Immunoengineering can overcome the glycocalyx armour of cancer cells.

Cancer cell glycocalyx is a major line of defence against immune surveillance. However, how specific physical properties of the glycocalyx are regulated on a molecular level, contribute to immune evasion and may be overcome through immunoengineering must be resolved. Here we report how cancer-associated mucins and their glycosylation contribute to the nanoscale material thickness of the glycocalyx and consequently modulate the functional interactions with cytotoxic immune cells. Natural-killer-cell-mediated cytotoxicity is inversely correlated with the glycocalyx thickness of the target cells. Changes in glycocalyx thickness of approximately 10 nm can alter the susceptibility to immune cell attack. Enhanced stimulation of natural killer and T cells through equipment with chimeric antigen receptors can improve the cytotoxicity against mucin-bearing target cells. Alternatively, cytotoxicity can be enhanced through engineering effector cells to display glycocalyx-editing enzymes, including mucinases and sialidases. Together, our results motivate the development of immunoengineering strategies that overcome the glycocalyx armour of cancer cells.

Bi-directional nucleosome sliding by the Chd1 chromatin remodeler integrates intrinsic sequence-dependent and ATP-dependent nucleosome positioning.

Chromatin remodelers use a helicase-type ATPase motor to shift DNA around the histone core. Although not directly reading out the DNA sequence, some chromatin remodelers exhibit a sequence-dependent bias in nucleosome positioning, which presumably reflects properties of the DNA duplex. Here, we show how nucleosome positioning by the Chd1 remodeler is influenced by local DNA perturbations throughout the nucleosome footprint. Using site-specific DNA cleavage coupled with next-generation sequencing, we show that nucleosomes shifted by Chd1 can preferentially localize DNA perturbations - poly(dA:dT) tracts, DNA mismatches, and single-nucleotide insertions - about a helical turn outside the Chd1 motor domain binding site, super helix location 2 (SHL2). This phenomenon occurs with both the Widom 601 positioning sequence and the natural +1 nucleosome sequence from the Saccharomyces cerevisiae SWH1 gene. Our modeling indicates that localization of DNA perturbations about a helical turn outward from SHL2 results from back-and-forth sliding due to remodeler action on both sides of the nucleosome. Our results also show that barrier effects from DNA perturbations can be extended by the strong phasing of nucleosome positioning sequences.

Agreeing to Stop: Reliable Latency-Adaptive Decision Making via Ensembles of Spiking Neural Networks.

Spiking neural networks (SNNs) are recurrent models that can leverage sparsity in input time series to efficiently carry out tasks such as classification. Additional efficiency gains can be obtained if decisions are taken as early as possible as a function of the complexity of the input time series. The decision on when to stop inference and produce a decision must rely on an estimate of the current accuracy of the decision. Prior work demonstrated the use of conformal prediction (CP) as a principled way to quantify uncertainty and support adaptive-latency decisions in SNNs. In this paper, we propose to enhance the uncertainty quantification capabilities of SNNs by implementing ensemble models for the purpose of improving the reliability of stopping decisions. Intuitively, an ensemble of multiple models can decide when to stop more reliably by selecting times at which most models agree that the current accuracy level is sufficient. The proposed method relies on different forms of information pooling from ensemble models and offers theoretical reliability guarantees. We specifically show that variational inference-based ensembles with p-variable pooling significantly reduce the average latency of state-of-the-art methods while maintaining reliability guarantees.

Impact of Trimetazidine on the Incident Heart Failure After Coronary Artery Revascularization.

ABSTRACT: Abnormal myocardial metabolism is a common pathophysiological process underlying ischemic heart disease and heart failure (HF). Trimetazidine is an antianginal agent with a unique mechanism of action that regulates myocardial energy metabolism and might have a beneficial effect in preventing HF in patients undergoing myocardial revascularization. We aimed to evaluate the potential benefit of trimetazidine in preventing incident hospitalization for HF after myocardial revascularization. Using the common data model, we identified patients without prior HF undergoing myocardial revascularization from 8 hospital databases in Korea. To compare clinical outcomes using trimetazidine, database-level hazard ratios (HRs) were estimated using large-scale propensity score matching for each database and pooled using a random-effects model. The primary outcome was incident hospitalization for HF. The secondary outcome of interest was major adverse cardiac events (MACEs). After propensity score matching, 6724 and 11,211 patients were allocated to trimetazidine new-users and nonusers, respectively. There was no significant difference in the incidence of hospitalization for HF between the 2 groups (HR: 1.08, 95% confidence interval [CI], 0.88-1.31; P = 0.46). The risk of MACE also did not differ between the 2 groups (HR: 1.07, 95% CI, 0.98-1.16; P = 0.15). In conclusion, the use of trimetazidine did not reduce the risk of hospitalization for HF or MACE in patients undergoing myocardial revascularization. Therefore, the role of trimetazidine in contemporary clinical practice cannot be expanded beyond its current role as an add-on treatment for symptomatic angina.

Photosensitizing deep-seated cancer cells with photoprotein-conjugated upconversion nanoparticles.

To resolve the problem of target specificity and light transmission to deep-seated tissues in photodynamic therapy (PDT), we report a cancer cell-targeted photosensitizer using photoprotein-conjugated upconversion nanoparticles (UCNPs) with high target specificity and efficient light transmission to deep tissues. Core-shell UCNPs with low internal energy back transfer were conjugated with recombinant proteins that consists of a photosensitizer (KillerRed; KR) and a cancer cell-targeted lead peptide (LP). Under near infrared (NIR)-irradiating condition, the UCNP-KR-LP generated superoxide anion radicals as reactive oxygen species via NIR-to-green light conversion and exhibited excellent specificity to target cancer cells through receptor-mediated cell adhesion. Consequently, this photosensitizing process facilitated rapid cell death in cancer cell lines (MCF-7, MDA-MB-231, and U-87MG) overexpressing integrin beta 1 (ITGB1) receptors but not in a cell line (SK-BR-3) with reduced ITGB1 expression and a non-invasive normal breast cell line (MCF-10A). In contrast to green light irradiation, NIR light irradiation exhibited significant PDT efficacy in cancer cells located beneath porcine skin tissues up to a depth of 10 mm, as well as in vivo tumor xenograft mouse models. This finding suggests that the designed nanocomposite is useful for sensing and targeting various deep-seated tumors.

DNA sequence and methylation prescribe the inside-out conformational dynamics and bending energetics of DNA minicircles.

Eukaryotic genome and methylome encode DNA fragments' propensity to form nucleosome particles. Although the mechanical properties of DNA possibly orchestrate such encoding, the definite link between 'omics' and DNA energetics has remained elusive. Here, we bridge the divide by examining the sequence-dependent energetics of highly bent DNA. Molecular dynamics simulations of 42 intact DNA minicircles reveal that each DNA minicircle undergoes inside-out conformational transitions with the most likely configuration uniquely prescribed by the nucleotide sequence and methylation of DNA. The minicircles' local geometry consists of straight segments connected by sharp bends compressing the DNA's inward-facing major groove. Such an uneven distribution of the bending stress favors minimum free energy configurations that avoid stiff base pair sequences at inward-facing major grooves. Analysis of the minicircles' inside-out free energy landscapes yields a discrete worm-like chain model of bent DNA energetics that accurately account for its nucleotide sequence and methylation. Experimentally measuring the dependence of the DNA looping time on the DNA sequence validates the model. When applied to a nucleosome-like DNA configuration, the model quantitatively reproduces yeast and human genomes' nucleosome occupancy. Further analyses of the genome-wide chromatin structure data suggest that DNA bending energetics is a fundamental determinant of genome architecture.

Manipulating Nanoparticle Aggregates Regulates Receptor-Ligand Binding in Macrophages.

The receptor-ligand interactions in cells are dynamically regulated by modulation of the ligand accessibility. In this study, we utilize size-tunable magnetic nanoparticle aggregates ordered at both nanometer and atomic scales. We flexibly anchor magnetic nanoparticle aggregates of tunable sizes over the cell-adhesive RGD ligand (Arg-Gly-Asp)-active material surface while maintaining the density of dispersed ligands accessible to macrophages at constant. Lowering the accessible ligand dispersity by increasing the aggregate size at constant accessible ligand density facilitates the binding of integrin receptors to the accessible ligands, which promotes the adhesion of macrophages. In high ligand dispersity, distant magnetic manipulation to lift the aggregates (which increases ligand accessibility) stimulates the binding of integrin receptors to the accessible ligands available under the aggregates to augment macrophage adhesion-mediated pro-healing polarization both in vitro and in vivo. In low ligand dispersity, distant control to drop the aggregates (which decreases ligand accessibility) repels integrin receptors away from the aggregates, thereby suppressing integrin receptor-ligand binding and macrophage adhesion, which promotes inflammatory polarization. Here, we present "accessible ligand dispersity" as a novel fundamental parameter that regulates receptor-ligand binding, which can be reversibly manipulated by increasing and decreasing the ligand accessibility. Limitless tuning of nanoparticle aggregate dimensions and morphology can offer further insight into the regulation of receptor-ligand binding in host cells.

Protein interactome and cell-type expression analyses reveal that cytoplasmic FMR1-interacting protein 1 (CYFIP1), but not CYFIP2, associates with astrocytic focal adhesion.

The two members of the cytoplasmic FMR1-interacting protein family, CYFIP1 and CYFIP2, are evolutionarily conserved multifunctional proteins whose defects are associated with distinct types of brain disorders. Even with high sequence homology between CYFIP1 and CYFIP2, several lines of evidence indicate their different functions in the brain; however, the underlying mechanisms remain largely unknown. Here, we performed reciprocal immunoprecipitation experiments using CYFIP1-2 × Myc and CYFIP2-3 × Flag knock-in mice and found that CYFIP1 and CYFIP2 are not significantly co-immunoprecipitated with each other in the knock-in brains compared with negative control wild-type (WT) brains. Moreover, CYFIP1 and CYFIP2 showed different size distributions by size-exclusion chromatography of WT mouse brains. Specifically, mass spectrometry-based analysis of CYFIP1-2 × Myc knock-in brains identified 131 proteins in the CYFIP1 interactome. Comparison of the CYFIP1 interactome with the previously identified brain region- and age-matched CYFIP2 interactome, consisting of 140 proteins, revealed only eight common proteins. Investigations using single-cell RNA-sequencing databases suggested non-neuronal cell- and neuron-enriched expression of Cyfip1 and Cyfip2, respectively. At the protein level, CYFIP1 was detected in both neurons and astrocytes, while CYFIP2 was detected only in neurons, suggesting the predominant expression of CYFIP1 in astrocytes. Bioinformatic characterization of the CYFIP1 interactome, and co-expression analysis of Cyfip1 with astrocytic genes, commonly linked CYFIP1 with focal adhesion proteins. Immunocytochemical analysis and proximity ligation assay suggested partial co-localization of CYFIP1 and focal adhesion proteins in cultured astrocytes. Together, these results suggest a CYFIP1-specific association with astrocytic focal adhesion, which may contribute to the different brain functions and dysfunctions of CYFIP1 and CYFIP2. Cover Image for this issue: https://doi.org/10.1111/jnc.15410.

GalaxyWater-CNN: Prediction of Water Positions on the Protein Structure by a 3D-Convolutional Neural Network.

Proteins interact with numerous water molecules to perform their physiological functions in biological organisms. Most water molecules act as solvent media; hence, their roles may be considered implicitly in theoretical treatments of protein structure and function. However, some water molecules interact intimately with proteins and require explicit treatment to understand their effects. Most physics-based computational methods are limited in their ability to accurately locate water molecules on protein surfaces because of inaccurate energy functions. Instead of relying on an energy function, this study attempts to learn the locations of water molecules from structural data. GalaxyWater-convolutional neural network (CNN) predicts water positions on protein chains, protein-protein interfaces, and protein-compound binding sites using a 3D-CNN model that is trained to generate a water score map on a given protein structure. The training data are compiled from high-resolution protein crystal structures resolved together with water molecules. GalaxyWater-CNN shows improved water prediction performance both in the coverage of crystal water molecules and in the accuracy of the predicted water positions when compared with previous energy-based methods. This method shows a superior performance in predicting water molecules that form hydrogen-bond networks precisely. The web service and the source code of this water prediction method are freely available at https://galaxy.seoklab.org/gwcnn and https://github.com/seoklab/GalaxyWater-CNN, respectively.

Serum phosphorus and subclinical coronary atherosclerosis in asymptomatic subjects without kidney dysfunction.

BACKGROUND AND AIMS: There is limited data on the association between serum phosphorus concentration (SPC) and subclinical coronary atherosclerosis in low-risk asymptomatic subjects without kidney dysfunction. MATERIALS AND METHODS: We retrospectively analyzed 1,636 Korean individuals (mean age 52.6 ± 7.6 years; males: 712 (43.5%)) without traditional cardiovascular risk factors (CVRFs) and kidney dysfunction who voluntarily underwent coronary computed tomography angiography (CCTA) as part of a general health examination. Traditional CVRFs were defined as follows: systolic/diastolic blood pressure ≥ 140/90 mmHg, fasting blood glucose ≥ 126 mg/dL, hemoglobin A1c ≥ 6.5%, total cholesterol ≥ 240 mg/dL, low-density lipoprotein cholesterol ≥ 160 mg/dL, high-density lipoprotein cholesterol < 40 mg/dL, body mass index ≥ 25.0 kg/m2, currently smoking, and medical history of hypertension, diabetes, and hyperlipidemia. Study participants were stratified into tertiles according to their SPC levels (≤ 3.2, 3.3 - 3.6, and ≥ 3.7 mg/dL). RESULTS: 297 (18.2%) study participants had subclinical coronary atherosclerosis, characterized by any coronary plaque on CCTA. In multivariable regression analysis, the risk of subclinical coronary atherosclerosis increased in the second (odds ratio (OR): 1.629; 95% confidence interval (CI): 1.149 - 2.308; p = 0.006) and third (OR: 1.645; 95% CI: 1.093 - 2.476; p = 0.017) SPC tertiles compared to the first SPC tertile. In addition, the risk of calcified plaque increased in the second (OR: 1.605; 95% CI: 1.124 - 2.292; p = 0.009) and third (OR 1.790; 95% CI 1.179 - 2.716; p = 0.006) SPC tertiles. CONCLUSION: In low-risk asymptomatic Korean individuals without kidney dysfunction, a higher SPC level was an independent predictor of subclinical coronary atherosclerosis.

Supporting decision-making regarding fertility preservation in patients with cancer: An integrative review.

INTRODUCTION: Recent reproductive technology for cancer patients has provided multiple options to preserve their fertility. Preserving fertility can increase quality of life of cancer patients. However, medical service providers and patients face difficulties in the decision-making process for the fertility preserving treatment because studies focusing on the concept of decision-making and various intervention materials are lack. This review aims to identify the attributes of interventions of studies on decision-making support interventions in cancer patients considering fertility preservation and provide best evidence for health professionals. METHODS: PubMed, CINAHL, Embase, Cochrane CENTRAL and DBpia databases were searched. An integrated review of the literature was conducted using Whittemore and Knafl's methodology. RESULTS: The search identified 1008 articles, of which 11 studies met eligible criteria. The attributes of the interventions were (1) provision of detailed and practical information of fertility preservation, (2) nondirective approaches to help patients to value their judgements, (3) emphasis on interactions through individualised consultations, (4) establishing connections with available resources and (5) reinforcement of decision-making support resources. CONCLUSION: Health professionals must acquire current knowledge and ethical and legal standards of fertility preservation and pass this information on to patients before the formation of fertility preservation decision-making support networks within the hospital and health systems.

CeRA-eSP: Code-Expanded Random Access to Enhance Success Probability of Massive MTC.

With the growing interest in the Internet of Things (IoT), research on massive machine-type communication (mMTC) services is being actively promoted. Because mMTC services are required to serve a large number of devices simultaneously, a lack of resources during initial access can be a significant problem when providing mMTC services in cellular networks. Various studies on efficient preamble transmission have been conducted to solve the random access problem of mMTC services. However, supporting a large number of devices simultaneously with limited resources is a challenging problem. In this study, we investigate code-expanded random access (CeRA), which extends the limited preamble resources to the code domain to decrease the high collision rate. To solve the existing CeRA phantom codeword and physical uplink shared channel (PUSCH) resource shortage problems, we propose an optimal preamble codeword set selection algorithm based on mathematical analysis. The simulation results indicate that the proposed code-expanded random access scheme to enhance success probability (CeRA-eSP) achieves a higher random access success rate with a lower access delay compared to the existing random access schemes.

Speeding up Training of Linear Predictors for Multi-Antenna Frequency-Selective Channels via Meta-Learning.

An efficient data-driven prediction strategy for multi-antenna frequency-selective channels must operate based on a small number of pilot symbols. This paper proposes novel channel-prediction algorithms that address this goal by integrating transfer and meta-learning with a reduced-rank parametrization of the channel. The proposed methods optimize linear predictors by utilizing data from previous frames, which are generally characterized by distinct propagation characteristics, in order to enable fast training on the time slots of the current frame. The proposed predictors rely on a novel long short-term decomposition (LSTD) of the linear prediction model that leverages the disaggregation of the channel into long-term space-time signatures and fading amplitudes. We first develop predictors for single-antenna frequency-flat channels based on transfer/meta-learned quadratic regularization. Then, we introduce transfer and meta-learning algorithms for LSTD-based prediction models that build on equilibrium propagation (EP) and alternating least squares (ALS). Numerical results under the 3GPP 5G standard channel model demonstrate the impact of transfer and meta-learning on reducing the number of pilots for channel prediction, as well as the merits of the proposed LSTD parametrization.

Angiotensin-Converting Enzyme Inhibitor-based Versus Angiotensin Receptor Blocker-based Optimal Medical Therapy After Percutaneous Coronary Intervention: A Nationwide Cohort Study.

ABSTRACT: Optimal medical therapy (OMT) plays a crucial role in the secondary prevention of established coronary artery disease. The renin-angiotensin system (RAS) is an important target of OMT. However, there is limited evidence on whether there is any difference in the combined effect of OMT according to the classes of RAS blockade [angiotensin-converting enzyme inhibitor (ACEI) vs. angiotensin receptor blocker (ARB)]. Based on the nationwide National Health Insurance database in South Korea, 39,096 patients who received OMT after percutaneous coronary intervention between July 2013 and June 2017 were enrolled. Patients were stratified into either acute myocardial infarction (AMI) or angina cohort and analyzed according to the class of RAS blockade included in OMT at discharge (ACEI vs. ARB). The primary end point was all-cause mortality. The study population had a median follow-up of 2.3 years (interquartile range, 1.3-3.3 years). In the propensity score-matched AMI cohort (8219 pairs), the risk for all-cause mortality was significantly lower in patients with ACEI-based OMT than in those with ARB-based OMT (hazard ratio 0.83 of ACEI, 95% confidence interval 0.73-0.94, P = 0.003). However, in the propensity score-matched angina cohort (6693 pairs), the mortality risk was comparable, regardless of the class of RAS blockade (hazard ratio 1.13, 95 confidence interval 0.99-1.29, P = 0.08). In conclusion, in this nationwide cohort study involving patients receiving OMT after percutaneous coronary intervention, ACEI-based OMT was associated with a significantly lower risk of all-cause mortality in patients with AMI in comparison with ARB, but not in those with angina.

GalaxyWater-wKGB: Prediction of Water Positions on Protein Structure Using wKGB Statistical Potential.

Proteins fold and function in water, and protein-water interactions play important roles in protein structure and function. In computational studies on protein structure and interaction, the effect of water is considered either implicitly or explicitly. Implicit water models are frequently used in protein structure prediction and docking because they are computationally much more efficient than explicit water models, which are often employed in molecular dynamics (MD) simulations. However, implicit water models that treat water as a continuous solvent medium cannot account for specific atomistic protein-water interactions that are critical for structure formation and interactions with other molecules. Various methods for predicting water molecules that form specific atomistic interactions with proteins have been developed. Methods involving MD simulations or the integral equation theory tend to produce more accurate results at a higher computational cost than simple geometry- or energy-based methods. Here, we present a novel method for predicting water positions on a protein surface called GalaxyWater-wKGB, which is based on a statistical potential, a water knowledge-based potential based on the generalized Born model (wKGB). This method is accurate and rapid because it does not require conformational sampling or iterative computation owing to the effective statistical treatment employed to derive the potential. The statistical potential describes specific protein atom-water interactions more accurately than conventional potentials by considering the dependence on the degree of solvent accessibility of protein atoms as well as on protein atom-water distances and orientations. The introduction of solvent accessibility allows effective consideration of competing nonspecific protein-water and intraprotein interactions. When tested on high-resolution protein crystal structures, this method could recover similar or larger fractions of crystallographic water 180 times faster than the sophisticated integral equation theory, 3D-RISM. A web service of this water prediction method is freely available at http://galaxy.seoklab.org/wkgb.

Effect of Brain and Pulse Waves on Safety Consciousness and Safety Commitment of Workers at Construction Sites.

Even though individual mental and health status largely affects the safety in industrial sites, most studies for preventing industrial accidents are mainly focused on external factors such as regulations, education, etc. In this study, the effect of individual factors on safety (i.e., safety consciousness and safety commitment) was analyzed by collecting brainwave and pulse data at construction sites where industrial accidents have occurred with the highest percentage. The effects of brain stress, concentration, brain activity, and left and right brain imbalance on safety accidents were evaluated through brain wave measurements. In addition, the effects of cumulative fatigue, physical vitality, autonomic nerve health, and autonomic balance were identified through pulse wave measurements. Data were acquired for 180 construction workers at various construction sites, and the workers were classified into three grades according to factors that affected safety accidents at construction sites. Then, the safety consciousness and safety commitment levels of workers corresponding to each grade of the influence factors were evaluated by conducting a questionnaire on safety consciousness and safety commitment. As a result, the characteristics of brain and pulse waves required to improve safety consciousness and safety commitment ability of workers at construction sites were explored.

Surface Charge-Dependent Cytotoxicity of Plastic Nanoparticles in Alveolar Cells under Cyclic Stretches.

Polystyrene nanoparticles (PS-NPs) derived from both environmental and occupational sources are an important class of ultrafine particles associated with human pulmonary disorders. The effects of surface charges of particle internalization and toxicity to alveolar cells, especially under conditions comparable to those found during breathing, have not been examined. Here, we applied cyclic stretches (CS) to human alveolar cells during nanoparticle exposure and show an enhanced accumulation of positively charged polystyrene nanoparticles as compared to similar negatively charged particles. The cellular uptake of the positive particles into live cells was visualized with three-dimensional optical diffraction tomography (3-D ODT). The simultaneous application of both periodic stretching as well as positively charged nanoparticles led to blebbing morphology and activation of apoptotic signaling compared to control cells. Our findings provide a better understanding of how surface charge mediates the uptake and toxicity of nanoplastics under the dynamical mechanical conditions relevant for breathing exposures.

Triglyceride glucose index is a useful marker for predicting subclinical coronary artery disease in the absence of traditional risk factors.

BACKGROUND: Atherosclerotic cardiovascular (CV) events commonly occur in individuals with a low CV risk burden. This study evaluated the ability of the triglyceride glucose (TyG) index to predict subclinical coronary artery disease (CAD) in asymptomatic subjects without traditional CV risk factors (CVRFs). METHODS: This retrospective, cross-sectional, and observational study evaluated the association of TyG index with CAD in 1250 (52.8 ± 6.5 years, 46.9% male) asymptomatic individuals without traditional CVRFs (defined as systolic/diastolic blood pressure ≥ 140/90 mmHg; fasting glucose ≥126 mg/dL; total cholesterol ≥240 mg/dL; low-density lipoprotein cholesterol ≥160 mg/dL; high-density lipoprotein cholesterol < 40 mg/dL; body mass index ≥25.0 kg/m2; current smoking; and previous medical history of hypertension, diabetes, or dyslipidemia). CAD was defined as the presence of any coronary plaque on coronary computed tomographic angiography. The participants were divided into three groups based on TyG index tertiles. RESULTS: The prevalence of CAD increased with elevating TyG index tertiles (group I: 14.8% vs. group II: 19.3% vs. group III: 27.6%; P < 0.001). Multivariate logistic regression models showed that TyG index was associated with an increased risk of CAD (odds ratio [OR] 1.473, 95% confidence interval [CI] 1.026-2.166); especially non-calcified (OR 1.581, 95% CI 1.002-2.493) and mixed plaques (OR 2.419, 95% CI 1.051-5.569) (all P < 0.05). The optimal TyG index cut-off for predicting CAD was 8.44 (sensitivity 47.9%; specificity 68.5%; area under the curve 0.600; P < 0.001). The predictive value of this cut-off improved after considering the non-modifiable factors of old age and male sex. CONCLUSIONS: TyG index is an independent marker for predicting subclinical CAD in individuals conventionally considered healthy.

Mechanism of polypurine tract primer generation by HIV-1 reverse transcriptase.

HIV-1 reverse transcriptase (RT) possesses both DNA polymerase activity and RNase H activity that act in concert to convert single-stranded RNA of the viral genome to double-stranded DNA that is then integrated into the DNA of the infected cell. Reverse transcriptase-catalyzed reverse transcription critically relies on the proper generation of a polypurine tract (PPT) primer. However, the mechanism of PPT primer generation and the features of the PPT sequence that are critical for its recognition by HIV-1 RT remain unclear. Here, we used a chemical cross-linking method together with molecular dynamics simulations and single-molecule assays to study the mechanism of PPT primer generation. We found that the PPT was specifically and properly recognized within covalently tethered HIV-1 RT-nucleic acid complexes. These findings indicated that recognition of the PPT occurs within a stable catalytic complex after its formation. We found that this unique recognition is based on two complementary elements that rely on the PPT sequence: RNase H sequence preference and incompatibility of the poly(rA/dT) tract of the PPT with the nucleic acid conformation that is required for RNase H cleavage. The latter results from rigidity of the poly(rA/dT) tract and leads to base-pair slippage of this sequence upon deformation into a catalytically relevant geometry. In summary, our results reveal an unexpected mechanism of PPT primer generation based on specific dynamic properties of the poly(rA/dT) segment and help advance our understanding of the mechanisms in viral RNA reverse transcription.

Long-term (10-year) outcomes of stenting or bypass surgery for acute coronary syndromes and stable ischemic heart disease with unprotected left main coronary artery disease.

BACKGROUND: Acuity of clinical presentation may influence decision making of percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) for left main coronary artery (LMCA) disease. However, it is undetermined whether clinical indication for myocardial revascularization may affect the relative long-term effect after PCI and CABG. METHODS: In the MAIN-COMPARE study including 2,240 patients with LMCA disease treated with PCI (n = 1102) or CABG (n = 1138), we examined interaction between acuity of clinical presentation (acute coronary syndromes [ACS] or non-ACS) and revascularization strategy on 10-year outcomes. Primary outcome was a composite of all-cause death, Q-wave myocardial infarction, or stroke. Secondary outcomes were all-cause death or target vessel revascularization. RESULTS: In overall patients, 1,603 patients (71.6%) presented with ACS and 637 patients (28.4%) presented with non-ACS. The 10-year adjusted risks for primary composite outcome were similar after PCI and CABG among patients who presented with non-ACS (hazard ratio [HR] 1.07; 95% CI 0.71-1.61) and those who presented with ACS (HR 1.00; 95% CI 0.81-1.24) (P for interaction = .29). The adjusted risks of death were also similar between 2 groups in non-ACS (HR 0.98; 95% CI 0.63-1.51) and ACS (HR 1.02; 95% CI 0.81-1.28) patients (P for interaction = .62). The adjusted risks of target vessel revascularization were consistently higher after PCI in non-ACS (HR 6.38; 95% CI 3.14-12.96) and ACS (HR 3.96; 95% CI 2.80-5.60) patients (P for interaction = .39). CONCLUSIONS: In patients with LMCA disease, we have identified no significant interaction between the acuity of clinical indication and the relative treatment effect of PCI versus CABG on 10-year clinical outcomes.