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Cognitive models aim to explain complex human behavior in terms of hypothesized mechanisms of the mind. These mechanisms can be formalized in terms of mathematical structures containing parameters that are theoretically meaningful. For example, in the case of perceptual decision making, model parameters might correspond to theoretical constructs like response bias, evidence quality, response caution, and the like. Formal cognitive models go beyond verbal models in that cognitive mechanisms are instantiated in terms of mathematics and they go beyond statistical models in that cognitive model parameters are psychologically interpretable. We explore three key elements used to formally evaluate cognitive models: parameter estimation, model prediction, and model selection. We compare and contrast traditional approaches with Bayesian statistical approaches to performing each of these three elements. Traditional approaches rely on an array of seemingly ad hoc techniques, whereas Bayesian statistical approaches rely on a single, principled, internally consistent system. We illustrate the Bayesian statistical approach to evaluating cognitive models using a running example of the Linear Ballistic Accumulator model of decision making (Brown SD, Heathcote A. The simplest complete model of choice response time: linear ballistic accumulation. Cogn Psychol 2008, 57:153–178). WIREs Cogn Sci 2018, 9:e1458. doi: 10.1002/wcs.1458 This article is categorized under: Neuroscience > Computation Psychology > Reasoning and Decision Making Psychology > Theory and Methods [ABSTRACT FROM AUTHOR]

The intensive evaluation effectively combines vocational evaluation and assistive technology practices with a certified vocational evaluation specialist (CVE) and an assistive technology practitioner (ATP) collaborating on a five-day evaluation, usually for participants who have severe and multiple disabilities. The CVE leads evaluation procedures and the ATP analyzes assistive technology and accommodation needs. Traditional vocational evaluation tools such as interviewing, psychometric testing, career exploration, work samples, and situational assessment are utilized. Observation of work performance and behavior is emphasized more than normative data. The provision of two professional staff is necessary to allow for concentration on each discipline as well as collaborative brainstorming. A multidisciplinary team approach is emphasized before, during, and at the conclusion of the intensive evaluation. The three goals of the intensive evaluation are to increase participants' performance, independence, and quality of life while emphasizing the "Four P's" (purpose, passion, patience, and professionalism) and making the evaluation fun. [ABSTRACT FROM AUTHOR]

Rationale: Incidence rates for pulmonary hypertension using diagnostic data in patients with cardiopulmonary disease are not known., Objectives: To determine incidence rates of, risk factors for, and mortality hazard associated with pulmonary hypertension among patients referred for transthoracic echocardiography., Methods: Retrospective cohort study using data from the Veterans Health Administration (1999-2020) and Vanderbilt University Medical Center (1994-2020). Pulmonary hypertension was defined as pulmonary artery systolic pressure >35mmHg with prevalent cases excluded. Heart failure and chronic obstructive pulmonary disease were the primary exposures of interest. The primary outcome was incident pulmonary hypertension. Secondarily, we examined mortality rate following incident diagnosis., Measurements and Main Results: We identified 245,067 VA patients (94% male, 20% Black) and 117,526 Vanderbilt patients (46% male, 11% Black) without pulmonary hypertension, of whom 38,882 VA patients and 8,061 Vanderbilt patients developed pulmonary hypertension. Only 18-19% of patients with echo-based pulmonary hypertension also had a diagnostic code. Hazard of pulmonary hypertension was 4-fold higher in patients with heart failure and chronic obstructive pulmonary disease compared to patients without either. Mortality rates increased from pulmonary artery systolic pressure of 35mmHg to 45mmHg then plateaued. Independent risk factors for incident pulmonary hypertension included older age, male sex, black race, and cardiometabolic comorbidities., Conclusions: Pulmonary hypertension incidence rates estimated by diagnostic data are higher than code-based rates. Heart failure and chronic obstructive pulmonary disease strongly associate with incident pulmonary hypertension. Pulmonary artery systolic pressure >45mmHg at diagnosis is associated with high mortality. New pulmonary hypertension on echocardiography is an important prognostic sign.

Introduction: Incidence rates (IRs) of RV dysfunction (RVD) are unknown. We examined the rates, risk factors, and heart failure (HF) hospitalization hazard associated with incident RVD in patients referred for Transthoracic Echocardiogram (TTE)., Methods: In this retrospective cohort study, we extracted tricuspid regurgitant velocity (TRV) and tricuspid annular systolic plane excursion (TAPSE) from TTEs at Vanderbilt (2010-2023). We followed patients from their earliest TTE with normal RV function (TAPSE≥17mm) and a reported TRV. The primary outcome was new RVD (TAPSE<17mm), and the secondary outcome was HF hospitalization after second TTE. Poisson regression and multivariable cox models estimated IRs and hazard ratios, adjusted for demographics, comorbidities, and TTE measures., Results: Among 45,753 patients (63 years [IQR 50-72], 45% Male, 13% Black) meeting inclusion criteria, 13,735 (30.1%) underwent a follow up TTE and 4,198 (9.2%) developed RVD. The IR of RVD in the full cohort was 3.2/100 person/years (95%CI 3.1-3.3) and 8.2 (95%CI 8.0-8.5) in the repeat TTE cohort. IRs increased with rising RVSP. Risk factors for incident RVD were most prominently HF (HR 1.88; 95%CI 1.75-2.03), left-sided valvular disease (HR 1.68; 95%CI 1.53-1.85), and other cardiovascular comorbidities. Baseline RVSP >35 mmHg associated with TAPSE decline over time. Incident RVD increased hazard of HF hospitalization (HR 2.02; 95%CI 1.85-2.21). Hazard of HF hospitalization increased when TAPSE declined by ≥5mm., Conclusions: RVD incidence is substantial among patients referred for TTE. Clinical monitoring is warranted if RVSP >35mmHg. Cardiovascular comorbidities drive RVD in this population. Incident RVD associates with increased hazard of HF hospitalization.

Background: Mitochondrial dysfunction, characterized by impaired lipid metabolism and heightened reactive oxygen species (ROS) generation, results in lipid peroxidation and ferroptosis. Ferroptosis is an inflammatory mode of cell death that promotes complement activation and macrophage recruitment. In pulmonary arterial hypertension (PAH), pulmonary arterial endothelial cells (PAEC) exhibit cellular phenotypes that promote ferroptosis. Moreover, there is ectopic complement deposition and inflammatory macrophage accumulation in the pulmonary vasculature. However, the effects of ferroptosis inhibition on these pathogenic mechanisms and the cellular landscape of the pulmonary vasculature are incompletely defined., Methods: Multi-omics and physiological analyses evaluated how ferroptosis inhibition modulated preclinical PAH. The impact of AAV1-mediated expression of the pro-ferroptotic protein ACSL4 on PAH was determined, and a genetic association study in humans further probed the relationship between ferroptosis and pulmonary hypertension (PH)., Results: Ferrostatin-1, a small-molecule ferroptosis inhibitor, mitigated PAH severity in monocrotaline rats. RNA-seq and proteomics analyses demonstrated ferroptosis was associated with PAH severity. RNA-seq, proteomics, and confocal microscopy revealed complement activation and pro-inflammatory cytokines/chemokines were suppressed by ferrostatin-1. Additionally, ferrostatin-1 combatted changes in endothelial, smooth muscle, and interstitial macrophage abundance and gene activation patterns as revealed by deconvolution RNA-seq. Ferroptotic PAEC damage associated molecular patterns restructured the transcriptomic signature, mitochondrial morphology, and promoted proliferation of pulmonary artery smooth muscle cells, and created a pro-inflammatory phenotype in monocytes in vitro . AAV1- Acsl4 induced an inflammatory PAH phenotype in rats. Finally, single-nucleotide polymorphisms in six ferroptosis genes identified a potential link between ferroptosis and PH severity in the Vanderbilt BioVU repository., Conclusions: Ferroptosis promotes PAH through metabolic and inflammatory mechanisms in the pulmonary vasculature.

Background: Early diagnosis of pulmonary hypertension (PH) is critical for effective treatment and management. We aimed to develop and externally validate an artificial intelligence algorithm that could serve as a PH screening tool, based on analysis of a standard 12-lead ECG., Methods: The PH Early Detection Algorithm (PH-EDA) is a convolutional neural network developed using retrospective ECG voltage-time data, with patients classified as "PH-likely" or "PH-unlikely" (controls) based on right heart catheterisation or echocardiography. In total, 39 823 PH-likely patients and 219 404 control patients from Mayo Clinic were randomly split into training (48%), validation (12%) and test (40%) sets. ECGs taken within 1 month of PH diagnosis (diagnostic dataset) were used to train the PH-EDA at Mayo Clinic. Performance was tested on diagnostic ECGs within the test sets from Mayo Clinic (n=16 175/87 998 PH-likely/controls) and Vanderbilt University Medical Center (VUMC; n=6045/24 256 PH-likely/controls). In addition, performance was tested on ECGs taken 6-18 months (pre-emptive dataset), and up to 5 years prior to a PH diagnosis at both sites., Results: Performance testing yielded an area under the receiver operating characteristic curve (AUC) of 0.92 and 0.88 in the diagnostic test sets at Mayo Clinic and VUMC, respectively, and 0.86 and 0.81, respectively, in the pre-emptive test sets. The AUC remained a minimum of 0.79 at Mayo Clinic and 0.73 at VUMC up to 5 years before diagnosis., Conclusion: The PH-EDA can detect PH at diagnosis and 6-18 months prior, demonstrating the potential to accelerate diagnosis and management of this debilitating disease., Competing Interests: Conflict of interest: H.M. DuBrock and R.P. Frantz report personal fees from Janssen Research and Development, LLC, a Johnson and Johnson company, outside the submitted work; and that additionally, Mayo Clinic may benefit financially from the algorithm described. T.E. Wagner, K. Carlson, C.L. Carpenter, S. Awasthi, M. Babu, A. Prasad, U. Yoo, R. Barve and V. Soundararajan are employees of nference, which received financial support from Janssen Research and Development, LLC, a Johnson and Johnson company, for work on this study. T.E. Wagner, S. Awasthi and V. Soundararajan also have patent application numbers 63/091,715 (non-invasive methods for detection of pulmonary hypertension) and 63/126,331 (systems and methods for diagnosing a health condition based on patient time series data) pending. K. Carlson, C.L. Carpenter, M. Babu, A. Prasad and R. Barve also have a patent application number 63/126,331 (systems and methods for diagnosing a health condition based on patient time series data) pending. Z.I. Attia, P.A. Friedman and S. Kapa have nothing to disclose apart from the fact that Mayo Clinic may financially benefit from the algorithm described in future. A.R. Hemnes, J. Annis and E.L. Brittain have no competing interests to report. S.J. Asirvatham reports personal fees from Abiomed, Atricure, Biotronik, Blackwell Futura, Boston Scientific, Medtronic, Medtelligence, Spectranetics, St. Jude, Zoll, Aegis, ATP, Nevro, Sanovas, Sorin Medical and FocusStart, outside the submitted work; and additionally, Mayo Clinic may financially benefit from the algorithm described in future. S.J. Asirvatham also receives royalties for work licensed through Mayo Clinic to a privately held company for contributions related to the use of nerve signal modulation to treat central, autonomic and peripheral nervous system disorders, including pain. Mayo Clinic receives royalties and owns equity in this company. The company does not currently license or manufacture any drug or device in the medical field. S.J. Asirvatham is a co-patent holder for technique to minimise coagulum formation during radiofrequency ablation. Products/techniques related to the above disclosures are not being discussed in this publication. M. Selej, P. Agron, E. Kogan, D. Quinn, P. Dunnmon and N. Khan are employees of Janssen Research and Development, LLC, a Johnson and Johnson company and own shares in the company., (Copyright ©The authors 2024.)

Despite consistent public health recommendations, obesity rates continue to increase. Physical activity (e.g. daily steps) is a well-established modifier of body weight. Genetic background is an important, but typically uncaptured, contributor to obesity risk. Leveraging physical activity, clinical, and genetic data from the All of Us Research Program, we measured the impact of genetic risk of obesity on the level of physical activity needed to reduce incident obesity. For example, we show that an additional 3,310 steps per day (11,910 steps total) would be needed to mitigate a 25% higher than average genetic risk of obesity. We quantify the number of daily steps needed to mitigate obesity risk across the spectrum of genetic risk. This work quantifies the relationship between physical activity and genetic risk showing significant independent effects and provides a first step towards personalized activity recommendations that incorporate genetic information to reduce incident obesity risk., Competing Interests: Competing Interests: There are no competing interests for any author. Also, all authors have no disclosures. The sponsor, All of Us Research Program, as well as Fitbit, were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.