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

AIMS: Proper arteriogenesis after tissue ischemia 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 ischemia-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 ischemic injury in 12-week high-fat diet fed mice. Additionally, we found that Raptor deficiency dampened vascular endothelial growth factor receptor 2 (VEGFR2) signaling in endothelial cells 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 endothelial cell-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. CONCLUSIONS: Collectively, our study demonstrated the crucial role of endothelial Raptor in promoting ischemia-induced arteriogenesis in T2DM by mediating VEGFR2 signaling. 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.

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.

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.

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.

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.

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.

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.

Applying MAP-MRI to Identify the WHO Grade and Main Genetic Features of Adult-type Diffuse Gliomas: A Comparison of Three Diffusion-weighted MRI Models.

RATIONALE AND OBJECTIVES: Currently, there is no noninvasive method to effectively judge the genotype of diffuse gliomas. We explored the association between mean apparent propagator-MRI (MAP-MRI) and WHO grade 2/3, IDH 1/2 mutations, and chromosome 1p/19q combined deletion genotypes in adult-type diffuse gliomas and compared it with the diagnostic efficiency of diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI). MATERIALS AND METHODS: We prospectively recruited 67 participantshistopathologically diagnosed with adult-type diffuse gliomas. Routine MRI, DKI, and DSI were performed before surgery. The extreme and average partial diffusion indexes of solid tumors were measured. A comprehensive assessment of statistically significant diffusion parameters was performed after Bonferroni correction, including ROC curves, correct classification percentage (CCP), integrated discrimination improvement (IDI), net reclassification improvement (NRI), and k-fold cross validation. RESULTS: For differentiating WHO grade 2/3, q-space inverse variance (QIV), mean kurtosis (MK), non-Gaussianity (NG), and return to the origin probability (RTOP) were different (p' < .05), with the mean QIV exhibiting the best diagnostic efficacy and stability (AUC = 0.973, CCP = 0.906). We observed significant differences in mean diffusivity (MD), mean square displacement, QIV, MK, and RTOP between the IDH wild-type and IDH mutant groups (p' < .001) (AUC, 0.806-0.978) and MAP-MRI showed a higher IDI than DTI and DKI (0.094-0.435, NRI > 0, respectively). For the chromosome 1p/19q combined deletion, the minimum QIV was different between the overall (p' < .05) and no significant differences  in MD and MK was observed. CONCLUSION: MAP-MRI effectively predicts the WHO grade 2/3, IDH 1/2 mutations, and chromosome 1p/19q combined deletion in adult-type diffuse gliomas, and it may perform better than DTI and DKT.

Evaluation of diffuse glioma grade and proliferation activity by different diffusion-weighted-imaging models including diffusion kurtosis imaging (DKI) and mean apparent propagator (MAP) MRI.

PURPOSE: To evaluate two advanced diffusion models, diffusion kurtosis imaging and the newly proposed mean apparent propagation factor-magnetic resonance imaging, in the grading of gliomas and the assessing of their proliferative activity. METHODS: Fifty-nine patients with clinically diagnosed and pathologically proven gliomas were enrolled in this retrospective study. All patients underwent DKI and MAP-MRI scans. Manually outline the ROI of the tumour parenchyma. After delineation, the imaging parameters were extracted using only the data from within the ROI including mean diffusion kurtosis (MK), return-to-origin probability (RTOP), Q-space inverse variance (QIV) and non-Gaussian index (NG), and the differences in each parameter in the classification of glioma were compared. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of these parameters. RESULTS: MK, NG, RTOP and QIV were significantly different amongst the different grades of glioma. MK, NG and RTOP had excellent diagnostic value in differentiating high-grade from low-grade glioma, with largest areas under the curve (AUCs; 0.929, 0.933 and 0.819, respectively; P < 0.01). MK and NG had the largest AUCs (0.912 and 0.904) when differentiating grade II tumours from III tumours (P < 0.01) and large AUCs (0.791 and 0.786) when differentiating grade III from grade IV tumours. Correlation analysis of tumour proliferation activity showed that MK, NG and QIV were strongly correlated with the Ki-67 LI (P < 0.001). CONCLUSION: MK, RTOP and NG can effectively represent the microstructure of these altered tumours. Multimodal diffusion-weighted imaging is valuable for the preoperative evaluation of glioma grade and tumour proliferative activity.

Multicenter analysis on the non-suicidal self-injury behaviors and related influencing factors-A case study of left-behind children in northeastern Sichuan.

BACKGROUND: Few studies have been conducted focusing on the non-suicidal self-injury (NSSI) incidence rate and influencing factors among left-behind children in northeastern Sichuan, China. In this study, we investigated the incidence rate of the NSSI behaviors, levels of anxiety and depression in left-behind children in northeastern Sichuan, and relevant sociodemographic factors. METHODS: The NSSI behaviors were identified using the Ottawa Self-injury Inventory (Chinese version). Its incidence rate and related influencing factors were evaluated by Cluster sampling; the Depression Anxiety Stress Scale-21 Items (DASS-21) was adopted to assess the levels of anxiety, depression, and stress. RESULTS: A total of 9450 adolescents met the inclusion criteria, including 543 with NSSI behaviors, and the prevalence of NSSI was 5.7 %. There were 3596 left-behind children, and 243 of them had NSSI behaviors, the NSSI incidence in left-behind children was 6.8 %. There were 5854 non-left-behind children, and the NSSI incidence in non-left-behind children was 5.1 %. Left-behind children's NSSI behaviors were remarkably correlated with five risk factors: being female (OR = 2.411, 95%CI = 1.773-3.279), parents' divorce (OR = 1.742, 95%CI = 1.262-2.404), elder age (OR = 1.120, 95%CI = 1.028-1.219), severe depression (OR = 1.212, 95%CI = 1.148-1.281), and high anxiety (OR = 1.170, 95%CI = 1.093-1.251). LIMITATIONS: This is a cross-sectional study, we cannot probe into the causality between NSSI behaviors and corresponding risk factors. Reporting and recalling biases may be unavoidable as questionnaires are performed by self-rating scales and retrospective reports. CONCLUSION: The NSSI behaviors are common in left-behind children in northeastern Sichuan. This study proposes that prevention and intervention measures are necessary for the healthy growth of such children.

Unstructured Self-Assembled Molecular Lamella Induces Ultrafast Thermal Transfer through a Cathode/Separator Interphase in Lithium-Ion Batteries.

Thermal issues associated with lithium-ion batteries (LIBs) can dramatically affect their life cycle and overall performance. However, the effective heat transfer is deeply restrained by the high thermal resistance across the cathode (lithium cobalt oxide, LCO)-separator (polyethylene, PE) interface. This work presents a new approach to tailoring the interfacial thermal resistance, namely, unstructured self-assembled lamella (USAL). Compared to the popular self-assembled monolayers, although the USAL gives a redundant interface and amorphous molecule patterns, it can also provide many benefits, including easy assembly, more thermal bridges, and ready pressurization. Three small organic molecules (SOMs) were assembled into an LCO-PE interface, providing unique functional groups, -NH2, -SH, and -CH3, to illustrate its energy conversion efficiency. Through molecular dynamics simulations, our results show that the USAL can facilitate interfacial heat transfer remarkably. A 3-aminopropyl trimethoxysilane (APTMS)-coated LCO-PE system with 11.4 Å thickness demonstrates the maximum enhancement of thermal conductance, about 320% of the pristine system. Such enhancement is attributed to the developed double heat passages by strong non-bonded interactions across LCO-SOM and PE-SOM interfaces, a tuned temperature field, and high compatibility between SOMs and PE. Importantly, due to SOMs' amorphous morphology, the pressure can be imposed and further enhance the interfacial heat transfer. Results show the improved thermal conductance rises the most for the APTMS-coated LCO-PE system with 11.4 Å thickness at 10 GPa, almost 685% higher than that of the pristine system. The high efficiency of heat transfer comes as a result of the enhanced binding strength across the LCO-SOM and SOM-PE interface, the reduced phonon scattering in PE and SOMs, and the high LCO stiffness. These investigations are expected to provide a new perspective for modulating the heat transfer across the interphase of LIBs and achieve more effective thermal management for the multi-material system.

Molecular self-assembled monolayers anomalously enhance thermal conductance across polymer-semiconductor interfaces.

Thermal issues have become increasingly important for the performance and lifetime of highly miniaturized and integrated devices. However, the high thermal resistance across the polymer/semiconductor interface greatly weakens the fast heat dissipation. In this study, applying the self-assembled monolayer (SAM) technique, organic molecules are employed as heat regulators to mediate interfacial thermal conductance (ITC) between semiconductors (silicon or Si) and polymers (polystyrene or PS). Silane-based SAM molecules with unique functional groups, such as -NH2, -CH3, -SH, and -Cl, are orderly assembled into Si-PS interfaces. Their roles in ITC and the heat transfer mechanism were systematically investigated. Molecular simulations demonstrate that the Si-PS interface decorated with SAM molecules can significantly facilitate heat transfer in varying degrees. Such a difference is primarily due to the different non-bonded interactions and compatibility between SAMs and PS. Compared with the pristine Si-PS interface, the interface incorporated with 3-chloropropyl trimethoxysilane shows the greatest improvement in ITC, about 507.02%. Such improvements are largely attributed to the SAM molecules, as the thermal bridges straighten the molecular SAM chains, develop strong non-bonded interactions with PS, provide the covalent bonding between Si and PS, exhibit a strong coupling effect between two materials' vibrational modes, and eliminate the discontinuities in the temperature field. Eventually, these demonstrations are expected to offer molecular insights to enable effective thermal management through surface engineering for critical-heat transfer materials and microelectronic devices.