Adversarial Deep Transfer Learning in Fault Diagnosis: Progress, Challenges, and Future Prospects.

Deep Transfer Learning (DTL) signifies a novel paradigm in machine learning, merging the superiorities of deep learning in feature representation with the merits of transfer learning in knowledge transference. This synergistic integration propels DTL to the forefront of research and development within the Intelligent Fault Diagnosis (IFD) sphere. While the early DTL paradigms, reliant on fine-tuning, demonstrated effectiveness, they encountered considerable obstacles in complex domains. In response to these challenges, Adversarial Deep Transfer Learning (ADTL) emerged. This review first categorizes ADTL into non-generative and generative models. The former expands upon traditional DTL, focusing on the efficient transference of features and mapping relationships, while the latter employs technologies such as Generative Adversarial Networks (GANs) to facilitate feature transformation. A thorough examination of the recent advancements of ADTL in the IFD field follows. The review concludes by summarizing the current challenges and future directions for DTL in fault diagnosis, including issues such as data imbalance, negative transfer, and adversarial training stability. Through this cohesive analysis, this review aims to offer valuable insights and guidance for the optimization and implementation of ADTL in real-world industrial scenarios.

Fire Detection in Ship Engine Rooms Based on Deep Learning.

Ship fires are one of the main factors that endanger the safety of ships; because the ship is far away from land, the fire can be difficult to extinguish and could often cause huge losses. The engine room has many pieces of equipment and is the principal place of fire; however, due to its complex internal environment, it can bring many difficulties to the task of fire detection. The traditional detection methods have their own limitations, but fire detection using deep learning technology has the characteristics of high detection speed and accuracy. In this paper, we improve the YOLOv7-tiny model to enhance its detection performance. Firstly, partial convolution (PConv) and coordinate attention (CA) mechanisms are introduced into the model to improve its detection speed and feature extraction ability. Then, SIoU is used as a loss function to accelerate the model's convergence and improve accuracy. Finally, the experimental results on the dataset of the ship engine room fire made by us shows that the mAP@0.5 of the improved model is increased by 2.6%, and the speed is increased by 10 fps, which can meet the needs of engine room fire detection.

[Omics Analysis of Ferroptosis and Establishment of Prognostic Model for multiple myeloma Patients].

OBJECTIVE: To explore the role of ferroptosis-related genes in multiple myeloma(MM) through TCGA database and FerrDb, and build a prognostic model of ferroptosis-related genes for MM patients. METHODS: Using the TCGA database containing clinical information and gene expression profile data of 764 patients with MM and the FerrDb database including ferroptosis-related genes, the differentially expressed ferroptosis-related genes were screened by wilcox.test function. The prognostic model of ferroptosis-related genes was established by Lasso regression, and the Kaplan-Meier survival curve was drawn. Then COX regression analysis was used to screen independent prognostic factors. Finally, the differential genes between high-risk and low-risk patients were screened, and enrichment analysis was used to explore the mechanism of the relationship between ferroptosis and prognosis in MM. RESULTS: 36 differential genes related to ferroptosis were screened out from bone marrow samples of 764 MM patients and 4 normal people, including 12 up-regulated genes and 24 down-regulated genes. Six prognosis-related genes (GCLM, GLS2, SLC7A11, AIFM2, ACO1, G6PD) were screened out by Lasso regression and the prognostic model with ferroptosis-related genes of MM was established. Kaplan-Meier survival curve analysis showed that the survival rate between high risk group and low risk group was significantly different(P<0.01). Univariate COX regression analysis showed that age, sex, ISS stage and risk score were significantly correlated with overall survival of MM patients(P<0.05), while multivariate COX regression analysis showed that age, ISS stage and risk score were independent prognostic indicators for MM patients (P<0.05). GO and KEGG enrichment analysis showed that the ferroptosis-related genes was mainly related to neutrophil degranulation and migration, cytokine activity and regulation, cell component, antigen processing and presentation, complement and coagulation cascades, haematopoietic cell lineage and so on, which may affect the prognosis of patients. CONCLUSION: Ferroptosis-related genes change significantly during the pathogenesis of MM. The prognostic model of ferroptosis-related genes can be used to predict the survival of MM patients, but the mechanism of the potential function of ferroptosis-related genes needs to be confirmed by further clinical studies.

[Clinical Research Advances of Duodenal-Type Follicular Lymphoma--Review].

Duodenal-type follicular lymphoma (DFL) is a unique subtype of follicular lymphoma (FL), which often involves the second portion of duodenum (descending part of duodenum). Due to its specific pathological features, such as lack of follicular dendritic cells meshwork and disappearance of activation-induced cytidine deaminase expression, DFL presents an inert clinical course and is often confined to the intestinal tract. Inflammation-related biomarkers suggest that the microenvironment may play a likely role in the pathogenesis and favorable prognosis of DFL. Since patients generally have no obvious clinical symptoms and low progression rate, the treatment regimen for DFL is mainly observation and waiting (W&W) strategy. This study will review the latest research progress of epidemiology, diagnosis, treatment and prognosis of DFL in recent years.

[Construction of a Prognostic Model of Multiple Myeloma Based on Metabolism-Related Genes].

OBJECTIVE: To screen the prognostic biomarkers of metabolic genes in patients with multiple myeloma (MM), and construct a prognostic model of metabolic genes. METHODS: The histological database related to MM patients was searched. Data from MM patients and healthy controls with complete clinical information were selected for analysis.The second generation sequencing data and clinical information of bone marrow tissue of MM patients and healthy controls were collected from human protein atlas (HPA) and multiple myeloma research foundation (MMRF) databases. The gene set of metabolism-related pathways was extracted from Molecular Signatures Database (MSigDB) by Perl language. The biomarkers related to MM metabolism were screened by difference analysis, univariate Cox risk regression analysis and LASSO regression analysis, and the risk prognostic model and Nomogram were constructed. Risk curve and survival curve were used to verify the grouping effect of the model. Gene set enrichment analysis (GSEA) was used to study the difference of biological pathway enrichment between high risk group and low risk group. Multivariate Cox risk regression analysis was used to verify the independent prognostic ability of risk score. RESULTS: A total of 8 mRNAs which were significantly related to the survival and prognosis of MM patients were obtained (P<0.01). As molecular markers, MM patients could be divided into high-risk group and low-risk group. Survival curve and risk curve showed that the overall survival time of patients in the low-risk group was significantly better than that in the high risk group (P<0.001). GSEA results showed that signal pathways related to basic metabolism, cell differentiation and cell cycle were significantly enriched in the high-risk group, while ribosome and N polysaccharide biosynthesis signaling pathway were more enriched in the low-risk group. Multivariate Cox regression analysis showed that the risk score composed of the eight metabolism-related genes could be used as an independent risk factor for the prognosis of MM patients, and receiver operating characteristic curve (ROC) showed that the molecular signatures of metabolism-related genes had the best predictive effect. CONCLUSION: Metabolism-related pathways play an important role in the pathogenesis and prognosis of patients with MM. The clinical significance of the risk assessment model for patients with MM constructed based on eight metabolism-related core genes needs to be confirmed by further clinical studies.

Combination of two target agonists of the thrombopoietin and thrombopoietin receptor in the treatment of elderly patients with refractory immune thrombocytopenia.

Immune thrombocytopenia (ITP) is common in the elderly. Because of the coexistence of multiple diseases, there are many reservations regarding corticosteroid use in the elderly. Thrombopoietin (TPO) and its analogs can promote platelet production, but it is often difficult to correct TP in a short period. Recombinant human TPO (rh-TPO) acting on the cell membrane and the small-molecule TPO-receptor (MPL) agonist acting on the transmembrane receptor may have synergistic effects and accelerate platelet production because of different sites of action in the signaling pathway. In this study, two elderly patients with refractory ITP were successfully treated with two TPO-MPL signaling pathway agonists: recombinant human thrombopoietin (rh-TPO) and eltrombopag. This combination is safe with rapid and lasting effects. However, in elderly patients with refractory, recurrent, and glucocorticoid contraindications, the combination of different TPO agonists' clinical efficacy and adverse reactions needs to be further evaluated.

New Lactobacillus plantarum membrane proteins (LpMPs) towards oral anti-inflammatory agents against dextran sulfate sodium-induced colitis.

Inflammatory bowel disease (IBD), a progressive and unpredictable colorectal inflammatory disease, is a global health problem. Currently, therapeutic strategies for the management of the disease are limited. Results from our previous studies indicated that probiotic Lactobacillus plantarum exhibits therapeutic effects against IBD, and through screening, we obtained an active 61-amino-acid long protein, L. plantarum membrane protein 1 (LpMP-1). Based on druggability-guided strategies, the search for LpMPs with lower molecular weights and better bioactivities contributes to the development of new anti-inflammatory agents to overcome the limitations of existing therapies against IBD. We used amino-acid-truncation strategies to obtain modified LpMPs (LpMP-2 - LpMP-9) using LpMP-1 as the parent template. Furthermore, we systematically evaluated the anti-colitis pharmacodynamics of these LpMPs in terms of symptomatology, histopathology, and cytokine levels in DSS-induced ulcerative colitis mice. Their possible targets of action against IBD was investigated under an iTRAQ-based pharmacoproteomic system and a docking-guided receptor-ligand relationship frame. We found a new active protein, LpMP-8, which had a lower molecular weight than LpMP-1. LpMP-8 was found to exhibit anti-colitis activity following oral administration in vivo (50 µg/kg) by improving symptoms of colitis, colonic ulcerations, and cytokine disorders. TLRs and TGF-ß were found to be involved in the action of LpMP-8 against colitis; LpMP-8 was to compete with TLR4-MD2-bound LPS and reverse TGF-ß and Smad2/7 disorders. Our probiotic-derived LpMP-8 was shown to elicit oral anti-colitis activity, and its significant efficacy is probably associated with TLR4 and TGF-ß.

Research on the Application of Visual Recognition in the Engine Room of Intelligent Ships.

In the engine room of intelligent ships, visual recognition is an essential technical precondition for automatic inspection. At present, the problems of visual recognition in marine engine rooms include missing detection, low accuracy, slow speed, and imperfect datasets. For these problems, this paper proposes a marine engine room equipment recognition model based on the improved You Only Look Once v5 (YOLOv5) algorithm. The channel pruning method based on batch normalization (BN) layer weight value is used to improve the recognition speed. The complete intersection over union (CIoU) loss function and hard-swish activation function are used to enhance detection accuracy. Meanwhile, soft-NMS is used as the non-maximum suppression (NMS) method to reduce the false rate and missed detection rate. Then, the main equipment in the marine engine room (MEMER) dataset is built. Finally, comparative experiments and ablation experiments are carried out on the MEMER dataset to verify the strategy's efficacy on the model performance boost. Specifically, this model can accurately detect 100.00% of diesel engines, 95.91% of pumps, 94.29% of coolers, 98.54% of oil separators, 64.21% of meters, 60.23% of reservoirs, and 75.32% of valves in the actual marine engine room.

[Screening of Differential Expression Autophagy Genes Related to the Prognosis of Diffuse Large B-Cell Lymphoma and Establishment of an Autophagy Model].

OBJECTIVE: To screen the differential expression of diffuse large B-cell lymphoma (DLBCL) autophagy-related gene (ARG), explore the mechanism of differential expression of autophagy gene (DEARG) in the occurrence and development of DLBCL and establish a prognostic model. METHODS: Using the NCICCR database containing clinical information and gene expression profile data of 481 patients with DLBCL and the HADb database containing 232 ARGs, the differential expression of ARG in DLBCL was determined by R language, the relationship between ARG and the occurrence and development of DLBCL was analyzed by GO and KEGG, the polygene prognostic model was established by Cox regression algorithm, the survival curve was drawn by Kaplan-Meier method, and the reliability of the prognostic model was evaluated by ROC curve. RESULTS: A total of 122 DEARGs were extracted from lymph node samples of 481 patients with DLBCL and 5 normal lymph nodes, including 4 up-regulated genes and 118 down-regulated genes. GO enrichment mainly focused on ontological annotations such as mitochondrial autophagy, autophagy regulation, and cell response to external stimuli. KEGG enrichment was mainly concentrated in cell senescence, NOD-like receptor signal pathway, PI3K-Akt signal pathway, and PD-1/PD-L1 signal pathway. Survival analysis was performed on 230 samples with complete clinical information. Univariate Cox analysis showed that 20 ARGs were significantly correlated with overall survival of DLBCL patients. Nine prognostic ARGs (HIF1A, CAPN1, ITPR1, PRKCQ, TRAIL, HDAC1, TSC2, NRG3, and MAPK3) were screened by multivariate Cox regression to establish DLBCL ARG prognostic model. Kaplan-Meier survival curve analysis showed that there was significant difference in survival rate between high risk group and low risk group (P<0.001). Multivariate Cox regression analysis showed that international prognostic index and risk value were independent prognostic indicators of DLBCL patients (P<0.05), the area under ROC curve was 0.762 and 0.747, respectively. CONCLUSION: DLBCL ARG prognostic model can be used to predict the prognosis of patients, but it still needs to be confirmed by a large sample of clinical studies.

Clinicopathological characteristics and prognostic significance of HDAC11 protein expression in non-small cell lung cancer: a retrospective study.

Background: Although the prognosis of non-small cell lung cancer (NSCLC) can be assessed based on pathological type, disease stage and inflammatory indicators, the prognostic scoring model of NSCLC still needs to improve. HDAC11 is associated with poor prognosis of partial tumors, but its prognostic relationship with NSCLC is poorly understood. In this study, the role of HDAC11 in NSCLC was studied to evaluate relationship with disease prognosis and potential therapeutic target. Methods: The clinicopathological and paracancerous tissues of patients with NSCLC primarily diagnosed in Tangdu Hospital from 2009 to 2013 were collected. Follow-up of patients were made every three months and the last follow-up period was December 2018. The expression of HDAC11 was assessed by immunohistochemistry (IHC). Then, weighted gene co-expression network analysis (WGCNA) was used to analyze the relationship between HDAC11 expression and the prognosis of lung adenocarcinoma (LUAD) patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Kaplan-Meier plotter database was used to verify the connection between hub genes and tumor stage and prognosis. We accessed the relationship between HDAC11 expression and clinicopathological features, and impact on the prognosis. Results: The study assessed 326 patients with NSCLC. Compared with adjacent tissues, HDAC11 expression was upregulated (HR =1.503, 95% CI: 1.172 to 1.927, P=0.001). Kaplan-Meier survival analyses showed that HDAC11 expression was closely related to OS of NSCLC patients (P=0.0011). Univariate and multivariate analyses showed that the independent risk factors of OS were clinical stage, HDAC11 expression, and HDAC11 differentiation (all P≤0.001). HDAC11 was significantly associated with prognosis in LUAD. A total of 1,174 differential genes and WGCNA were obtained to construct a co-expression network in LUAD. The GO and KEGG pathway enrichment analyses showed the relevance with staphylococcus aureus infection, NOD-like receptor signaling pathway, and others. The results of LUAD survival analysis showed that HDAC11-related genes NKX2-5 and FABP7 were significantly associated with LUAD prognosis. Conclusions: The high expression of HDAC11 is related to the poor prognosis of LUAD, and it is expected to become a therapeutic target and prognostic evaluation therapy for LUAD in the future. However, the relevant results need to be further studied and verified.

Porcine Fibrin Sealant Promotes Skin Wound Healing in Rats.

Objective: Fibrin sealant (FS) is widely used for skin wound healing, but data on porcine FS (PFS), a new type of FS, are limited. This study investigated the effects and potential mechanisms of porcine fibrin sealant (PFS) on skin wound healing in rats. Methods. Traumatic rats were randomly divided into three groups: control, PFS, and medical Vaseline. The wound area and wound index of the rats were measured within 14 days after surgery. Hematoxylin-eosin (H&E) staining and Masson staining were used to observe the pathological images and collagen formation on the wounded skin, respectively. To investigate the healing mechanisms, the enzyme-linked immunosorbent assay (ELISA) was used to detect platelet endothelial cell adhesion molecule-1 (CD31) and cluster of differentiation 34 (CD34) expression in the wounded skin. Additionally, quantitative real-time PCR (qRT-PCR) was used to evaluate the mRNA levels of the vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF), and epidermal growth factor (EGF), and transforming growth factor-ß1 (TGF-ß1). Meanwhile, TGF-ß1 protein expression was assessed by Western blot analysis. Results: Compared with the control group, both PFS and medical Vaseline treatment significantly reduced the wounded area and increased the wound closure rate. H&E staining showed that the cells in the PFS group proliferated rapidly, and the epidermis and dermis were thickened to some extent with a clear epidermal cell structure. Moreover, PFS promoted the formation of collagen and significantly increased the levels of CD31 and CD34 and the growth factors in the skin tissues of the traumatic rats. Conclusion: PFS effectively promoted skin wound healing, especially in tissue formation, reepithelialization, angiogenesis, and collagen deposition, in traumatic rat models. This study provides a new strategy and scientific foundation for PFS application in skin wound healing.

MoS2/WSe2 vdW Heterostructures Decorated with PbS Quantum Dots for the Development of High-Performance Photovoltaic and Broadband Photodiodes.

van der Waals heterostructures (vdWHs) overcoming the lattice and processing limitations of conventional heterostructures provide an opportunity to develop high-performance 2D vdWH solar cells and photodiodes. However, it is challenging to improve the sensitivity and response speed of 2D vdWH photovoltaic devices due to the low light absorption efficiency and electron/hole traps in heterointerfaces. Here, we design a PbS/MoS2/WSe2 heterostructure photodiode in which a light-sensitive PbS quantum dot (QD) layer combined with a MoS2/WSe2 heterostructure significantly enhances the photovoltaic response. The electron current in the heterostructure is increased by the effective collection of photogenerated electrons induced by PbS QDs. The device exhibits a broadband photovoltaic response from 405 to 1064 nm with a maximum responsivity of 0.76 A/W and a specific detectivity of 5.15 × 1011 Jones. In particular, the response speed is not limited by multiple electron traps in the PbS QDs/2D material heterointerface, and a fast rising/decaying time of 43/48 µs and a -3 dB cutoff frequency of over 10 kHz are achieved. The negative differential capacitance and frequency dependence of capacitance demonstrate the presence of interface states in the MoS2/WSe2 heterointerface that hamper the improvement of the response speed. The scheme to enhance photovoltaic performance without sacrificing response speed provides opportunities for the development of high-performance 2D vdWH optoelectronic devices.

Identification of Six Prognostic Genes in EGFR-Mutant Lung Adenocarcinoma Using Structure Network Algorithms.

This study aims to determine hub genes related to the incidence and prognosis of EGFR-mutant (MT) lung adenocarcinoma (LUAD) with weighted gene coexpression network analysis (WGCNA). From The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we used 253 EGFR-MT LUAD samples and 38 normal lung tissue samples. At the same time, GSE19188 was additionally included to verify the accuracy of the predicted gene. To discover differentially expressed genes (DEGs), the R package "limma" was used. The R packages "WGCNA" and "survival" were used to perform WGCNA and survival analyses, respectively. The functional analysis was carried out with the R package "clusterProfiler." In total, 1450 EGFR-MT-specific DEGs were found, and 7 tumor-related modules were marked with WGCNA. We found 6 hub genes in DEGs that overlapped with the tumor-related modules, and the overexpression level of B3GNT3 was significantly associated with the worse OS (overall survival) of the EGFR-MT LUAD patients (p < 0.05). Functional analysis of the hub genes showed the metabolism and protein synthesis-related terms added value. In conclusion, we used WGCNA to identify hub genes in the development of EGFR-MT LUAD. The established prognostic factors could be used as clinical biomarkers. To confirm the mechanism of those genes in EGFR-MT LUAD, further molecular research is required.

[Bioinformatics Analysis of the Influence of Coronavirus Infection on Hematopoietic System and Potential Intervention Drugs and Their Significance for COVID-19].

OBJECTIVE: To analyze and predict the effect of coronavirus infection on hematopoietic system and potential intervention drugs, and explore their significance for coronavirus disease 2019 (COVID-19). METHODS: The gene expression omnibus (GEO) database was used to screen the whole genome expression data related with coronavirus infection. The R language package was used for differential expression analysis and KEGG/GO enrichment analysis. The core genes were screened by PPI network analysis using STRING online analysis website. Then the self-developed apparent precision therapy prediction platform (EpiMed) was used to analyze diseases, drugs and related target genes. RESULTS: A database in accordance with the criteria was found, which was derived from SARS coronavirus. A total of 3606 differential genes were screened, including 2148 expression up-regulated genes and 1458 expression down-regulated genes. GO enrichment mainly related with viral infection, hematopoietic regulation, cell chemotaxis, platelet granule content secretion, immune activation, acute inflammation, etc. KEGG enrichment mainly related with hematopoietic function, coagulation cascade reaction, acute inflammation, immune reaction, etc. Ten core genes such as PTPRC, ICAM1, TIMP1, CXCR5, IL-1B, MYC, CR2, FSTL1, SOX1 and COL3A1 were screened by protein interaction network analysis. Ten drugs with potential intervention effects, including glucocorticoid, TNF-α inhibitor, salvia miltiorrhiza, sirolimus, licorice, red peony, famciclovir, cyclosporine A, houttuynia cordata, fluvastatin, etc. were screened by EpiMed plotform. CONCLUSION: SARS coronavirus infection can affect the hematopoietic system by changing the expression of a series of genes. The potential intervention drugs screened on these grounds are of useful reference significance for the basic and clinical research of COVID-19.

Bioinformatics analysis of SARS-CoV-2 infection-associated immune injury and therapeutic prediction for COVID-19.

Background: Severe acute respiratory syndrome coronavirus 2 is a highly contagious viral infection, without any available targeted therapies. The high mortality rate of COVID-19 is speculated to be related to immune damage. Methods: In this study, clinical bioinformatics analysis was conducted on transcriptome data of coronavirus infection. Results: Bioinformatics analysis revealed that the complex immune injury induced by coronavirus infection provoked dysfunction of numerous immune-related molecules and signaling pathways, including immune cells and toll-like receptor cascades. Production of numerous cytokines through the Th17 signaling pathway led to elevation in plasma levels of cytokines (including IL6, NF-κB, and TNF-α) followed by concurrent inflammatory storm, which mediates the autoimmune response. Several novel medications seemed to display therapeutic effects on immune damage associated with coronavirus infection. Conclusions: This study provided insights for further large-scale studies on the target therapy on reconciliation of immunological damage associated with COVID-19.

Observation of ZrNb14O37 Nanowires as a Lithium Container via In Situ and Ex Situ Techniques for High-Performance Lithium-Ion Batteries.

Based on the high theoretical capacity and relatively high safety voltage, niobium-based oxides are regarded as promising intercalation-type electrode materials for advanced lithium-ion batteries (LIBs). Here, ZrNb14O37 nanowires are fabricated via a facile electrospinning method, presenting a nanoparticle-in-nanowire architecture. As an anode for LIBs, the as-fabricated ZrNb14O37 nanowires maintain a capacity of 244.9 mA h g-1 at 100 mA g-1 and present excellent cycling capability (0.026% of capacity fading per cycle during 1000 cycles) as well as outstanding rate performance. In situ X-ray diffraction measurement is conducted to understand the fundamental reaction mechanism during the lithiation/delithiation process. The ex situ observations, including X-ray photoelectron spectroscopy and transmission electron microscopy, are further performed to provide more lines of evidence of the reaction mechanism. Moreover, the excellent electrochemical performance of the full cell constructed using ZrNb14O37 nanowires and LiCoO2 suggests that ZrNb14O37 nanowires are a promising anode material. This work sheds new light on understanding the lithium storage mechanism and may open new opportunities to develop new anode materials for LIBs.

Effect of Interaction between Adenosine and Nitric Oxide on Central Nervous System Oxygen Toxicity.

The metabolism of adenosine (ADO) and nitric oxide (NO) in brain tissues is closely associated with the change of oxygen content. They have contrary effects in the onset of hyperbaric oxygen (HBO)-induced central nervous system oxygen toxicity (CNS OT): ADO can suppress the onset, while NO promotes it. We adopted the ADO-augmenting measure and NO-inhibiting measure in this study and found the combined use had a far superior preventive and therapeutic effect in protecting against CNS OT compared with the use of either measure alone. So we hypothesized that there is an interaction between ADO and NO which has an important impact on the onset of CNS OT. On this basis, we administered ADO-augmenting or ADO-inhibiting drugs to rats. After exposure to HBO, the onset of CNS OT was evaluated, followed by the measurement of NO content in brain tissues. In another experiment, rats were administered NO-augmenting or NO-inhibiting drugs. After exposure to HBO, the onset of CNS OT was evaluated, followed by measurement of the activities of ADO metabolism-related enzymes in brain tissues. The results showed that, following ADO augmentation, the content of NO and its metabolite was significantly reduced, and the onset of CNS OT significantly improved. After ADO inhibition, just the opposite was observed. NO promotion resulted in a decrease in the activity of ADO-producing enzyme, an increase in the activity of ADO-decomposing enzyme, and an aggravation in CNS OT. The above results were all reversed after an inhibition in NO content. Studies have shown that exposure to HBO has a significant impact on the content of ADO and NO in brain tissues as well as their biological effects, and ADO and NO might have an intense interaction, which might generate an important effect on the onset of CNS OT. The prophylaxis and treatment effects of CNS OT can be greatly enhanced by augmenting ADO and inhibiting NO.

Bilayered Scaffold Prepared from a Kartogenin-Loaded Hydrogel and BMP-2-Derived Peptide-Loaded Porous Nanofibrous Scaffold for Osteochondral Defect Repair.

Recently, a bilayered scaffold with an anisotropic structure mimicking a native osteochondral tissue shows considerable potential for treating osteochondral defects. Herein, a bilayered scaffold consisting of biomimetic cartilage and a subchondral bone architecture was constructed for repairing osteochondral defect. A hydrogel prepared by the Schiff base reaction of gelatin, silk fibroin, and oxidized dextran was designed as the cartilage layer, while a nanofibrous scaffold with a macroporous structure prepared from the polymer blend of poly(l-lactic acid)/poly(lactic-co-glycolic acid)/poly(ε-caprolactone) using the dual phase separation technique served as a subchondral layer. The subchondral layer was then treated with polydopamine coating for osteogenic factor immobilization. To facilitate the chondrogenic and osteogenic differentiation of bone marrow mesenchymal stem cells on the bilayered scaffold, the cartilage-inducing drug kartogenin (KGN) and osteogenic-inducing factor bone morphogenetic protein 2-derived peptides (P24 peptides) were, respectively, loaded on the subchondral layer. Next, the in vitro release of KGN and P24 peptide from the corresponding layer was monitored, respectively, and the results showed that both the release time of KGN and P24 peptides would last for more than 28 days. The in vitro results indicated that the KGN-loaded cartilage layer and P24 peptides-loaded subchondral layer were capable of supporting cell proliferation, and induced the chondrogenic and osteogenic differentiation, respectively. Furthermore, the in vivo experiments suggested that the bilayered scaffold significantly accelerated the regeneration of the osteochondral tissue in the rabbit knee joint model. Consequently, this bilayered scaffold loaded with KGN and P24 peptides would be a promising candidate for repairing osteochondral defect.

Hyaluronic-acid-modified lipid-polymer hybrid nanoparticles as an efficient ocular delivery platform for moxifloxacin hydrochloride.

To improve the ocular bioavailability of the strongly hydrophilic moxifloxacin hydrochloride, hyaluronic-acid-modified lipid-polymer hybrid nanoparticles (HA-LCS-NPs) were designed and characterized. An in vivo precorneal retention study in rabbits showed that the mean residence time (MRT) and area under the curve (AUC0-6h) of HA-LCS-NPs were up to 6.74-fold and 4.29-fold higher than those of the commercial product. An in vitro corneal penetration study in rabbits demonstrated that the apparent permeability coefficient (Papp) of HA-LCS-NPs was increased by 3.29-fold compared to the commercial product, which might be observed because the surface-modified hyaluronic acid could expedite the cellular uptake of HA-LCS-NPs by receptor-mediated endocytosis. Moreover, in contrast with other formulations, the results of ex vivo fluorescence imaging showed that the fluorescence intensity was higher in the cornea and conjunctiva after administration of HA-LCS-NPs. Finally, an ocular irritation study indicated that HA-LCS-NPs displayed excellent ocular tolerance. In summary, the hyaluronic-acid-modified lipid-polymer hybrid nanoparticles with multifunctional properties might be a promising ocular drug delivery system for prolonged precorneal retention, better corneal permeability and enhanced ocular bioavailability.