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Background Microscopic colitis (MC) is a common cause of chronic watery diarrhea. Biopsies with characteristic histological features are crucial for establishing the diagnosis. The two main subtypes are collagenous colitis (CC) and lymphocytic colitis (LC) but incomplete forms exist. The disease course remains unpredictable varying from spontaneous remission to a relapsing course. Aim To identify possible histological predictors of course of disease. Methods Sixty patients from the European prospective MC registry (PRO-MC Collaboration) were included. Digitised histological slides stained with CD3 and Van Gieson were available for all patients. Total cell density and proportion of CD3 positive lymphocytes in lamina propria and surface epithelium were estimated by automated image analysis, and measurement of the subepithelial collagenous band was performed. Histopathological features were correlated to the number of daily stools and daily watery stools at time of endoscopy and at baseline as well as the clinical disease course (quiescent, achieved remission after treatment, relapsing or chronic active) at 1-year follow-up. Results Neither total cell density in lamina propria, proportion of CD3 positive lymphocytes in lamina propria or surface epithelium, or thickness of collagenous band showed significant correlation to the number of daily stools or daily watery stools at any point of time. None of the assessed histological parameters at initial diagnosis were able to predict clinical disease course at 1-year follow-up. Conclusions Our data indicate that the evaluated histological parameters were neither markers of disease activity at the time of diagnosis nor predictors of disease course.

Introduction Microscopic colitis is a chronic inflammatory bowel disease characterised by normal or almost normal endoscopic appearance of the colon, chronic watery, non-bloody diarrhoea and distinct histological abnormalities, which identify three histological subtypes, the collagenous colitis, the lymphocytic colitis and the incomplete microscopic colitis. With ongoing uncertainties and new developments in the clinical management of microscopic colitis, there is a need for evidence-based guidelines to improve the medical care of patients suffering from this disorder. Methods Guidelines were developed by members from the European Microscopic Colitis Group and United European Gastroenterology in accordance with the Appraisal of Guidelines for Research and Evaluation II instrument. Following a systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation methodology was used to assess the certainty of the evidence. Statements and recommendations were developed by working groups consisting of gastroenterologists, pathologists and basic scientists, and voted upon using the Delphi method. Results These guidelines provide information on epidemiology and risk factors of microscopic colitis, as well as evidence-based statements and recommendations on diagnostic criteria and treatment options, including oral budesonide, bile acid binders, immunomodulators and biologics. Recommendations on the clinical management of microscopic colitis are provided based on evidence, expert opinion and best clinical practice. Conclusion These guidelines may support clinicians worldwide to improve the clinical management of patients with microscopic colitis. Funding Agencies|UEG Activity Grant

SummaryBackground Bile acid diarrhoea is underdiagnosed and better diagnostic tests are needed. Fasting serum fibroblast growth factor-19 (FGF19) has insufficient diagnostic value, but this may be improved by stimulation. Aim To explore if an impaired FGF19 response identifies primary bile acid diarrhoea. Methods Eight patients with primary bile acid diarrhoea and eight healthy volunteers ingested (i) a meal plus 1250 mg chenodeoxycholic acid (CDCA), (ii) 1250 mg CDCA or (iii) the meal. Blood was sampled at fasting and repeatedly after stimulation. We analysed FGF19 by enzyme-linked immunosorbent assay and bile acids including 7α-hydroxy-4-cholesten-3-one by liquid chromatography-tandem mass spectrometry. Results Stimulation with the meal plus CDCA increased median FGF19 in healthy volunteers from fasting 62 pg/mL [interquartile range (IQR): 41–138] to 99 pg/mL (IQR: 67–147; P = 0.012) after 90 min and peaked after 150 min at 313 pg/mL (IQR: 54–512). This response was impaired in primary bile acid diarrhoea patients [fasting 56 pg/mL (IQR: 42–79); 90 min: 48 pg/mL [IQR: 37–63); 150 min: 57 pg/mL (48–198)]. Receiver operating characteristics (ROCAUC) for fasting FGF19 was 0.55 (P = 0.75) and at 90 min 0.84 (P = 0.02). The difference in FGF19 from fasting to 90 min after the meal plus CDCA separated the groups (ROCAUC 1.0; P = 0.001). 7α-hydroxy-4-cholesten-3-one was elevated in primary bile acid diarrhoea (P = 0.038) and not significantly affected by stimulation. Conclusions The FGF19 response following chenodeoxycholic acid plus meal is impaired in primary bile acid diarrhoea. This may provide a biochemical diagnostic test.

When predicting the chemical composition of food samples from near-infrared spectroscopy using partial least squares regression, deep knowledge of the origin of the information is not present. We are aiming at opening a Pandora's box of how the prediction of protein proceeds in a unique set of chemically diverse barley mutant samples. An external validation of the sources of co-variation in nature that are exploited by chemometric models would give a framework for manipulating the deciding information to make expensive calibration more economical. The barley samples were supplemented by two designed data sets: one mirroring the coarse composition of the barley samples by mixing six main chemical components and one set where the biological covariance between the six chemical components had been reduced. The three original data sets give remarkably comparable prediction models, albeit their regression coefficients are quite different. The origin of the prediction ability of the data is elucidated by splitting the natural barley samples into two parts: one based on simulated biology extracted from a set of chemical mixtures, and the residual after the chemistry has been removed from the raw data. As much as 98.1% of the spectral information in the natural barley data is explained through the simulated biology, leaving as little as 1.9% of the spectral information for the unexplained biological variation and noise. However, unexplained biological variation still gives a fair prediction of protein (RMSECV = 1.23 and r2 = 0.80, compared with RMSECV = 0.46 and r2 = 0.97 for the natural data), and it gives a clear principal component analysis separation of the three genotype classes. The results were interpreted by conducting spectral inspection on the origin of the unique covariate patterns appearing in self-organised biological systems that should motivate researchers and industry to investigate the compressive effect that the model has on the essential deterministic biological data. Copyright © 2012 John Wiley & Sons, Ltd.

Nielsen OH, Seidelin JB, Munck LK, Rogler G (Herlev Hospital, University of Copenhagen, Copenhagen; Koge Hospital, University of Copenhagen, Copenhagen, Denmark; and University Hospital of Zurich, Zurich, Switzerland). Use of biological molecules in the treatment of inflammatory bowel disease (Review). J Intern Med 2011; 270: 15–28. The introduction of biological agents (i.e. antitumour necrosis factor-α and anti-integrin treatments) for the treatment of inflammatory bowel disease (IBD) [i.e. Crohn’s disease (CD) and ulcerative colitis] has led to a substantial change in the treatment algorithms and guidelines, especially in CD. However, many questions still remain about the true efficacy and the best treatment regimens. Thus, a need for further treatment options still exists as up to 40% of IBD patients treated with the presently available biologicals do not have positive clinical responses. Better patient selection might maximize the clinical benefit for those in most need of an effective therapy to avoid disabling disease whilst also minimizing the complications associated with therapy. Further, the ‘trough-level strategy’ may help clinicians to optimize therapy and to avoid loss of response and/or immunogenicity. The idea behind this dosage regimen is that correct dosing must ensure that the patient’s lowest level of drug concentration (i.e. the trough level) occurring just before the next drug administration is high enough for the full effect to be seen. Controversy continues regarding the appropriate use of biologicals; therefore, in this review, we focus on considerations that might lead to a more rational strategy for antitumour necrosis factor-α agents in IBD, emphasizing the situations in which the risks may outweigh the benefits. Finally, the need for an appropriate strategy for stopping biological treatment is discussed.

An extension of chemometric theory was experimentally explored to explain the physiochemical basis of the very high efficiency of soft modelling of data from nature. Soft modelling in self-organisation was interpreted by studying the unique chemical patterns of mutants in an isogenic barley model on endosperm development. Extremely reproducible, differential Near Infrared (NIR) spectral patterns specifically overviewed the effect on cell composition of each mutant cause. Extended Canonical Variates Analysis (ECVA) classified spectra in wild type, starch and protein mutants. The spectra were interpreted by chemometric data analysis and by pattern inspection to morphological, genetic, molecular and chemical information. Deterministic chemical reactions were defined in the glucan pathway. A drastic mutation in a gene controlling the starch/β-glucan composition changed water activity that introduced a diffusive, stochastic effect on the catalysis of all active enzymes. 'Decision making' in self-organisation is autonomous and performed by the soft modelling of the chemical deterministic and stochastic reactions in the endosperm cell as a whole. Uncertainty in the analysis of endosperm emergence was experimentally delimited as the 'indeterminacy' in local molecular path modelling 'bottom up' and the 'irreducibility' of the phenomenological NIR spectra 'top down'. The experiment confirmed Ilya Prigogine's interpretation of self-organisation by his dynamic computer model programmed with a self-modeled non-local extension of quantum mechanics (QM). The significance of self-organisation explained by Prigogine here interpreted as physiochemical soft modelling introduces a paradigm shift in macroscopic science that forwards a major argument for soft mathematical modelling and chemometrics to obtain full scientific legitimacy.

A preliminary investigation of fish oils demonstrates that fluorescence excitation-emission landscapes evaluated by three-way chemometric methods may be a candidate for an inexpensive screening method to indicate the level of contamination by dioxins and PCBs, which are normally analysed by expensive and time-consuming physicochemical separation techniques such as GC-MS. Fluorescence landscapes of 88 fish oils have been investigated and showed great variation due to species, season and treatment, depicting a variation in natural fluorescent components. The fluorescence landscapes were analysed by PARAFAC. Samples with similar fluorescence fingerprints were selected from a PARAFAC score plot, and local significant prediction models with PARAFAC/MLR, N-PLSR and PLSR were established with correlation coefficients in the range from r = 0.69 (n = 10) to r = 0.97 (n = 75) for dioxin and of r = 0.92 (n = 12) for PCB. Application of PARAFAC/MLR and N-PLSR to fluorescence landscapes of fish oils resulted in local regression models for dioxin determination with prediction errors below 1 ng kg -1 , which is comparable to the reference method. In the PARAFAC model, two of the modes give the excitation and emission spectra of the pure underlying fluorophores, while the third mode gives their individual concentrations. Excitation and emission optima for three or four PARAFAC components in each data set were identified, representing both positive and negative (quenching) correlation components. It is hypothesized that the quenching correlation may be effected by the joint contribution of chlorinated organic compounds in the fish oil, including dioxins and PCBs. Other explanations for the results are discussed.

Prediction of the content of water, oil, and protein in rape and mustard seed was examined by a combination of low-field 1H nuclear magnetic resonance (LF-NMR) and chemometrics, enabling utilization of the entire relaxation curves in the data evaluation. To increase the range of relative contents, the untreated seeds were wetted and dried; each treatment was followed by NMR analysis. The chemometric results are compared to traditional evoluation by multiexponential fitting of the relaxation curves. For this purpose a new jackKnife validation procedure was developed to evaluate the number of exponential components objectively. Classification of the two kinds of seeds was easily performed by LN-NMR. Partial least squares regression to oil content in untreated rape and mustard seed yielded models with correlation coefficients of r=0.88 and 0.89 with root mean square error of cross-validation (RMSECV) of 0.84 and 0.45, respectively. The rapeseed model was based on one component, wheres the mustard seed model was based on two components. If the seeds were dried, the predictive performance improved to r=0.98 and RMSECV=0.38 for rapeseed and to r=0.95 and RMSECV=0.38 for mustard seed. Upon drying, prediction of protein content in mustard seed improved, whereas the prediction of protein for rapeseed deteriorated. Global models, including the combination of untreated, wet, and dry seeds, all resulted in a robust and good predictive performance with RMSECV in the range 0.8–1.3% to water, oil, and protein content. It was demonstrated that drying the seeds to simultaneously determine water and oil content was not necessary when chemometrics was applied on the relaxation curves.

Rapeseed meals derived from heat-treated seed samples representing a large variation in glucosinolate content, which was principally due to genetic differences, were fed to mice as the only protein source. A glucosinolate content corresponding to a level of more than 1 mg potential isothiocyanates and oxazolidinethiones per g of diet depressed the 11-day growth of mice as well as feed consumption and protein efficiency ratios.