Comparative Analysis of Learning Curves in Robotic Versus Laparoscopic Cholecystectomy: A Systematic Review.

Robotic surgery has undergone much development and increased use over the years; it has offered many benefits for the operating surgeon compared to the more restrictive nature of conventional laparoscopic surgery (CLS) which is the current standard of care. However, to the best of our knowledge, no studies have attempted to draw a comparison between the two in terms of the cases required for the learning curve to be achieved. The systematic review was performed at Barts Cancer Institute. A search of Cochrane, PubMed and Embase was made on 15 March 2024. Screening and risk of bias were done by two reviewers. Screening was done via the eligibility criteria by two reviewers. Data collection was done using Excel (Microsoft® Corp., Redmond, USA) and information was double-checked by another reviewer and transferred into a tabulated format. Seventeen studies were included, with the learning curve reported in 14 studies. The cases required to achieve the learning curve for multiport robotic cholecystectomy (MRC) ranged from 16 to 134 and for single-site robotic cholecystectomy (SSRC), it ranged from 10 to over 102 cases. Conventional laparoscopic cholecystectomy (CLC) was from 7 to 200. The improvement in operating times was measured in very different ways and was reported in 10 of the 17 studies. The studies that were available had a high level of heterogeneity making it difficult for comparisons to be made between studies. Several studies included only one surgeon resulting in the sample size of surgeons being too small and vulnerable to bias. As robotic surgery is still relatively novel, higher-quality studies have to be made in order for more conclusive conclusions to be made on the benefits of the learning curve of MRC and SSRC.

Multiomics Analysis of the PHLDA Gene Family in Different Cancers and Their Clinical Prognostic Value.

The PHLDA (pleckstrin homology-like domain family) gene family is popularly known as a potential biomarker for cancer identification, and members of the PHLDA family have become considered potentially viable targets for cancer treatments. The PHLDA gene family consists of PHLDA1, PHLDA2, and PHLDA3. The predictive significance of PHLDA genes in cancer remains unclear. To determine the role of pleckstrin as a prognostic biomarker in human cancers, we conducted a systematic multiomics investigation. Through various survival analyses, pleckstrin expression was evaluated, and their predictive significance in human tumors was discovered using a variety of online platforms. By analyzing the protein-protein interactions, we also chose a collection of well-known functional protein partners for pleckstrin. Investigations were also carried out on the relationship between pleckstrins and other cancers regarding mutations and copy number alterations. The cumulative impact of pleckstrin and their associated genes on various cancers, Gene Ontology (GO), and pathway analyses were used for their evaluation. Thus, the expression profiles of PHLDA family members and their prognosis in various cancers may be revealed by this study. During this multiomics analysis, we found that among the PHLDA family, PHLDA1 may be a therapeutic target for several cancers, including kidney, colon, and brain cancer, while PHLDA2 can be a therapeutic target for cancers of the colon, esophagus, and pancreas. Additionally, PHLDA3 may be a useful therapeutic target for ovarian, renal, and gastric cancer.

In Silico and In Vitro Study of Isoquercitrin against Kidney Cancer and Inflammation by Triggering Potential Gene Targets.

Kidney cancer has emerged as a major medical problem in recent times. Multiple compounds are used to treat kidney cancer by triggering cancer-causing gene targets. For instance, isoquercitrin (quercetin-3-O-ß-d-glucopyranoside) is frequently present in fruits, vegetables, medicinal herbs, and foods and drinks made from plants. Our previous study predicted using protein-protein interaction (PPI) and molecular docking analysis that the isoquercitrin compound can control kidney cancer and inflammation by triggering potential gene targets of IGF1R, PIK3CA, IL6, and PTGS2. So, the present study is about further in silico and in vitro validation. We performed molecular dynamic (MD) simulation, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, cytotoxicity assay, and RT-PCR and qRT-PCR validation. According to the MD simulation (250 ns), we found that IGF1R, PIK3CA, and PTGS2, except for IL6 gene targets, show stable binding energy with a stable complex with isoquercitrin. We also performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the final targets to determine their regulatory functions and signaling pathways. Furthermore, we checked the cytotoxicity effect of isoquercitrin (IQ) and found that 5 µg/mL and 10 µg/mL doses showed higher cell viability in a normal kidney cell line (HEK 293) and also inversely showed an inhibition of cell growth at 35% and 45%, respectively, in the kidney cancer cell line (A498). Lastly, the RT-PCR and qRT-PCR findings showed a significant decrease in PTGS2, PIK3CA, and IGF1R gene expression, except for IL6 expression, following dose-dependent treatments with IQ. Thus, we can conclude that isoquercitrin inhibits the expression of PTGS2, PIK3CA, and IGF1R gene targets, which in turn controls kidney cancer and inflammation.

Butyrate's (a short-chain fatty acid) microbial synthesis, absorption, and preventive roles against colorectal and lung cancer.

Butyrate, a short-chain fatty acid (SCFA) produced by bacterial fermentation of fiber in the colon, is a source of energy for colonocytes. Butyrate is essential for improving gastrointestinal (GI) health since it helps colonocyte function, reduces inflammation, preserves the gut barrier, and fosters a balanced microbiome. Human colonic butyrate producers are Gram-positive firmicutes, which are phylogenetically varied. The two most prevalent subgroups are associated with Eubacterium rectale/Roseburia spp. and Faecalibacterium prausnitzii. Now, the mechanism for the production of butyrate from microbes is a very vital topic to know. In the present study, we discuss the genes encoding the core of the butyrate synthesis pathway and also discuss the butyryl-CoA:acetate CoA-transferase, instead of butyrate kinase, which usually appears to be the enzyme that completes the process. Recently, butyrate-producing microbes have been genetically modified by researchers to increase butyrate synthesis from microbes. The activity of butyrate as a histone deacetylase inhibitor (HDACi) has led to several clinical trials to assess its effectiveness as a potential cancer treatment. Among various significant roles, butyrate is the main energy source for intestinal epithelial cells, which helps maintain colonic homeostasis. Moreover, people with non-small-cell lung cancer (NSCLC) have distinct gut microbiota from healthy adults and frequently have dysbiosis of the butyrate-producing bacteria in their guts. So, with an emphasis on colon and lung cancer, this review also discusses how the microbiome is crucial in preventing the progression of certain cancers through butyrate production. Further studies should be performed to investigate the underlying mechanisms of how these specific butyrate-producing bacteria can control both colon and lung cancer progression and prognosis.

A Network Pharmacology and Molecular-Docking-Based Approach to Identify the Probable Targets of Short-Chain Fatty-Acid-Producing Microbial Metabolites against Kidney Cancer and Inflammation.

(1) Background: A large and diverse microbial population exists in the human intestinal tract, which supports gut homeostasis and the health of the host. Short-chain fatty acid (SCFA)-secreting microbes also generate several metabolites with favorable regulatory effects on various malignancies and immunological inflammations. The involvement of intestinal SCFAs in kidney diseases, such as various kidney malignancies and inflammations, has emerged as a fascinating area of study in recent years. However, the mechanisms of SCFAs and other metabolites produced by SCFA-producing bacteria against kidney cancer and inflammation have not yet been investigated. (2) Methods: We considered 177 different SCFA-producing microbial species and 114 metabolites from the gutMgene database. Further, we used different online-based database platforms to predict 1890 gene targets associated with metabolites. Moreover, DisGeNET, OMIM, and Genecard databases were used to consider 13,104 disease-related gene targets. We used a Venn diagram and various protein-protein interactions (PPIs), KEGG pathways, and GO analyses for the functional analysis of gene targets. Moreover, the subnetwork of protein-protein interactions (through string and cytoscape platforms) was used to select the top 20% of gene targets through degree centrality, betweenness centrality, and closeness centrality. To screen the possible candidate compounds, we performed an analysis of the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of metabolites and then found the best binding affinity using molecular docking simulation. (3) Results: Finally, we found the key gene targets that interact with suitable compounds and function against kidney cancer and inflammation, such as MTOR (with glycocholic acid), PIK3CA (with 11-methoxycurvularin, glycocholic acid, and isoquercitrin), IL6 (with isoquercitrin), PTGS2 (with isoquercitrin), and IGF1R (with 2-amino-1-methyl-6-phenylimidazo[4,5-b] pyridine, isoquercitrin), showed a lower binding affinity. (4) Conclusions: This study provides evidence to support the positive effects of SCFA-producing microbial metabolites that function against kidney cancer and inflammation and makes integrative research proposals that may be used to guide future studies.

Explainable AI for Bioinformatics: Methods, Tools and Applications.

Artificial intelligence (AI) systems utilizing deep neural networks and machine learning (ML) algorithms are widely used for solving critical problems in bioinformatics, biomedical informatics and precision medicine. However, complex ML models that are often perceived as opaque and black-box methods make it difficult to understand the reasoning behind their decisions. This lack of transparency can be a challenge for both end-users and decision-makers, as well as AI developers. In sensitive areas such as healthcare, explainability and accountability are not only desirable properties but also legally required for AI systems that can have a significant impact on human lives. Fairness is another growing concern, as algorithmic decisions should not show bias or discrimination towards certain groups or individuals based on sensitive attributes. Explainable AI (XAI) aims to overcome the opaqueness of black-box models and to provide transparency in how AI systems make decisions. Interpretable ML models can explain how they make predictions and identify factors that influence their outcomes. However, the majority of the state-of-the-art interpretable ML methods are domain-agnostic and have evolved from fields such as computer vision, automated reasoning or statistics, making direct application to bioinformatics problems challenging without customization and domain adaptation. In this paper, we discuss the importance of explainability and algorithmic transparency in the context of bioinformatics. We provide an overview of model-specific and model-agnostic interpretable ML methods and tools and outline their potential limitations. We discuss how existing interpretable ML methods can be customized and fit to bioinformatics research problems. Further, through case studies in bioimaging, cancer genomics and text mining, we demonstrate how XAI methods can improve transparency and decision fairness. Our review aims at providing valuable insights and serving as a starting point for researchers wanting to enhance explainability and decision transparency while solving bioinformatics problems. GitHub: https://github.com/rezacsedu/XAI-for-bioinformatics.

Abundance, characteristics, and ecological risks of microplastics in the riverbed sediments around Dhaka city.

Microplastic (MP) pollution has become an escalating problem in Bangladesh due to its rapid urbanization, economic growth, and excessive use of plastics; however, data on MP pollution from fresh water resources in this country are limited. This study investigated microplastics pollution in riverbed sediments in the peripheral rivers of Dhaka, the capital of Bangladesh. Twenty-eight sediment samples were collected from the selected stations of the Buriganga, Turag, and Balu Rivers. Density separation and wet-peroxidation methods were employed to extract MP particles. Attenuated total reflectance-Fourier transform infrared spectroscopy was used to identify the polymers. The results indicated a medium-level abundance of MPs in riverbed sediment in comparison with the findings of other studies in freshwater sediments worldwide. Film shape, white and transparent color, and large-size (1-5 mm) MPs were dominant in the riverbed sediment. The most abundant polymers were polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET). Pollution load index (PLI) values greater than 1 were observed, indicating that all sampling sites were polluted with MPs. An assessment of ecological risks, using the abundance, polymer types, and toxicity of MPs in the sediment samples, suggested a medium to very high ecological risk of MP pollution of the rivers. The increased abundance of MPs and the presence of highly hazardous polymers, namely; polyurethane, acrylonitrile butadiene styrene, polyvinyl chloride, epoxy resin, and polyphenylene sulfide, were associated with higher ecological risks. Scanning electron microscopy (SEM) analysis indicated that the MPs were subjected to weathering actions, reducing the size of MPs, which caused additional potential ecological hazards in these river ecosystems. This investigation provides baseline information on MP pollution in riverine freshwater ecosystems for further in-depth studies of risk assessment and developing strategies for controlling MP pollution in Bangladesh.

A review on Impact of dietary interventions, drugs, and traditional herbal supplements on the gut microbiome.

The gut microbiome is the community of healthy, and infectious organisms in the gut and its interaction in the host gut intestine (GI) environment. The balance of microbial richness with beneficial microbes is very important to perform healthy body functions like digesting food, controlling metabolism, and precise immune function. Alternately, this microbial dysbiosis occurs due to changes in the physiochemical condition, substrate avidity, and drugs. Moreover, various categories of diet such as "plant-based", "animal-based", "western", "mediterranean", and various drugs (antibiotic and common drugs) also contribute to maintaining microbial flora inside the gut. The imbalance (dysbiosis) in the microbiota of the GI tract can cause several disorders (such as diabetes, obesity, cancer, inflammation, and so on). Recently, the major interest is to use prebiotic, probiotic, postbiotic, and herbal supplements to balance such microbial community in the GI tract. But, there has still a large gap in understanding the microbiome function, and its relation to the host diet, drugs, and herbal supplements to maintain the healthy life of the host. So, the present review is about the updates on the microbiome concerns related to diet, drug, and herbal supplements, and also gives research evidence to improve our daily habits regarding diet, drugs, and herbal supplements. Because our regular dietary plan and traditional herbal supplements can improve our health by balancing the bacteria in our gut.

Genetic association in CYP3A4 and CYP3A5 genes elevate the risk of prostate cancer.

BACKGROUND: CYP3A4 and CYP3A5 are biologically potential genes responsible for prostate cancer. AIM: We aimed to analyse the expression and association of CYP3A4 and CYP3A5 genes in prostate cancer. SUBJECTS AND METHODS: Web-based bioinformatics tools were used to assess the association of CYP3A4 and CYP3A5 genes with prostate cancer risks. A case-control study of 210 prostate cancer cases and 207 controls was also approved to determine the allelic variants of the CYP3A4 gene- rs2740574 (CYP3A4*1B) and the variant of CYP3A5 gene-rs776746 (CYP3A5*3) using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP). The risk of prostate cancer was estimated as odds ratio (OR) and 95% confidence interval (CI) using unrestricted logistic regression models. RESULTS: Our in silico data confirmed that both CYP3A4 and CYP3A5 genes are significantly associated with higher prostate cancer risks. In the case of CYP3A4*1B polymorphism, the heterozygote (*1 A/*1B), mutant (*1B/*1B), and combined heterozygote plus mutant (*1A/*1B+*1B/*1B) genotypes showed 3.52-fold, 3.90-fold, and 3.67-fold increased risk of prostate cancer, respectively. In the case of CYP3A5*3 polymorphism, the heterozygote (*1/*3), mutant (*3/*3), and combined (*1/*3+*3/*3) genotypes were found to be significantly associated with 5.11-, 5.49-, and 5.28-fold greater risk of prostate cancer, respectively. CONCLUSION: Our results indicate that CYP3A4*1B and CYP3A5*3 are significantly associated with increased prostate cancer risk.KEY MESSAGESBioinformatics tools were used and concluded that the CYP3A4 and CYP3A5 genes were significantly associated with the development and progression of prostate cancer.CYP3A4 and CYP3A5 polymorphisms were significantly associated with an increased risk of prostate cancer.Polymerase Chain Reaction (PCR)-Restriction Fragment Length Polymorphism (RFLP) was used to estimate polymorphisms of prostate cancer progression in the Bangladeshi population.

Effects of Green Tea (-)-Epigallocatechin-3-Gallate (EGCG) on Cardiac Function - A Review of the Therapeutic Mechanism and Potentials.

Heart disease, the leading cause of death worldwide, refers to various illnesses that affect heart structure and function. Specific abnormalities affecting cardiac muscle contractility and remodeling and common factors including oxidative stress, inflammation, and apoptosis underlie the pathogenesis of heart diseases. Epidemiology studies have associated green tea consumption with lower morbidity and mortality from cardiovascular diseases, including heart and blood vessel dysfunction. Among the various compounds found in green tea, catechins are believed to play a significant role in producing benefits to cardiovascular health. Comprehensive literature reviews have been published to summarize the tea catechins' antioxidative, anti-inflammatory, and anti-apoptosis effects in various diseases, such as cardiovascular diseases, cancers, and metabolic diseases. However, recent studies on tea catechins, especially the most abundant (-)-Epigallocatechin-3-Gallate (EGCG), revealed their capabilities in regulating cardiac muscle contraction by directly altering myofilament Ca2+ sensitivity on force development and Ca2+ ion handling in cardiomyocytes under both physiological and pathological conditions. In vitro and in vivo data also demonstrated that green tea extract or EGCG protected or rescued cardiac function, independent of their well-known effects against oxidative stress and inflammation. This mini-review will focus on the specific effects of tea catechins on heart muscle contractility at the molecular and cellular level, revisit their effects on oxidative stress and inflammation in various heart diseases, and discuss EGCG's potential as one of the lead compounds for new drug discovery for heart diseases.

Trichosanthes dioica seed lectin inhibits Ehrlich ascites carcinoma cells growth in vivo in mice by inducing G0 /G1 cell cycle arrest.

Trichosanthes dioica seed lectin (TDSL), having a molecular mass of 57 ± 2 kDa was purified in an alternative way. For the purification process, the galactose-sepharose-4B affinity column was used. The purified TDSL agglutinated human and mouse erythrocytes at the minimum concentration of 8  µg/ml. d-lactose and d-galactose were the most potent inhibitory sugars as observed. The purified lectin was a glycoprotein having 3.0% of a neutral sugar. The lectin exhibited maximum activity up to 60°C and pH range from 7.0 to 10.0 and stable up to 4.0 M urea as tested. The lectin demonstrated mild toxicity when administered against brine shrimp nauplii, and the LC50 value was calculated to be 84.0 µg/ml. Minimum agglutination of Ehrlich ascites carcinoma (EAC) cells caused by the lectin was found at the protein concentration of 1.56 µg/ml. TDSL inhibited 7, 50.2%, and 60.3% of the EAC cells growth in vivo in mice when administered with 0.75, 1.5, and 3.0 mg kg-1  day-1 (i.p.), respectively, for five consecutive days. After lectin treatment, red blood cell (RBC) and hemoglobin levels were increased significantly toward the normal compared with EAC cells-bearing control and normal mice. The tumor burden reduced to 29.5% and 67% after treatment with 1.5 and 3.0 mg kg-1  day-1 of the lectin. TDSL triggered the cell cycle arrest at the G0 /G1 phase, which was observed using flow cytometry. In conclusion, TDSL can be a candidate for the potent anticancer agents that exerts low toxicity toward brine shrimp nauplii. PRACTICAL APPLICATIONS: A 57 ± 2 kDa lectin (designated TDSL) was purified from Trichosanthes dioica seeds using a galactose-sepharose-4B affinity column. The lectin demonstrated mild toxicity and agglutinated Ehrlich ascites carcinoma (EAC) cells. The lectin inhibited 50.2% and 60.3% of the EAC cell growth in vivo in mice when administered with 1.5 and 3.0 mg kg-1  day-1 (i.p.), respectively, for five consecutive days. The lectin increased RBC and hemoglobin level toward the normal compared with lectin-treated EAC cells-bearing, EAC cells-bearing control and normal mice. The tumor burden reduced to 29.5% and 67% after treatment with 1.5 and 3.0 mg kg-1  day-1 lectin. TDSL triggered the cell cycle arrest at the G0 /G1 phase. The lectin can be a candidate for potent anticancer agents.

Deep learning-based clustering approaches for bioinformatics.

Clustering is central to many data-driven bioinformatics research and serves a powerful computational method. In particular, clustering helps at analyzing unstructured and high-dimensional data in the form of sequences, expressions, texts and images. Further, clustering is used to gain insights into biological processes in the genomics level, e.g. clustering of gene expressions provides insights on the natural structure inherent in the data, understanding gene functions, cellular processes, subtypes of cells and understanding gene regulations. Subsequently, clustering approaches, including hierarchical, centroid-based, distribution-based, density-based and self-organizing maps, have long been studied and used in classical machine learning settings. In contrast, deep learning (DL)-based representation and feature learning for clustering have not been reviewed and employed extensively. Since the quality of clustering is not only dependent on the distribution of data points but also on the learned representation, deep neural networks can be effective means to transform mappings from a high-dimensional data space into a lower-dimensional feature space, leading to improved clustering results. In this paper, we review state-of-the-art DL-based approaches for cluster analysis that are based on representation learning, which we hope to be useful, particularly for bioinformatics research. Further, we explore in detail the training procedures of DL-based clustering algorithms, point out different clustering quality metrics and evaluate several DL-based approaches on three bioinformatics use cases, including bioimaging, cancer genomics and biomedical text mining. We believe this review and the evaluation results will provide valuable insights and serve a starting point for researchers wanting to apply DL-based unsupervised methods to solve emerging bioinformatics research problems.

In vivo the antioxidative extract of Averrhoa carambola Linn. leaves induced apoptosis in Ehrilch ascites carcinoma by modulating p53 expression.

This study was designed to evaluate the antioxidant activity of methanol extract of Averrhoa carambolla Linn. leaves (MELA) using DPPH· and ABTS·+ free radical scavenging assays whereas its antineoplastic effect against Ehrlich ascites carcinoma (EAC) was assed using viable cell count, life span, body weight gain and hematological parameters of experimental mice. Results showed that rich phenolic and flavonoid content of MELA had moderate dose dependent free radical scavenging activity (IC50: 62.0 µg/mL for DPPH· and 6.0 µg/mL for ABTS·+). In vivo antineoplastic assay, MELA significantly (P < 0.05) decreased viable cells and body weight gain, increased the survival time and restored altered hematological profiles of cancer cell bearing mice. Fluorescence microscopic view of EAC cells derived from MELA-treated group showed apoptotic characteristics and this observation was also supported by overexpression of pro-apoptotic genes coding p53 and Bax proteins in treated cancer cells. The anti-apoptotic genes coding Bcl-2 protein was also absent in treated EAC cells as compared with the control. Moreover, phytochemical profiles of MELA as identified by GC/MS analysis are also consistent with its activities.

Therapy Resistance in Cancers: Phenotypic, Metabolic, Epigenetic and Tumour Microenvironmental Perspectives.

BACKGROUND: Chemoresistance is a vital problem in cancer therapy where cancer cells develop mechanisms to encounter the effect of chemotherapeutics, resulting in cancer recurrence. In addition, chemotherapy- resistant leads to the formation of a more aggressive form of cancer cells, which, in turn, contributes to the poor survival of patients with cancer. OBJECTIVE: In this review, we aimed to provide an overview of how the therapy resistance property evolves in cancer cells, contributing factors and their role in cancer chemoresistance, and exemplified the problems of some available therapies. METHODS: The published literature on various electronic databases including, Pubmed, Scopus, Google scholar containing keywords cancer therapy resistance, phenotypic, metabolic and epigenetic factors, were vigorously searched, retrieved and analyzed. RESULTS: Cancer cells have developed a range of cellular processes, including uncontrolled activation of Epithelial- Mesenchymal Transition (EMT), metabolic reprogramming and epigenetic alterations. These cellular processes play significant roles in the generation of therapy resistance. Furthermore, the microenvironment where cancer cells evolve effectively contributes to the process of chemoresistance. In tumour microenvironment immune cells, Mesenchymal Stem Cells (MSCs), endothelial cells and cancer-associated fibroblasts (CAFs) contribute to the maintenance of therapy-resistant phenotype via the secretion of factors that promote resistance to chemotherapy. CONCLUSION: To conclude, as these factors hinder successful cancer therapies, therapeutic resistance property of cancer cells is a subject of intense research, which in turn could open a new horizon to aim for developing efficient therapies.

Anti-hyperglycemic effect of the immature endosperm of sugar palm (Borassus flabellifer) fruit on type 2 diabetes mellitus patients-a case study.

AIM: This study aimed to investigate the nutrient contents and the anti-hyperglycemic effect of the immature endosperm of sugar palm (IESP) (Borassus flabellifer L.) fruit on type-2 diabetes mellitus (T2DM) patients. METHODS: This is a short type case study where patients (n = 30) with T2DM were randomly selected and fed IESP (100 mL) twice a day after a regular meal and continued this experiment up to 4th weeks. RESULT: The mean fasting blood glucose (FBG) level was markedly reduced from 1st week (15.74 mmol/L) to 4th week (10.53 mmol/L) among the patients who had normal body mass index (18.5-24.9). Only 16.67% diabetic patients had irregular FBG levels where 10% were in the previous stages after finishing the experimental period, and exceptionally in the case of 6.67% diabetic patients, this therapeutic juice was unsuccessful because of their irregular intake of insulin. The IESP was more effective on female (p ≤ 0.001) patients than males (p ≤ 0.05). CONCLUSION: The IESP could be considered as anti-hyperglycemic fruit, and this might be due to its nutrient contents, especially phytochemicals, fiber, sodium, potassium, copper, and zinc.

Identification of molecular signatures and pathways to identify novel therapeutic targets in Alzheimer's disease: Insights from a systems biomedicine perspective.

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. However, there are no peripheral biomarkers available that can detect AD onset. This study aimed to identify the molecular signatures in AD through an integrative analysis of blood gene expression data. We used two microarray datasets (GSE4226 and GSE4229) comparing peripheral blood transcriptomes of AD patients and controls to identify differentially expressed genes (DEGs). Gene set and protein overrepresentation analysis, protein-protein interaction (PPI), DEGs-Transcription Factors (TFs) interactions, DEGs-microRNAs (miRNAs) interactions, protein-drug interactions, and protein subcellular localizations analyses were performed on DEGs common to the datasets. We identified 25 common DEGs between the two datasets. Integration of genome scale transcriptome datasets with biomolecular networks revealed hub genes (NOL6, ATF3, TUBB, UQCRC1, CASP2, SND1, VCAM1, BTF3, VPS37B), common transcription factors (FOXC1, GATA2, NFIC, PPARG, USF2, YY1) and miRNAs (mir-20a-5p, mir-93-5p, mir-16-5p, let-7b-5p, mir-708-5p, mir-24-3p, mir-26b-5p, mir-17-5p, mir-193-3p, mir-186-5p). Evaluation of histone modifications revealed that hub genes possess several histone modification sites associated with AD. Protein-drug interactions revealed 10 compounds that affect the identified AD candidate biomolecules, including anti-neoplastic agents (Vinorelbine, Vincristine, Vinblastine, Epothilone D, Epothilone B, CYT997, and ZEN-012), a dermatological (Podofilox) and an immunosuppressive agent (Colchicine). The subcellular localization of molecular signatures varied, including nuclear, plasma membrane and cytosolic proteins. In the present study, it was identified blood-cell derived molecular signatures that might be useful as candidate peripheral biomarkers in AD. It was also identified potential drugs and epigenetic data associated with these molecules that may be useful in designing therapeutic approaches to ameliorate AD.

Phenotypic identification of CD19+CD5+CD1d+ regulatory B cells that produce interleukin 10 and transforming growth factor ß1 in human peripheral blood.

INTRODUCTION: Regulatory B cells (Bregs), a novel subpopulation of B cells, are a significant area of research due to their immune regulatory function in the immunological response. Bregs have been reported to regulate acute inflammation and immunity through the production of anti-inflammatory cytokines. MATERIAL AND METHODS: A B cell subpopulation was identified using flow cytometric analysis in two different processes: 1) after preparation and storage of peripheral blood mononuclear cells (PBMCs) using Ficoll density gradient centrifugation from a human blood sample, 2) followed by isolation and storage of B cells through magnetic separation using a B cell isolation kit and MS column. ELISA assays were performed to observe the cytokine production of interkleukin 10 (IL-10) and transforming growth factor ß1 (TGF-ß1) by this novel B cell subpopulation. RESULTS: Double positive staining of CD5+CD1d+ Bregs represents (19.27 ±1.52) from PBMCs, (33.32 ±2.95) from B cells accordingly (n = 40). Through ELISA assays, it has been found that B cell subpopulation produces IL-10 (0.56 ±0.08) and TGF-ß1 (0.90 ±0.12) (n = 40). CONCLUSIONS: These methods should be able to facilitate progress in research on Bregs through the following steps: 1) the regulatory role may be observed in comparison with particular autoimmune diseases, inflammation, cancer, and immunologic responses to find out whether Breg alteration and/or cytokine production is altered as well in these disorders or conditions. 2) If the alteration of Bregs and cytokine production is significant along with the clinical correlation, a further in vitro study can be initiated with exposure of certain drugs to overcome the alteration of the cytokine production; then, an in vivo study can be initiated.

Ligand-mediated protein degradation reveals functional conservation among sequence variants of the CUL4-type E3 ligase substrate receptor cereblon.

Upon binding to thalidomide and other immunomodulatory drugs, the E3 ligase substrate receptor cereblon (CRBN) promotes proteosomal destruction by engaging the DDB1-CUL4A-Roc1-RBX1 E3 ubiquitin ligase in human cells but not in mouse cells, suggesting that sequence variations in CRBN may cause its inactivation. Therapeutically, CRBN engagers have the potential for broad applications in cancer and immune therapy by specifically reducing protein expression through targeted ubiquitin-mediated degradation. To examine the effects of defined sequence changes on CRBN's activity, we performed a comprehensive study using complementary theoretical, biophysical, and biological assays aimed at understanding CRBN's nonprimate sequence variations. With a series of recombinant thalidomide-binding domain (TBD) proteins, we show that CRBN sequence variants retain their drug-binding properties to both classical immunomodulatory drugs and dBET1, a chemical compound and targeting ligand designed to degrade bromodomain-containing 4 (BRD4) via a CRBN-dependent mechanism. We further show that dBET1 stimulates CRBN's E3 ubiquitin-conjugating function and degrades BRD4 in both mouse and human cells. This insight paves the way for studies of CRBN-dependent proteasome-targeting molecules in nonprimate models and provides a new understanding of CRBN's substrate-recruiting function.

Right coronary artery perforation extending to the coronary sinus of Valsalva during percutaneous intervention successfully sealed with polytetrafluoroethylene-covered stent: a case report.

BACKGROUND: Right coronary artery perforation extending to the sinus of Valsalva is a rare and potentially fatal complication of percutaneous coronary intervention. There are no definite guidelines on the management strategies for such complications. Treatment modality depends on the patient's haemodynamic stability and the extent of aortic involvement. Polytetrafluoroethylene-covered stents have emerged as a revolutionary strategy, enabling efficient endovascular repair of the entry port of such dissections, particularly the coronary ostia, and obviating the need for high-risk emergent surgical intervention. CASE PRESENTATION: A 60 year old Bangladeshi gentleman underwent a coronary angiogram following a prior inferior ST elevation myocardial infarction (MI), 1 month previously. Coronary angiography done via right radial approach using 5 FR TIG catheter showed diffuse mid RCA disease with maximum 90% stenosis. Angioplasty of the RCA was planned. The RCA was cannulated with a 6-French JR 3.5 guiding catheter (USA). The lesion was crossed by a 0.014 inch guide wire and stented with a 2.75 × 38 mm novolimus-eluting DESyne stent, after predilatation. Immediately after stenting, a Type II perforation was observed in the ostial RCA, which progressed into the right coronary sinus of Valsalva. As the patient was haemodynamically stable with no ischaemia on ECG, we attempted to seal the ostial RCA with bare metal stents. Two successive bare metal stents failed to seal the aorto-coronary dissection. Ultimately, a 3.0 × 19 mm polytetrafluoroethylene-covered stent was deployed to seal the entry port in the ostial RCA, yielding a satisfactory angiographic result with only minimal contrast staining limited to the right sinus of Valsalva. The patient was closely monitored and discharged on dual antiplatelet therapy comprising of aspirin and prasugrel. He remained asymptomatic and with follow up echocardiograms showing no pericardial effusion nor extension of the dissection. CONCLUSIONS: The polytetrafluoroethylene-covered stent provides a safe and effective means of sealing iatrogenic aorto-coronary dissections complicated by Ellis type II or II perforations, thus avoiding emergency surgery. However, as they are associated with increased incidence of stent thrombosis, an efficient and prolonged post-PCI antiplatelet regimen is recommended.

Towards precision medicine: discovering novel gynecological cancer biomarkers and pathways using linked data.

BACKGROUND: Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing a massive amount of sequencing datasets. Often, these datasets are published from the isolated and different sequencing facilities. Consequently, the process of sharing and aggregating multisite sequencing datasets are thwarted by issues such as the need to discover relevant data from different sources, built scalable repositories, the automation of data linkage, the volume of the data, efficient querying mechanism, and information rich intuitive visualisation. RESULTS: We present an approach to link and query different sequencing datasets (TCGA, COSMIC, REACTOME, KEGG and GO) to indicate risks for four cancer types - Ovarian Serous Cystadenocarcinoma (OV), Uterine Corpus Endometrial Carcinoma (UCEC), Uterine Carcinosarcoma (UCS), Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) - covering the 16 healthy tissue-specific genes from Illumina Human Body Map 2.0. The differentially expressed genes from Illumina Human Body Map 2.0 are analysed together with the gene expressions reported in COSMIC and TCGA repositories leading to the discover of potential biomarkers for a tissue-specific cancer. CONCLUSION: We analyse the tissue expression of genes, copy number variation (CNV), somatic mutation, and promoter methylation to identify associated pathways and find novel biomarkers. We discovered twenty (20) mutated genes and three (3) potential pathways causing promoter changes in different gynaecological cancer types. We propose a data-interlinked platform called BIOOPENER that glues together heterogeneous cancer and biomedical repositories. The key approach is to find correspondences (or data links) among genetic, cellular and molecular features across isolated cancer datasets giving insight into cancer progression from normal to diseased tissues. The proposed BIOOPENER platform enriches mutations by filling in missing links from TCGA, COSMIC, REACTOME, KEGG and GO datasets and provides an interlinking mechanism to understand cancer progression from normal to diseased tissues with pathway components, which in turn helped to map mutations, associated phenotypes, pathways, and mechanism.