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The article announces the winners of Development's Outstanding Paper Prize for papers published in 2023. The winning papers focus on developmental and stem cell biology. One paper demonstrates the potential of genome engineering techniques and pharmacological upregulation of the Wnt signaling pathway in treating frizzled 2-associated congenital malformations in mouse models. Another paper explores how Frizzled2 receives WntA signaling during butterfly wing pattern formation, providing insights into the complexity and evolution of signaling pathways. The article also mentions a study on the development of primordial germ cell-like cells using stem cell technologies. Additionally, the article discusses a study on the molecular functioning of WntA in butterfly wing color patterning, which involved collaboration between international teams and faced challenges in rearing and injecting butterflies in the lab. The researchers plan to further investigate butterfly color patterns. [Extracted from the article]

The paper mulberry is a commonly found tree species with a long history of cultivation. It also serves as a crucial case study for understanding how woody plants adapt to low temperatures. Under cold treatment, we observed a substantial number of alternative splicing (AS) genes, showcasing the intricate landscape of AS events. We have detected all seven types of AS events, with the alternative 3′ splice site (A3) having the most. We observed that many genes that underwent differential AS were significantly enriched in starch and sucrose metabolism and circadian rhythm pathways. Moreover, a considerable proportion of differentially spliced genes (DSGs) also showed differential expression, with 20.38% and 25.65% under 12 h and 24 h cold treatments, respectively. This suggests a coordinated regulation between gene AS and expression, playing a pivotal role in the paper mulberry's adaptation to cold stress. We further investigated the regulatory mechanisms of AS, identifying 41 serine/arginine-rich (SR) splicing factors, among which 11 showed differential expression under cold treatment, while 29 underwent alternative splicing. Additionally, genes undergoing AS displayed significantly higher DNA methylation levels under cold stress, while normal splicing (non-AS) genes exhibited relatively lower methylation levels. These findings suggest that methylation may play an important role in governing gene AS. Finally, our research will provide useful information on the role of AS in the cold acclimation tolerance of the paper mulberry. [ABSTRACT FROM AUTHOR]

This article features an interview with Jingjing Sun and Angelike Stathopoulos, who conducted a study on the collective migration of caudal visceral mesoderm (CVM) cells in Drosophila embryos. They discovered that cell division coordinates two gene expression programs in migrating CVM cells. The researchers discuss their scientific backgrounds and the questions they are trying to answer in their lab. They also highlight the importance of the Drosophila system for their research. The study's key findings include the identification of two groups of genes that regulate the behaviors of CVM cells during migration, and the role of cell division in controlling gene expression programs. The researchers also discuss their motivations and future directions for their research. [Extracted from the article]

A high mortality rate was found in cancer patients with distant metastasis. Development of targeted drugs for effectively inhibiting cancer metastasis is the key for increasing therapeutic success. In the current study, a folding paper system was developed to mimic a tumor–vascular interface for the study of long-distance cell migration. Correlation between the cell migration distance and metastasis-associated gene was successfully analyzed by disassembling the stacked paper construct. The result revealed that the migration distance and number of migrated cells were highly correlated to cell characteristics. Moreover, immunocytochemistry was directly conducted on the paper layer to study the signaling pathway. Kelch-like and protein tyrosine phosphatase families were examined and the PTPN13 gene was shown to regulate long-distance cell migration. By analyzing the phosphorylated mTOR, the PTPN13 gene was further confirmed to be a tumor suppressor gene that inhibits long-distance cell migration. The folding paper system provides an alternative approach for long-distance cell migration. Metastasis-associated gene expression can be analyzed to potentially develop targeted drugs for cancer metastasis inhibition. [ABSTRACT FROM AUTHOR]

Background: The accelerating pace of biomedical publication has made it impractical to manually, systematically identify papers containing specific information and extract this information. This is especially challenging when the information itself resides beyond titles or abstracts. For emerging science, with a limited set of known papers of interest and an incomplete information model, this is of pressing concern. A timely example in retrospect is the identification of immune signatures (coherent sets of biomarkers) driving differential SARS-CoV-2 infection outcomes. Implementation: We built a classifier to identify papers containing domain-specific information from the document embeddings of the title and abstract. To train this classifier with limited data, we developed an iterative process leveraging pre-trained SPECTER document embeddings, SVM classifiers and web-enabled expert review to iteratively augment the training set. This training set was then used to create a classifier to identify papers containing domain-specific information. Finally, information was extracted from these papers through a semi-automated system that directly solicited the paper authors to respond via a web-based form. Results: We demonstrate a classifier that retrieves papers with human COVID-19 immune signatures with a positive predictive value of 86%. The type of immune signature (e.g., gene expression vs. other types of profiling) was also identified with a positive predictive value of 74%. Semi-automated queries to the corresponding authors of these publications requesting signature information achieved a 31% response rate. Conclusions: Our results demonstrate the efficacy of using a SVM classifier with document embeddings of the title and abstract, to retrieve papers with domain-specific information, even when that information is rarely present in the abstract. Targeted author engagement based on classifier predictions offers a promising pathway to build a semi-structured representation of such information. Through this approach, partially automated literature mining can help rapidly create semi-structured knowledge repositories for automatic analysis of emerging health threats. [ABSTRACT FROM AUTHOR]

Background: Spinal cord injury (SCI) is a nervous system disease leading to motor and sensory dysfunction below the injury level, and can result in paralysis. MicroRNAs (miRNAs) play a key role in SCI treatment, and related research provides insights for SCI diagnosis and treatment. Bibliometrics is an important tool for literature statistics and evaluation, objectively summarizing multidimensional information. This study comprehensively overviews the field through bibliometric analysis of miRNA and SCI research, providing contemporary resources for future collaboration and clinical treatment. Materials and methods: In this study, we searched the Web of Science Core Collection (WOSCC) database. After careful screening and data import, we extracted annual publications, citation counts, countries, institutions, authors, journals, highly cited articles, co-cited articles, keywords, and H-index. Bibliometrics and visualization analyses employed VOSviewer, CiteSpace, the R package "bibliometrix," and online analytic platforms. Using Arrowsmith, 1 we determined miRNA-SCI relationships and discussed potential miRNA mechanisms in SCI. Results: From 2008 to 2024, the number of related papers increased annually, reaching 754. The number of yearly publications remained high and entered a period of rapid development. Researchers from 50 countries/regions, 802 institutions, 278 journals, and 3,867 authors participated in the field. Currently, China has advantages in the number of national papers, citations, institutions, and authors. However, it is necessary to strengthen cooperation among different authors, institutions, and countries to promote the production of important academic achievements. The research in the field currently focuses on nerve injury, apoptosis, and gene expression. Future research directions mainly involve molecular mechanisms, clinical trials, exosomes, and inflammatory reactions. Conclusion: Overall, this study comprehensively analyzes the research status and frontier of miRNAs in SCI. A systematic summary provides a complete and intuitive understanding of the relationship between SCI and miRNAs. The presented findings establish a basis for future research and clinical application in this field. [ABSTRACT FROM AUTHOR]

This article is an interview with Charlotte Manser and Ruben Perez-Carrasco, discussing their recent paper on the molecular basis of developmental timing. The authors developed a mathematical framework to explore the tempo of development and identify molecular mechanisms that regulate it. They studied gene expression orbits and used mathematical methods to define function and tempo in a quantitative way. The paper aims to reach experimentalists in the developmental biology community and is published in the journal Development. Manser and Perez-Carrasco plan to continue exploring the role of tempo in different developmental systems and are excited about potential applications in synthetic biology and immunology. Outside of their research, they enjoy playing Dungeons & Dragons and have a shared love for music. [Extracted from the article]

Understanding biological mechanisms is fundamental for improving animal production and health to meet the growing demand for high-quality protein. As an emerging biotechnology, single-cell transcriptomics has been gradually applied in diverse aspects of animal research, offering an effective method to study the gene expression of high-throughput single cells of different tissues/organs in animals. In an unprecedented manner, researchers have identified cell types/subtypes and their marker genes, inferred cellular fate trajectories, and revealed cell‒cell interactions in animals using single-cell transcriptomics. In this paper, we introduce the development of single-cell technology and review the processes, advancements, and applications of single-cell transcriptomics in animal research. We summarize recent efforts using single-cell transcriptomics to obtain a more profound understanding of animal nutrition and health, reproductive performance, genetics, and disease models in different livestock species. Moreover, the practical experience accumulated based on a large number of cases is highlighted to provide a reference for determining key factors (e.g., sample size, cell clustering, and cell type annotation) in single-cell transcriptomics analysis. We also discuss the limitations and outlook of single-cell transcriptomics in the current stage. This paper describes the comprehensive progress of single-cell transcriptomics in animal research, offering novel insights and sustainable advancements in agricultural productivity and animal health. [ABSTRACT FROM AUTHOR]

Background: Medulloblastoma is one of the common primary central nervous system (CNS) malignancies in pediatric patients. The main treatment is surgical resection preceded and/or followed by chemoradiotherapy. However, their serious side effects necessitate a better understanding of medulloblastoma biology to develop novel therapeutic options. Main body: Circular RNA (circRNA) and long non-coding RNA (lncRNA) regulate gene expression via microRNA (miRNA) pathways. Although growing evidence has highlighted the significance of circRNA and lncRNA-associated competing endogenous RNA (ceRNA) networks in cancers, no study has comprehensively investigated them in medulloblastoma. For this aim, the Web of Science, PubMed, Scopus, and Embase were systematically searched to obtain the relevant papers published before 16 September 2023, adhering to the PRISMA-ScR statement. HOTAIR, NEAT1, linc-NeD125, HHIP-AS1, CRNDE, and TP73-AS1 are the oncogenic lncRNAs, and Nkx2-2as is a tumor-suppressive lncRNA that develop lncRNA-associated ceRNA networks in medulloblastoma. CircSKA3 and circRNA_103128 are upregulated oncogenic circRNAs that develop circRNA-associated ceRNA networks in medulloblastoma. Conclusion: In summary, this study has provided an overview of the existing evidence on circRNA and lncRNA-associated ceRNA networks and their impact on miRNA and mRNA expression involved in various signaling pathways of medulloblastoma. Suppressing the oncogenic ceRNA networks and augmenting tumor-suppressive ceRNA networks can provide ample opportunities for medulloblastoma treatment. [ABSTRACT FROM AUTHOR]

Cancer is one of the leading causes of deaths worldwide. Survival analysis and prediction of cancer patients is of great significance for their precision medicine. The robustness and interpretability of the survival prediction models are important, where robustness tells whether a model has learned the knowledge, and interpretability means if a model can show human what it has learned. In this paper, we propose a robust and interpretable model SurvConvMixer, which uses pathways customized gene expression images and ConvMixer for cancer short-term, mid-term and long-term overall survival prediction. With ConvMixer, the representation of each pathway can be learned respectively. We show the robustness of our model by testing the trained model on absolutely untrained external datasets. The interpretability of SurvConvMixer depends on gradient-weighted class activation mapping (Grad-Cam), by which we can obtain the pathway-level activation heat map. Then wilcoxon rank-sum tests are conducted to obtain the statistically significant pathways, thereby revealing which pathways the model focuses on more. SurvConvMixer achieves remarkable performance on the short-term, mid-term and long-term overall survival of lung adenocarcinoma, lung squamous cell carcinoma and skin cutaneous melanoma, and the external validation tests show that SurvConvMixer can generalize to external datasets so that it is robust. Finally, we investigate the activation maps generated by Grad-Cam, after wilcoxon rank-sum test and Kaplan–Meier estimation, we find that some survival-related pathways play important role in SurvConvMixer. [ABSTRACT FROM AUTHOR]

Increasing cellulase production in cellulolytic fungus Trichoderma reesei is of interest for biofuels and biorefineries. Previous studies indicated that secreted protein was occasionally accumulated in vacuoles; this phenomenon has also been reported in T. reesei. Therefore, alleviating vacuolar transport seems to be a promising strategy for improving cellulase production in T. reesei. Herein, we found that knockout of vps10, vps13, and vps21, among 11 vacuolar protein sorting factors, improved cellulase production in T. reesei. The filter paper activity in Δvps10, Δvps13, and Δvps21 increased by 1.28-, 2.45-, and 2.11-fold than that of the parent strain. Moreover, the β-glucosidase activity in Δvps13 and Δvps21 increased by 3.22- and 3.56-fold after 6 days of fermentation. Furthermore, we also found that the vacuolar trafficking towards vacuoles was partially impaired in three knockout mutants, and disruption of vps13 alleviated the autophagy process. These results indicated that alleviated transport and degradation towards vacuole in Δvps10, Δvps13, and Δvps21 might improve cellulase production. Of note, the expression of cellulase genes in Δvps13 and Δvps21 was dramatically increased in the late induction phase compared to the parent. These results suggested that Vps13 and Vps21 might influence the cellulase production at transcription level. And further transcriptome analysis indicated that increased cellulase gene expression might be attributed to the differential expression of sugar transporters. Our study unravels the effect of alleviating vacuolar transport through knockout vps10, vps13, and vps21 for efficient cellulase secretion, providing new clues for higher cellulase production in T. reesei. Key points: • Disruption of vps10, vps13 or vps21 improves cellulase production • Vacuolar transport is impaired in three vps KO mutants • Deletion of vps13 or vps21 increases the transcript of cellulase genes in late stage [ABSTRACT FROM AUTHOR]

Invasive paper wasps such as Polistes dominula are a major pest and problem for biodiversity around the globe. Safe and highly targeted methods for the control of these and other social wasp populations are needed. We attempted to identify potentially-lethal gene targets that could be used on adult paper wasps in a gene silencing or RNA interference (RNAi) approach. Double-stranded RNA (dsRNA) was designed to target genes for which silencing has proven lethal in other insects. dsRNA was provided either orally to foragers or directly injected into the wasps. We also provided the dsRNA unprotected or protected from degradation by gut nucleases in two different forms (lipofectamine and carbon quantum dots). The effects of oral delivery of 22 different gene targets to forager wasps was evaluated. The expression of five different genes was successfully reduced following dsRNA ingestion or injection. These gene targets included the FACT complex subunit spt16 (DRE4) and RNA-binding protein fusilli (FUSILLI), both of which have been previously shown to have potential as lethal targets for pest control in other insects. However, we found no evidence of significant increases in adult wasp mortality following ingestion or injection of dsRNA for these genes when compared with control treatments in our experiments. The methods we used to protect the dsRNA from digestive degradation altered gene expression but similarly did not influence wasp mortality. Our results indicate that while many of the same gene targets can be silenced and induce mortality in other insects, dsRNA and RNAi approaches may not be useful for paper wasp control. [ABSTRACT FROM AUTHOR]

Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of origin of a sample and discovering marker genes. Existing studies typically identify marker genes by statistically comparing healthy and cancer samples. However, this approach overlooks marker genes with low expression level differences and may be influenced by experimental results. This paper introduces "GENESO," a novel framework for pan-cancer classification and marker gene discovery using the occlusion method in conjunction with deep learning. we first trained a baseline deep LSTM neural network capable of distinguishing the origins and statuses of samples utilizing RNA-Seq data. Then, we propose a novel marker gene discovery method called "Symmetrical Occlusion (SO)". It collaborates with the baseline LSTM network, mimicking the "gain of function" and "loss of function" of genes to evaluate their importance in pan-cancer classification quantitatively. By identifying the genes of utmost importance, we then isolate them to train new neural networks, resulting in higher-performance LSTM models that utilize only a reduced set of highly relevant genes. The baseline neural network achieves an impressive validation accuracy of 96.59% in pan-cancer classification. With the help of SO, the accuracy of the second network reaches 98.30%, while using 67% fewer genes. Notably, our method excels in identifying marker genes that are not differentially expressed. Moreover, we assessed the feasibility of our method using single-cell RNA-Seq data, employing known marker genes as a validation test. [ABSTRACT FROM AUTHOR]

Hundreds of microbiota gene expressions are significantly different between healthy and diseased humans. The "bottleneck" preventing a mechanistic dissection of how they affect host biology/disease is that many genes are encoded by nonmodel gut commensals and not genetically manipulatable. Approaches to efficiently identify their gene transfer methodologies and build their gene manipulation tools would enable mechanistic dissections of their impact on host physiology. This paper will introduce a step‐by‐step protocol to identify gene transfer conditions and build the gene manipulation tools for nonmodel gut microbes, focusing on Gram‐negative Bacteroidia and Gram‐positive Clostridia organisms. This protocol enables us to identify gene transfer methods and develop gene manipulation tools without prior knowledge of their genome sequences, by targeting bacterial 16s ribosomal RNAs or expanding their compatible replication origins combined with clustered regularly interspaced short palindromic repeats machinery. Such an efficient and generalizable approach will facilitate functional studies that causally connect gut microbiota genes to host diseases. Highlights: A protocol introducing a step‐by‐step genetic manipulation method would facilitate the investigation of those functional genes encoded by nonmodel gut commensals.The gene‐editing tools could be established in nonmodel gut Bacteroidia and Clostridia without prior knowledge of their genome information.The genetic manipulation pipeline may serve as a high‐throughput genetics screening and manipulating platform for human gut microbes. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are small, non-coding RNAs that play a crucial role in regulating gene expression. Dysfunction in miRNAs can lead to various diseases, including cancers, neurological disorders, and cardiovascular conditions. To date, approximately 2000 miRNAs have been identified in humans. These small molecules have shown promise as disease biomarkers and potential therapeutic targets. Therefore, identifying miRNA biomarkers for diseases and developing effective miRNA drug delivery systems are essential. Nanotechnology offers promising new approaches to addressing scientific and medical challenges. Traditional miRNA detection methods include next-generation sequencing, microarrays, Northern blotting, and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Nanotechnology can serve as an effective alternative to Northern blotting and RT-qPCR for miRNA detection. Moreover, nanomaterials exhibit unique properties that differ from larger counterparts, enabling miRNA therapeutics to more effectively enter target cells, reduce degradation in the bloodstream, and be released in specific tissues or cells. This paper reviews the application of nanotechnology in miRNA detection and drug delivery systems. Given that miRNA therapeutics are still in the developing stages, nanotechnology holds great promise for accelerating miRNA therapeutics development. [ABSTRACT FROM AUTHOR]

Methylation represents a crucial class of modification that orchestrates a spectrum of regulatory roles in plants, impacting ornamental characteristics, growth, development, and responses to abiotic stress. The establishment and maintenance of methylation involve the coordinated actions of multiple regulatory factors. Methyltransferases play a pivotal role by specifically recognizing and methylating targeted sites, which induces alterations in chromatin structure and gene expression, subsequently influencing the release of volatile aromatic substances and the accumulation of pigments in plant petals. In this paper, we review the regulatory mechanisms of methylation modification reactions and their effects on the changes in aromatic substances and pigments in plant petals. We also explore the potential of methylation modifications to unravel the regulatory mechanisms underlying aroma and color in plant petals. This aims to further elucidate the synthesis, metabolism, and regulatory mechanisms of various methylation modifications related to the aroma and color substances in plant petals, thereby providing a theoretical reference for improving the aroma and color of plant petals. [ABSTRACT FROM AUTHOR]

As part of the field of DNA methylation identification, this study tackles the challenge of enhancing recognition performance by introducing a specialized deep learning framework called DeepPGD. DNA methylation, a crucial biological modification, plays a vital role in gene expression analyses, cellular differentiation, and the study of disease progression. However, accurately and efficiently identifying DNA methylation sites remains a pivotal concern in the field of bioinformatics. The issue addressed in this paper is the presence of methylation in DNA, which is a binary classification problem. To address this, our research aimed to develop a deep learning algorithm capable of more precisely identifying these sites. The DeepPGD framework combined a dual residual structure involving Temporal convolutional networks (TCNs) and bidirectional long short-term memory (BiLSTM) networks to effectively extract intricate DNA structural and sequence features. Additionally, to meet the practical requirements of DNA methylation identification, extensive experiments were conducted across a variety of biological species. The experimental results highlighted DeepPGD's exceptional performance across multiple evaluation metrics, including accuracy, Matthews' correlation coefficient (MCC), and the area under the curve (AUC). In comparison to other algorithms in the same domain, DeepPGD demonstrated superior classification and predictive capabilities across various biological species datasets. This significant advancement in algorithmic prowess not only offers substantial technical support, but also holds potential for research and practical implementation within the DNA methylation identification domain. Moreover, the DeepPGD framework shows potential for application in genomics research, biomedicine, and disease diagnostics, among other fields. [ABSTRACT FROM AUTHOR]

Transcriptome-wide association studies (TWAS) goal is to better understand the etiology of diseases and develop preventative and therapeutic approaches by examining the connections between genetic variants and phenotypes while overcoming the limitations of the genome-wide association study (GWAS). It is a valuable complement to GWAS, reducing the negative effects of multiple tests and enabling a more thorough investigation of gene expression patterns in various tissues. A systematic review is presented in this paper to identify articles that utilize TWAS to understand the genetic factors behind complex diseases. A detailed selection process was carried out using standard PRISMA criteria to select relevant articles for the review. Twenty-five articles passed the inclusion criteria and were selected for additional review. The studies cover a diverse range of disorders, including Tourette's syndrome, Alzheimer's disease, rheumatoid arthritis, and major depression. Leveraging gene expression data from different tissues and populations, these investigations successfully identified novel genes and pathways associated with the studied conditions. The collective findings highlight the transformative impact of integrative genomics in advancing our understanding of complex diseases, providing insights into potential therapeutic targets, and laying the foundation for precision medicine approaches. [ABSTRACT FROM AUTHOR]

Background: Excessive inflammation is a major cause of implant failure. The surface morphology, hydrophilicity, and loading of biomaterials are major properties modulating anti-inflammatory macrophage activation. This paper investigates the regulatory effects of modifying the surface of Titanium dioxide nanotubes (TNTs) with graphene oxide (GO) on the polarization of mouse monocyte macrophages (RAW264.7). Methods: TNT was produced by the anodic oxidation of titanium. GO was subsequently electrodeposited on the TNT to obtain a TNT–GO composite. The samples were characterised through scanning electron microscopy (SEM), Raman spectroscopy, and X-ray diffraction. RAW264.7 cells were separately seeded onto the surface of three groups of samples: pure Ti, TNT, and TNT–GO. Under the condition of lipopolysaccharide stimulation, the influence of the sample surfaces on the gene expression profiles was investigated through RNA sequence analysis. In addition, cell spreading was observed through SEM, cell adhesion and proliferation were analysed using the CCK8 assay, and the expression of inflammation-related factors was investigated by ELISA and cellular immunofluorescence staining. The production of reactive oxygen species (ROS) in the RAW264.7 cells on the surface of the three groups was detected via immunofluorescence staining. Results: The CCK8 results indicated that the adhesion and proliferation of the RAW264.7 cells were reduced on the TNT and TNT–GO surfaces. ELISA results revealed significant differences in the pro-inflammatory factors tumour necrosis factor-α and interleukin-6 secretion among the three groups at 24 h (p < 0.05). The secretion of pro-inflammatory factors significantly reduced and the expression of anti-inflammatory factor IL-10 increased on the TNT and TNT–GO surfaces. The RNA sequencing, ELISA, and cell immunofluorescence staining test results suggested that the inflammatory response of M1 polarization was reduced and the M2 polarization of macrophages was induced on the TNT–GO surface, which may be attributed to the reduction in ROS production. Conclusions: Under lipopolysaccharide stimulation, the inflammatory response of the RAW264.7 cells was reduced and the M2 polarization of macrophages was promoted on the TNT–GO surface, which may be caused by the reduced ROS production. Consequently, the designed TNT–GO material is promising for implants owing to its excellent inflammation regulation ability. [ABSTRACT FROM AUTHOR]

Simple Summary: The journey of discovering melanoma—the most dangerous type of skin cancer—biomarkers is never-ending. Under that assumption, this study attempts to partially fill a gap in that journey by identifying melanoma-related biomarkers. This research paper studied the genetic and molecular profiling of melanoma. A transcriptome-wide association study (TWAS) was conducted to reveal the significant biomarkers associated with melanoma. A molecular network was constructed to represent the significant interactions between genes and microRNAs (miRNAs). The related biological processes, the enriched pathways, and the associated diseases were identified. The hotspot biomarkers were discovered to elucidate further the mechanism of these genes and miRNAs in melanoma pathogenesis. This work reveals the pathogenesis and biologically important molecular interactions of melanoma and provides new insights into the molecular mechanisms of melanoma. A transcriptome-wide association study (TWAS) was conducted on genome-wide association study (GWAS) summary statistics of malignant melanoma of skin (UK Biobank dataset) and The Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM) gene expression weights to identify melanoma susceptibility genes. The GWAS included 2465 cases and 449,799 controls, while the gene expression testing was conducted on 103 cases. Afterward, a gene enrichment analysis was applied to identify significant TWAS associations. The melanoma's gene–microRNA (miRNA) regulatory network was constructed from the TWAS genes and their corresponding miRNAs. At last, a disease enrichment analysis was conducted on the corresponding miRNAs. The TWAS detected 27 genes associated with melanoma with p-values less than 0.05 (the top three genes are LOC389458 (RBAK), C16orf73 (MEIOB), and EIF3CL). After the joint/conditional test, one gene (AMIGO1) was dropped, resulting in 26 significant genes. The Gene Ontology (GO) biological process associated the extended gene set (76 genes) with protein K11-linked ubiquitination and regulation of cell cycle phase transition. K11-linked ubiquitin chains regulate cell division. Interestingly, the extended gene set was related to different skin cancer subtypes. Moreover, the enriched pathways were nsp1 from SARS-CoV-2 that inhibit translation initiation in the host cell, cell cycle, translation factors, and DNA repair pathways full network. The gene-miRNA regulatory network identified 10 hotspot genes with the top three: TP53, BRCA1, and MDM2; and four hotspot miRNAs: mir-16, mir-15a, mir-125b, and mir-146a. Melanoma was among the top ten diseases associated with the corresponding (106) miRNAs. Our results shed light on melanoma pathogenesis and biologically significant molecular interactions. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper reviews the role of ENO2, a protein involved in sugar metabolism, in advanced prostate cancer. Analysing five studies, we found that ENO2 levels tend to be higher in aggressive forms of prostate cancer, particularly those that have spread or become resistant to hormone therapy. This increased presence might be linked to how prostate cancer cells change their energy production as the disease progresses, shifting to rely more on sugar breakdown in advanced stages. The study also suggests that ENO2 can be influenced by the tumour's environment, such as low hormone levels or the presence of bone cells, which is relevant, as prostate cancer often spreads to bones. While not proving a direct causal relationship, the research indicates that ENO2 could be an important marker for aggressive disease and potentially a target for future treatments, warranting further investigation into its role in prostate cancer progression, especially in bone metastasis. Prostate cancer (PCa) is the second leading cause of male cancer deaths in the UK and the fifth worldwide. The presence of distant PCa metastasis can reduce the 5-year survival rate from 100% to approximately 30%. Enolase 2 (ENO2), a crucial glycolytic enzyme in cancer metabolism, is associated with the metastasis of multiple cancers and is also used as a marker for neuroendocrine tumours. However, its role in PCa metastasis remains unclear. In this study, we systematically reviewed the current literature to determine the association between ENO2 and metastatic PCa. Medline, Web of Science, and PubMed were searched for eligible studies. The search yielded five studies assessing ENO2 expression in PCa patients or cell lines. The three human studies suggested that ENO2 expression is correlated with late-stage, aggressive PCa, including castrate-resistant PCa (CRPC), metastatic CRPC, and neuroendocrine PCa (NEPC). This was further supported by two in vitro studies indicating that ENO2 expression can be regulated by the tumour microenvironment, such as androgen deprived conditions and the presence of bone-forming osteoblasts. Therefore, ENO2 may functionally contribute to PCa metastasis, possibly due to the unique metabolic features of PCa, which are glycolysis dependent only at the advanced metastatic stage. [ABSTRACT FROM AUTHOR]

The epigenetic machinery has received extensive attention due to its involvement in plant growth, development, and adaptation to environmental changes. Recent studies often highlight the epigenetic regulatory network by discussing various epigenetic mutants across various plant species. However, a systemic understanding of essential epigenetic regulatory mechanisms remains limited due to a lack of representative mutants involved in multiple biological processes. Colorless Non-ripening (Cnr), a spontaneous epimutant isolated from a commercial population, was initially characterized for its role in fruit ripening regulation. Cnr fruits exhibit an immature phenotype with yellow skin, attributed to hypermethylation of the SQUAMOSA PROMOTER BINDING PROTEIN-LIKECNR (SlSPL-CNR) promoter, resulting in the repression of gene expression. In addition to DNA methylation, this process also involves histone modification and microRNA, integrating multiple epigenetic regulatory factors. Interestingly, knockout mutants of SlSPL-CNR display phenotypical distinctions from Cnr in fruit ripening, indicating complex genetic and epigenetic control over the nonripening phenotype in Cnr fruits. Accumulating evidence suggests that Cnr epimutation is pleiotropic, participating in various biological processes such as Cd stress, Fe deficiency, vivipary, and cell death. Therefore, the Cnr epimutant serve as an excellent model for unveiling how epigenetic mechanisms are involved in diverse biological processes. This review paper focuses on recent research advances regarding the Cnr epimutant, delving into its complex genetic and epigenetic regulatory mechanisms, with the aim of enhancing our understanding and facilitating the development of high-quality, high-yield crops through epigenetic modification. [ABSTRACT FROM AUTHOR]

Boolean networks are largely employed to model the qualitative dynamics of cell fate processes by describing the change of binary activation states of genes and transcription factors with time. Being able to bridge such qualitative states with quantitative measurements of gene expressions in cells, as scRNA-seq, is a cornerstone for data-driven model construction and validation. On one hand, scRNA-seq binarisation is a key step for inferring and validating Boolean models. On the other hand, the generation of synthetic scRNA-seq data from baseline Boolean models provides an important asset to benchmark inference methods. However, linking characteristics of scRNA-seq datasets, including dropout events, with Boolean states is a challenging task. We present scBoolSeq, a method for the bidirectional linking of scRNA-seq data and Boolean activation state of genes. Given a reference scRNA-seq dataset, scBoolSeq computes statistical criteria to classify the empirical gene pseudocount distributions as either unimodal, bimodal, or zero-inflated, and fit a probabilistic model of dropouts, with gene-dependent parameters. From these learnt distributions, scBoolSeq can perform both binarisation of scRNA-seq datasets, and generate synthetic scRNA-seq datasets from Boolean traces, as issued from Boolean networks, using biased sampling and dropout simulation. We present a case study demonstrating the application of scBoolSeq's binarisation scheme in data-driven model inference. Furthermore, we compare synthetic scRNA-seq data generated by scBoolSeq with BoolODE's, data for the same Boolean Network model. The comparison shows that our method better reproduces the statistics of real scRNA-seq datasets, such as the mean-variance and mean-dropout relationships while exhibiting clearly defined trajectories in two-dimensional projections of the data. Author summary: The qualitative and logical modelling of cell dynamics has brought precious insight into gene regulatory mechanisms that drive cellular differentiation and fate decisions by predicting cellular trajectories and mutations for their control. However, the design and validation of these models is impeded by the quantitative nature of experimental measurements of cellular states. In this paper, we provide and assess a new methodology, scBoolSeq for bridging single-cell level pseudocounts of RNA transcripts with Boolean classification of gene activity levels. Our method, implemented as a Python package, enables both to binarise scRNA-seq data in order to match quantitative measurements with states of logical models, and to generate synthetic data from Boolean traces to benchmark inference methods. We show that scBoolSeq accurately captures the main statistical features of scRNA-seq data, including measurement dropouts, improving significantly the state of the art. Overall, scBoolSeq brings a statistically-grounded method for enabling the inference and validation of qualitative models from scRNA-seq data. [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]

Summary Computational cell-type deconvolution is an important analytic technique for modeling the compositional heterogeneity of bulk gene expression data. A conceptually new Bayesian approach to this problem, BayesPrism, has recently been proposed and has subsequently been shown to be superior in accuracy and robustness against model misspecifications by independent studies; however, given that BayesPrism relies on Gibbs sampling, it is orders of magnitude more computationally expensive than standard approaches. Here, we introduce the InstaPrism package which re-implements BayesPrism in a derandomized framework by replacing the time-consuming Gibbs sampling step with a fixed-point algorithm. We demonstrate that the new algorithm is effectively equivalent to BayesPrism while providing a considerable speed and memory advantage. Furthermore, the InstaPrism package is equipped with a precompiled, curated set of references tailored for a variety of cancer types, streamlining the deconvolution process. Availability and implementation The package InstaPrism is freely available at: https://github.com/humengying0907/InstaPrism. The source code and evaluation pipeline used in this paper can be found at: https://github.com/humengying0907/InstaPrismSourceCode. [ABSTRACT FROM AUTHOR]

Motivation Gene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, GSE analysis can be performed on fine-grained gene expression data to gain a nuanced understanding of phenotypes of interest. However, with the cellular heterogeneity in single-cell gene profiles, current statistical GSE analysis methods sometimes fail to identify enriched gene sets. Meanwhile, deep learning has gained traction in applications like clustering and trajectory inference in single-cell studies due to its prowess in capturing complex data patterns. However, its use in GSE analysis remains limited, due to interpretability challenges. Results In this paper, we present DeepGSEA, an explainable deep gene set enrichment analysis approach which leverages the expressiveness of interpretable, prototype-based neural networks to provide an in-depth analysis of GSE. DeepGSEA learns the ability to capture GSE information through our designed classification tasks, and significance tests can be performed on each gene set, enabling the identification of enriched sets. The underlying distribution of a gene set learned by DeepGSEA can be explicitly visualized using the encoded cell and cellular prototype embeddings. We demonstrate the performance of DeepGSEA over commonly used GSE analysis methods by examining their sensitivity and specificity with four simulation studies. In addition, we test our model on three real scRNA-seq datasets and illustrate the interpretability of DeepGSEA by showing how its results can be explained. Availability and implementation https://github.com/Teddy-XiongGZ/DeepGSEA [ABSTRACT FROM AUTHOR]

Introduction: Sports activity increases PGC1α and Nrf2, the regulatory factors of mitochondrial biogenesis. This paper aims to study the impact of two-month sodium citrate supplementation with Moderate-Intensity Continuous Training (MICT) on PGC-1α and Nrf2 expression in diabetic rats. Methods: Forty-five three-month-old male Wistar rats were haphazardly assigned to one of five equal groups (N=9): (1) healthy; (2) diabetic; (3) diabetes + exercise (DE); (4) diabetes+ supplementation (DS); and (5) diabetic + exercise + supplementation (DSE), matched according to their weights. After induction, exercises began on a treadmill for 8 weeks, five days a week. The MICT protocol ran at 70% of their maximum speed for 36 minutes. The rats supplemented with sodium-citrate- at 15 mmol/L in drinking water for two months. PGC-1α and Nrf2 expression were measured through Western blotting in the soleus muscle. Data were analyzed using univariate analysis of variance (ANOVA) and the Tukey post-hoc test. Cohen’s D effect size (ES) was calculated to compare the groups. Results: The results showed that induction of diabetes significantly reduced the expression of PGC-1α (P< 0.001; ES=1.36) and Nrf2 (P<0.088; ES=0.24), while exercise increased PGC-1α expression (P<0.001; ES=0.68). Sodium citrate supplementation, either alone or in combination with MICT activity, did not show a clear advantage for Nrf2 expression. Conclusion: MICT activity and sodium citrate supplementation, by increasing PGC-1α expression, can be considered therapeutic strategies for diabetic patients. However, to increase Nrf2 expression, further studies with different exercise intensities and doses of sodium citrate supplementation are needed. [ABSTRACT FROM AUTHOR]

Spatial transcripome (ST) profiling can reveal cells' structural organizations and functional roles in tissues. However, deciphering the spatial context of gene expressions in ST data is a challenge—the high-order structure hiding in whole transcriptome space over 2D/3D spatial coordinates requires modeling and detection of interpretable high-order elements and components for further functional analysis and interpretation. This paper presents a new method GraphTucker—graph-regularized Tucker tensor decomposition for learning high-order factorization in ST data. GraphTucker is based on a nonnegative Tucker decomposition algorithm regularized by a high-order graph that captures spatial relation among spots and functional relation among genes. In the experiments on several Visium and Stereo-seq datasets, the novelty and advantage of modeling multiway multilinear relationships among the components in Tucker decomposition are demonstrated as opposed to the Canonical Polyadic Decomposition and conventional matrix factorization models by evaluation of detecting spatial components of gene modules, clustering spatial coefficients for tissue segmentation and imputing complete spatial transcriptomes. The results of visualization show strong evidence that GraphTucker detect more interpretable spatial components in the context of the spatial domains in the tissues. Availability and implementation https://github.com/kuanglab/GraphTucker. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer remains one of the leading causes of death worldwide, which emphasizes the need for its early and accurate diagnosis and prognosis. Our review explores AI's potential in this field, analyzing 89 recent studies from 2020 through 2023. Specifically, these studies included AI applications for the analysis of multi-omics data: radiomics, pathomics, clinical records, and lab data. Notably, eight studies combined diverse omics data types (genomics, transcriptomics, epigenomics, and proteomics). Integration of AI for the analysis of clinical and omics data contributes to a significant advancement and is essential for safe clinical implementation. Cancer is one of the leading causes of death, making timely diagnosis and prognosis very important. Utilization of AI (artificial intelligence) enables providers to organize and process patient data in a way that can lead to better overall outcomes. This review paper aims to look at the varying uses of AI for diagnosis and prognosis and clinical utility. PubMed and EBSCO databases were utilized for finding publications from 1 January 2020 to 22 December 2023. Articles were collected using key search terms such as "artificial intelligence" and "machine learning." Included in the collection were studies of the application of AI in determining cancer diagnosis and prognosis using multi-omics data, radiomics, pathomics, and clinical and laboratory data. The resulting 89 studies were categorized into eight sections based on the type of data utilized and then further subdivided into two subsections focusing on cancer diagnosis and prognosis, respectively. Eight studies integrated more than one form of omics, namely genomics, transcriptomics, epigenomics, and proteomics. Incorporating AI into cancer diagnosis and prognosis alongside omics and clinical data represents a significant advancement. Given the considerable potential of AI in this domain, ongoing prospective studies are essential to enhance algorithm interpretability and to ensure safe clinical integration. [ABSTRACT FROM AUTHOR]

Transcription factors (TFs) are crucial in modulating gene expression and sculpting cellular and organismal phenotypes. The identification of TF–target gene interactions is pivotal for comprehending molecular pathways and disease etiologies but has been hindered by the demanding nature of traditional experimental approaches. This paper introduces a novel web application and package utilizing the R program, which predicts TF–target gene relationships and vice versa. Our application integrates the predictive power of various bioinformatic tools, leveraging their combined strengths to provide robust predictions. It merges databases for enhanced precision, incorporates gene expression correlation for accuracy, and employs pan-tissue correlation analysis for context-specific insights. The application also enables the integration of user data with established resources to analyze TF–target gene networks. Despite its current limitation to human data, it provides a platform to explore gene regulatory mechanisms comprehensively. This integrated, systematic approach offers researchers an invaluable tool for dissecting the complexities of gene regulation, with the potential for future expansions to include a broader range of species. [ABSTRACT FROM AUTHOR]

The global shear capacity of steel–concrete composite downstand cellular beams with precast hollow-core units is an important calculation as it affects the span-to-depth ratios and the amount of material used, hence affecting the embodied CO2 calculation when designers are producing floor grids. This paper presents a reliable tool that can be used by designers to alter and optimise grip options during the preliminary design stages, without the need to run onerous calculations. The global shear capacity prediction formula is developed using five machine learning models. First, a finite element model database is developed. The influence of the opening diameter, web opening spacing, tee-section height, concrete topping thickness, interaction degree, and the number of shear studs above the web opening are investigated. Reliability analysis is conducted to assess the design method and propose new partial safety factors. The Catboost regressor algorithm presented better accuracy compared to the other algorithms. An equation to predict the shear capacity of composite cellular beams with hollow-core units is proposed using gene expression programming. In general, the partial safety factor for resistance, according to the reliability analysis, varied between 1.25 and 1.26. [ABSTRACT FROM AUTHOR]

Simple Summary: Insects, like other animals, must face severe winter low temperature conditions in northern areas. Some insects even freeze entirely and wait out the winter until spring comes. Epigenetic modifications have been suggested to play a vital role in regulating the cold responses of insects. However, the dynamics of the enzymes involved in histone lysine methylation, histone H3 acetylation and methylation in response to cold winters in the freeze-tolerant goldenrod gall fly larvae Eurosta solidaginis and the freeze-avoiding gall moth caterpillars Epiblema scudderiana remains unclear. This paper investigates the modifications of key nuclear proteins that act as gene regulators and mainly focuses on proteins—called histones—that act to depress metabolism. The results indicate that histones are modified in E. solidaginis and Ep. scudderiana during winter. Significant reductions were observed in most of the targets of histone methylation/acetylation for decreasing temperatures of Ep. scudderiana larvae, whereas selected histone methylation/acetylation targets were conversely elevated in E. solidaginis. These epigenetic changes are shown to be an important element in winter survival. Overwintering survival by insects, whether of the freeze-tolerant or freeze-avoiding types, is typically associated with a strong suppression of metabolic rate (e.g., entry into diapause) that involves the differential expression of many genes with regulation at the transcriptional, translational or post-translational levels. Epigenetic modifications have been suggested to play a vital role in regulating cold responses of insects. However, knowledge of the roles of epigenetic mechanisms in modulating gene expression for winter survival of the larvae of two goldenrod gall formers, the freeze-tolerant dipteran Eurosta solidaginis and the freeze-avoiding lepidopteran Epiblema scudderiana, remain unknown. The current study evaluates the role of cold-induced lysine methylation and histone modifications, with enzymes of lysine methylation (SETD8, SETD7, SUV39H1, SMYD2 and ASH2L), as well as relative levels of histone H3 acetylation (H3K9ac, H3K18ac, H3K27ac, H3K56ac) and methylation (H3K4me1, H3K9me3, H3K36me2) examined in two insects. Significant (p < 0.05) reductions were observed in most of the targets of histone methylation/acetylation for decreasing temperatures of Ep. scudderiana larvae, whereas selected histone methylation/acetylation targets were conversely elevated (p < 0.05) in E. solidaginis, particularly under conditions of 5 °C for 4 h. Histone H3 expression was found to be variable without statistical differences in larval goldenrod gall moths and gall flies. These results provide basic information on the patterns of epigenetic regulation involved in insect cold hardiness. [ABSTRACT FROM AUTHOR]

The symbiotic relationship between arbuscular mycorrhizal fungi (AMF) and plants is well known for its benefits in enhancing plant growth and stress resistance. Research on whether key components of the AMF colonization process, such as MyC factors, can be directly utilized to activate plant symbiotic pathways and key functional gene expression is still lacking. In this paper, we found that, using a hydroponics system with Lotus japonicus, MyC factor analogue chitin oligomer 5 (CO5) had a more pronounced growth-promoting effect compared to symbiosis with AMF at the optimal concentration. Additionally, CO5 significantly enhanced the resistance of Lotus japonicus to various environmental stresses. The addition of CO5 activated symbiosis, nutrient absorption, and stress-related signaling pathways, like AMF symbiosis, and CO5 also activated a higher and more extensive gene expression profile compared to AMF colonization. Overall, the study demonstrated that the addition of MyC factor analogue CO5, by activating relevant pathways, had a superior effect on promoting plant growth and enhancing stress resistance compared to colonization by AMF. These findings suggest that utilizing MyC factor analogues like CO5 could be a promising alternative to traditional AMF colonization methods in enhancing plant growth and stress tolerance in agriculture. [ABSTRACT FROM AUTHOR]

The nonconventional yeast Kluyveromyces marxianus has potential for industrial production, but the lack of advanced synthetic biology tools for precise engineering hinders its rapid development. Here, we introduce a CRISPR-Cas9-mediated multilocus integration method for assembling multiple exogenous genes. Using SlugCas9-HF, a high-fidelity Cas9 nuclease, we enhance gene editing precision. Specific genomic loci predisposed to efficient integration and expression of heterologous genes are identified and combined with a set of paired CRISPR-Cas9 expression plasmids and donor plasmids to establish a CRISPR-based biosynthesis toolkit. This toolkit enables genome integration of large gene modules over 12 kb and achieves simultaneous quadruple-locus integration in a single step with 20% efficiency. As a proof-of-concept, we apply the toolkit to screen for gene combinations that promote heme production, revealing the importance of HEM4Km and HEM12Sc. This CRISPR-based toolkit simplifies the reconstruction of complex pathways in K. marxianus, broadening its application in synthetic biology. Fungi has been widely used as protein and drug production factories, in which efficient heterologous gene expression is fundamental. This paper provides a genome editing tool kit for heterologous gene expression in Kluyveromyces marxianus. [ABSTRACT FROM AUTHOR]

Background: Currently, no evidence exists on the expression of apoptosis (CASP3), autophagy (BECN1), and mitophagy (BNIP3) genes in the CA3 area after ischemia with long-term survival. Objective: The goal of the paper was to study changes in above genes expression in CA3 area after ischemia in the period of 6–24 months. Methods: In this study, using quantitative RT-PCR, we present the expression of genes associated with neuronal death in a rat ischemic model of Alzheimer's disease. Results: First time, we demonstrated overexpression of the CASP3 gene in CA3 area after ischemia with survival ranging from 0.5 to 2 years. Overexpression of the CASP3 gene was accompanied by a decrease in the activity level of the BECN1 and BNIP3 genes over a period of 0.5 year. Then, during 1-2 years, BNIP3 gene expression increased significantly and coincided with an increase in CASP3 gene expression. However, BECN1 gene expression was variable, increased significantly at 1 and 2 years and was below control values 1.5 years post-ischemia. Conclusions: Our observations suggest that ischemia with long-term survival induces neuronal death in CA3 through activation of caspase 3 in cooperation with the pro-apoptotic gene BNIP3. This study also suggests that the BNIP3 gene regulates caspase-independent pyramidal neuronal death post-ischemia. Thus, caspase-dependent and -independent death of neuronal cells occur post-ischemia in the CA3 area. Our data suggest new role of the BNIP3 gene in the regulation of post-ischemic neuronal death in CA3. This suggests the involvement of the BNIP3 together with the CASP3 in the CA3 in neuronal death post-ischemia. [ABSTRACT FROM AUTHOR]

Oxidative stress represents a critical facet of the array of abiotic stresses affecting crop growth and yield. In this paper, we investigated the potential differences in the functions of two highly homologous Arabidopsis DSS1 proteins in terms of maintaining genome integrity and response to oxidative stress. In the context of homologous recombination (HR), it was shown that overexpressing AtDSS1(I) using a functional complementation test increases the resistance of the Δdss1 mutant of Ustilago maydis to genotoxic agents. This indicates its conserved role in DNA repair via HR. To investigate the global transcriptome changes occurring in dss1 plant mutant lines, gene expression analysis was conducted using Illumina RNA sequencing technology. Individual RNA libraries were constructed from three total RNA samples isolated from dss1(I), dss1(V), and wild-type (WT) plants under hydrogen peroxide-induced stress. RNA-Seq data analysis and real-time PCR identification revealed major changes in gene expression between mutant lines and WT, while the dss1(I) and dss1(V) mutant lines exhibited analogous transcription profiles. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed significantly enriched metabolic pathways. Notably, genes associated with HR were upregulated in dss1 mutants compared to the WT. Otherwise, genes of the metabolic pathway responsible for the synthesis of secondary metabolites were downregulated in both dss1 mutant lines. These findings highlight the importance of understanding the molecular mechanisms of plant responses to oxidative stress. [ABSTRACT FROM AUTHOR]

Simple Summary: Though chemotherapy is generally known to be effective in the fight against cancer, its application is associated with a number of side effects, including toxic impacts on the ovaries. The most ovotoxic cytostatic chemotherapeutics are the classical alkylating compounds, particularly cyclophosphamide. Thus, it is of utmost importance to find effective means to protect ovaries against the negative influence of chemotherapeutic agents. This review paper presents the results of the current research work on the hitherto proposed agents potentially protecting the functions and state of ovaries exposed to chemotherapy. A large body of promising results have been reported, but as presented, it is necessary to undertake thorough and comprehensive studies aimed at providing an explicit evaluation of the efficacy of selected ovoprotecting agents and their possible clinical use in the future. Chemotherapy is one of the leading cancer treatments. Unfortunately, its use can contribute to several side effects, including gynotoxic effects in women. Ovarian reserve suppression and estrogen deficiency result in reduced quality of life for cancer patients and are frequently the cause of infertility and early menopause. Classic alkylating cytostatics are among the most toxic chemotherapeutics in this regard. They cause DNA damage in ovarian follicles and the cells they contain, and they can also induce oxidative stress or affect numerous signaling pathways. In vitro tests, animal models, and a few studies among women have investigated the effects of various agents on the protection of the ovarian reserve during classic chemotherapy. In this review article, we focused on the possible beneficial effects of selected hormones (anti-Müllerian hormone, ghrelin, luteinizing hormone, melatonin), agents affecting the activity of apoptotic pathways and modulating gene expression (C1P, S1P, microRNA), and several natural (quercetin, rapamycin, resveratrol) and synthetic compounds (bortezomib, dexrazoxane, goserelin, gonadoliberin analogs, imatinib, metformin, tamoxifen) in preventing gynotoxic effects induced by commonly used cytostatics. The presented line of research appears to provide a promising strategy for protecting and/or improving the ovarian reserve in the studied group of cancer patients. However, well-designed clinical trials are needed to unequivocally assess the effects of these agents on improving hormonal function and fertility in women treated with ovotoxic anticancer drugs. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper investigates the expression of miR-101-3p, miR-106a-5p, and miR-326 in colon cancer tissues compared to adjacent healthy tissues. This study involves 40 colon cancer patients, whose tissue samples were analyzed using qRT-PCR. Results indicate that these miRNAs are overexpressed in adjacent healthy tissues but decrease in advanced cancer stages. This study suggests a strong correlation between miR-106a-5p and miR-326 with colon cancer severity. The findings propose that miRNA profiling could be useful for early diagnosis and prognosis in colon cancer management. Early diagnosis and prognosis of cancer progression through biomarker profiling are crucial in managing colon cancer patients. Our research aimed to investigate the expression of miR-101-3p, miR-106a-5p, and miR-326 in tumor and adjacent healthy tissues of colon cancer patients and determine their potential diagnostic utility. This study included 40 patients divided into four groups according to the TNM staging classification. MiRNA expression was analyzed using qRT-PCR. The results showed that miR-101-3p, miR-106a-5p, and miR-326 are overexpressed in adjacent healthy tissues but decrease in advanced cancer stages. MiR-106a-5p and miR-326 are strongly correlated with colon cancer severity. These findings suggest that miRNA profiling could be useful for early diagnosis and prognosis in colon cancer management. [ABSTRACT FROM AUTHOR]

Gene therapy aims to modify or manipulate gene expression and change the biological characteristics of living cells to achieve the purpose of treating diseases. The safe, efficient, and stable expression of exogenous genes in cells is crucial for the success of gene therapy, which is closely related to the vectors used in gene therapy. Currently, gene therapy vectors are mainly divided into two categories: viral vectors and non-viral vectors. Viral vectors are widely used due to the advantages of persistent and stable expression, high transfection efficiency, but they also have certain issues such as infectivity, high immunological rejection, randomness of insertion mutation, carcinogenicity, and limited vector capacity. Non-viral vectors have the advantages of non-infectivity, controllable chemical structure, and unlimited vector capacity, but the transfection efficiency is low. With the rapid development of nanotechnology, the unique physicochemical properties of nanomaterials have attracted increasing attention in the field of drug and gene delivery. Among many nanomaterials, iron-based nanomaterials have attracted much attention due to their superior physicochemical properties, such as Fenton reaction, magnetic resonance imaging, magnetothermal therapy, photothermal therapy, gene delivery, magnetically-assisted drug delivery, cell and tissue targeting, and so on. In this paper, the research progress of iron-based nanomaterials in gene delivery and tumor gene therapy is reviewed, and the future application direction of iron-based nanomaterials is further prospected. [ABSTRACT FROM AUTHOR]

Epigenetics plays a crucial role in various clinical diseases, such as autism, by mediating the impact of environmental variables on genomic regulation. Autism spectrum disorder (ASD) is a neurological disorder influenced by both genetic and environmental factors that affect the developing brain. DNA methylation, histone tail modifications, and noncoding RNA activity can change the function of genes without altering nucleotide sequences. Genes and environment combine to produce the etiology of ASD. One of the main areas of ASD research now being studied is the effects of epigenetic factors on gene expression, such as DNA methylation. Autistic patients exhibit evidence of oxidative stress and impaired methylation, which may reflect the effects of toxic exposure on sulfur metabolism that may lead to cellular damage in the brain and altered expression of epigenetic genes. This review paper summarizes the findings of the supplementary therapy studies of ASD, showing that supplements, including B9, B12, B6, D, E, C, glutathione, omega-3, and choline, are highly effective in modifying methylation in autism, improving many nutrient and metabolic problems, and resulting in significant improvements in symptoms. [ABSTRACT FROM AUTHOR]

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Reactive oxygen species (ROSs) are byproducts of normal cellular metabolism and play pivotal roles in various physiological processes. Disruptions in the balance between ROS levels and the body's antioxidant defenses can lead to the development of numerous diseases. Glutathione peroxidase 3 (GPX3), a key component of the body's antioxidant system, is an oxidoreductase enzyme. GPX3 mitigates oxidative damage by catalyzing the conversion of hydrogen peroxide into water. Beyond its antioxidant function, GPX3 is vital in regulating metabolism, modulating cell growth, inducing apoptosis and facilitating signal transduction. It also serves as a significant tumor suppressor in various cancers. Recent studies have revealed aberrant expression of GPX3 in several non-neoplastic diseases, associating it with multiple pathological processes. This review synthesizes the current understanding of GPX3 expression and regulation, highlighting its extensive roles in noncancerous diseases. Additionally, this paper evaluates the potential of GPX3 as a diagnostic biomarker and explores emerging therapeutic strategies targeting this enzyme, offering potential avenues for future clinical treatment of non-neoplastic conditions. [ABSTRACT FROM AUTHOR]

This document discusses the trends and prospects of genetic and molecular research in plants, particularly in relation to crop breeding and increasing crop productivity. The article highlights the challenges posed by climate change and the need to meet the growing global demand for food. It emphasizes the importance of utilizing breeding methods based on plant physiology, genetics, and molecular research to overcome these challenges. The document also provides an overview of various studies and research papers focused on topics such as transcriptome analysis, epigenetics, genome analysis, gene editing, and plant stress-related studies. Overall, the document aims to contribute to the development of breeding technology and the improvement of crops to ensure food security and provide valuable breeding resources. [Extracted from the article]

Simple Summary: Enzymes of the detoxification system are known to play a crucial role in insecticide resistance in insects. The role of P450 monooxygenases in providing resistance to chlorfenapyr is ambiguous and of interest due to possible negative cross-resistance to pyrethroids and other insecticides, the resistance to which is ensured by increased activity of these enzymes. This study aimed to perform a biochemical and molecular evaluation of P450 monooxygenases in susceptible and chlorfenapyr-resistant strains of Musca domestica L. depending on sex. The chlorfenapyr-resistant strain of M. domestica L. did not differ from the susceptible strain in terms of the pattern of overall P450-monooxygenase activity: the larvae of both strains had lower enzymatic activity than the adults. However, the development of resistance to chlorfenapyr in house flies was accompanied by an increase in P450-monooxygenase activity without changes in CYP6D1 expression. PCR-RFLP analysis revealed a previously undescribed mutation in the promoter region of the CYP6D1 gene of M. domestica, the effect of which on the gene expression level was not detected. The house fly Musca domestica L. is one of the most common insects of veterinary and medical importance worldwide; its ability to develop resistance to a large number of insecticides is well known. Many studies support the involvement of cytochrome P-450-dependent monooxygenases (P450) in the development of resistance to pyrethroids, neonicotinoids, carbamates, and organophosphates among insects. In this paper, the monooxygenase activity and expression level of CYP6D1 were studied for the first time in a chlorfenapyr-resistant strain of house fly. Our studies demonstrated that P450 activity in adults of the susceptible strain (Lab TY) and chlorfenapyr-resistant strain (ChlA) was 1.56–4.05-fold higher than that in larvae. In females of the Lab TY and ChlA strains, this activity was 1.53- and 1.57-fold higher, respectively (p < 0.05), than that in males, and in contrast, the expression level of CYP6D1 was 21- and 8-fold lower, respectively. The monooxygenase activity did not vary between larvae of the susceptible strain Lab TY and the chlorfenapyr-resistant strain ChlA. Activity in females and males of the ChlA strain exceeded that in the Lab TY strain specimens by 1.54 (p = 0.08) and 1.83 (p < 0.05) times, respectively, with the same level of CYP6D1 expression. PCR-RFLP analysis revealed a previously undescribed mutation in the promoter region of the CYP6D1 gene in adults of the Lab TY and ChlA strains, and it did not affect the gene expression level. The obtained results show that the development of resistance to chlorfenapyr in M. domestica is accompanied by an increase in P450-monooxygenase activity without changes in CYP6D1 expression. [ABSTRACT FROM AUTHOR]

The identification of co-regulated genes and their Transcription-Factor Binding Sites (TFBSs) are the key steps toward understanding transcription regulation. In addition to effective laboratory assays, various bi-clustering algorithms for the detection of the co-expressed genes have been developed. Bi-clustering methods are used to discover subgroups of genes with similar expression patterns under to-be-identified subsets of experimental conditions when applied to gene expression data. By building two fuzzy partition matrices of the gene expression data with the Axiomatic Fuzzy Set (AFS) theory, this paper proposes a novel fuzzy bi-clustering algorithm for the identification of co-regulated genes. Specifically, the gene expression data are transformed into two fuzzy partition matrices via the sub-preference relations theory of AFS at first. One of the matrices considers the genes as the universe and the conditions as the concept, and the other one considers the genes as the concept and the conditions as the universe. The identification of the co-regulated genes (bi-clusters) is carried out on the two partition matrices at the same time. Then, a novel fuzzy-based similarity criterion is defined based on the partition matrices, and a cyclic optimization algorithm is designed to discover the significant bi-clusters at the expression level. The above procedures guarantee that the generated bi-clusters have more significant expression values than those extracted by the traditional bi-clustering methods. Finally, the performance of the proposed method is evaluated with the performance of the three well-known bi-clustering algorithms on publicly available real microarray datasets. The experimental results are in agreement with the theoretical analysis and show that the proposed algorithm can effectively detect the co-regulated genes without any prior knowledge of the gene expression data. [ABSTRACT FROM AUTHOR]

Background and Objective: The embryo and the fetus develop in a physiologically hypoxic environment, where vascularization is sustained by HIF-1, VEGF, and the β-adrenergic system. In animals, β3-adrenoceptors (β3-ARs), up-regulated by hypoxia, favor global fetal wellness to such an extent that most diseases related to prematurity are hypothesized to be induced or aggravated by a precocious β3-AR down-regulation, due to premature exposure to a relatively hyperoxic environment. In animals, β3-AR pharmacological agonism is currently investigated as a possible new therapeutic opportunity to counteract oxygen-induced damages. Our goal is to translate the knowledge acquired in animals to humans. Recently, we have demonstrated that fetuses become progressively more hypoxemic from mid-gestation to near-term, but starting from the 33rd–34th week, oxygenation progressively increases until birth. The present paper aims to describe a clinical research protocol, evaluating whether the expression level of HIF-1, β3-ARs, and VEGF is modulated by oxygen during intrauterine and postnatal life, in a similar way to animals. Materials and Methods: In a prospective, non-profit, single-center observational study we will enroll 100 preterm (group A) and 100 full-term newborns (group B). We will collect cord blood samples (T0) and measure the RNA expression level of HIF-1, β3-ARs, and VEGF by digital PCR. In preterms, we will also measure gene expression at 48–72h (T1), 14 days (T2), and 30 days (T3) of life and at 40 ± 3 weeks of post-menstrual age (T4), regardless of the day of life. We will compare group A (T0) vs. group B (T0) and identify any correlations between the values obtained from serial samples in group A and the clinical data of the patients. Our protocol has been approved by the Pediatric Ethical Committee for Clinical Research of the Tuscany region (number 291/2022). Expected Results: The observation that in infants, the HIF-1/β3-ARs/VEGF axis shows similar modulation to that of animals could suggest that β3-ARs also promote fetal well-being in humans. [ABSTRACT FROM AUTHOR]

Spontaneous tumour formation in higher plants can occur in the absence of pathogen invasion, depending on the plant genotype. Spontaneous tumour formation on the taproots is consistently observed in certain inbred lines of radish (Raphanus sativus var. radicula Pers.). In this paper, using Oxford Nanopore and Illumina technologies, we have sequenced the genomes of two closely related radish inbred lines that differ in their ability to spontaneously form tumours. We identified a large number of single nucleotide variants (amino acid substitutions, insertions or deletions, SNVs) that are likely to be associated with the spontaneous tumour formation. Among the genes involved in the trait, we have identified those that regulate the cell cycle, meristem activity, gene expression, and metabolism and signalling of phytohormones. After identifying the SNVs, we performed Sanger sequencing of amplicons corresponding to SNV-containing regions to validate our results. We then checked for the presence of SNVs in other tumour lines of the radish genetic collection and found the ERF118 gene, which had the SNVs in the majority of tumour lines. Furthermore, we performed the identification of the CLAVATA3/ESR (CLE) and WUSCHEL (WOX) genes and, as a result, identified two unique radish CLE genes which probably encode proteins with multiple CLE domains. The results obtained provide a basis for investigating the mechanisms of plant tumour formation and also for future genetic and genomic studies of radish. [ABSTRACT FROM AUTHOR]

This research paper presents a novel approach to identifying biomarkers that can be used to prognosticate patients with triple-negative breast cancer (TNBC) eligible for neoadjuvant therapy. The study utilized survival and RNA sequencing data from a cohort of TNBC patients and identified 276 genes whose expression was related to survival in such patients. The gene expression data were then used to classify patients into two major groups based on the presence or absence of Wingless/Integrated-pathway (Wnt-pathway) and mesenchymal (Mes) markers (Wnt/Mes). Patients with a low expression of Wnt/Mes-related genes had a favorable outcome, with no deaths observed during follow-up, while patients with a high expression of Wnt/Mes genes had a higher mortality rate of 50% within 19 months. The identified gene list could be validated and potentially used to shape treatment options for TNBC patients eligible for neoadjuvant therapy providing valuable insights into the development of more effective treatments for TNBC. Our data also showed significant variation in gene expression profiles before and after chemotherapy, with most tumors switching to a more mesenchymal/stem cell-like profile. To verify this observation, we performed an in silico analysis to classify breast cancer tumors in Prediction Analysis of Microarray 50 (PAM50) molecular classes before treatment and after treatment using gene expression data. Our findings demonstrate that following drug intervention and metastasis, certain tumors undergo a transition to alternative subtypes, resulting in diminished therapeutic efficacy. This underscores the necessity for reevaluation of patients who have experienced relapse or metastasis post-chemotherapy, with a focus on molecular subtyping. Tailoring treatment strategies based on these refined subtypes is imperative to optimize therapeutic outcomes for affected individuals. [ABSTRACT FROM AUTHOR]

Rapid advancements in gene technology have raised concerns regarding the potential abuse of techniques, such as gene doping, for enhancing athletic performance. To identify this possibility, a reliable procedure for detecting doping genes is required. Although detection methods for doping genes have been created, there are still areas for further improvement. One significant challenge is the high storage and transport costs of the test samples. For this issue, the dried blood spot (DBS) method can be a cost-effective solution. This study aimed to assess the practicality of incorporating DBSs into the gene doping detection process as a pilot study. Whole-blood samples were initially collected from mice engineered to express human erythropoietin from the rAAV vector. Then, the blood was placed in filter papers and left to dry at room temperature for five hours to form DBSs. These DBSs were subsequently preserved in sealed plastic bags at room temperature. After the extraction of DNA, DBSs were formed, and TaqMan-qPCR was utilized to detect the presence of rAAV vector-derived DNA. The finding confirmed that doping gene-specific fragments were successfully detected in DBSs. This outcome suggests that the DBS method is an effective approach to be considered when developing a comprehensive protocol for gene doping detection. [ABSTRACT FROM AUTHOR]