BACKGROUND:Bladder cancer is the 11th most common cancer in the United Kingdom, with approximately 10,500 new cases annually. Diagnosis and surveillance typically involve cystoscopy, an expensive, time-consuming, and uncomfortable procedure which has encouraged efforts to identify biomarkers, particularly in urine, given its direct contact with malignant tissue. METHODS:Urine collected from 100 participants (50 bladder cancer patients, 50 controls) was subjected to solvent extraction followed by gas chromatography-mass spectrometry (GC-MS) to determine potential volatile and semi-volatile biomarkers. The results were analysed using classical univariate statistics and machine learning methods. Five machine learning algorithms were evaluated, with recursive feature elimination (RFE) identifying optimal biomarker panels. RESULTS:Machine learning with XGBoost achieved area under the receiver operating characteristic curve (AUROC) of 0.869 (95% CI: 0.740-0.988), representing a significant improvement over the classical statistical approach (AUROC 0.752). An 8-metabolite panel achieved balanced sensitivity and specificity of 85%, or 95% sensitivity with 70% specificity when optimised for screening. CONCLUSIONS:The findings indicate that solvent extraction of urine shows promise for isolating putative biomarkers of bladder cancer. Employing machine learning achieved diagnostic accuracy potentially suitable for clinical deployment as a non-invasive bladder cancer detection tool.

Crohn’s disease (CD) is a chronic inflammatory disorder with increasing incidence in children. Dysbiosis of the gut microbiome is characteristic of CD but the underlying pathogenic mechanisms are uncertain. There is a need to decipher how microbial communities are structured to better understand this complex disease. Ecological analytical approaches including community assembly processes based on the null model and dynamic core microbiome analyses were applied to the stool microbiome and mycobiome of an inception cohort of paediatric inflammatory bowel disease cases and matched controls. CD bacterial and fungal signatures were less homogeneous than controls with CD diagnosis and severity of disease accounting for the most variation. Stochastic processes were identified as more common in structuring the CD microbiome than controls. Together with a reduction in alpha diversity in the microbiome, this indicates a less stable environment allowing opportunistic species to colonise; key CD associated taxa were Fusobacterium, Aggregatibacter and Clavispora-Candida. Integration of omics demonstrated volatile metabolites (including phenol and propan-1-ol) and functional genomic pathways positively correlated with identified key CD bacterial taxa and a biochemical marker of inflammation. A reduction in disease activity, following CD treatment, was associated with a reduction in stochasticity and in some CD-associated taxa alongside a shift in the core microbiome towards the control profile. Our study has identified mechanisms that underpin variability in CD microbiota during disease. Further longitudinal studies are required to investigate how microbial community structure changes with relapse, remission and the implications for novel therapies.

INTRODUCTION:Specific foods are associated with abdominal bloating, which can significantly affect quality of life. To identify responders to fiber-induced bloating and the mechanisms underpinning clinical and microbial responses. METHODS:Double-blind, placebo-controlled, randomized, 2-period, 2-challenge crossover trial in 41 individuals with functional bloating. Participants were randomized to 8 g/d of fructan or α-galacto-oligosaccharides (α-GOS) for 7 days with a 21-day washout. Clinical, nutritional, microbial (shotgun sequencing, metatranscriptomics), and fermentation (short-chain fatty acids, volatile organic compounds, breath hydrogen) profiles were characterized before each challenge to identify factors predicting response and after the challenge to elucidate mechanisms underpinning food-induced bloating. RESULTS:Thirty-nine participants completed both challenges (39 fructan, 40 α-GOS). Overall, 7 (7/39, 17.9%) participants were fructan responders and 8 (8/40, 20%) were α-GOS responders (experienced fiber-related symptom induction). Clinical metrics indicative of bloating distinguished responders and nonresponders to both challenges, including greater abdominal girth (fructan, P = 0.009; α-GOS, P = 0.030). α-GOS responders had higher breath hydrogen (H 2 ) prechallenge than α-GOS nonresponders ( P = 0.011). Trends were identified within metagenomic and metatranscriptomic gut microbial analyses, with higher carbohydrate active enzyme (CAZyme) diversity in fructan responders (prechallenge, adjusted P -value ( P adj) = 0.024; postchallenge, P adj = 0.042) and greater increase in gene expression for gamma-aminobutyric acid (GABA) degradation in α-GOS responders ( P adj = 0.041). DISCUSSION:A higher burden of GI symptoms predicts clinical response to fermentable fibers in functional bloating, while for α-GOS, higher repeated fasting breath H 2 is also a predictor. Gut microbiome function and fermentation is associated with functional bloating; however, further investigations are required to draw firm conclusions for the microbial influence in this interplay.

Bone resorption involves dissolution of minerals and enzymatic degradation of bone matrix. The primary enzyme is cathepsin K but other proteases including matrix metalloproteinases are involved. Some cathepsin K cleavage products have been partially identified, including cross-linked telopeptides of type I collagen. Here, we aimed to characterize the entire complement of bone breakdown products resulting from osteoclast action under controlled conditions in vitro. We analyzed extracellular media from human osteoclasts cultured on dentin substrates, using untargeted liquid chromatography mass spectrometry. We discovered 22 breakdown products resulting from osteoclastic action. These products were peptide fragment sequences that mapped to various collagen proteins present in bone and dentin. Nine peptide fragments mapped exclusively to collagen I alpha-1 chain (COL1A1), the most abundant protein in bone. We subsequently detected 21 of the fragment products, initially observed in vitro, in human serum and/or urine. Consistent positive correlations were observed between the COL1A1-specific peptide fragments and established bone biochemical markers in serum and urine. Ten urine fragments and two serum fragments markedly increased (p < .05) following total hip arthroplasty, capturing the transient local peri-prosthetic osteolysis observed in these patients (serum, n = 86 patients; urine, n = 83 patients). Among these candidate osteolytic markers, four (two COL1A1-specific products) showed decreases from baseline (p < .05) in patients on denosumab (n = 10 patients). Additionally, two fragment peptides were higher (p < .05, fold change >2) in urine from patients with bone metastasis (24 out of 112) among a lung cancer cohort. The range of collagen peptide fragments we discovered as a direct result of osteoclast activity indicates a complexity of bone resorption pathways not previously known, extending beyond the known proteolytic cleavage events in bone collagen proteins. Monitoring biofluid concentrations of these novel bone markers has the potential to capture multiple pathways of bone resorption activity beyond the existing assays based on cathepsin K.

AIMS:Eighty percent patients develop gastrointestinal (GI) symptoms during pelvic radiotherapy. The triggering event is a known enabling identification of pathophysiological changes. The focus of this study was feasibility (identification, recruitment, and retention), however, exploratory microbiome and metabolome analyses were performed. MATERIALS AND METHODS:Patients undergoing pelvic radiotherapy underwent faecal sampling (baseline, week 4, and 6 months), with assessment of GI toxicity using the Imflammatory Bowel Disease Questionnaire (IBDQ) bowel (IBDQB) subset. Participants were split into 2 groups based on IBDQB at week-4. Exploratory analysis was performed to identify differences in metabolome (gas chromatography-mass spectrometry) and microbiome (16s rRNA sequencing). RESULTS:Two hundred twenty-seven patients were screened, 69 were approached, and 17 were recruited over 18 months (mean age: 61.6 ± 15.3 years; 14 female; 1 withdrawal). Metabolome analysis showed lower heptanal and octanal in baseline samples of patients with higher GI toxicity; lower (methyltrisulfanyl)methane in week-4 samples of patients with higher GI toxicity; and higher butanoic acid and benzaldehyde in month 6 samples in patients with higher GI toxicity. Whole-group microbiome analysis showed a trend towards decreased alpha diversity at 4 weeks; no differences in beta diversity; and a trend towards increase in Lachnoclostridium and decrease in Ruminococcaceae Incertae sedis at week 4. Microbiome analysis split by GI toxicity showed lower alpha diversity for the high GI toxicity group (each timepoint); no significant difference in beta diversity between groups; more genera differentially abundant between the GI toxicity groups at 4 weeks, than at other timepoints. CONCLUSION:Recruitment was lower than anticipated. Attrition was low. Exploratory analysis suggests heptanal and octanal may have a role as a biomarker for GI toxicity, and lower alpha diversity may predict GI toxicity, with Lachnoclostridium and Ruminococcaceae Incertae sedis as bacteria of interest.

Fecal volatile organic compounds (VOCs) offer insights into gut microbiota function that may drive the pathogenesis of ulcerative colitis (UC). This cross-sectional study aimed to compare dietary intake and VOC patterns in UC patients with an ileoanal pouch compared to those with an intact colon. Seven-day food records and fecal samples were collected from UC patients with an intact colon (n = 28) or an ileoanal pouch (n = 11). Fecal VOC profiles were analyzed using gas chromatography-mass spectrometry. Dietary intake in both groups was largely similar. The mean Jaccard similarity index of VOC was 0.55 (95% CI:0.53, 0.56) in the pouch compared with 0.48 (0.47, 0.49) in the colon group (p < 0.01). A lower proportion of VOC classes was detected in the pouch, including sulfide (9% vs. 57%; p < 0.01), branched-chain fatty acids (BCFAs; 45%-64% vs. 93%-96%; p < 0.01), and ketones (45%-64% vs. 93%-96%; p < 0.01), along with a higher proportion of butyric acid (91% vs. 29%; p < 0.001). Unrelated to diet, VOC profiles show less functional diversity, reduced protein and greater carbohydrate fermentation, and altered production of secondary metabolites in the UC-pouch compared with the intact colon. These differences in the metabolic environment of the gut microbiota provide insights into pathogenesis and suggest that microbial-targeted interventions should be tailored accordingly.

Abstract Background Accurately recognizing that a person may be dying is central to improving their experience of care at the end-of-life. However, predicting dying is frequently inaccurate and often occurs only hours or a few days before death. Methods We performed urinary metabolomics analysis on patients with lung cancer to create a metabolite model to predict dying over the last 30 days of life. Results Here we show a model, using only 7 metabolites, has excellent accuracy in the Training cohort n = 112 (AUC = 0·85, 0·85, 0·88 and 0·86 on days 5, 10, 20 and 30) and Validation cohort n = 49 (AUC = 0·86, 0·83, 0·90, 0·86 on days 5, 10, 20 and 30). These results are more accurate than existing validated prognostic tools, and uniquely give accurate predictions over a range of time points in the last 30 days of life. Additionally, we present changes in 125 metabolites during the final four weeks of life, with the majority exhibiting statistically significant changes within the last week before death. Conclusions These metabolites identified offer insights into previously undocumented pathways involved in or affected by the dying process. They not only imply cancer’s influence on the body but also illustrate the dying process. Given the similar dying trajectory observed in individuals with cancer, our findings likely apply to other cancer types. Prognostic tests, based on the metabolites we identified, could aid clinicians in the early recognition of people who may be dying and thereby influence clinical practice and improve the care of dying patients.

Abstract Background As a dietary approach to reducing inflammation in ulcerative colitis (UC), the 4-SURE diet was designed to correct pathogenic alterations of excessive protein fermentation and hydrogen sulphide (H2S) production in the distal colon. Specific dietary objectives were achieved (Day et al,J Nutr 2022;152:1690) but it is uncertain whether mechanistic objectives could be achieved with 8 weeks of diet. Therefore, we aimed to perform a deep functional analysis (microbial and metabolomic) of the faeces. Methods Faecal samples of 28 adults with mild-moderately active UC were collected at week 0 and 8 of diet intervention, subsampled and stored at−80 °C. Shotgun metagenomic sequencing was used to identify genes involved in H2S metabolism. Metagenomic reads were trimmed, reads mapping to the human genome removed. Gene identification was performed using Diamond v2.1.9 for alignment against a database of genes involved in global sulphur cycling. Gas-chromatography mass-spectrometry was used to characterise volatile organic compounds (VOCs) with specific analysis of products of protein fermentation. Microbiota capacity to produce H2S was assessed by anaerobic incubation of homogenates followed by spectrophotometric determination of total H2S production. Results Majority of microbiome members belonged to the Bacteroidota and Bacillota phyla, with no significant difference in bacterial diversity determined between time points (p=0.16). However, using a Random Forest Classifier, known H2S producers, Odoribacter and Peptostreptococcaceae, were identified as the most important taxa in discriminating between pre and post-diet samples, with abundances markedly lower after diet intervention. A shift in microbiota metagenomic profiles putatively involved in H2S metabolism was identified post-diet, with differences (p<0.05, Wilcoxon signed-rank with Benjamini-Hochberg correction) in 12 of 23 analysed genes involved in H2S cycling determined, including iscS, cysK (Fig), metC, luxS, asrC and sseA. 173 faecal VOCs were identified across all samples. Indole (a specific marker of protein fermentation) decreased from 0.42 [-0.25,0.61] at week 0 to -0.28 [-0.77,0.48] at week 8 (p=0.007, FDR correction; Fig). Faecal H2S reduced from median 2.61 (interquartile range 2–4.96)µmol to 1.41 (0.81-2.27)µmol of H2S/g stool (wet weight)(p=0.002)(Fig). Conclusion Deep functional analysis of the faeces demonstrated the micro-environmental objectives of the 4-SURE diet successfully reduced protein fermentation, changed microbial community sulphur-metabolic gene profile and reduced H2S production ex vivo. Applying functional analysis to a diet study is novel, highlighting exemplar framework for including biomarkers of pathogenic relevance in analysis of therapeutic diets.

Digital pathology images, particularly whole slide images (WSIs), often contain macro-scale artifacts such as tissue folds, out-of-focus regions, and pen markings that can introduce bias and compromise the performance of machine learning models. The variability of tissue types, artifact appearances, and sample preparation and imaging conditions makes reliable artifact detection challenging. Here we introduce WSI Spectral Thresholding for Artifact Removal (WSI-STAR), a reference-free approach for detecting and removing macro-scale artifacts from WSIs that leverages the relative scale, spatial distribution, and spectral characteristics of macro-scale artifacts compared with tissue. Our pipeline combines spectral analysis and superpixel segmentation to effectively group and merge adjacent regions based on their frequency information, followed by an adaptive thresholding process. The result is an improved tissue mask that serves as a higher-quality input to downstream analysis.

Despite the huge pool of ideas on how diet can be manipulated to ameliorate or prevent illnesses, our understanding of how specific changes in diet influence the gastrointestinal tract is limited. This review aims to describe two innovative investigative techniques that are helping lift the veil of mystery about the workings of the gut. First, the gas-sensing capsule is a telemetric swallowable device that provides unique information on gastric physiology, small intestinal microbial activity, and fermentative patterns in the colon. Its ability to accurately measure regional and whole-gut transit times in ambulant humans has been confirmed. Luminal concentrations of hydrogen and carbon dioxide are measured by sampling through the gastrointestinal tract, and such application has enabled mapping of the relative amounts of fermentation of carbohydrates in proximal-versus-distal colon after manipulation of the types and amounts of dietary fiber. Second, changes in the smell of feces, via analysis of volatile organic compounds, occur in response to the diet, and by the presence and therapy of irritable bowel syndrome and inflammatory bowel disease. Such information is likely to aid our understanding of what dietary change can do to the colonic luminal microenvironment, and may value-add to diagnosis and therapeutic design. In conclusion, such methodologies enable a more complete physiological profile of the gastrointestinal tract to be created. Systematic description in various cohorts and effects of dietary interventions, particularly when co-ordinated with the analysis of microbiome, are needed.

Background Irritable bowel syndrome (IBS) is a common and debilitating disorder manifesting with abdominal pain and bowel dysfunction. A mainstay of treatment is dietary modification, fi cation, including restriction of FODMAPs (fermentable oligosaccharides, disaccharides, monosaccharides and polyols). A greater response to a low FODMAP diet has been reported in those with a distinct IBS microbiome termed IBS-P. We investigated whether this is linked to specific fi c changes in the metabolome in IBS-P. Methods Solid phase microextraction gas chromatography-mass spectrometry was used to examine the faecal headspace of 56 IBS cases (each paired with a non-IBS household control) at baseline, and after four-weeks of a low FODMAP diet (39 pairs). 50% cases had the IBS-P microbial subtype, while the others had a microbiome that more resembled healthy controls (termed IBS-H). Clinical response to restriction of FODMAPs was measured with the IBS-symptom severity scale, from which a pain sub score was calculated. Findings Two distinct metabotypes were identified fi ed and mapped onto the microbial subtypes. IBS-P was characterised by a fermentative metabolic profile fi le rich in short chain fatty acids (SCFAs). After FODMAP restriction significant fi cant reductions in SCFAs were observed in IBS-P. SCFA levels did not change significantly fi cantly in the IBS-H group. The magnitude of pain and overall symptom improvement were significantly fi cantly greater in IBS-P compared to IBS-H (p p = 0.016 and p = 0.026, respectively). Using just fi ve metabolites, a biomarker model could predict microbial subtype with accuracy (AUROC 0.797, sensitivity 78.6% (95% CI: 0.78-0.94), - 0.94), specificity fi city 71.4% (95% CI: 0.55-0.88). - 0.88). Interpretation A metabotype high in SCFAs can be manipulated by restricting fermentable carbohydrate, and is associated with an enhanced clinical response to this dietary restriction. This implies that SCFAs harbour pronociceptive potential when produced in a specific fi c IBS niche. By ascertaining metabotype, microbial subtype can be predicted with accuracy. This could allow targeted FODMAP restriction in those seemingly primed to respond best. Funding This research was co-funded by Addenbrooke's ' s Charitable Trust, Cambridge University Hospitals and the Wellcome Sanger Institute, and supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). Copyright (c) 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).