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Embedding catalysts inside of plastics affords accelerated chemical modification with programmable latency and pathways. Nanoscopically embedded enzymes can lead to near-complete degradation of polyesters via chain-end mediated processive depolymerization. The overall degradation rate and pathways have a strong dependence on the morphology of semicrystalline polyesters. Yet, most studies to date focus on pristine polymers instead of mixtures that contain additives and other components despite their nearly universal use in plastic production. Here, additives are introduced to purposely change the morphology of polycaprolactone (PCL) by increasing the bending and twisting of crystalline lamellae. These morphological changes immobilize chain ends preferentially at the crystalline/amorphous interfaces and limit chain-end accessibility by the embedded processive enzyme. This chain-end redistribution reduces the polymer-to-monomer conversion from >95% to less than 50%, causing formation of highly crystalline plastic pieces, including microplastics. By synergizing both random chain scission and processive depolymerization, it is feasible to navigate morphological changes in polymer/additive blends and to achieve near-complete depolymerization. The random scission enzymes in the amorphous domains create new chain ends that are subsequently bound and depolymerized by processive enzymes. Present studies further highlight the importance to consider how the host polymer's morphologies affect the reactions catalyzed by embedded catalytic species.

Pulmonary arterial hypertension (PAH) is a vasculopathy characterized by sustained elevated pulmonary arterial pressures in which the pulmonary vasculature undergoes significant structural and functional remodeling. To better understand disease mechanisms, in this review article we highlight recent insights into the regulation of pulmonary arterial cells by mechanical cues associated with PAH. Specifically, the mechanobiology of pulmonary arterial endothelial cells (PAECs), smooth muscle cells (PASMCs) and adventitial fibroblasts (PAAFs) has been investigated in vivo, in vitro, and in silico. Increased pulmonary arterial pressure increases vessel wall stress and strain and endothelial fluid shear stress. These mechanical cues promote vasoconstriction and fibrosis that contribute further to hypertension and alter the mechanical milieu and regulation of pulmonary arterial cells.

Here, we present a novel network model of the pulmonary arterial adventitial fibroblast (PAAF) that represents seven signalling pathways, confirmed to be important in pulmonary arterial fibrosis, as 92 reactions and 64 state variables. Without optimizing parameters, the model correctly predicted 80% of 39 results of input-output and inhibition experiments reported in 20 independent papers not used to formulate the original network. Parameter uncertainty quantification (UQ) showed that this measure of model accuracy is robust to changes in input weights and half-maximal activation levels (EC50), but is more affected by uncertainty in the Hill coefficient (n), which governs the biochemical cooperativity or steepness of the sigmoidal activation function of each state variable. Epistemic uncertainty in model structure, due to the reliance of some network components and interactions on experiments using non-PAAF cell types, suggested that this source of uncertainty had a smaller impact on model accuracy than the alternative of reducing the network to only those interactions reported in PAAFs. UQ highlighted model parameters that can be optimized to improve prediction accuracy and network modules where there is the greatest need for new experiments. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Cardiac myocytes transduce changes in mechanical loading into cellular responses via interacting cell signalling pathways. We previously reported a logic-based ordinary differential equation model of the myocyte mechanosignalling network that correctly predicts 78% of independent experimental results not used to formulate the original model. Here, we use Monte Carlo and polynomial chaos expansion simulations to examine the effects of uncertainty in parameter values, model logic and experimental validation data on the assessed accuracy of that model. The prediction accuracy of the model was robust to parameter changes over a wide range being least sensitive to uncertainty in time constants and most affected by uncertainty in reaction weights. Quantifying epistemic uncertainty in the reaction logic of the model showed that while replacing 'OR' with 'AND' reactions greatly reduced model accuracy, replacing 'AND' with 'OR' reactions was more likely to maintain or even improve accuracy. Finally, data uncertainty had a modest effect on assessment of model accuracy. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

The specialized light organ of the ponyfish supports the growth of the bioluminescent symbiont Photobacterium leiognathi. The bioluminescence of P. leiognathi is generated within a heteromeric protein complex composed of the bacterial luciferase and a 20-kDa lumazine binding protein (LUMP), which serves as a Förster resonance energy transfer (FRET) acceptor protein, emitting a cyan-colored fluorescence with an unusually long excited state lifetime of 13.6 ns. The long fluorescence lifetime and small mass of LUMP are exploited for the design of highly optimized encoded sensors for quantitative fluorescence anisotropy (FA) measurements of protein hydrodynamics. In particular, large differences in the FA values of the free and target-bound states of LUMP fusions appended with capture sequences of up to 20 kDa are used in quantitative FA imaging and analysis of target proteins. For example, a fusion protein composed of LUMP and a 5-kDa G protein binding domain is used as an FA sensor to quantify the binding of the GTP-bound cell division control protein 42 homolog (Cdc42) (21 kDa) in solution and within Escherichia coli. Additionally, the long fluorescence lifetime and the surface-bound fluorescent cofactor 6,7-dimethyl-8- (1'-dimethyl-ribityl) lumazine in LUMP are utilized in the design of highly optimized FRET probes that use Venus as an acceptor probe. The efficiency of FRET in a zero-length LUMP-Venus fusion is 62% compared to ∼ 31% in a related CFP-Venus fusion. The improved FRET efficiency obtained by using LUMP as a donor probe is used in the design of a FRET-optimized genetically encoded LUMP-Venus substrate for thrombin.

To identify how cardiomyocyte mechanosensitive signaling pathways are regulated by anisotropic stretch, micropatterned mouse neonatal cardiomyocytes were stretched primarily longitudinally or transversely to the myofiber axis. Four hours of static, longitudinal stretch induced differential expression of 557 genes, compared with 30 induced by transverse stretch, measured using RNA-seq. A logic-based ordinary differential equation model of the cardiac myocyte mechanosignaling network, extended to include the transcriptional regulation and expression of 784 genes, correctly predicted measured expression changes due to anisotropic stretch with 69% accuracy. The model also predicted published transcriptional responses to mechanical load in vitro or in vivo with 63-91% accuracy. The observed differences between transverse and longitudinal stretch responses were not explained by differential activation of specific pathways but rather by an approximately twofold greater sensitivity to longitudinal stretch than transverse stretch. In vitro experiments confirmed model predictions that stretch-induced gene expression is more sensitive to angiotensin II and endothelin-1, via RhoA and MAP kinases, than to the three membrane ion channels upstream of calcium signaling in the network. Quantitative cardiomyocyte gene expression differs substantially with the axis of maximum principal stretch relative to the myofilament axis, but this difference is due primarily to differences in stretch sensitivity rather than to selective activation of mechanosignaling pathways. [ABSTRACT FROM AUTHOR]

Gonadotropin-inhibitory hormone (GnIH) was originally identified in quail as a hypothalamic neuropeptide inhibitor of pituitary gonadotropin synthesis and release. However, GnIH neuronal fibers do not only terminate in the median eminence to control anterior pituitary function but also extend widely in the brain, suggesting it has multiple roles in the regulation of behavior. To identify the role of GnIH neurons in the regulation of behavior, we investigated the effect of RNA interference (RNAi) of the GnIH gene on the behavior of white-crowned sparrows, a highly social songbird species. Administration of small interfering RNA against GnIH precursor mRNA into the third ventricle of male and female birds reduced resting time, spontaneous production of complex vocalizations, and stimulated brief agonistic vocalizations. GnIH RNAi further enhanced song production of short duration in male birds when they were challenged by playbacks of novel male songs. These behaviors resembled those of breeding birds during territorial defense. The overall results suggest that GnIH gene silencing induces arousal. In addition, the activities of male and female birds were negatively correlated with GnIH mRNA expression in the paraventricular nucleus. Density of GnIH neuronal fibers in the ventral tegmental area was decreased by GnIH RNAi treatment in female birds, and the number of gonadotropin-releasing hormone neurons that received close appositions of GnIH neuronal fiber terminals was negatively correlated with the activity of male birds. In summary, GnIH may decrease arousal level resulting in the inhibition of specific motivated behavior such as in reproductive contexts.

Background: Personality disorders are now internationally recognised as a mental health priority. Nevertheless, there are no systematic reviews examining the global prevalence of personality disorders.Aims: To calculate the worldwide prevalence of personality disorders and examine whether rates vary between high-income countries and low- and middle-income countries (LMICs).Method: We systematically searched PsycINFO, MEDLINE, EMBASE and PubMed from January 1980 to May 2018 to identify articles reporting personality disorder prevalence rates in community populations (PROSPERO registration number: CRD42017065094).Results: A total of 46 studies (from 21 different countries spanning 6 continents) satisfied inclusion criteria. The worldwide pooled prevalence of any personality disorder was 7.8% (95% CI 6.1-9.5). Rates were greater in high-income countries (9.6%, 95% CI 7.9-11.3%) compared with LMICs (4.3%, 95% CI 2.6-6.1%). In univariate meta-regressions, significant heterogeneity was partly attributable to study design (two-stage v. one-stage assessment), county income (high-income countries v. LMICs) and interview administration (clinician v. trained graduate). In multiple meta-regression analysis, study design remained a significant predictor of heterogeneity. Global rates of cluster A, B and C personality disorders were 3.8% (95% CI 3.2, 4.4%), 2.8% (1.6, 3.7%) and 5.0% (4.2, 5.9%).Conclusions: Personality disorders are prevalent globally. Nevertheless, pooled prevalence rates should be interpreted with caution due to high levels of heterogeneity. More large-scale studies with standardised methodologies are now needed to increase our understanding of population needs and regional variations. [ABSTRACT FROM AUTHOR]

To identify how cardiomyocyte mechanosensitive signaling pathways are regulated by anisotropic stretch, micropatterned mouse neonatal cardiomyocytes were stretched primarily longitudinally or transversely to the myofiber axis. Four hours of static, longitudinal stretch induced differential expression of 557 genes, compared with 30 induced by transverse stretch, measured using RNA-seq. A logic-based ordinary differential equation model of the cardiac myocyte mechanosignaling network, extended to include the transcriptional regulation and expression of 784 genes, correctly predicted measured expression changes due to anisotropic stretch with 69% accuracy. The model also predicted published transcriptional responses to mechanical load in vitro or in vivo with 63-91% accuracy. The observed differences between transverse and longitudinal stretch responses were not explained by differential activation of specific pathways but rather by an approximately twofold greater sensitivity to longitudinal stretch than transverse stretch. In vitro experiments confirmed model predictions that stretch-induced gene expression is more sensitive to angiotensin II and endothelin-1, via RhoA and MAP kinases, than to the three membrane ion channels upstream of calcium signaling in the network. Quantitative cardiomyocyte gene expression differs substantially with the axis of maximum principal stretch relative to the myofilament axis, but this difference is due primarily to differences in stretch sensitivity rather than to selective activation of mechanosignaling pathways. NEW & NOTEWORTHY Anisotropic stretch applied to micropatterned neonatal mouse ventricular myocytes induced markedly greater acute transcriptional responses when the major axis of stretch was parallel to the myofilament axis than when it was transverse. Analysis with a novel quantitative network model of mechanoregulated cardiomyocyte gene expression suggests that this difference is explained by higher cell sensitivity to longitudinal loading than transverse loading than by the activation of differential signaling pathways.

Purpose: The increasing diabetes prevalence and advent of new treatments for its major visual-threatening complications (diabetic macular edema [DME] and proliferative diabetic retinopathy [PDR]), which require frequent life-long follow-up, have increased hospital demands markedly. Subsequent delays in patient's evaluation and treatment are causing sight loss. Strategies to increase capacity are needed urgently. The retinopathy (EMERALD) study tested diagnostic accuracy, acceptability, and costs of a new health care pathway for people with previously treated DME or PDR., Design: Prospective, multicenter, case-referent, cross-sectional, diagnostic accuracy study undertaken in 13 hospitals in the United Kingdom., Participants: Adults with type 1 or 2 diabetes previously successfully treated DME or PDR who, at the time of enrollment, had active or inactive disease., Methods: A new health care pathway entailing multimodal imaging (spectral-domain OCT for DME, and 7-field Early Treatment Diabetic Retinopathy Study [ETDRS] and ultra-widefield [UWF] fundus images for PDR) interpreted by trained nonmedical staff (ophthalmic graders) to detect reactivation of disease was compared with the current standard care (face-to-face examination by ophthalmologists)., Main Outcome Measures: Primary outcome: sensitivity of the new pathway., Secondary Outcomes: specificity; agreement between pathways; costs; acceptability; proportions requiring subsequent ophthalmologist assessment, unable to undergo imaging, and with inadequate images or indeterminate findings., Results: The new pathway showed sensitivity of 97% (95% confidence interval [CI], 92%-99%) and specificity of 31% (95% CI, 23%-40%) to detect DME. For PDR, sensitivity and specificity using 7-field ETDRS images (85% [95% CI, 77%-91%] and 48% [95% CI, 41%-56%], respectively) or UWF images (83% [95% CI, 75%-89%] and 54% [95% CI, 46%-61%], respectively) were comparable. For detection of high-risk PDR, sensitivity and specificity were higher when using UWF images (87% [95% CI, 78%-93%] and 49% [95% CI, 42%-56%], respectively, for UWF versus 80% [95% CI, 69-88%] and 40% [95% CI, 34%-47%], respectively, for 7-field ETDRS images). Participants preferred ophthalmologists' assessments; in their absence, they preferred immediate feedback by graders, maintaining periodic ophthalmologist evaluations. When compared with the current standard of care, the new pathway could save £1390 per 100 DME visits and between £461 and £1189 per 100 PDR visits., Conclusions: The new pathway has acceptable sensitivity and would release resources. Users' suggestions should guide implementation., (Copyright © 2020 American Academy of Ophthalmology. All rights reserved.)

Cardiac myocytes transduce changes in mechanical loading into cellular responses via interacting cell signalling pathways. We previously reported a logic-based ordinary differential equation model of the myocyte mechanosignalling network that correctly predicts 78% of independent experimental results not used to formulate the original model. Here, we use Monte Carlo and polynomial chaos expansion simulations to examine the effects of uncertainty in parameter values, model logic and experimental validation data on the assessed accuracy of that model. The prediction accuracy of the model was robust to parameter changes over a wide range being least sensitive to uncertainty in time constants and most affected by uncertainty in reaction weights. Quantifying epistemic uncertainty in the reaction logic of the model showed that while replacing 'OR' with 'AND' reactions greatly reduced model accuracy, replacing 'AND' with 'OR' reactions was more likely to maintain or even improve accuracy. Finally, data uncertainty had a modest effect on assessment of model accuracy. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Here, we present a novel network model of the pulmonary arterial adventitial fibroblast (PAAF) that represents seven signalling pathways, confirmed to be important in pulmonary arterial fibrosis, as 92 reactions and 64 state variables. Without optimizing parameters, the model correctly predicted 80% of 39 results of input-output and inhibition experiments reported in 20 independent papers not used to formulate the original network. Parameter uncertainty quantification (UQ) showed that this measure of model accuracy is robust to changes in input weights and half-maximal activation levels (EC 50 ), but is more affected by uncertainty in the Hill coefficient ( n ), which governs the biochemical cooperativity or steepness of the sigmoidal activation function of each state variable. Epistemic uncertainty in model structure, due to the reliance of some network components and interactions on experiments using non-PAAF cell types, suggested that this source of uncertainty had a smaller impact on model accuracy than the alternative of reducing the network to only those interactions reported in PAAFs. UQ highlighted model parameters that can be optimized to improve prediction accuracy and network modules where there is the greatest need for new experiments. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.