RESUMEN
Alzheimer's Disease (AD) is the leading cause of dementia. It results in cortical thickness changes and is associated with a decline in cognition and behaviour. Such decline affects multiple important day-to-day functions, including memory, language, orientation, judgment and problem-solving. Recent research has made important progress in identifying brain regions associated with single outcomes, such as individual AD status and general cognitive decline. The complex projection from multiple brain areas to multiple AD outcomes, however, remains poorly understood. This makes the assessment and especially the prediction of multiple AD outcomes - each of which may unveil an integral yet different aspect of the disease - challenging, particularly when some are not strongly correlated. Here, uniting residual learning, partial least squares (PLS), and predictive modelling, we develop an explainable, generalisable, and reproducible method called the Residual Partial Least Squares Learning (the re-PLS Learning) to (1) chart the pathways between large-scale multivariate brain cortical thickness data (inputs) and multivariate disease and behaviour data (outcomes); (2) simultaneously predict multiple, non-pairwise-correlated outcomes; (3) control for confounding variables (e.g., age and gender) affecting both inputs and outcomes and the pathways in-between; (4) perform longitudinal AD disease status classification and disease severity prediction. We evaluate the performance of the proposed method against a variety of alternatives on data from AD patients, subjects with mild cognitive impairment (MCI), and cognitively normal individuals (n=1,196) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our results unveil pockets of brain areas in the temporal, frontal, sensorimotor, and cingulate areas whose cortical thickness may be respectively associated with declines in different cognitive and behavioural subdomains in AD. Finally, we characterise re-PLS' geometric interpretation and mathematical support for delivering meaningful neurobiological insights and provide an open software package (re-PLS) available at https://github.com/thanhvd18/rePLS.
RESUMEN
ETHNOPHARMACOLOGICAL RELEVANCE: Cough-variant asthma (CVA) is one of the most common causes of chronic cough. Its pathogenesis is closely related to chronic airway inflammation and airway hyperresponsiveness. CVA belongs to the category of "wind cough" in Traditional Chinese medicine (TCM). Zi-Su-Zi decoction (ZSD) is a Chinese herbal formula that is clinically used for the treatment of cough and asthma, especially CVA. However, the mechanism of action remains unclear. AIM OF THE STUDY: In this study, we aimed to explore the potential mechanism by which ZSD improves CVA airway hyperresponsiveness. MATERIALS AND METHODS: The targets of ZSD in CVA were studied using a Network pharmacology. The main chemical components of ZSD were detected and analyzed using ultra-high-pressure liquid chromatography (UHPLC-MS/MS). In animal experiments, the rat model of CVA was established using Ovalbumin (OVA)/Aluminum hydroxide (AL(OH)3) sensitization. Moreover, the experiment also evaluated cough symptoms, percentage of eosinophils (EOS%), pulmonary function tests, histopathological sections, blood cytokine levels, mRNA and protein levels. RESULTS: The results showed that Network pharmacology suggested 276 targets of ZSD and CVA and found that ZSD treatment with CVA was closely related to the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway. UHPLC-MS/MS revealed that ZSD contained 52 main chemical components. Compared with the model group, the cough symptoms of the rats in the different ZSD concentration groups were relieved, the EOS% index was lowered, and body weight was increased. HE staining showed that ZSD reduced airway inflammation, edema and hyperplasia, thereby improving the pathological structure of lung tissue, and the effect of high-dose ZSD was especially significant. Our most important finding was that ZSD blocked the entry of hypoxia-inducible factor-1α (HIF-1α), signal transducer and activator of transcription-3 (STAT3) and nuclear factor kappa-B (NF-κB) into the nucleus by interfering with PI3K/AKT1/mechanistic target of rapamycin (mTOR), and janus kinase 2 (JAK2) signaling factors. Consequently, inhibiting the release of cytokines and immunoglobulin-E, thereby reducing airway hyperresponsiveness (AHR) and partially reverses airway remodeling. CONCLUSIONS: This study showed that ZSD can improve airway hyperresponsiveness and partially reverse airway remodeling by inhibiting the PI3K/AKT1/mTOR, JAK2/STAT3 and HIF-1α/NF-κB signaling pathways. Therefore, ZSD is an effective prescription for the treatment of CVA.
Asunto(s)
Asma , FN-kappa B , Ratas , Animales , FN-kappa B/metabolismo , Fosfatidilinositol 3-Quinasas/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , Fosfatidilinositol 3-Quinasa/metabolismo , Tos/tratamiento farmacológico , Janus Quinasa 2/metabolismo , Remodelación de las Vías Aéreas (Respiratorias) , Espectrometría de Masas en Tándem , Asma/metabolismo , Transducción de Señal , Serina-Treonina Quinasas TOR/metabolismo , Citocinas/metabolismo , InflamaciónRESUMEN
Panaxnotoginseng saponins (PNS) is one of the active components of traditional Chinese medicine Panax notoginseng which has the function of reducing oxygen consumption, expansion of the cerebrovascular system, and is antithrombotic. PNS also plays a role in the treatment of pulmonary fibrosis. In this study, we found that PNS suppresses fibroblast-like changes in A549 cells through epithelial-mesenchymal transition (EMT). PNS promoted E-cadherin (E-cad) in epithelial cells and decreased Fibronectin (FN) and Vimentin (Vim) expression in myofibroblasts in a dose-dependent manner. Further mechanism studies have shown that PNS inhibits the EMT process by regulating p38, JNK, and Erk signaling factors in the MAPK signaling pathway and then blocking Snail and TWIST1 transcription factors from entering the nucleus. This indicates that PNS can regulate epithelial-mesenchymal transition through MAPK and the Snail/TWIST1 signaling pathway, thereby exerting its antipulmonary fibrosis effect.
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The present paper aims at presenting a kinetic model that is supposed to result in the decomposition of methylparaben in completely mixed batch reactor (CMBR) using the UV/H2O2 process. The proposed model incorporates photochemical, chemical reactions and their constant rates to formulate the overall kinetic rate expressions which are integrated into MATLAB. Thus, the changes in pH values during the process of oxidation are taken into consideration. In addition, the effects of hydrogen peroxide (HP) dosage, as well as the concentration of hydroxyl radicals, are examined. Accordingly, the pseudo-first-order rate constant, its variation as functions of HP concentration, incident UV-light intensity and the limitations of the adopted approach are discussed. In line with that, the authors provided evidence of the validity of the kinetic model through the exposure of previous experimental studies as reported in the literature review then through the evidence of the present experimental data.