Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories.

This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QCT) with qualitative approaches to atherosclerotic disease burden codified in the multisociety 2022 CAD-RADS 2.0 Expert Consensus. 105 patients who underwent cardiac computed tomography angiography (CCTA) for chest pain were evaluated by a blinded core laboratory through FDA-cleared software (Cleerly, Denver, CO) that performs AI-QCT through artificial intelligence, analyzing factors such as % stenosis, plaque volume, and plaque composition. AI-QCT plaque volume was then staged by recently validated prognostic thresholds, and compared with CAD-RADS 2.0 clinical methods of plaque evaluation (segment involvement score (SIS), coronary artery calcium score (CACS), visual assessment, and CAD-RADS percent (%) stenosis) by expert consensus blinded to the AI-QCT core lab reads. Average age of subjects were 59 ± 11 years; 44% women, with 50% of patients at CAD-RADS 1-2 and 21% at CAD-RADS 3 and above by expert consensus. AI-QCT quantitative plaque burden staging had excellent agreement of 93% (k = 0.87 95% CI: 0.79-0.96) with SIS. There was moderate agreement between AI-QCT quantitative plaque volume and categories of visual assessment (64.4%; k = 0.488 [0.38-0.60]), and CACS (66.3%; k = 0.488 [0.36-0.61]). Agreement between AI-QCT plaque volume stage and CAD-RADS % stenosis category was also moderate. There was discordance at small plaque volumes. With ongoing validation, these results demonstrate a potential for AI-QCT as a rapid, reproducible approach to quantify total plaque burden.

Development and Validation of a Quantitative Coronary CT Angiography Model for Diagnosis of Vessel-Specific Coronary Ischemia.

BACKGROUND: Noninvasive stress testing is commonly used for detection of coronary ischemia but possesses variable accuracy and may result in excessive health care costs. OBJECTIVES: This study aimed to derive and validate an artificial intelligence-guided quantitative coronary computed tomography angiography (AI-QCT) model for the diagnosis of coronary ischemia that integrates atherosclerosis and vascular morphology measures (AI-QCTISCHEMIA) and to evaluate its prognostic utility for major adverse cardiovascular events (MACE). METHODS: A post hoc analysis of the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) studies was performed. In both studies, symptomatic patients with suspected stable coronary artery disease had prospectively undergone coronary computed tomography angiography (CTA), myocardial perfusion imaging (MPI), SPECT, or PET, fractional flow reserve by CT (FFRCT), and invasive coronary angiography in conjunction with invasive FFR measurements. The AI-QCTISCHEMIA model was developed in the derivation cohort of the CREDENCE study, and its diagnostic performance for coronary ischemia (FFR ≤0.80) was evaluated in the CREDENCE validation cohort and PACIFIC-1. Its prognostic value was investigated in PACIFIC-1. RESULTS: In CREDENCE validation (n = 305, age 64.4 ± 9.8 years, 210 [69%] male), the diagnostic performance by area under the receiver-operating characteristics curve (AUC) on per-patient level was 0.80 (95% CI: 0.75-0.85) for AI-QCTISCHEMIA, 0.69 (95% CI: 0.63-0.74; P < 0.001) for FFRCT, and 0.65 (95% CI: 0.59-0.71; P < 0.001) for MPI. In PACIFIC-1 (n = 208, age 58.1 ± 8.7 years, 132 [63%] male), the AUCs were 0.85 (95% CI: 0.79-0.91) for AI-QCTISCHEMIA, 0.78 (95% CI: 0.72-0.84; P = 0.037) for FFRCT, 0.89 (95% CI: 0.84-0.93; P = 0.262) for PET, and 0.72 (95% CI: 0.67-0.78; P < 0.001) for SPECT. Adjusted for clinical risk factors and coronary CTA-determined obstructive stenosis, a positive AI-QCTISCHEMIA test was associated with an HR of 7.6 (95% CI: 1.2-47.0; P = 0.030) for MACE. CONCLUSIONS: This newly developed coronary CTA-based ischemia model using coronary atherosclerosis and vascular morphology characteristics accurately diagnoses coronary ischemia by invasive FFR and provides robust prognostic utility for MACE beyond presence of stenosis.

Episodic fluid venting from sedimentary basins fueled by pressurized mudstones.

Subsurface sandstone reservoirs sealed by overlying, low-permeability layers provide capacity for long-term sequestration of anthropogenic waste. Leakage can occur if reservoir pressures rise sufficiently to fracture the seal. Such pressures can be generated within the reservoir by vigorous injection of waste or, over thousands of years, by natural processes. In either case, the precise role of intercalated mudstones in the long-term evolution of reservoir pressure remains unclear; these layers have variously been viewed as seals, as pressure sinks, or as pressure sources. Here, we use the geological record of episodic fluid venting in the Levant Basin to provide striking evidence for the pressure-source hypothesis. We use a Bayesian framework to combine recently published venting data, which record critical subsurface pressures since ∼2 Ma, with a stochastic model of pressure evolution to infer a pressure-recharge rate of ∼30 MPa/Myr. To explain this large rate, we quantify and compare a range of candidate mechanisms. We find that poroelastic pressure diffusion from mudstones provides the most plausible explanation for these observations, amplifying the ∼3 MPa/Myr recharge caused primarily by tectonic compression. Since pressurized mudstones are ubiquitous in sedimentary basins, pressure diffusion from mudstones is likely to promote seal failure globally.

RNAseq profiling of blood from patients with coronary artery disease: Signature of a T cell imbalance.

Background: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography either by invasive catheterization (ICA) or computed tomography (CTA). Prior studies employed single-molecule, amplification-independent RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. The present studies employed Illumina RNAseq and network co-expression analysis to identify systematic changes underlying CAD. Methods: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by Illumina total RNA sequencing (RNAseq) to identify transcripts associated with CAD in 177 patients presenting for elective invasive coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs) and to identify patterns of changes through whole genome co-expression network analysis (WGCNA). Results: The correlation between Illumina amplified RNAseq and the prior SeqLL unamplified RNAseq was quite strong (r = 0.87), but there was only 9 % overlap in the DEGs identified. Consistent with the prior RNAseq, the majority (93 %) of DEGs were down-regulated ~1.7-fold in patients with moderate to severe CAD (>20 % stenosis). DEGs were predominantly related to T cells, consistent with known reductions in Tregs in CAD. Network analysis did not identify pre-existing modules with a strong association with CAD, but patterns of T cell dysregulation were evident. DEGs were enriched for transcripts associated with ciliary and synaptic transcripts, consistent with changes in the immune synapse of developing T cells. Conclusions: These studies confirm and extend a novel mRNA signature of a Treg-like defect in CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

Dislocation theory of steady and transient creep of crystalline solids: Predictions for olivine.

In applications critical to the geological, materials, and engineering sciences, deformation occurs at strain rates too small to be accessible experimentally. Instead, extrapolations of empirical relationships are used, leading to epistemic uncertainties in predictions. To address these problems, we construct a theory of the fundamental processes affecting dislocations: storage and recovery. We then validate our theory for olivine deformation. This model explains the empirical relationships among strain rate, applied stress, and dislocation density in disparate laboratory regimes. It predicts the previously unexplained dependence of dislocation density on applied stress in olivine. The predictions of our model for Earth conditions differ from extrapolated empirical relationships. For example, it predicts rapid, transient deformation in the upper mantle, consistent with recent measurements of postseismic creep.

PRR14 organizes H3K9me3-modified heterochromatin at the nuclear lamina.

The eukaryotic genome is organized in three dimensions within the nucleus. Transcriptionally active chromatin is spatially separated from silent heterochromatin, a large fraction of which is located at the nuclear periphery. However, the mechanisms by which chromatin is localized at the nuclear periphery remain poorly understood. Here we demonstrate that Proline Rich 14 (PRR14) protein organizes H3K9me3-modified heterochromatin at the nuclear lamina. We show that PRR14 dynamically associates with both the nuclear lamina and heterochromatin, and is able to reorganize heterochromatin in the nucleus of interphase cells independent of mitosis. We characterize two functional HP1-binding sites within PRR14 that contribute to its association with heterochromatin. We also demonstrate that PPR14 forms an anchoring surface for heterochromatin at the nuclear lamina where it interacts dynamically with HP1-associated chromatin. Our study proposes a model of dynamic heterochromatin organization at the nuclear lamina via the PRR14 tethering protein.

Diabetes, Atherosclerosis, and Stenosis by AI.

OBJECTIVE: This study evaluates the relationship between atherosclerotic plaque characteristics (APCs) and angiographic stenosis severity in patients with and without diabetes. Whether APCs differ based on lesion severity and diabetes status is unknown. RESEARCH DESIGN AND METHODS: We retrospectively evaluated 303 subjects from the Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia (CREDENCE) trial referred for invasive coronary angiography with coronary computed tomographic angiography (CCTA) and classified lesions as obstructive (≥50% stenosed) or nonobstructive using blinded core laboratory analysis of quantitative coronary angiography. CCTA quantified APCs, including plaque volume (PV), calcified plaque (CP), noncalcified plaque (NCP), low-density NCP (LD-NCP), lesion length, positive remodeling (PR), high-risk plaque (HRP), and percentage of atheroma volume (PAV; PV normalized for vessel volume). The relationship between APCs, stenosis severity, and diabetes status was assessed. RESULTS: Among the 303 patients, 95 (31.4%) had diabetes. There were 117 lesions in the cohort with diabetes, 58.1% of which were obstructive. Patients with diabetes had greater plaque burden (P = 0.004). Patients with diabetes and nonobstructive disease had greater PV (P = 0.02), PAV (P = 0.02), NCP (P = 0.03), PAV NCP (P = 0.02), diseased vessels (P = 0.03), and maximum stenosis (P = 0.02) than patients without diabetes with nonobstructive disease. APCs were similar between patients with diabetes with nonobstructive disease and patients without diabetes with obstructive disease. Diabetes status did not affect HRP or PR. Patients with diabetes had similar APCs in obstructive and nonobstructive lesions. CONCLUSIONS: Patients with diabetes and nonobstructive stenosis had an association to similar APCs as patients without diabetes who had obstructive stenosis. Among patients with nonobstructive disease, patients with diabetes had more total PV and NCP.

The Tides of Enceladus' Porous Core.

The inferred density of Enceladus' core, together with evidence of hydrothermal activity within the moon, suggests that the core is porous. Tidal dissipation in an unconsolidated core has been proposed as the main source of Enceladus' geological activity. However, the tidal response of its core has generally been modeled assuming it behaves viscoelastically rather than poroviscoelastically. In this work, we analyze the poroviscoelastic response to better constrain the distribution of tidal dissipation within Enceladus. A poroviscoelastic body has a different tidal response than a viscoelastic one; pressure within the pores alters the stress field and induces a Darcian porous flow. This flow represents an additional pathway for energy dissipation. Using Biot's theory of poroviscoelasticity, we develop a new framework to obtain the tidal response of a spherically symmetric, self-gravitating moon with porous layers and apply it to Enceladus. We show that the boundary conditions at the interface of the core and overlying ocean play a key role in the tidal response. The ocean hinders the development of a large-amplitude Darcian flow, making negligible the Darcian contribution to the dissipation budget. We therefore infer that Enceladus' core can be the source of its geological activity only if it has a low rigidity and a very low viscosity. A future mission to Enceladus could test this hypothesis by measuring the phase lags of tidally induced changes of gravitational potential and surface displacements.

Influence of late Pleistocene sea-level variations on midocean ridge spacing in faulting simulations and a global analysis of bathymetry.

It is established that changes in sea level influence melt production at midocean ridges, but whether changes in melt production influence the pattern of bathymetry flanking midocean ridges has been debated on both theoretical and empirical grounds. To explore the dynamics that may give rise to a sea-level influence on bathymetry, we simulate abyssal hills using a faulting model with periodic variations in melt supply. For 100-ky melt-supply cycles, model results show that faults initiate during periods of amagmatic spreading at half-rates >2.3 cm/y and for 41-ky melt-supply cycles at half-rates >3.8 cm/y. Analysis of bathymetry across 17 midocean ridge regions shows characteristic wavelengths that closely align with the predictions from the faulting model. At intermediate-spreading ridges (half-rates >2.3 cm/y and [Formula: see text]3.8 cm/y) abyssal hill spacing increases with spreading rate at 0.99 km/(cm/y) or 99 ky (n [Formula: see text] 12; 95% CI, 87 to 110 ky), and at fast-spreading ridges (half-rates >3.8 cm/y) spacing increases at 38 ky (n [Formula: see text] 5; 95% CI, 29 to 47 ky). Including previously published analyses of abyssal-hill spacing gives a more precise alignment with the primary periods of Pleistocene sea-level variability. Furthermore, analysis of bathymetry from fast-spreading ridges shows a highly statistically significant spectral peak (P < 0.01) at the 1/(41-ky) period of Earth's variations in axial tilt. Faulting models and observations both support a linkage between glacially induced sea-level change and the fabric of the sea floor over the late Pleistocene.

Artificial Intelligence Advancements in the Cardiovascular Imaging of Coronary Atherosclerosis.

Coronary artery disease is a leading cause of death worldwide. There has been a myriad of advancements in the field of cardiovascular imaging to aid in diagnosis, treatment, and prevention of coronary artery disease. The application of artificial intelligence in medicine, particularly in cardiovascular medicine has erupted in the past decade. This article serves to highlight the highest yield articles within cardiovascular imaging with an emphasis on coronary CT angiography methods for % stenosis evaluation and atherosclerosis quantification for the general cardiologist. The paper finally discusses the evolving paradigm of implementation of artificial intelligence in real world practice.

Relationship Between Social Determinants of Health and Antihypertensive Medication Adherence in a Medicaid Cohort.

BACKGROUND: Little is known about the relationship between social determinants of health (SDH) and medication adherence among Medicaid beneficiaries with hypertension. METHODS: We conducted a posthoc subgroup analysis of 3044 adult Medicaid beneficiaries who enrolled in a parent prospective cohort study and had a diagnosis of hypertension based on their Medicaid claims during a 24-month period before study enrollment. We calculated the proportion of days covered by at least one antihypertensive medication during the first 12 months after study enrollment using the prescription claims data. We measured numerous SDH at the time of study enrollment and we categorized our hypertension cohort into 4 social risk groups based on their response profiles to the SDH variables. We compared the mean proportion of days covered by the different levels of the SDH factors. We modeled the odds of being covered by an antihypertensive medication daily throughout the follow-up period by social risk group, adjusted for age, sex, and disease severity using a generalized linear model. RESULTS: The nonrandom sample was predominately Black (93%), female (62%) and had completed high school (77%). The mean proportion of days covered varied significantly by different SDH, such as food insecurity (49%-56%), length of time living at present place (47%-57%), smoking status (50%-56%), etc. Social risk group was a significant predictor of medication adherence. Participants in the 2 groups with the most social risks were 36% (adjusted odds ratio=0.64 [95% CI, 0.53-0.78]) and 20% (adjusted odds ratio=0.80 [95% CI, 0.70-0.93]) less adherent to their hypertension therapy compared with participants in the group with the fewest social risks. CONCLUSIONS: Social risks are associated with lower antihypertensive medication adherence in the Medicaid population.

RNA sequencing of blood in coronary artery disease: involvement of regulatory T cell imbalance.

BACKGROUND: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography. Surprisingly, despite well-established clinical indications, up to 40% of the one million invasive cardiac catheterizations return a result of 'no blockage'. The present studies employed RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. METHODS: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by single-molecule sequencing of RNA (RNAseq) to identify transcripts associated with CAD (TRACs) in a discovery group of 96 patients presenting for elective coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs). RESULTS: Surprisingly, 98% of DEGs/TRACs were down-regulated ~ 1.7-fold in patients with mild to severe CAD (> 20% stenosis). The TRACs were independent of comorbid risk factors for CAD, such as sex, hypertension, and smoking. Bioinformatic analysis identified an enrichment in transcripts such as FoxP1, ICOSLG, IKZF4/Eos, SMYD3, TRIM28, and TCF3/E2A that are likely markers of regulatory T cells (Treg), consistent with known reductions in Tregs in CAD. A validation cohort of 80 patients confirmed the overall pattern (92% down-regulation) and supported many of the Treg-related changes. TRACs were enriched for transcripts associated with stress granules, which sequester RNAs, and ciliary and synaptic transcripts, possibly consistent with changes in the immune synapse of developing T cells. CONCLUSIONS: These studies identify a novel mRNA signature of a Treg-like defect in CAD patients and provides a blueprint for a diagnostic test for CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

CT ​Evaluation ​by ​Artificial ​Intelligence ​for ​Atherosclerosis, Stenosis and Vascular ​Morphology ​(CLARIFY): ​A ​Multi-center, international study.

BACKGROUND: Atherosclerosis evaluation by coronary computed tomography angiography (CCTA) is promising for coronary artery disease (CAD) risk stratification, but time consuming and requires high expertise. Artificial Intelligence (AI) applied to CCTA for comprehensive CAD assessment may overcome these limitations. We hypothesized AI aided analysis allows for rapid, accurate evaluation of vessel morphology and stenosis. METHODS: This was a multi-site study of 232 patients undergoing CCTA. Studies were analyzed by FDA-cleared software service that performs AI-driven coronary artery segmentation and labeling, lumen and vessel wall determination, plaque quantification and characterization with comparison to ground truth of consensus by three L3 readers. CCTAs were analyzed for: % maximal diameter stenosis, plaque volume and composition, presence of high-risk plaque and Coronary Artery Disease Reporting & Data System (CAD-RADS) category. RESULTS: AI performance was excellent for accuracy, sensitivity, specificity, positive predictive value and negative predictive value as follows: >70% stenosis: 99.7%, 90.9%, 99.8%, 93.3%, 99.9%, respectively; >50% stenosis: 94.8%, 80.0%, 97.0, 80.0%, 97.0%, respectively. Bland-Altman plots depict agreement between expert reader and AI determined maximal diameter stenosis for per-vessel (mean difference -0.8%; 95% CI 13.8% to -15.3%) and per-patient (mean difference -2.3%; 95% CI 15.8% to -20.4%). L3 and AI agreed within one CAD-RADS category in 228/232 (98.3%) exams per-patient and 923/924 (99.9%) vessels on a per-vessel basis. There was a wide range of atherosclerosis in the coronary artery territories assessed by AI when stratified by CAD-RADS distribution. CONCLUSIONS: AI-aided approach to CCTA interpretation determines coronary stenosis and CAD-RADS category in close agreement with consensus of L3 expert readers. There was a wide range of atherosclerosis identified through AI.

HeLa TI cell-based assay as a new approach to screen for chemicals able to reactivate the expression of epigenetically silenced genes.

Chemicals reactivating epigenetically silenced genes target diverse classes of enzymes, including DNMTs, HDACs, HMTs and BET protein family members. They can strongly influence the expression of genes and endogenous retroviral elements with concomitant dsRNA synthesis and massive transcription of LTRs. Chemicals reactivating gene expression may cause both beneficial effects in cancer cells and may be hazardous by promoting carcinogenesis. Among chemicals used in medicine and commerce, only a small fraction has been studied with respect to their influence on epigenetic silencing. Screening of chemicals reactivating silent genes requires adequate systems mimicking whole-genome processes. We used a HeLa TSA-inducible cell population (HeLa TI cells) obtained by retroviral infection of a GFP-containing vector followed by several rounds of cell sorting for screening purposes. Previously, the details of GFP epigenetic silencing in HeLa TI cells were thoroughly described. Herein, we show that the epigenetically repressed gene GFP is reactivated by 15 agents, including HDAC inhibitors-vorinostat, sodium butyrate, valproic acid, depsipeptide, pomiferin, and entinostat; DNMT inhibitors-decitabine, 5-azacytidine, RG108; HMT inhibitors-UNC0638, BIX01294, DZNep; a chromatin remodeler-curaxin CBL0137; and BET inhibitors-JQ-1 and JQ-35. We demonstrate that combinations of epigenetic modulators caused a significant increase in cell number with reactivated GFP compared to the individual effects of each agent. HeLa TI cells are competent to metabolize xenobiotics and possess constitutively expressed and inducible cytochrome P450 mono-oxygenases involved in xenobiotic biotransformation. Thus, HeLa TI cells may be used as an adequate test system for the extensive screening of chemicals, including those that must be metabolically activated. Studying the additional metabolic activation of xenobiotics, we surprisingly found that the rat liver S9 fraction, which has been widely used for xenobiotic activation in genotoxicity tests, reactivated epigenetically silenced genes. Applying the HeLa TI system, we show that N-nitrosodiphenylamine and N-nitrosodimethylamine reactivate epigenetically silenced genes, probably by affecting DNA methylation.

The evolving role of coronary CT angiography in Acute Coronary Syndromes.

In the United States, non-obstructive coronary disease has been on the rise, and each year, nearly one million adults suffer myocardial infarction, 70% of which are non-ST-segment elevation myocardial infarction (NSTEMI). In addition, approximately 15% of patients suffering NSTEMI will have subsequent readmission for a recurrent acute coronary syndrome (ACS). While invasive angiography remains the standard of care in the diagnostic and therapeutic approach to these patients, these methods have limitations that include procedural complications, uncertain specificity in diagnosis of the culprit lesion in patients with multi-vessel coronary artery disease (CAD), and challenges in following coronary disease over time. The role of coronary computed tomography angiography (CCTA) for evaluating patients with both stable and acute chest pain has seen a paramount upshift in the last decade. This paper reviews the established role of CCTA for the rapid exclusion of obstructive plaque in troponin negative acute chest pain, while exploring opportunities to address challenges in the current approach to evaluating NSTEMI.

Contemporary Cardiovascular Imaging Advancements and Social Media.

PURPOSE OF REVIEW: Social media (SoMe) as a means of knowledge dissemination has grown significantly in cardiovascular imaging in recent years. This media platform allows for a free exchange of ideas, the development of new communities, and the ability to disseminate advancements rapidly. While the social media platforms offer limitless potential, their public domain necessitates several important suggestions around best practices. RECENT FINDINGS: In cardiovascular imaging, specific hashtags have emerged to encompass the major modalities to include #EchoFirst, #YesCCT, #WhyCMR, and #CVNuc. Cardiovascular imaging journals have established major presences in the social media space as an avenue to present novel, high-quality, peer-reviewed content to new audiences. SUMMARY: This review paper aims to introduce basic concepts in social media and cardiovascular imaging while highlighting recent topics of high importance, influence, and attention in cardiovascular imaging to include the ISCHEMIA trial, COVID-19, structural imaging, and multimodality advances from throughout 2020.

The PRR14 heterochromatin tether encodes modular domains that mediate and regulate nuclear lamina targeting.

A large fraction of epigenetically silent heterochromatin is anchored to the nuclear periphery via 'tethering proteins' that function to bridge heterochromatin and the nuclear membrane or nuclear lamina. We previously identified a human tethering protein, PRR14, that binds heterochromatin through an N-terminal domain, but the mechanism and regulation of nuclear lamina association remained to be investigated. Here we identify an evolutionarily conserved PRR14 nuclear lamina binding domain (LBD) that is both necessary and sufficient for positioning of PRR14 at the nuclear lamina. We show that PRR14 associates dynamically with the nuclear lamina, and provide evidence that such dynamics are regulated through phosphorylation and dephosphorylation of the LBD. Furthermore, we identify a PP2A phosphatase recognition motif within the evolutionarily conserved C-terminal Tantalus domain of PRR14. Disruption of this motif affects PRR14 localization to the nuclear lamina. The overall findings demonstrate a heterochromatin anchoring mechanism whereby the PRR14 tether simultaneously binds heterochromatin and the nuclear lamina through two separable modular domains. Our findings also describe an optimal PRR14 LBD fragment that could be used for efficient targeting of fusion proteins to the nuclear lamina.

Life Care Planning - a Practical Illustration.

Life care planning is a method of estimating future care costs for patients with catastrophic disabilities. The life care planner determines an annual budget for care, including further medical and rehabilitative interventions, durable medical goods, disposable medical goods and supplies, and recreational equipment. After determining an annual budget, the life care planner must use scientifically sound methods of determining the patient's life expectancy in order to create a lifetime budget.