Exploring novel objective functions for simulating muscle coactivation in the neck

Musculoskeletal modeling allows for analysis of individual muscles in various situations. However, current techniques to realistically simulate muscle response when significant amounts of intentional coactivation is required are inadequate. This would include stiffening the neck or spine through muscle coactivation in preparation for perturbations or impacts. Muscle coactivation has been modeled previously in the neck and spine using optimization techniques that seek to maximize the joint stiffness by maximizing total muscle activation or muscle force. These approaches have not sought to replicate human response, but rather to explore the possible effects of active muscle. Coactivation remains a challenging feature to include in musculoskeletal models, and may be improved by extracting optimization objective functions from experimental data. However, the components of such an objective function must be known before fitting to experimental data. This study explores the effect of components in several objective functions, in order to recommend components to be used for fitting to experimental data. Four novel approaches to modeling coactivation through optimization techniques are presented, two of which produce greater levels of stiffness than previous techniques. Simulations were performed using OpenSim and MATLAB cooperatively. Results show that maximizing the moment generated by a particular muscle appears analogous to maximizing joint stiffness. The approach of optimizing for maximum moment generated by individual muscles may be a good candidate for developing objective functions that accurately simulate muscle coactivation in complex joints. This new approach will be the focus of future studies with human subjects.     

Asymmetric synthesis and receptor activity of chiral simplified resiniferatoxin (sRTX) analogues as transient receptor potential vanilloid 1 (TRPV1) ligands

The chiral isomers of the two potent simplified RTX-based vanilloids, compounds 2 and 3, were synthesized employing highly enantioselective PTC alkylation and evaluated as hTRPV1 ligands. The analysis indicated that the R-isomer was the eutomer in binding affinity and functional activity. The agonism of compound 2R was comparable to that of RTX. Docking analysis of the chiral isomers of 3 suggested the basis for its stereospecific activity and the binding mode of 3R.     

Function2Form Bridge—Toward synthetic protein holistic performance prediction

Protein engineering and synthetic biology stand to benefit immensely from recent advances in silico tools for structural and functional analyses of proteins. In the context of designing novel proteins, current in silico tools inform the user on individual parameters of a query protein, with output scores/metrics unique to each parameter. In reality, proteins feature multiple “parts”/functions and modification of a protein aimed at altering a given part, typically has collateral impact on other protein parts. A system for prediction of the combined effect of design parameters on the overall performance of the final protein does not exist. Function2Form Bridge (F2F-Bridge) attempts to address this by combining the scores of different design parameters pertaining to the protein being analyzed into a single easily interpreted output describing overall performance. The strategy comprises of (a) a mathematical strategy combining data from a myriad of in silico tools into an OP-score (a singular score informing on a user-defined overall performance) and (b) the F2F Plot, a graphical means of informing the wetlab biologist holistically on designed construct suitability in the context of multiple parameters, highlighting scope for improvement. F2F predictive output was compared with wetlab data from a range of synthetic proteins designed, built, and tested for this study. Statistical/machine learning approaches for predicting overall performance, for use alongside the F2F plot, were also examined. Comparisons between wetlab performance and F2F predictions demonstrated close and reliable correlations. This user-friendly strategy represents a pivotal enabler in increasing the accessibility of synthetic protein building and de novo protein design.     

Refining predictions of climate change impacts on plant species distribution through the use of local statistics

Bioclimate envelope models are often used to predict changes in species distribution arising from changes in climate. These models are typically based on observed correlations between current species distribution and climate data. One limitation of this basic approach is that the relationship modelled is assumed to be constant in space; the analysis is global with the relationship assumed to be spatially stationary. Here, it is shown that by using a local regression analysis, which allows the relationship under study to vary in space, rather than conventional global regression analysis it is possible to increase the accuracy of bioclimate envelope modelling. This is demonstrated for the distribution of Spotted Meddick in Great Britain using data relating to three time periods, including predictions for the 2080s based on two climate change scenarios. Species distribution and climate data were available for two of the time periods studied and this allowed comparison of bioclimate envelope model outputs derived using the local and global regression analyses. For both time periods, the area under the receiver operating characteristics curve derived from the analysis based on local statistics was significantly higher than that from the conventional global analysis; the curve comparisons were also undertaken with an approach that recognised the dependent nature of the data sets compared. Marked differences in the future distribution of the species predicted from the local and global based analyses were evident and highlight a need for further consideration of local issues in modelling ecological variables.     

The discovery of reverse tricyclic pyridone JAK2 inhibitors. Part 2: Lead optimization

This communication discusses the discovery of novel reverse tricyclic pyridones as inhibitors of Janus kinase 2 (JAK2). By using a kinase cross screening approach coupled with molecular modeling, a unique inhibitor–water interaction was discovered to impart excellent broad kinase selectivity. Improvements in intrinsic potency were achieved by utilizing a rapid library approach, while targeted structural changes to lower lipophilicity led to improved rat pharmacokinetics. This multi-pronged approach led to the identification of 31, which demonstrated encouraging rat pharmacokinetics, in vivo potency, and excellent off-target kinase selectivity.     

Lactate modeling and its application to endurance training

1. 1. In this short review, previous studies regarding the modeling of lactate (La) response to exercise and its application to endurance training have been summarized.

2. 2. Additionally the result of a recent study by the present authors are shown.

3. 3. Several models for La response to step and ramp exercise are already proposed and deductions derived from them are used for practical purposes such as the prediction of race performance in middle-and long-distance runners as well as for construction of their training regimens.

4. 4. Only a limited number of models however have tried to quantify whole body La kinetics to exercise in humans concomitantly with describing physiological mechanisms underlying the observed phenomenon.

5. 5. In a recent study described further in this paper a 2 compartment model was used for the purpose of clarifying the current “La production vs degradation” controversy during La adaptation to training.

6. 6. It was determined from this investigation that the La metabolic clearance rate during recovery is enhanced by the endurance training.

7. 7. This is in accordance with another recent observation of an increased La metabolic clearance rate at high absolute work rates and all relative work rates during exercise.

Gas7b (Growth Arrest Specific Protein 7b) Regulates Neuronal Cell Morphology by Enhancing Microtubule and Actin Filament Assembly

Neurons undergo several morphological changes as a part of normal neuron maturation process. Alzheimer disease is associated with increased neuroproliferation and impaired neuronal maturation. In this study, we demonstrated that Gas7b (growth arrest specific protein 7b) expression in a neuronal cell line, Neuro 2A, induces cell maturation by facilitating formation of dendrite-like processes and/or filopodia projections and that Gas7b co-localizes with neurite microtubules. Molecular analysis was performed to evaluate whether Gas7b associates with actin filaments and microtubules, and the data revealed two novel roles of Gas7b in neurite outgrowth: we showed that Gas7b enhances bundling of several microtubule filaments and connects microtubules with actin filaments. These results suggest that Gas7b governs neural cell morphogenesis by enhancing the coordination between actin filaments and microtubules. We conclude that lower neuronal Gas7b levels may impact Alzheimer disease progression.     

Selection of Powdery Mildew and Yellow Mosaic-Resistant Greengram Plants Regenerated Through Organogenesis

Several regenerants through organogenesis were obtained in greengram ( Vigna radiata L. wilczek). Cytokinins appear to be important in inducing organogenesis and IAA induces root induction. Heritable variations could be seen among organogenesis regenerants. Some of the regenerants showed resistance to powdery mildew while some others showed resistance to yellow mosaic virus disease. The disease resistant characters were stable also in R 3 and R 4 generations.     

β-Amyloid (Aβ) Oligomers Impair Brain-derived Neurotrophic Factor Retrograde Trafficking by Down-regulating Ubiquitin C-terminal Hydrolase,UCH-L1

We previously found that BDNF-dependent retrograde trafficking is impaired in AD transgenic mouse neurons. Utilizing a novel microfluidic culture chamber, we demonstrate that Aβ oligomers compromise BDNF-mediated retrograde transport by impairing endosomal vesicle velocities, resulting in impaired downstream signaling driven by BDNF/TrkB, including ERK5 activation, and CREB-dependent gene regulation. Our data suggest that a key mechanism mediating the deficit involves ubiquitin C-terminal hydrolase L1 (UCH-L1), a deubiquitinating enzyme that functions to regulate cellular ubiquitin. Aβ-induced deficits in BDNF trafficking and signaling are mimicked by LDN (an inhibitor of UCH-L1) and can be reversed by increasing cellular UCH-L1 levels, demonstrated here using a transducible TAT-UCH-L1 strategy. Finally, our data reveal that UCH-L1 mRNA levels are decreased in the hippocampi of AD brains. Taken together, our data implicate that UCH-L1 is important for regulating neurotrophin receptor sorting to signaling endosomes and supporting retrograde transport. Further, our results support the idea that in AD, Aβ may down-regulate UCH-L1 in the AD brain, which in turn impairs BDNF/TrkB-mediated retrograde signaling, compromising synaptic plasticity and neuronal survival.