Acoustic Characteristics of Treefrogs from Sichuan, China, with Comments on Systematic Relationship of Polypedates and Rhacophorus (Anura, Rhacophoridae)

Advertisement call characteristics of Polypedates chenfui, P. dugritei, and P. omeimontis, all from Sichuan, China, are described. Calls of the three species differ considerably from each other both in temporal and frequency patterns. Acoustically, these three species cannot be differentiated from some Rhacophorus species from Japan and Taiwan, and the systematic relationship of Polypedates and Rhacophorus needs reassessment

WAL-Net: Weakly supervised auxiliary task learning network for carotid plaques classification

The classification of carotid artery ultrasound images is a crucial means for diagnosing carotid plaques, holding significant clinical relevance for predicting the risk of stroke. Recent research suggests that utilizing plaque segmentation as an auxiliary task for classification can enhance performance by leveraging the correlation between segmentation and classification tasks. However, this approach relies on obtaining a substantial amount of challenging-to-acquire segmentation annotations. This paper proposes a novel weakly supervised auxiliary task learning network model (WAL-Net) to explore the interdependence between carotid plaque classification and segmentation tasks. The plaque classification task is primary task, while the plaque segmentation task serves as an auxiliary task, providing valuable information to enhance the performance of the primary task. Weakly supervised learning is adopted in the auxiliary task to completely break away from the dependence on segmentation annotations. Experiments and evaluations are conducted on a dataset comprising 1270 carotid plaque ultrasound images from Wuhan University Zhongnan Hospital. Results indicate that the proposed method achieved an approximately 1.3% improvement in carotid plaque classification accuracy compared to the baseline network. Specifically, the accuracy of mixed-echoic plaques classification increased by approximately 3.3%, demonstrating the effectiveness of our approach

CRISPR dynamics during the interaction between bacteria and phage in the first year of life

Gut microbiomes in infancy have a profound impact on health in adulthood. CRISPRs play an essential role in the interaction between bacteria and phages. However, the dynamics of CRISPRs in gut microbiomes during early life are poorly understood. In this study, using shotgun metagenomic sequencing data from 82 Swedish infants’ gut microbiomes, 1882 candidate CRISPRs were identified, and their dynamics were analysed. We found large-scale turnover of CRISPRs and their spacers during the first year of life. As well as changes in relative abundance of the bacteria containing CRISPR, acquisition, loss and mutation of spacers were observed within the same CRISPR array sampled over time. Accordingly, the inferred interaction network of bacteria and phage was distinct at different times. This research underpins CRISPR dynamics and their potential role in the interaction between bacteria and phage in early life

CRISPR dynamics during the interaction between bacteria and phage in the first year of life

Gut microbiomes in infancy have a profound impact on health in adulthood. CRISPRs play an essential role in the interaction between bacteria and phages. However, the dynamics of CRISPRs in gut microbiomes during early life are poorly understood. In this study, using shotgun metagenomic sequencing data from 82 Swedish infants' gut microbiomes, 1882 candidate CRISPRs were identified, and their dynamics were analysed. We found large-scale turnover of CRISPRs and their spacers during the first year of life. As well as changes in relative abundance of the bacteria containing CRISPR, acquisition, loss and mutation of spacers were observed within the same CRISPR array sampled over time. Accordingly, the inferred interaction network of bacteria and phage was distinct at different times. This research underpins CRISPR dynamics and their potential role in the interaction between bacteria and phage in early life.</p

Interleukin-17 Inhibits Adult Hippocampal Neurogenesis

Interleukin 17(A) (IL-17) is a potent pro-inflammatory cytokine that acts as a central regulator of inflammatory response within the brain, but its physiological roles under non-inflammatory conditions remain elusive. Here we report that endogenous IL-17 ablates neurogenesis in the adult dentate gyrus (DG) of hippocampus. Genetic deletion of IL-17 increased the number of adult-born neurons in the DG. Further, we found that IL-17 deletion altered cytokine network, facilitated basal excitatory synaptic transmission, enhanced intrinsic neuronal excitability, and increased expression of proneuronal genes in neuronal progenitor cells (NPCs). Our findings suggest a profound role of IL-17 in the negative regulation of adult hippocampal neurogenesis under physiology conditions

Validating quantum-supremacy experiments with exact and fast tensor network contraction

The quantum circuits that declare quantum supremacy, such as Google Sycamore [Nature \textbf{574}, 505 (2019)], raises a paradox in building reliable result references. While simulation on traditional computers seems the sole way to provide reliable verification, the required run time is doomed with an exponentially-increasing compute complexity. To find a way to validate current ``quantum-supremacy" circuits with more than $50$ qubits, we propose a simulation method that exploits the ``classical advantage" (the inherent ``store-and-compute" operation mode of von Neumann machines) of current supercomputers, and computes uncorrelated amplitudes of a random quantum circuit with an optimal reuse of the intermediate results and a minimal memory overhead throughout the process. Such a reuse strategy reduces the original linear scaling of the total compute cost against the number of amplitudes to a sublinear pattern, with greater reduction for more amplitudes. Based on a well-optimized implementation of this method on a new-generation Sunway supercomputer, we directly verify Sycamore by computing three million exact amplitudes for the experimentally generated bitstrings, obtaining an XEB fidelity of $0.191\%$ which closely matches the estimated value of $0.224\%$. Our computation scales up to $41,932,800$ cores with a sustained single-precision performance of $84.8$ Pflops, which is accomplished within $8.5$ days. Our method has a far-reaching impact in solving quantum many-body problems, statistical problems as well as combinatorial optimization problems where one often needs to contract many tensor networks which share a significant portion of tensors in common.Comment: 7 pages, 4 figures, comments are welcome

A Sandwich Electrochemical Immunosensor Using Magnetic DNA Nanoprobes for Carcinoembryonic Antigen

A novel magnetic nanoparticle-based electrochemical immunoassay of carcinoembryonic antigen (CEA) was designed as a model using CEA antibody-functionalized magnetic beads [DNA/Fe3O4/ZrO2; Fe3O4 (core)/ZrO2 (shell) nano particles (ZMPs)] as immunosensing probes. To design the immunoassay, the CEA antibody and O-phenylenediamine (OPD) were initially immobilized on a chitosan/nano gold composite membrane on a glassy carbon electrode (GCE/CS-nano Au), which was used for CEA recognition. Then, horseradish peroxidase (HRP)-labeled anti-CEA antibodies (HRP-CEA Ab2) were bound to the surface of the synthesized magnetic ZMP nanoparticles as signal tag. Thus, the sandwich-type immune complex could be formed between secondary antibody (Ab2) modified DNA/ZMPs nanochains tagged by HRP and GCE/CS-nano Au. Unlike conventional nanoparticle-based electrochemical immunoassays, the recognition elements of this immunoassay included both electron mediators and enzyme labels, which obviously simplifies the electrochemical measurement process. The sandwich-type immunoassay format was used for online formation of the immunocomplex of CEA captured in the detection cell with an external magnet. The electrochemical signals derived from HRP during the reduction of H2O2 with OPD as electron mediator were measured. The method displayed a high sensitivity for CEA detection in the range of 0.008–200 ng/mL, with a detection limit of 5 pg/mL (estimated at a signal-to-noise ratio of 3). The precision, reproducibility, and stability of the immunoassay were good. The use of the assay was evaluated with clinical serum samples, and the results were in excellent accordance with those obtained using the standard enzyme-linked immunosorbent assay (ELISA) method. Thus, the magnetic nanoparticle-based assay format is a promising approach for clinical applications, and it could be further developed for the detection of other biomarkers in cancer diagnosis