The impact of implicit theories on resilience among Chinese nurses: The chain mediating effect of grit and meaning in life

Implicit theories refer to assumptions people hold about different domains, also known as mindsets. There are two implicit theories on the malleability of one’s ability: entity theory and incremental theory. They constrain and regulate people’s understanding and responses to an individual’s behavior, leading to different social cognitive patterns and behavioral responses. Resilience is a positive adaptation in highly stressful situations that represents mechanisms for coping with and transcending difficult experiences, i.e., a person’s ability to successfully adapt to change, resist the adverse effects of stressors, avoid significant dysfunction, and be chronically affected by considered a protective factor for mental health. Although previous studies showed that individuals’ implicit theories are associated with resilience, this relationship has received little attention in the nursing population. It is unclear which variables may contribute to explaining the relationship between implicit theories and resilience. Therefore, the current study aims to deeply explore the relationship between implicit theories and the resilience of Chinese nurses. In addition, we also seek to demonstrate the chain mediating effects of grit and meaning in life on this relationship. We surveyed 709 Chinese nurses through online questionnaires using the self-made demographic questionnaire, the Implicit Theories Scale, the Short Grit Scale, the Meaning in Life Questionnaire, and the 10-item Connor-Davidson Resilience Scale. After controlling for demographic variables such as age, gender, educational background, marital status, professional title, and working years, the results reveal positive associations between Chinese nurses’ implicit theories and their resilience, and grit and meaning in life play a partial mediating role in this relationship, respectively. Furthermore, grit and meaning in life play a chain mediating role between implicit theories and resilience. These findings contribute to understanding the psychological impact mechanism of implicit theories on nurses’ resilience and provide a theoretical basis for nursing managers to formulate strategies to improve nurses’ psychological resilience

Robust Control for the Hybrid Energy System of an Electric Loader

With the wide application of electric vehicles and the development of battery technology, pure electric construction machinery (PECM) has received more and more attention due to its high efficiency and no pollution. The working conditions of construction machinery are complex and accompanied by periodical working conditions and heavy load. For electric construction machinery, a heavy load represents an energy supply with a large current. To adapt to the working conditions of PECM, this paper proposes a robust controller to regulate the current of the hybrid energy system (HES) which include the battery and supercapacitor. The V-type operating conditions of a 5-ton pure electric loader are the research focus to analyze the working principles of the HES. The topology and energy flow patterns of the HES are proposed and analyzed. The model of the battery, supercapacitor, and DC/DC converter are depicted, and the robust control method is designed. An electric loader experiment platform is created to verify the effectiveness of the robust control method. Compared with the proportional integral control effect, the experiment results show that the proposed control method had good control performance and could better regulate the current. It can be used as a reference value for other dual energy source PECM

ACACA reduces lipid accumulation through dual regulation of lipid metabolism and mitochondrial function via AMPK- PPARα- CPT1A axis

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is a multifaceted metabolic disorder, whose global prevalence is rapidly increasing. Acetyl CoA carboxylases 1 (ACACA) is the key enzyme that controls the rate of fatty acid synthesis. Hence, it is crucial to investigate the function of ACACA in regulating lipid metabolism during the progress of NAFLD. Methods Firstly, a fatty liver mouse model was established by high-fat diet at 2nd, 12th, and 20th week, respectively. Then, transcriptome analysis was performed on liver samples to investigate the underlying mechanisms and identify the target gene of the occurrence and development of NAFLD. Afterwards, lipid accumulation cell model was induced by palmitic acid and oleic acid (PA ∶ OA molar ratio = 1∶2). Next, we silenced the target gene ACACA using small interfering RNAs (siRNAs) or the CMS-121 inhibitor. Subsequently, experiments were performed comprehensively the effects of inhibiting ACACA on mitochondrial function and lipid metabolism, as well as on AMPK- PPARα- CPT1A pathway. Results This data indicated that the pathways significantly affected by high-fat diet include lipid metabolism and mitochondrial function. Then, we focus on the target gene ACACA. In addition, the in vitro results suggested that inhibiting of ACACA in vitro reduces intracellular lipid accumulation, specifically the content of TG and TC. Furthermore, ACACA ameliorated mitochondrial dysfunction and alleviate oxidative stress, including MMP complete, ATP and ROS production, as well as the expression of mitochondria respiratory chain complex (MRC) and AMPK proteins. Meanwhile, ACACA inhibition enhances lipid metabolism through activation of PPARα/CPT1A, leading to a decrease in intracellular lipid accumulation. Conclusion Targeting ACACA can reduce lipid accumulation by mediating the AMPK- PPARα- CPT1A pathway, which regulates lipid metabolism and alleviates mitochondrial dysfunction

Luminescent Ionogels with Excellent Transparency, High Mechanical Strength, and High Conductivity

The paper describes a new kind of ionogel with both good mechanical strength and high conductivity synthesized by confining the ionic liquid (IL) 1-butyl-3-methylimidazolium bis(trifluoromethane sulfonyl)imide ([Bmim][NTf2]) within an organic–inorganic hybrid host. The organic–inorganic host network was synthesized by the reaction of methyltrimethoxysilane (MTMS), tetraethoxysilane (TEOS), and methyl methacrylate (MMA) in the presence of a coupling agent, offering the good mechanical strength and rapid shape recovery of the final products. The silane coupling agent 3-methacryloxypropyltrimethoxysilane (KH-570) plays an important role in improving the mechanical strength of the inorganic–organic hybrid, because it covalently connected the organic component MMA and the inorganic component SiO2. Both the thermal stability and mechanical strength of the ionogel significantly increased by the addition of IL. The immobilization of [Bmim][NTf2] within the ionogel provided the final ionogel with an ionic conductivity as high as ca. 0.04 S cm−1 at 50 °C. Moreover, the hybrid ionogel can be modified with organosilica-modified carbon dots within the network to yield a transparent and flexible ionogel with strong excitation-dependent emission between 400 and 800 nm. The approach is, therefore, a blueprint for the construction of next-generation multifunctional ionogels

Evaluation of an Open Source Registration Package for Automatic Contour Propagation in Online Adaptive Intensity-Modulated Proton Therapy of Prostate Cancer

Objective: Our goal was to investigate the performance of an open source deformable image registration package, elastix, for fast and robust contour propagation in the context of online-adaptive intensity-modulated proton therapy (IMPT) for prostate cancer. Methods: A planning and 7–10 repeat CT scans were available of 18 prostate cancer patients. Automatic contour propagation of repeat CT scans was performed using elastix and compared with manual delineations in terms of geometric accuracy and runtime. Dosimetric accuracy was quantified by generating IMPT plans using the propagated contours expanded with a 2 mm (prostate) and 3.5 mm margin (seminal vesicles and lymph nodes) and calculating dosimetric coverage based on the manual delineation. A coverage of V95% ≥ 98% (at least 98% of the target volumes receive at least 95% of the prescribed dose) was considered clinically acceptable. Results: Contour propagation runtime varied between 3 and 30 s for different registration settings. For the fastest setting, 83 in 93 (89.2%), 73 in 93 (78.5%), and 91 in 93 (97.9%) registrations yielded clinically acceptable dosimetric coverage of the prostate, seminal vesicles, and lymph nodes, respectively. For the prostate, seminal vesicles, and lymph nodes the Dice Similarity Coefficient (DSC) was 0.87 ± 0.05, 0.63 ± 0.18, and 0.89 ± 0.03 and the mean surface distance (MSD) was 1.4 ± 0.5 mm, 2.0 ± 1.2 mm, and 1.5 ± 0.4 mm, respectively. Conclusion: With a dosimetric success rate of 78.5–97.9%, this software may facilitate online adaptive IMPT of prostate cancer using a fast, free and open implementation.Pattern Recognition and Bioinformatic

Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer

Purpose: To develop and validate a robust and accurate registration pipeline for automatic contour propagation for online adaptive Intensity-Modulated Proton Therapy (IMPT) of prostate cancer using elastix software and deep learning. Methods: A three-dimensional (3D) Convolutional Neural Network was trained for automatic bladder segmentation of the computed tomography (CT) scans. The automatic bladder segmentation alongside the computed tomography (CT) scan is jointly optimized to add explicit knowledge about the underlying anatomy to the registration algorithm. We included three datasets from different institutes and CT manufacturers. The first was used for training and testing the ConvNet, where the second and the third were used for evaluation of the proposed pipeline. The system performance was quantified geometrically using the dice similarity coefficient (DSC), the mean surface distance (MSD), and the 95% Hausdorff distance (HD). The propagated contours were validated clinically through generating the associated IMPT plans and compare it with the IMPT plans based on the manual delineations. Propagated contours were considered clinically acceptable if their treatment plans met the dosimetric coverage constraints on the manual contours. Results: The bladder segmentation network achieved a DSC of 88% and 82% on the test datasets. The proposed registration pipeline achieved a MSD of 1.29 ± 0.39, 1.48 ± 1.16, and 1.49 ± 0.44 mm for the prostate, seminal vesicles, and lymph nodes, respectively, on the second dataset and a MSD of 2.31 ± 1.92 and 1.76 ± 1.39 mm for the prostate and seminal vesicles on the third dataset. The automatically propagated contours met the dose coverage constraints in 86%, 91%, and 99% of the cases for the prostate, seminal vesicles, and lymph nodes, respectively. A Conservative Success Rate (CSR) of 80% was obtained, compared to 65% when only using intensity-based registration. Conclusion: The proposed registration pipeline obtained highly promising results for generating treatment plans adapted to the daily anatomy. With 80% of the automatically generated treatment plans directly usable without manual correction, a substantial improvement in system robustness was reached compared to a previous approach. The proposed method therefore facilitates more precise proton therapy of prostate cancer, potentially leading to fewer treatment-related adverse side effects.</p

Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer

Purpose: To develop and validate a robust and accurate registration pipeline for automatic contour propagation for online adaptive Intensity-Modulated Proton Therapy (IMPT) of prostate cancer using elastix software and deep learning. Methods: A three-dimensional (3D) Convolutional Neural Network was trained for automatic bladder segmentation of the computed tomography (CT) scans. The automatic bladder segmentation alongside the computed tomography (CT) scan is jointly optimized to add explicit knowledge about the underlying anatomy to the registration algorithm. We included three datasets from different institutes and CT manufacturers. The first was used for training and testing the ConvNet, where the second and the third were used for evaluation of the proposed pipeline. The system performance was quantified geometrically using the dice similarity coefficient (DSC), the mean surface distance (MSD), and the 95% Hausdorff distance (HD). The propagated contours were validated clinically through generating the associated IMPT plans and compare it with the IMPT plans based on the manual delineations. Propagated contours were considered clinically acceptable if their treatment plans met the dosimetric coverage constraints on the manual contours. Results: The bladder segmentation network achieved a DSC of 88% and 82% on the test datasets. The proposed registration pipeline achieved a MSD of 1.29 ± 0.39, 1.48 ± 1.16, and 1.49 ± 0.44 mm for the prostate, seminal vesicles, and lymph nodes, respectively, on the second dataset and a MSD of 2.31 ± 1.92 and 1.76 ± 1.39 mm for the prostate and seminal vesicles on the third dataset. The automatically propagated contours met the dose coverage constraints in 86%, 91%, and 99% of the cases for the prostate, seminal vesicles, and lymph nodes, respectively. A Conservative Success Rate (CSR) of 80% was obtained, compared to 65% when only using intensity-based registration. Conclusion: The proposed registration pipeline obtained highly promising results for generating treatment plans adapted to the daily anatomy. With 80% of the automatically generated treatment plans directly usable without manual correction, a substantial improvement in system robustness was reached compared to a previous approach. The proposed method therefore facilitates more precise proton therapy of prostate cancer, potentially leading to fewer treatment-related adverse side effects.Pattern Recognition and Bioinformatic

Linkage Engineering by Harnessing Supramolecular Interactions to Fabricate 2D Hydrazone-Linked Covalent Organic Framework Platforms toward Advanced Catalysis

10.1021/jacs.0c08436Journal of the American Chemical Society1424218138 - 1814

Characterization of spastic paraplegia in a family with a novel PSEN1 mutation

Spastic paraparesis has been described to occur in 13.7% of PSEN1 mutations and can be the presenting feature in 7.5%. In this paper, we describe a family with a particularly young onset of spastic paraparesis due to a novel mutation in PSEN1 (F388S). Three affected brothers underwent comprehensive imaging protocols, two underwent ophthalmological evaluations and one underwent neuropathological examination after his death at age 29. Age of onset was consistently at age 23 with spastic paraparesis, dysarthria and bradyphrenia. Pseudobulbar affect followed with progressive gait problems leading to loss of ambulation in the late 20s. Cerebrospinal fluid levels of amyloid-β, tau and phosphorylated tau and florbetaben PET were consistent with Alzheimer's disease. Flortaucipir PET showed an uptake pattern atypical for Alzheimer's disease, with disproportionate signal in posterior brain areas. Diffusion tensor imaging showed decreased mean diffusivity in widespread areas of white matter but particularly in areas underlying the peri-Rolandic cortex and in the corticospinal tracts. These changes were more severe than those found in carriers of another PSEN1 mutation, which can cause spastic paraparesis at a later age (A431E), which were in turn more severe than among persons carrying autosomal dominant Alzheimer's disease mutations not causing spastic paraparesis. Neuropathological examination confirmed the presence of cotton wool plaques previously described in association with spastic parapresis and pallor and microgliosis in the corticospinal tract with severe amyloid-β pathology in motor cortex but without unequivocal disproportionate neuronal loss or tau pathology. In vitro modelling of the effects of the mutation demonstrated increased production of longer length amyloid-β peptides relative to shorter that predicted the young age of onset. In this paper, we provide imaging and neuropathological characterization of an extreme form of spastic paraparesis occurring in association with autosomal dominant Alzheimer's disease, demonstrating robust diffusion and pathological abnormalities in white matter. That the amyloid-β profiles produced predicted the young age of onset suggests an amyloid-driven aetiology though the link between this and the white matter pathology remains undefined