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Protected aquatic wildlife is an important part of the aquatic ecosystems. This paper used CiteSpace document visualization software to analyze the literature on protected aquatic wildlife from 2001 to 2020 in the core database of Web of Science (WoS) and the full-text database of China National Knowledge Infrastructure (CNKI). This paper conducted the knowledge map analysis of annual publication volume, cooperative institutions, national cooperation and keyword clustering. The study found that a total of 634 foreign language papers were published in the past 20 years, with an upward trend in the number of publications, and 128 documents in Chinese showed a fluctuation trend; the organization with the largest number of foreign publications was the US Fish & Wildlife Service, with closer cooperation among research institutions, the organization with the largest number of domestic publications was the Qinghai Fishery Environmental Monitoring Station, with scattered cooperation among research institutions; the United States issued 58.20% of the articles, and had the most close communication with other countries, China issued only 3.31% of the articles, with limited international cooperation; foreign research hotspots were mainly population dynamic distribution, habitat use and genetic diversity and both marine and freshwater species had been studied; domestic research hotspots were mainly regional conservation measures, mainly focusing on the study of freshwater protected aquatic wildlife and there were limitations in the scope of the study. The comprehensive analysis suggested that China should enhance the communication and cooperation between domestic and foreign research institutions, attach importance to the conservation and research of marine endangered aquatic wildlife, strengthen the population dynamics assessment, and carry out domestic research on the habitat use and genetic diversity analysis of protected aquatic wildlife, so as to achieve the recovery of protected aquatic wildlife populations.

Abstract Background The combination of transcatheter arterial chemoembolization (TACE) plus sorafenib prolonged progression-free survival (PFS) and overall survival (OS) than sorafenib or TACE monotherapy for patients with hepatocellular carcinoma (HCC). This study assessed the efficacy and safety of radiotherapy (RT) plus monoclonal antibody against programmed cell death 1 (anti-PD1) versus TACE plus sorafenib for patients with advanced HCC. Methods Patients with advanced HCC who treated with RT plus anti-PD1 and TACE plus sorafenib were enrolled. Objective response rate (ORR), PFS, disease control rate (DCR) and OS were calculated to assess the antitumor response and the treatment-related adverse events to the safety. Results Between January 2018 to March 2021, 37 patients underwent RT plus anti-PD1 and 41 patients underwent TACE plus sorafenib. The baseline characteristics between the two groups were comparable. The ORR and DCR were significantly higher in the RT + PD1 group than the TACE plus sorafenib group according to RECIST 1.1 (54.05% vs. 12.20%, P

Background: Enlarged pores are amidst one of the top cosmetic concerns, especially among Chinese. Many small‐group studies have been conducted in understanding their prevalence and beauty relevance. Nonetheless, population‐level investigations are still lacking because of gaps in data collection and processing of large‐scale studies. Owing to the recent technological advancement enabled by artificial intelligence, databases on the scale of millions can be processed and analyzed readily. Materials and methods: Powered by big data capabilities, revealed a number of novel trends on pore conditions among over‐a‐million Chinese participants recruited via the "You Look Great Today" mobile application. A scoring model was constructed, which demonstrated high consistency with conventional grading method from dermatologists. Environmental data (weather, air pollution, light at night satellite) were applied to correlate with pore severity. Results: Intraclass correlations between the two scoring systems were strong, with coefficients ranging from 0.79 to 0.92 for different facial areas. Statistical differences in pore severity among all four facial areas (cheek, forehead, nose, and overall) were observed, with the cheek exhibiting the most severe pore condition. Interestingly, Chinese men suffer from more severe pore condition than females. Multiple environmental factors exhibited strong correlations with cheek pore severity and were statistically fitted into linear regressions. Specifically, incremental risk with Each Low Temperature, Low Humidity, And High Solar Exposure correlate to worse cheek pore conditions. Although the Pearson correlation was low between cheek pore severity and light at night, comparison between representative cities demonstrated that in geologically similar cities, higher light at night corresponds to more severe cheek pore conditions. Conclusion: Our study is showcasing a robust and reliable AI model in facial pore evaluation. More importantly, insights uncovered using this facile approach also bear significant cosmetic ramifications in treatment of pore enlargement. [ABSTRACT FROM AUTHOR]

Recently, cardiovascular disease has become the leading cause of death worldwide. Abnormal heart rate signals are an important indicator of cardiovascular disease. At present, the ECG signal acquisition instruments on the market are not portable and manual analysis is applied in data processing, which cannot address the above problems. To solve these problems, this study proposes an ECG acquisition and analysis system based on machine learning. The ECG analysis system responsible for ECG signal classification includes two parts: data preprocessing and machine learning models. Multiple types of models were built for overall classification, and model fusion was conducted. Firstly, traditional models such as logistic regression, support vector machines, and XGBoost were employed, along with feature engineering that primarily included morphological features and wavelet coefficient features. Subsequently, deep learning models, including convolutional neural networks and long short-term memory networks, were introduced and utilized for model fusion classification. The system’s classification accuracy for ECG signals reached 99.13%. Future work will focus on optimizing the model and developing a more portable instrument that can be utilized in the field.

In recent years, with the rapid development of renewable energy, the penetration rate of renewable energy generation in the active distribution network (ADN) has increased. Because of the instability of renewable energy generation, the operation stability of ADN has decreased. Due to the ability to cut peak load and fill valley load, battery energy storage systems (BESSs) can enhance the stability of the electric system. However, the placement and capacity of BESSs connected to ADN are extremely significant, otherwise, it will lead to a further decline in the stability of ADN. To ensure the effectiveness of the BESSs connected to the grid, this work uses the fuzzy kernel C-means (FKCM) method for scene clustering. Meanwhile, a multi-objective optimization model of BESS configuration is established with the objective of BESS configuration cost, voltage fluctuation, and load fluctuation, and solved by non-dominated sorting genetic algorithm-II (NSGA-II). In this work, the grey target decision method based on the entropy weight method (EWM) is used to obtain the optimal compromise solution from the Pareto non-dominated set. Moreover, the proposed method is tested and verified in the extended IEEE-33 node system and the extended IEEE-69 node system. The results show that the BESSs configuration scheme obtained by NSGA-II can effectively reduce the fluctuation of voltage and load, and improve the stability of ADN operation.

InSe, a member of the layered materials family, is a superior electronic and optical material which retains a direct bandgap feature from the bulk to atomically thin few-layers and high electronic mobility down to a single layer limit. We, for the first time, exploit strain to drastically modify the bandgap of two-dimensional (2D) InSe nanoflakes. We demonstrated that we could decrease the bandgap of a few-layer InSe flake by 160 meV through applying an in-plane uniaxial tensile strain to 1.06% and increase the bandgap by 79 meV through applying an in-plane uniaxial compressive strain to 0.62%, as evidenced by photoluminescence (PL) spectroscopy. The large reversible bandgap change of ∼239 meV arises from a large bandgap change rate (bandgap strain coefficient) of few-layer InSe in response to strain, ∼154 meV/% for uniaxial tensile strain and ∼140 meV/% for uniaxial compressive strain, representing the most pronounced uniaxial strain-induced bandgap strain coefficient experimentally reported in 2D materials. We developed a theoretical understanding of the strain-induced bandgap change through first-principles DFT and GW calculations. We also confirmed the bandgap change by photoconductivity measurements using excitation light with different photon energies. The highly tunable bandgap of InSe in the infrared regime should enable a wide range of applications, including electro-mechanical, piezoelectric and optoelectronic devices.

Abstract Brain–machine interface (BMI) is a device that translates neuronal information into commands, which is capable of controlling external software or hardware, such as a computer or robotic arm. In consequence, the electrodes with desirable electrical and mechanical properties for direct interacting between neural tissues and machines serves as the crucial and critical part of BMI technology. Nowadays, the development of material science provides many advanced electrodes for neural stimulating and recording. Particularly, the widespread applications of nanotechnologies have innovatively introduced biocompatible electrode that can have similar characteristics with neural tissue. This paper reviews the existing problems and discusses the latest development of electrode materials for BMI, including conducting polymers, silicon, carbon nanowires, graphene, and hybrid organic–inorganic nanomaterials. In addition, we will inspect at the technical and scientific challenges in the development of neural electrode for a broad application of BMI with focus on the biocompatibility, mechanical mismatch, and electrical performance of electrode materials.

Cytotoxic CD8 T cells are crucial for the host antigen-specific immune response to viral pathogens. Here we report the identification of an essential role for the serine/arginine-rich splicing factor (SRSF) 1 in CD8 T cell homeostasis and function. Specifically, SRSF1 is necessary for the maintenance of normal CD8 T lymphocyte numbers in the lymphoid compartment, and for the proliferative capacity and cytotoxic function of CD8 T cells. Furthermore, SRSF1 is required for antigen-specific IFN-γ cytokine responses in a viral infection challenge in mice. Transcriptomics analyses of Srsf1-deficient T cells reveal that SRSF1 controls proliferation, MAP kinase signaling and IFN signaling pathways. Mechanistically, SRSF1 controls the expression and activity of the Mnk2/p38-MAPK axis at the molecular level. Our findings reveal previously unrecognized roles for SRSF1 in the physiology and function of cytotoxic CD8 T lymphocytes and a potential molecular mechanism in viral immunopathogenesis.

The human ether-á-go-go-related gene (hERG) encodes the pore-forming subunit (Kv11.1), conducting a rapidly delayed rectifier K+ current (IKr). Reduction of IKr in pathological cardiac hypertrophy (pCH) contributes to increased susceptibility to arrhythmias. However, practical approaches to prevent IKr deficiency are lacking. Our study investigated the involvement of ubiquitin ligase Nedd4-2-dependent ubiquitination in IKr reduction and sought an intervening approach in pCH. Angiotensin II (Ang II) induced a pCH phenotype in guinea pig, accompanied by increased incidences of sudden death and higher susceptibility to arrhythmias. Patch-clamp recordings revealed a significant IKr reduction in pCH cardiomyocytes. Kv11.1 protein expression was decreased whereas its mRNA level did not change. In addition, Nedd4-2 protein expression was increased in pCH, accompanied by an enhanced Nedd4-2 and Kv11.1 binding detected by immunoprecipitation analysis. Cardiac-specific overexpression of inactive form of Nedd4-2 shortened the prolonged QT interval, reversed IKr reduction, and decreased susceptibility to arrhythmias. A synthesized peptide containing the PY motif in Kv11.1 C-terminus binding to Nedd4-2 and a cell-penetrating sequence antagonized Nedd4-2-dependent degradation of the channel and increased the surface abundance and function of hERG channel in HEK cells. In addition, in vivo administration of the PY peptide shortened QT interval and action potential duration, and enhanced IKr in pCH. We conclude that Nedd4-2-dependent ubiquitination is critically involved in IKr deficiency in pCH. Pharmacological suppression of Nedd4-2 represents a novel approach for antiarrhythmic therapy in pCH.

With the large-scale development of renewable energy sources such as wind and solar energy, the grid connection of renewable energy sources poses a certain threat to the security and stability of the power system, and also brings a great challenge to the economic dispatch of the distribution network. Traditional and single dispatching methods such as load demand response or network reconfiguration alone cannot meet the needs of a safe and economic operation of the distribution network. This article proposes an economic dispatching method for distribution networks with dispersed wind power considering network reconfiguration, and establishes an economic dispatching model with the objective function of minimizing distribution network operation cost, reconfiguration cost, and total system network loss. Based on the optimal scheduling of energy storage and reactive power compensation devices in the distribution network and the full utilization of demand response, a mixed integer second-order cone programming (MISOCP) method with multi-objective collaborative optimization is proposed. The results of the tests using the IEEE33 node system verify the feasibility and applicability of the proposed method in this article.

BackgroundRadiation-induced lung injury (RILI) is a severe side effect of radiotherapy for non-small cell lung cancer (NSCLC) ,and one of the major hindrances to improve the efficacy of radiotherapy. Previous studies have confirmed that sodium butyrate (NaB) has potential of anti-radiation toxicity. However, the mechanism of the protective effect of NaB against RILI has not yet been clarified. This study aimed to explore the underlying protective mechanisms of NaB against RILI in NSCLC through network pharmacology, molecular docking, molecular dynamic simulations and in vivo experiments.MethodsThe predictive target genes of NaB were obtained from the PharmMapper database and the literature review. The involved genes of RILI and NSCLC were predicted using OMIM and GeneCards database. The intersectional genes of drug and disease were identified using the Venny tool and uploaded to the Cytoscape software to identify 5 core target genes of NaB associated with RILI. The correlations between the 5 core target genes and EGFR, PD-L1, immune infiltrates, chemokines and chemokine receptors were analyzed using TIMER 2.0, TIMER and TISIDB databases. We constructed the mechanism maps of the 3 key signaling pathways using the KEGG database based on the results of GO and KEGG analyses from Metascape database. The 5 core target genes and drug were docked using the AutoDock Vina tool and visualized using PyMOL software. GROMACS software was used to perform 100 ns molecular dynamics simulation. Irradiation-induced lung injury model in mice were established to assess the therapeutic effects of NaB.ResultsA total of 51 intersectional genes involved in NaB against RILI in NSCLC were identified. The 5 core target genes were AKT1, TP53, NOTCH1, SIRT1, and PTEN. The expressions of the 5 core target genes were significantly associated with EGFR, PD-L1, immune infiltrates, chemokines and chemokine receptors, respectively. The results from GO analysis of the 51 intersectional genes revealed that the biological processes were focused on the regulation of smooth muscle cell proliferation, oxidative stress and cell death, while the three key KEGG pathways were enriched in PI3K-Akt signal pathway, p53 signal pathway, and FOXO signal pathway. The docking of NaB with the 5 core target genes showed affinity and stability, especially AKT1. In vivo experiments showed that NaB treatment significantly protected mice from RILI, with reduced lung histological damage. In addition, NaB treatment significantly inhibited the PI3K/Akt signaling pathway.ConclusionsNaB may protect patients from RILI in NSCLC through multiple target genes including AKT1, TP53, NOTCH1, SIRT1 and PTEN, with multiple signaling pathways involving, including PI3K-Akt pathway, p53 pathway, and FOXO pathways. Our findings effectively provide a feasible theoretical basis to further elucidate the mechanism of NaB in the treatment of RILI.

Abstract Background The optimal dose and fractionation scheme of stereotactic body radiation therapy (SBRT) for hepatocellular carcinoma (HCC) remains unclear due to different tolerated liver volumes and degrees of cirrhosis. In this study, we aimed to verify the dose-survival relationship to optimize dose selection for treatment of HCC. Methods This multicenter retrospective study included 602 patients with HCC, treated with SBRT between January 2011 and March 2017. The SBRT dosage was classified into high dose, moderate dose, and low dose levels: SaRT (BED10 ≥ 100 Gy), SbRT (EQD2 > 74 Gy to BED10