Synthesis of zirconium-based metal-organic framework/gelatin aerogel for removing phosphate and fluoride from aqueous solutions.

This study describes the preparation of novel hybrid aerogels derived from gelatin (Gel), incorporating Br-functionalized zirconium-based metal-organic framework (UiO-66-Br; MOF) as modifying agent to effectively eliminate phosphate and fluoride ions from aqueous environments. The adsorption performance of MOF decorated Gel (Gel-xMOF) hybrid aerogels was investigated under different conditions, including agitation time, adsorbent dosage, solution pH, initial phosphate and fluoride concentrations, coexisting ions, and temperature. The functional groups of the gelatin network, coupled with UiO-66-Br, enhanced the adsorption performance of phosphate and fluoride ions from aqueous solutions.

Efficient photo-assisted activation of peroxydisulfate by a novel Z-scheme sulfur-doped CN/DyFeO heterojunction for norfloxacin degradation: Activation mechanism and DFT studies on reaction pathways.

Peroxydisulfate (PDS) activation is a crucial process for wastewater treatment in complicated water matrices. However, it is frequently limited because of poor selectivity, sluggish kinetics, and short lifetime of radicals. Therefore, in this study, an efficient sulfur-doped CN/DyFeO (SCN/DyF) Z-scheme heterostructure catalyst was rationally developed using a simple wet-chemical strategy to photoactivate PDS, which can effectively degrade norfloxacin (NOR; 96.

Critical assessment of recent advancements in chitosan-functionalized iron and geopolymer-based adsorbents for the selective removal of arsenic from water.

Inorganic arsenic (As), a known carcinogen and major contaminant in drinking water, affects over 140 million people globally, with levels exceeding the World Health Organization's (WHO) guidelines of 10 μg L. Developing innovative technologies for effluent handling and decontaminating polluted water is critical. This paper summarizes the fundamental characteristics of chitosan-embedded composites for As adsorption from water.

Artificial intelligence system for identification of overlooked lung metastasis in abdominopelvic computed tomography scans of patients with malignancy.

Purpose: This study aimed to evaluate whether an artificial intelligence (AI) system can identify basal lung metastatic nodules examined using abdominopelvic computed tomography (CT) that were initially overlooked by radiologists.

Methods: We retrospectively included abdominopelvic CT images with the following inclusion criteria: a) CT images from patients with solid organ malignancies between March 1 and March 31, 2019, in a single institution; and b) abdominal CT images interpreted as negative for basal lung metastases. Reference standards for diagnosis of lung metastases were confirmed by reviewing medical records and subsequent CT images.

Removal of endocrine disruptors and pharmaceuticals by graphene oxide-based membranes in water: A review.

Membrane-based water treatment has emerged as a promising solution to address global water challenges. Graphene oxide (GO) has been successfully employed in membrane filtration processes owing to its reversible properties, large-scale production potential, layer-to-layer stacking, great oxygen-based functional groups, and unique physicochemical characteristics, including the creation of nano-channels. This review evaluates the separation performance of various GO-based membranes, manufactured by coating or interfacial polymerization with different support layers such as polymer, metal, and ceramic, for endocrine-disrupting compounds (EDCs) and pharmaceutically active compounds (PhACs).

Ultrasonic treatment of endocrine disrupting compounds, pharmaceuticals, and personal care products in water: An updated review.

Pharmaceuticals, personal care products (PPCPs), and endocrine-disrupting compounds (EDCs) have seen a recent sustained increase in usage, leading to increasing discharge and accumulation in wastewater. Conventional water treatment and disinfection processes are somewhat limited in effectively addressing this micropollutant issue. Ultrasonication (US), which serves as an advanced oxidation process, is based on the principle of ultrasound irradiation, exposing water to high-frequency waves, inducing thermal decomposition of HO while using the produced radicals to oxidize and break down dissolved contaminants.

Fabrication of MoS restrained magnetic chitosan polysaccharide composite for the photocatalytic degradation of organic dyes.

Chitosan (CS) polysaccharide is expected to exhibit greater ionic conductivity, which can be attributed to its increased amino group content when it is blended with different semiconducting materials. Herein, the work used this conducting ability of chitosan and prepared a heterogeneous MoS-induced magnetic chitosan (MF@CS) composite via the co-precipitation method, which was used to scrutinize the catalytic performance with Methylene Blue (MB) and Malachite Green (MG) dyes by visible light irradiation. The saturation magnetization value of the MF@CS composite is found to be 7.

Photocatalytic and electrocatalytic degradation of bisphenol A in the presence of graphene/graphene oxide-based nanocatalysts: A review.

Bisphenol A (BPA), a widely recognized endocrine disrupting compound, has been discovered in drinking water sources/finished water and domestic wastewater influent/effluent. Numerous studies have shown photocatalytic and electrocatalytic oxidation to be very effective for the removal of BPA, particularly in the addition of graphene/graphene oxide (GO)-based nanocatalysts. Nevertheless, the photocatalytic and electrocatalytic degradation of BPA in aqueous solutions has not been reviewed.

Effect of smoking on the diagnostic results and complication rates of percutaneous transthoracic needle biopsy.

Objective: To investigate the association of smoking with the outcomes of percutaneous transthoracic needle biopsy (PTNB).

Methods: In total, 4668 PTNBs for pulmonary lesions were retrospectively identified. The associations of smoking status (never, former, current smokers) and smoking intensity (≤ 20, 21-40, > 40 pack-years) with diagnostic results (malignancy, non-diagnostic pathologies, and false-negative results in non-diagnostic pathologies) and complications (pneumothorax and hemoptysis) were assessed using multivariable logistic regression analysis.

Ultrasonic treatment of dye chemicals in wastewater: A review.

The existence of pollutants, such as toxic organic dye chemicals, in water and wastewater raises concerns as they are inadequately eliminated through conventional water and wastewater treatment methods, including physicochemical and biological processes. Ultrasonic treatment has emerged as an advanced treatment process that has been widely applied to the decomposition of recalcitrant organic contaminants. Ultrasonic treatment has several advantages, including easy operation, sustainability, non-secondary pollutant production, and saving energy.

Sixty-four-fold data reduction of chest radiographs using a super-resolution convolutional neural network.

Objectives: To develop and validate a super-resolution (SR) algorithm generating clinically feasible chest radiographs from 64-fold reduced data.

Methods: An SR convolutional neural network was trained to produce original-resolution images (output) from 64-fold reduced images (input) using 128 × 128 patches (n = 127 030). For validation, 112 radiographs-including those with pneumothorax (n = 17), nodules (n = 20), consolidations (n = 18), and ground-glass opacity (GGO; n = 16)-were collected.

All-solid-state Z-scheme ZnFe-LDH/rGO/g-CN heterojunction for enhanced sonophotocatalytic degradation of ciprofloxacin: Performance and mechanistic insights.

The fabrication of all-solid-state Z-scheme sonophotocatalysts is vital for improving the transfer rate of photogenerated electrons to remove antibiotics present in wastewater. Herein, a novel indirect Z-scheme ZnFe-layered double hydroxide (LDH)/reduced graphene oxide (rGO)/graphitic carbon nitride (g-CN) heterojunction was synthesized using a simple strategy. The ZnFe-LDH/rGO/g-CN (ZF@rGCN) ternary composites were systematically characterized using different techniques.

Photocatalytic boron nitride-based nanomaterials for the removal of selected organic and inorganic contaminants in aqueous solution: A review.

Boron nitride (BN) coupled with various conventional and advanced photocatalysts has been demonstrated to exhibit extraordinary activity for photocatalytic degradation because of its unique properties, including a high surface area, constant wide-bandgap semiconducting property, high thermal-oxidation resistance, good hydrogen-adsorption performance, and high chemical/mechanical stability. However, only limited reviews have discussed the application of BN or BN-based nanomaterials as innovative photocatalysts, and it does not cover the recent results and the developments on the application of BN-based nanomaterials for water purification. Herein, we present a complete review of the present findings on the photocatalytic degradation of different contaminants by various BN-based nanomaterials.

Thermally-activated gelatin-chitosan-MOF hybrid aerogels for efficient removal of ibuprofen and naproxen.

Nonsteroidal anti-inflammatory drugs (NSAIDs) are one of the most frequently used drugs and have been frequently detected in aquatic environments. This paper demonstrates a thermally-activated gelatin-chitosan and amine-functionalized metal-organic framework (UiO-66-NH) aerogel (CGC-MOF), which was successfully synthesized for the efficient removal of ibuprofen (IBP) and naproxen (NPX). Various characterization tools were used to systematically analyze the microstructure and physicochemical properties of the synthesized aerogel.

Cigarette smoking and disproportionate changes of thoracic skeletal muscles in low-dose chest computed tomography.

Association between smoking intensity and the quantity and quality of thoracic skeletal muscles (TSMs) remains unexplored. Skeletal muscle index (SMI; skeletal muscle area/height) and percentage of normal attenuation muscle area (NAMA%) were measured to represent the quantity and quality of the skeletal muscles, respectively, and quantification was performed in pectoralis muscle at aortic arch (AA-PM), TSM at carina (C-TSM), erector spinae muscle at T12 (T12-ESM), and skeletal muscle at L1 (L1-SM). Among the 258 men (median age, 62 years [IQR: 58-69]), 183 were current smokers (median smoking intensity, 40 pack-years [IQR: 30-46]).

Usual Interstitial Pneumonia: Associations With Complications After Percutaneous Transthoracic Needle Lung Biopsy.

Changes in lung parenchyma elasticity in usual interstitial pneumonia (UIP) may increase the risk for complications after percutaneous transthoracic needle biopsy (PTNB) of the lung. The purpose of this article was to investigate the association of UIP findings on CT with complications after PTNB, including pneumothorax, pneumothorax requiring chest tube insertion, and hemoptysis. This retrospective single-center study included 4187 patients (mean age, 63.

The Performance of a Deep Learning-Based Automatic Measurement Model for Measuring the Cardiothoracic Ratio on Chest Radiographs.

Objective: Prior studies on models based on deep learning (DL) and measuring the cardiothoracic ratio (CTR) on chest radiographs have lacked rigorous agreement analyses with radiologists or reader tests. We validated the performance of a commercially available DL-based CTR measurement model with various thoracic pathologies, and performed agreement analyses with thoracic radiologists and reader tests using a probabilistic-based reference.

Materials And Methods: This study included 160 posteroanterior view chest radiographs (no lung or pleural abnormalities, pneumothorax, pleural effusion, consolidation, and = 40 in each category) to externally test a DL-based CTR measurement model.

Artificial Intelligence for Assessment of Endotracheal Tube Position on Chest Radiographs: Validation in Patients From Two Institutions.

Timely and accurate interpretation of chest radiographs obtained to evaluate endotracheal tube (ETT) position is important for facilitating prompt adjustment if needed. The purpose of our study was to evaluate the performance of a deep learning (DL)-based artificial intelligence (AI) system for detecting ETT presence and position on chest radiographs in three patient samples from two different institutions. This retrospective study included 539 chest radiographs obtained immediately after ETT insertion from January 1 to March 31, 2020, in 505 patients (293 men, 212 women; mean age, 63 years) from institution A (sample A); 637 chest radiographs obtained from January 1 to January 3, 2020, in 302 patients (157 men, 145 women; mean age, 66 years) in the ICU (with or without an ETT) from institution A (sample B); and 546 chest radiographs obtained from January 1 to January 20, 2020, in 83 patients (54 men, 29 women; mean age, 70 years) in the ICU (with or without an ETT) from institution B (sample C).

Erratum: Correction of Affiliations in the Article "Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019".

This corrects the article on p. e413 in vol. 35, PMID: 33258333.