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Rationale: Heteroatomic compounds are relatively abundant and believed to be bio-resistant in heavy crude oils. However, few studies have focused on the biodegradation of these heteroatomic compounds.Methods: Heteroatoms, especially N 1 species, in a blank crude oil and in three treated oils co-incubated with anaerobic sulfate-reducing bacteria, nitrate-reducing bacteria and fermentative consortia cultures were detected using negative-ion electrospray ionization coupled with high-field Fourier transform ion cyclotron resonance mass spectrometry.Results: The relative abundance of N 1 species in the three treated oils decreased, while the relative abundance of O 2 species increased. Remarkably, the relative abundances of N 1 species with low carbon number increased and those with higher carbon number decreased. Conclusions:These results revealed that the anaerobic biodegradations of heavy crude oil occurred. With direct evidences, the degradations of alkyl side chains of N 1 species by the anaerobic microbes could be deduced.

Using 454 pyrosequencing of 16S rRNA gene amplicons, microbial communities in samples of injection water and production water during a serial microbial enhanced oil recovery (MEOR) field trial in a water flooded high pour point oil reservoir were determined. There was a close microbial community compositional relationship between the injection water and the successful first round MEOR processed oil reservoir which was indicated by the result of 43 shared dominant operational taxonomic units detected in both the injection water and the production water. Alterations of microbial community after the injection of boost nutrients showed that microbes giving positive responses were mainly those belonging to the genera of Comamonas, Brevundimonas, Azospirillum, Achromobacter, Pseudomonas,and Hyphomonas, which were detected both in the injection water and in the production water and usually detected in oil reservoir environments or associated with hydrocarbon degradation. Additionally, microbes only dominant in the production waters were significantly inhibited with a sharp decline in their relative abundance. Based on these findings, a suggestion of re-optimization of the boost nutrients, targetting the microbes co-existing in the injection water and the oil reservoir and having survival ability in both surface and subsurface environments, rather than simple repeats for the subsequent in situ MEOR applications was proposed.a Bold microbe names are those that were activated. b Bold microbe names are those that were inhibited. c Abundance showing the relative abundances calculated based on the numbers of reads.694 | RSC Adv., 2018, 8, 690-697This journal is

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Complement dependent cytotoxicity (CDC) significantly contributes to Rituximab (RTX) and Ofatumumab (OFA) efficacies in the treatment of B-cell non-Hodgkin’s lymphoma (NHL) and chronic lymphocytic leukemia (CLL). Human CD59 (hCD59) is a key complement regulatory protein that restricts the formation of the membrane attack complex and thereby inhibits CDC. hCD59 is an important determinant of the sensitivity of NHL and CLL to RTX and OFA treatment. Recently, we developed a specific and potent hCD59 inhibitor, His-tagged ILYd4, which consists of 30 amino acid sequences extending from the N-terminus of ILYd4. Our previously published results indicate that His-tagged ILYd4 can be used as a lead candidate to further develop a potential therapeutic adjuvant for RTX and OFA treatment of RTX-resistant NHL and CLL. However, these studies were conducted using ILYd4 tagged on the N-terminus with 30 additional amino acids (AA) containing 6 X His used for immobilized metal affinity chromatograph. As a further step towards the development of ILYd4-based therapeutics, we investigated the impact of the removal of this extraneous sequence on the anti-hCD59 activity. In this paper, we report the generation and characterization of tag-free ILYd4. We demonstrate that tag-free ILYd4 has over three-fold higher anti-hCD59 activities than the His-tagged ILYd4. The enhanced RTX-mediated CDC effect on B-cell malignant cells comes from tag-free ILYd4’s improved functionality and physical properties including better solubility, reduced tendency to aggregation, and greater thermal stability. Therefore, tag-free ILYd4 is a better candidate for the further development for the clinical application.

Sharing information between connected and autonomous vehicles (CAVs) fundamentally improves the performance of collaborative object detection for self-driving. However, CAVs still have uncertainties on object detection due to practical challenges, which will affect the later modules in self-driving such as planning and control. Hence, uncertainty quantification is crucial for safety-critical systems such as CAVs. Our work is the first to estimate the uncertainty of collaborative object detection. We propose a novel uncertainty quantification method, called Double-M Quantification, which tailors a moving block bootstrap (MBB) algorithm with direct modeling of the multivariant Gaussian distribution of each corner of the bounding box. Our method captures both the epistemic uncertainty and aleatoric uncertainty with one inference pass based on the offline Double-M training process. And it can be used with different collaborative object detectors. Through experiments on the comprehensive collaborative perception dataset, we show that our Double-M method achieves more than 4× improvement on uncertainty score and more than 3% accuracy improvement, compared with the state-of-the-art uncertainty quantification methods. Our code is public on https://coperception. github.io/double-m-quantification/.