Construction of BaTiO3-TiO2 hollow sphere heterojunctions for enhanced microwave dynamic therapy in cancer treatment.

Cancer is one of the primary health concerns among humans due to its high incidence rate and lack of effective treatment. Currently, medical techniques to achieve the precise elimination of local cancer lesions with negligible damage to normal tissues are still intensely desired. Herein, we synthesized BaTiO3-TiO2 hollow spheres (BTHSs) for use in microwave dynamic therapy (MWDT) for cancer. Under UV irradiation, BTHSs can mediate the production of multiple reactive oxygen species (ROS), mainly 1O2, which results in a rapid photocatalytic degradation rate (97%), 1.6-fold that of commercial P25. Importantly, the ROS production process can be triggered by microwaves to effectively execute MWDT for cancer. Under microwave irradiation, BTHSs exhibit a remarkable therapeutic effect and slight cytotoxicity. In terms of mechanism, the enhanced ROS production efficiency of BTHSs can be attributed to their unique hollow structure and the formation of a type-II heterojunction by the incorporation of BaTiO3. The hollow structure increases the availability of active sites and enhances light scattering, while the BaTiO3-TiO2 heterojunction enhances the photocatalytic activity of TiO2 through charge transfer and electron-hole separation. Overall, this study provides important insights into the design and optimization of sensitizers for MWDT applications.

Epigenetic regulation of osteogenic differentiation of periodontal ligament stem cells in periodontitis.

Periodontitis is an inflammatory disease characterized by alveolar bone loss. Periodontal ligament stem cells (PDLSCs) have osteogenic differentiation potential, which can be influenced by epigenetics regulation in periodontitis. Therefore, this review aimed to shed light on the role of different epigenetic mechanisms in the osteogenic differentiation of PDLSCs and to consider the prospects of their possible therapeutic applications in periodontitis. Databases MEDLINE (through PubMed) and Web of Science were searched for the current knowledge of epigenetics in osteogenic differentiation of PDLSCs using the keywords "periodontal ligament stem cells", "epigenetic regulation", "epigenetics", "osteogenic differentiation", and "osteogenesis". All studies introducing epigenetic regulation and PDLSCs were retrieved. This review shows that epigenetic factors like DNMT, KDM6A, HDACi, some miRNAs, and lncRNAs can induce the osteogenic differentiation of PDLSCs in the noninflammatory microenvironment. However, the osteogenic differentiation of PDLSCs is inhibited in the inflammatory microenvironment through the upregulated DNA methylation of osteogenesis-related genes and specific changes in histone modification and noncoding RNA. Epigenetics of osteogenic differentiation of PDLSCs in inflammation exhibits the contrary effect compared with a noninflammatory environment. The application of epigenetic drugs to regulate the abnormal epigenetic status in periodontitis and focus on alveolar bone regeneration is promising.

Effects of bonded spurs, fixed and removable palatal crib in the early treatment of anterior open bite: A systematic review and meta-analysis.

INTRODUCTION: Bonded spurs, fixed or removable palatal cribs have been used to treat anterior open bite (AOB) in growing children. Different conclusions have been brought out by different authors. This meta-analysis aimed to evaluate the effect of bonded spurs, fixed and removable palatal cribs in the early treatment of AOB. METHODS: A comprehensive electronic search was carried out through PubMed, Embase (via Ovid), MEDLINE (via Ovid), Cochrane Central Register of Controlled Trials, and Web of Science up to May 1, 2022. This meta-analysis was performed in accordance with the Cochrane Handbook for Systematic Reviews of Interventions. The work was carried out by 2 reviewers in duplicate and independently, including electronic searching, data extracting, risk of bias assessment, quality of evidence grading, heterogeneity and statistical power analysis, and eligibility evaluation of the retrieved articles. RESULTS: Four studies out of 181 articles were recruited in the meta-analysis after applying the inclusion and exclusion criteria. The results showed that bonded lingual spurs and fixed palatal crib or spurs produced similar overbite changes (mean difference, -0.32; 95% confidence interval, -1.06 to 0.43; P = 0.41; I2 = 27%; meta power = 0.099). Fixed palatal crib and removable palatal crib also exhibited comparable effects in correcting AOB (mean difference, -0.02; 95% confidence interval, -0.90 to 0.86; P = 0.96; I2 = 0%; meta power = 0.2182). The quality of evidence about these 2 outcomes assessed with GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) was low. CONCLUSIONS: Bonded lingual spurs, fixed palatal crib or spurs, and removable palatal crib had similar effects in the early treatment of AOB. Because the number of included studies was limited and only the overbite changes before and after treatment were assessed, more clinical randomized controlled studies with longer follow-ups are needed to get more clinically significant advice.

LncRNA nuclear-enriched abundant transcript 1 aggravates cerebral ischemia/reperfusion injury through activating early growth response-1/RNA binding motif protein 25 axis.

Ischemic stroke is a major global health issue. Ischemia and subsequent reperfusion results in stroke-related brain injury. Previous studies have demonstrated that nuclear-enriched abundant transcript 1 (NEATa and early growth response 1 (EGR1) are involved in ischemia reperfusion (IR) injury). In this study, we aimed to explore the roles of NEAT1/EGR1 axis as well as its downstream effector RNA binding motif protein 25 (RBM25) in cerebral IR injury. Oxygen-glucose deprivation/reperfusion (OGD/R) and middle cerebral artery occlusion (MCAO) were used to establish in vitro and in vivo models of cerebral IR injury, respectively. According to our data, NEAT1, EGR1, and RBM25 levels were elevated in OGD/R-exposed SK-N-SH and SH-SY5Y cells and cerebral cortex of MCAO mice. NEAT1, EGR1, or RBM25 knockdown effectively reduced infarct volumes and apoptosis, and improved neurological function. Mechanistically, NEAT1 directly interacted with EGR1, which restrained WW domain containing E3 ubiquitin protein ligase 1 (WWP1)-mediated ubiquitination of EGR1 and subsequently caused EGR1 accumulation. EGR1 bound to RBM25 promoter and transcriptionally activated RBM25. Rescue experiments indicated that RBM25 overexpression abolished the therapeutic effects of NEAT1 knockdown. In conclusion, this work identified a novel NEAT1/EGR1/RBM25 axis in potentiating brain injury after IR insults, suggesting a potential therapeutic target for ischemic stroke.

Endoplasmic reticulum-mitochondria miscommunication is an early and causal trigger of hepatic insulin resistance and steatosis.

BACKGROUND & AIMS: Hepatic insulin resistance in obesity and type 2 diabetes was recently associated with endoplasmic reticulum (ER)-mitochondria miscommunication. These contact sites (mitochondria-associated membranes: MAMs) are highly dynamic and involved in many functions; however, whether MAM dysfunction plays a causal role in hepatic insulin resistance and steatosis is not clear. Thus, we aimed to determine whether and how organelle miscommunication plays a role in the onset and progression of hepatic metabolic impairment. METHODS: We analyzed hepatic ER-mitochondria interactions and calcium exchange in a time-dependent and reversible manner in mice with diet-induced obesity. Additionally, we used recombinant adenovirus to express a specific organelle spacer or linker in mouse livers, to determine the causal impact of MAM dysfunction on hepatic metabolic alterations. RESULTS: Disruption of ER-mitochondria interactions and calcium exchange is an early event preceding hepatic insulin resistance and steatosis in mice with diet-induced obesity. Interestingly, an 8-week reversal diet concomitantly reversed hepatic organelle miscommunication and insulin resistance in obese mice. Mechanistically, disrupting structural and functional ER-mitochondria interactions through the hepatic overexpression of the organelle spacer FATE1 was sufficient to impair hepatic insulin action and glucose homeostasis. In addition, FATE1-mediated organelle miscommunication disrupted lipid-related mitochondrial oxidative metabolism and induced hepatic steatosis. Conversely, reinforcement of ER-mitochondria interactions through hepatic expression of a synthetic linker prevented diet-induced glucose intolerance after 4 weeks' overnutrition. Importantly, ER-mitochondria miscommunication was confirmed in the liver of obese patients with type 2 diabetes, and correlated with glycemia, HbA1c and HOMA-IR index. CONCLUSIONS: ER-mitochondria miscommunication is an early causal trigger of hepatic insulin resistance and steatosis, and can be reversed by switching to a healthy diet. Thus, targeting MAMs could help to restore metabolic homeostasis. LAY SUMMARY: The literature suggests that interactions between the endoplasmic reticulum and mitochondria could play a role in hepatic insulin resistance and steatosis during chronic obesity. In the present study, we reappraised the time-dependent regulation of hepatic endoplasmic reticulum-mitochondria interactions and calcium exchange, investigating reversibility and causality, in mice with diet-induced obesity. We also assessed the relevance of our findings to humans. We show that organelle miscommunication is an early causal trigger of hepatic insulin resistance and steatosis that can be improved by nutritional strategies.

Investigation on Potential Biomarkers and Immune-Related Mechanisms of Ischemic Stroke.

BACKGROUND: This study aimed to reveal the detailed immune-related mechanisms underlying ischemic stroke (IS) and identify new immune-associated biomarkers for clinical management. METHODS: Differentially expressed genes (DEGs) between IS samples and normal controls were identified using the GSE16561 dataset. The feature genes of the immune cells were investigated using the GSE72642 dataset. Weighted correlation network analysis (WGCNA) was performed to reveal module genes, followed by an investigation of common DEGs and a functional enrichment analysis. Potential biomarkers were identified based on hub genes in protein-protein interaction networks and WGCNA. Finally, GSE158312 was used for biomarker verification. RESULTS: In total, 1230 DEGs were identified between the IS samples and normal controls. Seven clinically significant modules were identified using WGCNA. The yellow module genes were positively correlated with polymorphonuclear cells (PMNC), whereas the brown module genes were positively correlated with CD4+ T cells. Eight genes were selected as hub genes. These genes are mainly involved in functions such as the innate immune response. Upregulated TLR2 and ARG1 levels were significantly different between the two groups in the verification dataset. CONCLUSIONS: Our findings suggest ARG1 and TLR2 as novel biomarkers for IS. Upregulated TLR2 might play a role in IS development by participating in the innate immune response function.

Alterations of gut microbiota and metabolome with Parkinson's disease.

Gut microbiota and amino acids that are one of their metabolites play important roles in the mechanism of pathology of Parkinson's disease (PD). It has been reported that the level of amino acids in vivo participate in neurodegeneration by regulating adaptive immune response, while the current researches on alteration of amino acids in gut microbiota are still insufficient. We hypothesized that alterations in gut microbiota might be accompanied by altered concentrations of amino acids, leading to the occurrence of PD. In this study, we collected stool samples from PD and healthy controls to analyse fecal microbiome and targeted metabolome by 16S ribosomal RNA (16S rRNA) gene sequencing and gas chromatography coupled to mass spectrometry (GC-MS). At the genus level, there was a greater abundance of Alistipes, Rikenellaceae_RC9_gut_group, Bifidobacterium, Parabacteroides, while Faecalibacterium was decreased in fecal samples from PD patients. Moreover, fecal branched chain amino acids (BCAAs) and aromatic amino acids concentrations were significantly reduced in PD patients compared to controls. Our study not only finds the abundance of certain gut microbiota in PD,but also reveals that it is related to BCAAs and aromatic amino acids. These findings are beneficial to identifying new therapeutic targets for PD by regulating diet and/or gut microbiota.

Long non-coding RNA LINC01426 facilitates glioblastoma progression via sponging miR-345-3p and upregulation of VAMP8.

BACKGROUND: Long non-coding RNAs (lncRNAs) has been extensively reported play important roles in regulating the development and progression of cancers, including Glioblastoma (GBM). LINC01426 is a novel lncRNA that has been identified as an oncogenic gene in GBM. Herein, we attempted to elucidate the detailed functions and underlying mechanisms of LINC01426 in GBM. METHODS: LINC01426 expression in GBM cell lines and tissues were detected by quantitative real-time PCR (qRT-PCR). Cell Counting Kit-8 (CCK8) assays, colony formation assays, subcutaneous tumor formation assays were utilized to investigate the biological functions of LINC01426 in GBM. Dual-luciferase reporter assays, RNA immunoprecipitation (RIP) and bioinformatic analysis were performed to determine the underlying mechanisms. RESULTS: LINC01426 is up-regulated in malignant GBM tissues and cell lines and it is capable to promote GBM cell proliferation and growth. Mechanistically, LINC01426 serves as a molecular sponge to sequester the miR345-3p and thus enhancing the level of VAMP8, an oncogenic coding gene, to promote GBM progression. CONCLUSIONS: Our results revealed the detailed mechanisms of LINC01426 facilitated cell proliferation and growth in GBM and report the clinical value of LINC01426 for GBM prognosis and treatment.

Front Vehicle Detection Algorithm for Smart Car Based on Improved SSD Model.

Vehicle detection is an indispensable part of environmental perception technology for smart cars. Aiming at the issues that conventional vehicle detection can be easily restricted by environmental conditions and cannot have accuracy and real-time performance, this article proposes a front vehicle detection algorithm for smart car based on improved SSD model. Single shot multibox detector (SSD) is one of the current mainstream object detection frameworks based on deep learning. This work first briefly introduces the SSD network model and analyzes and summarizes its problems and shortcomings in vehicle detection. Then, targeted improvements are performed to the SSD network model, including major advancements to the basic structure of the SSD model, the use of weighted mask in network training, and enhancement to the loss function. Finally, vehicle detection experiments are carried out on the basis of the KITTI vision benchmark suite and self-made vehicle dataset to observe the algorithm performance in different complicated environments and weather conditions. The test results based on the KITTI dataset show that the mAP value reaches 92.18%, and the average processing time per frame is 15 ms. Compared with the existing deep learning-based detection methods, the proposed algorithm can obtain accuracy and real-time performance simultaneously. Meanwhile, the algorithm has excellent robustness and environmental adaptability for complicated traffic environments and anti-jamming capabilities for bad weather conditions. These factors are of great significance to ensure the accurate and efficient operation of smart cars in real traffic scenarios and are beneficial to vastly reduce the incidence of traffic accidents and fully protect people's lives and property.

Pedestrian Detection Algorithm for Intelligent Vehicles in Complex Scenarios.

Pedestrian detection is an important aspect of the development of intelligent vehicles. To address problems in which traditional pedestrian detection is susceptible to environmental factors and are unable to meet the requirements of accuracy in real time, this study proposes a pedestrian detection algorithm for intelligent vehicles in complex scenarios. YOLOv3 is one of the deep learning-based object detection algorithms with good performance at present. In this article, the basic principle of YOLOv3 is elaborated and analyzed firstly to determine its limitations in pedestrian detection. Then, on the basis of the original YOLOv3 network model, many improvements are made, including modifying grid cell size, adopting improved k-means clustering algorithm, improving multi-scale bounding box prediction based on receptive field, and using Soft-NMS algorithm. Finally, based on INRIA person and PASCAL VOC 2012 datasets, pedestrian detection experiments are conducted to test the performance of the algorithm in various complex scenarios. The experimental results show that the mean Average Precision (mAP) value reaches 90.42%, and the average processing time of each frame is 9.6 ms. Compared with other detection algorithms, the proposed algorithm exhibits accuracy and real-time performance together, good robustness and anti-interference ability in complex scenarios, strong generalization ability, high network stability, and detection accuracy and detection speed have been markedly improved. Such improvements are significant in protecting the road safety of pedestrians and reducing traffic accidents, and are conducive to ensuring the steady development of the technological level of intelligent vehicle driving assistance.

Effect of MicroRNA-126a-3p on Bone Marrow Mesenchymal Stem Cells Repairing Blood-brain Barrier and Nerve Injury after Intracerebral Hemorrhage.

OBJECTIVE: Intracerebral hemorrhage (ICH) is a disease that threatens human health due to its high morbidity and mortality. On behalf of finding the better methods in the treatment of ICH, researchers pay more attention to a new technology which is finding effective genes to modify stem cells. METHODS: In this study, we isolated, cultured and identified bone marrow mesenchymal stem cells (MSCs) in vitro. Further, the MSCs (transfected with lentivirus expressing microRNA-126a-3p (miR-126)) were injected into the type Ⅶ collagenase-induced ICH rats to investigate the recovery effects of blood-brain barrier (BBB) and nerve damage in vivo. RESULTS: The MSCs surface marker molecules (CD29: 98.5%; CD90: 96.5%) were highly expressed, and the blood cell surface molecule was negatively expressed (CD45: 2%). Meanwhile, it was verified that miR-126 facilitated the differentiation of MSCs into vascular endothelial cells, owing to the rise of markers (CD31 and VE-cadherin). The modified neurological severity score, modified limb placing test score, brain water content and evans blue content were reduced after transplanted miR-126-modified MSCs. It was found that miR-126 accelerated the differentiation of MSCs into vascular endothelial cells via immunohistochemical staining in vivo. HE staining indicated the area of edema was obviously decreased compared with that in ICH + vector-MSCs group. MiR-126-modified MSCs alleviated the cell apoptosis in brain tissues by TUNEL assay. In addition, the mRNA and protein expression of protease activated receptor-1 and matrix metalloproteinase-9 were diminished, whilst the expression of zonula occludens-1 (ZO-1) and claudin-5 were enhanced in ICH+miR-126-MSCs group. Immunofluorescence assay revealed that miR-126-modified MSCs decreased the disruption of tight junction (ZO-1 and claudin-5). CONCLUSIONS: All data illustrate that miR-126-modified MSCs repair BBB and nerve injury after ICH.

Improved Traffic Sign Detection and Recognition Algorithm for Intelligent Vehicles.

Traffic sign detection and recognition are crucial in the development of intelligent vehicles. An improved traffic sign detection and recognition algorithm for intelligent vehicles is proposed to address problems such as how easily affected traditional traffic sign detection is by the environment, and poor real-time performance of deep learning-based methodologies for traffic sign recognition. Firstly, the HSV color space is used for spatial threshold segmentation, and traffic signs are effectively detected based on the shape features. Secondly, the model is considerably improved on the basis of the classical LeNet-5 convolutional neural network model by using Gabor kernel as the initial convolutional kernel, adding the batch normalization processing after the pooling layer and selecting Adam method as the optimizer algorithm. Finally, the traffic sign classification and recognition experiments are conducted based on the German Traffic Sign Recognition Benchmark. The favorable prediction and accurate recognition of traffic signs are achieved through the continuous training and testing of the network model. Experimental results show that the accurate recognition rate of traffic signs reaches 99.75%, and the average processing time per frame is 5.4 ms. Compared with other algorithms, the proposed algorithm has remarkable accuracy and real-time performance, strong generalization ability and high training efficiency. The accurate recognition rate and average processing time are markedly improved. This improvement is of considerable importance to reduce the accident rate and enhance the road traffic safety situation, providing a strong technical guarantee for the steady development of intelligent vehicle driving assistance.

Lane Detection Algorithm for Intelligent Vehicles in Complex Road Conditions and Dynamic Environments.

Lane detection is an important foundation in the development of intelligent vehicles. To address problems such as low detection accuracy of traditional methods and poor real-time performance of deep learning-based methodologies, a lane detection algorithm for intelligent vehicles in complex road conditions and dynamic environments was proposed. Firstly, converting the distorted image and using the superposition threshold algorithm for edge detection, an aerial view of the lane was obtained via region of interest extraction and inverse perspective transformation. Secondly, the random sample consensus algorithm was adopted to fit the curves of lane lines based on the third-order B-spline curve model, and fitting evaluation and curvature radius calculation were then carried out on the curve. Lastly, by using the road driving video under complex road conditions and the Tusimple dataset, simulation test experiments for lane detection algorithm were performed. The experimental results show that the average detection accuracy based on road driving video reached 98.49%, and the average processing time reached 21.5 ms. The average detection accuracy based on the Tusimple dataset reached 98.42%, and the average processing time reached 22.2 ms. Compared with traditional methods and deep learning-based methodologies, this lane detection algorithm had excellent accuracy and real-time performance, a high detection efficiency and a strong anti-interference ability. The accurate recognition rate and average processing time were significantly improved. The proposed algorithm is crucial in promoting the technological level of intelligent vehicle driving assistance and conducive to the further improvement of the driving safety of intelligent vehicles.

Role of Peroxiredoxin 2 in the Protection Against Ferrous Sulfate-Induced Oxidative and Inflammatory Injury in PC12 Cells.

Peroxiredoxin 2 (Prdx2) is a ubiquitous antioxidant enzyme in mammalian brain. Although a protective role of Prdx2 has been established in cerebral ischemia and several neurodegenerative diseases, its contribution against iron-induced neurocytotoxicity still remains to be determined. Accordingly, in this study, we aimed to investigate the effects of Prdx2 on iron-induced cytotoxicity using an in vitro model in which PC12 cells are exposed to ferrous sulfate (FS). The FS treatment increased Prdx2 expression, and promoted lactate dehydrogenase (LDH) release and cell apoptosis in PC12 cells, accompanied by the increase in the Bax/Bcl2 ratio, cytochrome c release, and caspase-3 cleavage. FS exposure also increased the malondialdehyde content (lipid peroxidation), 3'-nitrotyrosine expression (protein nitration), γ-H2A.X formation (DNA oxidation), and promoted nuclear factor kappa B nuclear translocation, cyclooxygenase-2 expression, and release of tumor necrosis factor-α and interleukin-1ß. Lentivirus-mediated Prdx2 knockdown intensified the FS-induced LDH release and cell apoptosis by aggravating the oxidative and inflammatory damage. In conclusion, our findings demonstrated that Prdx2 played a vital role in the protection against iron-induced cytotoxicity in PC12 cells.

Whole-Body Dynamics-Based Aerial Fall Trajectory Optimization and Landing Control for Humanoid Robot.

When humanoid robots work in human environments, falls are inevitable due to the complexity of such environments. Current research on humanoid robot falls has mainly focused on falls on the ground, with little research on humanoid robots falling from the air. In this paper, we employ an extended state variable formulation that directly maps from the high-level motion strategy space to the full-body joint space to optimize the falling trajectory in order to protect the robot when falling from the air. In order to mitigate the impact force generated by the robot's fall, during the aerial phase, we employ simple proportion differentiation (PD) control. In the landing phase, we optimize the optimal contact force at the contact point using the centroidal dynamics model. Based on the contact force, the changes to the end-effector positions are solved using a dual spring-damper model. In the simulation experiments, we conduct three comparative experiments, and the simulation results demonstrate that the robot can safely fall 1.5 m from the ground at a pitch angle of 45°. Finally, we experimentally validate the methods on an actual robot by performing a side-fall experiment. The experimental results show that the proposed trajectory optimization and motion control methods can provide excellent shock absorption for the impact generated when a robot falls.

Clinical validation of near-infrared imaging for early detection of proximal caries in primary molars.

OBJECTIVES: The aim of this study was to validate the near-infrared imaging (NIRI) in comparison with visual inspection (VI) for early detection of proximal caries in primary molars. METHODS: VI and intraoral scans were performed on 126 patients aged 3-12 years with at least one non-cavitied and non-restored proximal tooth surface, who were scheduled for bite wing radiography (BWR) as part of their standard care. Teeth with signs of proximal cavities, restorations or residual caries were excluded in this study. BWR, a gold standard to diagnose proximal caries in primary molars, was used to validate the findings of NIRI and VI. The accuracy, sensitivity, specificity and the area under the curve (AUC) of NIRI and VI were calculated. RESULTS: The accuracy, sensitivity and specificity of NIRI were 82.89%, 74.10% and 90.97%, while those of VI were 71.64%, 43.88% and 97.14%, respectively. NIRI showed higher accuracy and sensitivity, and lower specificity (P < 0.001). The AUC of NIRI was higher than that of VI (0.826 vs 0.706; P < 0.05). CONCLUSIONS: NIRI showed higher sensitivity and lower specificity compared with VI when detecting proximal caries in primary molars. Therefore, it is recommended to use NIRI in combination with BWR to improve the detection rate of proximal caries in primary molars. CLINICAL SIGNIFICANCE: In children, there is a high incidence of proximal caries in primary molars, which require high technical sensitivity for detection. NIRI shows high sensitivity in detecting proximal caries, which may improve their detection rate in primary molars. THE CLINICAL TRIAL REGISTRATION NUMBER: ChiCTR2300070916.

KDM1A-mediated upregulation of METTL3 ameliorates Alzheimer's disease via enhancing autophagic clearance of p-Tau through m6A-dependent regulation of STUB1.

BACKGROUND: Alzheimer's disease (AD) is a severe neurodegenerative disorder that progressively destroys cognitive skills. Exploring the mechanism underlying autophagic clearance of phosphorylated tau (p-Tau) contributes to developing novel therapeutic strategies for AD. METHODS: SH-SY5Y and HT22 cells were treated with Aß1-42 to establish an in vitro model of AD. Cell viability was examined using CCK-8. TUNEL staining was applied to evaluate cell apoptosis. LC3 puncta was examined by IF staining. m6A modification level was evaluated through MeRIP. RNA pull-down and RIP assays were used for analyzing the interaction between IGF2BP1 and STUB1 transcripts. The binding of KDM1A to the promoter of METTL3 was confirmed by ChIP assays. APP/PS1 transgenic mice were used as an in vivo model of AD. Cognitive skills of mice were evaluated with the Morris water maze. Hippocampal damage and Aß deposition were detected through H&E and IHC staining. RESULTS: Dysregulated levels of autophagy, p-Tau and m6A was observed in an in vitro model of AD. Overexpression of METTL3 or STUB1 enhanced autophagy but reduced p-Tau level in Aß1-42-treated cells. METTL3 stabilized STUB1 mRNA through the m6A-IGF2BP1-dependent mechanism and naturally promoted STUB1 expression, thereby enhancing autophagic p-Tau clearance in Aß1-42-treated cells. Overexpression of KDM1A enhanced autophagy, m6A modification and autophagic p-Tau clearance in Aß1-42-treated cells. KDM1A-mediated upregulation of METTL3 promoted autophagic p-Tau clearance and ameliorated Alzheimer's disease both in vitro and in vivo. CONCLUSION: KDM1A-mediated upregulation of METTL3 enhances autophagic clearance of p-Tau through m6A-dependent regulation of STUB1, thus ameliorating Alzheimer's disease. Our study provides novel mechanistic insights into AD pathogenesis and potential drug targets for AD.

Experimental and Computational Studies on Octyl Hydroxamic Acid as an Environmentally Friendly Inhibitor of Cobalt Chemical Mechanical Polishing.

Octyl hydroxamic acid (OHA) was investigated as an inhibitor in H2O2-based alkaline silica dispersions for the polishing of cobalt (Co) films for interconnect applications. A combination of experiments and density functional theory (DFT) was used to investigate the inhibition effect and the mechanism of OHA on the Co surface. On the basis of the experiments, it can be proven that OHA has an inhibition effect on Co, which came from the inhibition of the cathodic reaction. The X-ray photoelectron spectroscopy (XPS) experiments show that the adsorption of OHA weakened the oxidation of the Co surface and protected the Co surface from corrosion. On the basis of the calculations, it can be proven that the OHAketone (ion) is most likely to react with the Co surface, and it can adsorb on the Co surface by Co-O bonds. This study provides important microscopic insights for understanding the corrosion protection of Co interconnect metals and helps to explain the corrosion inhibition mechanism of the organic-metal interface during the CMP process.

lncRNA MIR600HG Knockdown Alleviates Cognitive Impairment in Alzheimer's Disease Through NEDD4L Mediated PINK1 Degradation.

BACKGROUND: Growing evidence has demonstrated that long non-coding RNAs (lncRNAs) play a critical role in Alzheimer's disease (AD), which is characterized by sustained mitochondrial dysfunction, inevitable memory loss, and cognitive decline. However, the potential function of lncRNAs MIR600 Host Gene (MIR600HG) in AD remains unanswered. OBJECTIVE: Our study aimed to investigate the role of MIR600HG and its related molecular mechanism in AD. METHODS: The expression of MIR600HG was examined by qRT-PCR. The MIR600HG interacting proteins were identified by RNA pull-down assay and mass spectrometry and verified by RNA immunoprecipitation. Immunofluorescence staining was applied to examine the colocalization of PINK1 and NEDD4L. The PINK1 level and the activation of autophagy were detected by immunoblotting. Morris water maze test was performed to evaluate cognitive decline in AD mice model. RESULTS: MIR600HG expression was elevated during aging in two different types of AD transgenic mouse models. Next, we found that increased MIR600HG directly interact with NEDD4L, which promoted PINK1 ubiquitination and degradation, and as well as autophagy activation. Additionally, MIR600HG promoted Aß production and suppressed Cytochrome C Oxidase activity. Administration of AAV-shMIR600HG restored the Cytochrome C Oxidase activity and inhibited Aß production. Furthermore, PINK1 overexpression or MIR600HG knockdown significantly ameliorated the cognitive impairment in APP/PS1 mice. PINK1 depletion recovered the spatial memory defect in the AAV-shMIR600HG injected APP/PS1 mice. CONCLUSION: MIR600HG was increased in AD and promoted AD pathogenesis. Targeting MIR600HG significantly improved cognitive function in AD mice, which could pave the way for exciting new avenues in AD therapeutic strategy research.

HIF­1α protects PC12 cells from OGD/R­induced cell injury by regulating autophagy flux through the miR­20a­5p/KIF5A axis.

Hypoxia inducible factor 1α (HIF­1α) has been reported to play a key role in protecting neurons from ischaemic injury. However, the exact molecular mechanisms remain largely unclear. PC12 cells were exposed to oxygen glucose deprivation/reoxygenation (OGD/R) conditions to mimic ischaemic injury in vitro. The expression of the HIF­1α mRNA, miR­20a­5p, and kinesin family member 5A (KIF5A) mRNA was tested using qRT-PCR. Levels of the HIF­1α, LC3I/II, P62, LAMP2, cathepsin B (CTSB) and KIF5A proteins were determined using western blotting. The CCK­8 assay was conducted to assess PC12 cell viability. DQ­Red­BSA and LysoSensor Green DND­189 dyes were employed to measure the proteolytic activity and pH of lysosomes, respectively. The interaction between miR­20a­5p and HIF­1α or KIF5A was verified by performing chromatin immunoprecipitation (ChIP) and/or dual­luciferase reporter assays. TUNEL staining was adopted to assess PC12 cell death. GFP­LC3 and RFP­GFP­LC3 probes were used to examine the autophagy status and autophagy flux of PC12 cells. A rat middle cerebral artery occlusion­reperfusion (MCAO/R) model was established to investigate the role of the HIF­1α/miR­20a­5p/KIF5A axis in ischaemic stroke in vivo. OGD/R exposure initiated PC12 cell autophagy and injury. HIF­1α expression was substantially increased in PC12 cells after OGD/R exposure. Overexpression of HIF­1α reversed the effects of OGD/R on reducing cell viability, blocking autophagy flux and inducing lysosome dysfunction. These rescue effects of HIF­1α depended on KIF5A. HIF­1α negatively regulated miR­20a­5p expression by targeting its promoter region, and miR­20a­5p directly targeted and negatively regulated the KIF5A mRNA. Overexpression of miR­20a­5p abolished the effects of HIF­1α on rescuing OGD/R­induced injury in PC12 cells. The effects of the HIF­1α/miR­20a­5p/KIF5A axis were verified in MCAO/R rats. HIF­1α protects PC12 cells from OGD/R­induced cell injury by regulating autophagy flux through the miR­20a­5p/KIF5A axis.