Application of rumen and anaerobic sludge microbes for bio harvesting from lignocellulosic biomass

© 2019 Elsevier Ltd This study investigated the production of biogas, volatile fatty acids (VFAs), and other soluble organic from lignocellulosic biomass by two microbial communities (i.e. rumen fluid and anaerobic sludge). Four types of abundant lignocellulosic biomass (i.e. wheat straw, oaten hay, lurence hay and corn silage)found in Australia were used. The results show that rumen microbes produced four-time higher VFAs level than that of anaerobic sludge reactors, indicating the possible application of rumen microorganism for VFAs generation from lignocellulosic biomass. VFA production in the rumen fluid reactors was probably due to the presence of specific hydrolytic and acidogenic bacteria (e.g. Fibrobacter and Prevotella). VFA production corroborated from the observation of pH drop in the rumen fluid reactors indicated hydrolytic and acidogenic inhibition, suggesting the continuous extraction of VFAs from the reactor. Anaerobic sludge reactors on the other hand, produced more biogas than that of rumen fluid reactors. This observation was consistent with the abundance of methanogens in anaerobic sludge inoculum (3.98% of total microbes)compared to rumen fluid (0.11%). VFA production from lignocellulosic biomass is the building block chemical for bioplastic, biohydrogen and biofuel. The results from this study provide important foundation for the development of engineered systems to generate VFAs from lignocellulosic biomass

New insights to the difference in microbial composition and interspecies interactions between fouling layer and mixed liquor in a membrane bioreactor

This work examined fouling-associated microbial community in a carefully controlled laboratory-scale membrane bioreactor (MBR) at different fouling stages. In agreement with the literature, fouling severity was positively correlated with bound polysaccharide and protein content (indicators) in the mixed liquor. UPGMA clustering analysis with different indices indicated that although the biofouling layer (biofilm) and mixed liquor possessed highly similar microbial identity, important differences between the two communities' structures were also observed. This appears to be the first comprehensive study to apply differential abundance analysis (ANCOM) to identify microbial taxa driven the divergence in microbial structure including Victivallales, Coxiellales, unassigned Microgenomatia and Blastocatellia 11–24 (all presented at 0.6) with fouling indicators, confirming their important contributions to fouling propensity. The biofilm community exhibited a more complex structure with higher level of inter-species interaction and prevalence of positive connections (74.6%) compared to the mixed liquor community (42.2%), reflecting higher stability and synergy between microbial taxa in the biofilm. Results from this comprehensive investigation can support the development of new fouling control strategies

Gene network effects on brain microstructure and intellectual performance identified in 472 twins

A major challenge in neuroscience is finding which genes affect brain integrity, connectivity, and intellectual function. Discovering influential genes holds vast promise for neuroscience, but typical genome-wide searches assess approximately one million genetic variants one-by-one, leading to intractable false positive rates, even with vast samples of subjects. Even more intractable is the question of which genes interact and how they work together to affect brain connectivity. Here, we report a novel approach that discovers which genes contribute to brain wiring and fiber integrity at all pairs of points in a brain scan. We studied genetic correlations between thousands of points in human brain images from 472 twins and their nontwin siblings (mean age: 23.7 ± 2.1 SD years; 193 male/279 female). We combined clustering with genome-wide scanning to find brain systems with common genetic determination. We then filtered the image in a new way to boost power to find causal genes. Using network analysis, we found a network of genes that affect brain wiring in healthy young adults. Our new strategy makes it computationally more tractable to discover genes that affect brain integrity. The gene network showed small-world and scale-free topologies, suggesting efficiency in genetic interactions and resilience to network disruption. Genetic variants at hubs of the network influence intellectual performance by modulating associations between performance intelligence quotient and the integrity of major white matter tracts, such as the callosal genu and splenium, cingulum, optic radiations, and the superior longitudinal fasciculus

Low-carbon transition through a duty to divest: Back to the future, ahead to the past

PeerReviewe

Resource-efficient high-dimensional subspace teleportation with a quantum autoencoder.

Quantum autoencoders serve as efficient means for quantum data compression. Here, we propose and demonstrate their use to reduce resource costs for quantum teleportation of subspaces in high-dimensional systems. We use a quantum autoencoder in a compress-teleport-decompress manner and report the first demonstration with qutrits using an integrated photonic platform for future scalability. The key strategy is to compress the dimensionality of input states by erasing redundant information and recover the initial states after chip-to-chip teleportation. Unsupervised machine learning is applied to train the on-chip autoencoder, enabling the compression and teleportation of any state from a high-dimensional subspace. Unknown states are decompressed at a high fidelity (~0.971), obtaining a total teleportation fidelity of ~0.894. Subspace encodings hold great potential as they support enhanced noise robustness and increased coherence. Laying the groundwork for machine learning techniques in quantum systems, our scheme opens previously unidentified paths toward high-dimensional quantum computing and networking

Deep seabed mining: A note on some potentials and risks to the sustainable mineral extraction from the oceans

The rapidly increasing global populations and socio-economic development in the Global South have resulted in rising demand for natural resources. There are many plans for harvesting natural resources from the ocean floor, especially rare metals and minerals. However, if proper care is not taken, there is substantial potential for long-lasting and even irreversible physical and environmental impacts on the deep-sea ecosystems, including on biodiversity and ecosystem functioning. This paper reviews the literature on some potentials and risks to deep seabed mining (DSM), outlining its legal aspects and environmental impacts. It presents two case studies that describe the environmental risks related to this exploitative process. They include significant disturbance of the seabed, light and noise pollution, the creation of plumes, and negative impacts on the surface, benthic, and meso-and bathypelagic zones. The study suggests some of the issues interested companies should consider in preventing the potential physical and environmental damages DSM may cause. Sustainable mining and the use of minerals are vital in meeting various industrial demands

Statistical Inference of In Vivo Properties of Human DNA Methyltransferases from Double-Stranded Methylation Patterns

DNA methyltransferases establish methylation patterns in cells and transmit these patterns over cell generations, thereby influencing each cell's epigenetic states. Three primary DNA methyltransferases have been identified in mammals: DNMT1, DNMT3A and DNMT3B. Extensive in vitro studies have investigated key properties of these enzymes, namely their substrate specificity and processivity. Here we study these properties in vivo, by applying novel statistical analysis methods to double-stranded DNA methylation patterns collected using hairpin-bisulfite PCR. Our analysis fits a novel Hidden Markov Model (HMM) to the observed data, allowing for potential bisulfite conversion errors, and yields statistical estimates of parameters that quantify enzyme processivity and substrate specificity. We apply this model to methylation patterns established in vivo at three loci in humans: two densely methylated inactive X (Xi)-linked loci ( and ), and an autosomal locus (), where methylation densities are tissue-specific but moderate. We find strong evidence for a high level of processivity of DNMT1 at and , with the mean association tract length being a few hundred base pairs. Regardless of tissue types, methylation patterns at are dominated by DNMT1 maintenance events, similar to the two Xi-linked loci, but are insufficiently informative regarding processivity to draw any conclusions about processivity at that locus. At all three loci we find that DNMT1 shows a strong preference for adding methyl groups to hemi-methylated CpG sites over unmethylated sites. The data at all three loci also suggest low (possibly 0) association of the de novo methyltransferases, the DNMT3s, and are consequently uninformative about processivity or preference of these enzymes. We also extend our HMM to reanalyze published data on mouse DNMT1 activities in vitro. The results suggest shorter association tracts (and hence weaker processivity), and much longer non-association tracts than human DNMT1 in vivo

Sustainability practices at higher education institutions in Asia

Purpose: It is still unclear how Asian universities incorporate the theory or practice of sustainable development (SD) in their research and education programmes. To address this gap, the purpose of this paper is to report on a study that has examined how universities in Asian countries handle and address matters related to SD. Design/methodology/approach: The study used a bibliometric analysis and an online survey-method. The online survey data were analysed through descriptive analysis and one-sample student’s t-test. Findings: The study indicates that there is considerable variation among the Asian countries regarding sustainability practices in higher education institutions (HEIs). The HEIs in far eastern countries, such as Indonesia, Malaysia and Thailand are perceived to demonstrate more sustainability practices. Research limitations/implications: Even though a substantial number of participants participated in the survey, it did not cover all Asian countries. The online survey was carried out over a limited period of time, and not all HEIs in the field may have received information about the study. Practical implications: Asia is the largest continent facing a number of sustainability challenges. In this context, the contribution of HEIs is very important. The findings of the current study may serve as a baseline for Asian HEIs to take more initiatives towards SD goals, as HEIs are responsible for the education and training of hundreds of thousands of students who will be occupying key positions in industry, government or education in the coming years. Originality/value: The study contributes to the existing literature in two distinct ways. First, it was possible to develop a comprehensive instrument to measure sustainability practices in HEIs. Second, this study has filled the gap of the scarcity of studies regarding sustainability practices in HEIs in Asia