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BACKGROUND: Age-related alterations in the composition and function of gut microbiota may influence human health and disease mechanisms. However, connections between compositional changes in gut bacterial and fungal communities, and their role in the aging process, remain poorly understood. OBJECTIVE: Compare the gut microbiota and mycobiota composition in different age groups and evaluate the functionality. METHODS: In this study, we performed 16S rRNA and ITS2 gene-based microbial profiling analysis and shotgun metagenomics using the NextSeq platform. RESULTS: We observed a shift in compositional changes of human gut microbiota with age. Older individuals revealed a significantly different gut microbiota profile compared to younger individuals. For example, gut microbiota composition of the older individuals showed increase in genera Bacteroides, Blautia, Ruminococcaceae, and Escherichia coli. Additionally, older individuals had significant reduction in fungi belonging to saccharomyces cerevisiae and candida albicans in comparison to their younger counterparts. Moreover, metagenomics functional profiling analysis using shotgun metagenomics sequencing data showed substantial differences in the enrichment of 48 pathways between the young and older age groups. Metabolic pathways such as amino acid biosynthesis, carbohydrate metabolism, cell structure biosynthesis and vitamin biosynthesis were declined in the older age group, in comparison with the younger individuals. CONCLUSIONS: The identified differences provide a new insight to enrich our understanding of age-related changes in gut microbiota, their metabolic capabilities, and potential impact on health and disease conditions.

Introduction: The phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway plays a central role in regulating cell growth and proliferation and...

Phosphoinositide 3-kinase α (PI3Kα) is a propitious target for designing anticancer drugs. A series of new N’-(diphenylmethylene)benzenesulfonohydrazide was synthesized and characterized using FT-IR, NMR (1H and 13C), HRMS, and elemental analysis. Target compounds exhibited an antiproliferative effect against the human colon carcinoma (HCT-116) cell line. Our cheminformatics analysis indicated that the para-tailored derivatives [p-NO2 (3) and p-CF3 (7)] have better ionization potentials based on calculated Moran autocorrelations and ionization potentials. Subsequent in vitro cell proliferation assays validated our cheminformatics results by providing experimental evidence that both derivatives 3 and 7 exhibited improved antiproliferative activities against HCT-116. Hence, our results emphasized the importance of electron-withdrawing groups and hydrogen bond-acceptors in the rational design of small-molecule chemical ligands targeting PI3Kα. These results agreed with the induced-fit docking against PI3Kα, highlighting the role of p-substituted aromatic rings in guiding the ligand-PI3Kα complex formation, by targeting a hydrophobic pocket in the ligand-binding site and forming π-stacking interactions with a nearby tryptophan residue.

Coronaviruses (CoVs) are enveloped positive-stranded RNA viruses with spike (S) protein projections that allow the virus to enter and infect host cells. The S protein is a key virulence factor determining viral pathogenesis, host tropism, and disease pathogenesis. There are currently diverse corona viruses that are known to cause disease in humans. : The occurrence of Middle East respiratory syndrome coronavirus (MERS-CoV) and Severe Acute Respiratory Syndrome coronavirus (SARS-CoV), as fatal human CoV diseases, has induced significant interest in the medical field. The novel coronavirus disease (COVID-19) is an infectious disease caused by a novel strain of coronavirus (SAR-CoV-2). The SARS-CoV2 outbreak has been evolved in Wuhan, China, in December 2019, and identified as a pandemic in March 2020, resulting in 53.24 M cases and 1.20M deaths worldwide. : SARS-CoV-2 main proteinase (MPro), a key protease of CoV-2, mediates viral replication and transcription. SARS-CoV-2 MPro has been emerged as an attractive target for SARS-CoV-2 drug design and development. Diverse scaffolds have been released targeting SARS-CoV-2 MPro. In this review, we culminate the latest published information about SARS-CoV-2 main proteinase (MPro) and reported inhibitors.

Recently, an outbreak of a fatal coronavirus, SARS-CoV-2, has emerged from China and is rapidly spreading worldwide. Possible interaction of SARS-CoV-2 with DPP4 peptidase may partly contribute to the viral pathogenesis. An integrative bioinformatics approach starting with mining the biomedical literature for high confidence DPP4-protein/gene associations followed by functional analysis using network analysis and pathway enrichment was adopted. The results indicate that the identified DPP4 networks are highly enriched in viral processes required for viral entry and infection, and as a result, we propose DPP4 as an important putative target for the treatment of COVID-19. Additionally, our protein-chemical interaction networks identified important interactions between DPP4 and sitagliptin. We conclude that sitagliptin may be beneficial for the treatment of COVID-19 disease, either as monotherapy or in combination with other therapies, especially for diabetic patients and patients with pre-existing cardiovascular conditions who are already at higher risk of COVID-19 mortality.

In less than two months of its detection in Jordan, lineage B.1.1.529 recognized as Omicron, is constituting 55% of all confirmed coronavirus disease of 2019 (COVID-19) infections causing a rise in the daily cases in the country. Herein, we report on 500 cases, among the first identified Omicron infections in Jordan. We also report on the genomic diversity of 25 Omicron viruses identified in nasopharyngeal swabs from Jordan. Our results indicated that 96% of study participants were vaccinated who had asymptomatic, mild or moderate disease. One unvaccinated individual developed severe disease. The median age of Omicron cases was 30 years, and most frequent disease symptoms were: fever, coughing, sore throat, runny nose, general fatigue and muscle/joint pain. Viral genomic analysis results revealed that the BA.1 is the dominant Omicron sublineage in Jordan, with 45 to 58 total mutations. We identified a few amino acid modifications that could impact the accuracy of some polymerase chain reaction (PCR) tests. In summary, infections caused by BA.1 seem milder than earlier infections. However, it is unknown whether this change is due to alterations in the immunity landscape of the infected population or is the result of viral genetic mutations that reduced viral virulence. Hence, comparing similar studies from different countries is likely to give us a get a better understanding of this variant, its behavior and the impact on disease characteristics.

The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer. The most frequently used cancer biomarkers are derived from either biological materials or imaging data. Most cancer biomarkers suffer from a lack of high specificity. However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers. Such biomarkers can be used to diagnose cancer patients, to predict cancer prognosis, or even to predict treatment efficacy. Herein, we provide a summary of the current status of developing and applying Magnetic resonance imaging (MRI) biomarkers in cancer care. We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical applications in different cancer types.

The genomic analysis of the 556 viral sequences from Jordan uncovered three dominant genetic SARS-CoV-2 lineages that are currently circulating in Jordan: B.1.1.312 (76%), B.1.36.10 (11%), and B.1.1.7 (6%), replacing the genetic strains that were dominant before sustained community transmission in Jordan. This raises speculations about these new genetic lineages and their relationship to the severity of disease symptoms in Jordan.

Phosphoinositide 3-kinase α (PI3Kα) is a propitious target for designing anticancer drugs. A series of new N'-(diphenylmethylene)benzenesulfonohydrazide was synthesized and characterized using FT-IR, NMR (1H and 13C), HRMS, and elemental analysis. Target compounds exhibited an antiproliferative effect against the human colon carcinoma (HCT-116) cell line. Our cheminformatics analysis indicated that the para-tailored derivatives [p-NO2 (3) and p-CF3 (7)] have better ionization potentials based on calculated Moran autocorrelations and ionization potentials. Subsequent in vitro cell proliferation assays validated our cheminformatics results by providing experimental evidence that both derivatives 3 and 7 exhibited improved antiproliferative activities against HCT-116. Hence, our results emphasized the importance of electron-withdrawing groups and hydrogen bond-acceptors in the rational design of small-molecule chemical ligands targeting PI3Kα. These results agreed with the induced-fit docking against PI3Kα, highlighting the role of p-substituted aromatic rings in guiding the ligand-PI3Kα complex formation, by targeting a hydrophobic pocket in the ligand-binding site and forming π-stacking interactions with a nearby tryptophan residue.

Coronavirus Disease 2019 (COVID-19) is a contagious disease that affects the respiratory system. In addition to the severe effects of the disease on health, the pandemic caused a negative impact on basic needs and services, employment, education, and economy worldwide. In Jordan, the whole country locked down, and quarantine was enforced by the military forces, which successfully controlled the spread of the disease. This research aims to study the influence of the COVID-19 pandemic and its associated quarantine on university students' beliefs about online learning practice in Jordan. An online descriptive survey involved questions that covered students' demographic information, student's basic and advanced knowledge about COVID-19, students' online learning experience during the quarantine, and finally students' views on the enforced quarantine practice in Jordan. Results showed that students have a good knowledge (>50%) about the COVID-19 basic information and a moderate knowledge (90%) supported the military-enforced quarantine implemented in the country despite the hard time the students had during the quarantine. We conclude that university students were able to protect themselves from COVID-19 through their good knowledge about the infectious disease and their commitment to follow the rules imposed by the Government of Jordan. Nevertheless, the challenges caused by the pandemic and its associated quarantine, combined with the sudden unprecedented online experience, negatively impacted students' thoughts and beliefs about the online learning experience during the quarantine. Further studies need to be performed in this context. We hope our results will help decision-makers better understand the students' attitudes and motivation toward online learning and how this will affect their future plans and decisions.

Cancer is a multifactorial disease and the second leading cause of death worldwide. Diverse factors induce carcinogenesis, such as diet, smoking, radiation, and genetic defects. The phosphatidylinositol 3-kinase (PI3K&alpha, ) has emerged as an attractive target for anticancer drug design. Eighteen derivatives of N-phenyl-6-chloro-4-hydroxy-2-quinolone-3-carboxamide were synthesized and characterized using FT-IR, NMR (1H and 13C), and high-resolution mass spectra (HRMS). The series exhibited distinct antiproliferative activity (IC50 &micro, M) against human epithelial colorectal adenocarcinoma (Caco-2) and colon carcinoma (HCT-116) cell lines, respectively: compounds 16 (37.4, 8.9 &micro, M), 18 (50.9, 3.3 &micro, M), 19 (17.0, 5.3 &micro, M), and 21 (18.9, 4.9 &micro, M). The induced-fit docking (IFD) studies against PI3K&alpha, s showed that the derivatives occupy the PI3K&alpha, binding site and engage with key binding residues.

COVID-19 is a biphasic infectious disease with no approved vaccine or pharmacotherapy. The first drug that has shown promise in reducing COVID-19 mortality in severely-ill patients is dexamethasone, a cheap, well-known anti-inflammatory glucocorticoid, approved for the treatment of inflammatory conditions including respiratory diseases such as asthma and tuberculosis. However, about 80% of COVID-19 patients requiring oxygenation, and about 67% of patients on ventilators, are not responsive to dexamethasone therapy mainly. Additionally, using higher doses of dexamethasone for prolonged periods of time can lead to severe side effects and some patients may develop corticosteroid resistance leading to treatment failure. In order to increase the therapeutic efficacy of dexamethasone in COVID-19 patients, while minimizing dexamethasone-related complications that could result from using higher doses of the drug, we applied a chemocentric informatics approach to identify combination therapies. Our results indicated that combining dexamethasone with fast long-acting beta-2 adrenergic agonists (LABAs), such as formoterol and salmeterol, can ease respiratory symptoms hastily, until dexamethasone's anti-inflammatory and immunosuppressant effects kick in. Our studies demonstrated that LABAs and dexamethasone (or other glucocorticoids) exert synergistic effects that will augment both anti-inflammatory and fibronectin-mediated anticoagulant effects. We also propose other alternatives to LABAs that are supported by sound systems biology evidence, such as nitric oxide. Other drugs such as sevoflurane and treprostinil interact with the SARS-CoV-2 interactome and deserve further exploration. Moreover, our chemocentric informatics approach provides systems biology evidence that combination therapies for COVID-19 will have higher chances of perturbing the SARS-CoV-2 human interactome, which may negatively impact COVID-19 disease pathways.

[Coronaviruses (CoVs) are enveloped positive-stranded RNA viruses with spike (S) protein projections that allow the virus to enter and infect host cells. The S protein is a key virulence factor determining viral pathogenesis, host tropism, and disease pathogenesis. There are currently diverse corona viruses that are known to cause disease in humans. The occurrence of Middle East respiratory syndrome coronavirus (MERS-CoV) and Severe Acute Respiratory Syndrome coronavirus (SARS-CoV), as fatal human CoV diseases, has induced significant interest in the medical field. The novel coronavirus disease (COVID-19) is an infectious disease caused by a novel strain of coronavirus (SAR-CoV-2). The SARS-CoV2 outbreak has been evolved in Wuhan, China, in December 2019, and identified as a pandemic in March 2020, resulting in 53.24 M cases and 1.20M deaths worldwide. SARS-CoV-2 main proteinase (M

Even after one year of its first outbreak reported in China, the coronavirus disease 2019 (COVID-19) pandemic is still sweeping the World, causing serious infections and claiming more fatalities. COVID-19 is caused by the novel coronavirus SARS-CoV-2, which belongs to the genus Betacoronavirus (β-CoVs), which is of greatest clinical importance since it contains many other viruses that cause respiratory disease in humans, including OC43, HKU1, SARS-CoV, and MERS. The spike (S) glycoprotein of β-CoVs is a key virulence factor in determining disease pathogenesis and host tropism, and it also mediates virus binding to the host’s receptors to allow viral entry into host cells, i.e., the first step in virus lifecycle. Viral entry inhibitors are considered promising putative drugs for COVID-19. Herein, we mined the biomedical literature for viral entry inhibitors of other coronaviruses, with special emphasis on β-CoVs entry inhibitors. We also outlined the structural features of SARS-CoV-2 S protein and how it differs from other β-CoVs to better understand the structural determinants of S protein binding to its human receptor (ACE2). This review highlighted several promising viral entry inhibitors as potential treatments for COVID-19.

Background. Coronavirus disease 2019 (COVID-19) is expected to continue to cause worldwide fatalities until the World population develops ‘herd immunity’, or until a vaccine is developed and used as a prevention. However, the vaccine may prove ineffective due to rapid changes in viral antigenic determinants. Bacillus Calmette–Guerin (BCG) vaccine has been recognized for its beneficial effects on the immune system, and it is currently in being tested in clinical trials for COVID-19. However, BCG shortages may affect clinical decisions regarding the prioritization of BCG to protect from viral infections, hence, small-molecule BCG-mimics will be valuable alternatives. Methods. We developed and applied a systems biology workflow capable of identifying antiviral drugs and vaccines that can boast immunity and impact viral disease pathways to prevent the fatal consequences of COVID-19. Results. Our results indicate that BCG and small-molecule BCG-mimics affect the production and maturation of naive T cells, which results in enhanced long-lasting innate immune responses to tackle novel viruses. Our workflow identified several antiviral drugs including raltegravir and lopinavir as high confidence BCG mimics. Top hits including emetine and lopinavir were validated to inhibit the growth of novel coronavirus SARS-CoV-2 in vitro. Conclusions. Herein, we provide systems biology support for using BCG as a protection measure from the lethal consequences of emergent viruses including SARS-CoV-2. We also provide systems biology evidence that certain small molecule drugs could mimic the effects of BCG and serve as alternatives to BCG.

Background. Coronavirus disease 2019 (COVID-19) is expected to continue to cause worldwide fatalities until the World population develops ‘herd immunity’, or until a vaccine is developed and used as a prevention. However, the vaccine may prove ineffective due to rapid changes in viral antigenic determinants. Bacillus Calmette–Guerin (BCG) vaccine has been recognized for its beneficial effects on the immune system, and it is currently in being tested in clinical trials for COVID-19. However, BCG shortages may affect clinical decisions regarding the prioritization of BCG to protect from viral infections, hence, small-molecule BCG-mimics will be valuable alternatives. Methods. We developed and applied a systems biology workflow capable of identifying antiviral drugs and vaccines that can boast immunity and impact viral disease pathways to prevent the fatal consequences of COVID-19. Results. Our results indicate that BCG and small-molecule BCG-mimics affect the production and maturation of naive T cells, which results in enhanced long-lasting innate immune responses to tackle novel viruses. Our workflow identified several antiviral drugs including raltegravir and lopinavir as high confidence BCG mimics. Top hits including emetine and lopinavir were validated to inhibit the growth of novel coronavirus SARS-CoV-2 in vitro. Conclusions. Herein, we provide systems biology support for using BCG as a protection measure from the lethal consequences of emergent viruses including SARS-CoV-2. We also provide systems biology evidence that certain small molecule drugs could mimic the effects of BCG and serve as alternatives to BCG.

Background: Drugs incorporating heterocyclic chemical skeletons possess a plethora of therapeutic activities such as anticancer, antimicrobial, antihypertensive, and antipsychiatric effects. It is becoming routine, nowadays, to use cheminformatics and bioinformatics methods to elucidate the mechanism(s) of action of such drugs. Objective: To probe the activity of a recently published series of N1-(anthraquinon-2-yl) amidrazone piperazine derivatives employing computational strategies[1], identify their structural basis of binding to BCR/ABL kinase domain, and explain their anticancer activities in human breast adenocarcinoma (MCF-7) and chronic myelogenous leukemia (K562) cell lines. Methods: We applied an in silico integrative informatics approach integrating molecular descriptors, docking studies, cheminformatics, and network analysis. Results: Our results highlighted the possible involvement of the BCR/ABL and DRD2 pathways in the anticancer activity of the studied compounds, and induced fit docking (IFD) indicated that the BCR/ABL kinase domain is a putative drug target. Additionally, high-scoring docking poses identified a unique network of hydrogen bonding with amino acids Y253, K271, E286, V299, L301, T315, M318, I360, R362, V379, and D3810. Conclusion: Using an integrative informatics approach to characterize our anticancer compounds, we were able to explain the biological differences between synthesized and biologically validated amidrazone piperazine anticancer agents. We were also able to postulate a mechanism of action of this novel group of anticancer agents.

There is accumulating evidence in the biomedical literature suggesting the role of smoking in increasing the risk of oral diseases including some oral cancers. Smoking alters microbial attributes of the oral cavity by decreasing the commensal microbial population and increasing the pathogenic microbes. This study aims to investigate the shift in the salivary microbiota between smokers and non-smokers in Jordan. Our methods relied on high-throughput next-generation sequencing (NGS) experiments for V3-V4 hypervariable regions of the 16S rRNA gene, followed by comprehensive bioinformatics analysis including advanced multidimensional data visualization methods and statistical analysis approaches. Six genera&mdash, Streptococcus, Prevotella, Vellionella, Rothia, Neisseria, and Haemophilus&mdash, predominated the salivary microbiota of all samples with different percentages suggesting the possibility for the salivary microbiome to restored after quitting smoking. Three genera&mdash, Streptococcus, Prevotella, and Veillonella&mdash, showed significantly elevated levels among smokers at the expense of Neisseria in non-smokers. In conclusion, smoking has a definite impact on shifting the salivary microbiota in smokers. We can suggest that there is microbial signature at the genera level that can be used to classify smokers and non-smokers by Linear Discriminant Analysis Effect Size (LEfSe) based on the salivary abundance of genera. Proteomics and metabolomics studies are highly recommended to fully understand the effect of bacterial endotoxin release and xenobiotic metabolism on the bacterial interrelationships in the salivary microbiome and how they affect the growth of each other in the saliva of smokers.

Origanum syriacum is a medicinal plant widely used in Jordan both as a folk remedy and in the food and beverage industry. As the plant can be treated with pesticides during commercial production, three different methods for pesticide multiresidue analysis of this plant have been evaluated. One method based on soxhlet extraction followed by acetonitrile/petroleum ether (PE) partitioning was found to be particularly suitable. Extracts were cleaned-up using a Florisil column. Mean recoveries of pesticides from spiked herbal samples were 74-119%, with coefficients of variation between 1.0 and 23.6%. The limits of detection were in the range 0.0008-0.5 mg kg(-1). The method was used for the determination of pesticide residues in O. syriacum samples purchased from the local market. Seven out of eight samples contained detectable levels of dichlorodiphenyltrichloroethane (DDT), folpet, dicofol, hexachlorobenzene (HCB), hecachlorocyclohexane (HCH), quintozene, transchlordane and vinclozolin.

We have devised a chemocentric informatics methodology for drug discovery integrating independent approaches to mining biomolecular databases. As a proof of concept, we have searched for novel putative cognition enhancers. First, we generated Quantitative Structure-Activity Relationship (QSAR) models of compounds binding to 5-hydroxytryptamine-6 receptor (5-HT(6)R), a known target for cognition enhancers, and employed these models for virtual screening to identify putative 5-HT(6)R actives. Second, we queried chemogenomics data from the Connectivity Map ( http://www.broad.mit.edu/cmap/ ) with the gene expression profile signatures of Alzheimer's disease patients to identify compounds putatively linked to the disease. Thirteen common hits were tested in 5-HT(6)R radioligand binding assays and ten were confirmed as actives. Four of them were known selective estrogen receptor modulators that were never reported as 5-HT(6)R ligands. Furthermore, nine of the confirmed actives were reported elsewhere to have memory-enhancing effects. The approaches discussed herein can be used broadly to identify novel drug-target-disease associations.

Some antipsychotic drugs are known to cause valvular heart disease by activating serotonin 5-HT(2B) receptors. We have developed and validated binary classification QSAR models capable of predicting potential 5-HT(2B) actives. The classification accuracies of the models built to discriminate 5-HT(2B) actives from the inactives were as high as 80% for the external test set. These models were used to screen in silico 59,000 compounds included in the World Drug Index, and 122 compounds were predicted as actives with high confidence. Ten of them were tested in radioligand binding assays and nine were found active, suggesting a success rate of 90%. All validated actives were then tested in functional assays, and one compound was identified as a true 5-HT(2B) agonist. We suggest that the QSAR models developed in this study could be used as reliable predictors to flag drug candidates that are likely to cause valvulopathy.