Online Search Tool Research Articles

Clinical value and potential circulating of miR-99a as tumor suppressor biomarker in serum of oral squamous cell carcinoma and erosive atrophic lichen planus

ObjectivesOral squamous cell carcinoma (OSCC) is the most common type of oral neoplasms that consist of more over 90% of oral cancers. It was demonstrated that erosive atrophic oral lichen planus (OLP) has potential of malignancy transformation into OSCC. The microRNAs are non-coding regulator sequences involved in cancer process. The miR-99a involve in growth, proliferation, migration, invasion, and metastasis of tumor cells. Therefore, we evaluated miR-99a expression in serum of OSCC and erosive atrophic OLP patients in comparison to healthy control individuals to more investigate about level of miR-99a expression in potential premalignant disorder (erosive atrophic OLP) in comparison to malignant transformation form (OSCC). Gene ontology (GO) and pathway analyses were performed to better understand the importance of miR-99a in OSCC. Materials and methodsIn this cross-sectional study, total 90 serum samples from OSCC patients (n = 30), erosive atrophic OLP (n = 30) and healthy control individuals (n = 30) were collected, and then evaluated for miR-99a expression by qPCR. Pathway analysis and protein-protein interaction were done using STRING (v: 12.0), and (GO) terms and related genes were extracted from the GO online search tool. The statistical analysis was evaluated by Kruskal Wallis, Chi-Square, Kruskal Wallis, Spearman and Mann-Whitney tests. The p-value less than 0.05 was considered statistically significant. ResultsmiR-99a expression down regulated in OSCC in comparison to erosive atrophic OLP and control groups (p < 0.05). The miR-99a up regulated in grade I more than grades II and III (p < 0.05). We showed upregulation of miR-99a in early stage more than advanced stage (p < 0.05). Expression of miR-99a reduced accordance to the increasing of tumor size and lymph involvement levels (p < 0.05). The 165 determined targets were classified into three domains. The most significant enrichment in biological processes, cellular components, and molecular functions was in the cellular nitrogen compound biosynthetic process, cytosolic ribosome, and protein binding, respectively. ConclusionsWe highlighted tumor suppressive role of miR-99a in OSCC patients. It seems that miR-99a can be considered a valuable biomarker for the early diagnosis of erosive atrophic OLP before transformation. Clinical relevanceOur results may help to better understand the prognostic factor for oral squamous cell carcinoma to evaluate survival and subsequent tumor development. And it may also help to understand the pathogenesis of OSCC.

The development of Japanese-English and English-Japanese parallel corpus, including search system and its utilisation

Parallel corpora play a central role in translation studies, contrastive linguistics, bilingual lexicography and language teaching/learning, facilitating the comparison of linguistic features across languages. But it is challenging to construct a parallel corpus and there are few of them. Also, they can quickly become outdated and unusable. Professor Yasunori Nishina, Faculty of Global Communication, Kobe Gakuin University, Japan, is an expert in applied translation, corpus linguistics and applied linguistics working to develop a website for searching Japanese-English and English-Japanese parallel corpora. He is revitalising an existing unusable, unsearchable corpus with assistance from Lago NLP. He has a keen focus on design as he wants to ensure diversity of genres and translation directions and, in a world first, is incorporating the ability to analyse parallel corpora. The tool that Nishina and Lago NLP are developing with support from the JSPS KAKENHI grant number 20K00692 (and 23K00599 from 2023) is called Parallel Link. Nishina will also collaborate with a researcher at the University of Oxford, UK, where experts who developed the Japanese corpus online search tool are based. The University has established a collaborative relationship with the National Institute for Japanese Language and Linguistics (NINJAL), which is the centre for Japanese language research, and has carried out joint projects of the Oxford NINJAL Corpus of Old Japanese (ONCOJ). Nishina has completed the development of version 1.20 of Parallel Link and intends to develop it to version 2.0 in the coming years.

UniCarb-DB: An MS/MS Experimental Glycomic Fragmentation Database.

Glycosylation is a unique posttranslational modification that dynamically shapes the surface of cells. Glycans attached to proteins or lipids in a cell or tissue are studied as a whole and collectively designated as a glycome. UniCarb-DB is a glycomic spectral library of tandem mass spectrometry (MS/MS) fragment data. The current version of the database consists of over 1500 entries and over 1000 unique structures. Each entry contains parent ion information with associated MS/MS spectra, metadata about the original publication, experimental conditions, and biological origin. Each structure is also associated with the GlyTouCan glycan structure repository allowing easy access to other glycomic resources. The database can be directly utilized by mass spectrometry (MS) experimentalists through the conversion of data generated by MS into structural information. Flexible online search tools along with a downloadable version of the database are easily incorporated in either commercial or open-access MS software. This chapter highlights UniCarb-DB online search tool to browse differences of isomeric structures between spectra, a peak matching search between user-generated MS/MS spectra and spectra stored in UniCarb-DB and more advanced MS tools for combined quantitative and qualitative glycomics.

Exploring the health information-seeking practices of breast cancer patients in a middle-income country with a diverse ethnic population: a cross-sectional investigation.

Seeking health information is an important step for cancer patients to understand their condition and facilitate treatment. It also helps them deal with the unknown and aid in recovery. Therefore, it is vital to understand the factors that drive health information-seeking behavior. This study aims to achieve that objective in a localized context by surveying 421 breast cancer patients in an urban teaching hospital. The patients were presented with a 5-point questionnaire that explored their demography, health status, information-seeking behavior, and literacy level. The prevalence of health information-seeking initiatives reported was 60%. Patients with higher education (OR 3.31; 95% CI (1.39-7.87), p = 0.01), having their own business or were self-employed (OR 4.68; 95% CI (1.03-21.24), p = 0.046), and in a Medium 40 (M40) income level (OR 2.31; 95% CI (1.09-4.88), p = 0.03) and Top 20 (T20) level were more likely to seek health information. The mean e-Health Literacy Score (eHEALS) was 28.01 ± 5.0, with healthcare professionals having the highest level of trust (mean 4.22 ± 0.79) and most useful resource score (mean 4.21 ± 0.78). Even though Google was the most popular online search tool used by respondents, most of them seldom (23.77%) or had never (34.34%) discussed the online information they found with healthcare professionals. In conclusion, it is still best for patients to appraise the sought-after information with experts to avoid misinformation and treatment delay.

Cuproptosis-related gene SLC31A1 expression correlates with the prognosis and tumor immune microenvironment in glioma

Cuproptosis is a newly discovered form of cell death. It is regulated by a string of genes. The genes are identified to influence the tumor progression, but in glioma, the cuproptosis-related genes are little studied. The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) were used to screen for SLC31A1 gene expression in glioma and healthy tissue samples. The results were validated using the Gene Expression Omnibus (GEO) and quantitative real-time polymerase chain reaction (qPCR). The Human Protein Atlas (HPA) and the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to validate our results at the protein level. Multivariable analysis and Kaplan–Meier survival curves were used to examine the relationship among SLC31A1 gene expression, clinical parameters, and survival rates. The online Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) was used to find the genes and proteins that correlate to SLC31A1. The immune infiltration analysis was performed using the Tumor Immune Estimation Resource (TIMER) databases. Small interfering RNA was used to knock down the SLC31A1 expression, and the cell proliferation, apoptosis, and migration were analyzed using cell counting kit-8, flow cytometry, and transwell. The glioma patients have higher SLC31A1 expression levels, which increase as the World Health Organization (WHO) grade escalates. The survival analysis illustrates that the SLC31A1 gene expression negatively correlates with overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS). The immune infiltration analysis shows the SLC31A1 gene positively correlates with T helper 2 (Th2) cells, macrophages, and M2-type macrophages and negatively correlates with plasmacytoid dendritic cells (pDCs), natural killer (NK) CD56bright cells, and CD8 T cells. The in vitro KD experiment shows the SLC31A1 knockdown depressed the glioma cell proliferation and migration and promoted the apoptosis rate. The SLC31A1 gene expression can shorten the survival time of glioma patients. In vitro study shows that SLC31A1 can promote cell proliferation, and migration, and depress the cell apoptosis of glioma cells. It also can promote the formation of a tumor-suppressive microenvironment.

Prediction of cancer nanomedicines self-assembled from meta-synergistic drug pairs

Combination therapy is widely used in cancer medicine due to the benefits of drug synergy and the reduction of acquired resistance. To minimize emergent toxicities, nanomedicines containing drug combinations are being developed, and they have shown encouraging results. However, developing multi-drug loaded nanoparticles is highly complex and lacks predictability. Previously, it was shown that single drugs can self-assemble with near-infrared dye, IR783, to form cancer-targeted nanoparticles. A structure-based predictive model showed that only 4% of the drug space self-assembles with IR783. Here, we mapped the self-assembly outcomes of 77 small molecule drugs and drug pairs with IR783. We found that the small molecule drug space can be divided into five types, and type-1 drugs self-assemble with three out of four possible drug types that do not form stable nanoparticles. To predict the self-assembly outcome of any drug pair, we developed a machine learning model based on decision trees, which was trained and tested with F1-scores of 89.3% and 87.2%, respectively. We used literature text mining to capture drug pairs with biological synergy together with synergistic chemical self-assembly and generated a database with 1985 drug pairs for 70 cancers. We developed an online search tool to identify cancer-specific, meta-synergistic drug pairs (both chemical and biological synergism) and validated three different pairs in vitro. Lastly, we discovered a novel meta-synergistic pair, bortezomib-cabozantinib, which formed stable nanoparticles with improved biodistribution, efficacy, and reduced toxicity, even over single drugs, in an in vivo model of head and neck cancer.

(548) NIH Funding Trends for Men's and Women's Urologic Conditions

Abstract Introduction Existing literature reports a general trend of increasing National Institutes of Health (NIH) funding for surgeon-scientists in America and shows that urology has not benefited from this trend. NIH funding for urologists continues to lag behind that of our peers in other surgical specialties. Between 2010-2019 urology departments received the second-lowest amount of NIH funding of all surgical specialties, only above plastic surgery. The literature also shows that NIH awards significantly less money to male cancer research (i.e., prostate cancer) than female cancer research (i.e., breast cancer). We sought to explore further gender-specific grant variation within NIH urologic funding by exploring dollars awarded to benign gender-specific non-cancer topics of urologic research. We hypothesized that an NIH funding disparity would exist between men’s health urologic research and research devoted to women’s health urologic issues. Objective To explore NIH funding trends for men's and women's urologic health conditions via the NIH Reporter database Methods We used the publicly available NIH Research Portfolio Online Reporting Tools Expenditures and Results (NIH RePORTER) to perform our data collection. NIH RePORTER is an online search tool of the repository of NIH-funded research projects and is linked to publications, patents and clinical trials resulting from NIH funding. Data was queried for a ten-year period between 2012-2021. We used uniform search parameters including “Department Type: urology” to filter for publications from departments of urology, “Funding Mechanism: research project grant” to eliminate R&amp;D, and “Award Type: new” to capture only first-time awards in our search period. All authors were included in our search, which encompassed both trainees and non-trainees independent of Activity Code. We selected four women’s urological health issues and four men’s urological health issues to guide a keyword search. Our women’s urological health issues included overactive bladder, incontinence, and pelvic organ prolapse. In addition, we queried the NIH Spending Category of “Women’s Health”. Our men’s urological health issues include erectile dysfunction, Peyronie's disease, hypogonadism and male stress incontinence. Search terms related to these health conditions were used to query project title, projects terms and project abstracts in the NIH RePORTER. Results Results of our research findings are summarized in Table 1. Of the 12 projects identified that exclusively investigate either a men’s health condition or a women’s health condition, 7 focused on men’s health and 5 on women’s health. NIH spending on women’s health issues exceeded that for men's health conditions by $833,964, a 51% difference, even though fewer projects were identified related to women’s health conditions. Overall, fewer gender-exclusive projects were found than expected. For example, incontinence projects frequently included both male and female-bodied participants. Conclusions NIH appears to devote substantially less funding for investigating benign urologic men’s health issues than benign urologic women’s health issues. Further examination of this funding gap is warranted, and if confirmed it would be prudent to improve NIH urologic funding in general and men’s health research funding specifically. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Coloplast.

Mousepost 2.0, a major expansion of the resource.

The Mousepost 1.0 online search tool, launched in 2017, allowed to search for variations in all protein-coding gene sequences of 36 sequenced mouse inbred strains, compared to the reference strain C57BL/6J, which could be linked to strain-specific phenotypes and modifier effects. Because recently these genome sequences have been significantly updated and sequences of 16 extra strains added by the Mouse Genomes Project, a profound update, correction and expansion of the Mousepost 1.0 database has been performed and is reported here. Moreover, we have added a new class of protein disturbing sequence polymorphisms (besides stop codon losses, stop codon gains, small insertions and deletions, and missense mutations), namely start codon mutations. The current version, Mousepost 2.0 (https://mousepost.be), therefore is a significantly updated and invaluable tool available to the community and is described here and foreseen by multiple examples.

Using the Baidu index to understand Chinese interest in thyroid related diseases

Common thyroid diseases are hyperthyroidism, hypothyroidism, thyroiditis, thyroid tumor and so on. Baidu is currently the most widely used online search tool in China, has developed an internet search trends collection and analysis tool called the Baidu Index. The aim of the present study was to understand the trend and characteristics of public’s online attention to thyroid diseases, and to explore the value of Baidu Index in monitoring online retrieval behavior of thyroid-related information. Taking the period from January 1, 2011 to December 31, 2019 as the time range into consideration, we used the big data analysis tool of Baidu Index and took “thyroid nodules”, “thyroid cancer”, “thyroiditis” “hyperthyroidism” and “hypothyroidism” as the keywords, the data of “search index” and “media index” were recorded on a weekly basis, and all information were aggregated into quarterly and annual to generate the final data which was carried out for secondary analysis. Pearson correlation analysis was used to analyze the correlation between the search index of keywords and the year. One-way Analysis of Variance was used to analyze the differences between search index and media index. Among the five keywords, thyroid nodule search index had the highest growth rate (640%), followed by thyroid cancer (298%). The media’s attention to thyroid diseases had been declining year by year. Unlike the public’s attention, the media index of hyperthyroidism was significantly higher than other keywords. Over the past nine years, the public's attention to thyroid-related diseases has been increasing gradually. Baidu Index is an effective tool to track the health information query behavior of Chinese internet users, which can provide a cost-effective supplement to traditional monitoring system.

Cuproptosis-related gene FDX1 expression correlates with the prognosis and tumor immune microenvironment in clear cell renal cell carcinoma.

BackgroundCuproptosis, a newly discovered form of cell death, is regulated by protein lipoylation and is related to mitochondrial metabolism. However, further research is needed to determine how the cuproptosis-related gene ferredoxin 1 (FDX1) affects the tumor immune response and its prognostic significance in clear cell renal cell carcinoma (ccRCC).MethodsThe Cancer Genome Atlas was used to screen for FDX1 gene expression in ccRCC and healthy tissue samples. The results were validated using the Gene Expression Omnibus and the Human Protein Atlas. Multivariable analysis and Kaplan-Meier survival curves were used to examine the relationship between FDX1 gene expression, clinicopathological parameters, and overall survival (OS). The protein network containing FDX1 gene interaction was constructed using the online Search Tool for the Retrieval of Interacting Genes/Proteins. The relationship between FDX1 gene expression and immune cell infiltration in ccRCC was examined using Gene Ontology, gene set enrichment analysis (GSEA), and a single-sample GSEA. Using the Gene Expression Profiling Interactive Analysis and Tumor Immune Estimation Resource databases, we investigated the relationship between FDX1 gene expression, the degree of immune cell infiltration, and the corresponding gene marker sets.ResultsccRCC samples had significantly (p < 0.05) lower FDX1 gene expression levels than normal tissue samples. Lower FDX1 gene expression levels were strongly associated with higher cancer grades and more advanced tumor–node–metastasis stages. The findings of multivariate and univariate analyses illustrated that the OS in ccRCC patients with low FDX1 expression is shorter than in patients with high FDX1 expression (p < 0.05). Ferredoxin reductase and CYP11A1 are key proteins interacting with the FDX1 gene, and ccRCC with an FDX1 enzyme defect was associated with a low number of invading immune cells and their corresponding marker.ConclusionIn ccRCC, decreased FDX1 expression was linked to disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration.

Patients are Most Interested in Which Hip Arthroplasty Approach? A 15-year Google Trends Analysis

BackgroundThe purpose of this analysis was to assess the public interest in total hip arthroplasty (THA) based on approach by analyzing Google Trends online search volume trends between 2007 and 2021. MethodsData were obtained by querying the Google Trends online search tool for key terms and phrases relating to anterior, posterior, lateral, and minimally invasive approaches to THA. Data from January 2007 to December 2021 were utilized. Relative search volume (RSV) was generated for each THA approach group based on historical search volume trends in the United States. ResultsOver the 15-year period, Google Trends Search Data demonstrated a statistically significant increase (P < .001) in the RSV for all 4 major hip arthroplasty approaches. The growth in public interest for anterior hip arthroplasty was significantly greater than the growth for posterior (P = .02) and minimally invasive hip arthroplasty (P = .02). The difference in RSV growth between lateral and anterior approaches was not significant (P = .88). The average RSV for anterior hip arthroplasty was 59.0, which was significantly greater than the average RSV of all other groups. ConclusionsThe anterior approach to hip arthroplasty has demonstrated a consistent and statistically significant increase in RSV over the past 15 years that has outpaced the increases observed in the posterior and minimally invasive approaches. Despite the increase in public awareness and interest for anterior approach hip arthroplasty, it is yet to demonstrate any long-term clinical benefits over other approaches.

Bioinformatics-based identification of key genes and pathways associated with colorectal cancer diagnosis, treatment, and prognosis.

Colorectal cancer (CRC) is known to display a high risk of metastasis and recurrence. The main objective of our investigation was to shed more light on CRC pathogenesis by screening CRC datasets for the identification of key genes and signaling pathways, possibly leading to new approaches for the diagnosis and treatment of CRC. We downloaded the colorectal cancer datasets from the Gene Expression Omnibus (GEO) database site. We used GEO2R to screen for differentially expressed genes (DEGs) of which those with a fold change >1 were considered as up-regulated and those with a fold change <-1 were considered as down-regulated on the basis of a P < .05. “Gene ontology (GO)” and “Kyoto Encyclopedia of Genes and Genomes (KEGG)” data were analyzed by the “DAVID” software. The online search tool “STRING” was used to search for interacting genes or proteins and we used Cytoscape (v3.8.0) to generate a PPI network map and to identify key genes. Finally, survival analysis and stage mapping of key genes were performed using “GEPIA” with the aim of elucidating their potential impact on CRC. Our study revealed 120 intersecting genes of which 55 were up- and 65 were downregulated, respectively. GO analysis revealed that these genes were involved in cell proliferation, exosome secretion, G2/M transition, cytosol, protein binding, and protein kinase activity. KEGG pathway analysis showed that these genes were involved in cell cycle and mineral absorption. The Cytoscape PPI map showed 17 nodes and 262 edges, and 10 hub genes were identified by top 10 degrees. Survival analysis demonstrated that the AURKA, CCNB1, and CCNA2 genes were strongly associated with the survival rate of CRC patients. In addition, CCNB1, CCNA2, CDK1, CKS2, MAD2L1, and DLGAP5 could be correlated to pathological CRC staging. In this research, we identified key genes that may explain the molecular mechanism of occurrence and progression of CRC but may also contribute to an improvement in the clinical staging and prognosis of CRC patients.

FECH Expression Correlates with the Prognosis and Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is, by far, the most prevalent and fatal kind of kidney cancer. Ferrochelatase (FECH) is an enzyme that performs a significant function in the onset and progression of many distinct kinds of malignant tumors. Nevertheless, its predictive usefulness in renal clear cell carcinoma (RCC) has not yet been fully investigated. FECH expression in ccRCC and healthy adjoining tissues was primarily screened utilizing data sourced from The Cancer Genome Atlas (TCGA) and subsequently validated using data from an independent cohort derived from the Gene Expression Omnibus (GEO) and the Human Protein Atlas HPA databases. The relationship among FECH expression, clinicopathological parameters, and overall survival (OS) was assessed utilizing multivariate analysis and Kaplan-Meier survival curves. Additionally, the protein networks with FECH interaction were constructed with the aid of the online Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Gene ontology (GO) analysis, and gene set enrichment analysis (GSEA) were conducted based on TCGA data, and a single-sample GSEA was utilized to explore the link between FECH expression and the infiltration status of immune cells in the tumor. The Gene Expression Profiling Interactive Analysis (GEPIA) and TIMER databases were utilized to investigate the relationships of FECH expression with the infiltrating immune cells and the matching gene marker sets. FECH expression was shown to be substantially lowered in ccRCC tumors as opposed to that observed in normal tissues (p < 0.05). Lower levels of FECH expression were shown to have a strong association with higher grades of cancer and more advanced TNM stages. The findings of multivariate and univariate analyses illustrated that the OS in patients with ccRCC with low FECH expression is shorter in contrast with that in the high FECH expression group (p < 0.05). It was discovered that CPOX and frataxin are key proteins that interact with FECH. ccRCC with FECH deficiency was linked to the lack of infiltrating immune cells and their respective marker sets, which included CD4+ T cells. In ccRCC, decreased FECH expression was linked to disease progression, unfavorable prognosis, and impaired immune cell infiltration.

Identification of Hub Genes and Therapeutic Agents for IgA Nephropathy Through Bioinformatics Analysis and Experimental Validation.

BackgroundIgA nephropathy (IgAN) is the most common primary glomerular disease and the leading cause of the end-stage renal disease in the world. The pathogenesis of IgAN has not been well elucidated, and yet treatment is limited. High-throughput microarray has been applied for elucidating molecular biomarkers and potential mechanisms involved in IgAN. This study aimed to identify the potential key genes and therapeutics associated with IgAN using integrative bioinformatics and transcriptome-based computational drug repurposing approach.MethodsThree datasets of mRNA expression profile were obtained from the gene expression omnibus database and differentially expressed genes (DEGs) between IgAN glomeruli and normal tissue were identified by integrated analysis. Gene ontology and pathway enrichment analyses of the DEGs were performed by R software, and protein-protein interaction networks were constructed using the STRING online search tool. External dataset and immunohistochemical assessment of kidney biopsy specimens were used for hub gene validation. Potential compounds for IgAN therapy were obtained by Connectivity Map (CMap) analysis and preliminarily verified in vitro. Stimulated human mesangial cells were collected for cell proliferation and cell cycle analysis using cell counting kit 8 and flow cytometry, respectively.Results134 DEGs genes were differentially expressed across kidney transcriptomic data from IgAN patients and healthy living donors. Enrichment analysis showed that the glomerular compartments underwent a wide range of interesting pathological changes during kidney injury, focused on anion transmembrane transporter activity and protein digestion and absorption mostly. Hub genes (ITGB2, FCER1G, CSF1R) were identified and verified to be significantly upregulated in IgAN patients, and associated with severity of renal lesions. Computational drug repurposing with the CMap identified tetrandrine as a candidate treatment to reverse IgAN hub gene expression. Tetrandrine administration significantly reversed mesangial cell proliferation and cell cycle transition.ConclusionThe identification of DEGs and related therapeutic strategies of IgAN through this integrated bioinformatics analysis provides a valuable resource of therapeutic targets and agents of IgAN. Especially, our findings suggest that tetrandrine might be beneficial for IgAN, which deserves future research.

Prediction of Differentially Expressed Genes and a Diagnostic Signature of Preeclampsia via Integrated Bioinformatics Analysis

Background Preeclampsia (PE), which has a high incidence rate worldwide, is a potentially dangerous syndrome to pregnant women and newborns. However, the exact mechanism of its pathogenesis is still unclear. In this study, we used bioinformatics analysis to identify hub genes, establish a logistic model, and study immune cell infiltration to clarify the physiopathogenesis of PE. Methods We downloaded the GSE75010 and GSE10588 datasets from the GEO database and performed weighted gene coexpression network analysis (WGCNA) as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The online search tool for the retrieval of interacting genes and Cytoscape software were used to identify hub genes, which were then used to establish a logistic model. We also analyzed immune cell infiltration. Finally, we verified the expression of the genes included in the predictive model via RT-PCR. Results A total of 100 and 212 differently expressed genes were identified in the GSE75010 and GSE10588 datasets, respectively, and after overlapping with WGCNA results, 17 genes were identified. KEGG and GO analyses further indicated the involvement of these genes in bioprocesses, such as gonadotropin secretion, immune cell infiltration, and the SMAD and MAPK pathways. Additionally, protein-protein interaction network analysis identified 10 hub genes, six (FLT1, FLNB, FSTL3, INHA, TREM1, and SLCO4A1) of which were used to establish a logistic model for PE. RT-PCR analysis also confirmed that, except FSTL3, these genes were upregulated in PE. Our results also indicated that macrophages played the most important role in immune cell infiltration in PE. Conclusion This study identified 10 hub genes in PE and used 6 of them to establish a logistic model and also analyzed immune cell infiltration. These findings may enhance the understanding of PE and enable the identification of potential therapeutic targets for PE.

Diagnostic and prognostic factors in patients with prostate cancer: a systematic review

ObjectivesAs part of the PIONEER Consortium objectives, we have explored which diagnostic and prognostic factors (DPFs) are available in relation to our previously defined clinician and patient-reported outcomes for prostate...

Based on Network Pharmacology Tools to Investigate the Mechanism of Tripterygium wilfordii Against IgA Nephropathy.

Background: Immunoglobulin A nephropathy (IgAN) is the most common primary glomerular disease and poses a global major public health burden. The preparation of Tripterygium wilfordii Hook F (TwHF) is widely applied for treating patients with Immunoglobulin A nephropathy in China, while the molecular mechanisms remain unclear. This study aimed to verify the therapeutic mechanism of TwHF on IgAN by undertaking a holistic network pharmacology strategy in combination with in vitro and in vivo experiments.Methods: TwHF active ingredients and their targets were obtained via the Traditional Chinese Medicine Systems Pharmacology Database. The collection of IgAN-related target genes was collected from GeneCards and OMIM. TwHF-IgAN common targets were integrated and visualized by Cytoscape. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to determine the predominant molecular mechanisms and pathways of TwHF on the treatment of IgAN. The protein-protein interaction network was constructed by the STRING online search tool, and hub genes were identified using R software. The expression of hub gene and related signaling were evaluated in TwHF-treated mice through immunohistochemistry and western blot and further validated in human mesangial cells (HMCs). In addition, Cell counting kit 8 (CCK8) and flow cytometry were used to detect the effects of TwHF on cell proliferation and cell cycle of mesangial cells.Results: A total of 51 active ingredients were screened from TwHF and 61 overlapping targets related to IgAN were considered potential therapeutic targets, GO functions and KEGG analyses demonstrated that these genes were primarily associated with DNA-binding transcription factor binding, lipid and atherosclerosis pathway. Genes with higher degrees including AKT1, CXCL8, MMP9, PTGS2, CASP3, JUN are hub genes of TwHF against IgAN. Verification of hub gene JUN both in vitro and in vivo showed that TwHF significantly attenuated JUN phosphorylation in the kidneys of IgAN mice and aIgA1-activated HMCs, meanwhile suppressing HMCs proliferation and arresting G1-S cell cycle progression.Conclusion: Our research strengthened the mechanisms of TwHF in treating IgAN, inhibition of JUN activation may play a pivotal role in TwHF in alleviating IgAN renal injury.

Deploying an artificial intelligence-based online search tool to increase patients' access to and understanding of solid tumor gastrointestinal clinical trials.

The number and complexity of clinical trials is growing, making finding and accessing trials increasingly challenging. A key barrier to increasing recruitment efficiency is patients' low awareness of trials as an option. They rarely hear about trials from oncologists, unless these are based at a research center, which introduces trial population biases. Even if patients decide to search for trial information on their own, it is difficult for laypeople to understand. Trial search tools exist, but have multiple shortcomings: complex navigation, limited search functionality, data too complex for non-specialists, and next steps unclear. Access to trials via a novel trial search tool using technology, including artificial intelligence (AI), to restructure trial information and match patients to trials was the focus of this study. We focused on 6 gastrointestinal cancers for evaluating the search tool's AI model in which their trial information was restructured based on key eligibility differentiators identified. Research participants were recruited with the support of patient associations leveraging social media. They were asked to complete a survey evaluating an established tool and the novel tool to find trials relevant for them. They assessed aspects of the tools' usability on 5-level Likert scales. Survey respondents had a base level of awareness of trials, with patient associations and the internet as leading information sources. The novel tool made it easier to find trials, led to an improvement in ease of understanding information presented and provided more clarity on what the next steps towards enrollment would be. Overall, this led to higher patient satisfaction. Novel patient-focused tools can unlock trial access for all patients. Democratizing trial information will not only increase trial accrual, but also patient satisfaction while reducing disparities. This tool could also be of value for academic or community oncologists who face similar issues when navigating trials for patients.

Identification of key genes and pathways in mild and severe nonalcoholic fatty liver disease by integrative analysis

BackgroundThe global prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing. The pathogenesis of NAFLD is multifaceted, and the underlying mechanisms are elusive. We conducted data mining analysis to gain a better insight into the disease and to identify the hub genes associated with the progression of NAFLD. MethodsThe dataset GSE49541, containing the profile of 40 samples representing mild stages of NAFLD and 32 samples representing advanced stages of NAFLD, was acquired from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the R programming language. The Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database were used to perform the enrichment analysis and construct protein–protein interaction (PPI) networks, respectively. Subsequently, transcription factor networks and key modules were identified. The hub genes were validated in a mice model of high fat diet (HFD)-induced NAFLD and in cultured HepG2 cells by real-time quantitative PCR. ResultsBased on the GSE49541 dataset, 57 DEGs were selected and enriched in chemokine activity and cellular component, including the extracellular region. Twelve transcription factors associated with DEGs were indicated from PPI analysis. Upregulated expression of five hub genes (SOX9, CCL20, CXCL1, CD24, and CHST4), which were identified from the dataset, was also observed in the livers of HFD-induced NAFLD mice and in HepG2 cells exposed to palmitic acid or advanced glycation end products. ConclusionThe hub genes SOX9, CCL20, CXCL1, CD24, and CHST4 are involved in the aggravation of NAFLD. Our results offer new insights into the underlying mechanism of NAFLD progression.

Heat Shock Protein Beta 1 is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma.

BackgroundHepatocellular carcinoma (HCC) is one of the most serious malignancies. The main features of HCC are vascular invasion and drug resistance. Ferroptosis is a novel cell program that is involved in several diseases, such as cancer. Heat shock protein beta 1 (HSPB1) is a major component of heat shock proteins. A recent study showed that HSPB1 could be a new therapeutic target for colorectal cancer with 5-fluorouracil-acquired resistance. However, the functional role of HSPB1 in HCC remains unclear.AimThe aim of this study is to clarify HSPB1 expression in HCC and its potential therapeutic and prognostic value.MethodsWe collected data on HSPB1 expression levels in HCC and normal liver tissues from The Cancer Genome Atlas and Gene Expression Omnibus databases. We then validated it using immunohistochemistry (IHC). Receiver operating characteristic and Kaplan–Meier survival curves were used to investigate the role of HSPB1 in the prognosis analysis of HCC. Further, we used the online Search Tool for the Retrieval of Interacting Genes/Proteins website, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes to conduct enrichment analysis and identify the predictive signaling pathways. Meanwhile, we used the TIMER and GSVA package of R (v3.6.3) to analyze the association between HSPB1 and immunocyte infiltration.ResultsCompared to normal tissues, there was differential expression of HSPB1 in pan-cancers. HSPB1 expression was higher in HCC tissues than in normal tissues (p<0.05). There was an evident significant difference between HSPB1 mRNA levels and histologic grade, vascular invasion, and alpha-fetoprotein level (all p values<0.05). Univariate analysis indicated that HCC patients with high HSPB1 levels had shorter overall survival rates than those with low HSPB1 levels (p<0.05). MAPK14, HSPA8, MAPKAPK3, MAPKAPK5, and MAPKAPK2 are essential proteins that interact with HSPB1. There was a significant correlation between HSPB1 expression levels and immune cell infiltration, including CD4+ T cells (r=0.203, p<0.05).ConclusionHigh HSPB1 expression is closely associated with a worse prognosis in HCC patients, and HSPB1 may be a target of immunotherapy in HCC.