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At least 19 records

EMI Mitigation of a Ćuk-Based Power-Electronic System Using Switching-Sequence-Based Control

Switching-sequence-based control (SBC) laws when designed based on topological switching behavior can have positive effects on slow- and fast-scale dynamics of a power-electronic system (PES). The slow-scale control can encompass fast PES state regulation and tracking, based on predefined objective, while fastscale control can address differential-mode (DM) and commonmode (CM) spectral-peak energy associated with PES switching operation. Such control laws may offer enhanced programmability to conventional PES design where bulky electromagnetic interference (EMI) filters have been traditionally used to reduce EMI of switching power converters to meet EMI regulatory standards. An EMI filter is always a less programmable solution since it is usually designed for the worst-case EMI mitigation and usually overkill for a PES operating under reduced load condition. The control scheme outlined in this article offers EMI mitigation across wide operating regions without compromising PES regulation. Moreover, it does so by use of switching sequences that guarantee the reachability of the PES dynamics using an advanced Lyapunov-function-based approach. SBC is a powerful tool to generate control actions for a PES based on multivariate PES state constraints. Hence, contemporary EMI regulatory standards are used as constraints in the SBC formulation to operate the PES under wide operating regime while autonomously mitigating the EMI levels. The work may be of paramount importance for operating the ultra-fast-transition recent wide-bandgap semiconductor devices like GaN–FET and SiC MOSFET under higher power with increasing switching frequencies, which is usually desirable for increased power density and reduced switching losses. Here, a hardware Cuk–PES operated ´ with GaN–FETs is fabricated and is used for case illustration. It is shown by experimental results how SBC mitigate DM and CM EMI noise of the PES while maintaining regulation even for the higher order nonminimum phase PES, while reducing sensor requirements using state observer derived from the switching model of the PES.

42 ENGINEERING↗

CombAlign: a code for generating a one-to-many sequence alignment from a set of pairwise structure-based sequence alignments

In order to better define regions of similarity among related protein structures, it is useful to identify the residue-residue correspondences among proteins. Few codes exist for constructing a one-to-many multiple sequence alignment derived from a set of structure or sequence alignments, and a need was evident for creating such a tool for combining pairwise structure alignments that would allow for insertion of gaps in the reference structure. This report describes a new Python code, CombAlign, which takes as input a set of pairwise sequence alignments (which may be structure based) and generates a one-to-many, gapped, multiple structure- or sequence based sequence alignment (MSSA). The use and utility of CombAlign was demonstrated by generating gapped MSSAs using sets of pairwise structure-based sequence alignments between structure models of the matrix protein (VP40) and pre-small/secreted glycoprotein (sGP) of Reston Ebolavirus and the corresponding proteins of several other filoviruses. The gapped MSSAs revealed structure-based residue-residue correspondences, which enabled identification of structurally similar versus differing regions in the Reston proteins compared to each of the other corresponding proteins. CombAlign is a new Python code that generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA) given a set of pairwise sequence alignments (which may be structure based). CombAlign has utility in assisting the user in distinguishing structurally conserved versus divergent regions on a reference protein structure relative to other closely related proteins. CombAlign was developed in Python 2.6, and the source code is available for download from the GitHub code repository.

59 BASIC BIOLOGICAL SCIENCES↗

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

59 BASIC BIOLOGICAL SCIENCES↗

DNA Sequence-Based Identification of Fusarium : A Work in Progress

Accurate species-level identification of an etiological agent is crucial for disease diagnosis and management because knowing the agent’s identity connects it with what is known about its host range, geographic distribution, and toxin production potential. This is particularly true in publishing peer-reviewed disease reports, where imprecise and/or incorrect identifications weaken the public knowledge base. This can be a daunting task for phytopathologists and other applied biologists that need to identify Fusarium in particular, because published and ongoing multilocus molecular systematic studies have highlighted several confounding issues. Paramount among these are: (i) this agriculturally and clinically important genus is currently estimated to comprise more than 400 phylogenetically distinct species (i.e., phylospecies), with more than 80% of these discovered within the past 25 years; (ii) approximately one-third of the phylospecies have not been formally described; (iii) morphology alone is inadequate to distinguish most of these species from one another; and (iv) the current rapid discovery of novel fusaria from pathogen surveys and accompanying impact on the taxonomic landscape is expected to continue well into the foreseeable future. To address the critical need for accurate pathogen identification, our research groups are focused on populating two web-accessible databases (FUSARIUM-ID v.3.0 and the nonredundant National Center for Biotechnology Information nucleotide collection that includes GenBank) with portions of three phylogenetically informative genes (i.e., TEF1, RPB1, and RPB2) that resolve at or near the species level in every Fusarium species. The objectives of this Special Report, and its companion in this issue ( Torres-Cruz et al. 2022 ), are to provide a progress report on our efforts to populate these databases and to outline a set of best practices for DNA sequence-based identification of fusaria.

Plant Sciences↗

Asynchronous symmetry-based sequences for homonuclear dipolar recoupling in solid-state nuclear magnetic resonance

We show a theoretical framework, based on triple-mode Floquet theory, to analyze recoupling sequences derived from symmetry-based pulse sequences, which have a non-vanishing effective field and are not rotor synchronized. We analyze the properties of one such sequence, a homonuclear double-quantum recoupling sequence derived from the C7{sub 2}{sup 1} sequence. The new asynchronous sequence outperforms the rotor-synchronized version for spin pairs with small dipolar couplings in the presence of large chemical-shift anisotropy. The resonance condition of the new sequence is analyzed using triple-mode Floquet theory. Analytical calculations of second-order effective Hamiltonian are performed to compare the efficiency in suppressing second-order cross terms. Experiments and numerical simulations are shown to corroborate the results of the theoretical analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development and validation of a next-generation sequencing-based multigene assay to predict the prognosis of estrogen receptor-positive, HER2-negative breast cancer

Purpose: Multigene assays provide useful prognostic information regarding hormone receptor (HR)-positive breast cancer. Next-generation sequencing (NGS)-based platforms have numerous advantages including reproducibility and adaptability in local laboratories. Here we aimed to develop and validate an NGS-based multigene assay to predict the distant recurrence risk. Experimental Design: In total, 179 genes including 30 reference genes highly correlated with the 21-gene recurrence score (RS) algorithm were selected from public databases. Targeted RNA-sequencing was performed using 250 and 93 archived breast cancer samples with a known RS in the training and verification sets, respectively, to develop the algorithm and NGS–Prognostic Score (NGS-PS). The assay was validated in 413 independent samples with long-term follow-up data on distant metastasis. Results: In the verification set, the NGS-PS and 21-gene RS displayed 91.4% concurrence (85/93 samples). In the validation cohort of 413 samples, area under the receiver operating characteristic curve plotted using NGS-PS values classified for distant recurrence was 0.76. The best NGS-PS cut-off value predicting distant metastasis was 20. Furthermore, 269 and 144 patients were classified as low- and high-risk patients in accordance with the cut-off. Five- and 10-year estimates of distant metastasis–free survival (DMFS) for low- versus high-risk groups were 97.0% versus 77.8% and 93.2% versus 64.4%, respectively. The age-related HR for distant recurrence without chemotherapy was 9.73 (95% CI, 3.59–26.40) and 3.19 (95% CI, 1.40–7.29) for patients aged ≤50 and >50 years, respectively. Conclusions: The newly developed and validated NGS-based multigene assay can predict the distant recurrence risk in ER-positive, HER2-negative breast cancer.

60 APPLIED LIFE SCIENCES↗

A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

Accurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis. We present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 169,000 transcripts—twice that of the best current Arabidopsis transcriptome and including over 1500 novel genes. Seventy-eight percent of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We develop novel methods to determine splice junctions and transcription start and end sites accurately. Mismatch profiles around splice junctions provide a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identify high-confidence transcription start and end sites and remove fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provides higher resolution of transcript expression profiling and identifies cold-induced differential transcription start and polyadenylation site usage. AtRTD3 is the most comprehensive Arabidopsis transcriptome currently. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage analysis from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single-molecule sequencing analysis from any species.

transcription start and end sites↗

Triazine‐Based Sequence‐Defined Polymers with Side‐Chain Diversity and Backbone–Backbone Interaction Motifs

Abstract Sequence control in polymers, well‐known in nature, encodes structure and functionality. Here we introduce a new architecture, based on the nucleophilic aromatic substitution chemistry of cyanuric chloride, that creates a new class of sequence‐defined polymers dubbed TZPs. Proof of concept is demonstrated with two synthesized hexamers, having neutral and ionizable side chains. Molecular dynamics simulations show backbone–backbone interactions, including H‐bonding motifs and pi–pi interactions. This architecture is arguably biomimetic while differing from sequence‐defined polymers having peptide bonds. The synthetic methodology supports the structural diversity of side chains known in peptides, as well as backbone–backbone hydrogen‐bonding motifs, and will thus enable new macromolecules and materials with useful functions.

Grate, Jay W.↗

Triazine‐Based Sequence‐Defined Polymers with Side‐Chain Diversity and Backbone–Backbone Interaction Motifs

Abstract Sequence control in polymers, well‐known in nature, encodes structure and functionality. Here we introduce a new architecture, based on the nucleophilic aromatic substitution chemistry of cyanuric chloride, that creates a new class of sequence‐defined polymers dubbed TZPs. Proof of concept is demonstrated with two synthesized hexamers, having neutral and ionizable side chains. Molecular dynamics simulations show backbone–backbone interactions, including H‐bonding motifs and pi–pi interactions. This architecture is arguably biomimetic while differing from sequence‐defined polymers having peptide bonds. The synthetic methodology supports the structural diversity of side chains known in peptides, as well as backbone–backbone hydrogen‐bonding motifs, and will thus enable new macromolecules and materials with useful functions.

36 MATERIALS SCIENCE↗

Unified rational protein engineering with sequence-based deep representation learning

Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically rich and structurally, evolutionarily and biophysically grounded. We show that the simplest models built on top of this unified representation (UniRep) are broadly applicable and generalize to unseen regions of sequence space. Our data-driven approach predicts the stability of natural and de novo designed proteins, and the quantitative function of molecularly diverse mutants, competitively with the state-of-the-art methods. UniRep further enables two orders of magnitude efficiency improvement in a protein engineering task. Lastly, UniRep is a versatile summary of fundamental protein features that can be applied across protein engineering informatics.

59 BASIC BIOLOGICAL SCIENCES↗

Next-generation sequencing-based miRNA expression analysis in Parp1-deficient embryonic stem cell-derived exosomes

Highlights: • This is the first report for the extracellular role of Parp1 via exosomal miRNAs. • Parp1{sup −/−} embryonic stem cell-derived exosomes were examined for miRNA regulation. • Next-generation sequencing revealed upregulated and downregulated miRNAs. • Upregulated miRNAs were associated with five signaling pathways. • Gene ontology annotation for growth/stress-related signaling and cell communication. Poly (ADP-ribose) polymerase family, member 1 (Parp1) has pleiotropic and disparate functions in multiple cellular signaling pathways through post-translational protein modification. It contributes to the regulation of various cellular processes, including DNA damage repair, cell death, and cell differentiation, genetically or epigenetically. Meanwhile, the functions of Parp1 in intercellular signaling remain to be established. To examine the functions of Parp1 in intercellular signaling, we examined microRNA (miRNA) regulation in exosomes derived from Parp1-deficient (Parp1{sup −/−}) embryonic stem (ES) cells. The percentages of miRNAs among total RNAs, including small RNAs such as miRNAs, snRNAs, snoRNAs, tRNAs, exonic RNAs, and intronic RNAs, in Parp1{sup +/+} and Parp1{sup −/−} ES cell-derived exosomes were 8.2% and 3.5%, respectively. Overall, 329 distinct miRNAs exhibited ≥2-fold changes (118 upregulated; 211 downregulated). The upregulated miRNAs targeted 810 candidate genes, and the downregulated miRNAs targeted 716 candidate genes. Pathway analyses revealed that the upregulated miRNAs were significantly associated with five pathways including MAPK signaling cascades (p Parp1{sup −/−} ES cells. In quantitative analyses of miRNA expression, miR365-3p, let-7a-5p, miR196b-5p, miR203-3p, miR98-5p, and miR146a-5p were increased by ≥ 2-fold in Parp1{sup −/−} ES cell-derived exosomes. Gene ontology enrichment analyses revealed that the upregulated miRNAs were significantly annotated for growth and stress-related cell signaling and cell communication (p Parp1 deficiency in ES cells led to inhibition of cell–cell communication, possibly by intercellular signal transduction, suggesting that Parp1 functions extracellularly by regulating exosomal miRNAs.

60 APPLIED LIFE SCIENCES↗

Modified Pattern Sequence-based Forecasting for Electric Vehicle Charging Stations

Three algorithms for the forecasting of energy consumption at individual EV charging outlets have been applied to real world data from the UCLA campus. Out of these three algorithms, namely k-Nearest Neighbor (kNN), ARIMA, and Pattern Sequence Forecasting (PSF), kNN with k=1, was the best and PSF was the worst performing algorithm with respect to the SMAPE measure. The advantage of PSF is its increased robustness to noise by substituting the real valued time series with an integer valued one, and the advantage of NN is having the least SMAPE for our data. We propose a Modified PSF algorithm (MPSF) which is a combination of PSF and NN; it could be interpreted as NN on integer valued data or as PSF with considering only the most recent neighbor to produce the output. Some other shortcomings of PSF are also addressed in the MPSF. Results show that MPSF has improved the forecast performance.

Majidpour, Mostafa↗

Performance Evaluation of a Novel Sequence-Based Directional Detection Strategy for Protection of Active Distribution Networks

Directional elements are relied on to achieve selectivity in fault detection in power systems. Although such elements have been deployed successfully for many years, there is an increased need for novel methods to deal with the unique challenges of directional protection in modern distribution networks. This article analyzes the impact of inverter-based resources (IBRs) on existing directional protection methods in distribution systems. It identifies parts of such elements that pose a risk of misoperation when IBRs are used in distribution networks. The authors have developed a new directional detection method for unbalanced faults in such networks using superimposed symmetrical sequence quantities. The phase angle of the superimposed negative sequence admittance is used to determine fault direction. The paper also presents a real-time co-simulation platform between a simulated distribution system and physical protection relay, using OPAL-RT. An SEL-411L relay is used to program the detection algorithm. This hardware-in-the-loop (HIL) setup is used to verify the performance of the method and the results are compared with existing directional methods

24 POWER TRANSMISSION AND DISTRIBUTION↗

Illumina sequencing-based analysis of free-living bacterial community dynamics during an Akashiwo sanguine bloom in Xiamen sea, China

Although phytoplankton are the major source of marine dissolved organic matter (DOM), their blooms are a global problem that can greatly affect marine ecological systems, especially free-living bacteria, which are the primary DOM degraders. In this study, we analyzed free-living bacterial communities from Xiamen sea during an Akashiwo sanguine bloom using Illumina MiSeq sequencing of 16S rRNA gene amplicons. The bloom was probably stimulated by low salinity and ended after abatement of eutrophication pollution. A total of 658,446 sequence reads and 11,807 OTUs were obtained in both bloom and control samples with Alpha-proteobacteria and Gamma-proteobacteria being the predominant classes detected. The bloom decreased bacterial diversity, increased species evenness and significantly changed the bacterial community structure. Bacterial communities within the bloom were more homogeneous than those within the control area. The bacteria stimulated by this bloom included the SAR86 and SAR116 clades and the AEGEAN-169 marine group, but a few were suppressed. In addition, many bacteria known to be associated with phytoplankton were detected only in the bloom samples. This study revealed the great influence of an A. sanguinea bloom on free-living bacterial communities and provided new insights into the relationship between bacteria and A. sanguinea in marine ecosystems.

Science & Technology - Other Topics↗

Sequence-based analysis of the genus Ruminococcus resolves its phylogeny and reveals strong host association

It has become increasingly clear that the composition of mammalian gut microbial communities is substantially diet driven. These microbiota form intricate mutualisms with their hosts, which have profound implications on overall health. For example, many gut microbes are involved in the conversion of host-ingested dietary polysaccharides into host-usable nutrients. One group of important gut microbial symbionts are bacteria in the genus Ruminococcus . Originally isolated from the bovine rumen, ruminococci have been found in numerous mammalian hosts, including other ruminants, and non-ruminants such as horses, pigs and humans. All ruminococci require fermentable carbohydrates for growth, and their substrate preferences appear to be based on the diet of their particular host. Most ruminococci that have been studied are those capable of degrading cellulose, much less is known about non-cellulolytic non-ruminant-associated species, and even less is known about the environmental distribution of ruminococci as a whole. For this study, we capitalized on the wealth of publicly available 16S rRNA gene sequences, genomes and large-scale microbiota studies to both resolve the phylogenetic placement of described species in the genus Ruminococcus , and further demonstrate that this genus has largely unexplored diversity and a staggering host distribution. We present evidence that ruminococci are predominantly associated with herbivores and omnivores, and our data supports the hypothesis that very few ruminococci are found consistently in non-host-associated environments. This study not only helps to resolve the phylogeny of this important genus, but also provides a framework for understanding its distribution in natural systems.

16S rRNA↗

Sequence-based analysis of the Vitis vinifera L. cv Cabernet Sauvignon grape must mycobiome in three South African vineyards employing distinct agronomic systems

Recent microbiomic research of agricultural habitats has highlighted tremendous microbial biodiversity associated with such ecosystems. In addition, data generated in vineyards have furthermore highlighted significant regional differences in vineyard biodiversity, hinting at the possibility that such differences might be responsible for regional differences in wine style and character, a hypothesis referred to as "microbial terroir." The current study further contributes to this body of work by comparing the mycobiome associated with South African (SA) Cabernet Sauvignon grapes in three neighboring vineyards that employ different agronomic approaches, and comparing the outcome with similar data sets from Californian vineyards. The aim of this study was to fully characterize the mycobiomes associated with the grapes from these vineyards. The data revealed approximately 10 times more fungal diversity than what is typically retrieved from culture-based studies. The Biodynamic vineyard was found to harbor a more diverse fungal community (H = 2.6) than the conventional (H = 2.1) and integrated (H = 1.8) vineyards. The data show that ascomycota are the most abundant phylum in the three vineyards, with Aureobasidium pullulans and its close relative Kabatiella microsticta being the most dominant fungi. This is the first report to reveal a high incidence of K. microsticta in the grape/wine ecosystem. Different common wine yeast species, such as Metschnikowia pulcherrima and Starmerella bacillaris dominated the mycobiome in the three vineyards. The data show that the filamentous fungi are the most abundant community in grape must although they are not regarded as relevant during wine fermentation. Comparison of metagenomic datasets from the three SA vineyards and previously published data from Californian vineyards revealed only 25% of the fungi in the SA dataset was also present in the Californian dataset, with greater variation evident amongst ubiquitous epiphytic fungi.

59 BASIC BIOLOGICAL SCIENCES↗

Metastatic castration resistant prostate cancer with squamous cell, small cell, and sarcomatoid elements—a clinicopathologic and genomic sequencing-based discussion

Histologic variants are uncommon but well reported amongst cases of prostatic adenocarcinoma, including those in the setting of hormonal and/or chemoradiation therapy and castration resistance. However, the spectrum of morphologic phenotypes and molecular alterations present in such histologic variants are still incompletely understood. Herein, we describe a case of metastatic prostatic adenocarcinoma with hormonal and chemoradiation therapy-associated differentiation, displaying a combination of squamous cell, small cell, and sarcomatoid elements. The morphologic, immunohistochemical, and molecular observations are discussed with attention given to the gene alterations present, including in TP53, NF1, AR, PTEN, and RB1. Finally, we will compare our findings with those observed in uncommonly reported similar cases so as to detail the molecular underpinnings of such processes which may carry therapeutic implications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗