Neuropsychiatric Symptoms Mediated the Relationship Between Odor Identification and Cognition in Alzheimer's Disease Spectrum: A Structural Equation Model Analysis

Neuropsychiatric symptoms as a prodromal factor in Alzheimer's type neurodegenerative disease: A scoping review

Objective: Identifying neuropsychiatric symptoms (NPS) can aid in the early detection of Alzheimer's disease (AD); however, there is still a need for a greater consensus. This review aims to delineate the predominant NPS, compile a comprehensive list of the most commonly employed NPS assessment tools, and corroborate the principal findings regarding the link between NPS and neuropsychological assessment and neurobiological substrates. Methods: To conduct this scoping review, we followed the Preferred Reporting Items for Systematic Reviews guidelines and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). We searched for relevant articles published between 2017 and 2023 in MEDLINE, PsycINFO, PubMed, Web of Science, and Cochrane Library. Results: Of the 61 eligible articles, depression, anxiety, and apathy were the main NPSs. The Neuropsychiatric Inventory Questionnaire and Neuropsychiatric Inventory were the primary assessment tools used to evaluate NPS. Correlations between NPS severity and neurobiological markers were considered clinically significant. Furthermore, clinical procedures prioritized the use of global cognitive screening tools, assessments of executive functions, and functionality evaluations. Conclusion: Standardization of procedures is necessary because of the diversity of methods. The data show that NPS can predict the etiology, severity, form, and type of disease progression, serving as a precursor sign of AD. The results of the most common cognitive screening tools and NPS instruments provided an interesting overview of future clinical approaches.

Odor familiarity and improvement of olfactory identification test in Chinese population

Aims

This study aimed to design the Chinese Modified Olfactory Identification (CMOI) test based on the Sniffin' Sticks Olfactory Identification (SSOI) test by changing unfamiliar distractors and odors for more familiar ones for the Chinese population.

Materials and methods

We recruited 200 healthy volunteers (103 males and 97 females, aged 18-65 years, mean age 35.04 years, SD 10.96); in a survey, 100 volunteers rated their familiarity with 121 odors, including all the SSOI test odor descriptors and common odors in Chinese daily life. The SSOI test was modified according to the survey results. The other 100 volunteers were tested three times using the SSOI test, the Modified Distractors Olfactory Identification (MDOI) test established by modifying distractors in the SSOI test, and the CMOI test developed by using familiar unpleasant odors to displace the odors with low correct recognition rates in the MDOI test. We compared the test scores of the volunteers during the modification process.

Results

Volunteers were unfamiliar with 31 odor descriptors in the SSOI test; 23 distractors with low familiarity were displaced with more familiar distractors. The three odors with the lowest correct recognition rate in the MDOI test (apple, leather, and pineapple) were displaced with familiar unpleasant odors. The test scores were significantly higher in the CMOI test than in others (p < 0.0001); the correct recognition rate in the CMOI test was significantly higher than in the SSOI test (p < 0.01).

Conclusion

The test scores in the CMOI test were significantly improved; it prevented choosing wrongly due to unfamiliarity with an odor and its distractors.

A Spatial Spectrum Estimation Method for Optimization and Improvement of Resource Allocation and Management of Public Sport and Health Facilities

With the improvement of people's health awareness, the state increases the construction of public sport facilities, which complicates the allocation and management of resources. The existing spatial spectrum estimation method cannot eliminate the relevant interference data, resulting in duplicate data in the results of resource allocation and management, reducing the accuracy of resource allocation and management. In order to optimize the allocation and management of public sport facilities resources, this study proposes a spatial spectrum estimation method, which is used to deeply tap the potential information in public sport facilities resources and optimize the allocation and management. First, analyze the resources of public sport facilities and put forward the feature vector of allocation and management optimization. Then, use the spatial spectrum estimation method to learn the test samples, get the optimal threshold and weight, and build the resource allocation and management model of public sport facilities. Finally, the accuracy of spatial spectrum estimation method is 98% and the variation range is (0, 10), which is better than the accuracy of the original algorithm is 80% and the variation range is (0, 20). Moreover, change of the spatial spectrum estimation method is smoother, and the correlation between various analyses is better. In unit time, the amount of configuration and management data of spatial spectrum estimation method is higher than that of existing algorithms, which indirectly indicate that the configuration and management time of the spatial spectrum estimation method is short. At the same time, unstructured data account for a large proportion of the data tested this time. Therefore, the accuracy and variation range of the spatial spectrum estimation method is good, which is suitable for the construction of public sport facilities and realizes the optimization of resource allocation and management.