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This review illustrates heavy metals toxicity, currently available therapies and the role and efficacy of chelation therapy for its management. Heavy metals are necessary for various biological processes, but they become harmful in excess. Specifically, they induce oxidative stress by generating free radicals and reducing antioxidant levels. Heavy metals also alter the confirmation of protein and DNA and inhibit their function. Chelation therapy is commonly used to treat metals toxicity. Chelation is a chemical process that occurs when interaction between a central metal atom/ion and ligand leads to formation of a complex ring-like structure. The ligand has a donor ion/molecule, which has a lone pair of electrons and may be monodentate to polydentate. Each metal has a different reactivity with a ligand, so a specific chelation agent is required for each metal. Combination therapy with a chelating agent and an antioxidant led to improved outcome. Heavy metal poisoning is a common health problem because of mining, smelting, industrial, agricultural and sewage waste. Heavy metals can be efficiently excreted from the body following treatment with proper chelation agents. [ABSTRACT FROM AUTHOR]

Background: Chemo-resistance is the main obstacle in cancer therapy, limiting the effectiveness of drug treatment. Epigenetics-mediated changes are suggested as a critical factor paying the chemo-resistance phenotype. Since epigenetic modulations are a reversible phenomenon, reversion of epigenetic changes represents a promising therapeutic approach for cancer. However, heterogeneity in epigenetic marks in tumor cells makes it difficult to identify the specific epigenetic aberrations contributing to chemo-resistance. Our hypothesis aimed to explore this issue to add therapeutic options for cancer.Presentation Of the Hypothesis: Epigenetic alterations, the main mediator of cellular reprogramming, occur rapidly upon exposure to chemotherapy. Recent studies have demonstrated that reprogramming resets/erases the epigenetic marks established during differentiation to specific somatic cell types. To overcome the heterogeneous nature of cancer cells, we will attempt to make homogenous cancer cell colonies by reprogramming. Comparison of the drug-resistant cancer cells obtained from these colonies to parent cancer cells and reprogrammed cancer cells is an effective way to determine the precise epigenetic alterations underlying specific chemo-resistance.Testing the Hypothesis: Cellular reprogramming of cancer cells led to generation of homogenous colonies. Following lineage specification and long term drug treatment, the obtained drug resistance cells will be compared with parent cancer cells for whole genome epigenetic signature.Implications Of the Hypothesis: A key implication of this hypothesis is that determination of the usefulness of cellular reprogramming of cancer cells enabling the identification of specific epigenetic modulation associated with particular drug resistance will enable exploration of new research avenues for cancer treatment. [ABSTRACT FROM AUTHOR]

• Updated methods for spatial transcriptomic data analyses. • Analyses of spatial transcriptomics databases. • Challenges associated with AI-based methods in analyses of ST data. Spatial transcriptomics (ST) is a newly emerging field that integrates high-resolution imaging and transcriptomic data to enable the high-throughput analysis of the spatial localization of transcripts in diverse biological systems. The rapid progress in this field necessitates the development of innovative computational methods to effectively tackle the distinct challenges posed by the analysis of ST data. These platforms, integrating AI techniques, offer a promising avenue for understanding disease mechanisms and expediting drug discovery. Despite significant advances in the development of ST data analysis techniques, there is an ongoing need to enhance these models for increased biological relevance. In this review, we briefly discuss the ST-related databases and current deep-learning-based models for spatial transcriptome data analyses and highlight their roles and future perspectives in biomedical applications. [ABSTRACT FROM AUTHOR]

This study assessed the trends in inbreeding, effective population size, and genetic diversity across six Korean native chicken lines using pedigree records from 54,383 chickens. Understanding these genetic parameters is significantly important for maintaining healthy and viable chicken populations. The primary objective was to analyze the pedigree data to assess the levels of inbreeding and genetic diversity and to evaluate the effective population size across the different lines. Pedigree analysis revealed that pedigree completeness peaked in the first generation and declined in subsequent generations for all lines. Line A exhibited a mean inbreeding coefficient of 0.0201, whereas the other lines displayed lower mean values ranging from 0.0009 to 0.0098, indicating that inbreeding levels were within an acceptable range and considered safe from extinction. Average relatedness consistently increased with time. Individual increases in inbreeding were the highest in Line A (0.62%), with smaller increases in the other lines ranging from 0.02 to 0.23%. Effective population sizes varied from 81 to 2500, with average coancestry within parental populations ranging from 0.0032 to 0.0290. The f e /f a ratio between 1.00 and 1.69 in the 6 lines suggested a moderate impact during bottleneck events, with subsequent populations recovering well. The genetic diversity loss due to genetic drift and unequal founder contributions ranged from 0.66–3.15%, indicating that considerable genetic variability remains within the populations. The results of this study have practical applications in the management and conservation of genetic resources in poultry breeding programs. By highlighting the importance of monitoring inbreeding and maintaining genetic diversity, the findings can help develop strategies to ensure the long-term sustainability of these chicken lines. This study provides valuable insights into the genetic management of Korean native chicken lines, emphasizing the need for strategic breeding practices to preserve genetic health and diversity. [ABSTRACT FROM AUTHOR]

Abstract: Background: : Patients suffering from hemorrhagic fever with renal syndrome (HFRS) often showed strikingly reduced high-density lipoprotein (HDL)-cholesterol levels during the oliguric phase, indicating severe alterations in lipoprotein metabolism. Objective: : To compare changes in the functions and composition of HDL, lipoprotein metabolism parameters were analyzed in the sera of HFRS patients in the oliguric phase and after recovery. Methods: : The serum cholesterol, triglyceride (TG), and lipoprotein/apolipoprotein profiles of HFRS patients in the oliguric and recovery phases were compared with those of normal reference sera. The activities of HDL-associated enzymes, lecithin:cholesterol acyltransferase (LCAT), and paraoxonase (PON) were also assessed. Results: : In the oliguric phase, serum cholesterol was substantially decreased and serum TG was increased. As observed by electron microscopy, the sizes of the HDL particles from the HFRS patients were smaller than those seen in the reference sera, with more heterogeneous distribution. Serum amyloid A (SAA) and apolipoprotein (apo) C-III were overexpressed in the oliguric phase, particularly in the HDL fraction. However, in immunodetection, the levels of apoA-I in the HDL2 and HDL3 of the HFRS patients were lower than those of the reference HDL. Serum LCAT and PON activities were reduced significantly in the oliguric phase, which is associated with a reduction in HDL-cholesterol levels and HDL particle size. Conclusion: : Overexpression of both apoC-III and apoSAA in HDL and attenuated serum LCAT and PON activity were observed during the oliguric phase in HFRS patients. These results demonstrate that structural, functional, and compositional changes of HDL occurred to a substantial degree in the oliguric phase. [Copyright &y& Elsevier]