ABSTRACT
As one of the key components of electric vehicles, the enhancement of the performance of the power battery is closely intertwined with an efficient Battery Thermal Management System (BTMS). In the realm of BTMS, Flat Heat Pipes (FHP) have garnered considerable attention due to their lightweight structure and excellent thermal conductivity. Thus, a BTMS configuration scheme based on FHP is proposed in this study. Utilizing orthogonal design and fuzzy grey relational analysis as the evaluation methods, coupled with numerical simulations, an investigation into the influence of four structural parameters of the novel biomimetic fins (namely, the diameter, height, spacing of protrusions, and height of cooling fins) on the temperature distribution of the battery pack is conducted. The research findings indicate that to maintain the battery within an optimal operational temperature range, the optimal dimensional parameters should be controlled at 17.5 mm, 4 mm, 13 mm, and 90 mm, respectively. Subsequent sensitivity analysis reveals that the height of the protrusions exhibits the most significant influence on the maximum temperature of the module, whereas the height of the cooling fins exerts a considerable impact on the consistency of the module temperature. The optimized maximum temperature is determined to be 36.52 °C, with a temperature difference of 2.65 °C.
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In view of the special engineering properties of red clay and the waste of phosphogypsum resources, the expansion and contraction deformation and fissure evolution of phosphogypsum stabilized red clay under different conditions were investigated by laboratory tests and image processing system. The research results show that: (1) the absolute expansion and absolute shrinkage of phosphogypsum stabilized red clay are positively correlated with the compaction degree, the number of dry and wet cycles and the cement dosage, and negatively correlated with the initial water content and the phosphogypsum dosage; (2) the fissure rate increases with the increase of the number of dry and wet cycles, and decreases with the increase of the initial water content, the compaction degree, the cement, and the phosphogypsum dosage; (3) The relationship among absolute expansion rate (absolute shrinkage), degree of compaction and fracture rate can be fitted by the equation f(x,y) = ax+by+cx2+dy2+e; (4) Phosphogypsum has an obvious inhibiting effect on the expansion, shrinkage and cracking of the mix. It is recommended that the cement mixing amount of 6% and phosphogypsum: red clay = 1:1~1:2 as roadbed filler.
Subject(s)
Aluminum Silicates , Calcium Sulfate , Clay , Construction Materials , Phosphorus , Calcium Sulfate/chemistry , Clay/chemistry , Phosphorus/chemistry , Aluminum Silicates/chemistry , Water/chemistry , Materials TestingABSTRACT
Cancer is rarely the straightforward consequence of an abnormality in a single gene, but rather reflects a complex interplay of many genes, represented as gene modules. Here, we leverage the recent advances of model-agnostic interpretation approach and develop CGMega, an explainable and graph attention-based deep learning framework to perform cancer gene module dissection. CGMega outperforms current approaches in cancer gene prediction, and it provides a promising approach to integrate multi-omics information. We apply CGMega to breast cancer cell line and acute myeloid leukemia (AML) patients, and we uncover the high-order gene module formed by ErbB family and tumor factors NRG1, PPM1A and DLG2. We identify 396 candidate AML genes, and observe the enrichment of either known AML genes or candidate AML genes in a single gene module. We also identify patient-specific AML genes and associated gene modules. Together, these results indicate that CGMega can be used to dissect cancer gene modules, and provide high-order mechanistic insights into cancer development and heterogeneity.
Subject(s)
Breast Neoplasms , Deep Learning , Gene Regulatory Networks , Leukemia, Myeloid, Acute , Neural Networks, Computer , Humans , Leukemia, Myeloid, Acute/genetics , Breast Neoplasms/genetics , Cell Line, Tumor , Female , Gene Expression Regulation, Neoplastic , Neuregulin-1/genetics , Neuregulin-1/metabolismABSTRACT
Histopathological examinations heavily rely on hematoxylin and eosin (HE) and immunohistochemistry (IHC) staining. IHC staining can offer more accurate diagnostic details but it brings significant financial and time costs. Furthermore, either re-staining HE-stained slides or using adjacent slides for IHC may compromise the accuracy of pathological diagnosis due to information loss. To address these challenges, we develop PST-Diff, a method for generating virtual IHC images from HE images based on diffusion models, which allows pathologists to simultaneously view multiple staining results from the same tissue slide. To maintain the pathological consistency of the stain transfer, we propose the asymmetric attention mechanism (AAM) and latent transfer (LT) module in PST-Diff. Specifically, the AAM can retain more local pathological information of the source domain images through the design of asymmetric attention mechanisms, while ensuring the model's flexibility in generating virtual stained images that highly confirm to the target domain. Subsequently, the LT module transfers the implicit representations across different domains, effectively alleviating the bias introduced by direct connection and further enhancing the pathological consistency of PST-Diff. Furthermore, to maintain the structural consistency of the stain transfer, the conditional frequency guidance (CFG) module is proposed to precisely control image generation and preserve structural details according to the frequency recovery process. To conclude, the pathological and structural consistency constraints provide PST-Diff with effectiveness and superior generalization in generating stable and functionally pathological IHC images with the best evaluation score. In general, PST-Diff offers prospective application in clinical virtual staining and pathological image analysis.
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Overgrazing and climate change are the main causes of grassland degradation, and grazing exclusion is one of the most common measures for restoring degraded grasslands worldwide. Soil fungi can respond rapidly to environmental stresses, but the response of different grassland types to grazing control has not been uniformly determined. Three grassland types (temperate desert, temperate steppe grassland, and mountain meadow) that were closed for grazing exclusion for 9 years were used to study the effects of grazing exclusion on soil nutrients as well as fungal community structure in the three grassland types. The results showed that (1) in the 0-5 cm soil layer, grazing exclusion significantly affected the soil water content of the three grassland types (P < 0.05), and the pH, total phosphorous (TP), and nitrogen-to-phosphorous ratio (N/P) changed significantly in all three grassland types (P < 0.05). Significant changes in soil nutrients in the 5-10 cm soil layer after grazing exclusion occurred in the mountain meadow grasslands (P < 0.05), but not in the temperate desert and temperate steppe grasslands. (2) For the different grassland types, Archaeorhizomycetes was most abundant in the montane meadows, and Dothideomycetes was most abundant in the temperate desert grasslands and was significantly more abundant than in the remaining two grassland types (P < 0.05). Grazing exclusion led to insignificant changes in the dominant soil fungal phyla and α diversity, but significant changes in the ß diversity of soil fungi (P < 0.05). (3) Grazing exclusion areas have higher mean clustering coefficients and modularity classes than grazing areas. In particular, the highest modularity class is found in temperate steppe grassland grazing exclusion areas. (4) We also found that pH is the main driving factor affecting soil fungal community structure, that plant coverage is a key environmental factor affecting soil community composition, and that grazing exclusion indirectly affects soil fungal communities by affecting soil nutrients. The above results suggest that grazing exclusion may regulate microbial ecological processes by changing the soil fungal ß diversity in the three grassland types. Grazing exclusion is not conducive to the recovery of soil nutrients in areas with mountain grassland but improves the stability of soil fungi in temperate steppe grassland. Therefore, the type of degraded grassland should be considered when formulating suitable restoration programmes when grazing exclusion measures are implemented. The results of this study provide new insights into the response of soil fungal communities to grazing exclusion, providing a theoretical basis for the management of degraded grassland restoration.
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The promoting effects of collagen and its derivatives on bone health have been uncovered. However, the structure and effects of type II collagen peptides from squid cartilage (SCIIP) on osteoarthritis still need to be clarified. In this study, SCIIP was prepared from squid throat cartilage with pretreatment by 0.2 mol/L NaOH at a liquid-solid ratio of 10:1 for 18 h and hydrolyzation using alkaline protease and flavourzyme at 50 °C for 4 h. The structure of SCIIP was characterized as a molecular weight lower than 5 kDa (accounting for 87.7 %), a high glycine level of 35.0 %, typical FTIR and CD features of collagen peptides, and a repetitive sequence of Gly-X-Y. GP(Hyp)GPD and GPAGP(Hyp)GD were separated and identified from SCIIP, and their binding energies with TLR4/MD-2 were - 8.4 and - 8.0 kcal/mol, respectively. SCIIP effectively inhibited NO production in RAW264.7 macrophages and alleviated osteoarthritis in rats through the TLR4/NF-κB pathway. Therefore, SCIIP exhibited the potential for application as an anti-osteoarthritis supplement.
Subject(s)
Cartilage , Collagen Type II , Decapodiformes , Osteoarthritis , Animals , Decapodiformes/chemistry , Osteoarthritis/drug therapy , Collagen Type II/metabolism , Mice , Cartilage/chemistry , Cartilage/metabolism , RAW 264.7 Cells , Rats , Male , Peptides/chemistry , Peptides/pharmacology , Rats, Sprague-Dawley , Nitric Oxide/metabolism , NF-kappa B/metabolism , Toll-Like Receptor 4/metabolismABSTRACT
Targeting selective CO2 photoreduction into CH4 remains a challenge due to the sluggish reaction kinetics and poor hydrogenation ability of the unstable intermediate. Here, the active Pt2+ sites were photodeposited on the SrTiO3 photocatalyst, which was well demonstrated to manipulate the CH4 product selectivity. The results showed that SrTiO3 mainly yielded the CO (6.98 µmol g-1) product with poor CH4 (0.17 µmol g-1). With the Pt2+ modification, 100% CH4 selectivity could be obtained with an optimized yield rate of 8.07 µmol g-1. The prominent enhancement resulted from the following roles: (1) the strong electronic interaction between the Pt2+ cocatalyst and SrTiO3 could prompt efficient separation of the photoelectron-hole pairs. (2) The Pt2+ sites were active to capture and activate inert CO2 into HCO3- and CO32- species and allowed fast *COOH formation with the lowered reaction barrier. (3) Compared with SrTiO3, the formed *CO species could be captured tightly on the Pt2+ cocatalyst surface for generating the *CH2 intermediate by the following electron-proton coupling reaction, thus leading to the CH4 product with 100% selectivity.
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Ship emissions are a significant source of air pollution, and the primary policy to control is fuel oil quality improvement. However, the impact of this policy on particle size distribution and composition characteristics remains unclear. Measurements were conducted on nine different vessels (ocean-going vessels, coastal cargo ships, and inland cargo ships) to determine the impact of fuel upgrading (S < 0.1% m/m marine gas oil (MGO) vs S < 0.5% m/m heavy fuel oil (HFO)) on elemental carbon (EC) and polycyclic aromatic hydrocarbons (PAHs) emitted by ships. (1) Fuel improvement significantly reduced EC and PAH emission, by 31 ± 25 and 45 ± 38%, respectively. However, particle size distributions showed a trend toward finer particles, with the peak size decreasing from DP = 0.38-0.60 µm (HFO) to DP = 0.15-0.25 µm (MGO), and the emission factor of DP < 100 nm increased. (2) Changes in emission characteristics led to an increase in the toxicity of ultrafine particulate matter. (3) Ship types and engine conditions affected the EC and PAH particle size distributions. Inland ships have a more concentrated particle size distribution. Higher loads result in higher emissions. (4) The composition and engine conditions of fuel oils jointly affected pollutant formation mechanisms. MGO and HFO exhibited opposite EC emissions when emitting the same level of PAHs.
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Background: Insulin-like Growth Factor-1 (IGF-1) plays a crucial role in the growth and metabolic functions of various tissues and cells in the body. Recently, there has been increased attention to the association between IGF-1 and osteoarthritis (OA). However, there is controversy in current research regarding the correlation between IGF-1 levels and OA. Furthermore, the specific manner in which Body Mass Index (BMI), a key risk factor for OA, mediates the impact of IGF-1 levels on OA remains unclear. Object: This study aimed to investigate the bidirectional causal link between IGF-1 levels and OA in four body regions, and to explore how BMI influences the impact of IGF-1 on these types of OA. Method: Two-sample Mendelian Randomization (MR) and its combined forms were utilized to investigate the bidirectional relationship between IGF-1 levels and four types of OA, as well as the mediating role of BMI in the impact of IGF-1 levels on OA. Data from various Genome-Wide Association Studies (GWAS) and multiple analytical methods, including inverse variance weighted, MR-Egger regression, and weighted median were utilized. Sensitivity analyses, such as MR-Egger intercept, Cochran Q test, leave-one-out, and MR-PRESSO, were conducted to ensure the robustness of the results. Results: Higher IGF-1 levels are correlated with an increased risk for knee (OR, 1.07; 95% CI, 1.01-1.03; p = 1.49e-01; q = 9.86e-03), hip (OR, 1.13; 95% CI, 1.06-1.20; p = 7.61e-05; q = 7.44e-05), and hand OA (OR, 1.09; 95% CI, 1.01-1.17; p = 1.88e-02; q = 1.15e-02), but not spine OA but not spine OA (OR, 1.05; 95% CI, 0.99-1.10; p = 9.20e-02; q = 5.52e-02). Different types of OA do not affect IGF-1 levels. BMI mediates the increase in OA risk associated with higher IGF-1, including indirect spine OA risk through BMI. Conclusion: The study elucidates the bidirectional causality between IGF-1 levels and OA in various body parts, highlighting BMI's mediating role in the impact of IGF-1 levels on OA. This provides valuable insights for OA prevention, diagnosis, and treatment strategies. Future research will expand our study to include a broader spectrum of ethnicities and explore the underlying mechanisms involved.
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This work conducts the comprehensive theoretical study on the non-covalent complexation between cyclocarbons and C60 fullerene for the first time. The binding energy between cyclocarbons and C60 fullerene is significantly stronger than that between two C18 or two C60 fullerenes, indicating a particularly strong affinity. The cyclocarbons and C60 fullerene can spontaneously assemble into complexes in the gas phase at room temperature, and the hydrophobic effect caused by the solvent environment can promote this binding. The binding strength with C60 fullerene increases almost linearly with the increase of cyclocarbon size, and the C34@C60 dimer exhibits a perfect nano-Saturn structure. As the ring size increases, the angle between the two cyclocarbons of the 2:1 trimers formed by cyclocarbons and C60 fullerene gradually decreases. In C60@2C34 trimer, the fullerene is symmetrically surrounded by two cyclocarbons. The results on the trimers formed by cyclocarbon and C60 fullerenes in a 1:2 ratio showed when the cyclocarbon sandwiched between two fullerenes is not quite large, the trimers exhibit an ideal dumbbell-like structure, and the presence of the first fullerene has a significant synergistic effect on the binding of the second one. The cyclocarbon greatly promotes the dimerization of fullerenes, which acted as a "molecular glue".
ABSTRACT
Circumventing the conventional two-electron oxygen reduction pathway remains a great problem in enhancing the efficiency of H2O2 photosynthesis. A promising approach to achieve outstanding photocatalytic activity involves the utilization of redox intermediates. Here, we engineer a polyimide aerogel photocatalyst with photoreductive carbonyl groups for non-sacrificial H2O2 production. Under photoexcitation, carbonyl groups on the photocatalyst surface are reduced, forming an anion radical intermediate. The produced intermediate is oxidized by O2 to produce H2O2 and subsequently restores the carbonyl group. The high catalytic efficiency is ascribed to a photocatalytic redox cycle mediated by the radical anion, which not only promotes oxygen adsorption but also lowers the energy barrier of O2 reduction reaction for H2O2 generation. An apparent quantum yield of 14.28% at 420 ± 10 nm with a solar-to-chemical conversion efficiency of 0.92% is achieved. Moreover, we demonstrate that a mere 0.5 m2 self-supported polyimide aerogel exposed to natural sunlight for 6 h yields significant H2O2 production of 34.3 mmol m-2.
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Osteoarthritis (OA), a degenerative joint disorder, has an unclear immune infiltration mechanism in subchondral bone (SCB). Thus, this study aims to discern immune infiltration variations in SCB between early- and late-stages of OA and identify pertinent biomarkers. Utilizing the GSE515188 bulk-seq profile from the Gene Expression Omnibus database, we performed single-sample gene-set enrichment analysis alongside weighted gene co-expression network analysis to identify key cells and immune-related genes (IRGs) involved in SCB at both stages. At the meanwhile, differentially expressed genes (DEGs) were identified in the same dataset and intersected with IRGs to find IR-DEGs. Protein-protein interaction network and enrichment analyses and further gene filtering using LASSO regression led to the discovery of potential biomarkers, which were then validated by ROC curve analysis, single-cell RNA sequencing, qRT-PCR, western blot and immunofluorescence. ScRNA-seq analysis using GSE196678, qRT-PCR, western blot and immunofluorescence results confirmed the upregulation of their expression levels in early-stage OA SCB samples. Our comprehensive analysis revealed lymphocytes infiltration as a major feature in early OA SCB. A total of 13 IR-DEGs were identified, showing significant enrichment in T- or B-cell activation pathways. Three of them (CD247, POU2AF1, and TNFRSF13B) were selected via the LASSO regression analysis, and results from the ROC curve analyses indicated the diagnostic efficacy of these 3 genes as biomarkers. These findings may aid in investigating the mechanisms of SCB immune infiltration in OA, stratifying OA progression, and identifying relevant therapeutic targets.
Subject(s)
Disease Progression , Osteoarthritis , Humans , Osteoarthritis/genetics , Osteoarthritis/immunology , Osteoarthritis/pathology , Transcriptome , Protein Interaction Maps , Biomarkers , Lymphocytes/immunology , Gene Expression Profiling , Bone and Bones/pathology , Bone and Bones/immunology , Bone and Bones/metabolismABSTRACT
BACKGROUND: The patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patellar height and evaluated its performance and generalization ability to accurately measure the patellar height index. METHODS: We developed a dataset containing 3,923 lateral knee X-ray images. Notably, all X-ray images were from three tertiary level A hospitals, and 2,341 cases were included in the analysis after screening. By manually labeling key points, the model was trained using the residual network (ResNet) and high-resolution network (HRNet) for human pose estimation architectures to measure the patellar height index. Various data enhancement techniques were used to enhance the robustness of the model. The root mean square error (RMSE), object keypoint similarity (OKS), and percentage of correct keypoint (PCK) metrics were used to evaluate the training results. In addition, we used the intraclass correlation coefficient (ICC) to assess the consistency between manual and automatic measurements. RESULTS: The HRNet model performed excellently in keypoint detection tasks by comparing different deep learning models. Furthermore, the pose_hrnet_w48 model was particularly outstanding in the RMSE, OKS, and PCK metrics, and the Insall-Salvati index (ISI) automatically calculated by this model was also highly consistent with the manual measurements (intraclass correlation coefficient [ICC], 0.809-0.885). This evidence demonstrates the accuracy and generalizability of this deep learning system in practical applications. CONCLUSION: We successfully developed a deep learning-based automatic measurement system for the patellar height. The system demonstrated accuracy comparable to that of experienced radiologists and a strong generalizability across different datasets. It provides an essential tool for assessing and treating knee diseases early and monitoring and rehabilitation after knee surgery. Due to the potential bias in the selection of datasets in this study, different datasets should be examined in the future to optimize the model so that it can be reliably applied in clinical practice. TRIAL REGISTRATION: The study was registered at the Medical Research Registration and Filing Information System (medicalresearch.org.cn) MR-61-23-013065. Date of registration: May 04, 2023 (retrospectively registered).
Subject(s)
Deep Learning , Patella , Humans , Patella/diagnostic imaging , Patella/anatomy & histology , Retrospective Studies , Male , Female , Automation , Radiography/methods , Middle Aged , AdultABSTRACT
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a type of interstitial lung disease characterized by unknown causes and a poor prognosis. Recent research indicates that age-related mechanisms, such as cellular senescence, may play a role in the development of this condition. However, the relationship between cellular senescence and clinical outcomes in IPF remains uncertain. METHODS: Data from the GSE70867 database were meticulously analyzed in this study. The research employed differential expression analysis, as well as univariate and multivariate Cox regression analysis, to pinpoint senescence-related genes (SRGs) linked to prognosis and construct a prognostic risk model. The model's clinical relevance and its connection to potential biological processes were systematically assessed in training and testing datasets. Additionally, the expression location of prognosis-related SRGs was identified through immunohistochemical staining, and the correlation between SRGs and immune cell infiltration was deduced using the GSE28221 dataset. RESULT: The prognostic risk model was constructed based on five SRGs (cellular communication network factor 1, CYR61, stratifin, SFN, megakaryocyte-associated tyrosine kinase, MATK, C-X-C motif chemokine ligand 1, CXCL1, LIM domain, and actin binding 1, LIMA1). Both Kaplan-Meier (KM) curves (p = 0.005) and time-dependent receiver operating characteristic (ROC) analysis affirmed the predictive accuracy of this model in testing datasets, with respective areas under the ROC curve at 1-, 2-, and 3-years being 0.721, 0.802, and 0.739. Furthermore, qRT-RCR analysis and immunohistochemical staining verify the differential expression of SRGs in IPF samples and controls. Moreover, patients in the high-risk group contained higher infiltration levels of neutrophils, eosinophils, and M1 macrophages in BALF, which appeared to be independent indicators of poor prognosis in IPF patients. CONCLUSION: Our research reveals the effectiveness of the 5 SRGs model in BALF for risk stratification and prognosis prediction in IPF patients, providing new insights into the immune infiltration of IPF progression.
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Solid polymer electrolytes are promising electrolytes for safe and high-energy-density lithium metal batteries. However, traditional ether-based polymer electrolytes are limited by their low lithium-ion conductivity and narrow electrochemical window because of the well-defined and intimated Li+-oxygen binding topologies in the solvation structure. Herein, we proposed a new strategy to reduce the Li+-polymer interaction and strengthen the anion-polymer interaction by combining strong Li+-O (ether) interactions, weak Li+-O (ester) interactions with steric hindrance in polymer electrolytes. In this way, a polymer electrolyte with a high lithium ion transference number (0.80) and anion-rich solvation structure is obtained. This polymer electrolyte possesses a wide electrochemical window (5.5â V versus Li/Li+) and compatibility with both Li metal anode and high-voltage NCM cathode. Li||LiNi0.5Co0.2Mn0.3O2 full cells with middle-high active material areal loading (~7.5â mg cm-2) can stably cycle at 4.5â V. This work provides new insight into the design of polymer electrolytes for high-energy-density lithium metal batteries through the regulation of ion-dipole interactions.
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Recent therapeutic strategies for the treatment of triple-negative breast cancer (TNBC) have shifted the focus from vascular growth factors to endothelial cell metabolism. This study highlights the underexplored therapeutic potential of peri-tumoral electroacupuncture, a globally accepted non-pharmacological intervention for TNBC, and molecular mechanisms. Our study showed that peri-tumoral electroacupuncture effectively reduced the density of microvasculature and enhanced vascular functionality in 4T1 breast cancer xenografts, with optimal effects on day 3 post-acupuncture. The timely integration of peri-tumoral electroacupuncture amplified the anti-tumor efficacy of paclitaxel. Multi-omics analysis revealed Glyoxalase 1 (Glo1) and the associated methylglyoxal-glycolytic pathway as key mediators of electroacupuncture-induced vascular normalization. Peri-tumoral electroacupuncture notably reduced Glo1 expression in the endothelial cells of 4T1 xenografts. Using an in vivo matrigel plug angiogenesis assay, we demonstrated that either Glo1 knockdown or electroacupuncture inhibited angiogenesis. In contrast, Glo1 overexpression increased blood vessel formation. In vitro pharmacological inhibition and genetic knockdown of Glo1 in human umbilical vein endothelial cells inhibited proliferation and promoted apoptosis via downregulating the methylglyoxal-glycolytic pathway. The study using the Glo1-silenced zebrafish model further supported the role of Glo1 in vascular development. This study underscores the pivotal role of Glo1 in peri-tumoral electroacupuncture, spotlighting a promising avenue for enhancing vascular normalization and improving TNBC treatment outcomes.
Subject(s)
Electroacupuncture , Glycolysis , Lactoylglutathione Lyase , Neovascularization, Pathologic , Triple Negative Breast Neoplasms , Animals , Female , Humans , Mice , Cell Line, Tumor , Cell Proliferation , Electroacupuncture/methods , Endothelial Cells/metabolism , Human Umbilical Vein Endothelial Cells , Lactoylglutathione Lyase/metabolism , Lactoylglutathione Lyase/genetics , Mice, Inbred BALB C , Neovascularization, Pathologic/metabolism , Paclitaxel/pharmacology , Pyruvaldehyde/metabolism , Triple Negative Breast Neoplasms/genetics , Triple Negative Breast Neoplasms/metabolism , Triple Negative Breast Neoplasms/pathology , Triple Negative Breast Neoplasms/therapy , Xenograft Model Antitumor Assays , ZebrafishABSTRACT
BACKGROUND: Chromoblastomycosis (CMB) is a chronic granulomatous fungal infection that affect the skin and subcutaneous tissues. It is clinically problematic due to limited treatment options, low cure rates, and high rates of relapse. This underscores the necessity for innovative treatment approaches. In this study, potassium iodide (KI) combined with Methylene Blue (MB) mediated antimicrobial photodynamic therapy (PDT) were assessed in the treatment of Fonsecaea monophora (F. monophora) both in vitro and in vivo. And the underlying mechanism that contributes to the efficacy of this treatment approach was investigated. METHODS: In vitro experiments were conducted using different combinations and concentrations of MB, KI, and 660 nm light (60 mW/cm2) to inhibit F. monophora. The study was carried out using colony-forming unit (CFU) counts and scanning electron microscopy (SEM). The production of singlet oxygen (1O2), free iodine (I2), hydrogen peroxide (H2O2), and superoxide anion during the KI combined MB-mediated antimicrobial PDT process was also detected. In vivo experiments were developed using a Balb/c mouse paw infection model with F. monophora and treated with PBS, 10 mM KI, 2 mM MB +100 J/cm² and 10 mM KI+2 mM MB +100 J/cm² respectively. Inflammatory swelling, fungal load and histopathological analyses of the mouse footpads were assessed. RESULTS: KI enhanced the killing effect of MB-mediated antimicrobial PDT on the conidial spores of F. monophora at the cell and infected animal model level. During the process, the main antimicrobial agents in KI combined with MB- mediated antimicrobial PDT could produce stronger toxic active species including free I2 and H2O2. CONCLUSION: KI combined with MB-mediated antimicrobial PDT could be an effective adjunct therapy for treating CBM.
Subject(s)
Methylene Blue , Mice, Inbred BALB C , Photochemotherapy , Photosensitizing Agents , Potassium Iodide , Potassium Iodide/pharmacology , Methylene Blue/pharmacology , Methylene Blue/therapeutic use , Photochemotherapy/methods , Animals , Mice , Photosensitizing Agents/pharmacology , Chromoblastomycosis/drug therapy , Ascomycota/drug effects , Singlet Oxygen/metabolism , Hydrogen Peroxide/pharmacologyABSTRACT
This work reports on the preparation of uniform vesicle-structural carbon spheres doped with heteroatoms of N, P, and S, with the pore sizes strictly controlled by the hard templates of monodisperse submicron SiO2 spheres. The uniformly doped vesicular carbon microspheres are obtained in three steps: Stöber hydrolysis for the SiO2; in situ polymerization for the immobilization; and alkaline etching after carbonization. The size of the vesicles can be easily adjusted by regulating the particle size of the submicron SiO2 spheres, which has a significant effect on its electromagnetic wave (EMW) absorption performance. Compared with microspheres with pore sizes of 180 and 480 nm, when the vesicle aperture is 327 nm, with only 5.5 wt.% filling load and 1.9 mm thickness, the material shows the best EMW absorption behavior with the effective absorption bandwidth (EAB) covers the entire Ku band (6.32 GHz) and the minimum reflection loss (RLmin) of -36.10 dB, suggesting the optimized pore size of the microspheres can significantly improve the overall impedance matching of the material and achieve broadband wave absorption. This work paves the way for the enhancement of EMW absorption properties of porous material by optimizing the pore size of uniform apertures while maintaining their composition.
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BACKGROUND: Rotational alignment in total knee arthroplasty (TKA) is a crucial technical point that needs attention. We conducted a retrospective study to investigate whether a new robot-assisted TKA (RA-TKA) could improve the accuracy of rotational alignment and whether rotational alignment affects postoperative pain and functional evaluation of the knee. METHODS: A total of 136 consecutive patients who underwent TKA were included in this study. Half of the patients underwent RA-TKA and the other half underwent conventional TKA (CON-TKA) by the same group of surgeons. Collect the relevant parameters. RESULTS: The postoperative femoral rotation angle (FRA) was -0.72 ± 2.59° in the robot-assisted group and 1.13 ± 2.73° in the conventional group, and were statistically significantly different (p < 0.001). CONCLUSION: This study provides preliminary evidence that the RA-TKA provides more precise control of FRA than CON-TKA, and verifies that tibial rotation angle and combined rotation angle affect postoperative knee pain and functional evaluation.
Subject(s)
Arthroplasty, Replacement, Knee , Femur , Robotic Surgical Procedures , Humans , Arthroplasty, Replacement, Knee/methods , Robotic Surgical Procedures/methods , Retrospective Studies , Female , Male , Aged , Middle Aged , Rotation , Femur/surgery , Knee Joint/surgery , Knee Joint/physiopathology , Range of Motion, Articular , Pain, Postoperative/prevention & control , Pain, Postoperative/etiology , Treatment OutcomeABSTRACT
BACKGROUND: Huaier (Trametes robiniophila Murr), a traditional Chinese medicine, is widely used in China as a complementary and alternative therapy to treat hepatocellular carcinoma (HCC). Past studies have shown that Huaier can arrest the cell cycle, promote apoptosis and inhibit the proliferation of cancer cells. However, how it regulates the metabolism of HCC is still unclear. OBJECTIVE: This study explores the metabolic-related function of Huaier in treating HCC with an in-silico approach. METHODS: A network pharmacology and bioinformatics-based approach was employed to investigate the molecular pathogenesis of metabolic reprogramming in HCC with Huaier. The compounds of Huaier were obtained from public databases. Oral bioavailability and drug likeness were screened using the TCMSP platform. The differential gene expressions between HCC and non-tumor tissue were calculated and used to find the overlap from the targets of Huaier. The enrichment analysis of the overlapped targets by Metascape helped filter out the metabolism-related targets of Huaier in treating HCC. Protein-protein interaction (PPI) network construction and topological screening revealed the hub nodes. The prognosis and clinical correlation of these targets were validated from the cancer genome atlas (TCGA) database, and the interactions between the hub nodes and active ingredients were validated by molecular docking. RESULTS: The results showed that Peroxyergosterol, Daucosterol, and Kaempferol were the primary active compounds of Huaier involved in the metabolic reprogramming of HCC. The top 6 metabolic targets included AKR1C3, CYP1A1, CYP3A4, CYP1A2, CYP17A1, and HSD11B1. The decreased expression of CYP3A4 and increased expression of AKR1C3 were related to the poor overall survival of HCC patients. The molecular docking validated that Peroxyergosterol and Kaempferol exhibited the potential to modulate CYP3A4 and AKR1C3 from a computational perspective. CONCLUSION: This study provided a workflow for understanding the mechanism of Huaier in regulating the metabolic reprogramming of HCC.