Tropical terrestrial invertebrates—Where to from here?

There are over one million described invertebrate species on Earth, the majority of which are likely to inhabit the highly biodiverse rain forests around the equator. These are some of the most vulnerable ecosystems on Earth due to the pressures of deforestation and climate change with many of their inhabitants at risk of extinction. Invertebrates play a major role in ecosystem functioning from decomposition and nutrient cycling to herbivory and pollination; however, while our understanding of these roles is improving, we are far from being able to predict the consequences of further deforestation, climate change, and biodiversity loss due to the lack of comparative data and the high proportion of species which remain to be discovered. As we move into an era of increased pressure on old-growth habitats and biodiversity, it is imperative that we understand how changes to invertebrate communities, and the extinction of species, affect ecosystems. Innovative and comprehensive methods that approach these issues are needed. Here, we highlight priorities for future tropical terrestrial invertebrate research such as the efficiency of sustainable land management, exploration of innovative methods for better understanding of invertebrate ecology and behavior, and quantifying the role of invertebrates in ecosystem functioning.     

Unloading of the soleus in tail-suspended rats increases the number of intrafusal fibers in muscle spindles

Transmission electron microscopy was used to study the ultrastructure of muscle spindles (encapsulated stretch receptors) in m. soleus of adult Wistar rats after repeated hindlimb unloading. It was shown that the unloaded soleus contained not only spindles with a typical number of intrafusal fibers (four) but also spindles with five or six fibers. The increase in the number of intrafusal fibers in muscle spindles of the unloaded animals is likely to be caused by the proliferation of their satellite cells (myoblasts).     

Transients of delayed fluorescence induction signal and photosynthetic antennas: A possible relationship. Mathematical modeling approach

A mathematical model was developed for resolved temporal transients of experimentally recorded delayed fluorescence (DF) induction signal. During an intermittent light regime, antennas of the photosynthetic apparatus were treated as targets, repeatedly hit by potentially absorbable photons within a series of consecutive light flashes. Formulas were derived for the number of antennas, cumulatively hit by a specific number of photons, as a function of the flash serial number (time). Model parameters included number of absorbable photons in one flash, antenna sizes, and their number. A series of induction curves were analyzed, obtained from a Zea mays leaf segment and differing in the previous dark period (t _d). Each curve, consisting of the two most prominent DF transients (C and D), was fitted with several model types, differing in the number of absorbed photons. For both transients, the best fitting result was achieved when DF induction was linked to the second absorbed photon. As expected, model parameters related to antenna sizes showed weaker dependence on t _d than those referring to antenna number. With restrictions applied to this model, the two DF induction transients may be related to two classes of photosynthetic antennas. Their different sizes may have a predominant influence on the efficiency of photon absorption and possibly time-dependent appearance of DF transients. Published in Russian in Fiziologiya Rastenii, 2006, Vol. 53, No. 3, pp. 325–335. The text was submitted by the authors in English.     

Morpho-functional principle of neuroendocrine system analysis

A new approach to the analysis of the neuroendocrine system (NES) is suggested. It is based on the fact of structural and metabolic determination of any effect on cell and cell aggregates. The principle of a common communication channel in the NES is formulated and a possible method of its formalization is proposed.     

Towards a matrix mechanics framework for dynamic protein network

Protein–protein interaction networks are currently visualized by software generated interaction webs based upon static experimental data. Current state is limited to static, mostly non-compartmental network and non time resolved protein interactions. A satisfactory mathematical foundation for particle interactions within a viscous liquid state (situation within the cytoplasm) does not exist nor do current computer programs enable building dynamic interaction networks for time resolved interactions. Building mathematical foundation for intracellular protein interactions can be achieved in two increments (a) trigger and capture the dynamic molecular changes for a select subset of proteins using several model systems and high throughput time resolved proteomics and, (b) use this information to build the mathematical foundation and computational algorithm for a compartmentalized and dynamic protein interaction network. Such a foundation is expected to provide benefit in at least two spheres: (a) understanding physiology enabling explanation of phenomenon such as incomplete penetrance in genetic disorders and (b) enabling several fold increase in biopharmaceutical production using impure starting materials.     

Extended N6 substitution of rigid C2-arylethynyl nucleosides for exploring the role of extracellular loops in ligand recognition at the A3 adenosine receptor

2-Arylethynyl-(N)-methanocarba adenosine 5′-methyluronamides containing rigid N⁶-(trans-2-phenylcyclopropyl) and 2-phenylethynyl groups were synthesized as agonists for probing structural features of the A₃ adenosine receptor (AR). Radioligand binding confirmed A₃AR selectivity and N⁶-1S,2R stereoselectivity for one diastereomeric pair. The environment of receptor-bound, conformationally constrained N⁶ groups was explored by docking to an A₃AR homology model, indicating specific hydrophobic interactions with the second extracellular loop able to modulate the affinity profile. 2-Pyridylethynyl derivative 18 was administered orally in mice to reduce chronic neuropathic pain in the chronic constriction injury model.     

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.

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.     

Graphical modeling for gene set analysis: A critical appraisal

Current demand for understanding the behavior of groups of related genes, combined with the greater availability of data, has led to an increased focus on statistical methods in gene set analysis. In this paper, we aim to perform a critical appraisal of the methodology based on graphical models developed in Massa et al. ( 2010 ) that uses pathway signaling networks as a starting point to develop statistically sound procedures for gene set analysis. We pay attention to the potential of the methodology with respect to the organizational aspects of dealing with such complex but highly informative starting structures, that is pathways. We focus on three themes: the translation of a biological pathway into a graph suitable for modeling, the role of shrinkage when more genes than samples are obtained, the evaluation of respondence of the statistical models to the biological expectations. To study the impact of shrinkage, two simulation studies will be run. To evaluate the biological expectation we will use data from a network with known behavior that offer the possibility of carrying out a realistic check of respondence of the model to changes in the experimental conditions.