Volumetric analysis of the hypothalamic subunits in obstructive sleep apnea.

BACKGROUND: Obstructive sleep apnea (OSA) is a prevalent sleep disorder that is associated with structural brain damage and cognitive impairment. The hypothalamus plays a crucial role in regulating sleep and wakefulness. We aimed to evaluate hypothalamic subunit volumes in patients with OSA. METHODS: We enrolled 30 participants (15 patients with OSA and 15 healthy controls (HC)). Patients with OSA underwent complete overnight polysomnography (PSG) examination. All the participants underwent MRI. The hypothalamic subunit volumes were calculated using a segmentation technique that trained a 3D convolutional neural network. RESULTS: Although hypothalamus subunit volumes were comparable between the HC and OSA groups (lowest p = .395), significant negative correlations were found in OSA patients between BMI and whole left hypothalamus volume (R = -0.654, p = .008), as well as between BMI and left posterior volume (R = -0.556, p = .032). Furthermore, significant positive correlations were found between ESS and right anterior inferior volume (R = 0.548, p = .042), minimum SpO2 and the whole left hypothalamus (R = 0.551, p = .033), left tubular inferior volumes (R = 0.596, p = .019), and between the percentage of REM stage and left anterior inferior volume (R = 0.584, p = .022). CONCLUSIONS: While there were no notable differences in the hypothalamic subunit volumes between the OSA and HC groups, several important correlations were identified in the OSA group. These relationships suggest that factors related to sleep apnea severity could affect hypothalamic structure in patients.

Diffusion tensor imaging biomarkers and clinical assessments in amyotrophic lateral sclerosis (ALS) patients: an exploratory study.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive loss of upper and lower motor neurons. Biomarkers are needed to improve diagnosis, gauge progression, and evaluate treatment. Diffusion tensor imaging (DTI) is a promising biomarker for detecting microstructural alterations in the white matter tracts. This study aimed to assess DTI metrics as biomarkers and to examine their relationship with clinical assessments in patients with ALS. Eleven patients with ALS and 21 healthy controls (HCs) underwent 3T MRI with DTI. DTI metrics, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), were compared between key motor and extra-motor tract groups. Group comparisons and correlations between DTI metrics also correlated with clinical scores of disability (ALSFRS-R), muscle strength (dynamometry), and motor unit loss (MUNIX). Widespread differences were found between patients with ALS and HCs in DTI metrics, including decreased FA and increased diffusivity metrics. However, MD and RD are more sensitive metrics for detecting white matter changes in patients with ALS. Significant interhemispheric correlations between the tract DTI metrics were also observed. DTI metrics showed symmetry between the hemispheres and correlated with the clinical assessments. MD, RD, and AD increases significantly correlated with lower ALSFRS-R and MUNIX scores and weaker dynamometry results. DTI reveals microstructural damage along the motor and extra-motor regions in ALS patients. DTI metrics can serve as quantitative neuroimaging biomarkers for diagnosis, prognosis, monitoring of progression, and treatment. Combined analysis of imaging, electrodiagnostic, and functional biomarkers shows potential for characterizing disease pathophysiology and progression.

Determination of dialkyl phthalate esters in indoor air of PVC industry: Risk assessment for human health using Monte-Carlo simulations.

Dialkyl phthalate esters are incorporated to enhance the pliability and prevent brittleness in polyvinyl chloride (PVC) tubing. Exposure to these compounds occurs throughout human lifetimes via ingestion, inhalation, and direct skin contact. A study was conducted to evaluate concentrations of four specific phthalates-dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DBP), and di(2-ethylhexyl) phthalate (DEHP)-in the indoor air of both industrial and administrative sectors within the PVC manufacturing facilities. Air sampling was conducted in the spring season at two polyethylene factories in Zahedan Industrial Park (Sistan and Baluchestan Province, Iran). The outcomes demonstrated that mean concentrations of these substances in industrial along with administrative departments 485.7 µg/m3 and 49.83 µg/m3for DMP, 807.38 µg/m3 and 30.17 µg/m3 for DEP, 849.62 µg/m3 and 37.50 µg/m3 for DBP along with 1268.08 µg/m3 and 45.50 µg/m3 for DEHP respectively. The probabilistic lifetime cancer risk (LTCR) of DEHP in the indoor air of Zahedan PVC factories for men and women was determined using the Monte Carlo simulation technique. The computed mean LTCRs of DEHP for men and women in the indoor air of industrial and administrative departments in Zahedan PVC were 1.3 × 10-3, 1.2 × 10-3and 4.7 × 10-5,4.2 × 10-5respectively. Data showed that DEHP was a potential risk to human health.

Knowledge, attitudes, and practices of healthcare professionals regarding dengue fever in high-risk regions of southeastern Iran.

BACKGROUND: Dengue fever (DF) is one of the most prevalent arboviral infections worldwide. In Iran, the dengue-positive serological cases as well as the presence of the dengue vector Aedes aegypti have raised health concerns, highlighting the need to enhance the dengue surveillance system. This study aims to assess the knowledge, attitudes, and practices (KAP) of healthcare professionals (HCPs) regarding dengue fever in a large and high-risk region of southeastern Iran. METHODS: A total of 492 HCPs were recruited using a multi-stage sampling method from May 2022 to July 2023. Data were collected using a self-administered questionnaire. Data analysis was done using independent t-tests, one-way analysis of variance (ANOVA), one-factor and multi-factor general linear models, and simple and multiple regression models. RESULTS: About two-thirds (71%) of the participants did not receive any training on DF. A small percentage of participants were familiar with ovitrap (32.6%) and only 21.7% knew that destroying larval breeding sites could not eliminate the dengue vector. The knowledge of disease symptoms among HCPs was found to be lower in border areas compared to non-border areas (P = 0.018). However, the practice situation in HCPs working in border areas was better than in non-borders (P = 0.003). According to the multiple regression model, the most influential factors associated with knowledge, attitude, and practice were the type of healthcare facility and passing the DF training course. Additionally, education level, work experience, and gender were identified as other factors associated with it, respectively. Significant correlations were found between knowledge and practice (P < 0.001), indicating that higher knowledge led to better practice. Similarly, a positive attitude was significantly linked to better practice (P < 0.001). CONCLUSION: Regular, targeted, and continuous training courses are necessary to improve the knowledge level of HCPs, particularly those with lower education levels working in low-level health centers. Utilizing comprehensive dengue KAP studies to evaluate the status and impact of health education programs and identify gaps between knowledge and practice should be a research priority.

Breast percent density changes in digital mammography pre- and post-radiotherapy.

INTRODUCTION: Breast cancer (BC), the most frequently diagnosed malignancy among women worldwide, presents a public health challenge and affects mortality rates. Breast-conserving therapy (BCT) is a common treatment, but the risk from residual disease necessitates radiotherapy. Digital mammography monitors treatment response by identifying post-operative and radiotherapy tissue alterations, but accurate assessment of mammographic density remains a challenge. This study used OpenBreast to measure percent density (PD), offering insights into changes in mammographic density before and after BCT with radiation therapy. METHODS: This retrospective analysis included 92 female patients with BC who underwent BCT, chemotherapy, and radiotherapy, excluding those who received hormonal therapy or bilateral BCT. Percent/percentage density measurements were extracted using OpenBreast, an automated software that applies computational techniques to density analyses. Data were analysed at baseline, 3 months, and 15 months post-treatment using standardised mean difference (SMD) with Cohen's d, chi-square, and paired sample t-tests. The predictive power of PD changes for BC was measured based on the receiver operating characteristic (ROC) curve analysis. RESULTS: The mean age was 53.2 years. There were no significant differences in PD between the periods. Standardised mean difference analysis revealed no significant changes in the SMD for PD before treatment compared with 3- and 15-months post-treatment. Although PD increased numerically after radiotherapy, ROC analysis revealed optimal sensitivity at 15 months post-treatment for detecting changes in breast density. CONCLUSIONS: This study utilised an automated breast density segmentation tool to assess the changes in mammographic density before and after BC treatment. No significant differences in the density were observed during the short-term follow-up period. However, the results suggest that quantitative density assessment could be valuable for long-term monitoring of treatment effects. The study underscores the necessity for larger and longitudinal studies to accurately measure and validate the effectiveness of quantitative methods in clinical BC management.

Thalamic Alterations in Motor Neuron Diseases: A Systematic Review of MRI Findings.

BACKGROUND: Motor neuron diseases (MNDs) are progressive neurodegenerative disorders characterized by motor impairment and non-motor symptoms. The involvement of the thalamus in MNDs, especially in conditions such as amyotrophic lateral sclerosis (ALS), and its interaction with frontotemporal dementia (FTD), has garnered increasing research interest. This systematic review analyzed magnetic resonance imaging (MRI) studies that focused on thalamic alterations in MNDs to understand the significance of these changes and their correlation with clinical outcomes. METHODS: Following PRISMA 2020 guidelines, the PubMed and Scopus databases were searched from inception to June 2023 for studies related to MRI findings in the thalamus of patients with MNDs. Eligible studies included adult patients diagnosed with ALS or other forms of MND who underwent brain MRI, with outcomes related to thalamic alterations. Studies were evaluated for risk of bias using the Newcastle-Ottawa scale. RESULTS: A total of 52 studies (including 3009 MND patients and 2181 healthy controls) used various MRI techniques, including volumetric analysis, diffusion tensor imaging, and functional MRI, to measure thalamic volume, connectivity, and other alterations. This review confirmed significant thalamic changes in MNDs, such as atrophy and microstructural degradation, which are associated with disease severity, progression, and functional disability. Thalamic involvement varies across different MND subtypes and is influenced by the presence of cognitive impairment and mutations in genes including chromosome 9 open reading frame 72 (C9orf72). The synthesis of findings across studies indicates that thalamic pathology is a prevalent early biomarker of MNDs that contributes to motor and cognitive deficits. The thalamus is a promising target for monitoring as its dysfunction underpins a variety of clinical symptoms in MNDs. CONCLUSIONS: Thalamic alterations provide valuable insights into the pathophysiology and progression of MNDs. Multimodal MRI techniques are potent tools for detecting dynamic thalamic changes, indicating structural integrity, connectivity disruption, and metabolic activity.

Different types of mobile phone use while driving and influencing factors on intention and behavior: Insights from an expanded theory of planned behavior.

Mobile phone use while driving (MPUWD) is a significant concern due to its negative impact on road safety. This cross-sectional study aimed to assess different types of MPUWD and identify factors influencing intention and behavior among drivers in Zahedan. A total of 392 participants provided information on demographic and driving characteristics, as well as constructs derived from the Theory of Planned Behavior (TPB) augmented with moral norms. Findings revealed that a majority of drivers (86.4%) engaged in MPUWD, primarily involving calling, using applications, and texting. However, most participants did not intend to use their phones while driving in the following week. Multiple regression analysis identified age, receiving driving fines, subjective norm, and perceived behavior control as significant predictors of intention for MPUWD. Additionally, factors such as age, receiving driving fines, driving hours, car gearbox type, attitude, perceived behavior control, behavioral intention, and moral norm were significant predictors of actual MPUWD. Older participants demonstrated better behavior in various mobile phone activities while driving. Overall, the study emphasized that the main TPB constructs and moral norms have a greater influence compared to other variables in predicting MPUWD. Perceived behavioral control was the most important predictor of the intention and behavior of MPUWD. Understanding these factors can guide efforts to discourage MPUWD through targeted interventions and strategies to promote safer driving practices.

Marker-controlled watershed algorithm and fuzzy C-means clustering machine learning: automated segmentation of glioblastoma from MRI images in a case series.

Introduction and importance: Automated segmentation of glioblastoma multiforme (GBM) from MRI images is crucial for accurate diagnosis and treatment planning. This paper presents a new and innovative approach for automating the segmentation of GBM from MRI images using the marker-controlled watershed segmentation (MCWS) algorithm. Case presentation and methods: The technique involves several image processing techniques, including adaptive thresholding, morphological filtering, gradient magnitude calculation, and regional maxima identification. The MCWS algorithm efficiently segments images based on local intensity structures using the watershed transform, and fuzzy c-means (FCM) clustering improves segmentation accuracy. The presented approach achieved improved segmentation accuracy in detecting and segmenting GBM tumours from axial T2-weighted (T2-w) MRI images, as demonstrated by the mean characteristics performance metrics for GBM segmentation (sensitivity: 0.9905, specificity: 0.9483, accuracy: 0.9508, precision: 0.5481, F_measure: 0.7052, and jaccard: 0.9340). Clinical discussion: The results of this study underline the importance of reliable and accurate image segmentation for effective diagnosis and treatment planning of GBM tumours. Conclusion: The MCWS technique provides an effective and efficient approach for the segmentation of challenging medical images.

Machine Learning Approaches to Identify Affected Brain Regions in Movement Disorders Using MRI Data: A Systematic Review and Diagnostic Meta-analysis.

BACKGROUND: Movement disorders such as Parkinson's disease are associated with structural and functional changes in specific brain regions. Advanced magnetic resonance imaging (MRI) techniques combined with machine learning (ML) are promising tools for identifying imaging biomarkers and patterns associated with these disorders. PURPOSE/HYPOTHESIS: We aimed to systematically identify the brain regions most commonly affected in movement disorders using ML approaches applied to structural and functional MRI data. We searched the PubMed and Scopus databases using relevant keywords up to June 2023 for studies that used ML approaches to detect brain regions associated with movement disorders using MRI data. STUDY TYPE: A systematic review and diagnostic meta-analysis. POPULATION/SUBJECTS: Sixty-seven studies with 6,285 patients were included. FIELD STRENGTH/SEQUENCE: Studies utilizing 1.5T or 3T MR scanners and the acquisition of diffusion tensor imaging (DTI), structural MRI (sMRI), functional MRI (fMRI), or a combination of these were included. ASSESSMENT: The authors independently assessed the study quality using the CLAIM and QUADAS-2 criteria and extracted data on diagnostic accuracy measures. STATISTICAL TESTS: Sensitivity, specificity, accuracy, and area under the curve were pooled using random-effects models. Q statistics and the I2 index were used to evaluate heterogeneity, and Begg's funnel plot was used to identify publication bias. RESULTS: sMRI showed the highest sensitivity (93%) and mixed modalities had the highest specificity (90%) for detecting regional abnormalities. sMRI had a 94% sensitivity for identifying subcortical changes. The support vector machine (93%) and logistic regression (91%) models exhibited high diagnostic accuracies. DATA CONCLUSION: The combination of advanced MR neuroimaging techniques and ML is a promising approach for identifying brain biomarkers and affected regions in movement disorders with subcortical structures frequently implicated. Structural MRI, in particular, showed strong performance. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Efficacy of a facial-aging web app on sun protection behaviors among primary school students in Iran: a randomized controlled trial.

BACKGROUND: Skin cancers resulting from excessive exposure to solar ultraviolet (UV) radiation are on the rise. This study aims to investigate the impact of facial-aging app intervention on promoting safe and healthy behaviors and its influence on reducing students' UV exposure. METHOD: Utilizing a Pretest-Posttest repeated-measures design, we developed a theory-guided web app on the WhatsApp platform, named the Sunshine and Skin Health app. This app allows users to visualize their altered faces in three stages of adolescence, middle age, and old age based on sun protection behavior. The intervention continued within WhatsApp, incorporating 27 health messages grounded in the PMT theory, eight educational files, and a skin cancer video clip. The primary outcome is the change in sun protection behavior between the two groups (intervention and control) immediately after the intervention (T2) and the secondary outcome is the change in sun protection behavior between the two groups at 3 months follow-up (T3). The data are analyzed in SPSS 22 and a significance level of 0.05 is considered. RESULTS: The results revealed no significant difference between the two groups before the intervention. However, in the intervention group, there were significant differences in the utilization of sunglasses, hats, and sunscreen in the last month, as well as sunscreen reapplication after washing their hands and face, both immediately after the intervention and at the 3-month follow-up, compared to the control group (P = 0.001). Furthermore, a significant intervention effect, time effect, and interaction effect between group and time were observed in behaviors related to using sunscreen in the last month and sunscreen reapplication after washing hands and face (P = 0.001). Specifically, the intervention group exhibited a significant difference from Time 1 to 2 and from Time 1 to 3 (p = 0.001), but no significant difference from Time 2 to 3. In contrast, the control group did not show any significant differences over time. CONCLUSIONS: This study indicated that the Facial-Aging web app can effectively encourage safe behaviors in sunlight. To ensure the maintenance and sustainability of these behaviors over the long term, it is crucial to consider implementing booster sessions. TRIAL REGISTRATION: Iranian Registry of Clinical Trials IRCT20200924048825N1. Registered prospectively on 8 February 2021.

Purification, Molecular Docking and Cytotoxicity Evaluation of Bioactive Pentacyclic Polyhydroxylated Triterpenoids from Salvia urmiensis.

Triterpenoids, as one of the largest classes of naturally occurring secondary metabolites in higher plants, are of interest due to their high structural diversity and wide range of biological activities. In addition to several promising pharmacological activities such as antimicrobial, antiviral, antioxidant, anti-inflammatory and hepatoprotective effects, a large number of triterpenoids have revealed high potential for cancer therapy through their strong cytotoxicity on cancer cell lines and, also, low toxicity in normal cells. So, this study was aimed at discovering novel and potentially bioactive triterpenoids from the Salvia urmiensis species. For this, an ethyl acetate fraction of the acetone extract of the aerial parts of the plant was chromatographed to yield five novel polyhydroxylated triterpenoids (1: -5: ). Their structure was elucidated by extensive spectroscopic methods including 1D (1H, 13C, DEPT-Q) and 2D NMR (COSY, HSQC, HMBC, NOESY) experiments, as well as HRESIMS analysis. Cytotoxic activity of the purified compounds was also investigated by MTT assay against the MCF-7 cancer cell line. Furthermore, a molecular docking analysis was applied to evaluate the inhibition potential of the ligands against the nuclear factor kappa B (NF-κB) protein, which promotes tumor metastasis or affects gene expression in cancer disease. The 1ß,11ß,22α-trihydroxy-olean-12-ene-3-one (compound 4: ) indicated the best activity in both in vitro and in silico assays, with an IC50 value of 32 µM and a docking score value of - 3.976 kcal/mol, respectively.

A systematic review of brain metastases from lung cancer using magnetic resonance neuroimaging: Clinical and technical aspects.

INTRODUCTION: Brain metastases (BMs) are common in lung cancer (LC) and are associated with poor prognosis. Magnetic resonance imaging (MRI) plays a vital role in the detection, diagnosis and management of BMs. This review summarises recent advances in MRI techniques for BMs from LC. METHODS: This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted in three electronic databases: PubMed, Scopus and the Web of Science. The search was limited to studies published between January 2000 and March 2023. The quality of the included studies was evaluated using appropriate tools for different study designs. A narrative synthesis was carried out to describe the key findings of the included studies. RESULTS: Sixty-five studies were included. Standard MRI sequences such as T1-weighted (T1w), T2-weighted (T2w) and fluid-attenuated inversion recovery (FLAIR) were commonly used. Advanced techniques included perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and radiomics analysis. DWI and PWI parameters could distinguish tumour recurrence from radiation necrosis. Radiomics models predicted genetic mutations and the risk of BMs. Diagnostic accuracy was improved with deep learning (DL) approaches. Prognostic factors such as performance status and concurrent chemotherapy impacted survival. CONCLUSION: Advanced MRI techniques and specialised MRI methods have emerging roles in managing BMs from LC. PWI and DWI improve diagnostic accuracy in treated BMs. Radiomics and DL facilitate personalised prognosis and treatment. Magnetic resonance imaging plays a key role in the continuum of care for BMs of patients with LC, from screening to treatment monitoring.

Brain metastases from breast cancer using magnetic resonance imaging: A systematic review.

Despite improvements in imaging and treatment approaches, brain metastases (BMs) continue to be the primary cause of mortality and morbidity in about 20% of adult cancer patients. This research aimed to review the magnetic resonance imaging (MRI) and clinical characteristics of BMs resulting from breast cancer (BC). A systematic review of original research articles published from January 2000 to June 2023. We selected studies that reported MRI findings of BMs in BC patients. We excluded reviews, case reports, books/book chapters, animal studies and irrelevant records. We identified 24 studies that included 1580 BC patients with BMs. T1-weighted (T1-w) (pre- and postcontrast), T2-weighted (T2-w), fluid-attenuated inversion recovery (FLAIR) and T2*-weighted (T2*-w) was used to measure the lesion size, shape and area. In other studies, advanced structural techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI) and susceptibility-weighted imaging (SWI) were used to more precisely and sensitively evaluate the pathological area. Furthermore, functional and metabolic techniques like functional MRI (fMRI), magnetic resonance spectroscopy (MRS) and perfusion-weighted imaging (PWI) have also been utilised. The MRI findings of BMs varied depending on the MRI technique, the BC subtype, the lesion size and shape, the presence of haemorrhage or necrosis and the comparison with other brain tumours. Some MRI findings were associated with prognosis, recurrence or cognitive impairment in BC patients with BMs. MRI detects, characterises and monitors BMs from BC. Findings vary by MRI technique, BC subtype, lesion characteristics and comparison with other brain tumours. More research should validate emerging MRI techniques, determine the clinical implications of findings and explore the underlying mechanisms and biology of BMs from BC. MRI is a valuable tool for diagnosis, targeted therapy and studying BC metastasis.

Determinants of diabetes self-care activities in patients with type 2 diabetes based on self-determination theory.

AIMS: In type 2 diabetes control, self-management is an effective way to minimize the risk of developing complications and improve the quality of life. Self-determination theory (SDT) proposed a promising explanatory framework to predict self-regulated behavior which was particularly relevant for self-management. This study aimed to investigate whether SDT constructs can affect the self-management and controlling glycated hemoglobin A1c (HbA1c) levels in type 2 diabetic patients or not. METHODS: This cross-sectional study was conducted from August to December 2022 at two diabetes clinics in Zahedan. The study included 300 patients with type 2 diabetes. Data collection was done using a researcher-administrated questionnaire that included demographic data, diabetes self-care activities, and self-determination constructs including autonomous support, autonomous motivation, and perceived competence. RESULTS: The mean of the overall score of self-care activities was 34.62 ± 11.86 out of a maximum of 70. Patients in the fourth quarter (wealthiest) of the socioeconomic status had the highest mean self-care score (P = 0.003). There was a significant relationship between diet score with perceived competence (P = 0.009). Perceived competence (P<0.001) and controlled self-regulation (P<0.001) were the predictors of exercise score in diabetes patients. Independent self-regulation (P<0.001, r = 0.21) and overall self-regulation (P = 0.001, r = 0.19) were significantly related to blood-glucose testing score. There was a significant relationship between foot care score with perceived competence (P = 0.048, r = 0.11) and autonomous support (P = 0.013, r = 0.14). Multiple regression showed that exercise was the predictor of HbA1c (P = 0.014). CONCLUSION: Exercise is crucial for achieving good individualized glycemic control and reducing the risk of diabetes complications. The findings provided valuable insights into the determinants of self-care activities in patients with type 2 diabetes and underscore the need for interventions that address socioeconomic disparities, enhance perceived competence, and provide autonomy support to improve diabetes self-care.

Knowledge, attitudes, and practices regarding Crimean-Congo hemorrhagic fever in a high-prevalence suburban community, southeast of Iran.

Crimean Congo Hemorrhagic Fever (CCHF) is a zoonotic viral disease with a high mortality rate. The World Health Organization has classified it as a high-priority pathogen due to its severity. To manage this disease, knowledge, attitude, and practices (KAP) of the community play an important role. This study was conducted in a suburban area in southeastern Iran, an endemic region with a high occurrence of CCHF. A cross-sectional study was performed among 176 livestock farmers in Zahedan suburb, and data were collected through an interviewer-administered questionnaire. Single-factor and multi-factor analysis of variance was used to identify factors related to participants' knowledge, attitude, and risk of CCHF. All statistical analyses were conducted using SPSS 24, and a significance level of p ≤ 0.05 was adopted to determine statistical significance. Overall, the knowledge level about CCHF was moderate. Participants demonstrated a better understanding of high-risk occupations compared to the transmission routes and symptoms of CCHF. Conversely, their knowledge about the prevention and treatment of CCHF was found to be inadequate. The participants exhibited a good attitude towards CCHF prevention; most considered it a dangerous disease, believed in the effectiveness of preventive measures, and demonstrated the ability to address perceived obstacles. High-frequency engagement in high-risk behaviors related to CCHF was observed among the study participants. In the multi-factor model, the most critical factors associated with knowledge were age (p = 0.044), CCHF infection (p = 0.047), and CCHF education (p = 0.004). Income (p = 0.001), keeping livestock at home (p = 0.028), and receiving CCHF education (p = 0.012) were the most critical factors associated with attitude toward the risk of CCHF. The most important factors related to CCHF high-risk behavior were age (p = 0.045), gender (p = 0.028), and handling livestock (p < 0.001). These findings emphasize the need for maintaining health educational efforts on CCHF.

Prevalence and risk factors of pre-hypertension and hypertension among adults in Southeastern Iran: Findings from the baseline survey of the Zahedan adult cohort study.

Hypertension (HTN) stands as the leading modifiable risk factor for cardiovascular disease(CVD) and premature death globally. Understanding its prevalence and risk factors is essential for effective prevention and management of HTN. This study aimed to investigate the prevalence of Pre-hypertension (pre-HTN), HTN, and its risk factors in adults participating in the Zahedan adult cohort study (ZACS). This cross-sectional study used the baseline data of the ZACS. Ordinal logistic regression analysis was used to estimate crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for potential risk factors. Among the 10,016 participants in this study, 60.89% were women, with an average age of 50.44 ± 9.18 years. The prevalence of pre-HTN and HTN was 42.03% (men 45.44%, women 39.84%) and 18.47% (men 21.09%, women 16.79%), respectively. Being male, older age, having higher socioeconomic status (SES), being overweight and obese, having a family history of HTN, comorbidities such as diabetes and CVD, as well as abnormal blood lipid levels (triglycerides and HDL cholesterol) were the most significant predictors of pre-HTN and HTN. These findings highlight that more than half of the participants in this study exhibit pre-HTN or HTN, placing them at risk for CVD and stroke. Implementing comprehensive preventive strategies tailored to these identified risk factors is imperative to alleviate the disease burden, enhance disease management, and improve HTN treatment and control.

Antitumor activities of a novel fluorinated small molecule (A1) in CT26 colorectal cancer cells: molecular docking and in vitro studies.

Chemotherapeutic treatment of colorectal cancer (CRC) has not been satisfactory until now; therefore, the discovery of more efficient medications is of great significance. Based on available knowledge, the CXCL12/CXCR4 axis plays a significant role in tumorigenesis, and inhibition of CXCR4 chemokine receptor with AMD3100 is one of the most known therapeutic modalities in cancer therapy. Herein, N, N''-thiocarbonylbis(N'-(3,4-dimethylphenyl)-2,2,2-trifluoroacetimidamide) (A1) was synthesized as a potent CXCR4 inhibitor. A1 inhibitory activity was first evaluated employing Molecular Docking simulations in comparison with the most potent CXCR4 inhibitors. Then, the antiproliferative and cytotoxic effect of A1 on CT26 mouse CRC cells was investigated by MTT assay technique and compared with those of the control molecule, AMD3100. The impact of the target compounds IC50 on apoptosis, cell cycle arrest, and CXCR4 expression was determined by flow cytometry technique. Our finding demonstrated that A1 induces a cytotoxic effect on CT26 cells at 60 µg/mL concentration within 72 h and provokes cell apoptosis and G2/M cell cycle arrest in comparison with the untreated cells, while AMD3100 did not show a cytotoxic effect up to 800 µg/mL dose. The obtained results show that A1 (at a concentration of 40 µg/mL) significantly reduced the proliferation of CT26 cells treated with 100 ng/mL of CXCL12 in 72 h. Moreover, treatment with 60 µg/mL of A1 and 100 ng/mL of CXCL12 for 72 h significantly decreased the number of cells expressing the CXCR4 receptor compared to the control group treated with CXCL12. Eventually, the obtained results indicate that A1, as a dual-function fluorinated small molecule, may benefit CRC treatment through inhibition of CXCR4 and exert a cytotoxic effect on tumor cells.Communicated by Ramaswamy H. Sarma.

Automated segmentation of meningioma from contrast-enhanced T1-weighted MRI images in a case series using a marker-controlled watershed segmentation and fuzzy C-means clustering machine learning algorithm.

INTRODUCTION AND IMPORTANCE: Accurate segmentation of meningiomas from contrast-enhanced T1-weighted (CE T1-w) magnetic resonance imaging (MRI) is crucial for diagnosis and treatment planning. Manual segmentation is time-consuming and prone to variability. To evaluate an automated segmentation approach for meningiomas using marker-controlled watershed segmentation (MCWS) and fuzzy c-means (FCM) algorithms. CASE PRESENTATION AND METHODS: CE T1-w MRI of 3 female patients (aged 59, 44, 67 years) with right frontal meningiomas were analyzed. Images were converted to grayscale and preprocessed with Otsu's thresholding and FCM clustering. MCWS segmentation was performed. Segmentation accuracy was assessed by comparing automated segmentations to manual delineations. CLINICAL DISCUSSION: The approach successfully segmented meningiomas in all cases. Mean sensitivity was 0.8822, indicating accurate identification of tumors. Mean Dice similarity coefficient between Otsu's and FCM1 was 0.6599, suggesting good overlap between segmentation methods. CONCLUSION: The MCWS and FCM approach enables accurate automated segmentation of meningiomas from CE T1-w MRI. With further validation on larger datasets, this could provide an efficient tool to assist in delineating meningioma boundaries for clinical management.

Obstructive sleep apnea and attention deficits: A systematic review of magnetic resonance imaging biomarkers and neuropsychological assessments.

BACKGROUND AND OBJECTIVE: Obstructive sleep apnea (OSA) is a common sleep disorder that causes intermittent hypoxia and sleep fragmentation, leading to attention impairment and other cognitive deficits. Magnetic resonance imaging (MRI) is a powerful modality that can reveal the structural and functional brain alterations associated with attention impairment in OSA patients. The objective of this systematic review is to identify and synthesize the evidence on MRI biomarkers and neuropsychological assessments of attention deficits in OSA patients. METHODS: We searched the Scopus and PubMed databases for studies that used MRI to measure biomarkers related to attention alteration in OSA patients and reported qualitative and quantitative data on the association between MRI biomarkers and attention outcomes. We also included studies that found an association between neuropsychological assessments and MRI findings in OSA patients with attention deficits. RESULTS: We included 19 studies that met our inclusion criteria and extracted the relevant data from each study. We categorized the studies into three groups based on the MRI modality and the cognitive domain they used: structural and diffusion tensor imaging MRI findings, functional, perfusion, and metabolic MRI findings, and neuropsychological assessment findings. CONCLUSIONS: We found that OSA is associated with structural, functional, and metabolic brain alterations in multiple regions and networks that are involved in attention processing. Treatment with continuous positive airway pressure can partially reverse some of the brain changes and improve cognitive function in some domains and in some studies. This review suggests that MRI techniques and neuropsychological assessments can be useful tools for monitoring the progression and response to treatment of OSA patients.