Chiral electrochemiluminescence for simultaneous enantiomeric detection of aspartic acid and phenylalanine.

The burgeoning interest in rapid, simultaneous multi-target detection has propelled advancements in chiral electrochemiluminescence (ECL) assays. This study presents the design and implementation of a potential-resolved dual-color ECL sensor, engineered for the concurrent detection of aspartic acid (Asp) and phenylalanine (Phe) enantiomers. The sensor array was meticulously constructed by amalgamating anodic chiral ECL probe Ru(phen)2(L-Cys) nanocrystals with cathodic ECL probe ZnO nanoflowers (ZnO NFs). This research explored the potential of executing multianalyte assays via a potential-resolved ECL strategy, contributing to the advancements in the field of chiral ECL assays.

Structural neuroimaging markers of normal pressure hydrocephalus versus Alzheimer's dementia and Parkinson's disease, and hydrocephalus versus atrophy in chronic TBI-a narrative review.

Introduction: Normal Pressure Hydrocephalus (NPH) is a prominent type of reversible dementia that may be treated with shunt surgery, and it is crucial to differentiate it from irreversible degeneration caused by its symptomatic mimics like Alzheimer's Dementia (AD) and Parkinson's Disease (PD). Similarly, it is important to distinguish between (normal pressure) hydrocephalus and irreversible atrophy/degeneration which are among the chronic effects of Traumatic Brain Injury (cTBI), as the former may be reversed through shunt placement. The purpose of this review is to elucidate the structural imaging markers which may be foundational to the development of accurate, noninvasive, and accessible solutions to this problem. Methods: By searching the PubMed database for keywords related to NPH, AD, PD, and cTBI, we reviewed studies that examined the (1) distinct neuroanatomical markers of degeneration in NPH versus AD and PD, and atrophy versus hydrocephalus in cTBI and (2) computational methods for their (semi-) automatic assessment on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans. Results: Structural markers of NPH and those that can distinguish it from AD have been well studied, but only a few studies have explored its structural distinction between PD. The structural implications of cTBI over time have been studied. But neuroanatomical markers that can predict shunt response in patients with either symptomatic idiopathic NPH or post-traumatic hydrocephalus have not been reliably established. MRI-based markers dominate this field of investigation as compared to CT, which is also reflected in the disproportionate number of MRI-based computational methods for their automatic assessment. Conclusion: Along with an up-to-date literature review on the structural neurodegeneration due to NPH versus AD/PD, and hydrocephalus versus atrophy in cTBI, this article sheds light on the potential of structural imaging markers as (differential) diagnostic aids for the timely recognition of patients with reversible (normal pressure) hydrocephalus, and opportunities to develop computational tools for their objective assessment.

A ventriculomegaly feature computational pipeline to improve the screening of normal pressure hydrocephalus on CT.

OBJECTIVE: The objective of this study was to develop a computational pipeline that extracts objective features of ventriculomegaly from non-contrast CT (NCCT) for the accurate classification of idiopathic normal pressure hydrocephalus (NPH) from headache controls (HCs), Alzheimer's dementia (AD), and posttraumatic encephalomalacia (PTE). METHODS: Patients with possible NPH (n = 79) and a subset with definite NPH (DefNPH; n = 29) were retrospectively identified in the Veterans Affairs Informatics and Computing Infrastructure system, along with the AD (n = 62), PTE (n = 53), and HC (n = 59) cohorts. Image-processing pipelines were developed to extract a novel feature capturing the maximum eccentricity of the lateral ventricles (MaxEccLV), a proxy splenial angle (p-SA), the Evans indices (EI-x, -y, and -z), callosal angle, normalized maximum third-ventricle width, and CSF to brain volume ratio from their NCCT scans. The authors used t-tests to examine group differences in the features and multivariate logistic regression models for classification. Additionally, the NPH versus HC classifier was validated on external data. RESULTS: When NPH and DefNPH were compared with HC, AD, and PTE, significant differences were found in all features except the p-SA, which only significantly differed between NPH and PTE. The test-set area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were 0.98, 100%, and 98.3% for NPH versus HC classification; 0.94, 87.3%, and 85.5% for NPH versus AD; 0.96, 92.4%, and 90.6% for NPH versus PTE; and 0.96, 94%, and 88% for NPH versus the other groups using logistic regression under five-fold cross-validation. Consistently high performance was noted for DefNPH. The NPH versus HC classifier provided an AUC of 0.84, sensitivity of 76.9%, and specificity of 90% when assessed on external data. CONCLUSIONS: Including the novel MaxEccLV, this framework computes useful features of ventriculomegaly, which had not previously been algorithmically assessed on NCCT. This framework successfully classified possible and definite NPH from HC, AD, and PTE. Following validation on larger representative cohorts, this objective and accessible tool may aid in screening for NPH and differentiating it from symptomatic mimics such as AD and PTE.

GNTD: reconstructing spatial transcriptomes with graph-guided neural tensor decomposition informed by spatial and functional relations.

Spatially-resolved RNA profiling has now been widely used to understand cells' structural organizations and functional roles in tissues, yet it is challenging to reconstruct the whole spatial transcriptomes due to various inherent technical limitations in tissue section preparation and RNA capture and fixation in the application of the spatial RNA profiling technologies. Here, we introduce a graph-guided neural tensor decomposition (GNTD) model for reconstructing whole spatial transcriptomes in tissues. GNTD employs a hierarchical tensor structure and formulation to explicitly model the high-order spatial gene expression data with a hierarchical nonlinear decomposition in a three-layer neural network, enhanced by spatial relations among the capture spots and gene functional relations for accurate reconstruction from highly sparse spatial profiling data. Extensive experiments on 22 Visium spatial transcriptomics datasets and 3 high-resolution Stereo-seq datasets as well as simulation data demonstrate that GNTD consistently improves the imputation accuracy in cross-validations driven by nonlinear tensor decomposition and incorporation of spatial and functional information, and confirm that the imputed spatial transcriptomes provide a more complete gene expression landscape for downstream analyses of cell/spot clustering for tissue segmentation, and spatial gene expression clustering and visualizations.

Roles of Macrophages and Their Interactions with Schwann Cells After Peripheral Nerve Injury.

The adult peripheral nervous system has a significant ability for regeneration compared to the central nervous system. This is related to the unique neuroimmunomodulation after peripheral nerve injury (PNI). Unlike the repair of other tissues after injury, Schwann cells (SCs) respond immediately to the trauma and send out signals to precisely recruit macrophages to the injured site. Then, macrophages promote the degradation of the damaged myelin sheath by phagocytosis of local debris. At the same time, macrophages and SCs jointly secrete various cytokines to reconstruct a microenvironment suitable for nerve regeneration. This unique pathophysiological process associated with macrophages provides important targets for the repair and treatment of PNI, as well as an important reference for guiding the repair of other nerve injuries. To understand these processes more systematically, this paper describes the characteristics of macrophage activation and metabolism in PNI, discusses the underlying molecular mechanism of interaction between macrophages and SCs, and reviews the latest research progress of crosstalk regulation between macrophages and SCs. These concepts and therapeutic strategies are summarized to provide a reference for the more effective use of macrophages in the repair of PNI.

MOF-Enhanced Chiral ECL Recognition System: Dual-Function in Phenylalanine Enantiomer Detection and Coreaction Acceleration.

The accurate discernment and separation of chiral isomers with high precision remain a significant challenge in various industries and biological fields. In this investigation, an electrochemiluminescent (ECL) chiral recognition platform was devised to ascertain the presence of phenylalanine (Phe). Notably, a homochiral [Ni2(l-asp)2(bipy)] (Ni-LAB) was established as a dual-function coreactant accelerator and chiral recognition substrate. Ni-LAB facilitates the reaction between the coreactant (K2S2O8) and the luminescent entity 3,4,9,10-perylenetetracar-boxylic-l-cysteine (PTCA-cys), thereby enhancing the ECL luminescence efficiency and improving the sensitivity of the chiral sensor. The chiral recognition potential of Ni-LAB was assessed to differentiate between Phe chiral isomers, and the underlying mechanism was comprehensively elucidated. This system exhibited remarkable proficiency in detecting Phe enantiomers and precisely differentiating a single Phe enantiomer within a mixture, showcasing exceptional levels of selectivity, stability, and reproducibility. This study paves the way for the development of advanced chiral recognition systems, potentially revolutionizing the field of chiral sensing and discrimination.

Chiral Discrimination of Penicillamine Enantiomers: The Role of Aggregation-Caused Quenching in Achieving High Selectivity.

The recognition and separation of chiral isomers are of great importance in both industrial and biological applications. In this study, a chiral recognition system based on electrochemiluminescence was established for the detection of penicillamine (PA) enantiomers. The system utilized a homochiral [Zn2(BDC)(d-lac)] (Zn-BL) platform for the uniform distribution of Ru(bpy)32+ nanoparticles, effectively mitigating aggregation-caused quenching. The chiral recognition ability of Zn-BL was tested to distinguish between PA enantiomers, and the results indicated a substantial increase in the chiral electrochemiluminescence (ECL) signal when l-PA was present, in contrast to d-PA. The mechanism underlying ECL chiral discrimination was investigated using water contact angle measurements, DFT calculations, and electrochemical characterization. The system exhibited high selectivity, stability, and reproducibility for PA enantiomer detection. Furthermore, the proposed method can accurately identify one enantiomer of PA in a mixture. This study provides a reliable and sensitive approach for achieving the highly selective detection of chiral molecules.

Long non-coding RNAs influence aging process of sciatic nerves in SD rats.

OBJECTIVES: To investigate the long non-coding RNAs (lncRNAs) changes in the sciatic nerve (SN) in Sprague Dawley (SD) rats during aging. METHODS: Eighteen healthy SD rats were selected at the age of 1 month (1M) and 24 months (24M) and SNs were collected. High-throughput transcriptome sequencing and bioinformatics analysis were performed. Protein-protein interaction (PPI) networks and competing endogenous RNA (ceRNA) networks were established according to differentially expressed genes (DEGs). RESULT: As the length of lncRNAs increased, its proportion to the total number of lncRNAs decreased. A total of 4079 DElncRNAs were identified in Con vs. 24M. GO analysis was primarily clustered in nerve and lipid metabolism, extracellular matrix, and vascularization-related fields. There were 17 nodes in the PPI network of the target genes of up-regulating genes including Itgb2, Lox, Col11a1, Wnt5a, Kras, etc. Using quantitative RT-PCR, microarray sequencing accuracy was validated. There were 169 nodes constructing the PPI network of down-regulated target genes, mainly including Col1a1, Hmgcs1, Hmgcr. CeRNA interaction networks were constructed CONCLUSION: Lipid metabolism, angiogenesis, and ECM fields might play an important role in the senescence process in SNs. Col3a1, Serpinh1, Hmgcr, and Fdps could be candidates for nerve aging research.

Simultaneous electrochemical recognition of tryptophan and penicillamine enantiomers based on MOF-modified ß-CD.

Chiral recognition is of significant importance in the fields of chemical asymmetric synthesis and biological pharmaceutical research. In this work, an electrochemical chiral sensor with two kinds of chiral sites (chiral cavity for ß-cyclodextrin and chiral skeleton for Ca-sacc/MeOH) by electrooxidation ß-cyclodextrin onto Ca-sacc/MeOH was built. The proposed multichiral ß-CD@Ca-sacc/MeOH/GCE can be used for recognition of tryptophan and penicillamine enantiomers simultaneously with wide linear range, low detection limits value, high repeatability and stability within the available electrochemical window. The strategy for integration multichiral sources is crucial to construct novel chiral platforms for simultaneous recognition of multiple chiral compounds in complicated chiral systems.

Detecting spatially co-expressed gene clusters with functional coherence by graph-regularized convolutional neural network.

MOTIVATION: Clustering spatial-resolved gene expression is an essential analysis to reveal gene activities in the underlying morphological context by their functional roles. However, conventional clustering analysis does not consider gene expression co-localizations in tissue for detecting spatial expression patterns or functional relationships among the genes for biological interpretation in the spatial context. In this article, we present a convolutional neural network (CNN) regularized by the graph of protein-protein interaction (PPI) network to cluster spatially resolved gene expression. This method improves the coherence of spatial patterns and provides biological interpretation of the gene clusters in the spatial context by exploiting the spatial localization by convolution and gene functional relationships by graph-Laplacian regularization. RESULTS: In this study, we tested clustering the spatially variable genes or all expressed genes in the transcriptome in 22 Visium spatial transcriptomics datasets of different tissue sections publicly available from 10× Genomics and spatialLIBD. The results demonstrate that the PPI-regularized CNN constantly detects gene clusters with coherent spatial patterns and significantly enriched by gene functions with the state-of-the-art performance. Additional case studies on mouse kidney tissue and human breast cancer tissue suggest that the PPI-regularized CNN also detects spatially co-expressed genes to define the corresponding morphological context in the tissue with valuable insights. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/kuanglab/CNN-PReg. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Oral administration of hepcidin and chitosan benefits growth, immunity, and gut microbiota in grass carp (Ctenopharyngodon idella).

Intensive high-density culture patterns are causing an increasing number of bacterial diseases in fish. Hepcidin links iron metabolism with innate immunity in the process of resisting bacterial infection. In this study, the antibacterial effect of the combination of hepcidin (Cihep) and chitosan (CS) against Flavobacterium columnare was investigated. The dosing regimen was also optimized by adopting a feeding schedule of every three days and every seven days. After 56 days of feeding experiment, grass carp growth, immunity, and gut microbiota were tested. In vitro experiments, Cihep and CS can regulate iron metabolism and antibacterial activity, and that the combination of Cihep and CS had the best protective effect. In vivo experiments, Cihep and CS can improve the growth index of grass carp. After challenge with Flavobacterium columnare, the highest survival rate was observed in the Cihep+CS-3d group. By serum biochemical indicators assay and Prussian blue staining, Cihep and CS can increase iron accumulation and decrease serum iron levels. The contents of lysozyme and superoxide dismutase in Cihep+CS-3d group increased significantly. Meanwhile, Cihep and CS can significantly reduce the pathological damage of gill tissue. The 16S rRNA sequencing results showed that Cihep and CS can significantly increase the abundance and diversity of grass carp gut microbiota. These results indicated that the protective effect of consecutive 3-day feeding followed by a 3-day interval was better than that of consecutive 7-day feeding followed by a 7-day interval, and that the protective effect of Cihep in combination with chitosan was better than that of Cihep alone. Our findings optimize the feeding pattern for better oral administration of Cihep in aquaculture.

Hepcidin Protects Yellow Catfish (Pelteobagrus fulvidraco) against Aeromonas veronii-Induced Ascites Disease by Regulating Iron Metabolism.

Aeromonas veronii (A. veronii) is one of the main pathogens causing bacterial diseases in aquaculture. Although previous studies have shown that hepcidin as an antimicrobial peptide can promote fish resistance to pathogenic bacterial infections, but the mechanisms remain unclear. Here, we expressed and purified recombinant yellow catfish (Pelteobagrus fulvidraco) hepcidin protein (rPfHep). rPfHep can up-regulate the expression of ferritin and enhance the antibacterial activity in primary hepatocytes of yellow catfish. We employed berberine hydrochloride (BBR) and Fursultiamine (FSL) as agonists and antagonists for hepcidin, respectively. The results indicated that agonist BBR can inhibit the proliferation of pathogenic bacteria, and the antagonist FSL shows the opposite effect. After gavage administration, rPfHep and the agonist BBR can enhance the accumulation of iron in liver, which may hinder the iron transport and limit the amount of iron available to pathogenic bacteria. Moreover, rPfHep and the agonist BBR can also reduce the mortality rate, bacterial load and histological lesions in yellow catfish infected with A. veronii. Therefore, hepcidin is an important mediator of iron metabolism, and it can be used as a candidate target for prevent bacterial infections in yellow catfish. Hepcidin and BBR have potential application value in preventing anti-bacterial infection.

Corrigendum: A Detailed View of KIR Haplotype Structures and Gene Families as Provided by a New Motif-Based Multiple Sequence Alignment.

[This corrects the article DOI: 10.3389/fimmu.2020.585731.].

Imputation of spatially-resolved transcriptomes by graph-regularized tensor completion.

High-throughput spatial-transcriptomics RNA sequencing (sptRNA-seq) based on in-situ capturing technologies has recently been developed to spatially resolve transcriptome-wide mRNA expressions mapped to the captured locations in a tissue sample. Due to the low RNA capture efficiency by in-situ capturing and the complication of tissue section preparation, sptRNA-seq data often only provides an incomplete profiling of the gene expressions over the spatial regions of the tissue. In this paper, we introduce a graph-regularized tensor completion model for imputing the missing mRNA expressions in sptRNA-seq data, namely FIST, Fast Imputation of Spatially-resolved transcriptomes by graph-regularized Tensor completion. We first model sptRNA-seq data as a 3-way sparse tensor in genes (p-mode) and the (x, y) spatial coordinates (x-mode and y-mode) of the observed gene expressions, and then consider the imputation of the unobserved entries or fibers as a tensor completion problem in Canonical Polyadic Decomposition (CPD) form. To improve the imputation of highly sparse sptRNA-seq data, we also introduce a protein-protein interaction network to add prior knowledge of gene functions, and a spatial graph to capture the the spatial relations among the capture spots. The tensor completion model is then regularized by a Cartesian product graph of protein-protein interaction network and the spatial graph to capture the high-order relations in the tensor. In the experiments, FIST was tested on ten 10x Genomics Visium spatial transcriptomic datasets of different tissue sections with cross-validation among the known entries in the imputation. FIST significantly outperformed the state-of-the-art methods for single-cell RNAseq data imputation. We also demonstrate that both the spatial graph and PPI network play an important role in improving the imputation. In a case study, we further analyzed the gene clusters obtained from the imputed gene expressions to show that the imputations by FIST indeed capture the spatial characteristics in the gene expressions and reveal functions that are highly relevant to three different kinds of tissues in mouse kidney.

Hierarchical Canonical Correlation Analysis Reveals Phenotype, Genotype, and Geoclimate Associations in Plants.

The local environment of the geographical origin of plants shaped their genetic variations through environmental adaptation. While the characteristics of the local environment correlate with the genotypes and other genomic features of the plants, they can also be indicative of genotype-phenotype associations providing additional information relevant to environmental dependence. In this study, we investigate how the geoclimatic features from the geographical origin of the Arabidopsis thaliana accessions can be integrated with genomic features for phenotype prediction and association analysis using advanced canonical correlation analysis (CCA). In particular, we propose a novel method called hierarchical canonical correlation analysis (HCCA) to combine mutations, gene expressions, and DNA methylations with geoclimatic features for informative coprojections of the features. HCCA uses a condition number of the cross-covariance between pairs of datasets to infer a hierarchical structure for applying CCA to combine the data. In the experiments on Arabidopsis thaliana data from 1001 Genomes and 1001 Epigenomes projects and climatic, atmospheric, and soil environmental variables combined by CLIMtools, HCCA provided a joint representation of the genomic data and geoclimate data for better prediction of the special flowering time at 10°C (FT10) of Arabidopsis thaliana. We also extended HCCA with information from a protein-protein interaction (PPI) network to guide the feature learning by imposing network modules onto the genomic features, which are shown to be useful for identifying genes with more coherent functions correlated with the geoclimatic features. The findings in this study suggest that environmental data comprise an important component in plant phenotype analysis. HCCA is a useful data integration technique for phenotype prediction, and a better understanding of the interactions between gene functions and environment as more useful functional information is introduced by coprojections of multiple genomic datasets.

A Detailed View of KIR Haplotype Structures and Gene Families as Provided by a New Motif-Based Multiple Sequence Alignment.

Human chromosome 19q13.4 contains genes encoding killer-cell immunoglobulin-like receptors (KIR). Reported haplotype lengths range from 67 to 269 kb and contain 4 to 18 genes. The region has certain properties such as single nucleotide variation, structural variation, homology, and repetitive elements that make it hard to align accurately beyond single gene alleles. To the best of our knowledge, a multiple sequence alignment of KIR haplotypes has never been published or presented. Such an alignment would be useful to precisely define KIR haplotypes and loci, provide context for assigning alleles (especially fusion alleles) to genes, infer evolutionary history, impute alleles, interpret and predict co-expression, and generate markers. In order to extend the framework of KIR haplotype sequences in the human genome reference, 27 new sequences were generated including 24 haplotypes from 12 individuals of African American ancestry that were selected for genotypic diversity and novelty to the reference, to bring the total to 68 full length genomic KIR haplotype sequences. We leveraged these data and tools from our long-read KIR haplotype assembly algorithm to define and align KIR haplotypes at <5 kb resolution on average. We then used a standard alignment algorithm to refine that alignment down to single base resolution. This processing demonstrated that the high-level alignment recapitulates human-curated annotation of the human haplotypes as well as a chimpanzee haplotype. Further, assignments and alignments of gene alleles were consistent with their human curation in haplotype and allele databases. These results define KIR haplotypes as 14 loci containing 9 genes. The multiple sequence alignments have been applied in two software packages as probes to capture and annotate KIR haplotypes and as markers to genotype KIR from WGS.

Accurate and Efficient KIR Gene and Haplotype Inference From Genome Sequencing Reads With Novel K-mer Signatures.

The killer-cell immunoglobulin-like receptor (KIR) proteins evolve to fight viruses and mediate the body's reaction to pregnancy. These roles provide selection pressure for variation at both the structural/haplotype and base/allele levels. At the same time, the genes have evolved relatively recently by tandem duplication and therefore exhibit very high sequence similarity over thousands of bases. These variation-homology patterns make it impossible to interpret KIR haplotypes from abundant short-read genome sequencing data at population scale using existing methods. Here, we developed an efficient computational approach for in silico KIR probe interpretation (KPI) to accurately interpret individual's KIR genes and haplotype-pairs from KIR sequencing reads. We designed synthetic 25-base sequence probes by analyzing previously reported haplotype sequences, and we developed a bioinformatics pipeline to interpret the probes in the context of 16 KIR genes and 16 haplotype structures. We demonstrated its accuracy on a synthetic data set as well as a real whole genome sequences from 748 individuals from The Genome of the Netherlands (GoNL). The GoNL predictions were compared with predictions from SNP-based predictions. Our results show 100% accuracy rate for the synthetic tests and a 99.6% family-consistency rate in the GoNL tests. Agreement with the SNP-based calls on KIR genes ranges from 72%-100% with a mean of 92%; most differences occur in genes KIR2DS2, KIR2DL2, KIR2DS3, and KIR2DL5 where KPI predicts presence and the SNP-based interpretation predicts absence. Overall, the evidence suggests that KPI's accuracy is 97% or greater for both KIR gene and haplotype-pair predictions, and the presence/absence genotyping leads to ambiguous haplotype-pair predictions with 16 reference KIR haplotype structures. KPI is free, open, and easily executable as a Nextflow workflow supported by a Docker environment at https://github.com/droeatumn/kpi.

Efficient Sequencing, Assembly, and Annotation of Human KIR Haplotypes.

The homology, recombination, variation, and repetitive elements in the natural killer-cell immunoglobulin-like receptor (KIR) region has made full haplotype DNA interpretation impossible in a high-throughput workflow. Here, we present a new approach using long-read sequencing to efficiently capture, sequence, and assemble diploid human KIR haplotypes. Probes were designed to capture KIR fragments efficiently by leveraging the repeating homology of the region. IDT xGen® Lockdown probes were used to capture 2-8 kb of sheared DNA fragments followed by sequencing on a PacBio Sequel. The sequences were error corrected, binned, and then assembled using the Canu assembler. The location of genes and their exon/intron boundaries are included in the workflow. The assembly and annotation was evaluated on 16 individuals (8 African American and 8 Europeans) from whom ground truth was known via long-range sequencing with fosmid library preparation. Using only 18 capture probes, the results show that the assemblies cover 97% of the GenBank reference, are 99.97% concordant, and it takes only 1.8 haplotigs to cover 75% of the reference. We also report the first assembly of diploid KIR haplotypes from long-read WGS. Our targeted hybridization probe capture and sequencing approach is the first of its kind to fully sequence and phase all diploid human KIR haplotypes, and it is efficient enough for population-scale studies and clinical use. The open and free software is available at https://github.com/droeatumn/kass and supported by a environment at https://hub.docker.com/repository/docker/droeatumn/kass.

An investigation of mechanisms for the enhanced coagulation removal of Microcystis aeruginosa by low-frequency ultrasound under different ultrasound energy densities.

There is a lack of studies elaborating the differences in mechanisms of low-frequency ultrasound-enhanced coagulation for algae removal among different ultrasound energy densities, which are essential to optimizing the economy of the ultrasound technology for practical application. The performance and mechanisms of low-frequency ultrasound (29.4 kHz, horn type, maximum output amplitude = 10 µm) -coagulation process in removing a typical species of cyanobacteria, Microcystis aeruginosa, at different ultrasound energy densities were studied based on a set of comprehensive characterization approaches. The turbidity removal ratio of coagulation (with polymeric aluminum salt coagulant at a dosage of 4 mg Al/L) was considerably increased from 44.1% to 59.7%, 67.0%, and 74.9% with 30 s of ultrasonic pretreatment at energy densities of 0.6, 1.11, and 2.22 J/mL, respectively, indicating that low-frequency ultrasound-coagulation is a potential alternative to effectively control unexpected blooms of M. aeruginosa. However, the energy density of ultrasound should be deliberately considered because a high energy density (≥18 J/mL) results in a significant release of algal organic matter, which may threaten water quality security. The specific mechanisms for the enhanced coagulation removal by low-frequency ultrasonic pretreatment under different energy densities can be summarized as the reduction of cell activity (energy density ≥ 0.6 J/mL), the slight release of negatively charged algal organic matter from cells (energy density ≥ 1.11 J/mL), and the aggregation of M. aeruginosa cells (energy density ≥ 1.11 J/mL). This study provides new insights for the ongoing study of ultrasonic pretreatment for the removal of algae via coagulation.

A large-scale comparative study of isoform expressions measured on four platforms.

BACKGROUND: Most eukaryotic genes produce different transcripts of multiple isoforms by inclusion or exclusion of particular exons. The isoforms of a gene often play diverse functional roles, and thus it is necessary to accurately measure isoform expressions as well as gene expressions. While previous studies have demonstrated the strong agreement between mRNA sequencing (RNA-seq) and array-based gene and/or isoform quantification platforms (Microarray gene expression and Exon-array), the more recently developed NanoString platform has not been systematically evaluated and compared, especially in large-scale studies across different cancer domains. RESULTS: In this paper, we present a large-scale comparative study among RNA-seq, NanoString, array-based, and RT-qPCR platforms using 46 cancer cell lines across different cancer types. The goal is to understand and evaluate the calibers of the platforms for measuring gene and isoform expressions in cancer studies. We first performed NanoString experiments on 59 cancer cell lines with 404 custom-designed probes for measuring the expressions of 478 isoforms in 155 genes, and additional RT-qPCR experiments for a subset of the measured isoforms in 13 cell lines. We then combined the data with the matched RNA-seq, Exon-array, and Microarray data of 46 of the 59 cell lines for the comparative analysis. CONCLUSION: In the comparisons of the platforms for measuring the expressions at both isoform and gene levels, we found that (1) the agreement on isoform expressions is lower than the agreement on gene expressions across the four platforms; (2) NanoString and Exon-array are not consistent on isoform quantification even though both techniques are based on hybridization reactions; (3) RT-qPCR experiments are more consistent with RNA-seq and Exon-array than NanoString in isoform quantification; (4) different RNA-seq isoform quantification methods show varying estimation results, and among the methods, Net-RSTQ and eXpress are more consistent across the platforms; and (5) RNA-seq has the best overall consistency with the other platforms on gene expression quantification.