Glutamine dipeptide supplementation improves clinical responses in patients with diabetic foot syndrome

ABSTRACT The effect of glutamine dipeptide (GDP) supplementation in patients with diabetic foot syndrome was evaluated. A total of 22 patients took part in the study. GDP was supplied in 10 g sachets, and was dissolved in water immediately before use, with ingestion once a day, after lunch or after dinner (20 g/day) over a period of 30 days. Quantification of foot insensitive areas, oxidative stress, blood cytokines, and biochemical, hematological and toxicological parameters was performed before and after GDP supplementation. We observed an increase in blood levels of interferon-&#945; (P=0.023), interferon-&#947; (P=0.038), interleukin-4 (P=0.003), interleukin-6 (P=0.0025), interleukin-7 (P=0.028), interleukin-12 p40 (P=0.017), interleukin-13 (P=0.001), leukocytes (P=0.037), eosinophils (P=0.049), and typical lymphocytes (P<0.001) due to GDP administration. In addition, we observed a reduced number (P=0.048) of insensitive areas on the foot, and reduction (P=0.047) of fasting hyperglycemia. Patients also showed increased blood high density lipoprotein (P<0.01) and protein thiol groups (P=0.004). These favorable results were associated with the absence of renal and hepatic toxicity. These results are of clinical relevance, since supplementation with GDP over 30 days improved clinical responses in patients with diabetic foot syndrome

Water Vapor Vertical Profiles on Mars in Dust Storms Observed by TGO/NOMAD

It has been suggested that dust storms efficiently transport water vapor from the near‐surface to the middle atmosphere on Mars. Knowledge of the water vapor vertical profile during dust storms is important to understand water escape. During Martian Year 34, two dust storms occurred on Mars: a global dust storm (June to mid‐September 2018) and a regional storm (January 2019). Here we present water vapor vertical profiles in the periods of the two dust storms (Ls = 162–260° and Ls = 298–345°) from the solar occultation measurements by Nadir and Occultation for Mars Discovery (NOMAD) onboard ExoMars Trace Gas Orbiter (TGO). We show a significant increase of water vapor abundance in the middle atmosphere (40–100 km) during the global dust storm. The water enhancement rapidly occurs following the onset of the storm (Ls~190°) and has a peak at the most active period (Ls~200°). Water vapor reaches very high altitudes (up to 100 km) with a volume mixing ratio of ~50 ppm. The water vapor abundance in the middle atmosphere shows high values consistently at 60°S‐60°N at the growth phase of the dust storm (Ls = 195°–220°), and peaks at latitudes greater than 60°S at the decay phase (Ls = 220°–260°). This is explained by the seasonal change of meridional circulation: from equinoctial Hadley circulation (two cells) to the solstitial one (a single pole‐to‐pole cell). We also find a conspicuous increase of water vapor density in the middle atmosphere at the period of the regional dust storm (Ls = 322–327°), in particular at latitudes greater than 60°S

Performance with robotic surgery versus 3D-and 2D-laparoscopy during pancreatic and biliary anastomoses in a biotissue model: pooled analysis of two randomized trials

Background Robotic surgery may improve surgical performance during minimally invasive pancreatoduodenectomy as compared to 3D- and 2D-laparoscopy but comparative studies are lacking. This study assessed the impact of robotic surgery versus 3D- and 2D-laparoscopy on surgical performance and operative time using a standardized biotissue model for pancreatico- and hepatico-jejunostomy using pooled data from two randomized controlled crossover trials (RCTs). Methods Pooled analysis of data from two RCTs with 60 participants (36 surgeons, 24 residents) from 11 countries (December 2017-July 2019) was conducted. Each included participant completed two pancreatico- and two hepatico-jejunostomies in biotissue using 3D-robotic surgery, 3D-laparoscopy, or 2D-laparoscopy. Primary outcomes were the objective structured assessment of technical skills (OSATS: 12-60) rating, scored by observers blinded for 3D/2D and the operative time required to complete both anastomoses. Sensitivity analysis excluded participants with excess experience compared to others. Results A total of 220 anastomoses were completed (robotic 80, 3D-laparoscopy 70, 2D-laparoscopy 70). Participants in the robotic group had less surgical experience [median 1 (0-2) versus 6 years (4-12), p < 0.001], as compared to the laparoscopic group. Robotic surgery resulted in higher OSATS ratings (50, 43, 39 points, p = .021 and p < .001) and shorter operative time (56.5, 65.0, 81.5 min, p = .055 and p < .001), as compared to 3D- and 2D-laparoscopy, respectively, which remained in the sensitivity analysis. Conclusion In a pooled analysis of two RCTs in a biotissue model, robotic surgery resulted in better surgical performance scores and shorter operative time for biotissue pancreatic and biliary anastomoses, as compared to 3D- and 2D-laparoscopy.Surgical oncolog

Pose-informed deep learning method for SAR ATR

Synthetic aperture radar (SAR) images for automatic target classification (automatic target recognition (ATR)) have attracted significant interest as they can be acquired day and night under a wide range of weather conditions. However, SAR images can be time consuming to analyse, even for experts. ATR can alleviate this burden and deep learning is an attractive solution. A new deep learning Pose-informed architecture solution, that takes into account the impact of target orientation on the SAR image as the scatterers configuration changes, is proposed. The classification is achieved in two stages. First, the orientation of the target is determined using a Hough transform and a convolutional neural network (CNN). Then, classification is achieved with a CNN specifically trained on targets with similar orientations to the target under test. The networks are trained with translation and SAR-specific data augmentation. The proposed Pose-informed deep network architecture was successfully tested on the Military Ground Target Dataset (MGTD) and the Moving and Stationary Target Acquisition and Recognition (MSTAR) datasets. Results show the proposed solution outperformed standard AlexNets on the MGTD, MSTAR extended operating condition (EOC)1, EOC2 and standard operating condition (SOC)10 datasets with a score of 99.13% on the MSTAR SOC10

Searches for lepton-flavour-violating decays of the Higgs boson in s=13\sqrt{s}=13 TeV pp\mathit{pp} collisions with the ATLAS detector

This Letter presents direct searches for lepton flavour violation in Higgs boson decays, H → eτ and H → μτ , performed with the ATLAS detector at the LHC. The searches are based on a data sample of proton–proton collisions at a centre-of-mass energy √s = 13 TeV, corresponding to an integrated luminosity of 36.1 fb−1. No significant excess is observed above the expected background from Standard Model processes. The observed (median expected) 95% confidence-level upper limits on the leptonflavour-violating branching ratios are 0.47% (0.34+0.13−0.10%) and 0.28% (0.37+0.14−0.10%) for H → eτ and H → μτ , respectively.publishedVersio

Combination of searches for Higgs boson pairs in pp collisions at \sqrts = 13 TeV with the ATLAS detector

This letter presents a combination of searches for Higgs boson pair production using up to 36.1 fb(-1) of proton-proton collision data at a centre-of-mass energy root s = 13 TeV recorded with the ATLAS detector at the LHC. The combination is performed using six analyses searching for Higgs boson pairs decaying into the b (b) over barb (b) over bar, b (b) over barW(+)W(-), b (b) over bar tau(+)tau(-), W+W-W+W-, b (b) over bar gamma gamma and W+W-gamma gamma final states. Results are presented for non-resonant and resonant Higgs boson pair production modes. No statistically significant excess in data above the Standard Model predictions is found. The combined observed (expected) limit at 95% confidence level on the non-resonant Higgs boson pair production cross-section is 6.9 (10) times the predicted Standard Model cross-section. Limits are also set on the ratio (kappa(lambda)) of the Higgs boson self-coupling to its Standard Model value. This ratio is constrained at 95% confidence level in observation (expectation) to -5.0 &lt; kappa(lambda) &lt; 12.0 (-5.8 &lt; kappa(lambda) &lt; 12.0). In addition, limits are set on the production of narrow scalar resonances and spin-2 Kaluza-Klein Randall-Sundrum gravitons. Exclusion regions are also provided in the parameter space of the habemus Minimal Supersymmetric Standard Model and the Electroweak Singlet Model. For complete list of authors see http://dx.doi.org/10.1016/j.physletb.2019.135103</p

Comparison between simulated and observed LHC beam backgrounds in the ATLAS experiment at Ebeam =4 TeV

Results of dedicated Monte Carlo simulations of beam-induced background (BIB) in the ATLAS experiment at the Large Hadron Collider (LHC) are presented and compared with data recorded in 2012. During normal physics operation this background arises mainly from scattering of the 4 TeV protons on residual gas in the beam pipe. Methods of reconstructing the BIB signals in the ATLAS detector, developed and implemented in the simulation chain based on the \textscFluka Monte Carlo simulation package, are described. The interaction rates are determined from the residual gas pressure distribution in the LHC ring in order to set an absolute scale on the predicted rates of BIB so that they can be compared quantitatively with data. Through these comparisons the origins of the BIB leading to different observables in the ATLAS detectors are analysed. The level of agreement between simulation results and BIB measurements by ATLAS in 2012 demonstrates that a good understanding of the origin of BIB has been reached

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362