Coefficients of determination (<i>R</i>^<i>2</i>) for each predictor in simultaneous autoregressive regressions in linear and quadratic forms.

<p>“*” = <i>P</i><0.05</p><p>“**” = <i>P</i><0.01</p><p>“***” = <i>P</i><0.001.</p><p>“^L”, linear predictor</p><p>“^Q”, quadratic predictor.</p><p>IFO, the index of floristic overlap; MDE, mid-domain effects; MAT, mean annual temperature; MTCQ, mean temperature of the coldest quarter; PET, annual potential evapotranspiration; WI, warmth index; MAP, mean annual precipitation; Rain, rainfall; AI, aridity index; AET, annual actual evapotranspiration; S_temp, temperature seasonality; S_Prec, precipitation seasonality; ART, annual range in temperature.</p><p>Coefficients of determination (<i>R</i>^<i>2</i>) for each predictor in simultaneous autoregressive regressions in linear and quadratic forms.</p

Biogeographical Interpretation of Elevational Patterns of Genus Diversity of Seed Plants in Nepal

<div><p>This study tests if the biogeographical affinities of genera are relevant for explaining elevational plant diversity patterns in Nepal. We used simultaneous autoregressive (SAR) models to investigate the explanatory power of several predictors in explaining the diversity-elevation relationships shown in genera with different biogeographical affinities. Delta akaike information criterion (ΔAIC) was used for multi-model inferences and selections. Our results showed that both the total and tropical genus diversity peaked below the mid-point of the elevational gradient, whereas that of temperate genera had a nearly symmetrical, unimodal relationship with elevation. The proportion of temperate genera increased markedly with elevation, while that of tropical genera declined. Compared to tropical genera, temperate genera had wider elevational ranges and were observed at higher elevations. Water-related variables, rather than mid-domain effects (MDE), were the most significant predictors of elevational patterns of tropical genus diversity. The temperate genus diversity was influenced by energy availability, but only in quadratic terms of the models. Though climatic factors and mid-domain effects jointly explained most of the variation in the diversity of temperate genera with elevation, the former played stronger roles. Total genus diversity was most strongly influenced by climate and the floristic overlap of tropical and temperate floras, while the influences of mid-domain effects were relatively weak. The influences of water-related and energy-related variables may vary with biogeographical affinities. The elevational patterns may be most closely related to climatic factors, while MDE may somewhat modify the patterns. Caution is needed when investigating the causal factors underlying diversity patterns for large taxonomic groups composed of taxa of different biogeographical affinities. Right-skewed diversity-elevation patterns may be produced by the differential response of taxa with varying biogeographical affinities to climatic factors and MDE.</p></div

Climatic factors on elevation.

<p>Subgraphs: (a) = mean annual temperature (MAT), (b) = mean temperature of the coldest quarter (MTCQ), (c) = annual potential evapotranspiration (PET), (d) = warmth index (WI), (e) = mean annual precipitation (MAP), (f) = Rain, (g) = aridity index (AI), (h) = annual actual evapotranspiration (AET), (i) = temperature seasonality (S_Temp), (j) = precipitation seasonality (S_Prec), and (k) = annual range in temperature (ART).</p

Comparing the effects of climatic and the mid-domain effects on temperate genus diversity by partial regression.

<p>A shows the mid-domain effects; B shows climatic effects. Total variance explained by {A} = 0.963; Total variance explained by {B} = 0.976; Total variance explained by {A+B} = 0.996. [A.B] variance explained by {A} only = 0.019; [A:B] Variance Sharely explained = 0.944; [B.A] Variance explained by {B} only = 0.032; [1-(A+B)] Unexplained variance = 0.004. Moran′s index of residuals in the model was 0.017 at first class.</p

The relationship between genus diversity and elevation.

<p>The relationship between genus diversity and elevation.</p

The index of floristic overlap with elevation.

<p>The index of floristic overlap with elevation.</p

The proportion of tropical and temperate genera along the elevation gradients.

<p>The proportion of tropical and temperate genera along the elevation gradients.</p

Coefficients of determination (<i>R</i>^<i>2</i>) and Akaike information criterions (AIC) of the best SAR models.

<p>There were 8, 16 and 32 possible SAR models for tropical, temperate and total genus diversity, respectively (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140992#pone.0140992.s005" target="_blank">S5 Table</a>). For each biogeographical group, the ΔAICc compares the best model (ΔAICc = 0) with all of models generated, and any models with a ΔAICc of less than two in comparison with the best model were considered an equally good fit to the data.</p

Optical Injection of Gold Nanoparticles into Living Cells

The controlled injection of nanoscopic objects into living cells with light offers promising prospects for the development of novel molecular delivery strategies or intracellular biosensor applications. Here, we show that single gold nanoparticles from solution can be patterned on the surface of living cells with a continuous wave laser beam. In a second step, we demonstrate how the same particles can then be injected into the cells through a combination of plasmonic heating and optical force. We find that short exposure times are sufficient to perforate the cell membrane and inject the particles into cells with a survival rate of >70%

Substance P promotes the progression of bronchial asthma through activating the PI3K/AKT/NF-κB pathway mediated cellular inflammation and pyroptotic cell death in bronchial epithelial cells

NOD-like receptor family pyrin domain containing three (NLRP3) inflammasome-mediated pyroptotic cell death and inflammation contribute to the pathogenesis of bronchial asthma, and it is reported that Substance P (SP) plays important role in the process, however, the detailed molecular mechanisms by which SP participates in the aggravation of bronchial asthma have not been fully studied. Here, our clinical data showed that SP and its receptor Neurokinin-1 receptor (NK1R) were significantly elevated in the plasma and peripheral blood mononuclear cell (PBMC) collected from patients with bronchial asthma, and further pre-clinical experiments evidenced that SP suppressed cell viability, accelerated lactate dehydrogenase (LDH) release, and upregulated ASC, Caspase-1, NLRP3, IL-1β and IL-18 to promote pyroptotic cell death and cellular inflammation in the human bronchial epithelial cells and asthmatic mice models in vitro and in vivo. Interestingly, SP-induced pyroptotic cell death was reversed by NK1R inhibitor L732138. Then, we uncovered the underlying mechanisms, and found that SP activated the downstream PI3K/AKT/NF-κB signal pathway in a NK1R-dependent manner, and blockage of this pathway by both PI3K inhibitor (LY294002) and NF-κB inhibitor (MG132) reversed SP-induced pyroptotic cell death and recovered cell viability in bronchial epithelial cells. Collectively, we concluded that SP interacted with its receptor NK1R to activate the PI3K/AKT/NF-κB pathway, which further triggered NLRP3-mediated pyroptotic cell death in the bronchial epithelial cells, resulting in the aggravation of bronchial asthma.</p