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Investigation of the Virulence Factors of Enterococcus Strains Isolated from Seawater
No full textThis study aimed to investigate the antimicrobial resistance and virulence factors of Enterococci isolated from seawater using both phenotypic and genotypic methods. A comparison of the phenotypic virulence factors between Enterococcus faecalis and Enterococcus faecium strains revealed that gelatinase activity was 91.3% and 89.5%, respectively. Caseinase activity was observed at rates of 65.2% for E. faecalis and 31.5% for E. faecium. The capacity for strong adhesion in biofilm formation was 41.3% in E. faecalis and 42.1% in E. faecium. Serum resistance activity was noted at 54.3% for E. faecalis and 31.6% for E. faecium. Remarkably, hemagglutination activity showed a strong activity in 39.1% of E. faecalis strains, while E. faecium exhibited 0% activity. Antibacterial activity against Staphylococcus aureus ATCC 25923 was 32.6% for E. faecalis and 5.3% for E. faecium, and against Escherichia coli ATCC 25922, the activity was 23.9% and 0%, respectively. It was determined that one E. faecalis strain (2.17%) and one Enterococcus gallinarum strain (100%) contained at least four resistance genes. Additionally, one E. faecalis strain (2.17%) harbored up to 11 of the 12 tested antibiotic resistance genes. Notably, two E. faecalis strains (3.03%) exhibited the most virulent characteristics, encompassing 12 virulence gene regions. In contrast, one E. gallinarum strain (100%) manifested the least virulent characteristics, comprising three virulence gene regions. These findings indicate that marine Enterococci could pose a public health threat, necessitating ongoing surveillance.Funding Agency : İstanbul University.
Grant Number : 25252
HPV, EBV, CMV, and HSV in Head and Neck Cancer: Molecular Detection, Seroprevalence, and Clinical Correlations
Get PDF(1) Background: This study investigated the presence of human papillomavirus (HPV), HPV genotypes, Epstein-Barr virus (EBV), cytomegalovirus (CMV) and herpes simplex virus (HSV) in patients with Head and Neck Cancer (HNC) at both molecular and serological levels. (2) Methods Fifty patients with histopathologically confirmed HNC who were admitted to the Department of Otorhinolaryngology, Istanbul Faculty of Medicine. Viral DNA was detected using quantitative real-time PCR, and serological IgM and IgG antibodies were analyzed using the CMIA method; (3) Results: In blood samples, CMV and HSV DNA were not detected, whereas EBV DNA was identified in 2% and HPV DNA in 4% of patients. In tumor tissues, CMV DNA was detected in 8%, EBV DNA in 10%, and HPV DNA in 6%; HSV DNA is 6%. HPV genotypes 18, 45, and 69 were found in tissue samples. Serologically, IgG positivity for CMV, EBV, and HSV-1 exceeded 90%, whereas IgM positivity was low and not statistically significant; (4) Conclusions: HPV, EBV, and CMV DNA were detected at low frequencies in patients with HNC, while HSV DNA was absent. These findings underline the need for larger multi-center studies and support the consideration of routine viral screening, particularly for HPV, in specific tumor subtypes.Funding agency: Istanbul University.
Grant number: 40491
Feeding Challenges in Children With Down Syndrome: The Role of Aspiration and Clinical Subgroups
No full textBackground: Feeding difficulties, including aspiration risk, are common in children with Down syndrome. Identifying factors affecting feeding modality is crucial. Method: This cross-sectional study included 335 children with Down syndrome (aged 4–12 years; mean 5.2). Feeding was assessed using the Functional Oral Intake Scale (FOIS), the Screening Tool of Feeding Problems (STEP), and clinical observation. Aspiration risk was identified through STEP items and clinician evaluation. FOIS scores categorised feeding as oral or non-oral. Results: Of participants, 74.1% were oral feeders and 25.9% received non-oral nutrition. Aspiration risk was present in 33.7%. Cluster analysis revealed distinct subgroups defined by aspiration, oral sensory issues, and behavioural problems. Younger age was significantly associated with higher aspiration risk (OR = 0.38, p = 0.001). Conclusions: Aspiration risk influences feeding modality and subgroup characteristics. Early multidisciplinary assessment is essential, especially for younger children, to detect risk and guide safe, individualised feeding strategies
Use of autologous whole blood clot for hard-to-heal diabetic foot ulcers: a case series
No full textObjective: Diabetic foot ulcers (DFUs) are a severe complication of diabetes, contributing significantly to patient morbidity, healthcare costs and amputations. Current treatment approaches often fall short in addressing the challenges posed by hard-to-heal (chronic) wounds. This study evaluates the efficacy of autologous whole blood clot (AWBC) therapy in treating hard-to-heal DFUs.
Method: Patients with hard-to-heal DFUs who were unresponsive to previous treatments were included in this case series. Prior to AWBC application, the wounds underwent debridement and cleansing of the wound bed. For the treatment, 18ml of blood was drawn from the patients to create the clot placed on the wound. Patients were evaluated weekly for wound healing progress.
Results: AWBC treatment was initiated in 20 patients, resulting in an average wound size reduction of 59% (p<0.001). The mean number of applications per patient was 5.3±1.5. Adverse events included contact dermatitis in one patient and discontinuation by another due to slower-than-expected healing.
Conclusion: The results of this case series underscore AWBC's potential to restore the wound healing cascade by mimicking the extracellular matrix and promoting re-epithelialisation, angiogenesis and macrophage phenotype transition. AWBC represents a promising, cost-effective solution for DFU management, particularly in patients with complex comorbidities
Comparative prognostic performance of the FIB-4 index versus SYNTAX and GRACE scores in predicting major cardiovascular events in acute coronary syndrome
Get PDFIntroduction: The Fibrosis-4 (FIB-4) index, a non-invasive marker of liver fibrosis originally developed for non-alcoholic fatty liver disease (NAFLD), has gained attention for its prognostic value in cardiovascular disease. Aim: Given the shared metabolic risk between NAFLD and acute coronary syndrome (ACS), this study aimed to evaluate the association between FIB-4 and major adverse cardiovascular events (MACE) in patients with ACS, in comparison with conventional risk scores. Material and methods: This is an observational cohort study included 941 patients hospitalized with ACS between 2017 and 2021. Patients were classified into three FIB-4 categories: low, < 1.45; intermediate, 1.45–3.25; and high, ≥ 3.25. Clinical, laboratory, angiographic, and echocardiographic data were collected. MACE incidence was evaluated over a median follow-up of 67.5 months. Cox regression and receiver operating characteristic (ROC) analyses were performed. Results: MACE occurred in 37.9% of patients in the high FIB-4 group, compared to 28.7% and 29.2% in the low and intermediate groups, respectively (p = 0.046). FIB-4 was an independent predictor of MACE (hazard ratio [HR]: 1.547; 95% CI: 1.169–2.046; p = 0.002). ROC analysis demonstrated superior prognostic accuracy for FIB-4 (area under the ROC curve: 0.693) over SYNTAX (0.609) and GRACE (0.552) scores. A Kaplan-Meier analysis showed significantly lower survival in the high FIB-4 group (p = 0.007). Conclusions: The FIB-4 index is a robust, accessible predictor of adverse cardiovascular outcomes in ACS and may enhance conventional risk stratification strategies by integrating systemic metabolic burden into cardiovascular risk assessment
A machine learning assisted designing and chemical space generation of benzophenone based organic semiconductors with low lying LUMO energies
No full textCurrent study presents a machine learning (ML) approach to design benzophenone-based organic chromophore with their lowest possible LUMO energy (ELUMO). A dataset of their 1142 donors is collected from literature and their molecular descriptors are designed by using RDKit. Among various models, the Random Forest regression model produces accurate results to predict their ELUMO values. Based on these predictions, their 5000 new donors are designed with their Synthetic Accessibility Likelihood Index (SALI) scores. Their SHAP value analysis reveals that their electro topological state indices are the most critical descriptors to lowering ELUMOs. The top- performing donor are further extended with acceptors and their photovoltaic (PV) properties by density functional theory (DFT). Their results show their maximum open-circuit voltage (Voc) of 2.30 V, a short-circuit current (Jsc) of 47.19 mA/cm2, and a light-harvesting efficiency (LHE) of 93 %. This study demonstrates the potential of ML assisted design to design new organic chromophores.Funding agency : Taif University
Grant number : TU-DSPP-2024-9
Combating chronic kidney disease-associated cachexia: A literature review of recent therapeutic approaches
No full textIn 2008, the Society on Sarcopenia, Cachexia, and Wasting Disorders introduced a generic definition for all types of cachexia: "a complex metabolic syndrome associated with the underlying illness characterized by a loss of muscle, with or without fat loss". It is well-known that the presence of inflammatory burden in end-stage renal disease (ESRD) patients may lead to the evolution of cachexia. Since the etiology of cachexia in chronic kidney disease (CKD) is multifactorial, thus the successful treatment must involve several concomitant measures (nutritional interventions, appetite stimulants, and anti-inflammatory pharmacologic agents) to provide integrated effective therapeutic modalities to combat causative factors and alleviate the outcomes of patients. Given the high mortality rate associated with cachexia, developing new therapeutic modalities are prerequisite for ameliorating patients with CKD worldwide. The present review aims to discuss some therapeutic strategies and provide an update on advances in nutritional approaches to counteract cachexia
Advancements in telehealth: enhancing breast cancer detection and health automation through smart integration of IoT and CNN deep learning in residential and healthcare settings
Get PDFThe rapid evolution of telehealth, or telemedicine, has spurred crucial technological advancements aimed at addressing the early stages of complex cancer conditions, where conventional diagnostic methods face challenges. This research introduces a cancer detection system that utilizes Internet of Things (IoT)-based patient records and machine learning. The primary objective is to automate real-time breast cancer monitoring and detection in residential institutions and smart hospitals, thus enhancing the delivery of quality cancer healthcare. Background: Traditional diagnostic methods, particularly physical inspection, exhibit inherent limitations in identifying breast cancer at early stages. This research responds to this challenge by leveraging innovative technologies, such as IoT and deep learning-based techniques, to overcome the constraints of conventional approaches. Objective: The primary goal of this study is to develop and implement a cancer detection system that integrates IoT-based patient records and machine learning for real-time breast cancer monitoring in residential and healthcare settings. Method: The research employs a synergistic combination of IoT technology for collecting images of residential users and Convolutional Neural Network (CNN), a deep learning technique, for early cancer prediction. The focus lies on contributing to the overall well-being of individuals who may unknowingly be living with cancer. Result: Simulated outcomes after 25 epochs are presented, emphasizing the training accuracy of the model and its validation accuracy using the proposed VGG16 classifier. Graphical representations of the results indicate consistent performance metrics, with both validation and training accuracy exceeding 99%. Specifically, the training accuracy measures at an impressive 99.64%, while the validation accuracy stands at 99.12%. Main Findings: The study demonstrates the effectiveness of the integrated IoT and deep learning techniques in achieving high accuracy rates for early breast cancer prediction. The findings affirm the potential of this approach to assist dermatologists in identifying breast malignancies at treatable stages. Conclusion: This research establishes a foundational framework for the integration of IoT and deep learning techniques, presenting a promising avenue for advancing early cancer detection in smart healthcare systems. The proposed cancer detection system holds significant potential for improving healthcare outcomes and contributing to the overall well-being of individuals at risk of breast cancer
Cognitive impairment in CKD patients: a guidance document by the CONNECT network
No full textCognitive impairment is a prevalent and debilitating complication in patients with chronic kidney disease (CKD). This position paper, developed by the Cognitive Decline in Nephro-Neurology: European Cooperative Target network, provides guidance on the epidemiology, risk factors, pathophysiology, diagnosis and clinical management of CKD-related cognitive impairment. Cognitive impairment is significantly more common in CKD patients compared with the general population, particularly those undergoing haemodialysis. The development of cognitive impairment is influenced by a complex interplay of factors, including uraemic neurotoxins, electrolytes and acid-base disorders, anaemia, vascular damage, metabolic disturbances and comorbidities like diabetes and hypertension. Effective screening and diagnostic strategies are essential for early identification of cognitive impairment utilizing cognitive assessment tools, neuroimaging and circulating biomarkers. The impact of various drug classes, including antiplatelet therapy, oral anticoagulants, lipid-lowering treatments and antihypertensive drugs, on cognitive function is evaluated. Management strategies encompass pharmacological and non-pharmacological interventions, with recommendations for optimizing cognitive function while managing CKD-related complications. This guidance highlights the importance of addressing cognitive impairment in CKD patients through early detection, careful medication management and tailored therapeutic strategies to improve patient outcomes
The interface of depression and diabetes: treatment considerations
No full textThis state-of-the-art review explores the relationship between depression and diabetes, highlighting the two-way influences that make treatment challenging and worsen the outcomes of both conditions. Depression and diabetes often co-occur and share genetic, lifestyle, and psychosocial risk factors. Lifestyle elements such as diet, physical activity, and sleep patterns play a role on the development and management of both conditions, highlighting the need for integrated treatment strategies. The evidence suggests that traditional management strategies focusing on either condition in isolation fall short of addressing the intertwined nature of diabetes and depression. Instead, integrated care models encompassing psychological support and medical management are recommended to improve treatment efficacy and patient adherence. Such models require collaboration across multiple healthcare disciplines, including endocrinology, psychiatry, and primary care, to offer a holistic approach to patient care. This review also identifies significant patient-related barriers to effective management, such as stigma, psychological resistance, and health literacy, which need to be addressed through patient-centered education and support systems. Future directions for research include longitudinal studies in diverse populations to further elucidate causal relationships and the exploration of novel therapeutic targets, as well as the effectiveness of healthcare models aimed at preventing the onset of one condition in individuals diagnosed with the other.The "PON Ricerca e Innovazione-Istruzione e ricerca per il recupero-REACT-EU "fundsfromtheItalian Ministry of University and Research