Advances in modeling permeability and selectivity of the blood-brain barrier using microfluidics.

The blood-brain barrier (BBB) protects the brain by actively allowing the entry of ions and nutrients while limiting the passage of from toxins and pathogens. A healthy BBB has low permeability and high selectivity to maintain normal brain functions. Increased BBB permeability can result from neurological diseases and traumatic injuries.

Preclinical evaluation of a surgical assistant robot for use in minimally invasive abdominal surgeries.

In recent years, robotic assistance has become increasingly used and applied in minimally invasive surgeries. A new cooperative surgical robot system that includes a joystick-guided robotic scope holder was developed in this study, and its feasibility for use in minimally invasive abdominal surgery was evaluated in a preclinical setting. The cooperative surgical robot consists of a six-degree-of-freedom collaborative robot arm and a one-degree-of-freedom bidirectional telescopic end-effector specializing in surgical assistance.

Janus graphene nanoribbons with localized states on a single zigzag edge.

Topological design of π electrons in zigzag-edged graphene nanoribbons (ZGNRs) leads to a wealth of magnetic quantum phenomena and exotic quantum phases. Symmetric ZGNRs typically show antiferromagnetically coupled spin-ordered edge states. Eliminating cross-edge magnetic coupling in ZGNRs not only enables the realization of a class of ferromagnetic quantum spin chains, enabling the exploration of quantum spin physics and entanglement of multiple qubits in the one-dimensional limit, but also establishes a long-sought-after carbon-based ferromagnetic transport channel, pivotal for ultimate scaling of GNR-based quantum electronics.

Artificial Intelligence Models May Aid in Predicting Lymph Node Metastasis in Patients with T1 Colorectal Cancer.

Background/aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC.

Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC.

Rapid isolation of cytotoxic daphnane diterpenoids from Daphne altaica Pall. using MS-DIAL.

Daphnane diterpenoids occurring in plants of the Thymelaeaceae are the focus of natural product drug discovery because of the wide range of their therapeutically biological activities. Considering the limited occurrence in some plants of the Thymelaeaceae, it is imperative to design a strategy for the target isolation of daphnane diterpenoids. In this study, a strategy was developed to filter the data using MZmine, generate the molecular network using the Global Natural Product Social Molecular Network Platform (GNPS), and determine the retention time of target compounds using MS-DIAL.