Interpretable artificial intelligence to optimise use of imatinib after resection in patients with localised gastrointestinal stromal tumours: an observational cohort study.

BACKGROUND: Current guidelines recommend use of adjuvant imatinib therapy for many patients with gastrointestinal stromal tumours (GISTs); however, its optimal treatment duration is unknown and some patient groups do not benefit from the therapy. We aimed to apply state-of-the-art, interpretable artificial intelligence (ie, predictions or prescription logic that can be easily understood) methods on real-world data to establish which groups of patients with GISTs should receive adjuvant imatinib, its optimal treatment duration, and the benefits conferred by this therapy. METHODS: In this observational cohort study, we considered for inclusion all patients who underwent resection of primary, non-metastatic GISTs at the Memorial Sloan Kettering Cancer Center (MSKCC; New York, NY, USA) between Oct 1, 1982, and Dec 31, 2017, and who were classified as intermediate or high risk according to the Armed Forces Institute of Pathology Miettinen criteria and had complete follow-up data with no missing entries. A counterfactual random forest model, which used predictors of recurrence (mitotic count, tumour size, and tumour site) and imatinib duration to infer the probability of recurrence at 7 years for a given patient under each duration of imatinib treatment, was trained in the MSKCC cohort. Optimal policy trees (OPTs), a state-of-the-art interpretable AI-based method, were used to read the counterfactual random forest model by training a decision tree with the counterfactual predictions. The OPT recommendations were externally validated in two cohorts of patients from Poland (the Polish Clinical GIST Registry), who underwent GIST resection between Dec 1, 1981, and Dec 31, 2011, and from Spain (the Spanish Group for Research in Sarcomas), who underwent resection between Oct 1, 1987, and Jan 30, 2011. FINDINGS: Among 1007 patients who underwent GIST surgery in MSKCC, 117 were included in the internal cohort; for the external cohorts, the Polish cohort comprised 363 patients and the Spanish cohort comprised 239 patients. The OPT did not recommend imatinib for patients with GISTs of gastric origin measuring less than 15·9 cm with a mitotic count of less than 11·5 mitoses per 5 mm2 or for those with small GISTs (<5·4 cm) of any site with a count of less than 11·5 mitoses per 5 mm2. In this cohort, the OPT cutoffs had a sensitivity of 92·7% (95% CI 82·4-98·0) and a specificity of 33·9% (22·3-47·0). The application of these cutoffs in the two external cohorts would have spared 38 (29%) of 131 patients in the Spanish cohort and 44 (35%) of 126 patients in the Polish cohort from unnecessary treatment with imatinib. Meanwhile, the risk of undertreating patients in these cohorts was minimal (sensitivity 95·4% [95% CI 89·5-98·5] in the Spanish cohort and 92·4% [88·3-95·4] in the Polish cohort). The OPT tested 33 different durations of imatinib treatment (<5 years) and found that 5 years of treatment conferred the most benefit. INTERPRETATION: If the identified patient subgroups were applied in clinical practice, as many as a third of the current cohort of candidates who do not benefit from adjuvant imatinib would be encouraged to not receive imatinib, subsequently avoiding unnecessary toxicity on patients and financial strain on health-care systems. Our finding that 5 years is the optimal duration of imatinib treatment could be the best source of evidence to inform clinical practice until 2028, when a randomised controlled trial with the same aims is expected to report its findings. FUNDING: National Cancer Institute.

Is Precision Surgery Applicable to Colorectal Liver Metastases? A Systematic Review and Meta-analysis of Studies that Investigate the Association of Surgical Technique with Outcomes in the Context of Distinct Tumor Biology.

BACKGROUND: Although some data suggest that patients with mutRAS colorectal liver metastases (CRLM) may benefit from anatomic hepatectomy, this topic remains controversial. We performed a systematic review and meta-analysis to determine whether RAS mutation status was associated with prognosis relative to surgical technique [anatomic resection (AR) vs. nonanatomic resection (NAR)] among patients with CRLM. PATIENTS AND METHODS: A systematic review and meta-analysis of studies were performed to investigate the association of AR versus NAR with overall and liver-specific disease-free survival (DFS and liver-specific DFS, respectively) in the context of RAS mutation status. RESULTS: Overall, 2018 patients (831 mutRAS vs. 1187 wtRAS) were included from five eligible studies. AR was associated with a 40% improvement in liver-specific DFS [hazard ratio (HR) = 0.6, 95% confidence interval (CI) 0.44-0.81, p = 0.01] and a 28% improvement in overall DFS (HR = 0.72, 95% CI 0.54-0.95, p = 0.02) among patients with mutRAS tumors; in contrast, AR was not associated with any improvement in liver-specific DFS or overall DFS among wtRAS patients. These differences may have been mediated by the 40% decreased incidence in R1 resection among patients with mutRAS tumors who underwent AR versus NAR [relative risk (RR): 0.6, 95% CI 0.40-0.91, p = 0.02]. In contrast, the probability of an R1 resection was not decreased among wtRAS patients who underwent AR versus NAR (RR: 0.93, 95% CI 0.69-1.25, p = 0.62). CONCLUSIONS: The data suggest that precision surgery may be relevant to CRLM. Specifically, rather than a parenchymal sparing dogma for all patients, AR may have a role in individuals with mutRAS tumors.

Gradient synchronization for multivariate functional data, with application to brain connectivity.

Quantifying the association between components of multivariate random curves is of general interest and is a ubiquitous and basic problem that can be addressed with functional data analysis. An important application is the problem of assessing functional connectivity based on functional magnetic resonance imaging (fMRI), where one aims to determine the similarity of fMRI time courses that are recorded on anatomically separated brain regions. In the functional brain connectivity literature, the static temporal Pearson correlation has been the prevailing measure for functional connectivity. However, recent research has revealed temporally changing patterns of functional connectivity, leading to the study of dynamic functional connectivity. This motivates new similarity measures for pairs of random curves that reflect the dynamic features of functional similarity. Specifically, we introduce gradient synchronization measures in a general setting. These similarity measures are based on the concordance and discordance of the gradients between paired smooth random functions. Asymptotic normality of the proposed estimates is obtained under regularity conditions. We illustrate the proposed synchronization measures via simulations and an application to resting-state fMRI signals from the Alzheimer's Disease Neuroimaging Initiative and they are found to improve discrimination between subjects with different disease status.

Advancing minimally invasive hepato-pancreato-biliary surgery: ensuring safety with implementation.

BACKGROUND: Although minimally invasive hepato-pancreato-biliary (MIS HPB) surgery can be performed with good outcomes, there are currently no standardized requirements for centers or surgeons who wish to implement MIS HPB surgery. The aim of this study was to create a consensus statement regarding safe dissemination and implementation of MIS HPB surgical programs. METHODS: Sixteen key questions regarding safety in MIS HPB surgery were generated after a focused literature search and iterative review by three field experts. Participants for the working group were then selected using sequential purposive sampling and snowball techniques. Review of the 16 questions took place over a single 2-h meeting. The senior author facilitated the session, and a modified nominal group technique was used. RESULTS: Twenty three surgeons were in attendance. All participants agreed or strongly agreed that formal guidelines should exist for both institutions and individual surgeons interested in implementing MIS HPB surgery and that routine monitoring and reporting of institutional and surgeon technical outcomes should be performed. Regarding volume cutoffs, most participants (91%) agreed or strongly agreed that a minimum annual institutional volume cutoff for complex MIS HPB surgery, such as major hepatectomy or pancreaticoduodenectomy, should exist. A smaller proportion (74%) agreed or strongly agreed that a minimum annual surgeon volume requirement should exist. The majority of participants agreed or strongly agreed that surgeons were responsible for defining (100%) and enforcing (78%) guidelines to ensure the overall safety of MIS HPB programs. Finally, formal MIS HPB training, minimum case volume requirements, institutional support and infrastructure, and mandatory collection of outcomes data were all recognized as important aspects of safe implementation of MIS HPB surgery. CONCLUSIONS: Safe implementation of MIS HPB surgery requires a thoughtful process that incorporates structured training, sufficient volume and expertise, a proper institutional ecosystem, and monitoring of outcomes.

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches.

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we measured vertical, mediolateral, and anteroposterior acceleration using a waist-worn iPhone accelerometer during ambulation across a typical range of velocities. Fifteen TD and fifteen DMD children from 3 to 16 years of age underwent eight walking/running activities, including five 25 m walk/run speed-calibration tests at a slow walk to running speeds (SC-L1 to SC-L5), a 6-min walk test (6MWT), a 100 m fast walk/jog/run (100MRW), and a free walk (FW). For clinical anchoring purposes, participants completed a Northstar Ambulatory Assessment (NSAA). We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data. Extracted temporospatial gait CFs showed reduced step length and a greater mediolateral component of total power (TP) consistent with shorter strides and Trendelenberg-like gait commonly observed in DMD. ML approaches using temporospatial gait CFs and raw data varied in effectiveness at differentiating between DMD and TD controls at different speeds, with an accuracy of up to 100%. We demonstrate that by using ML with accelerometer data from a consumer-grade smartphone, we can capture DMD-associated gait characteristics in toddlers to teens.

Gait Event Detection and Travel Distance Using Waist-Worn Accelerometers across a Range of Speeds: Automated Approach.

Estimation of temporospatial clinical features of gait (CFs), such as step count and length, step duration, step frequency, gait speed, and distance traveled, is an important component of community-based mobility evaluation using wearable accelerometers. However, accurate unsupervised computerized measurement of CFs of individuals with Duchenne muscular dystrophy (DMD) who have progressive loss of ambulatory mobility is difficult due to differences in patterns and magnitudes of acceleration across their range of attainable gait velocities. This paper proposes a novel calibration method. It aims to detect steps, estimate stride lengths, and determine travel distance. The approach involves a combination of clinical observation, machine-learning-based step detection, and regression-based stride length prediction. The method demonstrates high accuracy in children with DMD and typically developing controls (TDs) regardless of the participant's level of ability. Fifteen children with DMD and fifteen TDs underwent supervised clinical testing across a range of gait speeds using 10 m or 25 m run/walk (10 MRW, 25 MRW), 100 m run/walk (100 MRW), 6-min walk (6 MWT), and free-walk (FW) evaluations while wearing a mobile-phone-based accelerometer at the waist near the body's center of mass. Following calibration by a trained clinical evaluator, CFs were extracted from the accelerometer data using a multi-step machine-learning-based process and the results were compared to ground-truth observation data. Model predictions vs. observed values for step counts, distance traveled, and step length showed a strong correlation (Pearson's r = -0.9929 to 0.9986, p < 0.0001). The estimates demonstrated a mean (SD) percentage error of 1.49% (7.04%) for step counts, 1.18% (9.91%) for distance traveled, and 0.37% (7.52%) for step length compared to ground-truth observations for the combined 6 MWT, 100 MRW, and FW tasks. Our study findings indicate that a single waist-worn accelerometer calibrated to an individual's stride characteristics using our methods accurately measures CFs and estimates travel distances across a common range of gait speeds in both DMD and TD peers.

Performance of the 7 th and 8 th Editions of the American Joint Committee on Cancer Staging System in Patients with Intraductal Papillary Mucinous Neoplasm-Associated PDAC : A Multi-institutional Analysis.

OBJECTIVE: To validate the 7 th and 8 th editions of the AJCC staging system for patients with invasive carcinomas arising in association with IPMN (IPMN-associated PDAC). BACKGROUND DATA: Although several studies have validated AJCC systems in patients with conventional PDAC, their applicability to IPMN-associated PDAC has not been assessed. METHODS: Two hundred seventy-five patients who underwent resection for IPMN-associated PDAC between 1996 and 2015 at 3 tertiary centers and had data on the size of the invasive component and lymph node status were identified. Concordance probability estimates (CPE) were calculated and recursive partitioning analysis was employed to identify optimal prognostic cutoffs for T and N. RESULTS: The CPE for the 7 th and 8 th editions of the AJCC schema were relatively good (0.64 for both) and similar for colloid and tubular subtypes (0.64 for both). The 8 th edition introduced T1a sub-staging and a new distinction between N1 and N2. The utility of the former was confirmed, although the latter did not improve prognostic discrimination. The successful validation of the 8th edition of the AJCC criteria in patients with tubular and colloid subtypes allowed us to compare these patients in early vs late T and N stages which showed that with advanced disease, the prognostic superiority of colloid tumors over their tubular counterparts diminishes. CONCLUSIONS: Our findings support the use of the AJCC 8 th edition in the IPMN-associated PDAC population, but suggest that certain cutoffs may need to be revisited. In advanced AJCC stages, patients with colloid vs tubular subtypes have comparable prognosis.

Demystifying BRAF Mutation Status in Colorectal Liver Metastases : A Multi-institutional, Collaborative Approach to 6 Open Clinical Questions.

OBJECTIVE: To investigate the clinical implications of BRAF -mutated (mut BRAF ) colorectal liver metastases (CRLMs). BACKGROUND: The clinical implications of mut BRAF status in CRLMs are largely unknown. METHODS: Patients undergoing resection for mut BRAF CRLM were identified from prospectively maintained registries of the collaborating institutions. Overall survival (OS) and recurrence-free survival (RFS) were compared among patients with V600E versus non-V600E mutations, KRAS/BRAF comutation versus mut BRAF alone, microsatellite stability status (Microsatellite Stable (MSS) vs instable (MSI-high)), upfront resectable versus converted tumors, extrahepatic versus liver-limited disease, and intrahepatic recurrence treated with repeat hepatectomy versus nonoperative management. RESULTS: A total of 240 patients harboring BRAF -mutated tumors were included. BRAF V600E mutation was associated with shorter OS (30.6 vs 144 mo, P =0.004), but not RFS compared with non-V600E mutations. KRAS/BRAF comutation did not affect outcomes. MSS tumors were associated with shorter RFS (9.1 vs 26 mo, P <0.001) but not OS (33.5 vs 41 mo, P =0.3) compared with MSI-high tumors, whereas patients with resected converted disease had slightly worse RFS (8 vs 11 mo, P =0.01) and similar OS (30 vs 40 mo, P =0.4) compared with those with upfront resectable disease. Patients with extrahepatic disease had worse OS compared with those with liver-limited disease (8.8 vs 40 mo, P <0.001). Repeat hepatectomy after intrahepatic recurrence was associated with improved OS compared with nonoperative management (41 vs 18.7 mo, P =0.004). All results continued to hold true in the multivariable OS analysis. CONCLUSIONS: Although surgery may be futile in patients with BRAF -mutated CRLM and concurrent extrahepatic disease, resection of converted disease resulted in encouraging survival in the absence of extrahepatic spread. Importantly, second hepatectomy in select patients with recurrence was associated with improved outcomes. Finally, MSI-high status identifies a better prognostic group, with regard to RFS while patients with non-V600E mutations have excellent prognosis.

Trajectories of brain volumes in young children are associated with maternal education.

Brain growth in early childhood is reflected in the evolution of proportional cerebrospinal fluid volumes (pCSF), grey matter (pGM), and white matter (pWM). We study brain development as reflected in the relative fractions of these three tissues for a cohort of 388 children that were longitudinally followed between the ages of 18 and 96 months. We introduce statistical methodology (Riemannian Principal Analysis through Conditional Expectation, RPACE) that addresses major challenges that are of general interest for the analysis of longitudinal neuroimaging data, including the sparsity of the longitudinal observations over time and the compositional structure of the relative brain volumes. Applying the RPACE methodology, we find that longitudinal growth as reflected by tissue composition differs significantly for children of mothers with higher and lower maternal education levels.

Testing homogeneity: the trouble with sparse functional data.

Testing the homogeneity between two samples of functional data is an important task. While this is feasible for intensely measured functional data, we explain why it is challenging for sparsely measured functional data and show what can be done for such data. In particular, we show that testing the marginal homogeneity based on point-wise distributions is feasible under some mild constraints and propose a new two-sample statistic that works well with both intensively and sparsely measured functional data. The proposed test statistic is formulated upon energy distance, and the convergence rate of the test statistic to its population version is derived along with the consistency of the associated permutation test. The aptness of our method is demonstrated on both synthetic and real data sets.

A YOLO-based AI system for classifying calcifications on spot magnification mammograms.

OBJECTIVES: Use of an AI system based on deep learning to investigate whether the system can aid in distinguishing malignant from benign calcifications on spot magnification mammograms, thus potentially reducing unnecessary biopsies. METHODS: In this retrospective study, we included public and in-house datasets with annotations for the calcifications on both craniocaudal and mediolateral oblique vies, or both craniocaudal and mediolateral views of each case of mammograms. All the lesions had pathological results for correlation. Our system comprised an algorithm based on You Only Look Once (YOLO) named adaptive multiscale decision fusion module. The algorithm was pre-trained on a public dataset, Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM), then re-trained and tested on the in-house dataset of spot magnification mammograms. The performance of the system was investigated by receiver operating characteristic (ROC) analysis. RESULTS: We included 1872 images from 753 calcification cases (414 benign and 339 malignant) from CBIS-DDSM. From the in-house dataset, 636 cases (432 benign and 204 malignant) with 1269 spot magnification mammograms were included, with all lesions being recommended for biopsy by radiologists. The area under the ROC curve for our system on the in-house testing dataset was 0.888 (95% CI 0.868-0.908), with a sensitivity of 88.4% (95% CI 86.9-8.99%), specificity of 80.8% (95% CI 77.6-84%), and an accuracy of 84.6% (95% CI 81.8-87.4%) at the optimal cutoff value. Using the system with two views of spot magnification mammograms, 80.8% benign biopsies could be avoided. CONCLUSION: The AI system showed good accuracy for classification of calcifications on spot magnification mammograms which were all categorized as suspicious by radiologists, thereby potentially reducing unnecessary biopsies.

Characteristics of breast cancers detected by screening mammography in Taiwan: a single institute's experience.

BACKGROUND/AIM: Breast cancer is the most common female malignancy in the world. Nearly ninety percent of screening-detected breast cancers were diagnosed with earlier stages of 0 to II in Taiwan. It's widely acknowledged that mammography screening of breast cancer can achieve the goal of early diagnosis and treatment in terms of preventive task while neglected interval cancers are associated with unfavorable tumor characteristics and worse outcomes. The purpose of this study was to explore the characteristics of screening-detected breast cancers in Taiwan. MATERIALS AND METHODS: Both screening and diagnostic mammography examinations with accompanied BI-RADS (breast imaging-reporting and data system) classification were extracted from the health information system and linked to cancer registry in Taiwan. Enrolled population included those attending their first mammography between 2012 and 2016, excluding subjects with previous breast cancer, or with missing or incomplete data. We compared treatment outcomes between breast cancers with either initial screening or diagnostic mammography (control group), and investigated the compositions of breast cancers detected by screening mammography through direct chart reviews. RESULTS: A total of 84,246 screening and 61,230 diagnostic mammography sessions were performed from 2010 to 2020. More positive results (BI-RADS 0, 3, 4 and 5) were observed for those attending the first diagnostic than the first screening mammography (43.58% versus 16.12%, p < 0.001). Earlier stages (0 and I) distribution (92% versus 81%, p < 0.0001), better survivorship (overall survival: 96.91% versus 92.17%, p = 0.007) and a lower HER2 (human epidermal growth factor receptor II) positive status and lower tumor grade were noted in breast cancers with initial screening rather than diagnostic mammography. Among 26,103 mammography screening invitees between 2012 and 2016, 325 breast cancers were ascertained from cancer registry. Of these, 234 had one, 72 had two and 19 had three episodes of mammography before cancer diagnosis. Extensive chart reviews revealed that women with and without breast symptoms constituted 29.9 and 70.1% of the 325 screening-detected breast cancers, with the latter further divided into false negative results (interval cancer), diagnosed at the first mammography, diagnostic at the secondary or subsequent mammography and those with a delayed biopsy or confirmatory imaging constituted (5.2, 47, 10.5 and 7.4%). CONCLUSION: Screening-detected breast cancers were a mixture of women with and without symptoms, those with a false negative result, true negative results with cancer detected at subsequent mammography and non-adherers. Despite this, efficacy of mammography screening was ascertained in Taiwan from this study. To further enhance earlier detection and decrease false negativity, the impact of repeated mammography, and additional sonography for symptomatic women, compliance following a positive screening mammography should not be overemphasized.

Meta-Learned Models of Cognition.

Psychologists and neuroscientists extensively rely on computational models for studying and analyzing the human mind. Traditionally, such computational models have been hand-designed by expert researchers. Two prominent examples are cognitive architectures and Bayesian models of cognition. While the former requires the specification of a fixed set of computational structures and a definition of how these structures interact with each other, the latter necessitates the commitment to a particular prior and a likelihood function which - in combination with Bayes' rule - determine the model's behavior. In recent years, a new framework has established itself as a promising tool for building models of human cognition: the framework of meta-learning. In contrast to the previously mentioned model classes, meta-learned models acquire their inductive biases from experience, i.e., by repeatedly interacting with an environment. However, a coherent research program around meta-learned models of cognition is still missing to this day. The purpose of this article is to synthesize previous work in this field and establish such a research program. We accomplish this by pointing out that meta-learning can be used to construct Bayes-optimal learning algorithms, allowing us to draw strong connections to the rational analysis of cognition. We then discuss several advantages of the meta-learning framework over traditional methods and reexamine prior work in the context of these new insights.

Reversal of pancreatic desmoplasia by a tumour stroma-targeted nitric oxide nanogel overcomes TRAIL resistance in pancreatic tumours.

OBJECTIVE: Stromal barriers, such as the abundant desmoplastic stroma that is characteristic of pancreatic ductal adenocarcinoma (PDAC), can block the delivery and decrease the tumour-penetrating ability of therapeutics such as tumour necrosis factor-related apoptosis-inducing ligand (TRAIL), which can selectively induce cancer cell apoptosis. This study aimed to develop a TRAIL-based nanotherapy that not only eliminated the extracellular matrix barrier to increase TRAIL delivery into tumours but also blocked antiapoptotic mechanisms to overcome TRAIL resistance in PDAC. DESIGN: Nitric oxide (NO) plays a role in preventing tissue desmoplasia and could thus be delivered to disrupt the stromal barrier and improve TRAIL delivery in PDAC. We applied an in vitro-in vivo combinatorial phage display technique to identify novel peptide ligands to target the desmoplastic stroma in both murine and human orthotopic PDAC. We then constructed a stroma-targeted nanogel modified with phage display-identified tumour stroma-targeting peptides to co-deliver NO and TRAIL to PDAC and examined the anticancer effect in three-dimensional spheroid cultures in vitro and in orthotopic PDAC models in vivo. RESULTS: The delivery of NO to the PDAC tumour stroma resulted in reprogramming of activated pancreatic stellate cells, alleviation of tumour desmoplasia and downregulation of antiapoptotic BCL-2 protein expression, thereby facilitating tumour penetration by TRAIL and substantially enhancing the antitumour efficacy of TRAIL therapy. CONCLUSION: The co-delivery of TRAIL and NO by a stroma-targeted nanogel that remodels the fibrotic tumour microenvironment and suppresses tumour growth has the potential to be translated into a safe and promising treatment for PDAC.

Cysteine-rich protein 2 deficiency attenuates angiotensin II-induced abdominal aortic aneurysm formation in mice.

BACKGROUND: Abdominal aortic aneurysm (AAA) is a relatively common and often fatal condition. A major histopathological hallmark of AAA is the severe degeneration of aortic media with loss of vascular smooth muscle cells (VSMCs), which are the main source of extracellular matrix (ECM) proteins. VSMCs and ECM homeostasis are essential in maintaining structural integrity of the aorta. Cysteine-rich protein 2 (CRP2) is a VSMC-expressed protein; however, the role of CRP2 in AAA formation is unclear. METHODS: To investigate the function of CRP2 in AAA formation, mice deficient in Apoe (Apoe-/-) or both CRP2 (gene name Csrp2) and Apoe (Csrp2-/-Apoe-/-) were subjected to an angiotensin II (Ang II) infusion model of AAA formation. Aortas were harvested at different time points and histological analysis was performed. Primary VSMCs were generated from Apoe-/- and Csrp2-/-Apoe-/- mouse aortas for in vitro mechanistic studies. RESULTS: Loss of CRP2 attenuated Ang II-induced AAA incidence and severity, accompanied by preserved smooth muscle α-actin expression and reduced elastin degradation, matrix metalloproteinase 2 (MMP2) activity, deposition of collagen, particularly collagen III (Col III), aortic tensile strength, and blood pressure. CRP2 deficiency decreased the baseline MMP2 and Col III expression in VSMCs and mitigated Ang II-induced increases of MMP2 and Col III via blunting Erk1/2 signaling. Rescue experiments were performed by reintroducing CRP2 into Csrp2-/-Apoe-/- VSMCs restored Ang II-induced Erk1/2 activation, MMP2 expression and activity, and Col III levels. CONCLUSIONS: Our results indicate that in response to Ang II stimulation, CRP2 deficiency maintains aortic VSMC density, ECM homeostasis, and structural integrity through Erk1/2-Col III and MMP2 axis and reduces AAA formation. Thus, targeting CRP2 provides a potential therapeutic strategy for AAA.

Identification of HnRNPC as a novel Tau exon 10 splicing factor using RNA antisense purification mass spectrometry.

Alternative splicing in Tau exon 10 generates 3 R- and 4 R-Tau proteoforms, which have equal abundance in healthy adult human brain. Aberrant alternative splicing in Tau exon 10 leads to distortion of the balanced 3 R- and 4 R-Tau expression levels, which is a causal factor to trigger toxic Tau aggregation, neuron dysfunction and patient death in a group of neurodegenerative diseases known as tauopathies. Hence, identification of regulators upstream of the Tau exon 10 splicing events are crucial to understanding pathogenic mechanisms driving tauopathies. In this study, we used RNA Antisense Purification with Mass Spectrometry (RAP-MS) analysis to identify RNA-binding proteins (RBPs) that interact with the Tau pre-mRNA near exon 10. Among the newly identified RBP candidates, we show that knockdown of hnRNPC induces Tau exon 10 skipping whereas overexpression of hnRNPC promotes Tau exon 10 inclusion. In addition, we show that hnRNPC interacts with the poly-uridine (U-tract) sequences in introns 9 and 10 of Tau pre-mRNA. Mutation of these U-tract motifs abolished binding of hnRNPC with Tau pre-mRNA fragment and blocked its impact on Tau exon 10 inclusion. These findings indicate that hnRNPC binds and utilizes these U-tract motifs located in introns 9 and 10 of Tau pre-mRNA to promote Tau exon 10 inclusion. Intriguingly, high hnRNPC expression level is associated with progressive supranuclear palsy (PSP), a sporadic tauopathy with pathological accumulation of Tau species that contain exon 10, which suggests a putative therapeutic role of hnRNPC for PSP treatment. [Figure: see text].

Telemental Health Collaborative Care Medication Management: Implementation and Outcomes.

Introduction: Access to quality mental health medication management (MM) in the United States is limited, even among those with employment-based health insurance. This implementation, feasibility, and outcome study sought to design and evaluate an evidence-based telemental health MM service using a collaborative care model (CoCM). Materials and Methods: CoCM MM was available to adult employees/dependents through their employer benefits, in addition to therapy. Outcomes included Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder-7 (GAD-7) collected at baseline and throughout participation. This analysis was not deemed to be human subjects research by the Western Institutional Review Board. Results: Over 17 months, 212 people enrolled and completed >2 assessments; the enrollees were 58.96% female with average age of 32.00 years (standard deviation [SD] = 7.38). In people with moderate to severe depression or anxiety, PHQ-9 and GAD-7 scores reduced by an average of 7.27 (SD = 4.80) and 6.71 (SD = 5.18) points after at least 12 ± 4 weeks in the program. At 24 ± 4 weeks, the PHQ-9 and GAD-7 reductions were on average 7.17 (SD = 5.00) and 6.03 (SD = 5.37), respectively. Approximately 65.88% of participants with either baseline depression or anxiety had a response on either the PHQ-9 or GAD-7 at 12 ± 4 weeks and 44.71% of participants experienced remission; at 24 ± 4 weeks, 56.41% had response and 41.03% experienced remission. Conclusions: An evidence-based CoCM telemedicine service within an employee behavioral health benefit is feasible and effective in reducing anxiety and depression symptoms when using measurement-based care. Widespread implementation of a benefit like this could expand access to evidence-based mental health MM.

Modeling sparse longitudinal data in early neurodevelopment.

Early childhood is a period marked by rapid brain growth accompanied by cognitive and motor development. However, it remains unclear how early developmental skills relate to neuroanatomical growth across time with no growth quantile trajectories of typical brain development currently available to place and compare individual neuroanatomical development. Even though longitudinal neuroimaging data have become more common, they are often sparse, making dynamic analyses at subject level a challenging task. Using the Principal Analysis through Conditional Expectation (PACE) approach geared towards sparse longitudinal data, we investigate the evolution of gray matter, white matter and cerebrospinal fluid volumes in a cohort of 446 children between the ages of 1 and 120 months. For each child, we calculate their dynamic age-varying association between the growing brain and scores that assess cognitive functioning, applying the functional varying coefficient model. Using local Fréchet regression, we construct age-varying growth percentiles to reveal the evolution of brain development across the population. To further demonstrate its utility, we apply PACE to predict individual trajectories of brain development.

Cost-effectiveness of a Digital Health Intervention for Acute Myocardial Infarction Recovery.

BACKGROUND: Acute myocardial infarction (AMI) is a common cause of hospital admissions, readmissions, and mortality worldwide. Digital health interventions (DHIs) that promote self-management, adherence to guideline-directed therapy, and cardiovascular risk reduction may improve health outcomes in this population. The "Corrie" DHI consists of a smartphone application, smartwatch, and wireless blood pressure monitor to support medication tracking, education, vital signs monitoring, and care coordination. We aimed to assess the cost-effectiveness of this DHI plus standard of care in reducing 30-day readmissions among AMI patients in comparison to standard of care alone. METHODS: A Markov model was used to explore cost-effectiveness from the hospital perspective. The time horizon of the analysis was 1 year, with 30-day cycles, using inflation-adjusted cost data with no discount rate. Currencies were quantified in US dollars, and effectiveness was measured in quality-adjusted life-years (QALYs). The results were interpreted as an incremental cost-effectiveness ratio at a threshold of $100,000 per QALY. Univariate sensitivity and multivariate probabilistic sensitivity analyses tested model uncertainty. RESULTS: The DHI reduced costs and increased QALYs on average, dominating standard of care in 99.7% of simulations in the probabilistic analysis. Based on the assumption that the DHI costs $2750 per patient, use of the DHI leads to a cost-savings of $7274 per patient compared with standard of care alone. CONCLUSIONS: Our results demonstrate that this DHI is cost-saving through the reduction of risk for all-cause readmission following AMI. DHIs that promote improved adherence with guideline-based health care can reduce hospital readmissions and associated costs.

Validation of International Classification of Diseases, Tenth Revision, Clinical Modification Codes for Identifying Cases of Chlamydia and Gonorrhea.

BACKGROUND: While researchers seek to use administrative health data to examine outcomes for individuals with sexually transmitted infections (STIs), the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes used to identify persons with chlamydia and gonorrhea have not been validated. Objectives were to determine the validity of using ICD-10-CM codes to identify individuals with chlamydia and gonorrhea. METHODS: We used data from electronic health records gathered from public and private health systems from October 1, 2015, to December 31, 2016. Patients were included if they were aged 13 to 44 years and received either (1) laboratory testing for chlamydia or gonorrhea or (2) an ICD-10-CM diagnosis of chlamydia, gonorrhea, or an unspecified STI. To validate ICD-10-CM codes, we calculated positive and negative predictive values, sensitivity, and specificity based on the presence of a laboratory test result. We further examined the timing of clinical diagnosis relative to laboratory testing. RESULTS: The positive predictive values for chlamydia, gonorrhea, and unspecified STI ICD-10-CM codes were 87.6%, 85.0%, and 32.0%, respectively. Negative predictive values were high (>92%). Sensitivity for chlamydia diagnostic codes was 10.6%, and gonorrhea was 9.7%. Specificity was 99.9% for both chlamydia and gonorrhea. The date of diagnosis occurred on or after the date of the laboratory result for 84.8% of persons with chlamydia, 91.9% for gonorrhea, and 23.5% for unspecified STI. CONCLUSIONS: Disease-specific ICD-10-CM codes accurately identify persons with chlamydia and gonorrhea. However, low sensitivities suggest that most individuals could not be identified in administrative data alone without laboratory test results.