"Stripe" transcription factors provide accessibility to co-binding partners in mammalian genomes.

Regulatory elements activate promoters by recruiting transcription factors (TFs) to specific motifs. Notably, TF-DNA interactions often depend on cooperativity with colocalized partners, suggesting an underlying cis-regulatory syntax. To explore TF cooperativity in mammals, we analyze ∼500 mouse and human primary cells by combining an atlas of TF motifs, footprints, ChIP-seq, transcriptomes, and accessibility. We uncover two TF groups that colocalize with most expressed factors, forming stripes in hierarchical clustering maps. The first group includes lineage-determining factors that occupy DNA elements broadly, consistent with their key role in tissue-specific transcription. The second one, dubbed universal stripe factors (USFs), comprises ∼30 SP, KLF, EGR, and ZBTB family members that recognize overlapping GC-rich sequences in all tissues analyzed. Knockouts and single-molecule tracking reveal that USFs impart accessibility to colocalized partners and increase their residence time. Mammalian cells have thus evolved a TF superfamily with overlapping DNA binding that facilitate chromatin accessibility.

Diverging neural dynamics for syntactic structure building in naturalistic speaking and listening.

The neural correlates of sentence production are typically studied using task paradigms that differ considerably from the experience of speaking outside of an experimental setting. In this fMRI study, we aimed to gain a better understanding of syntactic processing in spontaneous production versus naturalistic comprehension in three regions of interest (BA44, BA45, and left posterior middle temporal gyrus). A group of participants (n = 16) was asked to speak about the events of an episode of a TV series in the scanner. Another group of participants (n = 36) listened to the spoken recall of a participant from the first group. To model syntactic processing, we extracted word-by-word metrics of phrase-structure building with a top-down and a bottom-up parser that make different hypotheses about the timing of structure building. While the top-down parser anticipates syntactic structure, sometimes before it is obvious to the listener, the bottom-up parser builds syntactic structure in an integratory way after all of the evidence has been presented. In comprehension, neural activity was found to be better modeled by the bottom-up parser, while in production, it was better modeled by the top-down parser. We additionally modeled structure building in production with two strategies that were developed here to make different predictions about the incrementality of structure building during speaking. We found evidence for highly incremental and anticipatory structure building in production, which was confirmed by a converging analysis of the pausing patterns in speech. Overall, this study shows the feasibility of studying the neural dynamics of spontaneous language production.

The gender agency gap in fiction writing (1850 to 2010).

Works of fiction play a crucial role in the production of cultural stereotypes. Concerning gender, a widely held presumption is that many such works ascribe agency to men and passivity to women. However, large-scale diachronic analyses of this notion have been lacking. This paper provides an assessment of agency attributions in 87,531 fiction works written between 1850 and 2010. It introduces a syntax-based approach for extracting networks of character interactions. Agency is then formalized as a dyadic property: Does a character primarily serve as an agent acting upon the other character or as recipient acted upon by the other character? Findings indicate that female characters are more likely to be passive in cross-gender relationships than their male counterparts. This difference, the gender agency gap, has declined since the 19th century but persists into the 21st. Male authors are especially likely to attribute less agency to female characters. Moreover, certain kinds of actions, especially physical and villainous ones, have more pronounced gender disparities.

Cooperative recruitment of Yan via a high-affinity ETS supersite organizes repression to confer specificity and robustness to cardiac cell fate specification.

Cis-regulatory modules (CRMs) are defined by unique combinations of transcription factor-binding sites. Emerging evidence suggests that the number, affinity, and organization of sites play important roles in regulating enhancer output and, ultimately, gene expression. Here, we investigate how the cis-regulatory logic of a tissue-specific CRM responsible for even-skipped (eve) induction during cardiogenesis organizes the competing inputs of two E-twenty-six (ETS) members: the activator Pointed (Pnt) and the repressor Yan. Using a combination of reporter gene assays and CRISPR-Cas9 gene editing, we suggest that Yan and Pnt have distinct syntax preferences. Not only does Yan prefer high-affinity sites, but an overlapping pair of such sites is necessary and sufficient for Yan to tune Eve expression levels in newly specified cardioblasts and block ectopic Eve induction and cell fate specification in surrounding progenitors. Mechanistically, the efficient Yan recruitment promoted by this high-affinity ETS supersite not only biases Yan-Pnt competition at the specific CRM but also organizes Yan-repressive complexes in three dimensions across the eve locus. Taken together, our results uncover a novel mechanism by which differential interpretation of CRM syntax by a competing repressor-activator pair can confer both specificity and robustness to developmental transitions.

Brain and grammar: revealing electrophysiological basic structures with competing statistical models.

Acoustic, lexical, and syntactic information are simultaneously processed in the brain requiring complex strategies to distinguish their electrophysiological activity. Capitalizing on previous works that factor out acoustic information, we could concentrate on the lexical and syntactic contribution to language processing by testing competing statistical models. We exploited electroencephalographic recordings and compared different surprisal models selectively involving lexical information, part of speech, or syntactic structures in various combinations. Electroencephalographic responses were recorded in 32 participants during listening to affirmative active declarative sentences. We compared the activation corresponding to basic syntactic structures, such as noun phrases vs. verb phrases. Lexical and syntactic processing activates different frequency bands, partially different time windows, and different networks. Moreover, surprisal models based on part of speech inventory only do not explain well the electrophysiological data, while those including syntactic information do. By disentangling acoustic, lexical, and syntactic information, we demonstrated differential brain sensitivity to syntactic information. These results confirm and extend previous measures obtained with intracranial recordings, supporting our hypothesis that syntactic structures are crucial in neural language processing. This study provides a detailed understanding of how the brain processes syntactic information, highlighting the importance of syntactic surprisal in shaping neural responses during language comprehension.

Neural consequences of binaural beat stimulation on auditory sentence comprehension: an EEG study.

A growing literature has shown that binaural beat (BB)-generated by dichotic presentation of slightly mismatched pure tones-improves cognition. We recently found that BB stimulation of either beta (18 Hz) or gamma (40 Hz) frequencies enhanced auditory sentence comprehension. Here, we used electroencephalography (EEG) to characterize neural oscillations pertaining to the enhanced linguistic operations following BB stimulation. Sixty healthy young adults were randomly assigned to one of three listening groups: 18-Hz BB, 40-Hz BB, or pure-tone baseline, all embedded in music. After listening to the sound for 10 min (stimulation phase), participants underwent an auditory sentence comprehension task involving spoken sentences that contained either an object or subject relative clause (task phase). During the stimulation phase, 18-Hz BB yielded increased EEG power in a beta frequency range, while 40-Hz BB did not. During the task phase, only the 18-Hz BB resulted in significantly higher accuracy and faster response times compared with the baseline, especially on syntactically more complex object-relative sentences. The behavioral improvement by 18-Hz BB was accompanied by attenuated beta power difference between object- and subject-relative sentences. Altogether, our findings demonstrate beta oscillations as a neural correlate of improved syntactic operation following BB stimulation.

A syntax-lexicon trade-off in language production.

Spoken language production involves selecting and assembling words and syntactic structures to convey one's message. Here we probe this process by analyzing natural language productions of individuals with primary progressive aphasia (PPA) and healthy individuals. Based on prior neuropsychological observations, we hypothesize that patients who have difficulty producing complex syntax might choose semantically richer words to make their meaning clear, whereas patients with lexicosemantic deficits may choose more complex syntax. To evaluate this hypothesis, we first introduce a frequency-based method for characterizing the syntactic complexity of naturally produced utterances. We then show that lexical and syntactic complexity, as measured by their frequencies, are negatively correlated in a large (n = 79) PPA population. We then show that this syntax-lexicon trade-off is also present in the utterances of healthy speakers (n = 99) taking part in a picture description task, suggesting that it may be a general property of the process by which humans turn thoughts into speech.

Lipidomic-Based Algorithms Can Enhance Prediction of Obstructive Coronary Artery Disease.

Lipidomics emerges as a promising research field with the potential to help in personalized risk stratification and improve our understanding on the functional role of individual lipid species in the metabolic perturbations occurring in coronary artery disease (CAD). This study aimed to utilize a machine learning approach to provide a lipid panel able to identify patients with obstructive CAD. In this posthoc analysis of the prospective CorLipid trial, we investigated the lipid profiles of 146 patients with suspected CAD, divided into two categories based on the existence of obstructive CAD. In total, 517 lipid species were identified, from which 288 lipid species were finally quantified, including glycerophospholipids, glycerolipids, and sphingolipids. Univariate and multivariate statistical analyses have shown significant discrimination between the serum lipidomes of patients with obstructive CAD. Finally, the XGBoost algorithm identified a panel of 17 serum biomarkers (5 sphingolipids, 7 glycerophospholipids, a triacylglycerol, galectin-3, glucose, LDL, and LDH) as totally sensitive (100% sensitivity, 62.1% specificity, 100% negative predictive value) for the prediction of obstructive CAD. Our findings shed light on dysregulated lipid metabolism's role in CAD, validating existing evidence and suggesting promise for novel therapies and improved risk stratification.

Neural correlates of semantic-driven syntactic parsing in sentence comprehension.

For sentence comprehension, information carried by semantic relations between constituents must be combined with other information to decode the constituent structure of a sentence, due to atypical and noisy situations of language use. Neural correlates of decoding sentence structure by semantic information have remained largely unexplored. In this functional MRI study, we examine the neural basis of semantic-driven syntactic parsing during sentence reading and compare it with that of other types of syntactic parsing driven by word order and case marking. Chinese transitive sentences of various structures were investigated, differing in word order, case making, and agent-patient semantic relations (i.e., same vs. different in animacy). For the non-canonical unmarked sentences without usable case marking, a semantic-driven effect triggered by agent-patient ambiguity was found in the left inferior frontal gyrus opercularis (IFGoper) and left inferior parietal lobule, with the activity not being modulated by naturalness factors of the sentences. The comparison between each type of non-canonical sentences with canonical sentences revealed that the non-canonicity effect engaged the left posterior frontal and temporal regions, in line with previous studies. No extra neural activity was found responsive to case marking within the non-canonical sentences. A word order effect across all types of sentences was also found in the left IFGoper, suggesting a common neural substrate between different types of parsing. The semantic-driven effect was also observed for the non-canonical marked sentences but not for the canonical sentences, suggesting that semantic information is used in decoding sentence structure in addition to case marking. The current findings illustrate the neural correlates of syntactic parsing with semantics, and provide neural evidence of how semantics facilitates syntax together with other information.

Insulin resistance, coronary artery lesion complexity and adverse cardiovascular outcomes in patients with acute coronary syndrome.

BACKGROUND: Insulin resistance (IR) is linked to both the complexity of coronary artery lesions and the prognosis of acute coronary syndrome (ACS). However, the precise extent of this correlation and its impact on adverse cardiovascular outcomes in ACS patients remain unclear. Therefore, this study aims to investigate the intricate relationship between IR, coronary artery lesion complexity, and the prognosis of ACS through a cohort design analysis. METHOD: A total of 986 patients with ACS who underwent percutaneous coronary intervention (PCI) were included in this analysis. IR was assessed using the triglyceride-glucose (TyG) index, while coronary artery lesion complexity was evaluated using the SYNTAX score. Pearson's correlation coefficients were utilized to analyze the correlations between variables. The association of the TyG index and SYNTAX score with major adverse cardiovascular events (MACEs) in ACS was investigated using the Kaplan-Meier method, restricted cubic splines (RCS), and adjusted Cox regression. Additionally, a novel 2-stage regression method for survival data was employed in mediation analysis to explore the mediating impact of the SYNTAX score on the association between the TyG index and adverse cardiovascular outcomes, including MACEs and unplanned revascularization. RESULTS: During a median follow-up of 30.72 months, 167 cases of MACEs were documented, including 66 all-cause deaths (6.69%), 26 nonfatal myocardial infarctions (MIs) (2.64%), and 99 unplanned revascularizations (10.04%). The incidence of MACEs, all-cause death, and unplanned revascularization increased with elevated TyG index and SYNTAX score. Both the TyG index (non-linear, P = 0.119) and SYNTAX score (non-linear, P = 0.004) displayed a positive dose-response relationship with MACEs, as illustrated by the RCS curve. Following adjustment for multiple factors, both the TyG index and SYNTAX score emerged as significant predictors of MACEs across the total population and various subgroups. Mediation analysis indicated that the SYNTAX score mediated 25.03%, 18.00%, 14.93%, and 11.53% of the correlation between the TyG index and MACEs in different adjusted models, respectively. Similar mediating effects were observed when endpoint was defined as unplanned revascularization. CONCLUSION: Elevated baseline TyG index and SYNTAX score were associated with a higher risk of MACEs in ACS. Furthermore, the SYNTAX score partially mediated the relationship between the TyG index and adverse cardiovascular outcomes.

Association of the triglyceride glucose-body mass index with the extent of coronary artery disease in patients with acute coronary syndromes.

BACKGROUND: Studies have shown that insulin resistance is strongly associated with the development of cardiovascular disease, and the triglyceride glucose-body mass index (TyG-BMI index) is considered to be a reliable surrogate marker of insulin resistance. There are limited studies on the relationship between TyG-BMI index and the extent of coronary artery disease in patients with acute coronary syndrome (ACS). This study aimed to investigate the relationship between TyG-BMI index and the extent of coronary artery disease in patients with ACS. METHODS: Overall, 2,317 patients with ACS who underwent percutaneous coronary intervention at the Affiliated Hospital of Zunyi Medical University were included in this study. The TyG-BMI index was grouped according to the tertile method. The extent of coronary artery disease in patients with ACS was quantitatively assessed using the SYNTAX score, which was categorised as low (≤ 22), intermediate (23-32), and high risk (≥ 33). RESULTS: In the overall population, multivariate logistic regression analyses showed that TyG-BMI index was associated with mid/high SYNTAX score in patients with ACS (odds ratio [OR] = 1.0041; 95% confidence interval [CI] = 1.0000-1.0079; p = 0.0310). Subgroup analyses showed that TyG-BMI index was an independent risk factor for mid/high SYNTAX score in female ACS patients after adjusting for multiple confounders (OR = 1.0100; 95% CI = 1.0000-1.0200; p = 0.0050), and that the risk of mid/high SYNTAX score was 2.49 times higher in the T3 group (OR = 2.4900; 95% CI = 1.2200-5.0600; p = 0.0120). Restricted cubic spline analysis showed a linear correlation between TyG-BMI index and complex coronary artery disease (SYNTAX score > 22) in women with ACS. In female ACS patients, inclusion of the TyG-BMI index did not improve the predictive power of the underlying risk model (net reclassification improvement: 0.0867 [-0.0256-0.1989], p = 0.1301; integrated discrimination improvement: 0.0183 [0.0038-0.0329], p = 0.0135). CONCLUSIONS: TyG-BMI index is linearly associated with the degree of complex coronary artery disease in female ACS patients. However, the inclusion of the TyG-BMI index did not improve the predictive power of the underlying risk model for female ACS patients.

Progress in the Application of the Residual SYNTAX Score and Its Derived Scores.

The residual SYNTAX score (rSS) is employed for the quantification of residual coronary lesions and to guide revascularization. rSS can be combined with other examinations to evaluate the severity of vascular disease and play an evaluative and guiding role in various scenarios. Furthermore, combining rSS with other indicators, benefits prognosis evaluation, and rSS-derived scores have been increasingly used in clinical practice. This article reviews the progress in the clinical application of rSS and its derived scores for complex coronary arteries and other aspects, based on relevant literature.

The Relationship between Renal Resistive Index and Complexity of Coronary Lesions in Patients with Stable Coronary Artery Diseases.

Background: The most common cause of coronary artery diseases (CAD) is atherosclerosis. The synergy between percutaneous coronary intervention with TAXUS™ and cardiac surgery (SYNTAX) score was used to assess complex CAD lesions. The renal resistive index (RRI) is a Doppler ultrasound parameter calculated to assess renal haemodynamics. The direct relationship between CAD complexity and RRI was not yet investigated. The aim of our study was to investigate this relationship between RRI and SYNTAX score in stable CAD patients. Methods: This study included 214 patients with stable CAD and subsequent coronary angiography done at our institution. Regarding CAD complexity, these patients were classified into 166 patients with low SYNTAX score (SYNTAX ≤ 22), and 48 patients with high SYNTAX score (SYNTAX > 22). The demographic, laboratory, clinical, echocardiographic data and renal Doppler parameters; including RRI, were recorded. Results: Multivariate logistic regression analysis demonstrated that RRI (odds ratio, OR = 4.440, 95% (confidence interval) CI: 1.418-13.903, p = 0.010) was a novel independent predictor of high SYNTAX score in patients with stable CAD, in addition to other traditional predictors as diabetes mellitus (OR = 4.401, 95% CI: 1.081-17.923, p = 0.04), low-density lipoprotein cholesterol (LDL-C) (OR = 2.957, 95% CI: 1.920-8.995, p = 0.027), multi-vessel CAD (OR = 2.113, 95% CI: 1.241-2.280, p = 0.001) and Gensini score (OR = 6.539, 95% CI: 1.977-21.626, p = 0.002). Receiver operator characteristic curve analysis showed that RRI > 0.655 (sensitivity of 80%, specificity of 73.6%) was the best cut-off value for predicting high SYNTAX score. Conclusions: The non-invasively measured RRI is closely associated with high SYNTAX score in stable CAD patients.

Prognostic Capability of Clinical SYNTAX Score in Patients with Complex Coronary Artery Disease and Chronic Renal Insufficiency Undergoing Percutaneous Coronary Intervention.

Background: The SYNTAX score (SS) is useful for predicting clinical outcomes in patients undergoing percutaneous coronary intervention (PCI). The clinical SYNTAX score (CSS), developed by combining clinical parameters with the SS, enhances the risk model's ability to predict clinical outcomes. However, prior research has not yet evaluated the prognostic capacity of CSS in patients with complex coronary artery disease (CAD) and chronic renal insufficiency (CRI) who are undergoing PCI. We aimed to demonstrate the prognostic potential of CSS in assessing long-term adverse events in this high-risk patient cohort. Methods: A total of 962 patients with left main and/or three-vessel CAD and CRI were enrolled in the study spanning from January 2014 to September 2017. The CSS was calculated by multiplying the SS by the modified age, creatinine, and left ventricular ejection fraction (ACEF) score (age/ejection fraction + 1 for each 10 mL of creatinine clearance < 60 mL/min per 1.73 m 2 ). The patients were categorized into three groups based on their CSS values: low-CSS group (CSS < 18.0, n = 321), mid-CSS group (18.0 ≤ CSS < 28.3, n = 317), and high-CSS group (CSS ≥ 28.3, n = 324) as per the tertiles of CSS. The primary endpoints were all-cause mortality (ACM) and cardiac mortality (CM). The secondary endpoints included myocardial infarction (MI), unplanned revascularization, stroke, and major adverse cardiac and cerebrovascular events (MACCE). Results: At the median 3-year follow-up, the high-CSS group exhibited higher rates of ACM (19.4% vs. 6.6% vs. 3.6%, p < 0.001), CM (15.6% vs. 5.1% vs. 3.2%, p = 0.003), and MACCE (33.8% vs. 29.0% vs. 20.0%, p = 0.005) in comparison to the low and mid-CSS groups. Multivariable Cox regression analysis revealed that CSS was an independent predictor for all primary and secondary endpoints (p < 0 .05). Moreover, the C-statistics of CSS for ACM (0.666 vs. 0.597, p = 0.021) and CM (0.668 vs. 0.592, p = 0.039) were significantly higher than those of SS. Conclusions: The clinical SYNTAX score substantially enhanced the prediction of median 3-year ACM and CM in comparison with SS in complex CAD and CRI patients following PCI.

A Universal Cognitive Bias in Word Order: Evidence From Speakers Whose Language Goes Against It.

There is a long-standing debate in cognitive science surrounding the source of commonalities among languages of the world. Indeed, there are many potential explanations for such commonalities-accidents of history, common processes of language change, memory limitations, constraints on linguistic representations, and so on. Recent research has used psycholinguistic experiments to provide empirical evidence linking common linguistic patterns to specific features of human cognition, but these experiments tend to use English speakers, who in many cases have direct experience with the common patterns of interest. Here we highlight the importance of testing populations whose languages go against cross-linguistic trends. We investigate whether adult monolingual speakers of Kîîtharaka, which has an unusual way of ordering words, mirror the word-order preferences of English speakers. We find that they do, supporting the hypothesis that universal cognitive representations play a role in shaping word order.

Note similarities affect syntactic stability in zebra finches.

The acquisition of an acoustic template is a fundamental component of vocal imitation learning, which is used to refine innate vocalizations and develop a species-specific song. In the absence of a model, birds fail to develop species typical songs. In zebra finches (Taeniopygia guttata), tutored birds produce songs with a stereotyped sequence of distinct acoustic elements, or notes, which form the song motif. Songs of untutored individuals feature atypical acoustic and temporal structure. Here we studied songs and associated respiratory patterns of tutored and untutored male zebra finches to investigate whether similar acoustic notes influence the sequence of song elements. A subgroup of animals developed songs with multiple acoustically similar notes that are produced with alike respiratory motor gestures. These birds also showed increased syntactic variability in their adult motif. Sequence variability tended to occur near song elements which showed high similarity in acoustic structure and underlying respiratory motor gestures. The duration and depth of the inspirations preceding the syllables where syntactic variation occurred did not allow prediction of the following sequence of notes, suggesting that the varying duration and air requirement of the following expiratory pulse is not predictively encoded in the motor program. This study provides a novel method for calculation of motor/acoustic similarity, and the results of this study suggest that the note is a fundamental acoustic unit in the organization of the motif and could play a role in the neural code for song syntax.

The relationship between lymphocyte DNA damage, coronary artery disease, and blood trace elements.

Somatic DNA damage and causative factors (occupational exposures, foods, habits, etc.) are thought to contribute to the pathogenesis of atherosclerosis, although knowledge about their role in coronary artery disease (CAD) is still insufficient. This study aimed to determine the effects of lymphocyte-DNA damage and blood trace element concentrations on CAD. The single-cell alkaline comet was used in the measuring of the lymphocyte DNA damage in blood samples obtained from patients (n = 99) whose CAD grade was determined by the syntax score while the angiographic intervention was carried out. Blood trace element (n = 14) concentrations were monitored by the inductively coupled plasma-optical emission spectroscopy (ICP-OES) after microwave digestion. The relationship between the DNA damage frequencies of the participants and their syntax scores, blood trace element concentrations, and other demographic and clinic parameters were statistically analyzed. Significant correlations were detected between comet data and syntax score (r = 0.858, P < .001), age (r = 0.337, P < .001), blood-urea (r = 0.360, P < .001), creatinine (r = 0.388, P < .001), HbA1c (0.218, P < .05), ECG-QRS time (r = 0.286, P < .01), ECHO-EF (r = -0.377, P < .001), and platelet (r = -0.222, P < .05). The DNA damage frequencies of the groups formed according to their CAD scores were significantly different from the control group (P < .001) and also each other (P ≤ .01). Comet frequencies and CAD grades were found to be correlated with aging (P < .05). DNA damage frequency and syntax score values were significantly (P < .05) higher in males compared to females. Syntax scores were correlated with aging (r = 0.348, P < .01), ECHO-EF (r = 0.374, P < .001), blood-urea (r = 0.398, P < .001), creatinine (r = 0.433, P < .001), glucose (0.218, P < .05), and HbA1c (r = 0.200, P < .05). Significant correlations were observed between trace elements and demographic values, blood parameters, diseases, angio parameters, ECHO, and ECG parameters. It was observed that the concentrations of trace elements detected in the blood were 93.4% correlated with each other. Lymphocyte DNA damage is a strong biomarker for the atherosclerotic indicator of CAD. Aging is an effective factor both in the DNA damage frequency and CAD risk index. Creatinine and urea are factors that have the power to change the CAD risk index and DNA damage frequency. The higher DNA damage and CAD risk were monitored in males compared to females. The relationship between some biomarkers and blood trace element concentrations showed that further studies are needed to more accurately evaluate the relationship between trace elements, DNA damage frequencies, and CAD.

External validation of the SYNTAX score II 2020 in patients with chronic renal insufficiency.

BACKGROUND: The SYNTAX score Ⅱ 2020 (SSⅡ-2020) was created as a customized decision-making tool for individuals diagnosed with complex coronary artery disease (CAD). Nevertheless, there has been a scarcity of research investigating the long-term predictive significance of SSⅡ-2020 for patients with both CAD and chronic renal insufficiency (CRI) who undergo percutaneous coronary intervention (PCI). AIMS: We sought to showcase the prognostic capacity of SSII-2020 in evaluating long-term all-cause mortality (ACM) within this high-risk patient cohort. METHODS: A retrospective cohort comprising 1156 individuals diagnosed with CRI and exhibiting left main CAD, three-vessel CAD or both was included in this investigation. We categorized participants into three groups based on the optimal SSII-2020 threshold for predicting long-term ACM, determined using the X-tile software. RESULTS: At the median follow-up duration of 6.3 years, the ACM rates were determined to be 10% in the low, 17% in the moderate, and 28% in the high SSII-2020 groups (p < 0.001). Employing multivariate Cox regression analysis, it was observed that the high SSII-2020 group exhibited a 3.289-fold increased risk of ACM (95% confidence interval [CI]: 2.229-4.856, p < 0.001) compared with the low SSII-2020 group, whereas the high SSII-2020 group displayed a 1.757-fold (95% CI: 1.190-2.597, p = 0.005) in comparison to the median SSII-2020 groups. Compared with SSII, the SSII-2020 had an incremental value for predicting 7-year ACM (C-index: 0.662 vs. 0.534, p = 0.007; IDI: 0.016, p < 0.001). CONCLUSIONS: SSII-2020 enhances long-term ACM prediction, facilitates improved risk stratification, and improves clinical utility for PCI patients with complex CAD and CRI.

Anaphoric distance dependencies in visual narrative structure and processing.

Linguistic syntax has often been claimed as uniquely complex due to features like anaphoric relations and distance dependencies. However, visual narratives of sequential images, like those in comics, have been argued to use sequencing mechanisms analogous to those in language. These narrative structures include "refiner" panels that "zoom in" on the contents of another panel. Similar to anaphora in language, refiners indexically connect inexplicit referential information in one unit (refiner, pronoun) to a more informative "antecedent" elsewhere in the discourse. Also like in language, refiners can follow their antecedents (anaphoric) or precede them (cataphoric), along with having either proximal or distant connections. We here explore the constraints on visual narrative refiners created by modulating these features of order and distance. Experiment 1 examined participants' preferences for where refiners are placed in a sequence using a force-choice test, which revealed that refiners are preferred to follow their antecedents and have proximal distances from them. Experiment 2 then showed that distance dependencies lead to slower self-paced viewing times. Finally, measurements of event-related brain potentials (ERPs) in Experiment 3 revealed that these patterns evoke similar brain responses as referential dependencies in language (i.e., N400, LAN, Nref). Across all three studies, the constraints and (neuro)cognitive responses to refiners parallel those shown to anaphora in language, suggesting domain-general constraints on the sequencing of referential dependencies.

Text analysis framework for identifying mutations among non-small cell lung cancer patients from laboratory data.

BACKGROUND: Laboratory data can provide great value to support research aimed at reducing the incidence, prolonging survival and enhancing outcomes of cancer. Data is characterized by the information it carries and the format it holds. Data captured in Alberta's biomarker laboratory repository is free text, cluttered and rouge. Such data format limits its utility and prohibits broader adoption and research development. Text analysis for information extraction of unstructured data can change this and lead to more complete analyses. Previous work on extracting relevant information from free text, unstructured data employed Natural Language Processing (NLP), Machine Learning (ML), rule-based Information Extraction (IE) methods, or a hybrid combination between them. METHODS: In our study, text analysis was performed on Alberta Precision Laboratories data which consisted of 95,854 entries from the Southern Alberta Dataset (SAD) and 6944 entries from the Northern Alberta Dataset (NAD). The data covers all of Alberta and is completely population-based. Our proposed framework is built around rule-based IE methods. It incorporates topics such as Syntax and Lexical analyses to achieve deterministic extraction of data from biomarker laboratory data (i.e., Epidermal Growth Factor Receptor (EGFR) test results). Lexical analysis compromises of data cleaning and pre-processing, Rich Text Format text conversion into readable plain text format, and normalization and tokenization of text. The framework then passes the text into the Syntax analysis stage which includes the rule-based method of extracting relevant data. Rule-based patterns of the test result are identified, and a Context Free Grammar then generates the rules of information extraction. Finally, the results are linked with the Alberta Cancer Registry to support real-world cancer research studies. RESULTS: Of the original 5512 entries in the SAD dataset and 5017 entries in the NAD dataset which were filtered for EGFR, the framework yielded 5129 and 3388 extracted EGFR test results from the SAD and NAD datasets, respectively. An accuracy of 97.5% was achieved on a random sample of 362 tests. CONCLUSIONS: We presented a text analysis framework to extract specific information from unstructured clinical data. Our proposed framework has shown that it can successfully extract relevant information from EGFR test results.