Exposure to user-generated e-cigarette content on social media associated with greater vulnerability to e-cigarette use among youth non-users.

INTRODUCTION: Social media are important venues for youth's exposure to e-cigarette content. This study examined how exposure to user-generated e-cigarette content (i.e., content created and shared by individual social media users) is associated with vulnerabilities to e-cigarette use among youth non-users. METHODS: We pooled data from the 2021 and 2022 National Youth Tobacco Survey. Youth who have never used e-cigarettes were included. Weighted linear and logistic regressions were conducted to examine how exposure to user-generated e-cigarette content (from real-life friends, online-only friends, and celebrities/influencers) on social media was associated with e-cigarette use vulnerabilities measured by perceived norms, perceived risk, and susceptibility of use, controlling for demographics, advertising exposure, and mental health conditions. Multiple imputations were performed to account for missing data. RESULTS: Exposure to e-cigarette content on social media posted by real-life friends, online-only friends, and celebrities/influencers were associated with more positive descriptive norm (ßs = 1.56, 0.37, and 0.35, respectively, all ps < .001), more positive injunctive norm (ßs = 0.46, 0.19, and 0.10, respectively, all ps < .001), and higher odds of e-cigarette use susceptibility (ORs = 1.48, 1.50. 1.29, respectively, all ps < .001). Exposure to content posted by real-life and online-only friends were associated with reduced risk perception of e-cigarette use (ß = -0.04, p < 0.05 and ß = -0.07, p < 0.001). CONCLUSIONS: Our study highlighted that friends and celebrities/influencers are important sources on social media that can influence youth non-users' vulnerabilities to e-cigarette use. Interventional messages communicated through friends and influencers on social media may in turn help reduce e-cigarette vulnerability among youth non-users.

An Anthocyanin-Based Eco-Friendly Triboelectric Nanogenerator for pH Monitoring and Energy Harvesting.

In recent years, renewable and sustainable triboelectric nanogenerators have attracted attention due to their high energy conversion rate, and enhancing their functionality further contributes to their applicability across various fields. A pH-sensitive triboelectric nanogenerator (pH-TENG) has been prepared by electrostatic spinning technology, with anthocyanin as the pH indicator and environmentally friendly polyvinyl alcohol (PVA) as the substrate. Among many friction-negative materials, the pH-TENG exhibits the best combination with fluorinated ethylene propylene (FEP) and yields an open-circuit voltage of 62 V, a short-circuit current of 370 nA, and a transferred charge of 21.8 nC. At a frequency of 3 Hz, it can charge a 4.7 µF capacitor to 2 V within 45 s, effectively powering a thermometer. Furthermore, the presence of anthocyanin does not affect the pH-TENG's power generation performance and enables the monitoring of a wide range of environmental pH changes, with an ΔE change of 28.8 ± 7.6. Therefore, pH-TENG prepared with environmentally friendly materials can bring new available materials to the biological and medical fields.

Solidophobic Surface for Electrochemical Extraction of High-Valued Mg(OH)2 Coupled with H2 Production from Seawater.

A significant challenge in direct seawater electrolysis is the rapid deactivation of the cathode due to the large scaling of Mg(OH)2. Herein, we synthesized a Pt-coated highly disordered NiCu alloy (Pt-NiCu alloy) electrode with superior solidophobic behavior, enabling stable hydrogen generation (100 mA cm-2, >1000 h durability) and simultaneous production of Mg(OH)2 (>99.0% purity) in electrolyte enriched with Mg2+ and Ca2+. The unconventional solidophobic property primarily stems from the high surface energy of the NiCu alloy substrate, which facilitates the adsorption of surface water and thereby compels the bulk formation of Mg(OH)2 via homogeneous nucleation. The discovery of this solidophobic electrode will revolutionarily simplify the existing techniques for seawater electrolysis and increase the economic viability for seawater electrolysis.

Deep Learning Features and Metabolic Tumor Volume Based on PET/CT to Construct Risk Stratification in Non-small Cell Lung Cancer.

RATIONALE AND OBJECTIVES: To build a risk stratification by incorporating PET/CT-based deep learning features and whole-body metabolic tumor volume (MTVwb), which was to make predictions about overall survival (OS) and progression-free survival (PFS) for those with non-small cell lung cancer (NSCLC) as a complement to the TNM staging. MATERIALS AND METHODS: The study enrolled 590 patients with NSCLC (413 for training and 177 for testing). Features were extracted by employing a convolutional neural network. The combined risk stratification (CRS) was constructed by the selected features and MTVwb, which were contrasted and integrated with TNM staging. In the testing set, those were verified. RESULTS: Multivariate analysis revealed that CRS was an independent predictor of OS and PFS. C-indexes of the CRS demonstrated statistically significant increases in comparison to TNM staging, excepting predicting OS in the testing set (for OS, C-index=0.71 vs. 0.691 in the training set and 0.73 vs. 0.736 in the testing set; for PFS, C-index=0.702 vs. 0.686 in the training set and 0.732 vs. 0.71 in the testing set). The nomogram that combined CRS with TNM staging demonstrated the most superior model performance in the training and testing sets (C-index=0.741 and 0.771). CONCLUSION: The addition of CRS improves TNM staging's predictive power and shows potential as a useful tool to support physicians in making treatment decisions.

Mechanistic Insights into the Palladium-Catalyzed Perfluoroalkylative Carbonylation of Unactivated Alkenes to ß-Perfluoroalkyl Esters: A DFT Study.

Transition metal-catalyzed multicomponent carbonylation is an efficient synthetic strategy to access multifunctional esters in high yields with broad functional group tolerance and good chemoselectivity. Considering the development of highly efficient synthetic methods for esters, it remains significant to grasp the mechanism of constructing multifunctional esters. Herein, density functional theoretical calculations were carried out to acquire mechanistic insight into the synthesis of ß-perfluoroalkyl esters from a specific palladium-catalyzed perfluoroalkylative carbonylation of unactivated alkenes using carbon monoxide. A detailed mechanistic understanding of this reaction route includes (1) multistep radical reaction process, (2) C-C coupling and CO insertion, (3) ligand exchange, and (4) Pd-based intermediate oxidation and reductive elimination. The multistep radical process was fundamentally rationalized, including Rf· formation and radicals A and E from unactivated alkene and CO oxidation, respectively. The potential energy calculation indicated that the CO insertion into the perfluorinated alkyl radicals preceded Pd-catalyzed oxidation in the competitively multistep free radical reaction process. In addition, the I-/PhO- exchange step was predicted to be spontaneous to products. The IGMH analysis further attested to the reductive elimination process involved in the rate-determining step. Thus, a simple and valid density functional theory (DFT) approach was developed to reveal the multistep radical mechanism for the Pd-catalyzed perfluoroalkylative carbonylation of unactivated alkenes to access functional ß-perfluoroalkyl esters.

Electric field driven tourmaline/hematite dual mineral photocatalysis for efficient antibiotic removal.

Hematite (Fe2O3) has garnered attention due to its stability, economic viability, and non-toxic nature. However, the rapid recombination of charge carriers hampers its practical application. On the other hand, tourmaline's inherent surface electric field facilitates the rapid separation of photogenerated electrons and holes. In this study, two directly mined natural minerals, tourmaline and hematite (TFO), were successfully combined. Characterization and experiments indicate that the pronounced enhancement of photocatalytic activity in Fe2O3 is attributed to the electric field effect on the surface of tourmaline. TFO successfully removes 93% of tetracycline (TC, 50 ppm) within 60 min. The reaction rate constant for TFO composite material (0.0410 min-1) is 8.5 times that of tourmaline (0.0048 min-1) and 14.1 times that of hematite (0.0029 min-1). Simultaneously, it markedly improves light absorption and charge carrier separation capabilities. Through simulations of various natural environmental factors, TFO demonstrates excellent practicality. Analyzing and detecting active species revealed the involvement of four types of active species, with ·OH radicals making the most significant contribution. The photocatalytic mechanism was proposed. Furthermore, the degradation pathway of tetracycline and the toxicity of its metabolites were investigated. This work provides additional inspirations and insights for photocatalytic materials performance enhancement and natural resources green governance environment.

Cardiolipin oxidized by ROS from complex II acts as a target of gasdermin D to drive mitochondrial pore and heart dysfunction in endotoxemia.

Cardiac dysfunction, an early complication of endotoxemia, is the major cause of death in intensive care units. No specific therapy is available at present for this cardiac dysfunction. Here, we show that the N-terminal gasdermin D (GSDMD-N) initiates mitochondrial apoptotic pore and cardiac dysfunction by directly interacting with cardiolipin oxidized by complex II-generated reactive oxygen species (ROS) during endotoxemia. Caspase-4/11 initiates GSDMD-N pores that are subsequently amplified by the upregulation and activation of NLRP3 inflammation through further generation of ROS. GSDMD-N pores form prior to BAX and VDAC1 apoptotic pores and further incorporate into BAX and VDAC1 oligomers within mitochondria membranes to exacerbate the apoptotic process. Our findings identify oxidized cardiolipin as the definitive target of GSDMD-N in mitochondria of cardiomyocytes during endotoxin-induced myocardial dysfunction (EIMD), and modulation of cardiolipin oxidation could be a therapeutic target early in the disease process to prevent EIMD.

Multi-omics delineate growth factor network underlying exercise effects in an Alzheimer's mouse model.

Physical exercise represents a primary defense against age-related cognitive decline and neurodegenerative disorders like Alzheimer's disease (AD). To impartially investigate the underlying mechanisms, we conducted single-nucleus transcriptomic and chromatin accessibility analyses (snRNA-seq and ATAC-seq) on the hippocampus of mice carrying AD-linked NL-G-F mutations in the amyloid precursor protein gene (APPNL-G-F) following prolonged voluntary wheel-running exercise. Our study reveals that exercise mitigates amyloid-induced changes in both transcriptomic expression and chromatin accessibility through cell type-specific transcriptional regulatory networks. These networks converge on the activation of growth factor signaling pathways, particularly the epidermal growth factor receptor (EGFR) and insulin signaling, correlating with an increased proportion of immature dentate granule cells and oligodendrocytes. Notably, the beneficial effects of exercise on neurocognitive functions can be blocked by pharmacological inhibition of EGFR and the downstream phosphoinositide 3-kinases (PI3K). Furthermore, exercise leads to elevated levels of heparin-binding EGF (HB-EGF) in the blood, and intranasal administration of HB-EGF enhances memory function in sedentary APPNL-G-F mice. These findings offer a panoramic delineation of cell type-specific hippocampal transcriptional networks activated by exercise and suggest EGF-related growth factor signaling as a druggable contributor to exercise-induced memory enhancement, thereby suggesting therapeutic avenues for combatting AD-related cognitive decline.

Cornuside alleviates psoriasis-like skin lesions in mice by relieving inflammatory effects.

Psoriasis is a chronic inflammatory skin disease substantially affecting the quality of life, with no complete cure owing to its complex pathogenesis. Cornuside, a major bioactive compound present in Cornus officinalis Sieb. et Zucc., which is a well-known traditional Chinese medicine with a variety of biological and pharmacological activities, such as anti-apoptotic, antioxidant, and anti-inflammatory properties. However, its effects on psoriasis remain unclear. Our preliminary analysis of network pharmacology showed that cornuside may be involved in psoriasis by regulating the inflammatory response and IL-17 signaling pathway. Thus, we investigated the protective role and mechanism of cornuside in the pathogenesis of psoriasis in an imiquimod (IMQ)-induced psoriasis mouse model. In-vivo experiments demonstrated that cornuside-treated mice had reduced skin erythema, scales, thickness, and inflammatory infiltration. The Psoriasis Area Severity Index score was significantly lower than that of the IMQ group. Flow cytometry analysis indicated that cornuside effectively inhibited Th1- and Th17-cell infiltration and promoted aggregation of Th2 cells in skin tissues. Cornuside also inhibited the infiltration of macrophages to the skin. Furthermore, in-vitro experiments indicated that cornuside also decreased the polarization of M1 macrophages and reduced the levels of associated cytokines. Western blotting demonstrated that cornuside suppressed the phosphorylation of c-Jun N-terminal kinase (JNK) and extracellular receptor kinase (ERK) in bone marrow-derived macrophages. Our findings indicate that cornuside has a protective effect against IMQ-induced psoriasis by inhibiting M1 macrophage polarization through the ERK and JNK signaling pathways and modulating the infiltration of immune cells as well as the expression of inflammatory factors.

Remnant cholesterol is associated with unstable carotid plaque in a neurologically healthy population.

BACKGROUND: Remnant cholesterol (RC) is considered to be one of the most significant and important risk factors for atherosclerotic cardiovascular disease (ASCVD). Nonetheless, the association between RC and unstable carotid plaque remains unclear. Our primary objective is to ascertain whether RC exhibits an independent and significant association with unstable carotid plaque in a neurologically healthy population. METHODS: In the cross-sectional study, we enrolled neurologically healthy participants who visited our centre for health checkups between 2021 and 2022. All eligible participants underwent a standardised questionnaire, physical examinations and laboratory testing. The carotid plaque was evaluated with a standard carotid ultrasound and an advanced ultrasound imaging technique called superb microvascular imaging. The correlation between lipids and unstable carotid plaque was primarily assessed utilising univariate and multivariate logistic regression. RESULTS: The study totally enrolled 1100 participants who had an average age of 57.00 years (IQR: 49.00-63.00), with 67.55% being men. Among the participants, 321 (29.18%) had unstable carotid plaque. In the multivariate logistic regression analysis, higher RC had an independent association with an elevated incidence of unstable carotid plaque compared with the lowest concentrations of RC (OR=1.673, 95% CI 1.113 to 2.515, p=0.0134), but not other lipids. In addition, apolipoprotein A1 was negatively related to unstable carotid plaque (OR=0.549, 95% CI 0.364 to 0.830, p=0.0045). CONCLUSIONS: Elevated concentrations of RC are independently and excellently correlated with unstable carotid plaque within a neurologically healthy population.

Sensitive Detection of OCS Using Thermal Conversion Combined with Spectral Reconstruction Filtering Differential Optical Absorption Spectroscopy.

Carbonyl sulfide (OCS) is a toxic gas produced during industrial processes that poses risks to both human health and industrial equipment. Therefore, detecting OCS concentrations plays a crucial role in early hazard warning. This paper presents an online system for detecting OCS at the ppb level using thermal conversion and spectral reconstruction filtering differential optical absorption spectroscopy (SRF-DOAS). First, OCS, which is not suitable for DOAS due to its weak absorption characteristics, is completely transformed into SO2 with strong absorption characteristics under high-temperature conditions. Then, the spectral reconstruction filtering method (SRF) is proposed to eliminate the noise and interference. The core idea of the method is to arrange the spectrum according to the spectral intensity from small to large rather than wavelength, reconstructing the spectrum into a new spectrum with linear characteristics. The reconstructed spectrum can remove noise and interference by linear fitting and retain the characteristic of SO2 oscillation absorption. Next, we demonstrate the ability of the reconstructed spectral method to remove noise and interference by comparing the spectra of the inverse-reconstructed gas mixture and SO2. The relative deviation of 0.88% at 100 ppb and detection limit of 7.26 ppb*m for OCS were obtained using the SRF-DOAS method. Finally, the reliability of the system was confirmed by measurements of OCS concentrations in mixture gas of OCS and air, as well as in human exhaled breath.

Laboratory tests and analysis of drug resistance in non-tuberculous mycobacteria.

Background: This study analyzed the laboratory diagnosis results and drug resistance of patients infected with non-tuberculous mycobacterium (NTM). Methods: We collected information on patients with positive indicators of NTM infection at the Henan Provincial Chest Hospital from 2020 to 2022. Acid-fast smear, mycobacterium culture, QB-SPOT assay, GeneXpert MTB/RIF assay, immunoglobulin E test, tuberculosis antibody test, and microplate method for drug sensitivity test were analyzed using strain identification as the gold standard. Results: The 242 cases of NTM infection were predominantly detected with slow-growing mycobacteria (a detection rate of 87.19%), among which Mycobacterium intracellulare (66.53%), Mycobacterium avium (15.70%), and Mycobacterium chelonei/abscessus complex (11.16%) ranked the top three in terms of the isolation rate. Males patients accounted for a higher proportion (58.26%) than females (41.74%), and the majority of them were over 60 years (50.83%). Among laboratory tests for patients with NTM infection, mycobacterium culture showed a highest detected rate (87.20%) among laboratory tests. The results of the drug sensitivity test demonstrated that the resistance rate of NTM was generally high. Moreover, the Mycobacterium avium complex with the highest isolation rate showed 100% resistant to doxycycline and minocycline, but exhibited relatively high sensitivity to moxifloxacin (a resistance rate of 7.89%) and rifabutin (a resistance rate of 13.16%). The Mycobacterium chelonei/abscessus complex was 100% resistant to doxycycline and relatively sensitive to cefoxitin (29.17%) and clarithromycin (37.50%). Conclusion: The NTM species isolated by the Henan Provincial Chest Hospital is dominated by Mycobacterium intracellulare and the highest positive rate is detected by mycobacterium culture among laboratory tests. NTM infection generally exhibits a high rate of drug resistance. Accordingly, the accurate diagnosis of NTM diseases requires enhanced drug sensitivity testing to provide patients with targeted combination drug treatment.

Theoretical Study on Ion Diffusion Mechanism in W-Doped K3SbS4 as Solid-State Electrolyte for K-Ion Batteries.

The development of a solid-state electrolyte (SSE) is crucial for overcoming the side reactions of metal potassium anodes and advancing the progress of K-ion batteries (KIBs). Exploring the diffusion mechanism of the K ion in SSE is important for deepening our understanding and promoting its development. In this study, we conducted static calculations and utilized deep potential molecular dynamics (DeepMD) to investigate the behavior of cubic K3SbS4. The original K3SbS4 exhibited poor ionic conductivity, but we discovered that introducing heterovalent tungsten doping created vacancies, which significantly reduced the activation energy to 0.12 eV and enhanced the ionic conductivity to 1.80 × 10-2 S/cm. The diffusion of K-ions in K3SbS4 primarily occurs through the exchange of positions with K vacancies. This research provides insights into the design of SSE with high ionic conductivity. Furthermore, it highlights the effectiveness of DeepMD as a powerful tool for studying the SSE.

Ultrasensitive Near-Infrared Polarization Photodetectors with Violet Phosphorus/InSe van der Waals Heterostructures.

Near-infrared (NIR) polarization photodetectors with two-dimensional (2D) semiconductors and their van der Waals (vdW) heterostructures have presented great impact for the development of a wide range of technologies, such as in the optoelectronics and communication fields. Nevertheless, the lack of a photogenerated charge carrier at the device's interface leads to a poor charge carrier collection efficiency and a low linear dichroism ratio, hindering the achievement of high-performance optoelectronic devices with multifunctionalities. Herein, we present a type-II violet phosphorus (VP)/InSe vdW heterostructure that is predicted via density functional theory calculation and confirmed by Kelvin probe force microscopy. Benefiting from the type-II band alignment, the VP/InSe vdW heterostructure-based photodetector achieves excellent photodetection performance such as a responsivity (R) of 182.8 A/W, a detectivity (D*) of 7.86 × 1012 Jones, and an external quantum efficiency (EQE) of 11,939% under a 1064 nm photon excitation. Furthermore, the photodetection performance can be enhanced by manipulating the device geometry by inserting a few layers of graphene between the VP and InSe (VP/Gr/InSe). Remarkably, the VP/Gr/InSe vdW heterostructure shows a competitive polarization sensitivity of 2.59 at 1064 nm and can be integrated as an image sensor. This work demonstrates that VP/InSe and VP/Gr/InSe vdW heterostructures will be effective for promising integrated NIR optoelectronics.

Hammerhead-type FXR agonists induce an enhancer RNA Fincor that ameliorates nonalcoholic steatohepatitis in mice.

The nuclear receptor, farnesoid X receptor (FXR/NR1H4), is increasingly recognized as a promising drug target for metabolic diseases, including nonalcoholic steatohepatitis (NASH). Protein-coding genes regulated by FXR are well known, but whether FXR also acts through regulation of long non-coding RNAs (lncRNAs), which vastly outnumber protein-coding genes, remains unknown. Utilizing RNA-seq and global run-on sequencing (GRO-seq) analyses in mouse liver, we found that FXR activation affects the expression of many RNA transcripts from chromatin regions bearing enhancer features. Among these we discovered a previously unannotated liver-enriched enhancer-derived lncRNA (eRNA), termed FXR-induced non-coding RNA (Fincor). We show that Fincor is specifically induced by the hammerhead-type FXR agonists, including GW4064 and tropifexor. CRISPR/Cas9-mediated liver-specific knockdown of Fincor in dietary NASH mice reduced the beneficial effects of tropifexor, an FXR agonist currently in clinical trials for NASH and primary biliary cholangitis (PBC), indicating that amelioration of liver fibrosis and inflammation in NASH treatment by tropifexor is mediated in part by Fincor. Overall, our findings highlight that pharmacological activation of FXR by hammerhead-type agonists induces a novel eRNA, Fincor, contributing to the amelioration of NASH in mice. Fincor may represent a new drug target for addressing metabolic disorders, including NASH.

Non-alcoholic steatohepatitis, also known as NASH, is a severe condition whereby fat deposits around the liver lead to inflammation, swelling, scarring and lasting damage to the organ. Despite being one of the leading causes of liver-related deaths worldwide, the disease has no approved treatment. A protein known as Farnesoid X receptor (or FXR) is increasingly being recognized as a promising drug target for non-alcoholic steatohepatitis. Once activated, FXR helps to regulate the activity of DNA regions which are coding for proteins important for liver health. However, less is known about how FXR may act on non-coding regions, the DNA sequences that do not generate proteins but can be transcribed into RNA molecules with important biological roles. In response, Chen et al. investigated whether FXR activation of non-coding RNAs could be linked to the clinical benefits of hammerhead FXR agonists, a type of synthetic compounds that activates this receptor. To do so, genetic analyses of mouse livers were performed to identify non-coding RNAs generated when FXR was activated by the agonist. These experiments revealed that agonist-activated FXR induced a range of non-coding RNAs transcribed from DNA sequences known as enhancers, which help to regulate gene expression. In particular, hammerhead FXR agonists led to the production of a liver-specific enhancer RNA called Fincor. Additional experiments using tropifexor, a hammerhead FXR agonist currently into clinical trials, showed that this investigational new drug had reduced benefits in a mouse model of non-alcoholic steatohepatitis with low Fincor levels. This suggested that this enhancer RNA may play a key role in mediating the clinical benefits of hammerhead FXR agonists, encouraging further research into its role and therapeutic value.

A Soft Collaborative Robot for Contact-based Intuitive Human Drag Teaching.

Soft material-based robots, known for their safety and compliance, are expected to play an irreplaceable role in human-robot collaboration. However, this expectation is far from real industrial applications due to their complex programmability and poor motion precision, brought by the super elasticity and large hysteresis of soft materials. Here, a soft collaborative robot (Soft Co-bot) with intuitive and easy programming by contact-based drag teaching, and also with exceptional motion repeatability (< 0.30% of body length) and ultra-low hysteresis (< 2.0%) is reported. Such an unprecedented capability is achieved by a biomimetic antagonistic design within a pneumatic soft robot, in which cables are threaded to servo motors through tension sensors to form a self-sensing system, thus providing both precise actuation and dragging-aware collaboration. Hence, the Soft Co-bots can be first taught by human drag and then precisely repeat various tasks on their own, such as electronics assembling, machine tool installation, etc. The proposed Soft Co-bots exhibit a high potential for safe and intuitive human-robot collaboration in unstructured environments, promoting the immediate practical application of soft robots.

UHRF1 inhibition mitigates vascular endothelial cell injury and ameliorates atherosclerosis in mice via regulating the SMAD7/YAP1 axis.

BACKGROUND: Endothelial cell injury and dysfunction lead to cholesterol and lipid accumulation and atherosclerotic plaque formation in the arterial wall during atherosclerosis (AS) progression, Ubiquitin-like containing PHD and RING finger domain 1 (UHRF1), a DNA methylation regulator, was strongly upregulated in atherosclerotic plaque lesions in mice. This study aimed to investigate the precise biological functions and regulatory mechanisms of UHRF1 on endothelial dysfunction during AS development. METHODS: UHRF1 levels in the atherosclerotic plaque tissues and normal arterial intima from AS patients were tested with Western blot analysis and immunohistochemistry assays. Human umbilical vein endothelial cells (HUVECs) were stimulated with oxidized low-density lipoprotein (ox-LDL) to induce an injury model and then transfected with short hairpin RNA targeting UHRF1 (sh-UHRF1). Cell proliferation, migration, apoptosis, the levels of inflammatory cytokines including tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6), and the protein levels adhesion molecules including vascular cell adhesion molecule-1 (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1) were measured. Moreover, co-immunoprecipitation assay was used to determine the interactions between UHRF1 and DNA methyltransferases 1 (DNMT1), As well as mothers against DPP homolog 7 (SMAD7) and yes-associated protein 1 (YAP1). SMAD7 promoter methylation was examined with methylation-specific PCR. In addition, we established an AS mouse model to determine the in vivo effects of UHRF1 on AS progression. RESULTS: UHRF1 was upregulated in atherosclerotic plaque tissues and ox-LDL-treated HUVECs. UHRF1 knockdown mitigated ox-LDL-induced proliferation and migration inhibition, apoptosis and the production of TNF-α, IL-6, VCAM-1, and ICAM-1 in HUVECs. Mechanistically, UHRF1 promoted DNMT1-mediated SMAD7 promoter methylation and inhibited its expression. SMAD7 knockdown abolished the protective effects of UHRF1 knockdown on ox-LDL-induced HUVEC injury. Moreover, SMAD7 interacted with YAP1 and inhibited YAP1 expression by promoting YAP1 protein ubiquitination-independent degradation in HUVECs. YAP1 overexpression abrogated SMAD7 overexpression-mediated protective effects on ox-LDL-induced HUVEC injury. Finally, UHRF1 knockdown alleviated atherosclerotic plaque deposition and arterial lesions in AS mice. CONCLUSION: UHRF1 inhibition mitigates vascular endothelial cell injury and ameliorates AS progression in mice by regulating the SMAD7/YAP1 axis.

Co-Assembled Nanoparticles toward Multi-Target Combinational Therapy of Alzheimer's Disease by Making Full Use of Molecular Recognition and Self-Assembly.

The complex pathologies in Alzheimer's disease (AD) severely limit the effectiveness of single-target pharmic interventions, thus necessitating multi-pronged therapeutic strategies. While flexibility is essentially demanded in constructing such multi-target systems, for achieving optimal synergies and also accommodating the inherent heterogeneity within AD. Utilizing the dynamic reversibility of supramolecular strategy for conferring sufficient tunability in component substitution and proportion adjustment, amphiphilic calixarenes are poised to be a privileged molecular tool for facilely achieving function integration. Herein, taking ß-amyloid (Aß) fibrillation and oxidative stress as model combination pattern, a supramolecular multifunctional integration is proposed by co-assembling guanidinium-modified calixarene with ascorbyl palmitate and loading dipotassium phytate within calixarene cavity. Serial pivotal events can be simultaneously addressed by this versatile system, including 1) inhibition of Aß production and aggregation, 2) disintegration of Aß fibrils, 3) acceleration of Aß metabolic clearance, and 4) regulation of oxidative stress, which is verified to significantly ameliorate the cognitive impairment of 5×FAD mice, with reduced Aß plaque content, neuroinflammation, and neuronal apoptosis. Confronted with the extremely intricate clinical realities of AD, the strategy presented here exhibits ample adaptability for necessary alterations on combinations, thereby may immensely expedite the advancement of AD combinational therapy through providing an exceptionally convenient platform.

Spatial Trueness Evaluation of 3D-Printed Dental Model Made of Photopolymer Resin: Use of Special Structurized Dental Model.

(1) Background: Various 3D printers are available for dental practice; however, a comprehensive accuracy evaluation method to effectively guide practitioners is lacking. This in vitro study aimed to propose an optimized method to evaluate the spatial trueness of a 3D-printed dental model made of photopolymer resin based on a special structurized dental model, and provide the preliminary evaluation results of six 3D printers. (2) Methods: A structurized dental model comprising several geometrical configurations was designed based on dental crown and arch measurement data reported in previous studies. Ninety-six feature sizes can be directly measured on this original model with minimized manual measurement errors. Six types of photo-curing 3D printers, including Objet30 Pro using the Polyjet technique, Projet 3510 HD Plus using the Multijet technique, Perfactory DDP and DLP 800d using the DLP technique, Form2 and Form3 using the SLA technique, and each printer's respective 3D-printable dental model materials, were used to fabricate one set of physical models each. Regarding the feature sizes of the simulated dental crowns and dental arches, linear measurements were recorded. The scanned digital models were compared with the design data, and 3D form errors (including overall 3D deviation; flatness, parallelism, and perpendicularity errors) were measured. (3) Results: The lowest overall 3D deviation, flatness, parallelism, and perpendicularity errors were noted for the models printed using the Objet30 Pro (overall value: 45 µm), Form3 (0.061 ± 0.019 mm), Objet30 Pro (0.138 ± 0.068°), and Projet 3510 HD Plus (0.095 ± 0.070°), respectively. In color difference maps, different deformation patterns were observed in the printed models. The feature size proved most accurate for the Objet30 Pro fabricated models (occlusal plane error: 0.02 ± 0.36%, occlusogingival direction error: -0.06 ± 0.09%). (4) Conclusions: The authors investigated a novel evaluation approach for the spatial trueness of a 3D-printed dental model made of photopolymer resin based on a structurized dental model. This method can objectively and comprehensively evaluate the spatial trueness of 3D-printed dental models and has a good repeatability and generalizability.

An Appearance-Semantic Descriptor with Coarse-to-Fine Matching for Robust VPR.

In recent years, semantic segmentation has made significant progress in visual place recognition (VPR) by using semantic information that is relatively invariant to appearance and viewpoint, demonstrating great potential. However, in some extreme scenarios, there may be semantic occlusion and semantic sparsity, which can lead to confusion when relying solely on semantic information for localization. Therefore, this paper proposes a novel VPR framework that employs a coarse-to-fine image matching strategy, combining semantic and appearance information to improve algorithm performance. First, we construct SemLook global descriptors using semantic contours, which can preliminarily screen images to enhance the accuracy and real-time performance of the algorithm. Based on this, we introduce SemLook local descriptors for fine screening, combining robust appearance information extracted by deep learning with semantic information. These local descriptors can address issues such as semantic overlap and sparsity in urban environments, further improving the accuracy of the algorithm. Through this refined screening process, we can effectively handle the challenges of complex image matching in urban environments and obtain more accurate results. The performance of SemLook descriptors is evaluated on three public datasets (Extended-CMU Season, Robot-Car Seasons v2, and SYNTHIA) and compared with six state-of-the-art VPR algorithms (HOG, CoHOG, AlexNet_VPR, Region VLAD, Patch-NetVLAD, Forest). In the experimental comparison, considering both real-time performance and evaluation metrics, the SemLook descriptors are found to outperform the other six algorithms. Evaluation metrics include the area under the curve (AUC) based on the precision-recall curve, Recall@100%Precision, and Precision@100%Recall. On the Extended-CMU Season dataset, SemLook descriptors achieve a 100% AUC value, and on the SYNTHIA dataset, they achieve a 99% AUC value, demonstrating outstanding performance. The experimental results indicate that introducing global descriptors for initial screening and utilizing local descriptors combining both semantic and appearance information for precise matching can effectively address the issue of location recognition in scenarios with semantic ambiguity or sparsity. This algorithm enhances descriptor performance, making it more accurate and robust in scenes with variations in appearance and viewpoint.