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Abstract Background Some studies have shown that gut microbiota may be associated with dementia. However, the causal effects between gut microbiota and different types of dementia and whether cytokines act as a mediator remain unclear. Methods Gut microbiota, cytokines, and five dementia types, including Alzheimer’s disease (AD), frontotemporal dementia (FTD), dementia with Lewy body (DLB), vascular dementia (VD), and Parkinson’s disease dementia (PDD) were identified from large-scale genome-wide association studies (GWAS) summary data. We used Mendelian randomization (MR) to investigate the causal relationships between gut microbiota, cytokines, and five types of dementia. Inverse variance weighting (IVW) was used as the main statistical method. In addition, we explored whether cytokines act as a mediating factor in the pathway from gut microbiota to dementia. Results There were 20 positive and 16 negative causal effects between genetic liability in the gut microbiota and dementia. Also, there were five positive and four negative causal effects between cytokines and dementias. Cytokines did not act as mediating factors. Conclusions Gut microbiota and cytokines were causally associated with five types of dementia, and cytokines seemed not to be the mediating factors in the pathway from gut microbiota to dementia.

Abstract Background The American Heart Association has developed a novel cardiovascular health indicator called Life’s Essential 8 (LE8). However, no one has reported using LE8 to assess periodontitis. This study aimed to investigate the association between LE8 and periodontitis in American adults. Methods Data from the National Health and Nutrition Examination Survey (NHANES) from 2009 to 2014 were used for this investigation. LE8 was the independent variable, and it is divided into three grades: high, moderate, and low. Periodontitis was the dependent variable, and the classification of periodontitis was based on the criteria of Eke in 2012. Multivariable logistic regression models were used to explore the relationship between LE8 and periodontitis. Results A total of 9,039 participants with an average age of 52.16 ± 14.21 years were enrolled in this study, of whom 48.29% were male and 51.71% were female. The mean and standard deviation of LE8 was 66.29 ± 14.57, and the prevalence of periodontitis was 50.48% overall. The LE8 score and periodontitis in the fully adjusted logistic regression model showed a negative correlation (OR = 0.98; 95% CI, 0.98–0.99, p

Abstract Cytokine release syndrome (CRS) is the most common complication of chimeric antigen receptor redirected T cells (CAR-T) therapy. CAR-T toxicity management has been greatly improved, but CRS remains a prime safety concern. Here we follow serum cytokine levels and circulating immune cell transcriptomes longitudinally in 26 relapsed/refractory multiple myeloma patients receiving the CAR-T product, ciltacabtagene autoleucel, to understand the immunological kinetics of CRS. We find that although T lymphocytes and monocytes/macrophages are the major overall cytokine source in manifest CRS, neutrophil activation peaks earlier, before the onset of severe symptoms. Intracellularly, signaling activation dominated by JAK/STAT pathway occurred prior to cytokine cascade and displayed regular kinetic changes. CRS severity is accurately described and potentially predicted by temporal cytokine secretion signatures. Notably, CAR-T re-expansion is found in three patients, including a fatal case characterized by somatic TET2-mutation, clonal expanded cytotoxic CAR-T, broadened cytokine profiles and irreversible hepatic toxicity. Together, our findings show that a latent phase with distinct immunological changes precedes manifest CRS, providing an optimal window and potential targets for CRS therapeutic intervention and that CAR-T re-expansion warrants close clinical attention and laboratory investigation to mitigate the lethal risk.

Abstract Ligand-induced receptor dimerization or oligomerization is a widespread mechanism for ensuring communication specificity, safeguarding receptor activation, and facilitating amplification of signal transduction across the cellular membrane. However, cell-surface antigen-induced multimerization (dubbed AIM herein) has not yet been consciously leveraged in chimeric antigen receptor (CAR) engineering for enriching T cell-based therapies. We co-developed ciltacabtagene autoleucel (cilta-cel), whose CAR incorporates two B-cell maturation antigen (BCMA)-targeted nanobodies in tandem, for treating multiple myeloma. Here we elucidated a structural and functional model in which BCMA-induced cilta-cel CAR multimerization amplifies myeloma-targeted T cell-mediated cytotoxicity. Crystallographic analysis of BCMA–nanobody complexes revealed atomic details of antigen–antibody hetero-multimerization whilst analytical ultracentrifugation and small-angle X-ray scattering characterized interdependent BCMA apposition and CAR juxtaposition in solution. BCMA-induced nanobody CAR multimerization enhanced cytotoxicity, alongside elevated immune synapse formation and cytotoxicity-mediating cytokine release, towards myeloma-derived cells. Our results provide a framework for contemplating the AIM approach in designing next-generation CARs.

High quality marine natural resource management cannot be achieved without the support of data and information. Given the unique nature of marine data, the processing of marine environmental data often involves long time series or large-scale processing work. For data processing work mainly focused on intensive computing, universal cloud platforms have prominent issues of low efficiency. Based on a comprehensive analysis of the native resource scheduling algorithms on the Hadoop platform and the characteristics of intensive computing in ocean data processing, this paper innovatively proposes a genetic algorithm task scheduling strategy based on a competitive model. The use of chaotic algorithm mechanism as the basis for genetic algorithm population initialization ensures that the solution space obtained during each initialization can be uniformly distributed, effectively solving the problem of genetic algorithm solving speed being greatly affected by the initialization population and population evolution measurement. In addition, in order to speed up rate of convergence, competition mechanism is introduced and an adaptive evolution model based on population competition is proposed. Through the actual verification and comparison of the built models, it is proved that the improved algorithm is superior to the traditional genetic algorithm in rate of convergence and stability of the convergence results, and has greatly improved the ability and efficiency of improving the resource scheduling of the ocean cloud platform.

Abstract Chlorpyrifos and pyrimethanil are widely used insecticides/fungicides in agriculture. The residual pesticides/fungicides remaining in fruits and vegetables may do harm to human health if they are taken without notice by the customers. Therefore, it is important to develop methods and tools for the rapid detection of pesticides/fungicides in fruits and vegetables, which are highly demanded in the current markets. Surface-enhanced Raman spectroscopy (SERS) can achieve trace chemical detection, while it is still a challenge to apply SERS for the detection and identification of mixed pesticides/fungicides. In this work, we tried to combine SERS technique and deep learning spectral analysis for the determination of mixed chlorpyrifos and pyrimethanil on the surface of fruits including apples and strawberries. Especially, the multi-channel convolutional neural networks-gate recurrent unit (MC-CNN-GRU) classification model was used to extract sequence and spatial information in the spectra, so that the accuracy of the optimized classification model could reach 99% even when the mixture ratio of pesticide/fungicide varied considerably. This work therefore demonstrates an effective application of using SERS combined deep learning approach in the rapid detection and identification of different mixed pesticides in agricultural products.

Abstract Atopic dermatitis (AD) is a common skin disease involving important immune mechanisms. There is an unmet need for a treatment for this condition. Herein, we focused on elucidating the role of Bi2-xMnxO3 nanospheres (BM) in alleviating skin inflammation in AD-like C57BL/6 mice. The BM was fabricated via sacrificial templates and its biosafety was systematically evaluated. The BM was applied topically to skin lesions of AD-like C57BL/6 mice. The phenotypic and histological changes in the skin were examined carefully. The responses of barrier proteins, inflammatory cytokines and cells to BM were evaluated in HaCaT cells and AD mouse models. The data demonstrated that BM treatment alleviated the AD phenotypes and decreased the level of inflammatory factors, while increasing the expression of the barrier proteins filaggrin/involucrin in the skin. BM effectively reduced the expression of phosphorylated STAT6, which in turn reduced the expression of GATA3, and further decreased the differentiation ratio of Th2 cells, thereby reducing the expression of IL-4. In conclusion, topical drug therapy with BM provides a safe and effective treatment modality for AD by reducing IL-4 and increasing barrier proteins. Graphical Abstract

Abstract Background Limb-girdle muscular dystrophies (LGMDs) are a group of heterogeneous inherited diseases predominantly characterized by limb-girdle muscle weakness and dystrophic changes on histological analysis. The frequency of LGMD subtypes varies among regions in China and ethnic populations worldwide. Here, we analyzed the prevalence of LGMD subtypes, their corresponding clinical manifestations, and molecular data in a cohort of LGMD patients in Southeast China. Methods A total of 81 consecutive patients with clinically suspected LGMDs from 62 unrelated families across Southeast China were recruited for targeted next-generation sequencing and whole-exome sequencing from July 2017 to February 2020. Results Among 50 patients (41 families) with LGMDs, the most common subtypes were LGMD-R2/LGMD2B (36.6%) and LGMD-R1/LGMD2A (29.3%). Dystroglycanopathies (including LGMD-R9/LGMD2I, LGMD-R11/LGMD2K, LGMD-R14/LGMD2N and LGMD-R20/LGMD2U) were the most common childhood-onset subtypes and were found in 12.2% of the families. A total of 14.6% of the families had the LGMD-R7/LGMD2G subtype, and the mutation c.26_33dupAGGTGTCG in TCAP was the most frequent (83.3%). The only patient with the rare subtype LGMD-R18/LGMD2S had TRAPPC11 mutations; had a later onset than those previously reported, and presented with proximal‒distal muscle weakness, walking aid dependency, fatty liver disease and diabetes at 33 years of age. A total of 22.0% of the patients had cardiac abnormalities, and one patient with LMNA-related muscular dystrophy/LGMD1B experienced sudden cardiac death at 37 years of age. A total of 15.4% of the patients had restrictive respiratory insufficiency. Muscle imaging in patients with LGMD-R1/LGMD2A and LGMD-R2/LGMD2B showed subtle differences, including more severe fatty infiltration of the posterior thigh muscles in those with LGMD-R1/LGMD2A and edema in the lower leg muscles in those with LGMD-R2/LGMD2B. Conclusion We determined the prevalence of different LGMD subtypes in Southeast China, described the detailed clinical manifestations and distinct muscle MRI patterns of these LGMD subtypes and reported the frequent mutations and the cardiorespiratory involvement frequency in our cohort, all of which might facilitate the differential diagnosis of LGMDs, allowing more timely treatment and guiding future clinical trials.

User-generated data can reflect various viewpoints and experiences derived from people’s perception outcomes. The perceptual results can be obtained, often by combining subjective public perceptions of the landscape with physiological monitoring data. Accessing people’s perceptions of the landscape through text is a common method. It is hard to fully render nuances, emotions, and complexities depending only on text by superficial emotional tendencies alone. Numerical representations may lead to misleading conclusions and undermine public participation. In addition, the use of physiological test data does not reflect the subjective reasons for the comments made. Therefore, it is essential to deeply parse the text and distinguish between segments with different semantic differences. In this study, we propose a perceptual psychology-based workflow to extract and visualize multifaceted views from user-generated data. The analysis methods of FCN, LDA, and LSTM were incorporated into the workflow. Six areas in Fuzhou City, China, with 12 city parks, were selected as the study object. Firstly, 9987 review data and 1747 pictures with corresponding visitor trajectories were crawled separately on the Dianping and Liangbulu websites. For in-depth analysis of comment texts and making relevant heat maps. Secondly, the process of clauses was added to get a more accurate representation of the sentiment of things based on the LSTM sentiment analysis model. Thirdly, various factors affecting the perception of landscapes were explored. Based on such, the overall people’s perception of urban parks in Fuzhou was finally obtained. The study results show that (1) the texts in terms of ‘wind’, ‘temperature’, ‘structures’, ‘edge space (spatial boundaries)’, and ‘passed space’ are the five most representative factors of the urban parks in Fuzhou; (2) the textual analyses further confirmed the influence of spatial factors on perception in the temporal dimension; and (3) environmental factors influence people’s sense of urban parks concerning specificity, clocking behavior, and comfort feelings. These research results provide indispensable references for optimizing and transforming urban environments using user-generated data.

Objective: Despite being primary beneficiaries of human papillomavirus (HPV) vaccines, female university students in China exhibit low vaccination rates. This study aimed to assess their preferences for HPV vaccination services and evaluate the relative importance of various factors to inform vaccination strategy development. Methods: Through a literature review and expert consultations, we identified five key attributes for study: effectiveness, protection duration, waiting time, distance, and out-of-pocket (OOP) payment. A D-efficient design was used to create a discrete choice experiment (DCE) questionnaire. We collected data via face-to-face interviews and online surveys from female students across seven universities in China, employing mixed logit and latent class logit models to analyze the data. The predicted uptake and compensating variation (CV) were used to compare different vaccination service scenarios. Results: From 1178 valid questionnaires, with an effective response rate of 92.9%, we found that effectiveness was the most significant factor influencing vaccination preference, followed by protection duration, OOP payment and waiting time, with less concern for distance. The preferred services included a 90% effective vaccine, lifetime protection, a waiting time of less than three months, a travel time of more than 60 min, and low OOP payment. Significant variability in preferences across different vaccination service scenarios was observed, affecting potential market shares. The CV analysis showed female students were willing to spend approximately CNY 5612.79 to include a hypothetical ‘Service 5’ (a vaccine with higher valency than the nine-valent HPV vaccine) in their prevention options. Conclusions: The findings underscore the need for personalized, need-based HPV vaccination services that cater specifically to the preferences of female university students to increase vaccination uptake and protect their health.