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Double haploids (DHs) production and utilization is an important aspect of wheat breeding programs in worldwide, because, it provides many advantages over the conventional breeding program. Therefore, in vitro and in vivo responses of anther derived two bread wheat cultivars and their F1 crosses were investigated. Results showed significant genetic variation among the tested bread wheat genotypes. The pre-cold treated anther derived embryonic calli and shoot induction (%) were obtained from all genotypes that ranged 44 - 76% and 32 - 58% respectively. The highest shoot induction from embryonic calli was achieved from F1 cross of Zubkov x Atay-85, whereas, lowest induction was obtained from Atay-85 cultivar. The F1 cross (Zubkov x Atay-85) showed a better response in anther culture in term of shoots per plant and root induction than their respective parental genotypes.The present results indicated positive and significant heterotic effects of F1 crosses for calli and shoot induction that also showed less albino plant regeneration after colchicine treatments. Total number of 114 anthers driven DHs lines from two genotypes and their F1 crosses were regenerated, confirmed by flow-cytometry and evaluated under field condition. Some DHs lines were found to be significantly superior for agronomical traits including seed yield than the parental genotypes as well as local bread wheat (control) cultivars.

We report a case of nodular posterior scleritis in a 25-year-old male who presented with a 14-day history of unilateral decline in vision, pain, and redness in his right eye. Slit lamp examination of the right eye revealed dilated episcleral vessels present nasally as well as a choroidal mass at the nasal periphery of the fundus, associated with choroidal oedema. Systemic evaluation and imaging of the choroidal mass were performed to rule out choroidal tuberculoma and choroidal metastasis. Ultrasound B-scan of the right eye showed marked thickening of the nasal sclera resulting in sympathetic choroidal oedema without the characteristic T-sign. Nodular posterior scleritis with associated choroiditis, was diagnosed without any underlying systemic illness. The patient was immediately started on systemic steroids and later on subcutaneous Methotrexate as advised by the rheumatologist, to which he responded well and his vision significantly improved from 6/60 to 6/9, gradually during his treatment course.

Due to the significance of macular edema in retinal vascular diseases, this study aims to determine whether laser photocoagulation is effective in the treatment of macular edema and in the improvement of visual acuity. This is a prospective data study considering 80 patients with 52 eyes, with a follow-up of 6 weeks, 3 months, and six months with macular edema treated with double frequency yag laser photocoagulation in Aso Eye Hospital in Sulaymaniyah City, Kurdistan, Iraq, from February 2010 to October 2010. With six months of follow-up, visual acuity was improved in 36.4% of eyes, unchanged in 61.3%, and worsened in 2.3%. After this period the macular edema was improved in 78.85% and not improved in 21.15%. According to this study, baseline visual acuity and retinopathy severity were two important intervening factors in response to laser therapy. Comparing the current results with other studies, it has been found that, in assessing visual outcomes, laser photocoagulation is an effective modality in the treatment of macular edema, and it improves visual acuity in retinal vascular diseases.

ObjectiveDelirium is associated with worse outcomes in patients with stroke and neurocritical illness, but delirium detection in these patients can be challenging with existing screening tools. To address this gap, we aimed to develop and evaluate machine learning models that detect episodes of post-stroke delirium based on data from wearable activity monitors in conjunction with stroke-related clinical features.DesignProspective observational cohort study.SettingNeurocritical Care and Stroke Units at an academic medical center.PatientsWe recruited 39 patients with moderate-to-severe acute intracerebral hemorrhage (ICH) and hemiparesis over a 1-year period [mean (SD) age 71.3 (12.20), 54% male, median (IQR) initial NIH Stroke Scale 14.5 (6), median (IQR) ICH score 2 (1)].Measurements and main resultsEach patient received daily assessments for delirium by an attending neurologist, while activity data were recorded throughout each patient's hospitalization using wrist-worn actigraph devices (on both paretic and non-paretic arms). We compared the predictive accuracy of Random Forest, SVM and XGBoost machine learning methods in classifying daily delirium status using clinical information alone and combined with actigraph data. Among our study cohort, 85% of patients (n = 33) had at least one delirium episode, while 71% of monitoring days (n = 209) were rated as days with delirium. Clinical information alone had a low accuracy in detecting delirium on a day-to-day basis [accuracy mean (SD) 62% (18%), F1 score mean (SD) 50% (17%)]. Prediction performance improved significantly (p < 0.001) with the addition of actigraph data [accuracy mean (SD) 74% (10%), F1 score 65% (10%)]. Among actigraphy features, night-time actigraph data were especially relevant for classification accuracy.ConclusionsWe found that actigraphy in conjunction with machine learning models improves clinical detection of delirium in patients with stroke, thus paving the way to make actigraph-assisted predictions clinically actionable.

Automated diagnosis of eye diseases using machine and deep learning models has become increasingly popular. Glaucoma, cataracts, diabetic retinopathy, Myopia, and age-related macular degeneration are common eye diseases that can cause severe damage. It is crucial to detect eye diseases early to prevent any potentially serious consequences. Early detection of eye disease is vital for effective treatment. Doing in-depth reading to identify any potential signs of eye disease is highly recommended. This paper will review all machine learning models built to detect and classify eye diseases in addition to helping grasp all limitations and challenges in this field. Recognizing eye diseases is a difficult task that typically requires several years of medical experience. This research is to be conducted to serve as a starting point for finding the most versatile solution. This research aims to review eye disease classification using deep learning models, including VGG16, ResNet, and Inception. The general classification model consists of these steps: The first step is to collect the globally obtainable datasets for the eye disease and pre-process them to ensure the generalization of experiments. The goal is to train the model to recognize disease symptoms instead of tweaking the outcomes for a specific dataset section. With the successful deployment of deep learning techniques for image classification and object recognition, research is now directed towards deep learning techniques instead of traditional handcrafted methods. One possible solution for the eye diseases classification challenge is to use a pre-trained deep CNN model for representation and feature extraction. This solution can be followed by classifier methods, such as support vector machines (SVM), multilayer perceptron (MLP), etc. It has been detected that CNN-based methods learned on large-scale marked datasets can be used for eye disease classification tasks with limited training datasets.

Purpose – English instructors' pragmatic competence (PC) is an aspect of the overall communicative competence forming the basis of language instructors' knowledge. Their knowledge of pragmatics should not be overlooked when seeking to understand foreign language learners' communicative ability. This study aims to investigate the pragmatic awareness and teaching practices of non-native EFL instructors with different qualifications and from various cultural backgrounds in Saudi Arabia. Design/methodology/approach – To obtain a broader perspective, this study adopted a quantitative research design. An online questionnaire, developed from Ivanova (2018) and Tulgar (2016), was accessed by 320 instructors at one English teaching institute in Saudi Arabia. The questionnaire consisted of demographic information about participants and 12 closed Likert-type questions. Findings – The data analysis showed that most of the language instructors were aware of PC. However, some variations were evident in their views of the importance of pragmatics in teaching and learning and in their actual pragmatic teaching practices. Originality/value – This study emphasizes the importance of pragmatic awareness for EFL instructors. It indicates that while non-native English instructors' academic levels and cumulative experience in teaching English play a major role in teaching, instructors have several challenges in teaching pragmatics and promoting students' awareness of pragmatics in this context. For effective second language teaching of pragmatics, instructors, managers and policymakers need to recognize the importance of pragmatics and competencies that students need to develop in EFL contexts.

Klebsiella pneumoniae is recognized as an urgent public health threat because of the emergence of difficult-to-treat (DTR) strains and hypervirulent clones, resulting in infections with high morbidity and mortality rates. Despite its prominence, little is known about the genomic epidemiology of K. pneumoniae in resource-limited settings like Bangladesh. We sequenced genomes of 32 K. pneumoniae strains isolated from patient samples at the International Center for Diarrhoeal Disease Research, Bangladesh (icddr,b). Genome sequences were examined for their diversity, population structure, resistome, virulome, MLST, O and K antigens and plasmids. Our results revealed the presence of two K. pneumoniae phylogroups, namely KpI (K. pneumoniae) (97%) and KpII (K. quasipneumoniae) (3%). The genomic characterization revealed that 25% (8/32) of isolates were associated with high-risk multidrug-resistant clones, including ST11, ST14, ST15, ST307, ST231 and ST147. The virulome analysis confirmed the presence of six (19%) hypervirulent K. pneumoniae (hvKp) and 26 (81%) classical K. pneumoniae (cKp) strains. The most common ESBL gene identified was blaCTX-M-15 (50%). Around 9% (3/32) isolates exhibited a difficult-to-treat phenotype, harboring carbapenem resistance genes (2 strains harbored blaNDM-5 plus blaOXA-232, one isolate blaOXA-181). The most prevalent O antigen was O1 (56%). The capsular polysaccharides K2, K20, K16 and K62 were enriched in the K. pneumoniae population. This study suggests the circulation of the major international high-risk multidrug-resistant and hypervirulent (hvKp) K. pneumoniae clones in Dhaka, Bangladesh. These findings warrant immediate appropriate interventions, which would otherwise lead to a high burden of untreatable life-threatening infections locally.

Adapting to university life in Saudi Arabia can be difficult for international students. This qualitative research, based on the social adaption framework, explore in detail the problems that international students experience during their enrolment at Al-Imam Mohammad Ibn Saud Islamic University (IMSIU), which is located in Riyadh, Saudi Arabia. Utilizing purposeful sampling, 20 students participated in the semi-structured interviews. The interviews contained 16 questions to elicit the students’ perceptions about the challenges they encountered faced during their residence in Saudi Arabia. Findings revealed that international students experienced language barriers, had to deal with issues regarding culture shock, and had episodes of depression, nostalgia, stress, loneliness, and homesickness. However, these international students retained positive attitudes about their social adaptation and were satisfied with the resources and facilities provided at IMSIU. It was strongly suggested that student affairs officers, academic professionals, and social work practitioners, who interact with overseas students, should strive to help international students overcome possible language, communication, lifestyle, and institutional barriers. The implication is that international students should utilize various counseling and professional guidance resources to assist them adapt to the new lifestyle in the host country. This study could be replicated using a mixed-methods approach for future investigators.

In the current work electrical and ion transport parameters of polymer electrolyte (PE) system of chitosan (Ch)/poly(2-oxazoline) (POZ)loaded with various concentrations of lithium nitrate (LiNO3) salt were studied. The EIS analysis shows that the load of LiNO3 improves the conductivity of the PE. The depressed semicircle of EIS which its center is below the Zr-axis and the distribution of relaxation time (τ) of the electrolytes verify the non-Debye behavior of the electrolytes. The maximum conducting system (CSPZLI5) shows the highest conductivity of 1.46 × 10−3 S/cm. Transport parameters (number density (n), mobility (μ), viscosity (η), and diffusion coefficient (D) of ions) are measured by Trukhan and EIS methods and compared agreeably and it is also consistent with the conductivity results. The determined n value from EIS was found to increase from 1.69 × 1016cm−3 to 9.5 × 1019 cm−3. Distinguished areas of stability attributed to DC involvement were marked from AC spectra. Dielectric parameters (i.e. ε' and ε'') are high at the low-frequency (fr) window due to electrode polarization (EP). The loss tangent (tan δ) is used to measure the relaxation time (τ) and ion transport parameters. The τ for the PEs is set off to decrease with increase of LiNO3 amount. The minimum τ of 4.08 × 10−7 s confirms the LiNO3 role in increasing ion migration. The transport parameters (n, μ, D, and η) are also in relationship with the dielectric and impedance analyses. From electric modulus examination it is found that the EP contribution can be minimized and relaxation attributing to bulk effects can be highlighted.

Bread is the most consumed and staple food in many countries worldwide. It is made from dough of flour such as wheat and barley, and water. It usually contains flour improver potassium bromate (KBrO3) which is used by bakers. However, many studies have confirmed the deleterious effects of KBrO3 on human health. Therefore, this study aimed to determine the rate of KBrO3 in five main types of bread in Sulaimani city, Kurdistan-Iraq. The duration of the study was from August 2021 to November 2021. Thirty bread samples were collected from five main products that are extremely consumed by Kurdish citizens. The bread-type products were bakery bread (Nani frn), white hamburger bread (Samun), white bread known as Kurdish bread (Nani Hawrami), pizza, and brown barley bread. Single beam UV–visible spectrophotometer APEL-303 was used for the quantification of KBrO3 in bread samples. The results found that all 30 samples were had KBrO3 residues in their products with different concentrations. Samples of brown barley bread were having the least content of KBrO3 while samples from pizza dough were having the highest concentration of KBrO3. The present study concludes that all bread samples from five major bread types had potassium bromate above the permitted levels allowed by the United States Food and Drug Agency (FDA).

The use of machine and deep learning models for the automated detection of eye disorders has gained significant popularity. Glaucoma, cataracts, and diabetic retinopathy are prevalent ocular conditions that can result in substantial harm. Prompt identification of ocular disorders is crucial for optimal therapeutic intervention. A novel idea of implementing weighted ensemble deep learning, which is integrated with Two-Dimensional Discrete Wavelet Transform (2D DWT) and 2D Principal Component Analysis (2D PCA) for optimum feature selection for classification, has been proposed in this research. This work includes evaluating the performance of pre-trained deep-learning models in detecting eye problems using the Efficientb6 and Densnet169 models. Then, the impact of applying weighted ensemble learning on improving these pre-trained deep-learning models' eye disease classification performance is investigated. The proposed methodology comprises three essential stages: pre-processing, feature extraction, and classification. Various methods are utilized during the pre-processing stage, including implementing Data Augmentation, which involves modifying the training data. Different techniques are employed in the feature extraction stage to extract the useful features from the input data. Each of these techniques achieved different dimensionality reduction. Finally, both models of Efficientb6 and Densnet169 are employed for the extracted features to achieve exceptional performance. The proposed system accomplished a recognition rate of 96.1 with 0% dimensionality reduction when the ensemble learning model was implemented directly on the pre-processed data set, skipping the feature extraction stage. Furthermore, the system proposed achieved an accuracy of 94.9 with 67.3% dimensionality reduction when only one level of 2D DWT decompositions is used. Moreover, the system proposed obtained a comparable accuracy of 92.9 with 93.75% data reduction when the 2-level of 2D DWT decompositions is integrated with 2D PCA. The experiments undertaken in this research successfully achieved its aims of obtaining favorable outcomes of eye disease classification, reducing the data dimensions to decrease the deep learning model trainable parameters, and implementing complexity requirements. The findings of the suggested approach surpassed those shown in prior studies utilizing the same Kaggle datasets. [ABSTRACT FROM AUTHOR]

Background: Both obesity and depression pose significant public health challenges. Understanding the age-gender differences in the BMI-depression associations is crucial, especially in the Saudi context, where cultural norms, lifestyle factors, and socio-economic conditions may significantly influence these associations. We aimed to explore and elucidate these associations in Saudi adults, considering age and gender as crucial factors. Methods: The research utilized a cross-sectional web-based survey to examine the impact of age and gender on the associations between BMI and depression. The study included 4,683 Saudi adults aged 18–60 years. The questionnaire assessed socio-demographics, lifestyle factors, chronic illnesses, and self-reported height and weight to calculate BMI. Depression Inventory-II (BDI-II), a self-reported scale, was used to evaluate depression, categorizing participants into depression and non-depression groups. A snowball convenience sampling was utilized, with clear inclusion and exclusion criteria established to mitigate potential biases. Data analysis was stratified by age and gender, and binary logistic regression was utilized to determine the associations between depression and BMI, incorporating odds ratios (ORs) in both crude and adjusted forms, along with 95% confidence intervals (CIs). Results: The prevalence of depression was found to be 43.3%, while 21% of participants were classified as obese. Notably, individuals in the depression group were significantly older, predominantly female, and more likely to reside in the Western and Southern regions of Saudi Arabia. They had lower family income, were more frequently non-smokers, had a higher prevalence of chronic diseases, and had higher BMI. Moreover, obese individuals had significantly higher depression scores (p < 0.05). After adjusting for confounding factors, OR for depression was significantly higher among obese individuals (1.92 [1.56–3.36]). Stratified analysis by age and gender revealed higher ORs for depression among obese participants in older age and among women. Conclusion: This study highlights a significant association between obesity and increased prevalence of depression, with notable age and gender differences in this association. The findings suggest that older adults and women, particularly those with obesity, are at a higher risk for depression. These insights emphasize the importance of tailoring public health strategies and mental health interventions to address the specific needs of these vulnerable groups in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Background: The common illness known as Major depressive disorder (MDD) is defined by significantly increased rates of illness and disease, impairment, and suicidal thoughts. Numerous investigations have demonstrated the significant impact cystatin C plays in cognitive impairment and major depressive disorder (MDD). Aim:Toassess the relation between serum cystatin c concentration and depressive symptoms, suicidal ideation and cognitive dysfunctions in patients with MDD. Methods: this case-control study was carried out on 69 patients with major depressive disorder diagnosed according to DSM-V criteria that attended outpatient clinic of the Psychiatry department El-Azazy psychiatric hospital & Psychiatry department at Zagazig university hospitals and 69 healthy controls. Cystatin C level was measured. Results: Cystatin C level was significantly higher in major depression patients compared to controls. There was a significant positive correlation between cystatin C with age, Hamilton depression rating scale, BECK scale and MOCA scale. Cases in rural areas showed significant elevation in cystatin C level compared to cases in urban areas (p=0.025). There was a significant relation between degree of depression, suicidal ideation, cognitive dysfunction and cystatin C as it was significantly higher in these cases. Cystatin C was a significant predictor of major depressive disorder (AUC=0.851, P value<0.001). The suggested cut-off value (>1 mg/L) showed 66.7% sensitivity, 92.8% specificity, 90.3% PPV and 73.6% NPV Conclusion: Serum Cys C levels are associated with depressive symptoms, cognitive dysfunction and suicidal ideation in MDD patients. [ABSTRACT FROM AUTHOR]

Cadmium, a hazardous heavy metal prevalent in plants and soil, poses a significant threat to human health, particularly as approximately 60% of the global population consumes wheat, which can accumulate high levels of Cd through its roots. This uptake leads to the translocation of Cd to the shoots and grains, exacerbating the potential health risks. However, promising results have been observed with the use of moringa leaf extract (MLE) foliar spray in mitigating the adverse effects of Cd stress. The current experiment was conducted to find out the Cd stress tolerance of wheat varieties V1 = Akbar‐19 and V2 = Dilkash‐2020 under exogenous spray of MLE. The treatments of this study were T0 = 0% MLE + 0 µM Cd, T1 = 3% MLE + 0 µM Cd, T2 = 0% MLE + 400 µM Cd, and T3 = 3% MLE + 400 µM Cd. Cd stress demonstrated a significant reduction in morphological attributes as shoot and root fresh weight (22%), shoot and root dry weight (24.5%), shoot and root length (22.5%), area of leaf and number of leaves 30.5%, and photosynthetic attributes (69.8%) in comparison with control. Exposure of wheat plants to Cd toxicity cause oxidative stress, increased H2O2, and MDA up to 75% while foliar application of MLE reduced the activities of reactive oxygen species (ROS). The activity of catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), and ascorbic acid (AsA) increased up to 81.5% as well as organic osmolytes such as phenolics, total soluble proteins, and total soluble sugars were improved up to 77% by MLE applications under Cd stress. Higher accumulation of ionic contents root Na+ (22%) and Cd (44%) was documented in plants under Cd stress as compared to control, while uptake of root mineral ions Ca2+ and K+ was 35% more in MLE‐treated plants. In crux, Cd toxicity significantly declined the growth, photosynthetic, and biochemical parameters while 3% MLE application was found effective in alleviating the Cd toxicity by improving growth and physiological parameters while declining reactive oxygen species and root Na+ as well as Cd uptake in wheat. [ABSTRACT FROM AUTHOR]

Aim: Root canal treatment (RCT) is a common procedure practiced daily by dentists worldwide. The current systematic review aimed to evaluate and compare clinical studies on the quality of root canal fillings (RCFs) carried out by dentists with different levels of experience conducted worldwide with those conducted specifically in Saudi Arabia (SA). Materials and Methods: A full literature search was conducted in Clarivate Analytics' Web of Science, Elsevier's Scopus, Embase, CINHAL, and PubMed, without a restriction to studies published before January 2015. Also, a manual search was carried out by checking papers that may have been missed during the electronic search. The following keywords were used: [(quality of root canal filling(s)) OR (quality of root canal obturation)) and dental practitioners as (general dental practitioners; final year students; endodontist; specialist) AND (root canal obturation) OR (endodontic treatment)]. Parameters of the quality of RCFs, such as length, density, and taper, were assessed and counted. Results: A total of 13 worldwide and nine SA studies were included in this review, published between 2015 and 2023. Molars were the most treated teeth, at 42.3% and 40.2% for the worldwide and SA studies, respectively. Cases treated by final year students had the highest percentage, at 60.0% for both study groups. The percentages of acceptable quality, with regard to the length, density, and taper of RCFs, were 70.9%, 77.6%, and 84.3%, and 73.2%, 64.6%, and 67.8% for the worldwide and SA studies, respectively. Conclusion: The overall acceptable quality of RCFs was marginally higher in worldwide studies than in SA studies. Both prevalences can be considered as good, which indicates that the quality of RCFs is moving in the right direction. [ABSTRACT FROM AUTHOR]

Cesium-based halide double perovskites have wide range of applications, and have emerged as a promising class of materials in the field of photovoltaic, optoelectronics and catalysis. In this manuscript, the Wien2K simulation code is used to analyze the effect of multiple potentials on the optoelectronic, mechanical and structural traits of Cs2InBiF6 by employing the FP-LAPW method. The electron–ion interactions are taken in account by using LDA, GGA-PBE-sol, WC-GGA, GGA-PBE and TB-mBJ approximations. The crystal structure is relaxed and the results are fitted by using Birch–Murnaghan equation. The elastic properties reveal that Born's stability criteria are fulfilled by C11, C12 and C44. Furthermore, the hardness factor and machinability index reveals that material is highly malleable. The band structure profiles reveals direct bandgap of 2.22 eV, 2.25 eV, 2.28 eV, 2.32 eV and 3.00 eV for LDA, PBE-sol, WC-GGA, GGA and mBJ potentials, respectively. The electromagnetic interaction with the material reports maximum polarization and dispersion in the UV region making this material viable for sunscreens, UV-blocking coatings, and photodetectors. [ABSTRACT FROM AUTHOR]

To understand the current status of water resource utilization and explore the coordination degree of the coupled human–water–ecosystem in the Tarim River Basin, we used the water shortage rates and index of WUE to analyze the dynamic changes in water shortage and water use efficiency. We also applied the Gini coefficient to study the evolutionary trend of the degree of matching between water consumption and GDP in each sector. Based on the above analysis, we developed a human–water–ecosystem coupling coordination degree model incorporating various indicators relevant to the three subsystems to quantitatively assess the coupled and coordinated development status of the three subsystems of the human–water–ecosystem in the basin from 2004 to 2020. The main findings are as follows: (1) The Tarim River Basin suffers from water shortage in dry years, with a prominent supply–demand contradiction. In the severe drought years of 2009 and 2014, the water shortage rates reached 10.20% and 10.93%, respectively. (2) From 2004 to 2020, the Tarim River Basin's water use efficiency (WUE), and its five prefectures showed a clear upward trend. On a multi-year average, Bayingol Mongolian Autonomous Prefecture had the highest WUE, while the Hotan region had the lowest. (3) The multi-year average value of the match between water consumption and GDP for the entire basin is 0.28. By industry, the primary industry's match between water consumption and GDP is higher, while the secondary and tertiary industries have lower matches. (4) From 2004 to 2020, the coordination degree of coupled human–water–ecosystem in the five prefectures showed different degrees of upward trend, generally developing towards better coordination. In terms of multi-year averages, Bayingol Mongolian Autonomous Prefecture, located in the east, has the highest degree of coupled coordination. Meanwhile, Hotan, in the south, lags significantly behind the remaining four regions. Therefore, the Tarim River Basin should further improve and optimize the development model of sustainable water resource use. [ABSTRACT FROM AUTHOR]

Background: Knowledge regarding surgical site infections (SSIs) can help reduce hospital stay, morbidity, and mortality associated with SSI. Objectives: This study aimed to determine the knowledge and awareness of SSI among patients undergoing surgeries across Saudi Arabia. Methods: This multi-center cross-sectional study included adult patients (aged >18 years) who underwent surgery at six centers located across the five regions of Saudi Arabia. A 36-item questionnaire was used to elicit data regarding demographics, patient's health status, procedures, and hospitalization history and awareness and knowledge about SSIs. Results: A total of 375 patients were included (equally for all five regions of Saudi Arabia). Most patients were male (55.7%) and aged 18–34 years (44%). Most respondents (49.1%) had poor awareness; being illiterate and from the Northern region were significant factors (P = 0.001). Patients with no history of surgery (P = 0.001) or SSI (P = 0.003) also had poor awareness levels. In terms of knowledge, 45.8% and 35.2% of the participants had fair and poor knowledge, respectively, with the level of knowledge being significantly associated with region (P = 0.001). Patients those aged >65 years had poor knowledge (P = 0.033), while of males had good knowledge (P = 0.02). Patients with no history of surgery had poor knowledge of SSIs (P = 0.003). Only 32.8% of the patients recalled having been educated by healthcare workers. About 42% learned of SSIs from sources outside the hospital, with internet/social media platforms accounting for 48.4% of such sources. Conclusion: A significant proportion of the patients included in this study had poor awareness and knowledge of SSIs. The study highlights the need for strengthening the preoperative patient education in Saudi Arabia to reduce the likeliness of SSIs.

Background: Chronic hypervolemia is the main cause of cardiovascular complications in haemodialysis patients. Objectives: We aimed to study the effect of lung ultrasound-guided dry weight reduction strategy on the cardiovascular state of hypertensive haemodialysis patients. Patients and Methods: We carried out a single-blind two-arm randomized trial on 50 hypertensive haemodialysis patients in Qena University Hospital dialysis centre over 8 weeks from 1/11/2020 to 1/1/2021. Patients were divided into usual care group (control arm) and active group(study arm). In study group, dry weight reduction was assessed weekly by lung ultrasonography guided by the total number of B-lines, before the midweek session of haemodialysis. In the control group, dry weight probing was done according to clinical criteria. To assess outcomes, we compared the clinical and echocardiographic improvement in both groups including full clinical assessment, etc at baseline and at the study end. Results: In study group, dry weight was significantly reduced in comparison with the control group (−0.41 ± 0.32 vs. 0.04 ± 0.09 kg; P < 0.001), resulting in a statistically significant reduction in systolic and diastolic blood pressures (P < 0.001). Furthermore, a statistically significant reduction in echocardiographic indices of cardiac chambers dimensions occurred in study group, in addition to improvement of the diastolic function of both ventricles. Conclusion: Ultrafiltration based on assessment of fluid status using lung ultrasound dry weight reduction is better than that based on conventional method regarding both clinical and echocardiographic parameters.

يهدف البحث الحالي إلى بيان إسهامات تصميم الوظائف في المعالجة والحد من ظهور ضغوط العمل، وقد تضمنت مشكلة البحث الرئيسة (هل هناك دور واثر لتصميم الوظائف في معالجة ضغوط العمل التي يتعرض لها العاملين في المنظمة المبحوثة)، اختيرت مستشفى السلام التعليمي كميدان البحث، أما عينته فقد تم اختيار عينة عشوائية بواقع (40) فرد وزعت عليهم الأداة الأساسية لجمع البيانات المتمثلة باستمارة استبانة، اعتمدت الباحثتان على الحزمة البرمجية الإحصائية (SPSS, V18) وما هو متوافر منها من أساليب إحصائية تمكن الباحثتان من تحليل البيانات والتي تمثلت بالوسائل الوصفية (الوسط الحسابي والانحراف المعياري فضلا عن ارتباط بيرسون والانحدار) وتوصل البحث إلى مجموعة من النتائج بنيت في ضوئها جملة من الاستنتاجات والتي كانت من أهمها تحقق وجود تأثير وارتباط معنوي لتصميم الوظائف وضغوط العمل في الميدان المبحوث، واختتم البحث بجملة من التوصيات التي تتوافق والاستنتاجات التي توصلت إليها الباحثتان.