Prevalence and risk factors for dementia and mild cognitive impairment among older people in Southeast China: a community-based study.

BACKGROUND: With the aging population, the number of individuals with dementia in China is increasing rapidly. This community-based study aimed to investigate the prevalence and risk factors for dementia and mild cognitive impairment (MCI) among older adults in China. METHODS: In this study, 20,070 individuals aged ≥ 65 were recruited between January 1, 2022, and February 1, 2023, from ten communities in Xiamen City, China. We collected data on age, sex, level of education, and medical history, as well as global cognition and functional status. The prevalence of dementia and MCI was examined, and the risk factors for different groups were assessed. RESULTS: The overall prevalence of dementia and MCI was approximately 5.4% (95% confidence interval [CI], 5.1-5.7) and 7.7% (95% CI, 7.4-8.1), respectively. The results also indicated that dementia and MCI share similar risk factors, including older age, female sex, hypertension, and diabetes mellitus. Compared with individuals with no formal education, those with > 6 years of education had an odds ratio for MCI of 1.83 (95% CI, 1.49-2.25). We also found that only 5.5% of the positive participants chose to be referred to the hospital for further diagnosis and treatment during follow-up visits. CONCLUSIONS: This study estimated the prevalence and risk factors for dementia and MCI among individuals aged ≥ 65 years in Southeast China. These findings are crucial for preventing and managing dementia and MCI in China.

Automatic interictal epileptiform discharge (IED) detection based on convolutional neural network (CNN).

Clinical diagnosis of epilepsy significantly relies on identifying interictal epileptiform discharge (IED) in electroencephalogram (EEG). IED is generally interpreted manually, and the related process is very time-consuming. Meanwhile, the process is expert-biased, which can easily lead to missed diagnosis and misdiagnosis. In recent years, with the development of deep learning, related algorithms have been used in automatic EEG analysis, but there are still few attempts in IED detection. This study uses the currently most popular convolutional neural network (CNN) framework for EEG analysis for automatic IED detection. The research topic is transferred into a 4-labels classification problem. The algorithm is validated on the long-term EEG of 11 pediatric patients with epilepsy. The computational results confirm that the CNN-based model can obtain high classification accuracy, up to 87%. The study may provide a reference for the future application of deep learning in automatic IED detection.

Deep multi-modal intermediate fusion of clinical record and time series data in mortality prediction.

In intensive care units (ICUs), mortality prediction is performed by combining information from these two sources of ICU patients by monitoring patient health. Respectively, time series data generated from each patient admission to the ICU and clinical records consisting of physician diagnostic summaries. However, existing mortality prediction studies mainly cascade the multimodal features of time series data and clinical records for prediction, ignoring thecross-modal correlation between the underlying features in different modal data. To address theseissues, we propose a multimodal fusion model for mortality prediction that jointly models patients' time-series data as well as clinical records. We apply a fine-tuned Bert model (Bio-Bert) to the patient's clinical record to generate a holistic embedding of the text part, which is then combined with the output of an LSTM model encoding the patient's time-series data to extract valid features. The global contextual information of each modal data is extracted using the improved fusion module to capture the correlation between different modal data. Furthermore, the improved fusion module can be easily added to the fusion features of any unimodal network and utilize existing pre-trained unimodal model weights. We use a real dataset containing 18904 ICU patients to train and evaluate our model, and the research results show that the representations obtained by themodel can achieve better prediction accuracy compared to the baseline.

Integrative analysis of single-cell transcriptomics reveals age-associated immune landscape of glioblastoma.

Glioblastoma (GBM) is the most malignant tumor in center nervous system. Clinical statistics revealed that senior GBM patients had a worse overall survival (OS) comparing with that of patients in other ages, which is mainly related with tumor microenvironment including tumor-associated immune cells in particular. However, the immune heterogeneity and age-related prognosis in GBM are under studied. Here we developed a machine learning-based method to integrate public large-scale single-cell RNA sequencing (scRNA-seq) datasets to establish a comprehensive atlas of immune cells infiltrating in cross-age GBM. We found that the compositions of the immune cells are remarkably different across ages. Brain-resident microglia constitute the majority of glioblastoma-associated macrophages (GAMs) in patients, whereas dramatic elevation of extracranial monocyte-derived macrophages (MDMs) is observed in GAMs of senior patients, which contributes to the worse prognosis of aged patients. Further analysis suggests that the increased MDMs arisen from excessive recruitment and proliferation of peripheral monocytes not only lead to the T cell function inhibition in GBM, but also stimulate tumor cells proliferation via VEGFA secretion. In summary, our work provides new cues for the correlational relationship between the immune microenvironment of GBM and aging, which might be insightful for precise and effective therapeutic interventions for senior GBM patients.

Microglial Piezo1 senses Aß fibril stiffness to restrict Alzheimer's disease.

The pathology of Alzheimer's disease (AD) is featured with extracellular amyloid-ß (Aß) plaques, whose impact on the mechanical properties of the surrounding brain tissues is unclear. Microglia sense and integrate biochemical cues of the microenvironment. However, whether the microglial mechanosensing pathways influence AD pathogenesis is unknown. Here, we surveyed the elevated stiffness of Aß-plaque-associated tissues and observed the selective upregulation of the mechanosensitive ion channel Piezo1 in Aß-plaque-associated microglia. Piezo1 sensed the stiffness stimuli of Aß fibrils and subsequently induced Ca2+ influx for microglial clustering, phagocytosis, and compacting of Aß plaques. Microglia lacking Piezo1 led to the exacerbation of Aß pathology and cognitive decline, whereas pharmacological activation of microglial Piezo1 ameliorated brain Aß burden and cognitive impairment in 5 × FAD mice. Together, our results reveal that Piezo1, a mechanosensor of Aß fibril stiffness in microglia, represents a potential therapeutic target for AD.

Health threat of PM2.5-bound trace elements exposure on asthma hospital admission: A time-stratified case-crossover study.

Environmental pollution of trace elements has become of main concern due to the adverse effects. To estimate the impact of PM2.5-bound trace elements on human health, a time-stratified case-crossover study has been designed to examine the short-term associations between 28 elements and asthma hospitalizations from January 2019 to November 2021 in Xiamen, China. This research summarized the major components that pose health risks in different seasons and took risk assessment for different groups. We found that an inter-quartile range (IQR) increase of Ca, Fe, Mn, Pd, Si, and Ti was positively associated with the incidence of asthma in the lag of 0-4 days. In winter, the elements that predisposed the population to asthma attack were the most, such as Al, Ba, Ca, Cr, Cu, Fe, K, Mn, Pd, Si, and Ti, and these elements are at higher risk for longer periods of time. The discrepancy in risk levels and major elements of asthma diagnosis among various age groups were also found in this work. Our results provided insights into the development of specific policies to reduce the risk of asthma attacks due to exposure to PM2.5-bound trace elements.

Clinical tooth segmentation based on local enhancement.

The tooth arrangements of human beings are challenging to accurately observe when relying on dentists' naked eyes, especially for dental caries in children, which is difficult to detect. Cone-beam computer tomography (CBCT) is used as an auxiliary method to measure patients' teeth, including children. However, subjective and irreproducible manual measurements are required during this process, which wastes much time and energy for the dentists. Therefore, a fast and accurate tooth segmentation algorithm that can replace repeated calculations and annotations in manual segmentation has tremendous clinical significance. This study proposes a local contextual enhancement model for clinical dental CBCT images. The local enhancement model, which is more suitable for dental CBCT images, is proposed based on the analysis of the existing contextual models. Then, the local enhancement model is fused into an encoder-decoder framework for dental CBCT images. At last, extensive experiments are conducted to validate our method.

A genetic analysis of Chinese patients with early-onset Parkinson' s disease.

Genetic factors play an important role in early-onset Parkinson's disease (EOPD). The genetic spectrum of patients with EOPD varies widely among different ethnicities, with extensive investigations having been performed in Caucasian populations; however, research in Chinese populations remains limited. In this study, we performed multiplex ligation-dependent probe amplification assay and whole-exome sequencing in 15 unrelated Chinese EOPD patients with age of onset before 40 years. Among them, a patient carried compound heterozygous exon duplications in Parkin (exon 3 duplication and exon 4 duplication) (6.67 %) and two patients carried the homozygous pathogenic variant (p.D331Y) in PLA2G6 (13.33 %). Three novel variants in EIF4G1 (p.P1043S, p.R1505Q, and p.P266A) were identified and classified as uncertain significance. Additionally, a risk variant in GBA (p.L483P) was detected in one patient (6.67 %). PLA2G6 (13.33 %) was the most common causative gene among our EOPD patients. Furthermore, detailed clinical features were presented. Our results broaden the genetic spectrum and clinical phenotypic spectrum of EOPD patients.

A Moderate Duration of Stress Promotes Behavioral Adaptation and Spatial Memory in Young C57BL/6J Mice.

Stress may serve multiple roles in cerebral functioning, ranging from a highly appropriate behavioral adaptation to a critical risk factor for susceptibility to mood disorder and cognitive impairment. It is well known that E/I (excitation/inhibition) balance is essential for maintaining brain homeostasis. However, it remains largely unknown how GABAergic and Glutamatergic neurons respond to different stressful stimuli and whether the GABAergic-Glutamatergic neuron balance is related to the transition between adaptive and maladaptive behaviors. Here, we subjected 3-month-old mice to chronic mild stress (CMS) for a period of one, two, and four weeks, respectively. The results showed that the two-week CMS procedure produced adaptive effects on behaviors and cognitive performance, with a higher number of GABAergic neuron and VGluT1-positive neurons, increasing the expressions of p-GluN2B, Reelin, and syn-PSD-95 protein in the hippocampus. In contrast, the prolonged behavioral challenge (4 week) imposes a passive coping behavioral strategy and cognitive impairment, decreased the number of GABAergic neuron, hyperactivity of VGluT1-positive neuron, increased the ratio of p-GluN2B, and decreased the expression of Reelin, syn-PSD-95 in the hippocampus. These findings suggest that a moderate duration of stress probably promotes behavioral adaptation and spatial memory by maintaining a GABAergic-Glutamatergic neuron balance and promoting the expression of synaptic plasticity-related proteins in the brain.

Transformer-Based High-Frequency Oscillation Signal Detection on Magnetoencephalography From Epileptic Patients.

High-frequency oscillations (HFOs), observed within 80-500 Hz of magnetoencephalography (MEG) data, are putative biomarkers to localize epileptogenic zones that are critical for the success of surgical epilepsy treatment. It is crucial to accurately detect HFOs for improving the surgical outcome of patients with epilepsy. However, in clinical practices, detecting HFOs in MEG signals mainly depends on visual inspection by clinicians, which is very time-consuming, labor-intensive, subjective, and error-prone. To accurately and automatically detect HFOs, machine learning approaches have been developed and have demonstrated the promising results of automated HFO detection. More recently, the transformer-based model has attracted wide attention and achieved state-of-the-art performance on many machine learning tasks. In this paper, we are investigating the suitability of transformer-based models on the detection of HFOs. Specifically, we propose a transformer-based HFO detection framework for biomedical MEG one-dimensional signal data. For signal classification, we develop a transformer-based HFO (TransHFO) classification model. Then, we investigate the relationship between depth of deep learning models and classification performance. The experimental results show that the proposed framework outperforms the state-of-the-art HFO classifiers, increasing classification accuracy by 7%. Furthermore, we find that shallow TransHFO ( < 10 layers) outperforms deep TransHFO models (≥10 layers) on most data augmented factors.

The Oligodendrocyte Transcription Factor 2 OLIG2 regulates transcriptional repression during myelinogenesis in rodents.

OLIG2 is a transcription factor that activates the expression of myelin-associated genes in the oligodendrocyte-lineage cells. However, the mechanisms of myelin gene inactivation are unclear. Here, we uncover a non-canonical function of OLIG2 in transcriptional repression to modulate myelinogenesis by functionally interacting with tri-methyltransferase SETDB1. Immunoprecipitation and chromatin-immunoprecipitation assays show that OLIG2 recruits SETDB1 for H3K9me3 modification on the Sox11 gene, which leads to the inhibition of Sox11 expression during the differentiation of oligodendrocytes progenitor cells (OPCs) into immature oligodendrocytes (iOLs). Tissue-specific depletion of Setdb1 in mice results in the hypomyelination during development and remyelination defects in the injured rodents. Knockdown of Sox11 by siRNA in rat primary OPCs or depletion of Sox11 in the oligodendrocyte lineage in mice could rescue the hypomyelination phenotype caused by the loss of OLIG2. In summary, our work demonstrates that the OLIG2-SETDB1 complex can mediate transcriptional repression in OPCs, affecting myelination.

Sec13 promotes oligodendrocyte differentiation and myelin repair through autocrine pleiotrophin signaling.

Dysfunction of protein trafficking has been intensively associated with neurological diseases, including neurodegeneration, but whether and how protein transport contributes to oligodendrocyte (OL) maturation and myelin repair in white matter injury remains unclear. ER-to-Golgi trafficking of newly synthesized proteins is mediated by coat protein complex II (COPII). Here, we demonstrate that the COPII component Sec13 was essential for OL differentiation and postnatal myelination. Ablation of Sec13 in the OL lineage prevented OPC differentiation and inhibited myelination and remyelination after demyelinating injury in the central nervous system (CNS), while improving protein trafficking by tauroursodeoxycholic acid (TUDCA) or ectopic expression of COPII components accelerated myelination. COPII components were upregulated in OL lineage cells after demyelinating injury. Loss of Sec13 altered the secretome of OLs and inhibited the secretion of pleiotrophin (PTN), which was found to function as an autocrine factor to promote OL differentiation and myelin repair. These data suggest that Sec13-dependent protein transport is essential for OL differentiation and that Sec13-mediated PTN autocrine signaling is required for proper myelination and remyelination.

APOE4 genotype exacerbates the depression-like behavior of mice during aging through ATP decline.

Population-based studies reveal that apolipoprotein E (APOE) ε4 gene allele is closely associated with late-life depression (LLD). However, its exact role and underlying mechanism remain obscure. The current study found that aged apoE4-targeted replacement (TR) mice displayed obvious depression-like behavior when compared with age-matched apoE3-TR mice. Furthermore, apoE4 increased stress-induced depression-like behaviors, accompanied by declines in the hippocampal 5-HT (1A) radioligand [18F] MPPF uptake evidenced by positron emission tomography (PET). In [18F]-fluorodeoxyglucose PET ([18F]-FDG PET) analyses, the FDG uptake in the prefrontal cortex, temporal cortex and hippocampus of apoE4-TR mice significantly declined when compared with that of apoE3-TR mice after acute stress. Further biochemical analysis revealed that ATP levels in the prefrontal cortex of apoE4-TR mice decreased during aging or stress process and ATP supplementation effectively rescued the depression-like behaviors of elderly apoE4-TR mice. In primary cultured astrocytes from the cortex of apoE-TR mice, apoE4, when compared with apoE3, obviously decreased the mitochondrial membrane potential, mitochondrial respiration, and glycolysis in a culture time-dependent manner. Our findings highlight that apoE4 is a potential risk factor of depression in elderly population by impairing the glucose metabolism, reducing ATP level, and damaging mitochondrial functions in astrocytes, which indicates that in clinical settings ATP supplementation may be effective for elderly depression patients with apoE4 carrier.

ApoE4 increases susceptibility to stress-induced age-dependent depression-like behavior and cognitive impairment.

Though apolipoprotein E ε4 (APOE ε4) is a major genetic risk factor for late-onset Alzheimer's disease, its association with depression remains controversial. In present study, 3-month-old and 8-month-old apoE-targeted replacement (TR) mice were both subjected to chronic unpredictable mild stress (CUMS) for six weeks. The results showed that 8-month apoE4-TR mice were more susceptible to the CUMS-induced depression-like behaviors and cognitive impairment than age-matched apoE3-TR mice. Stress induced a loss of GABAergic neurons and decline of Reelin level in the prefrontal cortex (PFC) and in the dentate gyrus (DG) of the hippocampus in both 3-month-old and 8-month-old apoE-TR mice, which were more pronounced in the 8-month-old apoE4-TR mice. Of note, stress decreased the level of PSD95 in the hippocampal synaptosome and increased the phosphorylation of N-methyl-D-aspartate receptor subunit GluN2B in the hippocampus of 8-month-old apoE4-TR mice. However, the expressions of apoE and apoE receptor 2 (apoER2) were not affected by stress. The study provides rodent evidence that APOE ε4 may increase the risk of depression and dementia in the elderly population by impairing the GABAergic signaling pathway and enhancing the GluN2B phosphorylation, which signifies that GluN2B inhibitors in clinical settings may be effective for elderly depression patients with APOE4 carriers.

A Pathogenic Variant p.Phe177Val in PSEN1 Causes Early-Onset Alzheimer's Disease in a Chinese Family.

Familial Alzheimer's disease (FAD) present as a positive family history of cognitive decline, with early onset and an autosomal dominant inheritance pattern. FAD is mainly caused by the mutations in the genes encoding for amyloid precursor protein (APP), presenilin-1 (PSEN1), and presenilin-2 (PSEN2). In the present study, we identified a variant (c.529T > G, p.Phe177Val) in PSEN1 across three generations in a Chinese family with FAD using whole-exome sequencing. The mean age of onset was 39 years (range: 37 to 40 years) in this family. In cell transfection studies, the mutant PSEN1 protein carrying p.Phe177Val increased both the production of Aß42 and the ratio of Aß42 over Aß40, as compared to wild-type PSEN1. Our results confirm the pathogenicity of PSEN1 p.Phe177Val variant in FAD and broaden the clinical phenotype spectrum of FAD patients with PSEN1 p.Phe177Val variant.

Curcumin Ameliorates Memory Decline via Inhibiting BACE1 Expression and ß-Amyloid Pathology in 5×FAD Transgenic Mice.

Alzheimer's disease (AD) is the most common dementia and the trigger of its pathological cascade is widely believed to be the overproduction and accumulation of ß-amyloid protein (Aß) in the affected brain. However, effective AD remedies are still anxiously awaited. Recent evidence suggests that curcumin may be a potential agent for AD treatment. In this study, we used 5×FAD transgenic mice as an AD model to investigate the effects of curcumin on AD. Our results showed that curcumin administration (150 or 300 mg/kg/day, intragastrically, for 60 days) dramatically reduced Aß production by downregulating BACE1 expression, preventing synaptic degradation, and improving spatial learning and memory impairment of 5×FAD mice. These findings suggest that curcumin is a potential candidate for AD treatment.

A novel presenilin 1 mutation (F388L) identified in a Chinese family with early-onset Alzheimer's disease.

A subset of Alzheimer's disease (AD) occurrence shows autosomal dominant, familial inheritance patterns. Such familial AD (FAD) are caused by mutations in APP, PSEN1, and PSEN2 genes, which encode amyloid-ß (Aß) precursor protein, presenilin 1 (PS1), and presenilin 2 (PS2), respectively. Here, we report a novel PSEN1 mutation (c.1164C > G, p.F388L, mutation nomenclature according to National Center for Biotechnology Information Reference Sequence: NM_000021.3) occurring in a Chinese family with early-onset AD and cosegregating with affected family members. The average age at onset of this family was 43 years. The F388L mutation locates adjacent to the critical catalytic aspartate site (D385) of PS1. Overexpression of the F388L mutant significantly increased Aß42 secretion and the ratio of Aß42/Aß40 when compared with wild type PS1, consisting with the notion that FAD-associated PS1 mutations induce disease pathogenesis by increasing Aß42/Aß40 ratio. Our results identify a novel pathogenic PS1 F388L mutation in a Chinese FAD family.

Early-life stress leads to impaired spatial learning and memory in middle-aged ApoE4-TR mice.

BACKGROUND: Apolipoprotein E (ApoE) is a major lipid carrier that supports lipid transport and injury repair in the brain. The APOE ε4 allele is associated with depression, mild cognitive impairment (MCI) and dementia; however, the precise molecular mechanism through which ApoE4 influences the risk of disease development remains unknown. To address this gap in knowledge, we investigated the potential effects of chronic unpredictable mild stress (CUMS) on ApoE3 and ApoE4 target replacement (ApoE3-TR and ApoE4-TR) mice. RESULTS: All ApoE-TR mice exposed to CUMS at 3 months old recovered from a depression-like state by the age of 12 months. Of note, ApoE4-TR mice, unlike age-matched ApoE3-TR mice, displayed impaired spatial cognitive abilities, loss of GABAergic neurons, decreased expression of Reelin, PSD95, SYN and Fyn, and reduced phosphorylation of NMDAR2B and CREB. CONCLUSION: These results suggest that early-life stress may mediate cognitive impairment in middle-age ApoE4-TR mice through sustained reduction of GABAergic neurons and Reelin expression, which might further diminish the activation of the Fyn/NMDAR2B signaling pathway.