Genomic imprints of unparalleled growth.

Chlorella ohadii was isolated from desert biological soil crusts, one of the harshest habitats on Earth, and is emerging as an exciting new green model for studying growth, photosynthesis and metabolism under a wide range of conditions. Here, we compared the genome of C. ohadii, the fastest growing alga on record, to that of other green algae, to reveal the genomic imprints empowering its unparalleled growth rate and resistance to various stressors, including extreme illumination.

CO-labelling and Sampling in Algae for Flux Analysis of Photosynthetic and Central Carbon Metabolism.

The flux in photosynthesis can be studied by performing CO pulse labelling and analysing the temporal labelling kinetics of metabolic intermediates using gas or liquid chromatography linked to mass spectrometry. Metabolic flux analysis (MFA) is the primary approach for analysing metabolic network function and quantifying intracellular metabolic fluxes. Different MFA approaches differ based on the metabolic state (steady vs.

A machine vision system to detect and count laying hens in battery cages.

Manually counting hens in battery cages on large commercial poultry farms is a challenging task: time-consuming and often inaccurate. Therefore, the aim of this study was to develop a machine vision system that automatically counts the number of hens in battery cages. Automatically counting hens can help a regulatory agency or inspecting officer to estimate the number of living birds in a cage and, thus animal density, to ensure that they conform to government regulations or quality certification requirements.

Guidelines for multi-model comparisons of the impact of infectious disease interventions.

Background: Despite the increasing popularity of multi-model comparison studies and their ability to inform policy recommendations, clear guidance on how to conduct multi-model comparisons is not available. Herein, we present guidelines to provide a structured approach to comparisons of multiple models of interventions against infectious diseases. The primary target audience for these guidelines are researchers carrying out model comparison studies and policy-makers using model comparison studies to inform policy decisions.