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With the sustained growth of economy and significant changes in social demographics, the issue of elderly-related diseases has increasingly drawn attention particularly. Alzheimer's disease (AD),as a representative disease of neurodegenerative diseases has become a major challenge, affecting the health and quality of life among the elderly population severely. In recent years, the incidence, prevalence, and mortality rate of AD increase in China, imposing substantial economic burdens on families, society, and the entire healthcare system. To proactively address this challenge and respond to the national 'Healthy China Action' initiative, leading experts from Renji Hospital, Shanghai Jiao Tong University School of Medicine,and Chinese Center for Disease Control and Prevention Chronic Non-communicable Disease Control Center, Fudan University School of Public Health, Shanghai Mental Health Center, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, Fujian Medical University, and other authoritative institutions, have jointly authored the 'China Alzheimer Disease Report 2024'. Building upon previous editions of 2021, 2022, and 2023, this report updates epidemiological data on AD in China, thoroughly analyzes the latest economic burdens of the disease, and comprehensively evaluates the current status of AD diagnosis and treatment services, as well as the allocation of public health resources in our country. The release of the 'China Alzheimer Disease Report 2024' not only reflects China's progress and efforts in AD research and prevention, but also underscores the social heightened concern for elderly health issues. It aims to provide scientific and technical guidance and robust data support for the prevention, diagnosis, and treatment of AD, offering a professional basis for the government and relevant departments to formulate targeted health policies and intervention measures. Furthermore, it serves as a platform for promoting academic exchanges and cooperation in this field domestically and internationally. Through the dissemination and application of this report, we anticipate it will not only serve as a reference for professionals but also enhance public awareness of AD, promote active participation across various sectors of society, and jointly advance the development of elderly health care in China, empowering us towards achieving 'healthy aging'.

Street vendors are an indispensable part of the urban social ecosystem, but due to a lack of comprehensive understanding, many cities have adopted simple eviction policies, resulting in the gradual marginalization and stigmatization of the street economy. The efficient governance of street vendors requires the comprehensive investigation of their business scale and spatial distribution information. However, traditional methods have limitations in terms of automatically surveying large-scale street vendor information, particularly spatial distribution. This paper proposes a method for the automatic investigation spatial distribution of street vendors based on street-view images and a deep-learning object recognition model. Street-view images were collected at fixed intervals according to the urban road network, and 1,957 images containing one or more vendors were selected through human-machine interaction to establish street vendor label data. To achieve high recognition model accuracy, the category labels were subdivided into four categories: ground stalls, table stalls, tricycle stalls, and small truck stalls, based on the goods carriers used by street vendors. A deep neural-network-based image object detection model based on YOLO v4 was constructed to identify street vendors in the street-view image library, with an average F1 value of 0.77 and an mAP of 0.67. The accuracy of the model was satisfactory for investigating the number and location of street vendors covering the main roads in the city and then applying a kernel density distribution model to evaluate the spatial distribution pattern of street vendors. Using street vendors in Guangzhou as a case study, the proposed automatic investigation model identified 26,119 street vendors from 3,339,062 street-view images. The results showed that the street vendors were distributed in a multicenter aggregation pattern in the central urban area, mainly concentrated in areas with high pedestrian traffic, such as subway stations and urban villages; their numbers increased as road grades decreases. Street vendors were mainly distributed in areas with medium rents. The proposed method is helpful for performing the efficient, low-cost, and city-scale mapping of street vendors; the results obtained provide suggestions for formulating and implementing spatial governance policies for the informal economy and further provide suggestions for improving and implementing spatial governance policies for open and diverse urban street-view images. The results can be used as a reference for the location preference analysis of practitioners, the exploration of NIMBY syndrome, and the determination of the formalization zone. Although street-view images have an insufficient spatiotemporal coverage, using them to perform street vendor investigations is a low-cost and efficient method compared with the use of traditional investigation methods and data sources. In addition, the method proposed in this article can be coupled with multitask deep learning algorithms to investigate additional dimensions of street vendor information, such as the sex, age, and type of business of street vendors. Relevant research needs to be conducted in the future.

Objective To investigate the changes and significance of human beta-defensin-2 (HBD-2) and LL-37 in the gingival crevicular fluid of patients with periodontitis and type 2 diabetes mellitus (T2DM). Methods This study was conducted among 45- to 85-year-old patients in the Department of Stomatology and Internal Medicine of Shenzhen Center for Chronic Disease Control, including a healthy control group of 22 people, a systemically healthy control group of 19 people with periodontitis, a T2DM periodontal health group of 15 people, and a T2DM group of 21 people with periodontitis. The Florida periodontal probe was used for periodontal examination, and the clinical indexes, including probing depth (PD), clinical attachment level (CAL) and probing on bleeding (BOP), were recorded. The concentrations of HBD-2 and Ll-37 in gingival crevicular fluid were determined by ELISA. The differences in HBD-2, LL-37 and periodontal clinical indexes between the groups were compared, and correlation analysis was conducted.Results The PD values in T2DM with the periodontitis group were higher than those of the systemically healthy controls with periodontitis group (P < 0.05); the levels of HBD-2 and LL-37 in gingival crevicular fluid in systemically healthy controls with periodontitis group were significantly higher than those in the healthy control group (P < 0.05), the level of HBD-2 in gingival crevicular fluid in systemically healthy controls with periodontitis group was significantly higher than that in T2DM with periodontitis group (P < 0.05); and the antimicrobial peptides HBD-2 and LL-37 in gingival crevicular fluid were significantly positively correlated with the PD and CAL in systemically healthy controls with periodontitis group (P < 0.05), and there was no significant correlation between the antimicrobial peptides HBD-2, LL-37 in gingival crevicular fluid and PD, CAL in T2DM with periodontitis group (P > 0.05). Conclusion The levels of antimicrobial peptides HBD-2 and LL-37 in gingival crevicular fluid of middle-aged and elderly patients with T2DM periodontitis were lower, and there was no significant correlation with PD and CAL in periodontal clinical indicators.

Introduction: The emergence of multidrug-resistant Klebsiella pneumoniae (K. pneumoniae) and the decline of effective antibiotics lead to the urgent need for new antibacterial agents. The aim of this study is to investigate the therapeutic effect of antimicrobial peptides against gentamicin-resistant (RT) K. pneumoniae and to screen effective antimicrobial peptides. Methods: In this study, the RT strains were induced by gradient gentamicin, and the RT strains were selected by detecting the expression levels of efflux pump genes, porin genes, and biofilm formation genes of the strains combined with their effects on the cells. Then the effects of four antimicrobial peptides on the efflux pump activity, biofilm formation level and cell condition after infection were detected to explore the effects of antimicrobial peptides on RT strains. Finally, the RT strain was used to induce a mouse model of pneumonia, and the four antimicrobial peptides were used to treat pneumonia mice for in vivo experiments. The pathological changes in lung tissues in each group were detected to explore the antimicrobial peptide with the most significant effect on the RT strain in vivo. Results: The results showed that the minimal inhibitory concentrations of the RT strains (strain C and strain I) were significantly higher than those of the wild-type strain, and the expression of efflux pump, porin and biofilm formation genes was significantly increased. The antimicrobial peptides could effectively inhibit the biofilm formation and efflux pump protein function of the RT strains. In addition, the antimicrobial peptides showed promising antibacterial effects both in vitro and in vivo. Discussion: Our study provided a theoretical basis for the treatment of gentamicin resistant K. pneumoniae infection with antimicrobial peptides, and found that KLA was significantly superior to LL37, Magainin I, KLA and Dermaseptin (10 μg/mL in cells, 50 μg in mice). [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate dietary chitosan oligosaccharides (COS) supplementation on meat quality, chemical composition and oxidative stability in frizzled chickens. A total of 360 one-day-old female frizzled chickens with an average body weight of 34.38 ± 1.23 g were randomly allocated to four groups with six replications (10 chickens/replication) in this 84-day experiment. The chickens in the control group (CON) fed the basal diet and the other three experimental diets were based on the basal diet with 300, 600 and 900 mg/kg COS supplementation, respectively. The results indicated that dietary COS increased growth performance, eviscerated and breast muscle yield while decreased abdominal fat yield, accompanied with increasing pH45min, pH24h, Lightness, drip loss and cooking loss in breast and thigh muscle. The scavenging activity of 2,2-diphenyl-1-picrylhydrazyl, superoxide radical, hydroxyl radical and 2,2-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) diammonium salt, the activity of glutathione peroxidase (GSH-Px), superoxide dismutase (SOD) and catalase (CAT) in breast and thigh muscle were improved by COS while malondialdehyde content was decreased. COS up-regulated the gene expression of nuclear factor erythroid 2-related factor 2, heme oxygenase-1, NAD(P)H quinone dehydrogenase 1, SOD, CAT and GSH-Px in breast and thigh muscle. In conclusion, dietary COS supplementation improved meat quality by improving pH, colour, water holding capacity and anti-oxidant capacity, accompanied with decreased lipid metabolism in frizzled chickens. Dietary 600 mg/kg COS was recommended in frizzled chickens' diet to improve meat quality. COS improves growth performance of frizzled chickens. COS improves meat quality of frizzled chickens. COS enhances anti-oxidant capacity of frizzled chickens' meat. [ABSTRACT FROM AUTHOR]

Mammalian DNA derived from invertebrates (iDNA), including blowfly iDNA, is an alternative tool to conventional camera trapping in assessing mammalian diversity. The method has been used in tropical mammal surveillance but no attempt has been made to compare the efficacy of blowfly iDNA and camera trapping for monitoring mammal diversity in subtropical forests. We compared the blowfly iDNA monitoring with camera trapping to assess mammal diversity in the subtropical Jiulongfeng Nature Reserve (JLF), China, over a one-month period. The camera traps captured 2508 animal photos of 11 species belonging to four orders, eight genera, and eight families, whereas the blowfly iDNA method successfully detected ten species from six orders, eight genera, and eight families in JLF. Both methods were complementing each other instead of competing due to the low overlaps of mammal species detected. Of the total number of mammal species listed in JLF's threatened list, 40% and 10% were detected through camera traps and blowfly iDNA methods, respectively. The estimated species richness curves indicated that combining camera traps and blowfly traps would increase the detection of mammal species. The strategy would significantly contribute to mammalian diversity surveillance and conservation programs in the tropical and subtropical forests. [ABSTRACT FROM AUTHOR]