Association of Apolipoprotein C-III Gene Polymorphisms (rs2854116 and rs2854117) with Susceptibility to Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) in a Turkish Population.

: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the accumulation of fat in the liver, progressing from simple steatosis to various complications, with increasing prevalence in the modern world. Our study aimed to investigate the relationship between MASLD pathogenesis and the presence of apolipoprotein C-III (ApoC-III) gene variants rs2854116 and rs2854117 by comparing allele and genotype frequencies between MASLD patients and healthy individuals, as well as analyzing their association with biochemical parameters in Turkish populations. : The study included 202 MASLD patients and 100 healthy controls who presented to our outpatient clinic.

Investigation of prolonged PCR positivity in COVID-19 patients.

This study aimed to investigate prolonged severe acute respiratory syndrome coronavirus-2 polymerase chain reaction (PCR) positivity in hospitalized COVID-19 patients and evaluate the diagnostic performance of rapid antigen tests (RAgT) compared to real-time reverse transcription-PCR (RT-PCR). A prospective single-center study included 82 patients with prolonged PCR positivity (≥28 days). Serial RT-PCR and RAgT were performed at days 7 to 10, 14 to 20, and 28 to 30 post-diagnosis.

Radiologic and Clinical Correlates of Long-Term Post-COVID-19 Pulmonary Sequelae.

: The long-term sequelae of COVID-19 pneumonia, particularly the persistence of imaging abnormalities and their relationship to clinical symptoms, remain unclear. While the acute radiologic patterns are well-documented, the transition to chronic pulmonary changes-and their implications for long COVID symptoms-require systematic investigation. : Our study included 93 patients with moderate to severe COVID-19 pneumonia who were admitted to Istanbul Medical Faculty Hospital, each having one follow-up CT scan over a ten-month period.

Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs.

Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs), pancreatic cysts requiring surgery, from low-risk lesions remains a clinical challenge, often resulting in unnecessary procedures due to limited specificity of current methods. While radiomics and deep learning (DL) have been explored for pancreatic cancer, cyst-level malignancy risk stratification of IPMNs remains untapped. We conducted a multi-institutional study (seven centers, 359 T2W MRI images) to assess the feasibility of AI for predicting IPMN dysplasia grade using cyst-level image features.

Ethical framework for responsible foundational models in medical imaging.

The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection, diagnosis, and treatment planning. These large-scale artificial intelligence systems, trained on extensive multimodal and multi-center datasets, demonstrate remarkable versatility across diverse medical applications. However, their integration into clinical practice presents complex ethical challenges that extend beyond technical performance metrics.

Large Scale MRI Collection and Segmentation of Cirrhotic Liver.

Liver cirrhosis represents the end stage of chronic liver disease, characterized by extensive fibrosis and nodular regeneration that significantly increases mortality risk. While magnetic resonance imaging (MRI) offers a non-invasive assessment, accurately segmenting cirrhotic livers presents substantial challenges due to morphological alterations and heterogeneous signal characteristics. Deep learning approaches show promise for automating these tasks, but progress has been limited by the absence of large-scale, annotated datasets.

Persistent neurocognitive deficits in long COVID: Evidence of structural changes and network abnormalities following mild infection.

This study aimed to investigate the neurocognitive deficits, structural brain alterations, and network abnormalities in individuals who had a mild SARS-CoV-2 infection, with and without brain fog, as a symptom of long COVID. A cross-sectional study was conducted involving 75 participants, categorized into three groups: 24 healthy controls (HCs), 26 COVID-19 survivors without brain fog (woFOG), and 25 with brain fog (wFOG). Neuropsychological assessments included the Free and Cued Selective Reminding Test (FCSRT) and Addenbrooke's Cognitive Examination-Revised (ACE-R).

Metabolic syndrome and effect of gene polymorphisms: ADIPOQ, AGT, AGTR1, AGTR2, ApoC-III, NR3C1 and GNB3 gene polymorphisms.

Background: Metabolic syndrome (MetS) is defined as a metabolic dysfunction characterized by the co-occurrence of multiple risk factors. Our study aimed to elucidate the effects of ADIPOQ rs266729, rs17300539, and rs2241766, AGT rs699 and rs4762, AGTR1 rs5186, AGTR2 rs11091046, ApoC-III rs2854116 and rs2854117, NR3C1 rs10052957 and rs41423247, and GNB3 rs5443 gene polymorphisms on MetS.

Methods And Results: A total of 200 patients who met the diagnostic criteria for MetS at the Internal Medicine Outpatient Clinic of Istanbul University, Faculty of Medicine, between 01.

Detection of Peri-Pancreatic Edema using Deep Learning and Radiomics Techniques.

Pancreatitis is a major public health issue world-wide; studies show an increase in the number of people experiencing pancreatitis. Identifying peri-pancreatic edema is a pivotal indicator for identifying disease progression and prognosis, emphasizing the critical need for accurate detection and assessment in pancreatitis diagnosis and management. This study introduces a novel CT dataset sourced from 255 patients with pancreatic diseases, featuring annotated pancreas segmentation masks and corresponding diagnostic labels for peri-pancreatic edema condition.

DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Model.

Large-scale, big-variant, high-quality data are crucial for developing robust and successful deep-learning models for medical applications since they potentially enable better generalization performance and avoid overfitting. However, the scarcity of high-quality labeled data always presents significant challenges. This paper proposes a novel approach to address this challenge by developing controllable diffusion models for medical image synthesis, called DiffBoost.

The simpler modified fried frailty scale predicts 2-year mortality in older adults with heart failure: a pilot study.

Objective: The Simpler Modified Fried Frailty Scale (SMFFS) has recently been developed from the original Fried scale to ease its use in clinical practice, by transforming the items requiring measurements into the self-reported inquiries. Its predictive validity needs to be clarified, especially in populations with a high prevalence of frailty, such as patients with heart failure (HF). Primary aim of this study is to find out the prevalence of frailty in older patients with HF by using SMFFS and show its concordance with other frailty assessment tools.

Advances for Managing Pancreatic Cystic Lesions: Integrating Imaging and AI Innovations.

Pancreatic cystic lesions (PCLs) represent a spectrum of non-neoplasms and neoplasms with varying malignant potential, posing significant challenges in diagnosis and management. While some PCLs are precursors to pancreatic cancer, others remain benign, necessitating accurate differentiation for optimal patient care. Conventional approaches to PCL management rely heavily on radiographic imaging, and endoscopic ultrasound (EUS) guided fine-needle aspiration (FNA), coupled with clinical and biochemical data.

Foundational artificial intelligence models and modern medical practice.

Our opinion piece pays homage to the evolution of medical practices, tracing back to the era of Hippocrates, through significant historical milestones, and drawing parallels with the principles underpinning foundational artificial intelligence (AI) models. It emphasizes the shared ethos of both domains: a commitment to comprehensive care that values diverse data integration and individualized patient treatment. The excitement surrounding foundation models in medical imaging is understandable.

Large-scale multi-center CT and MRI segmentation of pancreas with deep learning.

Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-based pancreatic segmentation is more established, MRI-based segmentation methods are understudied, largely due to a lack of publicly available datasets, benchmarking research efforts, and domain-specific deep learning methods. In this retrospective study, we collected a large dataset (767 scans from 499 participants) of T1-weighted (T1 W) and T2-weighted (T2 W) abdominal MRI series from five centers between March 2004 and November 2022.

LEP rs7799039 and LEPR rs1137101 gene variants are not associated with clinical features in patients with metabolic syndrome in the Turkish population.

Objectives: Genetic predisposition plays a role in the etiology of metabolic syndrome (MetS), an important health problem worldwide. Leptin (LEP), produced by adipose tissue, plays a crucial role in the development of MetS. In this study, we evaluated the effects of LEP and LEP receptor (LEPR) variants on clinical findings and risk of developing MetS in the Turkish population.

Cognitive deficits and cortical volume loss in COVID-19-related hyposmia.

Background And Purpose: Studies have found that up to 73% of COVID-19 patients experience hyposmia. It is unclear if the loss of smell in COVID-19 is due to damage to the peripheral or central mechanisms. This study aimed to explore the impacts of COVID-19-induced hyposmia on brain structure and cognitive functions.

Evaluation of SARS-CoV-2-Positive Patients with Suspected Reinfection.

The aim of this study was to investigate the reinfection rates and characteristics of SARS-CoV-2 in individuals with SARS-CoV-2 RNA present in their clinical specimens for COVID-19. Our data from the COVID-19 Laboratory of Istanbul University were analyzed for 27,240 cases between 27 March 2020 to 8 February 2022. Demographic characteristics, vaccination statuses, comorbidities, and laboratory findings were evaluated in cases with suspected reinfection, as determined by the presence of SARS-CoV-2 RNA at a rate of 0.

Relationship between Psychological Resilience, Perceived Stress, Death Anxiety and Progression of Disease in Individuals with COVID-19.

Introduction: This study examines the association between perceived stress, death anxiety, psychological resilience and the sociodemographic and clinical features of patients with Coronavirus Disease 2019 (COVID-19).

Methods: 304 patients with COVID-19 diagnosis, who were admitted to İstanbul University İstanbul Faculty of Medicine Hospital "COVID-19 Patients Monitoring Center" were recruited. No sample selection was made, all the patients who were followed up and treated in the center were included.

The effect of DNA repair gene variants on COVID-19 disease: susceptibility, severity, and clinical course.

Oxidative stress (OS), which leads to DNA damage, plays a role in the pathogenesis of Coronavirus disease 2019 (COVID-19). We aimed to evaluate the role of DNA repair gene variants [X-ray repair cross complementing 4 () rs28360071, rs6869366, and X-ray cross-complementary gene 1 ( rs25487] in susceptibility to COVID-19 in a Turkish population. We also evaluated its effect on the clinical course of the disease.

The suppressor of cytokine signaling-1 () gene polymorphism and promoter methylation correlate with the course of COVID-19.

The suppressor of the cytokine signaling-1 (SOCS1) gene is a short sequence located on chromosome 16 that functions to induce an appropriate immune response and is an essential physiological regulator of interferon (IFN) signaling. In addition to comparing the global DNA and SOCS1 gene promoter methylation status between our patients with coronavirus disease 2019 (COVID-19) and healthy controls, this study demonstrates the effect of the SOCS1 rs33989964 polymorphism on patients with COVID-19. The study group included 139 patients diagnosed with COVID-19 in our hospital's clinics between June and December 2020, and the control group included 78 healthy individuals.