Dopamine Gates Visual Signals in Monkey Prefrontal Cortex Neurons

1. Download : Download high-res image (143KB)
2. Download : Download full-size image

     

Morpho-colorimetric characterization by image analysis to identify diaspores of wild plant species

Digital images of ex situ germplasm stored in the Sardinian Germplasm Bank (BG-SAR) were used for the application of image analysis techniques at the Stazione Sperimentale di Granicoltura per la Sicilia. The analysed accessions refer to 148 taxonomic units belonging to 102 genera and 47 families, typical of the Sardinian flora, and of the Mediterranean basin in general.The images of diaspores were acquired by a flatbed scanner and elaborated with a macro specially developed for the morphometric and colorimetric measurements. This method allowed carrying out a database for the characterization of autochthonous germplasm in entry to the bank and the realization of statistic classifiers for the discrimination of genera and species within the following families: Apiaceae, Boraginaceae, Caryophyllaceae, Cistaceae, Fabaceae and Scrophulariaceae. Such classifiers, based on the linear discriminant analysis (LDA) technique and checked by cross-validation, showed a performance included between 74.3% and 96.4%.In addition, for the genus Astragalus, it was possible to elaborate a classifier able to identify very similar taxa of a species complex, obtaining a performance between 83.7% and 100%. Such analysis proved the validity of the methodology also from the taxonomic point of view.Suggestions for subsequent methodological progress, which could offer applications in other research issues, such as ecological analysis, soil seed bank and archaeological botany are proposed.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Effects of serial anesthesia using ketamine or ketamine/medetomidine on hematology and serum biochemistry values in rhesus macaques (Macaca Mulatta)

Background  This study aimed at determining the cumulative effect of daily anesthesia, using two drug regimens, over hematological and biochemical parameters.
Methods  Blood samples were obtained from rhesus monkeys 20 minutes after intramuscular administration of ketamine or ketamine/medetomidine combination for three consecutive days and results were evaluated to determine their effect on hematological and serum biochemistry values. Statistical significance of drug, day, and interaction of these two variables were evaluated.
Results  Drug effect resulted in a dramatic increase of aspartate aminotransferase and creatine kinase values. Day effect resulted in decreases of RBC, HCT, Hgb, and alkaline phosphatase but an increase of other biochemical parameters evaluated. The drug/day interaction effect was found to be –significant for RBC, platelets, aspartate aminotransferase, alanine aminotransferase, and creatine kinase values.
Conclusion  The results of our study suggest a cumulative effect of serial anesthesia and should be an important consideration when interpreting hematology and serum biochemistry in rhesus macaques.     

Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

Fish finders have already been widely available in the fishing market for a number of years.However,the sizes of these fishfinders are too big and their prices are expensive to suit for the research of robotic fish or mini-submarine.The goal of thisresearch is to propose a low-cost fish detector and classifier which suits for underwater robot or submarine as a proximity sensor.With some pre-condition in hardware and algorithms,the experimental results show that the proposed design has good per-formance,with a detection rate of 100 % and a classification rate of 94 %.Both the existing type of fish and the group behaviorcan be revealed by statistical interpretations such as hovering passion and sparse swimming mode.     

Gross intestinal morphometry and allometry in primates

Although it is generally assumed that among mammals and within mammal groups, those species that rely on diets consisting of greater amounts of plant fiber have larger gastrointestinal tracts (GIT), statistical evidence for this simple claim is largely lacking. We compiled a dataset on the length of the small intestine, caecum, and colon in 42 strepsirrhine, platyrrhine, and catarrhine primate species, using specimens with known body mass (BM). We tested the scaling of intestine length with BM, and whether dietary proxies (percentage of leaves and a diet quality index) were significant covariates in these scaling relationships, using two sets of models: one that did not account for the phylogenetic structure of the data, and one that did. Intestine length mainly scaled geometrically at exponents that included 0.33 in the confidence interval; Strepsirrhini exhibited particularly long caeca, while those of Catarrhini were comparatively short. Diet proxies were only significant for the colon and the total large intestine (but not for the small intestine or the caecum), and only in conventional statistics (but not when accounting for phylogeny), indicating the pattern occurred across but not within clades. Compared to terrestrial Carnivora, primates have similar small intestine lengths, but longer large intestines. The data on intestine lengths presented here corroborate recent results on GIT complexity, suggesting that diet, as currently described, does not exhaustively explain GIT anatomy within primate clades.