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Genetic generalized epilepsies (GGE) exhibit widespread morphometric alterations in the subcortical structures. Subcortical structures are essential for understanding GGE pathophysiology, but their fine-grained morphological diversity has yet to be comprehensively investigated. Furthermore, the relationships between macroscale morphological disturbances and microscale molecular chemoarchitectures are unclear. High-resolution structural images were acquired from patients with GGE (n = 97) and sex- and age-matched healthy controls (HCs, n = 184). Individual measurements of surface shape features (thickness and surface area) of seven bilateral subcortical structures were quantified. The patients and HCs were then compared vertex-wise, and shape anomalies were co-located with brain neurotransmitter profiles. We found widespread morphological alterations in GGE and prominent disruptions in the thalamus, putamen, and hippocampus. Shape area dilations were observed in the bilateral ventral, medial, and right dorsal thalamus, as well as the bilateral lateral putamen. We found that the shape area deviation pattern was spatially correlated with the norepinephrine transporter and nicotinic acetylcholine (Ach) receptor (α4β2) profiles, but a distinct association was seen in the muscarinic Ach receptor (M1). The findings provided a comprehensive picture of subcortical morphological disruptions in GGE, and further characterized the associated molecular mechanisms. This information may increase our understanding of the pathophysiology of GGE. Genetic generalized epilepsies (GGE)exhibited widespread shape alterations in subcortical structures and these morphological anomalies linked to specific neurotransmitter profiles [ABSTRACT FROM AUTHOR]

Background: Cancer is a major public health concern and the second leading cause of death worldwide. Various studies have reported the use of serum microRNAs (miRNAs) as non-invasive biomarkers for cancer detection. However, large-scale pan-cancer studies based on serum miRNAs have been relatively scarce. Methods: An optimized machine learning workflow, combining least absolute shrinkage and selection operator (LASSO) analyses, recursive feature elimination (RFE), and fourteen kinds of machine learning algorithms, was use to screen out candidate miRNAs from 2540 serum miRNAs and constructed a potent diagnostic signature (Cancer-related Serum miRNA Signatures) for pan-cancer detection, based on a serum miRNA expression dataset of 38,223 samples. Result: Cancer-related Serum miRNA Signatures performed well in pan-cancer detection with an area under curve (AUC) of 0.999, 94.51% sensitivity, and 99.49% specificity in the external validation cohort, and represented an acceptable diagnostic performance for identifying early-stage tumors. Furthermore, the ability of multi-classification of tumors by serum miRNAs in pancreatic, colorectal, and biliary tract cancers was lower than that in other cancers, which showed accuracies of 59%, 58.5%, and 28.9%, respectively, indicating that the difference in serum miRNA expression profiles among a small number of tumor subtypes was not as significant as that between cancer samples and non-cancer controls. Conclusion: We have developed a serum miRNA signature using machine learning that may be a cost-effective risk tool for pan-cancer detection. Our findings will benefit not only the predictive diagnosis of cancer but also a preventive and more personalized screening plan. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamical responses and performances of mono-, bi-, and tri-stable nonlinear energy sinks in simultaneous vibration suppression and energy harvesting as well as solely vibration mitigation. To this end, a realizable multi-stable nonlinear energy sink composed of a bimorph cantilever beam and arrays of magnets is considered for vibration mitigation. The target vibrating structure is a simply-supported beam under a harmonic excitation. The proposed absorber can exhibit multi-stability based on the magnet gaps. First, using extended Hamilton's principle, the coupled continuous magneto-electromechanical equations governing the system are obtained. Next, the bifurcations of the absorber fixed points that lead to different stability states are analyzed. Then, the time- and frequency-responses of the coupled system are studied using time integration. The results show that the bi- and tri-stable absorbers perform well in case of strongly modulated responses. Furthermore, the response of the coupled system is verified using the harmonic balance method and pseudo-arclength continuation. Next, the potential well escape method based on the harmonic balance solution is exploited to investigate the strongly modulated response emergence and disappearance as well as its variations with the system parameters. The coupling mechanism of the nonlinear absorber to the host beam is also studied using linearization and compared with the harmonic balance solution. In addition, in order to compare the performances of the bi-stable and tri-stable absorbers, energy-based analyses are performed. The results reveal the average harvested power per average kinetic energy of the main system for a bi-stable absorber is higher than a tri-stable absorber. Furthermore, the bi-stable absorber can mitigate the host structure vibration more than the tri-stable absorber. Finally, it is observed that the bi-stable absorber suppresses the vibration more than its corresponding mono-stable absorber and harvests more energy over a broader frequency region. [ABSTRACT FROM AUTHOR]

The investigation into the distinctive difference of gait is of significance for the clinical diagnosis of neurodegenerative diseases. However, human gait is affected by many factors like behavior, occupation and so on, and they may confuse the gait differences among Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. For the purpose of examining distinctive gait differences of neurodegenerative diseases, this study extracts various features from both vertical ground reaction force and time intervals. Moreover, refined Lempel–Ziv complexity is proposed considering the detailed distribution of signals based on the median and quartiles. Basic features (mean, coefficient of variance, and the asymmetry index), nonlinear dynamic features (Hurst exponent, correlation dimension, largest Lyapunov exponent), and refined Lempel–Ziv complexity of different neurodegenerative diseases are compared statistically by violin plot and Kruskal–Wallis test to reveal distinction and regularities. The comparative analysis results illustrate the gait differences across these neurodegenerative diseases by basic features and nonlinear dynamic features. Classification results by random forest indicate that the refined Lempel–Ziv complexity can robustly enhance the diagnosis accuracy when combined with basic features. [ABSTRACT FROM AUTHOR]

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: To assess whether the diagnostic performance of Sonazoid contrast-enhanced ultrasound (SZUS) is non-inferior to that of SonoVue contrast-enhanced ultrasound (SVUS) in diagnosing hepatocellular carcinoma (HCC) in individuals with high risk. Materials and Methods: This prospective study was conducted from October 2020 to May 2022 and included participants with a high risk of HCC who underwent SZUS and SVUS. All lesions were confirmed by clinical or pathological diagnosis. Each nodule was classified according to the Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System version 2017 (CEUS LI-RADS v2017) for SVUS and SZUS and the modified CEUS LI-RADS (using Kupffer phase defect instead of late and mild washout) for SZUS. The diagnostic performance of both two modalities for all observations was compared. Analysis of the vascular phase and Kupffer phase imaging characteristics of CEUS was performed. Results: One hundred and fifteen focal liver lesions from 113 patients (94 HCCs, 12 non-HCC malignancies, and 9 benign lesions) were analysed. According to CEUS LI-RADS (v2017), SVUS and SZUS showed similar sensitivity (71.3% vs. 72.3%) and specificity (85.7% vs. 81.0%) in HCC diagnosis. However, the modified CEUS LI-RADS did not significantly improve the diagnostic efficacy of Sonazoid compared to CEUS LI-RADS v2017, having equivalent sensitivity (73.4% vs. 72.3%) and specificity (81.0% vs. 81.0%). The agreement between SVUS and SZUS for all observations was 0.610 (95% CI 0.475, 0.745), while for HCCs it was 0.452 (95% CI 0.257, 0.647). Conclusion: Using LI-RADS v2017, SZUS and SVUS showed non-inferior efficacy in evaluating HCC lesions. In addition, adding Kupffer phase defects to SZUS does not notably improve its diagnostic efficacy. [ABSTRACT FROM AUTHOR]

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

RNA modifications affect fundamental biological processes and diseases and are a research hotspot. Several micro-RNAs (miRNAs) exhibit genetic variant-targeted RNA modifications that can greatly alter their biofunctions and influence their effect on cancer. Therefore, the potential role of these miRNAs in cancer can be implicated in new prevention and treatment strategies. In this study, we determined whether RMvar-related miRNAs were closely associated with tumorigenesis and identified cancer-specific signatures based on these miRNAs with variants targeting RNA modifications using an optimized machine learning workflow. An effective machine learning workflow, combining least absolute shrinkage and selection operator analyses, recursive feature elimination, and nine types of machine learning algorithms, was used to screen candidate miRNAs from 504 serum RMvar-related miRNAs and construct a diagnostic signature for cancer detection based on 43,047 clinical samples (with an area under the curve value of 0.998, specificity of 93.1%, and sensitivity of 99.3% in the validation cohort). This signature demonstrated a satisfactory diagnostic performance for certain cancers and different conditions, including distinguishing early-stage tumors. Our study revealed the close relationship between RMvar-related miRNAs and tumors and proposed an effective cancer screening tool. [ABSTRACT FROM AUTHOR]

Deciphering the complex relationship between neuroanatomical connections and functional activity in primate brains remains a daunting task, especially regarding the influence of monosynaptic connectivity on cortical activity. Here, we investigate the anatomical-functional relationship and decompose the neuronal-tracing connectome of marmoset brains into a series of eigenmodes using graph signal processing. These cellular connectome eigenmodes effectively constrain the cortical activity derived from resting-state functional MRI, and uncover a patterned cellular-functional decoupling. This pattern reveals a spatial gradient from coupled dorsal-posterior to decoupled ventral-anterior cortices, and recapitulates micro-structural profiles and macro-scale hierarchical cortical organization. Notably, these marmoset-derived eigenmodes may facilitate the inference of spontaneous cortical activity and functional connectivity of homologous areas in humans, highlighting the potential generalizing of the connectomic constraints across species. Collectively, our findings illuminate how neuronal-tracing connectome eigenmodes constrain cortical activity and improve our understanding of the brain's anatomical-functional relationship. The relationship between neuroanatomical connections and functional activity is still unclear. Using graph signal processing, the authors show neuronal tracing connectome eigenmodes constrain cortical activity in marmosets. [ABSTRACT FROM AUTHOR]

Osteoporosis is a major public health concern that significantly increases the risk of fractures. The aim of this study was to develop a Machine Learning based predictive model to screen individuals at high risk of osteoporosis based on chronic disease data, thus facilitating early detection and personalized management. A total of 10,000 complete patient records of primary healthcare data in the German Disease Analyzer database (IMS HEALTH) were included, of which 1293 diagnosed with osteoporosis and 8707 without the condition. The demographic characteristics and chronic disease data, including age, gender, lipid disorder, cancer, COPD, hypertension, heart failure, CHD, diabetes, chronic kidney disease, and stroke were collected from electronic health records. Ten different machine learning algorithms were employed to construct the predictive mode. The performance of the model was further validated and the relative importance of features in the model was analyzed. Out of the ten machine learning algorithms, the Stacker model based on Logistic Regression, AdaBoost Classifier, and Gradient Boosting Classifier demonstrated superior performance. The Stacker model demonstrated excellent performance through ten-fold cross-validation on the training set and ROC curve analysis on the test set. The confusion matrix, lift curve and calibration curves indicated that the Stacker model had optimal clinical utility. Further analysis on feature importance highlighted age, gender, lipid metabolism disorders, cancer, and COPD as the top five influential variables. In this study, a predictive model for osteoporosis based on chronic disease data was developed using machine learning. The model shows great potential in early detection and risk stratification of osteoporosis, ultimately facilitating personalized prevention and management strategies. [ABSTRACT FROM AUTHOR]

Modern data mining techniques using machine learning (ML) and deep learning (DL) algorithms have been shown to excel in the regression-based task of materials property prediction using various materials representations. In an attempt to improve the predictive performance of the deep neural network model, researchers have tried to add more layers as well as develop new architectural components to create sophisticated and deep neural network models that can aid in the training process and improve the predictive ability of the final model. However, usually, these modifications require a lot of computational resources, thereby further increasing the already large model training time, which is often not feasible, thereby limiting usage for most researchers. In this paper, we study and propose a deep neural network framework for regression-based problems comprising of fully connected layers that can work with any numerical vector-based materials representations as model input. We present a novel deep regression neural network, iBRNet, with branched skip connections and multiple schedulers, which can reduce the number of parameters used to construct the model, improve the accuracy, and decrease the training time of the predictive model. We perform the model training using composition-based numerical vectors representing the elemental fractions of the respective materials and compare their performance against other traditional ML and several known DL architectures. Using multiple datasets with varying data sizes for training and testing, We show that the proposed iBRNet models outperform the state-of-the-art ML and DL models for all data sizes. We also show that the branched structure and usage of multiple schedulers lead to fewer parameters and faster model training time with better convergence than other neural networks. Scientific contribution: The combination of multiple callback functions in deep neural networks minimizes training time and maximizes accuracy in a controlled computational environment with parametric constraints for the task of materials property prediction. [ABSTRACT FROM AUTHOR]

This paper proposes an entropy-weighted local intensity clustering-based model for segmenting intensity inhomogeneous images caused by the bias field. The variational model minimizes an energy functional consisting of a regularization term of the total length of object boundaries and a data-fitting term partitioning the image. Specifically, the total length is approximated by the convolution of the heat kernel with the characteristic functions of the segmented regions of interest. The data-fitting term is derived from the multiplicative bias field resulting in a local intensity clustering property and further weighted by the local entropy. One of the most advantageous features of the proposed model is that it can simultaneously segment the image and estimate the bias field for intensity inhomogeneity correction. Moreover, a simple and efficient iterative convolution-thresholding scheme can be applied to realize the model, exhibiting the energy-decaying property. Finally, numerical simulations are carried out to validate the superior performance of the approach. [ABSTRACT FROM AUTHOR]

Objectives: Evidence on the health-related quality of life (HRQoL) among Chinese rural populations and its influence factors were limited. This study aimed to describe the distribution of HRQoL assessed by EQ-5D-5L and its determinants among a Chinese rural population. Methods: A total of 23,510 eligible participants (9542 men and 13,968 women) from the Henan rural cohort study were included. Tobit regression and generalized linear models were performed to investigate the associations between demographic characteristics, lifestyle factors, common chronic diseases, and HRQoL. Results: Of all respondents, the most frequently reported problem was pain/discomfort dimension (23.05%), followed by mobility (12.72%), anxiety/depression (7.77%), and usual activities (6.45%), while the least reported was the self-care dimension (3.84%). The more problems reported in all dimensions with age increased except anxiety/depression. The mean (standard deviation) utility index and VAS score were 0.954 (0.111) and 78.34 (14.80), respectively. The regression analysis indicated that increasing age, former drinkers, poor sleep quality, and suffering from common chronic diseases were significantly associated with low HRQoL, while high education level, average monthly income, and physical activity were significantly associated with high HRQoL. Conclusion: This study described the distribution of HRQoL and its influence factors among the Chinese rural population, which was helpful for medical institutions and policymakers to allocate medical resources and better understand HRQoL among the Chinese rural population. [ABSTRACT FROM AUTHOR]

Epilepsies are a group of neurological disorders characterized by abnormal spontaneous brain activity, involving multiscale changes in brain functional organizations. However, it is not clear to what extent the epilepsy-related perturbations of spontaneous brain activity affect macroscale intrinsic dynamics and microcircuit organizations, that supports their pathological relevance. We collect a sample of patients with temporal lobe epilepsy (TLE) and genetic generalized epilepsy with tonic-clonic seizure (GTCS), as well as healthy controls. We extract massive temporal features of fMRI BOLD time-series to characterize macroscale intrinsic dynamics, and simulate microcircuit neuronal dynamics used a large-scale biological model. Here we show whether macroscale intrinsic dynamics and microcircuit dysfunction are differed in epilepsies, and how these changes are linked. Differences in macroscale gradient of time-series features are prominent in the primary network and default mode network in TLE and GTCS. Biophysical simulations indicate reduced recurrent connection within somatomotor microcircuits in both subtypes, and even more reduced in GTCS. We further demonstrate strong spatial correlations between differences in the gradient of macroscale intrinsic dynamics and microcircuit dysfunction in epilepsies. These results emphasize the impact of abnormal neuronal activity on primary network and high-order networks, suggesting a systematic abnormality of brain hierarchical organization. An fMRI study suggests that epilepsy-related perturbations of spontaneous brain activity affect macroscale intrinsic dynamics and microcircuit organizations, and that they are highly spatially correlated. [ABSTRACT FROM AUTHOR]

The largest ever primate and one of the largest of the southeast Asian megafauna, Gigantopithecus blacki1, persisted in China from about 2.0 million years until the late middle Pleistocene when it became extinct2–4. Its demise is enigmatic considering that it was one of the few Asian great apes to go extinct in the last 2.6 million years, whereas others, including orangutan, survived until the present5. The cause of the disappearance of G. blacki remains unresolved but could shed light on primate resilience and the fate of megafauna in this region6. Here we applied three multidisciplinary analyses—timing, past environments and behaviour—to 22 caves in southern China. We used 157 radiometric ages from six dating techniques to establish a timeline for the demise of G. blacki. We show that from 2.3 million years ago the environment was a mosaic of forests and grasses, providing ideal conditions for thriving G. blacki populations. However, just before and during the extinction window between 295,000 and 215,000 years ago there was enhanced environmental variability from increased seasonality, which caused changes in plant communities and an increase in open forest environments. Although its close relative Pongo weidenreichi managed to adapt its dietary preferences and behaviour to this variability, G. blacki showed signs of chronic stress and dwindling populations. Ultimately its struggle to adapt led to the extinction of the greatest primate to ever inhabit the Earth.A multiproxy record of Gigantopithecus blacki provides insights into the ecological context of this species, which became extinct around 250,000 years ago, when increased seasonality led to a change in forest cover. [ABSTRACT FROM AUTHOR]

In recent years, materials science and engineering have increasingly focused on advanced composite powders. This study examines the preparation of micro–micro Ti-6Al-4V composite powders by electrostatic adsorption (EA). The necessity of this research lies in the demand for optimizing the Ti-6Al-4V composite powder formation process window for high-performance applications across industries. Achieving optimal EA parameters is crucial for enhancing the quality and efficiency of the powder formation process. In this study, the effect of stirring duration and guest particle loading on the EA process is investigated. The stirring time (1 to 25 min) and guest particle loading (10 to 60%) of the solution are varied to determine the ideal conditions for high adsorption efficiency. It was found that shorter stirring durations (1 min) and a lower guest particle load (10%) have a significant effect on adsorption efficiency. The results were analyzed using the DOE approach to guide future optimization of the process window. The study fills a research gap by utilizing the DOE approach to investigate stirring duration and guest particle loading, providing insights for optimizing the EA process for micro–micro Ti-6Al-4V composite powder. This approach has the potential to enhance cost-effective, durable composite powder production with broad applications in industries like aerospace and automotive. While our research currently focuses on stirring duration and guest particle loading, the application of the DOE approach lays the groundwork for future investigations into additional EA process parameters, such as pH value, particle size, and temperature to expand our understanding of efficient composite powder formation. [ABSTRACT FROM AUTHOR]

In this paper, we first derive a theoretical basis for spherical conformal parameterizations between a simply connected closed surface S and a unit sphere S 2 by minimizing the Dirichlet energy on C ¯ with stereographic projection. The Dirichlet energy can be rewritten as the sum of the energies associated with the southern and northern hemispheres and can be decreased under an equivalence relation by alternatingly solving the corresponding Laplacian equations. Based on this theoretical foundation, we develop a modified Dirichlet energy minimization with nonequivalence deflation for the computation of the spherical conformal parameterization between S and S 2 . In addition, under some mild conditions, we verify the asymptotically R-linear convergence of the proposed algorithm. Numerical experiments on various benchmarks confirm that the assumptions for convergence always hold and demonstrate the efficiency, reliability and robustness of the developed modified Dirichlet energy minimization. [ABSTRACT FROM AUTHOR]

Modern data mining methods have demonstrated effectiveness in comprehending and predicting materials properties. An essential component in the process of materials discovery is to know which material(s) will possess desirable properties. For many materials properties, performing experiments and density functional theory computations are costly and time-consuming. Hence, it is challenging to build accurate predictive models for such properties using conventional data mining methods due to the small amount of available data. Here we present a framework for materials property prediction tasks using structure information that leverages graph neural network-based architecture along with deep-transfer-learning techniques to drastically improve the model's predictive ability on diverse materials (3D/2D, inorganic/organic, computational/experimental) data. We evaluated the proposed framework in cross-property and cross-materials class scenarios using 115 datasets to find that transfer learning models outperform the models trained from scratch in 104 cases, i.e., ≈90%, with additional benefits in performance for extrapolation problems. We believe the proposed framework can be widely useful in accelerating materials discovery in materials science. [ABSTRACT FROM AUTHOR]

Objective: To explore the neuroimage change in Parkinson's disease (PD) patients with cognitive impairments, this study investigated the correlation between plasma biomarkers and morphological brain changes in patients with normal cognition and mild cognitive impairment. The objective was to identify the potential target deposition regions of the plasma biomarkers and to search for the relevant early neuroimaging biomarkers on the basis of different cognitive domains. Methods: Structural brain MRI and diffusion weighted images were analyzed from 49 eligible PD participants (male/female: 27/22; mean age: 73.4 ± 8.5 years) from a retrospective analysis. Plasma levels of α-synuclein, amyloid beta peptide, and total tau were collected. A comprehensive neuropsychological assessment of the general and specific cognitive domains was performed. Difference between PD patients with normal cognition and impairment was examined. Regression analysis was performed to evaluate the correlation between image-derived index and plasma biomarkers or neuropsychological assessments. Results: Significant correlation was found between plasma Aβ-42 level and fractional anisotropy of the middle occipital, angular, and middle temporal gyri of the left brain, as well as plasma T-tau level and the surface area of the isthmus or the average thickness of the posterior part of right cingulate gyrus. Visuospatial and executive function is positively correlated with axial diffusivity in bilateral cingulate gyri. Conclusion: In nondemented PD patients, the target regions for plasma deposition might be located in the cingulate, middle occipital, angular, and middle temporal gyri. Changes from multiple brain regions can be correlated to the performance of different cognitive domains. Clinical relevance statement: Cognitive impairment in Parkinson's disease is primarily linked to biomarkers associated with Alzheimer's disease rather than those related to Parkinson's disease and resembles the frontal variant of Alzheimer's disease, which may guide management strategies for cognitive impairment in Parkinson's disease. Key Points: • Fractional anisotropy, surface area, and thickness in the cingulate, middle occipital, angular, and middle temporal gyri can be significantly correlated with plasma Aβ-42 and T-tau level. • Axial diffusivity in the cingulate gyri was correlated with visuospatial and executive function. • The pattern of cognitive impairment in Parkinson's disease can be similar to the frontal variant than typical Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Evidence shows the relationships of individual environmental PAHs by their urinary metabolites with relative telomere length (RTL), which may be affected by biological gender differences. Since plasma parent PAHs are not metabolized, it may reflect human exposure to PAHs more realistically in daily life. Thus, exploring joint associations between plasma parent PAHs and RTL is urgent, which may identify the major contributor to its adverse effect. In this study, 2577 participants were obtained from the Henan Rural Cohort. The level of PAHs in blood samples was detected by gas chromatography coupled with tandem mass spectrometry. RTL in blood samples was detected by quantitative polymerase chain reaction. Generalized linear models or quantile g-computation were performed to evaluate the associations between the individual or a mixture of PAHs and RTL. Results from generalized linear models showed that each unit increment in BghiP value corresponded to a 0.098 (95%CI: 0.067, 0.129) increment in RTL for men; each unit increment in BaP, BghiP and Flu value corresponded to a 0.041 (95%CI: 0.014, 0.068), 0.081 (95%CI: 0.055, 0.107) and 0.016 (95%CI: 0.005, 0.027) increment in RTL for women. Results from quantile-g computation revealed that each one-quantile increment in the mixture of 10 PAHs corresponded to a 0.057 (95%CI: 0.021, 0.094) and 0.047 (95%CI: 0.003, 0.091) increment in RTL values of women and men, but these associations were mainly ascribed to three PAHs for women (BaP, Flu and BghiP) and men (BaP, BghiP and Pyr), respectively. Similar results were found in smoking men and cooking women without smoking. Our study found that exposure to 10 PAHs mixture was positively associated with RTL across gender, mainly attributed to Flu, BaP and BghiP, implicating that gender-specific associations may be ascribed to tobacco and cooking smoke pollution. The findings provided clues for effective measures to control PAHs pollutants-related aging disease. Clinical trial registration The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375. [ABSTRACT FROM AUTHOR]

Flexor hallucis longus (FHL) transfer is an effective surgery in treating insertional Achilles tendinopathy (IAT). However, limited data exist regarding the post-surgery changes in the transferred FHL. The study aimed to compare the sequential changes and hypertrophy of FHL after isolated FHL transfer (FHLT). We retrospectively enrolled patients who underwent isolated FHLT for insertional Achilles pathology from 2015 to 2020 and divided them into two groups based on whether reattachment of the residue Achilles stump to the FHL was performed or not. We recorded demographic characteristics, MRI parameters, and functional outcome. We also analyzed the correlation between the collected data and FHL hypertrophy. Results revealed no significant differences in most MRI parameters of FHL and functional outcomes between the groups. However, the fat distribution within the FHL showed significant reduction and notable 20.2% hypertrophy after FHLT. Interestingly, the hypertrophy of the FHL was significantly more pronounced in the non-reattached group. Furthermore, we observed a positive correlation between the follow-up period and FHL hypertrophy. In conclusion, the FHL demonstrated significant enlargement over time following FHLT. The compensatory hypertrophy of the transferred FHL was particularly evident and the cumulative incidences of FHL enlargement over time were higher in the non-reattached groupcompared to reattached group. However, both reattachment and non-reattachment of Achilles stump on FHL transfer for insertional Achilles tendinopathy carried similar postoperative functional outcomes. [ABSTRACT FROM AUTHOR]

The role of surgical resection in primary central nervous system lymphoma (PCNSL) was not recognized until recently. However, prognostic factors for surgically treated PCNSL remain unclear. In the present study, we aimed to identify and compare the prognostic value of comorbidity indices and immunohistochemical markers in patients with surgically and non-surgically treated PCNSL. This retrospective single-center study analyzed patients who underwent either surgical resection or stereotactic biopsy for newly diagnosed PCNSL between January 2012 and December 2021. Clinical demographics, comorbidity indices, and immunohistochemical markers were analyzed. We included 23 and 18 patients who underwent stereotactic biopsy and surgical resection, respectively. The median overall survival (OS) was 11.05 months. Using multivariate Cox regression, we identified pretreatment prognostic nutritional index (PNI) (p = 0.009), positive BCL2 staining (p = 0.026), and infratentorial involvement (p = 0.004) as independent prognostic factors of OS. Predictors of progression-free survival (PFS) included PNI (p = 0.040), infratentorial involvement (p = 0.021), and surgical resection for PCNSL (p = 0.048). Subgroup analyses revealed that positive BCL2 (p = 0.048) and PD-L1 (p = 0.037) staining were associated with worse OS in the biopsy group. PNI and infratentorial involvement could significantly impact both OS and PFS in patients with PCNSL. Surgical resection could predict favorable PFS but not OS. Moreover, BCL2 and PD-L1 expression can be employed as prognostic markers in these patients. [ABSTRACT FROM AUTHOR]

A model-based optimal dispatch framework was proposed to optimize operation of residential flexible loads considering their real-life operating characteristics, energy-related occupant behavior, and the benefits of different stakeholders. A pilot test was conducted for a typical household. According to the monitored appliance-level data, operating characteristics of flexible loads were identified and the models of these flexible loads were developed using multiple linear regression and K-means clustering methods. Moreover, a data-mining approach was developed to extract the occupant energy usage behavior of various flexible loads from the monitored data. Occupant behavior of appliance usage, such as daily turn-on times, turn-on moment, duration of each operation, preference of temperature setting, and flexibility window, were determined by the developed data-mining approach. Based on the established flexible load models and the identified occupant energy usage behavior, a many-objective nonlinear optimal dispatch model was developed aiming at minimizing daily electricity costs, occupants' dissatisfaction, CO2 emissions, and the average ramping index of household power profiles. The model was solved with the assistance of the NSGA-III and TOPSIS methods. Results indicate that the proposed framework can effectively optimize the operation of household flexible loads. Compared with the benchmark, the daily electricity costs, CO2 emissions, and average ramping index of household power profiles of the optimal plan were reduced by 7.3%, 6.5%, and 14.4%, respectively, under the TOU tariff, while those were decreased by 9.5%, 8.8%, and 23.8%, respectively, under the dynamic price tariff. The outputs of this work can offer guidance for the day-ahead optimal scheduling of household flexible loads in practice. [ABSTRACT FROM AUTHOR]

Background: Risks of adverse ecological effects of copper (Cu) consider of water quality parameters were not fully understood in China. Here, a national-scale exposure of Cu in Chinese surface water was investigated, and the first report using multiple linear regression approach to predict and correct toxicity data based on water chemistries in China. Risk of Cu was overestimated without considering water quality parameters in the previous studies. Results: Under prevalent water quality conditions of hardness = 150.0 mg/L, pH = 7.8, and dissolved organic carbon (DOC) = 3.0 mg/L, across China, the predicted no effect concentration for total, dissolved Cu was 9.71 μg/L. Based on results of the preliminary risk quotients method, 1.19% (a total of 43 in 3610 sites) were classified as "high risk", only one sixth of the percentage of sites with "high risk" than the proportion predicted when not considering water quality parameters, which was 7.51%. Similar results were obtained by application of both the margin of safety method (0.71% compared to 2.81%) and joint probability curve method (3.34% compared to 16.29%), both of which overestimated risks posed by Cu to aquatic organisms in China. Conclusion: After correcting for bioavailability based on water quality parameters, consider both concentrations and frequencies during ecological risk assessment, regions of China at greatest risk from adverse effects of Cu were the Hai River (Haihe), Huai Rivers (Huaihe) and Chao Lake. These findings provide a comprehensive method for a more accurate assessment of risks of adverse effects of Cu to aquatic life in surface waters. [ABSTRACT FROM AUTHOR]

Previous studies have shown that calcium (Ca), magnesium (Mg), and Ca/Mg ratio are associated with inflammation and metabolic disorders, but their relationship with non-alcoholic fatty liver disease (NAFLD) is unclear. Thus, we aimed to explore the association between Ca, Mg, Ca/Mg ratio, and NAFLD in Chinese adults. We conducted a case-control study based on the Kailuan Cohort in China, including 1816 cases and 1111 gender- and age-matched controls. Dose-response relationships between blood Ca, Mg, Ca/Mg ratio, and NAFLD were evaluated using restricted cubic splines. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. A negative association between blood Ca (overall association P < 0.001 and linear association P < 0.001) and NAFLD as well as Ca/Mg ratio (overall association P = 0.002 and linear association P = 0.024) and NAFLD was observed. Compared with the highest quartile, the adjusted OR (95% CI) for the lowest quartile of Ca and Ca/Mg ratio was 2.116 (1.679–2.667) and 1.358 (1.076–1.713), respectively. A U-shaped relationship was found for blood Mg and NAFLD, with the highest OR of 1.685 in the lowest quartile group when using the second quartile as a reference. Additionally, we observed the interaction between alanine aminotransferase and blood Ca (P = 0.024), total cholesterol (P = 0.017), low-density lipoprotein-cholesterol (P = 0.013), and blood Mg, as well as total cholesterol and Ca/Mg ratio (P = 0.014). Lower blood Ca and Ca/Mg ratio were significantly associated with the risk of NAFLD. Liver function or lipid metabolism parameters may modify their association, suggesting an individualized prevention strategy for NAFLD. [ABSTRACT FROM AUTHOR]

Contemporary materials science has seen an increasing application of various artificial intelligence techniques in an attempt to accelerate the materials discovery process using forward modeling for predictive analysis and inverse modeling for optimization and design. Over the last decade or so, the increasing availability of computational power and large materials datasets has led to a continuous evolution in the complexity of the techniques used to advance the frontier. In this Review, we provide a high-level overview of the evolution of artificial intelligence in contemporary materials science for the task of materials property prediction in forward modeling. Each stage of evolution is accompanied by an outline of some of the commonly used methodologies and applications. We conclude the work by providing potential future ideas for further development of artificial intelligence in materials science to facilitate the discovery, design, and deployment workflow. [ABSTRACT FROM AUTHOR]

Focal epilepsy accounts for 60% of all forms of epilepsy, but the pathogenic mechanism is not well understood. In this study, three novel mutations in NPRL3 (nitrogen permease regulator-like 3), c.937_945del, c.1514dupC and 6,706-bp genomic DNA (gDNA) deletion, were identified in three families with focal epilepsy by linkage analysis, whole exome sequencing (WES) and Sanger sequencing. NPRL3 protein is a component of the GATOR1 complex, a major inhibitor of mTOR signaling. These mutations led to truncation of the NPRL3 protein and hampered the binding between NPRL3 and DEPDC5, which is another component of the GATOR1 complex. Consequently, the mutant proteins enhanced mTOR signaling in cultured cells, possibly due to impaired inhibition of mTORC1 by GATOR1. Knockdown of nprl3 in Drosophila resulted in epilepsy-like behavior and abnormal synaptic development. Taken together, these findings expand the genotypic spectrum of NPRL3-associated focal epilepsy and provide further insight into how NPRL3 mutations lead to epilepsy. [ABSTRACT FROM AUTHOR]

In this paper, a non-pneumatic tire (NPT) based on the bionic petal structure has been proposed to have high load carrying capacity in low stress level. Firstly, according to GB/T 2977-2008 truck tire specifications, the numerical models of bionic petal NPTs (BP-NPTs) for five different spokes are developed. A set of third-order Bezier curves is introduced to control the geometric configuration. Then, the static and dynamic characteristics of BP-NPTs are investigated numerically, and compared with typical NPTs like Tweel and Hexagonal Honeycomb non-pneumatic wheel (NPW). The results indicate that BP-NPTs have better performance by taking all of these factors into consideration. Also, the influence law of key parameters including the curvature and thickness distribution on the load carrying capacity, the maximum local stresses of spokes and tread under static or dynamic load are obtained. Finally, a multi-objective optimization design method by involving the Hammersley test design, moving least-square agent model and particle swarm optimization is proposed to optimize BP-NPTs. The results demonstrate that the performance of optimized structure is significantly improved. The mass of tire and the maximum stress of spokes under dynamic loads are reduced by 9.3% and 12.3%, respectively, and the load carrying capacity is improved by 10.1%. It is indicated that the BP-NPTs have a bright future in the automobile application. [ABSTRACT FROM AUTHOR]

This study aims to explore the association of combined exposure to cooking fuel type and ambient ozone (O3) levels with hepatic fibrosis indices among rural adults. A total of 21,010 participants were derived from the Henan Rural Cohort. Information regarding cooking fuel type was collected through a questionnaire, and the concentration of ground-level O3 for each subject was obtained from the Tracking Air Pollution in China (TAP) dataset. A generalized linear model was used to examine the independent association of cooking fuel type or O3 exposure with hepatic fibrosis indices (FIB-4, APRI, and AST/ALT), and their possible interactions with advanced fibrosis were conducted. Compared to clean fuel users, solid fuel users had increased the risk of advanced fibrosis, the adjusted odds ratio (OR) of its assessment by FIB-4 1.240 (1.151, 1.336), by APRI 1.298 (1.185, 1.422), and by AST/ALT 1.135 (1.049, 1.227), respectively. Compared to low O3 exposure, the adjusted ORs of advanced fibrosis assessed by FIB-4, APRI, and AST/ALT in women with high O3 exposure were correspondingly 1.219 (1.138, 1.305), 1.110 (1.017, 1.212), and 0.883 (0.822, 0.949). The adjusted ORs of advanced fibrosis assessed by FIB-4, APRI, and AST/ALT for solid fuel users with high O3 exposure relative to clean fuel users with low O3 exposure in women were 1.557 (1.381, 1.755), 1.427 (1.237, 1.644), and 0.979 (0.863, 1.108), respectively. Significant additive effect of O3 exposure and solid fuel use on FIB-4-defined advanced fibrosis was observed in women, which was quantified by RERI (0.265, 95%CI: 0.052, 0.477), AP (0.170 95%CI: 0.045, 0.295), and SI (1.906, 95%CI: 1.058, 3.432). Solid fuel users with high O3 exposure were significantly associated with elevated hepatic fibrosis indices among rural women, suggesting that poor air quality may induce hepatocellular injury, and women might be more vulnerable to air pollution. The findings indicate that using cleaner fuels in cooking is an effective measure to maintain sustainable development of the environment and gain beneficial effect on human health. Clinical trial registration: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375 [ABSTRACT FROM AUTHOR]

Functional connectivity hierarchy is an important principle in the process of brain functional organization and an important feature reflecting brain development. However, atypical brain network hierarchy organization in Rolandic epilepsy have not been systematically investigated. We examined connectivity alteration with age and its relation to epileptic incidence, cognition, or underlying genetic factors in 162 cases of Rolandic epilepsy and 117 typically developing children, by measuring fMRI multi-axis functional connectivity gradients. Rolandic epilepsy is characterized by contracting and slowing expansion of the functional connectivity gradients, highlighting the atypical age-related change of the connectivity hierarchy in segregation properties. The gradient alterations are relevant to seizure incidence, cognition, and connectivity deficit, and development-associated genetic basis. Collectively, our approach provides converging evidence for atypical connectivity hierarchy as a system-level substrate of Rolandic epilepsy, suggesting this is a disorder of information processing across multiple functional domains, and established a framework for large-scale brain hierarchical research. Functional connectivity analyses in pediatric cases of Rolandic epilepsy and age-matched controls suggest that Rolandic epilepsy is a disorder of information processing across multiple functional neural domains. [ABSTRACT FROM AUTHOR]

Materials design aims to identify the material features that provide optimal properties for various engineering applications, such as aerospace, automotive, and naval. One of the important but challenging problems for materials design is to discover multiple polycrystalline microstructures with optimal properties. This paper proposes an end-to-end artificial intelligence (AI)-driven microstructure optimization framework for elastic properties of materials. In this work, the microstructure is represented by the Orientation Distribution Function (ODF) that determines the volume densities of crystallographic orientations. The framework was evaluated on two crystal systems, cubic and hexagonal, for Titanium (Ti) in Joint Automated Repository for Various Integrated Simulations (JARVIS) database and is expected to be widely applicable for materials with multiple crystal systems. The proposed framework can discover multiple polycrystalline microstructures without compromising the optimal property values and saving significant computational time. [ABSTRACT FROM AUTHOR]

Modern machine learning (ML) and deep learning (DL) techniques using high-dimensional data representations have helped accelerate the materials discovery process by efficiently detecting hidden patterns in existing datasets and linking input representations to output properties for a better understanding of the scientific phenomenon. While a deep neural network comprised of fully connected layers has been widely used for materials property prediction, simply creating a deeper model with a large number of layers often faces with vanishing gradient problem, causing a degradation in the performance, thereby limiting usage. In this paper, we study and propose architectural principles to address the question of improving the performance of model training and inference under fixed parametric constraints. Here, we present a general deep-learning framework based on branched residual learning (BRNet) with fully connected layers that can work with any numerical vector-based representation as input to build accurate models to predict materials properties. We perform model training for materials properties using numerical vectors representing different composition-based attributes of the respective materials and compare the performance of the proposed models against traditional ML and existing DL architectures. We find that the proposed models are significantly more accurate than the ML/DL models for all data sizes by using different composition-based attributes as input. Further, branched learning requires fewer parameters and results in faster model training due to better convergence during the training phase than existing neural networks, thereby efficiently building accurate models for predicting materials properties. [ABSTRACT FROM AUTHOR]

Differences in cellular radiosensitivity and the binding affinity of radiopharmaceuticals could directly affect the radiotherapeutic effects. In this study, we investigated the radionuclide (177Lu) induced radiosensitivity of serval non-small-cell lung cancer cells (NSCLCs) as well as the binding affinity of cetuximab to those cells. The apoptosis of NSCLCs caused by 177Lu was related to the DNA double-strand damage and was cell-type dependent. We also proved that the introduction of 177Lu to the antibody could enhance its cytotoxic effect on NSCLCs. The [177Lu]Lu-DOTA-cetuximab could accumulate in the HCC827 tumor xenografts with excellent stability according to in vivo SPECT/CT imaging and the biodistribution results. The [177Lu]Lu-DOTA-cetuximab showed high potential to be used for targeting diagnosis and radiotherapy in lung cancers. [ABSTRACT FROM AUTHOR]

The emergency room (ER) digital bedside card is a simple and important invention. It can be directly connected to the hospital information system to display important patient information in real time, reduce the workload of ER staff, improve their satisfaction, and provide useful information for patients and their families. We conducted a prospective study of ER staff using questionnaires and conducted Wilcoxon signed-rank test to compare before and after ER digital bedside card implementation in the Tamsui MacKay Memorial Hospital. Sixty participants of the ER staff joined the study before and after digital card implementation. After the ER digital bedside card was set up, the number of round trips from the nursing station to the ER bedside and the number of common questions asked by patients and their family members were significantly reduced. The cards reduced the response time for frequently asked questions by patients and their family members and significantly improved the satisfaction of ER staff. Our study showed that ER digital bedside cards reduced the workload of ER staff, provided patients and their families with useful information, and greatly improved ER staff satisfaction. This marks an important milestone in the future development of smart ER. [ABSTRACT FROM AUTHOR]

Evidence on the potential risk factors of normocytic anemia, the most prevalent morphology subtype of anemia, was scarce to date. The purpose of this study is to investigate the association of cooking fuel use or daily cooking duration with normocytic anemia and further explore the modification effect of mechanical ventilation. Participants totaling 29,448 from the Henan Rural Cohort were included in this study. Normocytic anemia was defined by hemoglobin (based on the World Health Organization criteria) and mean corpuscular volume. Cooking-related data was collected by questionnaire, and the average daily cooking duration was calculated by the weekly cooking frequency and the cooking duration of each meal. Logistic regression models were employed to derive the combined and independent associations of cooking fuel type and daily cooking duration with normocytic anemia and the modification effect of ventilation. Compared with people who never cooked, both clean fuel and solid fuel users were significantly associated with increased prevalent normocytic anemia [OR (95% CI) = 1.196 (1.014, 1.411) and 1.335 (1.105, 1.614), respectively], and the effect estimates on normocytic anemia risk were 1.260 (1.043, 1.523), 1.320 (1.104, 1.578), and 1.310 (1.081, 1.587) in participants who daily cooked < 1 h/day, 1–2 h/day, and ≥ 2 h/day, respectively. These relationships were attenuated in subjects with mechanical ventilation (All P < 0.05). Cooking with solid fuel or for a long duration are independently associated with prevalent normocytic anemia in rural population, and mechanical ventilation could attenuate these associations. Future efforts to reduce the burden of anemia could target the universal use of ventilation and solid fuel use or cooking duration reduction. Clinical trial registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375 [ABSTRACT FROM AUTHOR]

To investigate the outcomes of the modified radial tongue-shaped flap following stepwise surgery release for treating Benson type I camptodactyly of the 5th digit. A retrospective analysis involving patients with Benson type I camptodactyly of the 5th digit was performed. A total of 8 patients with 12 affected digits were included. Extent of surgical release depended on the degree of soft tissue contracture. Skin release, subcutaneous fascial release, and flexor digitorum superficialis tenotomy were performed in all 12 digits, sliding volar plate release in 2 digits, and intrinsic tendon transfer in 1 digit. The mean total passive motion of proximal interphalangeal joint significantly increased from 32.5° ± 16° to 86.3° ± 20.4°, while mean total active motion significantly increased from 22° ± 10.5° to 73.8° ± 27.5° (P < 0.05). Treatment outcomes were excellent in 6 patients, good in 3, moderate in 2, and poor in 1. Scar hyperplasia occurred in 1 patient. The radial tongue-shaped flap allowed for full coverage of the volar skin defect, and was considered aesthetically favorable. In addition, the stepwise surgical approach not only achieved good curative effects, but also allowed for individualization of treatment. [ABSTRACT FROM AUTHOR]

Potentially applied in low-noise applications such as structural health monitoring (SHM), a 1-axis piezoelectric MEMS accelerometer based on aerosol deposition is designed, fabricated, simulated, and measured in this study. It is a cantilever beam structure with a tip proof mass and PZT sensing layer. To figure out whether the design is suitable for SHM, working bandwidth and noise level are obtained via simulation. For the first time, we use aerosol deposition method to deposit thick PZT film during the fabrication process to achieve high sensitivity. In performance measurement, we obtain the charge sensitivity, natural frequency, working bandwidth and noise equivalent acceleration of 22.74 pC/g, 867.4 Hz, 10–200 Hz (within ±5% deviation) and 5.6 μ g / Hz (at 20 Hz). To demonstrate its feasibility for real applications, vibrations of a fan are measured by our designed sensor and a commercial piezoelectric accelerometer, and the results match well with each other. Moreover, shaker vibration measurement with ADXL1001 indicates that the fabricated sensor has a much lower noise level. In the end, we show that our designed accelerometer has good performance compared to piezoelectric MEMS accelerometers in relevant studies and great potential for low-noise applications compared to low-noise capacitive MEMS accelerometers. [ABSTRACT FROM AUTHOR]

Electroconvulsive therapy (ECT) is an effective neuromodulatory therapy for major depressive disorder (MDD). Treatment is associated with regional changes in brain structure and function, indicating activation of neuroplastic processes. To investigate the underlying neurobiological mechanism of macroscopic reorganization following ECT, we longitudinally (before and after ECT in two centers) collected magnetic resonance images for 96 MDD patients. Similar patterns of cortical thickness (CT) changes following ECT were observed in two centers. These CT changes were spatially colocalized with a weighted combination of genes enriched for neuroplasticity-related ontology terms and pathways (e.g., synaptic pruning) as well as with a higher density of D2/3 dopamine receptors. A multiple linear regression model indicated that the region-specific gene expression and receptor density patterns explained 40% of the variance in CT changes after ECT. In conclusion, these findings suggested that dopamine signaling and neuroplasticity-related genes are associated with the ECT-induced morphological reorganization. [ABSTRACT FROM AUTHOR]

We review two conflicting accounts of the argument-adjunct (a)symmetry found in topic structures in English and in the Romance languages. Based on the contrast, we examine topic structures in Mandarin Chinese, especially the behaviors of adjunct topics in multiple-topic sentences, embedded clauses, and non-declarative sentences. We observe a systematic extraction asymmetry in these environments between argument and circumstantial-adjunct topics, on the one hand, and manner-adjunct topics, on the other. The new findings from Mandarin Chinese suggest that the argument-adjunct asymmetry of the topic structure in English is only apparent, and the extraction asymmetry should be understood cross-linguistically as a movement-merger asymmetry (Haegeman 2012a: Adverbial clauses, main clause phenomena, and composition of the left periphery, OUP). In this respect, we propose that argument topics and circumstantial-adjunct topics in Chinese are base-generated in the fronted topic position, and manner-adjunct topics are results of syntactic movements. The topicalization asymmetry in Mandarin Chinese can be further unified with Tsai's (1994: On economizing the theory of A-bar dependencies, MIT dissertation) theory of the nominal-adverbial asymmetry of wh-dependencies in Chinese, where argument wh-phrases and circumstantial wh-phrases (including time, location, and instrumental wh-phrases) also resort to the base-generation strategy (through merger and LF binding), and manner-adverbial wh-phrases make use of the movement strategy (through LF movement). [ABSTRACT FROM AUTHOR]

Background: Inappropriate sleep duration is a potential cause of stroke. But the effect of napping on stroke risk remains controversial and the interaction between night sleep and napping duration remains unclear. The objective of this study was to examine the independent and combined effects of napping and nocturnal sleep duration on stroke. Methods: Subjects were derived from a rural cohort study in Henan. The Pittsburgh Sleep Quality Index (PSQI) was applied to identify nap duration and nocturnal sleep duration. Binary logistic regression was employed to indicate the dose–response relationships between naps, nocturnal sleep, total 24-h sleep duration, and stroke. Results: Among the 37,341 participants (14,485 men), 2600 suffered from a stroke. The odds ratios (ORs) and 95% confidence level (CI) for stroke in the fully adjusted model were 1.37 (1.13–1.65) for men nappers compared to non-nappers. Compared to 7–8 h of sleep per day, night sleep durations < 6 h and ≥ 9 h and 24-h sleep duration ≥ 10 h were linked to increased odds of stroke in men. The ORs (95%CI) were 1.34 (1.06–1.69) in nocturnal sleep duration < 6 h, 1.30 (1.06–1.59) in nocturnal sleep duration ≥ 9 h, and 1.40 (1.15–1.71) in 24-h sleep duration ≥ 10 h in men. In addition, long naps and prolonged nocturnal sleep duration have a joint effect on stroke in the fully adjusted model. Conclusion: The napping duration and nocturnal sleep duration have independently and jointly effects on stroke in rural populations. More research is required to explore the underlying mechanisms for this relationship. Clinical trial registration: The Henan Rural Cohort Study has been registered on the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) (http://www.chictr.org.cn/showproj.aspx?proj=11375). [ABSTRACT FROM AUTHOR]

Background: Anti-reflux mucosal intervention (ARMI), including anti-reflux mucosectomy (ARMS) and anti-reflux mucosal ablation (ARMA), is a promising endoscopic treatment for gastroesophageal reflux disease (GERD). Few studies reported a detailed analysis of the objective reflux parameters. Methods: Patients with chronic PPI-dependent GERD and receiving ARMI were prospectively enrolled. Comprehensive clinical symptom profiles, endoscopy results, and 24-h multichannel intraluminal impedance-pH (MII-pH) monitoring were collected and analyzed before and 3 months after ARMI. Results: Twenty-three patients undergoing ARMI (11 ARMS and 12 ARMA) were enrolled. The median (IQR) operative time and post-procedure stays were 50 (46–56) min and 2 (2–2) days without major complications. 73.9% of patients reported subjective global improvement. A significant decrease in the total reflux symptom index score was noted from 12 (5–19) to 8 (4–12) (P = 0.010). The esophageal acid exposure time (AET) significantly decreased from 4.6 (2.8–6.9) to 2.1 (1.1–5.6) (P = 0.013), and the number of acid refluxes and DeMeester score were significantly reduced. Three patients (13%) had increased AET (3.4% to 6.1%, 6.3% to 15.4%, and 3.2% to 5.6%); however, all reported global improvement and two patients could discontinue PPI subjectively. One patient (4.3%) had worsened erosive esophagitis and reflux symptoms. 56.5% of patients stopped PPI. Conclusions: ARMI is generally effective and safe in PPI-dependent patients. However, possible negative effects of ARMI exist in some patients; further application of MII-pH is necessitated to evaluate the treatment response after ARMI and avoid the detrimental effect of PPI discontinuation. Graph. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the associations between overall lifestyles and HRQoL, as well as the variations in age, sex, education level, and income. Methods: A total of 23,402 participants from the Henan rural cohort were included. The healthy lifestyle score (HLS) consists of five lifestyle factors: smoking, alcohol drinking, physical activity, diet, and body mass index. HRQoL was assessed by the EQ-5D-5L questionnaire. The general linear model and Tobit regression model were utilized to assess the associations of HLS with visual analogue score (VAS) and utility index. Results: Compared with participants with an HLS of 0–2, the corresponding regression coefficients (β) and 95% confidence intervals (CI) of participants with an HLS of 3, 4, and 5 for VAS score were 1.09 (0.59, 1.59), 1.92 (1.38, 2.46), and 2.60 (1.83, 3.37); the corresponding β and 95% CI for utility index were 0.02 (0.01, 0.03), 0.05 (0.03, 0.06), and 0.06 (0.04, 0.07). Notably, these positive associations were greater among the elderly, female, and those with lower education level and average monthly income (p for interaction < 0.05). For instance, the corresponding β and 95% CI of individuals with an HLS of 5 for utility index in average monthly income < 500 RMB, 500–999 RMB, and ≥ 1000 RMB groups were 0.08 (0.05, 0.11), 0.06 (0.03, 0.09), and 0.02 (− 0.00, 0.05). Conclusion: Engaging in healthier lifestyle habits was associated with a higher level of HRQoL, especially in the elderly, females, and those with low education level and average monthly income. [ABSTRACT FROM AUTHOR]

Part quality manufactured by the laser powder bed fusion process is significantly affected by porosity. Existing works of process–property relationships for porosity prediction require many experiments or computationally expensive simulations without considering environmental variations. While efforts that adopt real-time monitoring sensors can only detect porosity after its occurrence rather than predicting it ahead of time. In this study, a novel porosity detection-prediction framework is proposed based on deep learning that predicts porosity in the next layer based on thermal signatures of the previous layers. The proposed framework is validated in terms of its ability to accurately predict lack of fusion porosity using computerized tomography (CT) scans, which achieves a F1-score of 0.75. The framework presented in this work can be effectively applied to quality control in additive manufacturing. As a function of the predicted porosity positions, laser process parameters in the next layer can be adjusted to avoid more part porosity in the future or the existing porosity could be filled. If the predicted part porosity is not acceptable regardless of laser parameters, the building process can be stopped to minimize the loss. [ABSTRACT FROM AUTHOR]

Background and Purpose: Limited research focused on the association between household air pollution (HAP) and health-related quality of life (HRQoL). This study aimed to investigate the association of HAP with HRQoL and the effect modification of physical activity.Method: A total of 16,761 eligible participants were derived from the Henan Rural Cohort Study. Based on structured questionnaires, HAP was assessed by fuel type, cooking duration and kitchen ventilation; HRQoL was measured with utility index and VAS score from the European Quality of Life Five Dimension Five Level Scale (EQ-5D-5L); physical activity was assessed by the International Physical Activity Questionnaire. Generalized linear models and tobit regression models were utilized to explore the relationship of HAP with HRQoL. Further sensitivity analyses were conducted using structural equation models.Results: Compared with those who cooked with clean fuels, short-duration, or good kitchen ventilation, participants who cooked with solid fuels, long-duration, and poor ventilation had lower utility index and VAS score (All P < 0.001). The decrease in utility index for solid fuel users vs. clean fuel users were 0.06 [95%confidence interval (CI) 003, 0.08], 0.03 (95%CI 0.01, 0.04) and 0.02 (95%CI 0.01, 0.04) in low, moderate and high physical activity group, respectively, which decreased with physical activity levels (Pfor interaction < 0.05). Similar results were observed in associations of kitchen ventilation with utility index and VAS score.Conclusion: HAP negatively associated with HRQoL in rural population, and potential intervention aimed at maintaining adequate physical activity.Trail Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375 . [ABSTRACT FROM AUTHOR]

Mapping the functional topology from a multifaceted perspective and relating it to underlying cross-scale structural principles is crucial for understanding the structural-functional relationships of the cerebral cortex. Previous works have described a sensory-association gradient axis in terms of coupling relationships between structure and function, but largely based on single specific feature, and the mesoscopic underpinnings are rarely determined. Here we show a gradient pattern encoded in a functional similarity network based on data from Human Connectome Project and further link it to cytoarchitectonic organizing principles. The spatial distribution of the primary gradient follows an inferior-anterior to superior-posterior axis. The primary gradient demonstrates converging relationships with layer-specific microscopic gene expression and mesoscopic cortical layer thickness, and is captured by the geometric representation of a myelo- and cyto-architecture based laminar differentiation theorem, involving a dual origin theory. Together, these findings provide a gradient, which describes the functional topology, and more importantly, linking the macroscale functional landscape with mesoscale laminar differentiation principles. Analysis of functional MRI data from the Human Connectome Project reveals the presence of a cortical gradient, which reflects functional topology and links the macroscale functional landscape with mesoscale laminar differentiation principles. [ABSTRACT FROM AUTHOR]

Ferroelectricity, existing in either solid crystals or liquid crystals, gained widespread attention from science and industry for over a century. However, ferroelectricity has never been observed in both solid and liquid crystal phases of a material simultaneously. Inorganic ferroelectrics that dominate the market do not have liquid crystal phases because of their completely rigid structure caused by intrinsic chemical bonds. We report a ferroelectric homochiral cholesterol derivative, β-sitosteryl 4-iodocinnamate, where both solid and liquid crystal phases can exhibit the behavior of polarization switching as determined by polarization–voltage hysteresis loops and piezoresponse force microscopy measurements. The unique long molecular chain, sterol structure, and homochirality of β-sitosteryl 4-iodocinnamate molecules enable the formation of polar crystal structures with point group 2 in solid crystal phases, and promote the layered and helical structure in the liquid crystal phase with vertical polarization. Our findings demonstrate a compound that can show the biferroelectricity in both solid and liquid crystal phases, which would inspire further exploration of the interplay between solid and liquid crystal ferroelectric phases. Ferroelectricity normally exists in either solid crystals or liquid crystals. Here, the authors report a homochiral organic compound which shows ferroelectricity in both solid crystal and liquid crystal phases. [ABSTRACT FROM AUTHOR]

Robots with linear motion provide high accuracy and repeatability for industrial automation but may perform lower precision and stability when working long hours because of mechanical vibrations and thermal deformation caused by internal motors and ball screws. Structural health monitoring (SHM) can identify the discrepancy and avoid unexpected downtime costs, but electromagnetic interference (EMI) from the motor lowers the signal-to-noise ratio (SNR) of conventional wired sensors and may invalidate the feedback controller. This study presents an SHM system based on optical fiber Bragg grating (FBG) sensors, which provide accurate time-deformation relations and frequency spectrum results. The SHM-FBG system contributes to preventative maintenance and compares the dynamic signal of six selected points on a linear robot. The experiments also consider the boundary condition of (a) with spring loading and (b) without spring loading. Short message services (SMS) based on the long-term evolution (LTE) cellular network have converted the linear robot into an internet of things (IoT) device. The SHM-FBG system is designed to provide long-term observation of the electro-mechanical system and will send a short message to the administrator if mechanical vibrations or thermal deformations exceed predefined limits and detect acoustic emission of components before systematic failure. [ABSTRACT FROM AUTHOR]