Producing indices composed of multiple input variables has been embedded in some data processing and analytical methods. We aim to test the feasibility of creating data-driven indices by aggregating ...input variables according to principal component analysis (PCA) loadings. To validate the significance of both the theory-based and data-driven indices, we propose principles to review innovative indices. We generated weighted indices with the variables obtained in the first years of the two-year panels in the Medical Expenditure Panel Survey initiated between 1996 and 2011. Variables were weighted according to PCA loadings and summed. The statistical significance and residual deviance of each index to predict mortality in the second years was extracted from the results of discrete-time survival analyses. There were 237,832 surviving the first years of panels, represented 4.5 billion civilians in the United States, of which 0.62% (95% CI = 0.58% to 0.66%) died in the second years of the panels. Of all 134,689 weighted indices, there were 40,803 significantly predicting mortality in the second years with or without the adjustment of age, sex and races. The significant indices in the both models could at most lead to 10,200 years of academic tenure for individual researchers publishing four indices per year or 618.2 years of publishing for journals with annual volume of 66 articles. In conclusion, if aggregating information based on PCA loadings, there can be a large number of significant innovative indices composing input variables of various predictive powers. To justify the large quantities of innovative indices, we propose a reporting and review framework for novel indices based on the objectives to create indices, variable weighting, related outcomes and database characteristics. The indices selected by this framework could lead to a new genre of publications focusing on meaningful aggregation of information.
The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease ...mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.
Fused Deposition Modeling (FDM) can be used to manufacture any complex geometry and internal structures, and it has been widely applied in many industries, such as the biomedical, manufacturing, ...aerospace, automobile, industrial, and building industries. The purpose of this research is to characterize the polylactic acid (PLA) and polyethylene terephthalate glycol (PETG) materials of FDM under four loading conditions (tension, compression, bending, and thermal deformation), in order to obtain data regarding different printing temperatures and speeds. The results indicated that PLA and PETG materials exhibit an obvious tensile and compression asymmetry. It was observed that the mechanical properties (tension, compression, and bending) of PLA and PETG are increased at higher printing temperatures, and that the effect of speed on PLA and PETG shows different results. In addition, the mechanical properties of PLA are greater than those of PETG, but the thermal deformation is the opposite. The above results will be a great help for researchers who are working with polymers and FDM technology to achieve sustainability.
The purpose of this study was to determine whether applying repetitive constraint forces to the non-paretic leg during walking would induce motor learning of enhanced use of the paretic leg in ...individuals post-stroke. Sixteen individuals post chronic (> 6 months) stroke were recruited in this study. Each subject was tested in two conditions, i.e., applying a constraint force to the non-paretic leg during treadmill walking and treadmill walking only. For the constraint condition, subjects walked on a treadmill with no force for 1 min (baseline), with force for 7 min (adaptation), and then without force for 1 min (post-adaptation). For the treadmill only condition, a similar protocol was used but no force was applied. EMGs from muscles of the paretic leg and ankle kinematic data were recorded. Spatial–temporal gait parameters during overground walking pre and post treadmill walking were also collected. Integrated EMGs of ankle plantarflexors and hip extensors during stance phase significantly increased during the early adaptation period, and partially retained (15–21% increase) during the post-adaptation period for the constraint force condition, which were significantly greater than that for the treadmill only (3–5%) condition. The symmetry of step length during overground walking significantly improved (
p
= 0.04) after treadmill walking with the constraint condition, but had no significant change after treadmill walking only. Repetitively applying constraint force to the non-paretic leg during treadmill walking may lead to a motor learning of enhanced use of the paretic leg in individuals post-stroke, which may transfer to overground walking.
Estimation of the Digital Surface Model (DSM) and building heights from single-view aerial imagery is a challenging inherently ill-posed problem that we address in this paper by resorting to machine ...learning. We propose an end-to-end trainable convolutional-deconvolutional deep neural network architecture that enables learning mapping from a single aerial imagery to a DSM for analysis of urban scenes. We perform multisensor fusion of aerial optical and aerial light detection and ranging (Lidar) data to prepare the training data for our pipeline. The dataset quality is key to successful estimation performance. Typically, a substantial amount of misregistration artifacts are present due to georeferencing/projection errors, sensor calibration inaccuracies, and scene changes between acquisitions. To overcome these issues, we propose a registration procedure to improve Lidar and optical data alignment that relies on Mutual Information, followed by Hough transform-based validation step to adjust misregistered image patches. We validate our building height estimation model on a high-resolution dataset captured over central Dublin, Ireland: Lidar point cloud of 2015 and optical aerial images from 2017. These data allow us to validate the proposed registration procedure and perform 3D model reconstruction from single-view aerial imagery. We also report state-of-the-art performance of our proposed architecture on several popular DSM estimation datasets.
MicroRNAs (miRs) are a class of single-stranded RNA molecules of 15-27 nucleotides in length that regulate gene expression at the post-translational level. miR-21 is one of the earliest identified ...cancer-promoting 'oncomiRs', targeting numerous tumor suppressor genes associated with proliferation, apoptosis and invasion. The regulation of miR-21 and its role in carcinogenesis have been extensively investigated. Recent studies have focused on the diagnostic and prognostic value of miR-21 as well as its implication in the drug resistance of human malignancies. The further use of miR-21 as a biomarker and target for cancer treatments is likely to improve the outcome for patients with cancer. The present review highlights recent findings associated with the importance of miR-21 in hematological and non-hematological malignancies.
Blood–brain barrier (BBB) disruption contributes to neurodegenerative diseases. Loss of tight junction (TJ) proteins in cerebral endothelial cells (ECs) is a leading cause of BBB breakdown. We ...recently reported that miR‐195 provides vasoprotection, which urges us to explore the role of miR‐195 in BBB integrity. Here, we found cerebral miR‐195 levels decreased with age, and BBB leakage was significantly increased in miR‐195 knockout mice. Furthermore, exosomes from miR‐195‐enriched astrocytes increased endothelial TJ proteins and improved BBB integrity. To decipher how miR‐195 promoted BBB integrity, we first demonstrated that TJ proteins were metabolized via autophagic–lysosomal pathway and the autophagic adaptor p62 was necessary to promote TJ protein degradation in cerebral ECs. Next, proteomic analysis of exosomes revealed miR‐195‐suppressed thrombospondin‐1 (TSP1) as a major contributor to BBB disruption. Moreover, TSP1 was demonstrated to activate selective autophagy of TJ proteins by increasing the formation of claudin‐5‐p62 and ZO1‐p62 complexes in cerebral ECs while TSP1 impaired general autophagy. Delivering TSP1 antibody into the circulation showed dose‐dependent reduction of BBB leakage by 20%–40% in 25‐month‐old mice. Intravenous or intracerebroventricular injection of miR‐195 rescued TSP1‐induced BBB leakage. Dementia patients with BBB damage had higher levels of serum TSP1 compared to those without BBB damage (p = 0.0015), while the normal subjects had the lowest TSP1 (p < 0.0001). Taken together, the study implies that TSP1‐regulated selective autophagy facilitates the degradation of TJ proteins and weakens BBB integrity. An adequate level of miR‐195 can suppress the autophagy–lysosome pathway via a reduction of TSP1, which may be important for maintaining BBB function.
The present study revealed that thrombospondin‐1 (TSP1) is a key factor for BBB leakage and miR‐195 protects BBB integrity. We showed that cerebral miR‐195 reduces with age and blood‐brain barrier (BBB) leakage is increased in miR‐195 knockout mice. miR‐195‐regulated thrombospondin‐1 impairs BBB via selective autophagy of tight junctions. Furthermore, circulating TSP1 was higher in BBB‐damaged patients, which implied TSP1 as a new biomarker of BBB damage.
Mammalian innate immune sensor STING (STimulator of INterferon Gene) was recently found to originate from bacteria. During phage infection, bacterial STING sense c-di-GMP generated by the CD-NTase ...(cGAS/DncV-like nucleotidyltransferase) encoded in the same operon and signal suicide commitment as a defense strategy that restricts phage propagation. However, the precise binding mode of c-di-GMP to bacterial STING and the specific recognition mechanism are still elusive. Here, we determine two complex crystal structures of bacterial STING/c-di-GMP, which provide a clear picture of how c-di-GMP is distinguished from other cyclic dinucleotides. The protein-protein interactions further reveal the driving force behind filament formation of bacterial STING. Finally, we group the bacterial STING into two classes based on the conserved motif in β-strand lid, which dictate their ligand specificity and oligomerization mechanism, and propose an evolution-based model that describes the transition from c-di-GMP-dependent signaling in bacteria to 2'3'-cGAMP-dependent signaling in eukaryotes.
Frailty is associated with major health outcomes. However, the relationships between frailty and frailty symptoms haven't been well studied. This study aims to show the associations between frailty ...and frailty symptoms. The Health and Retirement Study (HRS) is an ongoing longitudinal biannual survey in the United States. Three of the most used frailty diagnoses, defined by the Functional Domains Model, the Burden Model, and the Biologic Syndrome Model, were reproduced according to previous studies. The associations between frailty statuses and input symptoms were assessed using odds ratios and correlation coefficients. The sample sizes, mean ages, and frailty prevalence matched those reported in previous studies. Frailty statuses were weakly correlated with each other (coefficients = 0.19 to 0.38, p 0.05 for all). One to six symptoms defined by the other two models were not significantly correlated with each of the three frailty statuses (p > 0.05 for all). Frailty statuses were significantly correlated with their own bias variables (p < 0.05 for all). Frailty diagnoses lack significant correlations with some of their own frailty symptoms and some of the frailty symptoms defined by the other two models. This finding raises questions like whether the frailty symptoms lacking significant correlations with frailty statuses could be included to diagnose frailty and whether frailty exists and causes frailty symptoms.
A
bstract
We explore scalar dark matter that is part of a lepton flavor triplet satisfying symmetry requirements under the hypothesis of minimal flavor violation. Beyond the standard model, the ...theory contains in addition three right-handed neutrinos that participate in the seesaw mechanism for light neutrino mass generation. The dark-matter candidate couples to standard-model particles via Higgs-portal renormalizable interactions as well as to leptons through dimension-six operators, all of which have minimal flavor violation built-in. We consider restrictions on the new scalars from the Higgs boson measurements, observed relic density, dark-matter direct detection experiments, LEP II measurements on
e
+
e
−
scattering into a photon plus missing energy, and searches for flavor-violating lepton decays. The viable parameter space can be tested further with future data. Also, we investigate the possibility of the new scalars’ couplings accounting for the tentative hint of Higgs flavor-violating decay
h
→
μτ
recently detected in the CMS experiment. They are allowed by constraints from other Higgs data to produce a rate of this decay roughly compatible with the CMS finding.
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