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Purpose: To explain the physical properties of ophthalmic viscoelastic devices (OVDs), covering their structural units, optimal features, existing viscoelastic materials, clinical applications, and potential side effects. Methods: This is a narrative review on the OVDs. A literature review was conducted in PubMed, Google Scholar, and Scopus databases. Studies that investigated physical characteristics, clinical applications, OVD commercial products, and their complications were included. Results: We included 42 articles from 2010 and discussed physical characteristics, properties of a desirable OVD, structural units of common OVDs, OVD commercial products, clinical applications, and also complications of OVDs. Conclusions: Today, viscoelastics hold a distinct and crucial role in intraocular surgery due to their remarkable properties. These materials safeguard the endothelium and epithelium, uphold anterior chamber depth, manage intraocular bleeding, ease tissue handling, and aid intraocular lens placement. Currently, the American market features 12 prevalent viscoelastic types, including 7 sodium hyaluronate derivatives (Healon, Healon-Greater Viscosity, Healon-5, Amvisc, Amvisc Plus, Advanced Medical Optics Vitrax, and Provisc), 2 hydroxypropyl methylcellulose 2% derivatives (OcuCoat and Cellugel), and 3 combinations of sodium hyaluronate and chondroitin sulfate (Viscoat, DisCoVisc, and DuoVisc). Despite the introduction of new viscoelastic materials annually, no single material encompasses all desired properties. Surgeons must select and employ suitable viscoelastics based on surgical conditions and patient requirements. Advancements in material development and understanding of physical properties and clinical applications continue to refine viscoelastic selection.

Abstract Vascular tissue engineering is a promising approach for regenerating damaged blood vessels and developing new therapeutic approaches for heart disease treatment. To date, different sources of cells have been recognized that offer assistance within the recovery of heart supply routes and veins with distinctive capacities and are compelling for heart regeneration. However, some challenges still remain that need to be overcome to establish the full potential application of these cells. In this paper, we review the different cell sources used for vascular tissue engineering, focusing on extraembryonic tissue-derived cells (ESCs), and elucidate their roles in cardiovascular disease. In addition, we highlight the intricate interplay between mechanical and biochemical factors in regulating mesenchymal stem cell (MSC) differentiation, offering insights into optimizing their application in vascular tissues.

Purpose: Whole-body bone scintigraphy (WBS) is one of the most widely used modalities in diagnosing malignant bone diseases during the early stages. However, the procedure is time-consuming and requires vigour and experience. Moreover, interpretation of WBS scans in the early stages of the disorders might be challenging because the patterns often reflect normal appearance that is prone to subjective interpretation. To simplify the gruelling, subjective, and prone-to-error task of interpreting WBS scans, we developed deep learning (DL) models to automate two major analyses, namely (i) classification of scans into normal and abnormal and (ii) discrimination between malignant and non-neoplastic bone diseases, and compared their performance with human observers. Materials and Methods: After applying our exclusion criteria on 7188 patients from three different centers, 3772 and 2248 patients were enrolled for the first and second analyses, respectively. Data were split into two parts, including training and testing, while a fraction of training data were considered for validation. Ten different CNN models were applied to single- and dual-view input (posterior and anterior views) modes to find the optimal model for each analysis. In addition, three different methods, including squeeze-and-excitation (SE), spatial pyramid pooling (SPP), and attention-augmented (AA), were used to aggregate the features for dual-view input models. Model performance was reported through area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, and specificity and was compared with the DeLong test applied to ROC curves. The test dataset was evaluated by three nuclear medicine physicians (NMPs) with different levels of experience to compare the performance of AI and human observers. Results: DenseNet121_AA (DensNet121, with dual-view input aggregated by AA) and InceptionResNetV2_SPP achieved the highest performance (AUC = 0.72) for the first and second analyses, respectively. Moreover, on average, in the first analysis, Inception V3 and InceptionResNetV2 CNN models and dual-view input with AA aggregating method had superior performance. In addition, in the second analysis, DenseNet121 and InceptionResNetV2 as CNN methods and dual-view input with AA aggregating method achieved the best results. Conversely, the performance of AI models was significantly higher than human observers for the first analysis, whereas their performance was comparable in the second analysis, although the AI model assessed the scans in a drastically lower time. Conclusion: Using the models designed in this study, a positive step can be taken toward improving and optimizing WBS interpretation. By training DL models with larger and more diverse cohorts, AI could potentially be used to assist physicians in the assessment of WBS images.

This study tests the hypothesis that corrosion properties under fatigue loading can be evaluated based on simple tensile tests without the need to perform costly and time-consuming corrosion fatigue tests. Two types of stainless steel 304L specimens, i.e., smooth and compact tension (CT), are exposed to static and fatigue loading in two aqueous solutions with different NaCl concentrations. Strain analysis, surface roughness measurements, scanning electrochemical microscopy (SECM), and Tafel polarization techniques are employed to unveil the effects of mechanical stress and strain on the corrosion behavior at micro and macro scales, a phenomenon known as electro-chemo-mechanical interaction. Finite element analysis (FEA) is performed to calculate the stress and strain field in the specimens. Digital image correlation (DIC) is used to validate the FEA results. The results indicate a strong correlation between the static stress, strain, and surface roughness with the corrosion rate. In particular, the study reveals a strong correlation between corrosion current (and corrosion current density) under fatigue loading with that under static tensile loading, thereby providing a means to evaluate the corrosion properties under fatigue loading solely from static tests. Fatigue loading leads to a progressive reduction in the corrosion potential as the number of cycles increases. The corrosion current density, icorr, is linked to the stress and accumulated plastic strain by an empirical equation, shedding lights on the complex electro-chemo-mechanical interaction. Additionally, opportunities for future research are discussed.

Abstract Emissions of ultrafine particles (UFPs; diameter 10 nm at nine stations and understand the major sources of UFPs (primary vs. secondary) in Tehran megacity. The study was carried out in Tehran in 2020. NOx and PNC were reported from a total of nine urban site locations in Tehran and BC concentrations were examined at two monitoring stations. Data from all stations showed diurnal changes with peak morning and evening rush hours. The hourly PNC was correlated with NOx. PNCs in Tehran were higher compared to those of many cities reported in the literature. The highest concentrations were at District 19 station (traffic) and the lowest was at Punak station (residential) such that the average PNC varied from 8.4 × 103 to 5.7 × 104 cm−3. In Ray and Sharif stations, the average contributions of primary and secondary sources of PNC were 67 and 33%, respectively. Overall, we conclude that a decrease in primary emission leads to a decrease in the total concentration of aerosols, despite an increase in the formation of new particles by photo nucleation.

The effect of cooking aerosol on the human heart was investigated in this study. The heart rate and blood pressure of 33 healthy adults were monitored before, exactly after, and two hours post-exposure (30 minutes, 60 minutes, 90 minutes, and 120 minutes after cooking). One hundred twenty grams of ground beef was fried in sunflower oil for twenty minutes using a gas stove without ventilation. Ultrafine particles, indoor temperature, relative humidity, carbon dioxide, oil, and meat temperatures were monitored during the experiment. The average particle emission rate (S) and average decay rate (a+k) for meat frying were found to be 2.09×1013 (SD=3.94 ×1013, R2=0.98, P

Background. Warts are a common skin disease affecting individuals of all ages worldwide. This clinical trial aims to compare the effectiveness of furosemide 0.125 Percent topical gel and KOH 10 Percent topical gel in treating patients with warts. Methods. Patients diagnosed with warts by dermatologists were included in the study and treated with either 0.125 Percent furosemide or 10 Percent KOH for two months. Patients were examined and imaged at the beginning of the study and in weeks 4 and 8 to assess the number, diameter, and height of warts and complications. Results. The study included 40 patients (48 lesions) with common warts, with 20 patients in each intervention group. In the furosemide group, the average diameter of warts decreased from 4.25 ± 1.43 mm in the first visit to 4.14 ± 1.47 mm in the final visit. In contrast, the average diameter of warts in the KOH group decreased from 3.89 ± 1.67 mm to 3.02 ± 1.49 mm. No complications were reported in the furosemide group, whereas seven complications related to redness and burning were observed in the KOH group. Conclusion. Furosemide 0.125 Percent is effective and safe for treating skin warts. However, it is less effective than KOH in reducing the diameter and height of warts. This study's findings suggest that furosemide can be a promising alternative to KOH in treating warts, especially for patients with sensitive skin or those who experience complications with KOH treatment. Further research is needed to determine the optimal treatment duration and dosage of furosemide for treating warts. Practical Implications. We can find new ways to reduce complications in treating warts.

Abstract Background This study aimed to investigate the value of clinical, radiomic features extracted from gross tumor volumes (GTVs) delineated on CT images, dose distributions (Dosiomics), and fusion of CT and dose distributions to predict outcomes in head and neck cancer (HNC) patients. Methods A cohort of 240 HNC patients from five different centers was obtained from The Cancer Imaging Archive. Seven strategies, including four non-fusion (Clinical, CT, Dose, DualCT-Dose), and three fusion algorithms (latent low-rank representation referred (LLRR),Wavelet, weighted least square (WLS)) were applied. The fusion algorithms were used to fuse the pre-treatment CT images and 3-dimensional dose maps. Overall, 215 radiomics and Dosiomics features were extracted from the GTVs, alongside with seven clinical features incorporated. Five feature selection (FS) methods in combination with six machine learning (ML) models were implemented. The performance of the models was quantified using the concordance index (CI) in one-center-leave-out 5-fold cross-validation for overall survival (OS) prediction considering the time-to-event. Results The mean CI and Kaplan-Meier curves were used for further comparisons. The CoxBoost ML model using the Minimal Depth (MD) FS method and the glmnet model using the Variable hunting (VH) FS method showed the best performance with CI = 0.73 ± 0.15 for features extracted from LLRR fused images. In addition, both glmnet-Cindex and Coxph-Cindex classifiers achieved a CI of 0.72 ± 0.14 by employing the dose images (+ incorporated clinical features) only. Conclusion Our results demonstrated that clinical features, Dosiomics and fusion of dose and CT images by specific ML-FS models could predict the overall survival of HNC patients with acceptable accuracy. Besides, the performance of ML methods among the three different strategies was almost comparable.

Abstract Infectious keratitis (IK) is a major cause of corneal opacity. IK can be caused by a variety of microorganisms. Typically, fungal ulcers carry the worst prognosis. Fungal cases can be subdivided into filamentous and yeasts, which shows fundamental differences. Delays in diagnosis or initiation of treatment increase the risk of ocular complications. Currently, the diagnosis of IK is mainly based on slit-lamp examination and corneal scrapings. Notably, these diagnostic methods have their drawbacks, including experience-dependency, tissue damage, and time consumption. Artificial intelligence (AI) is designed to mimic and enhance human decision-making. An increasing number of studies have utilized AI in the diagnosis of IK. In this paper, we propose to use AI to diagnose IK (model 1), differentiate between bacterial keratitis and fungal keratitis (model 2), and discriminate the filamentous type from the yeast type of fungal cases (model 3). Overall, 9329 slit-lamp photographs gathered from 977 patients were enrolled in the study. The models exhibited remarkable accuracy, with model 1 achieving 99.3%, model 2 at 84%, and model 3 reaching 77.5%. In conclusion, our study offers valuable support in the early identification of potential fungal and bacterial keratitis cases and helps enable timely management.

BACKGROUND: Nowadays, the issue of substance abuse is one of the major problems facing most countries in the world. The present study aimed to evaluate the effectiveness of cognitive-behavioral therapy (CBT) on mental health, life expectancy, and happiness in patients receiving methadone maintenance treatment (MMT). MATERIALS AND METHODS: The present study was performed from February 2021 to January 2022. The study was a clinical trial in which 60 people under MMT in psychology clinics in Kashan (Iran) were randomly assigned to the intervention and control groups (30 in each group) using purposeful sampling. Data were collected using the General Health Questionnaire, Schneider Hope Questionnaire, and Oxford Happiness Questionnaire in three stages: baseline, post-treatment, and follow-up. The data were analyzed using a mixed repeated-measures analysis of variance. RESULTS: The results showed that CBT is effective in improving mental health (P < 0.001), increasing life expectancy (P < 0.001), and increasing happiness (P < 0.001) in patients receiving MMT. CONCLUSION: Mental health, life expectancy, and happiness are important and influential issues in the lives of patients under MMT, which are promoted with CBT plus MMT. Therefore, in general, it can be concluded that CBT plus MMT has a significant effect on mental health, life expectancy, and happiness.

Résumé : Cette contribution s’intéresse au rôle de la variante-composante groupale dans le développement de la compétence scripturale en classe de FLE et a pour objectif d’étudier l’impact du travail collaboratif, en relation avec la composition groupale, auprès des apprenants de la deuxième année secondaire de filière scientifique, sur l’écriture et la co-écriture de textes. Dans cette optique, nous avons mis en place une démarche synergétique afin de permettre aux apprenants-scripteurs de travailler avec leurs pairs dans une sphère de partage et d’interaction pour accomplir cette tâche de co-construction des informations et par la même de co-écriture de textes. De ce fait, nous avons demandé aux participants de nous raconter un récit de voyage, en subdivisant la classe en trois sous-groupes de 12 élèves, et chaque sous-groupe se subdivise à son tour en binômes, en trinômes et en quatrinômes, en mettant la lumière sur le travail de groupe afin de tirer des enseignements de la variante groupale, qui aiderait le mieux les participants à rédiger un texte clair et structuré . Les résultats obtenus, sur le plan quantitatif et qualitatif, ont révélé que le choix de la composition groupale d’un groupe impair pourrait plus ou moins répondre aux besoins de ces apprenants-scripteurs. Mots-clés : compétence rédactionnelle, variante, collaboration, groupe, FLE.

Abstract This study aimed to investigate the diagnostic performance of machine learning-based radiomics analysis to diagnose coronary artery disease status and risk from rest/stress Myocardial Perfusion Imaging (MPI) single-photon emission computed tomography (SPECT). A total of 395 patients suspicious of coronary artery disease who underwent 2-day stress-rest protocol MPI SPECT were enrolled in this study. The left ventricle myocardium, excluding the cardiac cavity, was manually delineated on rest and stress images to define a volume of interest. Added to clinical features (age, sex, family history, diabetes status, smoking, and ejection fraction), a total of 118 radiomics features, were extracted from rest and stress MPI SPECT images to establish different feature sets, including Rest-, Stress-, Delta-, and Combined-radiomics (all together) feature sets. The data were randomly divided into 80% and 20% subsets for training and testing, respectively. The performance of classifiers built from combinations of three feature selections, and nine machine learning algorithms was evaluated for two different diagnostic tasks, including 1) normal/abnormal (no CAD vs. CAD) classification, and 2) low-risk/high-risk CAD classification. Different metrics, including the area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE), were reported for models’ evaluation. Overall, models built on the Stress feature set (compared to other feature sets), and models to diagnose the second task (compared to task 1 models) revealed better performance. The Stress-mRMR-KNN (feature set-feature selection-classifier) reached the highest performance for task 1 with AUC, ACC, SEN, and SPE equal to 0.61, 0.63, 0.64, and 0.6, respectively. The Stress-Boruta-GB model achieved the highest performance for task 2 with AUC, ACC, SEN, and SPE of 0.79, 0.76, 0.75, and 0.76, respectively. Diabetes status from the clinical feature family, and dependence count non-uniformity normalized, from the NGLDM family, which is representative of non-uniformity in the region of interest were the most frequently selected features from stress feature set for CAD risk classification. This study revealed promising results for CAD risk classification using machine learning models built on MPI SPECT radiomics. The proposed models are helpful to alleviate the labor-intensive MPI SPECT interpretation process regarding CAD status and can potentially expedite the diagnostic process.

This study presents the design and comprehensive 3D multiphysics simulation of a novel microfluidic immunosensor for non-invasive, real-time detection of pro-inflammatory biomarkers in human sweat. The patch-like device integrates magnetofluidic manipulation of antibody-functionalized magnetic nanoparticles (MNPs) with direct-field capacitive sensing (DF-CS). This unique combination enhances sensitivity, reduces parasitic capacitance, and enables a more compact design compared to traditional fringing-field approaches. A comprehensive 3D multiphysics simulation of the device, performed using COMSOL Multiphysics, demonstrates its operating principle by analyzing the sensor’s response to changes in the dielectric properties of the medium due to the presence of magnetic nanoparticles. The simulation reveals a sensitivity of 42.48% at 85% MNP occupancy within the detection zone, highlighting the sensor’s ability to detect variations in MNP concentration, and thus indirectly infer biomarker levels, with high precision. This innovative integration of magnetofluidic manipulation and DF-CS offers a promising new paradigm for continuous, non-invasive health monitoring, with potential applications in point-of-care diagnostics, personalized medicine, and preventive healthcare.

Introduction: In 2008, Iran acceded to the convention on the rights of persons with disabilities (CRPD), including the right to health and rehabilitation. However, the goals of this convention have not yet been achieved in Iran. This study provides solutions for implementing articles 25 (health) and 26 (rehabilitation) CRPD in Iran. Materials and Methods: This was a qualitative study conducted through content analysis. A total of 21 individuals were selected via the purposive sampling method. The data were collected through semi-structured interviews. The interviews continued until we reached information saturation. Data analysis was performed manually using the MAXQDA software version 10. Results: After the interviews, 860 initial codes were obtained. After removing the unrelated codes and merging the codes by overlap, 725 codes remained. The concepts were classified into four main categories and 15 subcategories: Development of a comprehensive rehabilitation program, culture and education, capacity building, and compliance with legal requirements. Conclusion: According to the results, because of severe problems in the field of health and rehabilitation of disabled people in Iran, taking necessary measures to solve these problems is essential. Hence, a comprehensive plan should be developed. Meanwhile, proper education, culture building, talents, and opportunities should be considered more carefully. Also, by facilitating services for people with disabilities and paying attention to the importance of being demanding, we can build capacity in the country. The findings of this research will provide a bright way for policymakers, administrators, and planners of the country.

Summary: The integrated stress response (ISR) is critical for cell survival under stress. In response to diverse environmental cues, eIF2α becomes phosphorylated, engendering a dramatic change in mRNA translation. The activation of ISR plays a pivotal role in the early embryogenesis, but the eIF2-dependent translational landscape in pluripotent embryonic stem cells (ESCs) is largely unexplored. We employ a multi-omics approach consisting of ribosome profiling, proteomics, and metabolomics in wild-type (eIF2α+/+) and phosphorylation-deficient mutant eIF2α (eIF2αA/A) mouse ESCs (mESCs) to investigate phosphorylated (p)-eIF2α-dependent translational control of naive pluripotency. We show a transient increase in p-eIF2α in the naive epiblast layer of E4.5 embryos. Absence of eIF2α phosphorylation engenders an exit from naive pluripotency following 2i (two chemical inhibitors of MEK1/2 and GSK3α/β) withdrawal. p-eIF2α controls translation of mRNAs encoding proteins that govern pluripotency, chromatin organization, and glutathione synthesis. Thus, p-eIF2α acts as a key regulator of the naive pluripotency gene regulatory network.

Abstract Background Primary care surveys are a key source of evaluative data; understanding how survey respondents compare to the intended population is important to understand results in context. The objective of this study was to examine the physician and patient representativeness of two primary care surveys (TRANSFORMATION and QUALICOPC) that each used different sampling and recruitment techniques. Methods We linked the physician and patient participants of the two surveys to health administrative databases. Patients were compared to other patients visiting the practice on the same day and other randomly selected dates using sociodemographic data, chronic disease diagnosis, and health system utilization. Physicians were compared to other physicians in the same practice, and other physicians in the intended geographic area using sociodemographic and practice characteristics. Results Physician respondents of the TRANSFORMATION survey included more males compared to their practice groups, but not to other physicians in the area. TRANSFORMATION physicians cared for a larger roster of patients than other physicians in the area. Patient respondents of the QUALICOPC survey did not have meaningful differences from other patients who visit the practice. Patient respondents of the TRANSFORMATION survey resided in more rural areas, had less chronic disease, and had lower use of health services than other patients visiting the practice. Conclusion Differences in survey recruitment methods at the physician and patient level may help to explain some of the differences in representativeness. When conducting primary care surveys, investigators should consider diverse methods of ensuring representativeness to limit the potential for nonresponse bias.

Abstract Background The increased scrutiny on public health brought upon by the ongoing COVID-19 pandemic provides a strong impetus for a renewal of public health systems. This paper seeks to understand priorities of public health decision-makers for reforms to public health financing, organization, interventions, and workforce. Methods We used an online 3-round real-time Delphi method of reaching consensus on priorities for public health systems reform. Participants were recruited among individuals holding senior roles in Canadian public health institutions, ministries of health and regional health authorities. In Round 1, participants were asked to rate 9 propositions related to public health financing, organization, workforce, and interventions. Participants were also asked to contribute up to three further ideas in relation to these topics in open-ended format. In Rounds 2 and 3, participants re-appraised their ratings in the view of the group’s ratings in the previous round. Results Eighty-six public health senior decision-makers from various public health organizations across Canada were invited to participate. Of these, 25/86 completed Round 1 (29% response rate), 19/25 completed Round 2 (76% retention rate) and 18/19 completed Round 3 (95% retention rate). Consensus (defined as more than 70% of importance rating) was achieved for 6 out of 9 propositions at the end of the third round. In only one case, the consensus was that the proposition was not important. Proposition rated consensually important relate to targeted public health budget, time frame for spending this budget, and the specialization of public health structures. Both interventions related and not related to the COVID-19 pandemic were judged important. Open-ended comments further highlighted priorities for renewal in public health governance and public health information management systems. Conclusion Consensus emerged rapidly among Canadian public health decision-makers on prioritizing public health budget and time frame for spending. Ensuring that public health services beyond COVID-19 and communicable disease are maintained and enhanced is also of central importance. Future research shall explore potential trade-offs between these priorities.

Photopletysmography (PPG) is a non-invasive and well known technology that enables the recording of the digital volume pulse (DVP). Although PPG is largely employed in research, several aspects remain unknown. One of these is represented by the lack of information about how many waveform classes best express the variability in shape. In the literature, it is common to classify DVPs into four classes based on the dicrotic notch position. However, when working with real data, labelling waveforms with one of these four classes is no longer straightforward and may be challenging. The correct identification of the DVP shape could enhance the precision and the reliability of the extracted bio markers. In this work we proposed unsupervised machine learning and deep learning approaches to overcome the data labelling limitations. Concretely we performed a K-medoids based clustering that takes as input 1) DVP handcrafted features, 2) similarity matrix computed with the Derivative Dynamic Time Warping and 3) DVP features extracted from a CNN AutoEncoder. All the cited methods have been tested first by imposing four medoids representative of the Dawber classes, and after by automatically searching four clusters. We then searched the optimal number of clusters for each method using silhouette score, the prediction strength and inertia. To validate the proposed approaches we analyse the dissimilarities in the clinical data related to obtained clusters.

Photoplethysmography (PPG) is a non-invasive and cost-efficient optical technique used to assess blood volume variations in the microcirculation. PPG technology is widely used in a variety of wearable sensors to investigate the cardiovascular system. Recent studies have demonstrated the utility of PPG analysis for carrying out large-scale screening to prevent and detect diabetes. However, most of these studies require feature extraction and/or several pre-processing steps. Over the past few years, the advent of deep learning has significantly impacted the analysis of biomedical signals. Despite their success in other fields, however, very few studies have focused on the application of deep learning to raw PPG signals for detecting diabetes. Existing studies have proposed large models trained on large amounts of data. In this paper, we present a Light CNN-based model for screening the presence of type 2 diabetes using a single raw pulse extracted from photoplethysmographic signals. In addition to the baseline architecture, we evaluate different model architectures that take as input age and biological sex or PPG handcrafted features. Furthermore, we apply transfer learning to all the tested architectures to evaluate the effectiveness of harnessing pre-trained models in detecting diabetes. We tested a model pre-trained on a general PPG shape dataset and another model pre-trained on a dataset containing hypertension PPG signals. Our model scored an AUC of 75.5 when trained with raw PPG waves, age, and biological sex without applying transfer learning, which is competitive with current state of the art.

Abstract Background Inappropriate lifestyle and poor self-management in diabetic patients lead to many complications including hypertension and increased disease burden. Because of insufficient studies on Effect of educational interventions on lifestyle, self-management and hypertension in diabetic patients, the present study aimed to evaluate the Effect of educational intervention based on PRECEDE model on lifestyle, self-management, and hypertension of diabetic patients. Methods This clinical trial was conducted on 300 diabetic patients with hypertension. The patients were selected using simple random sampling and divided into 2 groups of intervention (150 people) and control (150 people). The intervention group was trained through ten 50–55 min sessions on lifestyle skills, self-management, and hypertension control based on the PRECEDE model. Before and after the intervention, lifestyle skills, self-management, and PRECED model constructs were evaluated using a standard questionnaire. Data were analyzed by SPSS 20 software using t-test, Kolmogorov–Smirnov, and Chi-Square tests (P 0.05). Conclusion ‌ Based on the study's results, the PRECEDE model was found to be a non-invasive, non-pharmacological, cost-effective method without any complication and as a complementary action along with other methods in the treatment of diabetic patients.

Abstract Background Children are one of the most vulnerable social groups to infectious diseases, and prevention of urinary tract infections in children is very important; therefore, the present study aimed to investigate the effect of education based on health belief model (HBM) on promoting preventive behaviours of urinary tract infection in mothers with children under 6-years of age. Methods This quasi-experimental study was conducted on 150 women with children under 6 years of age referred to health centers in Fasa city, Iran in 2021. Subjects were selected using simple sampling method and were randomly divided into intervention (n = 75) and control (n = 75) groups. The educational intervention for the experimental group consisted of 6 virtual training sessions of 40–50 min using lecture, question and answer, group discussion and video clips. Two virtual follow-up sessions were also held one month and two months after the educational intervention. Three months after the educational intervention, both experimental and control groups completed the questionnaire. Data were analysed by using SPSS 22 through Chi-square, independent t-test, and paired t-test (p > 0.05). Results Before the intervention, based on independent t-test and paired t-test, the mean score of HBM constructs were not significantly different between the control and intervention groups (P > 0.05). However, while perceived barriers significantly decreased (P

Abstract Introduction Since hospitals play an important role in dealing with disaster victims, this study was conducted to audit the functional preparedness of the selected military hospital in response to incidents and disasters. Materials and methods This applied action research was conducted in all wards of a military hospital from September 2020 to September 2021. The functional preparedness of the hospital was assessed using a functional preparedness checklist containing 17 domains and the weaknesses of the hospital were identified. Then, during the hospital audit cycle, a plan was developed to improve work processes and the functional preparedness of different wards of the hospital in response to incidents and disasters using the FOCUS-PDCA model. The functional preparedness of the hospital was compared before and after the intervention and analyzed using SPSS22. Results The relative mean score of hospital preparedness in response to disasters was 508 out of 900 (56.44%) before the intervention, which was moderate. The relative mean score of the hospital preparedness in response to disasters was 561 (63.63%) after the intervention, which was good. The highest preparedness was related to risk assessment (85%) and the lowest preparedness was related to victims’ dead bodies (44%). Conclusion Considering the effect of action research on improving the hospital’s functional preparedness in response to disasters, other healthcare facilities are encouraged to incorporate auditing into their work plans.

Abstract VASA, also known as DDX4, is a member of the DEAD-box proteins and an RNA binding protein with an ATP-dependent RNA helicase. The VASA gene expression, which is required for human germ cell development, may lead to infertility. Immunocytochemistry and immunohistochemistry were used to examine the expression of VASA protein in the human testis sections of azoospermic patients, in-vitro and in-silico models. Some studies of fertile humans showed VASA expression in the basal and adluminal compartments of seminiferous tubules. Our Immunocytochemistry and immunohistochemistry in infertile humans showed expression of VASA in the luminal compartments of the seminiferous tubule. The immunohistochemical analysis of three human cases with different levels of non-obstructive azoospermia revealed a higher expression of VASA-positive cells. For this purpose, Enrichr and Shiny Gene Ontology databases were used for pathway enrichment analysis and gene ontology. STRING and Cytoscape online evaluation were applied to predict proteins' functional and molecular interactions and performed to recognize the master genes, respectively. According to the obtained results, the main molecular functions of the up-regulated and downregulated genes include the meiotic cell cycle, RNA binding, and differentiation. STRING and Cytoscape analyses presented seven genes, i.e., DDX5, TNP2, DDX3Y, TDRD6, SOHL2, DDX31, and SYCP3, as the hub genes involved in infertility with VASA co-function and protein–protein interaction. Our findings suggest that VASA and its interacting hub proteins could help determine the pathophysiology of germ cell abnormalities and infertility.

Rhino-orbital mucormycosis in an immunocompetent pediatric patient can present as an orbital mass. We report a 9-year-old male that presented with periorbital swelling and limitation of left eye movement from one month ago. The patient was treated at another center with a diagnosis of mucormycosis but was referred due to worsening symptoms. Orbital and paranasal sinus CT scan revealed opacities in the left paranasal sinus and soft tissue density in the medial and inferior orbital wall. The patient underwent orbitotomy and mass debulking surgery on suspicion of a possible neoplastic mass. Pathologic evaluations revealed mucormycosis. After receiving intravenous liposomal amphotericin-B that was followed by oral posaconazole syrup for two months and sinus debridement, the symptoms regressed. In immunocompromised pediatric patients, mucormycosis should be considered in the differential diagnosis of an orbital mass.

Background and Objective: Recently, significant efforts have been performed for the removal of various emerging pollutants (EPs) from water sources. Among these EPs, benzotriazole has been widely identified in aquatic environments, which has harmful health and environmental effects, so it is necessary to apply various methods to remove it. Up to date, the use of advanced oxidation processes (AOPs) as an efficient method for the degradation and mineralization of EPs pollutants from aqueous solutions has attracted so much attention. Therefore, in this research, the performance of the persulfate activation process using magnetic nanocatalyst iron oxide-activated carbon prepared from coconut shell for the removal of benzotriazole from aqueous solution, and also the effect of different parameters have been investigated. Materials and Method: This research is an experimental-laboratory study. The effect of various variables such as solution pH (2-10), catalyst dose (0.1-0.5 g/L), persulfate concentration (1-5 mM), and initial concentration of benzotriazole (10-50 mg/L) was investigated. The final concentration of benzotriazole was measured using a spectrometer. Also, the characteristics of the synthesized catalyst were investigated using numerous analyzes such as BET, FESEM, XRD, EDX and VSM, and Results: The results showed that the highest efficiency of the process for the removal of benzotriazole was attained at pH: 6, initial concentration: 10 mg/L, catalyst dosage: 0.5 g/L, persulfate concentration: 3 mM, and more than 80% of benzotriazole was removed. On the other hand, the results of catalyst characterization showed that the catalyst was perfectly synthesized and could be reused in five consecutive cycles. Conclusion: Based on the results of this research, this catalyst had a high performance for the removal of organic pollutants from aqueous solution.

Abstract Background There have been longstanding calls for public health systems transformations in many countries, including Canada. Core to these calls has been strengthening performance measurement. While advancements have been made in performance measurement for certain sectors of the health care system (primarily focused on acute and primary health care), effective use of indicators for measuring public health systems performance are lacking. This study describes the current state, anticipated challenges, and future directions in the development and implementation of a public health performance measurement system for Canada. Methods We conducted a qualitative study using semi-structured interviews with public health leaders (n = 9) between July and August 2021. Public health leaders included researchers, government staff, and former medical officers of health who were purposively selected due to their expertise and experience with performance measurement with relevance to public health systems in Canada. Thematic analysis included both a deductive approach for themes consistent with the conceptual framework and an inductive approach to allow new themes to emerge from the data. Results Conceptual, methodological, contextual, and infrastructure challenges were highlighted by participants in designing a performance measurement system for public health. Specifically, six major themes evolved that encompass 1) the mission and purpose of public health systems, including challenges inherent in measuring the functions and services of public health; 2) the macro context, including the impacts of chronic underinvestment and one-time funding injections on the ability to sustain a measurement system; 3) the organizational structure/governance of public health systems including multiple forms across Canada and underdevelopment of information technology systems; 4) accountability approaches to performance measurement and management; and 5) timing and unobservability in public health indicators. These challenges require dedicated investment, strong leadership, and political will from the federal and provincial/territorial governments. Conclusion Unprecedented attention on public health due to the coronavirus disease 2019 pandemic has highlighted opportunities for system improvements, such as addressing the lack of a performance measurement system. This study provides actionable knowledge on conceptual, methodological, contextual, and infrastructure challenges needed to design and build a pan-Canadian performance measurement system for public health.

One of the important questions regarding the mortgage is the disintegration or non-disintegration of the mortgage due to the falling of a part of the debt. Although Article 783 of the Civil Code prohibits the disintegration of mortgages, the provisions of this article seem to apply only to cases where the mortgagor, the mortgagee, the mortgage contract and the debt are units. There is no consensus in Imami jurisprudence and case law regarding the cases of mortgage disintegration. In Imami jurisprudence, the criterion of mortgage degradability is the number of mortgage contracts. However, there is a difference between them in the application of the multiplicity and non-multiplicity condition of the mortgage contract (the criterion of a single or multiple mortgage contract) and this difference in criteria leads them to disagree on the subject. Contrary to Imami jurisprudence, such a criterion was not presented in the case law. However, cases of mortgage disintegration have been identified and studied. However, jurists have not examined these cases in detail. Article 19 of 2014 Act on Elimination of Production Obstacles, on its territory (loans paid by the banking network to production units), accepted the sharing of mortgages in proportion to the payment of the debt and limited Article 783 of the Civil Code. Articles 113 and 119 of the Regulations for the Execution of the Provisions of Enforceable Official Acts also admitted the next multiplicity of mortgagors. In this research, while examining the voluntary and involuntary causes of mortgage disintegration, the advantages and disadvantages of Article 783 of the Civil Code and the shortcomings of the Civil Law in mortgage disintegration are revealed.

Objectives Personality differences between doctors and patients can affect treatment outcomes. We examine these trait disparities, as well as differences across medical specialities.Design Retrospective, observational statistical analysis of secondary data.Setting Data from two data sets that are nationally representative of doctors and the general population in Australia.Participants We include 23 358 individuals from a representative survey of the general Australian population (with subgroups of 18 705 patients, 1261 highly educated individuals and 5814 working in caring professions) as well as 19 351 doctors from a representative survey of doctors in Australia (with subgroups of 5844 general practitioners, 1776 person-oriented specialists and 3245 technique-oriented specialists).Main outcome measures Big Five personality traits and locus of control. Measures are standardised by gender, age and being born overseas and weighted to be representative of their population.Results Doctors are significantly more agreeable (a: standardised score −0.12, 95% CIs −0.18 to −0.06), conscientious (c: −0.27 to –0.33 to −0.20), extroverted (e: 0.11, 0.04 to 0.17) and neurotic (n: 0.14, CI 0.08 to 0.20) than the general population (a: −0.38 to –0.42 to −0.34, c: −0.96 to –1.00 to −0.91, e: −0.22 to –0.26 to −0.19, n: −1.01 to –1.03 to −0.98) or patients (a: −0.77 to –0.85 to −0.69, c: −1.27 to –1.36 to −1.19, e: −0.24 to –0.31 to −0.18, n: −0.71 to –0.76 to −0.66). Patients (−0.03 to –0.10 to 0.05) are more open than doctors (−0.30 to –0.36 to −0.23). Doctors have a significantly more external locus of control (0.06, 0.00 to 0.13) than the general population (−0.10 to –0.13 to −0.06) but do not differ from patients (−0.04 to –0.11 to 0.03). There are minor differences in personality traits among doctors with different specialities.Conclusions Several personality traits differ between doctors, the population and patients. Awareness about differences can improve doctor–patient communication and allow patients to understand and comply with treatment recommendations.

Background and Objectives: Adhesion of microorganisms on facemask surfaces is a major problem that produces contamination of the mask wearer either by inhalation or by direct contact. Generally, physicochemical properties of the material and the microorganism are responsible for this adhesion and are also reported to influence the filtration efficiency of facemasks. However, theses surface proprieties and their effect on particles attachment on facemask materials remain poorly documented. The purpose of this study was to investigate the physicochemical properties of seven facemasks and evaluate the influence of these characteristics on the adhesion of Sataphylococcus aureus. Materials and Methods: Physicochemical properties is done by contact angle method and scanning electron microscopy while theoretical adhesion of S. aureus is done according to XDLVO approach. Results: The obtained results showed that all masks have a hydrophobic character. The electron donor and electron acceptor parameters change depending on each mask. Chemical analysis demonstrates the presence of two chemical elements (carbon and oxygen). Predictive adhesion demonstrate that S. aureus has an attractive behavior towards the masks used but the potential of adhesion is not the same. Conclusion: Such information is valuable to understand attachment of biological particles and to contribute in the inhibition of this attachment.

In this paper, random vectors following the multivariate generalized hyperbolic (GH) distribution are compared using the hessian stochastic order. This family includes the classes of symmetric and asymmetric distributions by which different behaviors of kurtosis in skewed and heavy tail data can be captured. By considering some closed convex cones and their duals, we derive some necessary and sufficient conditions for some important applied stochastic orderings. The linear convex orderings are shown to be equivalent with a certain kind of hessian orderings. Based on copulas generated by the GH distributions, it is revealed that the ordering of the GH distributions in terms of their dependence structures corresponds to some hessian stochastic orderings being satisfied. The results are shown to be relevant to some insurance and economic applications.

Bearing capacity plays a significant role in evaluating the safety of the foundations rest on the slope. Many solutions have been proposed to assess the ultimate bearing capacity of foundation adjacent to the slope, however, the available analytical and empirical methods are associated with some shortcomings in view of slope material properties and geometry. Also, numerical methods suffer from the rigorous computational effort, and the accuracy of the outcome depends on the mesh and boundary effect. Therefore, a new analysis is employed in this research work that is able to consider all the effective parameters on the evaluation of ultimate bearing capacity. The results are compared with the existing numerical one in the literature and show good agreements. Also, in order to facilitate the use of the proposed method a Mathematica package code has been proposed to help the researcher to evaluate the bearing capacity of a shallow foundation rests on the slope.

Abstract Background In the medical management of acute myocardial infarction, the transport of patients and primary care provided by emergency medical technicians (EMTs) and paramedics are effective in reducing the mortality and disabilities. Therefore, the present study aimed to compare the outcomes of emergency medical services (EMS) vs. non-EMS transport of patients with ST-segment elevation myocardial infarction (STEMI) in southern Iran. Methods This is an analytical, cross-sectional study. The study population consisted of the individuals registered in Fasa Registry on Acute Myocardial Infarction (FaRMI) in the south of Iran. 2244 patients with STEMI were included in the study. Statistical analyses were performed using Chi-Square test and independent t-test at a significance level of P

Although ubiquitin ligases are known to control clock protein degradation, their other roles in clock neurons are unclear. Here the authors report that UBR4 promotes export of neuropeptides from the Golgi for axonal trafficking, which is important for circadian clock synchrony in mice and flies.

Injury, hospitalization, and even death are common consequences of falling for elderly people. Therefore, early and robust identification of people at risk of recurrent falling is crucial from a preventive point of view. This study aims to evaluate the effectiveness of an interpretable semi-supervised approach in identifying individuals at risk of falls by using the data provided by ankle-mounted IMU sensors. Our method benefits from the cause–effect link between a fall event and balance ability to pinpoint the moments with the highest fall probability. This framework also has the advantage of training on unlabeled data, and one can exploit its interpretation capacities to detect the target while only using patient metadata, especially those in relation to balance characteristics. This study shows that a visual-based self-attention model is able to infer the relationship between a fall event and loss of balance by attributing high values of weight to moments where the vertical acceleration component of the IMU sensors exceeds 5 m/s² during an especially short period. This semi-supervised approach uses interpretable features to highlight the moments of the recording that may explain the score of balance, thus revealing the moments with the highest risk of falling. Our model allows for the detection of 71% of the possible falling risk events in a window of 1 s (500 ms before and after the target) when compared with threshold-based approaches. This type of framework plays a paramount role in reducing the costs of annotation in the case of fall prevention when using wearable devices. Overall, this adaptive tool can provide valuable data to healthcare professionals, and it can assist them in enhancing fall prevention efforts on a larger scale with lower costs.

Electrokinetic remediation is a cost-effective and efficient method that utilizes electrical current to transport ions within the subsurface. This process aims to remediate soil contamination caused by industrial activities, which poses threats to wildlife, water quality, and air quality. To assess the impact of the electrokinetic process on tank leaching efficiency, two electrode configurations were tested: vertical and horizontal arrays. These tests considered variable electrode spacing and different voltages in the soil residue. Additionally, the movement of copper cations from the anode to the cathode under this process was investigated. Results show that the horizontal electrode array is more effective in transporting soil moisture because of its broader contact with the soil. After 20 days of using the electrokinetic method with vertical electrodes, the soil moisture content decreased by 12.28%; with horizontal electrodes, it dropped by 38.4%. Also, the concentration of copper in the soil near the cathode electrode increased from 0.54 to 0.77% after 20 days. The estimated copper ion content in the cathode area after 20 days was between 150 and 350 mol/m3, aligning closely with the measured value of 192.5 mol/m3. These results indicate that the electrokinetic process can significantly enhance copper recovery efficiency in tank leaching processes and curtail environmental side effects. Overall, this study provides valuable insights into the benefits of using the electrokinetic process to remediate leaching residue and improve the efficiency of industrial processes.

Within the realms of human thoughts on nature, Fourier analysis is considered as one of the greatest ideas currently put forwarded. The Fourier transform shows that any periodic function can be rewritten as the sum of sinusoidal functions. Having a Fourier transform view on real-world problems like the DNA sequence of genes, would make things intuitively simple to understand in comparison with their initial formal domain view. In this study we used discrete Fourier transform (DFT) on DNA sequences of a set of genes in the bovine genome known to govern milk production, in order to develop a new gene clustering algorithm. The implementation of this algorithm is very user-friendly and requires only simple routine mathematical operations. By transforming the configuration of gene sequences into frequency domain, we sought to elucidate important features and reveal hidden gene properties. This is biologically appealing since no information is lost via this transformation and we are therefore not reducing the number of degrees of freedom. The results from different clustering methods were integrated using evidence accumulation algorithms to provide in insilico validation of our results. We propose using candidate gene sequences accompanied by other genes of biologically unknown function. These will then be assigned some degree of relevant annotation by using our proposed algorithm. Current knowledge in biological gene clustering investigation is also lacking, and so DFT-based methods will help shine a light on use of these algorithms for biological insight.

Nitric acid (NA) is corrosive. On contact with the skin, liquid splashes with nitric acid and may produce severe burns. These burns usually take on a characteristic yellowish hue. We report the case of a 54-year-old man presenting a nitric acid burn with a pathognomonic skin lesion and perfect healing. NA is a chemical that is important in industry, and it is a very strong acid that is used for engraving, metal refining, electroplating, and fertilizer manufacturing. Skin contact with NA leads to severe burns. The pathophysiology depends on the type of concentration, the strength, quality, and duration of contact, and the penetration power of the acids concerned. The early and abundant irrigation with water or sterile isotonic saline solution, the use of panthenol-containing creams and covering with silver sulphadiazine dressing, carefully monitoring wounds, keeping wounds clean and moist, and preventing and managing secondary infection allow the healing.

IntroductionThis study was intended to investigate the clinical features and predisposing factors of fungal keratitis (FK), as well as molecular identification and antifungal susceptibility of causative agents in Tehran, Iran.MethodsThis cross-sectional study was carried out from April 2019 to May 2021. All fungi isolates were identified using conventional methods and were confirmed by DNA-PCR-based molecular assays. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) was used to identify yeast species. Minimum inhibitory concentrations (MIC) of eight antifungal agents were assessed according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) microbroth dilution reference method. ResultsFungal etiology was confirmed in 86 (7.23%) of 1189 corneal ulcers. A significant predisposing factor for FK was ocular trauma caused by plant materials. Therapeutic penetrating keratoplasty (PKP) was required in 60.4% of cases. The predominant fungal species isolated was Fusarium spp. (39.5%) followed by Aspergillus spp. (32.5%) and Candida spp. (16.2%).DiscussionThe MIC results indicate that amphotericin B may be appropriate for treating FK caused by Fusarium species. FK caused by Candida spp. can be treated with flucytosine, voriconazole, posaconazole, miconazole, and caspofungin. In developing countries such as Iran, corneal infection due to filamentous fungi is a common cause of corneal damage. In this region, fungal keratitis is observed primarily within the context of agricultural activity and subsequent ocular trauma. Fungal keratitis can be managed better with understanding the ”local“ etiologies and antifungal susceptibility patterns.

Background: The nano-particle of zinc oxide (nZn) and selenium (nSe) has recently attracted in animal feeding because of their high absorbability, catalytic efficiency, and low toxicity than organic and non-organic forms. The present study was done to evaluate the effect of nZn and nSe supplementation in the honey bee's diet under heat stress on antioxidant status, aminotransferase activity, and the relative gene expression of vg and sod-1. Materials and methods: Fifty honey bee colonies were randomly divided into five treatments and 10 replicates. Treatments were sugar syrup without or with nanoparticle supplementation, as: i) the control group (no additives); ii) 100 µgL−1 nano-zinc oxide (nZn-1); iii) 200 µg L − 1 of nano-zinc oxide (nZn-2); iv) 100 µg L − 1 nano-selenium (nSe-1); v) 200 µg L − 1 nano-selenium (nSe-2). On days 30 and 60 of experiment, the bee's samples were taken and antioxidant status, aminotransferase activities and relative genes expression of vg and sod-1 were measured. Results: The highest (P

Machine learning methods have been used in genetic studies to build models capable of predicting missing genotypes for both human and animal genetic variations. Genotype imputation is an important process of predicting unknown genotypes. The objective of this study was to investigate the idea of using machine learning as imputation to compare the family-based methods and tried to offer improving the imputation performance in different scenarios. Also, the accuracies of different methods i.e. Support vector Machine; SVM, Random forest; RF are compared. The final population were simulated in the form of different family structures. Therefore, 100 families including one sire with different number of genotyped progenies (2, 3, 4, 5 or 7) were simulated. The number of markers was set to 5000 for whole genome. The sires in families and other scenarios such as, BothParents, sire/dam and one progeny, sire and maternal grandsire were defined to investigate the ability of learning machine algorithm for imputation. The imputation accuracy ranged from 0.78 to 0.99 in different scenarios. Also, least amount of imputation accuracy were achieved for sire and maternal grand sire scenario with both methods. Increasing in number of progenies from 2 to 3 was considerably increased in imputation accuracy (SVM and RF). The imputation of non-genotyped individuals based on parent-offspring trios and close relatives paired is possible. But, the use of child- one parent genotyped, BothParents genotyped and sire and maternal grandsire genotyped, average imputation accuracy would not exceed 85%. While genotyped progenies are the best source of predicted genotypes for ungenotyped individuals and if the number of progeny is more than 4, the imputation accuracy is increased more than 95%. These results confirmed, that the performance of machine learning methods in family of trios has a good accuracy and computational speed, which can be used in estimated breeding value.

The aim of the present study was to examine the effect of quercetin on the survival and primary culture of ovine spermatogonial stem cells (SSCs). The two-time enzymatic digestion process was employed to obtain SSCs from lamb testes. In the next step, the use of filtration and differential plating methods caused an increase in the number of SSCs in the cell suspension resulting from enzymatic and mechanical digestions. Mitomycin-C-treated Sertoli cells were used to prepare the feeder layer. The stem cells were then cultured on the Sertoli cell feeder layer. The identification of the colonies was done through alkaline phosphatase staining methods and specific gene expression of ram's SSCs (nanog and Plzf). The results of methylthiazolyldiphenyl-tetrazolium bromide assay on SSCs 72 h after culture with different treatments of quercetin demonstrated that the highest percentage of survival was for 5 μM and 10 μM concentrations, respectively; however, compared to the control, no significant difference was observed. In comparison with the control, the concentration equal to and greater than 20 μM quercetin caused a significant decrease in the survival of SSCs (P < 0.05). Seven days after culture, 40 μM quercetin caused a substantial reduction in the mean number of colonies, compared to the control (P < 0.05). The results demonstrated that compared to the control, 5 μM to 40 μM of quercetin significantly reduced Plzf gene expression. Furthermore, the concentration equal to and higher than 10 μM quercetin significantly decreased bcl-2 gene expression in the cells under study (P < 0.05). Based on the findings of the present study, the use of quercetin for the primary culture of ovine SSCs is not recommended. It is suggested that the function of this antioxidant should be investigated on the differentiation of SSCs.

Background: Graft-versus-host disease (GVHD) is a life-threatening complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Identifiying the probable risk factors can help the clinicians manage the consequences of GVHD. The main aim of this study was to analyze the correlation of body mass index (BMI) as a risk factor with the GVHD incidence.Methods: This retrospective study was conducted on 199 patients who received allo-HSCT during 2007-2017, as well as their donors. Almost all included patients received 10/10 human leukocyte antigen )HLA(-matched allogeneic stem cell transplants. The clinical data, including BMI, underlying disease and GVHD incidence, were collected from the clinical records.Results: In the present study, GVHD was seen in 77 (38.6%) patients, including 59 acute and 18 chronic GVHD. The most frequent BMI range in both donors (35.5%) and recipients (45.2%) was between 18.5- 24.9 kg/m2. The transplants in which the BMI of donors were below 18.5 kg/m2 had 58% lower odds of GVHD incidence, compared to those with obese donors (CI: [0.21-0.85]; P = 0.05). Conversely, the donors with a BMI between 18.5 and 24.9 kg/m2 led to a 19% higher odds of GVHD incidence, especially acute GVHD, than transplants from donors with BMI above 30 kg/m2 (CI: [0.68-2.09]; P = 0.09). The recipients with a BMI between 18.5 and 24.9 kg/m2 had the odds of GVHD incidence 63% more than those with a BMI above 30 kg/m2 (CI: [0.89-3.06]; P= 0.3).Conclusions: The findings of the present study suggest the donor's BMI as a probable GVHD risk factor so that the BMI lower than 18.5 kg/m2 was statistically correlated with a decreased incidence of GVHD.

Background: Prostate cancer (PC) is the fourth most common and the second deadly cancer in the world. Various theories have been proposed to identify the characteristics of individuals and their surrounding environments that somehow affect their behaviors. The health belief model (HBM) is one of the theories that are useful for studying health problems and designing programs to prevent diseases and injuries. Objectives: The purpose of this study was to determine PC screening behaviors based on HBM in men aged 40-70 years old in Fasa city, Fars province, Iran. Methods: This was a descriptive, analytical, and cross-sectional study performed on 400 men aged 40-70 years in 2019. The data collection instrument was a standard questionnaire used in Anderson’s study, whose validity and reliability have been confirmed. Data were analyzed by SPSS 22 using descriptive (frequency, mean, and standard deviation) and inferential (the Pearson correlation coefficient and linear regression) statistics at the significance level of p