Structural identifiability of surface binding reactions involving heterogeneous analyte : application to surface plasmon resonance experiments

Binding affinities are useful measures of target interaction and have an important role in understanding biochemical reactions that involve binding mechanisms. Surface plasmon resonance (SPR) provides convenient real-time measurement of the reaction that enables subsequent estimation of the reaction constants necessary to determine binding affinity. Three models are considered for application to SPR experiments—the well mixed Langmuir model and two models that represent the binding reaction in the presence of transport effects. One of these models, the effective rate constant approximation, can be derived from the other by applying a quasi-steady state assumption. Uniqueness of the reaction constants with respect to SPR measurements is considered via a structural identifiability analysis. It is shown that the models are structurally unidentifiable unless the sample concentration is known. The models are also considered for analytes with heterogeneity in the binding kinetics. This heterogeneity further confounds the identifiability of key parameters necessary for reliable estimation of the binding affinit

Knee contact forces are not altered in early knee osteoarthritis.

OBJECTIVE: This study calculated knee contact forces (KCF) and its relations with knee external knee adduction moments (KAM) and/or flexion moments (KFM) during the stance phase of gait in patients with early osteoarthritis (OA), classified based on early joint degeneration on Magnetic Resonance Imaging (MRI). We aimed at assessing if altered KCF are already present in early structural degeneration. DESIGN: Three-dimensional motion and ground reaction force data in 59 subjects with medial compartment knee OA (N=23 established OA, N=16 early OA, N=20 controls) were used as input for a musculoskeletal model. KAM and KFM, and KCF were estimated using OpenSim software. RESULTS: No significant differences were found between controls and subjects with early OA. In early OA patients, KAM significantly explained 69% of the variance associated with the first peaks KCF but only KFM contributed to the second peaks KCF. The multiple correlation, combining KAM and KFM, showed to be higher. However, only 20% of the variance of second peak KCF was explained by both moments in established OA. CONCLUSION: KCF are not increased in patients with early OA, suggesting that knee joint overload is more a consequence of further joint degeneration in more advanced stages of OA. Additionally, our results clearly show that KAM is not sufficient to predict joint loading at the end of the stance, where KFM contributes substantially to the loading, especially in early OA

Measurement of νˉμ\bar{\nu}_{\mu} and νμ\nu_{\mu} charged current inclusive cross sections and their ratio with the T2K off-axis near detector

We report a measurement of cross section $\sigma(\nu_{\mu}+{\rm nucleus}\rightarrow\mu^{-}+X)$ and the first measurements of the cross section $\sigma(\bar{\nu}_{\mu}+{\rm nucleus}\rightarrow\mu^{+}+X)$ and their ratio $R(\frac{\sigma(\bar \nu)}{\sigma(\nu)})$ at (anti-)neutrino energies below 1.5 GeV. We determine the single momentum bin cross section measurements, averaged over the T2K $\bar{\nu}/\nu$-flux, for the detector target material (mainly Carbon, Oxygen, Hydrogen and Copper) with phase space restricted laboratory frame kinematics of $\theta_{\mu}$500 MeV/c. The results are $\sigma(\bar{\nu})=\left( 0.900\pm0.029{\rm (stat.)}\pm0.088{\rm (syst.)}\right)\times10^{-39}$ and $\sigma(\nu)=\left( 2.41\ \pm0.022{\rm{(stat.)}}\pm0.231{\rm (syst.)}\ \right)\times10^{-39}$in units of cm$^{2}$/nucleon and$R\left(\frac{\sigma(\bar{\nu})}{\sigma(\nu)}\right)= 0.373\pm0.012{\rm (stat.)}\pm0.015{\rm (syst.)}$.Comment: 18 pages, 8 figure

Search for Lorentz and CPT violation using sidereal time dependence of neutrino flavor transitions over a short baseline

A class of extensions of the Standard Model allows Lorentz and CPT violations, which can be identified by the observation of sidereal modulations in the neutrino interaction rate. A search for such modulations was performed using the T2K on-axis near detector. Two complementary methods were used in this study, both of which resulted in no evidence of a signal. Limits on associated Lorentz and CPT-violating terms from the Standard Model extension have been derived by taking into account their correlations in this model for the first time. These results imply such symmetry violations are suppressed by a factor of more than 10 20 at the GeV scale

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.New methods for child psychiatric diagnosis and treatment outcome evaluatio

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

Search for nucleon decay into charged antilepton plus meson in 0.316 megaton . years exposure of the Super-Kamiokande water Cherenkov detector

We have searched for proton decays into a charged antilepton (e+, μ+) plus a meson (η, ρ0, ω) and for neutron decays into a charged antilepton (e+, μ+) plus a meson (π−, ρ−) using Super-Kamiokande I-IV data, corresponding to 0.316  megaton⋅years of exposure. This measurement updates the previous published result by using 2.26 times more data and improved analysis methods. No significant evidence for nucleon decay is observed and lower limits on the partial lifetime of the nucleon are obtained. The limits range from 3×1031 to 1×1034  years at 90% confidence level, depending on the decay mode