Vector meson spectral function and dilepton rate in an effective mean field model

We have studied the vector meson spectral function (VMSF) in a hot and dense medium within an effective QCD model namely the Nambu-Jona-Lasinio (NJL) and its Polyakov Loop extended version (PNJL) with and without the effect of isoscalar vector interaction (IVI). The effect of the IVI has been taken into account using the ring approximation. We obtained the dilepton production rate (DPR) using the VMSF and observed that at moderate temperature it is enhanced in the PNJL model as compared to the NJL and Born rate due to the suppression of color degrees of freedom.Comment: 5 pages, 7 figures, conference proceedings of the XXI DAE-BRNS HEP Symposium, IIT Guwahati, December 2014; to appear in 'Springer Proceedings in Physics Series

Clinical and radiological features that predict malignant transformation in cystic lesions of the pancreas: a retrospective case note review [version 2; peer review: 2 approved]

BACKGROUND: Pancreatic cystic lesions (PCL) are being detected with increasing frequency. Current methods of stratifying risk of malignant transformation are imperfect. This study aimed to determine the frequency of pancreatic malignancy in patients with PCL and define clinical and radiological features that predict malignant transformation in patients managed by surgery and/or surveillance. METHODS: A retrospective cohort of adults who were evaluated in a tertiary hepatopancreaticobiliary centre between January 2000 - December 2013 with a confirmed PCL and followed up for at least 5 years. All cystic lesions were discussed at a weekly multidisciplinary meeting. RESULTS: A retrospective cohort of adults who were evaluated in a tertiary hepatopancreaticobiliary centre between January 2000 - December 2013 with a confirmed PCL and followed up for at least 5 years. All cystic lesions were discussed at a weekly multidisciplinary meeting. CONCLUSION: The sensitivity of standard diagnostic tests leading to immediate surgery for high-risk PCL (malignant or mucinous) was 92% but with a specificity of just 5%. Surveillance of PCL without high-risk features within a multidisciplinary meeting was associated with a low incidence of cancer development, supporting the use of worrisome clinical and radiological features in the initial stratification of PCL

Voice-assisted Image Labelling for Endoscopic Ultrasound Classification using Neural Networks

Ultrasound imaging is a commonly used technology for visualising patient anatomy in real-time during diagnostic and therapeutic procedures. High operator dependency and low reproducibility make ultrasound imaging and interpretation challenging with a steep learning curve. Automatic image classification using deep learning has the potential to overcome some of these challenges by supporting ultrasound training in novices, as well as aiding ultrasound image interpretation in patient with complex pathology for more experienced practitioners. However, the use of deep learning methods requires a large amount of data in order to provide accurate results. Labelling large ultrasound datasets is a challenging task because labels are retrospectively assigned to 2D images without the 3D spatial context available in vivo or that would be inferred while visually tracking structures between frames during the procedure. In this work, we propose a multi-modal convolutional neural network (CNN) architecture that labels endoscopic ultrasound (EUS) images from raw verbal comments provided by a clinician during the procedure. We use a CNN composed of two branches, one for voice data and another for image data, which are joined to predict image labels from the spoken names of anatomical landmarks. The network was trained using recorded verbal comments from expert operators. Our results show a prediction accuracy of 76% at image level on a dataset with 5 different labels. We conclude that the addition of spoken commentaries can increase the performance of ultrasound image classification, and eliminate the burden of manually labelling large EUS datasets necessary for deep learning applications

Quine, Ontology, and Physicalism

Quine's views on ontology and naturalism are well-known but rarely considered in tandem. According to my interpretation the connection between them is vital. I read Quine as a global epistemic structuralist. Quine thought we only ever know objects qua solutions to puzzles about significant intersections in observations. Objects are always accessed descriptively, via their roles in our best theory. Quine's Kant lectures contain an early version of epistemic structuralism with uncharacteristic remarks about the mental. Here Quine embraces mitigated anomalous monism, allowing introspection and the availability in principle of full physical descriptions of the perceptual states which get science off the ground. Later versions abandon these ideas. My epistemic-structural interpretation explains why. I argue first-personal introspective access to mental states is incompatible with global epistemic structuralism

Bone mineral content after renal transplantation

Forearm bone mineral content (BMC), as evaluated by photonabsorption densitometry, was measured in 28 cadaver kidney donor recipients who entered the study 8 weeks postoperatively and were followed up for 18 months. BMC decreased signifiantly (p<0.05) but marginally in placebo-treated patients (n=14) (initial BMC 1.09±0.25 g/cm; final BMC 1.05±0.24). Fourteen patients were prophylactically given 1,25(OH)2vitamin D3 in a dose which avoided hypercalcemia and hypercalciuria (sim0.25 µg/day); under 1,25(OH)2 vitamin D3 prophylaxis a significant decrease of forearm BMC was observed no longer (initial BMC 0.94±0.21 g/cm; final BMC 0.95±0.21), but the difference between placebo and 1,25(OH)2 vitamin D3 narrowly missed statistical significance (p=0.066). It is concluded that the decrease of forearm BMC is negligible in transplant recipients with low steroid regimens. The data suggest a trend for prophylaxis with 1,25(OH)2 vitamin D3 to slightly ameliorate forearm (cortical) BMC loss

The NeuroDante Project: Neurometric measurements of participant’s reaction to literary auditory stimuli from dante’s “divina commedia”

Neurodante. Progetto di analisi neurometrica di alcuni brani della Commedi

Fluoroquinolones and isoniazid-resistant tuberculosis: implications for the 2018 WHO guidance.

INTRODUCTION: 2018 World Health Organization (WHO) guidelines for the treatment of isoniazid (H)-resistant (Hr) tuberculosis recommend a four-drug regimen: rifampicin (R), ethambutol (E), pyrazinamide (Z) and levofloxacin (Lfx), with or without H ([H]RZE-Lfx). This is used once Hr is known, such that patients complete 6 months of Lfx (≥6[H]RZE-6Lfx). This cohort study assessed the impact of fluoroquinolones (Fq) on treatment effectiveness, accounting for Hr mutations and degree of phenotypic resistance. METHODS: This was a retrospective cohort study of 626 Hr tuberculosis patients notified in London, 2009-2013. Regimens were described and logistic regression undertaken of the association between regimen and negative regimen-specific outcomes (broadly, death due to tuberculosis, treatment failure or disease recurrence). RESULTS: Of 594 individuals with regimen information, 330 (55.6%) were treated with (H)RfZE (Rf=rifamycins) and 211 (35.5%) with (H)RfZE-Fq. The median overall treatment period was 11.9 months and median Z duration 2.1 months. In a univariable logistic regression model comparing (H)RfZE with and without Fqs, there was no difference in the odds of a negative regimen-specific outcome (baseline (H)RfZE, cluster-specific odds ratio 1.05 (95% CI 0.60-1.82), p=0.87; cluster NHS trust). Results varied minimally in a multivariable model. This odds ratio dropped (0.57, 95% CI 0.14-2.28) when Hr genotype was included, but this analysis lacked power (p=0.42). CONCLUSIONS: In a high-income setting, we found a 12-month (H)RfZE regimen with a short Z duration to be similarly effective for Hr tuberculosis with or without a Fq. This regimen may result in fewer adverse events than the WHO recommendations

Automation of route identification and optimisation based on data-mining and chemical intuition.

Data-mining of Reaxys and network analysis of the combined literature and in-house reactions set were used to generate multiple possible reaction routes to convert a bio-waste feedstock, limonene, into a pharmaceutical API, paracetamol. The network analysis of data provides a rich knowledge-base for generation of the initial reaction screening and development programme. Based on the literature and the in-house data, an overall flowsheet for the conversion of limonene to paracetamol was proposed. Each individual reaction-separation step in the sequence was simulated as a combination of the continuous flow and batch steps. The linear model generation methodology allowed us to identify the reaction steps requiring further chemical optimisation. The generated model can be used for global optimisation and generation of environmental and other performance indicators, such as cost indicators. However, the identified further challenge is to automate model generation to evolve optimal multi-step chemical routes and optimal process configurations.This work was funded in part by the EPSRC project “Terpenebased Manufacturing for Sustainable Chemical Feedstocks” EP/K014889. The PhD scholarship of WC is funded by the EPSRC Doctoral Training Centre in Sustainable Chemical Technologies (EP/G03768X/1). We gratefully acknowledge collaboration with RELX Intellectual Properties SA and their technical support, which enabled us to mine REAXYS. PMJ is grateful to Peterhouse and the Cambridge Trust for PhD scholarships

Radiocarbon dating of methane and carbon dioxide evaded from a temperate peatland stream

Streams draining peatlands export large quantities of carbon in different chemical forms and are an important part of the carbon cycle. Radiocarbon (14C) analysis/dating provides unique information on the source and rate that carbon is cycled through ecosystems, as has recently been demonstrated at the air-water interface through analysis of carbon dioxide (CO2) lost from peatland streams by evasion (degassing). Peatland streams also have the potential to release large amounts of methane (CH4) and, though 14C analysis of CH4 emitted by ebullition (bubbling) has been previously reported, diffusive emissions have not. We describe methods that enable the 14C analysis of CH4 evaded from peatland streams. Using these methods, we investigated the 14C age and stable carbon isotope composition of both CH4 and CO2 evaded from a small peatland stream draining a temperate raised mire. Methane was aged between 1617-1987 years BP, and was much older than CO2 which had an age range of 303-521 years BP. Isotope mass balance modelling of the results indicated that the CO2 and CH4 evaded from the stream were derived from different source areas, with most evaded CO2 originating from younger layers located nearer the peat surface compared to CH4. The study demonstrates the insight that can be gained into peatland carbon cycling from a methodological development which enables dual isotope (14C and 13C) analysis of both CH4 and CO2 collected at the same time and in the same way

Association between canine leishmaniosis and Ehrlichia canis co-infection: a prospective case-control study

Abstract Background In the Mediterranean basin, Leishmania infantum is a major cause of disease in dogs, which are frequently co-infected with other vector-borne pathogens (VBP). However, the associations between dogs with clinical leishmaniosis (ClinL) and VBP co-infections have not been studied. We assessed the risk of VBP infections in dogs with ClinL and healthy controls. Methods We conducted a prospective case-control study of dogs with ClinL (positive qPCR and ELISA antibody for L. infantum on peripheral blood) and clinically healthy, ideally breed-, sex- and age-matched, control dogs (negative qPCR and ELISA antibody for L. infantum on peripheral blood) from Paphos, Cyprus. We obtained demographic data and all dogs underwent PCR on EDTA-blood extracted DNA for haemoplasma species, Ehrlichia/Anaplasma spp., Babesia spp., and Hepatozoon spp., with DNA sequencing to identify infecting species. We used logistic regression analysis and structural equation modelling (SEM) to evaluate the risk of VBP infections between ClinL cases and controls. Results From the 50 enrolled dogs with ClinL, DNA was detected in 24 (48%) for Hepatozoon spp., 14 (28%) for Mycoplasma haemocanis, 6 (12%) for Ehrlichia canis and 2 (4%) for Anaplasma platys. In the 92 enrolled control dogs, DNA was detected in 41 (45%) for Hepatozoon spp., 18 (20%) for M. haemocanis, 1 (1%) for E. canis and 3 (3%) for A. platys. No Babesia spp. or “Candidatus Mycoplasma haematoparvum” DNA was detected in any dog. No statistical differences were found between the ClinL and controls regarding age, sex, breed, lifestyle and use of ectoparasitic prevention. A significant association between ClinL and E. canis infection (OR = 12.4, 95% CI: 1.5–106.0, P = 0.022) was found compared to controls by multivariate logistic regression. This association was confirmed using SEM, which further identified that younger dogs were more likely to be infected with each of Hepatozoon spp. and M. haemocanis, and dogs with Hepatozoon spp. were more likely to be co-infected with M. haemocanis. Conclusions Dogs with ClinL are at a higher risk of co-infection with E. canis than clinically healthy dogs. We recommend that dogs diagnosed with ClinL should be tested for E. canis co-infection using PCR