Super-resolution reconstruction improves multishell diffusion: using radiomics to predict adult-type diffuse glioma IDH and grade.

Objectives: Multishell diffusion scanning is limited by low spatial resolution. We sought to improve the resolution of multishell diffusion images through deep learning-based super-resolution reconstruction (SR) and subsequently develop and validate a prediction model for adult-type diffuse glioma, isocitrate dehydrogenase status and grade 2/3 tumors. Materials and methods: A simple diffusion model (DTI) and three advanced diffusion models (DKI, MAP, and NODDI) were constructed based on multishell diffusion scanning. Migration was performed with a generative adversarial network based on deep residual channel attention networks, after which images with 2x and 4x resolution improvements were generated. Radiomic features were used as inputs, and diagnostic models were subsequently constructed via multiple pipelines. Results: This prospective study included 90 instances (median age, 54.5 years; 39 men) diagnosed with adult-type diffuse glioma. Images with both 2x- and 4x-improved resolution were visually superior to the original images, and the 2x-improved images allowed better predictions than did the 4x-improved images (P<.001). A comparison of the areas under the curve among the multiple pipeline-constructed models revealed that the advanced diffusion models did not have greater diagnostic performance than the simple diffusion model (P>.05). The NODDI model constructed with 2x-improved images had the best performance in predicting isocitrate dehydrogenase status (AUC_validation=0.877; Brier score=0.132). The MAP model constructed with the original images performed best in classifying grade 2 and grade 3 tumors (AUC_validation=0.806; Brier score=0.168). Conclusion: SR improves the resolution of multishell diffusion images and has different advantages in achieving different goals and creating different target diffusion models.

Nanoporous amorphous carbon nanopillars with lightweight, ultrahigh strength, large fracture strain, and high damping capability.

Simultaneous achievement of lightweight, ultrahigh strength, large fracture strain, and high damping capability is challenging because some of these mechanical properties are mutually exclusive. Here, we utilize self-assembled polymeric carbon precursor materials in combination with scalable nano-imprinting lithography to produce nanoporous carbon nanopillars. Remarkably, nanoporosity induced via sacrificial template significantly reduces the mass density of amorphous carbon to 0.66 ~ 0.82 g cm-3 while the yield and fracture strengths of nanoporous carbon nanopillars are higher than those of most engineering materials with the similar mass density. Moreover, these nanopillars display both elastic and plastic behavior with large fracture strain. A reversible part of the sp2-to-sp3 transition produces large elastic strain and a high loss factor (up to 0.033) comparable to Ni-Ti shape memory alloys. The irreversible part of the sp2-to-sp3 transition enables plastic deformation, leading to a large fracture strain of up to 35%. These findings are substantiated using simulation studies. None of the existing structural materials exhibit a comparable combination of mass density, strength, deformability, and damping capability. Hence, the results of this study illustrate the potential of both dense and nanoporous amorphous carbon materials as superior structural nanomaterials.

PTPN14 aggravates neointimal hyperplasia via boosting PDGFRß signaling in smooth muscle cells.

Smooth muscle cell (SMC) phenotypic modulation, primarily driven by PDGFRß signaling, is implicated in occlusive cardiovascular diseases. However, the promotive and restrictive regulation mechanism of PDGFRß and the role of protein tyrosine phosphatase non-receptor type 14 (PTPN14) in neointimal hyperplasia remain unclear. Our study observes a marked upregulation of PTPN14 in SMCs during neointimal hyperplasia. PTPN14 overexpression exacerbates neointimal hyperplasia in a phosphatase activity-dependent manner, while SMC-specific deficiency of PTPN14 mitigates this process in mice. RNA-seq indicates that PTPN14 deficiency inhibits PDGFRß signaling-induced SMC phenotypic modulation. Moreover, PTPN14 interacts with intracellular region of PDGFRß and mediates its dephosphorylation on Y692 site. Phosphorylation of PDGFRßY692 negatively regulates PDGFRß signaling activation. The levels of both PTPN14 and phospho-PDGFRßY692 are correlated with the degree of stenosis in human coronary arteries. Our findings suggest that PTPN14 serves as a critical modulator of SMCs, promoting neointimal hyperplasia. PDGFRßY692, dephosphorylated by PTPN14, acts as a self-inhibitory site for controlling PDGFRß activation.

Tudor-SN promotes cardiomyocyte proliferation and neonatal heart regeneration through regulating the phosphorylation of YAP.

BACKGROUND: The neonatal mammalian heart exhibits considerable regenerative potential following injury through cardiomyocyte proliferation, whereas mature cardiomyocytes withdraw from the cell cycle and lose regenerative capacities. Therefore, investigating the mechanisms underlying neonatal cardiomyocyte proliferation and regeneration is crucial for unlocking the regenerative potential of adult mammalian heart to repair damage and restore contractile function following myocardial injury. METHODS: The Tudor staphylococcal nuclease (Tudor-SN) transgenic (TG) or cardiomyocyte-specific knockout mice (Myh6-Tudor-SN -/-) were generated to investigate the role of Tudor-SN in cardiomyocyte proliferation and heart regeneration following apical resection (AR) surgery. Primary cardiomyocytes isolated from neonatal mice were used to assess the influence of Tudor-SN on cardiomyocyte proliferation in vitro. Affinity purification and mass spectrometry were employed to elucidate the underlying mechanism. H9c2 cells and mouse myocardia with either overexpression or knockout of Tudor-SN were utilized to assess its impact on the phosphorylation of Yes-associated protein (YAP), both in vitro and in vivo. RESULTS: We previously identified Tudor-SN as a cell cycle regulator that is highly expressed in neonatal mice myocardia but downregulated in adults. Our present study demonstrates that sustained expression of Tudor-SN promotes and prolongs the proliferation of neonatal cardiomyocytes, improves cardiac function, and enhances the ability to repair the left ventricular apex resection in neonatal mice. Consistently, cardiomyocyte-specific knockout of Tudor-SN impairs cardiac function and retards recovery after injury. Tudor-SN associates with YAP, which plays important roles in heart development and regeneration, inhibiting phosphorylation at Ser 127 and Ser 397 residues by preventing the association between Large Tumor Suppressor 1 (LATS1) and YAP, correspondingly maintaining stability and promoting nuclear translocation of YAP to enhance the proliferation-related genes transcription. CONCLUSION: Tudor-SN regulates the phosphorylation of YAP, consequently enhancing and prolonging neonatal cardiomyocyte proliferation under physiological conditions and promoting neonatal heart regeneration after injury.

The physical basis for solvent flow in organic solvent nanofiltration.

Organic solvent nanofiltration (OSN) is an emerging membrane technology that could revolutionize chemical separations in numerous vital industries. Despite its significance, there remains a lack of fundamental understanding of solvent transport mechanisms in OSN membranes. Here, we use an extended Flory-Rehner theory, nonequilibrium molecular dynamic simulations, and organic solvent transport experiments to demonstrate that solvent flow in OSN membranes is driven by a pressure gradient. We show that solvent molecules migrate as clusters through interconnected pathways within the membrane pore structure, challenging the widely accepted diffusion-based view of solvent transport in OSN. We further reveal that solvent permeance is dependent on solvent affinity to the OSN membrane, which, in turn, controls the membrane pore structure. Our fundamental insights lay the scientific groundwork for the development of next-generation OSN membranes.

Role of endothelial Raptor in abnormal arteriogenesis after lower limb ischaemia in type 2 diabetes.

AIMS: Proper arteriogenesis after tissue ischaemia is necessary to rebuild stable blood circulation; nevertheless, this process is impaired in type 2 diabetes mellitus (T2DM). Raptor is a scaffold protein and a component of mammalian target of rapamycin complex 1 (mTORC1). However, the role of the endothelial Raptor in arteriogenesis under the conditions of T2DM remains unknown. This study investigated the role of endothelial Raptor in ischaemia-induced arteriogenesis during T2DM. METHODS AND RESULTS: Although endothelial mTORC1 is hyperactive in T2DM, we observed a marked reduction in the expression of endothelial Raptor in two mouse models and in human vessels. Inducible endothelial-specific Raptor knockout severely exacerbated impaired hindlimb perfusion and arteriogenesis after hindlimb ischaemic injury in 12-week high-fat diet fed mice. Additionally, we found that Raptor deficiency dampened vascular endothelial growth factor receptor 2 (VEGFR2) signalling in endothelial cells (ECs) and inhibited VEGF-induced cell migration and tube formation in a PTP1B-dependent manner. Furthermore, mass spectrometry analysis indicated that Raptor interacts with neuropilin 1 (NRP1), the co-receptor of VEGFR2, and mediates VEGFR2 trafficking by facilitating the interaction between NRP1 and Synectin. Finally, we found that EC-specific overexpression of the Raptor mutant (loss of mTOR binding) reversed impaired hindlimb perfusion and arteriogenesis induced by endothelial Raptor knockout in high-fat diet fed mice. CONCLUSION: Collectively, our study demonstrated the crucial role of endothelial Raptor in promoting ischaemia-induced arteriogenesis in T2DM by mediating VEGFR2 signalling. Thus, endothelial Raptor is a novel therapeutic target for promoting arteriogenesis and ameliorating perfusion in T2DM.

Beyond nothingness in the formation and functional relevance of voids in polymer films.

Voids-the nothingness-broadly exist within nanomaterials and impact properties ranging from catalysis to mechanical response. However, understanding nanovoids is challenging due to lack of imaging methods with the needed penetration depth and spatial resolution. Here, we integrate electron tomography, morphometry, graph theory and coarse-grained molecular dynamics simulation to study the formation of interconnected nanovoids in polymer films and their impacts on permeance and nanomechanical behaviour. Using polyamide membranes for molecular separation as a representative system, three-dimensional electron tomography at nanometre resolution reveals nanovoid formation from coalescence of oligomers, supported by coarse-grained molecular dynamics simulations. Void analysis provides otherwise inaccessible inputs for accurate fittings of methanol permeance for polyamide membranes. Three-dimensional structural graphs accounting for the tortuous nanovoids within, measure higher apparent moduli with polyamide membranes of higher graph rigidity. Our study elucidates the significance of nanovoids beyond the nothingness, impacting the synthesis‒morphology‒function relationships of complex nanomaterials.

Development and validation of the perceived restorative soundscape scale for children.

Introduction: Prolonged exposure to noise environments can induce stress and fatigue, even impacting individuals' physical and mental health. Conversely, positive soundscapes can have a beneficial impact on health by alleviating stress and fatigue, promoting psychological recovery. To assess the restorative potential of soundscapes, various scales have been developed to create environments conducive to recovery. However, current research on perceptual restorativeness soundscape scales primarily focuses on adults, lacking a dedicated scale for children to evaluate the restorative potential of their surrounding acoustic environments from their perspective. Methods: Therefore, this study introduces the development and validation process of the Perceived Restorativeness of Soundscapes Scale for Children (PRSS-C) using survey questionnaires and data statistical analysis. Results: The study comprises two experiments. Experiment one aims to develop an effective PRSS-C, evaluating the restorative potential of soundscapes in different environments (urban center, urban suburb, and urban peripheral forest) among 185 children aged 10-12. Through a series of analyses, a dual-factor structure scale consisting of 15 items is developed, revealing that the restorative potential of soundscapes is lower in urban centers than in urban suburbs and lower in urban suburbs than in urban peripheral forests. Experiment two aims to further validate the effectiveness of PRSS-C. 244 children aged 10-12 assess the restorative potential of soundscapes in similar environments (two city parks) using the PRSS-C developed in experiment one. Factor analysis confirms the dual-factor structure, with assessment results indicating that the restorative potential of soundscapes in Temple of Heaven Park is lower than in the National Botanical Garden. This suggests that PRSS-C enables children to differentiate the restorative potential of soundscapes in similar environments within the same city, further confirming its effectiveness. Discussion: This study successfully develops and validates the PRSS-C through two experiments. The use of this scale allows for the assessment of the restorative potential of acoustic environments surrounding children, providing an effective tool for evaluating and creating positive soundscapes for children.

CNP Ameliorates Macrophage Inflammatory Response and Atherosclerosis.

BACKGROUND: CNP (C-type natriuretic peptide), an endogenous short peptide in the natriuretic peptide family, has emerged as an important regulator to govern vascular homeostasis. However, its role in the development of atherosclerosis remains unclear. This study aimed to investigate the impact of CNP on the progression of atherosclerotic plaques and elucidate its underlying mechanisms. METHODS: Plasma CNP levels were measured in patients with acute coronary syndrome. The potential atheroprotective role of CNP was evaluated in apolipoprotein E-deficient (ApoE-/-) mice through CNP supplementation via osmotic pumps, genetic overexpression, or LCZ696 administration. Various functional experiments involving CNP treatment were performed on primary macrophages derived from wild-type and CD36 (cluster of differentiation 36) knockout mice. Proteomics and multiple biochemical analyses were conducted to unravel the underlying mechanism. RESULTS: We observed a negative correlation between plasma CNP concentration and the burden of coronary atherosclerosis in patients. In early atherosclerotic plaques, CNP predominantly accumulated in macrophages but significantly decreased in advanced plaques. Supplementing CNP via osmotic pumps or genetic overexpression ameliorated atherosclerotic plaque formation and enhanced plaque stability in ApoE-/- mice. CNP promoted an anti-inflammatory macrophage phenotype and efferocytosis and reduced foam cell formation and necroptosis. Mechanistically, we found that CNP could accelerate HIF-1α (hypoxia-inducible factor 1-alpha) degradation in macrophages by enhancing the interaction between PHD (prolyl hydroxylase domain-containing protein) 2 and HIF-1α. Furthermore, we observed that CD36 bound to CNP and mediated its endocytosis in macrophages. Moreover, we demonstrated that the administration of LCZ696, an orally bioavailable drug recently approved for treating chronic heart failure with reduced ejection fraction, could amplify the bioactivity of CNP and ameliorate atherosclerotic plaque formation. CONCLUSIONS: Our study reveals that CNP enhanced plaque stability and alleviated macrophage inflammatory responses by promoting HIF-1α degradation, suggesting a novel atheroprotective role of CNP. Enhancing CNP bioactivity may offer a novel pharmacological strategy for treating related diseases.

The mediating role of impulsivity between sleep quality and suicidal ideation in adolescent population: a multicenter cross-sectional study in the northeastern Sichuan, China.

Introduction: Suicidal ideation is a critical early stage in the progression towards suicidal be havior. Prior research has established links between sleep quality, impulsivity, and suicidal tendencies, yet the interaction among these factors has been less explored. This study aims to explore the mediating role of impulsivity in the relationship between sleep quality and suicidal ideation in adolescents. Methods: Employing a cross-sectional study design, 6,974 questionnaires were distributed,including the Socio-demographic Characteristics Questionnaire, Barratt Impulsiveness Scale, the Positive and Negative Suicide Ideation Inventory,and the Pittsburgh Sleep Quality Index Scale. The participants were high school and middle school students from 33 schools in northeastern Sichuan, China, selected through random cluster sampling. Results: Of these 6,786 questionnaires were analyzed. The participant distribution included 47.2% male and 52.8% female students, with 68.3% from junior schools and 31.7% from senior schools. The prevalence of suicidal ideation was found to be 13.6%. The analysis, which involved correlation analysis and the construction of a structural equation model, revealed that sleep quality had a significant positive effect on impulsivity (ß:0.289,p < 0.05), and impulsivity, in turn, had a positive impact on suicidal ideation (ß:0.355,p < 0.05).Moreover, sleep quality was directly linked to suicidal ideation (ß:0.208,p < 0.05). Thus, sleep quality affects suicidal ideation both directly and indirectly through impulsivity. Discussion: The results of this study suggest that both sleep quality and impulsivity are significant direct influencers of suicidal ideation among adolescents in the region studied, with impulsivity also playing an indirect role in the relationship between sleep quality and suicidal ideation.

The mediating role of sleep problems and depressed mood between psychological abuse/neglect and suicidal ideation in adolescent childhood: a multicentred, large sample survey in Western China.

BACKGROUND: Adolescent suicidal ideation are associated with factors including psychological abuse/neglect, sleep problems, and depressed mood, but the systematic effects of these factors on suicidal ideation remain unclear, which is a research gap this work aims to fill. METHODS: A multi-center, the cluster sampling method was employed to collect general demographic data, such as age, gender, the experience of being left behind, and parents' marital status, from 12,192 students across 17 secondary schools in China. The Child Psychological Abuse and Neglect Scale (CPANS), Pittsburgh Sleep Quality Index (PSQI), the Chinese version of the Depressed mood, Anxiety and Stress Scale - 21 Items (DASS-21) and Chinese version of Positive and Negative Suicide Ideation Inventory (PANSI) were utilized. Data were analyzed using t-tests, chi-square tests, correlation analyses, and structural equation modeling mediation analyses. RESULTS: The prevalence of psychological abuse/neglect and adolescent suicidal ideation was 34.8% and 13%, respectively. This mediation analysis suggests that, in the relationship between psychological abuse/neglect and suicidal ideation, sleep problems and depressed mood play both parallel and sequential mediating roles. CONCLUSION: Sleep problems and depressed mood play a mediating role in the development of suicidal ideation in adolescents. Good sleep habits and depressed mood interventions help reduce the risk of suicidal ideation in adolescents who experience psychological neglect/abuse.

Endothelial YAP Mediates Hyperglycemia-Induced Platelet Hyperactivity and Arterial Thrombosis.

BACKGROUND: Hyperglycemia-a symptom that characterizes diabetes-is highly associated with atherothrombotic complications. However, the underlying mechanism by which hyperglycemia fuels platelet activation and arterial thrombus formation is still not fully understood. METHODS: The profiles of polyunsaturated fatty acid metabolites in the plasma of patients with diabetes and healthy controls were determined with targeted metabolomics. FeCl3-induced carotid injury model was used to assess arterial thrombus formation in mice with endothelial cell (EC)-specific YAP (yes-associated protein) deletion or overexpression. Flow cytometry and clot retraction assay were used to evaluate platelet activation. RNA sequencing and multiple biochemical analyses were conducted to unravel the underlying mechanism. RESULTS: The plasma PGE2 (prostaglandin E2) concentration was elevated in patients with diabetes with thrombotic complications and positively correlated with platelet activation. The PGE2 synthetases COX-2 (cyclooxygenase-2) and mPGES-1 (microsomal prostaglandin E synthase-1) were found to be highly expressed in ECs but not in other type of vessel cells in arteries from both patients with diabetes and hyperglycemic mice, compared with nondiabetic individuals and control mice, respectively. A combination of RNA sequencing and ingenuity pathway analyses indicated the involvement of YAP signaling. EC-specific deletion of YAP limited platelet activation and arterial thrombosis in hyperglycemic mice, whereas EC-specific overexpression of YAP in mice mimicked the prothrombotic state of diabetes, without affecting hemostasis. Mechanistically, we found that hyperglycemia/high glucose-induced endothelial YAP nuclear translocation and subsequently transcriptional expression of COX-2 and mPGES-1 contributed to the elevation of PGE2 and platelet activation. Blockade of EP3 (prostaglandin E receptor 3) activation by oral administration of DG-041 reversed the hyperactivity of platelets and delayed thrombus formation in both EC-specific YAP-overexpressing and hyperglycemic mice. CONCLUSIONS: Collectively, our data suggest that hyperglycemia-induced endothelial YAP activation aggravates platelet activation and arterial thrombus formation via PGE2/EP3 signaling. Targeting EP3 with DG-041 might be therapeutic for diabetes-related thrombosis.

Tracking of Stem Cells in Chronic Liver Diseases: Current Trends and Developments.

Stem cell therapy holds great promise for future clinical practice for treatment of advanced liver diseases. However, the fate of stem cells after transplantation, including the distribution, viability, and the cell clearance, has not been fully elucidated. Herein, recent advances regarding the imaging tools for stem cells tracking mainly in chronic liver diseases with the advantages and disadvantages of each approach have been described. Magnetic resonance imaging is a promising clinical imaging modality due to non-radioactivity, excellent penetrability, and high spatial resolution. Fluorescence imaging and radionuclide imaging demonstrate relatively increased sensitivity, with the latter excelling in real-time monitoring. Reporter genes specialize in long-term tracing. Nevertheless, the disadvantages of low sensitivity, radiation, exogenous gene risk are inevitably present in each of these means, respectively. In this review, we aim to comprehensively evaluate the current state of methods for tracking of stem cell, highlighting their strengths and weaknesses, and providing insights into their future potential. Multimodality imaging strategies may overcome the inherent limitations of single-modality imaging by combining the strengths of different imaging techniques to provide more comprehensive information in the clinical setting.

Model incorporating multiple diffusion MRI features: development and validation of a radiomics-based model to predict adult-type diffuse gliomas grade.

OBJECTIVES: To develop and validate a radiomics-based model (ADGGIP) for predicting adult-type diffuse gliomas (ADG) grade by combining multiple diffusion modalities and clinical and imaging morphologic features. METHODS: In this prospective study, we recruited 103 participants diagnosed with ADG and collected their preoperative conventional MRI and multiple diffusion imaging (diffusion tensor imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging, and mean apparent propagator diffusion-MRI) data in our hospital, as well as clinical information. Radiomic features of the diffusion images and clinical information and morphological data from the radiological reports were extracted, and multiple pipelines were used to construct the optimal model. Model validation was performed through a time-independent validation cohort. ROC curves were used to evaluate model performance. The clinical benefit was determined by decision curve analysis. RESULTS: From June 2018 to May 2021, 72 participants were recruited for the training cohort. Between June 2021 and February 2022, 31 participants were enrolled in the prospective validation cohort. In the training cohort (AUC 0.958), internal validation cohort (0.942), and prospective validation cohort (0.880), ADGGIP had good accuracy in predicting ADG grade. ADGGIP was also significantly better than the single-modality prediction model (AUC 0.860) and clinical imaging morphology model (0.841) (all p < .01) in the prospective validation cohort. When the threshold probability was greater than 5%, ADGGIP provided the greatest net benefit. CONCLUSION: ADGGIP, which is based on advanced diffusion modalities, can predict the grade of ADG with high accuracy and robustness and can help improve clinical decision-making. CLINICAL RELEVANCE STATEMENT: Integrated multi-modal predictive modeling is beneficial for early detection and treatment planning of adult-type diffuse gliomas, as well as for investigating the genuine clinical significance of biomarkers. KEY POINTS: • Integrated model exhibits the highest performance and stability. • When the threshold is greater than 5%, the integrated model has the greatest net benefit. • The advanced diffusion models do not demonstrate better performance than the simple technology.

High-Throughput Screening and Prediction of High Modulus of Resilience Polymers Using Explainable Machine Learning.

The ability to store and release elastic strain energy, as well as mechanical strength, are crucial factors in both natural and man-made mechanical systems. The modulus of resilience (R) indicates a material's capacity to absorb and release elastic strain energy, with the yield strength (σy) and Young's modulus (E) as R = σy2/(2E) for linear elastic solids. To improve the R in linear elastic solids, a high σy and low E combination in materials is sought after. However, achieving this combination is a significant challenge as both properties typically increase together. To address this challenge, we propose a computational method to quickly identify polymers with a high modulus of resilience using machine learning (ML) and validate the predictions through high-fidelity molecular dynamics (MD) simulations. Our approach commences by training single-task ML models, multitask ML models, and Evidential Deep Learning models to forecast the mechanical properties of polymers based on experimentally reported values. Utilizing explainable ML models, we were able to determine the critical substructures that significantly impact the mechanical properties of polymers, such as E and σy. This information can be utilized to create and develop new polymers with improved mechanical characteristics. Our single-task and multitask ML models can predict the properties of 12 854 real polymers and 8 million hypothetical polyimides and uncover 10 new real polymers and 10 hypothetical polyimides with exceptional modulus of resilience. The improved modulus of resilience of these novel polymers was validated through MD simulations. Our method efficiently speeds up the discovery of high-performing polymers using ML predictions and MD validation and can be applied to other polymer material discovery challenges, such as polymer membranes, dielectric polymers, and more.

Investigating structure and dynamics of unentangled poly(dimethyl-co-diphenyl)siloxane via molecular dynamics simulation.

Polysiloxane is one of the most important polymeric materials in technological use. Polydimethylsiloxane displays glass-like mechanical properties at low temperatures. Incorporation of phenyl siloxane, via copolymerization for example, improves not only the low-temperature elasticity but also enhances its performance over a wide range of temperatures. Copolymerization with the phenyl component can significantly change the microscopic properties of polysiloxanes, such as chain dynamics and relaxation. However, despite much work in the literature, the influence of such changes is still not clearly understood. In this work, we systematically study the structure and dynamics of random poly(dimethyl-co-diphenyl)siloxane via atomistic molecular dynamics simulations. As the molar ratio ϕ of the diphenyl component increases, we find that the size of the linear copolymer chain expands. At the same time, the chain-diffusivity slows down by over an order of magnitudes. The reduced diffusivity appears to be a result of a complex interplay between the structural and dynamic changes induced by phenyl substitution.

Carbon Additive Manufacturing with a Near-Replica "Green-to-Brown" Transformation.

Nanocomposites containing nanoscale materials offer exciting opportunities to encode nanoscale features into macroscale dimensions, which produces unprecedented impact in material design and application. However, conventional methods cannot process nanocomposites with a high particle loading, as well as nanocomposites with the ability to be tailored at multiple scales. A composite architected mesoscale process strategy that brings particle loading nanoscale materials combined with multiscale features including nanoscale manipulation, mesoscale architecture, and macroscale formation to create spatially programmed nanocomposites with high particle loading and multiscale tailorability is reported. The process features a low-shrinking (<10%) "green-to-brown" transformation, making a near-geometric replica of the 3D design to produce a "brown" part with full nanomaterials to allow further matrix infill. This demonstration includes additively manufactured carbon nanocomposites containing carbon nanotubes (CNTs) and thermoset epoxy, leading to multiscale CNTs tailorability, performance improvement, and 3D complex geometry feasibility. The process can produce nanomaterial-assembled architectures with 3D geometry and multiscale features and can incorporate a wide range of matrix materials, such as polymers, metals, and ceramics, to fabricate nanocomposites for new device structures and applications.

Water transport in reverse osmosis membranes is governed by pore flow, not a solution-diffusion mechanism.

We performed nonequilibrium molecular dynamics (NEMD) simulations and solvent permeation experiments to unravel the mechanism of water transport in reverse osmosis (RO) membranes. The NEMD simulations reveal that water transport is driven by a pressure gradient within the membranes, not by a water concentration gradient, in marked contrast to the classic solution-diffusion model. We further show that water molecules travel as clusters through a network of pores that are transiently connected. Permeation experiments with water and organic solvents using polyamide and cellulose triacetate RO membranes showed that solvent permeance depends on the membrane pore size, kinetic diameter of solvent molecules, and solvent viscosity. This observation is not consistent with the solution-diffusion model, where permeance depends on the solvent solubility. Motivated by these observations, we demonstrate that the solution-friction model, in which transport is driven by a pressure gradient, can describe water and solvent transport in RO membranes.

Conformability of flexible sheets on spherical surfaces.

Three-dimensional surface-conformable electronics is a burgeoning technology with potential applications in curved displays, bioelectronics, and biomimetics. Flexible electronics are notoriously difficult to fully conform to nondevelopable surfaces such as spheres. Although stretchable electronics can well conform to nondevelopable surfaces, they need to sacrifice pixel density for stretchability. Various empirical designs have been explored to improve the conformability of flexible electronics on spherical surfaces. However, no rational design guidelines exist. This study uses a combination of experimental, analytical, and numerical approaches to systematically investigate the conformability of both intact and partially cut circular sheets on spherical surfaces. Through the analysis of thin film buckling on curved surfaces, we identify a scaling law that predicts the conformability of flexible sheets on spherical surfaces. We also quantify the effects of radial slits on enhancing conformability and provide a practical guideline for using these slits to improve conformability from 40% to more than 90%.

Effects of resourcefulness on internet game addiction among college students: The mediating role of anxiety and the moderating role of gender.

Introduction: The mechanism of internet game addiction is unclear. Whether anxiety mediates between resourcefulness and internet game addiction and whether gender affect its mediation role have not been studied previously. Methods: A total of 4,889 college students from a college in southwest China were included in this study to complete the investigation, in which three questionnaires were used for evaluation. Results: Pearson's correlation analysis indicated a remarkable negative correlation between resourcefulness with internet game addiction and anxiety, as well as a significant positive correlation between anxiety and this addiction. The structural equation model confirmed the mediation role of anxiety. The multi-group analysis confirmed the moderating role of gender in the mediation model. Discussion: These findings have advanced the results of existing studies, indicating the buffering effect of resourcefulness on internet game addiction and revealing the potential mechanism of this relationship.