Automated Food-Procuring Movement-Related Neuronal Activity in the Basolateral Amygdala of the Rat

We studied the impulse activity of neurons of the basal and lateral amygdalar nuclei generated when experimental animals (rats) performed fast stereotyped food-procuring movements by the forelimb. Within the basolateral amygdala, there are neurons whose activity is related to different stages of getting off the food, and according to the characteristics of their spiking these neurons should be divided into a number of subpopulations. Activation forestalling the movement initiation by 0.5-1.0 sec was observed in most neurons of the basolateral amygdala; this is considered a manifestation of excitation related to a motivation component of the food-procuring behavior. Activation of amygdalar neurons following movement initiation can result from generation in this structure of additional excitation necessary for successful performance of a complete food-procuring motor cycle.     

Expression of a lipocalin in prokaryote and eukaryote cells: quantification and structural characterization of recombinant bovine beta-lactoglobulin.

In this paper we quantify and characterize the expression of recombinant beta-lactoglobulin (rBLG) in prokaryote and eukaryote cells. In Escherichia coli we used the pET26 vector, which permits the secretion of rBLG in periplasm. We studied the expression of rBLG in COS-7 cells and in vivo in mouse tibialis muscle. The expression of rBLG was measured by two immunoassays specific, respectively, for BLG in its native and denatured conformation. We observed that rBLG was essentially expressed in a denatured form in E. coli even in the periplasm, whereas rBLG in eukaryote cells was found in its native conformation.     

New sharks of the genus Abdounia (Carcharhiniformes: Carcharhinidae) from the Upper Eocene of the Trans-Ural Region

Two new species of carcharhinid sharks from the Late Eocene deposits (Tavda Formation) of the southern Trans-Urals, Abdounia vassilyevae sp. nov., previously determined as A. aff. beaugei, and A. lata sp. nov., are described. To date, up to five Priabonian species of Abdounia have been recorded. New finds supplement the data on diversity, evolution, and paleobiogeography of Abdounia.     

Non‐pollinating cheater wasps benefit from seasonally poor performance of the mutualistic pollinating wasps at the northern limit of the range of Ficus microcarpa

1. Species interactions in tightly bound ecological mutualisms often feature highly specialised species' roles in which competitive exclusion may preclude multi‐species coexistence. Among the 800 fig (Ficus) species, it was originally considered that each was pollinated by their own wasp (Agaonidae). However, recent investigations show that this ‘one‐to‐one’ rule often breaks down, as fig species regularly host multiple agaonids but in ways suggesting that competitive processes still mediate biodiversity outcomes. 2. A phenological survey was conducted of the fig–fig wasp pair, Ficus microcarpa and its associated pollinating wasp, alongside its sister species, the cheating wasp, in Xishuangbanna, China. 3. Reproductive output underwent extreme seasonal variation. Seed and pollinator production fell markedly during cooler, drier months, although high levels of fig production continued. However, this resource was predominantly utilised by the cheater species, which offers no pollination services. Pollinators and cheaters rarely co‐occur, suggesting that temporal coexistence is constrained by competition for access to figs. 4. The overall findings indicate periodic rearrangements of mutualism dynamics, probably resulting from a strongly seasonal environment. Sympatric co‐occurrence may result from a window of opportunity for a functionally divergent agaonid, potentially due to constraints on the main pollinator in adapting to variable year‐round conditions that prevent competitive exclusion.     

Use of autonomous audio recordings for the rapid inventory of birds in the white‐sand forests of the Peruvian Amazon

White‐sand forests are patchily distributed ecosystems covering just 5% of Amazonia that host many specialist species of birds not found elsewhere, and these forests are threatened due to their small size and human exploitation of sand for construction projects. As a result, many species of birds that are white‐sand specialists are at risk of extinction, and immediate conservation action is paramount for their survival. Our objective was to evaluate current survey methods and determine the relative effect of the size of patches of these forests on the presence or absence of white‐sand specialists. Using point counts and autonomous recorders, we surveyed avian assemblages occupying patches of white‐sand forest in the Peruvian Amazon in April 2018. Overall, we detected 126 species, including 21 white‐sand forest specialists. We detected significantly more species of birds per survey point with autonomous recorders than point counts. We also found a negative relationship between avian species richness and distance from the edge of patches of white‐sand forest, but a significant, positive relationship when only counting white‐sand specialists. Although we detected more species with autonomous recorders, point counts were more effective for detecting canopy‐dwelling passerines. Therefore, we recommend that investigators conducting surveys for rare and patchily distributed species in the tropics use a mixed‐method approach that incorporates both autonomous recorders and visual observation. Finally, our results suggest that conserving large, continuous patches of white‐sand forest may increase the likelihood of survival of species of birds that are white‐sand specialists.     

Nearest Neighbor Classification Rule for Mixtures of Discrete and Continuous Random Variables

In this paper very simple nonparametric classification rule for mixtures of discrete and continuous random variables is described. It is based on the method of nearest neighbor proposed by Cover and Hart (1967). The bounds on the limit of the nearest neighbor rule risks are given. Both lower and upper bound depend on the Bayes risk and the loss function. Finally the method is compared with other existing methods on some practical data set.