The Influence of Modest Weight Gain on Taste and Smell Acuity in College Freshmen

Poster from the 2016 Food & Nutrition Conference & Expo. Poster Session: Food/Nutrition Science; Education; Management; Food Services/Culinary; Research

Peer Mentoring in College Freshmen: Effects on Physical and Mental Health

Poster from the 2018 Food & Nutrition Conference & Expo. Poster Session: Wellness and Public Health

Weight Gain and Decreased Sleep Duration in First-Year College Students: A Longitudinal Study

Poster from the 2017 Food & Nutrition Conference & Expo. Poster Session: Professional Skills; Nutrition Assessment & Diagnosis; Medical Nutrition Therapy

Data approximation strategies between generalized line scales and the influence of labels and spacing

Comparing sensory data gathered using different line scales is challenging. We tested whether adding internal labels to a generalized visual analog scale (gVAS) would improve comparability to a typical generalized labeled magnitude scale (gLMS). Untrained participants evaluated cheeses using one of four randomly assigned scales. Normalization to a cross‐modal standard and/or two gLMS transformations were applied to the data. Response means and distributions were lower for the gLMS than the gVAS, but no difference in resolving power was detected. The presence of labels, with or without line markings, caused categorical‐like lumping of responses. Closer low‐end label spacing for gLMS increased influenced participants to mark near higher intensity labels when they were evaluating low‐intensity samples. Although normalization reduced differences between scales, neither transformation nor normalization was supported as appropriate gLMS/gVAS approximation strategies. This study supports previous observations that neither scale offers a systematic advantage and that participant usage differences limit direct scale comparisons

Automated causal inference in application to randomized controlled clinical trials

Randomized controlled trials (RCTs) are considered the gold standard for testing causal hypotheses in the clinical domain; however, the investigation of prognostic variables of patient outcome in a hypothesized cause–effect route is not feasible using standard statistical methods. Here we propose a new automated causal inference method (AutoCI) built on the invariant causal prediction (ICP) framework for the causal reinterpretation of clinical trial data. Compared with existing methods, we show that the proposed AutoCI allows one to clearly determine the causal variables of two real-world RCTs of patients with endometrial cancer with mature outcome and extensive clinicopathological and molecular data. This is achieved via suppressing the causal probability of non-causal variables by a wide margin. In ablation studies, we further demonstrate that the assignment of causal probabilities by AutoCI remains consistent in the presence of confounders. In conclusion, these results confirm the robustness and feasibility of AutoCI for future applications in real-world clinical analysis

Pharmacokinetic Modeling of Non-Linear Brain Distribution of Fluvoxamine in the Rat

Introduction. A pharmacokinetic (PK) model is proposed for estimation of total and free brain concentrations of fluvoxamine. Materials and methods. Rats with arterial and venous cannulas and a microdialysis probe in the frontal cortex received intravenous infusions of 1, 3.7 or 7.3 mg.kg j1 of fluvoxamine. Analysis. With increasing dose a disproportional increase in brain concentrations was observed. Th

Prognostic Integrated Image-Based Immune and Molecular Profiling in Early-Stage Endometrial Cancer

Optimum risk stratification in early-stage endometrial cancer (EC) combines clinicopathological factors and the molecular EC classification defined by The Cancer Genome Atlas (TCGA). It is unclear whether analysis of intratumoral immune infiltrate improves this. We developed a machine-learning image-based algorithm to quantify density of CD8+ and CD103+ immune cells in tumor epithelium and stroma in 695 stage I endometrioid ECs from the PORTEC-1&-2 trials. The relationship between immune cell density and clinicopathological/molecular factors was analyzed by hierarchical clustering and multiple regression. The prognostic value of immune infiltrate by cell type and location was analyzed by univariable and multivariable Cox regression, incorporating the molecular EC classification. Tumor-infiltrating immune cell density varied substantially between cases, and more modestly by immune cell type and location. Clustering revealed three groups with high, intermediate and low densities, with highly significant variation in the proportion of molecular EC subgroups between them. Univariable analysis revealed intraepithelial CD8+ cell density as the strongest predictor of EC recurrence; multivariable analysis confirmed this was independent of pathological factors and molecular subgroup. Exploratory analysis suggested this association was not uniform across molecular subgroups, but greatest in tumors with mutant p53 and absent in DNA mismatch repair deficient cancers. Thus, this work identified that quantification of intraepithelial CD8+ cells improved upon the prognostic utility of the molecular EC classification in early-stage EC

Quantification of toxins in a Cry1Ac + CpTI cotton cultivar and its potential effects on the honey bee Apis mellifera L.

Transgenic Cry1Ac + CpTI cotton (CCRI41) is increasingly planted throughout China. However, negative effects of this cultivar on the honey bee Apis mellifera L., the most important pollinator for cultivated ecosystem, remained poorly investigated. The objective of our study was to evaluate the potential side effects of transgenic Cry1Ac + CpTI pollen from cotton on young adult honey bees A. mellifera L. Two points emphasized the significance of our study: (1) A higher expression level of insecticidal protein Cry1Ac in pollen tissues was detected (when compared with previous reports). In particular, Cry1Ac protein was detected at 300 ± 4.52 ng g−1 [part per billion (ppb)] in pollen collected in July, (2) Effects on chronic mortality and feeding behaviour in honey bees were evaluated using a no-choice dietary feeding protocol with treated pollen, which guarantee the highest exposure level to bees potentially occurring in natural conditions (worst case scenario). Tests were also conducted using imidacloprid-treated pollen at a concentration of 48 ppb as positive control for sublethal effect on feeding behaviour. Our results suggested that Cry1Ac + CpTI pollen carried no lethal risk for honey bees. However, during a 7-day oral exposure to the various treatments (transgenic, imidacloprid-treated and control), honey bee feeding behaviour was disturbed and bees consumed significantly less CCRI41 cotton pollen than in the control group in which bees were exposed to conventional cotton pollen. It may indicate an antifeedant effect of CCRI41 pollen on honey bees and thus bees may be at risk because of large areas are planted with transgenic Bt cotton in China. This is the first report suggesting a potential sublethal effect of CCRI41 cotton pollen on honey bees. The implications of the results are discussed in terms of risk assessment for bees as well as for directions of future work involving risk assessment of CCRI41 cotton

Molecular and Clinicopathologic Characterization of Mismatch Repair-Deficient Endometrial Carcinoma Not Related to MLH1 Promoter Hypermethylation

Universal tumor screening in endometrial carcinoma (EC) is increasingly adopted to identify individuals at risk of Lynch syndrome (LS). These cases involve mismatch repair-deficient (MMRd) EC without MLH1 promoter hypermethylation (PHM). LS is confirmed through the identification of germline MMR pathogenic variants (PV). In cases where these are not detected, emerging evidence highlights the significance of double-somatic MMR gene alterations as a sporadic cause of MMRd, alongside POLE/POLD1 exonuclease domain (EDM) PV leading to secondary MMR PV. Our understanding of the incidence of different MMRd EC origins not related to MLH1-PHM, their associations with clinicopathologic characteristics, and the prognostic implications remains limited. In a combined analysis of the PORTEC-1, -2, and -3 trials (n = 1254), 84 MMRd EC not related to MLH1-PHM were identified that successfully underwent paired tumor–normal tissue next-generation sequencing of the MMR and POLE/POLD1 genes. Among these, 37% were LS associated (LS-MMRd EC), 38% were due to double-somatic hits (DS-MMRd EC), and 25% remained unexplained. LS-MMRd EC exhibited higher rates of MSH6 (52% vs 19%) or PMS2 loss (29% vs 3%) than DS-MMRd EC, and exclusively showed MMR-deficient gland foci. DS-MMRd EC had higher rates of combined MSH2/MSH6 loss (47% vs 16%), loss of >2 MMR proteins (16% vs 3%), and somatic POLE-EDM PV (25% vs 3%) than LS-MMRd EC. Clinicopathologic characteristics, including age at tumor onset and prognosis, did not differ among the various groups. Our study validates the use of paired tumor–normal next-generation sequencing to identify definitive sporadic causes in MMRd EC unrelated to MLH1-PHM. MMR immunohistochemistry and POLE-EDM mutation status can aid in the differentiation between LS-MMRd EC and DS-MMRd EC. These findings emphasize the need for integrating tumor sequencing into LS diagnostics, along with clear interpretation guidelines, to improve clinical management. Although not impacting prognosis, confirmation of DS-MMRd EC may release patients and relatives from burdensome LS surveillance