Syntheses and biological activities of calix[4]resorcinarene derivatives modified by sulfonic acid and sulfonamides.

Functionalization of -propyl-resorcinolcalix[4]arene (1a) and -iso-butyl-resorcinolcalix[4]arene (1b) with sodium sulfite and formaldehyde solution gave two corresponding sulfonatomethylated calix[4]resorcinarenes 2a/b. Further modification of 2a/b with different primary amines afforded three calix[4]resorcinarene sulfonamides 3a/b and 4c. Antibacterial and antitumor tests were performed on the starting calix[4]resorcinarenes and their sulfonic acid and sulfonamide derivatives.

Development and validation of an interpretable delta radiomics-based model for predicting invasive ground-glass nodules in lung adenocarcinoma: a retrospective cohort study.

Background: Radiomics models based on computed tomography (CT) can be used to differentiate invasive ground-glass nodules (GGNs) in lung adenocarcinoma to help determine the optimal timing of GGN resection, improve the accuracy of prognostic prediction, and reduce unnecessary surgeries. However, general radiomics does not fully utilize follow-up data and often lacks model interpretation. Therefore, this study aimed to build an interpretable model based on delta radiomics to predict GGN invasiveness.

A Radiological-Radiomics model for differentiation between minimally invasive adenocarcinoma and invasive adenocarcinoma less than or equal to 3 cm: A two-center retrospective study.

Objective: To develop a Radiological-Radiomics (R-R) combined model for differentiation between minimal invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA) of lung adenocarcinoma (LUAD) and evaluate its predictive performance.

Methods: The clinical, pathological, and imaging data of a total of 509 patients (522 lesions) with LUAD diagnosed by surgical pathology from 2 medical centres were retrospectively collected, with 392 patients (402 lesions) from center 1 trained and validated using a five-fold cross-validation method, and 117 patients (120 lesions) from center 2 serving as an independent external test set. The least absolute shrinkage and selection operator (LASSO) method was utilized to filter features.

Global, regional, and national cancer burdens of respiratory and digestive tracts in 1990-2044: A cross-sectional and age-period-cohort forecast study.

Background: Understanding the current status and future trends of cancer burdens by systems provides important information for specialists, policymakers, and specific risk populations.

Methods: The aim of this study was to compare the current and future cancer burdens of the gastrointestinal (GI) and respiratory tracts in terms of their magnitude and distribution. Data from a total of eight cancers of the digestive and respiratory tracts in the Global Burden of Disease (GBD) database were collected.

Combination of Contrast-enhanced FlAIR and Contrast-enhanced T1WI: A Quick and Efficient Method in Detecting Brain Metastases of Lung Cancers.

Background: Some patients with suspected brain metastases (BM) could not tolerate longer scanning examinations according to the standardized MRI protocol.

Objective: The purpose of this study was to evaluate the clinical value of contrast-enhanced fast fluid-attenuated inversion recovery (CE FLAIR) imaging in combination with contrast-enhanced T1 weighted imaging (CE T1WI) in detecting BM of lung cancer and explore a quick and effective MRI protocol.

Material And Methods: In 201 patients with lung cancers and suspected BM, T1WI and FLAIR were performed before and after administration of gadopentetate dimeglumine.

Sublethal heat treatment enhances lactic acid uptake in macrophages via MCT1, leading to reduced paraspeckle formation and a subsequent decrease in macrophage pyroptosis.

Introduction: Heat ablation is one of the key modalities in treating liver cancer, yet the residual cancer tissues suffering sublethal heat treatment possess a potential for increased malignancy. This study conducts a comprehensive analysis of cellular dynamics, metabolic shifts, and macrophage polarization within the tumor microenvironment following sublethal heat treatment.

Methods: We observed significant acidification in tumor cell supernatants, attributed to increased lactic acid production.

Backlogs in formal interpretation of radiology examinations: a pilot global survey.

Objective: Anecdotal reports from imaging facilities globally suggest growing radiology interpretation reporting delays. This pilot study's primary aim was to estimate the backlog of formal interpretation of imaging examinations.

Methods: An online survey was distributed to radiologists globally to gather practice-specific characteristics, imaging volumes, and reporting for 3 types of examinations (brain/head CT scans, chest CT scans, and chest radiographs) at 4 time points: 7, 30, 90 days, and 6 months.

Improving the prediction of Spreading Through Air Spaces (STAS) in primary lung cancer with a dynamic dual-delta hybrid machine learning model: a multicenter cohort study.

Background: Reliable pre-surgical prediction of spreading through air spaces (STAS) in primary lung cancer is essential for precision treatment and surgical decision-making. We aimed to develop and validate a dual-delta deep-learning and radiomics model based on pretreatment computed tomography (CT) image series to predict the STAS in patients with lung cancer.

Method: Six hundred seventy-four patients with pre-surgery CT follow-up scans (with a minimum interval of two weeks) and primary lung cancer diagnosed by surgery were retrospectively recruited from three Chinese hospitals.

A deep learning and radiomics based Alberta stroke program early CT score method on CTA to evaluate acute ischemic stroke.

Background: Alberta stroke program early CT score (ASPECTS) is a semi-quantitative evaluation method used to evaluate early ischemic changes in patients with acute ischemic stroke, which can guide physicians in treatment decisions and prognostic judgments.

Objective: We propose a method combining deep learning and radiomics to alleviate the problem of large inter-observer variance in ASPECTS faced by physicians and assist them to improve the accuracy and comprehensiveness of the ASPECTS.

Methods: Our study used a brain region segmentation method based on an improved encoding-decoding network.

Non-linear modifications enhance prediction of pathological response to pre-operative PD-1 blockade in lung cancer: A longitudinal hybrid radiological model.

Major pathologic remission (MPR, residual tumor <10%) is a promising clinical endpoint for prognosis analysis in patients with lung cancer receiving pre-operative PD-1 blockade therapy. Most of the current biomarkers for predicting MPR such as PD-L1 and tumor mutation burden (TMB) need to be obtained invasively. They cannot overcome the spatiotemporal heterogeneity or provide dynamic monitoring solutions.

Joint two-stage convolutional neural networks for intracranial aneurysms detection on 3D TOF-MRA.

. This study aims to develop a three-dimensional convolutional neural network utilizing computer-aided diagnostic technology to facilitate the detection of intracranial aneurysms and automatically assess their location and extent, thereby enhancing the efficiency of radiologists, and streamlining clinical workflows..

Establishment and visualization of a model based on high-resolution CT qualitative and quantitative features for prediction of micropapillary or solid components in invasive lung adenocarcinoma.

Objective: To predict the existence of micropapillary or solid components in invasive adenocarcinoma, a model was constructed using qualitative and quantitative features in high-resolution computed tomography (HRCT).

Methods: Through pathological examinations, 176 lesions were divided into two groups depending on the presence or absence of micropapillary and/or solid components (MP/S): MP/S- group (n = 128) and MP/S + group (n = 48). Multivariate logistic regression analyses were used to identify independent predictors of the MP/S.

Serum total cholesterol levels associated with immediate memory performance in patients with chronic schizophrenia.

Cognitive impairments are common in patients with schizophrenia. Changes in total cholesterol (TC) may be involved in the development of schizophrenia and associated with cognitive function. This study aimed to investigate differences in serum TC level and cognitive function between schizophrenia patients and healthy controls and explore the relationship between serum TC level and cognitive function in patients with schizophrenia.

Prediction of high-grade patterns of stage IA lung invasive adenocarcinoma based on high-resolution CT features: a bicentric study.

Objectives: This study aims to predict the high-grade pattern (HGP) of stage IA lung invasive adenocarcinoma (IAC) based on the high-resolution CT (HRCT) features.

Methods: The clinical, pathological, and HRCT imaging data of 457 patients (from bicentric) with pathologically confirmed stage IA IAC (459 lesions in total) were retrospectively analyzed. The 459 lesions were classified into high-grade pattern (HGP) (n = 101) and non-high-grade pattern (n-HGP) (n = 358) groups depending on the presence of HGP (micropapillary and solid) in pathological results.

A method for distinguishing benign and malignant pulmonary nodules based on 3D dual path network aided by -means clustering analysis.

In the USA, there were about 1 ‍806 ‍590 new cancer cases in 2020, and 606 520 cancer deaths are expected to have occurred in 2021. Lung cancer has become the leading cause of death from cancer in both men and women (Siegel et al., 2020).

Gastric duplication cyst with ectopic pancreas in a teenager successfully resected by endoscopic submucosal dissection.

Background: Gastric duplication cyst associated with ectopic pancreas is rare and we aimed to alert clinician to this congenital anomaly.

Case Presentation: A 15-year-old girl presented with intermittent vomiting. Gastroscopy showed a submucosal tumor with an approximate diameter of 40 mm in the anterior wall of the gastric antrum.

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification.

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule. Here, a multiplexed assay is developed on an optimized nanoparticle-based laser desorption/ionization mass spectrometry platform for the sensitive and selective detection of serum metabolic fingerprints (SMFs). Integrative SMFs based multi-modal platforms are constructed for the early detection of LUAD and the classification of pulmonary nodule.

Determination of the geographical origin of Diels & Gilg using an electronic nose technique with multiple algorithms.

Diels & Gilg, an herbal medicinal plant, is planted widely in bamboo forests in southern China to promote economic benefits. Volatile compounds (VOCs) of from different geographical regions are difficult to identify in field forests. In this study, VOCs from leaf samples of different geographical origins were analyzed using an electronic nose with 10 different sensors.

Time-of-Flight Intracranial MRA at 3 T versus 5 T versus 7 T: Visualization of Distal Small Cerebral Arteries.

Background Three-dimensional (3D) time-of-flight (TOF) MR angiography (MRA) at 7 T has been reported to have high image quality for visualizing small perforating vessels. However, B inhomogeneity and more physiologic considerations limit its applications. Angiography at 5 T may provide another choice for intracranial vascular imaging.

[Segmentation of ground glass pulmonary nodules using full convolution residual network based on atrous spatial pyramid pooling structure and attention mechanism].

Accurate segmentation of ground glass nodule (GGN) is important in clinical. But it is a tough work to segment the GGN, as the GGN in the computed tomography images show blur boundary, irregular shape, and uneven intensity. This paper aims to segment GGN by proposing a fully convolutional residual network, , residual network based on atrous spatial pyramid pooling structure and attention mechanism (ResAANet).

Terahertz meta-biosensor based on high-Q electrical resonance enhanced by the interference of toroidal dipole.

Electrical dipole resonances typically have low Q factor and broad resonant linewidth caused by strong free-space coupling with high radiative loss. Here, we present a strategy for enhancing the Q factor of the electrical resonance via the interference of a toroidal dipole. To validate such a strategy, a metasurface consisting of two resonators is designed that responsible to the electric and toroidal dipoles.

Computed tomography versus frozen sections for distinguishing lung adenocarcinoma: A cohort study of concordance rate.

Background: Computed tomography (CT) imaging can help to predict the pathological invasiveness of early-stage lung adenocarcinoma and guide surgical resection. This retrospective study investigated whether CT imaging could distinguish pre-invasive lung adenocarcinoma from IAC. It also compared final pathology prediction accuracy between CT imaging and intraoperative frozen section analysis.