Sahand Karimzadhagh

Background and Aims: Gynecological cancers are a major global health burden, with ovarian, uterine, and cervical cancers being the most common types. Despite rising national incidence rates, recent comprehensive data for Gilan Province remain limited. This study investigated the incidence trends of gynecological cancers in Gilan Province, Northern Iran, from 2014 to 2018. Methods: A repeated cross‐sectional analysis was conducted using data from the National Cancer Registry and Guilan University of Medical Sciences. Newly diagnosed cases of gynecological cancers were identified and classified according to ICD‐O‐3. Statistical analyses included descriptive statistics, one‐way ANOVA for age group comparisons, and joinpoint regression to evaluate trends. Results: A total of 1058 cases were analyzed. The overall incidence rate rose by 98.2% over 5 years from 2014 to 2018, increasing from 10.72 to 21.25 cases per 100,000 individuals. The mean age of patients was 55.43 ± 3.63 years, showing no significant variation over time. Ovarian cancer was the most common type of gynecological cancer (42%), followed by corpus uteri (29.5%) and cervical cancer (15.2%), with 5‐year incidence rates of 35.15, 24.7, and 12.73 cases per 100,000 individuals, respectively. Joinpoint regression suggested significant annual increases in both crude (APC = 19.19%, p = 0.040) and age‐adjusted rates (APC = 22.22%, p < 0.001). While the cumulative 5‐year incidence of gynecological cancers was 83.78, significant geographic disparities were observed; Bandar‐e Anzali exhibited the highest rate (148.57), followed by Astaneh‐ye Ashrafiyeh (103.88), whereas Talesh reported the lowest (56.66). Conclusion: The incidence of gynecological cancers in Gilan province almost doubled during the study period, highlighting a substantial public health concern linked to long‐term burden and mortality rates. Interventions should prioritize community‐wide education, timely referrals, expanded access to diagnostic services, and enhanced awareness of early symptoms.

Background: Sebaceous neoplasms in Muir–Torre syndrome (MTS), a subtype of Lynch syndrome, tend to occur before visceral malignancies. MTS is associated with defects in mismatch repair (MMR) proteins, such as MLH1 and MSH2. Early screening for MMR deficiencies in sebaceous neoplasms has been proposed to aid in identifying MTS. Objectives: To determine, using immunohistochemistry (IHC), the prevalence of MMR defects in sebaceous neoplasms in an Iranian cohort. Methods: Samples of sebaceous tumours from tissue registries at two hospitals, collected between March 2014 and March 2019, were analysed using IHC for MLH1 and MSH2. Data analyses were performed using SPSS software version 21. Results: Twenty-five sebaceous neoplasms from 23 individuals were studied. Overall, 12 (48%) samples showed abnormal IHC results. Specifically, six (24%) samples had MSH2 deficiency, three (12%) exhibited MLH1 deficiency and another three (12%) were deficient in both. Two patients each had two sebaceous neoplasms; in one patient, both tumours showed MSH2 deficiency, while in the other, both tumours exhibited loss of expression for both MMR proteins. Neither tumour type nor patient sex was linked to MMR deficiency. However, tumours outside the head and neck region were significantly associated with MSH2 deficiency. Additionally, younger patients had a higher prevalence of MSH2 deficiency. Conclusions: Multiple sebaceous tumours, tumours presenting at a younger age and tumours located outside the head and neck area could be the most important predictors of IHC abnormalities. After validation by larger future studies, these predictors should be considered for targeted MTS screening strategies.

Skin cancer has one of the highest incidence rates among malignancies. A shortage of clinical expertise, particularly in primary care, contrasts with the promising performance of artificial intelligence (AI) models in assisting clinicians. However, a comprehensive evaluation of AI‐based diagnostic accuracy across various skin cancers is essential before integration into routine clinical practice. This umbrella review synthesizes evidence from meta‐analyses assessing AI model performance in skin cancer detection. We searched PubMed, Web of Science, and Embase for relevant meta‐analyses published until January 28, 2025. We included 11 meta‐analyses comprising 551 studies from various skin cancer types, clinical settings, and diagnostic modalities. Convolutional neural networks (CNN) and support vector machines (SVM) demonstrated the highest diagnostic performance, with CNN achieving the highest overall accuracy. AI models distinguishing melanoma from melanocytic lesions outperformed those detecting melanoma across all skin cancers, with SVM achieving the highest sensitivity (91%) and specificity (94%). For squamous cell carcinoma, machine learning models trained on hyperspectral imaging demonstrated the highest sensitivity (90.1%) and specificity (92.65%). In differentiating benign from malignant lesions, models exhibited a sensitivity of 87% and a specificity of 86.4%. AI‐assisted approaches significantly improved diagnostic accuracy among all clinicians, with generalists and nurse practitioners benefiting more than experienced dermatologists. Deep learning models in primary care, trained on smartphone images, achieved higher sensitivity (90%) and specificity (85%) than general practitioners. AI models significantly outperformed junior dermatologists and nonspecialists compared to senior dermatologists. Hence, integrating AI‐assisted tools into clinical workflows, particularly in primary settings, can enhance diagnostic accuracy and minimize missed cases.

Background and Objectives: Prosthetic hand development is undergoing a transformative phase, blending biomimicry and neural interface technologies to redefine functionality and sensory feedback. This article explores the symbiotic relationship between biomimetic design principles and neural interface technology (NIT) in advancing prosthetic hand capabilities. Methods: Drawing inspiration from biological systems, researchers aim to replicate the intricate movements and capabilities of the human hand through innovative prosthetic designs. Central to this endeavor is NIT, facilitating seamless communication between artificial devices and the human nervous system. Recent advances in fabrication methods have propelled brain–computer interfaces, enabling precise control of prosthetic hands by decoding neural activity. Results: Anatomical complexities of the human hand underscore the importance of understanding biomechanics, neuroanatomy, and control mechanisms for crafting effective prosthetic solutions. Furthermore, achieving the goal of a fully functional cyborg hand necessitates a multidisciplinary approach and biomimetic design to replicate the body’s inherent capabilities. By incorporating the expertise of clinicians, tissue engineers, bioengineers, electronic and data scientists, the next generation of the implantable devices is not only anatomically and biomechanically accurate but also offer intuitive control, sensory feedback, and proprioception, thereby pushing the boundaries of current prosthetic technology. Conclusion: By integrating machine learning algorithms, biomechatronic principles, and advanced surgical techniques, prosthetic hands can achieve real-time control while restoring tactile sensation and proprioception. This manuscript contributes novel approaches to prosthetic hand development, with potential implications for enhancing the functionality, durability, and safety of the prosthetic limb.

INTRODUCTION: First-degree relatives (FDRs) of patients with celiac disease (CeD) are at high risk for developing CeD. We conducted a systematic review and meta-analysis to estimate CeD prevalence and clinical manifestations by analyzing studies that used the anti-tissue transglutaminase antibody test for screening. METHODS: In this systematic review with meta-analysis, studies published in PubMed, Web of Science, Embase, and Scopus were searched up to January 11, 2024, using keywords related to CeD and FDRs. Random-effects models were used, with heterogeneity assessed using the Cochran Q test and the I ² statistic performed in STATA 18. RESULTS: Of 8,764 studies screened, 34 studies involving 10,016 FDRs of patients with CeD were included. The pooled estimates for seroprevalence and the biopsy-confirmed CeD prevalence in FDRs were 11% (95% CI: 9%–13%) and 7% (95% CI: 6%–9%), respectively. Daughters and sisters had the highest prevalence rates at 23% and 14%, compared with sons and brothers at 6% and 9%, respectively. Regional analysis revealed the highest seroprevalence estimates in Hungary (24%) and Cuba (19%), while the highest prevalence of biopsy-confirmed CeD was reported in Serbia (16%) and the United States (15%). Abdominal pain (42%), bloating (39%), and flatulence (38%) were the most common gastrointestinal symptoms, while 34% of FDRs with CeD were asymptomatic. In addition, pallor was the most frequent nongastrointestinal symptom (54%). DISCUSSION: Approximately 1 in 14 FDRs of patients with CeD is estimated to have CeD, with 1 in 4 daughters, 1 in 7 sisters, 1 in 11 brothers, 1 in 16 sons, and 1 in 20 fathers and mothers could be affected. Routine screening for FDRs could support early detection and management of CeD.

Background: Glioblastoma multiforme (GBM) poses a significant health challenge as the most common primary malignancy of the adult central nervous system. Gender‐ and age‐related differences in GBM influence prognosis and treatment complexities. This multicenter retrospective study explores gender and age disparities in GBM patients, investigating their impact on occurrence and survival outcomes.Methods: This multicenter retrospective study involved GBM patients treated in Guilan Province, Iran. Patients' data, including age, gender, tumor location, and histopathological diagnosis date, was collected from medical records.Results: In a cohort of 164 GBM patients, the average age was 54.34 ± 14.16 years, with a higher prevalence among men (59.8%) and patients aged ≤ 60 years (64.6%). The tumor sites exhibited overlapping features in 68% of cases, with the frontal and temporal lobes being the most common specific locations. The mean survival was 12.88 ± 14.14 months, one‐year survival of 45%, with women showing significantly higher one‐year survival (60% vs. 40%) and longer mean survival (16.14 ± 17.35 vs. 10.75 ± 11.15 months). Furthermore, Patients ≤ 60 years had significantly higher one‐year survival (75% vs. 35%). In subgroup analysis, women had significantly higher survival rates in patients ≤ 60 years. However, among patients over 60, women exhibited a more pronounced decline in survival rates, with no statistically significant difference between men and women in this age group.Conclusion: This study highlights that both age and gender significantly affect GBM survival outcomes. Younger patients, particularly women, exhibited better survival rates, while older patients, especially women, showed poorer outcomes. These findings suggest the need to stratify treatment approaches by both age and gender to optimize care and improve survival in GBM patients. Further research is recommended to explore these associations.

Background: Coeliac disease (CD) is common in patients with type 1 diabetes (T1D), but prevalence varies globally due to differing screening protocols. There have been substantial changes in screening guidelines over the past two decades.Aim: To evaluate CD prevalence in patients with T1D, focusing on screening studies using antitissue transglutaminase (anti‐tTG) antibody.Methods: We searched PubMed, Web of Science, Embase and Scopus for studies published up to 11 December 2023 using keywords related to CD and diabetes. We used random‐effects models for overall prevalence and all subgroups, with heterogeneity assessed using Cochran's Q test and the I² statistic performed in STATA 18.Results: We included 106 articles involving 65,102 T1D patients across 40 countries. The pooled CD seroprevalence and confirmed CD prevalence were 9% (95% confidence interval, CI, 8%–10%) and 6% (95% CI 5%–7%), respectively. The prevalence was higher in females and children. Denmark, Saudi Arabia and Libya exhibited the highest prevalence (11%), followed by India and Egypt (10%). Belgium, France, Germany, South Africa and the United States had the lowest prevalence (2%). High‐income countries showed significantly a lower CD prevalence than middle‐income countries (p = 0.03). Meta‐regression based on the Human Development Index (HDI) indicated that countries with higher HDI have lower seroprevalence and confirmed CD prevalence.Conclusion: Approximately 1 in 16 patients globally and 1 in 12 patients in Asia and the Middle East with T1D has CD. We suggest that all patients with T1D should be screened for CD.