Preparation and Optimization of MiR-375 Nano-Vector Using Two Novel Chitosan-Coated Nano-Structured Lipid Carriers as Gene Therapy for Hepatocellular Carcinoma.

Currently, there is still a lack of effective carriers with minimal side effects to deliver therapeutic miRNA. Thus, it is crucial to optimize novel drug delivery systems. MiR-375 has proven superior therapeutic potency in Hepatocellular carcinoma (HCC). The purpose of this study was to fabricate 2 novel and smart nano-carriers for the transportation efficiency of miR-375 in HCC cells and enhance its anti-tumor effects. We established the miR-375 construct through the pEGP- miR expression vector. Two nano-carriers of solid/liquid lipids and chitosan (CS) were strategically selected, prepared by high-speed homogenization, and optimized by varying nano-formulation factors. Thus, the two best nano-formulations were designated as F1 (0.5% CS) and F2 (1.5% CS) and were evaluated for miR-375 conjugation efficiency by gel electrophoresis and nanodrop assessment. Then, physio-chemical characteristics and stability tests for the miR-375 nano-plexes were all studied. Next, its efficiencies as replacement therapy in HepG2 cells have been assessed by fluorescence microscopy, flow cytometry, and cytotoxicity assay. The obtained data showed that two cationic nanostructured solid/liquid lipid carriers (NSLCs); F1 and F2 typically had the best physio-chemical parameters and long-term stability. Moreover, both F1 and F2 could form nano-plexes with the anionic miR-375 construct at weight ratios 250/1 and 50/1 via electrostatic interactions. In addition, these nano-plexes exhibited physical stability after three months and protected miR-375 from degradation in the presence of 50% fetal bovine serum (FBS). Furthermore, both nano-plexes could simultaneously deliver miR-375 into HepG2 cells and they ensure miR re-expression even in the presence of 50% FBS compared to free miR-375 (p-value < 0.001). Moreover, both F1 and F2 alone significantly exhibited minimal cytotoxicity in treated cells. In contrast, the nano-plexes significantly inhibited cell growth compared to free miR-375 or doxorubicin (DOX), respectively. More importantly, F2/miR-375 nano-plex exhibited more anti-proliferative activity in treated cells although its IC50 value was 55 times lower than DOX (p-value < 0.001). Collectively, our findings clearly emphasized the multifunctionality of the two CS-coated NSLCs in terms of their enhanced biocompatibility, biostability, conjugation, and transfection efficiency of therapeutic miR-375. Therefore, the NSLCs/miR-375 nano-plexes could serve as a novel and promising therapeutic strategy for HCC.

SIRT1 as a potential key regulator for mediating apoptosis in oropharyngeal cancer using cyclophosphamide and all-trans retinoic acid.

Although cyclophosphamide (CTX) has been used for recurrent or metastatic head and neck cancers, resistance is usually expected. Thus, we conducted this study to examine the effect of adding all-trans retinoic acid (ATRA) to CTX, to increase efficacy of CTX and reduce the risk of resistance developed. In this study, we investigated the combined effect of ATRA and CTX on the expression of apoptotic and angiogenesis markers in oropharyngeal carcinoma cell line (NO3), and the possible involved mechanisms. ATRA and CTX in combination significantly inhibited the proliferation of NO3 cells. Lower dose of CTX in combination with ATRA exhibited significant cytotoxicity than that of CTX when used alone, implying lower expected toxicity. Results showed that ATRA and CTX modulated oxidative stress; increased NOx and MDA, reduced GSH, and mRNA expression of Cox-2, SIRT1 and AMPK. Apoptosis was induced through elevating mRNA expressions of Bax and PAR-4 and suppressing that of Bcl-xl and Bcl-2, parallel with increased caspases 3 and 9 and decreased VEGF, endothelin-1 and CTGF levels. The primal action of the combined regimen on inflammatory signaling highlights its impact on cell death in NO3 cell line which was mediated by oxidative stress associated with apoptosis and suppression of angiogenesis.

A structural-based virtual screening and in vitro validation reveals novel effective inhibitors for SARS-CoV-2 helicase and endoribonuclease.

Researchers worldwide are looking for molecules that might disrupt the COVID-19 life cycle. Endoribonuclease, which is responsible for processing viral RNA to avoid detection by the host defense system, and helicase, which is responsible for unwinding the RNA helices for replication, are two key non-structural proteins. This study performs a hierarchical structure-based virtual screening approach for NSP15 and helicase to reach compounds with high binding probabilities. In this investigation, we incorporated a variety of filtering strategies for predicting compound interactions. First, we evaluated 756,275 chemicals from four databases using a deep learning method (NCI, Drug Bank, Maybridge, and COCONUT). Following that, two docking techniques (extra precision and induced fit) were utilized to evaluate the compounds' binding affinity, followed by molecular dynamic simulation supported by the MM-GBSA free binding energy calculation. Remarkably, two compounds (90616 and CNP0111740) exhibited high binding affinity values of -66.03 and -12.34 kcal/mol for helicase and NSP15, respectively. The VERO-E6 cell line was employed to test their in vitro therapeutic impact. The CC50 for CNP0111740 and 90616 were determined to be 102.767 µg/ml and 379.526 µg/ml, while the IC50 values were 140.176 µg/ml and 5.147 µg/ml, respectively. As a result, the selectivity index for CNP0111740 and 90616 is 0.73 and 73.73, respectively. Finally, these compounds were found to be novel, effective inhibitors for the virus; however, further in vivo validation is needed.Communicated by Ramaswamy H. Sarma.

In Silico Analysis of MicroRNA Expression Data in Liver Cancer.

Abnormal miRNA expression has been evidenced to be directly linked to HCC initiation and progression. This study was designed to detect possible prognostic, diagnostic, and/or therapeutic miRNAs for HCC using computational analysis of miRNAs expression. Methods: miRNA expression datasets meta-analysis was performed using the YM500v2 server to compare miRNA expression in normal and cancerous liver tissues. The most significant differentially regulated miRNAs in our study undergone target gene analysis using the mirWalk tool to obtain their validated and predicted targets. The combinatorial target prediction tool; miRror Suite was used to obtain the commonly regulated target genes. Functional enrichment analysis was performed on the resulting targets using the DAVID tool. A network was constructed based on interactions among microRNAs, their targets, and transcription factors. Hub nodes and gatekeepers were identified using network topological analysis. Further, we performed patient data survival analysis based on low and high expression of identified hubs and gatekeeper nodes, patients were stratified into low and high survival probability groups. Results: Using the meta-analysis option in the YM500v2 server, 34 miRNAs were found to be significantly differentially regulated (P-value ⩽ .05); 5 miRNAs were down-regulated while 29 were up-regulated. The validated and predicted target genes for each miRNA, as well as the combinatorially predicted targets, were obtained. DAVID enrichment analysis resulted in several important cellular functions that are directly related to the main cancer hallmarks. Among these functions are focal adhesion, cell cycle, PI3K-Akt signaling, insulin signaling, Ras and MAPK signaling pathways. Several hub genes and gatekeepers were found that could serve as potential drug targets for hepatocellular carcinoma. POU2F1 and PPARA showed a significant difference between low and high survival probabilities (P-value ⩽ .05) in HCC patients. Our study sheds light on important biomarker miRNAs for hepatocellular carcinoma along with their target genes and their regulated functions.

A cellular screening platform, stably expressing DENV2 NS5, defines a novel anti-DENV mechanism of action of Apigenin based on STAT2 activation.

Type I interferon (IFN-I) evasion by Dengue virus (DENV) is key in DENV pathogenesis. The non-structural protein 5 (NS5) antagonizes IFN-I response through the degradation of the signal transducer and activator of transcription 2 (STAT2). We developed a K562 cell-based platform, for high throughput screening of compounds potentially counteracting the NS5-mediated antagonism of IFN-I signaling. Upon a screening with a library of 1220 approved drugs, 3 compounds previously linked to DENV inhibition (Apigenin, Chrysin, and Luteolin) were identified. Luteolin and Apigenin determined a significant inhibition of DENV2 replication in Huh7 cells and the restoration of STAT2 phosphorylation in both cell systems. Apigenin and Luteolin were able to stimulate STAT2 even in the absence of infection. Despite the "promiscuous" and "pan-assay-interfering" nature of Luteolin, Apigenin promotes STAT2 Tyr 689 phosphorylation and activation, highlighting the importance of screening for compounds able to interact with host factors, to counteract viral proteins capable of dampening innate immune responses.

The oral microbiome of treated and untreated chronic HCV infection: A preliminary study.

OBJECTIVES: Chronic hepatitis C virus (HCV) infection is a debilitating disease that is lately treated using direct-acting antivirals (DAAs). Changes in the oral microbiome were detected in other liver diseases; however, oral microbiome was never investigated in patients having chronic HCV infection, whether pre- or post-treatment. MATERIALS AND METHODS: This case-control preliminary study enrolled three equal groups: Group (I): untreated HCV patients; group (II): HCV patients who achieved viral clearance after DAA administration; and group (III): healthy controls. For each participant, a buccal swab was harvested and its 16S rRNA was sequenced. RESULTS: The oral microbiome of chronic HCV patients had a significantly distinct bacterial community compared to healthy controls, characterized by high diversity and abundance of certain pathogenic species. These changes resemble that of oral lichen planus patients. After treatment by DAAs, the oral microbiome shifted to a community with partial similarity to both the diseased and the healthy ones. CONCLUSIONS: Chronic HCV is associated with dysbiotic oral microbiome having abundant pathogenic bacteria. With HCV clearance by DAAs, the oral microbiome shifts to approach the healthy composition.

Progress, pitfalls, and path forward of drug repurposing for COVID-19 treatment.

On 30 January 2020, the World Health Organization (WHO) declared the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic a public health emergency of international concern. The viral outbreak led in turn to an exponential growth of coronavirus disease 2019 (COVID-19) cases, that is, a multiorgan disease that has led to more than 6.3 million deaths worldwide, as of June 2022. There are currently few effective drugs approved for treatment of SARS-CoV-2/COVID-19 patients. Many of the compounds tested so far have been selected through a drug repurposing approach, that is, by identifying novel indications for drugs already approved for other conditions. We here present an up-to-date review of the main Food and Drug Administration (FDA)-approved drugs repurposed against SARS-CoV-2 infection, discussing their mechanism of action and their most important preclinical and clinical results. Reviewed compounds were chosen to privilege those that have been approved for use in SARS-CoV-2 patients or that have completed phase III clinical trials. Moreover, we also summarize the evidence on some novel and promising repurposed drugs in the pipeline. Finally, we discuss the current stage and possible steps toward the development of broadly effective drug combinations to suppress the onset or progression of COVID-19.

Targeting SARS-CoV-2 endoribonuclease: a structure-based virtual screening supported by in vitro analysis.

Researchers are focused on discovering compounds that can interfere with the COVID-19 life cycle. One of the important non-structural proteins is endoribonuclease since it is responsible for processing viral RNA to evade detection of the host defense system. This work investigates a hierarchical structure-based virtual screening approach targeting NSP15. Different filtering approaches to predict the interactions of the compounds have been included in this study. Using a deep learning technique, we screened 823,821 compounds from five different databases (ZINC15, NCI, Drug Bank, Maybridge, and NCI Diversity set III). Subsequently, two docking protocols (extra precision and induced fit) were used to assess the binding affinity of the compounds, followed by molecular dynamic simulation supported by the MM-GBSA free binding energy. Interestingly, one compound (ZINC000104379474) from the ZINC15 database has been found to have a good binding affinity of - 7.68 kcal/Mol. The VERO-E6 cell line was used to investigate its therapeutic effect in vitro. Half-maximal cytotoxic concentration and Inhibitory concentration 50 were determined to be 0.9 mg/ml and 0.01 mg/ml, respectively; therefore, the selectivity index is 90. In conclusion, ZINC000104379474 was shown to be a good hit for targeting the virus that needs further investigations in vivo to be a drug candidate.

Drug repurposing through virtual screening and in vitro validation identifies tigecycline as a novel putative HCV polymerase inhibitor.

The repurposing of marketed drugs for new indications is an elegant strategy to quickly and cost-efficiently address unmet medical needs. The hepatitis C virus (HCV) RNA-dependent RNA polymerase (RdRp) has been shown to be a valid drug target. We performed structure-based virtual screening to assess the off-label utilization of existing drugs as novel HCV inhibitors. The virtual screen showed that tigecycline could potentially dock with high affinity to the palm site of the HCV RdRp. In vitro validation showed that tigecycline had therapeutic indexes (CC50/EC50) greater than 13 and 6.5 against infectious HCV and subgenomic HCV replicons, respectively. Furthermore, tigecycline displayed synergistic activity with sofosbuvir and daclatasvir against HCV. In silico screening identified tigecycline as a putative inhibitor of HCV RdRp, which was validated in vitro and demonstrated synergistic effects in combination with first-line anti-HCV therapies.

Derivation of "Egyptian varices prediction (EVP) index": A novel noninvasive index for diagnosing esophageal varices in HCV Patients.

Introduction: Esophageal Varices (EVs) is one of the major dangerous complications of liver fibrosis. Upper Gastrointestinal (UGI) Endoscopy is necessary for its diagnosis. Repeated examinations for EVs screening severely burden endoscopic units in terms of cost and other side implications; moreover, the lack of public health resources in rural areas and primary hospitals should be considered, particularly in developing countries. So, an accurate noninvasive marker for EV is highly needed for liver disease patients. Objectives: This study sought to evaluate the values of several indices to determine how adequate are they in predicting EV and build a novel accurate prediction index. Methods: Five thousand and thirteen patients were enrolled. The laboratory tests, abdominal ultrasonography, liver stiffness measurement using Fibro-scan, and UGI endoscopy were performed. Ten common indices: Fib-4 score, AST-to-platelet ratio index, Fibrosis index, AST/ALT ratio Varices Prediction Rule, Baveno VI, APRI-Fib4 Combo, King score, "Model for End-Stage Liver Disease", and Lok Score were calculated. The significant predictors for EVs were identified by using "P-value Correlation-based Filter Selection" method, where a novel Egyptian Varices Prediction (EVP) index was developed using binary logistic regression. The diagnostic performance was evaluated by some parameters and the Area Under Curve (AUC). Results: EVP Index was correlated to EVs at 0.5; it achieved higher performance (AUC 0.788, accuracy 73.3%, and sensitivity 78%) than the other indices at a cutoff point of 0.423. Conclusion: EVP Index was a good noninvasive predictor. It had an acceptable performance for diagnosing EVs and it was only required regular laboratory tests and imaging data. It can provide a tool for classifying or arranging the patients according to the degree pre-emptive for selective endoscopy and the degree of severity. Also, it will enable clinicians to concentrate on one marker instead of a wide set of parameters.

Identifying potential novel insights for COVID-19 pathogenesis and therapeutics using an integrated bioinformatics analysis of host transcriptome.

The molecular mechanisms underlying the pathogenesis of COVID-19 have not been fully discovered. This study aims to decipher potentially hidden parts of the pathogenesis of COVID-19, potential novel drug targets, and identify potential drug candidates. Two gene expression profiles were analyzed, and overlapping differentially expressed genes (DEGs) were selected for which top enriched transcription factors and kinases were identified, and pathway analysis was performed. Protein-protein interaction (PPI) of DEGs was constructed, hub genes were identified, and module analysis was also performed. DGIdb database was used to identify drugs for the potential targets (hub genes and the most enriched transcription factors and kinases for DEGs). A drug-potential target network was constructed, and drugs were ranked according to the degree. L1000FDW was used to identify drugs that can reverse transcriptional profiles of COVID-19. We identified drugs currently in clinical trials, others predicted by different methods, and novel potential drug candidates Entrectinib, Omeprazole, and Exemestane for combating COVID-19. Besides the well-known pathogenic pathways, it was found that axon guidance is a potential pathogenic pathway. Sema7A, which may exacerbate hypercytokinemia, is considered a potential novel drug target. Another potential novel pathway is related to TINF2 overexpression, which may induce potential telomere dysfunction and damage DNA that may exacerbate lung fibrosis. This study identified new potential insights regarding COVID-19 pathogenesis and treatment, which might help us improve our understanding of the mechanisms of COVID-19.

Targeted delivery of miR-218 via decorated hyperbranched polyamidoamine for liver cancer regression.

Hepatocellular carcinoma (HCC) is one of most common causes of cancer death worldwide. MicroRNA (miRNA) replacement gene therapy is a novel approach for HCC management. MiR-218 is a promising tumor suppressor miRNA that is down-regulated in HCC. Here, our aim was the targeted delivery of miR-218 expressing DNA plasmid (pmiR-218) to suppress HCC in vitro and in vivo. Hyperbranched polyamidoamine was synthesized via simple and economically one-pot reaction followed by decoration with lactobionic acid (LA-PAMAM) to selectively deliver and restore miR-218 expression in HCC. In vitro cytotoxicity investigations revealed the high biocompatibility of LA-PAMAM. Furthermore, decoration of hyperbranched polymer with LA moieties enabled LA-PAMAM to deliver pmiR-218 more efficiently to HepG2 cells compared to both PMAMA and naked pmiR-218. Such efficient delivery of miR-218 resulted in suppression of HepG2 proliferation and down-regulation of its oncogenic HOXA1 target. In vivo, LA-PAMAM/pmiR-218 treatment of HCC induced by DEN and CCl4 in mice leads to an obvious decrease in the number and size of HCC nodules. In addition, LA-PAMAM/pmiR-218 significantly improved the liver histological features, as well as down-regulated the HOXA1 in liver tissue. In conclusion, this study showed the potential of LA-PAMAM carrier for the targeted delivery of tumor suppressor miR-218 as a therapeutic candidate for HCC.

Integrative assessment of CIP2A overexpression and mutational effects in human malignancies identifies possible deleterious variants.

KIAA1524 is the gene encoding the human cancerous inhibitor of PP2A (CIP2A) protein which is regarded as a novel target for cancer therapy. It is overexpressed in 65%-90% of tissues in almost all studied human cancers. CIP2A expression correlates with cancer progression, disease aggressivity in lung cancer besides poor survival and resistance to chemotherapy in breast cancer. Herein, a pan-cancer analysis of public gene expression datasets was conducted showing significant upregulation of CIP2A in cancerous and metastatic tissues. CIP2A overexpression also correlated with poor survival of cancer patients. To determine the non-coding variants associated with CIP2A overexpression, 5'UTR and 3'UTR variants were annotated and scored using RegulomeDB and Enformer deep learning model. The 5'UTR variants rs1239349555, rs1576326380, and rs1231839144 were predicted to be potential regulators of CIP2A overexpression scoring best on RegulomeDB annotations with a high "2a" rank of supporting experimental data. These variants also scored the highest on Enformer predictions. Analysis of the 3'UTR variants of CIP2A predicted rs56255137 and rs58758610 to alter binding sites of hsa-miR-500a-5 and (hsa-miR-3671, hsa-miR-5692a) respectively. Both variants were also found in linkage disequilibrium with rs11709183 and rs147863209 respectively at r2 ≥ 0.8. The aforementioned variants were found to be eQTL hits significantly associated with CIP2A overexpression. Further, analysis of rs11709183 and rs147863209 revealed a high "2b" rank on RegulomeDB annotations indicating a probable effect on DNAse transcription factors binding. The MuTarget analysis indicated that somatic mutations in TP53 are significantly associated with upregulated CIP2A in human cancers. Analysis of missense SNPs on CIP2A solved structure predicted seven deleterious effects. Four of these variants were also predicted as structurally and functionally destabilizing to CIP2A including; rs375108755, rs147942716, rs368722879, and rs367941403. Variant rs1193091427 was predicted as a potential intronic splicing mutation that might be responsible for the novel CIP2A variant (NOCIVA) in multiple myeloma. Finally, Enrichment of the Wnt/ß-catenin pathway within the CIP2A regulatory gene network suggested potential of therapeutic combinations between FTY720 with Wnt/ß-catenin, Plk1 and/or HDAC inhibitors to downregulate CIP2A which has been shown to be essential for the survival of different cancer cell lines.

In Silico and In Vivo Evaluation of SARS-CoV-2 Predicted Epitopes-Based Candidate Vaccine.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2, the causative agent of coronavirus disease (COVID-19)) has caused relatively high mortality rates in humans throughout the world since its first detection in late December 2019, leading to the most devastating pandemic of the current century. Consequently, SARS-CoV-2 therapeutic interventions have received high priority from public health authorities. Despite increased COVID-19 infections, a vaccine or therapy to cover all the population is not yet available. Herein, immunoinformatics and custommune tools were used to identify B and T-cells epitopes from the available SARS-CoV-2 sequences spike (S) protein. In the in silico predictions, six B cell epitopes QTGKIADYNYK, TEIYQASTPCNGVEG, LQSYGFQPT, IRGDEVRQIAPGQTGKIADYNYKLPD, FSQILPDPSKPSKRS and PFAMQMAYRFNG were cross-reacted with MHC-I and MHC-II T-cells binding epitopes and selected for vaccination in experimental animals for evaluation as candidate vaccine(s) due to their high antigenic matching and conserved score. The selected six peptides were used individually or in combinations to immunize female Balb/c mice. The immunized mice raised reactive antibodies against SARS-CoV-2 in two different short peptides located in receptor binding domain and S2 region. In combination groups, an additive effect was demonstrated in-comparison with single peptide immunized mice. This study provides novel epitope-based peptide vaccine candidates against SARS-CoV-2.

Telaprevir is a potential drug for repurposing against SARS-CoV-2: computational and in vitro studies.

Drug repurposing is an important approach to the assignment of already approved drugs for new indications. This technique bypasses some steps in the traditional drug approval system, which saves time and lives in the case of pandemics. Direct acting antivirals (DAAs) have repeatedly repurposed from treating one virus to another. In this study, 16 FDA-approved hepatitis C virus (HCV) DAA drugs were studied to explore their activities against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) human and viral targets. Among the 16 HCV DAA drugs, telaprevir has shown the best in silico evidence to work on both indirect human targets (cathepsin L [CTSL] and human angiotensin-converting enzyme 2 [hACE2] receptor) and direct viral targets (main protease [Mpro]). Moreover, the docked poses of telaprevir inside both hACE2 and Mpro were subjected to additional molecular dynamics simulations monitored by calculating the binding free energy using MM-GBSA. In vitro analysis of telaprevir showed inhibition of SARS-CoV-2 replication in cell culture (IC50 = 11.552 µM, CC50 = 60.865 µM, and selectivity index = 5.27). Accordingly, based on the in silico studies and supported by the presented in vitro analysis, we suggest that telaprevir may be considered for therapeutic development against SARS-CoV-2.

Impact of type 2 diabetes mellitus on the immunoregulatory characteristics of adipose tissue-derived mesenchymal stem cells.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder associated with several complications. Adipose tissue-derived mesenchymal stem cells (AT-MSCs) represent an emerging type of MSCs with high plasticity and immunoregulatory capabilities and are useful for treating inflammation-related disorders such as T2DM. However, the pathogenic microenvironment of T2DM may affect their therapeutic potential. We aimed to examine the impact of the diabetic milieu on the immunomodulatory/anti-inflammatory potential of AT-MSCs. METHODS: We assessed the proliferation potential, cell surface expression of MSC-characteristic markers and immunomodulatory markers, along with the gene expression and protein secretion of pro-inflammatory and anti-inflammatory cytokines and adipokines in AT-MSCs derived from T2DM patients (dAT-MSCs) vs. those derived from non-diabetic volunteers (ndAT-MSCs). Furthermore, we evaluated the IFN-γ priming effect on both groups. RESULTS: Our data revealed comparable proliferative activities in both groups. Flow cytometric analysis results showed a lower expression of CD200 and CD276 on dAT-MSCs vs. ndAT-MSCs. qPCR demonstrated upregulation of IL-1ß associated with a downregulation of IL-1RN in dAT-MSCs vs. ndAT-MSCs. IFN-γ priming induced an elevation in CD274 expression associated with IDO1 and ILRN overexpression and IL-1ß downregulation in both groups. ELISA analysis uncovered elevated levels of secreted IL-1ß, TNF, and visfatin/NAMPT in dAT-MSCs, whereas IL-1RA and IDO levels were reduced. ELISA results were also evident in the secretome of dAT-MSCs upon IFN-γ priming. CONCLUSIONS: This study suggests that the T2DM milieu alters the immunomodulatory characteristics of AT-MSCs with a shift towards a proinflammatory phenotype which may restrain their autologous therapeutic use. Furthermore, our findings indicate that IFN-γ priming could be a useful strategy for enhancing dAT-MSC anti-inflammatory potential.

Systematic auditing is essential to debiasing machine learning in biology.

Biases in data used to train machine learning (ML) models can inflate their prediction performance and confound our understanding of how and what they learn. Although biases are common in biological data, systematic auditing of ML models to identify and eliminate these biases is not a common practice when applying ML in the life sciences. Here we devise a systematic, principled, and general approach to audit ML models in the life sciences. We use this auditing framework to examine biases in three ML applications of therapeutic interest and identify unrecognized biases that hinder the ML process and result in substantially reduced model performance on new datasets. Ultimately, we show that ML models tend to learn primarily from data biases when there is insufficient signal in the data to learn from. We provide detailed protocols, guidelines, and examples of code to enable tailoring of the auditing framework to other biomedical applications.

Complete genome sequence and bioinformatics analysis of nine Egyptian females with clinical information from different geographic regions in Egypt.

Egyptians are at a crossroad between Africa and Eurasia, providing useful genomic resources for analyzing both genetic and environmental factors for future personalized medicine. Two personal Egyptian whole genomes have been published previously by us and here nine female whole genome sequences with clinical information have been added to expand the genomic resource of Egyptian personal genomes. Here we report the analysis of whole genomes of nine Egyptian females from different regions using Illumina short-read sequencers. At 30x sequencing coverage, we identified 12 SNPs that were shared in most of the subjects associated with obesity which are concordant with their clinical diagnosis. Also, we found mtDNA mutation A4282G is common in all the samples and this is associated with chronic progressive external ophthalmoplegia (CPEO). Haplogroup and Admixture analyses revealed that most Egyptian samples are close to the other north Mediterranean, Middle Eastern, and European, respectively, possibly reflecting the into-Africa influx of human migration. In conclusion, we present whole-genome sequences of nine Egyptian females with personal clinical information that cover the diverse regions of Egypt. Although limited in sample size, the whole genomes data provides possible geno-phenotype candidate markers that are relevant to the region's diseases.

Immunomodulatory and Antioxidative potentials of adipose-derived Mesenchymal stem cells isolated from breast versus abdominal tissue: a comparative study.

BACKGROUND: Adipose-derived stem cells (ASCs) are considered ideal candidates for both research and cellular therapy due to ease of access, large yield, feasibility, and efficacy in preclinical and clinical studies. Unlike the subcutaneous abdominal fat depot, breast ASCs features are still not well recognized, limiting their possible therapeutic use. ASCs were found to exert immunomodulatory and antioxidative activities for maintaining homeostasis and functionality of diseased/damaged tissues. This study aims to investigate the immunomodulatory and antioxidative potentials of breast versus abdominal isolated ASCs to find out which anatomical site provides ASCs with better immunoregulatory and oxidative stress resistance capabilities. METHODS: ASCs were isolated from abdominal and breast tissues. Gene expression analysis was conducted for a panel of immunomodulatory and antioxidative genes, as well as adipokines and proliferation genes. Flow cytometric analysis of a group of immunomodulatory surface proteins was also performed. Finally, the significantly expressed genes have undergone protein-protein interaction and functional enrichment in silico analyses. RESULTS: Our results revealed similar morphological and phenotypic characteristics for both breast and abdominal ASCs. However, a significant elevation in the expression of two potent immunosuppressive genes, IL-10 and IDO as well as the expression of the multifaceted immunomodulatory adipokine, visfatin, was detected in breast versus abdominal ASCs. Moreover, a significant overexpression of the antioxidative genes, GPX1, SIRT5, and STAT3 and the proliferation marker, Ki67, was also observed in breast ASCs relative to abdominal ones. In silico analysis showed that both of the differentially upregulated immunomodulatory and antioxidative mediators integratively involved in multiple biological processes and pathways indicating their functional association. CONCLUSION: Breast ASCs possess superior immunomodulatory and antioxidative capabilities over abdominal ASCs. Our findings shed light on the possible therapeutic applications of breast ASCs in immune-related and oxidative stress-associated diseases.

Machine Learning Prediction Models for Diagnosing Hepatocellular Carcinoma with HCV-related Chronic Liver Disease.

BACKGROUND AND OBJECTIVE: Considered as one of the most recurrent types of liver malignancy, Hepatocellular Carcinoma (HCC) needs to be assessed in a non-invasive way. The objective of the current study is to develop prediction models for Chronic Hepatitis C (CHC)-related HCC using machine learning techniques. METHODS: A dataset, for 4423 CHC patients, was investigated to identify the significant parameters for predicting HCC presence. In this study, several machine learning techniques (Classification and regression tree, alternating decision tree, reduce pruning error tree and linear regression algorithm) were used to build HCC classification models for prediction of HCC presence. RESULTS: Age, alpha-fetoprotein (AFP), alkaline phosphate (ALP), albumin, and total bilirubin attributes were statistically found to be associated with HCC presence. Several HCC classification models were constructed using several machine learning algorithms. The proposed HCC classification models provide adequate area under the receiver operating characteristic curve (AUROC) and high accuracy of HCC diagnosis. AUROC ranges between 95.5% and 99%, plus overall accuracy between 93.2% and 95.6%. CONCLUSION: Models with simplistic factors have the power to predict the existence of HCC with outstanding performance.