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Transglutaminase (TG) isoforms control diverse normal and pathophysiologic processes through their capacity to cross-link extracellular matrix (ECM) proteins. Their functional and signalling roles in cardiac fibrosis remain poorly understood, despite some evidence of TG2 involvement in abnormal ECM remodelling in heart diseases. In this study, we investigated the role of TG1 and TG2 in mediating fibrotic signalling, collagen cross-linking, and cell proliferation in healthy fibroblasts by siRNA-mediated knockdown. siRNA for TG1, TG2 or negative control was transfected into cultured neonatal rat ventricular fibroblasts and cardiomyocytes. mRNA expression of TGs and profibrotic, proliferation and apoptotic markers was assessed by qPCR. Cell proliferation and soluble and insoluble collagen were determined by ELISA and LC-MS/MS, respectively. TG1 and TG2 were both expressed in neonatal rat cardiomyocytes and fibroblasts before transfection. Other TGs were not detected before and after transfection. TG2 was predominantly expressed and more effectively silenced than TG1. Knocking down TG1 or TG2 significantly modified profibrotic markers mRNA expression in fibroblasts, decreasing connective tissue growth factor (CTGF) and increasing transforming growth factor-β1 compared to the negative siRNA control. Reduced expression of collagen 3A1 was found upon TG1 knockdown, while TG2 knockdown raised α-smooth muscle actin expression. TG2 knockdown further increased fibroblast proliferation and the expression of proliferation marker cyclin D1. Lower insoluble collagen content and collagen cross-linking were evidenced upon silencing TG1 or TG2. Transcript levels of collagen 1A1, fibronectin 1, matrix metalloproteinase-2, cyclin E2, and BCL-2-associated X protein/B-cell lymphoma 2 ratio were strongly correlated with TG1 mRNA expression, whereas TG2 expression correlated strongly with CTGF mRNA abundance. These findings support a functional and signalling role for TG1 and TG2 from fibroblasts in regulating key processes underlying myocardial ECM homeostasis and dysregulation, suggesting that these isoforms could be potential and promising targets for the development of cardiac fibrosis therapies.

ECG wave recognition is one of the new topics where only one of the ECG beat waves (P-QRS-T) was used to detect heart diseases. Normal, tachycardia, and bradycardia heart rhythm are hard to detect using either time-domain or frequency-domain features solely, and a time-frequency analysis is required to extract representative features. This paper studies the performance of two different spectrum representations, iris-spectrogram and scalogram, for different ECG beat waves in terms of recognition of normal, tachycardia, and bradycardia classes. These two different spectra are then sent to two different deep convolutional neural networks (CNN), i.e., Resnet101 and ShuffleNet, for deep feature extraction and classification. The results show that the best accuracy for detection of beats rhythm was using ResNet101 and scalogram of T-wave with an accuracy of 98.3%, while accuracy was 94.4% for detection using iris-spectrogram using also ResNet101 and QRS-Wave. Finally, based on these results we note that using deep features from time-frequency representation using one wave of ECG beat we can accurately detect basic rhythms such as normal, tachycardia, and bradycardia.

Primary hyperparathyroidism is a disease characterized by hypercalcemia and excessive production of parathyroid hormone. It is the most common cause of hypercalcemia in outpatient practice and the third common endocrine disorder. The incidence of primary hyperparathyroidism is increasing with age, and it is more common in women than in men. 80-85% of cases of primary hyperparathyroidism are due to single parathyroid adenoma. The majority of parathyroid adenomas contain a mixed cell population with predominance of chief cells. Primary hyperparathyroidism with clear cell adenoma is very rare. Here we are sharing two cases of water clear cell parathyroid adenoma associated with primary hyperparathyroidism presented with deferent clinical manifestations.

Introduction. Sleep disorders are extremely prevalent in the general population. College students are more susceptible to sleep problems. This is due to the increased competition in getting a job position and the current alterations in the labor market. Poor sleep is prevalent and has deleterious effects on college students, but its frequency among college students has not been documented in Jordan. So, the aims of this study are to assess the prevalence of daytime sleepiness among medical college students in Jordan and to look for any links between daytime sleepiness and academic performance. Methods. A cross-sectional study performed on medical and paramedical specialties students and Epworth sleepiness Sscale (ESS) was used. To assess the students’ academic performance, the cumulative grade point average was utilized. Results. 977 students from five medical colleges participated in the study. ESS scores were abnormal in 34.4% of students and were considered to have daytime sleepiness. Significant lower ESS scores were associated with students who reported good sleep quality than students who reported poor sleep quality. Significant lower ESS scores were reported by students who slept more than 7 hours compared with students who slept less than 6 hours. The ESS scores were not significantly associated with students’ CPGA. Conclusion. Daytime sleepiness is highly prevalent among medical students in Jordan. The data of this study might be very helpful to assess the academic policy makers to develop intervention strategies that resolve the sleep disturbances in college students and reduce its impact on the academic achievements.

Electroencephalogram (EEG) signal classification is a crucial and very difficult task. Meanwhile, extracting features that are representative and able to discriminate different types of EEG signals is a complex task. Such features are usually fed to machine learning algorithms to classify the EEG signals based on the extracted features. This paper proposed a highly accurate and real-time features extraction method that can be used to help physicians in detecting different types of seizures and states in EEG signals characterized by a set of features extracted from the power spectrum of the EEG window. This is achieved by applying the following four steps. First, the EEG signals dataset contains different classes of EEG signals: Normal Eye Closed, Normal Eye Opened, Focal Seizure, Non-Focal Seizure, and Ictal Seizure activities. Second, each EEG signal has a length of 4097 samples sampled with a sampling frequency of 173.6 Hz which resulted in 23.6 seconds in length, this signal will be truncated into windows (Sub-signals) with a length of 349 samples (Approximately 2 seconds) with a total number of 12 windows for each signal. Afterward, the Fourier Transform (FT) based power spectrum will be computed for each window, then a set of different features are extracted from each window's FT power spectrum, and these features are classified using different Machine Learning (ML) algorithms. The results showed that the proposed methodology yields around 98% accuracy for the five different classification scenarios using different ML algorithms. The suggested method is hence robust, fast, real-time, accurate, and simple.

Oil shale deposits with over 70 billion tons of proven reserves are considered one of Jordan's most important sources of energy. The current study investigated the mineralogy, geochemistry, and spectral characteristics of the Wadi Abu Ziad oil shales in northern Jordan. The mineralogical composition of the collected samples was analyzed using X-ray diffraction (XRD). Total organic matter (TOM) and calcium carbonate (CaCO3) contents were also determined. The spectral characteristics of oil shales were examined using a GER 3700 Spectroradiometer (0.35 to 2.5 µm) and Fourier transform infrared spectroscopy (FTIR) (4000 to 400 cm−1). XRD analysis revealed that the samples are composed primarily of quartz, calcite, and apatite. The average TOM and CaCO3 contents in the study area are 13.91% and 16.73%, respectively. The absorption features of oil shale samples are at 1.41 µm and 1.90 µm (H2O), 1.76 µm (C–H), 2.20 µm (Al–OH), and 2.33 µm (CO3). The FTIR absorption spectrum exhibits the absorption bands that characterize kaolinite, quartz (SiO2), calcite (CaCO3), and organic compounds in the oil shale samples. Spectroscopic analysis is a useful tool for identifying the mineralogical composition of oil shales and helps oil shale exploration using multispectral and hyperspectral remote sensing data.

Kidney stones are a common and extremely painful disease and can affect any part of the urinary tract. Ultrasound and computed tomography (CT) are the most frequent imaging modalities used for patients with acute flank pain. In this paper, we design an automated system for 3D kidney segmentation and stones detection in addition to their number and size evaluation. The proposed system is built based on CT kidney image series of 10 subjects, four healthy subjects (with no stones) and the rest have stones based on medical doctor diagnosis, and its performance is tested based on 32 CT kidney series images. The designed system shows its ability to extract kidney either in abdominal or pelvis non-contrast series CT images, and it distinguishes the stones from the surrounding tissues in the kidney image, besides to its ability to analyze the stones and classify them in vivo for further medical treatment. The result agreed with medical doctor's diagnosis. The system can be improved by analyzing the stones in the laboratory and using a large CT dataset. The present method is not limited to extract stones but, also a new approach is proposed to extract the 3D kidneys as well with accuracy 99%.

Aim: Pneumothorax (PNX), pneumomediastinum (PMD) and subcutaneous emphysema (SCE) are COVID-19 complications related to positive-pressure ventilation. We analyzed the pathophysiology of these complications without ventilation. Patients & methods: Out of 1845 admitted COVID-19 patients, we retrospectively collected data for 15 patients, from a tertiary medical center, from 1 October 2020 to 31 March 2021. Results: Five patients suffered from spontaneous PNX, 8/15 developed PMD and 8/15 developed SCE. The mean BMI was 29.7, as most patients were obese or overweight. Most patients had lymphocytopenia and increased C-reactive protein, ferritin and lactate dehydrogenase levels. Eleven patients succumbed to the disease. Conclusion: Risk factors of spontaneous PNX, PMD and SCE in COVID-19 patients need further investigations by conducting more comprehensive case–control studies., Lay abstract We have investigated spontaneous alveolar rupture as a complication in 15 COVID-19 patients. Manifested as pneumothorax, pneumomediastinum and subcutaneous emphysema, these complications are less common in patients without mechanical ventilation. Management of these patients was either conservative or by insertion of a chest tube. Eventually, 11 out of 15 patients have passed away due to respiratory failure., Graphical abstract

The novel coronavirus (nCoV-19) was first detected in December 2019. It had spread worldwide and was declared coronavirus disease (COVID-19) pandemic by March 2020. Patients presented with a wide range of symptoms affecting multiple organ systems predominantly the lungs. Severe cases required intensive care unit (ICU) admissions while there were asymptomatic cases as well. Although early detection of the COVID-19 virus by Real-time reverse transcription-polymerase chain reaction (RT-PCR) is effective, it is not efficient;as there can be false negatives, it is time consuming and expensive. To increase the accuracy of in-vivo detection, radiological image-based methods like a simple chest X-ray (CXR) can be utilized. This reduces the false negatives as compared to solely using the RT-PCR technique. This paper employs various image processing techniques besides extracted texture features from the radiological images and feeds them to different artificial intelligence (AI) scenarios to distinguish between normal, pneumonia, and COVID-19 cases. The best scenario is then adopted to build an automated system that can segment the chest region from the acquired image, enhance the segmented region then extract the texture features, and finally, classify it into one of the three classes. The best overall accuracy achieved is 93.1% by exploiting Ensemble classifier. Utilizing radiological data to conform to a machine learning format reduces the detection time and increase the chances of survival. © 2021, Brno University of Technology. All rights reserved.

BackgroundThe neuropeptide substance P is a potential biomarker and therapeutic target in cancer. The main objectives of this study were to investigate the expression level of substance P in different breast cancer molecular subtypes and identify its association with clinicopathological parameters of patients and with Ki-67 index.MethodsA retrospective analysis was performed for a total of 164 paraffin-embedded breast cancer tissue samples [42 Her2/neu-enriched, 40 luminal A, 42 luminal B (triple-positive) and 40 triple negative subtypes]. The tissue microarray slides containing specimens were used to determine the expression of substance p and Ki-67 by immunohistochemical staining.ResultsThe mean age of the cohort was 51.35 years. Twenty two percent of cases had low substance P expression levels (TS ≤ 5), while 78% had high expression levels (TS > 5). A significant association was found between SP expression level and breast cancer molecular subtype (p = 0.002), TNM stage (p = 0.034), pN stage (p = 0.013), axillary lymph node metastasis (p = 0.004), ER and PR statuses (pConclusionSP is overexpressed in most of the analyzed tissues and has a negative prognostic value in the breast cancer patients. Besides substance P is a potential therapeutic target in breast cancer.

As the recent development of the prosthetic control systems, it is necessary to develop the sub-components such as myoelectric control system. This sub-system is used to acquire electromyogram (EMG) signals from a person's muscles and convert it to movements to control prosthetic hands or fingers. Recently, researchers started focusing on providing feature extraction methods for both time domain and frequency domain for predicting either hand or finger movements. This paper proposes a new mixed feature set for both time and frequency domain for the classification of surface EMG (sEMG) into ten classes for controlling prosthetic finger movements. The features are based on enhanced statistical features extracted directly from a non-overlapped window with a predefined length which was selected carefully from the sEMG directly. Ten classes of individual and combined finger movements are to be recognized by using two sEMG channels from two electrodes are fixed on the human forearm to employ effective knowledge discovery and pattern recognition algorithms to enhance the recognition and classification accuracy. and the other features are statistical features extracted from Instantaneous frequency of the signal to utilize a suitable classifier helps detecting and recognizing the pattern from sEMG signals of different classes of the fingers movements either combined or single movement to enhance the classifier performances and to find the whole class of all extracted window ,a majority voting technique was applied.The method used the random forest as a classifier to build the classifier model which achieved an accuracy of 93.75% and sensitivity of 93.73% and specificity of 99.31%.

Purpose The purpose of this paper is to investigate the moderating effect of task complexity on external auditors’ cooperation (EAC), top management empowerment and internal auditors’ independence, which affect internal auditors’ effectiveness in the Jordanian public sector. Design/methodology/approach This paper utilised 117 usable questionnaires from financial managers and internal audit (IA) managers of the Jordanian public sector institutions. The collected data were analysed using partial least squares-structural equation modelling (PLS-SEM). Findings The results reveal that EAC, top management empowerment, and internal auditors’ independence are the factors which positively and significantly affect the internal auditors’ effectiveness, as supported by the resource-based theory, with incomplete support for the task complexity’s role as a moderator. Practical implications The findings are important for the decision-makers and regulators in introducing new legislation and regulation for the IA profession in the Jordanian public sector. Social implications It is shown that the factors affecting the internal auditors’ effectiveness can definitely enhance their ability to achieve the role of IA in protecting public funds and limiting financial and administrative corrupt practices, particularly in the public sector. Originality/value To the best knowledge of the authors, this study is one of the first studies that addresses task complexity as an interaction effect on the factors affecting internal auditors’ effectiveness in the public sector.

Heart sound and its recorded signal which is known as phonocardiograph (PCG) are one of the most important biosignals that can be used to diagnose cardiac diseases alongside electrocardiogram (ECG). Over the past few years, the use of PCG signals has become more widespread and researchers pay their attention to it and aim to provide an automated heart sound analysis and classification system that supports medical professionals in their decision. In this paper, a new method for heart sound features extraction for the classification of non-segmented signals using instantaneous frequency was proposed. The method has two major phases: the first phase is to estimate the instantaneous frequency of the recorded signal; the second phase is to extract a set of eleven features from the estimated instantaneous frequency. The method was tested into two different datasets, one for binary classification (Normal and Abnormal) and the other for multi-classification (Five Classes) to ensure the robustness of the extracted features. The overall accuracy, sensitivity, specificity, and precision for binary classification and multi-classification were all above 95% using both random forest and KNN classifiers.

The aim of the present study was to identify moral intelligence and its relation to conflict resolution skill among King Saud University students in the light of gender, the type of college (sciences or humanities) and the study level. Furthermore, this study attempted to find out whether it is possible to predict the conflict resolution skill among students of King Saud University (KSU) by their score on the moral intelligence scale. The sample of the study consisted of (360) students from KSU. The researchers used the correlative and comparative descriptive method. The findings of the study indicated that the score of the moral intelligence and conflict resolution skill was low. In addition, the findings showed that there was a difference in moral intelligence in favor of males, while there were no statistically significant differences in the moral intelligence based on the type of college or the study level. The study findings also revealed that there was a statistically significant correlation at the level of 0.01 between moral intelligence and conflict resolution skill. It was also found out that independent variables (dimensions of moral intelligence: sympathy, conscience, recognition of emotions & moral imagination) contribute to predicting the overall skill of conflict resolution. Keywords: conflict resolution, moral intelligence, KSU, KSA.

Objective: Basal cell carcinoma (BCC) is the most common malignancy in humans and represents a growing public health care problem. The major etiological factors contributing to BCC development are exposure to ultraviolet radiation and genetic alterations. BCC is primarily caused by dysregulation of sonic Hedgehog (HH) signaling pathway in basal cells of the skin. BCC can be classified into low risk non-aggressive and high risk aggressive subtypes. BCC subtypes differentiation is essential for prognosis and for better disease management and treatment strategies. The aim of this study was to assess the correlation between PTCH1 protein expression level and the aggressiveness of BCC histopathology. Methods: Archival paraffin embedded blocks containing BCC were retrieved from a cohort of 101 patients. Immunohistochemistry staining was performed to assess the expression level of PTCH1 which is a key component of Hedgehog pathway. Results: 101 paraffin embedded samples were evaluated and classified as high risk and low risk BCC subtypes by histopathological finding. High risk BCC subtypes were found in 40 samples (39.6%) and low risk subtypes were identified in 61 samples (60.4%). Nodular was the most frequent subtype which was found in (56/ 101), followed by infiltrative (22/101) and micronodular (14/ 101) subtypes. Positive PTCH1 expression was found highest in nodular subtypes (46.5%). Conclusion: In this study, the correlation between low risk or high risk BCC subtypes and PTCH1 expression level was not statistically significant (p>0.05), but the frequency of positive PTCH1 expression was found to be higher in low risk subtypes than high risk BCC subtypes.

A skin lesion is a very severe problem, especially in coastal countries. Early detection by a highly reliable classification of skin lesion causes a great reduction in the mortality rate. Recognition of melanoma is a complicated issue due to the high degree of visual similarities between melanoma and non-melanoma lesions. Various studies are carried out to overcome this problem and to obtain accurate screening of skin lesion, where the most recent method for segmenting and classifying the lesion is based on a deep learning algorithm. In this paper, (GoogleNet) and (AlexNet) are employed with transfer learning and optimization gradient descent adaptive momentum learning rate (ADAM). The proposed method is applied on Archive International Skin Imaging Collaboration (ISIC) database to classify images into three main classes (benign, melanoma, seborrheic keratosis) under the two scenarios; segmented and non-segmented lesion images. The overall accuracy of the non-segmented classification database is 92.2% and 89.8% for the non-segmented dataset. Utilizing optimization algorithm (ADAM) leads to a significant improvement in the classification results when they are compared with previous studies.

Neogene non-marine sedimentary rocks of the Bekaa Valley (Lebanon) are microfossil rich and show minimal lateral facies changes and post-depositional diagenetic alteration across continuous exposures. In this paper, we analyze the sedimentary facies and microfossils of three closely-spaced stratigraphic sections near the town of Zahle. The sedimentary sequence is divided, from base to top, into three intervals: (1) a massive conglomerate unit interpreted as alluvial fan deposits, (2) fossiliferous yellowish marls and limestone interpreted as perennial lacustrine deposits, and (3) an organic-rich marlstone intercalated with volcanic ash horizons interpreted as a palustrine interval representing an overall shallowing sequence. Intervals 2 and 3 contain a diverse microfossil assemblage comprising charophytes, terrestrial molluscs, a freshwater bivalve, ostracods as well as fish and mammal remains. The palaeoenvironmental characteristics and evolution of these lacustrine deposits are inferred through facies analysis and through comparison of microfossil tolerances with the ecological requirements of their nearest living relatives. Results suggest that during the Miocene the Bekaa Valley was occupied by a relatively shallow, stable, oligotrophic freshwater or slightly oligohaline lake that evolved to a very shallow eutrophic lake with a dense palustrine vegetation belt. The palaeolake ultimately regressed to the south due to climatic changes and tectonic stresses leaving the lacustrine deposits exposed in the area of Zahle as an erosional surface.

Breast cancer is one of the most common cancers in women's community, which is responsible for millions of death cases. The early diagnosis of breast cancer in its early stages increases the chance...

The internet of things (IoT) are developed toward making the objects smart and connectable using recent development in miniaturizing and communication technologies, IoT has wide application domains one of them is healthcare. this paper focusing on the IoT and their applications, integration, and advances in use in the healthcare sector. IoT is promising technology which will provide an advancement in healthcare providing techniques especially in telemetry and home care. Moreover, IoT will provide a framework for health data collection and sharing. This paper will discuss recent developments in applications and innovation of using IoT in healthcare such as miniaturizing technology and wearable technology as well as the changes facing the application of IoT in healthcare.

Paleogeographic interpretations have been carried out in Lebanon by means of paleontological analysis. This study is complementary to previous records which have explained the paleogeographic setting of the western side of Lebanon during the Cenozoic. Extensive fieldwork and sampling were performed in the area of Zahle (west part of the Bekaa Valley). Samples collected from this locality provided diverse microfossil assemblages. The results show that there is a major change in the paleogeographic setting during the transitional period extending from early Eocene to Miocene. These changes in paleogeographic setting resulted from repeated episodes of emergence and submergence due to oscillating tectonic movements, leading to variations in the sedimentation patterns across the Bekaa Basin. The new findings of calcareous nannofossils in the chalky facies of Zahle area frame the paleogeographic settings during the Paleocene and early Eocene. Regression was clearly recognized during the early middle Eocene, which was revealed by the change in marine setting from the deep in the early Eocene (represented by the chalky facies), to the shallow settings in the middle Eocene where the nummulite banks were formed. This sedimentation pattern appears to coincide with major break in the sea level curve already reported by many researchers. During the Oligocene, the collision between the African-Arabian and Eurasian plates started causing further uplift of the Lebanese structures and consequent partial erosion (non-sedimentation) of the above-mentioned lithologies. The sedimentation pattern during the Miocene in Lebanon reveals a major change shifting from a primarily marine regime to fully lacustrine.

Electrocardiogram (ECG) beat classification is a significant application in computer-aided analysis and diagnosis technologies. This paper proposed a method to detect, extract informative features, and classify ECG beats utilizing real ECG signals available in the standard MIT-BIH Arrhythmia database, with 10,502 beats had been extracted from it. The present study classifies the ECG beat into six classes, normal beat (N), Left bundle branch block beat, Right bundle branch block beat, Premature ventricular contraction, atrial premature beat, and aberrated atrial premature, using Gaussian mixture and wavelets features, and by applying principal component analysis for feature set reduction. The classification process is implemented utilizing two classifier techniques, the probabilistic neural network (PNN) algorithm and Random Forest (RF) algorithm. The achieved accuracy is 99.99%, and 99.97% for PNN and RF respectively. The precision is 99.99%, and 99.98% for PNN and RF respectively. The sensitivity is 99.99%, and 99.81% for PNN and RF respectively, while the specificity is 99.97%, 99.96% for PNN and RF respectively. It has been shown that the combination of Gaussian mixtures coefficients and the wavelets features have provided a valuable information about the heart performance and can be used significantly in arrhythmia classification.

To design comfortable and efficient hand tools, an objective measurement such as using surface electromyography (sEMG) is required, where the ergonomic design tries to find the most optimal and most fit design of hand-tool that doesn't cause stress on the hand muscles. The hand tool design optimization will be demonstrated in this study on designing shampoo bottles, where the design of bottle and its compatibility with the slippery watery area, in addition to the aesthetic considerations are important issues that must be taking by the manufacturers concerned with such industries. Six different designs of shampoo bottles, as outcomes of industrial design graduation project in the department of Industrial design at our university, were used in this study. The new designs, together with other traditionally bottle designs, were evaluated in simulated shampoo pouring task in the laboratory. Several important parameters extracted from the sEMG signal in both temporal domain and frequency domain provide useful information about the tested designs. Twenty healthy university students (10 males and 10 females; mean age of 21 ± 2 years) were included in this study. Each subject was asked to handle the bottle and simulate the shampoo pouring activity in gentle and delicate manner using the grasp pattern that is found most comfort for him/her. Muscular behavior during bottle holding and shampoo pouring tasks show that male and female have different preferences in dealing with different bottle design, where male have less hand stress with designs that achieve the best fit of their full hand, while female have less hand stress with designs that achieve the best fit of their fingertips, and therefore, the end-user gender must be considered in designs of such industries. Keywords: Surface electromyography, Ergonomic design, Hand-tools, Hand stress, Mean frequency, Euclidean distance, Root mean square, Gender considerations

BackgroundChest diseases are serious health problems that threaten the lives of people. The early and accurate diagnosis of such diseases is very crucial in the success of their treatment and cure. Pneumonia is one of the most widely occurred chest diseases responsible for a high percentage of deaths especially among children. So, detection and classification of pneumonia using the non-invasive chest x-ray imaging would have a great advantage of reducing the mortality rates.ResultsThe results showed that the best input image size in this framework was 64 64 based on comparison between different sizes. Using CNN as a deep features extractor and utilizing the 10-fold methodology the propose artificial intelligence framework achieved an accuracy of 94% for SVM and 93.9% for KNN, a sensitivity of 93.33% for SVM and 93.19% for KNN and a specificity of 96.68% for SVM and 96.60% for KNN.ConclusionsIn this study, an artificial intelligence framework has been proposed for the detection and classification of pneumonia based on chest x-ray imaging with different sizes of input images. The proposed methodology used CNN for features extraction that were fed to two different types of classifiers, namely, SVM and KNN; in addition to the SoftMax classifier which is the default CNN classifier. The proposed CNN has been trained, validated, and tested using a large dataset of chest x-ray images contains in total 5852 images.

ObjectivesThis study aimed to compare graft take rate after tympanoplasty between adults and paediatric patients, cartilage and fascia grafts, and overlay and underlay techniques.MethodsData were analysed in groups according to the technique (underlay vs overlay), age (paediatric patients vs adults) and graft (cartilage vs temporalis fascia). The main outcome measures were full graft take and the incidence of complications.ResultsA total of 198 patients (208 ears) were included. Overall, full graft take was achieved in 200 ears (96 per cent). The success rate was higher in adults compared with paediatric patients (97.5 per cent vs 92.25, respectively) but the difference was insignificant. Similarly, higher but insignificant graft take rate was found in the cartilage group compared with fascia group (98.6 per cent vs 94.9 per cent, respectively).ConclusionAll cases of overlay tympanoplasty had full graft take (success rate 100 per cent). In the underlay group, successful graft take was achieved in 154 cases (95 per cent). This difference was statistically insignificant.

Background The COVID-19 pandemic had many implications on healthcare services, including cellular pathology. The pandemic-related lockdown was applied in Jordan from March to May 2020. King Abdullah University Hospital (KAUH) was chosen to provide care for COVID-19 patients during that period. Since there was no experience in dealing with COVID-19 patients, the hospital maintained some essential services but canceled elective surgeries and procedures. The rationale was to prioritize care for COVID-19 patients and to provide better adherence to infection control policies and protect non-infected patients and healthcare workers. The purpose of the present study is to investigate the impact of COVID-19 pandemic restrictions on cellular pathology practice patterns at KAUH. Methods This is a retrospective observational study conducted at KAUH. All cellular pathology reports during the 2020 national lockdown were retrieved. The total numbers of specimens including types and procedures were recorded. Data were compared with the corresponding data in 2019 when there was no pandemic and when hospital and laboratory services were run in full capacity. Results 2020 lockdown period showed a 57.9% reduction in the total number of specimens received at the cellular pathology laboratory as compared to the corresponding period of 2019 (1400 versus 3322). Emergency procedures have represented 99.1% of the service during the lockdown with a remarkable diversity shift. Conclusion There was a significant drop in the number of specimens dealt with at KAUH cellular pathology laboratory during the COVID-19 pandemic-related national lockdown. We learned from this pandemic how to adapt to such circumstances by adjusting our way of working to reach the best level of staff safety while maintaining highly productive work. Implementing digital pathology platforms, working from home strategies and alternative training methodologies have emerged as an essential need., Highlights • COVID-19 pandemic-related lockdown had a major influence on healthcare services. • Pathology services and training of residents were influenced by the lockdown, too. • The pandemic taught us how to adapt to such circumstances by adjusting way of working. • Digital pathology platforms and strategies to work from home emerged as essential needs.

Background Lung cancer is a major health burden in Jordan. With the failure of tobacco control policies and the evolution of new smoking methods like water pipes and e-cigarettes, lung cancer is projected to further increase. This study investigates the epidemiology and the different histopathological subtypes of lung cancer in correlation with age, sex and smoking. Material and methods 434 tumors diagnosed in the main tertiary hospital in Northern Jordan throughout the period of 2004–2017 were included. Specimens were tested by H&E and immunohistochemical stains. Clinical data were collected from patients' medical files. IRB approval number 310/2016 was granted by Jordan University of Science and Technology review board. Results 86.9% of cases were males compared to 13.1% in females obtaining a male:female ratio of 6.6:1. The mean age was 63.8 years with a range of 28–103 years. Prevalence of cases increased with increasing age and smoking. Histopathologically, adenocarcinoma accounted for over half of the cases followed by Squamous cell carcinoma (SCC) and neuroendocrine tumors (NET) in both sexes. Adenocarcinoma had the lowest mean age; 62.74 years, while SCC had the highest mean age with 65.42 years. All subtypes increased with age but in different degrees. The increase was more pronounced in SCC and NET and less with adenocarcinoma. Adenocarcinoma was more common in both smokers and non-smokers. However, smokers to non-smokers ratio differed; where it was the highest in NET (6:1) compared to 4:1 in SCC and 2:1 in adenocarcinoma. Conclusion Median age of our patients was slightly lower than that previously reported in Jordan. This study also showed an increase in the relative incidence of adenocarcinoma compared to SCC., Highlights • Lung cancer was more common among males increasing with age and cigarette smoking. • Adenocarcinoma was the most frequent histological subtype of lung cancer. • Adenocarcinoma had higher frequency in younger age groups. • Frequency of squamous cell carcinoma was higher in older age groups. • Jordan is in urgent need to implement stricter tobacco control regulations.

Arabic and Hindi handwritten numeral detection and classification is one of the most popular fields in the automation research. It has many applications in different fields. Automatic detection and automatic classification of handwritten numerals have persistently received attention from researchers around the world due to the robotic revolution in the past decades. Therefore, many great efforts and contributions have been made to provide highly accurate detection and classification methodologies with high performance. In this paper, we propose a two-stage methodology for the detection and classification of Arabic and Hindi handwritten numerals. The classification was based on convolutional neural networks (CNNs). The first stage of the methodology is the detection of the input numeral to be either Arabic or Hindi. The second stage is to detect the input numeral according to the language it came from. The simulation results show very high performance, the recognition rate was close to 100%.

Background: About one in five women suffer from postpartum depression, placing it the leading complication during childbirth. Oxytocin has been suggested to play a key role in modulating maternal behaviour and stress-related disorders. However, there is little evidence to support its role in predicting postpartum depression. Our aim is to investigate the relationship between serum oxytocin level in the third trimester and early-onset postpartum depression symptoms and whether oxytocin is capable of predicting postpartum depression symptoms.Methods: A total of 172 healthy pregnant women participated in this cross-sectional descriptive study. The serum oxytocin level was measured between 34 and 37 weeks. A validated Edinburgh Postnatal Depression Scale (EPDS) was used to assess symptoms of depression four to six weeks postpartum. Participants with EPDS scores of 13 or more were considered having depressive symptoms. SPSS version 23 was used for data analysis. Descriptive statistics were provided. Independent sample t-test and Pearson r were used to examine differences in depression scores between selected demographic, psychosocial, and clinical variables. The level of significance for all analyses was set at α=0.05.Results: 8% of participants have scored 13 or above at the EPDS. Pearson r indicated that there was no correlation between EPDS scores and oxytocin level r(170)=0.10, p=0.23. Furthermore, there was no correlation between EPDS scores and oxytocin level among women with a lifetime history of depression, r(43)= - 0.13, p=0.37. Independent t-test has shown that participants with low education, low income, previous history of depression, positive family history of depression, positive family issues and absent emotional family support have scored significantly higher on EPDS scores than their counterparts. The association with a previous lifetime history of depression was noticeable t(170)= - 4.40, pConclusions: There was no relation between late antenatal third trimester serum oxytocin level and early onset postpartum depression symptoms. Third trimester serum oxytocin level alone was not capable of predicting early onset postpartum depression.

Purpose: Calcium-sensing receptor (CaSR) has been associated with breast cancer metastasis to the bone. Targeting chemoattractant factors, such as calcium, that are released in response to bone resorption could prevent metastasis and induce apoptosis of cancer cells. In the present study, we investigated the potential caspase 3/7 activation following treatment with a CaSR antagonist, NPS-2143, in breast cancer cells. In addition, the effects of NPS-2143 on breast cancer cell proliferation, migration and invasion were assessed. Methods: Colorimetric MTT assay was used to evaluate cell viability. Apo-one homogeneous caspase-3/7 assay was used to measure caspase 3/7 activities in breast cancer cells. Cell migration and invasion were assessed using scratch wound assay and matrigel invasion chambers, respectively. The protein expressions of p-ERK1/2, integrin β1 and Bcl-2 were evaluated using western blotting. Results: Our study revealed that NPS-2143 significantly reduced cell proliferation with half maximal (50%) inhibitory concentration (IC50) values of 4.08 and 5.71 µM in MDA-MB-231 and MCF-7 cells, respectively. NPS-2143 induced caspase 3/7 activation in MDA-MB-231 breast cancer cells which was accompanied with a remarkable reduction in the expression of Bcl-2 antiapoptotic protein. NPS-2143 suppressed migratory and invasive abilities of MDA-MB-231 cells with a significant reduction in the expression of p-ERK1/2 and integrin β1 proteins. Conclusion: Our study confirms the ability NPS-2143 to suppress proliferative, migratory and invasive effects of breast cancer cells which was accompanied by caspase 3/7 activation and suggests the potential of NPS-2143 as a promising anti-cancer molecule in breast cancer.

Oil shale deposits of the mid-Eocene Wadi Shallala Formation in northern Jordan consist of organic-rich limestones and chalks. These organic-rich deposits are exposed at the surface near Wadi Ash Shajara, in a 12-m-thick outcrop. For this study, a total of 21 oil shale samples were analysed for bulk elemental geochemistry, inorganic geochemistry, organic geochemistry and microfacies analysis. Three microfacies types were recognised: pelagic mudstone/wackestone, foraminiferal packstone and bioclastic packstone/wackestone. The observed cyclicity of these microfacies in the study area indicates fluctuations in depositional conditions in Neo-Tethys during the mid-Eocene. A shallow-water, calm, restricted marine environment with limited water circulation and low energy currents evolved into a deeper-water environment with open circulation at or just below the wave base. Wadi Shallala Formation in Wadi Ash Shajara composes mainly of chalk (CaCO3 = ~92 wt%) with a TOC of up to 5 wt % and comprises abundant calcareous nannofossils, foraminifera and ostracods as well as non-clastic components like calcitic fragments. The sulphur content of the analysed samples is significant (1.24 wt %) and is associated with the organic matter. Redox-sensitive elements (Fe, Ni, Zn, S and Zr) are enriched in the oil shale samples, indicating an anoxic depositional environment fluctuating between euxinic and sub-euxinic. These fluctuations in depositional conditions of the basin are a result of many factors such as climate, and tectonisms affected deposition of oil shales during Middle Eocene time.

ObjectiveTo evaluate the influence of different piston variables on hearing following stapedotomy.MethodsData were analysed in groups according to: piston material (titanium vs fluoroplastic), shaft diameter (0.4 mm vs 0.5 mm) and crimping style (manual crimping vs self-crimping). Pre- and post-operative average air–bone gap, air–bone gap difference, success rate and operative time were evaluated.Results and conclusionFifty-one patients (58 ears) were included. A post-operative air–bone gap of 10 dB or lower was achieved in 44 cases, with a success rate of 75.9 per cent; 52 cases (89.7 per cent) had an air–bone gap of 20 dB or lower. The success rate was higher, but not significantly, in fluoroplastic than in titanium pistons (85 per cent vs 70 per cent). Pistons with shaft diameters of 0.5 mm and 0.4 mm had success rates of 79 per cent and 72 per cent, respectively. No significant differences were found for any audiometric parameters. There were no significant differences between manual crimping and self-crimping pistons in terms of audiometric results or success rate.

AIMS OF THE STUDY The purpose of this study was to assess pharmacists' knowledge and attitude towards early detection of colorectal cancer (CRC) in Jordan and to explore potential predictor variables of such knowledge and attitude. METHODS USED TO CONDUCT THE STUDY An electronic, self-reported questionnaire was used to collect data about demographics, knowledge and attitude regarding early detection of CRC. Both content and face validity were tested in a panel of experts. The participants' responses were analysed using descriptive statistics and multiple linear regressions. RESULTS OF THE STUDY The 352 pharmacists (78% females, 94% Jordanian) had a median age of 28 years and graduated mostly (83%) from public universities. Surprisingly, 90% were not able to identify carcinoembryonic antigen (CEA) as a non-accurate diagnostic method and almost one-third did not identify the correct screening tests. On a scale of 5, the majority of participants (59%) had moderate knowledge scores (3 or 4) in case scenarios. The median knowledge Percent of Maximum Possible (POMP) score was 67% and higher scores were associated with more years since graduation, pharmacists with MSc degree and higher, working in urban areas, studying oncology course and received oncology training (P

BackgroundEarly detection and management of hearing loss are important to develop ordinary speaking language and academic skills during childhood. Lack of knowledge by either parents or health care providers could hinder the process of hearing loss diagnosis, such that the intervention will be less effective. There is little evidence about the knowledge and practice of family physicians regarding hearing screening in Saudi Arabia and worldwide.ObjectivesThis study aimed to assess family physicians’ knowledge, attitudes, and practices related to hearing loss in children. This in turn will help policy makers and educational institutions to establish and promote a program concerned with screening, diagnosis and intervention of paediatric hearing loss.MethodsA cross-sectional descriptive study enrolled 133 family physicians working at primary health centres in Saudi Arabia from March 2020 to September 2020. A self-reported questionnaire was used to assess the knowledge, attitudes, and practices of family physicians concerning hearing loss in children.ResultsThe majority of the participants were working under the umbrella of the Ministry of Health and around half of them did not screen any child for hearing loss. Despite that, 91.7% indicated the importance of neonatal hearing screening, 70.7% indicate infant candidacy for cochlear implant and only 33.1% know about the existence of the early hearing detection and intervention (EHDI) governmental program in kingdom of Saudi Arabia (KSA). Participants were able to identify factors associated with hearing loss such as a family history of hearing loss (85.6%), meningitis (75%) and craniofacial anomalies (51.5%). The most frequent specialists for patient referrals were ear nose and throat ENT (75.2%) and audiologists (67.7%).ConclusionThis study shows that family physicians have good general background about the benefits of EHDI programs and the management of hearing loss in the paediatric population. However, it also indicated insufficient knowledge in other domains of hearing loss, including assessments and the presence of the EHDI governmental program in KSA. Further actions on the involvement of family physicians in the process of neonatal hearing screening, diagnosis and intervention for hearing impairment are needed.

Patient: Female, 23-year-old Final Diagnosis: Thoracic outlet syndrome Symptoms: Cervical mass • pain • paresthesia Medication: — Clinical Procedure: CT scan • incisional biopsy • MRI • nerve conduction study • supraclavicular approach to the TOS Specialty: Surgery Objective: Rare disease Background: Osteoblastoma is a very rare bone tumor accounting for 1% of all bone tumors. Most of the time it involves the spine and long bones and it involves the ribs very rarely. While osteoblastoma occurrence in the first rib has been reported, causing neurogenic thoracic outlet syndrome (TOS) has never been reported. Case Report: A 23-year-old woman presented with a left cervical mass associated with pain and paresthesia in the medial aspect of the left upper extremity and 4th and 5th fingers for the previous 3 months. The patient denied any previous illness or trauma in her history. Physical examination revealed a hard mass in the posterior triangle of the left neck with altered sensation in the left 4th and 5th fingers. The patient was investigated by a chest roentgenogram, nerve conduction study, computer tomography (CT) of the chest, and magnetic resonance image (MRI), as well as incisional biopsy. Although all radiological investigations were suggesting osteochondroma with a differential diagnosis of chondrosarcoma, the incisional biopsy showed osteoblastoma. Radical surgical excision of the lesion followed through a left supraclavicular approach. The patient’s preoperative symptoms were relieved completely and there was no recurrence of the tumor at 2 years. Conclusions: Osteoblastoma of the first rib is very rare tumor and to present with TOS is extremely rare. The nonspecific radiological characteristics of the tumor, especially on CT, makes the preoperative certainty of the diagnosis unlikely.

Background Clear Cell Sarcoma of Soft Tissue (CCSST), or melanoma of the soft part, is a rare, aggressive tumor that originates in the aponeurosis and fasciae of the distal parts of the extremities. Reports from other sites of the body are rare. Objective We are reporting an extremely rare tumor that presented as a central left-sided lung mass and found to be clear cell sarcoma of soft tissue. Methods We report a 24-year-old male patient presented with recurrent attacks of left-sided chest pain associated with cough and dyspnea. Results Imaging showed a central left-sided 8*5.5*5 cm lung mass. The age of the patient and the radiological characteristics of the lesion were suggestive of a benign pathology. After histopathological assessment of the lesion, suspicion of the malignant process was raised, mainly melanoma of soft part and PEComa. The patient underwent left-sided pneumonectomy. The postoperative histological examination, immunohistochemical findings including positive staining for S-100, HMB-45, and Melan-A, and positive FISH study for EWSR1 gene rearrangements supported the diagnosis of CCSST originating primarily in the major fissure of left the lung. Conclusion The rarity of CCSST in general and tumors originating in the lung primarily raise the challenges in hypothesizing a differential diagnosis, choosing proper investigations and treatment methods. The histological examination, immunohistochemical, and cytogenetics of the tumor are mandatory to reach the final diagnosis.

Carbonate rocks represent significant aquifers and reservoir rocks in many parts of the world. In this study, twenty-one carbonate samples collected from the exposed rocks at Batroun and Chekka, northern Lebanon, are studied to investigate their lithological characteristics, nannofossil content, and their acoustic and petrophysical properties. Four microfacies are recognized in the studied rocks including packstone, wackstone, wack-mudstone, and the wack-packstone. Nannofossils are detected in the top part of the studied section indicating marine-type depositional conditions for the upper Cretaceous carbonate rocks. The Petrographic analysis revealed also that the studied rocks have moderate to high porosity which is consistent with the measured porosity on core samples. The low porosity of some samples is induced by cementation, which also reduced their permeability. The bulk density varies widely because of the many diagenetic processes that impacted the studied rocks. Moreover, because the primary and secondary wave velocities (Vp, and Vs) are greatly influenced by porosity and density, the samples exhibit extreme variations in acoustic velocities from low values which characterize soft, highly-porous, rocks to higher velocities which are characteristic of compact, massive, and highly-cemented carbonates. Some relationships between the measured petrophysical and acoustic parameters are studied to investigate their mutual dependence, and discuss the impacts of rock composition and diagenetic alterations on the petrophysical properties of the collected rocks. The obtained results are also important in characterizing their mechanical strength, and in the analysis of seismic reflection profiles acquired for equivalent offshore limestone reservoirs in the Levant and the Eastern Mediterranean regions.

Transport and acoustic measurements have been conducted on fifteen rock samples collected from central Lebanon to characterize the rock properties and to assess the impact of lithology, pore types, pore sizes, and textural parameters on the storage capacity and elastic characteristics. The spontaneous imbibition of selected samples was examined by detecting the moving capillary front across a sample. The coefficient of capillarity derived from the spontaneous imbibition is positively correlated with permeability. Seismic velocities in the studied rocks vary widely and are positively correlated with the rock density. Matrix-supported rocks with a larger proportion of micropores have lower seismic wave velocities, whereas the grain-supported carbonates exhibit low to moderate porosity and higher acoustic velocities. The elastic properties of the studied carbonates indicate a granular, rather than a crystalline, texture for the majority of the studied rocks. The widely variable elastic behavior of basically carbonate rocks implies that seismic reflection profiles in carbonate sequences may contain seismic reflections that do not result from non-carbonate intercalations but which result mainly from variable porosity, pore types, and shapes in the carbonate rocks themselves. This study provides important information on the textural, petrophysical, and elastic properties of carbonate rocks which are crucial for the assessment and understanding of the seismic reflection sections in subsurface carbonate reservoirs.

BackgroundAngiogenesis is mandatory for tumor growth and progression. The modest response to the anti-angiogenic therapies in non-small cell lung cancer reflects the presence of confounding molecular factors. The aims of this study were to investigate the expression levels of VEGF-A, CD31 and GRP78 and test for significant correlations between them.MethodsParaffin-embedded NSCLC tissue samples (71 adenocarcinoma and 23 squamous cell carcinoma) were retrospectively collected from 94 patients who underwent surgical resection between 2008 and 2015; and did not receive chemotherapy or radiotherapy prior to surgery. The expressions of VEGF-A, CD31 and GRP78 were determined by immunohistochemistry. ResultsHigh expression levels of VEGF-A, CD31 and GRP78 were observed in 15, 36 and 74 cases, respectively. Adenocarcinomas expressed higher levels of the aforementioned proteins as compared with squamous cell carcinomas (p-value < 0.05). Moreover, a statistically significant association was found between VEGF-A and CD31 expression levels (p-value = 0.006).ConclusionsOur study was the first to investigate the associations between GRP78 and the angiogenesis markers CD31 and VEGF-A in NSCLC patients. High GRP78 expression was revealed in the majority of the investigated samples. Nevertheless, no relationship was found between GRP78 and VEGF-A or CD31 which could be attributed to small sample size. On the other hand, the positive association between VEGF-A and CD31 expression levels suggests that VEGF-A may cooperate with CD31 to promote angiogenesis in NSCLC.

Aims: To evaluate the effectiveness of an interactive teaching intervention on medical students’ knowledge and attitudes about stem cell research and therapy. Methods: A quasi-experimental, one group pre-posttest study design was employed. A six-session interactive teaching course (intervention) was conducted for a duration of 6 weeks. Pre and post intervention surveys were used. Differences in students’ knowledge and attitude mean scores were examined using paired t-test, while gender differences were examined using independent t-test. Results: Seventy one sixth year medical students were invited to participate in this study. A pre-intervention survey was distributed to 58 students who agreed to participate (81.6%). Out of 58 students, only 48 (82.7%) completed the entire course. Total knowledge scores and attitude score significantly increased post intervention. Significant gender differences in knowledge and attitude scores were not detected post intervention. Conclusions: Integrating stem cell science into medical curricula coupled with interactive learning approach were effective in increasing students’ knowledge about recent advances in stem cell research and therapy, and in improving attitudes toward stem cells research and applications.

Blood pressure (BP) is a crucial vital sign of human health. Many methods have been developed for measuring blood pressure either invasive or noninvasive which attracts the attention of researchers. Recently a lot of researches and techniques have been done to find a relationship between the Pulse Transit Time (PTT) and both Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP). This paper proposed a system that focuses on estimating blood pressure utilizing the optical technique. Statistical features are extracted from PTT which are calculated using the Photoplethysmogram (PPG) and Electrocardiogram (ECG) signals. A surface fitting between these features and the SBP and DBP is done. The results show that the system achieves a Mean Absolute Error (MAE) of 4.13 and 6.89 for SBP and DBP respectively and Absolute Error (AE) of 3.77% and 5.76% for SBP and DBP respectively.

In general, many university-level students face difficulties in realizing the basic concepts of computed tomography (CT). Didactic computer simulation is preferred to be used in addition to conventional lectures in order to pave the way for better understanding. This paper proposes an educational tool to facilitate the understanding of basic CT concepts which are covered by many biomedical engineering programs around the world, using graphical user interface (GUI) programmed in MATLAB® environment. As well as it is classified to be an educational tool, this GUI can also help researchers to estimate and evaluate the impact of various key parameters in CT experiments. In this paper multi-projection x-ray images were acquired from scanning different samples (synthetic sea horse, fish, beetle and water bottle) using PHYWE XRCT 4.0 CT educational module.

Blood and its components play a very important role in human life and it considers the best indicator in determining many biological conditions. Pathologists used optical microscopic blood images to diagnose diseases; some of these diseases are Acquired Immune Deficiency Syndrome (AIDS), Leukemia, after recognizing white blood cells (WBCs) from those images. Recently, a Computer-aided diagnosis system is used for diagnosing blood from its microscopic images. In this research, microscopic WBCs images were classified using a hybrid system where Convolutional Neural Network (CNN) used as features extractor and different machine learning algorithms used as classifiers, then the performances of these classifiers were evaluated to recognize the best of them. These algorithms include Support Vector Machine (SVM), k-Nearest Neighbor (KNN) and Random Forest, for training and test parameters we used five features that were extracted from the images. According to results of performance, the RF performed better than the other methods with a testing accuracy reached 98.7%.