Modelling multi-protein complexes using PELDOR distance measurements for rigid body minimisation experiments using XPLOR-NIH

Crystallographic and NMR approaches have provided a wealth of structural information about protein domains. However, often these domains are found as components of larger multi domain polypeptides or complexes. Orienting domains within such contexts can provide powerful new insight into their function. The combination of site specific spin labelling and Pulsed Electron Double Resonance (PELDOR) provide a means of obtaining structural measurements that can be used to generate models describing how such domains are oriented. Here we describe a pipeline for modelling the location of thio-reactive nitroxyl spin locations to engineered sties on the histone chaperone Vps75. We then use a combination of experimentally determined measurements and symmetry constraints to model the orientation in which homodimers of Vps75 associate to form homotetramers using the XPLOR-NIH platform. This provides a working example of how PELDOR measurements can be used to generate a structural model

Investigating the dynamic nature of the ABC transporters: ABCB1 and MsbA as examples for the potential synergies of MD theory and EPR applications

ABC transporters are primary active transporters found in all kingdoms of life. Human multidrug resistance transporter ABCB1, or P-glycoprotein, has an extremely broad substrate spectrum and confers resistance against chemotherapy drug treatment in cancer cells. The bacterial ABC transporter MsbA is a lipid A flippase and a homolog to the human ABCB1 transporter, with which it partially shares its substrate spectrum. Crystal structures of MsbA and ABCB1 have been solved in multiple conformations, providing a glimpse into the possible conformational changes the transporter could be going through during the transport cycle. Crystal structures are inherently static, while a dynamic picture of the transporter in motion is needed for a complete understanding of transporter function. Molecular dynamics (MD) simulations and electron paramagnetic resonance (EPR) spectroscopy can provide structural information on ABC transporters, but the strength of these two methods lies in the potential to characterise the dynamic regime of these transporters. Information from the two methods is quite complementary. MD simulations provide an all atom dynamic picture of the time evolution of the molecular system, though with a narrow time window. EPR spectroscopy can probe structural, environmental and dynamic properties of the transporter in several time regimes, but only through the attachment sites of an exogenous spin label. In this review the synergistic effects that can be achieved by combining the two methods are highlighted, and a brief methodological background is also presented

HER2 gene amplification and EGFR expression in a large cohort of surgically staged patients with nonendometrioid (type II) endometrial cancer

Type II endometrial cancers (uterine serous papillary and clear cell histologies) represent rare but highly aggressive variants of endometrial cancer (EC). HER2 and EGFR may be differentially expressed in type II EC. Here, we evaluate the clinical role of HER2 and EGFR in a large cohort of surgically staged patients with type II (nonendometrioid) EC and compare the findings with those seen in a representative cohort of type I (endometrioid) EC. In this study HER2 gene amplification was studied by fluorescence in situ hybridisation (FISH) and EGFR expression by immunohistochemistry. Tissue microarrays were constructed from 279 patients with EC (145 patients with type I and 134 patients with type II EC). All patients were completely surgically staged and long-term clinical follow up was available for 258 patients. The rate of HER2 gene amplification was significantly higher in type II EC compared with type I EC (17 vs 1%, P<0.001). HER2 gene amplification was detected in 17 and 16% of the cases with uterine serous papillary and clear cell type histology, respectively. In contrast, EGFR expression was significantly lower in type II compared with type I EC (34 vs 46%, P=0.041). EGFR expression but not HER2 gene amplification was significantly associated with poor overall survival in patients with type II EC, (EGFR, median survival 20 vs 33 months, P=0.028; HER2, median survival 18 vs 29 months, P=0.113) and EGFR expression retained prognostic independence when adjusting for histology, stage, grade, and age (EGFR, P=0.0197; HER2, P=0.7855). We conclude that assessment of HER2 gene amplification and/or EGFR expression may help to select type II EC patients who could benefit from therapeutic strategies targeting both HER2 and EGFR

COVID-19 infection and nanomedicine applications for development of vaccines and therapeutics: An overview and future perspectives based on polymersomes

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which emerged in December 2019 and caused the coronavirus disease 2019 (COVID-19) pandemic, took the world by surprise with an unprecedented public health emergency. Since this pandemic began, extraordinary efforts have been made by scientists to understand the pathogenesis of COVID-19, and to fight the infection by providing various preventive, diagnostic and treatment opportunities based on either novel hypotheses or past experiences. Despite all the achievements, COVID-19 continues to be an accelerating health threat with no specifically approved vaccine or therapy. This review highlights the recent advances in COVID-19 infection, with a particular emphasis on nanomedicine applications that can help in the development of effective vaccines or therapeutics against COVID-19. A novel future perspective has been proposed in this review based on utilizing polymersome nano-objects for effectively suppressing the cytokine storm, which may reduce the severity of COVID-19 infection

Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors

Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19) has imposed huge challenges on the healthcare facilities, and impacted every aspect of life. This has led to the development of several vaccines against COVID-19 within one year. This study aimed to assess the attitudes and the side effects among Arab communities after receiving a COVID-19 vaccine and use of machine learning (ML) tools to predict post-vaccination side effects based on predisposing factors. Methods: An online-based multinational survey was carried out via social media platforms from June 14 to 31 August 2021, targeting individuals who received at least one dose of a COVID-19 vaccine from 22 Arab countries. Descriptive statistics, correlation, and chi-square tests were used to analyze the data. Moreover, extensive ML tools were utilized to predict 30 post vaccination adverse effects and their severity based on 15 predisposing factors. The importance of distinct predisposing factors in predicting particular side effects was determined using global feature importance employing gradient boost as AutoML. Results: A total of 10,064 participants from 19 Arab countries were included in this study. Around 56% were female and 59% were aged from 20 to 39 years old. A high rate of vaccine hesitancy (51%) was reported among participants. Almost 88% of the participants were vaccinated with one of three COVID-19 vaccines, including Pfizer BioNTech (52.8%), AstraZeneca (20.7%), and Sinopharm (14.2%). About 72% of participants experienced post-vaccination side effects. This study reports statistically significant associations (p < 0.01) between various predisposing factors and post-vaccinations side effects. In terms of predicting post-vaccination side effects, gradient boost, random forest, and XGBoost outperformed other ML methods. The most important predisposing factors for predicting certain side effects (i.e., tiredness, fever, headache, injection site pain and swelling, myalgia, and sleepiness and laziness) were revealed to be the number of doses, gender, type of vaccine, age, and hesitancy to receive a COVID-19 vaccine. Conclusions: The reported side effects following COVID-19 vaccination among Arab populations are usually non-life-threatening; flu-like symptoms and injection site pain. Certain predisposing factors have greater weight and importance as input data in predicting post-vaccination side effects. Based on the most significant input data, ML can also be used to predict these side effects; people with certain predicted side effects may require additional medical attention, or possibly hospitalization

Comprehensive Structural and Molecular Comparison of Spike Proteins of SARS-CoV-2, SARS-CoV and MERS-CoV, and Their Interactions with ACE2

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has recently emerged in China and caused a disease called coronavirus disease 2019 (COVID-19). The virus quickly spread around the world, causing a sustained global outbreak. Although SARS-CoV-2, and other coronaviruses, SARS-CoV and Middle East respiratory syndrome CoV (MERS-CoV) are highly similar genetically and at the protein production level, there are significant differences between them. Research has shown that the structural spike (S) protein plays an important role in the evolution and transmission of SARS-CoV-2. So far, studies have shown that various genes encoding primarily for elements of S protein undergo frequent mutation. We have performed an in-depth review of the literature covering the structural and mutational aspects of S protein in the context of SARS-CoV-2, and compared them with those of SARS-CoV and MERS-CoV. Our analytical approach consisted in an initial genome and transcriptome analysis, followed by primary, secondary and tertiary protein structure analysis. Additionally, we investigated the potential effects of these differences on the S protein binding and interactions to angiotensin-converting enzyme 2 (ACE2), and we established, after extensive analysis of previous research articles, that SARS-CoV-2 and SARS-CoV use different ends/regions in S protein receptor-binding motif (RBM) and different types of interactions for their chief binding with ACE2. These differences may have significant implications on pathogenesis, entry and ability to infect intermediate hosts for these coronaviruses. This review comprehensively addresses in detail the variations in S protein, its receptor-binding characteristics and detailed structural interactions, the process of cleavage involved in priming, as well as other differences between coronaviruses

Artificial Neural Networks Model for Predicting Type 2 Diabetes Mellitus Based on VDR Gene FokI Polymorphism, Lipid Profile and Demographic Data

Type 2 diabetes mellitus (T2DM) is a multifactorial disease associated with many genetic polymorphisms; among them is the FokI polymorphism in the vitamin D receptor (VDR) gene. In this case-control study, samples from 82 T2DM patients and 82 healthy controls were examined to investigate the association of the FokI polymorphism and lipid profile with T2DM in the Jordanian population. DNA was extracted from blood and genotyped for the FokI polymorphism by polymerase chain reaction (PCR) and DNA sequencing. Lipid profile and fasting blood sugar were also measured. There were significant differences in high-density lipoprotein (HDL) cholesterol and triglyceride levels between T2DM and control samples. Frequencies of the FokI polymorphism (CC, CT and TT) were determined in T2DM and control samples and were not significantly different. Furthermore, there was no significant association between the FokI polymorphism and T2DM or lipid profile. A feed-forward neural network (FNN) was used as a computational platform to predict the persons with diabetes based on the FokI polymorphism, lipid profile, gender and age. The accuracy of prediction reached 88% when all parameters were included, 81% when the FokI polymorphism was excluded, and 72% when lipids were only included. This is the first study investigating the association of the VDR gene FokI polymorphism with T2DM in the Jordanian population, and it showed negative association. Diabetes was predicted with high accuracy based on medical data using an FNN. This highlights the great value of incorporating neural network tools into large medical databases and the ability to predict patient susceptibility to diabetes

The Use of Conjunctions as Grammatical Cohesion in the Speeches of Her Majesty Queen Rania of Jordan

Halliday and Hasan (1976) differentiated between four types of conjunctions namely, additive, causal, temporal and adversative. Thus, conjunctions are words used to combine two sentences, this paper examines the conjunctions in the speeches of Her Majesty Queen Rania of Jordan based on Halliday and Hasan (ibid). The investigator in this current study selected four different speeches which were delivered by Queen Rania in Jordan and USA in the years 2007, 2009, 2011 and 2013. The results show that there are some differences in the frequency of additive, causal, adversative and temporal conjunctions. The study concluded that, additive conjunctions were the most frequent conjunctions followed by adversative conjunctions and then causal conjunctions and finally the least occurrences were for temporal conjunctions

Association of Breastfeeding Duration with Susceptibility to Allergy, Influenza, and Methylation Status of TLR1 Gene

Background and Objectives: This study aimed to investigate the possible association between exclusive breastfeeding duration during early infancy and susceptibility to allergy and influenza in adulthood. Furthermore, we also investigated the association of breastfeeding duration with DNA methylation at two sites in the promoter of the toll-like receptor-1 (TLR1) gene, as well as the association between DNA methylation of the toll-like receptor-1 (TLR1) gene and susceptibility to different diseases. Materials and Methods: Blood samples were collected from 100 adults and classified into two groups according to breastfeeding duration (&lt;6 months and &ge;6 months) during infancy. Subjects were asked to complete a questionnaire on their susceptibilities to different diseases and sign a consent form separately. Fifty-three samples underwent DNA extraction, and the DNA samples were divided into two aliquots, one of which was treated with bisulfite reagent. The promoter region of the TLR1 gene was then amplified by polymerase chain reaction (PCR) and sequenced. Results: We found a significant association between increased breastfeeding duration and a reduction in susceptibility to influenza and allergy, as well asa significant reduction in DNA methylation within the promoter of the TLR1 gene. No association was found between DNA methylation and susceptibility to different diseases. Conclusions: The findings demonstrate the significance of increased breastfeeding duration for improved health outcomes at the gene level

A Pragmatic Analysis of Spatial Deixis in the Discussions of the General Budget by the Jordanian MPs for the Financial Year 2017

Pragmatics as a sub-branch of applied linguistics deals with language and its context. Deixis belongs to the area of pragmatics because it directly involves the relationship between the structure of language and the context in which it is used Levinson (1983:55). The present study investigates the use of spatial deixis in the speeches delivered by the Jordanian parliament members discussing the general budget. Ten different speeches were randomly selected from a number of speeches delivered by members of the eighteenth Jordanian parliament in discussion of general budget 2017. The study analyses spatial deixis in terms of occurrence frequency. The study concludes that proximal terms are the most frequent used by MPs followed by distal terms whereas medial terms were the least occurred ones