Mild Focused Ultrasound-Induced Microscopic Heating of Nanoparticles Observed by Lanthanide Luminescence for Precise Sonothermal Cancer Therapy.

Focused ultrasound (FUS) is a recognized tool that can be used clinically for the thermal ablation of tumors. However, excessive heat can cause side effects on the ultrasound transmission path and normal tissues around the tumor. To address the issue, this work detected for the first time the effect of microscopic heating of nanoparticles under the action of FUS through the luminescence intensity ratio (LIR) and luminescence lifetime of temperature-responsive lanthanide-doped nanoparticles.

A Multi-Robot Task Allocation Method Based on the Synergy of the K-Means++ Algorithm and the Particle Swarm Algorithm.

Addressing challenges in the traditional K-means algorithm, such as the challenge of selecting initial clustering center points and the lack of a maximum limit on the number of clusters, and where the set of tasks in the clusters is not reasonably sorted after the task assignment, which makes the cooperative operation of multiple robots inefficient, this paper puts forward a multi-robot task assignment method based on the synergy of the K-means++ algorithm and the particle swarm optimization (PSO) algorithm. According to the processing capability of the robots, the K-means++ algorithm that limits the maximum number of clusters is used to cluster the target points of the task. The clustering results are assigned to the multi-robot system using the PSO algorithm based on the distances between the robots and the centers of the clusters, which divides the multi-robot task assignment problem into a multiple traveling salesmen problem.

Integrated regulatory and metabolic networks of the tumor microenvironment for therapeutic target prioritization.

Translation of genomic discovery, such as single-cell sequencing data, to clinical decisions remains a longstanding bottleneck in the field. Meanwhile, computational systems biological models, such as cellular metabolism models and cell signaling pathways, have emerged as powerful approaches to provide efficient predictions in metabolites and gene expression levels, respectively. However, there has been limited research on the integration between these two models.

Distinct association between chronic Epstein-Barr virus infection and T cell compartments from pediatric heart, kidney, and liver transplant recipients.

Chronic Epstein-Barr virus (EBV) infection after pediatric organ transplantation (Tx) accounts for significant morbidity and mortality. The risk of complications, such as posttransplant lymphoproliferative disorders, in high viral load (HVL) carriers is the highest in heart Tx recipients. However, the immunologic signatures of such a risk have been insufficiently defined.

Metabolomic profiles in relapsing-remitting and progressive multiple sclerosis compared to healthy controls: a five-year follow-up study.

Introduction And Objectives: Multiple sclerosis (MS) is a disease of the central nervous system associated with immune dysfunction, demyelination, and neurodegeneration. The disease has heterogeneous clinical phenotypes such as relapsing-remitting MS (RRMS) and progressive multiple sclerosis (PMS), each with unique pathogenesis. Metabolomics research has shown promise in understanding the etiologies of MS disease.

Integrated Graph Propagation and Optimization with Biological Applications.

Mathematical models that utilize network representations have proven to be valuable tools for investigating biological systems. Often dynamic models are not feasible due to their complex functional forms that rely on unknown rate parameters. Network propagation has been shown to accurately capture the sensitivity of nodes to changes in other nodes; without the need for dynamic systems and parameter estimation.

Expanded Imaging Classification of Autosomal Dominant Polycystic Kidney Disease.

Background: The Mayo Clinic imaging classification of autosomal dominant polycystic kidney disease (ADPKD) uses height-adjusted total kidney volume (htTKV) and age to identify patients at highest risk for disease progression. However, this classification applies only to patients with typical diffuse cystic disease (class 1). Because htTKV poorly predicts eGFR decline for the 5%-10% of patients with atypical morphology (class 2), imaging-based risk modeling remains unresolved.

Long-term trajectory of kidney function in autosomal-dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cyst and kidney growth, which is hypothesized to cause loss of functioning renal mass and eventually end-stage kidney disease. However, the time course of decline in glomerular filtration rate (GFR) is poorly defined. The Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease study is a 14-year observational cohort study of 241 adults with ADPKD.