Analysis Of Patterns Research Articles

Magnetic 3D macroporous MOF oriented urinary exosome metabolomics for early diagnosis of bladder cancer

Bladder cancer (BCa) exhibits the escalating incidence and mortality due to the untimely and inaccurate early diagnosis. Urinary exosome metabolites, carrying critical tumor cell information and directly related to bladder, emerge as promising non-invasive diagnostic biomarkers of BCa. Herein, the magnetic 3D ordered macroporous zeolitic imidazolate framework-8 (magMZIF-8) is synthesized and used for efficient urinary exosome isolation. Notably, beyond retaining the single crystals and micropores of conventional ZIF-8, MZIF-8 is further enhanced with highly oriented and ordered macropores (150 nm) and the large specific surface area (973 m2·g–1), which could enable the high purity and yield separation of exosomes via leveraging the combination of size exclusion, affinity, and electrostatic interactions between magMZIF-8 and the surfaces of exosome. Furthermore, the magnetic and hydrophilic properties of magMZIF-8 will further simplify the process and enhance the efficiency of separation. After conditional optimization, a 50 mL of urine is sufficient for exosome metabolomics analysis, and the time for isolating exosomes from 42 urine samples was 2 hours only. Incorporating machine learning algorithms with LC-MS/MS analysis of the metabolic patterns obtained from isolated exosomes, early-stage BCa patients were differentiated from healthy controls, with area under the curve (AUC) value of 0.844–0.9970 in the training set and 0.875-1.00 in the test set, signifying its potential as a reliable diagnostic tool. This study offers a promising approach for the non-invasive and efficient diagnosis of BCa on a large scale via exosome metabolomics.Graphical

High temporal resolution paleoclimate reconstruction by the analysis of growth patterns and stable isotopes of fossil shells of the long-lived bivalve Mercenaria stimpsoni from MIS 5e, 7 and 9

High temporal resolution paleoclimate reconstruction by the analysis of growth patterns and stable isotopes of fossil shells of the long-lived bivalve Mercenaria stimpsoni from MIS 5e, 7 and 9

Novel assessment of CPAP adherence data reveals distinct diurnal patterns.

Obstructive sleep apnea (OSA) is a prevalent condition effectively treated by continuous positive airway pressure (CPAP) therapy. CPAP adherence data, routinely gathered in clinical practice, include detailed information regarding both duration and timing of use. The purpose of the present study was to develop a systematic way to measure the diurnal pattern of CPAP adherence data and to see if distinct patterns exist in a clinical cohort. Machine learning techniques were employed to analyze CPAP adherence data. A cohort of 200 unselected patients was assessed and a cluster analysis was subsequently performed. Application of this methodology to 17 patients with different visually noted patterns was carried out to further assess performance. Each 30-day period of CPAP use for each patient was characterized by four variables describing the time of day of initiation and discontinuation of CPAP use, as well as the consistency of use during those times. Further analysis identified six distinct clusters, reflecting different timing and adherence patterns. Specifically, clusters with relatively normal timing versus delayed timing were identified. Finally, application of this methodology showed generally good performance with limitations in the ability to characterize shift worker and non-24 rhythms. This study demonstrates a methodology for analysis of diurnal patterns from CPAP adherence data. Furthermore, distinct timing and adherence patterns are demonstrated. The potential impact of these patterns on the beneficial effects of CPAP requires elucidation.

Resting state of human brain measured by fMRI experiment is governed more dominantly by essential mode as a global signal rather than default mode network

Resting-state of the human brain has been described by a combination of various basis modes including the default mode network (DMN) identified by fMRI BOLD signals in human brains. Whether DMN is the most dominant representation of the resting-state has been under question. Here, we investigated the unexplored yet fundamental nature of the resting-state. In the absence of global signal regression for the analysis of brain-wide spatial activity pattern, the fMRI BOLD spatiotemporal signals during the rest were completely decomposed into time-invariant spatial-expression basis modes (SEBMs) and their time-evolution basis modes (TEBMs). Contrary to our conventional concept above, similarity clustering analysis of the SEBMs from 166 human brains revealed that the most dominant SEBM cluster is an asymmetric mode where the distribution of the sign of the components is skewed in one direction, for which we call essential mode (EM), whereas the second dominant SEBM cluster resembles the spatial pattern of DMN. Having removed the strong 1/f noise in the power spectrum of TEBMs, the genuine oscillatory behavior embedded in TEBMs of EM and DMN-like mode was uncovered around the low-frequency range below 0.2 Hz.

Cross-Time-Scale Analysis of Year-Round Atmospheric Circulation Patterns and Their Impacts on Rainfall and Temperatures in the Iberian Peninsula

Abstract This study presents a framework to assess climate variability and change through atmospheric circulation patterns (CPs) and their link with regional processes across time scales. We evaluate the CP impacts on daily rainfall and maximum and minimum temperatures in the Iberian Peninsula using sea level pressure (SLP) during 1950–2022. Different sensitivity analyses are performed, employing multiple spatial domains and number of patterns. An optimal classification is found in midlatitudes, centered over the Mediterranean basin and covering part of the North Atlantic Ocean, which can identify atmospheric configurations significantly related to discriminated rainfall and temperature anomalies, with clear seasonal behavior. The temporal variability of CPs is studied across time scales showing, e.g., that transitions between patterns are faster in autumn and spring, and that CPs exhibit distinct temporal variability at intraseasonal, seasonal, interannual, and decadal scales, including significant long-term trends on their frequency. CPs influence temperature and precipitation variations throughout the year. The winter season exhibits the largest atmospheric circulation variability, while the summer is dominated by persistent high-pressure structures—the subtropical Azores high—leading to warm and dry conditions. Based on an interannual correlation analysis, some CPs are significantly associated with the North Atlantic Oscillation (NAO), stronger during winter, indicating the NAO modulation on the regional-to-local climatic features. Overall, this approach arises as a dynamic cross-time-scale framework that can be adapted to specific user needs and levels of regional detail, being useful to study climate drivers for climate change and to perform a process-based evaluation of climate models.

ChatKG: Visualizing time-series patterns aided by intelligent agents and a knowledge graph

Line-chart visualizations of temporal data enable users to identify interesting patterns for the user to inquire about. Using Intelligent Agents (IA), Visual Analytic tools can automatically uncover explicit knowledge related information to said patterns. Yet, visualizing the association of data, patterns, and knowledge is not straightforward. In this paper, we present ChatKG, a novel visual analytics strategy that allows exploratory data analysis of a Knowledge Graph that associates temporal sequences, the patterns found in each sequence, the temporal overlap between patterns, the related knowledge of each given pattern gathered from a multi-agent IA, and the IA’s suggestions of related datasets for further analysis visualized as annotations. We exemplify and informally evaluate ChatKG by analyzing the world’s life expectancy. For this, we implement an oracle that automatically extracts relevant or interesting patterns, populates the Knowledge Graph to be visualized, and, during user interaction, inquires the multi-agent IA for related information and suggests related datasets to be displayed as visual annotations. Our tests and an interview conducted showed that ChatKG is well suited for temporal analysis of temporal patterns and their related knowledge when applied to history studies.

Systematic analysis of mixing and segregation patterns of binary mixtures in fluidised beds for multi-functional processes

Systematic analysis of mixing and segregation patterns of binary mixtures in fluidised beds for multi-functional processes

Pain-Discriminating Information Decoded From Spatiotemporal Patterns of Hemodynamic Responses Measured by fMRI in the Human Brain.

Functional magnetic resonance imaging (fMRI) has been widely used in studying the neural mechanisms of pain in the human brain, primarily focusing on where in the brain pain-elicited neural activities occur (i.e., the spatial distribution of pain-related brain activities). However, the temporal dynamics of pain-elicited hemodynamic responses (HDRs) measured by fMRI may also contain information specific to pain processing but have been largely neglected. Using high temporal resolution fMRI (TR = 0.8 s) data acquired from 62 healthy participants, in the present study we aimed to test whether pain-distinguishing information could be decoded from the spatial pattern of the temporal dynamics (i.e., the spatiotemporal pattern) of HDRs elicited by painful stimuli. Specifically, the peak latency and the response duration were used to characterize the temporal dynamics of HDRs to painful laser stimuli and non-painful electric stimuli, and then were compared between the two conditions (i.e., pain and no-pain) using a voxel-wise univariate analysis and a multivariate pattern analysis. Furthermore, we also tested whether the two temporal characteristics of pain-elicited HDRs and their spatial patterns were associated with pain-related behaviors. We found that the spatial patterns of HDR peak latency and response duration could successfully discriminate pain from no-pain. Interestingly, we also observed that the Pain Vigilance and Awareness Questionnaire (PVAQ) scores were correlated with the average response duration in bilateral insula and secondary somatosensory cortex (S2) and could also be predicted from the across-voxel spatial patterns of response durations in the middle cingulate cortex and middle frontal gyrus only during painful condition but not during non-painful condition. These findings indicate that the spatiotemporal pattern of pain-elicited HDRs may contain pain-specific information and highlight the importance of studying the neural mechanisms of pain by taking advantage of the high sensitivity of fMRI to both spatial and temporal information of brain responses.

Liquid and gas permeabilities of nanostructured layers: Three-dimensional lattice Boltzmann simulation

Liquid water and gas permeabilities in nanostructured catalyst layers (CLs) (pore size ∼10–150 nm) and microporous layers (MPLs) (pore size ∼50 nm-5 μm) are crucial to reduce the mass transport loss in proton exchange membrane fuel cells (PEMFCs). Experimental measurement of their permeabilities poses great challenges due to their brittle and thin characteristics. Presently, considerable discrepancy exists in the reported permeability values for CLs and MPLs in the literature with variation spanning several orders of magnitude. This study digitally reconstructed various nanostructures of similar pore size as CLs and MPLs to calculate their permeabilities using the Lattice Boltzmann Method (LBM) based on no-slip (e.g. for liquid water flow in MPL and CL's secondary pores) or slip condition (e.g. for gas flow in MPL). Analysis was performed to evaluate the range of pore size in nanostructures for the two boundary conditions. A comprehensive investigation was conducted under various parameters such as the Reynolds number (Re), sphere diameter, porosity, and pore structure. The results revealed that permeability exhibits an increasing trend with the diameter and porosity. The predicted permeability of randomly arranged spheres agrees well with established correlations. The random sphere structure demonstrates higher permeability than their body-centered cubic (BCC) and face-centered cubic (FCC) counterparts. Under slip boundary condition, the permeability was enhanced, compared to the no-slip condition. This study's novelty lies in using distinct boundary conditions to assess the permeabilities of liquid and air, based on flow pattern analysis in the CL and MPL pore structures. A new empirical correlation describing the influence of the Knudsen number (Kn) on the slip permeability was developed, exhibiting consistency with simulation across the entire porosity spectrum.

Hydrological drought life-cycle: Faster onset and recovery in humid than semi-arid basins in China

The hydrological drought life-cycle begins at the onset and includes intensification and recovery stages. Previous studies have mainly considered each stage separately, so a comprehensive life-cycle pattern analysis is lacking. Moreover, differences in hydrological drought life-cycle patterns across different climatic basins still need in-depth research. This study proposed an integrated framework for analyzing the life-cycle patterns of hydrological droughts and used it to compare semi-arid and humid basins of China. The empirical analysis involved long-term (≥30 years) monthly runoff and precipitation data from six basins—three in semi-arid and three in humid zones of China. We identified the onset thresholds of hydrological drought events from the response relationship of hydrological drought to meteorological drought, considering both duration and severity thresholds. Then, using the “time–speed” process relationship, the intensification and recovery stages of hydrological drought events were quantified. Finally, the life-cycle patterns of hydrological drought in humid and semi-arid basins of China were compared. The results indicated that: (1) the proposed integrated framework, utilizing life-cycle analysis techniques to investigate the onset thresholds, intensification, and recovery of hydrological drought, provided valuable insights into their differences across different climatic basins; (2) compared to the semi-arid basins of northern China, the humid basins exhibited lower onset thresholds, slower intensification, and quicker recovery. This indicated that, in the humid basins of southern China, the onset thresholds for hydrological drought are reached rapidly after meteorological drought, followed by more gradual intensification and faster recovery stages. This underscored the importance of recognizing the distinctive life-cycle patterns of hydrological drought in different climatic zones so that tailored strategies for effective drought prevention and mitigation can be devised

Commercial forensic interviewing in the South African context: the Ponaletso CFI framework

Purpose The continued prevalence of financial crime and the lack of effective commercial forensic interviewing strategies prompted the development, presented here, of a conceptual framework to explain the relational dynamics conducive to interactions during a commercial forensic interview (CFI). The purpose of this study is to present such a framework which may facilitate the process of obtaining admissible evidence in different forums. Design/methodology/approach A grounded theory approach was adopted to develop a conceptual framework, drawing on the findings of a scoping review, direct observations of interactions involving commercial forensic practitioners (FPs) and interviewees, and data obtained from semi-structured interviews, making use of critical realism as a meta-theoretical framework. Findings Data obtained from the review informed the integrated approach of the conceptual framework, thus combining the structure of the PEACE model and creating an optimal interpersonal context informed by the person-centred approach (PCA). Observational data were used to identify the relational qualities associated with the interpersonal styles (clusters of relational qualities) of FPs in the CFI context, thereby contributing to complex relational dynamics. Interview data were used both to describe effective and ineffective interpersonal styles and how they played out in the CFI with interviewees, yielding information that unfortunately proved not to be admissible in a legal context. The findings of the different phases indicated the need for an integrated conceptual approach, the Ponaletso CFI framework, which draws on the structure of the PEACE model and the PCA, as expressed in the relational qualities of interactional pattern analysis (IPA). The framework consists of the interview stage (before, during and after), the structure (phases) of the PEACE model, the type of questions (open- or closed-ended) according to the PCA, FPs’ interpersonal styles (clusters of relational qualities as explained by IPA) and the observable relational dynamics between FPs and interviewees. When FPs use the Ponaletso CFI framework, there is a greater likelihood of extracting admissible evidence because the interview is guided by a clear structure with a step-by-step questioning approach by FPs, while taking into consideration the relational dynamics to which they contribute. Originality/value The proposed conceptual framework considers relational dynamics and how FPs can navigate towards optimal relational dynamics in CFI contexts. FPs can apply the structure, ask appropriate questions at the relevant phases and observe the relational dynamics playing out in the interpersonal context of the CFI. To the best of the authors’ knowledge, this is the first attempt at creating an integrated interviewing framework for conducting CFIs aligned with the legal context in South Africa. Using the Ponaletso CFI framework may aid FPs in obtaining admissible evidence and facilitate an optimal interpersonal context during commercial forensic investigations while respecting interviewees’ constitutional rights.

CATOM : Causal Topology Map for Spatiotemporal Traffic Analysis with Granger Causality in Urban Areas.

The transportation network is an important element in an urban system that supports daily activities, enabling people to travel from one place to another. One of the key challenges is the network complexity, which is composed of many node pairs distributed over the area. This spatial characteristic results in the high dimensional network problem in understanding the 'cause' of problems such as traffic congestion. Recent studies have proposed visual analytics systems aimed at understanding these underlying causes. Despite these efforts, the analysis of such causes is limited to identified patterns. However, given the intricate distribution of roads and their mutual influence, new patterns continuously emerge across all roads within urban transportation. At this stage, a well-defined visual analytics system can be a good solution for transportation practitioners. In this paper, we propose a system, CATOM (Causal Topology Map), for the cause-effect analysis of traffic patterns based on Granger causality for extracting causal topology maps. CATOM discovers causal relationships between roads through the Granger causality test and quantifies these relationships through the causal density. During the design process, the system was developed to fully utilize spatial information with visualization techniques to overcome the previous problems in the literature. We also evaluate the usability of our approach by conducting a SUS(System Usability Scale) test and traffic cause analysis with the real-world data from two study sites in collaboration with domain experts.

Analysis of the Book Loan Patterns of College Students through Library Circulation Statistics

Analysis of the Book Loan Patterns of College Students through Library Circulation Statistics

Genome-wide analysis of the Amorphophallus konjac AkCSLA gene family and its functional characterization in drought tolerance of transgenic arabidopsis

BackgroundAmorphophallus konjac (A. konjac), a perennial tuberous plant, is widely cultivated for its high konjac glucomannan (KGM) content, a heteropolysaccharide with diverse applications. The cellulose synthase-like (CSL) gene family is known to be a group of processive glycan synthases involved in the synthesis of cell-wall polysaccharides and plays an important role in the biological process of KGM. However, in A. konjac the classification, structure, and function of the AkCSLA superfamily have been studied very little.ResultsBioinformatics methods were used to identify the 11 AkCSLA genes from the whole genome of Amorphophallus konjac and to systematically analyze their characteristics, phylogenetic evolution, promoter cis-elements, expression patterns, and subcellular locations. Phylogenetic analysis revealed that the AkCSLA gene family can be divided into three subfamilies (Groups I- III), which have close relationships with Arabidopsis. The promoters of most AkCSLA family members contain MBS elements and ABA response elements. Analysis of expression patterns in different tissues showed that most AkCSLAs are highly expressed in the corms. Notably, PEG6000 induced down-regulation of the expression of most AkCSLAs, including AkCSLA11. Subcellular localization results showed that AkCSLA11 was localized to the plasma membrane, Golgi apparatus and endoplasmic reticulum. Transgenic Arabidopsis experiments demonstrated that overexpression of AkCSLA11 reduced the plant’s drought tolerance. This overexpression also inhibited the expression of drought response genes and altered the sugar components of the cell wall. These findings provide new insights into the response mechanisms of A. konjac to drought stress and may offer potential genetic resources for improving crop drought resistance.ConclusionIn conclusion, the study reveals that the AkCSLA11 gene from A. konjac negatively impacts drought tolerance when overexpressed in Arabidopsis. This discovery provides valuable insights into the mechanisms of plant response to drought stress and may guide future research on crop improvement for enhanced resilience.

한국어 중급 교재의 대화문에 나타난 대인적 기능의 실현 양상 분석

Objectives This study aimed to analyze the realization patterns of interpersonal functions in dialogues of inter-mediate Korean language textbooks from the perspective of Systemic Functional Linguistics. Methods This study analyzed the interpersonal functions and their realization patterns in dialogues from Korean intermediate integrated textbooks published in the late 2000s. By establishing two main analytical categories—mood system and mood metaphor—and conducting distribution and realization pattern analyses for each cat-egory, we explored the linguistic characteristics of textbook dialogues from the perspective of Systemic Functional Linguistics. Results In the textbook dialogues, declarative sentences were most frequent, followed by interrogative, imper-ative, and suggestive sentences. For honorific forms, the combination of ‘하십시오체+해요체’ was most common, followed by ‘해라체+해체’, with the ‘하게체’ being least frequent. For mood metaphors, interrogative forms func-tioning as statements or commands were most frequently observed. Conclusions The study confirmed that the analyzed Korean textbook dialogues accurately reflect the language us-age patterns of native Korean speakers, and demonstrated the effectiveness of the Systemic Functional Linguistics approach in textbook analysis.

Transcriptome and WGCNA Analyses Reveal Key Genes Regulating Anthocyanin Biosynthesis in Purple Sprout of Pak Choi (Brassica rapa L. ssp. chinensis)

Chinese cabbage is rich in vitamins, fibre, and nutrients and is one of the primary vegetables consumed in autumn and winter in South Asia. ‘Purple pak choi’ sprouts are particularly rich in anthocyanins and are favoured by consumers. However, reports on the regulation of anthocyanin synthesis in purple pak choi sprouts do not exist. In this study, we examined the phenotypic development of purple pak choi sprouts after germination. The total anthocyanin content increased from 0.02 to 0.52 mg/g FW from days 0 to 6. RNA-seq data analysis revealed an increase in differentially expressed genes corresponding to the development of purple pak choi sprouts. Expression pattern analysis of genes associated with the anthocyanin biosynthesis pathway revealed a significant upregulation of structural genes during the purple phase, suggesting that the transcription factors PAP2 and MYBL2 may play crucial regulatory roles. BraPAP2.A03, BraTT8.A09, and BraMYBL2.A07 exhibited strong interactions with key genes in the anthocyanin biosynthesis pathway, specifically BraDFR.A09. Furthermore, the expression of BraPAP2.A03 aligned with the expression patterns of most anthocyanin biosynthesis-related genes, whereas those of BraTT8.A09 and BraMYBL2.A07 corresponded with the expression pattern of BraDFR.A09. These results provide valuable insights into regulatory mechanisms underlying anthocyanin synthesis in purple pak choi sprouts.

Genetic profile of carbapenem-resistant <i>Acinetobacter baumannii</i> strains

The purpose of the research: the molecular genetic characteristic ofA. baumanniicarbapenem-resistant strains, including clonal affiliation, resistome and virulome pattern analysis, description of genetic environment resistance determinants, comparative genetic analysis, and assessment of phylogenetic relationships are presented in the work. The studiedA. baumanniistrains belonged to sequence types ST2Pas/ST2062.2063Oxf(n = 5) and ST78Pas/ST1757Oxf(n = 2). The nucleotide sequences of the studiedA. baumanniiST2Pas/ST2062.2063Oxfstrains were grouped into a single cluster according to phylogenetic analysis. And the sequences of theA. baumanniiST78Pas/ST1757Oxfstrains were combined with the nucleotide sequence of theA. baumanniiAbCTX5 strain, isolated in France in 2015. The presence of intrinsic (OXA-51-like) and acquired carbapenemases genes was shown inA. baumanniistrains. In particular,blaOXA-23are identified in members of ST2Pas/ST2062.2063Oxf, and inA. baumanniiST78Pas/ST1757Oxfstrains —blaOXA-72as part of the plasmid DNA. TheA. baumanniiST78Passtrains possessed additional extended-spectrum beta-lactamase genes. Тhe CTX-M-115 cephalosporinase gene are present in both strains, and theA. baumanniistrain NNAb_2023.3 has theblaCARB-16gene. MostA. baumanniistrains are characterized by the presence of acquired genes for enzymatic modification of macrolides(mph(E), msr(E)), chloramphenicols(catB8), aminoglycosides(aadA, aph(3'')-Ib, aph(6)-Id, aac(6')-Ib, aph(3')-Ia, armA). A comparative analysis showed that inA. baumanniiST2Pas/ST2062.2063Oxfstrains the resistance determinants to macrolides and aminoglycosides are located in the Tn6279-like transposon, and the aminoglycosidases genesaph(3'')-Ib, aph(6)-Idare associated with theIS91-like mobile element. InA. baumanniiST78Pas/ST1757Oxfstrains, resistance genes to aminoglycosides, macrolides, sulfonamides, and beta-lactamase genes are grouped in a region from 60 to 80 Kb long between theglmSandhutCgenes. The presence of mutations in thegyrAandparCgenes associated with resistance to fluoroquinolones were characterized in allA. baumanniistrains. Thus, new knowledge about the genetic profile of carbapenem-resistantA. baumanniistrains representing epidemically significant international clonal lineage has been obtained.

Comparative analysis of antibiotic sensitivity pattern in Streptococcus mutans isolated from dental caries of different age & sex group in Dhaka city, Bangladesh

Comparative analysis of antibiotic sensitivity pattern in Streptococcus mutans isolated from dental caries of different age & sex group in Dhaka city, Bangladesh

Genome-Wide Identification, Characterization and Expression Patterns of the DBB Transcription Factor Family Genes in Wheat

Double B-box (DBB) proteins are plant-specific transcription factors (TFs) that play crucial roles in plant growth and stress responses. This study investigated the classification, structure, conserved motifs, chromosomal locations, cis-elements, duplication events, expression levels, and protein interaction network of the DBB TF family genes in common wheat (Triticum aestivum L.). In all, twenty-seven wheat DBB genes (TaDBBs) with two conserved B-box domains were identified and classified into six subgroups based on sequence features. A collinearity analysis of the DBB family genes among wheat, Arabidopsis, and rice revealed some duplicated gene pairs and highly conserved genes in wheat. An expression pattern analysis indicated that wheat TaDBBs were involved in plant growth, responses to drought stress, light/dark, and abscisic acid treatment. A large number of cis-acting regulatory elements related to light response are enriched in the predicted promoter regions of 27 TaDBBs. Furthermore, some of TaDBBs can interact with COP1 or HY5 based on the STRING database prediction and yeast two-hybrid (Y2H) assay, indicating the potential key roles of TaDBBs in the light signaling pathway. Conclusively, our study revealed the potential functions and regulatory mechanisms of TaDBBs in plant growth and development under drought stress, light, and abscisic acid.

Spatial Pattern Analysis of Rural Development Success Rates Based on the New Rural Development Paradigm (NRDP) Indicators: A Case Study of Cimenyan District

Spatial Pattern Analysis of Rural Development Success Rates Based on the New Rural Development Paradigm (NRDP) Indicators: A Case Study of Cimenyan District