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Treatment-resistant patients with focal epilepsy of unknown cause display reduced neurogranin levels: a preliminary study
No full textBackground and purpose-The role of synaptic dysfunction in focal epilepsy of unknown cause is not well understood. Neurogranin is a post-synaptic protein used as a biomarker of synaptic disintegration in patients with dementia. Methods-To evaluate the association between synaptic loss, cognitive impairment and seizure activity in epilepsy, we collected sera of 51 patients with focal epilepsy of unknown cause, 26 with frontal lobe epilepsy (FLE) and 25 with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS), and 25 healthy controls. Serum neurogranin levels were measured by ELISA and we sought for potential correlations between neurogranin levels versus clinical features, cognitive test and quality of life scores of the patients. Results-Neurogranin levels were significantly reduced in MTLE-HS patients as compared to FLE patients and healthy controls but were not correlated with any of the clinical and cognitive variables. Both FLE and MTLE-HS patients with treatment resistance showed significantly reduced neurogranin levels. Conclusion-Our results suggest that MTLE-HS patients suffer from reduced synaptic protein production rather than increased synaptic breakdown. Reduction of neurogranin is associated with resistance to anti-epileptic treatment implying the role of this protein in the control of seizures. Neurogranin might serve as a biomarker for monitorization of seizure activity in focal epilepsies
The effect of pelvic proprioceptive neuromuscular facilitation techniques in patients with sacroiliac joint dysfunction: A randomized controlled study
No full textBackground Despite the widespread presence of sacroiliac joint dysfunction (SIJD) among causes of low back pain, SIJD is still overlooked. Objective This study aimed to investigate the effect of pelvic proprioceptive neuromuscular facilitation techniques (PNF) in patients with SIJD. Methods This prospective, single-blinded, randomized controlled study was conducted between December 2023 and March 2024. Fourty patients diagnosed with SIJD, with pain for at least 4 weeks initially, aged between 18 and 40, were randomly allocated into experimental group (EG, n = 20) and control group (CG, n = 20) using a computer-based randomised numbered list. The CG received patient education consisting of basic lumbar stabilization exercises (LSE); the EG received exercise training consisting of pelvic PNF techniques in addition to patient education. The interventions of both groups were applied 3 days a week for 6 weeks. Pain, mobility, flexibility, lumbar range of motion, posture, trunk flexor muscle endurance, and trunk extensor muscle endurance were assessed by VAS, Modified Schober's test, sit-and-reach test, goniometer, New York Posture Rating Chart, flexor endurance test, ve Biering-S & oslash;rensen test, respectively, before and after interventions. The Shapiro-Wilk test was used to assess normality, while intra-group and inter-group comparisons were conducted using either the Paired sample T-test or the Independent samples T-test. Results Of the EG (n = 20, 30,88 +/- 14,23 years), 82.35% (n = 14) were female, while the CG (n = 20, 27,18 +/- 7,58 years) comprised 76.47% (n = 13) females. The mean body mass index for the EG was 23.71 +/- 3.68 kg/m(2), compared to 23.51 +/- 3.68 kg/m(2) in the CG. Baseline values of pain (p = 0.152, 95% CI [-0.342-2.107]), mobility (p = 0.407, 95% CI [-12.699-5.405]), flexibility (p = 0.758, 95% CI [-2.293-3.116]), posture (p = 0.913, [-2.422-3.613]), trunk flexor muscle endurance (p = 0.336, 95% CI [-3.213-5.955]), and trunk extensor muscle endurance (p = 0.405, 95% CI [-2.927-4.842]) of the groups were similar. Both the EG and CG achieved significant improvements in reducing pain (p < 0.001). The improvement in the pain was significantly higher in the EG compared to the CG (p < 0.001, dcohen = -1.030). There were significantly change in the scores of mobility, flexibility, and lumbar range of motion only in the EG. All changes had a medium or high effect size (p < 0.001, dcohen = 0.631; p = 0.011, dcohen = 0.417; p < 0.05, dcohen = 0.649, respectively). Conclusion Incorporating the pelvic proprioceptive neuromuscular facilitation techniques into the rehabilitation protocols for patients with sacroiliac joint dysfunction may prove beneficial, potentially enhancing pain relief while also improving mobility, flexibility, and lumbar range of motion
Assessment of the potential of drug-drug interactions among population-based oldest-old people in Turkiye
Full text linkBackground: The risk of potential drug-drug interactions is highest in oldest-old people. Thus, the aim of this study was to investigate the frequency and type of potential drug-drug interactions in population-based oldest-old people. Methods: The type of study was descriptive. Ethical permission was obtained (13.04.2022/153). All participants were informed, and their written consent was obtained. The "oldest-old" were defined as those who were >= 85 years of age during the study period and living in Turkiye. These people were reached from every region of Turkiye via the snowball method and were visited at their homes. Data were collected via face-to-face interviews. Age, sex, city of residence, and generic names of regularly used medications were recorded. The medications used were analyzed according to the Beers 2019 (R) Criteria and UpToDate (R) Lexicomp (R) drug interaction guides. SPSS was used for statistical analysis, and p = 1 potential drug-drug interaction, according to the UpToDate analysis. The median number of medications used continuously was 4.0 (minimum = 0, maximum = 19). The median number of potential drug-drug interactions was 1.0 (minimum = 0, maximum = 21). As the number of medications used increased, the number of potential drug-drug interactions also increased (r = 0.737; p = 0.001). The number of potential drug-drug interactions decreased with increasing age (r = -0.104; p = 0.015). According to the Beers 2019 (R) Criteria, potential drug-drug interactions were detected in only eight patients. The concordance between the Beers 2019 (R) Criteria and the UpToDate (R) Lexicomb (R) drug interaction data was poor compared with the number of potential drug-drug interactions (kappa = 0.024, p < 0.001). Central nervous system medications are a common group that can cause potential drug-drug interactions according to both guidelines. Moreover, potentially inappropriate medications defined by the Beers 2019 (R) Criteria were the most common causes of potential drug-drug interactions, according to UpToDate (R) Lexicomb (R) drug interactions. The frequency of potential drug-drug interactions was found to be high in the population-based oldest-old people interviewed in Turkiye. It has been determined that the use of more than one guide inthe evaluation of potential drug-drug interactions is safer
Ensemble-based classification algorithm to enhance stability of energy management in IoT-based smart grid networks
No full textThe exponential increase in electricity consumption makes renewable energy management a necessity within the global warming context. Internet of things (IoT) has a key role in effective data transmission for better managing of energy dissipation in smart grids. Since smart grid network deployment involves huge complexities due to the large data volume being generated, applying artificial intelligent methods is essential to better manage the process. Moreover, reducing energy consumption in a stable smart grid system and fault detection are important in managing electricity congestions, power failure and grid stability problems. This paper aims to present a novel prediction architecture involving ensemble bagging trees and analysis of variance (ANOVA) as a feature selection strategy to improve stability of energy consumption and maximise prediction factors such as accuracy, precision, recall and F1-score in IoT-based smart grids. Experimental and simulation results show that the proposed architecture can decrease training time and improve accuracy of prediction with 99.999% on validation (training) data and 100% on test data than other state-of-the-are machine learning mechanisms
Transanal Specimen Extraction After Laparoscopic Sigmoidectomy for Sigmoid Volvulus
Full text linkObjective: Sigmoid resection can be performed using conventional and laparoscopic methods. Specimen removal from the natural orifice after laparoscopic surgery is increasingly preferred. This approach can reduce wound complications and the length of hospitalization. In this study, we present the results from cases of sigmoid volvulus treated with laparoscopic surgery and transanal specimen removal. Methods: A retrospective analysis was performed on eight cases in which patients diagnosed with sigmoid volvulus underwent elective laparoscopic sigmoid colon resection and transanal specimen extraction. The patients were evaluated in terms of age, gender, comorbidities, operation time, surgical difficulties, length of hospital stay, and complications. Results: Laparoscopic sigmoid resection and transanal specimen extraction were performed on eight patients. All patients were male, and the median age was 68 years (28-86 years). Five of the patients had comorbidities. The median operative time was 195 minutes (180-360). Transanal specimen extraction was successful in all patients. Anastomotic leakage occurred in one patient and subileus occurred in two patients. The median hospital stay was 5.5 days (3-21). Conclusion: Transanal specimen extraction after laparoscopic resection is an easy, feasible, and safe method. Sigmoid volvulus is the ideal disease for the application of this procedure because it does not involve mass-like lesions such as tumors and diverticula
Sex-Specific Longitudinal Changes in Metabolic, Endocrine, Renal, Cardiovascular, and Inflammatory Biomarkers of Vaccinated COVID-19 Survivors: 30-Month Follow-Up Study
Full text linkObjectives: Sex-based disparities in COVID-19 outcomes are well-documented, with men experiencing greater acute severity and women showing increased vulnerability to post-viral syndromes. However, longitudinal immunometabolic trajectories in vaccinated individuals remain underexplored. In this study, sex-based differences in long-term metabolic, endocrine, renal, cardiovascular, and inflammatory responses were investigated among vaccinated individuals recovering from SARS-CoV-2 infection. Methods: This retrospective single-center cohort study included 426 adults (199 females, 227 males) with PCR-confirmed symptomatic COVID-19 and at least two vaccine doses. Serial assessments were conducted at baseline, 18-, 24-, and 30-month post-infection. Parameters included fasting glucose, HbA1c, lipid profile, thyroid function, renal markers, CRP, D-dimer, fibrinogen, troponin, and hematologic indices. Statistical analyses assessed longitudinal changes and sex-stratified correlations. Results: Fasting glucose and HbA1c levels significantly declined over time, more prominently in males. Glucose correlated with age and BMI only in females. Lipid levels remained largely unchanged, although males had higher baseline triglycerides. Females showed rising TSH levels and persistently lower free T3; males exhibited higher creatinine, urea, and troponin levels throughout. Inflammatory markers declined significantly in both sexes, with males displaying higher CRP and troponin, and females showing sustained fibrinogen elevation and a temporary lymphocyte surge. D-dimer was elevated in females at the 30-month point. Conclusions: Sex-specific physiological recovery patterns were evident among vaccinated COVID-19 survivors. Males exhibited earlier metabolic and cardiac alterations, while females had more persistent endocrine and inflammatory shifts. These findings underscore the need for sex-tailored long-term monitoring strategies prioritizing early metabolic and cardiac screening in men and prolonged immunoendocrine surveillance in women
Scalable and low-power reversible logic for future devices: QCA and IBM-based gate realization
No full textOne such revolutionary approach to changing the nano-electronic landscape is integrating reversible logic with quantum dot technology that will replace the conventional complementary metal-oxide semiconductors (CMOS) circuits for ultra-high speed, low density, and energy-efficient digital designs. The implementation of the reversible structure under the most inflexible conditions, as executed by quantum laws, is a highly challenging task. Furthermore, the enormous occupying areas seriously compromise the accuracy of the output in quantum dot circuits. Because of this challenge, quantum circuits can be employed as fundamental building blocks in highperformance digital systems since their implementation has a key impact on overall system performance. This study discusses a paradigm shift in nanoscale digital design by using a 4 x 4 reversible gate that redefines the basis of efficiency and precision. This reversible gate is elaborately used in a reversible full-adder circuit, fully symbolizing the core of minimum area, ultra-low energy consumption, and perfect output accuracy. The proposed reversible circuits have been fully realized using quantum-dot cellular automata technology (QCA), simulated, and verified by the highly reliable tool such as Qiskit IBM and QCADesigner 2.0.3. Furthermore, simulations results demonstrated the superiority of the QCA-based proposed adder, which reduced occupied area by 7.14 %, and cell count by 11.57 %, respectively. This work resolves some problems and opens new boundaries toward the future of digital circuits by addressing the main challenges of stability and pushing the boundaries of reversible logic design
EDUCATIONAL ADMINISTRATION FACTORS AFFECTING EDUCATOR MOTIVATION IN CLINICAL EDUCATION: A QUALITATIVE STUDY
No full textObjective: This study aims to investigate and compare the educational management factors that affect the motivation of educators involved in clinical education at two medical faculties-one from a public university and the other from a foundation university. Material and Method: This study is based on a doctoral dissertation in Medical Education. Qualitative research methods were applied in the study. Participants were recruited from both-a foundation and a state university using the purposeful sampling method. Male and female faculty with the titles of professor, associate professor, and assistant professor from internal and surgical departments were included in the study. A total of 30 in-depth one-on-one interviews were conducted with 15 participants from each institution. Informed consent was obtained from all participants. Semi-structured forms were used during the interviews. All interviews were audio and video recorded. Thematic analysis method was employed to analyze the data. Results: Injustice in management and education administration; uncertainty and double standards in the rules, unclarity in operation and management processes, delayed decision-making, conflict between education and patient care services, lack of communication between the management and the faculty, lack of faculty and support staff in education, and a performance system that causes disadvantage to the educator are negative motivation factors. Conclusion: Ensuring justice in management and education administration; determining and complying with the rules, operation and management processes, fast and effective decision-making, organizing education and patient care services in a way that they do not hinder each other, a participatory and communicative approach in management, providing sufficient workforce at all levels in education, preventing the disadvantage of providing training in the performance system are among the first steps that should be taken to increase educator motivation in clinical education
Effect of structured pre-dialysis education on the clinical outcomes of kidney patients
No full textBackground The aim of this study is to evaluate the effect of pre-dialysis education on clinical, laboratory, quality of life, and self-care ability of patients on dialysis treatment. Methods This observational study recruited 202 patients (108 patients who received systematic pre-dialysis education; education group- and 94 patients who started dialysis without education; noneducation group). We evaluated and compared quality of life, self-care ability, psychological/depressive status, and biochemical parameters between groups. Results The education group had a significantly higher self-care score (98.3 +/- 8.5) (82.4 +/- 21.5, p < 0.001), lower depressive symptoms (2.8%, 0.9%, and 0.9%, respectively) compared with the non-education group (31.9%, 20.2%, and 2.8%, respectively, p < 0.001). Quality of life scale results were significantly higher in the education group (p < 0.001 for each). Phosphate, parathormone, BUN, and residual renal function level were significantly lower (p < 0.01), and haemoglobin was significantly higher (p < 0.01) compared to those in the non-education group. Conclusion Our study shows that systematic education practices in the pre-dialysis period were associated with improved quality of life, increased self-care ability, increased psychosocial well-being, and positive effects on clinical outcomes in dialysis patients
Unified Deep Learning Method for Accurate Brain Tumor Segmentation Using Vertical Voxel Grouping and Wavelet Features
No full textBrain tumor segmentation plays a vital role in medical imaging, enabling accurate diagnosis and guiding treatment decisions. Despite notable progress driven by deep neural networks (DNNs) and multi-parametric magnetic resonance imaging (mpMRI), the complexity and heterogeneity of tumor tissues make precise segmentation a persistent challenge. In this paper, we propose a novel method that integrates Vertically grouped Voxel Feature Extraction (VFE), wavelet-based multi-resolution detail enhancement, and a modified UNet-VGG16+ architecture. The VFE component enhances tumor region contrast and suppresses irrelevant background areas by grouping column-wise voxel intensities within each slice. As a result, the average image contrast is increased by 23.78%, thereby improving the ability of Deep Neural Networks (DNNs) to focus on tumor regions. The wavelet-based enhancement captures multi-resolution details to more clearly delineate tumor boundaries while also reducing noise. The UNet-VGG16+ architecture leverages transfer learning to efficiently process these enhanced features for accurate segmentation. Extensive experiments on the BraTS21 dataset demonstrate that the proposed method achieves a mean Dice score of 94.69%, with segmentation accuracies of 93.3%, 93.1%, and 94.4% for Enhancing Tumor (ET), Whole Tumor (WT), and Tumor Core (TC), respectively. Comparative evaluations show consistent and statistically significant improvements over state-of-the-art models (p< 0.001). Further validation on the BraTS18 dataset confirms the model's generalizability. These results highlight the effectiveness of combining spatially structured voxel aggregation with frequency-domain analysis for robust and high-precision brain tumor segmentation