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Alzheimer's disease (AD) is rapidly becoming one of the most expensive, burdening, and deadly diseases of this century. Up to now, there is still a lack of pharmacotherapy with substantial efficacy, and physical exercise is a promising and low‐cost way to aid in delaying the process of AD. The aim of this review is to summarise the efficacy of different physical exercise approaches and doses in the management of AD, including aerobic exercise, resistance exercise and multicomponent exercise. A literature search using MeSH terms for each topic is undertaken using PubMed and the Web of Science Core Collection database, supplemented by hand searching for additional references. Retrieved articles were reviewed, synthesised, and summarised. This review shows that aerobic exercise has been almost unanimously recognised for the improvement of cognition, neuropsychiatric symptoms and activities of daily living. Resistance exercise also shows a good prospect in the above aspects and has a unique advantage in enhancing muscle strength, while multicomponent physical activity does not seen to significantly improve cognitive function. Each type of exercise has a dose effect, but for individuals with AD, the most appropriate exercise dose is still controversial. [ABSTRACT FROM AUTHOR]

To address the challenges of multi-scale objects, dense distributions, occlusions, and numerous small targets in UAV image detection, we present CMS-YOLOv7, a real-time target detection method based on an enhanced YOLOv7 model. Firstly, the detection layer P2 for small targets was added to YOLOv7 to enhance the detection ability of small and medium-sized targets, and the deep detection head P5 was taken out to mitigate the influence of excessive downsampling on small target images. The anchor frame was calculated by the K-means++ method. Using the concept of Inner-IoU, the Inner-MPDIoU loss function was constructed to control the range of the auxiliary border and improve detection performance. Furthermore, the CARAFE module was introduced to replace traditional upsampling methods, offering improved integration of semantic information during the image upsampling process and enhancing feature mapping accuracy. Simultaneously, during the feature extraction stage, a non-strided convolutional SPD-Conv module was constructed using space-to-depth techniques. This module replaced certain convolutional operations to minimize the loss of fine-grained information and improve the model's ability to extract features from small targets. Experiments on the UAV aerial photo dataset VisDrone2019 demonstrated that compared with the baseline YOLOv7 object detection algorithm, CMS-YOLOv7 achieved an improvement of 3.5% mAP@0.5, 3.0% mAP@0.5:0.95, and the number of parameters decreased by 18.54 M. The ability of small target detection was significantly enhanced. [ABSTRACT FROM AUTHOR]

This study exploits the correlation between Yellow River flooding and human capital accumulation using county-level data from Anhui, Hebei, Henan, Jiangsu, and Shandong provinces in China. Employing a spatial regression discontinuity approach, we compare the differences in human capital accumulation within and beyond the Yellow River floodplain areas (YRFA). Empirical results show human capital accumulation in the YRFA is at least 12.1 percent lower than outside the YRFA. Furthermore, our results demonstrate intergenerational transmission and gender differences in the negative impact of the Yellow River flooding on human capital accumulation. The baseline specifications of this study are not affected by drought and overall natural disasters. This paper documents historical human capital accumulation, clan power, and social trust, through which Yellow River flooding has a long-term impact. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the leading cause of dementia and presents a considerable disease burden. Its pathology involves substantial neuronal loss, primarily attributed to neuronal apoptosis. Although sirtuin 4 (SIRT4) has been implicated in regulating apoptosis in various diseases, the role of SIRT4 in AD pathology remains unclear. The study used APP/PS1 mice as an animal model of AD and amyloid-β (Aβ)1-42-treated HT-22 cells as an AD cell model. SIRT4 expression was determined by quantitative real-time polymerase chain reaction, Western blot, and immunofluorescence. A Sirt4 knockdown model was established by intracranial injection of lentivirus-packaged sh-SIRT4 and cellular lentivirus transfection. Immunohistochemistry and flow cytometry were used to examine Aβ deposition in mice and apoptosis, respectively. Protein expression was assessed by Western blot analysis. The UCSC and JASPAR databases were used to predict upstream transcription factors of Sirt4. Subsequently, the binding of transcription factors to Sirt4 was analyzed using a dual-luciferase assay and chromatin immunoprecipitation. SIRT4 expression was upregulated in both APP/PS1 mice and Aβ-treated HT-22 cells compared with their respective control groups. Sirt4 knockdown in animal and cellular models of AD resulted in reduced apoptosis, decreased Aβ deposition, and amelioration of learning and memory impairments in mice. Mechanistically, SIRT4 modulates apoptosis via the mTOR pathway and is negatively regulated by the transcription factor signal transducer and activator of transcription 2 (STAT2). Our study findings suggest that targeting the STAT2-SIRT4-mTOR axis may offer a new treatment approach for AD. NEW & NOTEWORTHY: The study reveals that in Alzheimer's disease models, SIRT4 expression increases, contributing to neuronal apoptosis and amyloid-β deposition. Reducing SIRT4 lessens apoptosis and amyloid-β accumulation, improving memory in mice. This process involves the mTOR pathway, regulated by STAT2 transcription factor. These findings suggest targeting the STAT2-SIRT4-mTOR axis as a potential Alzheimer's treatment strategy. [ABSTRACT FROM AUTHOR]