Molecular identification of lactic acid bacteria from traditional fermented foods and screening exopolysaccharide production by using food wastes.

In this study, lactic acid bacteria (LAB) isolation from fermented foods and molecular identification using magnetic bead technology were performed. And then exopolysaccharide (EPS) production possibility was tested in agar medium, and the positive ones were selected for the next step. The bacteria that could produce higher carbohydrate level were grown in MRS medium fortified with whey and pumpkin waste.

AKT1 and MAPK8: New Targets for Gestational Diabetes Mellitus?

Gestational diabetes mellitus (GDM) disrupts placental function and increases risks for pregnancy. This study investigates the potential involvement of AKT1 and MAPK8 genes, known for their roles in insulin resistance and cell signaling, in GDM pathophysiology. Placental tissues from GDM patients and healthy controls were analyzed using real-time PCR to quantify gene expression levels.

The efficacy of topically applied Sappan wood ( L.) ethanol extract during incision wound healing in albino rats.

Background: Medical manifestations in the form of incisions, burns, and trauma will trigger a natural wound-healing process that involves complex interactions between cells. Brazilin and other secondary metabolites found in Sappan wood have numerous bioactive qualities, including anti-inflammatory, anti-cancer, and antioxidant properties.

Aim: This study aimed to investigate the efficacy of Sappan wood ( L.

Entamoeba histolytica in Different Water Sources of Niğde Province of Turkey.

Purpose: This study was carried out to determine the presence of Entamoeba histolytica in water sources of Niğde province in Turkey, between June and November 2021.

Methods: A total of 90 water samples were taken from 15 different water sources (drinking water, well water, spring water, wastewater and dam water) every month and the presence of E. histolytica antigens in the samples was examined by ELISA.

Extracellular production of azurin by reusable magnetic FeO nanoparticle-immobilized Pseudomonas aeruginosa.

Azurin, found in the periplasm of Pseudomonas aeruginosa, has garnered significant attention as a potential anticancer agent in recent years. High-level secretion of proteins into the culture medium, offers a significant advantage over periplasmic or cytoplasmic expression. In this study, for the first time, P.

Determination of nutritional value and methane production potential of styrax tree (.) leaves.

This study aimed to determine the effect of nutritional values of the "styrax tree" (Styrax officinalis L.) on in vitro gas production, organic matter digestibility (OMD), and metabolic energy (ME) content. In this study, styrax leaf samples were collected for analysis in three different periods: May, July and September.

Structural, wide band gap half-metallic, and pressure-dependent thermodynamic predictions of LiTMMgO (TM = V, Nb, and Ta) double perovskites.

Context: LiVMgO, LiNbMgO, and LiTaMgO double perovskite compounds were energetically the most stable in the FM phase. The lattice constants were 7.63 Å, 7.

Ecofaunistic Study and Egg Morphology: Egg Laying Behavior of Hydrometra stagnorum (Linnaeus, 1753) (Gerromorpha: Heteroptera) Newly Recorded From the Karabük Province of Western Black Sea (Türkiye).

This study examines the egg-laying behavior and egg morphology of Hydrometra stagnorum (Linnaeus, 1753) (Gerromorpha: Heteroptera) to provide ecofaunistic information about the species. Newly recorded H. stagnorum samples were collected from the Karabük province of Western Black Sea region of Türkiye.

A self-inducible heterologous protein expression system in ().

Unlabelled:  (previously described as ) is a yeast that produces high-level heterologous proteins with a wide range of applications in medicine and industry. The methanol-induced alcohol oxidase I promoter (P) is frequently used for protein expression in this yeast. However, limitations on the use of methanol have been observed in large-scale production, including its flammability, toxicity, and need for special handling.

Docosahexaenoic acid eliminates endoplasmic reticulum stress and inflammatory pathways in diabetic rat keratopathy.

Diabetic keratopathy, characterized by corneal structural changes, is a common complication of diabetes mellitus (DM). Docosahexaenoic acid (DHA), an omega-3 fatty acid, has shown potential therapeutic benefits in various diabetic complications. This study aimed to investigate the protective effect of DHA on corneal tissue in streptozotocin (STZ)-induced type 2 DM in rats.

A deep learning-based real-time hypothermia and hyperthermia monitoring system with a simple body sensor.

A real-time hypothermia and hyperthermia monitoring system with a simple body sensor based on a Convolutional Neural Network (CNN) is presented. The sensor is produced with 3D-printed thermochromic material. Due to the color change feature of thermochromic materials with temperature, 3D-printed thermochromic Polylactic Acid (PLA) material was used to monitor temperature changes visually.

Combining features on vertical ground reaction force signal analysis for multiclass diagnosing neurodegenerative diseases.

Neurodegenerative diseases (NDDs), which are caused by the degeneration of neurons and their functions, affect a significant part of the world's population. Although gait disorders are one of the critical and common markers to determine the presence of NDDs, diagnosing which NDD the patients have among a group of NDDs using gait data is still a significant challenge to be addressed. In this study, we addressed the multi-class classification of NDDs and aim to diagnose Parkinson's disease (PD), Amyotrophic lateral sclerosis disease (AD), and Huntington's disease (HD) from a group containing NDDs and healthy control subjects.

Multimodal analysis of cortical activation in young male adults with internet gaming disorder: A resting state EEG-fNIRS study.

Background: Internet gaming disorder (IGD) has become increasingly prevalent worldwide and is recognized as a significant public health concern because of its negative consequences on individuals mental and physical health, social relationships, academic performance and overall well-being. While research on IGD has gained significant momentum in the past decade, the neural substrates underlying this disorder remains unclear. This study aims to investigate resting-state cortical activation in male subjects with IGD using a concurrent functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG) hybrid system.

A grafting approach for nisin-chitosan bio-based antibacterial films: preparation and characterization.

Nisin is a bacteriocin produced by Gram-positive lactic acid bacterium,and currently recognized in the Generally Recognızed as Safe (GRAS) category due to its non-toxicity. Herein, nisin has been grafted to chitosan structure to obtain natural bio-active films with enhanced antibacterial activity. Grafting was performed using ethyl ester lysine diisocyanate and dimer fatty acid-based diisocyanate (DDI); two different close to fully bio-based diisocyanates and Disuccinimidyl suberate; a homo-bifunctional molecule acting as a crosslinker between amino groups.

Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science.

Federated learning is a collaborative machine learning paradigm where multiple parties jointly train a predictive model while keeping their data. On the other hand, multi-label learning deals with classification tasks where instances may simultaneously belong to multiple classes. This study introduces the concept of Federated Multi-Label Learning (FMLL), combining these two important approaches.

Enhancing the texture and nutritional value of pumpkin dessert/jam through vacuum impregnation pre-treatment with calcium and vitamin D3.

This study involved fortifying pumpkin slices with calcium and vitamin D3 using vacuum impregnation (VI) pre-treatment and assessing the quality characteristics of the resulting desserts/jams. Slices were subjected to immersion or VI pre-treatments for 30, 60, and 90 min in a solution containing calcium oxide and vitamin D3. Calcium ions contributed to the hardness of desserts, with VI reducing processing time.

Analyzing antimicrobial activity of ZnO/FTO, Sn-Cu-doped ZnO/FTO thin films: Production and characterizations.

In the developing field of nanotechnology, ZnO (zinc oxide) based semiconductor samples have emerged as the foremost choice due to their immense potential for advancing the development of cutting-edge nanodevices. Due to its excellent chemical stability, low cost, and non-toxicity to biological systems, it is also utilized in various investigations. In this study, the successive ionic layer adsorption and reaction (SILAR) method was used to generate FTO (fluorine-doped tin oxide)/ZnO, and tin (Sn)-copper (Cu)-doped ZnO thin films at varying concentrations on FTO substrates.

Association analysis of indel variants and gene expression identifies MDM4 as a novel locus for skeletal muscle hypertrophy and power athlete status.

Insertions and deletions (indels) are the second most common type of variation in the human genome. However, limited data on their associations with exercise-related phenotypes have been documented. The aim of the present study was to examine the association between 18,370 indel variants and power athlete status, followed by additional studies in 357,246 individuals.

Elastocaloric, barocaloric and magnetocaloric effects in spin crossover polymer composite films.

Giant barocaloric effects were recently reported for spin-crossover materials. The volume change in these materials suggests that the transition can be influenced by uniaxial stress, and give rise to giant elastocaloric properties. However, no measurements of the elastocaloric properties in these compounds have been reported so far.

Exploring allocryptopine as a neuroprotective agent against oxidative stress-induced neural apoptosis via Akt/GSK-3β/tau pathway modulation.

Alzheimer's disease (AD) is characterized by neuronal loss due to hyperphosphorylated proteins induced by oxidative stress. AD remains a formidable challenge in the medical field, as current treatments focusing on single biomarkers have yielded limited success. Hence, there's a burgeoning interest in investigating novel compounds that can target mechanisms, offering alternative therapeutic approaches.

Data-driven exploratory method investigation on the effect of dyslexia education at brain connectivity in Turkish children: a preliminary study.

Dyslexia is a specific learning disability that is neurobiological in origin and is characterized by reading and/or spelling problems affecting the development of language-related skills. The aim of this study is to reveal functional markers based on dyslexia by examining the functions of brain regions in resting state and reading tasks and to analyze the effects of special education given during the treatment process of dyslexia. A total of 43 children, aged between 7 and 12, whose native language was Turkish, participated in the study in three groups including those diagnosed with dyslexia for the first time, those receiving special education for dyslexia, and healthy children.

Trajectory Analysis of 6-DOF Industrial Robot Manipulators by Using Artificial Neural Networks.

Robot manipulators are robotic systems that are frequently used in automation systems and able to provide increased speed, precision, and efficiency in the industrial applications. Due to their nonlinear and complex nature, it is crucial to optimize the robot manipulator systems in terms of trajectory control. In this study, positioning analyses based on artificial neural networks (ANNs) were performed for robot manipulator systems used in the textile industry, and the optimal ANN model for the high-accuracy positioning was improved.

Machine Learning Model Development to Predict Power Outage Duration (POD): A Case Study for Electric Utilities.

In the face of increasing climate variability and the complexities of modern power grids, managing power outages in electric utilities has emerged as a critical challenge. This paper introduces a novel predictive model employing machine learning algorithms, including decision tree (DT), random forest (RF), k-nearest neighbors (KNN), and extreme gradient boosting (XGBoost). Leveraging historical sensors-based and non-sensors-based outage data from a Turkish electric utility company, the model demonstrates adaptability to diverse grid structures, considers meteorological and non-meteorological outage causes, and provides real-time feedback to customers to effectively address the problem of power outage duration.

Development and Integration of a Digital Twin Model for a Real Hydroelectric Power Plant.

In this study, a digital twin model of a hydroelectric power plant has been created. Models of the entire power plant have been created and malfunction situations of a sensor located after the inlet valve of the plant have been analyzed using a programmable logic controller (PLC). As a feature of the digital twin (DT), the error prediction and prevention function has been studied specifically for the pressure sensor.