Adaptation of prelimbic cortex mediated by IL-6/STAT3/Acp5 pathway contributes to the comorbidity of neuropathic pain and depression in rats.

BACKGROUND: The adaption of brain region is fundamental to the development and maintenance of nervous system disorders. The prelimbic cortex (PrL) participates in the affective components of the pain sensation. However, whether and how the adaptation of PrL contributes to the comorbidity of neuropathic pain and depression are unknown. METHODS: Using resting-state functional magnetic resonance imaging (rs-fMRI), genetic knockdown or overexpression, we systematically investigated the activity of PrL region in the pathogenesis of neuropathic pain/depression comorbid using the combined approaches of immunohistochemistry, electrophysiology, and behavior. RESULTS: The activity of PrL and the excitability of pyramidal neurons were decreased, and the osteoclastic tartrate-resistant acid phosphatase 5 (Acp5) expression in PrL neurons was upregulated following the acquisition of spared nerve injury (SNI)-induced comorbidity. Genetic knockdown of Acp5 in pyramidal neurons, but not parvalbumin (PV) neurons or somatostatin (SST) neurons, attenuated the decrease of spike number, depression-like behavior and mechanical allodynia in comorbidity rats. Overexpression of Acp5 in PrL pyramidal neurons decreased the spike number and induced the comorbid-like behavior in naïve rats. Moreover, the expression of interleukin-6 (IL-6), phosphorylated STAT3 (p-STAT3) and acetylated histone H3 (Ac-H3) were significantly increased following the acquisition of comorbidity in rats. Increased binding of STAT3 to the Acp5 gene promoter and the interaction between STAT3 and p300 enhanced acetylation of histone H3 and facilitated the transcription of Acp5 in PrL in the modeled rodents. Inhibition of IL-6/STAT3 pathway prevented the Acp5 upregulation and attenuated the comorbid-like behaviors in rats. CONCLUSIONS: These data suggest that the adaptation of PrL mediated by IL-6/STAT3/Acp5 pathway contributed to the comorbidity of neuropathic pain/depression induced by SNI.

Low-Light Image Enhancement via the Absorption Light Scattering Model.

Low light often leads to poor image visibility, which can easily affect the performance of computer vision algorithms. First, this paper proposes the absorption light scattering model (ALSM), which can be used to reasonably explain the absorbed light imaging process for low-light images. In addition, the absorbing light scattering image obtained via ALSM under a sufficient and uniform illumination can reproduce hidden outlines and details from the low-light image. Then, we identify that the minimum channel of ALSM obtained above exhibits high local similarity. This similarity can be constrained by superpixels, which effectively prevent the use of gradient operations at the edges so that the noise is not amplified quickly during enhancement. Finally, by analyzing the monotonicity between the scene reflection and the atmospheric light or transmittance in ALSM, a new low-light image enhancement method is identified. We replace atmospheric light with inverted atmospheric light to reduce the contribution of atmospheric light in the imaging results. Moreover, a soft jointed mean-standard-deviation (MSD) mechanism is proposed that directly acts on the patches represented by the superpixels. The MSD can obtain a smaller transmittance than that obtained by the minimum strategy, and it can be automatically adjusted according to the information of the image. The experiments on challenging low-light images are conducted to reveal the advantages of our method compared with other powerful techniques.

Detangling the Effects of Environmental Filtering and Dispersal Limitation on Aggregated Distributions of Tree and Shrub Species: Life Stage Matters.

The pervasive pattern of aggregated tree distributions in natural communities is commonly explained by the joint effect of two clustering processes: environmental filtering and dispersal limitation, yet little consensus remains on the relative importance of the two clustering processes on tree aggregations. Different life stages of examined species were thought to be one possible explanation of this disagreement, because the effect of environmental filtering and dispersal limitation are expected to increase and decrease with tree life stages, respectively. However, few studies have explicitly tested these expectations. In this study, we evaluated these expectations by three different methods (species-habitat association test based on Poisson Clustering model and spatial point pattern analyses based on Heterogeneous Poisson model and the jointly modeling approach) using 36 species in a 20-ha subtropical forest plot. Our results showed that the percentage of species with significant habitat association increased with life stages, and there were fewer species affected by dispersal limitation in later life stages compared with those in earlier stages. Percentage of variance explained by the environmental filtering and dispersal limitation also increases and decreases with life stages. These results provided a promising alternative explanation on the existing mixed results about the relative importance of the two clustering processes. These findings also highlighted the importance of plant life stages for fully understanding species distributions and species coexistence.

[Applicability analysis of spatially explicit model of leaf litter in evergreen broad-leaved forests].

The spatially explicit model of leaf litter can help to understand its dispersal process, which is very important to predict the distribution pattern of leaves on the surface of the earth. In this paper, the spatially explicit model of leaf litter was developed for 20 tree species using litter trap data from the mapped forest plot in an evergreen broad-leaved forest in Tiantong, Zhejiang Pro- vince, eastern China. Applicability of the model was analyzed. The model assumed an allometric equation between diameter at breast height (DBH) and leaf litter amount, and the leaf litter declined exponentially with the distance. Model parameters were estimated by the maximum likelihood method. Results showed that the predicted and measured leaf litter amounts were significantly correlated, but the prediction accuracies varied widely for the different tree species, averaging at 49.3% and ranging from 16.0% and 74.0%. Model qualities of tree species significantly correlated with the standard deviations of the leaf litter amount per trap, DBH of the tree species and the average leaf dry mass of tree species. There were several ways to improve the forecast precision of the model, such as installing the litterfall traps according to the distribution of the tree to cover the different classes of the DBH and distance apart from the parent trees, determining the optimal dispersal function of each tree species, and optimizing the existing dispersal function.

[Topographic distribution patterns of forest gap within an evergreen broad-leaved forest in Tiantong region of Zhejiang Province, Eastern China].

To explore the effects of multi-dimensional topographic factors on forest gap distribution, the forest gaps in a 20 hm2 dynamic monitoring plot of an evergreen broad-leaved forest in Tiantong region of Zhejiang were taken as the objects to study the distribution patterns of the gap fraction, gap density, and gap area under the effects of altitude, slope degree, slope shape, slope aspect, and slope position by using a geographic information system (GIS) software. In the plot, the gap fraction was 13.1% , gap density was 9.5 ind.hm-2, and average gap area was 137.82 m2. Because of the greater intensity of typhoon disturbance at high altitudes, the gap fraction and gap density at the high altitude (> or =500 m) sections were significantly larger than those at the medium and low altitude (<500 m) sections. The heavy precipitation produced by typhoon could easily cause small scale landslide, and thus, lead to the gap fraction and gap density being larger in valley area than in side-slope and ridge. It was suggested that typhoon and its produced heavy precipitation could be the main causes of the significant differences in the forest gaps along the gradients of altitude and slope position.