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A parametric study of several parameters relevant to design safety on the spent nuclear fuel (SNF) rod response under a drop accident is presented. In the view of the complexity of interactions between the independent safety-related parameters, a factorial design of experiment is employed as an efficient method to investigate the main effects and the interactions between them. A detailed single full-length fuel rod is used with consideration of post-irradiated fuel conditions under horizontal and vertical free-drops onto an unyielding surface using finite-element analysis. Critical drop heights and critical g-loads that yield the threshold plastic strain in the cladding are numerically estimated to evaluate the fuel rod structural resistance to impact load. The combinatory effects of four uncertain parameters (pellet-cladding interfacial bonding, material properties, spacer grid stiffness, rod internal pressure) and the interactions between them on the fuel rod response are investigated. The principal finding of this research showed that the effects of above-mentioned parameters on the load-carrying capacity of fuel rod are significantly different. This study could help to prioritize the importance of data in managing and studying the structural integrity of the SNF. Keywords: Spent nuclear fuel, Drop impact, Structural response, Design of experiments, Finite-element analysis

Introduction: Hyperlipidemia increases the risk of many diseases including coronary artery disease and atherosclerosis. Nutritional knowledge may act as a deterrent against unhealthy nutrition trend which is strongly associated with hyperlipidemia. We aim to evaluate the dietary habits and their influence on serum lipid profiles among university students. Methods: This study was an analytical descriptive design that started in June and finished in September 2018. A total of 200 students (100 males and 100 females), aged between 18-22 years were evaluated. Sociodemographic data and health-related data situations, lifestyle practices, and eating habits of the study population were reported by an interview questionnaire. The biochemical evaluation for total cholesterol (TC), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and Triglycerides (TG) was carried out. A significant result means that the P-value for the hypothesis tests was less than 0.05 at confidence intervals 95%. Results: Male students were more likely to be healthier eating habits compared to female students in terms of regular breakfast intake, regular lunch intake, and regular dinner intake. The majority of students (67.5%) eat two to three meals per day. Most students (60.0%) thought that eating meats, vegetables and other variety of foods are the keys to point of a balanced diet. On the other hand, the prevalence of hypercholesterolemia was significantly higher in male students than females and, the prevalence of elevated LDL was higher in female students than males. Conclusion: Despite the students having some unhealthy eating habits, however, their eating habits were non significantly associated with a higher prevalence of the three hyperlipidemias.

Double spatial modulation (DSM) is a transmission technique which has been recently proposed for multiple-input multiple-output (MIMO) communication systems. DSM has a higher spectral efficiency compared with classical spatial modulation (SM), as it doubles the number of active transmit antennas. In this paper, transmit antenna selection (TAS) is applied to DSM in order to enhance the bit error rate (BER) performance. In particular, we integrate two sub-optimal TAS algorithms to DSM; namely, capacity-optimized antenna selection (COAS) and antenna selection based on amplitude and antenna correlation (A-C-AS). Simulation results of these two algorithms are presented and compared with the optimal Euclidean distance-optimized antenna selection (EDAS) using MATLAB software. Our results show a complexity-performance trade-off. Although there is a negligible loss of BER, our algorithms are much less complex than EDAS.

Abstract Background Ictal asystole is a rare phenomenon. Most reported cases are in persons with long-standing focal epilepsy originating from the temporal lobe. Its occurrence may complicate the clinical presentation or delay diagnosis, and it is thought to be associated with increased risk of sudden unexpected death in epilepsy. Case presentation We report the case of a 55-year-old female person with epilepsy who suffered ictal asystole for 10 s while under monitoring at the Epilepsy Monitoring Unit. We then review briefly the pathophysiology and current management modalities for this phenomenon. Discussion The first step in management of this condition is usually the optimization of anti-seizure drugs. In our case, a 2-year fall-free period was achieved with optimization of medical treatment. Pacemaker implantation can also be attempted to prevent ictal asystole-related falls and injury, while refractory cases may benefit from epilepsy surgery in terms of both seizure control and prevention of ictal asystole.

Nowadays, skin disease among humans has been a common disease, especially in America millions of people are suffering from various kinds of skin disease. Usually, these diseases have hidden dangers which lead to human not only lack of self-confidence and psychological depression but also a risk of skin cancer. Diagnosis of these kinds of diseases usually required medical experts with high-level instruments due to a lack of visual resolution in skin disease images. Moreover, manual diagnosis of skin disease is often subjective, time-consuming, and required more human effort. Thus, there is a need to develop a computer-aided system that automatically diagnoses the skin disease problem. Moreover, most of the existing works in skin disease used convolutional neural networks (CNN) with classical loss functions, which limit the model to learn discriminative features from skin images. Thus to address the above mention problem we proposed a new framework by fine-tuning layers of ResNet152 and InceptionResNet-V2 models with a triplet loss function. In the proposed framework, first, we learning the embedding from input images into Euclidean space by using deep CNN ResNet152 and InceptionResNet-V2 model. Second, we compute L-2 distance among corresponding images from euclidean space to learn discriminative features of skin disease images by using triplet loss function. Finally, classify the input images using these L-2 distances. Human face skin disease images used in the proposed framework are acquired from the Hospital in Wuhan China. Experiment results and their analysis shows the effectiveness of the proposed framework which achieve better accuracy than many existing works in skin disease tasks.

Abstract Background Familial cases of adult acute myeloid leukemia (AML) with germline‐mutated CCAAT/enhancer‐binding protein‐α (CEBPA) gene are a rare entity classified in World Health Organization (WHO) classification 2016. Most families reported in the literature show an autosomal dominant inheritance pattern consistent with a single‐gene mutation. Methods Here we studied a Syrian family with four individuals suffering from AML for CEBPA gene mutations by Sanger sequencing. Results The father, his three affected, and one yet unaffected child had the same mutation in the N‐terminal region of CEBPA (c.198dupC), resulting in termination at Tyr67Leufs*41. All affected family members had a good primary response to chemotherapy and achieved complete remission. Conclusion Overall, another AML family with CEBPA gene mutation is added to the literature, presenting with yet unreported FAB subtype M5 and absence of CD7 expression in some family members.

An understanding of indoor environmental quality (IEQ) and its effects on occupant well-being can inform building system design and operation. The use of wearables in field studies to collect subjective and objective health performance indicators (HPIs) from a large number of occupants could deliver important improvements in IEQ. To facilitate the use of wearables in IEQ studies, there is a need to identify which HPIs should be collected and to evaluate data accessibility from these devices. To address this issue, a literature review of previous IEQ studies was conducted to identify relationships between different IEQ factors and HPIs, with a focus on HPIs that were collected using wearables. A preliminary assessment of data accessibility from a selected wearable device (Fitbit Versa 2) was performed and documented. The review suggested the need to further investigate and collect sleep quality parameters, heart rate, stress response, as well as subjective ratings of comfort using wearables. The data accessibility assessment revealed issues related to missing data points and data resolution from the examined device. A set of recommendations is outlined to inform future studies.

Summary:. Since its first emergence, coronavirus disease 2019 (COVID-19) took the world by surprise, causing more than two million deaths and 100 million infections to date. The virus’s most prevalent clinical symptoms have become well known, yet the rarer symptoms, on the other hand, need to be more widely recognized. Various studies have reflected the possibilities of potential skin lesions being the presenting signs of COVID-19 infection. Acquaintance with the cutaneous presentations of COVID-19 may help in early diagnosis and management of infected patients. Herein we report two cases that presented for plastic surgical interventions in which skin manifestations were the first indicators of COVID-19 infection or postvaccination sequel. The cases were operated upon in different hospitals by different surgical teams.

Poststroke depression (PSD) is common and remains a significant risk factor for poor outcomes. This prospective study is aimed at assessing the prevalence, severity, and predictors of PSD among Jordanian stroke survivors. A total of 151 patients who were consequently admitted to a tertiary teaching hospital with ischemic or hemorrhagic strokes were enrolled. Participants were screened on admission for premorbid depression using the PHQ-9 questionnaire; then, screening for PSD was repeated one and three months after stroke using the same tool. Depression prevalence at each screening was reported, and logistic regression analysis was conducted to evaluate for significant predictors. PHQ-9 scores suggestive of depression were reported by 15%, 24.83%, and 17.39% of respondents on admission and after one and three months, respectively. Scores suggesting severe depression were reported by 0.71%, 2.13%, and 6.52% of respondents, respectively. Significant predictors of PSD were having chronic kidney disease, current smoking status, moderate or severe disability (mRS score) at stroke onset, and severe dependence (BI) after one month (p values 0.007, 0,002, 0.014, and 0.031, respectively). Patients with secondary and high school education levels were less likely to get depression compared with illiterate patients (p 0.042). This study showed that nearly one in four Jordanian stroke survivors experienced PSD after one month. In contrast, while the overall PSD prevalence declined towards the end of follow-up period, patients who remained depressed showed a tendency towards higher PSD severity.

Sentiment analysis has recently become increasingly important with a massive increase in online content. It is associated with the analysis of textual data generated by social media that can be easily accessed, obtained, and analyzed. With the emergence of COVID-19, most published studies related to COVID-19’s conspiracy theories were surveys on the people's sentiments and opinions and studied the impact of the pandemic on their lives. Just a few studies utilized sentiment analysis of social media using a machine learning approach. These studies focused more on sentiment analysis of Twitter tweets in the English language and did not pay more attention to other languages such as Arabic. This study proposes a machine learning model to analyze the Arabic tweets from Twitter. In this model, we apply Word2Vec for word embedding which formed the main source of features. Two pretrained continuous bag-of-words (CBOW) models are investigated, and Naïve Bayes was used as a baseline classifier. Several single-based and ensemble-based machine learning classifiers have been used with and without SMOTE (synthetic minority oversampling technique). The experimental results show that applying word embedding with an ensemble and SMOTE achieved good improvement on average of F1 score compared to the baseline classifier and other classifiers (single-based and ensemble-based) without SMOTE.

Breast cancer disease is one of the most recorded cancers that lead to morbidity and maybe death among women around the world. Recent research statistics have exposed that one from 8 females in the USA and one from 10 females in Europe are contaminated by breast cancer. The challenge with this disease is how to develop a relaxed and fast diagnosing method. One of the attractive ways of early breast cancer diagnosis is based on the mammogram images analysis of the breast using a computer-aided diagnosing (CAD) tool. This paper firstly aimed to propose an efficient method for diagnosing tumors based on mammogram images of breasts using a machine learning approach. Secondly, this paper aimed to the development of a CAD software program for breast cancer diagnosing based on the proposed method in the first step. The followed step-by-step procedure of the proposed method is performed by passing the Mammographic Image Analysis Society (MIAS) through five steps of image preprocessing, image segmentation using seeded region growing (SRG) algorithm, feature extraction using different feature’s extraction classes, and important and effectiveness feature selection using the Sequential Forward Selection (SFS) technique, and finally, the Support Vector Machine (SVM) algorithm is used as a binary classifier in two classification levels. The first level classifier is used to categorize the given image as normal or abnormal while the second-level classifier is used for further classifying the abnormal image as either a malignant or benign cancer. The proposed method is studied and investigated in two phases: the training phase and the testing phase, with the MIAS dataset of mammogram images, using 70% and 30% ratios of dataset images for the training and testing sets, respectively. The practical implementation of the proposed method and the graphical user interface (GUI) CAD tool are carried out using MATLAB software. Experimental results of the proposed method have shown that the accuracy of the proposed method reached 100% in classifying images as normal and abnormal mammogram images while the classification accuracy for benign and malignant is equal to 87.1%.

Background: Colorectal cancer is a leading cause of mortality worldwide. Resistance of this cancer to the available chemotherapeutic agents creates a need to develop new therapeutic agents. Pentoxifylline (PTX) has been shown to have anticancer effects on multiple cancer types. Objective: In this study, we evaluated the anticancer effect of PTX in CRC cells. Methods: We measured PTX's effect on cell proliferation using the MTT assay and on cell death induction by PI staining/flowcytometry. We also assessed the effect of treatment on mitochondrial membrane potential (MMP). Results: We found that PTX arrested the growth SW480 CRC cells with a peak effect plateauing at 10 mM of PTX after 72 h of treatment. Surprisingly, similar effect wasn't noticed in HCT-116 cells. Similar pattern of effect was noticed on apoptosis of both cell lines, as PTX induced more apoptosis on SW480 cells with no similar effect on HCT-116 cells. Studies using variable caspase inhibitors showed involvement of primarily capsase-9, as well as caspases-2 and -3 but not capsase-8. PTX also induced MMP changes leading to caspase-dependent apoptotic cell death. In addition to that, results indicated that apoptosis was caspase-dependent and was mediated through the mitochondria. Conclusion: These findings indicate that PTX has a promising antitumor activity against CRC cells and warrants further clinical evaluation.

Recently, transfer learning approaches appeared to reduce the need for many classified medical images. However, these approaches still contain some limitations due to the mismatch of the domain between the source domain and the target domain. Therefore, this study aims to propose a novel approach, called Dual Transfer Learning (DTL), based on the convergence of patterns between the source and target domains. The proposed approach is applied to four pre-trained models (VGG16, Xception, ResNet50, MobileNetV2) using two datasets: ISIC2020 skin cancer images and ICIAR2018 breast cancer images, by fine-tuning the last layers on a sufficient number of unclassified images of the same disease and on a small number of classified images of the target task, in addition to using data augmentation techniques to balance classes and to increase the number of samples. According to the obtained results, it has been experimentally proven that the proposed approach has improved the performance of all models, where without data augmentation, the performance of the VGG16 model, Xception model, ResNet50 model, and MobileNetV2 model are improved by 0.28%, 10.96%, 15.73%, and 10.4%, respectively, while, with data augmentation, the VGG16 model, Xception model, ResNet50 model, and MobileNetV2 model are improved by 19.66%, 34.76%, 31.76%, and 33.03%, respectively. The Xception model obtained the highest performance compared to the rest of the models when classifying skin cancer images in the ISIC2020 dataset, as it obtained 96.83%, 96.919%, 96.826%, 96.825%, 99.07%, and 94.58% for accuracy, precision, recall, F1-score, sensitivity, and specificity respectively. To classify the images of the ICIAR 2018 dataset for breast cancer, the Xception model obtained 99%, 99.003%, 98.995%, 99%, 98.55%, and 99.14% for accuracy, precision, recall, F1-score, sensitivity, and specificity, respectively. Through these results, the proposed approach improved the models’ performance when fine-tuning was performed on unclassified images of the same disease.

Severe aortic stenosis (AS) is a common pathological condition in an ageing population imposing significant morbidity and mortality. Based on distinct hemodynamic features, i.e., ejection fraction (EF), transvalvular gradient and stroke volume, four different AS subtypes can be distinguished: (i) normal EF and high gradient, (ii) reduced EF and high gradient, (iii) reduced EF and low gradient, and (iv) normal EF and low gradient. These subtypes differ with respect to pathophysiological mechanisms, cardiac remodeling, and prognosis. However, little is known about metabolic changes in these different hemodynamic conditions of AS. Thus, we carried out metabolomic analyses in serum samples of 40 AS patients (n = 10 per subtype) and 10 healthy blood donors (controls) using ultrahigh-performance liquid chromatography–tandem mass spectroscopy. A total of 1293 biochemicals could be identified. Principal component analysis revealed different metabolic profiles in all of the subgroups of AS (All-AS) vs. controls. Out of the determined biochemicals, 48% (n = 620) were altered in All-AS vs. controls (p < 0.05). In this regard, levels of various acylcarnitines (e.g., myristoylcarnitine, fold-change 1.85, p < 0.05), ketone bodies (e.g., 3-hydroxybutyrate, fold-change 11.14, p < 0.05) as well as sugar metabolites (e.g., glucose, fold-change 1.22, p < 0.05) were predominantly increased, whereas amino acids (e.g., leucine, fold-change 0.8, p < 0.05) were mainly reduced in All-AS. Interestingly, these changes appeared to be consistent amongst all AS subtypes. Distinct differences between AS subtypes were found for metabolites belonging to hemoglobin metabolism, diacylglycerols, and dihydrosphingomyelins. These findings indicate that relevant changes in substrate utilization appear to be consistent for different hemodynamic subtypes of AS and may therefore reflect common mechanisms during AS-induced heart failure. Additionally, distinct metabolites could be identified to significantly differ between certain AS subtypes. Future studies need to define their pathophysiological implications.

Background: This study sought to determine whether (1) evidence is available of interactions between anodal tDCS and oscillated tDCS stimulation patterns to increase the power of endogenous brain oscillations and (2) the frequency matching the applied anodal otDCS’s frequency and the brain’s dominant intrinsic frequency influence power shifting during stimulation pattern sessions by both anodal DCS and anodal oscillated DCS. Method: Rats received different anodal tDCS and otDCS stimulation patterns using 8.5 Hz and 13 Hz state-related dominant intrinsic frequencies of anodal otDCS. The rats were divided into groups with specific stimulation patterns: group A: tDCS–otDCS (8.5 Hz)–otDCS (13 Hz); group B: otDCS (8.5 Hz)–tDCS–otDCS (13 Hz); group C: otDCS (13 Hz)–tDCS–otDCS (8.5 Hz). Acute relative power changes (i.e., following 10 min stimulation sessions) in six frequency bands—delta (1.5–4 Hz), theta (4–7 Hz), alpha-1 (7–10 Hz), alpha-2 (10–12 Hz), beta-1 (12–15 Hz) and beta-2 (15–20 Hz)—were compared using three factors and repeated ANOVA measurement. Results: For each stimulation, tDCS increased theta power band and, above bands alpha and beta, a drop in delta power was observed. Anodal otDCS had a mild increasing power effect in both matched intrinsic and delta bands. In group pattern stimulations, increased power of endogenous frequencies matched exogenous otDCS frequencies—8.5 Hz or 13 Hz—with more potent effects in upper bands. The power was markedly more potent with the otDCS–tDCS stimulation pattern than the tDCS–otDCS pattern. Significance: The findings suggest that the otDCS–tDCS pattern stimulation increased the power in matched intrinsic oscillations and, significantly, in the above bands in an ascending order. We provide evidence for the successful corporation between otDCS (as frequency-matched guidance) and tDCS (as a power generator) rather than tDCS alone when stimulating a desired brain intrinsic band (herein, tES specificity).

Information systems security is a core factor in the development and using of computer information systems which provides security for the data and privacy for users; and humans are one of the major key players in this field. Some of human behaviors that leads to security breaches in computer information systems include Ignorance, negligence, indifference, and lack of awareness in information security. In this research, we are spotting the light on the importance of information system security policies in higher educational institutions in Palestine – Hebron University case study. The importance of this research lies in knowing the reality of information systems security policies in Palestinian universities and knowing the factors affecting adherence to information security policies such as knowledge of information security, experience, and educational level. The study concluded that the degree of knowledge about the security of information systems and their adherence by the staff of Hebron University was high. The study also concluded that there are statistically significant differences related to the staff adherence to information systems security policies according to the educational level and experience. The study has recommended the necessity of following up the implementation of information systems security policies, and updating and reviewing them in line with the requirements of the next phase and the tremendous technological development the world is witnessing.

The soybean oil, medium-chain triglycerides, olive oil, and fish oil lipid (SMOFlipid) is increasingly being used worldwide without definite evidence of its benefits. We examined the effect of SMOFlipid on growth velocity and neonatal morbidities in very preterm infants. Very preterm infants who received soybean-based lipid emulsion between January 2015 and 2018 were compared with those who received SMOFlipids between 2019 and January 2022 in our neonatal tertiary center. Linear regression analysis was conducted to analyze the association between type of lipid emulsion and growth velocity. Modified log-Poisson regression with generalized linear models and a robust variance estimator (Huber–White) were applied to adjust for potential confounding factors. A total of 858 infants met our inclusion criteria. Of them, 238 (27.7%) received SMOFlipid. SMOFlipid was associated with lower growth velocity between birth and 36-week corrected gestational age compared with intralipid Δ weight z-score (adjusted mean difference (aMD) −0.67; 95% CI −0.69, −0.39). Subgroup analysis indicated that mainly male infants in the SMOFlipid–LE group had a lower Δ weight z-score compared to those in the intralipid group (p < 0.001), with no difference observed in females (p = 0.82). SMOFlipid was associated with a lower rate of bronchopulmonary dysplasia (BPD) (aRR 0.61; 95% CI 0.46, 0.8) and higher rate of late-onset sepsis compared with intralipid (aRR 1.44; 95% CI 1.22–1.69). SMOFlipid was associated with lower growth velocity and BPD but higher rate of late-onset sepsis—it is a double-edged sword.

Pituitary apoplexy is a clinical syndrome caused by hemorrhage or infarction of a pituitary adenoma. There have been a few reports in the literature of rapid onset of pituitary apoplexy after goserelin injection. To the best of our knowledge, there is no publication in the literature reporting re-introducing goserelin therapy for patients with prostate cancer after the onset of pituitary apoplexy. In this case report, we present the onset and clinico-radiological course of pituitary apoplexy induced by the initiation of goserelin and during continuation of goserelin with up to five-years follow-up.

Medical education continually adapts to the needs of future health care professionals, with student motivation in research being a pivotal aspect. This study at Alfaisal University aimed to explore the motivations, benefits, and challenges faced by medical students in extracurricular research activities. Using a mixed-method approach, we combined quantitative surveys with qualitative group interviews. Findings revealed that both extrinsic (e.g., enhancing postgraduate training prospects) and intrinsic (e.g., personal interest and skill refinement) factors significantly motivate students to be involved in research activities. Participants unanimously acknowledged skill enhancement, particularly in literature comprehension, creative ideation, and networking. However, challenges such as conflicts with course scheduling, lack of hands-on experiences, and mentorship issues were identified as potential barriers to research participation. Addressing these barriers and understanding motivations can inform the design of research programs, enhancing the overall student research experience. This study underscores the importance of research in medical education, emphasizing the need for institutions to prioritize addressing challenges and leveraging benefits to prepare medical students for a research-integrated clinical future.

Steganography is the technique of hiding secret data (message) within any media such as digital color image. In this paper we will merge steganography process with cryptography process in order to increase the security of the proposed method. The steganography process will based on LSB method, while the cryptography process will based on generating a huge private key and selecting a special function for encryption decryption. The proposed method will be implemented in order to calculate some performance parameters to prove the efficiency of the proposed method.

Abstract Aims Volume overload (VO) and pressure overload (PO) induce differential cardiac remodelling responses including distinct signalling pathways. Extracellular signal‐regulated kinases 1 and 2 (ERK1/2), key signalling components in the mitogen‐activated protein kinase (MAPK) pathways, modulate cardiac remodelling during pressure overload (PO). This study aimed to assess their role in VO‐induced cardiac remodelling as this was unknown. Methods and results Aortocaval fistula (Shunt) surgery was performed in mice to induce cardiac VO. Two weeks of Shunt caused a significant reduction of cardiac ERK1/2 activation in wild type (WT) mice as indicated by decreased phosphorylation of the TEY (Thr‐Glu‐Tyr) motif (−28% as compared with Sham controls, P < 0.05). Phosphorylation of other MAPKs was unaffected. For further assessment, transgenic mice with cardiomyocyte‐specific ERK2 overexpression (ERK2tg) were studied. At baseline, cardiac ERK1/2 phosphorylation in ERK2tg mice remained unchanged compared with WT littermates, and no overt cardiac phenotype was observed; however, cardiac expression of the atrial natriuretic peptide was increased on messenger RNA (3.6‐fold, P < 0.05) and protein level (3.1‐fold, P < 0.05). Following Shunt, left ventricular dilation and hypertrophy were similar in ERK2tg mice and WT littermates. Left ventricular function was maintained, and changes in gene expression indicated reactivation of the foetal gene program in both genotypes. No differences in cardiac fibrosis and kinase activation was found amongst all experimental groups, whereas apoptosis was similarly increased through Shunt in ERK2tg and WT mice. Conclusions VO‐induced eccentric hypertrophy is associated with reduced cardiac ERK1/2 activation in vivo. Cardiomyocyte‐specific overexpression of ERK2, however, does not alter cardiac remodelling during VO. Future studies need to define the pathophysiological relevance of decreased ERK1/2 signalling during VO.

Abstract Background The discovery and development of anticancer still remain a challenge especially regarding the problem of cancer cell selectivity. Matrix metalloproteinase (MMP) was broadly studied as one of the protein targets to stop cancer angiogenesis as well as its cell migration. Main text The MMP degrades extracellular matrix (ECM) such as collagen and gelatin which are important to control the cell migration from one to other sites. In cancer, this cell migration is regarded with metastasis, which is essential for the formation of new blood vessels called angiogenesis. The most common target in MMP, i.e. the catalytic site, is currently reported as being the non-selective target for inhibitor compounds that inhibit all MMPs but is associated with adverse side effects. Hemopexin, especially in MMP9 (PEX9) was found to be different from other domains in the MMP family which could potentially be the next target for anticancer due to the availability of its crystal structure in the Protein Data Bank (PDB). Conclusion The PEX9 crystal structure was resolved as a homodimer connected by a hydrophobic area between two blades along the β-propeller which its structure and function for computational drug modelling can be studied.

Abstract Background Stereotactic ablative radiotherapy (SABR) has emerged as a new treatment option for patients with oligometastatic disease. SABR delivers precise, high-dose, hypofractionated radiotherapy, and achieves excellent rates of local control for primary tumors or metastases. A recent randomized phase II trial evaluated SABR in a group of patients with a small burden of oligometastatic disease (mostly with 1–3 metastatic lesions), and found that SABR was associated with benefits in progression-free survival and overall survival. The goal of this phase III trial is to assess the impact of SABR in patients with 4–10 metastatic cancer lesions. Methods One hundred and fifty-nine patients will be randomized in a 1:2 ratio between the control arm (consisting of standard of care palliative-intent treatments), and the SABR arm (consisting of standard of care treatment + SABR to all sites of known disease). Randomization will be stratified by two factors: histology (Group 1: prostate, breast, or renal; Group 2: all others), and type of pre-specified systemic therapy (Group 1: immunotherapy/targeted; Group 2: cytotoxic; Group 3: observation). SABR is to be completed within 2 weeks, allowing for rapid initiation of systemic therapy. Recommended SABR doses are 20 Gy in 1 fraction, 30 Gy in 3 fractions, or 35 Gy in 5 fractions, chosen to minimize risks of toxicity. The primary endpoint is overall survival, and secondary endpoints include progression-free survival, time to development of new metastatic lesions, quality of life, and toxicity. Translational endpoints include assessment of circulating tumor cells, cell-free DNA, and tumor tissue as prognostic and predictive markers, including assessment of immunological predictors of response and long-term survival. Discussion This study will provide an assessment of the impact of SABR on clinical outcomes and quality of life, to determine if long-term survival can be achieved for selected patients with 4–10 oligometastatic lesions. Trial registration Clinicaltrials.gov identifier: NCT03721341. Date of registration: October 26, 2018.

Summary: Background & aims: Metabolic syndrome is a cluster of the most dangerous heart attack risk factors. The present study aimed to examine the effects of vitamin C supplementation with and without endurance physical activity on components of metabolic syndrome in a group of Iraqi adults. Methods: In a parallel-randomized placebo controlled trial, 120 metabolic syndrome patients were randomly assigned into four groups. Fasting blood samples were taken at study baseline and after 12 weeks of intervention. All statistical analysis was performed using SPSS version 20. Results: The mean vitamin C levels was increased significantly in both vitamin C and vitamin C plus physical activity groups (P value = 0.001). Vitamin C plus physical activity led to a significant reduction in systolic blood pressure compared to the placebo group (P value = 0.04). In addition, a significant changes in serum levels of total cholesterol were seen following vitamin C plus physical activity than that in the placebo group (P value = 0.04). Furthermore, vitamin C supplementation significantly affected BMI compared with the placebo group (P value = 0.02). No significant differences were found between the study groups in terms of triglyceride, LDL-C, HDL-C, fasting blood sugar, weight, waist circumference and diastolic blood pressure. Conclusion: Daily supplementation of vitamin C (500 mg/day), for 12 weeks resulted in a significant reduction in BMI. However, the combination of physical activities and vitamin C supplements may improve systolic blood pressure and serum levels of total cholesterol in metabolic syndrome patients and this combination should be recommended. Trial registration: WHO-ICTRP, IRCT20161110030823N2. Registered 01 February 2018, http://apps.who.int/trialsearch/Trial2.aspx?TrialID=IRCT20161110030823N2. Keywords: Iraq, Metabolic syndrome, Physical activity, Vitamin C

Colour image retrieval, identification and recognition play an important role in vital computerized applications, so creating an image signature which can be used as a key to identify the image is an essential and important problem to be solved. In this paper a new method of image signature extraction will be proposed. The proposed method will be implemented and tested and the experimental results will be compared with other method results to prove the efficiency of the proposed method by mean of creating a unique signature which will require a minimum memory space and a smaller time to extract the signature.

Deep learning algorithms have achieved remarkable results in the natural language processing(NLP) and computer vision. Hence, a trend still going on to use these algorithms, such as convolution and recurrent neural networks, for text analytic task to extract useful information. Features extraction is one of the important reasons behind the success of these networks. Moreover passing features from one layer to another layer within the network and one network to another network have done. However multilevel and multitype features fusion remains unexplored in sentiment analysis. So, in this paper, we use three datasets to display the advantages of extracting and fusing multilevel as well as multitype features from different neural networks. Multilevel features are from different layers of the same network, and multitype features are from different network architectures. Experiment results demonstrate that the proposed model based on multilevel and multitype weighted features fusion outperforms than many exiting works with an accuracy of 80.2%, 48.2%, and 87.0% on MR, SST1, and SST2 datasets respectively.

Cloud computing is extensively used in a variety of applications and domains, however task and resource scheduling remains an area that requires improvement. Put simply, in a heterogeneous computing system, task scheduling algorithms, which allow the transfer of incoming tasks to machines, are needed to satisfy high performance data mapping requirements. The appropriate mapping between resources and tasks reduces makespan and maximises resource utilisation. In this contribution, we present a novel scheduling algorithm using Directed Acyclic Graph (DAG) based on the Prediction of Tasks Computation Time algorithm (PTCT) to estimate the preeminent scheduling algorithm for prominent cloud data. In addition, the proposed algorithm provides a significant improvement with respect to the makespan and reduces the computation and complexity via employing Principle Components Analysis (PCA) and reducing the Expected Time to Compute (ETC) matrix. Simulation results confirm the superior performance of the algorithm for heterogeneous systems in terms of efficiency, speedup and schedule length ratio, when compared to the state-of-the-art Min-Min, Max-Min, QoS-Guide and MiM-MaM scheduling algorithms.

Atherosclerosis, cardiovascular diseases (CVDs), and inflammation are important problems in chronic kidney disease (CKD) patients on chronic hemodialysis (HD). Prevention of CKD patients of CVD can lower the mortality rate in them. Omega 3 may help in the treatment of inflammation and lipid abnormalities in end-stage renal disease (ESRD) patients on chronic HD. This study aimed to evaluate the effect of high-dose Omega 3 on lipid profile and inflammatory markers in ESRD children on chronic HD. This clinical trial was conducted on 49 ESRD children on chronic HD selected from pediatric HD unit of Menoufia University Hospital. The study was conducted for a period of three months. The selected children were supplemented with 2000-mg Omega 3 tablets daily; lipid profile and inflammatory markers were assessed at the beginning and at the end of the study. Supplementation with high-dose Omega 3 resulted in a highly statistically significant decrease in total cholesterol, triglyceride, low-density lipoprotein, interleukin-6, C- reactive protein levels and a highly statistically significant increase in high-density lipoprotein (P 0.05). Supplementation with highdose Omega 3 caused significant improvement in lipid profile and inflammatory markers of children on chronic HD.

Encryption of digital color image is the process of conversion original digital color image into an encrypted one to protect the image from hacking or to prevent an authorized person to get the valuable information located in the color image. The process of color image encryption-decryption is very important issue in human activities and here in this paper we will introduce a new simple, efficient and highly secure method to be used for color image encryption-decryption. The proposed method will be tested and implemented, the efficiency parameters of the proposed method will be calculated and will be compared with other methods parameters to prove the efficiency issues of the proposed method.

In 2020, the global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection (also known as COVID-19) has led to pandemic health issues with significant changes in individual and community practices. Preterm birth could be one of the risks in pregnant mothers who are infected by the SARS-CoV-2. Preterm births contribute upto 10% of all births and incur significant impact on the child health and cost to the health care system. However, the association of city lockdown during COVID-19 pandemic with the rate of preterm births is unclear. In a cohort study, we examined the association of city lockdown during the COVID-19 pandemic with the births at different gestations in three different cities. Compared with the pre-pandemic epoch, the associative relationships ranged from a decrease in all births, all births across all preterm gestations and to preterm births in moderately and late preterm gestations. We concluded that there were variable associative relationships of city lockdown during COVID-19 pandemic with preterm births. This could be related to the differences in health, societal and cultural factors, which will inspire further studies in this area.

The presented study suggests a new nature–inspired metaheuristic optimization algorithm referred to as Red Colobuses Monkey (RCM) that can be used for optimization problems; this algorithm mimics the behavior related to red monkeys in nature. In preparation for proving the suggested algorithm's advantages, a set of standard unconstrained and constrained test functions is employed, sixty–four of identified test functions utilized in optimization were applied as benchmarks for checking the RCM performance. The solutions have also been upgrading their positions based on the optimal solution, which was reached thus far. Also, RCM can replace the worst red monkey by the best child found so far to give an extra enhancement to the solutions. Also, comparative performance checks with Biogeography–Based Optimizer (BBO), Artificial–Bee–Colony (ABC), Particle Swarm Optimization (PSO), and Gravitational Search Algorithm (GSA) were done. The acquired results showed that RCM is competitive in comparison to the chosen metaheuristic algorithms.

Preterm birth is the leading cause of infant death worldwide, but the causes of preterm birth are largely unknown. During the early COVID-19 lockdowns, dramatic reductions in preterm birth were reported; however, these trends may be offset by increases in stillbirth rates. It is important to study these trends globally as the pandemic continues, and to understand the underlying cause(s). Lockdowns have dramatically impacted maternal workload, access to healthcare, hygiene practices, and air pollution - all of which could impact perinatal outcomes and might affect pregnant women differently in different regions of the world. In the international Perinatal Outcomes in the Pandemic (iPOP) Study, we will seize the unique opportunity offered by the COVID-19 pandemic to answer urgent questions about perinatal health. In the first two study phases, we will use population-based aggregate data and standardized outcome definitions to: 1) Determine rates of preterm birth, low birth weight, and stillbirth and describe changes during lockdowns; and assess if these changes are consistent globally, or differ by region and income setting, 2) Determine if the magnitude of changes in adverse perinatal outcomes during lockdown are modified by regional differences in COVID-19 infection rates, lockdown stringency, adherence to lockdown measures, air quality, or other social and economic markers, obtained from publicly available datasets. We will undertake an interrupted time series analysis covering births from January 2015 through July 2020. The iPOP Study will involve at least 121 researchers in 37 countries, including obstetricians, neonatologists, epidemiologists, public health researchers, environmental scientists, and policymakers. We will leverage the most disruptive and widespread “natural experiment” of our lifetime to make rapid discoveries about preterm birth. Whether the COVID-19 pandemic is worsening or unexpectedly improving perinatal outcomes, our research will provide critical new information to shape prenatal care strategies throughout (and well beyond) the pandemic.

This study examines the relationship between corporate social responsibility (CSR) reporting, board gender diversity (BGEND) and real earnings management (REM). It also investigates how the relationship between CSR reporting and REM differs between gender-diverse and non-diverse firms. Content analysis was used to measure CSR reporting. The ordinary least square regression is used to examine the relationships for a sample of 475 firm-year observations listed on the Amman Stock Exchange during 2011–2016. The results show that CSR reporting is significantly and negatively associated with REM in the Jordanian market. Nevertheless, BGEND is negatively and significantly related to REM. More importantly, the results show that BGEND moderates the CSR-REM relationship. Further, when the sample is split into board gender-diverse and non-diverse firms, the CSR-REM significant negative relationship is evident only in the former, corroborating the moderating role of the BGEND in Jordan. This study contributes to the literature on CSR, BGEND, and REM by offering evidence for the moderating role of BGEND on the CSR-REM relationship, supporting the view that females are more sensitive to ethics. Regulators and stakeholders should be aware of the potential effect of engagement in CSR reporting and the benefits of having a gender-diverse board on financial reporting quality.

This study investigates the relationship between the Chairman’s characteristics (age, title, tenure, and ownership) and the firm’s operating performance (measured by profitability and liquidity), and whether the Chief Executive Officer’s (CEO) effectiveness (a combination of non-duality, age, and tenure) strengthens or impairs this relationship. Based on a total sample of 267 observations, we use Ordinary Least Squares (OLS) regression to investigate the hypotheses established for the top 89 non-financial firms listed on the Malaysian Main Market during 2017 to 2019. The findings show that Chairman age is positively and significantly associated with the firm’s profitability but not with liquidity. Conversely, Chairman ownership is positively and significantly associated with liquidity but not with profitability. These findings suggest that the age and ownership of the Chairman may significantly boost operating performance. However, Chairman tenure is negatively and significantly associated with operating performance (profitability and liquidity), suggesting that long-tenured Chairmen are associated with poor operating performance. Chairman title is insignificantly related to operating performance. Importantly, the results also show that CEO effectiveness strengthens the relationship between Chairman tenure and liquidity. However, CEO effectiveness impairs the relationship between Chairman title and profitability and Chairman ownership and liquidity. Additional analysis is conducted to further check the validity of the main results and to avoid any possible effect of endogeneity issues. To our knowledge, this paper is the first to investigate the impact of Chairman characteristics on operating performance with the moderating effect of CEO effectiveness, specifically in a developing economy.

In cases of nuclear and radiological accidents, public health and emergency response need to assess the magnitude of radiation exposure regardless of whether they arise from disaster, negligence, or deliberate act. Here we report the establishment of a national reference dose–response calibration curve (DRCC) for dicentric chromosome (DC), prerequisite to assess radiation doses received in accidental exposures. Peripheral blood samples were collected from 10 volunteers (aged 20–40 years, median = 29 years) of both sexes (three females and seven males). Blood samples, cytogenetic preparation, and analysis followed the International Atomic Energy Agency EPR-Biodosimetry 2011 report. Irradiations were performed using 320 kVp X-rays. Metafer system was used for automated and assisted (elimination of false-positives and inclusion of true-positives) metaphases findings and DC scoring. DC yields were fit to a linear–quadratic model. Results of the assisted DRCC showed some variations among individuals that were not statistically significant (homogeneity test, P = 0.66). There was no effect of age or sex (P > 0.05). To obtain representative national DRCC, data of all volunteers were pooled together and analyzed. The fitted parameters of the radiation-induced DC curve were as follows: Y = 0.0020 (±0.0002) + 0.0369 (±0.0019) *D + 0.0689 (±0.0009) *D2. The high significance of the fitted coefficients (z-test, P < 0.0001), along with the close to 1.0 p-value of the Poisson-based goodness of fit (χ2 = 3.51, degrees of freedom = 7, P = 0.83), indicated excellent fitting with no trend toward lack of fit. The curve was in the middle range of DRCCs published in other populations. The automated DRCC over and under estimated DCs at low (2 Gy) doses, respectively, with a significant lack of goodness of fit (P < 0.0001). In conclusion, we have established the reference DRCC for DCs induced by 320 kVp X-rays. There was no effect of age or sex in this cohort of 10 young adults. Although the calibration curve obtained by the automated (unsupervised) scoring misrepresented dicentric yields at low and high doses, it can potentially be useful for triage mode to segregate between false-positive and near 2-Gy exposures from seriously irradiated individuals who require hospitalization.

Background and Objective: Coronavirus disease 2019 (COVID-19) characterized by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created serious concerns about its potential adverse effects. There are limited data on clinical, radiological, and neonatal outcomes of pregnant women with COVID-19 pneumonia. This study aimed to assess clinical manifestations and neonatal outcomes of pregnant women with COVID-19.Methods: We conducted a systematic article search of PubMed, EMBASE, Scopus, Google Scholar, and Web of Science for studies that discussed pregnant patients with confirmed COVID-19 between January 1, 2020, and April 20, 2020, with no restriction on language. Articles were independently evaluated by two expert authors. We included all retrospective studies that reported the clinical features and outcomes of pregnant patients with COVID-19.Results: Forty-seven articles were assessed for eligibility; 13 articles met the inclusion criteria for the systematic review. Data is reported for 235 pregnant women with COVID-19. The age range of patients was 25–40 years, and the gestational age ranged from 8 to 40 weeks plus 6 days. Clinical characteristics were fever [138/235 (58.72%)], cough [111/235 (47.23%)], and sore throat [21/235 (8.93%)]. One hundred fifty six out of 235 (66.38%) pregnant women had cesarean section, and 79 (33.62%) had a vaginal delivery. All the patients showed lung abnormalities in CT scan images, and none of the patients died. Neutrophil cell count, C-reactive protein (CRP) concentration, ALT, and AST were increased but lymphocyte count and albumin levels were decreased. Amniotic fluid, neonatal throat swab, and breastmilk samples were taken to test for SARS-CoV-2 but all found negativ results. Recent published evidence showed the possibility of vertical transmission up to 30%, and neonatal death up to 2.5%. Pre-eclampsia, fetal distress, PROM, pre-mature delivery were the major complications of pregnant women with COVID-19.Conclusions: Our study findings show that the clinical, laboratory and radiological characteristics of pregnant women with COVID-19 were similar to those of the general populations. The possibility of vertical transmission cannot be ignored but C-section should not be routinely recommended anymore according to latest evidences and, in any case, decisions should be taken after proper discussion with the family. Future studies are needed to confirm or refute these findings with a larger number of sample sizes and a long-term follow-up period.

Overexpression of c-Myc plays an essential role in leukemogenesis and drug resistance, making c-Myc an attractive target for cancer therapy. However, targeting c-Myc directly is impossible, and c-Myc upstream regulator pathways could be targeted instead. This study investigated the effects of thymoquinone (TQ), a bioactive constituent in Nigella sativa, on the activation of upstream regulators of c-Myc: the JAK/STAT and PI3K/AKT/mTOR pathways in HL60 leukemia cells. Next-generation sequencing (NGS) was performed for gene expression profiling after TQ treatment. The expression of c-Myc and genes involved in JAK/STAT and PI3K/AKT/mTOR were validated by quantitative reverse transcription PCR (RT-qPCR). In addition, Jess assay analysis was performed to determine TQ’s effects on JAK/STAT and PI3K/AKT signaling and c-Myc protein expression. The results showed 114 significant differentially expressed genes after TQ treatment (p < 0.002). DAVID analysis revealed that most of these genes’ effect was on apoptosis and proliferation. There was downregulation of c-Myc, PI3K, AKT, mTOR, JAK2, STAT3, STAT5a, and STAT5b. Protein analysis showed that TQ also inhibited JAK/STAT and PI3K/AKT signaling, resulting in inhibition of c-Myc protein expression. In conclusion, the findings suggest that TQ potentially inhibits proliferation and induces apoptosis in HL60 leukemia cells by downregulation of c-Myc expression through inhibition of the JAK/STAT and PI3K/AKT signaling pathways.