Increased visceral fat area to skeletal muscle mass ratio is positively associated with the risk of metabolic dysfunction-associated steatotic liver disease in a Chinese population.

BACKGROUND: The diagnosis and comprehension of nonalcoholic fatty liver disease (NAFLD), recently redefined as metabolic dysfunction-associated steatotic liver disease (MASLD) are gaining a better understanding. In this study, we examined the association between visceral fat area and skeletal muscle mass ratio (VSR) and the prevalence of MASLD in a Chinese population. METHODS: A cross-sectional study was conducted involving 10,916 individuals who underwent bioelectrical impedance analysis, along with anthropometric and biochemical measurements, from January 2022 to June 2023. According to the VSR distribution, sex-specific quartiles of VSR within the study population were defined. Linear trend tests were performed for the categorized VSR variables. Logistic regression models were performed to estimate the odds ratio and 95% confidence intervals between VSR distribution and MASLD prevalence stratified by sex. RESULTS: The prevalence of MASLD was 37.94% in the overall population (56.34% male), and it gradually increased with higher VSR levels in both genders (P < 0.001). Logistic regression analysis demonstrated a significant association between VSR and MASLD prevalence after adjusting for confounders. The odds ratio (95% confidence interval) for MASLD, comparing the lowest to the highest VSR quartile, was 3.159 (2.671, 3.736) for men and 2.230 (1.764, 2.819) for women (all P < 0.001). Restricted cubic splines also indicated significant non-linear relationships between VSR and MASLD prevalence. CONCLUSIONS: VSR is positively associated with the prevalence of MASLD in this Chinese population, with a notably higher risk for men as VSR increases compared to women.

Life and disease status of patients with Parkinson's disease during and after zero-COVID in China: an online survey.

BACKGROUND: Little is known about the impact of the COVID-19 pandemic on patients with Parkinson's disease (PD) at different stages of the pandemic. This study aims to assess the lives and disease status of PD patients during the zero-COVID policy period and after ending the zero-COVID policy. METHODS: This multicenter cross-sectional study included two online surveys among PD patients in China, from May 30 to June 30 in 2022 and from January 1 to February 28 in 2023, respectively. The survey questionnaires contained four sections: (1) status of COVID-19 infection; (2) impact on motor and non-motor symptoms; (3) impact on daily and social lives; and (4) impact on PD disease management. RESULTS: A total of 1764 PD patients participated in the first online survey, with 200 patients having lockdown experience and 3 being COVID-19-positive (0.17%). In addition, 537 patients participated in the second online survey, with 467 patients having COVID-19 infection (86.96%). (1) During zero-COVID, all of the COVID-19-positive patients had mild symptoms of COVID-19 and no death was reported. After zero-COVID, 83.51% of the COVID-19-positive patients had mild symptoms. The overall death rate and inpatient mortality rate of COVID-19-positive PD patients were 3.21% and 30.00%, respectively. (2) During zero-COVID, 49.43% of PD patients reported worsening of PD-related symptoms (lockdown vs. unlockdown, 60.50% vs. 48.02%, P = 0.0009). After zero-COVID, 54.93% of PD patients reported worsening of PD-related symptoms (COVID-19 positive vs. COVID-19 negative, 59.31% vs. 25.71%, P < 0.0001). (3) During zero-COVID, 62.36% of patients felt worried, and 'limited outdoor activities' (55.39%) was the top reason for mental health problems. After zero-COVID, 59.03% of patients felt worried, with 'poor health' (58.10%) being the top reason. The PD patients tended to change their daily activities from offline to online, and their economic and caregiver burdens increased both during and after zero-COVID. (4) Most PD patients would like to choose online rehabilitation during (69.56%) and after zero-COVID (69.27%). The demand for online medication purchasing also increased during (47.00%) and after zero-COVID (26.63%). CONCLUSIONS: The COVID-19 pandemic aggravated the motor and non-motor symptoms of PD patients either during or after the zero-COVID policy period. The PD patients also experienced prominent mental health problems, changes in daily activities, and increases in economic and caregiver burdens. The COVID-19 pandemic has changed ways of PD management with increasing demands for online medication purchasing and rehabilitation.

N-Channel MOSFET Reliability Issue Induced by Visible/Near-Infrared Photons in Image Sensors.

Image sensors such as single-photon avalanched diode (SPAD) arrays typically adopt in-pixel quenching and readout circuits, and the under-illumination first-stage readout circuits often employs high-threshold input/output (I/O) or thick-oxide metal-oxide-semiconductor field-effect transistors (MOSFETs). We have observed reliability issues with high-threshold n-channel MOSFETs when they are exposed to strong visible light. The specific stress conditions have been applied to observe the drain current (Id) variations as a function of gate voltage. The experimental results indicate that photo-induced hot electrons generate interface trap states, leading to Id degradation including increased off-state current (Ioff) and decreased on-state current (Ion). The increased Ioff further activates parasitic bipolar junction transistors (BJT). This reliability issue can be avoided by forming an inversion layer in the channel under appropriate bias conditions or by reducing the incident photon energy.

Immune modulation of gut microbiota and its metabolites in chronic hepatitis B.

The gut microbiota is a diverse ecosystem consisting of 100 trillion microbiomes. The interaction between the host's gut and distal organs profoundly impacts various functions such as metabolism, immunity, neurology, and nutrition within the human body. The liver, as the primary immune organ, plays a crucial role in maintaining immune homeostasis by receiving a significant influx of gut-derived components and toxins. Perturbations in gut microbiota homeostasis have been linked to a range of liver diseases. The advancements in sequencing technologies, such as 16S rRNA and metagenomics, have opened up new avenues for comprehending the intricate physiological interplay between the liver and the intestine. Metabolites produced by the gut microbiota function as signaling molecules and substrates, influencing both pathological and physiological processes. Establishing a comprehensive host-bacterium-metabolism axis holds tremendous potential for investigating the mechanisms underlying liver diseases. In this review, we have provided a summary of the detrimental effects of the gut-liver axis in chronic liver diseases, primarily focusing on hepatitis B virus-related chronic liver diseases. Moreover, we have explored the potential mechanisms through which the gut microbiota and its derivatives interact with liver immunity, with implications for future clinical therapies.

Study on the correlation between lifestyle and negative conversion time in patients diagnosed with coronavirus disease (COVID-19): a retrospective cohort study.

BACKGROUND: As of early December 2022, China eased the coronavirus disease (COVID-19) restriction, affecting over 80% of the country's population and posing a severe threat to public health. Previous studies mostly focused factors on the severity/mortality rate of hospitalized COVID-19 patients, but limited studies explored factors associated with virus-negative conversion, particularly lifestyles. Therefore, the aim of our study was to analyze the correlation between lifestyle factors and the negative conversion time in COVID-19 patients. METHODS: We recruited individuals aged 18 years or older who had a clear time record for both the diagnosis and negative conversion of COVID-19 and completed the electronic questionnaire with no missing data. Dietary data collected from the questionnaire was analyzed using exploratory factor analysis to establish dietary patterns. Age segmentation was performed using restricted cubic spline (RCS) plots. The association between lifestyle factors and the time to negative conversion in different age groups, was assessed using Kaplan-Meier plots and Cox regression analysis. RESULT: Out of 514 participants, all achieved viral negative conversion within a median time of 11 days. Based on nutrient intake, we identified four dietary patterns. The relationship between age and negative conversion rate, as depicted by RCS plots, exhibited an inverted "U" shape. We categorized age into three segments: <35 years, 35-45 years, and ≥ 45 years. For individuals under 35, our study indicated that a higher protein intake was linked to a faster recovery among COVID-19 patients, while medical staff or those receiving prescription treatments exhibited a slower recovery rate (P < 0.05). The 35 ~ 45 age group showed that adequate sleep and physical exercise were associated with a shorter time to negative conversion, whereas southern regions and a higher intake of carbohydrates were related with a longer conversion time (P < 0.05). Among individuals aged ≥ 45 years, the negative conversion time was primarily associated with physical exercise and being a medical staff member(P < 0.05). CONCLUSION: Our research suggests that adequate sleep, physical exercise and a higher protein intake can help alleviate COVID-19 symptoms, while a higher level of carbohydrates intake may hinder recovery from COVID-19.

Diagnostic role of transient elastography in patients with autoimmune liver diseases: A systematic review and meta-analysis.

BACKGROUND: Noninvasive methods have been developed to detect fibrosis in many liver diseases due to the limits of liver biopsy. However, previous studies have focused primarily on chronic viral hepatitis and nonalcoholic fatty liver disease. The diagnostic value of transient elastography for autoimmune liver diseases (AILDs) is worth studying. AIM: To compare the diagnostic accuracy of imaging techniques with serum biomarkers of fibrosis in AILD. METHODS: The PubMed, Cochrane Library and EMBASE databases were searched. Studies evaluating the efficacy of noninvasive methods in the diagnosis of AILDs [autoimmune hepatitis (AIH), primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC)] were included. The summary area under the receiver operating characteristic curve (AUROC), diagnostic odds ratio, sensitivity and specificity were used to assess the accuracy of these noninvasive methods for staging fibrosis. RESULTS: A total of 60 articles were included in this study, and the number of patients with AIH, PBC and PSC was 1594, 3126 and 501, respectively. The summary AUROC of transient elastography in the diagnosis of significant fibrosis, advanced fibrosis and cirrhosis in patients with AIH were 0.84, 0.88 and 0.90, respectively, while those in patients with PBC were 0.93, 0.93 and 0.91, respectively. The AUROC of cirrhosis for patients with PSC was 0.95. However, other noninvasive indices (aspartate aminotransferase to platelet ratio index, aspartate aminotransferase/alanine aminotransferase ratio, fibrosis-4 index) had corresponding AUROCs less than 0.80. CONCLUSION: Transient elastography exerts better diagnostic accuracy in AILD patients, especially in PBC patients. The appropriate cutoff values for staging advanced fibrosis and cirrhosis ranged from 9.6 to 10.7 and 14.4 to 16.9 KPa for PBC patients.

Genomic prediction of pig growth traits based on machine learning.

This study aimed to assess and compare the performance of different machine learning models in predicting selected pig growth traits and genomic estimated breeding values (GEBV) using automated machine learning, with the goal of optimizing whole-genome evaluation methods in pig breeding. The research employed genomic information, pedigree matrices, fixed effects, and phenotype data from 9968 pigs across multiple companies to derive four optimal machine learning models: deep learning (DL), random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGB). Through 10-fold cross-validation, predictions were made for GEBV and phenotypes of pigs reaching weight milestones (100 kg and 115 kg) with adjustments for backfat and days to weight. The findings indicated that machine learning models exhibited higher accuracy in predicting GEBV compared to phenotypic traits. Notably, GBM demonstrated superior GEBV prediction accuracy, with values of 0.683, 0.710, 0.866, and 0.871 for B100, B115, D100, and D115, respectively, slightly outperforming other methods. In phenotype prediction, GBM emerged as the best-performing model for pigs with B100, B115, D100, and D115 traits, achieving prediction accuracies of 0.547, followed by DL at 0.547, and then XGB with accuracies of 0.672 and 0.670. In terms of model training time, RF required the most time, while GBM and DL fell in between, and XGB demonstrated the shortest training time. In summary, machine learning models obtained through automated techniques exhibited higher GEBV prediction accuracy compared to phenotypic traits. GBM emerged as the overall top performer in terms of prediction accuracy and training time efficiency, while XGB demonstrated the ability to train accurate prediction models within a short timeframe. RF, on the other hand, had longer training times and insufficient accuracy, rendering it unsuitable for predicting pig growth traits and GEBV.

Correlation of White Blood Cell, Neutrophils, and Hemoglobin with Metabolic Syndrome and Its Components.

Background: Metabolic syndrome (MetS) is a global health problem. White blood cell (WBC), neutrophils and neutrophil-to-lymphocyte ratio (NLR) are valid indicators involved in acute and chronic inflammation. The aims of our study were to analyze the correlation and severity of these indicators with MetS and its components, and explore the diagnostic value of their combined tests for MetS. Methods: A total of 7726 subjects were recruited, and laboratory biomarkers were collected. The differences of indicators between MetS group and non-MetS group were analyzed. The linear trend between each indicator and the increasing number of metabolic disorders was analyzed using trend variance test. The correlation between each indicator and MetS with its components was analyzed by logistic regression. Results: The levels of WBC, neutrophil, and hemoglobin grew significantly in the MetS group compared to non-MetS group, and gradually increased with the increased number of MetS disorders. Logistic regression analysis indicated significant correlations between WBC, neutrophils, and hemoglobin with MetS and its components. ROC curve analysis showed WBC, neutrophils, and hemoglobin served as good predictors for MetS, especially in adults aged under 40. Conclusion: Our study indicated that WBC, neutrophils, and hemoglobin are efficient indicators for predicting MetS and evaluate its severity.

Early detection of lung cancer in a real-world cohort via tumor-associated immune autoantibody and imaging combination.

Background: Efficient early detection methods for lung cancer can significantly decrease patient mortality. One promising approach is the use of tumor-associated autoantibodies (TAABs) as a diagnostic tool. In this study, the researchers aimed to evaluate the potential of seven TAABs in detecting lung cancer within a population undergoing routine health examinations. The results of this study could provide valuable insights into the utility of TAABs for lung cancer screening and diagnosis. Methods: In this study, the serum concentrations of specific antibodies were measured using enzyme-linked immunosorbent assay (ELISA) in a cohort of 15,430 subjects. The efficacy of both a 7-TAAB panel and LDCT for lung cancer detection were evaluated through receiver operating characteristic (ROC) analyses, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) being assessed and compared. These results could have significant implications for the development of improved screening methods for lung cancer. Results: Over the 12-month observation period, 26 individuals were diagnosed with lung cancer. The 7-TAAB panel demonstrated promising sensitivity (61.5%) and a high degree of specificity (88.5%). The panel's area under the receiver operating characteristic (ROC) curve was 0.8062, which was superior to that of any individual TAAB. In stage I patients, the sensitivity of the panel was 50%. In our cohort, there was no gender or age bias observed. This 7-TAAB panel showed a sensitivity of approximately 60% in detecting lung cancer, regardless of histological subtype or lesion size. Notably, ground-glass nodules had a higher diagnostic rate than solid nodules (83.3% vs. 36.4%, P = 0.021). The ROC analyses further revealed that the combination of LDCT with the 7-TAAB assay exhibited a significantly superior diagnostic efficacy than LDCT alone. Conclusion: In the context of the study, it was demonstrated that the 7-TAAB panel showed improved detective efficacy of LDCT, thus serving as an effective aid for the detection of lung cancer in real-world scenarios.

Sex difference in biological change and mechanism of Alzheimer's disease: From macro- to micro-landscape.

Alzheimer's disease (AD) is the most common form of dementia and numerous studies reported a higher prevalence and incidence of AD among women. Although women have longer lifetime, longevity does not wholly explain the higher frequency and lifetime risk in women. It is important to understand sex differences in AD pathophysiology and pathogenesis, which could provide foundation for future clinical AD research. Here, we reviewed the most recent and relevant literature on sex differences in biological change of AD from macroscopical neuroimaging to microscopical pathologic change (neuronal degeneration, synaptic dysfunction, amyloid-beta and tau accumulation). We also discussed sex differences in cellular mechanisms related to AD (neuroinflammation, mitochondria dysfunction, oxygen stress, apoptosis, autophagy, blood-brain-barrier dysfunction, gut microbiome alteration, bulk and single cell/nucleus omics) and possible causes underlying these differences including sex-chromosome, sex hormone and hypothalamic-pituitary- adrenal (HPA) axis effects.

Links between COVID-19 and Parkinson's disease/Alzheimer's disease: reciprocal impacts, medical care strategies and underlying mechanisms.

The impact of coronavirus disease 2019 (COVID-19) pandemic on patients with neurodegenerative diseases and the specific neurological manifestations of COVID-19 have aroused great interest. However, there are still many issues of concern to be clarified. Therefore, we review the current literature on the complex relationship between COVID-19 and neurodegenerative diseases with an emphasis on Parkinson's disease (PD) and Alzheimer's disease (AD). We summarize the impact of COVID-19 infection on symptom severity, disease progression, and mortality rate of PD and AD, and discuss whether COVID-19 infection could trigger PD and AD. In addition, the susceptibility to and the prognosis of COVID-19 in PD patients and AD patients are also included. In order to achieve better management of PD and AD patients, modifications of care strategies, specific drug therapies, and vaccines during the pandemic are also listed. At last, mechanisms underlying the link of COVID-19 with PD and AD are reviewed.

Alterations in gut microbiome and metabolomics in chronic hepatitis B infection-associated liver disease and their impact on peripheral immune response.

Gut dysbiosis has been reported in chronic hepatitis B (CHB) infection, however its role in CHB progression and antiviral treatment remains to be clarified. Herein, the present study aimed to characterize gut microbiota (GM) in patients with chronic hepatitis B virus infection-associated liver diseases (HBV-CLD) by combining microbiome with metabolome analyses and to evaluate their effects on peripheral immunity. Fecal samples from HBV-CLD patients (n = 64) and healthy controls (n = 17) were collected for 16s rRNA sequencing. Fecal metabolomics was measured with untargeted liquid chromatography-mass spectrometry in subgroups of 58 subjects. Lineage changes of peripheral blood mononuclear cells (PBMCs) were determined upon exposure to bacterial extracts (BE) from HBV-CLD patients. Integrated analyses of microbiome with metabolome revealed a remarkable shift of gut microbiota and metabolites in HBV-CLD patients, and disease progression and antiviral treatment were found to be two main contributing factors for the shift. Concordant decreases in Turicibacter with 4-hydroxyretinoic acid were detected to be inversely correlated with serum AST levels through host-microbiota-metabolite interaction analysis in cirrhotic patients. Moreover, depletion of E.hallii group with elevated choline was restored in patients with 5-year antiviral treatment. PBMC exposure to BE from non-cirrhotic patients enhanced expansion of T helper 17 cells; however, BE from cirrhotics attenuated T helper 1 cell count. CHB progression and antiviral treatment are two main factors contributing to the compositional shift in microbiome and metabolome of HBV-CLD patients. Peripheral immunity might be an intermediate link in gut microbe-host interplay underlying CHB pathogenesis.

Integrated analyses of microbiome with metabolomics revealed a remarkable shift of gut microbiota and metabolites in HBV-CLD patients. Disease progression and entecavir treatment were found to be two main contributing factors for the shift. Novel host-microbiota-metabolite interplay was investigated (red, positive correlation; blue, negative correlation). Ex vivo results showed that exposure of PBMCs to BE from non-cirrhotic patients promoted expansion of T helper 17 cells whilst BE from cirrhotic patients attenuated T helper 1 cell count, suggesting peripheral immunity may be one of mechanisms by which overall bacterial products exert profibrotic effects and have an impact on prognosis of HBV-CLD patients. Our research confers new insights into the role of gut dysbiosis and metabolomics in the pathogenesis of HBV-CLD, and underscores that disrupted peripheral immunity homeostasis during the microbe-host interplay may contribute to fibrosis progression in HBV-CLD. CHB, chronic hepatitis B (treatment-naive); Crrh, cirrhosis; ETV, entecavir; HBV-CLD, chronic hepatitis B virus infection-associated liver diseases; HCs, healthy controls; MCFAs, medium chain fatty acids; NC, non-cirrhosis; Th1, T helper 1; Th17, T helper 17.Abbreviations: ALB, albumin; ALP, alkaline phosphatase; ANOISM, analysis of similarities; AST, aspartate aminotransferase; BE, bacterial extracts; BMI, body mass index; CC, compensated cirrhosis; CHB, chronic hepatitis B; DB, direct bilirubin; DC, decompensated cirrhosis; DCA, deoxycholic acid; ETV, entecavir; FDR, false discovery rate; GGT, γ-glutamyl transpeptidase; GM, gut microbiota; HBV, hepatitis B virus; HBV-CLD, chronic hepatitis B virus infection-associated liver diseases; HCs, healthy controls; HCC, hepatocellular carcinoma; LC-MS, liquid chromatography-mass spectrometry; LRE, liver-related events; LS, liver stiffness; ImP, imidazole propionate; IQR, interquartile range; MCFAs, medium chain fatty acids; OCT, organic cation transporter; OPLS-DA, orthogonal partial least square discriminant analysis; PBMCs, peripheral blood mononuclear cells; PERMANOVA, permutational multivariate analysis of variance; PLS-DA, partial least square discriminant analysis; PCA, principal component analysis; PcoA, principal coordinates analysis; PT, prolonged prothrombin time; SDs, standard deviations; TB, total bilirubin; Tregs, regulatory T cells; Th1, T helper 1; Th17, T helper 17.

MRCG: A MRI Retrieval Framework With Convolutional and Graph Neural Networks for Secure and Private IoMT.

In the context of Industry 4.0, the medical industry is horizontally integrating the medical resources of the entire industry through the Internet of Things (IoT) and digital interconnection technologies. Speeding up the establishment of the public retrieval database of diagnosis-related historical data is a common call for the entire industry. Among them, the Magnetic Resonance Imaging (MRI) retrieval system, which is one of the key tools for secure and private the Internet of Medical Things (IoMT), is significant for patients to check their conditions and doctors to make clinical diagnoses securely and privately. Hence, this paper proposes a framework named MRCG that integrates Convolutional Neural Network (CNN) and Graph Neural Network (GNN) by incorporating the relationship between multiple gallery images in the graph structure. First, we adopt a Vgg16-based triplet network jointly trained for similarity learning and classification task. Next, a graph is constructed from the extracted features of triplet CNN where each node feature encodes a query-gallery image pair. The edge weight between nodes represents the similarity between two gallery images. Finally, a GNN with skip connections is adopted to learn on the constructed graph and predict the similarity score of each query-gallery image pair. Besides, Focal loss is also adopted while training GNN to tackle the class imbalance of the nodes. Experimental results on some benchmark datasets, including the CE-MRI dataset and a public MRI dataset from the Kaggle platform, show that the proposed MRCG can achieve 88.64% mAP and 86.59% mAP, respectively. Compared with some other state-of-the-art models, the MRCG can also outperform all the baseline models.

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.

Catechol-functionalized sulfobetaine polymer for uniform zwitterionization via pH transition approach.

The study aims to develop a modification strategy to facilitate uniform catechol-assisted zwitterionization on nitinol alloy for bio-compatibility and fouling resistance. Catechol-functionalized polysulfobetaine methacrylate (pSBMA/DA) is synthesized via dopamine-initiated photo-polymerization. Under UV irradiation, semiquinone radicals from dopamine (DA) can be generated, and prevented loss of one electron to intramolecular cyclization and intermolecular dimerization in a solution at pH 2. Pseudo-first-order polymerization kinetics, and relations of apparent rate constant and number average molecular weight with the molar ratio of DA in photopolymerization for pSBMA/DA are unveiled. In a solution at pH 3, PSBMA/DA begins aggregation, kept catechol moieties from premature oxidization, and enabled even deposition on the nitinol substrate. After pH regulation to 8.5, pSBMA/DA extends, and concurrently catechol moieties are activated to interact with the nitinol surface via the formation of bidentate binding. X-ray photoelectron spectroscopy (XPS) analysis revealed that a shorter pSBMA/DA chain with higher catechol content provides more anchoring sites to enhance zwitterionic moieties coverage on substrates. Interestingly, atomic force microscopy (AFM) images revealed a smooth and uniform deposition of pSBMA/DA using the pH-transition method. Strong ionic hydration of pSBMA/DA coating on nitinol surface repels non-specific adsorption of bio-foulants, permitting excellent antifouling properties. Zwitterion-modified nitinol achieved a reduction rate of 99.9% against Escherichia coli and Staphylococcus aureus attachment. In addition, pSBMA/DA exhibits a robust antifouling performance to NIH 3T3 mouse fibroblasts in culture media after incubation for 24 h. Overall, the pSBMA/DA coating via pH transition approach opens up a promising strategy to facilitate uniform surface functionalization for antifouling and coating technology.

Genetic profiles of familial late-onset Alzheimer's disease in China: The Shanghai FLOAD study.

Compared with early-onset familial AD (FAD), the heritability of most familial late-onset Alzheimer's disease (FLOAD) cases still remains unclear. However, there are few reported genetic profiles of FLOAD to date. In the present study, targeted sequencing of selected candidate genes was conducted for each of 90 probands with FLOAD and 101 unrelated matched normal controls among Chinese Han population. Results show a significantly lower rate of mutation in APP and PSENs, and APOE ε4 genetic risk is higher for FLOAD. Among the Chinese FLOAD population, the most frequent variant was CR1 rs116806486 [5.6%, 95% CI (1.8%, 12.5%)], followed by coding variants of TREM2 (4.4%, 95%CI (1.2%, 10.9%)) and novel mutations of ACE [3.3%, 95%CI (0.7%, 9.4%)]. Next, we found that novel pathogenic mutations in ACE including frame-shift and nonsense mutations were in association with FLOAD regardless of APOE ε4 status. Evidence from the Alzheimer's disease Neuroimaging Initiative (ADNI) database also supported this finding in different ethnicities. Results of in vitro analysis suggest that frame-shift and nonsense mutations in ACE may be involved in LOAD through decreased ACE protein levels without affecting direct processing of APP.

Integrating peripheral blood and brain transcriptomics to identify immunological features associated with Alzheimer's disease in mild cognitive impairment patients.

Background: Immune system dysfunction has been proven to be an important pathological event in Alzheimer's disease (AD). Mild cognitive impairment (MCI), as a transitional stage between normal cognitive function and AD, was an important research object for the screening of early diagnostic markers and therapeutic targets for AD. However, systematic assessment of peripheral immune system changes in MCI patients and consistent analysis with that in the CNS were still lacking. Methods: Peripheral blood transcriptome data from the AddNeuroMed Cohort (n = 711) was used as a training dataset to assess the abundance of 24 immune cells through ImmuCellAI and to identify MCI-related immune signaling pathways and hub genes. The expression level of the immune hub gene was validated in peripheral blood (n = 587) and brain tissue (78 entorhinal cortex, 140 hippocampi, 91 temporal cortex, and 232 frontal cortex) validation datasets. Finally, reliable immune hub genes were applied for Gene Set Enrichment Analysis and correlation analysis of AD pathological characteristics. Results: MCI patients have early changes in the abundance of various types of immune cells in peripheral blood, accompanied by significant changes in NF-kB, TNF, JAK-STAT, and MAPK signaling pathways. Five hub immune-related differentially expressed genes (NFKBIA, CD4, RELA, CASP3, and HSP90AA1) were screened by the cytoHubba plugin in Cytoscape and the least absolute shrinkage and selection operator (LASSO) regression. Their expression levels were significantly correlated with infiltration score and the abundance of monocytes, natural killer cells, Th2 T cells, T follicular helper cells, and cytotoxic T cells. After validation with independent datasets derived from peripheral blood and brain, RELA and HSP90AA1 were identified as two reliable immune hub genes in MCI patients and had consistent changes in AD. The Gene Set Enrichment Analysis (GSEA) showed that their expression levels were closely associated with Alzheimer's disease, JAK-STAT, calcium signaling pathway, etc. In addition, the expression level of RELA was positively correlated with ß- and γ-secretase activity and Braak stage. The expression level of HSP90AA1 was negatively correlated with α- and ß-secretase activity. Conclusion: Immune system dysfunction was an early event in AD. It provides a new target for the early diagnosis and treatment of AD.

Injection of amyloid-ß to lateral ventricle induces gut microbiota dysbiosis in association with inhibition of cholinergic anti-inflammatory pathways in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disease and its pathogenesis is still unclear. There is dysbiosis of gut microbiota in AD patients. More importantly, dysbiosis of the gut microbiota has been observed not only in AD patients, but also in patients with mild cognitive impairment (MCI). However, the mechanism of gut microbiota dysbiosis in AD is poorly understood. Cholinergic anti-inflammatory pathway is an important pathway for the central nervous system (CNS) regulation of peripheral immune homeostasis, especially in the gut. Therefore, we speculated that dysfunction of cholinergic anti-inflammatory pathway is a potential pathway for dysbiosis of the gut microbiota in AD. METHODS: In this study, we constructed AD model mice by injecting Aß1-42 into the lateral ventricle, and detected the cognitive level of mice by the Morris water maze test. In addition, 16S rDNA high-throughput analysis was used to detect the gut microbiota abundance of each group at baseline, 2 weeks and 4 weeks after surgery. Furthermore, immunofluorescence and western blot were used to detect alteration of intestinal structure of mice, cholinergic anti-inflammatory pathway, and APP process of brain and colon in each group. RESULTS: Aß1-42 i.c.v induced cognitive impairment and neuron damage in the brain of  mice. At the same time, Aß1-42 i.c.v induced alteration of gut microbiota at 4 weeks after surgery, while there was no difference at the baseline and 2 weeks after surgery. In addition, changes in colon structure and increased levels of pro-inflammatory factors were detected in Aß1-42 treatment group, accompanied by inhibition of cholinergic anti-inflammatory pathways. Amyloidogenic pathways in both the brain and colon were accelerated in Aß1-42 treatment group. CONCLUSIONS: The present findings suggested that Aß in the CNS can induce gut microbiota dysbiosis, alter intestinal structure and accelerate the amyloidogenic pathways, which were related to inhibiting cholinergic anti-inflammatory pathways.