Multimodal ECG heartbeat classification method based on a convolutional neural network embedded with FCA

Arrhythmias are irregular heartbeat rhythms caused by various conditions. Automated ECG signal classification aids in diagnosing and predicting arrhythmias. Current studies mostly focus on 1D ECG signals, overlooking the fusion of multiple ECG modalities for enhanced analysis. We converted ECG signals into modal images using RP, GAF, and MTF, inputting them into our classification model. To optimize detail retention, we introduced a CNN-based model with FCA for multimodal ECG tasks. Achieving 99.6% accuracy on the MIT-BIH arrhythmia database for five arrhythmias, our method outperforms prior models. Experimental results confirm its reliability for ECG classification tasks.

Three-Phase-Heterojunction Cu/Cu2O-Sb2O3 Catalyst Enables Efficient CO2 Electroreduction to CO and High-Performance Aqueous Zn-CO2 Battery

Zn-CO2 batteries are excellent candidates for both electrical energy output and CO2 utilization, whereas the main challenge is to design electrocatalysts for electrocatalytic CO2 reduction reactions with high selectivity and low cost. Herein, the three-phase heterojunction Cu-based electrocatalyst (Cu/Cu2O-Sb2O3-15) is synthesized and evaluated for highly selective CO2 reduction to CO, which shows the highest faradaic efficiency of 96.3% at -1.3 V versus reversible hydrogen electrode, exceeding the previously reported best values for Cu-based materials. In situ spectroscopy and theoretical analysis indicate that the Sb incorporation into the three-phase heterojunction Cu/Cu2O-Sb2O3-15 nanomaterial promotes the formation of key *COOH intermediates compared with the normal Cu/Cu2O composites. Furthermore, the rechargeable aqueous Zn-CO2 battery assembled with Cu/Cu2O-Sb2O3-15 as the cathode harvests a peak power density of 3.01 mW cm-2 as well as outstanding cycling stability of 417 cycles. This research provides fresh perspectives for designing advanced cathodic electrocatalysts for rechargeable Zn-CO2 batteries with high-efficient electricity output together with CO2 utilization.

Cichoric acid targets RANKL to inhibit osteoclastogenesis and prevent ovariectomy-induced bone loss

BACKGROUND AND AIM

Osteoporosis, a systemic metabolic bone disease, is characterized by the decline of bone mass and quality due to excessive osteoclast activity. Currently, drug-targeting osteoclasts show promising therapy for osteoporosis. In this study, we investigated the effect of cichoric acid (CA) on receptor activator of nuclear kappa-B ligand (RANKL)-induced osteoclastogenesis and the bone loss induced by ovariectomy in mice.

EXPERIMENTAL PROCEDURE

Molecular docking technologies were employed to examine the interaction between CA and RANKL. CCK8 assay was used to evaluate the cell viability under CA treatment. TRAcP staining, podosome belt staining, and bone resorption assays were used to test the effect of CA on osteoclastogenesis and osteoclast function. Further, an OVX-induced osteoporosis mice model was employed to identify the effect of CA on bone loss using micro-CT scanning and histological examination. To investigate underlying mechanisms, network pharmacology was applied to predict the downstream signaling pathways, which were verified by Western blot and immunofluorescence staining.

KEY RESULTS

The molecular docking analysis revealed that CA exhibited a specific binding affinity to RANKL, engaging multiple binding sites. CA inhibited RANKL-induced osteoclastogenesis and bone resorption without cytotoxic effects. Mechanistically, CA suppressed RANKL-induced intracellular reactive oxygen species, nuclear factor-kappa B, and mitogen-activated protein kinase pathways, followed by abrogated nuclear factor activated T-cells 1 activity. Consistent with this finding, CA attenuated post-ovariectomy-induced osteoporosis by ameliorating osteoclastogenesis.

CONCLUSIONS AND IMPLICATIONS

CA inhibited osteoclast activity and bone loss by targeting RANKL. CA might represent a promising candidate for treating osteoclast-related diseases, such as osteoporosis.

Covalent organic framework/layered double hydroxide composite-coated poly(ether ether ketone) jacket for stir bar sorptive extraction of Sudan dyes

A novel coating for stir bar sorptive extraction was developed by growing a covalent organic framework, TpPa-1 (derived from phenylenediamine and 1,3,5-trimethylphloroglucinol), onto the surface of Ni-Al layered double hydroxide. Using a poly(ether ether ketone) tube as the supporting substrate, a TpPa-1/layered double hydroxide-coated stir bar was fabricated and demonstrated excellent extraction performance for Sudan dyes. Notably, its extraction efficiency significantly exceeded that of stir bars modified with only TpPa-1 or Ni-Al layered double hydroxide. Based on this innovative coating, a stir bar sorptive extraction-high performance liquid chromatography method was established. This method exhibited low limits of detection (0.04-0.08 ng/mL) for the analysis of Sudan dyes. It also featured a wide linear range (0.25-100 or 200 ng/mL) and demonstrated good repeatability with relative standard deviations ≤6.22%. The recoveries obtained for spiked lake water and chili powder samples were 93.5%-105.2% and 87.8%-100.6%, respectively, demonstrating the practical potential of the developed method for detecting trace Sudan dyes in real samples.

Identification of gene biomarkers for brain diseases via multi-network topological semantics extraction and graph convolutional network

BACKGROUND

Brain diseases pose a significant threat to human health, and various network-based methods have been proposed for identifying gene biomarkers associated with these diseases. However, the brain is a complex system, and extracting topological semantics from different brain networks is necessary yet challenging to identify pathogenic genes for brain diseases.

RESULTS

In this study, we present a multi-network representation learning framework called M-GBBD for the identification of gene biomarker in brain diseases. Specifically, we collected multi-omics data to construct eleven networks from different perspectives. M-GBBD extracts the spatial distributions of features from these networks and iteratively optimizes them using Kullback-Leibler divergence to fuse the networks into a common semantic space that represents the gene network for the brain. Subsequently, a graph consisting of both gene and large-scale disease proximity networks learns representations through graph convolution techniques and predicts whether a gene is associated which brain diseases while providing associated scores. Experimental results demonstrate that M-GBBD outperforms several baseline methods. Furthermore, our analysis supported by bioinformatics revealed CAMP as a significantly associated gene with Alzheimer's disease identified by M-GBBD.

CONCLUSION

Collectively, M-GBBD provides valuable insights into identifying gene biomarkers for brain diseases and serves as a promising framework for brain networks representation learning.

Unveiling the super tolerance of Candida nivariensis to oxidative stress: insights into the involvement of a catalase

Yeast cells involved in fermentation processes face various stressors that disrupt redox homeostasis and cause cellular damage, making the study of oxidative stress mechanisms crucial. In this investigation, we isolated a resilient yeast strain, Candida nivariensis GXAS-CN, capable of thriving in the presence of high concentrations of H2O2. Transcriptomic analysis revealed the up-regulation of multiple antioxidant genes in response to oxidative stress. Deletion of the catalase gene Cncat significantly impacted H2O2-induced oxidative stress. Enzymatic analysis of recombinant CnCat highlighted its highly efficient catalase activity and its essential role in mitigating H2O2. Furthermore, over-expression of CnCat in Saccharomyces cerevisiae improved oxidative resistance by reducing intracellular ROS accumulation. The presence of multiple stress-responsive transcription factor binding sites at the promoters of antioxidative genes indicates their regulation by different transcription factors. These findings demonstrate the potential of utilizing the remarkably tolerant C. nivariensis GXAS-CN or enhancing the resistance of S. cerevisiae to improve the efficiency and cost-effectiveness of industrial fermentation processes.IMPORTANCEEnduring oxidative stress is a crucial trait for fermentation strains. The importance of this research is its capacity to advance industrial fermentation processes. Through an in-depth examination of the mechanisms behind the remarkable H2O2 resistance in Candida nivariensis GXAS-CN and the successful genetic manipulation of this strain, we open the door to harnessing the potential of the catalase CnCat for enhancing the oxidative stress resistance and performance of yeast strains. This pioneering achievement creates avenues for fine-tuning yeast strains for precise industrial applications, ultimately leading to more efficient and cost-effective biotechnological processes.

Bidirectional causal relationship between psychiatric disorders and osteoarthritis: A univariate and multivariate Mendelian randomization study

BACKGROUND

Observational studies have shown associations between psychiatric disorders and osteoarthritis (OA). However, the causal impact of different psychiatric disorder types on specific sites of osteoarthritis remains unclear. This study aimed to comprehensively understand the potential causal associations between psychiatric disorders and osteoarthritis using Mendelian randomization (MR) analysis.

METHODS

We collected data from genome-wide association studies of knee osteoarthritis (KOA) (n = 403,124), hip osteoarthritis (HOA) (n = 393,873), osteoarthritis of the knee or hip (KHOA) (n = 417,596), as well as three psychiatric disorders: bipolar disorder (n = 41,917), major depressive disorder (n = 170,756), and schizophrenia (n = 76,755) among European populations. We applied bidirectional univariate and multivariate MR analyses, including inverse variance weighted, Mendelian randomization-Egger, weighted median, simple mode, and weighted mode. We considered p < .05 as a criterion for identifying potential evidence of association. Bonferroni correction was used for multiple tests.

RESULTS

Our univariate MR analysis results demonstrated that bipolar disorder is a protective factor for KOA (OR = 0.90, 95% CI = 0.83 to 0.97, p = 0.0048) and may also be protective for KHOA (p = 0.02). Conversely, major depression has a positive causal effect on both KOA (OR = 1.27; 95% CI = 1.08 to 1.49; p = 0.0036) and KHOA (OR = 1.24; 95% CI = 1.12 to 1.37; p = 3.62×10-05 ). Furthermore, our analysis suggested that KHOA may be a risk factor for major depression (OR = 1.06; 95% CI = 1.00 to 1.12; p = 0.0469) in reverse MR. After adjusting smoking (OR = 1.46; 95% CI = 1.19 to 1.65; p = 0.0032) and body mass index (OR = 1.44; 95% CI = 1.09 to 1.81; p = 8.56×10-04 ), the casual association between major depression and KHOA remained.

CONCLUSION

Our study indicates that major depression is a great risk factor for KHOA, increasing the likelihood of their occurrence. However, further in-depth studies will be required to validate these results and elucidate the underlying molecular mechanisms.

Transcriptional expression of PHR2 is positively controlled by the calcium signaling transcription factor Crz1 through its binding motif in the promoter

IMPORTANCE

The fungal cell wall consists of glucans, mannoproteins, and chitin and is essential for cell viability, morphogenesis, and pathogenesis. The enzymes of the GH72 family are responsible for ß-(1,3)-glucan elongation and branching, which is crucial for the formation of the glucan-chitin polymer at the bud neck of yeast cells. In the human fungal pathogen Candida albicans, there are five GH72 enzyme-encoding genes: PHR1, PHR2, PHR3, PGA4, and PGA5. It is known that expression of PHR1 and PHR2 is controlled by the pH-responsive Rim101 pathway through the transcription factor Rim101. In this study, we have demonstrated that the transcription expression of PHR2 is also controlled by the transcription factor Crz1 through its binding motif in the promoter. Therefore, we have uncovered a dual-control mechanism by which PHR2 expression is negatively regulated via CaRim101 through the pH-responsive pathway and positively modulated by CaCrz1 through the calcium/calcineurin signaling pathway.

A biosynthetic network for protoberberine production in Coptis chinensis

Protoberberine alkaloids are a group of tetracyclic isoquinoline compounds known for their well-established antimicrobial and anti-inflammatory properties. The richness and diversity of protoberberine alkaloids accumulated in the Coptis genus necessitate a comprehensive examination of the biosynthetic machinery to understand their ecological significance. Here, from Coptis chinensis we identified CcCYP719A1, which could install a methylenedioxy bridge on either ring A or ring D of the protoberberine backbone, thus diverging metabolite flux towards the biosynthesis of various protoberberine components. We also obtained CcCYP719A2 and CcCYP719A3, which underwent positive selection after diverging from CcCYP719A1 and maintained specific catalytic activity on ring D. Further, we resolved the biosynthetic pathway of jatrorrhizine by identifying two demethylases, which could also modulate protoberberine composition by removing the C-3 methyl group and methylenedioxy bridge of ring D, allowing demethylated metabolites to be redirected into different routes. Moreover, we characterized 2-O-methyltransferase CcOMT1 and flavin-dependent oxidase CcTHBO, respectively responsible for the commonly observed 2-O-methylation and aromatic ring-C assembly in protoberberine alkaloids. Overall, this study reveals an interconnected metabolite network from which diverse protoberberine alkaloids originate. It provides valuable insights into the existence of undiscovered protoberberine components, and paves the way for the targeted production of desired protoberberine components for potential therapeutic development.

IKK/NF-κB and ROS signal axes are involved in Tenacissoside H mediated inhibitory effects on LPS-induced inflammatory osteolysis

Periodontal disease and arthroplasty prosthesis loosening and destabilization are both associated with osteolysis, which is predominantly caused by abnormal bone resorption triggered by pro-inflammatory cytokines. Osteoclasts (OCs) are critical players in the process. Concerns regarding the long-term efficacy and side effects of current frontline therapies, however, remain. Alternative therapies are still required. The aim of this work was to investigate the involvement of Tenacissoside H (TDH) in RANKL-mediated OC differentiation, as well as inflammatory osteolysis and associated processes. In vitro, bone marrow-derived macrophages (BMMs) cultured with RANKL and M-CSF were used to detect TDH in the differentiation and function of OCs. Real-time quantitative PCR was used to measure the expression of specific genes and inflammatory factors in OCs. Western blot was used to identify NFATc1, IKK, NF-κB, MAPK pathway, and oxidative stress-related components. Finally, an LPS-mediated calvarial osteolysis mouse model was employed to explore TDH's role in inflammatory osteolysis. The results showed that in vivo TDH inhibited the differentiation and resorption functions of OCs and down-regulated the transcription of osteoclast-specific genes, as well as Il-1β, Il-6 and Tnf-α. In addition, TDH inhibited the IKK and NF-κB signalling pathways and down-regulated the level of ROS. In vivo studies revealed that TDH improves the bone loss caused by LPS. TDH may be a new candidate or treatment for osteoclast-associated inflammatory osteolytic disease.

BMSC-exosomes miR-25-3p Regulates the p53 Signaling Pathway Through PTEN to Inhibit Cell Apoptosis and Ameliorate Liver Ischemia‒reperfusion Injury

BACKGROUND

Hepatic ischemia‒reperfusion injury (HIRI) is a pathological phenomenon during liver surgery, and bone marrow-mesenchymal stem cell (BMSC) exosomes (BMSC-Exos) regulate cell apoptosis and reduce ischemia‒reperfusion injury. We aimed to investigate the roles of BMSC-Exos and miR-25b-3p (enriched in BMSC-Exos) in HIRI and elucidate the underlying mechanisms.

APPROACHES AND RESULTS

An HIRI mouse model was constructed and preinjected with BMSC-Exos, agomir-miR-25, agomir-miR-NC, or PBS via the tail vein. Compared with mice with HIRI, mice with HIRI preinjected with BMSC-Exos had significantly decreased alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels and alleviated liver necrosis (P < 0.05). Quantitative hepatic transcriptomics showed that mice with HIRI preinjected with BMSC-Exos exhibited increased cell division, hematopoietic or lymphoid organ development and metabolic processes. miRNA sequencing of BMSC-Exos revealed that miR-25, which is related to I/R injury, was enriched in the exosomes. Compared with HIRI + NC mice, HIRI + miR-25b-3p mice had significantly increased miR-25b-3p expression, decreased ALT/AST levels and apoptosis-related protein expression (P < 0.05), and alleviated liver necrosis. The proliferation of AML-12 cells transfected with miR-25b-3p was significantly higher than that in the mimic NC group (P < 0.01) after hypoxia induction, and the apoptosis rate of cells was significantly lower than that in the NC group (P < 0.01). PTEN was identified as a miR-25b-3p target gene. PTEN expression was significantly diminished in miR-25b-3p-transfected AML12 cells (P < 0.05). HIRI + agomir-miR-25 mice displayed reduced PTEN expression and decreased p53 and cleaved caspase 3 levels compared to HIRI + NC mice.

CONCLUSIONS

We revealed the roles and underlying mechanisms of BMSC-Exos and miR-25 in HIRI, contributing to the prevention and treatment of HIRI.

Pseudomonas aeruginosa Strain 91: A Multifaceted Biocontrol Agent against Banana Fusarium Wilt

Banana Fusarium wilt (BFW), caused by the soil-borne fungus Fusarium oxysporum f. sp. cubense (Foc), poses significant threats to banana cultivation. Currently, effective control methods are lacking, and biological control has emerged as a possible strategy to manage BFW outbreaks. In this investigation, 109 bacterial strains were isolated from the rhizospheric soil surrounding banana plants in search of potent biological agents against Foc. Strain 91 exhibited the highest antifungal activity against the causal agent of Foc and was identified as Pseudomonas aeruginosa through 16S rRNA gene sequencing and scanning electron microscopy (SEM). Elucidation of strain 91's inhibitory mechanism against Foc revealed a multifaceted antagonistic approach, encompassing the production of bioactive compounds and the secretion of cell wall hydrolytic enzymes. Furthermore, strain 91 displayed various traits associated with promoting plant growth and showed adaptability to different carbon sources. By genetically tagging with constitutively expressing GFP signals, effective colonization of strain 91 was mainly demonstrated in root followed by leaf and stem tissues. Altogether, our study reveals the potential of P. aeruginosa 91 for biocontrol based on inhibition mechanism, adaptation, and colonization features, thus providing a promising candidate for the control of BFW.

Beyond Human Detection: A Benchmark for Detecting Common Human Posture

Human detection is the task of locating all instances of human beings present in an image, which has a wide range of applications across various fields, including search and rescue, surveillance, and autonomous driving. The rapid advancement of computer vision and deep learning technologies has brought significant improvements in human detection. However, for more advanced applications like healthcare, human-computer interaction, and scene understanding, it is crucial to obtain information beyond just the localization of humans. These applications require a deeper understanding of human behavior and state to enable effective and safe interactions with humans and the environment. This study presents a comprehensive benchmark, the Common Human Postures (CHP) dataset, aimed at promoting a more informative and more encouraging task beyond mere human detection. The benchmark dataset comprises a diverse collection of images, featuring individuals in different environments, clothing, and occlusions, performing a wide range of postures and activities. The benchmark aims to enhance research in this challenging task by designing novel and precise methods specifically for it. The CHP dataset consists of 5250 human images collected from different scenes, annotated with bounding boxes for seven common human poses. Using this well-annotated dataset, we have developed two baseline detectors, namely CHP-YOLOF and CHP-YOLOX, building upon two identity-preserved human posture detectors: IPH-YOLOF and IPH-YOLOX. We evaluate the performance of these baseline detectors through extensive experiments. The results demonstrate that these baseline detectors effectively detect human postures on the CHP dataset. By releasing the CHP dataset, we aim to facilitate further research on human pose estimation and to attract more researchers to focus on this challenging task.

Mitochondrial-targeting Mn3O4/UIO-TPP nanozyme scavenge ROS to restore mitochondrial function for osteoarthritis therapy

Excessive reactive oxygen species (ROS)-induced mitochondrial damage has impact on osteoarthritis (OA). Nanozyme mimics as natural enzyme alternatives to scavenge excessive ROS has offered a promising strategy for OA therapy. Herein, we reported a novel mitochondrial-targeting Mn3O4/UIO-TPP nanozyme using metal-organic frameworks with loaded Mn3O4 as the enzyme-like active core combining mitochondria-targeting triphenylphosphine (TPP) groups to serve as ROS scavengers for therapy of OA. With sequential catalysis of superoxide dismutase-like, catalase (CAT)-like, and hydroxyl radical (·OH) scavenging potentials, the nanozyme can target mitochondria by crossing subcellular barriers to effectively eliminate ROS to restore mitochondrial function and inhibit inflammation and chondrocyte apoptosis. It also has favorable biocompatibility and biosafety. Based on anterior cruciate ligament transection-induced OA joint models, this mitochondrial-targeting nanozyme effectively mitigated the inflammatory response with the Pelletier score reduction of 49.9% after 8-week therapy. This study offers a prospective approach to the design of nanomedicines for ROS-related diseases.

Liquid Content Detection In Transparent Containers: A Benchmark

Various substances that possess liquid states include drinking water, various types of fuel, pharmaceuticals, and chemicals, which are indispensable in our daily lives. There are numerous real-world applications for liquid content detection in transparent containers, for example, service robots, pouring robots, security checks, industrial observation systems, etc. However, the majority of the existing methods either concentrate on transparent container detection or liquid height estimation; the former provides very limited information for more advanced computer vision tasks, whereas the latter is too demanding to generalize to open-world applications. In this paper, we propose a dataset for detecting liquid content in transparent containers (LCDTC), which presents an innovative task involving transparent container detection and liquid content estimation. The primary objective of this task is to obtain more information beyond the location of the container by additionally providing certain liquid content information which is easy to achieve with computer vision methods in various open-world applications. This task has potential applications in service robots, waste classification, security checks, and so on. The presented LCDTC dataset comprises 5916 images that have been extensively annotated through axis-aligned bounding boxes. We develop two baseline detectors, termed LCD-YOLOF and LCD-YOLOX, for the proposed dataset, based on two identity-preserved human posture detectors, i.e., IPH-YOLOF and IPH-YOLOX. By releasing LCDTC, we intend to stimulate more future works into the detection of liquid content in transparent containers and bring more focus to this challenging task.

Substitution of D-Arginine at Position 11 of α-RgIA Potently Inhibits α7 Nicotinic Acetylcholine Receptor

Conotoxins are a class of disulfide-rich peptides found in the venom of cone snails, which have attracted considerable attention in recent years due to their potent activity on ion channels and potential for therapeutics. Among them, α-conotoxin RgIA, a 13-residue peptide, has shown great promise as a potent inhibitor of α9α10 nAChRs for pain management. In this study, we investigated the effect of substituting the naturally occurring L-type arginine at position 11 of the RgIA sequence with its D-type amino acid. Our results indicate that this substitution abrogated the ability of RgIA to block α9α10 nAChRs, but instead endowed the peptide with the ability to block α7 nAChR activity. Structural analyses revealed that this substitution induced significant alteration of the secondary structure of RgIA[11r], which consequently affected its activity. Our findings underscore the potential of D-type amino acid substitution as a promising strategy for designing novel conotoxin-based ligands targeting different types of nAChRs.

An Automated Skill Assessment Framework Based on Visual Motion Signals and a Deep Neural Network in Robot-Assisted Minimally Invasive Surgery

Surgical skill assessment can quantify the quality of the surgical operation via the motion state of the surgical instrument tip (SIT), which is considered one of the effective primary means by which to improve the accuracy of surgical operation. Traditional methods have displayed promising results in skill assessment. However, this success is predicated on the SIT sensors, making these approaches impractical when employing the minimally invasive surgical robot with such a tiny end size. To address the assessment issue regarding the operation quality of robot-assisted minimally invasive surgery (RAMIS), this paper proposes a new automatic framework for assessing surgical skills based on visual motion tracking and deep learning. The new method innovatively combines vision and kinematics. The kernel correlation filter (KCF) is introduced in order to obtain the key motion signals of the SIT and classify them by using the residual neural network (ResNet), realizing automated skill assessment in RAMIS. To verify its effectiveness and accuracy, the proposed method is applied to the public minimally invasive surgical robot dataset, the JIGSAWS. The results show that the method based on visual motion tracking technology and a deep neural network model can effectively and accurately assess the skill of robot-assisted surgery in near real-time. In a fairly short computational processing time of 3 to 5 s, the average accuracy of the assessment method is 92.04% and 84.80% in distinguishing two and three skill levels. This study makes an important contribution to the safe and high-quality development of RAMIS.

Research on force and position control performance of the tendon sheath system with time-varying parameters and flexible robotic arms

BACKGROUND

The tendon-sheath-system (TSS) is an excellent medium for remote power transmission, which is widely used in laparoscopic surgery robots. Since the operation process requires the robot to move continuously, this time-varying characteristic further aggravates the force and position transmission loss caused by the nonlinear friction of TSS, which affects the control accuracy of the surgical robot.

METHOD

A time-varying tendon-sheath transmission model (RT model) is proposed. A feedforward control system is designed to improve tendon-sheath transmission accuracy. Furthermore, a tendon-sheath transmission model with velocity characteristics (RV model) is established.

RESULT

Force, position, and velocity experiments were carried out on the platform of TSS with a robotic arm. The results show that the R-square values of force and position compensation are at least 96.57% and 99.16%.

CONCLUSION

The proposed RT and RV models are effective in compensating for the TSS transmission loss during the operation of the surgical robot.

Inhibition of PD-1 Alters the SHP1/2-PI3K/Akt Axis to Decrease M1 Polarization of Alveolar Macrophages in Lung Ischemia-Reperfusion Injury

Polarization of alveolar macrophages (AMs) into the M1 phenotype contributes to inflammatory responses and tissue damage that occur during lung ischemia-reperfusion injury (LIRI). Programmed cell death factor-1 (PD-1) regulates polarization of macrophages, but its role in LIRI is unknown. We examined the role of PD-1 in AM polarization in models of LIRI in vivo and in vitro. Adult Sprague-Dawley rats were subjected to ischemia-reperfusion with or without pretreatment with a PD-1 inhibitor, SHP1/2 inhibitor, or Akt activator. Lung tissue damage and infiltration by M1-type AMs were assessed. As an in vitro complement to the animal studies, rat alveolar macrophages in culture were subjected to oxygen/glucose deprivation and reoxygenation. Levels of SHP1/2 and Akt proteins were evaluated using Western blots, while levels of pro-inflammatory cytokines were measured using enzyme-linked immunosorbent assays. Injury upregulated PD-1 both in vivo and in vitro. Inhibiting PD-1 reduced the number of M1-type AMs, expression of SHP1 and SHP2, and levels of inflammatory cytokines. At the same time, it partially restored Akt activation. Similar results were observed after inhibition of SHP1/2 or activation of the PI3K/Akt pathway. PD-1 promotes polarization of AMs to the M1 phenotype and inflammatory responses through the SHP1/2-PI3K/Akt axis. Inhibiting PD-1 may be an effective therapeutic strategy to limit LIRI.

Fe-Curcumin Nanozyme-Mediated Reactive Oxygen Species Scavenging and Anti-Inflammation for Acute Lung Injury

Pneumonia, such as acute lung injury (ALI), has been a type of lethal disease that is generally caused by uncontrolled inflammatory response and excessive generation of reactive oxygen species (ROS). Herein, we report Fe-curcumin-based nanoparticles (Fe-Cur NPs) with nanozyme functionalities in guiding the intracellular ROS scavenging and meanwhile exhibiting anti-inflammation efficacy for curing ALI. The nanoparticles are noncytotoxic when directing these biological activities. Mechanism studies for the anti-inflammation aspects of Fe-Cur NPs were systematically carried out, in which the infected cells and tissues were alleviated through downregulating levels of several important inflammatory cytokines (such as TNF-α, IL-1β, and IL-6), decreasing the intracellular Ca2+ release, inhibiting NLRP3 inflammasomes, and suppressing NF-κB signaling pathways. In addition, we performed both the intratracheal and intravenous injection of Fe-Cur NPs in mice experiencing ALI and, importantly, found that the accumulation of such nanozymes was enhanced in lung tissue (better than free curcumin drugs), demonstrating its promising therapeutic efficiency in two different administration methods. We showed that the inflammation reduction of Fe-Cur NPs was effective in animal experiments and that ROS scavenging was also effectively achieved in lung tissue. Finally, we revealed that Fe-Cur NPs can decrease the level of macrophage cells (CD11bloF4/80hi) and CD3+CD45+ T cells in mice, which could help suppress the inflammation cytokine storm caused by ALI. Overall, this work has developed the strategy of using Fe-Cur NPs as nanozymes to scavenge intracellular ROS and as an anti-inflammation nanodrugs to synergistically cure ALI, which may serve as a promising therapeutic agent in the clinical treatment of this deadly disease. Fe-Cur NP nanozymes were designed to attenuate ALI by clearing intracellular ROS and alleviating inflammation synergistically. Relevant cytokines, inflammasomes, and signaling pathways were studied.

A pH-responsive mesoporous silica nanoparticles-based drug delivery system with controlled release of andrographolide for OA treatment

Andrographolide (AG) has favorable anti-inflammatory and antioxidative capacity. However, it has low bioavailability due to high lipophilicity and can be easily cleared by the synovial fluid after intra-articular injection, leading to low therapeutic efficiency in osteoarthritis (OA). Herein, we designed a nano-sized pH-responsive drug delivery system (DDS) for OA treatment by using modified mesoporous silica nanoparticles (MSNs) with pH-responsive polyacrylic acid (PAA) for loading of AG to form AG@MSNs-PAA nanoplatform. The nanoparticles have uniform size (∼120 nm), high drug loading efficiency (22.38 ± 0.71%) and pH-responsive properties, beneficial to sustained release in OA environment. Compared with AG, AG@MSNs-PAA showed enhanced antiarthritic efficacy and chondro-protective capacity based on IL-1β-stimulated chondrocytes and anterior cruciate ligament transection-induced rat OA model, as demonstrated by lower expression of inflammatory factors and better prevention of proteoglycan loss. Therefore, the AG@MSNs-PAA nanoplatform may be developed as a promising OA-specific and on-demand DDS.

Procyanidin A2, a polyphenolic compound, exerts anti-inflammatory and anti-oxidative activity in lipopolysaccharide-stimulated RAW264.7 cells

Procyandin A2 (PCA2) is a polyphenolic compound which is isolated from grape seeds. It has been reported that PCA2 exhibits antioxidative and anti-inflammatory effects, but its molecular mechanism is still poorly understood. This study tests the hypothesis that PCA2 suppresses lipopolysaccharide (LPS)-induced inflammation and oxidative stress through targeting the nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), and NF-E2-related factor 2 (Nrf2) pathways in RAW264.7 cells. PCA2 (20, 40, 80 μM) exhibited no significant cytotoxicity in RAW264.7 cells and showed an inhibitory effect on an LPS-induced nitrite level. Pro-inflammatory cytokines like tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), prostaglandin E2 (PGE2), nitric oxide (NO), and reactive oxygen species (ROS) were suppressed by PCA2 with a concentration range of 0–80 μM. The mRNA levels of TNF-α and IL-6 were inhibited by PCA2 (80 μM). The hallmark-protein expression of the NF-κB (p-IKKα/β, p-IκBα, and p-p65) and MAPK (p-p38, p-JNK, and p-ERK) pathways were decreased by PCA2 in LPS-stimulated RAW264.7 cells. In addition, immunofluorescence results indicated that PCA2 (80 μM) promoted the translocation of NF-κB/p65 from the cytoplasm into the nucleus. PCA2 upregulated the expressions of Nrf2 and HO-1 and downregulated the expression of Keap-1. Simultaneously, PCA2 (80 μM) reversed LPS-induced Nrf2 translocation from the nucleus into the cytoplasm. Collectively, PCA2 protect cells against the damage from inflammation and oxidative injury, which suggest a potential therapeutic strategy for inflammatory and oxidative stress through targeting NF-κB, MAPK, and Nrf2 pathways in RAW264.7 cells.

A Dual Targeting Magnetic Nanoparticle for Human Cancer Detection

Malignant tumors are a major threat to human life and high lymphatic vessel density is often associated with metastatic tumors. With the discovery of molecules targeted at the lymphatic system such as lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1) and Podoplanin, many studies have been performed to determine the role of lymphatic endothelial cells (LECs) in tumor metastasis. However, disadvantages such as non-specificity and high cost limit their research and diagnostic applications. In this study, Fe₃O₄@KCTS, a core-shell type of magnetic nanoparticles, was prepared by activating Fe₃O₄ with carbodiimide and cross-linking it with α-ketoglutarate chitosan (KCTS). The LYVE-1 and Podoplanin antibodies were then incorporated onto the surface of these magnetic nanoparticles and as a result, dual-targeting magnetic nanoprobes were developed. The experimental tests of this study demonstrated that a dual-targeting magnetic nanoprobe with high-purity LECs from tumor tissues was successfully developed, providing a basis for clinical application of LECs in colorectal cancer treatment as well as in early clinical diagnosis using bimodal imaging.