Contrasting effects of low-severity fire on stemflow production between coexisting pine and oak trees.

As climate change intensifies, fires events are predicted to increase in forest ecosystems. Fire alters the ecosystem structure and consequently, the hydrological cycle. However, little is known about the impacts of forest fire on stemflow. A field experiment was conducted to evaluate the short-term response of stemflow production to low-severity fire in a coniferous and broadleaved mixed forest. Results demonstrated low-severity fire changed stemflow yield and had insignificant effect on the correlation between stemflow efficiency and rainfall or plant morphological variables. In unburned site Quercus acutissima and Pinus massoniana and in burned site Q. acutissima and P. massoniana, stemflow percentage averaged 3.86, 0.37, 1.20, and 0.47 %, whereas funneling ratio averaged 38.8, 4.2, 11.4, and 5.1, respectively. Fire substantially decreased the stemflow percentage and funneling ratio of Q. acutissima (P < 0.05) and slightly enhanced P. massoniana (P > 0.05). The responses of stemflow production to fire differed significantly between oak and pine trees. Fire made Q. acutissima become less effective in funneling rain to the forest ground, which is attributed to that the scaly bark was burned to highly furrowed bark that delivers less water to tree base. Burned P. massoniana was more productive in draining stemflow relative to unburned trees and is attributed to the bark which was still flaky regardless of. Additionally, the higher canopy openness allows more rain to funnel to the trunk. Stemflow efficiency was reduced in response to fire and limited the transfer of water and nutrients from canopy to soil and can reduce the competitiveness of Q. acutissima after fire disturbance.

Chimera states and cluster solutions in Hindmarsh-Rose neural networks with state resetting process.

The neuronal state resetting model is a hybrid system, which combines neuronal system with state resetting process. As the membrane potential reaches a certain threshold, the membrane potential and recovery current are reset. Through the resetting process, the neuronal system can produce abundant new firing patterns. By integrating with the state resetting process, the neuronal system can generate irregular limit cycles (limit cycles with impulsive breakpoints), resulting in repetitive spiking or bursting with firing peaks which can not exceed a presetting threshold. Although some studies have discussed the state resetting process in neurons, it has not been addressed in neural networks so far. In this paper, we consider chimera states and cluster solutions in Hindmarsh-Rose neural networks with state resetting process. The network structures are based on regular ring structures and the connections among neurons are assumed to be bidirectional. Chimera and cluster states are two types of phenomena related to synchronization. For neural networks, the chimera state is a self-organization phenomenon in which some neuronal nodes are synchronous while the others are asynchronous. Cluster synchronization divides the system into several subgroups based on their synchronization characteristics, with neuronal nodes in each subgroup being synchronous. By improving previous chimera measures, we detect the spike inspire time instead of the state variable and calculate the time between two adjacent spikes. We then discuss the incoherence, chimera state, and coherence of the constructed neural networks using phase diagrams, time series diagrams, and probability density histograms. Besides, we further contrast the cluster solutions of the system under local and global coupling, respectively. The subordinate state resetting process enriches the firing mode of the proposed Hindmarsh-Rose neural networks.

KIT, NRAS, BRAF and FMNL2 mutations in oral mucosal melanoma and a systematic review of the literature.

Oral mucosal melanoma (OMM) is an aggressive malignant tumor derived from melanocytes in the oral cavity. The genetic etiology of OMM has not been extensively investigated to date. In the present study, the aim was to detect novel gene mutations in patients with OMM. Mutation analysis of KIT, BRAF and NRAS was conducted by polymerase chain reaction. In addition, the relevant literature was searched using the PubMed database, and previous findings were compared with the results of the present study. Among the 9 patients with OMM examined, KIT, BRAF and NRAS mutations were detected, and these mutations were all observed at a frequency of 11.1% (1/9 patients). Notably, a novel FMNL2 mutation in 2 patients with OMM was identified by exome sequencing. In conclusion, the current study observed KIT, BRAF, NRAS and FMNL2 mutations in patients with OMM, which may be of benefit for elucidating the underlying mechanism of OMM pathogenesis.