Assessment of low-dose cisplatin as a model of nausea and emesis in beagle dogs, potential for repeated administration

Cisplatin is a highly emetogenic cancer chemotherapy agent, which is often used to induce nausea and emesis in animal models. The cytotoxic properties of cisplatin also cause adverse events that negatively impact on animal welfare preventing repeated administration of cisplatin. In this study, we assessed whether a low (subclinical) dose of cisplatin could be utilized as a model of nausea and emesis in the dog while decreasing the severity of adverse events to allow repeated administration. The emetic, nausea-like behavior and potential biomarker response to both the clinical dose (70 mg/m2) and low dose (15 mg/m2) of cisplatin was assessed. Plasma creatinine concentrations and granulocyte counts were used to assess adverse effects on the kidneys and bone marrow, respectively. Nausea-like behavior and emesis was induced by both doses of cisplatin, but the latency to onset was greater in the low-dose group. No significant change in plasma creatinine was detected for either dose groups. Granulocytes were significantly reduced compared with baseline (P = 0.000) following the clinical, but not the low-dose cisplatin group. Tolerability of repeated administration was assessed with 4 administrations of an 18 mg/m2 dose cisplatin. Plasma creatinine did not change significantly. Cumulative effects on the granulocytes occurred, they were significantly decreased (P = 0.03) from baseline at 3 weeks following cisplatin for the 4th administration only. Our results suggest that subclinical doses (15 and 18 mg/m2) of cisplatin induce nausea-like behavior and emesis but have reduced adverse effects compared with the clinical dose allowing for repeated administration in crossover studies

Effect of storage temperature on Vitamin C, total phenolics, UPLC phenolic acid profile and antioxidant capacity of eleven potato (Solanum tuberosum) varieties

Storage of potato tubers at low temperature affects their metabolism and may alter their phytochemical properties. There is a need to elucidate the changes in antioxidant compounds, activity and enzymes during storage of tubers. Eleven Indian potato varieties were evaluated for antioxidant parameters, after 0, 30, 60 and 90 days of storage at room temperature, 15 °C and 4 °C. Total phenolics (0.0786–0.1546 mg gallic acid equivalents⋅g−1 FW) and vitamin C content (0.0828–0.2416 mg⋅g−1 FW) varied among the varieties and were different with storage temperature; their levels fluctuated during storage but remained above the initial level until the last day of observation. Phenolic acid profiling by UPLC identified 12 compounds among which the most abundant was chlorogenic acid followed by gallic acid, sinapic acid and ellagic acid. Except para-coumaric acid which decreased at 4 °C, all the phenolic acids increased with storage. Caffeic acid, chlorogenic acid, protocatechuic acid and gallic acid mostly correlated with total phenolic content (r = 0.456, 0.482, 0.588 and 0.620, respectively). Antioxidant activity against both DPPH and ABTS radicals increased during the initial days of storage and then dropped to a level comparable or lower than the original value, irrespective of the storage temperature. Correlation study revealed that chlorogenic acid, gallic acid and ferulic acid mostly contributed to antioxidant activity. Activity of both antioxidant enzymes, superoxide dismutase and ascorbate peroxidase, increased initially but then decreased to values lower than the initial level and were not influenced by storage temperature. Correlation with antioxidant activity indicated that the enhancement of reactive oxygen scavenging species in cold stored tubers could result mainly from ascorbate peroxidase activity. Our results demonstrate that storage temperature adversely influences the metabolism and the content of antioxidant compounds in potato tubers, with subsequent increase on their antioxidant capacity

Improving Breast Cancer Survival Analysis through Competition-Based Multidimensional Modeling

Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models

Breeding Experience and the Heritability of Female Mate Choice in Collared Flycatchers

Heritability in mate preferences is assumed by models of sexual selection, and preference evolution may contribute to adaptation to changing environments. However, mate preference is difficult to measure in natural populations as detailed data on mate availability and mate sampling are usually missing. Often the only available information is the ornamentation of the actual mate. The single long-term quantitative genetic study of a wild population found low heritability in female mate ornamentation in Swedish collared flycatchers. One potentially important cause of low heritability in mate ornamentation at the population level is reduced mate preference expression among inexperienced individuals.Applying animal model analyses to 21 years of data from a Hungarian collared flycatcher population, we found that additive genetic variance was 50 percent and significant for ornament expression in males, but less than 5 percent and non-significant for mate ornamentation treated as a female trait. Female breeding experience predicted breeding date and clutch size, but mate ornamentation and its variance components were unrelated to experience. Although we detected significant area and year effects on mate ornamentation, more than 85 percent of variance in this trait remained unexplained. Moreover, the effects of area and year on mate ornamentation were also highly positively correlated between inexperienced and experienced females, thereby acting to remove difference between the two groups.The low heritability of mate ornamentation was apparently not explained by the presence of inexperienced individuals. Our results further indicate that the expression of mate ornamentation is dominated by temporal and spatial constraints and unmeasured background factors. Future studies should reduce unexplained variance or use alternative measures of mate preference. The heritability of mate preference in the wild remains a principal but unresolved question in evolutionary ecology

Transglutaminase 2 in human diseases

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Bioenergetic status modulates motor neuron vulnerability and pathogenesis in a zebrafish model of spinal muscular atrophy

Degeneration and loss of lower motor neurons is the major pathological hallmark of spinal muscular atrophy (SMA), resulting from low levels of ubiquitously-expressed survival motor neuron (SMN) protein. One remarkable, yet unresolved, feature of SMA is that not all motor neurons are equally affected, with some populations displaying a robust resistance to the disease. Here, we demonstrate that selective vulnerability of distinct motor neuron pools arises from fundamental modifications to their basal molecular profiles. Comparative gene expression profiling of motor neurons innervating the extensor digitorum longus (disease-resistant), gastrocnemius (intermediate vulnerability), and tibialis anterior (vulnerable) muscles in mice revealed that disease susceptibility correlates strongly with a modified bioenergetic profile. Targeting of identified bioenergetic pathways by enhancing mitochondrial biogenesis rescued motor axon defects in SMA zebrafish. Moreover, targeting of a single bioenergetic protein, phosphoglycerate kinase 1 (Pgk1), was found to modulate motor neuron vulnerability in vivo. Knockdown of pgk1 alone was sufficient to partially mimic the SMA phenotype in wild-type zebrafish. Conversely, Pgk1 overexpression, or treatment with terazosin (an FDA-approved small molecule that binds and activates Pgk1), rescued motor axon phenotypes in SMA zebrafish. We conclude that global bioenergetics pathways can be therapeutically manipulated to ameliorate SMA motor neuron phenotypes in vivo

Emerging technologies for the production of renewable liquid transport fuels from biomass sources enriched in plant cell walls

Plant cell walls are composed predominantly of cellulose, a range of non-cellulosic polysaccharides and lignin. The walls account for a large proportion not only of crop residues such as wheat straw and sugarcane bagasse, but also of residues of the timber industry and specialist grasses and other plants being grown specifically for biofuel production. The polysaccharide components of plant cell walls have long been recognized as an extraordinarily large source of fermentable sugars that might be used for the production of bioethanol and other renewable liquid transport fuels. Estimates place annual plant cellulose production from captured light energy in the order of hundreds of billions of tons. Lignin is synthesized in the same order of magnitude and, as a very large polymer of phenylpropanoid residues, lignin is also an abundant, high energy macromolecule. However, one of the major functions of these cell wall constituents in plants is to provide the extreme tensile and compressive strengths that enable plants to resist the forces of gravity and a broad range of other mechanical forces. Over millions of years these wall constituents have evolved under natural selection to generate extremely tough and resilient biomaterials. The rapid degradation of these tough cell wall composites to fermentable sugars is therefore a difficult task and has significantly slowed the development of a viable lignocellulose-based biofuels industry. However, good progress has been made in overcoming this so-called recalcitrance of lignocellulosic feedstocks for the biofuels industry, through modifications to the lignocellulose itself, innovative pre-treatments of the biomass, improved enzymes and the development of superior yeasts and other microorganisms for the fermentation process. Nevertheless, it has been argued that bioethanol might not be the best or only biofuel that can be generated from lignocellulosic biomass sources and that hydrocarbons with intrinsically higher energy densities might be produced using emerging and continuous flow systems that are capable of converting a broad range of plant and other biomasses to bio-oils through so-called 'agnostic' technologies such as hydrothermal liquefaction. Continued attention to regulatory frameworks and ongoing government support will be required for the next phase of development of internationally viable biofuels industries.Hwei-Ting Tan, Kendall R. Corbin and Geoffrey B. Finche

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson’s disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function