Pyrolysis gas as a carbon source for biogas production via anaerobic digestion

Carbon is an important resource for anaerobes to enhance biogas production. In this study, the possibility of using simulated pyrolysis gas (SPG) as a carbon source for biogas production was investigated. The effects of stirring speed (SS), gas holding time (GHT), and H2 addition on biomethanation of SPG were evaluated. The diversity and structure of microbial communities were also analyzed under an illumina MiSeq platform. Results indicated that at a GHT of 14 h and an SS at 400 rpm, SPG with up to 64.7% CH4could be bio-upgraded to biogas. Gas–liquid mass transfer is the limitation for SPG biomethanation. For the first time, it has been noticed that the addition of H2 can bioupgrade SPG to high quality biogas (with 91.1% CH4). Methanobacterium was considered as a key factor in all reactors. This study provides an idea and alternative way to convert lignocellulosic biomass and solid organic waste into energy (e.g., pyrolysis was used as a pretreatment to produce pyrolysis gas from biomass, and then, pyrolysis gas was bioupgraded to higher quality biogas via anaerobic digestion)

Electro-Optical Detection of ZnO-Based Unbalanced Fabry-Perot Resonators

Zinc oxide films prepared by magnetron sputtering are introduced to the electro-optical detection to improve the voltage sensitivity. With the help of large piezoelectric effect, ZnO films make up for the deficiency of the low electro-optical coefficient. In this paper, we illustrated the mechanism of piezo-induced enhancements, and measured the electric signals on the line of coplanar waveguides. This method breaks through the limit of material species for optoelectronically responsive sensing, and shows promising applications in optical detection.

How autophagy, a potential therapeutic target, regulates intestinal inflammation

Inflammatory bowel disease (IBD) is a group of disorders that cause chronic inflammation in the intestines, with the primary types including ulcerative colitis and Crohn’s disease. The link between autophagy, a catabolic mechanism in which cells clear protein aggregates and damaged organelles, and intestinal health has been widely studied. Experimental animal studies and human clinical studies have revealed that autophagy is pivotal for intestinal homeostasis maintenance, gut ecology regulation and other aspects. However, few articles have summarized and discussed the pathways by which autophagy improves or exacerbates IBD. Here, we review how autophagy alleviates IBD through the specific genes (e.g., ATG16L1, IRGM, NOD2 and LRRK2), crosstalk of multiple phenotypes with autophagy (e.g., Interaction of autophagy with endoplasmic reticulum stress, intestinal antimicrobial defense and apoptosis) and autophagy-associated signaling pathways. Moreover, we briefly discuss the role of autophagy in colorectal cancer and current status of autophagy-based drug research for IBD. It should be emphasized that autophagy has cell-specific and environment-specific effects on the gut. One of the problems of IBD research is to understand how autophagy plays a role in intestinal tract under specific environmental factors. A better understanding of the mechanism of autophagy in the occurrence and progression of IBD will provide references for the development of therapeutic drugs and disease management for IBD in the future

Gaussian Boson Sampling with Pseudo-Photon-Number Resolving Detectors and Quantum Computational Advantage

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ~ 600 years using exact methods, whereas our quantum computer, Jiuzhang 3.0, takes only 1.27 us to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier ~ 3.1*10^10 years.Comment: submitted on 10 Apri

Gaussian Boson Sampling with Pseudo-Photon-Number-Resolving Detectors and Quantum Computational Advantage

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for the characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical spoofing mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ∼600 yr using exact methods, whereas our quantum computer, Jizhāng 3.0, takes only 1.27 μs to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier∼3.1×1010 yr.</p

Nucleocapsid Protein as Early Diagnostic Marker for SARS

Serum samples from 317 patients with patients with severe acute respiratory syndrome (SARS) were tested for the nucleocapsid (N) protein of SARS-associated coronavirus, with sensitivities of 94% and 78% for the first 5 days and 6–10 days after onset, respectively. The specificity was 99.9%. N protein can be used as an early diagnostic maker for SARS

Improving Species Identification of Ancient Mammals Based on Next-Generation Sequencing Data

The taxonomical identification merely based on morphology is often difficult for ancient remains. Therefore, universal or specific PCR amplification followed by sequencing and BLAST (basic local alignment search tool) search has become the most frequently used genetic-based method for the species identification of biological samples, including ancient remains. However, it is challenging for these methods to process extremely ancient samples with severe DNA fragmentation and contamination. Here, we applied whole-genome sequencing data from 12 ancient samples with ages ranging from 2.7 to 700 kya to compare different mapping algorithms, and tested different reference databases, mapping similarities and query coverage to explore the best method and mapping parameters that can improve the accuracy of ancient mammal species identification. The selected method and parameters were tested using 152 ancient samples, and 150 of the samples were successfully identified. We further screened the BLAST-based mapping results according to the deamination characteristics of ancient DNA to improve the ability of ancient species identification. Our findings demonstrate a marked improvement to the normal procedures used for ancient species identification, which was achieved through defining the mapping and filtering guidelines to identify true ancient DNA sequences. The guidelines summarized in this study could be valuable in archaeology, paleontology, evolution, and forensic science. For the convenience of the scientific community, we wrote a software script with Perl, called AncSid, which is made available on GitHub