Assessment of Biphasic Calcium Phosphate mixed with injectable platelet rich fibrin (i-PRF) on healing of surgically created bone defects in a sheep animal model (A Histological Analysis)

Aims: Assessment of Biphasic Calcium Phosphate mixed with injectable platelet-rich fibrin (i-PRF) on healing of surgically created bone defects in a sheep animal model. Materials and Methods: In each tibia / radius of five sheep, three defects each measuring 7mm in diameter and 4mm in depth were created. The defects were filled with study materials and in the following order: from a proximal to distal orientation; the first defect was filled with biphasic calcium phosphate alone, the second left empty to be filled by physiological clot, and the third with i-PRF mixed with biphasic calcium phosphate. Histological examination of bone defects was made to assess bone formation at fourtime intervals (two, four, six and eight weeks) post-surgically. Results: Regarding bone formation, histological findings showed the presence of a significant difference within the time intervals in the BCP+i-PRF group and in the BCP group when compared with the control group with the highest mean being at eight weeks post-surgery in the BCP+i-PRF group. Conclusions: Both BCP and i-PRF, enhanced bone formation when compared to the control group and throughout the period of study and as disclosed by histological findings

Impact of Biphasic Calcium Phosphate mixed with injectable platelet rich fibrin (i-PRF) on bone density in surgically created bone defects in a sheep animal model (A Radiographic Assessment)

Aims: To assess bone density means with Biphasic calcium phosphate alone or mixed with injectable platelet-rich fibrin in bone defects created surgically in sheep’s tibia / radius using standard radiographic assessment. Materials and Methods: Three bony defects of 4mm full and 7 mm in diameter were created in every tibias/radius of five sheep. The defects were stuffed within the following order: from a proximal to distal orientation; 1st defect was full of biphasic calcium phosphate alone, the second was left empty to be filled by physiological clot and also the third with i-PRF mixed with BCP and covered with absorbable collagen membrane for tissue guiding and then sutured. Densitometric analysis of bone defects was made to measure density of bone at four-time intervals (two, four, six and eight weeks) post-surgically. Results: Densitometric analysis results showed a major distinction within the BCP+i-PRF group and BCP group compared with the control one and at all-time intervals with the best density being in the 1st group followed by the BCP alone group and least in the control group. Conclusions: BCP and i-PRF, both of them increased and sustained bone density (synergistic effect) throughout the study period as revealed by densitometric data

A Comparison of Chemical Compounds between Anti-Diabetic Drug and Some Medicinal Plants

Type 2 diabetes (T2D) is a kind of diabetes marked by high blood sugar, insulin, and insulin insufficiency. Adult-onset diabetes is another name for it. Increased thirst, frequent urination, and unexplained weight loss are common indications and symptoms. Metformin side effects include metallic taste, weakness, diarrhea, stomach upset, lactic acidosis, and vomiting. Two other side effects are asthenia and a Vitamin B12 deficiency. Many recent studies and most health experts recommend basil seed as a better Metformin substitute. The research investigates why patients who consume basil seeds have a similar response to those who take Metformin. The methodology of the study consisted of two main steps, first step is to analyze basil and use HPLC to determine its chemical components. The second step is to compare the broken-down components to Metformin-composed materials, which is done by diluting with methanol/water (50:50 v/v) and removing the fat layer using 20 mL hexane. The findings showed that basil seed and Metformin had the most similar component structure, thus the foundlings concluded that patients had the same responses without the Metformin side effects, implying that basil seed stabilizes blood sugar levels

Understanding Key Bidding Factors Considered by Top Jordanian Contractors

One of the most crucial decisions that is regularly exercised by construction contractors is to determine whether to bid or not to bid on a certain project. The purpose of this paper is to understand key factors that are considered by top Jordanian contractors in their bid/no-bid decision making. Previous research in the Jordanian construction market reported the importance weights of 53 bid/no-bid factors (El-Mashaleh, 2013). Based on that work, this paper discusses the top bidding factors and compares them with international related work. Additionally, the paper examines the reliability of El-Mashaleh’s (2013) study based on Cronbach's alpha reliability test. Furthermore, the paper tests the degree of consensus among the respondents of El-Mashaleh’s (2013) work regarding the ranking of the 53 bid/no-bid decision factors based on Kendall's coefficient of concordance. Finally, analysis of variance (ANOVA) is conducted to test statistical significant differences in the importance weights of the 53 bidding factors between public and private bidders. Cronbach's alpha reliability test proves that the adopted scale of measurement for the importance of the bid/no-bid factors has excellent internal consistency reliability. Kendall's coefficient of concordance reveals a significant degree of consensus among the respondents regarding the ranking of the bid/no-bid decision factors. Analysis of variance (ANOVA) indicates statistical significant differences in importance weights between public and private bidders for 6 factors out of the 53 factors considered

Host genetic susceptibility to mycetoma

Mycetoma is one of the badly neglected tropical diseases characterised by subcutaneous painless swelling, multiple sinuses and discharge containing aggregates of the infecting organism known as grains. Risk factors conferring susceptibility to mycetoma include environmental factors, pathogen factors such as virulence and the infecting dose in addition to host factors such as immunological and genetic predisposition. Epidemiological evidence suggests that host genetic factors may regulate susceptibility to mycetoma and other fungal infections but they are likely to be complex genetic traits where multiple genes interact with each other and environmental factors, as well as the pathogen, to cause disease. This paper reviews what is known about genetic predisposition to fungal infections that might be relevant to mycetoma as well as all studies carried out to explore host genetic susceptibility to mycetoma. Most studies were investigating polymorphisms in candidate genes related to the host immune response. A total of 13 genes had allelic variants found to be associated with mycetoma and these genes lie in different pathways and systems such as innate and adaptive immune systems, sex hormones biosynthesis and some genes coding for host enzymes. None of these studies have been replicated. Advances in genomic science and the supporting technology have paved the way for large-scale genome-wide association and next generation sequencing (NGS) studies, underpinning a new strategy to systematically interrogate the genome for variants associated with mycetoma. Dissecting the contribution of host genetic variation to susceptibility to mycetoma will enable the identification of pathways that are potential targets for new treatments for mycetoma and will also enhance the ability to stratify “at-risk” individuals allowing the possibility to develop preventive and personalised clinical care strategies in the future

QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology.

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber cross-sectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the "patchy" distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigator-specific needs and provides novel analytical approaches for quantifying muscle morphology

QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber crosssectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the “patchy” distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigatorspecific needs and provides novel analytical approaches for quantifying muscle morphology

A population-based study of 15,000 people on Knowledge and awareness of lung cancer symptoms and risk factors in Saudi Arabia

Background: Lung cancer is currently the most fatal form of cancer worldwide, ranking as the fourth most prevalent type in Saudi Arabia, particularly among males. This trend is expected to increase with growing population, lifestyle changes, and aging population. Understanding the awareness of the Saudi population regarding the risk factors and symptoms of lung cancer is necessary to attenuate the predicted increase in cases. Method: A cross-sectional, population-based survey was performed using a previously validated questionnaire (Lung CAM). Multiple linear regression analysis was used to assess variables associated with deficiency in knowledge and awareness of risk factors and symptoms of lung cancer. Results: Majority of the 15,099 respondents were male (65%), aged between 18 and 30 years (53%), 50% of which were educated up to a bachelor’s degree level. Overall awareness of lung cancer signs and symptoms was 53%, with painful cough and coughing up blood being the best-known symptoms. Conversely, persistent shoulder pain (44%) and clubbing fingers (47%) were the least known lung cancer symptoms. Also, 60% of the respondents showed low confidence in identifying the signs and symptoms of lung cancer. The overall awareness of the risk factors for lung cancer development was 74%, with first-hand (74%) and second-hand (68%) smoking being the most known risk factors. However, only ≤ 62% know the other non-smoking risk factors. Awareness of the risk factors and symptoms of lung cancer depended on age, gender, education, marital and employment status (p < 0.001). Conclusion: Public awareness of the risk factors and symptoms of lung cancer in Saudi Arabia is inadequate and heavily dependent on education and socio-economic status. Awareness can be improved through campaigns to raise awareness about other lesser-known lung cancer risk factors and symptoms

A population-based study of 15,000 people on Knowledge and awareness of lung cancer symptoms and risk factors in Saudi Arabia

Background: Lung cancer is currently the most fatal form of cancer worldwide, ranking as the fourth most prevalent type in Saudi Arabia, particularly among males. This trend is expected to increase with growing population, lifestyle changes, and aging population. Understanding the awareness of the Saudi population regarding the risk factors and symptoms of lung cancer is necessary to attenuate the predicted increase in cases. Method: A cross-sectional, population-based survey was performed using a previously validated questionnaire (Lung CAM). Multiple linear regression analysis was used to assess variables associated with deficiency in knowledge and awareness of risk factors and symptoms of lung cancer. Results: Majority of the 15,099 respondents were male (65%), aged between 18 and 30 years (53%), 50% of which were educated up to a bachelor’s degree level. Overall awareness of lung cancer signs and symptoms was 53%, with painful cough and coughing up blood being the best-known symptoms. Conversely, persistent shoulder pain (44%) and clubbing fingers (47%) were the least known lung cancer symptoms. Also, 60% of the respondents showed low confidence in identifying the signs and symptoms of lung cancer. The overall awareness of the risk factors for lung cancer development was 74%, with first-hand (74%) and second-hand (68%) smoking being the most known risk factors. However, only ≤ 62% know the other non-smoking risk factors. Awareness of the risk factors and symptoms of lung cancer depended on age, gender, education, marital and employment status (p < 0.001). Conclusion: Public awareness of the risk factors and symptoms of lung cancer in Saudi Arabia is inadequate and heavily dependent on education and socio-economic status. Awareness can be improved through campaigns to raise awareness about other lesser-known lung cancer risk factors and symptoms

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020