A Risk Prediction Model Based on Machine Learning for Cognitive Impairment Among Chinese Community-Dwelling Elderly People With Normal Cognition: Development and Validation Study

Background: Identifying cognitive impairment early enough could support timely intervention that may hinder or delay the trajectory of cognitive impairment, thus increasing the chances for successful cognitive aging.Objective: We aimed to build a prediction model based on machine learning for cognitive impairment among Chinese community-dwelling elderly people with normal cognition.Methods: A prospective cohort of 6718 older people from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) register, followed between 2008 and 2011, was used to develop and validate the prediction model. Participants were included if they were aged 60 years or above, were community-dwelling elderly people, and had a cognitive Mini-Mental State Examination (MMSE) score >= 18. They were excluded if they were diagnosed with a severe disease (eg, cancer and dementia) or were living in institutions. Cognitive impairment was identified using the Chinese version of the MMSE. Several machine learning algorithms (random forest, XGBoost, naive Bayes, and logistic regression) were used to assess the 3-year risk of developing cognitive impairment. Optimal cutoffs and adjusted parameters were explored in validation data, and the model was further evaluated in test data. A nomogram was established to vividly present the prediction model.Results: The mean age of the participants was 80.4 years (SD 10.3 years), and 50.85% (3416/6718) were female. During a 3-year follow-up, 991 (14.8%) participants were identified with cognitive impairment. Among 45 features, the following four features were finally selected to develop the model: age, instrumental activities of daily living, marital status, and baseline cognitive function. The concordance index of the model constructed by logistic regression was 0.814 (95% CI 0.781-0.846). Older people with normal cognitive functioning having a nomogram score of less than 170 were considered to have a low 3-year risk of cognitive impairment, and those with a score of 170 or greater were considered to have a high 3-year risk of cognitive impairment.Conclusions: This simple and feasible cognitive impairment prediction model could identify community-dwelling elderly people at the greatest 3-year risk for cognitive impairment, which could help community nurses in the early identification of dementia

Nicotinamide reverses deficits in puberty-born neurons and cognitive function after maternal separation.

Background Early life stress (ELS) is associated with the development of schizophrenia later in life. The hippocampus develops significantly during childhood and is extremely reactive to stress. In rodent models, ELS can induce neuroinflammation, hippocampal neuronal loss, and schizophrenia-like behavior. While nicotinamide (NAM) can inhibit microglial inflammation, it is unknown whether NAM treatment during adolescence reduces hippocampal neuronal loss and abnormal behaviors induced by ELS. Methods Twenty-four hours of maternal separation (MS) of Wistar rat pups on post-natal day (PND)9 was used as an ELS. On PND35, animals received a single intraperitoneal injection of BrdU to label dividing neurons and were given NAM from PND35 to PND65. Behavioral testing was performed. Western blotting and immunofluorescence staining were used to detect nicotinamide adenine dinucleotide (NAD+)/Sirtuin3 (Sirt3)/superoxide dismutase 2 (SOD2) pathway-related proteins. Results Compared with controls, only MS animals in the adult stage (PND56–65) but not the adolescent stage (PND31–40) exhibited pre-pulse inhibition deficits and cognitive impairments mimicking schizophrenia symptoms. MS decreased the survival and activity of puberty-born neurons and hippocampal NAD+ and Sirt3 expression in adulthood. These observations were related to an increase in acetylated SOD2, microglial activation, and significant increases in pro-inflammatory IL-1β, TNF-α, and IL-6 expression. All the effects of MS at PND9 were reversed by administering NAM in adolescence (PND35–65). Conclusions MS may lead to schizophrenia-like phenotypes and persistent hippocampal abnormalities. NAM may be a safe and effective treatment in adolescence to restore normal hippocampal function and prevent or ameliorate schizophrenia-like behavior

Manufacturing of AcMNPV baculovirus vectors to enable gene therapy trials

Over the past two decades, baculoviruses have become workhorse research tools for transient transgene expression. Although they have not yet been used directly as a gene therapy vector in the clinical setting, numerous preclinical studies have suggested the highly promising potential of baculovirus as a delivery vector for a variety of therapeutic applications including vaccination, tissue engineering, and cancer treatment. As such, there is growing interest in using baculoviruses as human gene therapy vectors, which has led to advances in baculovirus bioprocessing methods. This review provides an overview of the current approaches for scaled-up amplification, concentration, purification, and formulation of AcMNPV baculoviruses, and highlights the key regulatory requirements that must be met before gene therapy clinical trials can be initiated

Metal–Organic Frameworks–Based Memristors: Materials, Devices, and Applications

Facing the explosive growth of data, a number of new micro-nano devices with simple structure, low power consumption, and size scalability have emerged in recent years, such as neuromorphic computing based on memristor. The selection of resistive switching layer materials is extremely important for fabricating of high performance memristors. As an organic-inorganic hybrid material, metal-organic frameworks (MOFs) have the advantages of both inorganic and organic materials, which makes the memristors using it as a resistive switching layer show the characteristics of fast erasing speed, outstanding cycling stability, conspicuous mechanical flexibility, good biocompatibility, etc. Herein, the recent advances of MOFs-based memristors in materials, devices, and applications are summarized, especially the potential applications of MOFs-based memristors in data storage and neuromorphic computing. There also are discussions and analyses of the challenges of the current research to provide valuable insights for the development of MOFs-based memristors

Understanding Morphology Compatibility for High-Performance Ternary Organic Solar Cells

Ternary organic solar cells are emerging as a promising strategy to enhance device power conversion efficiency by broadening the range of light absorption via the incorporation of additional light-absorbing components. However, how to find compatible materials that allow comparable loadings of each component remains a challenge. In this article, we focus on studying the donor polymer compatibilities in ternary systems from a morphological point of view. Four typical donor polymers with different chemical structures and absorption ranges were mutually combined to form six distinct ternary systems with fullerene derivative acceptors. Two compatible ternary systems were identified as showing significant improvements of efficiency from both binary control devices. Ternary morphologies were characterized by grazing incident X-ray scattering and correlated with device performance. We find that polymers that have strong lamellar interactions and relatively similar phase separation behaviors with the fullerene derivative are more likely to be compatible in ternary systems. This result provides guidance for polymer selection for future ternary organic solar cell research while relaxing the limitation of chemical structure similarity and greatly extends the donor candidate pool

Additional file 1 of Nicotinamide reverses deficits in puberty-born neurons and cognitive function after maternal separation

Additional file 1. Line graph depicting the stimulus protocol to assess the sensorimotor gating