Predictors of weight loss and reversal of comorbidities in malabsorptive bariatric surgery

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Massive Weight Loss Decreases Corticosteroid-Binding Globulin Levels and Increases Free Cortisol in Healthy Obese Patients An adaptive phenomenon?

OBJECTIVE—Obesity, insulin resistance, and weight loss have been associated with changes in hypothalamic-pituitary-adrenal (HPA) axis. So far, no conclusive data relating to this association are available. In this study, we aim to investigate the effects of massive weight loss on cortisol suppressibility, cortisol-binding globulin (CBG), and free cortisol index (FCI) in formerly obese women. RESEARCH DESIGN AND METHODS—Ten glucose-normotolerant, fertile, obese women (BMI >40 kg/m2, aged 38.66 ± 13.35 years) were studied before and 2 years after biliopancreatic diversion (BPD) when stable weight was achieved and were compared with age-matched healthy volunteers. Cortisol suppression was evaluated by a 4-mg intravenous dexamethasone suppression test (DEX-ST). FCI was calculated as the cortisol-to-CBG ratio. Insulin sensitivity was measured by an euglycemic-hyperinsulinemic clamp, and insulin secretion was measured by a C-peptide deconvolution method. RESULTS—No difference was found in cortisol suppression after DEX-ST before or after weight loss. A decrease in ACTH was significantly greater in control subjects than in obese (P = 0.05) and postobese women (P ≤ 0.01) as was the decrease in dehydroepiandrosterone (P ≤ 0.05 and P ≤ 0.01, respectively). CBG decreased from 51.50 ± 12.76 to 34.33 ± 7.24 mg/l (P ≤ 0.01) following BPD. FCI increased from 11.15 ± 2.85 to 18.16 ± 6.82 (P ≤ 0.05). Insulin secretion decreased (52.04 ± 16.71 vs. 30.62 ± 16.32 nmol/m−2; P ≤ 0.05), and insulin sensitivity increased by 163% (P ≤ 0.0001). Serum CBG was related to BMI (r0 = 0.708; P = 0.0001), body weight (r0 = 0.643; P = 0.0001), body fat percent (r0 = 0.462; P = 0.001), C-reactive protein (r0 = 0.619; P = 0.004), and leptin (r0 = 0.579; P = 0.007) and negatively to M value (r0 = −0.603; P = 0.005). CONCLUSIONS—After massive weight loss in morbidly obese subjects, an increase of free cortisol was associated with a simultaneous decrease in CBG levels, which might be an adaptive phenomenon relating to environmental changes. This topic, not addressed before, adds new insight into the complex mechanisms linking HPA activity to obesity

Growth hormone and ghrelin secretion in severely obese women before and after bariatric surgery.

Abstract OBJECTIVE: The objective was to evaluate ghrelin and growth hormone (GH) interactions and responses to a growth hormone-releasing hormone (GHRH)/arginine test in severe obesity before and after surgically-induced weight loss. RESEARCH METHODS AND PROCEDURES: Our study population included 11 severely obese women 39 +/- 12 years of age, with a mean BMI of 48.6 +/- 2.4 kg/m2, re-studied in a phase of stabilized body weight, with a BMI of 33.4 +/- 1.2 kg/m2, 18 months after having successfully undergone biliopancreatic diversion (BPD). A GHRH/arginine test was performed before and 18 months after BPD to evaluate ghrelin and GH interactions. Active ghrelin, measured by radioimmunoassay (RIA), and GH, measured by chemiluminescence assay, were assayed before and after the GHRH/arginine test. RESULTS: Fasting serum GH levels and GH area under the curve (AUC) significantly increased from 0.2 +/- 0.05 ng/mL to 1 +/- 0.3 ng/mL (p < 0.05) and from 514.76 +/- 98.7 ng/mL for 120 minutes to 1957.3 +/- 665.1 ng/mL for 120 minutes after bariatric surgery (p < 0.05), respectively. Although no significant change in fasting ghrelin levels was observed (573 +/- 77.9 before BPD vs. 574.1 +/- 32.7 after BPD), ghrelin AUC significantly increased from -3253.9 +/- 2180.9 pg/mL for 120 minutes to 1142.3 +/- 916.4 pg/mL for 120 minutes after BPD (p < 0.05). Fasting serum insulin-like growth factor (IGF)-1 concentration did not change significantly (133.6 +/- 9.9 ng/mL before vs. 153.3 +/- 25.2 ng/mL after BPD). DISCUSSION: Our study demonstrates that the mechanisms involved in ghrelin and GH secretion after the secretagogue stimulus (GHRH/arginine) are consistent with patterns observed in other population

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press