CELLULASE6 and MANNANASE7 affect cell differentiation and silique dehiscence in Arabidopsis

Cellulases, hemicellulases and pectinases play important roles in fruit development and maturation, but mutants with defects in the fruit have not been reported for cellulase or hemicellulase genes. Here we report the functional characterization of cellulase gene CEL6 and hemicellulase gene MAN7 in silique development and dehiscence in Arabidopsis. These genes were found to be expressed in vegetative and reproductive organs, and their expression in the silique partially depended on the IND and ALC transcriptional factors. Mutant alleles of cel6 and man7 exhibited delayed secondary cell wall thickening and altered cell morphology in the valve margin and impaired silique dehiscence. Cells in the separation layer in nearly mature siliques of the single mutants and the cel6-1 man7-3 double mutant remained intact whereas they degenerated in the wild-type control. Phenotypic studies of single, double, triple and quadruple mutants revealed that the higher-order mutant combinations of the cel6-1, man7-3, and pectinase adpg1-1 and adpg2- 1 mutations produced more severe silique indehiscent phenotypes than the corresponding lower-order mutant combinations, except for some combinations involving cel6-1, man7-3, and adpg2-1. Our results demonstrate that the ability of the silique to dehisce can be manipulated to different degrees by altering the activities of proteins of different types.Plant Biology, Ecology and Evolutio

Aging and Sex Influence Cortical Auditory-Motor Integration for Speech Control

It is well known that acoustic change in speech production is subject to age-related declines. How aging alters cortical sensorimotor integration in speech control, however, remains poorly understood. The present event-related potential study examined the behavioral and neural effects of aging and sex on the auditory-motor processing of voice pitch errors. Behaviorally, older adults produced significantly larger vocal compensations for pitch perturbations than young adults across the sexes, while the effects of sex on vocal compensation did not exist for both young and older adults. At the cortical level, there was a significant interaction between aging and sex on the N1-P2 complex. Older males produced significantly smaller P2 amplitudes than young males, while young males produced significantly larger N1 and P2 amplitudes than young females. In addition, females produced faster N1 responses than males regardless of age, while young adults produced faster P2 responses than older adults across the sexes. These findings provide the first neurobehavioral evidence that demonstrates the aging influence on auditory feedback control of speech production, and highlight the importance of sex in understanding the aging of the neuromotor control of speech production

Production of high‐purity hydrogen and layered doubled hydroxide by the hydrolysis of Mg‐Al alloys

Hydrogen is becoming an important clean energy and layered doubled hydroxide (LDH) is of great interest for many applications, including water treatment, environmental remediation, and chemical catalysis. The production of high‐purity hydrogen and LDH by the hydrolysis of Mg‐Al alloys is reported. The effects of initial pH, reaction temperature, reaction time, and alloy's Mg/Al mass ratio on the rate of hydrogen generation and the purity of LDH are evaluated and the solid hydrolysis products are characterized by different techniques. The initial rate of hydrogen generation increases with decreasing initial pH and increasing reaction temperature and Mg/Al ratio while the purity of LDH increases with Mg/Al ratio, reaction temperature and time. This study may provide a new, green, and sustainable approach for storage of hydrogen and material for water treatment

Ndrg2 regulates vertebral specification in differentiating somites

AbstractIt is generally thought that vertebral patterning and identity are globally determined prior to somite formation. Relatively little is known about the regulators of vertebral specification after somite segmentation. Here, we demonstrated that Ndrg2, a tumor suppressor gene, was dynamically expressed in the presomitic mesoderm (PSM) and at early stage of differentiating somites. Loss of Ndrg2 in mice resulted in vertebral homeotic transformations in thoracic/lumbar and lumbar/sacral transitional regions in a dose-dependent manner. Interestingly, the inactivation of Ndrg2 in osteoblasts or chondrocytes caused defects resembling those observed in Ndrg2−/− mice, with a lower penetrance. In addition, forced overexpression of Ndrg2 in osteoblasts or chondrocytes also conferred vertebral defects, which were distinct from those in Ndrg2−/− mice. These genetic analyses revealed that Ndrg2 modulates vertebral identity in segmented somites rather than in the PSM. At the molecular level, combinatory alterations of the amount of Hoxc8-11 gene transcripts were detected in the differentiating somites of Ndrg2−/− embryos, which may partially account for the vertebral defects in Ndrg2 mutants. Nevertheless, Bmp/Smad signaling activity was elevated in the differentiating somites of Ndrg2−/− embryos. Collectively, our findings unveiled Ndrg2 as a novel regulator of vertebral specification in differentiating somites

Brain entropy changes in classical trigeminal neuralgia

BackgroundClassical trigeminal neuralgia (CTN) is a common and severe chronic neuropathic facial pain disorder. The pathological mechanisms of CTN are not fully understood. Recent studies have shown that resting-state functional magnetic resonance imaging (rs-fMRI) could provide insights into the functional changes of CTN patients and the complexity of neural processes. However, the precise spatial pattern of complexity changes in CTN patients is still unclear. This study is designed to explore the spatial distribution of complexity alterations in CTN patients using brain entropy (BEN).MethodsA total of 85 CTN patients and 79 age- and sex-matched healthy controls (HCs) were enrolled in this study. All participants underwent rs-fMRI and neuropsychological evaluations. BEN changes were analyzed to observe the spatial distribution of CTN patient complexity, as well as the relationship between these changes and clinical variables. Sixteen different machine learning methods were employed to classify the CTN patients from the HCs, and the best-performing method was selected.ResultsCompared with HCs, CTN patients exhibited increased BEN in the thalamus and brainstem, and decreased BEN in the inferior semilunar lobule. Further analyses revealed a low positive correlation between the average BEN values of the thalamus and neuropsychological assessments. Among the 16 machine learning methods, the Conditional Mutual Information Maximization-Random Forest (CMIM-RF) method yielded the highest area under the curve (AUC) of 0.801.ConclusionsOur study demonstrated that BEN changes in the thalamus and pons and inferior semilunar lobule were associated with CTN and machine learning methods could effectively classify CTN patients and HCs based on BEN changes. Our findings may provide new insights into the neuropathological mechanisms of CTN and have implications for the diagnosis and treatment of CTN

Probabilistic Naming of Functions in Stripped Binaries

Debugging symbols in binary executables carry the names of functions and global variables. When present, they greatly simplify the process of reverse engineering, but they are almost always removed (stripped) for deployment. We present the design and implementation of punstrip, a tool which combines a probabilistic fingerprint of binary code based on high-level features with a probabilistic graphical model to learn the relationship between function names and program structure. As there are many naming conventions and developer styles, functions from different applications do not necessarily have the exact same name, even if they implement the exact same functionality. We therefore evaluate punstrip across three levels of name matching: exact; an approach based on natural language processing of name components; and using Symbol2Vec, a new embedding of function names based on random walks of function call graphs. We show that our approach is able to recognize functions compiled across different compilers and optimization levels and then demonstrate that punstrip can predict semantically similar function names based on code structure. We evaluate our approach over open source C binaries from the Debian Linux distribution and compare against the state of the art

Action means more than words: how effective can a global action-learning program for entrepreneurship education be? A comparison of the outcomes in Singapore, China, Korea and New Zealand

We review the effectiveness of the same action-learning entrepreneurship program in four countries