Diversity of Ophiostomatoid Fungi Associated with Dendroctonus armandi Infesting Pinus armandii in Western China.

Pinus armandii (P. armandii) is extensively abundant in western China and, as a pioneer tree, and prominently influences local ecology. However, pine forests in this region have been significantly damaged by Dendroctonus armandi (D. armandi) infestations, in close association with ophiostomatoid fungi. This study aimed to identify the diversity of ophiostomatoid fungi associated with D. armandi infesting P. armandii in western China. A total of 695 ophiostomatoid fungal strains were isolated from 1040 tissue pieces from D. armandi galleries and 89 adult beetles at four sites. In this study, based on multiloci DNA sequence data, as well as morphological and physiological characteristics, seven species belonging to five genera were identified including three known species, Esteyea vermicola, Graphium pseudormiticum and L. wushanense, two novel taxa, Graphilbum parakesiyea and Ophiostoma shennongense, and an unidentified Ophiostoma sp. 1. A neotype of Leptographium qinlingense. Ophiostoma shennongense was the dominant taxon (78.99%) in the ophiostomatoid community. This study provides a valuable scientific theoretical basis for the occurrence and management of D. armandi in the future.

Inhibitory effect of Astragalus Membranaceus on osteoporosis in SAMP6 mice by regulating vitaminD/FGF23/Klotho signaling pathway.

Spontaneous senile osteoporosis severely threatens the health of the senior population which has emerged as a severe issue for society. A SAMP6 mouse model was utilized to estimate the impact of intragastrically administered Astragalus Membranaceus (AR) on spontaneous senile osteoporosis. Bone mineral density (BMD) and bone microstructure were measured using Micro-CT; contents of calcium and phosphorus were determined with the colorimetric method; and gene and protein expressions of fibroblast growth factor 23 (FGF23), Klotho, Vitamin D receptor (VDR), CYP27B1 and CYP24A1 were detected using qPCR, Western blot and ELISA assays, respectively. The findings indicated that AR could improve the femoral BMD and bone microstructure, elevate the contents of calcium and phosphorus, and increase the expression of Klotho, VDR, and CYP27B1 whereas decreasing the expression of FGF23 and CYP24A1 in SAMP6 mice in a dose independent manner. The present study has demonstrated that AR can promote osteogenesis and alleviate osteoporosis. It is also expected to provide a new insight for the treatment of spontaneous senile osteoporosis and to serve as a research basis for AR application.

Decreased mitochondrial DNA copy number in children with cerebral palsy quantified by droplet digital PCR.

BACKGROUND: Mitochondrial DNA copy number is a potential biomarker for mitochondrial dysfunction and is involved in a variety of disease states including autism, neurodegenerative diseases and traumatic brain injury, but few studies on mitochondrial DNA copy number in cerebral palsy have been reported. Therefore, this study aims to investigate the role of mitochondrial DNA copy number in children with cerebral palsy. METHODS: A total of 104 children with cerebral palsy and 78 typically developing children were enrolled in this study. All children with cerebral palsy were diagnosed according to clinical criteria and furtherly divided into clinical subtypes. Mitochondrial DNA copy number was quantified by droplet digital PCR. RESULTS: We observed a significant reduction in mitochondrial DNA copy number from children with cerebral palsy comparing to healthy controls (216.76 ± 71.39 vs 359.66 ± 72.78, p < 0.001). An upward trend in mitochondrial DNA copy number alteration with the increase of age was found in healthy controls rather than in children with cerebral palsy. In addition, the mitochondrial DNA copy number in children with spastic hemiplegia was higher than that in children with spastic quadriplegia (152.27 ± 49.78 vs 90.64 ± 21.55, p = 0.001). CONCLUSIONS: Our results suggest that on the basis of accurate quantification by droplet digital PCR, the declined mitochondrial DNA copy number probably has certain implications for mitochondrial dysfunction in children with cerebral palsy, which provides a new clue for the investigation on the molecular mechanism and clinical characteristics of cerebral palsy.

Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study.

Recent fMRI studies have demonstrated that resting-state functional connectivity (FC) is of nonstationarity. Temporal variability of FC reflects the dynamic nature of brain activity. Exploring temporal variability of FC offers a new approach to investigate reorganization and integration of brain networks after stroke. Here, we examined longitudinal alterations of FC temporal variability in brain networks after stroke. Nineteen stroke patients underwent resting fMRI scans across the acute stage (within-one-week after stroke), subacute stage (within-two-weeks after stroke), and early chronic stage (3-4 months after stroke). Nineteen age- and sex-matched healthy individuals were enrolled. Compared with the controls, stroke patients exhibited reduced regional temporal variability during the acute stages, which was recovered at the following two stages. Compared with the acute stage, the subacute stage exhibited increased temporal variability in the primary motor, auditory, and visual cortices. Across the three stages, the temporal variability in the ipsilesional precentral gyrus (PreCG) was increased first and then reduced. Increased temporal variability in the ipsilesional PreCG from the acute stage to the subacute stage was correlated with motor recovery from the acute stage to the early chronic stage. Our results demonstrated that temporal variability of brain network might be a potential tool for evaluating and predicting motor recovery after stroke.

Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.

Altered Coupling between Motion-Related Activation and Resting-State Brain Activity in the Ipsilesional Sensorimotor Cortex after Cerebral Stroke.

Functional connectivity maps using resting-state functional magnetic resonance imaging (rs-fMRI) can closely resemble task fMRI activation patterns, suggesting that resting-state brain activity may predict task-evoked activation or behavioral performance. However, this conclusion was mostly drawn upon a healthy population. It remains unclear whether the predictive ability of resting-state brain activity for task-evoked activation would change under different pathological conditions. This study investigated dynamic changes of coupling between patterns of resting-state functional connectivity (RSFC) and motion-related activation in different stages of cerebral stroke. Twenty stroke patients with hand motor function impairment were involved. rs-fMRI and hand motion-related fMRI data were acquired in the acute, subacute, and early chronic stages of cerebral stroke on a 3-T magnetic resonance (MR) scanner. Sixteen healthy participants were enrolled as controls. For each subject, an activation map of the affected hand was first created using general linear model analysis on task fMRI data, and then an RSFC map was determined by seeding at the peak region of hand motion activation during the intact hand task. We then measured the extent of coupling between the RSFC maps and motion-related activation maps. Dynamic changes of the coupling between the two fMRI maps were estimated using one-way repeated measures analysis of variance across the three stages. Moreover, imaging parameters were correlated with motor performances. Data analysis showed that there were different coupling patterns between motion-related activation and RSFC maps associating with the affected motor regions during the acute, subacute, and early chronic stages of stroke. Coupling strengths increased as the recovery from stroke progressed. Coupling strengths were correlated with hand motion performance in the acute stage, while coupling recovery was negatively correlated with the recovery outcome of hand motion performance in the early chronic stages. Couplings between RSFC and motion-related activation were dynamically changed with stroke progression, which suggested changes in the prediction of resting-state brain activity for task-evoked brain activity in different pathological states. The changes in coupling strength between these two types of brain activity implicate a reparative mechanism of brain injury and may represent a biomarker for predicting motor recovery in cerebral stroke.