scholarly journals Metabolomics-based discrimination of patients with remitted depression from healthy controls using 1H-NMR spectroscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ching-I. Hung ◽  
Gigin Lin ◽  
Meng-Han Chiang ◽  
Chih-Yung Chiu
Keyword(s):  
Nmr Spectroscopy ◽  
Predictive Accuracy ◽  
Tricarboxylic Acid Cycle ◽  
Support Vector ◽  
Healthy Controls ◽  
Metabolic Pathway Analysis ◽  
Full Remission ◽  
Remitted Depression ◽  
Plasma Metabolite

AbstractThe aim of the study was to investigate differences in metabolic profiles between patients with major depressive disorder (MDD) with full remission (FR) and healthy controls (HCs). A total of 119 age-matched MDD patients with FR (n = 47) and HCs (n = 72) were enrolled and randomly split into training and testing sets. A 1H-nuclear magnetic resonance (NMR) spectroscopy-based metabolomics approach was used to identify differences in expressions of plasma metabolite biomarkers. Eight metabolites, including histidine, succinic acid, proline, acetic acid, creatine, glutamine, glycine, and pyruvic acid, were significantly differentially-expressed in the MDD patients with FR in comparison with the HCs. Metabolic pathway analysis revealed that pyruvate metabolism via the tricarboxylic acid cycle linked to amino acid metabolism was significantly associated with the MDD patients with FR. An algorithm based on these metabolites employing a linear support vector machine differentiated the MDD patients with FR from the HCs with a predictive accuracy, sensitivity, and specificity of nearly 0.85. A metabolomics-based approach could effectively differentiate MDD patients with FR from HCs. Metabolomic signatures might exist long-term in MDD patients, with metabolic impacts on physical health even in patients with FR.

FUZZY BRIDGED REFINEMENT DOMAIN ADAPTATION: LONG-TERM BANK FAILURE PREDICTION

2013 ◽  
Vol 12 (01) ◽  
pp. 1350003 ◽  
Author(s):  
VAHID BEHBOOD ◽  
JIE LU ◽  
GUANGQUAN ZHANG
Keyword(s):  
Test Data ◽  
Prediction Models ◽  
Predictive Accuracy ◽  
Domain Adaptation ◽  
Failure Prediction ◽  
Bank Failure ◽  
Training Data ◽  
Support Vector ◽  
Target Domain

Machine learning methods, such as neural network (NN) and support vector machine, assume that the training data and the test data are drawn from the same distribution. This assumption may not be satisfied in many real world applications, like long-term financial failure prediction, because the training and test data may each come from different time periods or domains. This paper proposes a novel algorithm known as fuzzy bridged refinement-based domain adaptation to solve the problem of long-term prediction. The algorithm utilizes the fuzzy system and similarity concepts to modify the target instances' labels which were initially predicted by a shift-unaware prediction model. The experiments are performed using three shift-unaware prediction models based on nine different settings including two main situations: (1) there is no labeled instance in the target domain; (2) there are a few labeled instances in the target domain. In these experiments bank failure financial data is used to validate the algorithm. The results demonstrate a significant improvement in the predictive accuracy, particularly in the second situation identified above.

scholarly journals The Role of Cell Metabolism in Innate Immune Memory

2020 ◽  
pp. 1-9
Author(s):  
Anaisa Valido Ferreira ◽  
Jorge Domiguéz-Andrés ◽  
Mihai Gheorghe Netea
Keyword(s):  
Metabolic Pathways ◽  
Tricarboxylic Acid Cycle ◽  
Cell Metabolism ◽  
Innate Immune ◽  
Immune Memory ◽  
Functional Changes ◽  
Trained Immunity ◽  
Health And Disease

Immunological memory is classically attributed to adaptive immune responses, but recent studies have shown that challenged innate immune cells can display long-term functional changes that increase nonspecific responsiveness to subsequent infections. This phenomenon, coined <i>trained immunity</i> or <i>innate immune memory</i>, is based on the epigenetic reprogramming and the rewiring of intracellular metabolic pathways. Here, we review the different metabolic pathways that are modulated in trained immunity. Glycolysis, oxidative phosphorylation, the tricarboxylic acid cycle, amino acid, and lipid metabolism are interplaying pathways that are crucial for the establishment of innate immune memory. Unraveling this metabolic wiring allows for a better understanding of innate immune contribution to health and disease. These insights may open avenues for the development of future therapies that aim to harness or dampen the power of the innate immune response.

scholarly journals Modeling of Cutting Force in the Turning of AISI 4340 Using Gaussian Process Regression Algorithm

2021 ◽  
Vol 11 (9) ◽  
pp. 4055
Author(s):  
Mahdi S. Alajmi ◽  
Abdullah M. Almeshal
Keyword(s):  
Gaussian Process ◽  
Cutting Force ◽  
Predictive Accuracy ◽  
Gaussian Process Regression ◽  
Machining Process ◽  
Support Vector ◽  
Process Data ◽  
Cutting Force Prediction ◽  
Artificial Neural Network Ann ◽  
Aisi 4340

Machining process data can be utilized to predict cutting force and optimize process parameters. Cutting force is an essential parameter that has a significant impact on the metal turning process. In this study, a cutting force prediction model for turning AISI 4340 alloy steel was developed using Gaussian process regression (GPR), support vector machines (SVM), and artificial neural network (ANN) methods. The GPR simulations demonstrated a reliable prediction of surface roughness for the dry turning method with R2 = 0.9843, MAPE = 5.12%, and RMSE = 1.86%. Performance comparisons between GPR, SVM, and ANN show that GPR is an effective method that can ensure high predictive accuracy of the cutting force in the turning of AISI 4340.

scholarly journals Stabilizing the framework of SAPO-34 zeolite toward long-term methanol-to-olefins conversion

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Liu Yang ◽  
Chang Wang ◽  
Lina Zhang ◽  
Weili Dai ◽  
Yueying Chu ◽  
...  
Keyword(s):  
Nmr Spectroscopy ◽  
Zeolite Catalyst ◽  
Catalytic Efficiency ◽  
Dynamic Changes ◽  
Structural Dynamic ◽  
Term Stability ◽  
Long Term Stability ◽  
Hydrocarbon Pool ◽  
Intrinsic Good

AbstractAs a commercial MTO catalyst, SAPO-34 zeolite exhibits excellent recyclability probably due to its intrinsic good hydrothermal stability. However, the structural dynamic changes of SAPO-34 catalyst induced by hydrocarbon pool (HP) species and the water formed during the MTO conversion as well as its long-term stability after continuous regenerations are rarely investigated and poorly understood. Herein, the dynamic changes of SAPO-34 framework during the MTO conversion were identified by 1D 27Al, 31P MAS NMR, and 2D 31P-27Al HETCOR NMR spectroscopy. The breakage of T-O-T bonds in SAPO-34 catalyst during long-term continuous regenerations in the MTO conversion could be efficiently suppressed by pre-coking. The combination of catalyst pre-coking and water co-feeding is established to be an efficient strategy to promote the catalytic efficiency and long-term stability of SAPO-34 catalysts in the commercial MTO processes, also sheds light on the development of other high stable zeolite catalyst in the commercial catalysis.

scholarly journals A New Integrated Approach for Municipal Landfill Siting Based on Urban Physical Growth Prediction: A Case Study Mashhad Metropolis in Iran

2021 ◽  
Vol 13 (5) ◽  
pp. 949
Author(s):  
Salman Qureshi ◽  
Saman Nadizadeh Shorabeh ◽  
Najmeh Neysani Samany ◽  
Foad Minaei ◽  
Mehdi Homaee ◽  
...  
Keyword(s):  
Urban Growth ◽  
Integrated Approach ◽  
Physical Growth ◽  
Support Vector ◽  
Markov Chain Method ◽  
Physical Expansion ◽  
Hierarchy Process ◽  
The City

Due to irregular and uncontrolled expansion of cities in developing countries, currently operational landfill sites cannot be used in the long-term, as people will be living in proximity to these sites and be exposed to unhygienic circumstances. Hence, this study aims at proposing an integrated approach for determining suitable locations for landfills while considering their physical expansion. The proposed approach utilizes the fuzzy analytical hierarchy process (FAHP) to weigh the sets of identified landfill location criteria. Furthermore, the weighted linear combination (WLC) approach was applied for the elicitation of the proper primary locations. Finally, the support vector machine (SVM) and cellular automation-based Markov chain method were used to predict urban growth. To demonstrate the applicability of the developed approach, it was applied to a case study, namely the city of Mashhad in Iran, where suitable sites for landfills were identified considering the urban growth in different geographical directions for this city by 2048. The proposed approach could be of use for policymakers, urban planners, and other decision-makers to minimize uncertainty arising from long-term resource allocation.

Anti-CD20 therapy corrects a CD8 regulatory T cell deficit in multiple sclerosis

2021 ◽  
pp. 135245852110033
Author(s):  
Quentin Howlett-Prieto ◽  
Xuan Feng ◽  
John F Kramer ◽  
Kevin J Kramer ◽  
Timothy W Houston ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Regulatory T Cells ◽  
B Cell ◽  
Regulatory T Cell ◽  
Healthy Controls ◽  
Regulatory Cells ◽  
Long Term Treatment ◽  
Anti Cd20

Objective: To determine the effect of long-term anti-CD20 B-cell-depleting treatment on regulatory T cell immune subsets that are subnormal in untreated MS patients. Methods: 30 clinically stable MS patients, before and over 38 months of ocrelizumab treatment, were compared to 13 healthy controls, 29 therapy-naïve MS, 9 interferon-β-treated MS, 3 rituximab-treated MS, and 3 rituximab-treated patients with other autoimmune inflammatory diseases. CD8, CD28, CD4, and FOXP3 expression in peripheral blood mononuclear cells was quantitated with flow cytometry. Results: CD8+ CD28− regulatory cells rose from one-third of healthy control levels before ocrelizumab treatment (2.68% vs 7.98%), normalized by 12 months (13.5%), and rose to 2.4-fold above healthy controls after 18 months of ocrelizumab therapy (19.0%). CD4+ FOXP3+ regulatory cells were lower in MS than in healthy controls (7.98%) and showed slight long-term decreases with ocrelizumab. CD8+ CD28− and CD4+ FOXP3+ regulatory T cell percentages in IFN-β-treated MS patients were between those of untreated MS and healthy controls. Interpretation: Long-term treatment with ocrelizumab markedly enriches CD8+ CD28− regulatory T cells and corrects the low levels seen in MS before treatment, while slightly decreasing CD4+ FOXP3+ regulatory T cells. Homeostatic enrichment of regulatory CD8 T cells provides a mechanism, in addition to B cell depletion, for the benefits of anti-CD20 treatment in MS.

Lymphopenia and risk for long-term mortality among patients undergoing coronary angiography

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
B Zafrir ◽  
R Jaffe ◽  
H Sliman ◽  
O Barnett-Griness ◽  
W Saliba
Keyword(s):  
Coronary Angiography ◽  
Mortality Risk ◽  
Predictive Accuracy ◽  
Cohort Analysis ◽  
Cox Proportional Hazards ◽  
Cross Sectional ◽  
Distribution Width ◽  
Increased Risk ◽  
Long Term Mortality

Abstract Background Lymphopenia has been shown to be associated with adverse prognosis in chronic disease states that are related to immune dysregulation. Purpose We aimed to determine the association between lymphopenia and all-cause mortality in patients presenting to coronary angiography with or without acute coronary syndromes (ACS). We also investigated whether elevated red blood cell distribution width (RDW), an established cardiovascular prognostic marker, further refines risk stratification and improves predictive accuracy beyond lymphocytes count. Methods Retrospective cohort analysis of patients undergoing coronary angiography for evaluation or treatment of coronary artery disease between 2003 and 2018. Long-term mortality risk associated with relative (1000–1500 /μL) or severe (&lt;1000 /μL) lymphopenia was analyzed using Cox proportional hazards regression models, adjusting for comorbidities, ACS and RDW. Results Overall, 15179 patients underwent coronary angiography, at a mean age of 65±12 years. On cross-sectional analysis, lymphopenia was associated with kidney disease, cancer, heart failure and presentation with ACS, but lower rates of smoking and obesity. During a median follow-up of 7 (IQR 3.5–11.5) years, 4253 patients died. Compared to normal lymphocytes count (1500–5000 /μL), the multivariable adjusted hazard ratio (HR) (95% confidence interval) for mortality was 1.31 (1.21–1.41) and 1.97 (1.75–2.22) for relative and severe lymphopenia, respectively. The increase in mortality associated with severe lymphopenia was significant in patients presenting with non-ACS [HR 2.18 (1.74–2.73)], ST-segment elevation myocardial infarction (STEMI) [HR 1.59 (1.15–2.21)], or unstable angina/non-STEMI [HR 2.00 (1.70–2.34)]; p-for-interaction 0.626. The association of lymphopenia with mortality remained significant after additional adjustment to RDW. High RDW (&gt;14.5%) was associated with increased mortality risk in each of the lymphocytes count groups, and improved the predictive accuracy with AUC increase from 0.609 (0.601–0.616) to 0.646 (0.639–0.654) (p&lt;0.001). Conclusions Lymphopenia is associated with increased risk for long-term mortality in patients undergoing coronary angiography, regardless of coronary presentation. High RDW may enhance the predictive ability of lymphopenia. Lymphocyte count and mortality risk Funding Acknowledgement Type of funding source: None

scholarly journals Expected Genetic Contributions and Their Impact on Gene Flow and Genetic Gain

Genetics ◽  
1999 ◽  
Vol 153 (2) ◽  
pp. 1009-1020 ◽  
Author(s):  
J A Woolliams ◽  
P Bijma ◽  
B Villanueva
Keyword(s):  
Gene Flow ◽  
Genetic Gain ◽  
Overlapping Generations ◽  
Predictive Accuracy ◽  
Index Theory ◽  
Previous Theory ◽  
Selection Indices ◽  
Breeding Groups ◽  
Genetic Contributions

Abstract Long-term genetic contributions (ri) measure lasting gene flow from an individual i. By accounting for linkage disequilibrium generated by selection both within and between breeding groups (categories), assuming the infinitesimal model, a general formula was derived for the expected contribution of ancestor i in category q (μi(q)), given its selective advantages (si(q)). Results were applied to overlapping generations and to a variety of modes of inheritance and selection indices. Genetic gain was related to the covariance between ri and the Mendelian sampling deviation (ai), thereby linking gain to pedigree development. When si(q) includes ai, gain was related to E[μi(q)ai], decomposing it into components attributable to within and between families, within each category, for each element of si(q). The formula for μi(q) was consistent with previous index theory for predicting gain in discrete generations. For overlapping generations, accurate predictions of gene flow were obtained among and within categories in contrast to previous theory that gave qualitative errors among categories and no predictions within. The generation interval was defined as the period for which μi(q), summed over all ancestors born in that period, equaled 1. Predictive accuracy was supported by simulation results for gain and contributions with sib-indices, BLUP selection, and selection with imprinted variation.

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