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"Wang, JingJing"
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Oxidative Stress in Pancreatic Beta Cell Regeneration
Pancreatic β cell neogenesis and proliferation during the neonatal period are critical for the generation of sufficient pancreatic β cell mass/reserve and have a profound impact on long-term protection against type 2 diabetes (T2D). Oxidative stress plays an important role in β cell neogenesis, proliferation, and survival under both physiological and pathophysiological conditions. Pancreatic β cells are extremely susceptible to oxidative stress due to a high endogenous production of reactive oxygen species (ROS) and a low expression of antioxidative enzymes. In this review, we summarize studies describing the critical roles and the mechanisms of how oxidative stress impacts β cell neogenesis and proliferation. In addition, the effects of antioxidant supplements on reduction of oxidative stress and increase of β cell proliferation are discussed. Exploring the roles and the potential therapeutic effects of antioxidants in the process of β cell regeneration would provide novel perspectives to preserve and/or expand pancreatic β cell mass for the treatment of T2D.
Journal Article
Role of maternal–fetal immune tolerance in the establishment and maintenance of pregnancy
Abstract
Normal pregnancy is a contradictory and complicated physiological process. Although the fetus carries the human leukocyte antigen (HLA) inherited from the paternal line, it does not cause maternal immune rejection. As the only exception to immunological principles, maternal–fetal immune tolerance has been a reproductive immunology focus. In early pregnancy, fetal extravillous trophoblast cells (EVTs) invade decidual tissues and come into direct contact with maternal decidual immune cells (DICs) and decidual stromal cells (DSCs) to establish a sophisticated maternal–fetal crosstalk. This study reviews previous research results and focuses on the establishment and maintenance mechanism of maternal–fetal tolerance based on maternal–fetal crosstalk. Insights into maternal–fetal tolerance will not only improve understanding of normal pregnancy but will also contribute to novel therapeutic strategies for recurrent spontaneous abortion, pre-eclampsia, and premature birth.
Journal Article
The impact of intelligent devices utilization on household medical expenditure of older adults in China
With the rapid development of artificial intelligence, there is an increasing utilization of intelligent devices by older adults. The relationship between the utilization of intelligent devices and household medical expenditure has garnered widespread attention in academic circles. This paper employs data from the 2020 China Longitudinal Aging Social Survey (CLASS) to investigate the impact of intelligent device utilization by 9,718 older adults on household medical consumption. The research findings indicate that the utilization of intelligent devices significantly reduces household medical expenditure, and this conclusion remains valid after placebo tests and endogeneity treatments. From the perspective of heterogeneity, the impact of intelligent device utilization on household medical expenditure is more pronounced among higher age, those living with family, residents of eastern and western regions, and areas with high digital coverage. Quantile regression results reveal a “inverted U-shaped” trend in the impact of intelligent device utilization on household medical expenditure, with an initial increase followed by a decrease. Mechanism analysis suggests that intelligent device utilization reduces household medical expenditure by improving the health behaviors and decreasing the demand for medical services. Based on these findings, this paper argues that enterprises and research institutions should continue to develop intelligent devices tailored to the characteristics of older adults. The government should provide financial subsidies to purchase intelligent devices for older adults. By fully enhancing the utilization of intelligent devices in elderly health management, we can together provide a reference for controlling the excessive growth of medical expenses.
Journal Article
An Enhanced Indoor Positioning Algorithm Based on Fingerprint Using Fine-Grained CSI and RSSI Measurements of IEEE 802.11n WLAN
Received signal strength indication (RSSI) obtained by Medium Access Control (MAC) layer is widely used in range-based and fingerprint location systems due to its low cost and low complexity. However, RSS is affected by noise signals and multi-path, and its positioning performance is not stable. In recent years, many commercial WiFi devices support the acquisition of physical layer channel state information (CSI). CSI is an index that can characterize the signal characteristics with more fine granularity than RSS. Compared with RSS, CSI can avoid the effects of multi-path and noise by analyzing the characteristics of multi-channel sub-carriers. To improve the indoor location accuracy and algorithm efficiency, this paper proposes a hybrid fingerprint location technology based on RSS and CSI. In the off-line phase, to overcome the problems of low positioning accuracy and fingerprint drift caused by signal instability, a methodology based on the Kalman filter and a Gaussian function is proposed to preprocess the RSSI value and CSI amplitude value, and the improved CSI phase is incorporated after the linear transformation. The mutation and noisy data are then effectively eliminated, and the accurate and smoother outputs of the RSSI and CSI values can be achieved. Then, the accurate hybrid fingerprint database is established after dimensionality reduction of the obtained high-dimensional data values. The weighted k-nearest neighbor (WKNN) algorithm is applied to reduce the complexity of the algorithm during the online positioning stage, and the accurate indoor positioning algorithm is accomplished. Experimental results show that the proposed algorithm exhibits good performance on anti-noise ability, fusion positioning accuracy, and real-time filtering. Compared with CSI-MIMO, FIFS, and RSSI-based methods, the proposed fusion correction method has higher positioning accuracy and smaller positioning error.
Journal Article
Construction of a human cell landscape at single-cell level
Single-cell analysis is a valuable tool for dissecting cellular heterogeneity in complex systems
1
. However, a comprehensive single-cell atlas has not been achieved for humans. Here we use single-cell mRNA sequencing to determine the cell-type composition of all major human organs and construct a scheme for the human cell landscape (HCL). We have uncovered a single-cell hierarchy for many tissues that have not been well characterized. We established a ‘single-cell HCL analysis’ pipeline that helps to define human cell identity. Finally, we performed a single-cell comparative analysis of landscapes from human and mouse to identify conserved genetic networks. We found that stem and progenitor cells exhibit strong transcriptomic stochasticity, whereas differentiated cells are more distinct. Our results provide a useful resource for the study of human biology.
Single-cell RNA sequencing is used to generate a dataset covering all major human organs in both adult and fetal stages, enabling comparison with similar datasets for mouse tissues.
Journal Article
Application of Artificial Intelligence in Geriatric Care: Bibliometric Analysis
Artificial intelligence (AI) can improve the health and well-being of older adults and has the potential to assist and improve nursing care. In recent years, research in this area has been increasing. Therefore, it is necessary to understand the status of development and main research hotspots and identify the main contributors and their relationships in the application of AI in geriatric care via bibliometric analysis.
Using bibliometric analysis, this study aims to examine the current research hotspots and collaborative networks in the application of AI in geriatric care over the past 23 years.
The Web of Science Core Collection database was used as a source. All publications from inception to August 2022 were downloaded. The external characteristics of the publications were summarized through HistCite and the Web of Science. Keywords and collaborative networks were analyzed using VOSviewers and Citespace.
We obtained a total of 230 publications. The works originated in 499 institutions in 39 countries, were published in 124 journals, and were written by 1216 authors. Publications increased sharply from 2014 to 2022, accounting for 90.87% (209/230) of all publications. The United States and the International Journal of Social Robotics had the highest number of publications on this topic. The 1216 authors were divided into 5 main clusters. Among the 230 publications, 4 clusters were modeled, including Alzheimer disease, aged care, acceptance, and the surveillance and treatment of diseases. Machine learning, deep learning, and rehabilitation had also become recent research hotspots.
Research on the application of AI in geriatric care has developed rapidly. The development of research and cooperation among countries/regions and institutions are limited. In the future, strengthening the cooperation and communication between different countries/regions and institutions may further drive this field's development. This study provides researchers with the information necessary to understand the current state, collaborative networks, and main research hotspots of the field. In addition, our results suggest a series of recommendations for future research.
Journal Article
The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market
This paper presents an optimization method for scheduling a multi-energy VPP (Virtual Power Plant) supply–demand balance in the power market environment of Jiangxi Province. The primary objective of this method is to improve the operational efficiency of the power grid, reduce energy costs, and facilitate economical and efficient energy distribution in the power market. The method takes into account the characteristics and uncertainties of renewable energy sources such as solar and wind energy, and incorporates advanced multi-objective optimization algorithms. Furthermore, it integrates real-time market price feedback to achieve the accurate allocation of power supply and demand. Through a case study of a multi-energy VPP in Jiangxi Province, this paper examines the optimal combination model for various energy sources within VPP, and analyzes the impact of different market environments on supply–demand balance. The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. Compared with traditional power supply models, it reduces average electricity costs by 15% and increases renewable energy utilization efficiency by 20%.
Journal Article
Th17 Cells and IL-17A in Ischemic Stroke
The neurological injury and repair mechanisms after ischemic stroke are complex. The inflammatory response is present throughout stroke onset and functional recovery, in which CD4 + T helper(Th) cells play a non-negligible role. Th17 cells, differentiated from CD4 + Th cells, are regulated by various extracellular signals, transcription factors, RNA, and post-translational modifications. Th17 cells specifically produce interleukin-17A(IL-17A), which has been reported to have pro-inflammatory effects in many studies. Recently, experimental researches showed that Th17 cells and IL-17A play an important role in promoting stroke pathogenesis (atherosclerosis), inducing secondary damage after stroke, and regulating post-stroke repair. This makes Th17 and IL-17A a possible target for the treatment of stroke. In this paper, we review the mechanism of action of Th17 cells and IL-17A in ischemic stroke and the progress of research on targeted therapy.
Journal Article
Normative data and percentile curves for axial length and axial length/corneal curvature in Chinese children and adolescents aged 4–18 years
PurposeTo develop age-specific and gender-specific reference percentile charts for axial length (AL) and AL/corneal radius of curvature (AL/CR) and, to use percentiles to determine probability of myopia and estimate refractive error (RE).MethodsAnalysis of AL, cycloplegic RE and CR of 14 127 Chinese participants aged 4–18 years from 3 studies. AL and AL/CR percentiles estimated using Lambda-Mu-Sigma method and compared for agreement using intraclass correlation (ICC). Logistic regression was used to model risk of myopia based on age, gender, AL and AL/CR percentiles. Accuracy of AL progression and RE estimated using percentiles was validated using an independent sample of 5742 eyes of children aged 7–10 years.ResultsAge-specific and gender-specific AL and AL/CR (3rd, 5th, 10th, 25th, 50th, 75th, 90th and 95th) percentiles are presented. Concordance between AL and AL/CR percentiles improved with age (0.13 at 4 years to >0.75 from 13 years) and a year-to-year change was observed for all except <10th percentile from 15 years. Increasing age, AL and AL/CR was associated with a more myopic RE (r2=0.45,0.70 and 0.83, respectively). The sensitivity and specificity of the model to estimate probability of myopia was 86.0% and 84.5%, respectively. Estimation of 1-year change in AL using percentiles correlated highly with actual AL (ICC=0.98). Concordance of estimated to actual RE was high (ICC=0.80) and within ±0.50D and ±1.0D of actual RE for 47.4% and 78.9% of eyes, respectively.ConclusionAge-specific and gender-specific AL and AL/CR percentiles provide reference data, aid in identifying and monitoring individuals at risk of myopia and have utility in screening for myopia. AL/CR percentiles were more accurate in estimating probability of myopia in younger children.
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