Vitamin A deficiency (VAD) plays an essential role in the pathogenesis of Alzheimer’s disease (AD). However, the specific mechanism by which VAD aggravates cognitive impairment is still unknown. At the intersection of microbiology and neuroscience, the gut-brain axis is undoubtedly contributing to the formation and function of neurological systems, but most of the previous studies have ignored the influence of gut microbiota on the cognitive function in VAD. Therefore, we assessed the effect of VAD on AD pathology and the decline of cognitive function in AD model mice and determined the role played by the intestinal microbiota in the process. Twenty 8-week-old male C57BL/6J amyloid precursor protein/presenilin 1 (APP/PS1) transgenic mice were randomly assigned to either a vitamin A normal (VAN) or VAD diet for 45 weeks. Our results show that VAD aggravated the behavioral learning and memory deficits, reduced the retinol concentration in the liver and the serum, decreased the transcription of vitamin A (VA)-related receptors and VA-related enzymes in the cortex, increased amyloid-β peptides (Aβ40 and Aβ42) in the brain and gut, upregulate the translation of beta-site APP-cleaving enzyme 1 (BACE1) and phosphorylated Tau in the cortex, and downregulate the expression of brain-derived neurotrophic factor (BDNF) and γ-aminobutyric acid (GABA) receptors in the cortex. In addition, VAD altered the composition and functionality of the fecal microbiota as exemplified by a decreased abundance of Lactobacillus and significantly different α- and β-diversity. Of note, the functional metagenomic prediction (PICRUSt analysis) indicated that GABAergic synapse and retinol metabolism decreased remarkably after VAD intervention, which was in line with the decreased expression of GABA receptors and the decreased liver and serum retinol. In summary, the present study provided valuable facts that VAD exacerbated the morphological, histopathological, molecular biological, microbiological, and behavioral impairment in the APP/PS1 transgenic mice, and the intestinal microbiota may play a key mediator role in this mechanism.

Background: Cognitive decline poses one of the greatest global challenges for health and social care, particularly in China, where the burden on the older adult population is most pronounced. Despite the rapid expansion of internet access, there is still limited understanding of the long-term cognitive impacts of internet use among middle-aged and older adults. Objective: This study aims to explore the association between internet use and age-related cognitive decline among middle-aged and older Chinese adults. To gain a more comprehensive understanding of the effects of internet use, we also focused on assessing the impact of both the frequency of internet use and the types of internet devices on cognition. Moreover, we assessed the mediating role of internet use on cognitive function for characteristics significantly linked to cognition in stratified analysis. Methods: We analyzed data based on 12,770 dementia-free participants aged ≥45 years from the China Health and Retirement Longitudinal Study. We used a fixed effects model to assess the relationship between internet use and cognitive decline and further validated it using multiple linear regression analysis, generalized estimating equations, propensity score matching, inverse probability of treatment weighting, and overlap weighting. We further examined the varying effects of internet device type and frequency on cognitive function using fixed effects models and Spearman rank correlations. The Karlson-Holm-Breen method was used to estimate the mediating role of internet use in the urban-rural cognitive gap. Results: Participants using the internet (n=1005) were younger, more likely to be male, more educated, married, retired and living in an urban area and had higher cognitive assessment scores than nonusers (n=11,765). After adjusting for demographic and health-related risk factors, there was a positive correlation between internet use and cognitive function (β=0.551, 95% CI 0.391-0.710). Over the follow-up period, persistent internet users had a markedly lower 5-year incidence of neurodegenerative diseases, at 2.2% (15/671), compared with nonusers, at 5.3% (379/7099; P<.001). The negative impact of aging (>50 years) on cognitive function was consistently less pronounced among internet users than among nonusers. Furthermore, increased frequency of internet use was associated with greater cognitive benefits for middle-aged and older adults (rs=0.378, P<.001). Among digital devices used for internet access, cell phones (β=0.398, 95% CI 0.283-0.495) seemed to have a higher level of cognitive protection than computers (β=0.147, 95% CI 0.091-0.204). The urban-rural disparity in cognitive function was partially attributed to the disparity in internet use (34.2% of the total effect, P<.001). Conclusions: This study revealed that the use of internet by individuals aged 45 years and older is associated with a reduced risk of cognitive decline. Internet use has the potential to be a viable, cost-effective, nonpharmacological intervention for cognitive decline among middle-aged and older adults.

Background: Malnutrition is prevalent in elderly inpatients and is associated with various adverse outcomes during their hospital stay, but the diagnosis of malnutrition still lacks widely applicable criteria. This study aimed to investigate the association of malnutrition diagnosed with the SGA, ESPEN 2015, and GLIM criteria, respectively, with in-hospital complications in elderly patients. Method: Hospitalized patients over 65 years old who had been assessed with the SGA guideline for malnutrition at admission were retrospectively recruited from a large observational cohort study conducted in 34 level-A tertiary hospitals in 18 cities in China from June to September 2014. Malnutrition was then retrospectively diagnosed using the GLIM and ESPEN 2015 criteria, respectively, for comparison with the results of the SGA scale. The risk factors for malnutrition were analyzed using logistic regression, and the value of the three diagnostic criteria in predicting the in-hospital complications was subsequently explored using multivariate regression and the random forest machine learning algorithm. Results: A total of 2526 subjects who met the inclusion and exclusion criteria of the study were selected from the 7122 patients in the dataset, with an average age of 74.63 ± 7.12 years, 59.2% male, and 94.2% married. According to the GLIM, SGA, and ESPEN 2015 criteria, the detection rates of malnutrition were 37.8% (956 subjects), 32.8% (829 subjects), and 17.0% (429 subjects), respectively. The diagnostic consistency between the GLIM and the SGA criteria is better than that between the ESPEN 2015 and the SGA criteria (Kappa statistics, 0.890 vs. 0.590). Logistic regression showed that the risk of developing complications in the GLIM-defined malnutrition patients is 2.414 times higher than that of normal patients, higher than those of the ESPEN 2015 and SGA criteria (1.786 and 1.745 times, respectively). The random forest classifications show that the GLIM criteria have a higher ability to predict complications in these elderly patients than the SGA and ESPEN 2015 criteria with a mean decrease in accuracy of 12.929, 10.251, and 5.819, respectively, and a mean decrease in Gini of 2.055, 1.817, and 1.614, respectively. Conclusion: The prevalence of malnutrition diagnosed with the GLIM criteria is higher than that of the SGA and the ESPEN 2015 criteria. The GLIM criteria are better than the SGA and the ESPEN 2015 criteria for predicting in-hospital complications in elderly patients.

Background: Alzheimer’s disease (AD) is an age-related neurodegenerative disorder with no effective interventions for curing or modifying its progression. However, emerging research suggests that vitamin A in the diet may play a role in both the prevention and treatment of AD, although the exact mechanisms are not fully understood.Objectives: This study aims to investigate the dietary vitamin A modifies the gut microbiota and intestinal tissue transcriptome, impacting intestinal permeability and the release of inflammatory factors, thereby influencing Aβ pathology shedding light on its potential as a dietary intervention for AD prevention and treatment.Methods: The APP/PS1-AD mouse model was employed and divided into three dietary groups: vitamin A-deficient (VAD), normal vitamin A (VAN), and vitamin A-supplemented (VAS) for a 12-week study. Neurobehavioral functions were assessed using the Morris Water Maze Test (MWM). Enzyme-linked immunosorbent assay (ELISA) was used to quantify levels of Diamine Oxidase (DAO), D-lactate, IL-6, IL-1β, and TNF-a cytokines. Serum vitamin A levels were analyzed via LC-MS/MS analysis. Immunohistochemical analysis and morphometry were performed to evaluate the deposition of Aβ in brain tissue. The gut microbiota of APP/PS1 mice was analyzed using 16S rRNA sequencing analysis. Additionally, transcriptomic analysis was conducted on intestinal tissue from APP/PS1 mice.Results: No significant changes in food intake and body weight were observed among the groups. However, the VAD and VAS groups showed reduced food intake compared to the VAN group at various time points. In terms of cognitive function, the VAN group performed better in the Morris Water Maze Test, indicating superior learning and memory abilities. The VAD and VAS groups exhibited impaired performance, with the VAS group performing relatively better than the VAD group. Serum vitamin A concentrations differed significantly among the groups, with the VAS group having the highest concentration. Aβ levels were significantly higher in the VAD group compared to both the VAN and VAS groups. Microbial analysis revealed that the VAS and VAN groups had higher microbial diversity than the VAD group, with specific taxa characterizing each group. The VAN group was characterized by taxa such as Actinohacteriota and Desulfovibrionaceae, while the VAD group was characterized by Parabacteroides and Tannerellaceae. The VAS group showed similarities with both VAN and VAD groups, with taxa like Desulfobacterota and Desulfovibrionaceae being present. The VAD vs. VAS, VAD vs. VAN, and VAS vs. VAN comparisons identified 571, 313, and 243 differentially expressed genes, respectively, which associated with cellular and metabolic processes, and pathway analysis revealed enrichment in pathways related to chemical carcinogenesis, drug metabolism, glutathione metabolism, and immune-related processes. The VAD group exhibited higher levels of D-lactate, diamine oxidase, and inflammatory cytokines (TNF-a, IL-1β, IL-6) compared to the VAN and VAS groups.Conclusion: Dietary vitamin A supplementation modulates the gut microbiota, intestinal permeability, inflammatory factors, and Aβ protein formation, offering insights into the pathogenesis of AD and potential therapeutic avenues for further exploration. This research highlights the intricate interplay between diet, gut microbiota, and neurodegenerative processes, emphasizing the importance of dietary interventions in managing AD-related pathologies.

Colorectal cancer (CRC) is the third most common malignancy of the digestive tract and the fifth leading cause of cancer-related mortality in China. Sporamin, a Kunitz-type trypsin inhibitor isolated from sweet potato, is a potential anti-cancer agent with activities against a number of malignant tumor cells in vitro. The liver secretes a myriad of endocrine factors that may facilitate the growth and transformation of tumors in the development of CRC. To investigate the effects of sporamin on liver morphology and biomarkers of xenografted CRC in the liver of athymic BALB/c mice. Twenty-seven male BALB/c nude mice were randomly divided into control, vehicle, and sporamin groups. Mice in the latter two groups were intraperitoneally xenografted with LoVo colorectal carcinoma cells and intragastrically infused with saline or sporamin (0.5 g/kg body weight/d), respectively, for 3 wk. Hematoxylin and eosin (HE) staining of the sections was performed to observe morphological changes in hepatic tissue and real-time fluorescent quantitative PCR (qPCR) and enzyme-linked immunosorbent assay (ELISA) were used to measure the expression of β-catenin and vascular endothelial growth factor (VEGF) in the liver. Sporamin significantly reduced the number and weight of tumor nodules formed in the abdominal cavity. Compared with the vehicle group, the mean tumor weight (± SD) in the sporamin group was significantly reduced (0.44 ± 0.10 g vs 0.26 ± 0.15 g) and the total number of tumors decreased from 93 to 55. HE staining showed that enlargement of the nucleus and synthesis of proteins within hepatocytes, as well as infiltration of inflammatory cells into the liver, were attenuated by sporamin. Immunohistochemical staining and ELISA showed that the concentrations of β-catenin and VEGF in the liver were significantly reduced by sporamin. Compared with the vehicle group, the expression of β-catenin measured in integrated optical density units per area was reduced in the sporamin group (47.29 ± 9.10 vs 26.14 ± 1.72; P = 0.003). Expression of VEGF was also reduced after sporamin intervention from 20.78 ± 2.06 in the vehicle group to 15.80 ± 1.09 in the sporamin group (P = 0.021). Compared with the vehicle group, the concentration of β-catenin decreased from 134.42 ± 22.04 pg/mL to 109.07 ± 9.65 pg/mL after sporamin intervention (P = 0.00002). qPCR indicated that compared to the vehicle group, relative mRNA expression of β-catenin and VEGF in the liver of mice in the sporamin-treated group was significantly reduced to 71% ± 1% (P = 0.000001) and 23% ± 7% (P = 0.00002), respectively, of the vehicle group levels. Sporamin down-regulates the expression and secretion of β-catenin and VEGF in the liver, which subsequently inhibits the transcription of downstream genes involved in cancer progression and angiogenesis.

Background and aims: Malnutrition is widely present and influences the prognosis of elderly inpatients, so it is helpful to be able to identify it with a convenient method. However, in the widely accepted criteria for malnutrition, the Global Leadership Initiative on Malnutrition (GLIM), a lot of metrics can be used to define the phenotypic and etiological criteria. To identify muscle mass reduction, anthropometric parameters such as calf circumference (CC) and hand grip strength (HGS) are preferable to other expensive methods in many situations because they are easy and inexpensive to measure, but their applicability needs to be verified in specific clinical scenarios. This study aims to verify the value of CC- and HGS-identified muscle loss in diagnosing malnutrition and predicting in-hospital complications (IHC) and prolonged length of hospital stay (PLOS) in elderly inpatients using machine learning methods. Methods: A sample of 7122 elderly inpatients who were enrolled in a previous multicenter cohort study in China were screened for eligibility for the current study and were then retrospectively diagnosed for malnutrition using 33 GLIM criteria that differ in their combinations of phenotypic and etiological criteria, in which CC or CC+HGS were used to identify muscle mass reduction. The diagnostic consistency with the subjective global assessment (SGA) criteria at admission was evaluated according to Kappa coefficients. The association and the predictive value of the GLIM-defined malnutrition with 30-day IHC and PLOS were evaluated with logistic regression and randomized forest models. Results: In total, 2526 inpatients (average age 74.63 ± 7.12 years) were enrolled in the current study. The prevalence of malnutrition identified by the 33 criteria combinations ranged from 3.3% to 27.2%. The main IHCs was infectious complications (2.5%). The Kappa coefficients ranged from 0.130 to 0.866. Logistic regression revealed that malnutrition was identified by 31 GLIM criteria combinations that were significantly associated with 30-day IHC, and 22 were significantly associated with PLOS. Random forest prediction revealed that GLIM 15 (unconscious weight loss + muscle mass reduction, combined with disease burden/inflammation) performs best in predicting IHC; GLIM 30 (unconscious weight loss + muscle mass reduction + BMI reduction, combined with disease burden/inflammation) performs best in predicting PLOS. Importantly, CC alone performs better than CC+HGS in the criteria combinations for predicting adverse clinical outcomes. Conclusion: Muscle mass reduction defined by a reduced CC performs well in the GLIM criteria combinations for diagnosing malnutrition and predicting IHC and PLOS in elderly Asian inpatients. The applicability of other anthropometric parameters in these applications needs to be further explored.