Anti-Depressant Properties of Crocin Molecules in Saffron

This is the final version. Available on open access from MDPI via the DOI in this recordSaffron is a valued herb, obtained from the stigmas of the C. sativus Linn (Iridaceae), with therapeutic effects. It has been described in pharmacopoeias to be variously acting, including as an anti-depressant, anti-carcinogen, and stimulant agent. The therapeutic effects of saffron are harbored in its bioactive molecules, notably crocins, the subject of this paper. Crocins have been demonstrated to act as a monoamine oxidase type A and B inhibitor. Furthermore, saffron petal extracts have experimentally been shown to impact contractile response in electrical field stimulation. Other research suggests that saffron also inhibits the reuptake of monoamines, exhibits N-methyl-d-aspartate antagonism, and improves brain-derived neurotrophic factor signaling. A host of experimental studies found saffron/crocin to be similarly effective as fluoxetine and imipramine in the treatment of depression disorders. Saffron and crocins propose a natural solution to combat depressive disorders. However, some hurdles, such as stability and delivery, need to be overcome.USDA/NIFA1890 Capacity Building ProgramAgricultural Research Station, North Carolina Agricultural and Technical State UniversityNational Institute of Food and Agriculture (NIFA

A Saffron Spice Separation System with Computer Vision

A separation device is described to obtain saffron spice after harvesting. To set the separation device, a vertical wind tunnel is developed which measures the terminal velocities of parts of saffron flower, with variations for different regions and years of production. The separation device is equipped with a vision system, which evaluates the separation and the percentage of purity of the saffron spice obtained after separation. In this paper, the design and the realization of the wind tunnel and of the separation device are described and the separation of the flower is performed and discussed, evaluating the separation efficiency

Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review

Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and symptoms that appear in early childhood. ASD is also associated with communication deficits and repetitive behavior in affected individuals. Various ASD detection methods have been developed, including neuroimaging modalities and psychological tests. Among these methods, magnetic resonance imaging (MRI) imaging modalities are of paramount importance to physicians. Clinicians rely on MRI modalities to diagnose ASD accurately. The MRI modalities are non-invasive methods that include functional (fMRI) and structural (sMRI) neuroimaging methods. However, diagnosing ASD with fMRI and sMRI for specialists is often laborious and time-consuming; therefore, several computer-aided design systems (CADS) based on artificial intelligence (AI) have been developed to assist specialist physicians. Conventional machine learning (ML) and deep learning (DL) are the most popular schemes of AI used for diagnosing ASD. This study aims to review the automated detection of ASD using AI. We review several CADS that have been developed using ML techniques for the automated diagnosis of ASD using MRI modalities. There has been very limited work on the use of DL techniques to develop automated diagnostic models for ASD. A summary of the studies developed using DL is provided in the Supplementary Appendix. Then, the challenges encountered during the automated diagnosis of ASD using MRI and AI techniques are described in detail. Additionally, a graphical comparison of studies using ML and DL to diagnose ASD automatically is discussed. We suggest future approaches to detecting ASDs using AI techniques and MRI neuroimaging

Effects of Short-Term Continuous Montmorency Tart Cherry Juice Supplementation in Participants with Metabolic Syndrome

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s00394-020-02355-5Purpose: Metabolic Syndrome (MetS) augments the incidence of cardiovascular disease by two-fold and type II diabetes mellitus by five-fold. Montmorency tart cherries are rich in phytochemicals shown to improve biomarkers related to cardio-metabolic health in humans. This study aimed to examine cardio-metabolic responses after 7-days Montmorency tart cherry juice (MTCJ) supplementation and also acute on short-term supplementation responses to a single bolus, in humans with MetS. Methods: In a randomised, single-blind, placebo-controlled, crossover trial, 12 participants with MetS (50 ± 10 years; 6M/6F), consumed MTCJ or placebo (PLA) for 7 days. Blood-based and functional cardio-metabolic biomarkers were measured pre- and post-supplementation, and acute responses measured pre-bolus and up to 5 h post-bolus on the 7th day. Results: 24-h ambulatory systolic (P = 0.016), diastolic (P = 0.009) blood pressure and mean arterial pressure (P = 0.041) were significantly lower after 7-days MTCJ supplementation compared to PLA. Glucose (P = 0.038), total cholesterol (P = 0.036), LDL (P = 0.023) concentrations, total cholesterol:HDL ratio (P = 0.004) and respiratory exchange ratio values (P = 0.009) were significantly lower after 6-days MTCJ consumption compared to PLA. Conclusions: This study revealed for the first time in humans that MTCJ significantly improved 24-h BP, fasting glucose, total cholesterol and total cholesterol:HDL ratio, and also lowered resting respiratory exchange ratio compared to a control group. Responses demonstrated clinically relevant improvements on aspects of cardio-metabolic function, emphasising the potential efficacy of MTCJ in preventing further cardio-metabolic dysregulation in participants with MetS. Registered at clinicaltrials.gov (NCT03619941).Peer reviewedFinal Accepted Versio

Dynamics of interferon-gamma release assay and cytokine profiles in blood and respiratory tract specimens from mice with tuberculosis and the effect of therapy

There are limitations on diagnostic methods to differentiate between active and latent tuberculosis (TB), and the prediction of latent progression to TB disease is yet complex. Traditionally, tuberculosis-specific host immune response was visualized using the tuberculin skin test. Nowadays, IFN-γ release assays (IGRA) provide a more specific and sensitive tool, by which exposure to Mtb could be determined. However, the merit of IGRA aids in diagnosing active TB is yet unclear. We adapted IGRA for use in mice, and quantifying bead-based flow cytometry techniques were used to assess cytokine profiles during the course of untreated infection and to investigate the value of IGRA and cytokines as biomarkers for therapy response. High variability of IGRA results during progression of active TB infection related to various phases of infection was obtained. However, a significant decrease in IGRA results and in levels of IFN-γ, IL-17, IP-10 or MIG was observed and appeared to be associated with successful therapy. This outcome does not support the value of IGRA to accurately diagnose active TB or to monitor infection progression. However, IGRA proved to be a useful biomarker to monitor therapy success. In addition, different cytokines might serve as biomarkers

Differentiation of Glioma and Radiation Injury in Rats Using In Vitro Produce Magnetically Labeled Cytotoxic T-Cells and MRI

A limitation with current imaging strategies of recurrent glioma undergoing radiotherapy is that tumor and radiation injury cannot be differentiated with post contrast CT or MRI, or with PET or other more complex parametric analyses of MRI data. We propose to address the imaging limitation building on emerging evidence indicating that effective therapy for recurrent glioma can be attained by sensitized T-cells following vaccination of primed dendritic cells (DCs). The purpose of this study was to determine whether cord blood T-cells can be sensitized against glioma cells (U-251) and if these sensitized cytotoxic T-cells (CTLs) can be used as cellular magnetic resonance imaging probes to identify and differentiate glioma from radiation necrosis in rodent models.Cord blood T and CD14+ cells were collected. Isolated CD14+ cells were then converted to dendritic cells (DCs), primed with glioma cell lysate and used to sensitize T-cells. Phenotypical expression of the generated DCs were analyzed to determine the expression level of CD14, CD86, CD83 and HLA-DR. Cells positive for CD25, CD4, CD8 were determined in generated CTLs. Specificity of cytotoxicity of the generated CTLs was also determined by lactate dehydrogenase (LDH) release assay. Secondary proliferation capacity of magnetically labeled and unlabeled CTLs was also determined. Generated CTLs were magnetically labeled and intravenously injected into glioma bearing animals that underwent MRI on days 3 and 7 post- injection. CTLs were also administered to animals with focal radiation injury to determine whether these CTLs accumulated non-specifically to the injury sites. Multi-echo T2- and T2*-weighted images were acquired and R2 and R2* maps created. Our method produced functional, sensitized CTLs that specifically induced U251 cell death in vitro. Both labeled and unlabeled CTLs proliferated equally after the secondary stimulation. There were significantly higher CD25 positive cells (p = <0.006) in CTLs. In addition, T2- and T2*-weighted MR images showed increased low signal intensity areas in animals that received labeled CTLs as compared to the images from animals that received control cells. Histological analysis confirmed the presence of iron positive cells in sites corresponding to MRI low signal intensity regions. Significant differences (p = <0.001) in tumor R2 and R2* values were observed among the groups of animals. Animals with radiation injury exhibited neither MRI hypointense areas nor presence of iron positive cells.Our results indicate that T-cells can be effectively sensitized by in vitro methods and used as cellular probes to identify and differentiate glioma from radiation necrosis

Measurements of branching fraction ratios and CP-asymmetries in suppressed B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^- decays

We report the first reconstruction in hadron collisions of the suppressed decays B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^-, sensitive to the CKM phase gamma, using data from 7 fb^-1 of integrated luminosity collected by the CDF II detector at the Tevatron collider. We reconstruct a signal for the B^- -> D(-> K^+ pi^-)K^- suppressed mode with a significance of 3.2 standard deviations, and measure the ratios of the suppressed to favored branching fractions R(K) = [22.0 \pm 8.6(stat)\pm 2.6(syst)]\times 10^-3, R^+(K) = [42.6\pm 13.7(stat)\pm 2.8(syst)]\times 10^-3, R^-(K)= [3.8\pm 10.3(stat)\pm 2.7(syst]\times 10^-3, as well as the direct CP-violating asymmetry A(K) = -0.82\pm 0.44(stat)\pm 0.09(syst) of this mode. Corresponding quantities for B^- -> D(-> K^+ pi^-)pi^- decay are also reported.Comment: 8 pages, 1 figure, accepted by Phys.Rev.D Rapid Communications for Publicatio

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Identification of Mycobacterium tuberculosis-Specific Th1, Th17 and Th22 Cells Using the Expression of CD40L in Tuberculous Pleurisy

Important advances have been made in the immunodiagnosis of tuberculosis (TB) based on the detection of Mycobacterium tuberculosis (MTB)-specific T cells. However, the sensitivity and specificity of the immunological approach are relatively low because there are no specific markers for antigen-specific Th cells, and some of the Th cells that do not produce cytokines can be overlooked using this approach. In this study, we found that MTB-specific peptides of ESAT-6/CFP-10 can stimulate the expression of CD40L specifically in CD4+ T cells but not other cells from pleural fluid cells (PFCs) in patients with tuberculous pleurisy (TBP). CD4+CD40L+ but not CD4+CD40L− T cells express IFN-γ, IL-2, TNF-α, IL-17 or IL-22 after stimulation with MTB-specific peptides. In addition, CD4+CD40L+ T cells were found to be mostly polyfunctional T cells that simultaneously produce IFN-γ, IL-2 and TNF-α and display an effector or effector memory phenotype (CD45RA−CD45RO+CCR7−CD62L−ICOS−). To determine the specificity of CD4+CD40L+ T cells, we incubated PFCs with ESTA-6/CFP-10 peptides and sorted live CD4+CD40L+ and CD4+CD40L− T cells by flow cytometry. We further demonstrated that sorted CD4+CD40L+, but not CD4+CD40L− fractions, principally produced IFN-γ, IL-2, TNF-α, IL-17 and IL-22 following restimulation with ESTA-6/CFP-10 peptides. Taken together, our data indicate that the expression of CD40L on MTB-specific CD4+ T cells could be a good marker for the evaluation and isolation of MTB-specific Th cells and might also be useful in the diagnosis of TB

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO