Epilepsy Diagnosis from EEG Signals Using Continuous Wavelet Transform-Based Depthwise Convolutional Neural Network Model.

Epilepsy is a prevalent neurological disorder characterized by seizures that significantly impact individuals and their social environments. Given the unpredictable nature of epileptic seizures, developing automated epilepsy diagnosis systems is increasingly important. Epilepsy diagnosis traditionally relies on analyzing EEG signals, with recent deep learning methods gaining prominence due to their ability to bypass manual feature extraction.

A Comprehensive CNN Model for Age-Related Macular Degeneration Classification Using OCT: Integrating Inception Modules, SE Blocks, and ConvMixer.

: Age-related macular degeneration (AMD) is a significant cause of vision loss in older adults, often progressing without early noticeable symptoms. Deep learning (DL) models, particularly convolutional neural networks (CNNs), demonstrate potential in accurately diagnosing and classifying AMD using medical imaging technologies like optical coherence to-mography (OCT) scans. This study introduces a novel CNN-based DL method for AMD diagnosis, aiming to enhance computational efficiency and classification accuracy.

Sex differences in clinical and polysomnographic features of obstructive sleep apnea: The Turkish sleep apnea database (TURKAPNE) cohort.

Background: Previous reports from relatively small clinical cohorts have suggested that the clinical presentation of obstructive sleep apnea (OSA) differs between men and women.

Objective: We aimed to explore sex differences in clinical and polysomnographic features of OSA in a large nationwide registry.

Methods: Participants from the ongoing Turkish Sleep Apnea Database (TURKAPNE) Study from 34 centers were included in the current analysis.

Enhanced Panoramic Radiograph-Based Tooth Segmentation and Identification Using an Attention Gate-Based Encoder-Decoder Network.

Background: Dental disorders are one of the most important health problems, affecting billions of people all over the world. Early diagnosis is important for effective treatment planning. Precise dental disease segmentation requires reliable tooth numbering, which may be prone to errors if performed manually.

Temporal trajectory and left ventricular ejection fraction association of eight circulating biomarkers in first acute myocardial infarction patients: a 12-month prospective cohort study.

Aims: Our study aimed to explore the temporal trajectory of eight circulating biomarkers, measured serially over 12 months, in a prospective observational cohort of patients with acute myocardial infarction (AMI) and to investigate the association between these biomarkers and left ventricular ejection fraction (LVEF) during follow-up assessments.

Methods And Results: We enrolled 155 patients admitted for a first AMI requiring percutaneous coronary intervention (PCI). Baseline characteristics, laboratory test results, and cardiac ultrasound examinations were collected at pre-PCI (H0), immediately post-PCI (H24), at discharge (D3), and at 6 months (M6) and 12 months (M12) post-PCI.

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing.

A hybrid approach based on multipath Swin transformer and ConvMixer for white blood cells classification.

White blood cells (WBC) play an effective role in the body's defense against parasites, viruses, and bacteria in the human body. Also, WBCs are categorized based on their morphological structures into various subgroups. The number of these WBC types in the blood of non-diseased and diseased people is different.

Spatial-attention ConvMixer architecture for classification and detection of gastrointestinal diseases using the Kvasir dataset.

Gastrointestinal (GI) disorders, encompassing conditions like cancer and Crohn's disease, pose a significant threat to public health. Endoscopic examinations have become crucial for diagnosing and treating these disorders efficiently. However, the subjective nature of manual evaluations by gastroenterologists can lead to potential errors in disease classification.

Rationale and design of the PACIFIC-PRESERVED (PhenomApping, ClassIFication and Innovation for Cardiac dysfunction in patients with heart failure and PRESERVED left ventricular ejection fraction) study.

Background: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome that is poorly defined, reflecting an incomplete understanding of its pathophysiology.

Aim: To redefine the phenotypic spectrum of HFpEF.

Methods: The PACIFIC-PRESERVED study is a prospective multicentre cohort study designed to perform multidimensional deep phenotyping of patients diagnosed with HFpEF (left ventricular ejection fraction≥50%), patients with heart failure with reduced ejection fraction (left ventricular ejection fraction≤40%) and subjects without overt heart failure (3:2:1 ratio).

Structural EEG signal analysis for sleep apnea classification.

Objectives: Diagnosing the sleep apnea can be critical in preventing the person having sleep disorder from unhealthy results. The aim of this study is to obtain a sleep apnea scoring approach by comparing parametric and non-parametric power spectral density (PSD) estimation methods from EEG signals recorded from different brain regions (C4-M1 and O2-M1) for transient signal analysis of sleep apnea patients.

Methods: Power Spectral Density (PSD) methods (Burg, Yule-Walker, periodogram, Welch and multi-taper) are examined for the detection of apnea transition states including pre-apnea, intra-apnea and post-apnea together with statistical methods.

The PACIFIC ontology for heterogeneous data management in cardiology.

With the emergence of health data warehouses and major initiatives to collect and analyze multi-modal and multisource data, data organization becomes central. In the PACIFIC-PRESERVED (PhenomApping, ClassIFication, and Innovation for Cardiac Dysfunction - Heart Failure with PRESERVED LVEF Study, NCT04189029) study, a data driven research project aiming at redefining and profiling the Heart Failure with preserved Ejection Fraction (HFpEF), an ontology was developed by different data experts in cardiology to enable better data management in a complex study context (multisource, multiformat, multimodality, multipartners). The PACIFIC ontology provides a cardiac data management framework for the phenomapping of patients.

HCG18, LEF1AS1 and lncCEACAM21 as biomarkers of disease severity in the peripheral blood mononuclear cells of COVID-19 patients.

Background: Even after 3 years from SARS-CoV-2 identification, COVID-19 is still a persistent and dangerous global infectious disease. Significant improvements in our understanding of the disease pathophysiology have now been achieved. Nonetheless, reliable and accurate biomarkers for the early stratification of COVID-19 severity are still lacking.

Firalink: A bioinformatics pipeline for long non-coding RNA data analysis.

Summary: The Firalink bioinformatics pipeline has been developed to analyse long non-coding RNA (lncRNA) data generated by targeted sequencing. This pipeline has been first implemented for use with the FIMICS panel containing 2906 lncRNAs useful for investigations in cardiovascular disease. It has been subsequently tested and validated using a panel of lncRNAs targeting brain disease.

An evaluation of the use of inhalers in asthma and chronic obstructive pulmonary disease.

Objectives: Inhaled therapy is the treatment of choice for obstructive lung diseases such as asthma and chronic obstructive pulmonary disease (COPD). However, the maximum benefit from such therapy depends on the correct use of inhaler devices. In this study, our primary aim was to evaluate inhaler techniques in patients with asthma and COPD in order to identify common errors.

FIMICS: A panel of long noncoding RNAs for cardiovascular conditions.

Cardiovascular disorders such as heart failure are leading causes of mortality. Patient stratification via identification of novel biomarkers could improve management of cardiovascular diseases of complex etiologies. Long-noncoding RNAs (lncRNAs) are highly tissue-specific in nature and have emerged as important biomarkers in human diseases.

Association of miR-144 levels in the peripheral blood with COVID-19 severity and mortality.

Coronavirus disease-2019 (COVID-19) can be asymptomatic or lead to a wide symptom spectrum, including multi-organ damage and death. Here, we explored the potential of microRNAs in delineating patient condition and predicting clinical outcome. Plasma microRNA profiling of hospitalized COVID-19 patients showed that miR-144-3p was dynamically regulated in response to COVID-19.

Evaluation of transcutaneous carbon dioxide and saturation monitoring during fiberoptic bronchoscopy.

Introduction: The aim of the study was to assess the effects of interventions during bronchoscopy on ventilation and determine the risk factors for hypoventilation related to both interventions and patients' demographical and clinical characteristics.

Materials And Methods: A total of 74 patients who underwent fiberoptic bronchoscopy (FOB) were included in the study. Oxygen saturation (SpO2) and partial carbon dioxide pressure (PCO2) were measured transcutaneously (TcSO2 and TcPCO2) using a sensor consisting of a probe placed on the earlobe.

The effectiveness of oropharyngeal exercises compared to inspiratory muscle training in obstructive sleep apnea: A randomized controlled trial.

Background: Inspiratory muscle training (IMT) and oropharyngeal exercises (OE) have different advantages and disadvantages and a comparison of these modalities has been recommended. The aim of this study was to compare the effects of IMT and OE on important outcomes for patients with OSAS.

Methods: This was a randomized controlled clinical trial.

Pentraxin 3 in primary percutaneous coronary intervention for ST elevation myocardial infarction is associated with early irreversible myocardial damage : Kinetic profile, relationship to interleukin 6 and infarct size.

Background: The inflammatory marker long pentraxin 3 (PTX3) has been shown to be a strong predictor of 30-day and one-year mortality after acute myocardial infarction. The aim of this study was to evaluate the kinetic profile of PTX3 and its relationship with interleukin 6 (IL-6), high-sensitive C-reactive protein (hs-CRP) and infarct size.

Methods: PTX3, IL-6 and hs-CRP were measured at predefined time points, at baseline (before percutaneous coronary intervention (PCI)), at 12 and 72 hours after PCI in 161 patients with first-time ST elevation myocardial infarction (STEMI).

Biomarkers Associated with Atrial Fibrillation in Patients with Ischemic Stroke: A Pilot Study from the NOR-FIB Study.

Background And Purpose: Cardioembolic stroke due to paroxysmal atrial fibrillation (AF) may account for 1 out of 4 cryptogenic strokes (CS) and transient ischemic attacks (TIAs). The purpose of this pilot study was to search for biomarkers potentially predicting incident AF in patients with ischemic stroke or TIA.

Methods: Plasma samples were collected from patients aged 18 years and older with ischemic stroke or TIA due to AF (n = 9) and large artery atherosclerosis (LAA) with ipsilateral carotid stenosis (n = 8) and age- and sex-matched controls (n = 10).

Extensive Exposure to Tear Gases in Ankara.

Objectives: The most common chemical substances used as mass control agents are chloroacetophenone, chlorobenzylidene malononitrile, and oleoresin capsicum. These agents not only have local and rapid effects but also have systemic and long-term effects. The aim of the present study was to discuss the patterns of tear gas exposure and to investigate its effects on respiratory functions.

MicroRNAs: Key Regulators to Understand Osteoclast Differentiation?

MicroRNAs (miRNAs) are small non-coding single-stranded RNAs that represent important posttranscriptional regulators of protein-encoding genes. In particular, miRNAs play key roles in regulating cellular processes such as proliferation, migration, and cell differentiation. Recently, miRNAs emerged as critical regulators of osteoclasts (OCs) biology and have been involved in OCs pathogenic role in several disorders.