cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.12552
title: Metformin inhibits diabetes induced ferroptosis in renal proximal tubular epithelial cells by up-regulating NRF2 expression
title: 二甲双胍通过上调Nrf2表达抑制糖尿病肾小管上皮细胞铁死亡

description: 【ABSTRACT】 AIM: To investigate the mechanism of metformin in inhibiting ferroptosis of diabetic renal tubular epithelial cells by promoting the expression of Nrf2. METHODS: 8-week-old DBA2/J male mice were divided into normal control group, Met group, DM group and DM+Met group. HK-2 cells were divided into four groups: normal glucose group, Met group, high glucose group (30 mmmol/L) and HG + Met group. The changes of Scr, BUN ,ROS, the protein and mRNA expression levels of Nrf2, GPX4 and FTH-1 were measured in the kidney of mice or HK-2 cells. The contents of MDA, Fe2+ and GSH were also detected in renal tissues or the HK-2cells. RESULTS: Compared with the DM group, the levels of BUN, Scr and the score of renal pathological injury scores were significantly reduced and the protein expressions of Nrf2, GPX4 and FTH-1 were significantly increased in the kidney tissue of diabetes mice treated with metformin(all p＜0.05) . Compared with the HG group, the expression levels of Nrf2, GPX4, FTH-1 protein and mRNA were significantly promoted, the GSH content was increased and intracellular ROS, MDA, and Fe2+content were decreased in high glucose-induced HK-2 cells treated with metformin ( all p＜0.05).CONCLUSION:Metformin can suppress ferroptosis induced by high glucose and alleviate diabetic tubulopathy. The mechanism may be through up-regulating the expression of Nrf2 in renal tubular epithelial cells.
description: 【ABSTRACT】 AIM: To investigate the mechanism of metformin in inhibiting ferroptosis of diabetic renal tubular epithelial cells by promoting the expression of Nrf2. METHODS: 8-week-old DBA2/J male mice were divided into normal control group, Met group, DM group and DM+Met group. HK-2 cells were divided into four groups: normal glucose group, Met group, high glucose group (30 mmmol/L) and HG + Met group. The changes of Scr, BUN ,ROS, the protein and mRNA expression levels of Nrf2, GPX4 and FTH-1 were measured in the kidney of mice or HK-2 cells. The contents of MDA, Fe2+ and GSH were also detected in renal tissues or the HK-2cells. RESULTS: Compared with the DM group, the levels of BUN, Scr and the score of renal pathological injury scores were significantly reduced and the protein expressions of Nrf2, GPX4 and FTH-1 were significantly increased in the kidney tissue of diabetes mice treated with metformin(all p＜0.05) . Compared with the HG group, the expression levels of Nrf2, GPX4, FTH-1 protein and mRNA were significantly promoted, the GSH content was increased and intracellular ROS, MDA, and Fe2+content were decreased in high glucose-induced HK-2 cells treated with metformin ( all p＜0.05).CONCLUSION:Metformin can suppress ferroptosis induced by high glucose and alleviate diabetic tubulopathy. The mechanism may be through up-regulating the expression of Nrf2 in renal tubular epithelial cells.
DOI: 10.57760/sciencedb.o00130.03734
title: The design of emulated target trials and the application in evaluating vaccine effectiveness
title: 模拟目标临床试验设计及在疫苗保护效果评价中的应用

description: Randomized controlled trials have long been regarded as the "gold standard" for evaluating vaccine efficacy. However, conducting RCTs for vaccines in real-world studies is not always feasible due to limitations in research resources and ethical considerations. In recent years, the emulated target trial, a novel research framework, has emerged. This method applies the design principles of randomized trials to observational studies by using observational data to emulate the randomization and grouping of a clinical trial, thereby assessing vaccine effectiveness in the real world. The application of emulated target trials enhances the quality and utility of real-world evidence. This article explains the fundamental principles, design elements, advantages, and limitations of using emulated target trials to evaluate vaccine effectiveness, providing theoretical methods and guidance for conducting such studies in China.
description: Randomized controlled trials have long been regarded as the "gold standard" for evaluating vaccine efficacy. However, conducting RCTs for vaccines in real-world studies is not always feasible due to limitations in research resources and ethical considerations. In recent years, the emulated target trial, a novel research framework, has emerged. This method applies the design principles of randomized trials to observational studies by using observational data to emulate the randomization and grouping of a clinical trial, thereby assessing vaccine effectiveness in the real world. The application of emulated target trials enhances the quality and utility of real-world evidence. This article explains the fundamental principles, design elements, advantages, and limitations of using emulated target trials to evaluate vaccine effectiveness, providing theoretical methods and guidance for conducting such studies in China.
DOI: 10.15468/dl.jgzegc
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "TaxonKey is Cydia pomonella (Linnaeus, 1758)",
 "Year 1970-1980"
 ]
}

 The dataset includes 64 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001083-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.j00125.00035
title: Revealing the Correlation of High-frequency Performance of Supercapacitors with Doped Nitrogen Species
title: Revealing the Correlation of High-frequency Performance of Supercapacitors with Doped Nitrogen Species

description: Nitrogen doping has been widely used to enhance the performance of carbon electrodes in supercapacitors, particularly in terms of high-frequency response. However, the charge storage and ion response mechanisms of different nitrogen species at high frequencies is still unclear. In this study, we employ carbonized melamine foam with open surface structure as a simplified model material, enabling a comprehensive analysis of their impact on the ionic response behavior of high-frequency supercapacitors. Through a combination of experiments and first-principles calculations, we uncover that pyrrolic nitrogen, characterized by a higher adsorption energy, enhances the charge storage capacity of the electrode at high frequencies. On the other hand, graphitic nitrogen, with a lower adsorption energy, promotes rapid ion response. Furthermore, we propose the use of adsorption energy as a practical descriptor for electrode/electrolyte design in high-frequency applications, offering a more universal approach for optimizing the performance of N-doped carbon materials. This research contributes to the advancement of high-frequency supercapacitor technology and provides guidance for the development of improved N-doped carbon materials.
description: Nitrogen doping has been widely used to enhance the performance of carbon electrodes in supercapacitors, particularly in terms of high-frequency response. However, the charge storage and ion response mechanisms of different nitrogen species at high frequencies is still unclear. In this study, we employ carbonized melamine foam with open surface structure as a simplified model material, enabling a comprehensive analysis of their impact on the ionic response behavior of high-frequency supercapacitors. Through a combination of experiments and first-principles calculations, we uncover that pyrrolic nitrogen, characterized by a higher adsorption energy, enhances the charge storage capacity of the electrode at high frequencies. On the other hand, graphitic nitrogen, with a lower adsorption energy, promotes rapid ion response. Furthermore, we propose the use of adsorption energy as a practical descriptor for electrode/electrolyte design in high-frequency applications, offering a more universal approach for optimizing the performance of N-doped carbon materials. This research contributes to the advancement of high-frequency supercapacitor technology and provides guidance for the development of improved N-doped carbon materials.
DOI: 10.57760/sciencedb.hjs.00080
title: Prediction of heat transfer parameters of nuclear reactor based on physical information machine learning algorithm
title: 基于物理信息机器学习算法的核反应堆换热系数预测——数据集

description: The accurate prediction of the heat transfer coefficient (HTC) under extremely high parameter conditions in nuclear reactors is crucial for reactor design and operation. However, this involves complex phenomena influenced by multiple factors across different flow patterns, and the physical mechanisms are not fully understood. Due to the lack of experimental data that meet the high temperature and pressure parameters of actual reactors, semi-empirical relationships that heavily rely on experimental data find it difficult to meet the requirements for high-precision numerical calculations in nuclear reactors.Deep learning algorithms can effectively solve complex nonlinear problems, but they have limitations such as poor extrapolation performance and overfitting. This study develops an HTC prediction model by combining prior physical information from the Jens-Lottes relationship and Thom relationship with machine learning algorithms, including multilayer perceptrons, backpropagation neural networks, and random forests. The model is trained and validated using experimental data from circular tube channels, and the applicability and prediction accuracy of six different machine learning algorithm models based on physical information are evaluated.
description: The accurate prediction of the heat transfer coefficient (HTC) under extremely high parameter conditions in nuclear reactors is crucial for reactor design and operation. However, this involves complex phenomena influenced by multiple factors across different flow patterns, and the physical mechanisms are not fully understood. Due to the lack of experimental data that meet the high temperature and pressure parameters of actual reactors, semi-empirical relationships that heavily rely on experimental data find it difficult to meet the requirements for high-precision numerical calculations in nuclear reactors.Deep learning algorithms can effectively solve complex nonlinear problems, but they have limitations such as poor extrapolation performance and overfitting. This study develops an HTC prediction model by combining prior physical information from the Jens-Lottes relationship and Thom relationship with machine learning algorithms, including multilayer perceptrons, backpropagation neural networks, and random forests. The model is trained and validated using experimental data from circular tube channels, and the applicability and prediction accuracy of six different machine learning algorithm models based on physical information are evaluated.
DOI: 10.57760/sciencedb.12568
title: TRIM56 restricts Coxsackievirus B infection by mediating the ubiquitination of viral RNA-dependent RNA polymerase 3D
title: TRIM56 restricts Coxsackievirus B infection by mediating the ubiquitination of viral RNA-dependent RNA polymerase 3D

description: The data includes Western blot data and RT qPCR data 
description: The data includes Western blot data and RT qPCR data
DOI: 10.15468/dl.qjqc7t
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "TaxonKey is Cydia pomonella (Linnaeus, 1758)",
 "Year 1980-1990"
 ]
}

 The dataset includes 24 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001084-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.12586
title: NIW in the northern SCS
title: NIW in the northern SCS

description: Near inertial internal wave energy induced by typhoon Mangkhut in September 2018 at 20.4N, 110.6E in the northern South China Sea
description: Near inertial internal wave energy induced by typhoon Mangkhut in September 2018 at 20.4N, 110.6E in the northern South China Sea
DOI: 10.57760/sciencedb.12589
title: Sequence information of the influenza B subtype pseudoteped virus library
title: Sequence information of the influenza B subtype pseudoteped virus library

description: The database contains sequence information for all strains used in this study, which was obtained from the GISAID
description: The database contains sequence information for all strains used in this study, which was obtained from the GISAID
DOI: 10.57760/sciencedb.12605
title: Guanosine enhances the bactericidal effect of cefotaxime sodium on Streptococcus suis by activating bacterial metabolism
title: Guanosine enhances the bactericidal effect of cefotaxime sodium on Streptococcus suis by activating bacterial metabolism

description: The emergence and rapid development of antibiotic resistance poses a serious threat to global public health. Streptococcus suis (S. suis) is an important zoonotic pathogen, and the development of its antibiotic resistance has made the infections difficult to treat. The combination of non-antibiotic compounds with antibiotics is considered a promising strategy against multidrug-resistant bacteria. However, the mechanism by which metabolites act as antibiotic adjuvant remains unclear. Here, we found that guanosine metabolism was repressed in multidrug-resistant S. suis. Exogenous guanosine promoted the antibacterial effects of ceftiofur sodium (CEF) in vitro and in vivo. Furthermore, we demonstrated that exogenous guanosine promoted the biosynthesis of purine pathway, TCA cycle and bacterial respiration, which make bacteria more sensitive to the killing effect of antibacterial. In addition, the function of the cell membrane is affected by guanosine and the accumulation of antimicrobials in the bacteria increased. Bacterial-oxidative stress and DNA damage induced by guanosine is also one of the mechanisms by which the antibacterial effect is enhanced. These results suggest that guanosine is a promising adjuvant for antibacterial drugs and provide new theoretical basis for the clinical treatment of S. suis infection.
description: The emergence and rapid development of antibiotic resistance poses a serious threat to global public health. Streptococcus suis (S. suis) is an important zoonotic pathogen, and the development of its antibiotic resistance has made the infections difficult to treat. The combination of non-antibiotic compounds with antibiotics is considered a promising strategy against multidrug-resistant bacteria. However, the mechanism by which metabolites act as antibiotic adjuvant remains unclear. Here, we found that guanosine metabolism was repressed in multidrug-resistant S. suis. Exogenous guanosine promoted the antibacterial effects of ceftiofur sodium (CEF) in vitro and in vivo. Furthermore, we demonstrated that exogenous guanosine promoted the biosynthesis of purine pathway, TCA cycle and bacterial respiration, which make bacteria more sensitive to the killing effect of antibacterial. In addition, the function of the cell membrane is affected by guanosine and the accumulation of antimicrobials in the bacteria increased. Bacterial-oxidative stress and DNA damage induced by guanosine is also one of the mechanisms by which the antibacterial effect is enhanced. These results suggest that guanosine is a promising adjuvant for antibacterial drugs and provide new theoretical basis for the clinical treatment of S. suis infection.
DOI: 10.57760/sciencedb.12600
title: Research on the Application of Geofence Buffer in UAV Path Tracking
title: 地理围栏缓冲区在无人机路径跟踪中的应用研究

description: In environments characterized by high complexity and dense obstacles, the actual flight trajectories of unmanned aerial vehicles (UAVs) often deviate from the predetermined optimal paths, particularly when shortest path algorithms are utilized for route planning. This deviation is especially pronounced, thereby increasing the risk of collision with obstacles. To address this challenge, the concept of geofence buffer zones is introduced in this study. By establishing buffer areas of specific widths around obstacles and deploying artificial potential field functions within these areas, the existing path tracking algorithms are enhanced, significantly reducing the likelihood of collisions between UAVs and obstacles. Furthermore, a series of comparative experiments are conducted on multi-rotor UAVs in a virtually dense obstacle environment using software-in-the-loop simulation technology. The experimental conditions include no minimum speed limit, a set minimum speed limit, and various turning radii. The results quantitatively confirm the significant effectiveness of geofence buffer zones in obstacle avoidance. The findings of this research not only provide a new perspective on path planning and tracking for UAVs in complex environments but also offer theoretical support for enhancing their autonomous flight capabilities.
description: In environments characterized by high complexity and dense obstacles, the actual flight trajectories of unmanned aerial vehicles (UAVs) often deviate from the predetermined optimal paths, particularly when shortest path algorithms are utilized for route planning. This deviation is especially pronounced, thereby increasing the risk of collision with obstacles. To address this challenge, the concept of geofence buffer zones is introduced in this study. By establishing buffer areas of specific widths around obstacles and deploying artificial potential field functions within these areas, the existing path tracking algorithms are enhanced, significantly reducing the likelihood of collisions between UAVs and obstacles. Furthermore, a series of comparative experiments are conducted on multi-rotor UAVs in a virtually dense obstacle environment using software-in-the-loop simulation technology. The experimental conditions include no minimum speed limit, a set minimum speed limit, and various turning radii. The results quantitatively confirm the significant effectiveness of geofence buffer zones in obstacle avoidance. The findings of this research not only provide a new perspective on path planning and tracking for UAVs in complex environments but also offer theoretical support for enhancing their autonomous flight capabilities.
DOI: 10.57760/sciencedb.12606
title: SILK ROAD TOURISM
title: SILK ROAD TOURISM

description: Uzbekistan is synonymous with the Silk Road, with much of this famous trade route passing through its territory. Cities like Andijan, Kokand, Bukhara, Shakhrisabz, Samarkand, and Khiva flourished as trade and craft centers along the Silk Road.
description: Uzbekistan is synonymous with the Silk Road, with much of this famous trade route passing through its territory. Cities like Andijan, Kokand, Bukhara, Shakhrisabz, Samarkand, and Khiva flourished as trade and craft centers along the Silk Road.
DOI: 10.57760/sciencedb.12609
title: Surface Modification of Medical Grade Biomaterials by Using Low-Temperature -Processed Dual Functional Ag-TiO2 coating for preventing Biofilm Formation
title: Surface Modification of Medical Grade Biomaterials by Using Low-Temperature -Processed Dual Functional Ag-TiO2 coating for preventing Biofilm Formation

description: All raw data are provided
description: All raw data are provided
DOI: 10.57760/sciencedb.12610
title: Data Table of Traffic Blockage in Tibet Passage
title: 进藏通道交通阻断数据表

description: Traffic interruption data
description: Traffic interruption data
DOI: 10.57760/sciencedb.12628
title: Kazakhstan, Kostanay region Fire 2022
title: Kazakhstan, Kostanay region Fire 2022

description: These data include the results of machine learning applied to the case of finding the fire area of the Kostanay region in Kazakhstan in 2022. The source data is available, in the form of a stack of images in visible and false colors. Also, there are ROI files where the selected areas are assigned two classes： fire and no fire. And then machine learning methods are used for data in the infrared range of Landsat-8 and Sentinel-2.
description: These data include the results of machine learning applied to the case of finding the fire area of the Kostanay region in Kazakhstan in 2022. The source data is available, in the form of a stack of images in visible and false colors. Also, there are ROI files where the selected areas are assigned two classes： fire and no fire. And then machine learning methods are used for data in the infrared range of Landsat-8 and Sentinel-2.
DOI: 10.57760/sciencedb.12629
title: Data of K-Ar dating of small samples using isotope dilution measurement of potassium
title: Data of K-Ar dating of small samples using isotope dilution measurement of potassium

description: We present a detailed procedure for precise determination of potassium concentrations of small geological samples using isotope dilution (ID). To significantly reduce the Ar+ related interference, a “cold plasma” technique is used on a Nu plasma multicollector ICPMS, facilitating the precise measurement of 41K+/39K+ at high mass resolution mode. The K concentrations of USGS standards (BHVO-2, BCR-2, AGV-2 and SBC-1) were determined by ID, with overall analytical uncertainties better than 2.5%. The variance is most likely dominated by weighing errors for small samples, and chemical heterogeneities under 5 mg sub-sampling scale. Using this technique, we were able to determine the K contents of single clay pellets (~0.1mg) previously degassed under vacuum to measure Ar concentrations, thereby enabling precise measurement of K-Ar ages.
description: We present a detailed procedure for precise determination of potassium concentrations of small geological samples using isotope dilution (ID). To significantly reduce the Ar+ related interference, a “cold plasma” technique is used on a Nu plasma multicollector ICPMS, facilitating the precise measurement of 41K+/39K+ at high mass resolution mode. The K concentrations of USGS standards (BHVO-2, BCR-2, AGV-2 and SBC-1) were determined by ID, with overall analytical uncertainties better than 2.5%. The variance is most likely dominated by weighing errors for small samples, and chemical heterogeneities under 5 mg sub-sampling scale. Using this technique, we were able to determine the K contents of single clay pellets (~0.1mg) previously degassed under vacuum to measure Ar concentrations, thereby enabling precise measurement of K-Ar ages.
DOI: 10.57760/sciencedb.12633
title: Mobile MAX-DOAS measurements for emission quantifications and source analysis of NO2, HCHO and HONO during Chengdu 2023 FISU World
title: Mobile MAX-DOAS measurements for emission quantifications and source analysis of NO2, HCHO and HONO during Chengdu 2023 FISU World

description: 共享数据包括成都大学生运动会期间通过移动 MAX-DOAS 测量的 NO2、HCHO 和 HONO 的空间分布
description: 共享数据包括成都大学生运动会期间通过移动 MAX-DOAS 测量的 NO2、HCHO 和 HONO 的空间分布