Corrigendum to "LogNNet model as a fast, simple and economical AI instrument in the diagnosis and prognosis of COVID-19" [MethodsX 10 (2023) 102194].

[This corrects the article DOI: 10.1016/j.mex.

Effects of exogenous ghrelin treatment on oxidative stress, inflammation and histological parameters in a fat-fed streptozotocin rat model.

In this study, the anti-inflammatory, antioxidative, and protective effects of ghrelin were investigated in a fat-fed streptozotocin (STZ) rat model and compared with metformin, diabetes and the healthy control groups. Histopathological evaluations were performed on H&E-stained pancreas and brain sections. Biochemical parameters were investigated by enzyme-linked immunosorbent assay.

Effect of abemaciclib and curcumin administration on sex hormones, reproductive functions, and oxidative DNA expression in rats.

This study investigated whether abemaciclib (ABE) administration had any adverse effects on ovarian and sex hormones in female rats, and the protective effect of curcumin. Forty female rats were equally divided into the sham control, DMSO, curcumin (CMN), ABE, and ABE+CMN groups. Pharmaceuticals were administered by gavage daily for 28 days.

Investigating the individual and combined effects of coenzyme Q10 and vitamin C on CLP-induced cardiac injury in rats.

Sepsis-induced cardiac injury represents a major clinical challenge, amplifying the urgency for effective therapeutic interventions. This study aimed to delve into the individual and combined prophylactic effects of Vitamin C (Vit C) and Coenzyme Q10 (CoQ10) against inflammatory heart injury in a cecal ligation and puncture (CLP) induced polymicrobial sepsis rat model. Thirty adult female Sprague-Dawley rats were randomly divided into five groups: Control, CLP, Vitamin C, CoQ10, and Vit C + CoQ10, each consisting of six rats.

Effects of mask use on cardiopulmonary functions and coronaphobia in the COVID-19 pandemic: an observational study among university students.

Mask use during the coronavirus disease 2019 (COVID-19) pandemic has been widely recommended and mandated worldwide. However, there is a lack of comprehensive research on the potential adverse health effects of mask usage. This study aimed to investigate and evaluate the negative effects of surgical mask use on scientifically proven cardiopulmonary functions in undergraduate and associate degree students, as well as its impact on coronaphobia.

ENHANCED EFFICACY OF RESVERATROL-LOADED SILVER NANOPARTICLE IN ATTENUATING SEPSIS-INDUCED ACUTE LIVER INJURY: MODULATION OF INFLAMMATION, OXIDATIVE STRESS, AND SIRT1 ACTIVATION.

Sepsis-induced acute liver injury is a life-threatening condition involving inflammation, oxidative stress, and endothelial dysfunction. In the present study, the preventive effects of resveratrol (RV) alone and RV-loaded silver nanoparticles (AgNPs + RV) against sepsis-induced damage were investigated and compared in a rat model of polymicrobial sepsis induced by cecal ligation and puncture (CLP). Rats were divided into four groups: Sham, CLP, RV, and AgNPs + RV.

A new treatment approach: Melatonin and ascorbic acid synergy shields against sepsis-induced heart and kidney damage in male rats.

Aim: To investigate the combined therapeutic potential of melatonin and ascorbic acid in mitigating sepsis-induced heart and kidney injury in male rats and assess the combination therapy's effects on inflammation, cellular damage, oxidative stress, and vascular function-related markers.

Materials And Methods: Cecal ligation and puncture (CLP) induced sepsis in male rats, which were divided into five groups: Sham, CLP, MEL (melatonin), ASA (ascorbic acid), and MEL+ASA (melatonin and ascorbic acid). Rats were treated, and heart and kidney tissues were collected for biochemical and histopathological analyses.

Protective effect of melatonin and ascorbic acid combination on sepsis-induced lung injury: An Experimental study.

This study investigated the synergistic protective effects of melatonin (MEL) and ascorbic acid (vitamin C, ASA) in treating sepsis-induced lung injury in rats. Rats were divided into five groups: control, cecal ligation and puncture (CLP), CLP + MEL, CLP + ASA and CLP + MEL + ASA. The effects of MEL (10 mg/kg), ASA (100 mg/kg) and their combination on oxidative stress, inflammation and histopathology were evaluated in septic rats' lung tissues.

LogNNet model as a fast, simple and economical AI instrument in the diagnosis and prognosis of COVID-19.

Rapid and effective detection of the diagnosis and prognosis of COVID-19 disease is important in terms of reducing the mortality of the disease and reducing the pressure on health systems. Methods such as PCR testing and computed tomography used for this purpose in current health systems are costly, require an expert team and take time. This study offers a fast, economical and reliable approach for the early diagnosis and prognosis of infectious diseases, especially COVID-19.

Effect of ferritin, INR, and D-dimer immunological parameters levels as predictors of COVID-19 mortality: A strong prediction with the decision trees.

Background And Objective: A hyperinflammatory environment is thought to be the distinctive characteristic of COVID-19 infection and an important mediator of morbidity. This study aimed to determine the effect of other immunological parameter levels, especially ferritin, as a predictor of COVID-19 mortality via decision-trees analysis.

Material And Method: This is a retrospective study evaluating a total of 2568 patients who died (n = 232) and recovered (n = 2336) from COVID-19 in August and December 2021.

Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application.

Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet of Things (IoT). In particular, machine learning (ML) sensors for the prompt diagnosis of COVID-19 are an important option for IoT application in healthcare and ambient assisted living (AAL). Determining a COVID-19 infected status with various diagnostic tests and imaging results is costly and time-consuming.

Effect of curcumin on lipid profile, fibrosis, and apoptosis in liver tissue in abemaciclib-administered rats.

Abemaciclib (ABEM) is an important antitumor agent for breast cancer treatment. However, the side-effects of ABEM are unclear in the liver. This study investigated the protective effect of curcumin (CURC) on liver damage caused by ABEM.

Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network.

Since February 2020, the world has been engaged in an intense struggle with the COVID-19 disease, and health systems have come under tragic pressure as the disease turned into a pandemic. The aim of this study is to obtain the most effective routine blood values (RBV) in the diagnosis and prognosis of COVID-19 using a backward feature elimination algorithm for the LogNNet reservoir neural network. The first dataset in the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 tests.

What is the impact and efficacy of routine immunological, biochemical and hematological biomarkers as predictors of COVID-19 mortality?

It remains important to investigate the changing and impact of routine blood values (RBVs) in order to predict mortality and follow an appropriate treatment in COVID-19 patients. In the study, the importance of RBVs in the mortality of patients with COVID-19 was investigated. The changes in the biochemical, hematological, and immunological parameters of patients who recovered (n = 4364) and died (n = 233) from COVID-19 over time and their relationship with the mortality of the disease were evaluated retrospectively.

Prediction of diagnosis and prognosis of COVID-19 disease by blood gas parameters using decision trees machine learning model: a retrospective observational study.

The coronavirus disease 2019 (COVID-19) epidemic went down in history as a pandemic caused by corona-viruses that emerged in 2019 and spread rapidly around the world. The different symptoms of COVID-19 made it difficult to understand which variables were more influential on the diagnosis, course and mortality of the disease. Machine learning models can accurately assess hidden patterns among risk factors by analyzing large-datasets to quickly predict diagnosis, prognosis and mortality of diseases.

COVID-19 is more dangerous for older people and its severity is increasing: a case-control study.

Coronavirus disease 2019 (COVID-19) triggers important changes in routine blood tests. In this retrospective case-control study, biochemical, hematological and inflammatory biomarkers between March 10, 2020, and November 30, 2020 from 3969 COVID-19 patients (3746 in the non-intensive care unit (non-ICU) group and 223 in the ICU group) were analyzed by dividing into three groups as spring, summer and autumn. In the non-ICU group, lymphocyte to monocyte ratio was lower in autumn than the other two seasons and neutrophil to lymphocyte ratio was higher in autumn than the other two seasons.

Forecasting of Oxidant/Antioxidant levels of COVID-19 patients by using Expert models with biomarkers used in the Diagnosis/Prognosis of COVID-19.

Background: Early detection of oxidant-antioxidant levels and special care in severe patients are important in combating the COVID-19 epidemic. However, this process is costly and time consuming. Therefore, there is a need for faster, reliable and economical methods.

The effectiveness of blood routine parameters and some biomarkers as a potential diagnostic tool in the diagnosis and prognosis of Covid-19 disease.

Since February-2020, the world has been battling a tragic public-health crisis with the emergence and spread of 2019-nCoV. Due to the lack of information about the pathogenesis-specific treatment of Covid-19, early diagnosis and timely treatment are important. However, there is still a lack of information about routine-blood-parameteres (RBP) findings and effects in the disease process.

How do routine laboratory tests change in coronavirus disease 2019?

How the routine laboratory tests change in terms of coronavirus disease 2019 (COVID-19) was retrospectively analyzed in a large group of patients. Biochemical, hematological and inflammatory variables of a totaly 555 ( = 532 in non-intensive care unit (non-ICU),  = 23 in ICU) patients diagnosed with COVID-19 were analyzed accessing them through the laboratory information system. White blood cell (WBC), neutrophil (NEU), platelet large cell ratio, neutrophil to lymphocyte ratio (NLR), derived NLR (d-NLR), aspartate aminotransferase, urea, creatine kinase (CK) myocardial band (CK-MB), procalcitonin (PCT) values were high whereas lymphocyte (LYM), eosinophil, red blood cells (RBC), hemoglobin, lymphocyte to monocyte ratio, estimated glomerular filtration rate values were low in the ICU group when compared with non-ICU.