The Effect of Aromatherapy Massage on Cramp Frequency, Pain Intensity, and Quality of Life in Hemodialysis Patients With Muscle Cramps: A Randomized, Placebo-Controlled, Mixed Study.

Muscle cramps, which are frequently encountered in hemodialysis patients, affect individuals bio-psycho-socially, limit their activities of daily living, and reduce their quality of life. In this study, we aimed to evaluate the effects of aromatherapy massage applied in 12 sessions over 4 weeks on cramp frequency, pain severity, and quality of life. The study was conducted as a pretest-posttest, randomized controlled, and single-blinded using a quantitative and qualitative research design.

Efficacy of transbronchial biopsy and frequency of pneumothorax in lung transplant recipients: single center experience.

Objective: Bronchoscopy plays a critical role in the diagnosis and management of lung transplant recipients. We retrospectively evaluated the safety, complications, and efficacy of transbronchial biopsy (TBB) in detecting and grading early rejection.

Materials And Methods: We retrospectively assessed the complications associated with TBB and the adequacy of pathological diagnoses in patients who underwent lung transplantation at Koşuyolu Yüksek İhtisas Training and Research Hospital from December 1, 2016, to April 30, 2023.

Navigating Gynecological Oncology with Different Versions of ChatGPT: A Transformative Breakthrough or the Next Black Box Challenge?

Introduction: The study evaluates the performance of large language model (LLM) versions of ChatGPT-ChatGPT-3.5, ChatGPT-4, and ChatGPT-Omni-in addressing inquiries related to the diagnosis and treatment of gynecological cancers, including ovarian, endometrial, and cervical cancers.

Methods: A total of 804 questions were equally distributed across four categories: True/False, Multiple-Choice, Open-Ended, and Case-scenario, with each question type representing varying levels of complexity.

Cardioish: Lead-Based Feature Extraction for ECG Signals.

Electrocardiography (ECG) signals are commonly used to detect cardiac disorders, with 12-lead ECGs being the standard method for acquiring these signals. The primary objective of this research is to propose a new feature engineering model that achieves both high classification accuracy and explainable results using ECG signals. To this end, a symbolic language, named Cardioish, has been introduced.

ChMinMaxPat: Investigations on Violence and Stress Detection Using EEG Signals.

Background And Objectives: Electroencephalography (EEG) signals, often termed the letters of the brain, are one of the most cost-effective methods for gathering valuable information about brain activity. This study presents a new explainable feature engineering (XFE) model designed to classify EEG data for violence detection. The primary objective is to assess the classification capability of the proposed XFE model, which uses a next-generation feature extractor, and to obtain interpretable findings for EEG-based violence and stress detection.

Triglyceride-glucose index in patients with non-functioning adrenal incidentaloma, cortisol-secreting adrenal incidentaloma and healthy controls.

Objective: Cushing's syndrome increases the risk of cardiovascular disease. The triglyceride-glucose (TyG) index has been linked to an increased risk of cardiometabolic disorders. Whether patients with non-functioning adrenal incidentaloma (NFAI) or cortisol-secreting adrenal incidentaloma (CSAI) have altered TyG index is unknown.

Exploring the impact of developmental dysplasia of the hip on refugees with temporary protected status in Türkiye.

Objective: In this study, we examined whether there was a change in the number of children who had been screened by hip ultrasound, the age of first diagnosis, and the number of invasive and conservative treatments applied due to developmental dysplasia of the hip between 2016 and 2022 among refugees who were in "Temporary Protection Status" in Türkiye?

Methods: The records were collected via the e-health database of the Turkish Ministry of Health. Over 1 month old were included in the study.

Results: The number of ultrasonography (USG) that was performed for developmental dysplasia of the hip survey had significantly increased over time.

Utilization of AI - reshaping the future of food safety, agriculture and food security - a critical review.

Artificial intelligence is an emerging technology which harbors a suite of mechanisms that have the potential to be leveraged for reaping value across multiple domains. Lately, there is an increased interest in embracing applications associated with Artificial Intelligence to positively contribute to food safety. These applications such as machine learning, computer vision, predictive analytics algorithms, sensor networks, robotic inspection systems, and supply chain optimization tools have been established to contribute to several domains of food safety such as early warning of outbreaks, risk prediction, detection and identification of food associated pathogens.

Impact of right-sided breast cancer adjuvant radiotherapy on the liver.

Background: In patients with right-sided breast cancer the liver can be partially irradiated during adjuvant radiotherapy (RT). We aimed to determine breast cancer RT effects on liver using with magnetic resonance elastography (MRE) and biological results.

Patients And Methods: This retrospective study enrolled 34 patients diagnosed with right-sided breast cancer who underwent adjuvant RT.

Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals.

Electroencephalography (EEG) signals provide information about the brain activities, this study bridges neuroscience and machine learning by introducing an astronomy-inspired feature extraction model. In this work, we developed a novel feature extraction function, black-white hole pattern (BWHPat) which dynamically selects the most suitable pattern from 14 options. We developed BWHPat in a four-phase feature engineering model, involving multileveled feature extraction, feature selection, classification, and cortex map generation.

QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals.

The most cost-effective data collection method is electroencephalography (EEG), which obtains meaningful information about the brain. Therefore, EEG signal processing is crucial for neuroscience and machine learning (ML). Therefore, a new EEG stress dataset has been collected, and an explainable feature engineering (XFE) model has been proposed using the Directed Lobish (DLob) symbolic language.

TATPat based explainable EEG model for neonatal seizure detection.

The most cost-effective data collection method is electroencephalography (EEG) to obtain meaningful information about the brain. Therefore, EEG signal processing is very important for neuroscience and machine learning (ML). The primary objective of this research is to detect neonatal seizures and explain these seizures using the new version of Directed Lobish.

MetaWise: Combined Feature Selection and Weighting Method to Link the Serum Metabolome to Treatment Response and Survival in Glioblastoma.

Glioblastoma (GBM) is a highly malignant and devastating brain cancer characterized by its ability to rapidly and aggressively grow, infiltrating brain tissue, with nearly universal recurrence after the standard of care (SOC), which comprises maximal safe resection followed by chemoirradiation (CRT). The metabolic triggers leading to the reprogramming of tumor behavior and resistance are an area increasingly studied in relation to the tumor molecular features associated with outcome. There are currently no metabolomic biomarkers for GBM.

: a computer tool at the Bilbao Crystallographic Server for the study of pseudo-symmetric or distorted structures.

is a free online program at the Bilbao Crystallographic Server (https://www.cryst.ehu.

Towards dynamically configured databases for CIFs: the new modulated structures open database at the Bilbao Crystallographic Server.

This article presents a web-based framework to build a database without in-depth programming knowledge given a set of CIF dictionaries and a collection of CIFs. The framework consists of two main elements: the public site that displays the information contained in the CIFs in an ordered manner, and the restricted administrative site which defines how that information is stored, processed and, eventually, displayed. Thus, the web application allows users to easily explore, filter and access the data, download the original CIFs, and visualize the structures via .

Management of airway complications following lung transplantation: first interventional bronchoscopy report from Türkiye.

Background/aim: Lung transplantation is the treatment of last resort for many chronic lung diseases. Airway complications (AC) following lung transplantation, such as bronchial stenosis, dehiscence, malacia, and fistula, account for frequent hospital admissions, additional treatment costs, decreased quality of life, and reduced survival rates. Beyond surgical and medical preventive efforts, interventional bronchoscopy (IB) can be used in the management of these complications.

Relationship between functional status and fatigue after COVID-19 infection: a multicenter study from Türkiye.

Background/aim: Symptoms of COVID-19 may persist for months. One of the persistent symptoms of COVID-19 is fatigue, which reduces functional status. The relationship between fatigue, functional status, and various other factors has received little attention, which this study aims to address.

Lobish: Symbolic Language for Interpreting Electroencephalogram Signals in Language Detection Using Channel-Based Transformation and Pattern.

Electroencephalogram (EEG) signals contain information about the brain's state as they reflect the brain's functioning. However, the manual interpretation of EEG signals is tedious and time-consuming. Therefore, automatic EEG translation models need to be proposed using machine learning methods.

Sensitivity of frozen section analysis in patients with ovarian adult granulosa cell tumor, a multi-center study.

Introduction: We aimed to demonstrate the sensitivity of frozen section for patients with adult granulosa cell tumor (AGCT) and analyze the clinico-pathological factors that may be associated with sensitivity.

Material Methods: This is a multicenter study including data of 10 Gynecological Oncology Departments. Frozen-section results of patients who had ovarian AGCT at the final pathology report were retrospectively analyzed.

Sedentary behavior and associated factors on admissions to internal medicine wards.

The relationship between sedentary lifestyle and chronic diseases is well known. This study examined the prevalence and factors associated with reduced physical activity (PA) among internal medicine inpatients on admission. In this single-center, cross-sectional study, inpatients aged 50 years or older were prospectively enrolled at a tertiary care facility in Ankara, Türkiye.

Development of a reusable polymeric fluorescence sensor based on acryloyl β-cyclodextrin for the determination of aflatoxin B in grain products.

AFB1 is a harmful substance that can be found in agricultural products and can seriously affect human health, even in trace amounts. Therefore, monitoring AFB1 levels to ensure food safety and protect public health is crucial. New, highly reliable, selective, and rapid detection methods are needed to achieve this goal.