Multi-contrast x-ray identification of inhomogeneous materials and their discrimination through deep learning approaches

Recent innovations in x-ray technology (namely phase-based and energy-resolved imaging) offer unprecedented opportunities for material discrimination; however, they are often used in isolation or in limited combinations. Here we show that the optimized combination of contrast channels (attenuation at three x-ray energies, ultra-small angle scattering at two, standard deviation of refraction) significantly enhances material identification abilities compared to dual-energy x-ray imaging alone, and that a combination of off-the-shelf machine learning approaches can effectively discriminate, e.g., threat materials, in complex datasets. The methodology is validated on a range of materials and image datasets that are both an order of magnitude larger than those used in previous studies. Our results can provide an effective methodology to discriminate, and in some cases identify, different materials in complex imaging scenarios, with prospective applications across the life and physical sciences. While the detection of threat materials is used as a demonstrator here, the methodology could be equally applied to, e.g., the distinction between diseased and healthy tissues or degraded vs. pristine materials

Enhanced detection of threat materials by dark-field x-ray imaging combined with deep neural networks

X-ray imaging has been boosted by the introduction of phase-based methods. Detail visibility is enhanced in phase contrast images, and dark-field images are sensitive to inhomogeneities on a length scale below the system’s spatial resolution. Here we show that dark-field creates a texture which is characteristic of the imaged material, and that its combination with conventional attenuation leads to an improved discrimination of threat materials. We show that remaining ambiguities can be resolved by exploiting the different energy dependence of the dark-field and attenuation signals. Furthermore, we demonstrate that the dark-field texture is well-suited for identification through machine learning approaches through two proof-of-concept studies. In both cases, application of the same approaches to datasets from which the dark-field images were removed led to a clear degradation in performance. While the small scale of these studies means further research is required, results indicate potential for a combined use of dark-field and deep neural networks in security applications and beyond

A Phase 2a active-comparator-controlled study to evaluate the efficacy and safety of efinopegdutide in patients with nonalcoholic fatty liver disease

Background and aimsThis study assessed the effects of the GLP-1/glucagon receptor co-agonist efinopegdutide relative to the selective GLP-1 receptor agonist semaglutide on liver fat content (LFC) in patients with nonalcoholic fatty liver disease (NAFLD).MethodsThis was a Phase 2a, randomized, active-comparator-controlled, parallel-group, open-label study. A magnetic resonance imaging-estimated proton density fat fraction assessment was performed to determine LFC at screening and Week 24. Participants with an LFC of ≥10% at screening were randomized 1:1 to open-label efinopegdutide 10 mg subcutaneous (SC) once weekly or semaglutide 1 mg SC once weekly for 24 weeks, stratified according to concurrent diagnosis of type 2 diabetes. Both drugs were titrated to the target dose over an 8-week time period. The primary efficacy endpoint was relative reduction from baseline in LFC (%) after 24 weeks of treatment.ResultsAmong 145 randomized participants (efinopegdutide N=72, semaglutide N=73), 33.1% had T2DM. At baseline, mean body mass index was 34.3 kg/m2and mean LFC was 20.3%. The least squares (LS) mean relative reduction from baseline in LFC at Week 24 was significantly (p<0.001) greater with efinopegdutide (72.7% [90% CI: 66.8, 78.7]) than with semaglutide (42.3% [90% CI: 36.5, 48.1]). Both treatment groups had an LS mean percent reduction from baseline in body weight at Week 24 (efinopegdutide 8.5% vs semaglutide 7.1%; p=0.085). Slightly higher incidences of adverse events and drug-related adverse events were observed in the efinopegdutide group compared with the semaglutide group, primarily related to an imbalance in gastrointestinal adverse events.ConclusionsIn patients with NAFLD, treatment with efinopegdutide 10 mg weekly led to a significantly greater reduction in LFC than semaglutide 1 mg weekly. (EudraCT: 2020-005136-30; NCT: 04944992) IMPACT AND IMPLICATIONS: Currently, there are no approved therapies for nonalcoholic steatohepatitis (NASH). The weight loss associated with glucagon-like peptide-1 (GLP-1) receptor agonists has been shown to decrease hepatic inflammation in patients with NASH. In addition to reducing liver fat content (LFC) indirectly through weight loss, glucagon receptor agonism may also reduce LFC by acting on the liver directly to stimulate fatty acid oxidation and reduce lipogenesis. This study demonstrated that treatment of nonalcoholic fatty liver disease (NAFLD) patients with the GLP-1/glucagon receptor co-agonist efinopegdutide at 10 mg weekly led to a significantly greater reduction in LFC compared with the GLP-1 receptor agonist semaglutide at 1 mg weekly, suggesting that efinopegdutide may be an effective treatment for NASH.Clinical trial numberEudraCT: 2020-005136-30; NCT: 04944992

Coronary Plaque Morphology and the Anti-Inflammatory Impact of Atorvastatin: A Multicenter 18F-Fluorodeoxyglucose Positron Emission Tomographic/Computed Tomographic Study.

BACKGROUND: Nonobstructive coronary plaques manifesting high-risk morphology (HRM) associate with an increased risk of adverse clinical cardiovascular events. We sought to test the hypothesis that statins have a greater anti-inflammatory effect within coronary plaques containing HRM. METHODS AND RESULTS: In this prospective multicenter study, 55 subjects with or at high risk for atherosclerosis underwent 18F-fluorodeoxyglucose positron emission tomographic/computed tomographic imaging at baseline and after 12 weeks of treatment with atorvastatin. Coronary arterial inflammation (18F-fluorodeoxyglucose uptake, expressed as target-to-background ratio) was assessed in the left main coronary artery (LMCA). While blinded to the PET findings, contrast-enhanced computed tomographic angiography was performed to characterize the presence of HRM (defined as noncalcified or partially calcified plaques) in the LMCA. Arterial inflammation (target-to-background ratio) was higher in LMCA segments with HRM than those without HRM (mean+/-SEM: 1.95+/-0.43 versus 1.67+/-0.32 for LMCA with versus without HRM, respectively; P=0.04). Moreover, atorvastatin treatment for 12 weeks reduced target-to-background ratio more in LMCA segments with HRM than those without HRM (12 week-baseline Deltatarget-to-background ratio [95% confidence interval]: -0.18 [-0.35 to -0.004] versus 0.09 [-0.06 to 0.26]; P=0.02). Furthermore, this relationship between coronary plaque morphology and change in LMCA inflammatory activity remained significant after adjusting for baseline low-density lipoprotein and statin dose (beta=-0.27; P=0.038). CONCLUSIONS: In this first study to evaluate the impact of statins on coronary inflammation, we observed that the anti-inflammatory impact of statins is substantially greater within coronary plaques that contain HRM features. These findings suggest an additional mechanism by which statins disproportionately benefit individuals with more advanced atherosclerotic disease. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00703261

Biofabrication of Anisotropic Gold Nanotriangles Using Extract of Endophytic Aspergillus clavatus as a Dual Functional Reductant and Stabilizer

Biosynthesis of metal and semiconductor nanoparticles using microorganisms has emerged as a more eco-friendly, simpler and reproducible alternative to the chemical synthesis, allowing the generation of rare forms such as nanotriangles and prisms. Here, we report the endophytic fungus Aspergillus clavatus, isolated from surface sterilized stem tissues of Azadirachta indica A. Juss., when incubated with an aqueous solution of chloroaurate ions produces a diverse mixture of intracellular gold nanoparticles (AuNPs), especially nanotriangles (GNT) in the size range from 20 to 35 nm. These structures (GNT) are of special interest since they possess distinct plasmonic features in the visible and IR regions, which equipped them with unique physical and optical properties exploitable in vital applications such as optics, electronics, catalysis and biomedicine. The reaction process was simple and convenient to handle and was monitored using ultraviolet–visible spectroscopy (UV–vis). The morphology and crystalline nature of the GNTs were determined from transmission electron microscopy (TEM), atomic force spectroscopy (AFM) and X-ray diffraction (XRD) spectroscopy. This proposed mechanistic principal might serve as a set of design rule for the synthesis of anisotropic nanostructures with desired architecture and can be amenable for the large scale commercial production and technical applications

Correlation Functions of Large N Chern-Simons-Matter Theories and Bosonization in Three Dimensions

We consider the conformal field theory of N complex massless scalars in 2+1 dimensions, coupled to a U(N) Chern-Simons theory at level k. This theory has a 't Hooft large N limit, keeping fixed \lambda = N/k. We compute some correlation functions in this theory exactly as a function of \lambda, in the large N (planar) limit. We show that the results match with the general predictions of Maldacena and Zhiboedov for the correlators of theories that have high-spin symmetries in the large N limit. It has been suggested in the past that this theory is dual (in the large N limit) to the Legendre transform of the theory of fermions coupled to a Chern-Simons gauge field, and our results allow us to find the precise mapping between the two theories. We find that in the large N limit the theory of N scalars coupled to a U(N)_k Chern-Simons theory is equivalent to the Legendre transform of the theory of k fermions coupled to a U(k)_N Chern-Simons theory, thus providing a bosonization of the latter theory. We conjecture that perhaps this duality is valid also for finite values of N and k, where on the fermionic side we should now have (for N_f flavors) a U(k)_{N-N_f/2} theory. Similar results hold for real scalars (fermions) coupled to the O(N)_k Chern-Simons theory.Comment: 49 pages, 16 figures. v2: added reference

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed

Biosynthesis of Gold Nanoparticles by Foliar Broths: Roles of Biocompounds and Other Attributes of the Extracts

Biosynthesis of nanoparticles has arisen as a promising alternative to conventional synthetic methodologies owing to its eco-friendly advantages, and the involved bioprotocol still needs further clarification. This research, for the first time from the standpoint of statistics, confirmed an electrostatic force or ionic bond-based interaction between the chloroauric ions and the involved bioconstituents and manifested that reducing sugars and flavonoids were both important reductants responsible for conversion of Au(III) to Au(0). The result also demonstrated that the proteins were not the reducing agents, yet they might be protection agents in biosynthesis of gold nanoparticles (GNPs). Besides, a significant linear relationship was found between the anti-oxidant ability of the foliar broths and their capability to reduce Au(III) into Au(0). Furthermore, the preliminary investigation based on the boxplot on the size/shape distribution of the biosynthesized GNPs revealed that gold nanospheres with higher degree of homogeneity in size tended to be promoted by foliar broths containing higher content of reducing sugars/flavonoids and proteins. Otherwise, i.e., for those broths with lower content of the above biocompounds, sphere GNPs of wider size distribution or even gold nanotriangles tended to be fabricated

A shape tailored gold-conductive polymer nanocomposite as a transparent electrode with extraordinary insensitivity to volatile organic compounds (VOCs)

In this study, the transparent conducting polymer of poly (3,4-ethylenendioxythiophene): poly(styrene sulphonate) (PEDOT:PSS) was nanohybridized via inclusion of gold nanofillers including nanospheres (NSs) and nanorods (NRs). Such nanocomposite thin films offer not only more optimum conductivity than the pristine polymer but also excellent resistivity against volatile organic compounds (VOCs). Interestingly, such amazing properties are achieved in the diluted regimes of the nanofillers and depend on the characteristics of the interfacial region of the polymer and nanofillers, i.e. the aspect ratio of the latter component. Accordingly, a shape dependent response is made that is more desirable in case of using the Au nanorods with a much larger aspect ratio than their nanosphere counterparts. This transparent nanocomposite thin film with an optimized conductivity and very low sensitivity to organic gases is undoubtedly a promising candidate material for the touch screen panel production industry. Considering PEDOT as a known material for integrated electrodes in energy saving applications, we believe that our strategy might be an important progress in the field.Peer reviewe

Outcome of a risk-related therapeutic strategy used prospectively in a population-based study of Hodgkin's lymphoma in adolescents

The aim was to assess outcome in a population-based cohort of adolescents with Hodgkin's lymphoma (HL) diagnosed in the UK's northern region over a 10-year period. Among a population of 3.09 million, 55 of 676 patients (8%) diagnosed with HL were aged 13–19. Seven had nodular lymphocyte-predominant HL, 48 classical HL (cHL). Of the latter, 36 were ⩾16 years. Application of the Scottish and Newcastle Lymphoma Group (SNLG) prognostic index meant 21 patients were considered high risk (index ⩾0.5). They received PVACEBOP multi-agent chemotherapy as primary therapy. Standard risk patients (SNLG index <0.5) were treated with standard ChlVPP or ABVD chemotherapy±radiotherapy. Scottish and Newcastle Lymphoma Group indexing is not valid for patients under 16. Twelve patients therefore received UKCCSG protocols (n=8), ABVD plus radiotherapy (n=2), or PVACEBOP (n=2). Forty-six patients with cHL (96%) achieved complete remission. Seven patients relapsed but all entered complete remission after salvage therapy. Five patients died: three of HL, one in an accident and one of disseminated varicella complicating cystic fibrosis. Five- and 10-year overall survival was 93 and 86%, respectively; disease-specific survival was 95 and 92%. The data suggest that older adolescents with high-risk HL require intensive protocols as primary therapy to secure optimal outcome