Short-term follow-up of single-port thoracoscopic rib fracture reduction and internal fixation for the treatment of multiple rib fractures.

Objective: The objective of this study was to evaluate the short-term outcomes of single-port thoracoscopic rib fracture reduction and internal fixation for the treatment of multiple rib fractures.

Methods: This study included 149 patients with multiple rib fractures admitted to the Second People's Hospital Affiliated with Fujian University of Chinese Medicine between June 2021 and April 2024. The patients were divided into two groups based on the surgical method.

Enhanced photocatalytic activity of porous TiO containing C/P/K derived from grapefruit peel.

Grapefruit peel possesses a porous structure and a significant specific surface area. In this study, we introduce an innovative and eco-friendly approach for synthesizing porous TiO. This was accomplished by employing grapefruit peel as a bio-template and tetrabutyl titanate as the precursor, utilizing a two-step rotary impregnation-calcination process.

Waste Biomass-Mediated Synthesis of TiO/P, K-Containing Grapefruit Peel Biochar Composites with Enhanced Photocatalytic Activity.

In this study, TiO/P, K-containing grapefruit peel biochar (TiO/P, K-PC) composites were synthesized biomimetically using grapefruit peel as the bio-template and carbon source and tetrabutyl titanate as the titanium source. This was achieved using the two-step rotary impregnation-calcination method. Adjusting the calcination temperature of the sample in an air atmosphere could regulate the mass ratio of TiO to carbon.

Glutamine addiction in tumor cell: oncogene regulation and clinical treatment.

After undergoing metabolic reprogramming, tumor cells consume additional glutamine to produce amino acids, nucleotides, fatty acids, and other substances to facilitate their unlimited proliferation. As such, the metabolism of glutamine is intricately linked to the survival and progression of cancer cells. Consequently, targeting the glutamine metabolism presents a promising strategy to inhibit growth of tumor cell and cancer development.

Extracellular vesicle-cell adhesion molecules in tumours: biofunctions and clinical applications.

Cell adhesion molecule (CAM) is an umbrella term for several families of molecules, including the cadherin family, integrin family, selectin family, immunoglobulin superfamily, and some currently unclassified adhesion molecules. Extracellular vesicles (EVs) are important information mediators in cell-to-cell communication. Recent evidence has confirmed that CAMs transported by EVs interact with recipient cells to influence EV distribution in vivo and regulate multiple cellular processes.

Crosstalk between autophagy and CSCs: molecular mechanisms and translational implications.

Cancer stem cells(CSCs) play a key role in regulating tumorigenesis, progression, as well as recurrence, and possess typical metabolic characteristics. Autophagy is a catabolic process that can aid cells to survive under stressful conditions such as nutrient deficiency and hypoxia. Although the role of autophagy in cancer cells has been extensively studied, CSCs possess unique stemness, and their potential relationship with autophagy has not been fully analyzed.

Diagnosis of lung squamous cell carcinoma based on metagenomic Next-Generation Sequencing.

Background: The clinical treatment of patients suspected of pulmonary infections often rely on empirical antibiotics. However, preliminary diagnoses were based on clinical manifestations and conventional microbiological tests, which could later be proved wrong. In this case, we presented a patient whose initial diagnosis was lung abscess, but antibiotic treatments had no effect, and metagenomic Next-Generation Sequencing (mNGS) indicated presence of neoplasm.

A machine learning approach for predicting urine output after fluid administration.

Background And Objective: To develop a machine learning model to predict urine output (UO) in sepsis patients after fluid resuscitation.

Methods: We identified sepsis patients in the Multiparameter Intelligent Monitoring in Intensive Care-III v1.4 database according to the Sepsis-3 criteria.

Automation of the kidney function prediction and classification through ultrasound-based kidney imaging using deep learning.

Prediction of kidney function and chronic kidney disease (CKD) through kidney ultrasound imaging has long been considered desirable in clinical practice because of its safety, convenience, and affordability. However, this highly desirable approach is beyond the capability of human vision. We developed a deep learning approach for automatically determining the estimated glomerular filtration rate (eGFR) and CKD status.

Reconstruction of sparse-view X-ray computed tomography using adaptive iterative algorithms.

In this paper, we propose two reconstruction algorithms for sparse-view X-ray computed tomography (CT). Treating the reconstruction problems as data fidelity constrained total variation (TV) minimization, both algorithms adapt the alternate two-stage strategy: projection onto convex sets (POCS) for data fidelity and non-negativity constraints and steepest descent for TV minimization. The novelty of this work is to determine iterative parameters automatically from data, thus avoiding tedious manual parameter tuning.