Shahid Sadoughi University of Medical Sciences is a public university located in the center of Iran in the World Heritage city of Yazd. The university offers degrees in 102 programs in medicine, dentistry, pharmacy, nursing, midwifery, paramedical sciences, and health services ranging from associate degrees to sub-specialties and fellowships. The university administers 9 hospitals and over 90 clinics throughout the city and province of Yazd..
Drinking water is the main source of fluoride, which prevents dental caries at recommended levels; however, excessive intake has been associated with adverse outcomes, including noncommunicable diseases. This cross-sectional study, conducted in 2023, included 600 adults aged 18–75 years residing in urban and rural areas of Zarand and Sarbisheh cities, Iran. Demographic characteristics and determinants of fluoride exposure were collected using a structured questionnaire. Anthropometric measurements, including body mass index (BMI) and waist circumference (WC), as well as blood pressure parameters, including systolic blood pressure (BP) and diastolic blood pressure (DBP), were measured through physical examinations. Drinking water samples were collected from 43 villages and 4 cities. Simple linear regression and generalized linear model–based tree (GLM-tree) analyses were applied to assess the associations, while accounting for potential confounding and moderating factors. The mean age of participants was 40.27 ± 14.54 years, and 68.8
Prolyl Endo-Protease (PEP) is one of the crucial enzymes found in the salivary gland of Eurygaster integriceps. This study reveals PEP structure via in silico methods. BLAST was performed on the sequence to find the most appropriate template. The model of the 3D structure was made using the template, and quality evaluation was performed for all models. The determination of ligand binding sites as well as the refinement of the 3D structure was performed. In the topology model presented here, this protein doesn’t have any transmembrane region. Five pockets on protein surfaces were obtained using the GHECOM server. COFACTOR software is used for finding ligand binding sites, indicating the involvement of conserved residues, especially 173, 472, 475, 553, 554, 599, 644, 645, and 681 in the ligand binding site. Overall, this study provides detailed information, which can help design highly efficient pesticides by inhibiting the Eurygaster integriceps proteases.
This study evaluated the efficiency of various extraction methods for tannin recovery from pistachio soft hulls and assessed the antimicrobial activity of the resulting extracts. Two pistachio varieties (Ahmetaga and Ohadi) were selected. Tannin extraction methods, including Soxhlet extraction (SE), sonication (S), maceration (M), decoction (D), percolation (P), and microwave-assisted extraction (MAE), were investigated. The antimicrobial activity of high-tannin extracts was evaluated using phenol coefficient tests. The highest tannin content from Ahmetaga pistachio soft hulls was achieved using MAE (68.86 ± 0.25 µg. mL−1) and S (58.52 ± 11.90 µg. mL−1). For Ohadi pistachio soft hulls, the highest yield was obtained via hydroalcoholic percolation (HAP) (73.07 ± 6.69 µg.mL−1), followed by acetone Soxhlet extraction (AcSE) (70.09 ± 4.46 µg.mL−1) and maceration (M) (67.46 ± 0.74 µg.mL−1). The highest Phenol Coefficient (PC = 2) was achieved for the Ohadi extract produced by the M method. There was a statistically significant variation in tannin content based on both the pistachio cultivar and the extraction method employed (P < 0.05). Ohadi extracts exhibited superior tannin contents (73.06 ± 6.69 µg. mL−1) compared to the Ahmetaga cultivar. Specifically, the extracts obtained via M and HAP methods from Ohadi soft hulls contained higher concentrations of tannins than the corresponding extracts prepared from Ahmetaga hulls.
Abstract Bladder cancer represents the ninth most commonly diagnosed malignancy worldwide, with substantial morbidity and mortality. Conventional diagnostic modalities—including cystoscopy, urine cytology, cross-sectional imaging, and histopathological examination—are limited by operator-dependent variability, modest sensitivity for early-stage disease, and significant interobserver discordance. Artificial intelligence (AI), and particularly deep learning (DL)-based approaches, has emerged as a transformative paradigm to enhance diagnostic accuracy and standardize assessment across the complete diagnostic continuum. This narrative review critically synthesizes contemporary evidence on AI applications in bladder cancer diagnosis, encompassing cystoscopic tumor detection, urine cytology analysis, radiomics-based staging, computational pathology, multimodal fusion architectures, and intraoperative guidance. Across validation cohorts, AI-enhanced cystoscopy achieves sensitivity of 91–99% and specificity of 87–99%. AI-augmented urine cytology demonstrates substantial sensitivity improvements, with the VisioCyt system achieving 84.9% overall sensitivity compared with 43% for conventional cytology. Radiomics and deep learning approaches for imaging analysis achieve area under the curve values ranging from 0.834 to 0.997 for staging and muscle-invasion prediction. Computational pathology systems achieve diagnostic accuracy meeting or exceeding that of experienced pathologists while providing standardized, reproducible assessments. Notwithstanding these advances, challenges including data standardization, model interpretability, prospective clinical validation, regulatory harmonization, and health-economic evaluation must be addressed to enable widespread clinical implementation. This review identifies critical research priorities and discusses pathways for responsible translation of AI innovations into routine urologic practice.
