A mini review of recent advances in environmentally friendly microplastic removal technologies in water systems.

The current increase in microplastic (MP) occurrence worldwide is predicted to cause severe environmental crises in the future. Therefore, it is imperative to develop innovative MP removal technologies that can effectively mitigate MP emissions in any given scenario. This review discusses recent environmentally friendly advances in MP removal technologies that aim to overcome the limitations of current technologies, prevent secondary pollution, and utilize low energy.

Initial Evaluation of the Safety and Performance of Single-Port Robotic-Assisted Thymectomy Via Subxiphoid Incision.

Background: Sternotomy is the traditional approach for thymectomy. However, over the last 2 decades minimally invasive surgical approaches (multiport thoracoscopic and robotic-assisted surgery) have proven feasible, offering similar survival, lower morbidity and shorter length of stay. Single-port (SP), subxiphoid thymectomy potentially offers less pain and allows bilateral visualization of the mediastinum.

A microRNA is the effector gene of a classic evolutionary hotspot locus.

In Lepidoptera (butterflies and moths), the genomic region around the gene is a "hotspot" locus, repeatedly implicated in generating intraspecific melanic wing color polymorphisms across 100 million years of evolution. However, the identity of the effector gene regulating melanic wing color within this locus remains unknown. We show that none of the four candidate protein-coding genes within this locus, including , serve as major effectors.

Rapid response to fast viral evolution using AlphaFold 3-assisted topological deep learning.

The fast evolution of SARS-CoV-2 and other infectious viruses poses a grand challenge to the rapid response in terms of viral tracking, diagnostics, and design and manufacture of monoclonal antibodies (mAbs) and vaccines, which are both time-consuming and costly. This underscores the need for efficient computational approaches. Recent advancements, like topological deep learning (TDL), have introduced powerful tools for forecasting emerging dominant variants, yet they require deep mutational scanning (DMS) of viral surface proteins and associated three-dimensional (3D) protein-protein interaction (PPI) complex structures.