Prominent Pattern Research Articles

Improving DNA-Binding Protein Prediction Using Three-Part Sequence-Order Feature Extraction and a Deep Neural Network Algorithm.

Identification of the DNA-binding protein (DBP) helps dig out information embedded in the DNA-protein interaction, which is significant to understanding the mechanisms of DNA replication, transcription, and repair. Although existing computational methods for predicting the DBPs based on protein sequences have obtained great success, there is still room for improvement since the sequence-order information is not fully mined in these methods. In this study, a new three-part sequence-order feature extraction (called TPSO) strategy is developed to extract more discriminative information from protein sequences for predicting the DBPs. For each query protein, TPSO first divides its primary sequence features into N- and C-terminal fragments and then extracts the numerical pseudo features of three parts including the full sequence and these two fragments, respectively. Based on TPSO, a novel deep learning-based method, called TPSO-DBP, is proposed, which employs the sequence-based single-view features, the bidirectional long short-term memory (BiLSTM) and fully connected (FC) neural networks to learn the DBP prediction model. Empirical outcomes reveal that TPSO-DBP can achieve an accuracy of 87.01%, covering 85.30% of all DBPs, while achieving a Matthew's correlation coefficient value (0.741) that is significantly higher than most existing state-of-the-art DBP prediction methods. Detailed data analyses have indicated that the advantages of TPSO-DBP lie in the utilization of TPSO, which helps extract more concealed prominent patterns, and the deep neural network framework composed of BiLSTM and FC that learns the nonlinear relationships between input features and DBPs. The standalone package and web server of TPSO-DBP are freely available at https://jun-csbio.github.io/TPSO-DBP/.

Machine understanding and deep learning representation

Practical ability manifested through robust and reliable task performance, as well as information relevance and well-structured representation, are key factors indicative of understanding in the philosophical literature. We explore these factors in the context of deep learning, identifying prominent patterns in how the results of these algorithms represent information. While the estimation applications of modern neural networks do not qualify as the mental activity of persons, we argue that coupling analyses from philosophical accounts with the empirical and theoretical basis for identifying these factors in deep learning representations provides a framework for discussing and critically evaluating potential machine understanding given the continually improving task performance enabled by such algorithms.

الصنعة البديعية عند أحمد شوقي: دراسة تحليلية بلاغية لقصيدة "غاندي بطل الهند"

The embellishment elements are the most important in achieving internal rhyme in Arabic poems because the value of poetry is based on the impact it has on the minds of readers and listeners through its musical structure. As a result, this study focuses on Ahmed Shawqi's poem "Gandhi Hero of India," with the objective of revealing the rhythmic and semantic functions of each of the rhetorical styles jinās, ṭibāq, tawāzī al tarkībī, and Taqsīm. This study adopted the analytical method, which analyzes the poetic verses according to the science of Badīʿ. The importance of the study is reflected in the fact that it sheds light on the extent to which the poet invests these literary devices in displaying images and emotions consistent with the nature of the text. The study concluded that the poet used al jinās al nāqiṣ in its most prominent patterns, the ṭibāq in its linguistic and contextual forms, and he also distributed the two words of these two literary styles between the two halves of the poetic verse, which strengthens the poem rhythmically and semantically. It also concluded that the complete and partial grammatical parallelism on the vertical and horizontal levels provided the poem with a distinct rhythm and semantic richness, in addition to the phenomenon of al Taqsīm al ʿaḍūḍī which played a role in moving the internal rhyme that drew readers' attention to the text's content.

Stereo-EEG recordings extend known distributions of canonical movement-related oscillations

Objective. Previous electrophysiological research has characterized canonical oscillatory patterns associated with movement mostly from recordings of primary sensorimotor cortex. Less work has attempted to decode movement based on electrophysiological recordings from a broader array of brain areas such as those sampled by stereoelectroencephalography (sEEG), especially in humans. We aimed to identify and characterize different movement-related oscillations across a relatively broad sampling of brain areas in humans and if they extended beyond brain areas previously associated with movement. Approach. We used a linear support vector machine to decode time-frequency spectrograms time-locked to movement, and we validated our results with cluster permutation testing and common spatial pattern decoding. Main results. We were able to accurately classify sEEG spectrograms during a keypress movement task versus the inter-trial interval. Specifically, we found these previously-described patterns: beta (13–30 Hz) desynchronization, beta synchronization (rebound), pre-movement alpha (8–15 Hz) modulation, a post-movement broadband gamma (60–90 Hz) increase and an event-related potential. These oscillatory patterns were newly observed in a wide range of brain areas accessible with sEEG that are not accessible with other electrophysiology recording methods. For example, the presence of beta desynchronization in the frontal lobe was more widespread than previously described, extending outside primary and secondary motor cortices. Significance. Our classification revealed prominent time-frequency patterns which were also observed in previous studies that used non-invasive electroencephalography and electrocorticography, but here we identified these patterns in brain regions that had not yet been associated with movement. This provides new evidence for the anatomical extent of the system of putative motor networks that exhibit each of these oscillatory patterns.

On the exine ultrastructure of fossil ginkgoaleans: In situ pollen of Sorosaccus Harris

The morphology and exine ultrastructure have been studied of pollen grains from pollen cones of Sorosaccus sibiricus Prynada from the Ust’-Baley (Aalenian, Siberia), Sorosaccus sp. from the Vladimirovka (Aalenian-Bajocian, Siberia), and S. ex gr. sibiricus Prynada from the Tyrma (Tithonian–Berriasian, Russian Far East) localities. The pollen grains are boat-shaped and monosulcate. A finely granulate pattern is discernible under high magnification of light microscope in pollen grains from Vladimirovka and Tyrma; SEM shows that this pattern is formed by flat verrucae. TEM shows that sculptural elements are present on the surface of pollen grains from Ust’-Baley, although it is not evident in LM and SEM. By previous data on modern and fossil members, we believed that ginkgoalean pollen grains can be differentiated from similar boat-shaped monosulcate pollen of other affinities by a ratio of ectexinal sublayers (a thick homogeneous tectum, a thin infratectum of one row of structural elements, and a thin foot layer) in combination with an ectexine that is greatly reduced in the aperture region. Freshly obtained data have revealed another set of characters, with a less prominent tectum by comparison to underlying sublayers, an infratectum with small granules within the alveoli, and a prominent verrucate surface pattern that is distinguishable even in transmitted light. Ginkgoaleans are characterized by more than one set of ultrastructural characters of the exine.

Sequence similarity between SARS-CoV-2 nucleocapsid and multiple sclerosis-associated proteins provides insight into viral neuropathogenesis following infection

The novel coronavirus SARS-CoV-2 continues to cause death and disease throughout the world, underscoring the necessity of understanding the virus and host immune response. From the start of the pandemic, a prominent pattern of central nervous system (CNS) pathologies, including demyelination, has emerged, suggesting an underlying mechanism of viral mimicry to CNS proteins. We hypothesized that immunodominant epitopes of SARS-CoV-2 share homology with proteins associated with multiple sclerosis (MS). Using PEPMatch, a newly developed bioinformatics package which predicts peptide similarity within specific amino acid mismatching parameters consistent with published MHC binding capacity, we discovered that nucleocapsid protein shares significant overlap with 22 MS-associated proteins, including myelin proteolipid protein (PLP). Further computational evaluation demonstrated that this overlap may have critical implications for T cell responses in MS patients and is likely unique to SARS-CoV-2 among the major human coronaviruses. Our findings substantiate the hypothesis of viral molecular mimicry in the pathogenesis of MS and warrant further experimental exploration.

Machine learning on academic education: Bibliometric studies

The use of Machine Learning exhibits significant promise in facilitating advancements in the field of education. It is vital to conduct a comprehensive review of existing research to ascertain the significance of utilizing Machine Learning as a viable approach to enhance educational advancements. This bibliometric analysis provides a comprehensive overview of the advancements in the application of machine learning techniques within the field of education. This study utilizes publication and citation data from many academic literature sources to elucidate prominent patterns, areas of research emphasis, and scholarly collaborations within this field. The findings of the bibliometric analysis reveal a significant increase in scholarly attention toward the application of machine learning in the field of education during the past several years. The scope of these investigations encompasses a diverse array of subjects, such as personalized learning, predictive analytics, automated evaluation, learning recommendations, and online exam proctoring. The findings of this study also demonstrate a notable rise in the level of collaboration among scholars from many fields, highlighting the significance of interdisciplinary approaches in tackling the intricate challenges associated with the integration of machine learning in education.

Push-pull factors and means-end chain framework of cyberloafing: a soft laddering study using LadderUX

PurposePrevious studies on cyberloafing have so far not focused on the interlinkages among push factors, pull factors, consequences of actions and value orientations of the employees in a comprehensive manner. The purpose of this study is to close that gap by integrating push-pull theory with means-end chain framework.Design/methodology/approachUsing a soft-laddering technique, semi-structured interviews were conducted with 21 Indian employees from various organizations with prior written consent. After performing the content analysis and preparation of ladders, an implication matrix and a hierarchical value map were constructed using the LadderUX tool.Findings“Upholding conversational conformity,” “achieving efficiency through noise cancellation,” “addressing occasional requirements,” “social networking as a coping mechanism,” “staying informed and sharing opinions,” “attempting job or profile alteration” and “fulfilling transactional obligations” turned out to be the seven prominent means-end chain patterns, with their respective push-pull factors, consequences and value orientations. This study also suggested the multifaceted character of cyberloafing in a continuum, from “serious-destructive” to “minor-positive” to “facilitative-productive.”Research limitations/implicationsThis study has been conducted by focusing on cyberloafing at physical workplaces and not in the context of distributed work environments.Practical implicationsThe findings of this study will enable organizations to frame an appropriate set of guidelines to control this behavior.Originality/valueTo the best of the authors’ knowledge, this study is the first to integrate the push-pull theory and means-end chain framework to explore the nuances of cyberloafing among employees.

Blending as a Word-Formation Process

Although there are several ways of creating new words, the article investigates the morphological process that is referred to as lexical blending. Even if this minor word-formation process is increasingly popular, it is still not clearly defined and limited. This process is present in many languages, and is clear proof of how inventive a language can be. The first part of the article presents an examination of defining characteristics of blending and blend words according to different authors. The second part of the article is of a practical nature. Some of the key characteristics of blends discussed in the first part are tested on the basis of a corpus, which was compiled specifically for this purpose and contains 458 English and 396 French blends. Blends from each language are analysed separately in order to reveal any major discrepancies between English and French. The focal points of the analysis are the lexical categories of blends and of the source words entering each blend, the presence or absence of shortening of source words, the type of shortening of source words, the structural patterns of blends, the presence or absence of overlap between the source words, the type of overlap and the frequency of infixation. These parameters are corroborated by the statistical analysis of the corpus in order to reveal any prominent structural patterns in both languages. Additionally, some of these points of analysis are compared to the findings presented by Vincent Renner in “French and English lexical blends in contrast” (2018). His study includes 97 French and 374 English blends from two corresponding dictionaries in both languages, namely the Grand Robert de la langue française and the Shorter Oxford English Dictionary.

CHANGING FAMILY DESTINIES, DIVERGENT FAMILY CAREGIVING PATTERNS: DO BIRTH COHORTS, GENDER, RACE, AND SES MATTER?

Abstract Over the past few decades, Americans have experienced a series of demographic transitions include prolonged longevity and rise in the complexities of family structures. The Baby Boomer cohort is at the forefront of these transitions, which has profound implications on their later-life family relations and practices of family caregiving. Most caregiving literature has focused on static care experiences over a short time, while neglecting long-term care experiences. Using 10 waves of longitudinal data from HRS (2000-2018) and latent profile analysis, I identified five prominent long-term caregiving patterns: light parental caregivers (44.1%), intensive spousal caregivers (5.6%), sandwiched caregivers (5.5%), light grandchildren caregivers (38.7%), and heavy grandchildren caregivers (6.2%). Further, I conduct multinominal logistic regression to investigate how birth cohorts, gender, race, and education shaped these patterns. Results suggested that later cohorts have seen a decline in intensive spousal caregivers, light and heavy grandchildren caregivers, but an increase in light parental caregivers. Women are more likely to be sandwiched caregivers than men, and black caregivers are more likely to be intensive spousal caregivers, heavy grandchildren caregivers, and sandwiched caregivers than white. By contrast, white and more educated caregivers are more likely to be light parental caregivers, and this pattern becomes more pronounced in later cohorts. The findings suggest divergent destinies of family caregiving patterns among later cohorts. More disadvantaged groups are shouldering heavier care responsibilities than advantaged groups. Targeted care services should be implemented to ease the care burdens of the vulnerable population.

How ESG Contribute to the High-Quality Development of State-Owned Enterprise in China: A Multi-Stage fsQCA Method

The purpose of this study is to explore what configurations of dimensions corresponding to environmental, social responsibility, governance (ESG) and firm contextual factors can lead to the high-quality development of state-owned enterprises (SOEs). A configuration analysis framework with six conditions including environmental, social responsibility, and governance (ESG), innovation intensity, capital structure, and firm size was constructed. Moreover, the multi-stage qualitative comparative analysis (QCA) approach was conducted on a sample of 692 annual observations of SOEs from 2017 to 2019. Findings suggested that three equifinal patterns can produce the high-quality development of SOEs, which are resource and capability prominent pattern, sustainability driven pattern, responsibility and growth balanced pattern, respectively. Each pattern is a conjunctural combination of different ESG and firm conditions. The number of resource and capability prominent pattern decreased in the third year, while the proportion of sustainability driven pattern increased, in which the environmental dimension played a core role rather than the social dimension. Different ESG dimensions and firm conditions have both complementary and substitutive relationships, but firm size is a common condition in all configurations. This study provided a holistic empirical explanation of how ESG leads to sustainability issues in SOEs.

Approximate zero-crossing: a new interpretable, highly discriminative and low-complexity feature for EEG and iEEG seizure detection

Objective. Long-term monitoring of people with epilepsy based on electroencephalography (EEG) and intracranial EEG (iEEG) has the potential to deliver key clinical information for personalised epilepsy treatment. More specifically, in outpatient settings, the available solutions are not satisfactory either due to poor classification performance or high complexity to be executed in resource-constrained devices (e.g. wearable systems). Therefore, we hypothesize that obtaining high discriminative features is the main avenue to improve low-complexity seizure-detection algorithms. Approach. Inspired by how neurologists recognize ictal EEG data, and to tackle this problem by targeting resource-constrained wearable devices, we introduce a new interpretable and highly discriminative feature for EEG and iEEG, namely approximate zero-crossing (AZC). We obtain AZC by applying a polygonal approximation to mimic how our brain selects prominent patterns among noisy data and then using a zero-crossing count as a measure of the dominating frequency. By employing Kullback–Leiber divergence, leveraging CHB-MIT and SWEC-ETHZ iEEG datasets, we compare the AZC discriminative power against a set of 56 classical literature features (CLF). Moreover, we assess the performances of a low-complexity seizure detection method using only AZC features versus employing the CLF set. Main results. Three AZC features obtained with different approximation thresholds are among the five with the highest median discriminative power. Moreover, seizure classification based on only AZC features outperforms an equivalent CLF-based method. The former detects 102 and 194 seizures, against 99 and 161 for the latter (CHB-MIT and SWEC-ETHZ, respectively). Moreover, the AZC-based method keeps a similar false-alarm rate (i.e. an average of 2.1 and 1.0, against 2.0 and 0.5, per day). Significance. We propose a new feature and demonstrate its capability in seizure classification for both scalp and intracranial EEG. We envision the use of such a feature to improve outpatient monitoring with resource-constrained devices.

Exploring the dynamic transitions of polysubstance use patterns among Canadian youth using Latent Markov Models on COMPASS data

Understanding what factors lead to youth polysubstance use (PSU) patterns and how the transitions between use patterns can inform the design and implementation of PSU prevention programs. We explore the dynamics of PSU patterns from a large cohort of Canadian secondary school students using machine learning techniques. We employed a multivariate latent Markov model (LMM) on COMPASS data, with a linked sample (N=8824) of three-annual waves, Wave I (WI, 2016-17, as baseline), Wave II (WII, 2017-18), and Wave III (WIII, 2018-19). Substance use indicators, i.e., cigarette, e-cigarette, alcohol and marijuana, were self-reported and were categorized into never/occasional/current use. Four distinct use patterns were identified: no-use (S1), single-use of alcohol (S2), dual-use of e-cigarettes and alcohol (S3), and multi-use (S4). S1 had the highest prevalence (60.5%) at WI, however, S3 became the prominent use pattern (32.5%) by WIII. Most students remained in the same subgroup over time, particularly S4 had the highest transition probability (0.87) across the three-wave. With time, those who transitioned typically moved towards a higher use pattern, with the most and least likely transition occurring S2→S3 (0.45) and S3→S2 (<0.01), respectively. Among all covariates being examined, truancy, being measured by the # of classes skipped, significantly affected transition probabilities from any low→high (e.g., ORS2→S4=2.41, 95% CI [2.11, 2.72], p < 0.00001) and high→low (e.g., ORS3→S1=0.38, 95% CI [0.33, 0.44], p < 0.00001) use directions over time. Older students, blacks (vs. whites), and breakfast eaters were less likely to transition from low→high use direction. Students with more weekly allowance, with more friends that smoked, longer sedentary time, and attended attended school unsupportive to resist or quit drug/alcohol were more likely to transition from low→high use direction. Except for truancy, all other covariates had inconsistent effects on the transition probabilities from the high→low use direction. This is the first study to ascertain the dynamics of use patterns and factors in youth PSU utilizing LMM with population-based longitudinal health surveys, providing evidence in developing programs to prevent youth PSU. The Applied Health Sciences scholarship; the Microsoft AI for Good grant; the Canadian Institutes of Health Research, Health Canada, the Canadian Centre on Substance Abuse, the SickKids Foundation, the Ministère de la Santé et des Services sociaux of the province of Québec.

Morpho-anatomical and palynological properties of endemic Astragalus tmoleus var. bounacanthus (Fabaceae)

Astragalus tmoleus Boiss. var. bounacanthus (Boiss.) Chamberlain is a member of the Pterophorus Bunge section of the Fabaceae family and consists of the spiny cushion-forming shrub. In this study, morphological, anatomical and pollen properties of the plant, an endemic species for Turkey, have been investigated in detail. Morphological characters such as the shape of paripinnate leaves, stipules and bracts, the flower number in the inflorescence, the stenonychioid type of standard and the reniform type of seed can be helpful to distinguish A. tmoleus var. bounacanthus. The stem, leaf and rachis characteristics of the plant were examined in anatomical studies. There is a secondary growth in stem anatomy. The number of vascular bundles is 15-18 in a circle. The shape of the transversal section of the rachis is polygonal or almost orbicular. The sclerenchyma tissue is located on the vascular bundles in the rachis. A. tmoleus var. bounacanthus has equifasial leaves. The stomata type is anomocytic and occurs on both leaflet epidermises. The pollen grains of A. tmoleus var. bounacanthus have tricolpate aperture and they are subprolate-shaped. While the pollen exine sculpturing is microreticulate, the seed surface sculpturing is a prominent undulate-ridged pattern formed by irregular cells. Scanning electron microscopy (SEM) is used to determine pollen and seed morphology.

Appraisal of gravity-based lineaments around Central Indian Ridge (CIR) in different geological periods: Evidence of frequent ridge jumps in the southern block of CIR

• Application of edge Enhancement to mark the lineaments over the CNIR. • Power spectrum analysis to differentiate long and short lineaments. • Comparison of spreading rate with length of lineaments. • Analysis of lineament orientation and plate movement in different geologic era. • Southern CNIR witnessed frequent ridge jumps for stability of the RTJ . This paper presents an approach for utilizing the balanced edge detection technique in satellite-derived gravity data to study the tectonic movement in past geological periods. The research is initiated by examining the normalized total horizontal derivative (NTHD) edge detection technique based on a moving window. NTHD is found to be effective for both shallow and deep-seated bodies. The noise in the gravity map could be effectively eliminated using a larger window size. The lineaments are marked over the Central Indian Ridge (CIR) using NTHD. Analysis of various geological periods and the lineaments shows that the speed and direction of the tectonic Plate play an essential role in deciding the length and orientation of lineaments formed. The most prominent lineament pattern observed over the CIR is in the NE-SW, ENE-WSW, and NNE-SSW, possibly associated with plate movement during Late Cretaceous to Late Eocene and after the Early Miocene period. In addition, a few lineaments are also found to be oriented in NW-SE, E-W, and N-S. The N-S lineaments might be the consequence of the movement of the Indian Plate in a northward direction for a short time during the Late Eocene and Early Miocene. The E-W lineaments result from the transfer of the Reunion hotspot from the Indian to the African Plate. The high lineament density and circular statistical values indicate left flank of the CIR undergoes rigorous tectonic activity. The high value of circular statistics indicates the chaotic arrangement of lineaments in the southern block of the CIR.

A long-term view on recent changes in abundance of common skate complex in the North Sea

Following decades of declines, populations of large fish recently started to increase in the North Sea, presumably due to reduced fishing pressure. However, population recovery may be too readily claimed, since standardised sampling of fish stocks commenced only in the 1970s, well after many species had already collapsed. A true recovery must be seen from a long-term perspective. The critically endangered common skate (Dipturus batis, Rajidae) species complex is an example of a large-bodied fish that mostly disappeared before standardised monitoring took place. Here, we put the recent increase in population size into a 120-year perspective, throughout three geographical divisions in the North Sea. We analysed a large range of mostly undisclosed historical data and contemporary sources. A reconstruction of Dutch commercial landings data confirms that the species used to be very abundant between 1901 and 1920, and shows how it steadily declined from 1920 onwards until it got extirpated around 1970. Based on a quantitative analysis of standardised catch numbers from fishery-independent surveys time, we conclude that the current abundance of the species is still below historical baselines and represents a local recovery at most. We further demonstrate a prominent and consistent pattern in size distribution, with larger (mature) individuals only occurring in the northern North Sea. A large dataset on historical stomach contents from the central North Sea confirmed the diet of young common skate, which consisted predominantly of shrimps. Our review exemplifies the importance of marine historical ecology to deduce the natural richness of the North Sea.

Special issue introduction: Contemporary international anti-feminism

AbstractIn recent years, conservative governments and their civil society allies have undermined international women’s rights treaties and SOGI rights initiatives and challenged domestic rights protections. The articles in this special issue grapple with these trends by analysing the ideologies, discourses, and strategies of contemporary anti-feminism in global and comparative contexts. Several prominent patterns emerge: the core significance of social hierarchy and biological essentialism to anti-feminist conservative thought; the polarizing demonization of feminists by religious conservatives and populist nationalists; the appropriation of rights discourses and advocacy tactics by anti-feminist campaigns; and the strategic importance of law and legal language as a terrain of rights contestation. Taken together, this research suggests that anti-feminism is not incidental to reactionary anti-democratic politics, but instead a constitutive element of political movements that seek to naturalize inequality and legally enforce conformity with conservative social norms.

Assessing LAPAN-A3 Satellite with Line Imager Space Application (LISA) Sensor for Oil Spill Detection

LAPAN-A3 (LA3) data has been utilized for earth observation in monitoring natural resources. While most applications are toward land resources monitoring, recent utilization indicates the possibility of LA3 detecting oil spill events on the sea surface. This research provides information regarding the ability of sensors characteristics of LA3 to detect oil slicks and its initial results by examining multispectral bands combination using Optimum Index Factor (OIF), and Digital Number (DN) extraction is carried out on each LA3 band in water-oil-water since LA3 is not able to change DN to reflectance value. In this study, besides using LA3 data, Sentinel-2 data was also used as comparative data and results in validation. Based on the results of the OIF calculation, the combination of the Blue-Green-NIR (BGN) band has the highest value compared to other combinations. This indicates that the BGN band combination is appropriate for visualizing oil and distinguishing between oil and water. The pattern formed from the visualization results with the combination of the BGN band is silvery in crude oil and greenish in ship waste disposal. The result is also strengthened by DN extraction from slick oil samples that shows a prominent pattern on the Blue and Green bands. Finally, this study can conclude that LA3 has great potential to detect oil spills visually but still requires further research for reflectance analysis by converting the DN value into reflectance.

Role of religious programs in Islamic satellite channels directed at instilling religious values among expatriates

The research includes the topic of religious programs in specialized religious channels through the following main question: What is the role of directed English-speaking religious channels in spreading religious values among the members of the community Islam in Europe and Britain? This research is descriptive in terms of type, as it describes the phenomenon under study to identify its characteristics, characteristics and influencing factors to reach the results. Research-based on research questions and objectives for data collection. The objectives of the research were summarized by identifying the most prominent patterns and habits of the Islamic community's follow-up to religious satellite channels and the disclosure of the roles and functions performed by religious channels in instilling religious values among the public, in addition to investigating the contents that the members of the Islamic community are keen to follow in those channels, and reaching the most important The religious values that satellite channels seek to spread or inculcate among the members of the community, and identify the most major repercussions of the public's continuous follow-up to religious satellite channels.

Clinical significance of asymmetric venous vasculature on minimum-intensity projection in patients with moyamoya disease.

This study analyzed the clinical significance and characteristics of asymmetric venous blood flow in patients with Moyamoya disease (MMD) using minimum intensity projection (minIP) susceptibility-weighted imaging. The minIP views of 30 patients diagnosed with MMD were retrospectively analyzed using clinical features, brain magnetic resonance angiography, electroencephalography, and brain single-photon emission computed tomography (SPECT). Simultaneously, differences between patients with acute cerebral infarction and non-MMD causes were analyzed. Twelve (40.0%) of the 30 patients had asymmetrical venous flow, which is usually seen in patients with acute cerebral infarction (P = .146). They also had significantly higher Suzuki stages than symmetric patients (P = .014), with five (41.7%) and three (25.0%) of them in stages 4 and 5, respectively. When the Suzuki stages of both hemispheres were different, more veins were found in the stenotic hemisphere (88.9%). Brain SPECT showed more severe hypoperfusion on the side with prominent vascularity in the minIP view (100.0%). Additionally, asymmetric blood flow was observed in 66.7% of the patients with cerebral infarction caused by MMD, whereas only 11.1% of the children with cerebral infarction caused by non-MMD had asymmetry (P = .005). Patients with MMD showed asymmetric hypointensity of the cortical veins with a minIP appearance. The venous structure showed greater signal loss on SWI and was more prominent in the hemisphere where stenosis was advanced or infarction occurred in other examinations. Cerebral infarction in patients with MMD tended to occur with asymmetrically prominent venous patterns with damaged areas in minIP images, which had distinct characteristics from those of patients without MMD.