first used to profile single-cell transcriptome in plants in 2019, it has been extensively employed to perform different research in plants. Recently, scRNA-seq was also quickly adopted by the cotton research community to solve lots of scientific questions which have been never solved. In this comment, we highlighted the significant progress in employing scRNA-seq to cotton genetic and genomic study and its future potential applications. [ABSTRACT FROM AUTHOR]

AI technologies can pose a major national security concern. AI programs could be used to develop chemical and biological agents which circumvent existing protective measures or medical treatments, or to design pathogens with capabilities they do not naturally possess (gain-of-function research). Although Australia has a strong legislative framework relating to research into genetically modified organisms, the framework requires the interaction of more than 10 different government departments, universities and funding agencies. Further, there are few guidelines about the responsible use of AI in biological research where existing laws and policies do not apply to research that is conducted “virtually”, even where that research may have national security implications. This article explores these under-scrutinised concepts in Australia’s biological security frameworks. [ABSTRACT FROM AUTHOR]

Drug delivery systems play a pivotal role in targeted pharmaceutical transport and controlled release at specific sites. Liposomes, commonly used as drug carriers, constitute a fundamental part of these systems. Moreover, the drug–liposome model serves as a robust platform for investigating interaction processes at both cellular and molecular levels. To advance our understanding of drug carrier uptake mechanisms, we employed fluorescence lifetime imaging microscopy (FLIM) and fluorescence correlation spectroscopy (FCS), leveraging the unique benefits of two-photon (2P) excitation. Our approach utilized giant unilamellar vesicles (GUVs) as a simplified model system for cell membranes, labelled with the amphiphilic fluorescent dye 3,3′-dioctadecyloxa-carbocyanine (DiOC18(3)). Additionally, large unilamellar vesicles (LUVs) functioned as a drug carrier system, incorporating the spectrally distinct fluorescent sulforhodamine 101 (SRh101) as a surrogate drug. The investigation emphasized the diverse interactions between GUVs and LUVs based on the charged lipids employed. We examined the exchange kinetics and structural alterations of liposome carriers during the uptake process. Our study underscores the significance of employing 2P excitation in conjunction with FLIM and FCS. This powerful combination offers a valuable methodological approach for studying liposome interactions, positioning them as an exceptionally versatile model system with a distinct technical advantage. [ABSTRACT FROM AUTHOR]

For many biomedical applications, laser-assisted methods are essential to enhance the three-dimensional (3D) resolution of a light microscope. In this report, we review possibilities to improve the 3D imaging potential by axial tomography. This method allows us to rotate the object in a microscope into the best perspective required for imaging. Furthermore, images recorded under variable angles can be combined to one image with isotropic resolution. After a brief review of the technical state of the art, we show some biomedical applications, and discuss future perspectives for Deep View Microscopy and Molecular Imaging. [ABSTRACT FROM AUTHOR]

Play is a suite of apparently non‐functional, pleasurable behaviours observed in human and non‐human animals. Although the phenomenon has been studied extensively, no adaptationist behavioural theory of how play evolved can be supported by the available evidence. However, the advancement of the extended evolutionary synthesis and developments in systems biology offer alternative avenues for non‐adaptationist physiological hypotheses. I therefore propose a hypothesis of play, based upon a complex ACh activity that is under agential control of the organism, whereby play initiates ACh‐mediated feedforward and feedback processes which act to: (i) regulate metabolic processes; (ii) form new ACh receptors via ACh mRNA activity; (iii) mediate attention, memory consolidation and learning; and (iv) mediate social behaviours, reproduction and embryonic development. However, play occurs across taxa, but does not occur across all taxonomic groups or within all species of a taxonomic group. Thus, to support the validity of the proposed hypothesis, I further propose potential explanations for this anomaly, which include sampling and observer biases, altricial versus precocial juvenile development, and the influence of habitat niche and environmental conditions on behaviour. The proposed hypothesis thus offers new avenues for study in both the biological and social sciences, in addition to having potential applications in applied sciences, such as animal welfare and biomedical research. Crucially, it is hoped that this hypothesis will promote further study of a valid and behaviourally significant, yet currently enigmatic, biological phenomenon. [ABSTRACT FROM AUTHOR]

An anonymous online survey in French was used to assess if endometriosis patients would be as ready as unaffected women to donate their menstrual blood for biological research on endometriosis and evaluate potential barriers to such donation. It was distributed in September 2022 by social media and two mailing lists, including a French patient organization. The questionnaire assessed participant age and brief medical history (hormonal contraception, endometriosis diagnosis, type of endometriosis), menstrual experience (menstrual blood abundance, dysmenorrhea), and whether participants would donate menstrual blood. Women who self-declared with an established endometriosis diagnosis versus no endometriosis were compared. Seven hundred seventy-eight women answered the survey. Among women with menstruation (n = 568), 78% are willing to donate menstrual blood for research. Importantly, this proportion was higher in women who declared having an established endometriosis diagnosis (83%, n = 299) compared to self-declared unaffected women (68%, n = 134, p < 0.001). The previous use of a menstrual cup and dysmenorrhea were significantly associated with the willingness to donate menstrual blood, while the use of hormonal contraception was significantly associated with an unwillingness to donate. Only the previous use of the menstrual cup had a predictive value for menstrual blood donation. No significant relationship was observed between menstrual blood donation and age, heavy menstrual bleeding and in endometriosis patients, endometriosis subtypes. In conclusion, women affected or not by endometriosis are largely willing to donate their menstrual blood for research on endometriosis, dysmenorrhea is not a barrier for donation, and women who use a menstrual cup are the more likely to donate. [ABSTRACT FROM AUTHOR]

Elucidating the 3D nanoscale structure of tissues and cells is essential for understanding the complexity of biological processes. Electron microscopy (EM) offers the resolution needed for reliable interpretation, but the limited throughput of electron microscopes has hindered its ability to effectively image large volumes. We report a workflow for volume EM with FAST-EM, a novel multibeam scanning transmission electron microscope that speeds up acquisition by scanning the sample in parallel with 64 electron beams. FAST-EM makes use of optical detection to separate the signals of the individual beams. The acquisition and 3D reconstruction of ultrastructural data from multiple biological samples is demonstrated. The results show that the workflow is capable of producing large reconstructed volumes with high resolution and contrast to address biological research questions within feasible acquisition time frames. [ABSTRACT FROM AUTHOR]

The ability of shape memory polymers to change shape upon external stimulation makes them exceedingly useful in various areas, from biomedical engineering to soft robotics. Especially, shape memory hydrogels (SMHs) are well-suited for biomedical applications due to their inherent biocompatibility, excellent shape morphing performance, tunable physiochemical properties, and responsiveness to a wide range of stimuli (e.g., thermal, chemical, electrical, light). This review provides an overview of the unique features of smart SMHs from their fundamental working mechanisms to types of SMHs classified on the basis of applied stimuli and highlights notable clinical applications. Moreover, the potential of SMHs for surgical, biomedical, and tissue engineering applications is discussed. Finally, this review summarizes the current challenges in synthesizing and fabricating reconfigurable hydrogel-based interfaces and outlines future directions for their potential in personalized medicine and clinical applications. [ABSTRACT FROM AUTHOR]

Scientific validation of the interventions used for the treatment of various ailments in Ayush systems of medicine (ASM) is currently an emerging field. The stakeholders hesitate to promote the traditional knowledge to resolve the current health issues without exploring the scientific rationale and rigorous experimentation. It seems that scientific validation of traditional approaches has become a roadblock for the translation of the aged old experiences and wisdom into clinical practice. This systematic review has been done to study the evolving research trends, existing policy, current regulatory mechanism and publication criteria for the research meant for scientific validation of ASM. This review is based on the analysis of the published clinical trials, ethical and regulatory guidelines published between 2001 and 2022. The major databases were searched such as Medline, AYUSH Research Portal, Google Scholar, Scopus, Science Direct and Web of Science. The analysis showed that the trends for scientific validation studies had continuously been on the rise in the past two decades. The guidelines for validation studies, safety studies, good clinical practices and ethical guidelines for biomedical research had been framed for research in ASM. We observed that there were no defined minimum standards for an intervention to be declared scientifically validated so that the research could be directional. Our study concludes that the concept of scientific validation of traditional approaches has not been comprehensively defined so far. As a result, scientific validation studies are not conducted in such a direction leading to achieve the set targets in the near future. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes is caused by a complex combination of genetic predisposition and lifestyle factors, which contributes to its rising global incidence. a-amylase is a critical pharmaceutical target for reducing postprandial hyperglycemia in diabetes and other metabolic diseases. Because of the numerous side effects associated with synthetic anti-diabetic drugs, the use of natural substances for diabetes management has grown in popularity in recent years. Methods: In this study, potential a-amylase inhibitors were identified using virtual screening approaches, with a focus on bioactive compounds derived from Zingiber officinale. A comprehensive screening of 383 compounds was performed against the a-amylase active site. Following that, 14 compounds were identified as having greater binding energy efficacy than the control compounds. Results: The compounds LTS0006138, LTS0117761, LTS0176515, LTS0102243, and LTS0018665 exhibited notable interactions with the catalytic residues of a-amylase in this study, particularly by forming hydrogen bonds with multiple residues within the enzyme. Furthermore, an analysis of the molecular properties and descriptors of these five compounds showed promising drug-like properties. Conclusion: These compounds show promise as potential novel a-amylase inhibitors; nevertheless, further experimental validation is required to optimize their potency as a-amylase inhibitors. [ABSTRACT FROM AUTHOR]

Cell culture is a vital method in biological and biomedical research. The global cell culture market, valued at around USD 26.54 billion in 2023, is projected to surpass USD 63.60 billion by 2032. While two-dimensional cell culture has led to significant advancements in biology, its simplicity does not accurately reflect the complex in vivo environment. This can result in misleading data with limited predictive value for in vivo applications, prompting increased interest in three-dimensional (3D) cultivation methods. The 3D cell culture mimics the behavior and organization of cells in vivo by emulating the extracellular matrix (ECM), providing better insights into 3D interactions among cells and between cells and the matrix, thus reconstructing their natural microenvironment. In this review we will outline the various types of 3D models (include spheroids, organoids, bio-printed structures, and tissue chips). Subsequently, we will examine the methodologies employed to develop 3D culture systems (include four category methods). Lastly, the practical applications and challenges of these 3D models will be addressed. The future research will likely concentrate on incorporating cutting-edge technologies to improve the reproducibility and applicability of 3D models in research. [ABSTRACT FROM AUTHOR]

Reports of low replicability and translatability of biomedical research have called the value of animal models into question. The problems are real, but abandoning animal research is not the solution. Rather, improving the translatability of model-based research requires attention to relevant differences between humans and models, and to attributes of the models themselves that are essential to both robust science and effective translation. One is biological plasticity, the responsiveness of individual organisms to complex and variable environments. Though under-represented in model systems (for both historical and practical reasons), plasticity is central to human biology. While there are good reasons to minimize environmentally-induced variation in model-based research, doing so may undermine its translatability by eliding the kinds of external influences that are critical to human development, health, and disease. Accounting for plasticity can strengthen both the replicability and the translatability of model-based studies; this paper identifies strategies for doing so at each stage of the research process. [ABSTRACT FROM AUTHOR]

Background: Understanding the anatomical structure of the human kidney, particularly its zonal and segmental organization, is crucial for both theoretical knowledge and practical applications in surgical procedures. That is why the purpose of the article was to study the variants of the zonal and segmental structure of human kidneys. Methods: 116 corrosive preparations of the arterial system of the human kidney served as the material for the study. The authors identified their extra-organ branches: a) the number of arterial vessels in the kidney hilum; b) the topographic and anatomical features of the renal artery trunks. In a 3D projection, zones of local zonal blood supply to areas of the renal parenchyma were identified, depending on the di- and trichotomic variants of the division of the main renal artery, A. renalis (I). Results: It was found that some lines of the passage of the zones of natural divisibility of the kidneys with different variants of the division of A. renalis (I). There were from 5 to 7 (6 ± 1) segments in the kidneys on average. It is possible that if a four-zone blood supply system with corresponding zones of natural kidney divisibility is found in the kidneys, where the zones mostly don’t coincide with the boundaries of the passage of segments in their classical version, the number of segments will be even greater. Conclusion: The results of the conducted study show that considering the generally accepted zones and boundaries of the passage of segments with zones of natural divisibility, which were not previously considered, the kidneys have an individual segmental structure, which requires revision. The authors believe that the generally accepted classical five-segment kidney model is outdated. [ABSTRACT FROM AUTHOR]

Background: Vascular corrosion casting is an old method that has found application by anatomists for a long time. Initially, the viscosity of casting media was very high and thus the technique failed to cast the entire circulatory system from the arterial injection site through small arteries, arterioles, capillaries, venules, small veins and caval veins. Casting media soon were improved and thus enabled casting of the entire circulatory system. Examination of these vascular casts under the light microscope does not allow a thorough analysis with high resolution. Only when in 1971 Murakami applied Scanning Electron Microscopy SEM. to study vascular corrosion casts a breakthrough was achieved and for the first time, microvascular networks, too, were able to be analysed with a spatial resolution high enough to study the surface of the casts also termed injection replicas. and a depth of focus high enough to examine a large field of view enabling to reliably trace individual vessels either over very short or over extremely long distances. Scanning electron microscopy SEM. is a tool with great potential for morphological research. The images generated via SEM have great resolution and a high depth of focus, which gives SEM micrographs pseudo three-dimensionality. Adversely, the high depth of focus prevents accurate dimensional or spatial measurements of imaged microstructures from either the SEM video-display, printed micrographs or from photonegatives. Macroscopic objects are viewed close up using binocular vision. Binocular vision is also used in microscopy where stereophotogrammetry and related techniques applying stereo paired images, and a variety of hardware tools calculate the third dimension z-coordinate. using the parallax. Morphometric SEM 3D analysis is currently used to analyse i. the geometry of microvascular trees in terms of vascular parameters i.e., diameters, interbranching distances, branching angles and intervascular distances. and ii. to determine bifurcation indices, asymmetry and area ratios given in arterial bifurcations respectively in venous mergings. Moreover, it allows to generate anaglyphic 3D images and to calculate optimality principles underlying the construction and maintenance of such delicate vascular networks i.e. principles of minimal lumen volume, minimal pumping power, minimal lumen surface and minimal endothelial shear force. Aim: The main goal of the method is to characterize microvascular networks in human and animal tissues in order to demonstrate their anatomical situations and to reflect onto their physiological conditions. These methods enable not only to qualitatively describe but also to quantitatively explore the microvascularisation by means of three-dimensional morphometry and thus to compare different developmental stages and progress of disease. Conclusions: The combination of the techniques described above allows a thorough study of microvascular networks in healthy- and pathologic tissues and organs. This enables i. to enhance the knowledge of vascular- / anatomical situations and development, ii. to compare the physiological conditions in health and different pathologies and iii. to gain insights and to develop therapeutical strategies in various clinical pictures, which are critically dependent on a proper functioning vascularization. [ABSTRACT FROM AUTHOR]

Transcriptomics is one of the largest areas of research in biological sciences. Aside from RNA expression levels, the significance of RNA spatial context has also been unveiled in the recent decade, playing a critical role in diverse biological processes, from subcellular kinetic regulation to cell communication, from tissue architecture to tumor microenvironment, and more. To systematically unravel the positional patterns of RNA molecules across subcellular, cellular, and tissue levels, spatial transcriptomics techniques have emerged and rapidly became an irreplaceable tool set. Herein, we review and compare current spatial transcriptomics techniques on their methods, advantages, and limitations, as well as applications across a wide range of biological investigations. This review serves as a comprehensive guide to spatial transcriptomics for researchers interested in adopting this powerful suite of technologies. [ABSTRACT FROM AUTHOR]

The Family Commelinaceae is considered one of the largest families in the plant kingdom, comprising 41 genera and 731 species. The biodiversity in Maha Sarakham Province plays a significant role in the daily lives of its inhabitants. It’s used as local food, vegetables, medicinal and ornamental plants, rituals, natural dyes, traditional cosmetics, and construction materials. This study aimed to determine Commelinaceae’s diversity, conservation status and traditional uses in Maha Sarakham Province, northeastern Thailand. Seven genera with 26 species of Commelinaceae were collected between January and December 2021 in field surveys. The genus diversity was Murdannia (7 species), Cyanoyis and Tradescantea (5 species each), Commelina (4 species), Callisia (3 species), Amischotolype and Floscopa (1 species each). Callisia repens, Callisia fragrans, and Tradescantia spathacea are popular ornamental species with varied leaf colour. Commelinaceae is significantly distributed in the Kantharawichai District in four ecosystems: deciduous dipterocarp forest (13 species), mixed deciduous forest (4 species), river basin (5 species) and 11 species in home gardens. This study reported 15 native (57.69%) and 11 cultivated species (42.31%) grouped into non-common species (50%) and common species (50%). The phenology is presented from June to September. The conservation status of five species is Least Concern (LC). The study revealed that 16 species from the research area are used for food, ornamental (9 species), rituals (1 species), medicine (4 species), and other purposes (8 species). This study provides important biological resource data on Commelinaceae; to our knowledge, this is the first biodiversity survey of the family [ABSTRACT FROM AUTHOR]

Large genomic datasets are created through numerous activities, including recreational genealogical investigations, biomedical research, and clinical care. At the same time, genomic data has become valuable for reuse beyond their initial point of collection, but privacy concerns often hinder access. Beacon services have emerged to broaden accessibility to such data. These services enable users to query for the presence of a particular minor allele in a dataset, and information helps care providers determine if genomic variation is spurious or has some known clinical indication. However, various studies have shown that this process can leak information regarding if individuals are members of the underlying dataset. There are various approaches to mitigate this vulnerability, but they are limited in that they (1) typically rely on heuristics to add noise to the Beacon responses; (2) offer probabilistic privacy guarantees only, neglecting data utility; and (3) assume a batch setting where all queries arrive at once. In this article, we present a novel algorithmic framework to ensure privacy in a Beacon service setting with a minimal number of query response flips. We represent this problem as one of combinatorial optimization in both the batch setting and the online setting (where queries arrive sequentially). We introduce principled algorithms with both privacy and, in some cases, worstcase utility guarantees. Moreover, through extensive experiments, we show that the proposed approaches significantly outperform the state of the art in terms of privacy and utility, using a dataset consisting of 800 individuals and 1.3 million single nucleotide variants. [ABSTRACT FROM AUTHOR]

Functional data analysis has demonstrated significant success in time series analysis. In recent biomedical research, it has also been used to analyze sequence variations in genome-wide association studies (GWAS). The observations of genetic variants, called single-nucleotide polymorphisms (SNPs), of an individual are distributed over the loci of a DNA sequence. Thus, it can be regarded as a realization of a stochastic process, which is no different from a time series. However, SNPs are usually coded as the number of minor alleles, which are categorical. The usual least-square smoothing in FDA only works well when the data is continuous and normally distributed. The normality assumption will be violated for categorical SNP data. In this work, we propose a two-step method for smoothing categorical SNPs using a novel method and constructing haplotypes having strong associations with the disease using functional generalized linear models. We show its effectiveness through a real-world PennCATH dataset. [ABSTRACT FROM AUTHOR]

Ascorbic acid (AA) has many health benefits, including immune and cardiovascular deficiency protection, prenatal problems, and skin diseases. Unfortunately, AA is easily oxidized and has limited bioavailability. Thus, the development of formulations that stabilize and enhance the efficacy of AA is a challenge. In this study, 4% AA was encapsulated in two recently developed gels, a hydrogel and a bigel. The hydrogel was formed exclusively with lipids and water, and the bigel was a combination of the hydrogel with an oleogel formed with olive oil and beeswax. The effect of AA in gel microstructures was determined using X-ray scattering, rheology, and texture analysis. Additionally, the capacity of these materials to protect AA from degradation upon temperature and sunlight was studied. Results showed that the incorporation of AA into both materials did not affect their microstructure. Moreover, hydrogel-protected AA showed only 2% degradation after three months at 8 °C, while in aqueous solution, it degraded by 12%. Regarding sunlight, bigel showed a good shielding effect, exhibiting only 2% AA degradation after 22 h of exposure, whereas in aqueous solution, AA degraded by 10%. These results suggest that both proposed gels could be used in biomedical applications and the field of food. [ABSTRACT FROM AUTHOR]