High-resolution analysis of tomato leaf elongation: the application of novel time-series analysis techniques

Characterization of the Temporal Trends in the Rate of Cattle Carcass Condemnations in the US and Dynamic Modeling of the Condemnation Reasons in California With a Seasonal Component

Based on the 2016 National Cattlemen's Beef Association statistics, the cattle inventory in the US reached 93.5 million head, from which 30.5 million were commercial slaughter in 2016. California ranked fourth among all the US states that raise cattle and calves, with 5.15 million head and approximately 1.18 million slaughtered animals per year. Approximately 0.5% of cattle carcasses in the US are condemned each year, which has an important economic impact on cattle producers.In this study, we first described and compared the temporal trends of cattle carcass condemnations in all the US states from Jan-2005 to Dec-2014. Then, we focused on the condemnation reasons with a seasonal component in California and used dynamic harmonic regression (DHR) models both to model (from Jan-2005 to Dec-2011) and predict (from Jan-2012 to Dec-2014) the carcass condemnations rate in different time horizons (3 to 12 months).Data consisted of daily reports of 35 condemnation reasons per cattle type reported in 684 federally inspected slaughterhouses in the US from Jan-2005 to Dec-2014 and the monthly slaughtered animals per cattle type per states. Almost 1.5 million carcasses were condemned in the US during the 10 year study period (Jan 2005-Dec 2014), and around 40% were associated with three condemnation reasons: malignant lymphoma, septicemia and pneumonia. In California, emaciation, eosinophilic myositis and malignant lymphoma were the only condemnation reasons presenting seasonality and, therefore, the only ones selected to be modeled using DHRs. The DHR models for Jan-2005 to Dec-2011 were able to correctly model the dynamics of the emaciation, malignant lymphoma and eosinophilic myositis condemnation rates with coefficient of determination (Rt2) of 0.98, 0.87 and 0.78, respectively. The DHR models for Jan-2012 to Dec-2014 were able to predict the rate of condemned carcasses 3 month ahead of time with mean relative prediction error of 33, 11, and 38%, respectively. The systematic analysis of carcass condemnations and slaughter data in a more real-time fashion could be used to identify changes in carcass condemnation trends and more timely support the implementation of prevention and mitigation strategies that reduce the number of carcass condemnations in the US.

Diel patterns of leaf and root growth: endogenous rhythmicity or environmental response?

Plants are sessile organisms forced to adjust to their surrounding environment. In a single plant the photoautotrophic shoot is exposed to pronounced environmental variations recurring in a day-night 24 h (diel) cycle, whereas the heterotrophic root grows in a temporally less fluctuating environment. The contrasting habitats of shoots and roots are reflected in different diel growth patterns and their responsiveness to environmental stimuli. Differences between diel leaf growth patterns of mono- and dicotyledonous plants correspond to their different organization and placement of growth zones. In monocots, heterotrophic growth zones are organized linearly and protected from the environment by sheaths of older leaves. In contrast, photosynthetically active growth zones of dicot leaves are exposed directly to the environment and show characteristic, species-specific diel growth patterns. It is hypothesized that the different exposure to environmental constraints and simultaneously the sink/source status of the growing organs may have induced distinct endogenous control of diel growth patterns in roots and leaves of monocot and dicot plants. Confronted by strong temporal fluctuations in environment, the circadian clock may facilitate robust intrinsic control of leaf growth in dicot plants.

NeuroRhythmics: software for analyzing time-series measurements of saltatory movements in neuronal processes

Time-lapse imaging of living neurons both in vivo and in vitro has revealed that the growth of axons and dendrites is highly dynamic and characterized by alternating periods of extension and retraction. These growth dynamics are associated with important features of neuronal development and are differentially affected by experimental treatments, but the underlying cellular mechanisms are poorly understood. NeuroRhythmics was developed to semi-automate specific quantitative tasks involved in analysis of two-dimensional time-series images of processes that exhibit saltatory elongation. This software provides detailed information on periods of growth and nongrowth that it identifies by transitions in elongation (i.e. initiation time, average rate, duration) and information regarding the overall pattern of saltatory growth (i.e. time of pattern onset, frequency of transitions, relative time spent in a state of growth vs. nongrowth). Plots and numeric output are readily imported into other applications. The user has the option to specify criteria for identifying transitions in growth behavior, which extends the potential application of the software to neurons of different types or developmental stage and to other time-series phenomena that exhibit saltatory dynamics. NeuroRhythmics will facilitate mechanistic studies of periodic axonal and dendritic growth in neurons.