Sequence Matching Research Articles

Spectral Analysis and Validation of Parietal Signals for Different Arm Movements

Brain signal analysis plays a significant role in attaining data related to motor activities. The parietal region of the brain plays a vital role in muscular movements. This approach aims to demonstrate a unique technique to identify an ideal region of the human brain that generates signals responsible for muscular movements; perform statistical analysis to provide an absolute characterization of the signal and validate the obtained results using a prototype arm. This can enhance the practical implementation of these frequency extractions for future neuro-prosthetic applications and the characterization of neurological diseases like Parkinson’s disease (PD). To play out this handling method, electroencephalogram (EEG) signals are gained while the subject is performing different wrist and elbow movements. Then, the frontal brain signals and just the parietal signals are separated from the obtained EEG signal by utilizing a band pass filter. Then, feature extraction is carried out using Fast Fourier Transform (FFT). Subsequently, the extraction process is done by Daubechies (db4) and Haar wavelet (db1) in MATLAB and classified using the Levenberg-Marquardt Algorithm. The results of the frequency changes that occurred during various wrist movements in the parietal region are compared with the frequency changes that occurred in frontal EEG signals. This proposed algorithm also uses the deep learning pattern analysis network to evaluate the matching sequence for each action that takes place. Maximum accuracy of 97.2% and maximum error range of 0.6684% are achieved during the analysis. Results of this research confirm that the Levenberg-Marquardt algorithm, along with the newly developed deep learning hybrid PatternNet, provides a more accurate range of frequency changes than any other classifier used in previous works of literature. Based on the analysis, the peak-to-peak value is used to define the threshold for the prototype arm, which performs all the intended degrees of freedom (DOF), verifying the results. These results would aid the specialists in their decision-making by facilitating the analysis and interpretation of brain signals in the field of neuroscience, specifically in tremor analysis in PD.

EVOLUTION AT THE MICROFERMENTER LEVEL OF THE GROWTH DYNAMICS OF Saccharomyces cerevisiae AND Starmella bacillaris YEASTS WITH POTENTIAL FOR USE IN WINEMAKING AT THE PIETROASA WINERY

The grape surface hosts a complex community of yeast Saccharomyces and non-Saccharomyces species responsible for spontaneous alcoholic fermentation in wine industry. The yeast strains used for this study were isolated from ‘Tămâioasă Românească’ and ‘Busuioacă de Bohotin’ grape varieties from Pietroasa vineyard, and the isolates were identified through a molecular method. Identification of yeast strains through the BLASTn analysis of the 5.8S-ITS region revealed that PFE5 strain showed the best sequence match to Saccharomyces cerevisiae (98% similarity) and PFE15 strain to Starmerella bacillaris (99.78% similarity), respectively. In this first micro-pilot study, the differences between Sacharomyces and non-Saccharomyces yeasts in batch (for Starmella bacillaris) and fed-batch fermentation system (for S. cerevisae) and how these regimes influence the culture growth were assessed. The applied fed-batch process was capable for producing two times more S. cerevisae yeast biomass than Starmella bacillaris through a batch process. In addition, the yield of S. cerevisiae converting the substrate into biomass was 42.3%, almost double compared to the yield of Starmella bacillaris. Moreover, the cell wet weight (WCW) for S. cerevisae was 32.5 g/L and for Starmella bacillaris 15.35 g/L, respectively. Both yeast biomass will be used at Pietroasa winery for inoculation separately or mixed as co-culture for ‘Tămâioasă Românească’ and ‘Busuioacă de Bohotin’ grape juice.

1230. Identification of Subclinical Healthcare-Associated Clusters of Staphylococcus epidermidis in an Orthopedic Patient Population.

Abstract Background Prosthetic joint infections (PJIs) cause increased morbidity and mortality for patients. Staphylococcus epidermidis (S. epidermidis) can readily form biofilm on implanted medical devices, making this typically commensal species a common cause of PJIs. This study investigates genetic, epidemiologic, and environmental factors contributing to positive S. epidermidis joint cultures. Methods We identified S. epidermidis isolates from hip or knee cultures obtained between 2017-20 in patients with one or more prior corresponding intraarticular procedure at our hospital. Whole genome sequencing and single nucleotide polymorphism (SNP) based clonality analysis was performed using the epiXact® service at Day Zero Diagnostics, including species identification, in silico multi-locus sequence typing (MLST), phylogenomic analysis, along with genotypic assessment of the prevalence of specific antibiotic resistance and virulence genes. Additional epidemiologic review was performed to compare cluster and noncluster cases. Results Sixty phenotypically distinct S. epidermidis joint isolates were identified from 44 patients. After removal of duplicates and impure samples, 46 samples were used for genomic sequencing, and 45 were used for MLST. Four S. epidermidis strains showed phenotypic susceptibility to oxacillin yet harbored mecA, and two showed phenotypic resistance despite not having mecA (Figure 1). Notably, smr was found in all isolates. MupA positivity was not observed. We also identified six clonal clusters, all with SNP distances < 10 (Figure 2). Each cluster consisted of between 2-4 patients. Cluster isolates accounted for 14/45 (31.1%) of S. epidermidis isolates sequenced. Further epidemiologic investigation showed ties to common aspirations or operative procedures although no specific common source was identified. These subclinical clusters appear to be self-limited, suggesting benefit to common infection control practices. Phylogenetic tree of S. epidermidis population and heatmap showing the presence/absence of specific genomic features. Circle color on node tip corresponds to sequence type (MLST). Color strips (right panel) showing genomic feature (gene or marker) presence/absence inferred from WGS de novo assemblies. Green cells correspond to a full match found, and gray cells to no match found. Empty rows correspond to external reference genomes used as controls. *AMR: antimicrobial resistance; ST: sequence type; SNP distance values for all pairs of samples of matching multi-locus sequence types. Only samples belonging to matching multi-locus sequence types (MLSTs) with more than one sample are shown. Blue cells correspond to pairwise distance of < 25 SNPs indicating clonality. 13 isolates with unique MLSTs are not shown. 10 isolates were not included due to having multi-strain or multi-species contamination. *ST: sequence type; SNP: single-nucleotide polymorphism; Univariate analysis of clonal isolates versus non-clonal isolates. Samples not included in the multi-locus sequence type analysis due to contamination were excluded from the univariate analysis. *PJI: prosthetic joint infection; MSIS: Musculoskeletal Infection Society; Conclusion The majority of S. epidermidis isolated from clinical joint samples are diverse in origin, but we identified an important subset of 31% that belonged to subclinical healthcare-associated clusters. Clusters appeared to resolve spontaneously over time, suggesting benefit to routine infection control practices. Diagram of clonal isolate clusters Potential relationships and modes of transmission between clonal isolates in each cluster. *PJI: prosthetic joint infection; MSIS: Musculoskeletal Infection Society; SNP: single-nucleotide polymorphism; Disclosures Mohamad Sater, PhD, Day Zero Diagnostics: Employee|Day Zero Diagnostics: Stocks/Bonds Ian C. Herriott, Bachelor's of Science, Day Zero Diagnostics: Employee|Day Zero Diagnostics: Stocks/Bonds Miriam H. Huntley, PhD, Day Zero Diagnostics: Employee|Day Zero Diagnostics: Ownership Interest.

324. Detection of Antibiotic Resistance Genes and Associated Genera Direct from Blood Samples by Multiplex PCR and Next Generation Sequencing

Abstract Background While blood culture and genotypic or phenotypic testing is standard procedure for identification of sepsis pathogens and resistance, blood culture negative sepsis occurs in 40-60% of patients. A culture independent diagnostic can identify pathogens that do not grow in culture and may provide a more sensitive indicator to blood stream infections. Here we discuss an assay that combines multiplex PCR with next generation sequencing (NGS) to detect resistance genes and pathogenic genera directly from whole blood. These genes include mecA, mecC, vanA, vanB, blaKPC, blaOXA-48 family, blaNDM, blaVIM, blaIMP, blaCMY-2, blaDHA, and blaCTX-M-14 and blaCTX-M-15 groups. Methods K2EDTA whole blood samples were spiked with low titers of antimicrobial resistant bacterial isolates. Sample processing involved chemical lysis of red blood cells, concentration and mechanical lysis of pathogen cells, and multiplex amplification of resistance genes and 16S rRNA gene. A synthetic DNA oligo was added at a fixed concentration as a read control. Samples were sequenced on Illumina platforms. NGS data was analyzed using a bioinformatics pipeline to process and match sequences to curated databases with BLAST. The number of reads per sequence was normalized by the number of reads for the read control, resulting in a read-control-normalized (RCN) value that could be used to establish positivity cutoffs. Results Resistance genes in bacterial pathogen spiked samples were identified at titers ≤ 10 CFU/mL. Owing to a unique dual indexing strategy, cross-reactivity was absent or low enough that cutoffs could be set using RCN values without reducing sensitivity. The expected genus was also detected at ≤ 10 CFU/mL for all samples; however, genera that may be representative of reagent or environmental contamination were observed at levels higher than a universal RCN cutoff in some samples. Conclusion We have shown that this NGS assay can detect 13 antimicrobial resistance genes with high sensitivity and specificity direct from blood. Bacterial genera associated with these genes were detected by this assay. As there is a risk of detection of contaminating species with a 16S target, further research into low DNA reagents or environmental controls may be required. Disclosures Daniel Gamero, BS, T2 Biosystems, inc: WO2018213641A8, EP3861013A1, WO2020055887A1, WO2020252084A1, WO2020257691A1|T2 Biosystems, inc: Stocks/Bonds Kelly Dabrowski, M.S., T2 Biosystems, Inc: Stocks/Bonds Analisa DeVito, B.S., T2 Biosystems, Inc: Stocks/Bonds Roger Smith, Ph.D., T2 Biosystems, Inc: US20180188195A1, EP3849938A1,WO2020257691A1, WO2020252084A1|T2 Biosystems, Inc: Stocks/Bonds Jessica L. Snyder, Ph.D., T2 Biosystems, Inc: CA3062882A1,US20180171388A1,WO2017180745A1 , EP3861013A1 , AU2020296183A1, WO2020055887A1, WO2020252084A1|T2 Biosystems, Inc: Stocks/Bonds.

Interpretable Anomaly Detection in Event Sequences via Sequence Matching and Visual Comparison.

Anomaly detection is a common analytical task that aims to identify rare cases that differ from the typical cases that make up the majority of a dataset. When analyzing event sequence data, the task of anomaly detection can be complex because the sequential and temporal nature of such data results in diverse definitions and flexible forms of anomalies. This, in turn, increases the difficulty in interpreting detected anomalies. In this article, we propose a visual analytic approach for detecting anomalous sequences in an event sequence dataset via an unsupervised anomaly detection algorithm based on Variational AutoEncoders. We further compare the anomalous sequences with their reconstructions and with the normal sequences through a sequence matching algorithm to identify event anomalies. A visual analytics system is developed to support interactive exploration and interpretations of anomalies through novel visualization designs that facilitate the comparison between anomalous sequences and normal sequences. Finally, we quantitatively evaluate the performance of our anomaly detection algorithm, demonstrate the effectiveness of our system through case studies, and report feedback collected from study participants.

The Irish Remonstrance: Prototype for the Declaration of Arbroath

It has long been known that there are similarities between the Declaration of Arbroath and the text known as the Irish Remonstrance which antedates it by three years and survives only in Scottish sources. Both are letters to Pope John XXII complaining of injustices the senders experience at English hands, asking him to intervene that they may be left in peace having a prince of their own ruling over them, the Declaration asserting that the Scots have chosen Robert I as their king, the Remonstrance that the Irish have selected his younger brother, Edward Bruce. Being diplomatic letters both naturally follow a set formula but this paper argues that, when broken into their constituent parts, they make (most notably in their exordium and narratio) a series of about a dozen important points in support of their case, in such a matching sequence as to indicate that the author of the Declaration relied heavily on the text of the Remonstrance. Given the high regard in which the Declaration is justifiably held, and the rather poor opinion modern scholarship has had of its Irish exemplar, the paper advocates a re-evaluation of the latter.

A CRISPR view on autophagy.

Autophagy is a fundamental pathway for the degradation of cytoplasmic content in response to pleiotropic extracellular and intracellular stimuli. Recent advances in the autophagy field have demonstrated that different organelles can also be specifically targeted for autophagy with broad implications on cellular and organismal health. This opens new dimensions in the autophagy field and more unanswered questions on the rationale and underlying mechanisms to degrade different organelles. Functional genomics via clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9-based screening has gained popularity in the autophagy field to understand the common and unique factors that are implicated in the signaling, recognition, and execution of different cargo-specific autophagies. We focus on recent applications of CRISPR-based screens in the autophagy field, their discoveries, and the future directions of autophagy screens.

On the Timescales of Embodied Intelligence for Autonomous Adaptive Systems

Embodiment is a crucial concept for the autonomy and adaptivity of systems working in the physical world with high degrees of uncertainty and complexity. The physical bodies of autonomous adaptive systems heavily influence the information flow from the environment to the central processing (and vice versa), requiring us to consider the full triad of brain, body, and environment to investigate intelligent behavior. This article provides a structured review of embodied intelligence with a special emphasis on the concept of timescales and their role in self-organization and the emergence of complex behavior. We classify embodied interactions into three types—cross-timescale matching, separation, and nontemporal sequences—and discuss how these interactions were studied in the past as well as how they can contribute to the systematic investigation of complex autonomous and adaptive systems in both biological and artificial entities.

First report of Fusarium commune causing root rot of soybean seedlings in Indiana.

In the summer of 2020, 127 soybean [Glycine max (L.) Merr] seedlings (V1-V3 stage) with reduced growth vigor were sampled as part of a bulk collection of seedling pathogens from Purdue's Agronomy Center for Research and Education in West Lafayette, Indiana. After rinsing off soil, one plant displayed prominent necrotic lesions on both cotyledons and the hypocotyl and rot of the roots. Root tissue segments measuring roughly 5 mm in length and adjacent to lesions were excised and surface sterilized in 0.6% NaOCl for 10 min, then in 70% ethanol for 2 min, rinsed thrice in sterile distilled H2O, and plated on dichloran-chloramphenicol-peptone agar (Andrews and Pitt 1986). Single-spore cultures were produced and grown on potato dextrose agar. The isolate (AC101) developed white aerial mycelium, rings of magenta coloration in the media, and pale orange sporodochia with age. Microscopic observation of two-week-old cultures grown on synthetic low-nutrient agar (NRRL Medium No. 4) in the dark at 28°C revealed 2-3 septate falcate macroconidia measuring 17.1 - 43.9 × 2.8 - 3.5 µm (avg. 29.4 × 3.1 µm, n=20); 0-1 septate straight to slightly curved microconidia measuring 3.9 - 8.6 × 1.9 - 2.5 µm (avg. 7.0 × 2.2 µm, n=20); and round chlamydospores borne singly or doubly with diameter measuring 6.1 - 14.2 µm (avg. 8.9 µm, n=20). These characteristics were consistent with descriptions of Fusarium commune K. Skovg., O'Donnell & Nirenberg (Skovgaard et al. 2003). DNA was extracted from aerial mycelium and the internal transcribed spacer (ITS) region using ITS1/ITS4 primers (White et al. 1990) (GenBank accession MW463361), the mitochondrial small subunit (mtSSU) rDNA using MS1/MS2 primers (White et al. 1990) (MW466537), and the translation elongation factor 1-alpha (TEF1α) gene using 983F/1567R primers (Rehner and Buckley 2005) (MW475296) were amplified and sequenced. Blast searches in GenBank showed that these sequences had 100% identity with corresponding sequences of F. commune (ITS: MN452698; mtSSU: AF362277; and TEF1α: KU171720). The matching mtSSU sequence was an accession from the original species description (Skovgaard et al. 2003). A pathogenicity test was conducted under greenhouse conditions (20-29°C, avg. 24°C) following the infested soil protocol of Ellis et al. (2013a). Ten seeds (cv. Williams) each were used in inoculated and mock-inoculated control treatments with one seed per foam cup. Root rot symptoms similar to, but more destructive than those observed in the field, were observed 14 days after planting on all inoculated plants but not on controls. Inoculated plants reached VE stage compared to controls which reached VC. Disease symptoms included severe necrotic lesions on the cotyledons, dark brown rot of the developing tap root, and brown hypocotyl lesions similar to field symptoms. F. commune was successfully reisolated from inoculated plants, but not from controls, as described above. F. commune has been reported to cause soybean root rot in China (Chang et al. 2018), Korea (Choi et al. 2020), as well as Iowa (Ellis et al. 2013b). To our knowledge this is the first report of F. commune infecting soybean seedlings in the state of Indiana. The expanded distribution of this soybean pathogen warrants heightened attention for its control.

New insights into transmission pathways and possible off-target effects of insecticidal dsRNA released by treated plants

RNAi has shown great potential in controlling pests and pathogens, and dsRNA-based pesticides have been used in different ways. Due to off-target effects, the transmission pathways and possible impacts of dsRNA on non-target organisms after release should be researched. Here, we tested pathways of dsRNA transmission through the rice-hopper-spider food chain and their efficiency for triggering RNAi.The results revealed five new pathways by which plants transfer dsRNA into the environment through the food chain. We found that ingestion of the tissues or guttation droplets of treated plant could trigger both targeted and off-target RNAi both in consumers and predators. Ingestion of consumer hoppers could also result in localized RNAi in the midguts of the predator spiders. Trace amounts of dsRNA were detected in plant root excretions and in hopper honeydew. Cutting the root tips dramatically increased the levels of dsRNA in root excretions. Host shifting experiments proved that hoppers could transfer a trace amount of dsRNA via vomit. With specially designed dsRNAs, we showed that dsRNA sharing matching sequences of 29 bp or 32 bp in length with non-target genes could trigger off-target RNAi, but that dsRNA sharing 13 bp matching sequences could not.We conclude that field-released pesticidal dsRNA could be transmitted via the hydrophilic transport system in plants, and that this may pose a safety risk to non-target animal consumers that are closely related to target pests. Rational use of pesticidal dsRNAs should involve careful consideration of dsRNA design to manage the biosafety risk.

Molecular Assessment of Domain I of Apical Membrane Antigen I Gene in Plasmodium falciparum: Implications in Plasmodium Invasion, Taxonomy, Vaccine Development, and Drug Discovery.

Given its global morbidity and mortality rates, malaria continues to be a major public health concern. Despite significant progress in the fight against malaria, efforts to control and eradicate the disease globally are in jeopardy due to lack of a universal vaccine. The conserved short peptide sequences found in Domain I of Plasmodium falciparum apical membrane antigen 1 (PfAMA1), which are exposed on the parasite cell surface and in charge of Plasmodium falciparum invasion of host cells, make PfAMA1 a promising vaccine candidate antigen. The precise amino acids that make up these conserved short peptides are still unknown, and it is still difficult to pinpoint the molecular processes by which PfAMA1 interacts with the human host cell during invasion. The creation of a universal malaria vaccine based on the AMA1 antigen is challenging due to these knowledge limitations. This study used genome mining techniques to look for these particular short peptides in PfAMA1. Thirty individuals with Plasmodium falciparum malaria had blood samples taken using Whatman's filter papers. DNA from the parasite was taken out using the Chelex technique. Domain I of the Plasmodium falciparum AMA1 gene was amplified using nested polymerase chain reactions, and the amplified products were removed, purified, and sequenced. The DNA sequence generated was converted into the matching amino acid sequence using bioinformatic techniques. These amino acid sequences were utilized to search for antigenic epitopes, therapeutic targets, and conserved short peptides in Domain I of PfAMA1. The results of this investigation shed important light on the molecular mechanisms behind Plasmodium invasion of host cells, a potential PfAMA1 vaccine antigen sequence, and prospective malaria treatment options in the future. Our work offers fresh information on malaria medication and vaccine research that has not been previously discussed.

Multi-Wavelength Spatiotemporal Mode-Locked Fiber Laser at 1.55 μm

We propose and demonstrate an effective and simple multi-wavelength spatiotemporal mode-locked (STML) laser. The laser introduces a multimode interference (MMI) effect using the core diameter mismatch of the fibers, thus enabling simultaneous mode-locking at multiple wavelengths. For the multi-wavelength mode-locking, each wavelength exists a matching pulse sequence, and different wavelengths can possess the same pulse state or different states. Meanwhile, at the dual-wavelength operation, by adjusting the polarization controllers, not only the central wavelength can be continuously adjusted from 1552.93 nm to 1572.64 nm, but also the wavelength interval can be adjusted from 2 nm to 19 nm, which benefits from the tunability of the MMI effect. Moreover, the spectral channels can be consecutively increased from 2 to 4. The obtained results provide a platform for understanding and studying the multi-wavelength STML properties. This flexible all-fiber laser has great potential for applications in the fields of optical signal processing, fiber sensing, and information coding.

Viruses Broaden the Definition of Life by Genomic Incorporation of Artificial Intelligence and Machine Learning Processes.

Viruses have been classified as non-living because they require a cellular host to support their replicative processes. Empirical investigations have significantly advanced our understanding of the many strategies employed by viruses to usurp and divert host regulatory and metabolic processes to drive the synthesis and release of infectious particles. The recent emergence of SARS-CoV-2 has permitted us to evaluate and discuss a potentially novel classification of viruses as living entities. The ability of SARS CoV-2 to engender comprehensive regulatory control of integrative cellular processes is strongly suggestive of an inherently dynamic informational registry that is programmatically encoded by linear ssRNA sequences responding to distinct evolutionary constraints. Responses to positive evolutionary constraints have resulted in a single-stranded RNA viral genome that occupies a threedimensional space defined by conserved base-paring resulting from a complex pattern of both secondary and tertiary structures. Additionally, regulatory control of virus-mediated infectious processes relies on extensive protein-protein interactions that drive conformational matching and shape recognition events to provide a functional link between complementary viral and host nucleic acid and protein domains. We also recognize that the seamless integration of complex replicative processes is highly dependent on the precise temporal matching of complementary nucleotide sequences and their corresponding structural and non-structural viral proteins. Interestingly, the deployment of concerted transcriptional and translational activities within targeted cellular domains may be modeled by artificial intelligence (AI) strategies that are inherently fluid, self-correcting, and adaptive at accommodating temporal changes in host defense mechanisms. An in-depth understanding of multiple self-correcting AIassociated viral processes will most certainly lead to novel therapeutic development platforms, notably the design of efficacious neuropharmacological agents to treat chronic CNS syndromes associated with long-COVID. In summary, it appears that viruses, notably SARS-CoV-2, are very much alive due to acquired genetic advantages that are intimately entrained to existential host processes via evolutionarily constrained AI-associated learning paradigms.

Txp40, an insecticidal toxin protein from Xenorhabdus nematophila: Purification, toxicity assessment and biophysical characterization

Txp40 is a ubiquitous toxin from Xenorhabdus and Photorhabdus bacteria, exhibits insecticidal activity against a wide range of insect pests belonging to Lepidoptera and Diptera orders. Initially, Txp40 affects midgut of the target insect and further damages some other tissues like fat bodies but the detailed mode of action is not known. Txp40 shares no significant sequence match to any proteins with known structure or function, suggesting that it is a novel type of insecticidal toxin. Here, we report purification, toxicity and biophysical characterization of the Txp40b toxin from X. nematophila (ATCC, 19061). The recombinant Txp40b was found toxic to Galleria mellonella larvae with LD50 of 30.42 ng larva−1. Circular dichroism spectroscopy revealed that purified Txp40b is an α-helix rich protein with a relatively lower melting temperature of 45 °C. In-silico model generated suggests two domain structure of Txp40b toxin. Detailed structural analysis of Txp40b will provide new insights about the mode of action and possibly it would illustrate a new domain and/or motif in the area of insecticidal proteins.

Lightweight Pattern Matching Method for DNA Sequencing in Internet of Medical Things.

An area of medical science, that is, gaining prominence, is DNA sequencing. Genetic mutations responsible for the disease have been detected using DNA sequencing. The research is focusing on pattern identification methodologies for dealing with DNA-sequencing problems relating to various applications. A few examples of such problems are alignment and assembly of short reads from next generation sequencing (NGS), comparing DNA sequences, and determining the frequency of a pattern in a sequence. The approximate matching of DNA sequences is also well suited for many applications equivalent to the exact matching of the sequence since the DNA sequences are often subject to mutation. Consequently, recognizing pattern similarity becomes necessary. Furthermore, it can also be used in virtually every application that calls for pattern matching, for example, spell-checking, spam filtering, and search engines. According to the traditional approach, finding a similar pattern in the case where the sequence length is ls and the pattern length is lp occurs in O (ls∗lp). This heavy processing is caused by comparing every character of the sequence repeatedly with the pattern. The research intended to reduce the time complexity of the pattern matching by introducing an approach named “optimized pattern similarity identification” (OPSI). This methodology constructs a table, entitled “shift beyond for avoiding redundant comparison” (SBARC), to bypass the characters in the texts that are already compared with the pattern. The table pertains to the information about the character distance to be skipped in the matching. OPSI discovers at most spots of similar patterns occur in the sequence (by ignoring è mismatches). The experiment resulted in the time complexity identified as O (ls. è). In comparison to the size of the pattern, the allowed number of mismatches will be much smaller. Aspects such as scalability, generalizability, and performance of the OPSI algorithm are discussed. In comparison with the hamming distance-based approximate pattern matching algorithm, the proposed algorithm is found to be 69% more efficient.

BinDiffNN : Learning Distributed Representation of Assembly for Robust Binary Diffing Against Semantic Differences

Binary diffing is a process to discover the differences and similarities in functionality between two binary programs. Previous research on binary diffing approaches it as a <i>function matching</i> problem to formulate an initial 1:1 mapping between functions, and later a sequence matching ratio is computed to classify two functions being an <i>exact</i> match, a <i>partial</i> match or <i>no-match</i> . The accuracy of existing techniques is best only when detecting exact matches and they are not efficient in detecting partially changed functions; especially those with minor patches. These drawbacks are due to two major challenges (i) In the 1:1 mapping phase, using a strict policy to match function features (ii) In the classification phase, considering an assembly snippet as a normal text, and using sequence matching for similarity comparison. Instruction has a unique structure i.e. mnemonics and registers have a specific position in instruction and also have a semantic relationship, which makes assembly code different from general text. Sequence matching performs best for general text but it fails to detect structural and semantic changes at an instruction level thus, its use for classification produces many false results. In this research, we have addressed the aforementioned underlying challenges by proposing a two-fold solution. For the 1:1 mapping phase, we have proposed computationally inexpensive features, which are compared with distance-based selection criteria to map similar functions and filter unmatched functions. For the classification phase, we have proposed a Siamese binary-classification neural network where each branch is an attention-based distributed learning embedding neural network — that learn the semantic similarity among assembly instructions, learn to highlight the changes at an instruction level and a final stage fully connected layer learn to accurately classify two 1:1 mapped function either an <i>exact</i> or a partial match. We have used x86 kernel binaries for training and achieved <inline-formula><tex-math notation="LaTeX">$\sim 99\%$</tex-math></inline-formula> classification accuracy; which is higher than existing binary <i>diffing</i> techniques and tools.

3D Reconstruction Method of Space Target on Optical Images with Wide Baseline via Neural Radiance Field

3D reconstruction of space targets using optical measurement data is an important topic in the field of space surveillance and spacecraft service in orbit. The core of current mainstream 3D reconstruction methods is to establish feature association between optical images. In space-based optical imaging scenes, the texture of target region is missing and the range of view is large, which causes great difficulties in feature extraction and matching of image sequences. Neural radiance field technology does not need to extract explicit features, and its implicit expression of 3D scenes has great potential for solving reconstruction problems in weak texture and broad baseline cases. Therefore, a novel 3D reconstruction method for a sequence of images based on neural radiance field is proposed. The proposed method breaks through the limitation of traditional 3D reconstruction methods which rely on rich texture and narrow baseline image sequences. Simulation experiments show that compared with the existing methods for space target images with weak texture and wide baseline, our method performs better in terms of accuracy and completeness.

Extensive diversity and rapid turnover of phage defense repertoires in cheese-associated bacterial communities

BackgroundPhages are key drivers of genomic diversity in bacterial populations as they impose strong selective pressure on the evolution of bacterial defense mechanisms across closely related strains. The pan-immunity model suggests that such diversity is maintained because the effective immune system of a bacterial species is the one distributed across all strains present in the community. However, only few studies have analyzed the distribution of bacterial defense systems at the community-level, mostly focusing on CRISPR and comparing samples from complex environments. Here, we studied 2778 bacterial genomes and 188 metagenomes from cheese-associated communities, which are dominated by a few bacterial taxa and occur in relatively stable environments.ResultsWe corroborate previous laboratory findings that in cheese-associated communities nearly identical strains contain diverse and highly variable arsenals of innate and adaptive (i.e., CRISPR-Cas) immunity systems suggesting rapid turnover. CRISPR spacer abundance correlated with the abundance of matching target sequences across the metagenomes providing evidence that the identified defense repertoires are functional and under selection. While these characteristics align with the pan-immunity model, the detected CRISPR spacers only covered a subset of the phages previously identified in cheese, providing evidence that CRISPR does not enable complete immunity against all phages, and that the innate immune mechanisms may have complementary roles.ConclusionsOur findings show that the evolution of bacterial defense mechanisms is a highly dynamic process and highlight that experimentally tractable, low complexity communities such as those found in cheese, can help to understand ecological and molecular processes underlying phage-defense system relationships. These findings can have implications for the design of robust synthetic communities used in biotechnology and the food industry.DbLYqYwr-FU-DxBRk3MVnLVideo

Craspase is a CRISPR RNA-guided, RNA-activated protease.

The CRISPR-Cas type III-E RNA-targeting effector complex gRAMP/Cas7-11 is associated with a caspase-like protein (TPR-CHAT/Csx29) to form Craspase (CRISPR-guided caspase). Here, we use cryo-electron microscopy snapshots of Craspase to explain its target RNA cleavage and protease activation mechanisms. Target-guide pairing extending into the 5' region of the guide RNA displaces a gating loop in gRAMP, which triggers an extensive conformational relay that allosterically aligns the protease catalytic dyad and opens an amino acid side-chain-binding pocket. We further define Csx30 as the endogenous protein substrate that is site-specifically proteolyzed by RNA-activated Craspase. This protease activity is switched off by target RNA cleavage by gRAMP and is not activated by RNA targets containing a matching protospacer flanking sequence. We thus conclude that Craspase is a target RNA-activated protease with self-regulatory capacity.

High-performance strategy for the construction of electrochemical biosensor for simultaneous detection of miRNA-141 and miRNA-21 as lung cancer biomarkers

In this study, the dual signal-labeled hairpin-structured DNA (dhDNA)-based probes have been developed to construct a novel nano-biosensor. This one hairpin-structured probe consists of a thiolated methylene blue-labeled hairpin capture probe (MB-HCP) as an inner reference probe and a ferrocene-modified anti-miRNA-21 DNA probe (Fc-AP-21). This novel integrated structure of MB-HCP and Fc-AP-21 was designed on one sensing interface for sensitive and simultaneous detection of the miRNA-141 and miRNA-21 in one single assay. The proposed strategy has a good ability to reduce the interference of environmental factors and it was designed to control the initial responses of Fc-AP to MB-HCP ((IFc/IMB)0) at a 1:1 ratio, which is desirable for further increase in the sensitivity and signal-to-noise ratio of the biosensor operation. Besides, the biosensor was first prepared by immobilizing the dhDNA (Fc-AP-21/MB-HCP) onto the modified glassy carbon electrode. After hybridization with the anti-miRNA-141 complementary sequence (ACP-141), the dhDNA structure was compelled to open and form the final structure of the biosensor. Also, the miRNA-141 and miRNA-21 dissociate duplex structures due to the highly matched sequences between the miRNA-141 and ACP-141 and the miRNA-21 and Fc-AP-21. A linear relationship was found between the logarithm of miRNA-141 and miRNA-21 concentrations and the signal changes. This feature was used to detect the two miRNAs. This sensitive biosensor provided low detection limits of 0.89 and 1.24 fM for the miRNA-141 and miRNA-21, respectively. Also, it has wide linear ranges of 2.0 to 105 fM, with highly selective and accurate results for its application in plasma samples. Therefore, this strategy can be promising as a suitable platform for simultaneous and early detection of various cancer biomarkers.