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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]

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]

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]

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]

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]

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]

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]

Despite significant advances in the diagnosis and treatment of cardiovascular diseases, recent calls have emphasized the unmet need to improve precision-based approaches in cardiovascular disease. Although some studies provide preliminary evidence of the diagnostic and prognostic potential of circulating coding and non-coding RNAs, the complex RNA biology and lack of standardization have hampered the translation of these markers into clinical practice. In this position paper of the CardioRNA COST action CA17129, we provide recommendations to standardize the RNA development process in order to catalyse efforts to investigate novel RNAs for clinical use. We list the unmet clinical needs in cardiovascular disease, such as the identification of high-risk patients with ischaemic heart disease or heart failure who require more intensive therapies. The advantages and pitfalls of the different sample types, including RNAs from plasma, extracellular vesicles, and whole blood, are discussed in the sample matrix, together with their respective analytical methods. The effect of patient demographics and highly prevalent comorbidities, such as metabolic disorders, on the expression of the candidate RNA is presented and should be reported in biomarker studies. We discuss the statistical and regulatory aspects to translate a candidate RNA from a research use only assay to an in-vitro diagnostic test for clinical use. Optimal planning of this development track is required, with input from the researcher, statistician, industry, and regulatory partners. [ABSTRACT FROM AUTHOR]

They describe the structure of the MRN Complex and its function in double-strand break (DSB) repair and analyze the different germline alterations of the MRN complex genes in autosomal recessive syndromes, as well as the association between heterozygous germline alterations in these genes and cancer predisposition. In the rapidly evolving landscape of molecular genetics and genomics, this Special Issue brings together a collection of insightful review articles that delve into the forefront of scientific exploration. The authors also propose a possible explanation of the discrepancies in the published results of the effects of the OXTR gene polymorphisms and methylation on different diseases [[2]]. [Extracted from the article]

Paper mulberry vein banding virus (PMVBV), a member of the genus Badnavirus in the family Caulimoviridae, infects paper mulberry (Broussonetia papyrifera), a dicotyledonous plant. Putative promoter regions in the PMVBV genome were tested using recombinant plant expression vectors, revealing that the promoter activity of three genome fragments was about 1.5-fold higher than that of the 35S promoter of cauliflower mosaic virus in Nicotiana benthamiana. In transformed transgenic Arabidopsis thaliana plants, these promoter constructs showed constitutive expression. Based on the activity and gene expression patterns of these three promoter constructs, a fragment of 384 bp (named PmVP) was deduced to contain the full-length promoter of the PMVBV genome. The results suggest that the PMVBV-derived promoter can be used for the constitutive expression of transgenes in dicotyledonous plants. [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]

Aging is associated with substantial physiological changes and constitutes a major risk factor for neurological disorders including dementia. Alterations in gene expression upon aging have been extensively studied; however, an in-depth characterization of post-transcriptional regulatory events remains elusive. Here, we profiled the age-related changes of the transcriptome and translatome in the female mouse hippocampus by RNA sequencing of total RNA and polysome preparations at four ages (3-, 6-, 12-, 20-month-old); and we implemented a variety of bioinformatics approaches to unravel alterations in transcript abundance, alternative splicing, and polyadenylation site selection. We observed mostly wellcoordinated transcriptome and translatome expression signatures across age including upregulation of transcripts related to immune system processes and neuroinflammation, though transcripts encoding ribonucleoproteins or associated with mitochondrial functions, calcium signaling and the cell-cycle displayed substantial discordant profiles, suggesting translational control associated with age-related deficits in hippocampal-dependent behavior. By contrast, alternative splicing was less preserved, increased with age and was associated with distinct functionally-related transcripts encoding proteins acting at synapses/dendrites, RNA-binding proteins; thereby predicting regulatory roles for RBM3 and CIRBP. Only minor changes in polyadenylation site selection were identified, indicating pivotal 3'-end selection in young adults compared to older groups. Overall, our study provides a comprehensive resource of age-associated post-transcriptional regulatory events in the mouse hippocampus, enabling further examination of the molecular features underlying age-associated neurological diseases. [ABSTRACT FROM AUTHOR]

Objective: Cervical cancer screening by primary human papilloma virus detection and cytology is fraught with low specificity and variable sensitivity, respectively. Cytology-histology correlation remains modest. Biomarkers associated with early genetic events in cervical squamous carcinogenesis and detectable in cytology material are likely to be relevant. Human telomerase RNA component (hTERC) gene overexpression and aneuploidy are promising candidates in view of their reported early and consistent association with cervical squamous oncogenesis., Methods: We analysed hTERC gene expression and chromosome 7 ploidy by fluorescent in-situ hybridisation (FISH) in 50 women with cytological precursor squamous intraepithelial lesions and available histology outcomes. Results were expressed as percentages of cells showing ≥3 signals, mean signals/nucleus, and maximum amplitude across various cytology and histology categories. Proportions of positive cases were calculated from threshold values derived from 6 controls. Distribution of above indices with respect to ≥cervical intraepithelial neoplasia 2 (CIN2) was explored., Results: For both genetic aberrations, there was significant positive correlation (for all indices) between the proportion of positive cases and worsening cytological and histological outcomes (P < .05), with significant intergroup differences (P < .05). High-grade lesions (≥CIN2) had significantly higher results compared to

This document is a summary of a special issue of the International Journal of Molecular Sciences titled "The Molecular and Cellular Pathophysiologic Mechanisms Underlying Ocular Diseases and Emerging Therapies." The special issue focuses on the prevalence and rising global public health concerns of visual impairment and ophthalmic diseases. It aims to enhance researchers' and eyecare professionals' understanding of the risk factors, biomarkers, and cellular and molecular mechanisms underlying various eye diseases. The special issue includes eight papers, including original research papers, reviews, and a case report, covering topics such as diabetic retinopathy, retinal diseases, tear biomarkers, and uveal melanoma. The papers provide new advancements in the molecular and cellular pathogenesis of eye diseases and the development of preventive measures and emerging therapies. The document concludes by expressing hope that the special issue will inspire further research and understanding of eye diseases. [Extracted from the article]

Introduction and aim. Opioids have pain-relieving and anti- inflammatory properties, as demonstrated in animal models of colitis and abdominal pain. Kappa opioid receptors (KOP) are not well characterized, but KOP ligands influence the progression or inhibition of cancer growth. In this study we focused on the level of expression of prodynorphin and kappa opioid receptors in experimental colorectal cancer. Material and methods. The effects of U50488H, a selective KOP agonist, and Nor-binaltorphimine (nor-BNI), a selective KOP antagonist, were tested in in vitro and in vivo models. Colitis-associated colorectal cancer was induced in mice using azoxymethane and dextran sodium sulfate, and U50488H was injected intraperitoneally twice a week at the dose of 1 mg/kg. MC-38 cell line was used to verify the impact of KOP ligands on the cell viability. Gene and protein expression was assessed using real time RT-PCR and western blot. Results. U50488H decreased cell viability after 24 hours in MC-38 cells. Nor-Bni had no effect on the cell viability, but counteracted U50488H. The mixture of U50488H and Nor-Bni had a worse effect than U50488H alone. In vivo, the colonic length did not differ between AOM/DSS and U50488H-treated groups. In mice trated with AOM/DSS we observed a thicker submucosal and muscle layer with increased immune cell infiltration as compared to U50488H-treated mice. Conclusion. U50488H shown the ability to influence the development of the colonic cancer in mice. [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]

Alzheimer's disease (AD) is a severe neurodegenerative disease for which there is currently no effective treatment. Mild cognitive impairment (MCI) is an early disease that may progress to AD. The effective diagnosis of AD and MCI in the early stage has important clinical significance. Methods: To this end, this paper proposed a hypergraph-based netNMF (HGnetNMF) algorithm for integrating structural magnetic resonance imaging (sMRI) of AD and MCI with corresponding gene expression profiles. Results: Hypergraph regularization assumes that regions of interest (ROIs) and genes were located on a non-linear low-dimensional manifold and can capture the inherent prevalence of two modalities of data and mined high-order correlation features of the two data. Further, this paper used the HG-netNMF algorithm to construct a brain structure connection network and a protein interaction network (PPI) with potential role relationships, mine the risk (ROI) and key genes of both, and conduct a series of bioinformatics analyses. Conclusion: Finally, this paper used the risk ROI and key genes of the AD and MCI groups to construct diagnostic models. The AUC of the AD group and MCI group were 0.8 and 0.797, respectively. [ABSTRACT FROM AUTHOR]

This document discusses the use of omics analysis, such as genomics, transcriptomics, proteomics, and metabolomics, in plant research to uncover the physiological mechanisms of plant development, stress responses, and key trait formation. The document includes ten papers that cover topics such as hormone effects on cutting rooting in woody plants, gene expression in sandalwood and maize, volatile aroma formation in pears, and the transcriptional regulation of miRNAs in plants. The research papers highlight the importance of combining omics and physiological analyses to enhance plant conservation and utilization. Two review papers provide an overview of phosphate-binding loop guanosine triphosphatases (P-loop GTPases) and the transcriptional regulation of miRNAs in plants. The authors emphasize the need for further research using innovative omics techniques to expand our knowledge of plant physiology. [Extracted from the article]

Introduction and aim. Canine mammary cancer (CMC) is one of the most common malignancy in female dogs. Although there are many cell markers useful in the diagnosis of cancer in veterinary medicine, the expression of SOX 10 has not yet been well characterized. In human oncology, SOX10 expression is positively correlated with negative prognostic factors for breast cancer. Studies indicate similar mechanisms in the process of oncogenesis in humans and dogs. The aim of our work is to confirm that SOX 10 can be a new cellular marker in the diagnosis of mammary carcinomas in bitches. Material and methods. The study was carried out on 53 samples of canine mammary carcinoma, 14 samples of adenoma and 10 samples of normal glandular tissue. The material was stained with hematoxylin and eosin (H&E) to confirm the histological type and histological grade (Grading) according to the Elston and Ellis classification Immunohistochemistry of SOX10 expression was performed. The percentage of cells showing positive expression was assessed according to the following scale: 0% of cells 0 points, 1-10% of cells 1 point, 11- 50% 2 points, 51-80% 3 points, 81-100% 4 points. Results. Statistical analysis showed significantly higher expression in simple carcinoma compared to normal tissue (p=0.008) and in cancer compared to normal tissue (p=0.008) and significantly lower protein expression in benign tumors compared to G2 tumors (p=0.004). Conclusion. The obtained results may suggest a significant role of SOX10 in the progression of carcinogenesis in mammary tumors in bitches, similarly to the case of triple-negative breast cancer in females. [ABSTRACT FROM AUTHOR]

Introduction and aim. Growth differentiation factor 11 (GDF11) is a novel member of TGF-β superfamily. Its role is confirmed in embryogenesis, rejuvenation, and aging. GDF11 is involved in inflammatory response as it inhibits the release of pro-inflammatory cytokines and NLRP3 inflammasome activation. Moreover, GDF11 has clinicopathological signifi- cance in colorectal cancer and is proposed as a possible prognostic factor. The aim of our study is to assess the activity of GDF11 during development of colitis and colorectal cancer in mice. Material and methods. Male C57BL/6 mice were used in our experiments. Colitis was induced by dextran sodium sulfate (DSS) addition into drinking water. Single injection of azoxymethane (AOM) and repeated cycles of DSS were used to induce colitis-associated colorectal cancer. At different time points mice were sacrificed. Human and mouse colorectal cancer cell lines were used in our project to verify GDF11 expression. MC-38 cells were stimulated with the cytokines for 24 hours. We isolated RNA and protein to perform real-time RT-PCR and Western Blot. Statistical analysis was performed using GraphPad Software. Results. We found that GDF11 expression at mRNA level is increased in the mouse colon during aging. GDF11 expression is elevated during the experimental colitis and during the period of recovery. GDF11 expression is changed at initial stage of colorectal cancer in mice. Its expression also differs among different human cell lines. LPS induced an increase of GDF11 expression. Conclusion. We confirmed that GDF11 is crucial at all stages of development of experimental colitis and colitis-associated colorectal cancer. [ABSTRACT FROM AUTHOR]

Introduction and aim. Endometrial cancer (EC) is the most common malignancy developing in the uterus. In 80% of cases, this cancer occurs in postmenopausal women, and only 5% of cases are recorded before the age of 40. This cancer is currently the fourth most common female cancer in the world and accounts for 7% of cancers in women. The risk factors for its occurrence are age, Caucasian race, positive family history, nulliparity, early first and late last menstruation, occurrence of anovulatory cycles, obesity. A number of these risk factors are related to high levels of endogenous estrogens. Both endogenous and exogenous estrogens stimulate endometrial proliferation, preventing cell secretion. Long-term stimulation of the glandular epithelium causes its growth, and in the final phase it can lead to the development of cancer. The basis for the diagnosis of endometrial cancer is histopathological examination. Material and methods. During the preparation of the presentation 4 databases (PubMed, Google Scholar, Sciencedirect, Medscape) were searched for studies science publications from October 2018 to June 2022 in English. The search terms were: „endometrial cancer", „microsatellite instability in endometrial cancer" in the title or abstract or as keywords. A total of 36 references, excluding duplicates, were identified. Analysis of literature. Studies indicate that microsatellite instability (MSI) is important for the development of various cancers, including endometrial cancer. MSI is the result of changes in mismatch repair (MMR) protein genes and is found in 15-43% of sporadic endometrial cancers. Mutations mainly concern conservative domains and are deletions, insertions, transitions and transversions. Immunohistochemical evaluation of MMR protein expression is performed from postoperative material in parallel with histopathological examination. Four monoclonal antibodies are used: anti-MLH1, anti-PMS2, anti-MSH2 and anti-MSH6. Numerous studies have shown that impairment of the MMR system is correlated with increased expansion of the PD-1 and PD-L1 proteins. Conclusion. Disturbances in the expression of proteins in this system may therefore serve as predictive biomarkers giving a chance for the use of modern anti-PD1 therapy [ABSTRACT FROM AUTHOR]

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]

• Different cultivars exhibited different sensitivity to light. • Different phenolics showed different sensitivity to light. • Bagging inhibited the synthesis of most phenolics in peach fruit. • Bagging suppressed the expression of most structural genes and transcription factors. • PpHY5 homolog PpHYH was induced by high light. Bagging is a vital cultivation measure for producing high-quality peach fruit, which affects the appearance and internal quality of the fruit by mainly intervening in its exposure to light. However, it is not entirely clear whether bagging affects the content of phenolic compounds or which compounds are most sensitive to bagging treatment, and the regulatory role of bagging on phenolic synthetic-related genes is also unknown. In this experiment, four peach cultivars, 'BJ', 'XH', 'RG', and 'HYT', were bagged with four different types of bags at 50 days after full bloom, with no bag as control, and all fruits were harvested at the commercial maturation stage. The study found that bagged fruits had higher L*, b*, and h° values but lower a* and C* values than non-bagged fruits. Different cultivars and different phenolics exhibited different sensitivities to bagging treatments. Light intensity not only played a decisive role in the accumulation of anthocyanins in peach fruit but also had a strong and widespread impact on other phenolic substances. Overall, light not onlly significantly promoted the accumulation of cyanidin 3-glucoside, cyanidin 3-rutinoside, epicatechin, and rutin but also increased the accumulation of catechin, chlorogenic acid, and neochlorogenic acid to some extent, while shading by bagging inhibited the accumulation of these phenolics. Correspondingly, high light induced the upregulation of most structural genes and transcription factors, including PpPAL1, PpC3H1, PpC3H2, PpDFR, PpLDOX, PpUFGT, and PpMYB10.1 , while low light inhibited the expression of these genes in the four varieties. In addition, PpHY5 homolog PpHYH was induced by high light, which might participate in the biosynthesis of the light-regulated phenolic in peach fruit. This study lays the foundation for further analysis of the regulation mechanism of light on the synthesis of phenolic compounds in peach fruit. [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]

Introduction and aim. Hereditary motor neuropathy type VB (HMN5B) is a rare neurological disorder inherited in an autosomal dominant way. It is characterized by weakness and atrophy of the distal muscles, mainly the internal muscles of the hands and of the lower extremities. A mutation of the REEP1 gene is responsible for the onset of the disease. This scientific work describes a clinical case of a nine-year-old boy with HMN, who had an undescribed variant of the REEP1 gene. Description of the case. Parents with a 9-year-old son, previously consulted at the Neurology Clinic because of the neuropathic neuromuscular disorders, appealed to the Genetics Clinic. Due to the recommendation, they did the Trio-WES/ NGS test at the Neurology Clinic. The test result showed a pathogenic mutation of the REEP1 gene of the autosomal dominant sense change type, inherited from the Mother. The gene variant turned out to be unknown. Changes with lower expression of neurological function were found in the woman's Family (Father, Siblings). Based on the Trio-WES/NGS examination and clinical picture, the boy was diagnosed with hereditary distal motor neuropathy type VB. Currently, he is in good contact, the neurological deficit includes an abnormal gait with a drooping right foot. The patient is under neurological care. Conclusion. Hereditary motor neuropathies are a heterogeneous group of conditions, which are included into the group of genetic neuropathies. The REEP1 mutations can be identified in two other diseases: hereditary spastic paraplegia and congenital axonal neuropathy. [ABSTRACT FROM AUTHOR]

Diagnostics are at the basis and core of our work as plant pathologists. Seruga Musi'c and Plavec (Croatia) authored such a paper entitled "Differentiation of the Flavescence dorée phytoplasma genetic clusters by multiplex real-time PCR assay targeting the I map i gene". The last EC paper in the phytoplasma section of this issue by Galetto and collaborators (Italy), although once again focused on FDp, deals with the transcriptional profile of selected Flavescence dorée phytoplasma genes during infection of insect vectors and host plants. [Extracted from the article]

Plant Genomics - Advancing Our Understanding of Plants Plant genomics has made significant progress in recent years, enabling researchers to identify genes and genomic regions responsible for plant growth, development, and stress response. Genome editing technologies such as CRISPR/Cas9 have revolutionized the field of plant genomics and provided researchers with powerful tools to precisely modify plant genomes. [Extracted from the article]

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]

Pectin lyase (PMGL) is an industrially important enzyme with widespread applications in the food, paper, and textile industries, owing to its capacity for direct degradation of highly esterified pectin. In this study, PMGL-Ba derived from Bacillus licheniformis underwent mining and heterologous expression in P. pastoris. Furthermore, diverse strategies, encompassing the optimization of expression cassette components, elevation of gene dosage, and co-expression of chaperone factors, were employed to augment PMGL-Ba production in P. pastoris. The signaling peptide OST1-pre-α-MF-pro and promoter AOX1 were finally selected as expression elements. By overexpressing the transcription factor Hac1p in conjunction with a two-copy PMGL-Ba setup, a strain yielding high PMGL-Ba production was achieved. In shake flask fermentation lasting 144 h, the total protein concentration reached 1.81 g/L, and the enzyme activity reached 1821.36 U/mL. For further scale up production, high-density fermentation transpired in a 5 L fermenter for 72 h. Remarkably, the total protein concentration increased to 12.49 g/L, and the enzyme activity reached an impressive 12668.12 U/mL. The successful heterologous and efficient expression of PMGL-Ba not only furnishes a valuable biological enzyme for industrial applications but also contributes to cost reduction in the utilization of biological enzymes in industrial applications. [ABSTRACT FROM AUTHOR]

Diabetes alters the function of ion channels responsible for regulating arterial smooth muscle membrane potential, resulting in vasoconstriction. Our prior research demonstrated an elevation of TMEM16A in diabetic arteries. Here, we explored the mechanisms involved in Transmembrane protein 16A (TMEM16A) gene expression. Our data indicate that a Snail-mediated repressor complex regulates arterial TMEM16A gene transcription. Snail expression was reduced in diabetic arteries while TMEM16A expression was upregulated. The TMEM16A promoter contained three canonical E-box sites. Electrophoretic mobility and super shift assays revealed that the −154 nt E-box was the binding site of the Snail repressor complex and binding of the repressor complex decreased in diabetic arteries. High glucose induced a biphasic contractile response in pressurized nondiabetic mouse hindlimb arteries incubated ex vivo. Hindlimb arteries incubated in high glucose also showed decreased phospho-protein kinase D1 and TMEM16A expression. In hindlimb arteries from nondiabetic mice, administration of a bolus dose of glucose activated protein kinase D1 signaling to induce Snail degradation. In both in vivo and ex vivo conditions, Snail expression exhibited an inverse relationship with the expression of protein kinase D1 and TMEM16A. In diabetic mouse arteries, phospho-protein kinase D1 increased while Akt2 and pGSK3β levels declined. These results indicate that in nondiabetic mice, high glucose triggers a transient deactivation of the Snail repressor complex to increase arterial TMEM16A expression independently of insulin signaling. Conversely, insulin resistance activates GSK3β signaling and enhances arterial TMEM16A channel expression. These data have uncovered the Snail-mediated regulation of arterial TMEM16A expression and its dysfunction during diabetes. NEW & NOTEWORTHY: The calcium-activated chloride channel, TMEM16A, is upregulated in the diabetic vasculature to cause increased vasoconstriction. In this paper, we have uncovered that the TMEM16A gene expression is controlled by a Snail-mediated repressor complex that uncouples with both insulin-dependent and -independent pathways to allow for upregulated arterial protein expression thereby causing vasoconstriction. The paper highlights the effect of short- and long-term glucose-induced dysfunction of an ion channel expression as a causative factor in diabetic vascular disease. [ABSTRACT FROM AUTHOR]

Purpose. As a scientific field, bioinformatics has drawn remarkable attention from various fields, such as information technology, mathematics, and modern biological sciences, in recent years. The topic models originating from the field of natural language processing have become the focus of attention with the rapid accumulation of biological datasets. Thus, this research is aimed at modeling the topic content of the bioinformatics literature presented by Iranian researchers in the Scopus Citation Database. Methodology. This research was a descriptive-exploratory study, and the studied population included 3899 papers indexed in the Scopus database, which had been indexed in this database until March 9, 2022. The topic modeling was then performed on the abstracts and titles of the papers. A combination of LDA and TF-IDF was utilized for topic modeling. Findings. The data analysis with topic modeling resulted in identifying seven main topics "Molecular Modeling," "Gene Expression," "Biomarker," "Coronavirus," "Immunoinformatics," "Cancer Bioinformatics," and "Systems Biology." Moreover, "Systems Biology" and "Coronavirus" had the largest and smallest clusters, respectively. Conclusion. The present investigation demonstrated an acceptable performance for the LDA algorithm in classifying the topics included in this field. The extracted topic clusters indicated excellent consistency and topic connection with each other. [ABSTRACT FROM AUTHOR]

Background: Cancer subtype classification is helpful for personalized cancer treatment. Although, some approaches have been developed to classifying caner subtype based on high dimensional gene expression data, it is difficult to obtain satisfactory classification results. Meanwhile, some cancers have been well studied and classified to some subtypes, which are adopt by most researchers. Hence, this priori knowledge is significant for further identifying new meaningful subtypes. Results: In this paper, we present a combined parallel random forest and autoencoder approach for cancer subtype identification based on high dimensional gene expression data, ForestSubtype. ForestSubtype first adopts the parallel RF and the priori knowledge of cancer subtype to train a module and extract significant candidate features. Second, ForestSubtype uses a random forest as the base module and ten parallel random forests to compute each feature weight and rank them separately. Then, the intersection of the features with the larger weights output by the ten parallel random forests is taken as our subsequent candidate features. Third, ForestSubtype uses an autoencoder to condenses the selected features into a two-dimensional data. Fourth, ForestSubtype utilizes k-means++ to obtain new cancer subtype identification results. In this paper, the breast cancer gene expression data obtained from The Cancer Genome Atlas are used for training and validation, and an independent breast cancer dataset from the Molecular Taxonomy of Breast Cancer International Consortium is used for testing. Additionally, we use two other cancer datasets for validating the generalizability of ForestSubtype. ForestSubtype outperforms the other two methods in terms of the distribution of clusters, internal and external metric results. The open-source code is available at https://github.com/lffyd/ForestSubtype. Conclusions: Our work shows that the combination of high-dimensional gene expression data and parallel random forests and autoencoder, guided by a priori knowledge, can identify new subtypes more effectively than existing methods of cancer subtype classification. [ABSTRACT FROM AUTHOR]

Simple Summary: Neurofibromatosis Type 1 is an inherited tumour predisposition syndrome with a varied clinical phenotype. Long-term monitoring through imaging is inconsistent and varies in high- and low-income countries. Implementation of a clinical practice guideline through a multidisciplinary clinic is instrumental to the care of adult Neurofibromatosis Type 1 patients. This systematic review aims to evaluate the association between a country's socioeconomic status and diagnostic modalities and strategies used for adult Neurofibromatosis Type 1 patients. Our results show multiple imaging modalities are used in high-income countries; however, there is limited use in low-income countries. The two most common diagnostic modalities used in developed countries are WB MRI and FDG PET/CT. Background: Neurofibromatosis Type 1 is an autosomal dominant tumour-predisposition condition commonly diagnosed in childhood and fully penetrant by adulthood. Long-term monitoring through imaging is inconsistent and varies between high- and low-income countries. Implementation of a clinical practice guideline through a multidisciplinary clinic is instrumental to the care of adult Neurofibromatosis Type 1 patients. We aim to systematically review international diagnostic modalities and strategies to evaluate any association between a country's socioeconomic status and diagnostic modalities or strategies used for Neurofibromatosis Type 1 patients. Methods: We searched PubMed, Embase, Web of Science, and Cochrane. Relevant clinical information on the surveillance of adult Neurofibromatosis Type 1 patients worldwide was reviewed, extracted, and synthesised. Results: We identified 51 papers reporting on 7724 individuals. Multiple imaging modalities are actively employed in high-income and upper-middle-income countries for surveying adult Neurofibromatosis Type 1 patients. We did not find any relevant papers from low- and middle-income countries. Conclusions: This systematic review suggests that there is robust data on diagnostic modalities for adult Neurofibromatosis Type 1 patients in high-income countries, but not for low- and middle-income countries. There is a lack of data on consolidated diagnostic strategies from both high- and low-income countries. Efforts should be made to publish data on usual clinical practice in low- and middle-income countries to develop clinical practice guidelines describing best medical practice to fit a local context. [ABSTRACT FROM AUTHOR]

Gene expression is highly impacted by the environment and can be reflective of past events that affected developmental processes. It is therefore expected that gene expression can serve as a signal of a current or future phenotypic traits. In this paper we identify sets of genes, which we call Prognostic Transcriptomic Biomarkers (PTBs), that can predict firmness in Malus domestica (apple) fruits. In apples, all individuals of a cultivar are clones, and differences in fruit quality are due to the environment. The apples transcriptome responds to these differences in environment, which makes PTBs an attractive predictor of future fruit quality. PTBs have the potential to enhance supply chain efficiency, reduce crop loss, and provide higher and more consistent quality for consumers. However, several questions must be addressed. In this paper we answer the question of which of two common modeling approaches, Random Forest or ElasticNet, outperforms the other. We answer if PTBs with few genes are efficient at predicting traits. This is important because we need few genes to perform qPCR, and we answer the question if qPCR is a cost-effective assay as input for PTBs modeled using high-throughput RNA-seq. To do this, we conducted a pilot study using fruit texture in the 'Gala' variety of apples across several postharvest storage regiments. Fruit texture in 'Gala' apples is highly controllable by post-harvest treatments and is therefore a good candidate to explore the use of PTBs. We find that the RandomForest model is more consistent than an ElasticNet model and is predictive of firmness (r2 = 0.78) with as few as 15 genes. We also show that qPCR is reasonably consistent with RNA-seq in a follow up experiment. Results are promising for PTBs, yet more work is needed to ensure that PTBs are robust across various environmental conditions and storage treatments. [ABSTRACT FROM AUTHOR]

Down syndrome is a well-studied aneuploidy condition in humans, which is associated with various disease phenotypes including cardiovascular, neurological, haematological and immunological disease processes. This review paper aims to discuss the research conducted on gene expression studies during fetal development. A descriptive review was conducted, encompassing all papers published on the PubMed database between September 1960 and September 2022. We found that in amniotic fluid, certain genes such as COL6A1 and DSCR1 were found to be affected, resulting in phenotypical craniofacial changes. Additionally, other genes such as GSTT1, CLIC6, ITGB2, C21orf67, C21orf86 and RUNX1 were also identified to be affected in the amniotic fluid. In the placenta, dysregulation of genes like MEST, SNF1LK and LOX was observed, which in turn affected nervous system development. In the brain, dysregulation of genes DYRK1A, DNMT3L, DNMT3B, TBX1, olig2 and AQP4 has been shown to contribute to intellectual disability. In the cardiac tissues, dysregulated expression of genes GART, ETS2 and ERG was found to cause abnormalities. Furthermore, dysregulation of XIST, RUNX1, SON, ERG and STAT1 was observed, contributing to myeloproliferative disorders. Understanding the differential expression of genes provides insights into the genetic consequences of DS. A better understanding of these processes could potentially pave the way for the development of genetic and pharmacological therapies. [ABSTRACT FROM AUTHOR]

During its first decade of life, Physiological Reports has become a home for well‐conceived and rigorously performed exercise physiology and metabolism studies. The breadth of research within this area is impressive, covering exercise‐induced increases in skeletal muscle gene expression to the effects of exercise on the gut microbiome. The purpose of the current review is to highlight some of the impactful exercise physiology and metabolism papers published in the journal and to look ahead to what areas exercise physiology publications might address in the next 10 years. [ABSTRACT FROM AUTHOR]

Cancer is a leading cause of death globally. The majority of cancer cases are only diagnosed in the late stages of cancer due to the use of conventional methods. This reduces the chance of survival for cancer patients. Therefore, early detection consequently followed by early diagnoses are important tasks in cancer research. Gene expression microarray technology has been applied to detect and diagnose most types of cancers in their early stages and has gained encouraging results. In this paper, we address the problem of classifying cancer based on gene expression for handling the class imbalance problem and the curse of dimensionality. The oversampling technique is utilized to overcome this problem by adding synthetic samples. Another common issue related to the gene expression dataset addressed in this paper is the curse of dimensionality. This problem is addressed by applying chi-square and information gain feature selection techniques. After applying these techniques individually, we proposed a method to select the most significant genes by combining those two techniques (CHiS and IG). We investigated the effect of these techniques individually and in combination. Four benchmarking biomedical datasets (Leukemia-subtypes, Leukemia-ALLAML, Colon, and CuMiDa) were used. The experimental results reveal that the oversampling techniques improve the results in most cases. Additionally, the performance of the proposed feature selection technique outperforms individual techniques in nearly all cases. In addition, this study provides an empirical study for evaluating several oversampling techniques along with ensemble-based learning. The experimental results also reveal that SVM-SMOTE, along with the random forests classifier, achieved the highest results, with a reporting accuracy of 100%. The obtained results surpass the findings in the existing literature as well. [ABSTRACT FROM AUTHOR]

Deep learning (DL) plays a critical role in processing and converting data into knowledge and decisions. DL technologies have been applied in a variety of applications, including image, video, and genome sequence analysis. In deep learning the most widely utilized architecture is Convolutional Neural Networks (CNN) are taught discriminatory traits in a supervised environment. In comparison to other classic neural networks, CNN makes use of a limited number of artificial neurons, therefore it is ideal for the recognition and processing of wheat gene sequences. Wheat is an essential crop of cereals for people around the world. Wheat Genotypes identification has an impact on the possible development of many countries in the agricultural sector. In quantitative genetics prediction of genetic values is a central issue. Wheat is an allohexaploid (AABBDD) with three distinct genomes. The sizes of the wheat genome are quite large compared to many other kinds and the availability of a diversity of genetic knowledge and normal structure at breeding lines of wheat, Therefore, genome sequence approaches based on techniques of Artificial Intelligence (AI) are necessary. This paper focuses on using the Wheat genome sequence will assist wheat producers in making better use of their genetic resources andmanaging genetic variation in their breeding program, as well as propose a novel model based on deep learning for offering a fundamental overview of genomic prediction theory and current constraints. In this paper, the hyperparameters of the network are optimized in the CNN to decrease the requirement formanual search and enhance network performance using a new proposed model built on an optimization algorithm and Convolutional Neural Networks (CNN). [ABSTRACT FROM AUTHOR]

Simple Summary: This paper delves into the issue of metastatic endometrial cancer (EC), which significantly impacts treatment success and overall survival rates. The study explores various factors contributing to metastasis, including the molecular profile of EC, hormone activity (like estrogen and prolactin), and pro-inflammatory adipocytokines. It also investigates how altered microRNA expression affects gene regulation linked to the dissemination of the cancer. The paper highlights the importance of imaging techniques, particularly transvaginal ultrasound with tumor-free distance (uTFD), in detecting metastases. Additionally, it discusses how diagnostic and therapeutic methods can influence the spread of EC, with hysteroscopy potentially increasing risk in advanced stages and laparoscopic hysterectomy being safer if performed with care. This research could improve our understanding of EC and guide better diagnostic and treatment strategies. The presence of metastatic endometrial cancer (EC) is a key problem in treatment failure associated with reduced overall survival rates. The most common metastatic location is the pelvic lymph nodes, and the least common is the brain. The presence of metastasis depends on many factors, including the molecular profile of cancer (according to the TCGA—Genome Atlas), the activity of certain hormones (estrogen, prolactin), and pro-inflammatory adipocytokines. Additionally, an altered expression of microRNAs affecting the regulation of numerous genes is also related to the spread of cancer. This paper also discusses the value of imaging methods in detecting metastases; the primary role is attributed to the standard transvaginal USG with the tumor-free distance (uTFD) option. The influence of diagnostic and therapeutic methods on EC spread is also described. Hysteroscopy, according to the analysis discussed above, may increase the risk of metastases through a fluid medium, mainly performed in advanced stages of EC. According to another analysis, laparoscopic hysterectomy performed with particular attention to avoiding risky procedures (trocar flushing, tissue traumatization, preserving a margin of normal tissue) was not found to increase the risk of EC dissemination. [ABSTRACT FROM AUTHOR]