Associations Between Neuroinflammation-Related Conditions and Alzheimer's Disease: A Study of US Insurance Claims Data.

Background: Early detection of Alzheimer's disease (AD) is a key component for the success of the recently approved lecanemab and aducanumab. Patients with neuroinflammation-related conditions are associated with a higher risk for developing AD. Objective: Investigate the incidence of AD among patients with neuroinflammation-related conditions including epilepsy, hemorrhage stroke, multiple sclerosis (MS), and traumatic brain injury (TBI). Methods: We used Optum's de-identified Clinformatics Data Mart Database (CDM). We derived covariate-matched cohorts including patients with neuroinflammation-related conditions and controls without the corresponding condition. The matched cohorts were: 1) patients with epilepsy and controls (N = 67,825 matched pairs); 2) patients with hemorrhage stroke and controls (N = 81,510 matched pairs); 3) patients with MS and controls (N = 9,853 matched pairs); and 4) patients TBI and controls (N = 104,637 matched pairs). We used the Cox model to investigate the associations between neuroinflammation-related conditions and AD. Results: We identified that epilepsy, hemorrhage stroke, and TBI were associated with increased risks of AD in both males and females (hazard ratios [HRs]≥1.74, p < 0.001), as well as in gender- and race-conscious subpopulations (HRs≥1.64, p < 0.001). We identified that MS was associated with increased risks of AD in both males and females (HRs≥1.47, p≤0.004), while gender- and race-conscious subgroup analysis shown mixed associations. Conclusions: Patients with epilepsy, hemorrhage stroke, MS, and/or TBI are associated with a higher risk of developing AD. More attention on cognitive status should be given to older patients with these conditions.

Sildenafil as a Candidate Drug for Alzheimer's Disease: Real-World Patient Data Observation and Mechanistic Observations from Patient-Induced Pluripotent Stem Cell-Derived Neurons.

Background: Alzheimer's disease (AD) is a chronic neurodegenerative disease needing effective therapeutics urgently. Sildenafil, one of the approved phosphodiesterase-5 inhibitors, has been implicated as having potential effect in AD. Objective: To investigate the potential therapeutic benefit of sildenafil on AD. Methods: We performed real-world patient data analysis using the MarketScan® Medicare Supplemental and the Clinformatics® databases. We conducted propensity score-stratified analyses after adjusting confounding factors (i.e., sex, age, race, and comorbidities). We used both familial and sporadic AD patient induced pluripotent stem cells (iPSC) derived neurons to evaluate the sildenafil's mechanism-of-action. Results: We showed that sildenafil usage is associated with reduced likelihood of AD across four new drug compactor cohorts, including bumetanide, furosemide, spironolactone, and nifedipine. For instance, sildenafil usage is associated with a 54% reduced incidence of AD in MarketScan® (hazard ratio [HR] = 0.46, 95% CI 0.32- 0.66) and a 30% reduced prevalence of AD in Clinformatics® (HR = 0.70, 95% CI 0.49- 1.00) compared to spironolactone. We found that sildenafil treatment reduced tau hyperphosphorylation (pTau181 and pTau205) in a dose-dependent manner in both familial and sporadic AD patient iPSC-derived neurons. RNA-sequencing data analysis of sildenafil-treated AD patient iPSC-derived neurons reveals that sildenafil specifically target AD related genes and pathobiological pathways, mechanistically supporting the beneficial effect of sildenafil in AD. Conclusions: These real-world patient data validation and mechanistic observations from patient iPSC-derived neurons further suggested that sildenafil is a potential repurposable drug for AD. Yet, randomized clinical trials are warranted to validate the causal treatment effects of sildenafil in AD.

An analysis of stimulation methods used in rehabilitation equipment for children with cerebral palsy.

Objective: This paper summarizes the research progress into stimulation methods used in rehabilitation equipment for pediatric cerebral palsy (CP) for the past 20 years from 2003 to 2023. We also provide ideas for innovative research and development of artificial intelligence-based rehabilitation equipment. Methods: Through a certain search strategy, Keywords are searched in the China National Knowledge Network Database (CNKI), the Wanfang Database knowledge service platform, the Chongqing VIP information service, PubMed, Web of Science, Cochrane, ScienceDirect, Medline, Embase, and IEEE database. A total of 3,049 relevant articles were retrieved, and 49 articles were included that mentioned research and development of rehabilitation equipment. We excluded articles that were not specific to children with CP, were duplicated or irrelevant literature, were missing data, the full article was not available, the article did not describe the method of stimulation used with the rehabilitation equipment on children with CP, were not Chinese and English, and were the types of reviews and commentaries. Results: Physical stimulation is the main stimulation method of rehabilitation equipment for children with CP. Force stimulation is the main mode of physical stimulation, and there are 17 articles that have verified the clinical efficacy of force stimulation-based equipment. Conclusion: Research on the stimulation mode of pediatric cerebral palsy rehabilitation equipment is likely to focus on simulating the force of the Chinese medicine called "tuina manipulation." When this method is combined with artificial intelligence and personalized direction we believe this will lay the foundation for future development of a novel therapy for children with CP.

Research on the Solid-Liquid Composite Casting Process of Incoloy825/P110 Steel Composite Pipe.

Bimetallic composites have a wide range of application prospects in various industries. Different bonding temperatures, as one of the influencing factors, directly affect the bonding effectiveness as well as the performance and application of the materials. Using metallurgical bonding techniques ensures a strong bond at the interface of bimetallic materials, resulting in high-quality composite pipe billets. This paper describes an Incoloy825/P110 steel bimetal composite material made by the solid-liquid composite method. By utilizing ProCAST 14.5 software for simulation and deriving theoretical formulas, an initial range of temperatures for bimetallic preparation has been tentatively determined. And this temperature range will be utilized for on-site experiments to prepare bimetallic samples. After the preparation process is completed, samples will be selected. The influence of the external mold temperature on the interface bonding of Incoloy825/P110 steel solid-liquid composite material is studied using an ultra-depth three-dimensional morphology microscope and a scanning electron microscope. Through research, the optimal preheating temperature range for the solid-liquid composite outer mold of Incoloy825/P110 bimetallic composite material has been determined. The casting temperature of the inner mold has a significant impact on the interface bonding of this bimetal composite material. As the casting temperature of the inner mold increases, the interface thickness gradually increases. At lower temperatures, the interface thickness is lower and the bonding is poorer. At higher temperatures, melting may occur, leading to coarse grains at the interface. When the temperatures of the inner and outer molds are within a certain range, a new phase appears at the interface. Indeed, it increases the strength of the interface bonding. Due to co-melting of the bimetal near the interface, element migration occurs, resulting in increased Ni and Cr content at the interface and enhanced corrosion resistance.

Breviscapine ameliorates autophagy by activating the JAK2/STAT5/BCL2 pathway in a transient cerebral ischemia rat model.

Breviscapine (Bre), an extract from Erigeron breviscapus, has been widely used to treat cerebral ischemia but the mechanisms of its neuroprotective effects need to be clarified. The present study investigated whether Bre could alleviate excessive autophagy induced by cerebral ischemia in the rat middle cerebral artery occlusion (MCAO) ischemia model via activating the Janus kinase 2 (JAK2)/signal transducer and activator of transcription 5 (STAT5)/B-cell lymphoma 2 (BCL2) pathway. Rats were randomly divided into 5 groups, i.e. Sham group, MCAO+saline group, MCAO+Bre group, MCAO+DMSO (Dimethyl sulfoxide) group, and MCAO+Bre+AG490 (Tyrphostin AG490, the inhibitor of STAT5) group. The model was established and neuroprotection was evaluated by determining infarct volumes and conducting neurological behavioral tests. Autophagy levels in the infarct penumbra were detected using transmission electron microscopy and Western blotting. The expression of proteins in the JAK2/STAT5/BCL2 pathway was tested by Western blotting. Compared to the MCAO+saline group, the infarct volumes in the MCAO+Bre group were significantly reduced and neurological behavior improved. Breviscapine administration also significantly increased p-JAK2, p-STAT5, and BCL2 expression but decreased autolysosome numbers; it also downregulated Beclin-1 expression and the LC3II/LCI ratio. The JAK2 inhibitor AG490 reversed these effects. These findings indicate that breviscapine can improve neural recovery following ischemia through alleviating excessive autophagy and activation of the JAK2/STAT5/BCL2 axis.

Study of the molecular structure of proteins in fermented Maize-Soybean meal-based rations based on FTIR spectroscopy.

This research investigates the dynamic alterations that occur in protein molecular structure during the fermentation process of feed. Fourier transform infrared spectroscopy (FTIR), coupled with deconvolution, second derivative and curve-fitting methodologies, was employed to comparatively analyse the protein molecular structures in fermented feed. At the 48-h fermentation mark, the α-helix and ß-sheet contents reached their peaks, while the random coil and ß-turn contents were at their lowest. Simultaneously, the ß-sheet/α-helix ratio was minimized. FTIR spectroscopy emerged as a comprehensive tool, revealing the nuanced changes in molecular structure throughout the fermentation process of corn-soybean meal feed. When integrated with spectral quantitative analysis, it provides a novel perspective for evaluating the nutritional value of fermented feed.

TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.

OBJECTIVE: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMRs) for personalized precision management of chronic disease progression. MATERIALS AND METHODS: We first perform requirement analysis with clinicians and data scientists to determine the visual analytics tasks of the TrajVis system as well as its design and functionalities. A graph AI model for chronic kidney disease (CKD) trajectory inference named DisEase PrOgression Trajectory (DEPOT) is used for system development and demonstration. TrajVis is implemented as a full-stack web application with synthetic EMR data derived from the Atrium Health Wake Forest Baptist Translational Data Warehouse and the Indiana Network for Patient Care research database. A case study with a nephrologist and a user experience survey of clinicians and data scientists are conducted to evaluate the TrajVis system. RESULTS: The TrajVis clinical information system is composed of 4 panels: the Patient View for demographic and clinical information, the Trajectory View to visualize the DEPOT-derived CKD trajectories in latent space, the Clinical Indicator View to elucidate longitudinal patterns of clinical features and interpret DEPOT predictions, and the Analysis View to demonstrate personal CKD progression trajectories. System evaluations suggest that TrajVis supports clinicians in summarizing clinical data, identifying individualized risk predictors, and visualizing patient disease progression trajectories, overcoming the barriers of AI implementation in healthcare. DISCUSSION: The TrajVis system provides a novel visualization solution which is complimentary to other risk estimators such as the Kidney Failure Risk Equations. CONCLUSION: TrajVis bridges the gap between the fast-growing AI/ML modeling and the clinical use of such models for personalized and precision management of chronic diseases.

Artificial intelligence and open science in discovery of disease-modifying medicines for Alzheimer's disease.

The high failure rate of clinical trials in Alzheimer's disease (AD) and AD-related dementia (ADRD) is due to a lack of understanding of the pathophysiology of disease, and this deficit may be addressed by applying artificial intelligence (AI) to "big data" to rapidly and effectively expand therapeutic development efforts. Recent accelerations in computing power and availability of big data, including electronic health records and multi-omics profiles, have converged to provide opportunities for scientific discovery and treatment development. Here, we review the potential utility of applying AI approaches to big data for discovery of disease-modifying medicines for AD/ADRD. We illustrate how AI tools can be applied to the AD/ADRD drug development pipeline through collaborative efforts among neurologists, gerontologists, geneticists, pharmacologists, medicinal chemists, and computational scientists. AI and open data science expedite drug discovery and development of disease-modifying therapeutics for AD/ADRD and other neurodegenerative diseases.

Genome-wide meta-analyses of cross substance use disorders in European, African, and Latino ancestry populations.

Genetic risks for substance use disorders (SUDs) are due to both SUD-specific and SUD-shared genes. We performed the largest multivariate analyses to date to search for SUD-shared genes using samples of European (EA), African (AA), and Latino (LA) ancestries. By focusing on variants having cross-SUD and cross-ancestry concordant effects, we identified 45 loci. Through gene-based analyses, gene mapping, and gene prioritization, we identified 250 SUD-shared genes. These genes are highly expressed in amygdala, cortex, hippocampus, hypothalamus, and thalamus, primarily in neuronal cells. Cross-SUD concordant variants explained ~ 50% of the heritability of each SUD in EA. The top 5% individuals having the highest polygenic scores were approximately twice as likely to have SUDs as others in EA and LA. Polygenic scores had higher predictability in females than in males in EA. Using real-world data, we identified five drugs targeting identified SUD-shared genes that may be repurposed to treat SUDs.