Zahedan University of Medical Sciences

The global rise of chronic diseases requiring long-term management highlights the need for effective palliative care. Nurses play a central role in providing this care, yet frequently face ethical challenges such as moral distress, complex decision-making, and occupational stress. This systematic review aimed to identify, categorize, and synthesize evidence on nurses’ ethical perspectives, challenges, and professional interventions in palliative care for patients with chronic diseases in both hospital and home settings. The review addressed the following questions: (1) What are nurses’ ethical perspectives in delivering palliative care ? (2) What ethical challenges and decision-making dilemmas do they encounter? (3) Which strategies and interventions support ethically sound care? Following PRISMA 2020 guidelines, five databases (PubMed, Scopus, Web of Science, SID, and Magiran) and gray literature via Google Scholar were systematically searched for studies published between 2015 and 2025 in English or Persian. Eligible studies included qualitative, quantitative, mixed-methods, and peer-reviewed reviews addressing nurses’ ethical challenges in palliative care. Qualitative data were analyzed using inductive content analysis, quantitative findings were synthesized descriptively, and mixed-methods results were integrated to allow convergence across study designs. Extracted codes were organized into themes, grouped into categories, and synthesized into overarching domains. Thirty-four studies met inclusion criteria. Four main domains of ethical challenges emerged: (1) Clinical decision-making and patient autonomy—dilemmas regarding life-sustaining treatments, medication and fluid management, palliative sedation, and conflicts between patient preferences and family/cultural expectations; (2) Justice and resource allocation—insufficient ethics education, high workload, limited organizational support, poor interprofessional collaboration, and scarce resources; (3) Beneficence and patient-centered care—ethical issues related to technological innovations, informed consent, data privacy, and environmental pressures such as ICU or emergency care conditions; (4) Non-maleficence and moral distress prevention—moral distress, burnout, reduced ethical courage, and legal concerns affecting clinical decisions. Nurses encounter substantial ethical challenges in delivering palliative care for patients with chronic diseases. Addressing these challenges requires ethics education, structured organizational guidance, interprofessional collaboration, and context-sensitive strategies to safeguard patient dignity and reduce moral distress. These findings provide evidence for policymakers, educators, and managers to develop practical interventions and ethical frameworks across diverse care settings.

Introduction: This study compared the effects of mouthwashes containing chitosan/zinc oxide nanoparticles, 0.2% chlorhexidine, 1.5% hydrogen peroxide (Colgate), and distilled water on the color and microhardness of bleached enamel. Materials and Methods: Sixty bovine incisors were randomly divided into four groups (n = 15). After polishing and tea staining for six days, baseline color and microhardness were recorded using the CIELAB system and Vickers test. The enamel surfaces were bleached three times with 40% hydrogen peroxide. After ten days, measurements were repeated. The bleached samples were then immersed in 5 ml of each mouthwash twice daily for 14 days. The synthetic mouthwash contained 1% chitosan and 500 µg/ml zinc oxide nanoparticles. Color and microhardness were re-evaluated, and data were analyzed using the Kruskal–Wallis and post-hoc tests (α = 0.05). Results: Significant color differences were observed between the mouthwash groups and water (p < 0.05), with no significant difference between chlorhexidine and the nanoparticle mouthwash. Both the nanoparticle and Colgate mouthwashes similarly increased enamel microhardness, while chlorhexidine caused a slight decrease. Conclusion: Mouthwash containing chitosan and zinc oxide nanoparticles improved bleached enamel microhardness without affecting color stability compared to 0.2% chlorhexidine.

• Artificial intelligence (AI) models demonstrate consistently high diagnostic performance for intracranial aneurysm rupture status or rupture-related risk assessment across multiple metrics. • Diagnostic performance of human readers varies substantially according to expertise, with expert readers outperforming non-experts in sensitivity but showing similar overall accuracy. • Human–AI collaborative approaches show promising diagnostic performance in individual studies; however, current evidence is limited and highly dependent on integration strategy. • Considerable methodological heterogeneity, inconsistent outcome definitions, and limited head-to-head comparisons restrict definitive conclusions regarding comparative superiority. • Standardized definitions, transparent reporting, and multicenter prospective studies are required to clarify the optimal role of AI and Human–AI collaboration in aneurysm care. Accurate assessment of intracranial aneurysm rupture risk remains challenging, with conventional clinical scores showing limited predictive performance. Artificial intelligence (AI) has emerged as a potential adjunct to imaging-based risk stratification, yet the relative performance of AI, human experts, and Human–AI collaboration has not been systematically quantified. A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. PubMed, Scopus, Web of Science, and Embase were searched. Studies comparing AI-alone, human-alone, or Human–AI approaches for intracranial aneurysm rupture status or rupture-related risk assessment were included. The outcomes of interest were sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). Random-effects models were applied when appropriate, and methodological quality was assessed using the ROBINS-I tool. Seventeen studies were included. AI-alone models demonstrated consistently high diagnostic performance across sensitivity, accuracy, and AUC, although substantial heterogeneity was observed across methodologies and imaging modalities. Human reader sensitivity varied according to expertise, with expert readers achieving higher sensitivity than non-experts but similar overall accuracy. Human–AI collaborative approaches showed high diagnostic metrics in individual studies; however, the number of eligible studies was limited, and integration strategies were heterogeneous, precluding definitive pooled comparisons. Current evidence indicates that AI models can achieve high diagnostic performance in intracranial aneurysm rupture risk assessment and may serve as a valuable adjunct to clinical expertise. While Human–AI collaboration shows promise, available data remain exploratory and strategy-dependent. Standardized outcome definitions and multicenter prospective studies are required before firm conclusions regarding comparative effectiveness or clinical superiority can be established.

Non-Hodgkin lymphoma (NHL) represents a diverse spectrum of lymphoid malignancies, which are defined by abnormal proliferation of lymphocytes and the absence of Reed-Sternberg cells. Both genetic and epigenetic mechanisms play critical roles in the etiology of this group of cancers. In this context, the present study aimed to assess the potential relationship between three specific single nucleotide polymorphisms (SNPs) in the MALAT1 gene namely rs619586 A>G, rs664589 C>G, and rs3200401 C>T and their association with susceptibility to NHL in a population sample from Zahedan, Iran. A case-control study design was utilized, comprising 185 individuals diagnosed with NHL (118 men and 67 women; mean age: 45.46 ± 15.44 years) and an equal number of age- and sex-matched healthy controls (106 men and 79 women; mean age: 43.26 ± 12.27 years). Genomic DNA was isolated from peripheral blood leukocytes using the conventional salting-out method. Genotyping for the selected MALAT1 polymorphisms was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and amplification refractory mutation system PCR (ARMS-PCR) methodologies. Statistical evaluations were performed using chi-square tests, independent sample t-tests, and logistic regression models to analyze the data. The rs3200401 C>T polymorphism of the MALAT1 gene was significantly associated with a reduced risk of NHL, suggesting a protective effect (P<0.05). Similarly, the rs619586 A>G variant showed a significant protective association with NHL. In contrast, the rs664589 C>G polymorphism did not show any significant differences in genotype or allele frequencies between NHL patients and healthy subjects (P>0.05). The findings suggest that MALAT1 gene polymorphisms, particularly rs3200401 and rs619586, as well as the TCG haplotype, may influence susceptibility to non-Hodgkin lymphoma and serve as potential genetic biomarkers. However, further studies involving larger and ethnically diverse cohorts are required to validate these associations.

Background: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women of reproductive age and is often associated with impaired glucose tolerance (IGT). Evidence on the prevalence of IGT in Iranian women with PCOS is limited. Objectives: This descriptive-analytical study aimed to assess the prevalence of IGT and to compare its frequency between women with and without PCOS referred to the infertility clinic of Ali Ibn Abi Talib Hospital in Zahedan, Iran, during 2019 - 2021. Methods: This prospective case-control study included 280 women, 225 with PCOS and 55 controls. Fasting blood glucose (FBG) and oral glucose tolerance test (OGTT) values were measured. Data were analyzed using chi-square, t-test, or Mann-Whitney U test, as appropriate. Results: The mean age of women with PCOS was 28.75 ± 4.31 years versus 29.34 ± 4.61 in controls (P = 0.367). Although the prevalence of IGT was higher among women with PCOS (32.89%) than among controls (23.64%), this difference was not statistically significant (P = 0.184). In contrast, the mean 2-hour post-load glucose level was significantly higher in the PCOS group (130.00 ± 25.57 mg/dL) compared with controls (122.30 ± 23.73 mg/dL; P = 0.038). Receiver operating characteristic (ROC) analysis demonstrated a modest discriminatory ability of the 2-hour post-load glucose value for identifying IGT, with an area under the curve of 0.589 (95% CI: 0.501 - 0.677; P = 0.041). Conclusions: Women with PCOS exhibited higher mean post-load glucose levels compared with controls, although the prevalence of IGT did not differ significantly between groups. Periodic glucose tolerance screening is recommended for early detection of metabolic abnormalities and prevention of type 2 diabetes.

Abstract Heart disease remains a leading cause of morbidity and mortality worldwide, highlighting the need for accurate and scalable predictive models to support early diagnosis and clinical decision-making. In this study, we investigate the effectiveness of machine learning approaches for heart disease prediction using a large, publicly available clinical dataset obtained from IEEE DataPort. The dataset integrates multiple established heart disease cohorts and includes key demographic and clinical variables relevant to cardiovascular risk assessment. Two supervised machine learning models—Random Forest and Support Vector Machine (SVM)—were developed and evaluated to classify the presence of heart disease. Model performance was assessed using accuracy, precision, and recall metrics. The Random Forest model achieved an accuracy of 0.89, with a precision of 0.85 and a recall of 0.83, demonstrating strong overall performance and balanced predictive capability. The SVM model achieved an accuracy of 0.88, with a recall of 0.85 and a precision of 0.81, indicating robust sensitivity in identifying positive cases.

Considering the historical use of three plant species Punica granatum, Quercus infectoria, and Achillea millefolium in traditional medicine for hemostatic purposes, along with the variation observed in some experimental research, the aim of this study was to comparatively evaluate the effect of methanol extracts derived from these three medicinal plants on blood clotting time in vitro. Methanolic (70%) extracts of P. granatum flower, Q. infectoria galls and A. millefolium aerial parts were prepared by maceration method. The total tannin and phenolic content were determined using a colorimetric method. The cytotoxic activity of extracts on NIH/3T3 cell lines was evaluated by the colorimetric MTT assay. Non-toxic concentrations were tested in vitro on blood coagulation profiles including prothrombin time (PT) and activated partial thromboplastin time (aPTT) of healthy human volunteers. Q. infectoria had the highest phenolic content at 287.18 mg gal/g, followed by P. granatum and A. millefolium. P. granatum exhibited the highest tannin content (119.21 mg catechin/g DW), followed by Q. infectoria (109.30 mg catechin/g DW) and A. millefolium (54.35mg catechin/g DW). The highest total flavonoid content was found in P. granatum, A. millefolium, and Q. infectoria with 98, 85.5, 5.22 mg Rutin/g DW, respectively. Non-toxic concentrations were selected to perform coagulation experiments. Based on the plant-derived coagulation assays, pomegranate extract notably reduced the PT to 11.57 ± 0.37 s compared with the control value of 14.47 ± 0.41 s. Conversely, gall oak extract markedly increased the coagulation time to 17.07 ± 1.07 s. Similarly, pomegranate significantly decreased aPTT to 33.83 ± 0.79 s relative to the control (36.30 ± 2.04 s), whereas gall oak considerably prolonged it to 50.00 ± 2.04 s. Methanolic extracts of P. granatum show promise as procoagulants, while Q. infectoria acts as an anticoagulant, and A. millefolium remains neutral in this context.

Background: Multiple sclerosis (MS) is a leading cause of non-traumatic neurological disability in young adults, and headaches often intensify the day-to-day burden by worsening headache-related quality of life (QoL). Evidence for low-cost, nurse-delivered behavioral options such as progressive muscle relaxation (PMR) in MS headache care remains limited. We evaluated whether a brief PMR program is associated with lower headache impact on QoL measured by the Headache Impact Test (HIT-6). Methods: In a controlled quasi-experimental, parallel-group, pretest–posttest study (Zahedan, Iran; 2023), adults with neurologist-confirmed MS and recurrent headaches were allocated to PMR (n = 30) or usual care (n = 30). PMR included three nurse-led group sessions (20 - 30 minutes on three consecutive days) plus structured daily home practice for six weeks with weekly telephone support. HIT-6 (range 36 - 78; higher = worse) was collected at baseline and 3 months. Baseline comparability used t-tests/χ². The primary endpoint (3-month HIT-6) was analyzed via ANCOVA adjusting for baseline HIT-6 and MS duration (α = 0.05). Results: Sixty participants completed follow-up (PMR n = 30; Control n = 30). Groups were similar in age and sex; MS duration was longer in PMR. Baseline HIT-6 did not differ. At 3 months, the PMR group showed lower HIT-6 than controls in adjusted analysis: Adjusted Mean Difference (PMR-Control) = -5.64 (95% CI -9.58 to -1.69; p = 0.006; partial η² = 0.128). The adjusted between-group difference in HIT-6 (-5.64 points) exceeded the 3-point MCID, supporting clinical interpretability. Conclusions: A brief, nurse-delivered PMR program with structured home practice was associated with a clinically interpretable reduction in headache impact (HIT-6) at 3 months versus usual care. Given its low cost, safety, and feasibility, PMR appears to be a pragmatic adjunct to multidisciplinary MS services. Larger, multicenter randomized trials with longer follow-up and objective adherence tracking are warranted.