First-in-human study of a pharmacological duodenal exclusion therapy shows reduced postprandial glucose and insulin and increased bile acid and gut hormone concentrations.

AIMS: To address the need for noninvasive alternatives to metabolic surgery or duodenal exclusion devices for the management of type 2 diabetes (T2D) and obesity by developing an orally administered therapeutic polymer, GLY-200, designed to bind to and enhance the barrier function of mucus in the gastrointestinal tract to establish duodenal exclusion noninvasively. MATERIALS AND METHODS: A Phase 1, randomized, double-blind, placebo-controlled, single- (SAD) and multiple-ascending-dose (MAD) healthy volunteer study was conducted. In the SAD arm, four cohorts received a single dose of 0.5 g up to 6.0 g GLY-200 or placebo, while in the MAD arm, four cohorts received 5 days of twice-daily or three-times-daily dosing (total daily dose 2.0 g up to 6.0 g GLY-200 or placebo). Assessments included safety and tolerability (primary) and exploratory pharmacodynamics, including serum glucose, insulin, bile acids and gut hormones. RESULTS: No safety signals were observed; tolerability signals were limited to mild to moderate dose-dependent gastrointestinal events. In the MAD arm (Day 5), reductions in glucose and insulin and increases in bile acids, glucagon-like peptide-1, peptide YY and glicentin, were observed following a nonstandardized meal in subjects receiving twice-daily dosing of 2.0 g GLY-200 (N = 9) versus those receiving placebo (N = 8). CONCLUSIONS: GLY-200 is safe and generally well tolerated at doses of ≤2.0 g twice daily. Pharmacodynamic results mimic the biomarker signature observed after Roux-en-Y gastric bypass and duodenal exclusion devices, indicating a pharmacological effect in the proximal small intestine. This study represents the first clinical demonstration that duodenal exclusion can be achieved with an oral drug and supports further development of GLY-200 for the treatment of obesity and/or T2D.

Novel Circulating Tumor Cell Assay for Detection of Colorectal Adenomas and Cancer.

OBJECTIVES: There is a significant unmet need for a blood test with adequate sensitivity to detect colorectal cancer (CRC) and adenomas. We describe a novel circulating tumor cell (CTC) platform to capture colorectal epithelial cells associated with CRC and adenomas. METHODS: Blood was collected from 667 Taiwanese adults from 2012 to 2018 before a colonoscopy. The study population included healthy control subjects, patients with adenomas, and those with stage I-IV CRC. CTCs were isolated from the blood using the CellMax platform. The isolated cells were enumerated, and an algorithm was used to determine the likelihood of detecting adenoma or CRC. Nominal and ordinal logistic regression demonstrated that CTC counts could identify adenomas and CRC, including CRC stage. RESULTS: The CellMax test demonstrated a significant association between CTC counts and worsening disease status (Cuzick's P value < 0.0001) with respect to the adenoma-carcinoma sequence. The test showed high specificity (86%) and sensitivity across all CRC stages (95%) and adenomatous lesions (79%). The area under the curve was 0.940 and 0.868 for the detection of CRC and adenomas, respectively. DISCUSSION: The blood-based CTC platform demonstrated high sensitivity in detecting adenomas and CRC, as well as reasonable specificity in an enriched symptomatic patient population. TRANSLATIONAL IMPACT: If these results are reproduced in an average risk population, this test has the potential to prevent CRC by improving patient compliance and detecting precancerous adenomas, eventually reducing CRC mortality.

Precision Bariatrics: Toward a New Paradigm of Personalized Devices in Obesity Therapeutics.

The prevalence and complexity of obesity and its associated metabolic complications highlight the importance of building a rigorous investigative framework for the development of novel weight loss therapies. Device-based interventions in particular constitute a market poised for rapid expansion in the coming years. Optimizing outcomes for this new class of therapies requires attention to an evolving taxonomy of subdivisions within the broader obesity phenotype and a means for stratifying patients toward maximally effective interventions. Extant bariatric devices implicitly prioritize anatomic variables as surrogates for physiology, a somewhat arbitrary assumption that merits empiric validation. Utilizing the governing principles of systems biology and recent innovations in clinical trial design, a robust and precise research infrastructure can and should be developed to more effectively mitigate this contemporary epidemic.

Primary endoscopic therapies for obesity and metabolic diseases.

PURPOSE OF REVIEW: Endoscopic approaches to obesity may help fulfill the unmet need of over half the US adult population who would benefit from therapy for obesity but are not receiving it. Endoluminal approaches have the potential to be more efficacious than antiobesity medications and have a lower risk-cost profile compared with bariatric surgery. This review outlines the current state of primary endoscopic weight loss and metabolic therapies and sheds light on the challenges faced toward making endoscopic bariatric therapies 'ready for prime time'. RECENT FINDINGS: Endoscopic approaches to obesity are being increasingly modeled on the proposed mechanisms contributing to the benefits of bariatric surgery.Therapies targeted at the stomach induce weight loss with only a proportional benefit to underlying metabolic disorders.Therapies targeting the proximal small bowel appear to modulate various neurohormonal pathways resulting in an improvement in metabolic profile in excess to that accounted for by weight loss itself. SUMMARY: Rigorous scientific assessment of endoscopic approaches to obesity is necessary to allow its integration into the treatment algorithm of obesity. The endoscopic armamentarium against obesity continues to evolve with the endoscopist poised to be a key player in the management of this disease. VIDEO ABSTRACT: http://links.lww.com/COG/A12.

Mechanical stretch is a highly selective regulator of gene expression in human bladder smooth muscle cells.

Application of mechanical stimuli has been shown to alter gene expression in bladder smooth muscle cells (SMC). To date, only a limited number of "stretch-responsive" genes in this cell type have been reported. We employed oligonucleotide arrays to identify stretch-sensitive genes in primary culture human bladder SMC subjected to repetitive mechanical stimulation for 4 h. Differential gene expression between stretched and nonstretched cells was assessed using Significance Analysis of Microarrays (SAM). Expression of 20 out of 11,731 expressed genes ( approximately 0.17%) was altered >2-fold following stretch, with 19 genes induced and one gene (FGF-9) repressed. Using real-time RT-PCR, we tested independently the responsiveness of 15 genes to stretch and to platelet-derived growth factor-BB (PDGF-BB), another hypertrophic stimulus for bladder SMC. In response to both stimuli, expression of 13 genes increased, 1 gene (FGF-9) decreased, and 1 gene was unchanged. Six transcripts (HB-EGF, BMP-2, COX-2, LIF, PAR-2, and FGF-9) were evaluated using an ex vivo rat model of bladder distension. HB-EGF, BMP-2, COX-2, LIF, and PAR-2 increased with bladder stretch ex vivo, whereas FGF-9 decreased, consistent with expression changes observed in vitro. In silico analysis of microarray data using the FIRED algorithm identified c-jun, AP-1, ATF-2, and neurofibromin-1 (NF-1) as potential transcriptional mediators of stretch signals. Furthermore, the promoters of 9 of 13 stretch-responsive genes contained AP-1 binding sites. These observations identify stretch as a highly selective regulator of gene expression in bladder SMC. Moreover, they suggest that mechanical and growth factor signals converge on common transcriptional regulators that include members of the AP-1 family.

Prediction of mortality in an Indian intensive care unit. Comparison between APACHE II and artificial neural networks.

OBJECTIVE: To compare hospital outcome prediction using an artificial neural network model, built on an Indian data set, with the APACHE II (Acute Physiology and Chronic Health Evaluation II) logistic regression model. DESIGN: Analysis of a database containing prospectively collected data. SETTING: Medical-neurological ICU of a university hospital in Mumbai, India. SUBJECTS: Two thousand sixty-two consecutive admissions between 1996 and 1998. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The 22 variables used to obtain day-1 APACHE II score and risk of death were recorded. Data from 1,962 patients were used to train the neural network using a back-propagation algorithm. Data from the remaining 1,000 patients were used for testing this model and comparing it with APACHE II. There were 337 deaths in these 1,000 patients; APACHE II predicted 246 deaths while the neural network predicted 336 deaths. Calibration, assessed by the Hosmer-Lemeshow statistic, was better with the neural network (H=22.4) than with APACHE II (H=123.5) and so was discrimination (area under receiver operating characteristic curve =0.87 versus 0.77, p=0.002). Analysis of information gain due to each of the 22 variables revealed that the neural network could predict outcome using only 15 variables. A new model using these 15 variables predicted 335 deaths, had calibration (H=27.7) and discrimination (area under receiver operating characteristic curve =0.88) which was comparable to the 22-variable model (p=0.87) and superior to the APACHE II equation (p<0.001). CONCLUSION: Artificial neural networks, trained on Indian patient data, used fewer variables and yet outperformed the APACHE II system in predicting hospital outcome.

Reproducibility of gene expression across generations of Affymetrix microarrays.

BACKGROUND: The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips (HuGeneFL and HG-U95A) was measured. RESULTS: Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. CONCLUSION: We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.