Cross-adaptation and molecular modeling study of receptor mechanisms common to four taste stimuli in humans

Psychophysical cross-adaptation experiments were performed with two carbohydrates, sucrose (SUC) and fructose (FRU), and two sweeteners, acesulfame-K (MOD) and dulcin (DUL). Seven subjects were asked to match concentrations that elicited the same intensity as a sucrose reference (30 g/l). Cross-adaptation levels were calculated as the ratio of isointense concentrations measured for a given stimulus before and under adaptation. On average, cross-adaptation between SUC and FRU is low and apparently reciprocal. By contrast, cross-adaptation between SUC and MOD is clearly non-reciprocal: SUC adapts MOD significantly (24%, P < 0.005), but MOD fails to adapt SUC (2%, P < 0.79). Significant and reciprocal cross-enhancement is observed between DUL and MOD (approximately -20%, P < 0.03), and also between SUC and DUL (approximately -15%, P < 0.08). In parallel, molecular modeling of the four tastants was performed in order to look for the 12 common binding motifs that were isolated on 14 other tastants in a previous study. SUC and FRU each display 10 out of the 12 binding motifs, whereas DUL and MOD only display four and five distinct motifs respectively and do not have any motif in common. Experimental cross-adaptation levels seem to correlate well with the number of motifs that molecules have in common. FRU and SUC share a majority of binding motifs and correlatively show mutual cross-adaptation. Four motifs of MOD are found among the 10 motifs of SUC, which may explain why SUC cross-adapts MOD but not vice versa. By contrast, DUL and MOD do not share any motif and do not cross- adapt. The various molecular mechanisms that may be responsible for cross-adaptation and/or cross-enhancement are discussed in light of our results.      

Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information

Background  

Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio.     

The Progressive Increase of Food Waste in America and Its Environmental Impact

Food waste contributes to excess consumption of freshwater and fossil fuels which, along with methane and CO₂ emissions from decomposing food, impacts global climate change. Here, we calculate the energy content of nationwide food waste from the difference between the US food supply and the food consumed by the population. The latter was estimated using a validated mathematical model of metabolism relating body weight to the amount of food eaten. We found that US per capita food waste has progressively increased by ∼50% since 1974 reaching more than 1400 kcal per person per day or 150 trillion kcal per year. Food waste now accounts for more than one quarter of the total freshwater consumption and ∼300 million barrels of oil per year.     

Prolonged cigarette smoke exposure alters mitochondrial structure and function in airway epithelial cells

Background

Cigarette smoking is the major risk factor for COPD, leading to chronic airway inflammation. We hypothesized that cigarette smoke induces structural and functional changes of airway epithelial mitochondria, with important implications for lung inflammation and COPD pathogenesis.

Methods

We studied changes in mitochondrial morphology and in expression of markers for mitochondrial capacity, damage/biogenesis and fission/fusion in the human bronchial epithelial cell line BEAS-2B upon 6-months from ex-smoking COPD GOLD stage IV patients to age-matched smoking and never-smoking controls.

Results

We observed that long-term CSE exposure induces robust changes in mitochondrial structure, including fragmentation, branching and quantity of cristae. The majority of these changes were persistent upon CSE depletion. Furthermore, long-term CSE exposure significantly increased the expression of specific fission/fusion markers (Fis1, Mfn1, Mfn2, Drp1 and Opa1), oxidative phosphorylation (OXPHOS) proteins (Complex II, III and V), and oxidative stress (Mn-SOD) markers. These changes were accompanied by increased levels of the pro-inflammatory mediators IL-6, IL-8, and IL-1β. Importantly, COPD primary bronchial epithelial cells (PBECs) displayed similar changes in mitochondrial morphology as observed in long-term CSE-exposure BEAS-2B cells. Moreover, expression of specific OXPHOS proteins was higher in PBECs from COPD patients than control smokers, as was the expression of mitochondrial stress marker PINK1.

Conclusion

The observed mitochondrial changes in COPD epithelium are potentially the consequence of long-term exposure to cigarette smoke, leading to impaired mitochondrial function and may play a role in the pathogenesis of COPD.     

Antioxidant, cytotoxic and hemolytic effects of sulfated galactans from edible red alga Hypnea musciformis

Polysaccharides, galactans, obtained from edible red seaweed Hypnea musciformis were characterized by molecular weight and infrared spectroscopy analysis and were evaluated for antioxidant activity in vitro and for their effects on cell viability. The main components were galactose and sulfate presenting low protein contamination. These sulfated galactans (F1.0) showed a polydisperse profile, and signs in infrared analysis were attributed to a sulfate ester S?=?O bond, the presence of a 3,6-anhydrogalactose C–O bond, nonsulfated β-d-galactose, and a C–O–SO₄ bond in galactose C4. The NMR analysis showed signals at about 95 and 92 attributed to anomeric carbon of 4-linked 3,6-anhydro-α-d-galactopyranose residue of κ-carrageenans and 4-linked 3,6-anhydro-α-d-galactopyranose2-sulfate of ι-carrageenans. Sulfated galactan F1.0 showed strong antioxidant activity under lipid peroxidation assay where F1.0 at 8 mg mL^?1 promoted 57.92% peroxidation inhibition and displayed the scavenging activity on hydroxyl radicals in a dose-dependent manner leading to 32.5% scavenging of these radicals when 5 mg mL^?1 of sulfated galactan F1.0 was used. The sulfated galactan fraction also exhibited strong inhibition on the H₂O₂-induced hemolysis model. Sulfated galactan F1.0 displayed low cytotoxic action in 3 T3 cells and moderate antitumoral action in HeLa cells. These results suggest that sulfated galactan F1.0 from H. musciformis has antioxidant potential, which is a great effect for a compound used as food and in the food industry.     

Evolution of an adenocarcinoma in response to selection by targeted kinase inhibitors

Background

Adenocarcinomas of the tongue are rare and represent the minority (20 to 25%) of salivary gland tumors affecting the tongue. We investigated the utility of massively parallel sequencing to characterize an adenocarcinoma of the tongue, before and after treatment.

Results

In the pre-treatment tumor we identified 7,629 genes within regions of copy number gain. There were 1,078 genes that exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations, administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A recurring metastasis possessed 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumors and 9 new somatic protein coding mutations. The observed mutations and amplifications were consistent with therapeutic resistance arising through activation of the MAPK and AKT pathways.

Conclusions

We conclude that complete genomic characterization of a rare tumor has the potential to aid in clinical decision making and identifying therapeutic approaches where no established treatment protocols exist. These results also provide direct in vivo genomic evidence for mutational evolution within a tumor under drug selection and potential mechanisms of drug resistance accrual.     

Novel monoclonal antibody-based Helicobacter pylori stool antigen test

BACKGROUND: A number of noninvasive tests have been developed to establish the presence of Helicobacter pylori infection. Although polyclonal antibody-based stool antigen testing has a good sensitivity and specificity, it is less accurate than urea breath testing. Recently, a monoclonal antibody-based stool antigen test demonstrated an excellent performance in diagnosing H. pylori infection in adults and in pediatric populations. AIM: To evaluate the diagnostic accuracy of a novel stool test based on monoclonal antibodies to detect H. pylori antigens in frozen human stool in the pretreatment setting. PATIENTS AND METHODS: Stool specimens were prospectively collected from 78 patients undergoing gastroscopy and stored at -20 degrees C until tested. Helicobacter pylori infection was evaluated by histology, rapid urease testing and urea breath tests ((13)C-UBT). Positivity of the three tests was considered the gold standard for H. pylori active infection. Patients with no positive test were considered negative. The gold standard was compare to the results of the monoclonal antibody stool antigen test. Frozen stool specimens were tested using a novel monoclonal-antibody-based enzyme immunoassay (HePy-Stool, Biolife-Italiana, Milan, Italy). RESULTS: The sensitivity and specificity of the monoclonal stool antigen test were 97%[95% confidence interval, (CI) 86-100] and 94% (95% CI: 81-99), respectively. Negative and positive predictive values were 97% (95% CI: 85-99), and 95% (95% CI: 83-99), respectively. The diagnostic accuracy was 96% (95% CI: 88-99). The likelihood ratio for a positive test was 17 and for a negative test was 0. CONCLUSIONS: Although the (13)C-UBT is the most accurate among the available noninvasive tests, our results show that an H. pylori stool test using monoclonal antibody might be an excellent alternative.     

Predicting expected progeny difference for marbling score in Angus cattle using artificial neural networks and Bayesian regression models

Background

Artificial neural networks (ANN) mimic the function of the human brain and are capable of performing massively parallel computations for data processing and knowledge representation. ANN can capture nonlinear relationships between predictors and responses and can adaptively learn complex functional forms, in particular, for situations where conventional regression models are ineffective. In a previous study, ANN with Bayesian regularization outperformed a benchmark linear model when predicting milk yield in dairy cattle or grain yield of wheat. Although breeding values rely on the assumption of additive inheritance, the predictive capabilities of ANN are of interest from the perspective of their potential to increase the accuracy of prediction of molecular breeding values used for genomic selection. This motivated the present study, in which the aim was to investigate the accuracy of ANN when predicting the expected progeny difference (EPD) of marbling score in Angus cattle. Various ANN architectures were explored, which involved two training algorithms, two types of activation functions, and from 1 to 4 neurons in hidden layers. For comparison, BayesCπ models were used to select a subset of optimal markers (referred to as feature selection), under the assumption of additive inheritance, and then the marker effects were estimated using BayesCπ with π set equal to zero. This procedure is referred to as BayesCpC and was implemented on a high-throughput computing cluster.

Results

The ANN with Bayesian regularization method performed equally well for prediction of EPD as BayesCpC, based on prediction accuracy and sum of squared errors. With the 3K-SNP panel, for example, prediction accuracy was 0.776 using BayesCpC, and ranged from 0.776 to 0.807 using BRANN. With the selected 700-SNP panel, prediction accuracy was 0.863 for BayesCpC and ranged from 0.842 to 0.858 for BRANN. However, prediction accuracy for the ANN with scaled conjugate gradient back-propagation was lower, ranging from 0.653 to 0.689 with the 3K-SNP panel, and from 0.743 to 0.793 with the selected 700-SNP panel.

Conclusions

ANN with Bayesian regularization performed as well as linear Bayesian regression models in predicting additive genetic values, supporting the idea that ANN are useful as universal approximators of functions of interest in breeding contexts.