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Sepsis, a disease caused by severe infection, has a high mortality rate. At present, there is a lack of reliable algorithmic models for biomarker mining and diagnostic model construction for sepsis. Programmed cell death (PCD) has been shown to play a vital role in disease occurrence and progression, and different PCD-related genes have the potential to be targeted for the treatment of sepsis. In this paper, we analyzed PCD-related genes in sepsis. Implicated PCD processes include apoptosis, necroptosis, ferroptosis, pyroptosis, netotic cell death, entotic cell death, lysosome-dependent cell death, parthanatos, autophagy-dependent cell death, oxeiptosis, and alkaliptosis. We screened for diagnostic-related genes and constructed models for diagnosing sepsis using multiple machine-learning models. In addition, the immune landscape of sepsis was analyzed based on the diagnosis-related genes that were obtained. In this paper, 10 diagnosis-related genes were screened for using machine learning algorithms, and diagnostic models were constructed. The diagnostic model was validated in the internal and external test sets, and the Area Under Curve (AUC) reached 0.7951 in the internal test set and 0.9627 in the external test set. Furthermore, we verified the diagnostic gene via a qPCR experiment. The diagnostic-related genes and diagnostic genes obtained in this paper can be utilized as a reference for clinical sepsis diagnosis. The results of this study can act as a reference for the clinical diagnosis of sepsis and for target discovery for potential therapeutic drugs. [ABSTRACT FROM AUTHOR]

Abstract: We described a novel approach to directly amplify genomic DNA from whole blood and dried blood spotted on filter paper without any DNA isolation by using the PCR buffer with a higher pH, which was optimized as pH 9.1–9.6. Direct PCR on blood treated with various anticoagulants showed that the buffer worked well with the blood treated by citrate, EDTA, or heparinate. DNA fragments with different lengths could be efficiently amplified directly from various forms of blood samples. By coupling the buffer with tetra-PCR, a “true” single-tube genotyping was realized by using whole blood or paper-dried blood as starting material. [Copyright &y& Elsevier]

Eucalyptus globulus is one of the most economically important plantation hardwoods for paper making. However, its low transformation frequency has prevented genetic engineering of this species with useful genes. We found the hypocotyl section with a shoot apex has the highest regeneration ability among another hypocotyl sections, and have developed an efficient Agrobacterium-mediated transformation method using these materials. We then introduced a salt tolerance gene, namely a bacterial choline oxidase gene ( codA) with a GUS reporter gene, into E. globulus. The highest frequency of transgenic shoot regeneration from hypocotyls with shoot apex was 7.4% and the average frequency in four experiments was 4.0%, 12-fold higher than that from hypocotyls without shoot apex. Using about 10,000 explants, over 250 regenerated buds were confirmed as transformants by GUS analysis. Southern blot analysis of 100 elongated shoots confirmed successful generation of stable transformants. Accumulation of glycinebetaine was investigated in 44 selected transgenic lines, which showed 1- to 12-fold higher glycinebetaine levels than non-transgenic controls. Rooting of 16 transgenic lines was successful using a photoautotrophic method under enrichment with 1,000 ppm CO. The transgenic whole plantlets were transplanted into potting soil and grown normally in a growth room. They showed salt tolerance to 300 mM NaCl. The points of our system are using explants with shoot apex as materials, inhibiting the elongation of the apex on the selection medium, and regenerating transgenic buds from the side opposite to the apex. This approach may also solve transformation problems in other important plants. [ABSTRACT FROM AUTHOR]

Background: Post-stroke upper limb (UL) motor improvement is associated with adaptive neuroplasticity and motor learning. Both intervention-related (including provision of intensive, variable, and task-specific practice) and individual-specific factors (including the presence of genetic polymorphisms) influence improvement. In individuals with stroke, most commonly, polymorphisms are found in Brain Derived Neurotrophic Factor (BDNF), Apolipoprotein (APOE) and Catechol-O-Methyltransferase (COMT). These involve a replacement of cystine by arginine (APOEε4) or valines by 1 or 2 methionines (BDNF:val66met, met66met; COMT:val158met; met158met). However, the implications of these polymorphisms on post-stroke UL motor improvement specifically have not yet been elucidated. Objective: Examine the influence of genetic polymorphism on post-stroke UL motor improvement. Design: Systematic Review and Meta-Analysis. Methods: We conducted a systematic search of the literature published in English language. The modified Downs and Black checklist helped assess study quality. We compared change in UL motor impairment and activity scores between individuals with and without the polymorphisms. Meta-analyses helped assess change in motor impairment (Fugl Meyer Assessment) scores based upon a minimum of 2 studies/time point. Effect sizes (ES) were quantified based upon the Rehabilitation Treatment Specification System as follows: small (0.08-0.18), medium (0.19 -0.40) and large (≥0.41). Results: We retrieved 10 (4 good and 6 fair quality) studies. Compared to those with BDNF val66met and met66met polymorphism, meta-analyses revealed lower motor impairment (large ES) in those without the polymorphism at intervention completion (0.5, 95% CI: 0.11-0.88) and at retention (0.58, 95% CI:0.06-1.11). The presence of CoMT val158met or met158met polymorphism had similar results, with lower impairment (large ES ≥1.5) and higher activity scores (large ES ranging from 0.5-0.76) in those without the polymorphism. Presence of APOEε4 form did not influence UL motor improvement. Conclusion: Polymorphisms with the presence of 1 or 2 met alleles in BDNF and COMT negatively influence UL motor improvement. Registration: https://osf.io/wk9cf/. Plain language summary: This research paper focuses on the impact of variations in DNA sequence in certain genes on improvement seen in the arms in people who have had a stroke. In this study, we studied the role of 3 genes previously identified as having variations in DNA sequence. The authors searched published research articles from 2000 onwards and selected articles that satisfied certain criteria. We then checked the quality of the selected papers. Next, we combined common data from same tests used to examine motor improvement in the arms to check if there was an overall effect. A total of 10 papers were found. The selected articles were either good or moderate in quality. Variations in DNA structure in 2 out of the 3 genes studied affected the ability to improve the use of the arms in daily life after a stroke. Such information can have important implications in the extent of recovery that is possible after a stroke. It can also be helpful to decide the best rehabilitation options that can be offered to help maximize their ability to use the arms after a stroke. [ABSTRACT FROM AUTHOR]

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Background: Lung cancer is one of the cancers with the highest mortality rate in China. With the rapid development of high-throughput sequencing technology and the research and application of deep learning methods in recent years, deep neural networks based on gene expression have become a hot research direction in lung cancer diagnosis in recent years, which provide an effective way of early diagnosis for lung cancer. Thus, building a deep neural network model is of great significance for the early diagnosis of lung cancer. However, the main challenges in mining gene expression datasets are the curse of dimensionality and imbalanced data. The existing methods proposed by some researchers can't address the problems of high-dimensionality and imbalanced data, because of the overwhelming number of variables measured (genes) versus the small number of samples, which result in poor performance in early diagnosis for lung cancer. Method: Given the disadvantages of gene expression data sets with small datasets, high-dimensionality and imbalanced data, this paper proposes a gene selection method based on KL divergence, which selects some genes with higher KL divergence as model features. Then build a deep neural network model using Focal Loss as loss function, at the same time, we use k-fold cross validation method to verify and select the best model, we set the value of k is five in this paper. Result: The deep learning model method based on KL divergence gene selection proposed in this paper has an AUC of 0.99 on the validation set. The generalization performance of model is high. Conclusion: The deep neural network model based on KL divergence gene selection proposed in this paper is proved to be an accurate and effective method for lung cancer prediction. [ABSTRACT FROM AUTHOR]

Hence, the Special Issue "Tree Genetics: Molecular and Functional Characterization of Genes" aimed to collect woody species gene-centered studies, with a special emphasis on functions related to trees' tolerance and resilience to global changes. Two research papers investigate the role of specific genes in the response of trees to pathogens: the function of thaumatin-like proteins (TLP), as most of them exhibit antifungal activity, was investigated in [[4]]; four TLP genes were isolated, identified, and characterized, and their role in defense response demonstrated in I Picea likiangensis i . Indeed, six papers focus on broadleaved trees and four on conifers, including economically relevant species for a plethora of different uses, but also rare/endangered species [[3]] and ecologically important trees [[4]]. [Extracted from the article]

Comments on a study on the effect of the deletion of the p53 gene on the reduced cancer and premature aging phenotypes. Factors that contributed to the deletion of the genes; Background on the phenotypic consequences of the haploinsufficiency of genes; Reasons behind the activation of p53.

Simple Summary: A bibliometric analysis was carried out to know the evolution of research on genes associated with meat tenderness, of interest for the development of selection programs. Since 1993, studies have been limited to a few researchers in high-income countries due to the costs associated with the techniques. The main findings showed that the scientific production had a discontinuous growth because science experienced a significant change since approximately 2010. Marker-assisted selection was widely used, evaluating mainly CAPN (calpain) and CAST (calpastatin) genes for their contribution to meat tenderness, especially in cattle. However, the effects are small; therefore, genomic selection was implemented by genotyping thousands of single nucleotide polymorphisms (SNPs) for further explanation of genetic variation. The results shown are important for scholars to identify emerging methodologies and gaps in the literature and to know who the prolific authors and institutions in the field for possible collaborations, etc., are. Tenderness is one of the main characteristics of meat because it determines its price and acceptability. This is the first bibliometric study on the trend of research on the role of genes in meat tenderness. A total of 175 original and English-language articles published up to 2021 were retrieved from Scopus. The bibliometric analysis was carried out with VOSviewer (version 1.6.18, Eck and Waltman, Leiden, Netherlands) and complemented with the Analyze search results service from Scopus. Erroneous and duplicate data were eliminated, and incomplete information was added to standardize the results. Scientific production was evaluated by means of quantity, quality and structure indicators. As a first glance, 8.816% of authors have published more than 50% of papers mainly related to genes encoding the calpain (CAPN)-calpastatin (CAST) system and single nucleotide polymorphisms (SNPs). Among other findings, a strong link was found between the contribution of the main countries (led by the United States with) and their institutions (led by the USDA Agricultural Research Service with) to their gross domestic product. Most studies on the topic are published in the Journal of Animal Science, and other journals with high impact according to the number of citations and different metrics. Finally, when evaluating the most cited articles, the occurrence and association of the main keywords, it was confirmed that research is focused on the role of CAPN and CAST genes and of SNPs in beef tenderness. The change in science was emphasized; although marker-assisted selection is still used, genes have an infinitesimal effect on complex traits. Therefore, since about 2010, new research groups adopted genomic selection to evaluate dense panels of SNPs and better explain genetic variation in meat tenderness. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) and single nucleotide polymorphisms (SNPs) play important roles in disease risk and development, especially cancer. Importantly, when SNPs are located in pre-miRNAs, they affect their splicing mechanism and change the function of miRNAs. To improve disease risk assessment, we propose an approach and developed a software tool, IsomiR_Find, to identify disease/phenotype-related SNPs and isomiRs in individuals. Our approach is based on the individual's samples, with SNP information extracted from the 1000 Genomes Project. SNPs were mapped to pre-miRNAs based on whole-genome coordinates and then SNP-pre-miRNA sequences were constructed. Moreover, we developed matpred2, a software tool to identify the four splicing sites of mature miRNAs. Using matpred2, we identified isomiRs and then verified them by searching within individual miRNA sequencing data. Our approach yielded biomarkers for biological experiments, mined functions of miRNAs and SNPs, improved disease risk assessment, and provided a way to achieve individualized precision medicine. [ABSTRACT FROM AUTHOR]

The article discusses the role played by epigenetics in the field of reproductive medicine. The natural times when developmental epigenetic reprogramming takes place in gametes almost matches the time of human assisted reproduction when the gametes and embryos are handled in an in vitro environemnt. Information is also given on genomic imprinting and in vitro culture of embryos.

To illustrate the results achieved by genes in premature ovarian insufficiency (POI) and collaborations in the field, and to explore key themes and future directions. Articles and reviews related to POI genes published between 1990 and 2022 were retrieved from the Web of Science core collection (WoSCC) for the total bibliometric analysis. Tools were analyzed for publication, country, institution, journal, authors, reference, keywords, subject categories, funding agencies, and research hotspots using a bibliometric online analysis platform, Bibliographic Co-occurrence Matrix Builder (BICOMB), CiteSpace V, and VOSviewer. A total of 2,232 papers were included in this study. Articles were published in 52 countries, with the United States publishing the most, followed by China. A total of 308 institutions contributed to relevant publications. Shandong University published the most papers. Qin Y's team published the most relevant papers. Human reproduction and fertility and sterility are the two journals with the most papers. X-chromosome abnormalities, transcription factor mutations, and FMR1 genes are the directions of more POI, and DNA repair is the keyword of the research frontier in recent years. This study summarizes the relevant literature on POI gene research for the first time and analyzes the current hotspots and future trends in this field. The findings can further reveal the etiology, diagnosis, and treatment of POI, which is beneficial for researchers to grasp the genetic dynamics of POI women. [ABSTRACT FROM AUTHOR]

Yu et al. constructed a weighted four-layer disease-disease similarity network to characterize the associations at different levels between diseases. He et al. proposed an NRLMFMDA (neighborhood regularized logistic matrix factorization method for miRNA-disease association prediction) by integrating miRNA functional similarity, disease semantic similarity, Gaussian interaction profile kernel similarity, and experimental validation of disease-miRNA association. Liu et al. classified muscle-invasive bladder cancer into two conservative subtypes using miRNA, mRNA, and lncRNA expression data; investigated subtype-related biological pathways; and evaluated the subtype classification performance using machine learning methods. [Extracted from the article]

Cluster analysis is a principal approach to discover unknown tumor subtypes. Innovative and effective cluster analysis methods are of great significance for tumor diagnosis and malignant tumor treatment. Existing studies on the cluster analysis of tumor gene data generally have defects in aspects such as unsatisfactory performance in clustering highdimensional and high-noise data, and insufficient accuracy in selecting cluster centers. To overcome these defects, this paper performed cluster analysis on tumor gene data based on an improved Density peaks clustering (DPC) algorithm. At first, this paper elaborated on the composition and storage format of tumor tissue samples used in the experiment, gave the tumor gene expression profile data in the matrix format, and introduced the preprocessing process of gene expression profile data. Then, this paper carried out feature selection of tumor gene expression profile data. At last, this paper innovatively divided the target gene density into two parts of K-nearest neighbor local density and neighborhood density, thereby completing the improvement of conventional DPC algorithm and expanding its application scenarios. Combining with experiment, the clustering results of the algorithm before and after introducing the idea of Approximate Nearest Neighbor (ANN) were given, which had verified the effectiveness of the algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

Background and Aims: Cyanobacteria are considered as favorable source for new pharmaceutical compounds. To date, the majority of bioactive metabolites isolated from cyanobacteria are either polyketides (PKSs) or non-ribosomal peptides. Despite of several worldwide studies on prevalence of PKSs, none of them included the terrestrial cyanobacteria of the Lavasan. Therefore, this study aimed to detectthe PKS genes and correlation of the presence of these genes with antimicrobial compounds synthesis. Materials and Methods: Morphological and molecular identification of the terrestrial strains was performed after culture and purification. Amplification of polyketide synthase and phylogenetic trees were used for phylogenetic analysis. Nucleotide and protein sequences were deposited in GenBank. Lastly, to show the correlation of this gene with antimicrobial compounds synthesis, antibiogram bioassay was used. Results: Phylogentic analysis revealed that most of the identified 16SrRNA genes and PKS domains had more than 90% similarity to their closest matches in the Gen-Bank. In addition, antibiogram assessment showedthe different pattern of inhibition, indicating the involvement of variety antimicrobial substances. Conclusions: According to the results of this sudy, it seems the antibiogram bioassay and molecular detection of polyketide synthase genes are useful techniques for the assessment of productive species of natural products and the possible role of polyketide synthase enzyme complexes in the biosynthesis of biologically active compounds. [ABSTRACT FROM AUTHOR]

This document is a publisher's note regarding an issue with the authorship of a paper titled "Identification and characterization of GRIM-1, a cell-death-associated gene product." The journal received a complaint from Jonathan D'Cunha, who stated that he did not consent to or was contacted about the publication of the paper. The corresponding author, Dhananjaya Kalvakolanu, attempted to contact Dr. D'Cunha regarding authorship but did not receive a response. As a result, Jonathan D'Cunha has been removed as an author of the paper and its subsequent retraction notice. [Extracted from the article]

Profiles of gene expression, which is in cell state present at molecular level, have huge potential medical diagnosis tool. Compared to the various genes conclude, presented training information sets usually have a fairly small sample size in the cancer type classification. These training information limitations constitute a challenge to various classification technologies. A reliable selection technique for genes relevant for sample classification is required in order to the speed up processing rate, decrease predictive error rate, and to avoid incomprehensibility because of genes investigated many number. [ABSTRACT FROM AUTHOR]

This paper suggests studies on genetically engineering nonhuman animal genes have globalized over the last 30 years. The results unveil maps that give a global overview of universities' studies into engineering animal genes, by purpose and by species, at a state scale. A network map also shows how studies on engineering animal genes are co-constituted internationally, at a state scale. Some of the more notable map findings are developed using a novel ontological approach. This ontology relates the being of an animal, a constitutive lack, to power relations. The beings of animals are trapped into serving capital through the engineering of their genes. This reconfiguration allows the ensnaring of the body in agricultural, or other, power relations. The scale of this carceral archipelago is positioned as a global risk. Life energy, by nature, resists capture. Therefore, the paper concludes that the clock is ticking on genetic scientists' Faustian bargain. [ABSTRACT FROM AUTHOR]

Background: With the emergence of Oxford Nanopore technology, now the on-site sequencing of 16S rRNA from environments is available. Due to the error level and structure, the analysis of such data demands some database of reference sequences. However, many taxa from complex and diverse environments, have poor representation in publicly available databases. In this paper, we propose the METASEED pipeline for the reconstruction of full-length 16S sequences from such environments, in order to improve the reference for the subsequent use of on-site sequencing. Results: We show that combining high-precision short-read sequencing of both 16S and full metagenome from the same samples allow us to reconstruct high-quality 16S sequences from the more abundant taxa. A significant novelty is the carefully designed collection of metagenome reads that matches the 16S amplicons, based on a combination of uniqueness and abundance. Compared to alternative approaches this produces superior results. Conclusion: Our pipeline will facilitate numerous studies associated with various unknown microorganisms, thus allowing the comprehension of the diverse environments. The pipeline is a potential tool in generating a full length 16S rRNA gene database for any environment. [ABSTRACT FROM AUTHOR]

Inflammatory bowel disease (IBD) is a complex disease that develops through a sequence of molecular events that are still poorly defined. This process is driven by a multitude of context-dependent genes that play different roles based on their environment. The complexity and multi-faceted nature of these genes make it difficult to study the genetic basis of IBD. The goal of this article is to review the key genes in the pathophysiology of IBD and highlight new technology that can be used in further research. This paper examines Nanostring RNA probe technology, which uses tissue analyzed without the use of enzymes, transcription, or amplification. Nanostring offers several panels of genes to test, including an inflammation panel of 234 genes. This article analyzes this panel and reviews the literature for each gene's effect in IBD for use as a framework to review the pathophysiology of the disease. The panel was narrowed to 26 genes with significant evidence of mechanistic potential in IBD, which were then categorized into specific areas of pathogenesis. These include gut barrier breakdown, inappropriate recognition of commensal bacteria, immune cell activation, proinflammatory cytokine release, and subsequent impairment of the anti-inflammatory response. The eventual goal of this paper is the creation of a customized panel of IBD genes that can be used to better understand the genetic mechanism of IBD and aid in the development of future therapies in IBD. [ABSTRACT FROM AUTHOR]

Phylogenetic inference of polyploid species is the first step towards understanding their patterns of diversification. In this paper, we review the challenges and limitations of inferring species relationships of polyploid plants using traditional phylogenetic sequencing approaches, as well as the mischaracterization of the species tree from single or multiple gene trees. We provide a roadmap to infer interspecific relationships among polyploid lineages by comparing and evaluating the application of current phylogenetic, phylogenomic, transcriptomic, and whole‐genome approaches using different sequencing platforms. For polyploid species tree reconstruction, we assess the following criteria: (1) the amount of prior information or tools required to capture the genetic region(s) of interest; (2) the probability of recovering homeologs for polyploid species; and (3) the time efficiency of downstream data analysis. Moreover, we discuss bioinformatic pipelines that can reconstruct networks of polyploid species relationships. In summary, although current phylogenomic approaches have improved our understanding of reticulate species relationships in polyploid‐rich genera, the difficulties of recovering reliable orthologous genes and sorting all homeologous copies for allopolyploids remain a challenge. In the future, assembled long‐read sequencing data will assist the recovery and identification of multiple gene copies, which can be particularly useful for reconstructing the multiple independent origins of polyploids. [ABSTRACT FROM AUTHOR]

Soursop (Annona muricata L.) is a tropical fruit highly valued for its unique flavor, nutritional value, and health-promoting properties. The ripening process of soursop involves complex changes in gene expression and metabolite accumulation, which have been studied using various omics technologies. Transcriptome analysis has provided insights into the regulation of key genes involved in ripening, while metabolic compound analysis has revealed the presence of numerous bioactive compounds with potential health benefits. However, the integration of transcriptome and metabolite compound data has not been extensively explored in soursop. Therefore, in this paper, we present a comprehensive analysis of the transcriptome and phenolic compound profiles of soursop during ripening. The integration analysis showed that the genes and phenolic compounds were mainly involved in the starch and sucrose metabolism pathways during soursop ripening. Further, the phenolic compounds Kaempferol 3-Q-galactoside, Procyanidin C1, Procyanidin trimmer C1, and m-Coumaric, as well as the genes Ubiquitin-like protein 5 (UBL5_ARATH), ATP-dependent zinc metalloprotease FTSH8 (FTSH8_ORYSJ), Zinc transporter 4 (ZIP4_ARATH), Thioredoxin-like 3-1 (TRL31_ORYSJ), Mitogen-activated protein kinase YODA (YODA_ARATH), R-mandelonitrile lyase-like (MGL_ARATH), 26s protease regulatory subunit 6A homolog (PRS6_SOLLC), Cytochrome P450 72A13 (C7A13ARATH), Cytochrome P450 84A1 (C84A1_ARATH) and Homoserine O-trans-acetylase (MET2-ORYSJ) were correlated and differentially accumulated and expressed, respectively. Our study provides new insights into the molecular mechanisms underlying soursop ripening and may contribute to the development of strategies for improving the nutritional quality and shelf life of this important fruit. [ABSTRACT FROM AUTHOR]