Biodegradability during Anaerobic Fermentation Process Impacted by Heavy Metals

In the past decades, biotechnologies for reutilizing the biomass harvested from the metal-contaminated land draw attention to many scientists. Among those technologies, anaerobic fermentation is proven as an efficient conversion process for biowaste reduction with simultaneous recovery of biogas as an energy source. During the process of anaerobic fermentation, the release of metals from the biomass will impact the growth and performance of microorganisms in reactors, which then results the variation of substrate degradation. In this chapter, the impact of metals on the degradation of substrate at different stages of fermentation process, as indicated by variations of lignocelluloses, chemical oxygen demands (COD), volatile fatty acids (VFAs), etc., will be summarized. The objective is to rationalize the relationship between metal presence and substrate degradability and give suggestions for future research on metal-contaminated biomass reutilization

Monthly extended ocean predictions based on a convolutional neural network via the transfer learning method

Sea surface temperature anomalies (SSTAs) and sea surface height anomalies (SSHAs) are indispensable parts of scientific research, such as mesoscale eddy, current, ocean-atmosphere interaction and so on. Nowadays, extended-range predictions of ocean dynamics, especially in SSTA and SSHA, can provide daily prediction services in the range of 30 days, which bridges the gap between synoptic-scale weather forecasts and monthly average scale climate predictions. However, the forecast efficiency of extended range remains problematic. With the development of ocean reanalysis and satellite remote sensing products, large amounts datasets provide an unprecedented opportunity to use big data for the extended range prediction of ocean dynamics. In this study, a hybrid model, combing convolutional neural network (CNN) model with transfer learning (TL), was established to predict SSTA and SSHA at monthly scales, which makes full use of these data resources that arise from delayed gridding reanalysis products and real-time satellite remote sensing observations. The proposed model, where both ocean and atmosphere reanalysis datasets serve as the pretraining dataset and the satellite remote sensing observations are employed for fine-tuning based on the transfer learning (TL) method, can effectively capture the evolving spatial characteristics of SSTAs and SSHAs with low prediction errors over the 30 days range. When the forecast lead time is 30 days, the root means square errors for the SSTAs and SSHAs model results are 0.32°C and 0.027 m in the South China Sea, respectively, indicating that this model has not only satisfactory prediction performance but also offers great potential for practical operational applications in improving the skill of extended-range predictions

Poly A- Transcripts Expressed in HeLa Cells

BACKGROUND: Transcripts expressed in eukaryotes are classified as poly A+ transcripts or poly A- transcripts based on the presence or absence of the 3' poly A tail. Most transcripts identified so far are poly A+ transcripts, whereas the poly A- transcripts remain largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: We developed the TRD (Total RNA Detection) system for transcript identification. The system detects the transcripts through the following steps: 1) depleting the abundant ribosomal and small-size transcripts; 2) synthesizing cDNA without regard to the status of the 3' poly A tail; 3) applying the 454 sequencing technology for massive 3' EST collection from the cDNA; and 4) determining the genome origins of the detected transcripts by mapping the sequences to the human genome reference sequences. Using this system, we characterized the cytoplasmic transcripts from HeLa cells. Of the 13,467 distinct 3' ESTs analyzed, 24% are poly A-, 36% are poly A+, and 40% are bimorphic with poly A+ features but without the 3' poly A tail. Most of the poly A- 3' ESTs do not match known transcript sequences; they have a similar distribution pattern in the genome as the poly A+ and bimorphic 3' ESTs, and their mapped intergenic regions are evolutionarily conserved. Experiments confirmed the authenticity of the detected poly A- transcripts. CONCLUSION/SIGNIFICANCE: Our study provides the first large-scale sequence evidence for the presence of poly A- transcripts in eukaryotes. The abundance of the poly A- transcripts highlights the need for comprehensive identification of these transcripts for decoding the transcriptome, annotating the genome and studying biological relevance of the poly A- transcripts

Single-cell transcriptome sequencing reveals heterogeneity of gastric cancer: progress and prospects

Gastric cancer is one of the most serious malignant tumor and threatens the health of people worldwide. Its heterogeneity leaves many clinical problems unsolved. To treat it effectively, we need to explore its heterogeneity. Single-cell transcriptome sequencing, or single-cell RNA sequencing (scRNA-seq), reveals the complex biological composition and molecular characteristics of gastric cancer at the level of individual cells, which provides a new perspective for understanding the heterogeneity of gastric cancer. In this review, we first introduce the current procedure of scRNA-seq, and discuss the advantages and limitations of scRNA-seq. We then elaborate on the research carried out with scRNA-seq in gastric cancer in recent years, and describe how it reveals cell heterogeneity, the tumor microenvironment, oncogenesis and metastasis, as well as drug response in to gastric cancer, to facilitate early diagnosis, individualized therapy, and prognosis evaluation

Transcriptome profile of halofuginone resistant and sensitive strains of Eimeria tenella

The antiparasitic drug halofuginone is important for controlling apicomplexan parasites. However, the occurrence of halofuginone resistance is a major obstacle for it to the treatment of apicomplexan parasites. Current studies have identified the molecular marker and drug resistance mechanisms of halofuginone in Plasmodium falciparum. In this study, we tried to use transcriptomic data to explore resistance mechanisms of halofuginone in apicomplexan parasites of the genus Eimeria (Apicomplexa: Eimeriidae). After halofuginone treatment of E. tenella parasites, transcriptome analysis was performed using samples derived from both resistant and sensitive strains. In the sensitive group, DEGs associated with enzymes were significantly downregulated, whereas the DNA damaging process was upregulated after halofuginone treatment, revealing the mechanism of halofuginone-induced parasite death. In addition, 1,325 differentially expressed genes (DEGs) were detected between halofuginone resistant and sensitive strains, and the DEGs related to translation were significantly downregulated after halofuginone induction. Overall, our results provide a gene expression profile for further studies on the mechanism of halofuginone resistance in E. tenella

Rectangular Coordination Polymer Nanoplates: Large-Scale, Rapid Synthesis and Their Application as a Fluorescent Sensing Platform for DNA Detection

In this paper, we report on the large-scale, rapid synthesis of uniform rectangular coordination polymer nanoplates (RCPNs) assembled from Cu(II) and 4,4′-bipyridine for the first time. We further demonstrate that such RCPNs can be used as a very effective fluorescent sensing platform for multiple DNA detection with a detection limit as low as 30 pM and a high selectivity down to single-base mismatch. The DNA detection is accomplished by the following two steps: (1) RCPN binds dye-labeled single-stranded DNA (ssDNA) probe, which brings dye and RCPN into close proximity, leading to fluorescence quenching; (2) Specific hybridization of the probe with its target generates a double-stranded DNA (dsDNA) which detaches from RCPN, leading to fluorescence recovery. It suggests that this sensing system can well discriminate complementary and mismatched DNA sequences. The exact mechanism of fluorescence quenching involved is elucidated experimentally and its use in a human blood serum system is also demonstrated successfully

Poly(m-Phenylenediamine) Nanospheres and Nanorods: Selective Synthesis and Their Application for Multiplex Nucleic Acid Detection

In this paper, we demonstrate for the first time that poly(m-phenylenediamine) (PMPD) nanospheres and nanorods can be selectively synthesized via chemical oxidation polymerization of m-phenylenediamine (MPD) monomers using ammonium persulfate (APS) as an oxidant at room temperature. It suggests that the pH value plays a critical role in controlling the the morphology of the nanostructures and fast polymerization rate favors the anisotropic growth of PMPD under homogeneous nucleation condition. We further demonstrate that such PMPD nanostructures can be used as an effective fluorescent sensing platform for multiplex nucleic acid detection. A detection limit as low as 50 pM and a high selectivity down to single-base mismatch could be achieved. The fluorescence quenching is attributed to photoinduced electron transfer from nitrogen atom in PMPD to excited fluorophore. Most importantly, the successful use of this sensing platform in human blood serum system is also demonstrated