The fluoroquinolone compounds potentiate the antifungal activity of the echinocandins against Aspergillus fumigatus.

The antifungal drugs of the echinocandin family show high efficacy against Aspergillus fumigatus. However, their paradoxical effect, which restores fungal growth at high drug concentrations, and the emergence of resistant strains necessitate improvements. We identified 13 fluoroquinolone compounds from a chemical library containing 10,000 compounds that potentiate the antifungal activity of caspofungin.

Optimizing prone CT use for suspected interstitial lung abnormalities.

Objectives: We investigated whether supine chest CT alone suffices for diagnosing ILAs, thereby reducing the need for prone chest CT.

Materials And Methods: Patients who underwent prone chest CT for suspected ILAs from January 2021 to July 2023, with matching supine CT within 1 year, were retrospectively evaluated. Five multinational thoracic radiologists independently rated ILA suspicion and fibrosis scores (1 to 5-point) and ILA extent (1-100%) using supine CT first, then combined supine-prone CT after a 1-month washout.

Low-Dose CT Screening in East Asian Women Who Have Never Smoked: Association between Family History of Lung Cancer and Ground-Glass Nodule Prevalence and Growth.

Background Characteristics of ground-glass nodules (GGNs) in Asian women who have never smoked with family history of lung cancer (FHLC) remain unexamined. Purpose To investigate the differences in GGN progression to lung cancer at low-dose CT (LDCT) screening between Asian women who have never smoked with and without FHLC, and to examine associations between FHLC and GGN prevalence and growth. Materials and Methods This single-center retrospective study included East Asian women who had never smoked and had no personal history of lung cancer who underwent baseline LDCT for a health checkup between January 2011 and December 2015.

TMEM39A and TMEM131 facilitate bulk transport of ECM proteins through large COPII vesicle formation.

The growth of Caenorhabditis elegans involves multiple molting processes, during which old cuticles are shed and new cuticles are rapidly formed. This process requires the regulated bulk secretion of cuticle components. The transmembrane protein-39 (TMEM-39) mutant exhibits distinct dumpy and ruptured phenotypes characterized by notably thin cuticles.

Assessing the impact of frailty in elderly patients undergoing emergency laparotomies in Singapore.

Introduction: The global rise in ageing populations poses challenges for healthcare systems. By 2030, Singapore anticipates a quarter of its population to be aged 65 or older. This study addresses the dearth of research on frailty's impact on emergency laparotomy (EL) outcomes in this demographic, emphasising the growing significance of this surgical intervention.

Impact of antibacterial detergent on used-towel microbiomes at species-level and its effect on malodor control.

The impact of antibacterial detergent on microbial exchanges and its subsequent effect on malodor in used towels were examined. Homogenization of microbiome among postwashed and indoor dried towels that was dominated by known malodor-producing bacteria. The microbial exchange was attenuated, and the abundance of malodor-producing bacteria was reduced in towels laundered with antibacterial detergent.

Clinical Utility of a CT-based AI Prognostic Model for Segmentectomy in Non-Small Cell Lung Cancer.

Background Currently, no tool exists for risk stratification in patients undergoing segmentectomy for non-small cell lung cancer (NSCLC). Purpose To develop and validate a deep learning (DL) prognostic model using preoperative CT scans and clinical and radiologic information for risk stratification in patients with clinical stage IA NSCLC undergoing segmentectomy. Materials and Methods In this single-center retrospective study, transfer learning of a pretrained model was performed for survival prediction in patients with clinical stage IA NSCLC who underwent lobectomy from January 2008 to March 2017.

Extracellular Vesicles in Therapeutics: A Comprehensive Review on Applications, Challenges, and Clinical Progress.

Small Extracellular Vesicles (sEVs) are typically 30-150 nm in diameter, produced inside cells, and released into the extracellular space. These vesicles carry RNA, DNA, proteins, and lipids that reflect the characteristics of their parent cells, enabling communication between cells and the alteration of functions or differentiation of target cells. Owing to these properties, sEVs have recently gained attention as potential carriers for functional molecules and drug delivery tools.

Measurement Variability of Same-Day CT Quantification of Interstitial Lung Disease: A Multicenter Prospective Study.

Purpose To investigate quantitative CT (QCT) measurement variability in interstitial lung disease (ILD) on the basis of two same-day CT scans. Materials and Methods Participants with ILD were enrolled in this multicenter prospective study between March and October 2022. Participants underwent two same-day CT scans at an interval of a few minutes.

Association between body fat decrease during the first year after diagnosis and the prognosis of idiopathic pulmonary fibrosis: CT-based body composition analysis.

Background: The prognostic role of changes in body fat in patients with idiopathic pulmonary fibrosis (IPF) remains underexplored. We investigated the association between changes in body fat during the first year post-diagnosis and outcomes in patients with IPF.

Methods: This single-center, retrospective study included IPF patients with chest CT scan and pulmonary function test (PFT) at diagnosis and a one-year follow-up between January 2010 and December 2020.

Fleischner Society: Glossary of Terms for Thoracic Imaging.

Members of the Fleischner Society have compiled a glossary of terms for thoracic imaging that replaces previous glossaries published in 1984, 1996, and 2008, respectively. The impetus to update the previous version arose from multiple considerations. These include an awareness that new terms and concepts have emerged, others have become obsolete, and the usage of some terms has either changed or become inconsistent to a degree that warranted a new definition.

Prospective evaluation of deep learning image reconstruction for Lung-RADS and automatic nodule volumetry on ultralow-dose chest CT.

Purpose: To prospectively evaluate whether Lung-RADS classification and volumetric nodule assessment were feasible with ultralow-dose (ULD) chest CT scans with deep learning image reconstruction (DLIR).

Methods: The institutional review board approved this prospective study. This study included 40 patients (mean age, 66±12 years; 21 women).

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.

Value of CT quantification in progressive fibrosing interstitial lung disease: a deep learning approach.

Objectives: To evaluate the relationship of changes in the deep learning-based CT quantification of interstitial lung disease (ILD) with changes in forced vital capacity (FVC) and visual assessments of ILD progression, and to investigate their prognostic implications.

Methods: This study included ILD patients with CT scans at intervals of over 2 years between January 2015 and June 2021. Deep learning-based texture analysis software was used to segment ILD findings on CT images (fibrosis: reticular opacity + honeycombing cysts; total ILD extent: ground-glass opacity + fibrosis).

Effects of EDTA on the leaching behaviors of Cs(I) and Co(II) from cement waste forms.

Cementation is extensively employed for immobilizing radionuclides in low- and intermediate-level radioactive wastes generated during the decommissioning of nuclear power plants. Ethylenediaminetetraacetic acid (EDTA), used as a decontamination agent during the decommissioning process, can be introduced into the cement waste form containing radionuclides. This study investigated the effects of the EDTA present in simulated radioactive decommissioning wastes on the leaching behaviors of Co and Cs immobilized in the cement waste form.

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.

Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study.

Objectives: To develop and validate CT-based deep learning (DL) models that learn morphological and histopathological features for lung adenocarcinoma prognostication, and to compare them with a previously developed DL discrete-time survival model.

Methods: DL models were trained to simultaneously predict five morphological and histopathological features using preoperative chest CT scans from patients with resected lung adenocarcinomas. The DL score was validated in temporal and external test sets, with freedom from recurrence (FFR) and overall survival (OS) as outcomes.

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).

75% radiation dose reduction using deep learning reconstruction on low-dose chest CT.

Objective: Few studies have explored the clinical feasibility of using deep-learning reconstruction to reduce the radiation dose of CT. We aimed to compare the image quality and lung nodule detectability between chest CT using a quarter of the low dose (QLD) reconstructed with vendor-agnostic deep-learning image reconstruction (DLIR) and conventional low-dose (LD) CT reconstructed with iterative reconstruction (IR).

Materials And Methods: We retrospectively collected 100 patients (median age, 61 years [IQR, 53-70 years]) who received LDCT using a dual-source scanner, where total radiation was split into a 1:3 ratio.