A bifunctional catalyst of Ru supported in zeolite HZSM-5, Ru/HZSM-5 (Si/Al = 25), exhibited excellent hydrodeoxygenation activity toward the conversion of lignin-derived phenolic monomers and dimers to cycloalkanes in aqueous solution. The oxygen-containing groups in mono- and binuclear phenols were removed through a cleavage of C–O bonds in phenolics followed by an integrated metal- and acid-catalyzed hydrogenation and dehydration. As a bifunctional catalyst Ru/HZSM-5, the presence of both the Brønsted acid site in the pores of HZSM-5 for dehydration and a metallic function of Ru for hydrogenation was indispensible for the formation of alkanes from lignin-derived phenolics. Our findings also reveal that the Ru/HZSM-5 with the lowest Si/Al ratio of HZSM-5 proved to be most selective to cycloalkanes, indicating that more acid sites over zeolite are favorable for the dehydration of cyclohexanol during hydrodeoxygenation process, which leads higher selectivity to hydrocarbons. This approach for the construction of bifunctional catalyst highlights an efficient route for hydrodeoxygenation of lignin-derived phenolic oil to transportation biofuels.

Cellulose and cellobiose were selectively converted into sorbitol over water-tolerant phosphotungstic acid (PTA)/metal- organic-framework-hybrid-supported ruthenium catalysts, Ru-PTA/MIL-100(Cr), under aqueous hydrogenation conditions. The goal was to investigate the relationship between the acid/metal balance of bifunctional catalysts Ru-PTA/MIL-100(Cr) and their performance in the catalytic conversion of cellulose and cellobiose into sugar alcohols. The control of the amount and strength of acid sites in the supported PTA/MIL-100(Cr) was achieved through the effective control of encapsulated-PTA loading in MIL-100(Cr). This design and preparation method led to an appropriately balanced Ru-PTA/MIL-100(Cr) in terms of Ru dispersion and hydrogenation capacity on the one hand, and acid site density of PTA/MIL-100(Cr) (responsible for acid-catalyzed hydrolysis) on the other hand. The ratio of acid site density to the number of Ru surface atoms (nA /nRu ) of Ru-PTA/MIL-100(Cr) was used to monitor the balance between hydrogenation and hydrolysis functions; the optimum balance between the two catalytic functions, that is, 8.84

Segraves. 2019. A meta-analysis of whole genome duplication and the effects on flowering traits in plants. American Journal of Botany 106(3): 469-476. PREMISE OF THE STUDY:Polyploidy, or whole genome duplication (WGD), is common in plants despite theory suggesting that polyploid establishment is challenging and polyploids should be evolutionarily transitory. There is renewed interest in understanding the mechanisms that could facilitate polyploid establishment and explain their pervasiveness in nature. In particular, premating isolation from their diploid progenitors is suggested to be a crucial factor. To evaluate how changes in assortative mating occur, we need to understand the phenotypic effects of WGD on reproductive traits. METHODS:We used literature surveys and a meta-analysis to assess how WGD affects floral morphology, flowering phenology, and reproductive output in plants. We focused specifically on comparisons of newly generated polyploids (neopolyploids) and their parents to mitigate potential confounding effects of adaptation and drift that may be present in ancient polyploids.KEY RESULTS: The results indicated that across a broad representation of angiosperms, floral morphology traits increased in size, reproductive output decreased, and flowering phenology was unaffected by WGD. Additionally, we found that increased trait variation after WGD was uncommon for the phenotypic traits examined. CONCLUSIONS:Our results suggest that the phenotypic effects on traits important to premating isolation of neopolyploids are small, in general. Changes in flowering phenology, reproductive output, and phenotypic variation resulting from WGD may be less critical in facilitating premating isolation and neopolyploid establishment. However, floral traits for which size is an important component of function (e.g., pollen transfer) could be strongly influenced by WGD.

No abstract

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. Although previous TS studies revealed structural abnormalities in distinct cortico-basal ganglia circuits, the topological alterations of the whole-brain white matter (WM) structural networks remain poorly understood. Here, we used diffusion MRI probabilistic tractography and graph theoretical analysis to investigate the topological organization of WM networks in 44 drug-naive TS children and 41 age and gender matched healthy children. The WM networks were constructed by estimating inter-regional connectivity probability and the topological properties were characterized using graph theory. We found that both TS and control groups showed an efficient small-world organization in WM networks. However, compared to controls, TS children exhibited decreased global and local efficiency, increased shortest path length and small-worldness, indicating a disrupted balance between local specialization and global integration in structural networks. Although both TS and control groups showed highly similar hub distributions, TS children exhibited significant decreased nodal efficiency, mainly distributed in the default-mode, language, visual and sensorimotor systems. Furthermore, two separate networks showing significantly decreased connectivity in TS group were identified using network based statistical (NBS) analysis, primarily composed of the parieto-occipital cortex, precuneus and paracentral lobule.. Importantly, we combined support vector machine and multiple kernel learning frameworks to fuse multiple levels of network topological features for classification of individuals, achieving high accuracy of 86.47%.

Tourette syndrome (TS) is a childhood-onset neurological disorder. To date, accurate TS diagnosis remains challenging due to its varied clinical expressions and dependency on qualitative description of symptoms. Therefore, identifying accurate and objective neuroimaging biomarkers may help improve early TS diagnosis. As resting-state functional MRI (rs-fMRI) has been demonstrated as a promising neuroimaging tool for TS diagnosis, previous rs-fMRI studies on TS revealed functional connectivity (FC) changes in a few local brain networks or circuits. However, no study explored the disrupted topological organization of whole-brain FC networks in TS children. Meanwhile, very few studies have examined brain functional networks using machine-learning methods for diagnostics. In this study, we construct individual whole-brain, ROI-level FC networks for 29 drug-naive TS children and 37 healthy children. Then, we use graph theory analysis to investigate the topological disruptions between groups. The identified disrupted regions in FC networks not only involved the sensorimotor association regions but also the visual, default-mode and language areas, all highly related to TS. Furthermore, we propose a novel classification framework based on similarity network fusion (SNF) algorithm, to both diagnose an individual subject and explore the discriminative power of FC network topological properties in distinguishing between TS children and controls. We achieved a high accuracy of 88.79%, and the involved discriminative regions for classification were also highly related to TS. Together, both the disrupted topological properties between groups and the discriminative topological features for classification may be considered as comprehensive and helpful neuroimaging biomarkers for assisting the clinical TS diagnosis.

No abstract

No abstract