Sequence Composition Research Articles

WLIP, WLIPβ, and WLIPγ Produced from Pseudomonas canadensis Q3-1 via Precursor-Directed Biosynthesis and Their Roles on Biocontrol of Phytophthora Blight in Peppers.

White line-inducing principle (WLIP, 1), together with two new cyclic lipopeptides (CLPs) WLIPβ (2) and WLIPγ (3), were characterized from the supernatant of Pseudomonas canadensis Q3-1 via precursor-directed biosynthesis (PDB) in the current study. They were purified from the supernatant of P. canadensis Q3-1 by solid-phase extraction (SPE) and high-performance liquid chromatography (HPLC), and their structures were mainly determined via bioinformatic analyses, spectrometric and spectroscopic techniques, as well as single crystal X-ray diffraction (XRD). These WLIPs share (R)-3-hydroxydecanoic acid (HDA), but they differ from each other in the composition of peptidic sequences. In addition, these CLPs showed biocontrol activities against Phytophthora blight (caused by Phytophthora capsici) in peppers. Collectively, this study has shown that PDB could be used for generating new CLPs in Pseudomonas spp. Moreover, we have confirmed that WLIP, WLIPβ, and WLIPγ could be used as lead agrochemicals to control Phytophthora blight in peppers.

Engineered RNA‐Binding Proteins: Studying and Controlling RNA Regulation

AbstractThe complexity of eukaryotic organisms is intricately tied to transcriptome‐level processes, notably alternative splicing and the precise modulation of gene expression through a sophisticated interplay involving RNA‐binding protein (RBP) networks and their RNA targets. Recent advances in our understanding of the molecular pathways responsible for this control have paved the way for the development of tools capable of steering and managing RNA regulation and gene expression. The fusion between a rapidly developing understanding of endogenous RNA regulation and the burgeoning capabilities of CRISPR‐Cas and other programmable RBP platforms has given rise to an exciting frontier in engineered RNA regulators. This review offers an overview of the existing toolkit for constructing synthetic RNA regulators using programmable RBPs and effector domains, capable of altering RNA sequence composition or fate, and explores their diverse applications in both basic research and therapeutic contexts.

Prediction of DNA i-motifs via machine learning.

i-Motifs (iMs), are secondary structures formed in cytosine-rich DNA sequences and are involved in multiple functions in the genome. Although putative iM forming sequences are widely distributed in the human genome, the folding status and strength of putative iMs vary dramatically. Much previous research on iM has focused on assessing the iM folding properties using biophysical experiments. However, there are no dedicated computational tools for predicting the folding status and strength of iM structures. Here, we introduce a machine learning pipeline, iM-Seeker, to predict both folding status and structural stability of DNA iMs. The programme iM-Seeker incorporates a Balanced Random Forest classifier trained on genome-wide iMab antibody-based CUT&Tag sequencing data to predict the folding status and an Extreme Gradient Boosting regressor to estimate the folding strength according to both literature biophysical data and our in-house biophysical experiments. iM-Seeker predicts DNA iM folding status with a classification accuracy of 81% and estimates the folding strength with coefficient of determination (R2) of 0.642 on the test set. Model interpretation confirms that the nucleotide composition of the C-rich sequence significantly affects iM stability, with a positive correlation with sequences containing cytosine and thymine and a negative correlation with guanine and adenine.

MRSLpred-a hybrid approach for predicting multi-label subcellular localization of mRNA at the genome scale.

In the past, several methods have been developed for predicting the single-label subcellular localization of messenger RNA (mRNA). However, only limited methods are designed to predict the multi-label subcellular localization of mRNA. Furthermore, the existing methods are slow and cannot be implemented at a transcriptome scale. In this study, a fast and reliable method has been developed for predicting the multi-label subcellular localization of mRNA that can be implemented at a genome scale. Machine learning-based methods have been developed using mRNA sequence composition, where the XGBoost-based classifier achieved an average area under the receiver operator characteristic (AUROC) of 0.709 (0.668-0.732). In addition to alignment-free methods, we developed alignment-based methods using motif search techniques. Finally, a hybrid technique that combines the XGBoost model and the motif-based approach has been developed, achieving an average AUROC of 0.742 (0.708-0.816). Our method-MRSLpred-outperforms the existing state-of-the-art classifier in terms of performance and computation efficiency. A publicly accessible webserver and a standalone tool have been developed to facilitate researchers (webserver: https://webs.iiitd.edu.in/raghava/mrslpred/).

Alcohol consumption's effects on working memory: Examining familial confounding.

The purpose of our study was to provide a more rigorous test of the causal hypothesis that chronic alcohol use impairs working memory performance. We measured linear associations between a latent factor representing alcohol consumption and accuracy across four working memory tasks before and after accounting for familial confounding using a cotwin control design. Specifically, this study examined accuracy through a latent working memory score, the National Institutes of Health (NIH) Toolbox List Sorting, NIH Toolbox Picture Sequence, Penn Word Memory, and 2-back tasks. The study included data from 158 dizygotic and 278 monozygotic twins (Mage = 29 ± 3 years). In our initial sample-wide analysis, we did not detect any statistically significant associations between alcohol use and working memory accuracy. However, our cotwin control analyses showed that twins with greater levels of alcohol use exhibited worse scores on the latent working memory composite measure (B = -.25, CI [-.43, -.08], p < .01), Picture Sequence (B = -.31, CI [-.55, -.08], p < .01), and List Sorting (B = -.28, CI [-.51, -.06 ], p = .01) tasks than did their cotwins. These results are consistent with a potentially causal relationship between alcohol use and working memory performance that can be detected only after accounting for confounding familial factors. This highlights the importance of understanding the mechanisms that may underlie negative associations between alcohol use and cognitive performance, as well as the potential factors that influence both alcohol behaviors and cognition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Seq2Sat and SatAnalyzer toolkit: Towards comprehensive microsatellite genotyping from sequencing data.

Accurate and efficient microsatellite loci genotyping is an essential process in population genetics that is also used in various demographic analyses. Protocols for next-generation sequencing of microsatellite loci enable high-throughput and cross-compatible allele scoring, common issues that are not addressed by conventional capillary-based approaches. To improve this process, we have developed an all-in-one software, called Seq2Sat (sequence to microsatellite), in C++ to support automated microsatellite genotyping. It directly takes raw reads of microsatellite amplicons and conducts read quality control before inferring genotypes based on depth-of-read, read ratio, sequence composition and length. We have also developed a module for sex identification based on sex chromosome-specific locus amplicons. To allow for greater user access and complement autoscoring, we developed SatAnalyzer (microsatellite analyzer), a user-friendly web-based platform that conducts reads-to-report analyses by calling Seq2Sat for genotype autoscoring and produces interactive genotype graphs for manual editing. SatAnalyzer also allows users to troubleshoot multiplex optimization by analysing read quality and distribution across loci and samples in support of high-quality library preparation. To evaluate its performance, we benchmarked our toolkit Seq2Sat/SatAnalyzer against a conventional capillary gel method and existing microsatellite genotyping software, MEGASAT, using two datasets. Results showed that SatAnalyzer can achieve >99.70% genotyping accuracy and Seq2Sat is ~5 times faster than MEGASAT despite many more informative tables and figures being generated. Seq2Sat and SatAnalyzer are freely available on github (https://github.com/ecogenomicscanada/Seq2Sat) and dockerhub (https://hub.docker.com/r/rocpengliu/satanalyzer).

Flavor Characteristics of Umami Peptides from Wuding Chicken Revealed by Molecular Dynamics Simulation.

Wuding chicken is famous for its delicious meat, and HLEEEIK, LDDALR, and ELY were jointly extracted from different processing stages of Wuding chicken. However, whether these peptides can be used as umami supplements is unclear. The sensory evaluation tests were used to study the taste characteristics. The secondary structure of the peptides and their interaction with T1R1/T1R3 were predicted by the circular dichroism spectrum and molecular dynamics simulation. The umami threshold was 0.03125 to 0.06250 mg/mL, all of which could increase umami, saltiness, sweetness, and mask bitterness. Compared with HLEEEIK, the frequency of umami active fragments and the improvement rate of the umami score of EEE increased by 133.35% and 40.09%, respectively. Peptides were dominated by umami taste according to sensory analysis, among which EE-3 (3.18) has the highest umami intensity followed by LR-4 (2.58), HK-7 (2.13), and EY-3 (1.82). The main secondary structure of umami peptides was β-folding, and Tyr74, Arg323, Arg272, and Gln35 were the key amino acid residues for binding of umami peptides to the receptor. This study further elucidated that the umami intensity of the peptides could be altered by changing the sequence composition of the peptides, which enhanced our understanding of the complex flavor properties of umami peptides.

The origin and structural evolution of de novo genes in Drosophila

Recent studies reveal that de novo gene origination from previously non-genic sequences is a common mechanism for gene innovation. These young genes provide an opportunity to study the structural and functional origins of proteins. Here, we combine high-quality base-level whole-genome alignments and computational structural modeling to study the origination, evolution, and protein structures of lineage-specific de novo genes. We identify 555 de novo gene candidates in D. melanogaster that originated within the Drosophilinae lineage. Sequence composition, evolutionary rates, and expression patterns indicate possible gradual functional or adaptive shifts with their gene ages. Surprisingly, we find little overall protein structural changes in candidates from the Drosophilinae lineage. We identify several candidates with potentially well-folded protein structures. Ancestral sequence reconstruction analysis reveals that most potentially well-folded candidates are often born well-folded. Single-cell RNA-seq analysis in testis shows that although most de novo gene candidates are enriched in spermatocytes, several young candidates are biased towards the early spermatogenesis stage, indicating potentially important but less emphasized roles of early germline cells in the de novo gene origination in testis. This study provides a systematic overview of the origin, evolution, and protein structural changes of Drosophilinae-specific de novo genes.

Helicity of a tardigrade disordered protein contributes to its protective function during desiccation.

To survive extreme drying (anhydrobiosis), many organisms, spanning every kingdom of life, accumulate intrinsically disordered proteins (IDPs). For decades, the ability of anhydrobiosis-related IDPs to form transient amphipathic helices has been suggested to be important for promoting desiccation tolerance. However, evidence empirically supporting the necessity and/or sufficiency of helicity in mediating anhydrobiosis is lacking. Here, we demonstrate that the linker region of CAHS D, a desiccation-related IDP from the tardigrade Hypsibius exemplaris, that contains significant helical structure, is the protective portion of this protein. Perturbing the sequence composition and grammar of the linker region of CAHS D, through the insertion of helix-breaking prolines, modulating the identity of charged residues, or replacement of hydrophobic amino acids with serine or glycine residues results in variants with different degrees of helical structure. Importantly, correlation of protective capacity and helical content in variants generated through different helix perturbing modalities does not show as strong a trend, suggesting that while helicity is important, it is not the only property that makes a protein protective during desiccation. These results provide direct evidence for the decades-old theory that helicity of desiccation-related IDPs is linked to their anhydrobiotic capacity.

Reliable method for predicting the binding affinity of RNA-small molecule interactions using machine learning.

Ribonucleic acids (RNAs) play important roles in cellular regulation. Consequently, dysregulation of both coding and non-coding RNAs has been implicated in several disease conditions in the human body. In this regard, a growing interest has been observed to probe into the potential of RNAs to act as drug targets in disease conditions. To accelerate this search for disease-associated novel RNA targets and their small molecular inhibitors, machine learning models for binding affinity prediction were developed specific to six RNA subtypes namely, aptamers, miRNAs, repeats, ribosomal RNAs, riboswitches and viral RNAs. We found that differences in RNA sequence composition, flexibility and polar nature of RNA-binding ligands are important for predicting the binding affinity. Our method showed an average Pearson correlation (r) of 0.83 and a mean absolute error of 0.66 upon evaluation using the jack-knife test, indicating their reliability despite the low amount of data available for several RNA subtypes. Further, the models were validated with external blind test datasets, which outperform other existing quantitative structure-activity relationship (QSAR) models. We have developed a web server to host the models, RNA-Small molecule binding Affinity Predictor, which is freely available at: https://web.iitm.ac.in/bioinfo2/RSAPred/.

Order effects in task-free learning: Tuning to information-carrying sound features

Event-related potentials (ERPs) acquired during task-free passive listening can be used to study how sensitivity to common pattern repetitions and rare deviations changes over time. These changes are purported to represent the formation and accumulation of precision in internal models that anticipate future states based on probabilistic and/or statistical learning. This study features an unexpected finding; a strong order-dependence in the speed with which deviant responses are elicited that anchors to first learning. Participants heard four repetitions of a sequence in which an equal number of short (30 msec) and long (60 msec) pure tones were arranged into four blocks in which one was common (the standard, p = .875) and the other rare (the deviant, p = .125) with probabilities alternating across blocks. Some participants always heard the sequences commencing with the 30 msec deviant block, and others always with the 60 msec deviant block first. A deviance-detection component known as mismatch negativity (MMN) was extracted from responses and the point in time at which MMN reached maximum amplitude was used as the dependent variable. The results show that if participants heard sequences commencing with the 60 msec deviant block first, the MMN to the 60 msec and 30 msec deviant peaked at an equivalent latency. However, if participants heard sequences commencing with the 30 msec deviant first, the MMN peaked earlier to the 60 msec deviant. Furthermore, while the 30 msec MMN latency did not differ as a function of sequence composition, the 60 msec MMN latency did and was earlier when the sequences began with a 30 msec deviant first. By examining MMN latency effects as a function of age and hearing level it was apparent that the differentiation in 30 msec and 60 msec MMN latency expands with older age and raised hearing threshold due to prolongation of the time taken for the 30 msec MMN to peak. The observations are discussed with reference to how the initial sound composition may tune the auditory system to be more sensitive to different cues (i.e., offset responses vs perceived loudness). The order-effect demonstrates a remarkably powerful anchoring to first learning that might reflect initial tuning to the most valuable discriminating feature within a given listening environment, an effect that defies explanation based on statistical information alone.

Genome-wide identification of rubber tree pathogenesis-related 10 (PR-10) proteins with biological relevance to plant defense

Pathogenesis-related 10 (PR-10) is a group of small intracellular proteins that is one of 17 subclasses of pathogenesis-related proteins in plants. The PR-10 proteins have been studied extensively and are well-recognized for their contribution to host defense against phytopathogens in several plant species. Interestingly, the accumulation of PR-10 proteins in the rubber tree, one of the most economically important crops worldwide, after being infected by pathogenic organisms has only recently been reported. In this study, the homologous proteins of the PR-10 family were systemically identified from the recently available rubber tree genomes in the NCBI database. The sequence compositions, structural characteristics, protein physical properties, and phylogenetic relationships of identified PR-10 proteins in rubber trees support their classification into subgroups, which mainly consist of Pru ar 1-like major allergens and major latex-like (MLP) proteins. The rubber tree PR10-encoding genes were majorly clustered on chromosome 15. The potential roles of rubber tree PR-10 proteins are discussed based on previous reports. The homologous proteins in the PR-10 family were identified in the recent genomes of rubber trees and were shown to be crucial in host responses to biotic challenges. The genome-wide identification conducted here will accelerate the future study of rubber tree PR-10 proteins. A better understanding of these defense-related proteins may contribute to alternative ways of developing rubber tree clones with desirable traits in the future.

Three-state coherent control using narrowband and passband sequences.

In this work, we propose a comprehensive design for narrowband and passband composite pulse sequences by involving the dynamics of all states in the three-state system. The design is quite universal as all pulse parameters can be freely employed to modify the coefficients of error terms. Two modulation techniques, the strength and phase modulations, are used to achieve arbitrary population transfer with a desired excitation profile, while the system keeps minimal leakage to the third state. Furthermore, the current sequences are capable of tolerating inaccurate waveforms, detuning errors, and work well when rotating wave approximation is not strictly justified. Therefore, this work provides versatile adaptability for shaping various excitation profiles in both narrowband and passband sequences.

Genome-wide identification and characterization of the sucrose invertase gene family in Hemerocallis citrina.

Sucrose invertase is an important catalytic enzyme that is widely distributed in plants and can irreversibly hydrolyze sucrose into fructose and glucose. Daylily is an important perennial flower worldwide and a traditional vegetable in East Asia. Previous studies have suggested that sucrose invertase is involved in the aging of daylily flowers. However, knowledge about the number, physicochemical properties, and expression patterns of daylily sucrose invertases is still lacking. Identifying the daylily sucrose invertase family genes in the genome is highly important for understanding phylogenetic evolution and determining the genetic function of sucrose invertase. To obtain basic knowledge about the number, classification, sequence composition, and physicochemical properties of sucrose invertases in daylily, bioinformatics software was used to analyze the genome of Hemerocallis citrina (H. citrina), and the basic properties of sucrose invertase genes and proteins were obtained. Then, combined with transcriptome data from flower organs at different developmental stages, the expression patterns of each gene were clarified. Finally, the reliability of the transcriptome data was verified by quantitative real-time polymerase chain reaction (PCR). Through software analysis, 35 sucrose invertases were identified from the H. citrina genome and named HcINV1-HcINV35; these enzymes belong to three subfamilies: cell wall invertases, vacuolar invertases, and chloroplast invertases. The amino acid composition, motif types, promoter composition, gene structure, protein physicochemical properties, gene chromosomal localization, and evolutionary adaptability of daylily invertases were determined; these results provided a comprehensive understanding of daylily invertases. The transcriptome expression profile combined with fluorescence quantitative reverse transcription-polymerase chain reaction (RT‒PCR) analysis suggested that almost all daylily invertase genes were expressed in flower organs, but even genes belonging to the same subfamily did not exhibit the same expression pattern at different developmental stages, suggesting that there may be redundancy or dissimilation in the function of daylily sucrose invertases.

Grain-size and geochemical investigations on the Novyi Tik site (NW Ukraine) and their significance for understanding the local sedimentary environment in the Pleistocene

&#x0D; &#x0D; &#x0D; Grain size and geochemical composition of the loess-palaeosol sequences are important evidence of the sedimentary environment in the Pleistocene, which enables to revela- tion of the sedimentation rates, the origin of deposits, and the sources of material that contributed to the loess accumulation and pedogenesis. The Kd index (10-50 μm / &lt;5 μm), and the Ti/Zr, Ti/Nb and Ce/Y ratios considered to be indicators of aeolian silt accumulation, whereas the ratio of physical sand to physical clay have been suggested to reveal the relationship between sedimentation and pedogenesis. The grain size and geochemical analysis were applied at the Novyi Tik section (Volyn’ Upland), which is characterized by detailed stratigraphy and lateral diversity of palaeosols and deposits. Based on grain size and geochemical data from the section, four main units have been distinguished, which represent periods with similar sedimentary environment such as MIS 10-7, MIS 6, MIS 5 and MIS 4-2. During MIS 9 and 7, pedogenesis pre- vailed with a slight sedimentary contribution; during short-term cooling, thin loess beds were formed. High loess accumulation rates occurred during MIS 6, however, the source of aeolian dust material was different from those to other loess units. At the end of MIS 6, a period of dynamic sedimentation began, which resulted in the sandy grain-size composition of soils and non-soil deposits of MIS 5. The highest sedimentation rates presumably occurred during the stadials, therefore the soils could inherit the grain-size composition of the parent material. Moreover, during MIS 5 in the valley of the Styr River, episodes of aeolian sand accumulation could take place, since the sandy grain-size composition of soils of that time is widespread throughout the basin of the modern Khrinnyky reservoir. At the end of MIS 5, abrupt changes occurred in the sedimentary environment: sand sedimentation almost ceased and a period of aeolian silt accumulation began, and proceeded until the Holocene.&#x0D; &#x0D; &#x0D;

Molecular detection of Batrachochytrium dendrobatidis (Chytridiomycota) and culturable skin bacteria associated with three critically endangered species of Atelopus (Anura: Bufonidae) in Ecuador.

Chytridiomycosis is a fungal disease responsible for massive amphibian die-offs worldwide, caused by the fungus Batrachochytrium dendrobatidis (Bd). Potential symbiotic relationships between frogs and the bacteria residing on their skin-referred to as skin-bacteria-may inhibit Bd growth, aiding in resistance to this lethal disease. This research had three main objectives: (1) to detect the presence of Bd in native populations of Atelopus balios, A. bomolochos, and A. nanay in the central Andes and coastal southern regions of Ecuador; (2) to identify the culturable skin-bacteria; and (3) to analyze differences among the bacterial communities in the three Atelopus species studied. Skin swabs were collected from two populations of A. balios (107-203 m a.s.l.) and one population each of A. bomolochos and A. nanay (3,064-3,800 m a.s.l.). These swabs served two purposes: first, to detect Bd using conventional PCR; and second, to isolate culturable bacteria, which were characterized through DNA sequencing, molecular phylogeny, and community composition similarity analysis (Jaccard index). Results showed that Bd was present in all species, with positive Bd PCR amplification found in 11 of the 12 sampled amphibians. The culturable skin-bacteria were classified into 10 genera: Pseudomonas (31.4%), Stenotrophomonas (14.3%), Acinetobacter (11.4%), Serratia (11.4%), Aeromonas (5.7%), Brucella (5.7%), Klebsiella (5.7%), Microbacterium (5.7%), Rhodococcus (5.7%), and Lelliottia (2.9%). The Jaccard index revealed that bacterial genera were least similar in A. bomolochos and A. balios (J=0.10), while the highest similarity at the genus level was between A. bomolochos and A. nanay (J=0.33). At the clade-species level, only A. bomolochos and A. nanay show common bacteria (J=0.13). Culturable bacterial communities of specimens diagnosed as Bd positive (n=10) or Bd negative (n=1) share a J value of 0.1 at genus and 0.04 at species-clade level. The prevalence of Bd and the composition of cutaneous bacteria could be influenced by Bd reservoirs, Atelopus biology, and intrinsic environmental conditions. This research contributes to understanding the relationship between endangered Andean species and Bd, and explores the potential use of native skin-bacteria as biocontrol agents against Bd.

Application of Seismic Attribute Analysis Technology Guided by Model Forward Modeling in L29 Area

Taking the SaErTU and Putaohua oil layers in the L29 well area of LHP oilfield in the northern Songliao Basin as the research object, In response to the difficulty of interference between thin interbedded sand and mudstone and strong reflection between strata, which have a significant impact on fine prediction of sand bodies, a stratigraphic model is established based on the geological characteristics of the target layer to eliminate the impact of stratigraphic reflection; Then add a thin layer of sand body to its interior, establish a thin interlayer model, and obtain a geological model that is more in line with the actual situation of the target layer. Using forward simulation, analyze the seismic response characteristics of sand bodies, extract 30 seismic attributes from 4 categories: amplitude statistics, composite seismic trace statistics, sequence and frequency spectrum statistics, and calculate the correlation between cumulative sandstone thickness and seismic attributes, and select a sensitive seismic attribute set;By combining sedimentary and drilling data, the seismic attribute with the highest sensitivity to the target layer is selected. The multi-level dimensionality reduction and gradual improvement of seismic attribute selection methods using “model forward modeling, attribute analysis, relevant optimization, and drilling implementation” can effectively improve the prediction accuracy of thin interbedded sand bodies and greatly reduce the risk of oilfield exploration and development.

Simulation-guided tunable DNA probe design for mismatch tolerant hybridization.

The ability to both sensitively and specifically assess the sequence composition of a nucleic acid strand is an ever-growing field. Designing a detection scheme that can perform this function when the sequence of the target being detected deviates significantly from the canonical sequence however is difficult in part because probe/primer design is based on established Watson-Crick base-pairing rules. We present here a robust and tunable toehold-based exchange probe that can detect a sequence with a variable number of SNPs of unknown identity by inserting a series of controlled, sequential mismatches into the protector seal of the toehold probe, in an effort to make the protector seal "sloppy". We show that the mismatch-tolerant system follows predicted behavior closely even with targets containing up to four mismatches that thermodynamically deviate from the canonical sequence by up to 15 kcal/mole. The system also performs faithfully regardless of the global mismatch position on either the protector seal or target. Lastly, we demonstrate the generalizability of the approach by testing the increasingly mismatch-tolerant protectors on HIV clinical samples to show that the system is capable of resolving multiple, iteratively mutated sequences derived from numerous HIV sub-populations with remarkable precision.

Current MR imaging of cartilage in the context of knee osteoarthritis (part1) : Principles and sequences

Magnetic resonance imaging (MRI) is the clinical method of choice for cartilage imaging in the context of degenerative and nondegenerative joint diseases. The MRI-based definitions of osteoarthritis rely on the detection of osteophytes, cartilage pathologies, bone marrow edema and meniscal lesions but currently ascientific consensus is lacking. In the clinical routine proton density-weighted, fat-suppressed 2D turbo spin echo sequences with echo times of 30-40 ms are predominantly used, which are sufficiently sensitive and specific for the assessment of cartilage. The additionally acquired T1-weighted sequences are primarily used for evaluating other intra-articular and periarticular structures. Diagnostically relevant artifacts include magic angle and chemical shift artifacts, which can lead to artificial signal enhancement in cartilage or incorrect representations of the subchondral lamina and its thickness. Although scientifically validated, high-resolution 3D gradient echo sequences (for cartilage segmentation) and compositional MR sequences (for quantification of physical tissue parameters) are currently reserved for scientific research questions. The future integration of artificial intelligence techniques in areas such as image reconstruction (to reduce scan times while maintaining image quality), image analysis (for automated identification of cartilage defects), and image postprocessing (for automated segmentation of cartilage in terms of volume and thickness) will significantly improve the diagnostic workflow and advance the field further.

Efficient Zero-Sequence Impedance Measurement in Autotransformers Using Low-Voltage Excitation

In accordance with the IEEE standard, the zero-sequence impedance test of transformers necessitates an open or short circuit test on the high-voltage side winding. Power source excitation is applied to the high-voltage test winding using a high-capacity test power supply. To circumvent the need for a large-capacity, high-voltage test power supply in field tests, this paper proposes a method for measuring zero-sequence impedance in autotransformers based on low-voltage excitation and disconnection testing. By applying a three-phase power supply to the lowest voltage side of the autotransformer and creating a disconnection condition, an unbalanced test scenario is established. Subsequently, the composite sequence network equivalent circuit for one-phase and two-phase disconnections between the high-voltage side and the low-voltage side of the transformer is formulated. Calculation formulas for the zero-sequence impedance of the autotransformer under various conditions are derived. The accuracy of the zero-sequence impedance is verified using MATLAB/Simulink simulation software 2018b, evaluating double-winding and three-winding autotransformers in breaking tests under different connection modes. The error is found to be less than 3%. The results of this study affirm the high accuracy of the proposed method.