Reverse-engineered exclusive enteral nutrition in pediatric Crohn's disease: A pilot trial.

BACKGROUND: In pediatric Crohn's disease (CD), commercial formulas used as exclusive enteral nutrition (EEN) are effective at inducing remission. This study aims to assess the impact of a whole-food blended smoothie as EEN on CD activity and the intestinal microbiome. METHODS: A 4-week prospective trial assessed the impact of EEN with a whole-food smoothie on newly diagnosed mild-to-moderate active pediatric CD. The smoothie with a multivitamin were developed to meet age-appropriate nutritional requirements. Assessment over 4 weeks included Pediatric Crohn's Disease Activity Index (PCDAI), serum laboratories, fecal calprotectin (FCP), and stool collection for metagenomic shotgun sequencing and microbiota composition analysis. Clinical remission was defined as PCDAI ≤ 10 at week 4. RESULTS: Ten participants were enrolled with median age 14.5 years, and 8 completed the trial. Baseline mean PCDAI was 26.3 ± 9.1 and mean FCP 1149 ± 718 µg/g. At week 4, 80% of participants achieved clinical remission. FCP decreased by over half in 60% of participants, with FCP below 250 µg/g in 60% and below 100 µg/g in 40%. Microbiome analysis showed a significant increase in species richness over 4 weeks (p = 0.01). Compared to baseline, the relative abundance at week 2 and at week 4 was significantly increased for Bifidobacterium and Streptococcus and decreased for Blautia (p < 0.05 for all). CONCLUSION: A whole-food blended smoothie was effective for inducing clinical remission and decreasing FCP in pediatric CD similar to commercial EEN formulas. Further research may give insight into data-driven whole-food dietary approaches for CD management. CLINICALTRIALS: gov NCT03508193.

Alterations in the fecal microbiota in patients with advanced cystic fibrosis liver disease after 6 months of elexacaftor/tezacaftor/ivacaftor.

BACKGROUND: Cystic fibrosis associated liver disease (CFLD) carries a significant disease burden with no effective preventive therapies. According to the gut-liver axis hypothesis for CFLD pathogenesis, dysbiosis and increased intestinal inflammation and permeability permit pathogenic bacterial translocation into the portal circulation, leading to hepatic inflammation and fibrosis. Evaluating the effect of CFTR (cystic fibrosis transmembrane conductance regulator) modulation with elexacaftor/tezacaftor/ivacaftor (ETI) may help determine the role of CFTR in CFLD and increase understanding of CFLD pathogenesis, which is critical for developing therapies. We aimed to characterize the fecal microbiota in participants with CF with and without advanced CFLD (aCFLD) before and after ETI. METHODS: This is an ancillary analysis of stool samples from participants ages ≥12 y/o enrolled in PROMISE (NCT04038047). Included participants had aCFLD (cirrhosis with or without portal hypertension, or non-cirrhotic portal hypertension) or CF without liver disease (CFnoLD). Fecal microbiota were defined by shotgun metagenomic sequencing at baseline and 1 and 6 months post-ETI. RESULTS: We analyzed 93 samples from 34 participants (11 aCFLD and 23 CFnoLD). Compared to CFnoLD, aCFLD had significantly higher baseline relative abundances of potential pathogens Streptococcus salivarius and Veillonella parvula. Four of 11 aCFLD participants had an initially abnormal fecal calprotectin that normalized 6 months post-ETI, correlating with a significant decrease in S. salivarius and a trend towards decreasing V. parvula. CONCLUSIONS: These results support an association between dysbiosis and intestinal inflammation in CFLD with improvements in both post-ETI, lending further support to the gut-liver axis in aCFLD.

Characterization of cerebrospinal fluid (CSF) microbiota at the time of initial surgical intervention for children with hydrocephalus.

OBJECTIVE: To characterize the microbiota of the cerebrospinal fluid (CSF) from children with hydrocephalus at the time of initial surgical intervention. STUDY DESIGN: CSF was obtained at initial surgical intervention. One aliquot was stored in skim milk-tryptone-glucose-glycerol (STGG) medium and the second was unprocessed; both were then stored at -70°C. Bacterial growth for CSF samples stored in STGG were subsequently characterized using aerobic and anaerobic culture on blood agar and MALDI-TOF sequencing. All unprocessed CSF samples underwent 16S quantitative polymerase chain reaction (qPCR) sequencing, and a subset underwent standard clinical microbiological culture. CSF with culture growth (either after storage in STGG or standard clinical) were further analyzed using whole-genome amplification sequencing (WGAS). RESULTS: 11/66 (17%) samples stored in STGG and 1/36 (3%) that underwent standard clinical microbiological culture demonstrated bacterial growth. Of the organisms present, 8 were common skin flora and 4 were potential pathogens; only 1 was also qPCR positive. WGAS findings and STGG culture findings were concordant for only 1 sample, identifying Staphylococcus epidermidis. No significant difference in time to second surgical intervention was observed between the STGG culture-positive and negative groups. CONCLUSION(S): Using high sensitivity methods, we detected the presence of bacteria in a subset of CSF samples at the time of first surgery. Therefore, the true presence of bacteria in CSF of children with hydrocephalus cannot be ruled out, though our findings may suggest these bacteria are contaminants or false positives of the detection methods. Regardless of origin, the detection of microbiota in the CSF of these children may not have any clinical significance.

A Refined, Controlled 16S rRNA Gene Sequencing Approach Reveals Limited Detection of Cerebrospinal Fluid Microbiota in Children with Bacterial Meningitis.

Advances in both laboratory and computational components of high-throughput 16S amplicon sequencing (16S HTS) have markedly increased its sensitivity and specificity. Additionally, these refinements have better delineated the limits of sensitivity, and contributions of contamination to these limits, for 16S HTS that are particularly relevant for samples with low bacterial loads, such as human cerebrospinal fluid (CSF). The objectives of this work were to (i) optimize the performance of 16S HTS in CSF samples with low bacterial loads by defining and addressing potential sources of error, and (ii) perform refined 16S HTS on CSF samples from children diagnosed with bacterial meningitis and compare results with those from microbiological cultures. Several bench and computational approaches were taken to address potential sources of error for low bacterial load samples. We compared DNA yields and sequencing results after applying three different DNA extraction approaches to an artificially constructed mock-bacterial community. We also compared two postsequencing computational contaminant removal strategies, decontam R and full contaminant sequence removal. All three extraction techniques followed by decontam R yielded similar results for the mock community. We then applied these methods to 22 CSF samples from children diagnosed with meningitis, which has low bacterial loads relative to other clinical infection samples. The refined 16S HTS pipelines identified the cultured bacterial genus as the dominant organism for only 3 of these samples. We found that all three DNA extraction techniques followed by decontam R generated similar DNA yields for mock communities at the low bacterial loads representative of CSF samples. However, the limits of detection imposed by reagent contaminants and methodologic bias precluded the accurate detection of bacteria in CSF from children with culture-confirmed meningitis using these approaches, despite rigorous controls and sophisticated computational approaches. Although we did not find current DNA-based diagnostics to be useful for pediatric meningitis samples, the utility of these methods for CSF shunt infection remains undefined. Future advances in sample processing methods to minimize or eliminate contamination will be required to improve the sensitivity and specificity of these methods for pediatric meningitis. IMPORTANCE Advances in both laboratory and computational components of high-throughput 16S amplicon sequencing (16S HTS) have markedly increased its sensitivity and specificity. These refinements have better delineated the limits of sensitivity, and contributions of contamination to these limits, for 16S HTS that are particularly relevant for samples with low bacterial loads such as human cerebrospinal fluid (CSF). The objectives of this work were to (i) optimize the performance of 16S HTS in CSF samples by defining and addressing potential sources of error, and (ii) perform refined 16S HTS on CSF samples from children diagnosed with bacterial meningitis and compare results with those from microbiological cultures. We found that the limits of detection imposed by reagent contaminants and methodologic bias precluded the accurate detection of bacteria in CSF from children with culture-confirmed meningitis using these approaches, despite rigorous controls and sophisticated computational approaches.

Elexacaftor/tezacaftor/ivacaftor and gastrointestinal outcomes in cystic fibrosis: Report of promise-GI.

BACKGROUND: Elexacaftor/tezacaftor/ivacaftor (ETI) improves pulmonary disease in people with cystic fibrosis (PwCF), but its effect on gastrointestinal symptoms, which also affect quality of life, is not clear. METHODS: PROMISE is a 56-center prospective, observational study of ETI in PwCF >12 years and at least one F508del allele. Gastrointestinal symptoms, evaluated by validated questionnaires: Patient Assessment of Upper Gastrointestinal Disorders-Symptom (PAGI-SYM), Patient Assessment of Constipation-Symptom (PAC-SYM), Patient Assessment of Constipation-Quality of Life (PAC-QOL)), fecal calprotectin, steatocrit and elastase-1 were measured before and 6 months after ETI initiation. Mean difference and 95% confidence intervals were obtained from linear regression with adjustment for age and sex. RESULTS: 438 participants fully completed at least 1 questionnaire. Mean (SD) for baseline PAGI-SYM, PAC-SYM, and PAC-QOL total scores were 0.56 (0.59), 0.47 (0.45), and 0.69 (0.53) out of maximum 5, 4, and 5, respectively (higher score indicates greater severity). Corresponding age- and sex-adjusted 6 months mean changes (95% CI) in total scores were -0.15 (-0.21, -0.09) for PAGI-SYM, -0.14 (-0.19, -0.09) for PAC-SYM, and -0.15 (-0.21, -0.10) for PAC-QOL. While statistically significant, changes were small and unlikely to be of clinical importance. Fecal calprotectin showed a change (95% CI) from baseline of -66.2 µg/g (-86.1, -46.2) at 6 months, while fecal elastase and steatocrit did not meaningfully change. CONCLUSIONS: After 6 months of ETI, fecal markers of inflammation decreased. Gastrointestinal symptoms improved, but the effect size was small. Pancreatic insufficiency did not improve.

Molecular Characterization of Microbiota in Cerebrospinal Fluid From Patients With CSF Shunt Infections Using Whole Genome Amplification Followed by Shotgun Sequencing.

Understanding the etiology of cerebrospinal fluid (CSF) shunt infections and reinfections requires detailed characterization of associated microorganisms. Traditionally, identification of bacteria present in the CSF has relied on culture methods, but recent studies have used high throughput sequencing of 16S rRNA genes. Here we evaluated the method of shotgun DNA sequencing for its potential to provide additional genomic information. CSF samples were collected from 3 patients near the beginning and end of each of 2 infection episodes. Extracted total DNA was sequenced by: (1) whole genome amplification followed by shotgun sequencing (WGA) and (2) high-throughput sequencing of the 16S rRNA V4 region (16S). Taxonomic assignments of sequences from WGA and 16S were compared with one another and with conventional microbiological cultures. While classification of bacteria was consistent among the 3 approaches, WGA provided additional insights into sample microbiological composition, such as showing relative abundances of microbial versus human DNA, identifying samples of questionable quality, and detecting significant viral load in some samples. One sample yielded sufficient non-human reads to allow assembly of a high-quality Staphylococcus epidermidis genome, denoted CLIMB1, which we characterized in terms of its MLST profile, gene complement (including putative antimicrobial resistance genes), and similarity to other annotated S. epidermidis genomes. Our results demonstrate that WGA directly applied to CSF is a valuable tool for the identification and genomic characterization of dominant microorganisms in CSF shunt infections, which can facilitate molecular approaches for the development of better diagnostic and treatment methods.

Infants with cystic fibrosis have altered fecal functional capacities with potential clinical and metabolic consequences.

BACKGROUND: Infants with cystic fibrosis (CF) suffer from gastrointestinal (GI) complications, including pancreatic insufficiency and intestinal inflammation, which have been associated with impaired nutrition and growth. Recent evidence identified altered fecal microbiota taxonomic compositions in infants with CF relative to healthy infants that were characterized by differences in the abundances of taxa associated with GI health and nutrition. Furthermore, these taxonomic differences were more pronounced in low length infants with CF, suggesting a potential link to linear growth failure. We hypothesized that these differences would entail shifts in the microbiome's functional capacities that could contribute to inflammation and nutritional failure in infants with CF. RESULTS: To test this hypothesis, we compared fecal microbial metagenomic content between healthy infants and infants with CF, supplemented with an analysis of fecal metabolomes in infants with CF. We identified notable differences in CF fecal microbial functional capacities, including metabolic and environmental response functions, compared to healthy infants that intensified during the first year of life. A machine learning-based longitudinal metagenomic age analysis of healthy and CF fecal metagenomic functional profiles further demonstrated that these differences are characterized by a CF-associated delay in the development of these functional capacities. Moreover, we found metagenomic differences in functions related to metabolism among infants with CF that were associated with diet and antibiotic exposure, and identified several taxa as potential drivers of these functional differences. An integrated metagenomic and metabolomic analysis further revealed that abundances of several fecal GI metabolites important for nutrient absorption, including three bile acids, correlated with specific microbes in infants with CF. CONCLUSIONS: Our results highlight several metagenomic and metabolomic factors, including bile acids and other microbial metabolites, that may impact nutrition, growth, and GI health in infants with CF. These factors could serve as promising avenues for novel microbiome-based therapeutics to improve health outcomes in these infants.

Characterization of cerebrospinal fluid (CSF) microbiota from patients with CSF shunt infection and reinfection using high throughput sequencing of 16S ribosomal RNAgenes.

BACKGROUND: Nearly 20% of patients with cerebrospinal fluid (CSF) shunt infection develop reinfection. It is unclear whether reinfections are caused by an organism previously present or are independent infection events. OBJECTIVE: We used bacterial culture and high throughput sequencing (HTS) of 16S ribosomal RNA (rRNA) genes to identify bacteria present in serial CSF samples obtained from children who failed CSF shunt infection treatment. We hypothesized that organisms that persist in CSF despite treatment would be detected upon reinfection. DESIGN/METHODS: Serial CSF samples were obtained from 6 patients, 5 with 2 infections and 1 with 3 infections; the study was limited to those for which CSF samples were available from the end of infection and beginning of reinfection. Amplicons of the 16S rRNA gene V4 region were sequenced. Taxonomic assignments of V4 sequences were compared with bacterial species identified in culture. RESULTS: Seven infection dyads averaging 13.5 samples per infection were analyzed. A median of 8 taxa [interquartile range (IQR) 5-10] were observed in the first samples from reinfection using HTS. Conventional culture correlated with high abundance of an organism by HTS in all but 1 infection. In 6 of 7 infection dyads, organisms identified by culture at reinfection were detected by HTS of culture-negative samples at the end of the previous infection. The median Chao-Jaccard abundance-based similarity index for matched infection pairs at end of infection and beginning of reinfection was 0.57 (IQR 0.07-0.87) compared to that for unmatched pairs of 0.40 (IQR 0.10-0.60) [p = 0.46]. CONCLUSION(S): HTS results were generally consistent with culture-based methods in CSF shunt infection and reinfection, and may detect organisms missed by culture at the end of infection treatment but detected by culture at reinfection. However, the CSF microbiota did not correlate more closely within patients at the end of infection and beginning of reinfection than between any two unrelated infections. We cannot reject the hypothesis that sequential infections were independent.

CFTR dysregulation drives active selection of the gut microbiome.

Patients with cystic fibrosis (CF) have altered fecal microbiomes compared to those of healthy controls. The magnitude of this dysbiosis correlates with measures of CF gastrointestinal (GI) disease, including GI inflammation and nutrient malabsorption. However, whether this dysbiosis is caused by mutations in the CFTR gene, the underlying defect in CF, or whether CF-associated dysbiosis augments GI disease was not clear. To test the relationships between CFTR dysfunction, microbes, and intestinal health, we established a germ-free (GF) CF mouse model and demonstrated that CFTR gene mutations are sufficient to alter the GI microbiome. Furthermore, flow cytometric analysis demonstrated that colonized CF mice have increased mesenteric lymph node and spleen TH17+ cells compared with non-CF mice, suggesting that CFTR defects alter adaptive immune responses. Our findings demonstrate that CFTR mutations modulate both the host adaptive immune response and the intestinal microbiome.

Fecal dysbiosis in infants with cystic fibrosis is associated with early linear growth failure.

Most infants with cystic fibrosis (CF) have pancreatic exocrine insufficiency that results in nutrient malabsorption and requires oral pancreatic enzyme replacement. Newborn screening for CF has enabled earlier diagnosis, nutritional intervention and enzyme replacement for these infants, allowing most infants with CF to achieve their weight goals by 12 months of age1. Nevertheless, most infants with CF continue to have poor linear growth during their first year of life1. Although this early linear growth failure is associated with worse long-term respiratory function and survival2,3, the determinants of body length in infants with CF have not been defined. Several characteristics of the CF gastrointestinal (GI) tract, including inflammation, maldigestion and malabsorption, may promote intestinal dysbiosis4,5. As GI microbiome activities are known to affect endocrine functions6,7, the intestinal microbiome of infants with CF may also impact growth. We identified an early, progressive fecal dysbiosis that distinguished infants with CF and low length from infants with CF and normal length. This dysbiosis included altered abundances of taxa that perform functions that are important for GI health, nutrient harvest and growth hormone signaling, including decreased abundance of Bacteroidetes and increased abundance of Proteobacteria. Thus, the GI microbiota represent a potential therapeutic target for the correction of low linear growth in infants with CF.

Human gut bacteria contain acquired interbacterial defence systems.

The human gastrointestinal tract consists of a dense and diverse microbial community, the composition of which is intimately linked to health. Extrinsic factors such as diet and host immunity are insufficient to explain the constituents of this community, and direct interactions between co-resident microorganisms have been implicated as important drivers of microbiome composition. The genomes of bacteria derived from the gut microbiome contain several pathways that mediate contact-dependent interbacterial antagonism1-3. Many members of the Gram-negative order Bacteroidales encode the type VI secretion system (T6SS), which facilitates the delivery of toxic effector proteins into adjacent cells4,5. Here we report the occurrence of acquired interbacterial defence (AID) gene clusters in Bacteroidales species that reside within the human gut microbiome. These clusters encode arrays of immunity genes that protect against T6SS-mediated intra- and inter-species bacterial antagonism. Moreover, the clusters reside on mobile elements, and we show that their transfer is sufficient to confer resistance to toxins in vitro and in gnotobiotic mice. Finally, we identify and validate the protective capability of a recombinase-associated AID subtype (rAID-1) that is present broadly in Bacteroidales genomes. These rAID-1 gene clusters have a structure suggestive of active gene acquisition and include predicted immunity factors of toxins derived from diverse organisms. Our data suggest that neutralization of contact-dependent interbacterial antagonism by AID systems helps to shape human gut microbiome ecology.

Direct Lung Sampling Indicates That Established Pathogens Dominate Early Infections in Children with Cystic Fibrosis.

Culture and sequencing have produced divergent hypotheses about cystic fibrosis (CF) lung infections. Culturing suggests that CF lungs are uninfected before colonization by a limited group of CF pathogens. Sequencing suggests diverse communities of mostly oral bacteria inhabit lungs early on and diversity decreases as disease progresses. We studied the lung microbiota of CF children using bronchoscopy and sequencing, with measures to reduce contamination. We found no evidence for oral bacterial communities in lung lavages that lacked CF pathogens. Lavage microbial diversity varied widely, but decreases in diversity appeared to be driven by increased CF pathogen abundance, which reduced the signal from contaminants. Streptococcus, Prevotella, and Veillonella DNA was detected in some lavages containing CF pathogens, but DNA from these organisms was vastly exceeded by CF pathogen DNA and was not associated with inflammation. These findings support the hypothesis that established CF pathogens are primarily responsible for CF lung infections.

Acute Flares of Knee Osteoarthritis (the ACT-FLARE Study): Protocol for a Web-Based Case-Crossover Study in Community-Dwelling Adults.

BACKGROUND: The cardinal feature of osteoarthritis (OA) is pain. Although heterogeneity in pain and function have been demonstrated in the long-term course of OA, the more proximate determinants of acute flare-ups remain less clear. How short-term intermittent or transient exposures trigger acute flare-ups has important implications for effective and sustainable self-management strategies. OBJECTIVE: The primary objective of this study is to identify potential triggers of acute flares in knee OA. Secondary objectives are to determine their course and consequences and describe high-risk participant profiles. METHODS: We carried out a Web-based case-crossover study. This study aims to recruit 620 community-dwelling adults aged ≥40 years, resident in England, and who have knee pain, with or without a recorded diagnosis of knee OA, and no preexisting diagnosis of inflammatory arthropathy. Participants will be recruited via 3 routes: (1) general practice registers, (2) offline community advertisement, and (3) online social media advertisement. By using questionnaires comparing periods before participants' self-reported flare-up episodes (hazard periods) with periods during the study when their knee OA symptoms are stable (control periods), triggers preceding flare-ups will be identified and examined using conditional logistic regression. Time-to-resolution of flare-up will be examined by monitoring people's daily pain, bothersomeness, and medication usage until the participant reports when their flare-up episode ends. Rates of flare-ups will be examined across different participant and flare characteristics using regression models to identify high-risk participant profiles. A study-specific Patient Advisory Group (PAG) is providing suggestion, input, and ongoing support for all stages of the research process. RESULTS: Participant recruitment opened in July 2018 and is anticipated to continue for 6 months. The study results will be disseminated through a number of channels, including relevant national or international conferences and peer-reviewed publication in a medical journal, via advocacy or charity organizations, such as Versus Arthritis and across social media. Findings will be fed back to members of our PAG, study participants, and clinicians from participating primary care general practices. The PAG will also take an active role in the overall dissemination strategy. CONCLUSIONS: This study will provide empirical evidence to help patients identify common knee OA flare triggers and provide health care professionals with questions to identify patients at most risk of frequent flare-ups. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13428.

Human and Extracellular DNA Depletion for Metagenomic Analysis of Complex Clinical Infection Samples Yields Optimized Viable Microbiome Profiles.

Metagenomic sequencing is a promising approach for identifying and characterizing organisms and their functional characteristics in complex, polymicrobial infections, such as airway infections in people with cystic fibrosis. These analyses are often hampered, however, by overwhelming quantities of human DNA, yielding only a small proportion of microbial reads for analysis. In addition, many abundant microbes in respiratory samples can produce large quantities of extracellular bacterial DNA originating either from biofilms or dead cells. We describe a method for simultaneously depleting DNA from intact human cells and extracellular DNA (human and bacterial) in sputum, using selective lysis of eukaryotic cells and endonuclease digestion. We show that this method increases microbial sequencing depth and, consequently, both the number of taxa detected and coverage of individual genes such as those involved in antibiotic resistance. This finding underscores the substantial impact of DNA from sources other than live bacteria in microbiological analyses of complex, chronic infection specimens.

Acute flares of knee osteoarthritis in primary care: a feasibility and pilot case-crossover study.

BACKGROUND: Osteoarthritis (OA) is a leading cause of persistent pain and disability. Traditionally viewed as a slowly progressive disease, the impact of symptom variability on prognosis remains unclear. 'Acute-on-chronic' episodes are a well-recognised feature of many long-term conditions but only recently formally described in OA. This study aimed to develop a web-based data collection platform and establish key methodological design parameters, to develop a larger community-based study investigating acute flares of knee OA in England. METHODS: The study is a 9-week feasibility and pilot web-based observational case-crossover study. Adults aged ≥ 40 years registered with two general practices who had consulted their general practitioner for knee pain/OA in the last 2 years were recruited. Participants completed a baseline questionnaire and scheduled (control-period) questionnaires at follow-up weeks 1, 5, and 9. Participants were invited to self-declare via the website on any occasion they experienced a knee pain flare-up lasting ≥ 24 h. Upon notification, an event-driven (case-period) questionnaire comparable to the scheduled questionnaires was completed and daily measurements on the course and consequences were taken until resolution. A sub-study of 10 participants logged daily pain measurements. The analysis estimated key parameters including recruitment (selective non-participation, eligibility, consent), retention, and flare-up capture processes. Questionnaire completeness and website usability were evaluated. RESULTS: Of 442 patients invited, 14 completed baseline questionnaires. Eligibility rate was 26.9% (95% CI 19.3, 36.2), consent rate 53.6% (35.8, 70.5), and overall recruitment rate 3.2% (1.9, 5.2). Compared to those mailed, baseline responders were more likely to be male and ≥ 65 years, as were those reporting ≥ 1 flare-up. Eleven scheduled questionnaires were completed (mean response 35%). Although seven participants (50%) self-declared 11 flare-ups, only one event-driven questionnaire was completed and three participants contributed daily flare measurement for four flares. Missing data was ≤ 3.7% across completed baseline, scheduled, and event-driven questionnaires. Aspects of website usability require minor refinement. CONCLUSIONS: Recruitment was not feasible with the current strategy. An evaluation of processes has suggested several substantial changes in design that may enhance recruitment, retention, and data quality in a future full-scale study.

Cost-Utility Analysis of Routine Anxiety and Depression Screening in Patients Consulting for Osteoarthritis: Results From a Clinical, Randomized Controlled Trial.

OBJECTIVE: To investigate the cost-effectiveness (cost-utility) of introducing general practitioner screening for anxiety and depression in patients consulting for osteoarthritis (OA). METHODS: A cluster-randomized trial-based economic evaluation to assess general practitioners screening for anxiety and depression symptoms in patients consulting for OA compared to usual care (screening for pain intensity) was undertaken over a 12-month period from a UK National Health Service and societal perspective. Patient-level mean costs and mean quality-adjusted life years (QALYs) were estimated, and cost-effectiveness acceptability curves controlling for cluster-level data were constructed. The base-case analysis used the net benefit regressions approach. The 2-stage nonparametric sampling technique was explored in a sensitivity analysis. RESULTS: The base-case analysis demonstrated that the intervention was as costly as, and less effective than, the control (QALY differential -0.029 [95% confidence interval -0.062, 0.003]). In the base-case analyses, general practitioner screening for anxiety and depression was unlikely to be a cost-effective option (probability <5% at £20,000/QALY). Similar results were observed in all sensitivity analyses. CONCLUSION: Prompting general practitioners to routinely screen and manage comorbid anxiety and depression in patients presenting with OA is unlikely to be cost-effective. Further research is needed to explore clinically effective and cost-effective models of managing anxiety and depression in patients presenting with clinical OA.

Adaptation of commensal proliferating Escherichia coli to the intestinal tract of young children with cystic fibrosis.

The mature human gut microbiota is established during the first years of life, and altered intestinal microbiomes have been associated with several human health disorders. Escherichia coli usually represents less than 1% of the human intestinal microbiome, whereas in cystic fibrosis (CF), greater than 50% relative abundance is common and correlates with intestinal inflammation and fecal fat malabsorption. Despite the proliferation of E. coli and other Proteobacteria in conditions involving chronic gastrointestinal tract inflammation, little is known about adaptation of specific characteristics associated with microbiota clonal expansion. We show that E. coli isolated from fecal samples of young children with CF has adapted to growth on glycerol, a major component of fecal fat. E. coli isolates from different CF patients demonstrate an increased growth rate in the presence of glycerol compared with E. coli from healthy controls, and unrelated CF E. coli strains have independently acquired this growth trait. Furthermore, CF and control E. coli isolates have differential gene expression when grown in minimal media with glycerol as the sole carbon source. While CF isolates display a growth-promoting transcriptional profile, control isolates engage stress and stationary-phase programs, which likely results in slower growth rates. Our results indicate that there is selection of unique characteristics within the microbiome of individuals with CF, which could contribute to individual disease outcomes.

Analysis of Fascin-1 in Relation to Gleason Risk Classification and Nuclear ETS-Related Gene Status of Human Prostate Carcinomas: An Immunohistochemical Study of Clinically Annotated Tumours From the Wales Cancer Bank.

Although prostate-specific antigen (PSA) testing can identify early-stage prostate cancers, additional biomarkers are needed for risk stratification. In one study, high levels of the actin-bundling protein, fascin-1, were correlated with lethal-phase, hormone-refractory prostate cancer. Analyses of independent samples are needed to establish the value of fascin-1 as a possible biomarker. We examined fascin-1 by immunohistochemistry in tumour specimens from the Wales Cancer Bank in comparison with nuclear-located ETS-related gene (ERG), an emerging marker for aggressive prostate cancer. Fascin-1 was elevated in focal areas of a minority of tumours, yet fascin-1-positivity did not differentiate tumours of low-, intermediate-, or high-risk Gleason scores and did not correlate with PSA status or biochemical relapse after surgery. Stromal fascin-1 correlated with high Gleason score. Nuclear ERG was upregulated in tumours but not in stroma. The complexities of fascin-1 status indicate that fascin-1 is unlikely to provide a suitable biomarker for prediction of aggressive prostate cancers.

Root System Water Consumption Pattern Identification on Time Series Data.

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers' detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system's 0.348 precision.

Identification of transcript regulatory patterns in cell differentiation.

MOTIVATION: Studying transcript regulatory patterns in cell differentiation is critical in understanding its complex nature of the formation and function of different cell types. This is done usually by measuring gene expression at different stages of the cell differentiation. However, if the gene expression data available are only from the mature cells, we have some challenges in identifying transcript regulatory patterns that govern the cell differentiation. RESULTS: We propose to exploit the information of the lineage of cell differentiation in terms of correlation structure between cell types. We assume that two different cell types that are close in the lineage will exhibit many common genes that are co-expressed relative to those that are far in the lineage. Current analysis methods tend to ignore this correlation by testing for differential expression assuming some sort of independence between cell types. We employ a Bayesian approach to estimate the posterior distribution of the mean of expression in each cell type, by taking into account the cell formation path in the lineage. This enables us to infer genes that are specific in each cell type, indicating the genes are involved in directing the cell differentiation to that particular cell type. We illustrate the method using gene expression data from a study of haematopoiesis. AVAILABILITY AND IMPLEMENTATION: R codes to perform the analysis are available in http://www1.maths.leeds.ac.uk/∼arief/R/CellDiff/. CONTACT: a.gusnanto@leeds.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.