Phenotype Classification of Zebrafish Embryos by Supervised Learning

Zebrafish is increasingly used to assess biological properties of chemical substances and thus is becoming a specific tool for toxicological and pharmacological studies. The effects of chemical substances on embryo survival and development are generally evaluated manually through microscopic observation by an expert and documented by several typical photographs. Here, we present a methodology to automatically classify brightfield images of wildtype zebrafish embryos according to their defects by using an image analysis approach based on supervised machine learning. We show that, compared to manual classification, automatic classification results in 90 to 100% agreement with consensus voting of biological experts in nine out of eleven considered defects in 3 days old zebrafish larvae. Automation of the analysis and classification of zebrafish embryo pictures reduces the workload and time required for the biological expert and increases the reproducibility and objectivity of this classification.     

Structural Insight of a Trimodular Halophilic Cellulase with a Family 46 Carbohydrate-Binding Module

Cellulases are the key enzymes used in the biofuel industry. A typical cellulase contains a catalytic domain connected to a carbohydrate-binding module (CBM) through a flexible linker. Here we report the structure of an atypical trimodular cellulase which harbors a catalytic domain, a CBM46 domain and a rigid CBM_X domain between them. The catalytic domain shows the features of GH5 family, while the CBM46 domain has a sandwich-like structure. The catalytic domain and the CBM46 domain form an extended substrate binding cleft, within which several tryptophan residues are well exposed. Mutagenesis assays indicate that these residues are essential for the enzymatic activities. Gel affinity electrophoresis shows that these tryptophan residues are involved in the polysaccharide substrate binding. Also, electrostatic potential analysis indicates that almost the entire solvent accessible surface of CelB is negatively charged, which is consistent with the halophilic nature of this enzyme.     

Solving the N-Queens problem with a binary Hopfield-type network

The application of a discrete Hopfield-type neural network to solving the NP-Hard optimization problem — the N-Queens Problem (NQP) — is presented. The applied network is binary, and at every moment each neuron potential is equal to either 0 or 1. The network can be implemented in the asynchronous mode as well as in the synchronous one with n parallel running processors. In both cases the convergence rate is up to 100%, and the experimental estimate of the average computational complexity is polynomial. Based on the computer simulation results and the theoretical analysis, the proper network parameters are established. The behaviour of the network is explained.     

Modeling the Role of Negative Cooperativity in Metabolic Regulation and Homeostasis

A significant proportion of enzymes display cooperativity in binding ligand molecules, and such effects have an important impact on metabolic regulation. This is easiest to understand in the case of positive cooperativity. Sharp responses to changes in metabolite concentrations can allow organisms to better respond to environmental changes and maintain metabolic homeostasis. However, despite the fact that negative cooperativity is almost as common as positive, it has been harder to imagine what advantages it provides. Here we use computational models to explore the utility of negative cooperativity in one particular context: that of an inhibitor binding to an enzyme. We identify several factors which may contribute, and show that acting together they can make negative cooperativity advantageous.     

Application of the Red List Index as an indicator of habitat change

For the first time ever, the International Union for Conservation of Nature Red List Index for habitat types was calculated for an entire country, Finland. The RLIs were based on species threat assessments from 2000 and 2010 and included habitat definitions for all 10,131 species of 12 organism groups. The RLIs were bootstrapped to track statistically significant changes. The RLI changes of species grouped by habitats were negative for all habitat types except for forests and rural biotopes which showed a stable trend. Trends of beetles and true bugs were positive in rural and forest habitats. Other 16 observed trends of species group and habitat combinations were negative. Several trends observed were in accordance with studies focusing on particular taxa and habitats, and drivers for their change. This study demonstrates the usefulness of the RLI as a tool for observing habitat change based on species threat assessment data.     

α‐ketoglutarate delays age‐related fertility decline in mammals

The fecundity reduction with aging is referred as the reproductive aging which comes earlier than that of chronological aging. Since humans have postponed their childbearing age, to prolong the reproductive age becomes urgent agenda for reproductive biologists. In the current study, we examined the potential associations of α‐ketoglutarate (α‐KG) and reproductive aging in mammals including mice, swine, and humans. There is a clear tendency of reduced α‐KG level with aging in the follicle fluids of human. To explore the mechanisms, mice were selected as the convenient animal model. It is observed that a long term of α‐KG administration preserves the ovarian function, the quality and quantity of oocytes as well as the telomere maintaining system in mice. α‐KG suppresses ATP synthase and alterations of the energy metabolism trigger the nutritional sensors to down‐regulate mTOR pathway. These events not only benefit the general aging process but also maintain ovarian function and delay the reproductive decline. Considering the safety of the α‐KG as a naturally occurring molecule in energy metabolism, its utility in reproduction of large mammals including humans deserves further investigation.