Investigation of diaphragmatic motion and projected lung area in diaphragm paralysis patients using dynamic chest radiography.

Background: Dynamic chest radiography (DCR) is a novel and supplementary examination in respiratory diseases. The investigation of other chest diseases using DCR has been explored, identifying a certain correlation of the pulmonary function test (PFT). However, there is a lack of research using DCR parameters to quantitatively evaluate chest disease. The purpose of this study was to investigate the diagnostic value of DCR for diaphragm paralysis (DP). Methods: This retrospective study recruited 118 participants, which include 18 patients with DP, 48 healthy volunteers, and 52 patients with respiratory disease. Comparison of DCR parameters relationships among 3 groups was performed using one-way analysis of variance (ANOVA) and Kruskal-Wallis test. The receiver operating characteristic (ROC) curve was used to compare the value of the DCR parameters to diagnose DP. Results: The differences of excursion of diaphragm (ED) in normal (nb) and forced breathing (fb), ED(fb)-ED(nb), and the parameters of projected lung area (PLA) in inspiratory (ins) and expiratory phase (exp), PLA.exp(fb), PLA.ins(fb)-PLA.ins(nb), and PLA.exp(fb)-PLA.exp(nb) among the 3 groups were statistically significant. The highest area under the curve (AUC) of right-side parameter was the ED(fb)-ED(nb), for which the AUC was 0.8950 [95% confidence interval (CI): 0.7618-1.000], whereas that of the left-side parameter was ED(fb), for which the AUC was 0.9176 [95% confidence interval (CI): 0.8524-0.9829]. Conclusions: The parameters of DCR have good diagnostic value for DP. The highest diagnostic efficiency for DP on the right side is the ED(fb)-ED(nb), with a sensitivity of 95% and a specificity of 78.6%, whereas on the left side is ED(fb), with a sensitivity of 80% and a specificity of 88.2%.

Central Nervous System Disturbances by Thiamethoxam in Japanese Quail (Coturnix japonica): In Vivo, ex Vivo, and in Silico Study.

The neurotoxic effects of neonicotinoids (NEOs) have been widely reported in relation to the poisoning of wild birds, yet the underlying molecular mechanism has remained elusive. This study employed Japanese quails (Coturnix japonica) and primary quail embryonic neurons as in vivo and ex vivo models, respectively, to investigate the neurotoxic effects and mechanism of thiamethoxam (TMX), a representative neonicotinoid insecticide, at environmentally relevant concentrations. Following a 28-day exposure to TMX, metabolomic analysis of quail brain revealed TMX-induced changes in glutamatergic, GABA-ergic, and dopaminergic function. Subsequent ex vivo and in silico experimentation revealed that the activation of nicotinic acetylcholine receptors and calcium signaling, induced by clothianidin (CLO), the primary metabolite of TMX, served as upstream events for the alterations in neurotransmitter synthesis, metabolism, release, and uptake. Our findings propose that the disruption of the central nervous system, caused by environmentally significant concentrations of NEOs, may account for the avian poisoning events induced by NEOs.

Cytotoxic effects of NIR responsive chitosan-polymersome layer coated melatonin-upconversion nanoparticles on HGC27 and AGS gastric cancer cells: Role of the ROS/PI3K/Akt/mTOR signaling pathway.

In this study, a formulation of NaGdF4:Tm/Er@NaGdF4 (core@shell) UCNPs loaded with melatonin drug was synthesized. The novel melatonin-loaded UCNPs were then encapsulated within NIR-responsive biopolymeric chitosan (CS) based polymersome and investigated against gastric cancer (HGC27 & AGS) cells. The photolysis of the ONB moiety and disruption of the disulfide linkage in the polymersome induced by NIR light facilitated by the NaGdF4:Tm/Er@NaGdF4 UCNPs and GSH results in an increased release of melatonin drug. The DLS and zeta potential measurements exhibit a reduced particle size (21.9 ± 3.56 nm) and a low zeta potential (17.91 mV). Furthermore, drug release profiles demonstrated superior melatonin drug release (79.78 %) at pH 5.0 for CS-polymersome-coated melatonin-UCNPs resembling the Hixson-Crowell model. Remarkably, CS-polymersome-coated melatonin-UCNPs exhibit excellent anti-proliferative properties for HGC27 (IC50 = 0.096 µM) and AGS (IC50 = 0.16 µM) cancer cells. The flow cytometry data demonstrate a significant elevation in ROS levels which promoted cell death in both HGC-27 and AGS cells. The observed cell mortality in HGC-27 and AGS cells is primarily caused by the destruction of the nucleus, mtDNA, rupture of disulfide (R-S-S-R) bonds, and nuclear DNA. Contrarily, L929 and HUVECs cells incubated with CS-polymersome coated melatonin-UCNPs (100 µg/mL) reveal a notable cell viability of 88.7 % and 93 % indicating superior biocompatibility. The western blotting analysis revealed the induction of autophagy by CS-polymersome-coated melatonin-UCNPs which subsequently led to apoptosis by regulating the ROS/PI3K/Akt/mTOR molecular signaling pathway.

What drives college students to use AI for L2 learning? Modeling the roles of self-efficacy, anxiety, and attitude based on an extended technology acceptance model.

Prior research highlights the critical role of AI in enhancing second language (L2) learning. However, the factors that practically affect L2 learners to engage with AI resources are still underexplored. Given the widespread availability of digital devices among college students, they are particularly poised to benefit from AI-assisted L2 learning. As such, this study, grounded in an extended Technology Acceptance Model (TAM), investigates the predictors of college L2 learners' actual use of AI tools, focusing on AI self-efficacy, AI-related anxiety, and their overall attitude toward AI. Data was gathered from 429 L2 learners at Chinese universities via an online questionnaire, utilizing four established scales. Through structural equation modeling (SEM) via AMOS 24, the results indicate that AI self-efficacy could negatively affect AI anxiety, and positively influence both learners' attitude toward AI and their actual use of AI tools. Besides, AI anxiety negatively predicted the actual use of AI. Moreover, AI self-efficacy was a positive predictor of AI use through reducing AI anxiety, enhancing attitude toward AI, or a combination of both. This study also discusses the theoretical and pedagogical implications and suggests directions for future research.

Rational Fabrication of Nickel Vanadium Sulfide Encapsulated on Graphene as an Advanced Electrode for High-Performance Supercapacitors.

Supercapacitors (SCs) are widely recognized as competitive power sources for energy storage. The hierarchical structure of nickel vanadium sulfide nanoparticles encapsulated on graphene nanosheets (NVS/G) was fabricated using a cost-effective and scalable solvothermal process. The reaction contents of the composites were explored and optimized. TEM images displayed the nickel vanadium sulfide nanoparticles (NVS NPs) with 20-30 nm average size anchored to graphene nanosheets. The interconnection of graphene nanosheets encapsulating NVS nanoparticles effectively reduces the ion diffusion path between the electrode and electrolyte, thereby enhancing electrochemical performance. The NVS/G composite demonstrated improved electrochemical performance, achieving a maximum of 1437 F g-1 specific capacitance at 1 A g-1, remarkable rate capability retaining of 1050 F g-1 at 20 A g-1, and exceptional cycle stability with 91.2% capacitance retention following 10,000 cycles. The NVS/G composite was employed as a cathode, and reduced graphene oxide (rGO) was used as an anode material to assemble a device. Importantly, asymmetric SCs using NVS/G//rGO achieved 74.7 W h kg-1 energy density at 0.8 kW kg-1 power density, along with outstanding stability with 88.2% capacitance retention following 10,000 cycles. These superior properties of the NVS/G electrode highlight its significant potential in energy storage applications.

Construction and validation of a risk score system for diagnosing invasive adenocarcinoma presenting as pulmonary pure ground-glass nodules: a multi-center cohort study in China.

Background: Anxiety-driven clinical interventions have been queried due to the nondeterminacy of pure ground-glass nodules (pGGNs). Although radiomics and radiogenomics aid diagnosis, standardization and reproducibility challenges persist. We aimed to assess a risk score system for invasive adenocarcinoma in pGGNs. Methods: In a retrospective, multi-center study, 772 pGGNs from 707 individuals in The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital were grouped into training (509 patients with 558 observations) and validation (198 patients with 214 observations) sets consecutively from January 2017 to November 2021. An additional test set of 143 observations in Hainan Cancer Hospital was analyzed in the same period. Computed tomography (CT) signs and clinical features were manually collected, and the quantitative parameters were achieved by artificial intelligence (AI). The positive cutoff score was ≥3. Risk scores system 3 combined carcinoma history, chronic obstructive pulmonary disease (COPD), maximum diameters, nodule volume, mean CT values, type II or III vascular supply signs, and other radiographic characteristics. The evaluation included the area under the curves (AUCs), accuracy, sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) for both the risk score systems 1, 2, 3 and the AI model. Results: The risk score system 3 [AUC, 0.840; 95% confidence interval (CI): 0.789-0.890] outperformed the AI model (AUC, 0.553; 95% CI: 0.487-0.619), risk score system 1 (AUC, 0.802; 95% CI: 0.754-0.851), and risk score system 2 (AUC, 0.816; 95% CI: 0.766-0.867), with 88.0% (0.850-0.904) accuracy, 95.6% (0.932-0.972) PPV, 0.620 (0.535-0.702) NPV, 89.6% (0.864-0.920) sensitivity, and 80.6% (0.717-0.872) specificity in the training sets. In the validation and test sets, risk score system 3 performed best with AUCs of 0.769 (0.678-0.860) and 0.801 (0.669-0.933). Conclusions: An AI-based risk scoring system using quantitative image parameters, clinical features, and radiographic characteristics effectively predicts invasive adenocarcinoma in pulmonary pGGNs.

Photovoltaic nanocells for high-performance large-scale-integrated organic phototransistors.

A high-performance large-scale-integrated organic phototransistor needs a semiconductor layer that maintains its photoelectric conversion ability well during high-resolution pixelization. However, lacking a precise design for the nanoscale structure, a trade-off between photoelectric performance and device miniaturization greatly limits the success in commercial application. Here we demonstrate a photovoltaic-nanocell enhancement strategy, which overcomes the trade-off and enables high-performance organic phototransistors at a level beyond large-scale integration. Embedding a core-shell photovoltaic nanocell based on perovskite quantum dots in a photocrosslinkable organic semiconductor, ultralarge-scale-integrated (>221 units) imaging chips are manufactured using photolithography. 27 million pixels are interconnected and the pixel density is 3.1 × 106 units cm-2, at least two orders of magnitude higher than in existing organic imaging chips and equivalent to the latest commercial full-frame complementary metal-oxide-semiconductor camera chips. The embedded photovoltaic nanocells induce an in situ photogating modulation and enable photoresponsivity and detectivity of 6.8 × 106 A W-1 and 1.1 × 1013 Jones (at 1 Hz), respectively, achieving the highest values of organic imaging chips at large-scale or higher integration. In addition, a very-large-scale-integrated (>216 units) stretchable biomimetic retina based on photovoltaic nanocells is manufactured for neuromorphic imaging recognition with not only resolution but also photoresponsivity and power consumption approaching those of the biological counterpart.

TCFormer: Visual Recognition via Token Clustering Transformer.

Transformers are widely used in computer vision areas and have achieved remarkable success. Most state-of-the-art approaches split images into regular grids and represent each grid region with a vision token. However, fixed token distribution disregards the semantic meaning of different image regions, resulting in sub-optimal performance. To address this issue, we propose the Token Clustering Transformer (TCFormer), which generates dynamic vision tokens based on semantic meaning. Our dynamic tokens possess two crucial characteristics: (1) Representing image regions with similar semantic meanings using the same vision token, even if those regions are not adjacent, and (2) concentrating on regions with valuable details and represent them using fine tokens. Through extensive experimentation across various applications, including image classification, human pose estimation, semantic segmentation, and object detection, we demonstrate the effectiveness of our TCFormer. The code and models for this work are available at https://github.com/zengwang430521/TCFormer.

Validating the AI-assisted second language (L2) learning attitude scale for Chinese college students and its correlation with L2 proficiency.

The positive impact of Artificial Intelligence (AI) on second language (L2) learning is well-documented. An individual's attitude toward AI significantly influences its adoption. Despite this, no specific scale has been designed to measure this attitude, particularly in the Chinese context. To address this gap, our study aims to construct the AI-Assisted L2 Learning Attitude Scale for Chinese College Students (AL2AS-CCS) and evaluate its reliability, validity, and relationship with L2 proficiency. Our research comprises two phases, each involving separate samples. In Phase One (Sample 1: n = 379), we conducted exploratory factor analysis (EFA) to determine the factor structure of the AL2AS-CCS. The resulting two-factor structure consists of 12 items, categorized into cognitive and behavioral components. In Phase Two (Sample 2: n = 429), we performed confirmatory factor analysis (CFA) to validate the factor structure and assess model fit. CFA in Sample 2 confirmed the factor structure and demonstrated a good model fit. Additionally, the AL2AS-CCS exhibited high criterion validity, internal consistency, and cross-gender invariance. Our findings suggest that the AL2AS-CCS is a valid measurement tool for assessing Chinese college students' attitude toward AI-assisted L2 learning. Moreover, Chinese college students were discovered to maintain a moderately positive attitude toward AI-assisted L2 learning. Additionally, a positive correlation was identified between this attitude and their L2 proficiency.

Enzymatic cascade reactors on carbon nanotube transistor detecting trace prostate cancer biomarker.

Biosensors based on carbon nanotube field-effect transistors (CNT-FETs) have shown great potential in biomarker detection due to their high sensitivity because of appreciable semiconducting electrical properties. However, background signal interferences in complex mediums may results in low signal-to-noise ratio, which may impose challenges for precise biomarker detection in physiological fluids. In this work, we develop an enzymatic CNT-FET, with scalable production at wafer scale, for detection of trace sarcosine that is a biopsy-correlated biomarker of prostate cancer. Enzymatic cascade rectors are constructed on the CNT to improve the reaction efficiency, thereby, enhancing the signal transduction. As such, a limit of detection as low as 105 zM is achieved in buffer solution. Owing to the enhanced reaction efficiency, the testing of clinical serum samples yields significant signal difference to discriminate the prostate cancer (PCa) samples from the benign prostatic hyperplasia (BPH) samples (P = 1.07 × 10-5), demonstrating immense potential in practical applications.

Magnetic Stimulation of Gigantocellular Reticular Nucleus with Iron Oxide Nanoparticles Combined Treadmill Training Enhanced Locomotor Recovery by Reorganizing Cortico-Reticulo-Spinal Circuit.

Background: Gigantocellular reticular nucleus (GRNs) executes a vital role in locomotor recovery after spinal cord injury. However, due to its unique anatomical location deep within the brainstem, intervening in GRNs for spinal cord injury research is challenging. To address this problem, this study adopted an extracorporeal magnetic stimulation system to observe the effects of selective magnetic stimulation of GRNs with iron oxide nanoparticles combined treadmill training on locomotor recovery after spinal cord injury, and explored the possible mechanisms. Methods: Superparamagnetic iron oxide (SPIO) nanoparticles were stereotactically injected into bilateral GRNs of mice with moderate T10 spinal cord contusion. Eight-week selective magnetic stimulation produced by extracorporeal magnetic stimulation system (MSS) combined with treadmill training was adopted for the animals from one week after surgery. Locomotor function of mice was evaluated by the Basso Mouse Scale, Grid-walking test and Treadscan analysis. Brain MRI, anterograde virus tracer and immunofluorescence staining were applied to observe the tissue compatibility of SPIO in GRNs, trace GRNs' projections and evaluate neurotransmitters' expression in spinal cord respectively. Motor-evoked potentials and H reflex were collected for assessing the integrity of cortical spinal tract and the excitation of motor neurons in anterior horn. Results: (1) SPIO persisted in GRNs for a minimum of 24 weeks without inducing apoptosis of GRN cells, and degraded slowly over time. (2) MSS-enabled treadmill training dramatically improved locomotor performances of injured mice, and promoted cortico-reticulo-spinal circuit reorganization. (3) MSS-enabled treadmill training took superimposed roles through both activating GRNs to drive more projections of GRNs across lesion site and rebalancing neurotransmitters' expression in anterior horn of lumbar spinal cord. Conclusion: These results indicate that selective MSS intervention of GRNs potentially serves as an innovative strategy to promote more spared fibers of GRNs across lesion site and rebalance neurotransmitters' expression after spinal cord injury, paving the way for the structural remodeling of neural systems collaborating with exercise training, thus ultimately contributing to the reconstruction of cortico-reticulo-spinal circuit.

Function Electrical Stimulation Effect on Muscle Fatigue Based on Fatigue Characteristic Curves of Dumbbell Weightlifting Training.

The parameter setting of functional electrical stimulation (FES) is important for active recovery training since it affects muscle health. Among the FES parameters, current amplitude is the most influential factor. To explore the FES effect on the maximum stimulation time, this study establishes a curve between FES current amplitude and the maximum stimulation time based on muscle fatigue. We collect 10 subjects' surface electromyography under dumbbell weightlifting training and analyze the muscle fatigue state by calculating the root mean square (RMS) of power. By analyzing signal RMS, the fatigue characteristic curves under different fatigue levels are obtained. According to the muscle response under FES, the relationship curve between the current amplitude and the maximum stimulation time is established and FES parameters' effect on the maximum stimulation time is obtained. The linear curve provides a reference for FES parameter setting, which can help to set stimulation time safely, thus preventing the muscles from entering an excessive fatigue state and becoming more active to muscle recovery training.

DIAS: A dataset and benchmark for intracranial artery segmentation in DSA sequences.

The automated segmentation of Intracranial Arteries (IA) in Digital Subtraction Angiography (DSA) plays a crucial role in the quantification of vascular morphology, significantly contributing to computer-assisted stroke research and clinical practice. Current research primarily focuses on the segmentation of single-frame DSA using proprietary datasets. However, these methods face challenges due to the inherent limitation of single-frame DSA, which only partially displays vascular contrast, thereby hindering accurate vascular structure representation. In this work, we introduce DIAS, a dataset specifically developed for IA segmentation in DSA sequences. We establish a comprehensive benchmark for evaluating DIAS, covering full, weak, and semi-supervised segmentation methods. Specifically, we propose the vessel sequence segmentation network, in which the sequence feature extraction module effectively captures spatiotemporal representations of intravascular contrast, achieving intracranial artery segmentation in 2D+Time DSA sequences. For weakly-supervised IA segmentation, we propose a novel scribble learning-based image segmentation framework, which, under the guidance of scribble labels, employs cross pseudo-supervision and consistency regularization to improve the performance of the segmentation network. Furthermore, we introduce the random patch-based self-training framework, aimed at alleviating the performance constraints encountered in IA segmentation due to the limited availability of annotated DSA data. Our extensive experiments on the DIAS dataset demonstrate the effectiveness of these methods as potential baselines for future research and clinical applications. The dataset and code are publicly available at https://doi.org/10.5281/zenodo.11401368 and https://github.com/lseventeen/DIAS.

The cognitive effect of non-invasive brain stimulation combined with cognitive training in Alzheimer's disease and mild cognitive impairment: a systematic review and meta-analysis.

BACKGROUND: Non-invasive brain stimulation (NIBS) combined with cognitive training (CT) may have shown some prospects on improving cognitive function in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, data from clinical trials or meta-analysis involving NIBS combined with CT have shown controversial results. The aim of this systematic review and meta-analysis was to evaluate short-term and long-term effects of NIBS combined with CT on improving global cognition and other specific cognitive domains in patients with AD and MCI. METHODS: This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Five electronic databases including PubMed, Web of Science, EBSCO, Cochrane Library and Embase were searched up from inception to 20 November 2023. The PEDro scale and the Cochrane's risk of bias assessment were used to evaluate risk of bias and methodological quality of included studies. All statistical analyses were conducted with Review Manager 5.3. RESULTS: We included 15 studies with 685 patients. The PEDro scale was used to assess methodological quality with a mean score of 7.9. The results of meta-analysis showed that NIBS combined with CT was effective on improving global cognition in AD and MCI (SMD = 0.52, 95% CI (0.18, 0.87), p = 0.003), especially for patients accepting repetitive transcranial magnetic stimulation (rTMS) combined with CT (SMD = 0.46, 95% CI (0.14, 0.78), p = 0.005). AD could achieve global cognition improvement from NIBS combined with CT group (SMD = 0.77, 95% CI (0.19, 1.35), p = 0.01). Transcranial direct current stimulation (tDCS) combined with CT could improve language function in AD and MCI (SMD = 0.29, 95% CI (0.03, 0.55), p = 0.03). At evaluation follow-up, rTMS combined with CT exhibited larger therapeutic responses to AD and MCI in global cognition (SMD = 0.55, 95% CI (0.09, 1.02), p = 0.02). AD could achieve global cognition (SMD = 0.40, 95% CI (0.03, 0.77), p = 0.03) and attention/working memory (SMD = 0.72, 95% CI (0.23, 1.20), p = 0.004) improvement after evaluation follow-up from NIBS combined with CT group. CONCLUSIONS: Overall, NIBS combined with CT, particularly rTMS combined with CT, has both short-term and follow-up effects on improving global cognition, mainly in patients with AD. tDCS combined with CT has advantages on improving language function in AD and MCI. Future more studies need evaluate cognitive effects of NIBS combined with CT on other specific cognitive domain in patients with cognitive deterioration.

A novel yeast-based biosensor for the quick determination of Deoxynivalenol.

Mycotoxins are commonly found in food materials and severely threaten human health. Antibodies play a key role as a part of immunological techniques in detecting mycotoxins. Therefore, highly specific antibodies and detection techniques against mycotoxins need to be developed for advancements in medical research. In this study, we presented a novel strategy for quickly screening highly specific antigen-binding fragment (Fab) antibodies based on yeast surface display (YSD) and detecting small-molecule compounds based on a YSD biosensor. We constructed a yeast surface display Deoxynivalenol (DON)-Fab library with 105 cfu/mL with a galactose-inducible bidirectional promoter. By conducting efficient magnetic-activated cell sorting and fluorescence-activated cell sorting (MACS/FACS), four kinds of DON-selective yeasts were screened. As Fab@YSD C4# showed high sensitivity, we used it to build a one-pot Fab@YSD chemiluminescence biosensor with DON-BSA@Biotin and Streptavidin-alkaline phosphatase (SA-ALP). This method showed a low operational threshold (LOD = 0.166 pg/mL) and a high population range (linear range = 0.001-132.111 ng/mL) within 40 min, which facilitated the detection of DON with high specificity and better recovery in real samples (wheat, corn, flour, and cornmeal). Our results suggested that the Fab@YSD chemiluminescence biosensor is an inexpensive, reproducible, user-friendly, and sensitive method for detecting DON and may be used to quickly detect other small-molecule contaminants in food items.

CDK4/6 inhibitors dephosphorylate RNF26 to stabilize TSC1 and increase the sensitivity of ccRCC to mTOR inhibitors.

BACKGROUND: The combined use of CDK4/6 inhibitors and mTOR inhibitors has achieved some clinical success in ccRCC. Exploring the underlying mechanism of the CDK4/6 pathway in cancer cells and the drug interactions of CDK4/6 inhibitors in combination therapy could help identify new therapeutic strategies for ccRCC. Notably, CDK4/6 inhibitors inactivate the mTOR pathway by increasing the protein levels of TSC1, but the mechanism by which CDK4/6 inhibitors regulate TSC1 is still unclear. METHODS: Mass spectrometry analysis, coimmunoprecipitation analysis, GST pull-down assays, immunofluorescence assays, Western blot analysis and RT‒qPCR analysis were applied to explore the relationships among CDK4, RNF26 and TSC1. Transwell assays, tube formation assays, CCK-8 assays, colony formation assays and xenograft assays were performed to examine the biological role of RNF26 in renal cancer cells.TCGA-KIRC dataset analysis and RT‒qPCR analysis were used to examine the pathways affected by RNF26 silencing. RESULTS: CDK4/6 inhibitors stabilized TSC1 in cancer cells. We showed that CDK4 enhances the interaction between TSC1 and RNF26 and that RNF26 activates the mTOR signaling pathway in ccRCC, contributes to ccRCC progression and angiogenesis, and promotes tumorigenesis. We then found that RNF26 functions as an E3 ligase of TSC1 to regulate CDK4-induced TSC1. This finding suggested that RNF26 promotes ccRCC progression and angiogenesis to some extent by negatively regulating TSC1. CONCLUSION: Our results revealed a novel CDK4/RNF26/TSC1 axis that regulates the anticancer efficacy of CDK4/6 inhibitors and mTOR inhibitors in ccRCC.

Repeated trans-spinal magnetic stimulation promotes microglial phagocytosis of myelin debris after spinal cord injury through LRP-1.

Spinal cord injury (SCI) is a serious trauma of the central nervous system. The clearance of myelin debris is a critical step in the functional recovery following spinal cord injury (SCI). Recent studies have begun to reveal critical roles for professional phagocytes in the central nervous system, microglia, and their receptors in the control of myelin debris in neurodegenerative disease. Repeated trans-spinal magnetic stimulation (rTSMS) has been demonstrated as a noninvasive SCI treatment that enhances tissue repair and functional recovery. In this study, we investigated the role and molecular mechanism of rTSMS on microglial phagocytosis of myelin debris in a rat SCI model. In our studies, we found that rTSMS significantly promoted the motor function recovery of SCI rats associated with the inhibition the neuroinflammation and glia scar formation. Immunofluorescence results further showed that the rTSMS promotes the clearance of myelin debris by microglia in vivo and in vitro. Additionally, receptor-associated protein (RAP), a Low-density lipoprotein receptor-related protein-1 (LRP-1) inhibitor, could cancel the accelerated microglial phagocytosis of myelin debris after rTSMS in vitro experiments. Simultaneously, Elisa's results and western blotting respectively showed that rTSMS significantly decreased the levels of soluble LRP-1(sLRP-1) and the LRP-1 splicing enzyme of ADAM17. In conclusion, rTSMS could promote the clearance of myelin debris by microglia through LRP-1 to improve the functional recovery of SCI rats.

SOX9 functionalized scaffolds as a barrier to against cartilage fibrosis.

Hyaline cartilage regeneration will bring evangel to millions of people suffered from cartilage diseases. However, uncontrollable cartilage fibrosis and matrix mineralization are the primary causes of cartilage regeneration failure in many tissue engineering scaffolds. This study presents a new attempt to avoid endochondral ossification or fibrosis in cartilage regeneration therapy by establishing biochemical regulatory area. Here, SOX9 expression plasmids are assembled in cellulose gels by chitosan gene vectors to fabricate SOX9+ functionalized scaffolds. RT-qPCR, western blot and biochemical analysis all show that the SOX9 reinforcement strategy can enhance chondrogenic specific proteins expression and promote GAG production. Notably, the interference from SOX9 has resisted osteogenic inducing significantly, showing an inhibition of COL1, OPN and OC production, and the inhibition efficiency was about 58.4 %, 22.8 % and 76.9 % respectively. In vivo study, implantation of these scaffolds with BMSCs can induce chondrogenic differentiation and resist endochondral ossification effectively. Moreover, specific SOX9+ functionalized area of the gel exhibited the resistance to matrix mineralization, indicating the special biochemical functional area for cartilage regeneration. These results indicate that this strategy is effective for promoting the hyaline cartilage regeneration and avoiding cartilage fibrosis, which provides a new insight to the future development of cartilage regeneration scaffolds.

Surface Molecular Engineering for Fully Textured Perovskite/Silicon Tandem Solar Cells.

Developing large-scale monolithic perovskite/silicon tandem devices based on industrial Czochralski silicon wafers will likely have to adopt double-side textured architecture, given their optical benefits and low manufacturing costs. However, the surface engineering strategies that are widely used in solution-processed perovskites to regulate the interface properties are not directly applicable to micrometric textures. Here, we devise a surface passivation strategy by dynamic spray coating (DSC) fluorinated thiophenethylammonium ligands, combining the advantages of providing conformal coverage and suppressing phase conversion on textured surfaces. From the viewpoint of molecular engineering, theoretical calculation and experimental results demonstrate that introducing trifluoromethyl group provide more effective surface passivation through strong interaction and energy alignment by forming a dipole layer. Consequently, the DSC treatment of this bifunctional molecule enables the tandem cells based on industrial silicon wafers to achieve a certified stabilized power conversion efficiency of 30.89 %. In addition, encapsulated devices display excellent operational stability by retaining over 97 % of their initial performance after 600 h continuous illumination.

Exploring the Impact of a Supportive Work Environment on Chinese L2 Teachers' Emotions: A Partial Least Squares-SEM Approach.

Second language (L2) teachers' emotions can influence their well-being and students' performance. However, most of the existing studies have focused on the role of individual factors in affecting L2 teachers' emotions, while leaving environmental factors underexplored. To fill this gap, this study aimed to examine how the four dimensions of a supportive work environment (SWE) (perceived climate, PC; supervisory relationship, SR; peer group interaction, PGI; and perceived organization support, POS) relate to L2 teachers' emotions (enjoyment, anxiety, pride, and anger). A sample of 406 Chinese L2 teachers completed two valid scales to measure their SWE and emotions. The data were analyzed by Partial Least Squares-Structural Equation Modeling (SEM) using Smart PLS 3 software. The results showed that (1) PC, PGI, and POS had a positive and significant effect on enjoyment, while SR had no significant effect; (2) PGI and POS had a negative and significant effect on anxiety, while PC and SR had no significant effect; (3) PGI had a positive and significant effect on pride, while the other three dimensions had no significant effect; and (4) POS had a negative and significant effect on anger, while the other three dimensions had no significant effect. The study concludes with some implications for L2 teachers' education.