Heat stress is one of the most critical issues jeopardising animal welfare and productivity during the warm season in dairy cattle farms. The global trend of increase in average and peak temperatures is making the problem more and more serious. Many devices have been introduced in livestock farms to monitor and control temperature-humidity index, as well as animal behaviour and production parameters. The consequent availability of collected databases has increasingly enhanced the research aimed to understand the consequences of heat stress in cattle, in relation to genetic, reproductive, productive and behavioural features. Moreover, these investigations laid the foundations for the development, calibration, validation and test of numerical models quantifying the individual responses to heat stress conditions. In this work, a generalised additive model with mixed effects has been developed to analyse the relationship between milk production, animal behaviour and environmental parameters based on data surveyed in 2016 in an Italian dairy farm. Each cow has been characterised in terms of her response to heat conditions, and the results led to define three classes of susceptibility to heat stress within the herd. These attributes have then been related to the various phenotypic parameters collected by the precision livestock farming devices used in the farm. The study provides a model to understand the effects of heat stress conditions on individual animals in relation to the main parameters describing their rearing conditions; moreover, the results contribute to improve the herd management by lending indications to define targeted treatments according to the cow’s characteristics. 相似文献
Rescoring of mass spectrometry (MS) search results using spectral predictors can strongly increase peptide spectrum match (PSM) identification rates. This approach is particularly effective when aiming to search MS data against large databases, for example, when dealing with nonspecific cleavage in immunopeptidomics or inflation of the reference database for noncanonical peptide identification. Here, we present inSPIRE (in silico Spectral Predictor Informed REscoring), a flexible and performant open-source rescoring pipeline built on Prosit MS spectral prediction, which is compatible with common database search engines. inSPIRE allows large-scale rescoring with data from multiple MS search files, increases sensitivity to minor differences in amino acid residue position, and can be applied to various MS sample types, including tryptic proteome digestions and immunopeptidomes. inSPIRE boosts PSM identification rates in immunopeptidomics, leading to better performance than the original Prosit rescoring pipeline, as confirmed by benchmarking of inSPIRE performance on ground truth datasets. The integration of various features in the inSPIRE backbone further boosts the PSM identification in immunopeptidomics, with a potential benefit for the identification of noncanonical peptides. 相似文献
An experimental study with captive individuals and study of video recordings of wild monkeys explored whether and how tufted capuchin monkeys use onehand to hold one or more objects with multiple grips (compound grips). A task designed to elicit compound grip was presented to five captive tufted capuchin monkeys (Sapajus spp). The monkeys held one to four balls in onehand and dropped the balls individually into a vertical tube. Multiple simple grips and independent digit movements enabled separate control of multiple objects in one hand. Monkeys always supported the wrist on the horizontal edge of the tube before releasing the ball. Increasing the number of balls decreased the likelihood that the monkeys managed the task. Wild bearded capuchins (Sapajus libidinosus) used compound grips spontaneously to store multiple food items. Compound grips have been described in macaques, gorillas, chimpanzees, and humans, and now in a New World primate. We predict that any primate species that exhibits precision grips and independent digit movement can perform compound grips. Our findings suggest many aspects of compound grip that await investigation. 相似文献
Introduction: Cancer is one of the leading causes of morbidity and mortality worldwide. A hallmark of cancer is evasion of apoptosis leading to tumor progression and drug resistance. Biomarker research has become a sign of the times, and proteins involved in apoptosis may be used for clinical diagnostic or prognostic purposes in cancer treatment. The recent progress in proteomic technology has triggered an emerging number of researchers to study the molecular mechanisms that regulate the apoptotic signal transduction pathways in cancer.
Areas covered: A PubMed search for ‘Proteomics’ and ‘cancer’ and ‘chemotherapy’ and ‘apoptosis’ has been conducted for literature until December 2017.
Results: The study of apoptotic protein signatures in cancer provides valuable information for more effective prognosis, response to therapy and the identification of novel drug targets. A huge number of bioinformatic tools are available to interpret raw data. For quantification, mass spectrometry is the most reliable technique.
Expert commentary: This field of research is, however, still in its infancy and more intensive research is warranted to explore the full potential of biomarkers for clinical use. Progress in this field is influenced by the detection limit of current quantification methods as well as patient and cancer inter-individual profiles. 相似文献