JIMR: Joint Semantic and Geometry Learning for Point Scene Instance Mesh Reconstruction.

Point scene instance mesh reconstruction is a challenging task since it requires both scene-level instance segmentation and instance-level mesh reconstruction from partial observations simultaneously. Previous works either adopt a detection backbone or a segmentation one, and then directly employ a mesh reconstruction network to produce complete meshes from incomplete instance point clouds. To further boost the mesh reconstruction quality with both local details and global smoothness, in this work, we propose JIMR, a joint framework with two cascaded stages for semantic and geometry understanding. In the first stage, we propose to perform both instance segmentation and object detection simultaneously. By making both tasks promote each other, this design facilitates subsequent mesh reconstruction by providing more precisely-segmented instance points and better alignment benefiting from predicted complete bounding boxes. In the second stage, we propose a complete-then-reconstruct procedure, where the completion module explicitly disentangles completion from reconstruction, and enables the usage of pre-trained weights of existing powerful completion and reconstruction networks. Moreover, we propose a comprehensive confidence score to filter proposals considering the quality of instance segmentation, bounding box detection, semantic classification, and mesh reconstruction at the same time. Experiments show that our proposed JIMR outperforms state-of-the-art methods regarding instance reconstruction qualitatively and quantitatively.

Enhanced Piezocatalytic Performance of Li-doped BaTiO3 Through a Facile Sonication-Assisted Precipitation Approach.

Piezocatalysis-induced dye degradation has garnered significant attention as an effective method for addressing wastewater treatment challenges. In our study, we employed a room-temperature sonochemical method to synthesize piezoelectric barium titanate nanoparticles (BaTiO3: BTO) with varying levels of Li doping. This approach not only streamlined the sample preparation process but also significantly reduced the overall time required for synthesis, making it a highly efficient and practical method. One of the key findings was the exceptional performance of the Li-doped BTO nanoparticles. With 20 mg of Li additive, we achieved 90% removal of Rhodamine B (RhB) dye within a relatively short timeframe of 150 minutes, all while subjecting the sample to ultrasonic vibration. This rapid and efficient dye degradation was further evidenced by the calculated kinetic rate constant, which indicated seven times faster degradation rate compared to pure BTO. The enhanced piezoelectric performance observed in the Li-doped BTO nanoparticles can be attributed to the strategic substitution of Li atoms, which facilitated a more efficient transfer of charge charges at the interface. Overall, our study underscores the potential of piezocatalysis coupled with advanced materials like Li-doped BTO nanoparticles as a viable and promising solution for wastewater treatment, offering both efficiency and environmental sustainability.

Multi-interface Engineering of MXenes for Self-Powered Wearable Devices.

Self-powered wearable devices with integrated energy supply module and sensitive sensors have significantly blossomed for continuous monitoring of human activity and the surrounding environment in healthcare sectors. The emerging of MXene-based materials has brought research upsurge in the fields of energy and electronics, owing to their excellent electrochemical performance, large surface area, superior mechanical performance, and tuneable interfacial properties, where their performance can be further boosted via multi-interface engineering. Herein, a comprehensive review of recent progress in MXenes for self-powered wearable devices is discussed from the aspects of multi-interface engineering. The fundamental properties of MXenes including electronic, mechanical, optical, and thermal characteristics are discussed in detail. Different from previous review works on MXenes, multi-interface engineering of MXenes from termination regulation to surface modification and their impact on the performance of materials and energy storage/conversion devices are summarized. Based on the interfacial manipulation strategies, potential applications of MXene-based self-powered wearable devices are outlined. Finally, proposals and perspectives are provided on the current challenges and future directions in MXene-based self-powered wearable devices. This article is protected by copyright. All rights reserved.

Progress of Polymer Electrolytes Worked in Solid-State Lithium Batteries for Wide-Temperature Application.

Solid-state Li-ion batteries have emerged as the most promising next-generation energy storage systems, offering theoretical advantages such as superior safety and higher energy density. However, polymer-based solid-state Li-ion batteries face challenges across wide temperature ranges. The primary issue lies in the fact that most polymer electrolytes exhibit relatively low ionic conductivity at or below room temperature. This sensitivity to temperature variations poses challenges in operating solid-state lithium batteries at sub-zero temperatures. Moreover, elevated working temperatures lead to polymer shrinkage and deformation, ultimately resulting in battery failure. To address this challenge of polymer-based solid-state batteries, this review presents an overview of various promising polymer electrolyte systems. The review provides insights into the temperature-dependent physical and electrochemical properties of polymers, aiming to expand the temperature range of operation. The review also further summarizes modification strategies for polymer electrolytes suited to diverse temperatures. The final section summarizes the performance of various polymer-based solid-state batteries at different temperatures. Valuable insights and potential future research directions for designing wide-temperature polymer electrolytes are presented based on the differences in battery performance. This information is intended to inspire practical applications of wide-temperature polymer-based solid-state batteries.

Potential therapeutic role of spermine via Rac1 in osteoporosis: Insights from zebrafish and mice.

Osteoporosis is a prevalent metabolic bone disease. While drug therapy is essential to prevent bone loss in osteoporotic patients, current treatments are limited by side effects and high costs, necessitating the development of more effective and safer targeted therapies. Utilizing a zebrafish ( Danio rerio) larval model of osteoporosis, we explored the influence of the metabolite spermine on bone homeostasis. Results showed that spermine exhibited dual activity in osteoporotic zebrafish larvae by increasing bone formation and decreasing bone resorption. Spermine not only demonstrated excellent biosafety but also mitigated prednisolone-induced embryonic neurotoxicity and cardiotoxicity. Notably, spermine showcased protective attributes in the nervous systems of both zebrafish embryos and larvae. At the molecular level, Rac1 was identified as playing a pivotal role in mediating the anti-osteoporotic effects of spermine, with P53 potentially acting downstream of Rac1. These findings were confirmed using mouse ( Mus musculus) models, in which spermine not only ameliorated osteoporosis but also promoted bone formation and mineralization under healthy conditions, suggesting strong potential as a bone-strengthening agent. This study underscores the beneficial role of spermine in osteoporotic bone homeostasis and skeletal system development, highlighting pivotal molecular mediators. Given their efficacy and safety, human endogenous metabolites like spermine are promising candidates for new anti-osteoporotic drug development and daily bone-fortifying agents.

Ynamide Coupling Reagents: Origin and Advances.

ConspectusSince the pioneering work of Curtius and Fischer, chemical peptide synthesis has witnessed a century's development and evolved into a routine technology. However, it is far from perfect. In particular, it is challenged by sustainable development because the state-of-the-art of peptide synthesis heavily relies on legacy reagents and technologies developed before the establishment of green chemistry. Over the past three decades, a broad range of efforts have been made for greening peptide synthesis, among which peptide synthesis using unprotected amino acid represents an ideal and promising strategy because it does not require protection and deprotection steps. Unfortunately, C → N peptide synthesis employing unprotected amino acids has been plagued by undesired polymerization, while N → C inverse peptide synthesis with unprotected amino acids is retarded by severe racemization/epimerization owing to the iterative activation and aminolysis of high racemization/epimerization susceptible peptidyl acids. Consequently, there is an urgent need to develop innovative coupling reagents and strategies with novel mechanisms that can address the long-standing notorious racemization/epimerization issue of peptide synthesis.This Account will describe our efforts in discovery of ynamide coupling reagents and their application in greening peptide synthesis. Over an eight-year journey, ynamide coupling reagents have evolved into a class of general coupling reagents for both amide and ester bond formation. In particular, the superiority of ynamide coupling reagents in suppressing racemization/epimerization enabled them to be effective for peptide fragment condensation, and head-to-tail cyclization, as well as precise incorporation of thioamide substitutions into peptide backbones. The first practical inverse peptide synthesis using unprotected amino acids was successfully accomplished by harnessing such features and taking advantage of a transient protection strategy. Ynamide coupling reagent-mediated ester bond formation enabled efficient intermolecular esterification and macrolactonization with preservation of α-chirality and the configuration of the conjugated α,ß-C-C double bond. To make ynamide coupling reagents readily available with reasonable cost and convenience, we have developed a scalable one-step synthetic method from cheap starting materials. Furthermore, a water-removable ynamide coupling reagent was developed, offering a column-free purification of the target coupling product. In addition, the recycle of ynamide coupling reagent was accomplished, thereby paving the way for their sustainable industrial application.As such, this Account presents the whole story of the origin, mechanistic insights, preparation, synthetic applications, and recycle of ynamide coupling reagents with a perspective that highlights their future impact on peptide synthesis.

Carbon emissions of power transmission and transformation projects in the whole life cycle for smart sustainable energy systems.

The study investigates the optimization of life cycle carbon emissions in smart sustainable energy systems through power transformation and transmission project power load predictions. Firstly, a multi-task learning-based short-term user load forecasting technique is developed, where the power load curves of multiple residential customers are grouped and classified using the K-means clustering method. Additionally, the Bidirectional Long Short-Term Memory (BiLSTM) technique is introduced to anticipate the power load intelligently. Secondly, a life cycle carbon emission assessment model for the power transmission and transformation project (PTTP) is constructed based on the life cycle assessment (LCA) method, which divides the project's life cycle into four stages: production, installation and construction, operation and maintenance, and demolition. Finally, an experimental evaluation of this model is conducted. The results demonstrate that compared with the baseline model Long Short-Term Memory (LSTM), this model achieves a significantly lower average Mean Absolute Error (MAE) at 3.62% while achieving significantly higher accuracy in power load forecasting at 94.34%. A comprehensive examination of carbon emissions across all four phases reveals that overall carbon emissions are highest during the operation and maintenance stage followed by the equipment production stage and installation/construction stage, with the lowest overall carbon emissions observed. Hence, this study endeavors to forecast power load demand with precision and identify the principal determinants of carbon emissions in power engineering. By discerning and managing these key factors, an optimal, energy-efficient intelligent power load scheme can be derived.

Inverse Peptide Synthesis Using Transient Protected Amino Acids.

Peptide therapeutics have experienced a rapid resurgence over the past three decades. While a few peptide drugs are biologically produced, most are manufactured via chemical synthesis. The cycle of prior protection of the amino group of an α-amino acid, activation of its carboxyl group, aminolysis with the free amino group of a growing peptide chain, and deprotection of the N-terminus constitutes the principle of conventional C → N peptide chemical synthesis. The mandatory use of the Nα-protecting group invokes two additional operations for incorporating each amino acid, resulting in poor step- and atom-economy. The burgeoning demand in the peptide therapeutic market necessitates cost-effective and environmentally friendly peptide manufacturing strategies. Inverse peptide chemical synthesis using unprotected amino acids has been proposed as an ideal and appealing strategy. However, it has remained unsuccessful for over 60 years due to severe racemization/epimerization during N → C peptide chain elongation. Herein, this challenge has been successfully addressed by ynamide coupling reagent employing a transient protection strategy. The activation, transient protection, aminolysis, and in situ deprotection were performed in one pot, thus offering a practical peptide chemical synthesis strategy formally using unprotected amino acids as the starting material. Its robustness was exemplified by syntheses of peptide active pharmaceutical ingredients. It is also amenable to fragment condensation and inverse solid-phase peptide synthesis. The compatibility to green solvents further enhances its application potential in large-scale peptide production. This study offered a cost-effective, operational convenient, and environmentally benign approach to peptides.

Nosocomial surveillance of multidrug-resistant Acinetobacter baumannii: a genomic epidemiological study.

Acinetobacter baumannii is a major opportunistic pathogen causing hospital-acquired infections, and it is imperative to comprehend its evolutionary and epidemiological dynamics in hospitals to prevent and control nosocomial transmission. Here, we present a comprehensive genomic epidemiological study involving the genomic sequencing and antibiotic resistance profiling of 634 A. baumannii strains isolated from seven intensive care units (ICUs) of a Chinese general hospital over 2 consecutive years. Our study reveals that ST2 is highly dominant (90.54%) in the ICUs, with 98.90% of the ST2 exhibiting multidrug resistant or extensively drug resistant. Phylogenetic analyses of newly sequenced genomes and public data suggest that nosocomial isolates originated outside the hospital but evolved inside. The major lineages appear to be stable, with 9 of the 28 identified nosocomial epidemic clones infecting over 60% of the affected patients. However, outbreaks of two highly evolved clones have been observed in different hospitals, suggesting significant inter-hospital transmission chains. By coupling patient medical records and genomic divergence of the ST2, we found that cross-ward patient transfer played a crucial role in pathogen's nosocomial transmission. Additionally, we identified 831 potential adaptive evolutionary loci and 44 associated genes by grouping and comparing the genomes of clones with different prevalence. Overall, our study provides a comprehensive and contemporary survey on the epidemiology and genomic evolution of A. baumannii in a large Chinese general hospital. These findings shed light on the nosocomial evolution and transmission of A. baumannii and offers valuable information for transmission prevention and antibiotic therapy.IMPORTANCEThis study delved into the genomic evolution and transmission of nosocomial Acinetobacter baumannii on a large scale, spanning both an extended time period and the largest sample size to date. Through molecular epidemiological investigations based on genomics, we can directly trace the origin of the pathogen, detecting and monitoring outbreaks of infectious diseases in a timely manner, and ensuring public health safety. In addition, this study also collects a large amount of genomic and antibiotic resistance detection data, which is helpful for phenotype prediction based on genomic sequencing. It enables patients to receive personalized antibiotic treatment quickly, helps doctors select antibiotics more accurately, and contributes to reducing the use of antibiotics and lowering the risk of antibiotic resistance development.

ZmWAK02 encoding an RD-WAK protein confers maize resistance against gray leaf spot.

Gray leaf spot (GLS) caused by Cercospora zeina or C. zeae-maydis is a major maize disease throughout the world. Although more than 100 QTLs resistant against GLS have been identified, very few of them have been cloned. Here, we identified a major resistance QTL against GLS, qRglsSB, explaining 58.42% phenotypic variation in SB12×SA101 BC1 F1 population. By fine-mapping, it was narrowed down into a 928 kb region. By using transgenic lines, mutants and complementation lines, it was confirmed that the ZmWAK02 gene, encoding an RD wall-associated kinase, is the responsible gene in qRglsSB resistant against GLS. The introgression of the ZmWAK02 gene into hybrid lines significantly improves their grain yield in the presence of GLS pressure and does not reduce their grain yield in the absence of GLS. In summary, we cloned a gene, ZmWAK02, conferring large effect of GLS resistance and confirmed its great value in maize breeding.

High-Performance Optoelectronic Gas Sensing Based on All-Inorganic Mixed-Halide Perovskite Nanocrystals with Halide Engineering.

Gas sensors are of great interest to portable and miniaturized sensing technologies with applications ranging from air quality monitoring to explosive detection and medical diagnostics, but the existing chemiresistive NO2 sensors still suffer from issues such as poor sensitivity, high operating temperature, and slow recovery. Herein, a high-performance NO2 sensors based on all-inorganic perovskite nanocrystals (PNCs) is reported, achieving room temperature operation with ultra-fast response and recovery time. After tailoring the halide composition, superior sensitivity of ≈67 at 8 ppm NO2 is obtained in CsPbI2 Br PNC sensors with a detection level down to 2 ppb, which outperforms other nanomaterial-based NO2 sensors. Furthermore, the remarkable optoelectronic properties of such PNCs enable dual-mode operation, i.e., chemiresistive and chemioptical sensing, presenting a new and versatile platform for advancing high-performance, point-of-care NO2 detection technologies.

Efficient Crowd Counting via Dual Knowledge Distillation.

Most researchers focus on designing accurate crowd counting models with heavy parameters and computations but ignore the resource burden during the model deployment. A real-world scenario demands an efficient counting model with low-latency and high-performance. Knowledge distillation provides an elegant way to transfer knowledge from a complicated teacher model to a compact student model while maintaining accuracy. However, the student model receives the wrong guidance with the supervision of the teacher model due to the inaccurate information understood by the teacher in some cases. In this paper, we propose a dual-knowledge distillation (DKD) framework, which aims to reduce the side effects of the teacher model and transfer hierarchical knowledge to obtain a more efficient counting model. First, the student model is initialized with global information transferred by the teacher model via adaptive perspectives. Then, the self-knowledge distillation forces the student model to learn the knowledge by itself, based on intermediate feature maps and target map. Specifically, the optimal transport distance is utilized to measure the difference of feature maps between the teacher and the student to perform the distribution alignment of the counting area. Extensive experiments are conducted on four challenging datasets, demonstrating the superiority of DKD. When there are only approximately 6% of the parameters and computations from the original models, the student model achieves a faster and more accurate counting performance as the teacher model even surpasses it.

MiR-20b-5p involves in vascular aging induced by hyperhomocysteinemia.

Hyperhomocysteinemia (HHcy) is an independent risk factor of atherosclerosis (AS). Some reports have shown that homocysteine (Hcy) could accelerate the development of AS by promoting endothelial cell senescence. miRNAs were widely involved in the pathophysiology of HHcy. However, few studies have focused on the changes of miRNA-mRNA networks in the artery of HHcy patients. For this reason, RNA-sequencing was adopted to investigate the expression of miRNA and mRNA in HHcy model mouse arteries. We found that the expression of 216 mRNAs and 48 miRNAs were significantly changed. Using TargetScan and miRDB web tools, 29 miRNA-mRNA pairs were predicted. Notably, miR-20b-5p and FJX1 shared the highest predicted score in TargetScan, and further study indicated that the miR-20b-5p inhibitor significantly upregulated the FJX1 expression in HHcy human umbilical vein endothelial cells (HUVECs) model. PPI analysis revealed an important sub-network which was centered on CDK1. Gene ontology (GO) enrichment analysis showed that HHcy had a significant effect on cell cycle. Further experiments found that Hcy management increased reactive oxygen species (ROS) generation, the activity of senescence associated ß-galactosidase (SA-ß-gal) and the protein expression of p16 and p21 in HUVECs, which were rescued by miR-20b-5p inhibitor. In general, our research indicated the important role of miR-20b-5p in HHcy-related endothelial cell senescence.

Highly Selective Ionic Gel-Based Gas Sensor for Halogenated Volatile Organic Compound Detection: Effect of Dipole-Dipole Interaction.

Halogenated volatile organic compounds (abbreviated as X-VOCs) are a class of hazardous gas pollutants that are difficult to detect due to their thermal stability, chemical inertness, and poisoning effect on gas sensors at high temperatures. In this work, room-temperature detection of X-VOCs is achieved using a surface acoustic wave (SAW) gas sensor coated with a 1-ethyl-3-methylimidazolium bis(trifluoromethylsufonyl)imide (EMIM-TFSI)-based ionic gel film. We experimentally verify that the high selectivity of the ionic gel-based SAW gas sensor for X-VOCs is due to the presence of halogen atoms in these gas molecules. Meanwhile, the sensor has very little response to common organic gases such as ethanol, isopropanol, and acetone, reflecting a low cross-sensitivity to nonhalogenated VOCs. This unique advantage shows potential applications in selective detection of X-VOCs and is validated by comparison with a commercial metal oxide semiconductor (MOS) sensor. Furthermore, the internal sensing mechanism is explored by the density functional theory (DFT) method. The simulation results demonstrate that the X-VOC molecules are highly polarized by the inductive effect of halogen atom substitution, which is beneficial for being adsorbed by the EMIM-TFSI ionic liquid via dipole-dipole interaction.

Identification of apoptosis-related key genes and the associated regulation mechanism in thoracic aortic aneurysm.

BACKGROUND: This study investigated the role of apoptosis-related genes in thoracic aortic aneurysms (TAA) and provided more insights into TAA's pathogenesis and molecular mechanisms. MATERIAL/METHODS: Two gene expression datasets (GSE9106 and GSE26155) were retrieved from the Gene Expression Omnibus (GEO) database. Apoptosis-related genes were obtained from the KEGG apoptosis pathway (hsa04210). Differentially expressed apoptosis-related genes were identified by performing differential expression analysis using limma for TAA blood and tissue samples. GO and KEGG enrichment analysis of the differentially expressed apoptosis genes was performed using the Metascape web tool. The miRNA-mRNA regulatory network was reconstructed using the ENCORI and miRDB databases, and functional enrichment analysis was performed on the related miRNAs using the miEAA tool. The correlation between the expression levels of differentially expressed apoptosis-related genes and genes involved in immune infiltration in TAA was calculated using the CIBERSORT algorithm. The apoptosis modification patterns mediated by differentially expressed apoptosis-related genes were systematically assessed in TAA samples. RESULTS: A total of 9 differentially-expressed apoptosis-related genes were identified in TAA samples compared with normal samples. 150 miRNAs and 6 mRNAs regulatory networks were reconstructed using the ENCORI and miRDB databases. Immune infiltration analysis revealed that the GZMB had the strongest positive correlation with activated NK cells and the DFFA presented the strongest positive correlation with T cells follicular helper. 3 distinct apoptosis modification patterns mediated by 9 differentially-expressed apoptosis-related genes were identified. They differ in immune characteristics and drug sensitivity, and their biological functions in these subtypes were further studied. CONCLUSIONS: This study identified key apoptosis-related genes related to TAA and evaluated the modification patterns of key apoptosis genes in TAA, providing insights into potential targets and mechanisms of TAA pathogenesis and progression.

Layered Polymer Stacking for Stable Interfaces and Dendrite Growth Inhibition in All-Solid-State Lithium Batteries.

To improve the ionic conductivity and cycling stability of solid-state lithium batteries based on poly(ethylene oxide) (PEO) electrolytes, we developed a sandwich-structured composite polymer electrolyte (sandwich-CPE) PEO-TiN/PEO-LiYF4/PEO-TiN. The sandwich-CPE delivers a high ionic conductivity of 1.7 × 10-4 S cm-1 at 30 °C and a wide potential window of 0 to 5.0 V (vs Li/Li+). Adding PEO-TiN leads to the formation of Li3N between Li and sandwich-CPE during cycling, which effectively reduces the level of Li dendrite formation. Additionally, PEO-TiN acts as a sacrificial layer to stop the entry of Li dendrites into the interlayer PEO-LiYF4. Using the sandwich-CPE, LiFePO4 retains a reversible capacity of 113.8 mA h g-1 at 30 °C after 300 cycles under 0.5 C. For high-voltage cells, LiNi0.5Co0.2Mn0.3O2 retains a capacity retention of 71.4% at 45 °C after 300 cycles under 0.2 C among 3.0-4.3 V, while Li3V2(PO4)3 delivers an initial discharge capacity of 108.1 mA h g-1 at 60 °C and retains 81.6% after 500 cycles under 1 C among 2.8-4.4 V. These results demonstrate the strong electrochemical compatibility of the sandwich-CPE, enabling high reversible capacity and good cycling stability for solid-state Li batteries with different cathodes at different temperatures and current rates.

The interaction between hyperuricemia and low-density lipoprotein cholesterol increases the risk of 1-year post-discharge all-cause mortality in ST-segment elevation myocardial infarction patients.

BACKGROUND AND AIMS: Hyperuricemia is a known risk factor for cardiovascular diseases, but little is known on whether the association between hyperuricemia and poor outcomes in ST-segment elevation myocardial infarction (STEMI) is modified by low-density lipoprotein cholesterol (LDL-c). This study aimed to investigate the effect of the interaction between hyperuricemia and LDL-c on the risk of 1-year post-discharge all-cause mortality in STEMI patients. METHODS AND RESULTS: A total of 1396 STEMI patients were included. Cox proportional hazards models were used to determine the association between hyperuricemia and 1-year all-cause mortality in the overall population and subgroups stratified based on LDL-c levels (<3.0 mmol/L or ≥3.0 mmol/L). Multivariate analysis indicated that hyperuricemia was associated with 1-year mortality (HR: 2.66; 95% CI: 1.30-5.47; p = 0.008). However, the prognostic effect of hyperuricemia was only observed in patients with LDL-c level ≥3.0 mmol/L (HR: 12.90; 95% CI: 2.98-55.77; p < 0.001), but not in those with LDL-c level <3.0 mmol/L (HR: 0.91, 95% CI: 0.30-2.79, p = 0.875). The interaction between hyperuricemia and LDL-c levels had a significant effect on 1-year mortality. CONCLUSION: Hyperuricemia was associated with increased 1-year post-discharge mortality in patients with LDL-c level≥ 3.0 mmol/L, but not in those with LDL-c level< 3.0 mmol/L.

High-efficiency electrocatalytic nitrite reduction toward ammonia synthesis on CoP@TiO2 nanoribbon array.

Electrochemical reduction of nitrite (NO2-) can satisfy the necessity for NO2- contaminant removal and deliver a sustainable pathway for ammonia (NH3) generation. Its practical application yet requires highly efficient electrocatalysts to boost NH3 yield and Faradaic efficiency (FE). In this study, CoP nanoparticle-decorated TiO2 nanoribbon array on Ti plate (CoP@TiO2/TP) is verified as a high-efficiency electrocatalyst for the selective reduction of NO2- to NH3. When measured in 0.1 M NaOH with NO2-, the freestanding CoP@TiO2/TP electrode delivers a large NH3 yield of 849.57 µmol h-1 cm-2 and a high FE of 97.01% with good stability. Remarkably, the subsequently fabricated Zn-NO2- battery achieves a high power density of 1.24 mW cm-2 while delivering a NH3 yield of 714.40 µg h-1 cm-2.

Upregulation of circ_0080968 in diabetic foot ulcer inhibits wound healing via repressing the migration and promoting proliferation of keratinocytes.

BACKGROUND: Diabetic foot ulcer (DFU) is a serious chronic complication of diabetes mellitus whose pathogenesis remains unclear. Circular RNA (circRNA) refers to a group of covalently closed non-coding RNAs that are reported to be dysregulated in patients with DFU. However, the mechanism whereby dysregulation in circRNAs contributes to DFU remains unclear. In this study, we investigated the role of dysregulated circRNAs in DFU. MATERIALS AND METHODS: A gene expression dataset was downloaded from the Gene Expression Omnibus portal and analyzed by the limma package of R. The levels of 24 upregulated circRNAs were detected in two independent cohorts by RT-qPCR. Interactions between miRNAs and circRNAs were predicted through bioinformatics and confirmed using a dual luciferase assay. The circularity and subcellular localization of circRNA-080968 was examined by northern blotting after digestion with RNase-R and in situ hybridization. Cell migration and proliferation were examined using Transwell and MTT assays. The apoptotic cells were detected by flow cytometry. RESULTS: The level of circRNA-080968 was upregulated in DFU tissues compared to that of non-DFU samples and normal human wounds. CircRNA-080968 was mainly localized in the cytoplasm and its overexpression inhibited the migration and promoted the proliferation of keratinocytes. MiR-326 and miR-766-3p were identified to interact with and be negatively correlated with circRNA-080968 levels. Increased glucose upregulated circRNA-080968, and its overexpression accelerated the degradation of both miR-326 and miR-766-3p. Reduced levels of miR-326 and miR-766-3p upregulated the expression of several genes controlling cell adhesion and proliferation which are related to the pathogenesis of DFU. CONCLUSIONS: The upregulation of circRNA-080968 in DFU induced the degradation of miR-326 and miR-766-3p, which further repressed the migration and increased the proliferation of keratinocytes.