Species-specific and pathotype-specific binding of bacteria to zymogen granule membrane glycoprotein 2 (GP2)

With interest we read the paper by Juste et al 1 proposing the amount of zymogen-granule membrane glycoprotein 2 (GP2) on the surface of intestinal bacteria as a Crohn\u27s disease (CD) marker. Indeed, a decreased GP2 level was found on microbes in patients with CD as compared to those of healthy controls. GP2 is a homologue to the urinary Tamm–Horsefall protein demonstrating an antimicrobial function by binding type 1-fimbriated uropathogenic Escherichia coli (UPEC). Likewise, GP2 seems to interact with intestinal bacteria as a specific receptor of bacterial type-1 fimbriae (FimH) on intestinal microfold cells that are partaking in immune responses against such microbes.2 GP2 is overexpressed in the inflamed intestine of patients with CD and has an immunomodulating role in innate and acquired immune responses.3 ,4Interestingly, GP2 was identified as autoantigen of pancreatic antibodies in CD.4 Altogether, these findings indicate two major GP2 sources (pancreatic/intestinal) and support a role for GP2 in the interaction between the immune system and intestinal microbiota.3 Thus, loss of tolerance to GP2 could play a role in CD\u27s pathophysiology supposed to be exacerbated by preceding intestinal infections. In general, the findings by Juste et al 1 may be explained by a lower pancreatic GP2 secretion, an impaired GP2 binding to bacteria, or by a higher prevalence of bacteria with poor or no GP2 binding in patients with CD

Screening and engineering of colour centres in diamond

We present a high throughput and systematic method for the screening of colour centres in diamond with the aim of searching for and reproducibly creating new optical centres down to the single defect level, potentially of interest for a wide range of diamond-based quantum applications. The screening method presented here should, moreover, help to identify some already indexed defects among hundreds in diamond (Zaitsev 2001 Optical Properties of Diamond (Berlin: Springer)) but also some promising defects of a still unknown nature, such as the recently discovered ST1 centre (Lee et al 2013 Nat. Nanotechnol. 8 487; John et al 2017 New J. Phys. 19 053008). We use ion implantation in a systematic manner to implant several chemical elements. Ion implantation has the advantage of addressing single atoms inside the bulk with defined depth and high lateral resolution, but the disadvantage of producing intrinsic defects. The implanted samples are annealed in vacuum at different temperatures (between 600 degrees C and 1600 degrees C with 200 degrees C steps) and fully characterised at each step in order to follow the evolution of the defects: formation, dissociation, diffusion, re-formation and charge state, at the ensemble level and, if possible, at the single centre level. We review the unavoidable ion implantation defects (such as the GR1 and 3H centres), discuss ion channeling and thermal annealing and estimate the diffusion of the vacancies, nitrogen and hydrogen. We use different characterisation methods best suited for our study (from widefield fluorescence down to subdiffraction optical imaging of single centres) and discuss reproducibility issues due to diamond and defect inhomogeneities. Nitrogen is also implanted for reference, taking advantage of the considerable knowledge on NV centres as a versatile sensor in order to retrieve or deduce the conditions and local environment in which the different implanted chemical elements are embedded. We show here the preliminary promising results of a long-term study and focus on the elements O, Mg, Ca, F and P from which fluorescent centres were found.Peer reviewe

Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model

Summary Background Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive, fatal motor neuron disease with a variable natural history. There are no accurate models that predict the disease course and outcomes, which complicates risk assessment and counselling for individual patients, stratification of patients for trials, and timing of interventions. We therefore aimed to develop and validate a model for predicting a composite survival endpoint for individual patients with ALS. Methods We obtained data for patients from 14 specialised ALS centres (each one designated as a cohort) in Belgium, France, the Netherlands, Germany, Ireland, Italy, Portugal, Switzerland, and the UK. All patients were diagnosed in the centres after excluding other diagnoses and classified according to revised El Escorial criteria. We assessed 16 patient characteristics as potential predictors of a composite survival outcome (time between onset of symptoms and non-invasive ventilation for more than 23 h per day, tracheostomy, or death) and applied backward elimination with bootstrapping in the largest population-based dataset for predictor selection. Data were gathered on the day of diagnosis or as soon as possible thereafter. Predictors that were selected in more than 70% of the bootstrap resamples were used to develop a multivariable Royston-Parmar model for predicting the composite survival outcome in individual patients. We assessed the generalisability of the model by estimating heterogeneity of predictive accuracy across external populations (ie, populations not used to develop the model) using internal–external cross-validation, and quantified the discrimination using the concordance (c) statistic (area under the receiver operator characteristic curve) and calibration using a calibration slope. Findings Data were collected between Jan 1, 1992, and Sept 22, 2016 (the largest data-set included data from 1936 patients). The median follow-up time was 97·5 months (IQR 52·9–168·5). Eight candidate predictors entered the prediction model: bulbar versus non-bulbar onset (univariable hazard ratio [HR] 1·71, 95% CI 1·63–1·79), age at onset (1·03, 1·03–1·03), definite versus probable or possible ALS (1·47, 1·39–1·55), diagnostic delay (0·52, 0·51–0·53), forced vital capacity (HR 0·99, 0·99–0·99), progression rate (6·33, 5·92–6·76), frontotemporal dementia (1·34, 1·20–1·50), and presence of a C9orf72 repeat expansion (1·45, 1·31–1·61), all p<0·0001. The c statistic for external predictive accuracy of the model was 0·78 (95% CI 0·77–0·80; 95% prediction interval [PI] 0·74–0·82) and the calibration slope was 1·01 (95% CI 0·95–1·07; 95% PI 0·83–1·18). The model was used to define five groups with distinct median predicted (SE) and observed (SE) times in months from symptom onset to the composite survival outcome: very short 17·7 (0·20), 16·5 (0·23); short 25·3 (0·06), 25·2 (0·35); intermediate 32·2 (0·09), 32·8 (0·46); long 43·7 (0·21), 44·6 (0·74); and very long 91·0 (1·84), 85·6 (1·96). Interpretation We have developed an externally validated model to predict survival without tracheostomy and non-invasive ventilation for more than 23 h per day in European patients with ALS. This model could be applied to individualised patient management, counselling, and future trial design, but to maximise the benefit and prevent harm it is intended to be used by medical doctors only. Funding Netherlands ALS Foundation

“What’s measured gets done”: a call for a European semester for cancer to improve cancer outcomes in Central and Southeastern Europe

Abstract Cancer mortality varies widely across Europe, and survival depends on where you live. In particular, the inequality between countries in Central and South-Eastern Europe (CEE) and Western Europe (WE) is striking. The COVID-19 pandemic has brought existing inequalities into sharp focus, and the economic disruption it has caused threatens to deepen them. The Central European Cooperative Oncology Group (CECOG) has created a platform with the aim to reduce health inequalities and to improve patient access to cancer care. The subject of discussion is the value of new treatments to create willingness to invest in improving cancer outcomes while managing the budget. The platform includes various stakeholders as scientific leaders, policy makers, payers, patients and industry

Species-specific and pathotype-specific binding of bacteria to zymogen granule membrane glycoprotein 2 (GP2)

With interest we read the paper by Juste et al 1 proposing the amount of zymogen-granule membrane glycoprotein 2 (GP2) on the surface of intestinal bacteria as a Crohn's disease (CD) marker. Indeed, a decreased GP2 level was found on microbes in patients with CD as compared to those of healthy controls. GP2 is a homologue to the urinary Tamm–Horsefall protein demonstrating an antimicrobial function by binding type 1-fimbriated uropathogenic Escherichia coli (UPEC). Likewise, GP2 seems to interact with intestinal bacteria as a specific receptor of bacterial type-1 fimbriae (FimH) on intestinal microfold cells that are partaking in immune responses against such microbes.2 GP2 is overexpressed in the inflamed intestine of patients with CD and has an immunomodulating role in innate and acquired immune responses.3 ,4Interestingly, GP2 was identified as autoantigen of pancreatic antibodies in CD.4 Altogether, these findings indicate two major GP2 sources (pancreatic/intestinal) and support a role for GP2 in the interaction between the immune system and intestinal microbiota.3 Thus, loss of tolerance to GP2 could play a role in CD's pathophysiology supposed to be exacerbated by preceding intestinal infections. In general, the findings by Juste et al 1 may be explained by a lower pancreatic GP2 secretion, an impaired GP2 binding to bacteria, or by a higher prevalence of bacteria with poor or no GP2 binding in patients with CD.This article is from Gut 64 (2015): 517–519, doi:10.1136/gutjnl-2014-307854. Posted with permission.</p