The effect of EEG and fNIRS in the digital assessment and digital therapy of Alzheimer’s disease: a systematic review

In the context of population aging, the growing problem of Alzheimer’s disease (AD) poses a great challenge to mankind. Although there has been considerable progress in exploring the etiology of AD, i.e., the important role of amyloid plaques and neurofibrillary tangles in the progression of AD has been widely accepted by the scientific community, traditional treatment and monitoring modalities have significant limitations. Therefore novel evaluation and treatment modalities for Alzheimer’s disease are called for emergence. In this research, we sought to review the effectiveness of digital treatment based on monitoring using functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). This work searched four electronic databases using a keyword approach and focused on journals focusing on AD and geriatric cognition. Finally, 21 articles were included. The progress of digital therapy and outcome monitoring in AD was reviewed, including digital therapy approaches on different platforms and different neuromonitoring techniques. Because biomarkers such as theta coherence, alpha and beta rhythms, and oxyhemoglobin are effective in monitoring the cognitive level of AD patients, and thus the efficacy of digital therapies, this review particularly focuses on the biomarker validation results of digital therapies. The results show that digital treatment based on biomarker monitoring has good effectiveness. And the effectiveness is reflected in the numerical changes of biomarker indicators monitored by EEG and fNIRS before and after digital treatment. Increases or decreases in the values of these indicators collectively point to improvements in cognitive function (mostly moderate to large effect sizes). The study is the first to examine the state of digital therapy in AD from the perspective of multimodal monitoring, which broadens the research perspective on the effectiveness of AD and gives clinical therapists a “reference list” of treatment options. They can select a specific protocol from this “reference list” in order to tailor digital therapy to the needs of individual patients

Gut microbiota-derived trimethylamine-N-oxide: a bridge between dietary fatty acid and cardiovascular disease?

Cardiovascular disease (CVD) is a serious disease that endangers human health and is one of the leading causes of death. Recent studies have reported that gut microbiota plays an important role in the development of CVD, especially its metabolite trimethylamine-N-oxide (TMAO). Dietary precursors, such as choline, L-carnitine, phosphatidylcholine and betaine were metabolized to trimethylamine (TMA) under the action of gut microbiota, and subsequently oxidized by hepatic flavin monooxygenases (FMOs) to form TMAO. Dietary fat is one of three major nutrients in food, has been found to have a positive or negative effect on the development of CVD. Multiple clinical and experimental evidences suggested that dietary fatty acids (FAs) can affect TMAO production through gut microbiota and/or FMO3 enzyme activity. This article summarizes the existing gut microbiota-mediated reduction of TMA, discusses the molecular mechanism of dietary FAs in the pathobiology of CVD from the view of TMAO. Therefore, this review provides new insight into the association of dietary FAs and CVD, paving the way for dietary FAs therapy for CVD

Foodomics: a new perspective on gut probiotics nutrition and health research

Probiotics that are living microorganisms, can produce health benefits to the host when administered in sufficient amounts. Various high throughput and sensitivity technology have been employed in the research of gut probiotics, since their extremely sophisticated action mechanism. Foodomics that integrated multiple omics technologies has been widely used for gut probiotics study. This article reviews the advanced technologies in foodomics and gives a comprehensive, critical overview of current state of the art, future challenges and trends of foodomics in gut probiotics nutrition and health investigation

Dynamic placement of the linker histone H1 associated with nucleosome arrangement and gene transcription in early Drosophila embryonic development

The linker histone H1 is critical to maintenance of higher-order chromatin structures and to gene expression regulation. However, H1 dynamics and its functions in embryonic development remain unresolved. Here, we profiled gene expression, nucleosome positions, and H1 locations in early Drosophila embryos. The results show that H1 binding is positively correlated with the stability of beads-on-a-string nucleosome organization likely through stabilizing nucleosome positioning and maintaining nucleosome spacing. Strikingly, nucleosomes with H1 placement deviating to the left or the right relative to the dyad shift to the left or the right, respectively, during early Drosophila embryonic development. H1 occupancy on genic nucleosomes is inversely correlated with nucleosome distance to the transcription start sites. This inverse correlation reduces as gene transcription levels decrease. Additionally, H1 occupancy is lower at the 5\u27 border of genic nucleosomes than that at the 3\u27 border. This asymmetrical pattern of H1 occupancy on genic nucleosomes diminishes as gene transcription levels decrease. These findings shed new lights into how H1 placement dynamics correlates with nucleosome positioning and gene transcription during early Drosophila embryonic development

Curcumin ameliorates gestational diabetes in mice partly through activating AMPK

Context: In vitro and in vivo research has shown that curcumin can alleviate diabetes and the relevant complications. Objective: To investigate the effect of curcumin on gestational diabetes (GD). Materials and methods: C57 BL/KsJdb/+(db/+) mice and C57 BL/KsJ+/+ mice (10–12 weeks old) were divided into four groups (n = 15): normal pregnancy (C57 BL/KsJ+/+), GD (C57 BL/KsJdb/+), GD plus low dose curcumin (50 mg/kg, orally gavage every day) and GD plus high dose curcumin (100 mg/kg, orally gavage every day). The tolerance of glucose and insulin were measured on gestation day 10. Body weight at birth and litter size of offspring were investigated, and the expression of oxidative stress factors [thiobarbituric acid reactive substance (TBARS), glutathione (GSH), superoxide dismutase (SOD) and catalase (CAT)] and AMP-activated protein kinase (AMPK), phospho-AMPK, histone deacetylases 4 (HDAC4), pHDAC4 and glucose-6-phosphatase (G6Pase) in the livers were analyzed by ELISA and Western blot on gestation day 20. Results: High dose curcumin could partly ameliorate the intolerance of glucose and insulin, and completely restore the litter size and the body weight of GD mice through decreased TBARS expression (p < 0.05) and increased GSH, SOD and CAT expression (p < 0.05). Enhanced AMPK activation, accompanied with decreased HDAC4 and G6Pase expression (p < 0.05) were partly contributed to the alleviation of GD mediated by curcumin. Conclusions: Although further detailed mechanism needs to be deciphered, curcumin can be considered as an alternative treatment for gestational diabetes

Middle East Respiratory Syndrome and Medical Students: Letter from China

Objectives: The present study aimed to investigate the knowledge of Middle East Respiratory Syndrome (MERS) among Chinese medical students. Methods: A structured questionnaire on MERS was conducted among 214 medical students in China. Results: The average correction of the single question varied from 36.0% to 89.7%. There is a significant difference on MERS knowledge among different majors of medical students (p &lt; 0.05). Management students scored significantly higher than students of other majors (p &lt; 0.05). Conclusion: Chinese medical students had good knowledge of MERS. The MERS knowledge score varied among students of different majors. Education on disease control should be included in the school curriculum

Key Information Extraction and Talk Pattern Analysis Based on Big Data Technology: A Case Study on YiXi Talks

In the attempt to extract key information and talk patterns from YiXi talks in China to realize “strategic reading” for readers and newcomers of the speaking field, text mining methods are used by this work. The extraction of key information is realized by keyword extraction using the TF-IDF algorithm to show key information of one talk or one category of talks. Talk pattern recognition is realized by manual labeling (100 transcripts) and rule-based automatic programs (590 transcripts). The labeling accuracy rate of “main narrative angle” recognition is the highest (70.34%), followed by “opening form” (65.25%) and “main narrative object”, and the “ending form” is around 50%, with the overall accuracy of the rule-based automatic recognition program for talk patterns at approximately 60%. The obtained results show that the proposed keyword extraction technology for transcripts can provide “strategic reading” to a certain extent. Mature speech mode can be summarized as follows: speakers tend to adopt a self-introducing opening format. They tell stories and experiences through a first-person narrative angle and express expectations and prospects for the future. This pattern is reasonable and can be referenced by new speakers

A Modified Spatiotemporal Fusion Algorithm Using Phenological Information for Predicting Reflectance of Paddy Rice in Southern China

Satellite data for studying surface dynamics in heterogeneous landscapes are missing due to frequent cloud contamination, low temporal resolution, and technological difficulties in developing satellites. A modified spatiotemporal fusion algorithm for predicting the reflectance of paddy rice is presented in this paper. The algorithm uses phenological information extracted from a moderate-resolution imaging spectroradiometer enhanced vegetation index time series to improve the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). The algorithm is tested with satellite data on Yueyang City, China. The main contribution of the modified algorithm is the selection of similar neighborhood pixels by using phenological information to improve accuracy. Results show that the modified algorithm performs better than ESTARFM in visual inspection and quantitative metrics, especially for paddy rice. This modified algorithm provides not only new ideas for the improvement of spatiotemporal data fusion method, but also technical support for the generation of remote sensing data with high spatial and temporal resolution

Key Information Extraction and Talk Pattern Analysis Based on Big Data Technology: A Case Study on YiXi Talks

In the attempt to extract key information and talk patterns from YiXi talks in China to realize &ldquo;strategic reading&rdquo; for readers and newcomers of the speaking field, text mining methods are used by this work. The extraction of key information is realized by keyword extraction using the TF-IDF algorithm to show key information of one talk or one category of talks. Talk pattern recognition is realized by manual labeling (100 transcripts) and rule-based automatic programs (590 transcripts). The labeling accuracy rate of &ldquo;main narrative angle&rdquo; recognition is the highest (70.34%), followed by &ldquo;opening form&rdquo; (65.25%) and &ldquo;main narrative object&rdquo;, and the &ldquo;ending form&rdquo; is around 50%, with the overall accuracy of the rule-based automatic recognition program for talk patterns at approximately 60%. The obtained results show that the proposed keyword extraction technology for transcripts can provide &ldquo;strategic reading&rdquo; to a certain extent. Mature speech mode can be summarized as follows: speakers tend to adopt a self-introducing opening format. They tell stories and experiences through a first-person narrative angle and express expectations and prospects for the future. This pattern is reasonable and can be referenced by new speakers