Astragalus membranaceus Polysaccharide Regulates Small Intestinal Microbes and Activates IL-22 Signal Pathway to Promote Intestinal Stem Cell Regeneration in Aging Mice.

Aging can cause degenerative changes in multiple tissues and organs. Gastrointestinal diseases and dysfunctions are common in the elderly population. In this study, we investigated the effects of Astragalus membranaceus polysaccharide (APS) and Astragalus membranaceus ethanol extract (AEE) on age-related intestinal dysfunction and gut microbiota dysbiosis in naturally aging mice. The energy expenditure and physical activity of 23-month-old C57BL6/J mice were recorded using a metabolic cage system. Pathological changes in the intestine were evaluated using Alcian blue staining. The protein levels of leucine-rich repeats containing G protein-coupled receptor 5 (Lgr5) and Stat3 in the small intestine were determined using immunohistochemistry. The intestinal cell migration distance was assessed using bromodeoxyuridine (BrdU) immunofluorescence staining. The gene transcription levels of intestinal stem cell (ISC) markers and ISC-related signaling pathways were detected using quantitative real-time PCR (qRT-PCR). Microbiota analysis based on 16S rDNA was performed to evaluate the composition of the gut microbiota. APS and AEE improved a series of aging phenotypes in female but not in male aging mice. APS and AEE ameliorate intestinal dysfunction and histopathological changes in aging mice. APS had a more significant anti-aging effect than AEE, particularly on intestinal dysfunction. APS promotes ISC regeneration by activating the IL-22 signaling pathway. Cohousing (CH) experiments further confirmed that APS induced the IL-22 signaling pathway by increasing the abundance of Lactobacillus, thereby promoting the regeneration of ISCs. Our results show that APS may serve as a promising agent for improving age-related intestinal dysfunction.

DDFC: deep learning approach for deep feature extraction and classification of brain tumors using magnetic resonance imaging in E-healthcare system.

This research explores the use of gated recurrent units (GRUs) for automated brain tumor detection using MRI data. The GRU model captures sequential patterns and considers spatial information within individual MRI images and the temporal evolution of lesion characteristics. The proposed approach improves the accuracy of tumor detection using MRI images. The model's performance is benchmarked against conventional CNNs and other recurrent architectures. The research addresses interpretability concerns by employing attention mechanisms that highlight salient features contributing to the model's decisions. The proposed model attention-gated recurrent units (A-GRU) results show promising results, indicating that the proposed model surpasses the state-of-the-art models in terms of accuracy and obtained 99.32% accuracy. Due to the high predictive capability of the proposed model, we recommend it for the effective diagnosis of Brain tumors in the E-healthcare system.

[Related factors of endogenous erythropoietin and its association with 10-year risks of cardiovascular disease in a community-based Chinese study].

OBJECTIVE: To investigate the associated factors of endogenous erythropoietin (EPO) and its association with 10-year risks of atherosclerotic cardiovascular disease in a Chinese community-based general population. METHODS: The participants of this study were from an atherosclerosis cohort survey which was established by the Department of Cardiology, Peking University First Hospital in 2011. The cohort survey was performed in the Gucheng and Pingguoyuan communities of Shijingshan district in Beijing, China. The inclusion criteria of this study were: (1) endogenous EPO was measured; (2) health questionnaire data and other clinical data were complete; (3) participatants who had cardiovascular or cerebrovascular diseases (defined as self-reported coronary heart disease, stroke or transient ischemic attack) or anemia or estimated glomerular filtration rate (eGFR) < 60 mL/(min·1.73 m2) at baseline were excluded. Multivariate linear regression model was used to examine the associated factors of endogenous EPO. The participants were grouped into low (< 5%), moderate (5%-10%) and high risk (≥10%) groups, based on predicted 10-year cardiovascular disease risk using the prediction for atherosclerotic cardiovascular disease risk in China (China-PAR) equations. RESULTS: A total of 4 013 participants were included. Mean age of them was (55.9±8.2) years, 62.2% (n=2 496) of them were female, and 46.3% (n=1 859), 70.9% (n=2 845), 21.9% (n=879) had hypertension, dyslipidemia and diabetes, individually. The average body mass index was (26.1±3.3) kg/m2. The median of EPO level was 12.8 (9.3-17.4) IU/L and 25.1% (n=998) were at high 10-years risk of cardiovascular disease. Hemoglobin (ß=-0.05, 95%CI: -0.07 to -0.04) and eGFR ≥90 mL/(min·1.73 m2) (ß=-0.05, 95%CI: -0.07 to -0.04) were associated with lower in transformed EPO levels while hypertension (ß=0.08, 95%CI: 0.05 to 0.12) and obesity (ß=0.14, 95%CI: 0.09 to 0.18) were associated with higher in transformed EPO levels in multivariate linear regression analyses. Ten-year cardiovascular disease risks were positively associated with in transformed EPO levels (ß=0.07, 95%CI: 0.05 to 0.09). The participants at moderate and high cardiovascular disease risks had significant higher EPO levels than the low risk group (all P < 0.05). CONCLUSION: In community-based Beijing populations, endogenous EPO was associated with hemoglobin, renal function, obesity and hypertension. Individuals at high 10-years cardiovascular disease risks have higher endogenous EPO levels. Endogenous EPO may be a potential risk marker of cardiovascular disease.

The novel HLA-A*02:405 allele characterized by sequencing-based typing.

HLA-A*02:405 differs from HLA-A*02:06:01:01 by one nucleotide substitution in codon 161 in exon 3.

Identification of the novel HLA-B*15:270 allele by Sanger dideoxy nucleotide sequencing.

HLA-B*15:270 differs from HLA-B*15:12:01 by one nucleotide substitution at position 679 in exon 4.

Thirty-day outcomes of in-hospital multi-vessel versus culprit-only revascularization strategy for ST-segment elevation myocardial infarction with multivessel coronary disease.

BACKGROUND: Many studies have demonstrated the benefit of complete multivessel revascularization versus culprit-only intervention in patients of ST-segment elevation myocardial infarction (STEMI) and multivessel coronary artery disease. However, only a few single-center retrospective studies were performed on small Chinese cohorts. Our study aims to demonstrate the advantage of multivessel percutaneous intervention (PCI) strategy on 30-day in-hospital outcomes to patients with STEMI and multivessel disease in larger Chinese population. METHODS: From the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome (CCC-ACS) project, 5935 patients with STEMI and multivessel disease undergoing PCI and hospitalized for fewer than 30 days were analyzed. After 5: 1 propensity score matching, 3577 patients with culprit-only PCI and 877 with in-hospital multivessel PCI were included. The primary outcome was major adverse cardiovascular and cerebrovascular event (MACCE), defined as a composite of myocardial infarction, all-cause death, stent thrombosis, heart failure, and stroke. RESULTS: Multivariable logistic regression analysis revealed that in-hospital multivessel PCI was associated with lower risk of 30-day MACCE (adjusted OR = 0.75, 95% CI: 0.57-0.98, P = 0.032) than culprit-only PCI and conferred no increased risk of all-cause death, myocardial infarction, stent thrombosis, stroke, or bleeding. Subgroup analysis showed that MACCE reduction was observed more often from patients with trans-femoral access (OR = 0.34, 95% CI: 0.15-0.74) than with trans-radial access (OR = 0.87, 95% CI: 0.66-1.16, P for interaction = 0.017). CONCLUSIONS: The in-hospital multivessel PCI strategy was associated with a lower risk of 30-day MACCE than culprit-only PCI in patients with STEMI and multivessel coronary artery disease.

The novel HLA-A*02:404 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-A*02:404 differs from HLA-A*02:06:01:01 by one nucleotide substitution in codon 116 in exon 3.

Characterization of the novel HLA-B*15:269 allele by sequencing-based typing.

HLA-B*15:269 differs from HLA-B*15:63 by two nucleotide substitutions in exon 3.

IL-10-dependent Effect of Chinese Medicine Abelmoschus manihot on Alleviating Intestinal Inflammation and Modulating Gut Microbiota.

Inflammatory bowel disease (IBD) is a recurrent disease associated with a potential risk of colorectal cancer. Abelmoschus manihot (AM), a Chinese herbal medicine, is known to alleviate IBD. However, its mechanism of action requires further clarification. Here, we focused on the role of IL-10 and the gut microbiota in the mechanism of action of AM. The effects of AM on intestinal inflammation, mucus production, and gut microbes were evaluated in dextran sodium sulfate (DSS)-induced acute and chronic IBD models and in IL-10-deficient mice (IL-10[Formula: see text]). AM exhibited protective effects on acute and chronic models of IBD in wild-type mice by restoring body weight and colon length, promoting IL-10 secretion, and decreasing TNF-[Formula: see text] levels. Moreover, AM alleviated inflammatory infiltration, increased mucin 2 transcription, and increased the number of goblet cells in the colon. On the contrary, these effects were diminished in IL-10[Formula: see text] mice, which implied that the effect of AM on intestinal inflammation is IL-10-dependent. A gut microbial sequencing analysis showed that gut microbial dysbiosis was modulated by AM intervention. The regulatory effects of AM on Eggerthellaceae, Sutterellaceae, Erysipelotrichaceae, Burkholderiaceae, Desulfovibrionaceae, and Enterococcaceae were dependent on IL-10. These results revealed that AM ameliorated IBD and modulated gut microbes by promoting IL-10 secretion, indicating that AM has the potential to improve IBD and that AM is IL-10-dependent.

Federated Fusion of Magnified Histopathological Images for Breast Tumor Classification in the Internet of Medical Things.

Breast tumor detection and classification on the Internet of Medical Things (IoMT) can be automated with the potential of Artificial Intelligence (AI). However, challenges arise when dealing with sensitive data due to the dependence on large datasets. To address this issue, we propose an approach that combines different magnification factors of histopathological images using a residual network and information fusion in Federated Learning (FL). FL is employed to preserve the privacy of patient data, while enabling the creation of a global model. Using the BreakHis dataset, we compare the performance of FL with centralized learning (CL). We also performed visualizations for explainable AI. The final models obtained become available for deployment on internal IoMT systems in healthcare institutions for timely diagnosis and treatment. Our results demonstrate that the proposed approach outperforms existing works in the literature on multiple metrics.

Smartphone Addiction among Students and its Harmful Effects on Mental Health, Oxidative Stress, and Neurodegeneration towards Future Modulation of Anti-Addiction Therapies: A Comprehensive Survey based on SLR, Research Questions, and Network Visualization Techniques.

BACKGROUND: Addiction is always harmful to the human body. Smartphone addiction also affects students' mental and physical health. AIM: This study aims to determine the research volume conducted on students who are affected by smartphone addiction and design a database. We intended to highlight critical problems for future research. In addition, this paper enterprises a comprehensive and opinion-based image of smartphone-addicted students. METHODOLOGY: We used two types of methods, such as systematic literature review and research questions based on the Scopus database to complete this study. We found 27 research articles and 11885 subjects (mean ±SD: 440.19 ± 513.58) using the PRISMA technique in this study. Additionally, we have deeply investigated evidence to retrieve the current understanding of smartphone addiction from physical changes, mental changes, behavioural changes, impact on performance, and significant concepts. Furthermore, the effect of this addiction has been linked to cancers, oxidative stress, and neurodegenerative disorders. RESULTS: This work has also revealed the future direction and research gap on smartphone addiction among students and has also tried to provide goals for upcoming research to be accomplished more significantly and scientifically. CONCLUSION: This study suggests future analysis towards identifying novel molecules and pathways for the treatment and decreasing the severity of mobile addiction.

A novel HLA allele, HLA-B*07:248, detected in a Chinese hematopoietic stem cell donor and platelet donor.

HLA-B*07:248 has one nucleotide change from HLA-B*07:18:01 where Tyrosine (Y) is changed to Serine (S).

MCNN: a multi-level CNN model for the classification of brain tumors in IoT-healthcare system.

The classification of brain tumors is significantly important for diagnosing and treating brain tumors in IoT healthcare systems. In this work, we have proposed a robust classification model for brain tumors employing deep learning techniques. In the design of the proposed method, an improved Convolutional neural network is used to classify Meningioma, Glioma, and Pituitary types of brain tumors. To test the multi-level convolutional neural network model, brain magnetic resonance image data is utilized. The MCNN model classification results were improved using data augmentation and transfer learning methods. In addition, hold-out and performance evaluation metrics have been employed in the proposed MCNN model. The experimental results show that the proposed model obtained higher outcomes than the state-of-the-art techniques and achieved 99.89% classification accuracy. Due to the higher results of the proposed approach, we recommend it for the identification of brain cancer in IoT-healthcare systems.

Speech silence character as a diagnostic biomarker of early cognitive decline and its functional mechanism: a multicenter cross-sectional cohort study.

BACKGROUND: Language deficits frequently occur during the prodromal stages of Alzheimer's disease (AD). However, the characteristics of linguistic impairment and its underlying mechanism(s) remain to be explored for the early diagnosis of AD. METHODS: The percentage of silence duration (PSD) of 324 subjects was analyzed, including patients with AD, amnestic mild cognitive impairment (aMCI), and normal controls (NC) recruited from the China multi-center cohort, and the diagnostic efficiency was replicated from the Pitt center cohort. Furthermore, the specific language network involved in the fragmented speech was analyzed using task-based functional magnetic resonance. RESULTS: In the China cohort, PSD increased significantly in aMCI and AD patients. The area under the curve of the receiver operating characteristic curves is 0.74, 0.84, and 0.80 in the classification of NC/aMCI, NC/AD, and NC/aMCI+AD. In the Pitt center cohort, PSD was verified as a reliable diagnosis biomarker to differentiate mild AD patients from NC. Next, in response to fluency tasks, clusters in the bilateral inferior frontal gyrus, precentral gyrus, left inferior temporal gyrus, and inferior parietal lobule deactivated markedly in the aMCI/AD group (cluster-level P < 0.05, family-wise error (FWE) corrected). In the patient group (AD+aMCI), higher activation level of the right pars triangularis was associated with higher PSD in in both semantic and phonemic tasks. CONCLUSIONS: PSD is a reliable diagnostic biomarker for the early stage of AD and aMCI. At as early as aMCI phase, the brain response to fluency tasks was inhibited markedly, partly explaining why PSD was elevated simultaneously.

Microstructure and Properties of Densified Gd2O3 Bulk.

In this work, Gd2O3 bulks were sintered at temperatures ranging from 1400 °C to 1600 °C for times from 6 h to 24 h, and their microstructure and properties were studied for a wider application of materials in thermal barrier coatings. The densification of the Gd2O3 bulk reached 96.16% when it was sintered at 1600 °C for 24 h. The elastic modulus, hardness, fracture toughness and thermal conductivity of the bulks all increased with the rise in sintering temperature and extension of sintering time, while the coefficient of thermal expansion decreased. When the Gd2O3 bulk was sintered at 1600 °C for 24 h, it had the greatest elastic modulus, hardness, fracture toughness and thermal conductivity of 201.15 GPa, 9.13 GPa, 15.03 MPa·m0.5 and 2.75 W/(m·k) (at 1100 °C), respectively, as well as the smallest thermal expansion coefficients of 6.69 × 10-6/°C (at 1100 °C).

DACBT: deep learning approach for classification of brain tumors using MRI data in IoT healthcare environment.

The classification of brain tumors (BT) is significantly essential for the diagnosis of Brian cancer (BC) in IoT-healthcare systems. Artificial intelligence (AI) techniques based on Computer aided diagnostic systems (CADS) are mostly used for the accurate detection of brain cancer. However, due to the inaccuracy of artificial diagnostic systems, medical professionals are not effectively incorporating them into the diagnosis process of Brain Cancer. In this research study, we proposed a robust brain tumor classification method using Deep Learning (DL) techniques to address the lack of accuracy issue in existing artificial diagnosis systems. In the design of the proposed approach, an improved convolution neural network (CNN) is used to classify brain tumors employing brain magnetic resonance (MR) image data. The model classification performance has improved by incorporating data augmentation and transfer learning methods. The results confirmed that the model obtained high accuracy compared to the baseline models. Based on high predictive results we suggest the proposed model for brain cancer diagnosis in IoT-healthcare systems.

Correction: First-principles insights into hydrogen trapping in interstitial-vacancy complexes in vanadium carbide.

Correction for 'First-principles insights into hydrogen trapping in interstitial-vacancy complexes in vanadium carbide' by Shuai Tang et al., Phys. Chem. Chem. Phys., 2022, DOI: https://doi.org/10.1039/d2cp02425j.

Dietary Grape Seed Proanthocyanidin Alleviates the Liver Injury Induced by Long-Term High-Fat Diets in Sprague Dawley Rats.

In mammals, the liver is the most important organ that plays a vital function in lipid metabolism. Grape seed proanthocyanidin (GSPE) is a kind of natural polyphenolic compound primarily obtained from grape skin and seeds. Recent research found it had high bioavailability in defending against obesity, hyperlipidemia, inflammatory, oxidative stress, and targeting liver tissue. However, the mechanism of GSPE in regulating obesity induced by dietary high-fat (HF) was not fully understood, particularly the influences on liver functions. Therefore, this study aimed to investigate the effects of GSPE supplementation on the liver function and lipid metabolic parameters in rats fed HF diets long-term. A total of 40 healthy female Sprague Dawley rats were selected. After 8 weeks of obesity model feeding, the rats were randomly divided into four treatments: NC, standard diet; NC + GSPE, standard diet + 500 mg/kg body weight GSPE; HF, high-fat diet; HG + GSPE, high fat diet + 500 mg/kg body weight GSPE. Results indicated that long-term HF feeding caused severe liver problems including megalohepatia, steatosis, inflammation, and hepatocyte apoptosis. The supplementation of GSPE alleviated these symptoms. The results of the current experiment confirmed that GSPE addition up-regulated the expression of the Wnt3a/ß-catenin signaling pathway, thereby restraining the liver cell endoplasmic reticulum stress and hepatocyte apoptosis. Furthermore, the microRNA-103 may play a role in this signal-regulated pathway. In summary, GSPE had a protective effect on the liver and the current experiment provided a reference for the application of GSPE in animal nutrition as a kind of natural feed additive.

First-principles insights into hydrogen trapping in interstitial-vacancy complexes in vanadium carbide.

Hydrogen trapping is a key factor in designing advanced vanadium alloys and steels, where the influence of carbon vacancies is still elusive. Herein we have investigated the effect of carbon vacancies on the hydrogen trapping of defect-complexes in vanadium carbide using first-principles calculations. When a carbon vacancy is present, the second nearest neighboring trigonal interstitial is a stable hydrogen trapping site. A C vacancy enhances the hydrogen trapping ability by reducing the chemical and mechanical effects on H atom solution energy. Electronic structure analysis shows that C vacancies increase the charge density and the Bader atomic volume, leading to a lower H atom solution energy. The strength of the V-H bond is predominant in determining the hydrogen trapping ability in the presence of a C vacancy, in contrast to that of a C-H bond when the C vacancy is absent.