Sociodemographic and clinical risk factors associated with in-hospital tuberculosis mortality in Türkiye, 2008-2018.

Introduction: Tuberculosis (TB) is an infectious disease that can be fatal if left untreated or poorly treated, and it is associated with many morbidities. Deaths may provide better understanding of the associated factors and help guide interventions to reduce mortality. In this study, it was aimed to reveal some of the features that predict hospital mortality in patients with TB and to present some alarming findings for clinicians.

Advancements in wearable technology for monitoring lactate levels using lactate oxidase enzyme and free enzyme as analytical approaches: A review.

Lactate is a metabolite that holds significant importance in human healthcare, biotechnology, and the food industry. The need for lactate monitoring has led to the development of various devices for measuring lactate concentration. Traditional laboratory methods, which involve extracting blood samples through invasive techniques such as needles, are costly, time-consuming, and require in-person sampling.

Treatment Results of Multidrug-Resistant Tuberculosis Patients in the Aegean Region.

Objective: We aimed to evaluate 109 rifampicin-resistant or multidrug-resistant tuberculosis patients who are treated in Izmir Chest Diseases MDR Tuberculosis Centre.

Material And Methods: The patient profile, side effects, treatment success, and mortality of rifampicin-resistant or multidrugresistant tuberculosis patients who were followed up and treated in our hospital's tuberculosis service between 2010 and 2018 were analyzed retrospectively.

Results: Of the rifampicin-resistant or multidrug-resistant tuberculosis patients, 83 (76.

Review of functionalized nano porous membranes for desalination and water purification: MD simulations perspective.

Today, it is known that most of the water sources in the world are either drying out or contaminated. With the increasing population, the water demand is increasing drastically almost in every sector each year, which makes processes like water treatment and desalination one of the most critical environmental subjects of the future. Therefore, developing energy-efficient and faster methods are a must for the industry.

MWCNT/Ruthenium hydroxide aerogel supercapacitor production and investigation of electrochemical performances.

In this study, the material obtained from the sonication of the double-walled carbon nanotube and ruthenium chloride was produced as an aerogel. Then, symmetrical supercapacitor devices were made using them, and their electrochemical properties were investigated. XRD and FTIR were used in the structural analysis of the aerogel, STEM in surface images, and elemental analyses in EDX.

Fabrication of sensor based on polyvinyl alcohol functionalized tungsten oxide/reduced graphene oxide nanocomposite for electrochemical monitoring of 4-aminophenol.

4-aminophenol (4-AP) is one of the major environmental pollutants which is broadly exploited as drug intermediate in the pharmaceutical formulations. The extensive release of 4-AP in the environment without treatment has become a serious issue that has led several health effects on humans. This work describe the determination of 4-AP through a new chemically modified sensor based on polyvinyl alcohol functionalized tungsten oxide/reduced graphene oxide (PVA/WO/rGO) nanocomposite.

Determination of D&C Red 33 and Patent Blue V Azo dyes using an impressive electrochemical sensor based on carbon paste electrode modified with ZIF-8/g-CN/Co and ionic liquid in mouthwash and toothpaste as real samples.

Synthetic azo dyes are widely used in a variety of industries, but many of them pose a risk to human health, particularly when consumed in large quantities. As a result, their existence in products should be closely monitored. D&C red 33 and Patent Blue V are mostly used in cosmetics, especially in toothpaste and mouthwashes.

Electrochemical neuron-specific enolase (NSE) immunosensor based on CoFeO@Ag nanocomposite and AuNPs@MoS/rGO.

Small cell lung cancer (SCLC) is highly associated with the risk of early metastasis. Neuron-specific enolase (NSE), a biomarker of SCLC, is directly related to tumor burden and early diagnosis. This biomarker exists in nerve tissue and neuroendocrine tissue.

Congo red dye removal from aqueous environment by cationic surfactant modified-biomass derived carbon: Equilibrium, kinetic, and thermodynamic modeling, and forecasting via artificial neural network approach.

Herein, it was aimed to optimize, model, and forecast the biosorption of Congo Red onto biomass-derived biosorbent. Therefore, the waste-orange-peels were processed to fabricate biomass-derived carbon, which was activated by ZnCl and modified with cetyltrimethylammonium bromide. The physicochemical properties of the biosorbents were explored by scanning electron microscopy and N adsorption/desorption isotherms.

A molecularly imprinted electrochemical biosensor based on hierarchical TiNbO (TNO) for glucose detection.

A novel molecularly imprinted electrochemical biosensor for glucose detection is reported based on a hierarchical N-rich carbon conductive-coated TNO structure (TNO@NC). Firstly, TNO@NC was fabricated by a novel polypyrrole-chemical vapor deposition (PPy-CVD) method with minimal waste generation. Afterward, the electrode modification with TNO@NC was performed by dropping TNO@NC particles on glassy carbon electrode surfaces by infrared heat lamp.

Three-dimensional porous reduced graphene oxide decorated with carbon quantum dots and platinum nanoparticles for highly selective determination of azo dye compound tartrazine.

In this work, an electrochemical sensor for the azo dye compound tartrazine (TRT) determination was proposed. A screen-printed carbon electrode (SPCE) was modified by depositing three-dimensional porous reduced graphene oxide decorated with carbon quantum dots and platinum nanoparticles (Pt/CQDs@rGO/SPCE). The resulting amount of TRT was observed by differential pulse voltammetry.

Sensitive sandwich-type electrochemical SARS-CoV‑2 nucleocapsid protein immunosensor.

A sensitive and fast sandwich-type electrochemical SARS-CoV‑2 (COVID-19) nucleocapsid protein immunosensor was prepared based on bismuth tungstate/bismuth sulfide composite (BiWO/BiS) as electrode platform and graphitic carbon nitride sheet decorated with gold nanoparticles (Au NPs) and tungsten trioxide sphere composite (g-CN/Au/WO) as signal amplification. The electrostatic interactions between capture antibody and BiWO/BiS led to immobilization of the capture nucleocapsid antibody. The detection antibody was then conjugated to g-CN/Au/WO via the affinity of amino-gold.

A green and sensitive guanine-based DNA biosensor for idarubicin anticancer monitoring in biological samples: A simple and fast strategy for control of health quality in chemotherapy procedure confirmed by docking investigation.

Drug efficiency can be considerably boosted while adverse effects can be reduced by precisely monitoring the concentration of anti-cancer drugs. Thus, one of the most important parameters for human health is the monitoring and detection of anticancer drugs during chemotherapy treatment. Herein, a glassy carbon electrode (GCE) was modified by Pt- and Pd-incorporated ZnO nanoparticles-decorated single-wall carbon nanotubes (Pt-Pd-ZnO/SWCNTs) nanocomposites, and ds-DNA (Calf Thymus) that was a biological recognition element, and it was aimed to be utilized as an ultrasensitive and effective electroanalytical biosensor for idarubicin (IDR) monitoring.

An electrochemical molecularly imprinted sensor based on CuBiO/rGO@MoS nanocomposite and its utilization for highly selective and sensitive for linagliptin assay.

The molecularly imprinted polymers (MIP) is an outstanding electrochemical tool that demonstrates good chemical sensitivity and stability. These main advantages, coupled with the material's vast microfabrication flexibility, make molecularly imprinted sensors an attractive sensing device. Herein, it was aimed to develop a state-of-art molecularly imprinted sensor based on CuBiO/rGO@MoS nanocomposite to be utilized for the detection of linagliptin (LNG), a novel hypoglycemic drug.

Utilization of a double-cross-linked amino-functionalized three-dimensional graphene networks as a monolithic adsorbent for methyl orange removal: Equilibrium, kinetics, thermodynamics and artificial neural network modeling.

Herein, it is aimed to develop a high-performance monolithic adsorbent to be utilized in methyl orange (MO) adsorption. Therefore, amino-functionalized three-dimensional graphene networks (3D-GN) fulfilling the requirements of reusability and high capacity have been fabricated via hydrothermal self-assembly approach followed by a double-crosslinking strategy. The potential utilization of 3D-GN as an adsorbent for removal MO has been assessed using both batch-adsorption studies and an artificial neural network (ANN) approach.

Development of smart camera systems based on artificial intelligence network for social distance detection to fight against COVID-19.

In this work, an artificial intelligence network-based smart camera system prototype, which tracks social distance using a bird's-eye perspective, has been developed. "MobileNet SSD-v3", "Faster-R-CNN Inception-v2", "Faster-R-CNN ResNet-50" models have been utilized to identify people in video sequences. The final prototype based on the Faster R-CNN model is an integrated embedded system that detects social distance with the camera.

Sustainable electrode material for high-energy supercapacitor: biomass-derived graphene-like porous carbon with three-dimensional hierarchically ordered ion highways.

Biomass-derived carbonaceous materials have been deemed to be one of the up-and-coming electrode materials for high-performance energy storage systems due to their cost-neutral abundant resources, sustainable nature, easy synthesis methods, and environmentally benign features. In this work, various graphene-like porous carbon networks (GPCs) with three-dimensional (3D) hierarchically ordered "ion highways" have been synthesized by the carbonization/activation of orange-peel wastes for use as an electrode material in high-energy supercapacitors. The porous structures and surface morphologies of the GPCs were rationally fine-tuned as a function of the activation agent ratio.

Determination of COVID-19 pneumonia based on generalized convolutional neural network model from chest X-ray images.

X-ray units have become one of the most advantageous candidates for triaging the new Coronavirus disease COVID-19 infected patients thanks to its relatively low radiation dose, ease of access, practical, reduced prices, and quick imaging process. This research intended to develop a reliable convolutional-neural-network (CNN) model for the classification of COVID-19 from chest X-ray views. Moreover, it is aimed to prevent bias issues due to the database.

Electrochemical immunosensor development based on core-shell high-crystalline graphitic carbon nitride@carbon dots and CdZnS/d-TiCT MXene composite for heart-type fatty acid-binding protein detection.

Acute myocardial infarction (AMI) is a significant health problem owing to its high mortality rate. Heart-type fatty acid-binding protein (h-FABP) is an important biomarker in the diagnosis of AMI. In this work, an electrochemical h-FABP immunosensor was developed based on CdZnS/d-TiCT MXene (MXene: Transition metal carbide or nitride) composite as signal amplificator and core-shell high-crystalline graphitic carbon nitride@carbon dots (hc-g-CN@CDs) as electrochemical sensor platform.

COVID-19 diagnosis from chest X-ray images using transfer learning: Enhanced performance by debiasing dataloader.

Background: Chest X-ray imaging has been proved as a powerful diagnostic method to detect and diagnose COVID-19 cases due to its easy accessibility, lower cost and rapid imaging time.

Objective: This study aims to improve efficacy of screening COVID-19 infected patients using chest X-ray images with the help of a developed deep convolutional neural network model (CNN) entitled nCoV-NET.

Methods: To train and to evaluate the performance of the developed model, three datasets were collected from resources of "ChestX-ray14", "COVID-19 image data collection", and "Chest X-ray collection from Indiana University," respectively.

Estimations of giant dipole resonance parameters using artificial neural network.

In this study; Giant Dipole Resonance (GDR) parameters of the spherical nucleus have been estimated by using artificial neural network (ANN) algorithms. The ANN training has been carried out with the Levenberg-Marquardt feed-forward algorithm in order to provide fast convergence and stability in ANN training and experimental data, taken from Reference Input Parameter Library (RIPL). R values of the system have been found as 0.

Five Years' Evaluation of the BD ProbeTec System for the Direct Molecular Detection of Mycobacterium tuberculosis Complex in Respiratory and Nonrespiratory Clinical Samples.

In this study, Mycobacterium tuberculosis complex was detected by BD ProbeTec ET system in 4716 respiratory and 167 nonrespiratory samples [mostly (98%) smear negative). Sensitivity, specificity, positive and negative predictive values were 81.8%, 98.

Disseminated tuberculosis infection and paradoxical reaction during antimycobacterial treatment related to TNF-alpha blocker agent Infliximab.

Tumor necrosis factor (TNF)-alpha inhibitors play an important role in the treatment of immun-mediated diseases such as Crohn's disease. But they also have been related to increased risk for disseminated Mycobacterium tuberculosis infections and paradoxical response to antimycobacterial treatment. Here we report a disseminated tuberculosis case and a paradoxical response to treatment after receiving TNF-inhibitor agent Infliximab for Crohn's disease.