Magnetic-field-induced electronic instability of Weyl-like fermions in compressed black phosphorus

Revealing the role of Coulomb interaction in topological semimetals with Dirac/Weyl-like band dispersion shapes a new frontier in condensed matter physics. Topological node-line semimetals (TNLSMs), anticipated as a fertile ground for exploring electronic correlation effects due to the anisotropy associated with their node-line structure, have recently attracted considerable attention. In this study, we report an experimental observation for correlation effects in TNLSMs realized by black phosphorus (BP) under hydrostatic pressure. By performing a combination of nuclear magnetic resonance measurements and band calculations on compressed BP, a magnetic-field-induced electronic instability of Weyl-like fermions is identified under an external magnetic field parallel to the so-called nodal ring in the reciprocal space. Anomalous spin fluctuations serving as the fingerprint of electronic instability are observed at low temperatures, and they are observed to maximize at approximately 1.0 GPa. This study presents compressed BP as a realistic material platform for exploring the rich physics in strongly coupled Weyl-like fermions.Comment: 10 pages, 4 figure

Highly potent multivalent VHH antibodies against Chikungunya isolated from an alpaca naïve phage display library

Background Chikungunya virus (CHIKV) is a re-emerged mosquito-borne alphavirus that can cause musculoskeletal diseases, imposing a substantial threat to public health globally. High-affinity antibodies are need for diagnosis and treatment of CHIKV infections. As a potential diagnostic and therapeutic agent, the multivalent VHH antibodies is a promising tookit in nanomedicine. Here, we developed potent multivalent VHH antibodies from an alpaca naïve phage display library targeting the E2 glycoprotein of the CHIKV virus. Results In the present study, we generated 20 VHH antibodies using a naïve phage display library for binders to the CHIKV E2 glycoprotein. Of these, multivalent VHH antibodies Nb-2E8 and Nb-3C5 had specific high-affinity binding to E2 protein within the nanomolar range. The equilibrium dissociation constant (KD) was between 2.59–20.7 nM, which was 100-fold stronger than the monovalent antibodies’ affinity. Moreover, epitope mapping showed that Nb-2E8 and Nb-3C5 recognized different linear epitopes located on the E2 glycoprotein domain C and A, respectively. A facile protocol of sandwich ELISA was established using BiNb-2E8 as a capture antibody and HRP-conjugated BiNb-3C5 as a detection antibody. A good linear correlation was achieved between the OD450 value and the E2 protein concentration in the 5–1000 ng/mL range (r = 0.9864, P < 0.0001), indicating its potential for quantitative detection of the E2 protein. Conclusions Compared to monovalent antibodies, multivalent VHH antibodies Nb-2E8 and Nb-3C5 showed high affinity and are potential candidates for diagnostic applications to better detect CHIKV virions in sera. Graphical Abstrac

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging

Aim: The detection and segmentation of cerebral microbleeds (CMBs) images are the focus of clinical diagnosis and treatment. However, segmentation is difficult in clinical practice, and missed diagnosis may occur. Few related studies on the automated segmentation of CMB images have been performed, and we provide the most effective CMB segmentation to date using an automated segmentation system.Materials and Methods: From a research perspective, we focused on the automated segmentation of CMB targets in susceptibility weighted imaging (SWI) for the first time and then constructed a deep learning network focused on the segmentation of micro-objects. We collected and marked clinical datasets and proposed a new medical micro-object cascade network (MMOC-Net). In the first stage, U-Net was utilized to select the region of interest (ROI). In the second stage, we utilized a full-resolution network (FRN) to complete fine segmentation. We also incorporated residual atrous spatial pyramid pooling (R-ASPP) and a new joint loss function.Results: The most suitable segmentation result was achieved with a ROI size of 32 × 32. To verify the validity of each part of the method, ablation studies were performed, which showed that the best segmentation results were obtained when FRN, R-ASPP and the combined loss function were used simultaneously. Under these conditions, the obtained Dice similarity coefficient (DSC) value was 87.93% and the F2-score (F2) value was 90.69%. We also innovatively developed a visual clinical diagnosis system that can provide effective support for clinical diagnosis and treatment decisions.Conclusions: We created the MMOC-Net method to perform the automated segmentation task of CMBs in an SWI and obtained better segmentation performance; hence, this pioneering method has research significance