ABSTRACT
The series-parallel hybrid system has attracted much attention from scholars for its effective integration of the power advantages and operating characteristics of different power sources, which is influenced by international emission regulations, energy-saving and emission reduction policies. As such, a series-parallel hybrid powertrain is introduced to the amphibious vehicle, and an innovative powertrain topology architecture is proposed. Meanwhile, the operation mode and energy efficiency characteristics are investigated during the working process. Firstly, the energy flow simulation model of a series-parallel gas-electric hybrid propulsion system is constructed using a modular modeling approach. Secondly, four operating modes, namely mechanical propulsion, electric propulsion, hybrid propulsion and charging mode, were formulated due to the fact that the propulsion system has multiple forms of power sources in the form of natural gas engine and reversible motor. Meanwhile, the energy flow states were investigated under different operating modes. Meanwhile, a comprehensive investigation of the energy efficiency associated with propulsion, storage and start-up energy was conducted for each specific mode. The results of the research indicated that the energy efficiency of the electric propulsion mode can reach up to 35.15 %, which is the gain from the wide operating range of the motor's high efficiency. The hybrid propulsion mode can obtain the highest energy efficiency of 35.88 %, which fully demonstrates the advantages of coordinating and complementing the two power sources, the natural gas engine and the reversible electric motor. This investigation also provides theoretical and empirical support for optimizing energy matching and formulating energy management strategies.
ABSTRACT
Lung cancer ranks as the 2nd most common cancer globally. It's the most prevalent cancer in men and the 2nd most common in women. The prominent events in EGFR-mutated non-small-cell lung cancer (NSCLC) include the emergence of the L858R mutation within EGFR exon 21. Despite the promising efficacy of EGFR inhibitors in managing lung cancer, the development of acquired resistance poses a significant hurdle. In the current investigation, we focused on the screening of two phytochemicals, namely Dehydrocostus lactone and Mokkolactone, derived from the Saussurea lappa plant, as potential inhibitors targeting EGFR L858R mutant lung cancer. The chloroform and ethanol extract of the plant demonstrated anti-proliferative activity through the Resazurin chemosensitivity assay, exhibiting an IC50 value of 37.90 ± 0.29 µg/ml with selectivity index 2.4. Through a GC-MS study, we identified 11 phytochemicals for further insilico analysis. These compounds underwent ADMET assessment followed by drug likeliness analysis before being subjected to molecular docking against EGFR L858R, identified through protein-protein interaction network analysis. All phytochemicals exhibited binding energy scores ranging from -6.9 to -8.1 kcal/mol. Dehydrocostus lactone and Mokkolactone were specifically identified for their binding profile. Findings from 100 ns molecular dynamics simulations demonstrated their enhanced stability compared to the reference ligand DJK. This was evident in the root mean square deviation (RMSD) values, ranging from 0.23 ± 0.01 nm to 0.30 ± 0.05 nm, the radius of gyration values, from 1.71 ± 0.01 nm to 1.72 ± 0.01 nm, and the solvent accessible surface area values, from 155.39 ± 2.40 nm2 to 159.32 ± 2.14 nm2. Additionally, favourable characteristics were observed in terms of hydrogen bonding, principal component analysis, and free energy landscape analysis. Examination of their electronic structure via density functional theory revealed efficient properties, with the highest occupied molecular orbital-least unoccupied molecular orbital energy gap values ranging from -3.984 eV to -6.547 eV. Further, in vivo analysis is required to gain a more comprehensive understanding and efficacy of these identified phytochemicals against lung cancer.
ABSTRACT
Cardenolides are a class of steroidal glycoside compounds that are mainly distributed in plants, have significant physiological activity in the heart, and have been used clinically for over 200 years. To provide a reference for further research and development of these compounds, the phytochemical and biological properties of natural cardenolides (295 compounds in total) isolated between 2010 and 2023 from 17 families and hundreds of species belonging to 70-80 genera were reviewed. In vitro and in vivo studies have indicated that antitumor, antibacterial, and antiviral activities are the most commonly reported pharmacological properties of cardenolides. Antitumor activities have been thoroughly studied to understand their structure-activity relationships, revealing numerous potential anticancer molecules that lay the theoretical foundation for further development of traditional Chinese medicinal herbs and the creation of new drugs.
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Two rare 8-hydroxysteroid glycosides (6-7), and their downstream metabolites (1-5) with an unprecedented 6/6/5/5/5-pentacyclic scaffold, together with seven known analogues (8-14) were isolated from the twigs and leaves of Strophanthus divaricatus. Their structures were fully assigned by analysis of the spectroscopic and ECD data, NMR calculations, X-ray crystallographic study, and chemical methods. In addition, the inhibitory effects of 1-14 on liver and lung cancer cell lines were evaluated, and preliminary structure-activity relationship was discussed. Data-independent acquisition (DIA)-based quantitative proteomic analysis and biological verification of H1299 cells suggested that this family of compounds may play an anticancer role by suppressing both DNA damage response (DDR) and mTOR/S6K signaling pathways.
Subject(s)
DNA Damage , Dose-Response Relationship, Drug , Drug Screening Assays, Antitumor , Glycosides , Signal Transduction , TOR Serine-Threonine Kinases , Humans , TOR Serine-Threonine Kinases/metabolism , TOR Serine-Threonine Kinases/antagonists & inhibitors , Structure-Activity Relationship , Glycosides/chemistry , Glycosides/pharmacology , Glycosides/isolation & purification , DNA Damage/drug effects , Signal Transduction/drug effects , Molecular Structure , Cell Proliferation/drug effects , Steroids/chemistry , Steroids/pharmacology , Steroids/isolation & purification , Ribosomal Protein S6 Kinases/metabolism , Ribosomal Protein S6 Kinases/antagonists & inhibitors , Antineoplastic Agents, Phytogenic/pharmacology , Antineoplastic Agents, Phytogenic/chemistry , Antineoplastic Agents, Phytogenic/isolation & purification , Cell Line, Tumor , Antineoplastic Agents/pharmacology , Antineoplastic Agents/chemistryABSTRACT
Background: Cervical cancer is among the most prevalent malignancies worldwide. This study explores the relationships between angiogenesis-related genes (ARGs) and immune infiltration, and assesses their implications for the prognosis and treatment of cervical cancer. Additionally, it develops a diagnostic model based on angiogenesis-related differentially expressed genes (ARDEGs). Methods: We systematically evaluated 15 ARDEGs using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). Immune cell infiltration was assessed using a single-sample gene-set enrichment analysis (ssGSEA) algorithm. We then constructed a diagnostic model for ARDEGs using Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and evaluated the diagnostic value of this model and the hub genes in predicting clinical outcomes and immunotherapy responses in cervical cancer. Results: A set of ARDEGs was identified from the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and UCSC Xena database. We performed KEGG, GO, and GSEA analyses on these genes, revealing significant involvement in cell proliferation, differentiation, and apoptosis. The ARDEGs diagnostic model, constructed using LASSO regression analysis, showed high predictive accuracy in cervical cancer patients. We developed a reliable nomogram and decision curve analysis to evaluate the clinical utility of the ARDEG diagnostic model. The 15 ARDEGs in the model were associated with clinicopathological features, prognosis, and immune cell infiltration. Notably, ITGA5 expression and the abundance of immune cell infiltration (specifically mast cell activation) were highly correlated. Conclusion: This study identifies the prognostic characteristics of ARGs in cervical cancer patients, elucidating aspects of the tumor microenvironment. It enhances the predictive accuracy of immunotherapy outcomes and establishes new strategies for immunotherapeutic interventions.
ABSTRACT
In aquaculture, viral diseases pose a significant threat and can lead to substantial economic losses. The primary defense against viral invasion is the innate immune system, with interferons (IFNs) playing a crucial role in mediating the immune response. With advancements in molecular biology, the role of non-coding RNA (ncRNA), particularly microRNAs (miRNAs), in gene expression has gained increasing attention. While the function of miRNAs in regulating the host immune response has been extensively studied, research on their immunomodulatory effects in teleost fish, including silver carp (Hyphthalmichthys molitrix), is limited. Therefore, this research aimed to investigate the immunomodulatory role of microRNA-30b-5p (miR-30b-5p) in the antiviral immune response of silver carp (Hypophthalmichthys molitrix) by targeting cytokine receptor family B5 (CRFB5) via the JAK/STAT signaling pathway. In this study, silver carp were stimulated with polyinosinic-polycytidylic acid (poly (I:C)), resulting in the identification of an up-regulated miRNA (miR-30b-5p). Through a dual luciferase assay, it was demonstrated that CRFB5, a receptor shared by fish type I interferon, is a novel target of miR-30b-5p. Furthermore, it was found that miR-30b-5p can suppress post-transcriptional CRFB5 expression. Importantly, this study revealed for the first time that miR-30b-5p negatively regulates the JAK/STAT signaling pathway, thereby mediating the antiviral immune response in silver carp by targeting CRFB5 and maintaining immune system stability. These findings not only contribute to the understanding of how miRNAs act as negative feedback regulators in teleost fish antiviral immunity but also suggest their potential therapeutic measures to prevent an excessive immune response.
Subject(s)
Carps , Fish Proteins , MicroRNAs , Poly I-C , Signal Transduction , Animals , Carps/genetics , Carps/immunology , Carps/virology , Carps/metabolism , Fish Diseases/immunology , Fish Diseases/virology , Fish Diseases/genetics , Fish Proteins/genetics , Fish Proteins/metabolism , Gene Expression Regulation/drug effects , Immunity, Innate/genetics , Janus Kinases/metabolism , MicroRNAs/genetics , MicroRNAs/metabolism , Poly I-C/pharmacology , STAT Transcription Factors/metabolism , STAT Transcription Factors/geneticsABSTRACT
As a paradigm shift in tandem with the expansion of ICT, smart electronic health systems hold great promise for enhancing healthcare delivery and illness prevention efforts. These systems acquire an in-depth understanding of patient health states through the real-time collection and analysis of medical data enabled by the Internet of Things (IoT) and machine learning. With the widespread use of cutting-edge artificial intelligence and machine learning techniques, predictive analytics in medicine can assist in making the shift from a reactive to a proactive healthcare strategy. With the ability to rapidly and precisely evaluate massive amounts of data, draw intelligent conclusions, and solve difficult issues, artificial neural networks could revolutionize several industries. Two cardiac illnesses were assessed in this study using a multilayer perceptron artificial neural network that incorporated a genetic algorithm and an error-back propagation mechanism. The ability of artificial neural networks to handle consecutive time series data is crucial for optimizing resources in smart electronic health systems, especially with the increasing volume of patient information and the broad use of electronic clinical records. This requires the creation of more accurate predictive models. Through the use of Internet of Things (IoT) sensors, the proposed system gathers data, which is then used to do predictive analytics on patient history-related electronic clinical data saved in the cloud. A smart healthcare system that uses Mu-LTM (multidirectional long-term memory) to accurately monitor and predict the risk of heart disease has a coverage error of 97.94 %, an accuracy of 97.89 %, a sensitivity of 97.96 %, and a specificity of 97.99 %. In comparison to other smart heart disease prediction systems, the F1-score of 97.95 % and precision of 97.71 % is very good.
ABSTRACT
Mutations in the DDHD2 (DDHD domain containing 2) gene cause autosomal recessive spastic paraplegia type 54 (SPG54), a rare neurodegenerative disorder characterized by the early childhood onset of progressive spastic paraplegia. DDHD2 is reported as the principal brain triacylglycerol (TAG) lipase whose dysfunction causes massive lipid droplet (LD) accumulation in the brains of SPG54 patients. However, the precise functions of DDHD2 in regulating LD catabolism are not yet fully understood. In a recent study, we demonstrate that DDHD2 interacts with multiple members of the Atg8-family proteins (MAP1LC3/LC3s, GABARAPs), which play crucial roles in lipophagy. DDHD2 possesses two LC3-interacting region (LIR) motifs that contribute to its LD-eliminating activity. Moreover, DDHD2 enhances the colocalization between LC3B and LDs to promote lipophagy. LD·ATTEC, a compound that tethers LC3 to LDs to enhance their macroautophagic/autophagic clearance, effectively counteracts DDHD2 deficiency-induced LD accumulation. These findings provide insights into the dual functions of DDHD2 as a TAG lipase and cargo receptor for lipophagy in neuronal LD catabolism, and also suggest a potential therapeutic approach for treating SPG54 patients.
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Aromatic sulfones are the prevailing scaffolds in pharmaceutical and material sciences. However, compared to their widespread application, the selective deuterium labeling of these structures is restricted due to their electron-deficient properties. This study presents two comprehensive strategies for the deuteration of aromatic sulfones. The base-promoted deuteration uses DMSO-d6 as the deuterium source, resulting in a rapid H/D exchange within 2 h. Meanwhile, a silver-catalyzed protocol offers a much milder option by using economical D2O to furnish the labeled sulfones.
ABSTRACT
Although sulfonation plays crucial roles in various biological processes and is frequently utilized in medicinal chemistry to improve water solubility and chemical diversity of drug leads, it is rare and underexplored in ribosomally synthesized and post-translationally modiï¬ed peptides (RiPPs). Biosynthesis of RiPPs typically entails modification of hydrophilic residues, which substantially increases their chemical stability and bioactivity, albeit at the expense of reducing water solubility. To explore sulfonated RiPPs that may have improved solubility, we conducted co-occurrence analysis of RiPP class-defining enzymes and sulfotransferase (ST), and discovered two distinctive biosynthetic gene clusters (BGCs) encoding both lanthipeptide synthetase (LanM) and ST. Upon expressing these BGCs, we characterized the structures of novel sulfonated lanthipeptides and determined the catalytic details of LanM and ST. We demonstrate that SslST-catalyzed sulfonation is leader-independent but relies on the presence of A ring formed by LanM. Both LanM and ST are promiscuous towards residues in the A ring, but ST displays strict regioselectivity toward Tyr5. The recognition of cyclic peptide by ST was further discussed. Bioactivity evaluation underscores the significance of the ST-catalyzed sulfonation. This study sets up the starting point to engineering the novel lanthipeptide STs as biocatalysts for hydrophobic lanthipeptides improvement.
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MicroRNAs (miRNAs) are highly conserved endogenous single-stranded non-coding RNA molecules that play a crucial role in regulating gene expression to maintain normal physiological functions in fish. Nevertheless, the specific physiological role of miRNAs in lower vertebrates, particularly in comparison to mammals, remains elusive. Additionally, the mechanisms underlying the control of antiviral responses triggered by viral stimulation in fish are still not fully understood. In this study, we investigated the regulatory impact of miR-1388 on the signaling pathway mediated by IFN regulatory factor 3 (IRF3). Our findings revealed that following stimulation with the viral analog poly(I:C), the expression of miR-1388 was significantly upregulated in primary immune tissues and macrophages. Through a dual luciferase reporter assay, we corroborated a direct targeting relationship between miR-1388 and tumor necrosis factor receptor (TNFR)-associated factor 3 (TRAF3). Furthermore, our study demonstrated a distinct negative post-transcriptional correlation between miR-1388 and TRAF3. We observed a significant negative post-transcriptional regulatory association between miR-1388 and the levels of antiviral genes following poly(I:C) stimulation. Utilizing reporter plasmids, we elucidated the role of miR-1388 in the antiviral signaling pathway activated by TRAF3. By intervening with siRNA-TRAF3, we validated that miR-1388 regulates the expression of antiviral genes and the production of type I interferons (IFN-Is) through its interaction with TRAF3. Collectively, our experiments highlight the regulatory influence of miR-1388 on the IRF3-mediated signaling pathway by targeting TRAF3 post poly(I:C) stimulation. These findings provide compelling evidence for enhancing our understanding of the mechanisms through which fish miRNAs participate in immune responses.
Subject(s)
Carps , MicroRNAs , Poly I-C , TNF Receptor-Associated Factor 3 , Animals , MicroRNAs/genetics , MicroRNAs/metabolism , Poly I-C/pharmacology , Carps/genetics , Carps/metabolism , Carps/virology , TNF Receptor-Associated Factor 3/genetics , TNF Receptor-Associated Factor 3/metabolism , Down-Regulation/drug effects , Down-Regulation/genetics , Interferon Regulatory Factor-3/metabolism , Interferon Regulatory Factor-3/genetics , Gene Expression Regulation/drug effects , Fish Proteins/genetics , Fish Proteins/metabolism , Signal TransductionABSTRACT
Previous findings have suggested a close association between oxygen vacancies in SnO2 and charge carrier recombination as well as perovskite decomposition at the perovskite/SnO2 interface. Underlying the fundamental mechanism holds great significance in achieving a more favorable balance between the efficiency and stability. In this study, we prepared three SnO2 samples with different oxygen vacancy concentrations and observed that a low oxygen vacancy concentration is conducive to long-term device stability. Iodide ions were observed to easily diffuse into regions with high oxygen vacancies, thereby speeding up the deprotonation of FAI, as made evident by the detection of the decomposition product formamide. In contrast, a high oxygen vacancy concentration in SnO2 could prevent hole injection, leading to a decrease in interfacial recombination losses. To suppress this decomposition reaction and address the trade-off, we designed a bilayer SnO2 structure to ensure highly efficient carrier transport still while maintaining a chemically inert surface. As a result, an enhanced efficiency of 25.06% (certified at 24.55% with an active area of 0.09 cm2 under fast scan) was achieved, and the extended operational stability maintained 90% of their original efficiency (24.52%) after continuous operation for nearly 2000 h. Additionally, perovskite submodules with an active area of 14 cm2 were successfully assembled with a PCE of up to 22.96% (20.09% with an aperture area).
ABSTRACT
Objective:To evaluate the diagnostic efficacy of traditional radiomics, deep learning, and deep learning radiomics in differentiating normal and inner ear malformations on temporal bone computed tomographyï¼CTï¼. Methods:A total of 572 temporal bone CT data were retrospectively collected, including 201 cases of inner ear malformation and 371 cases of normal inner ear, and randomly divided into a training cohortï¼n=458ï¼ and a test cohortï¼n=114ï¼ in a ratio of 4â¶1. Deep transfer learning features and radiomics features were extracted from the CT images and feature fusion was performed to establish the least absolute shrinkage and selection operator. The CT results interpretated by two chief otologists from the National Clinical Research Center for Otorhinolaryngological Diseases served as the gold standard for diagnosis. The model performance was evaluated using receiver operating characteristicï¼ROCï¼, and the accuracy, sensitivity, specificity, and other indicators of the models were calculated. The predictive power of each model was compared using the Delong test. Results:1 179 radiomics features were obtained from traditional radiomics, 2 048 deep learning features were obtained from deep learning, and 137 features fusion were obtained after feature screening and fusion of the two. The area under the curveï¼AUCï¼ of the deep learning radiomics model on the test cohort was 0.964 0ï¼95%CI 0.931 4-0.996 8ï¼, with an accuracy of 0.922, sensitivity of 0.881, and specificity of 0.945. The AUC of the radiomics features alone on the test cohort was 0.929 0ï¼95%CI 0.882 2-0.974 9ï¼, with an accuracy of 0.878, sensitivity of 0.881, and specificity of 0.877. The AUC of the deep learning features alone on the test cohort was 0.947 0ï¼95%CI 0.898 2-0.994 8ï¼, with an accuracy of 0.913, sensitivity of 0.810, and specificity of 0.973. The results indicated that the prediction accuracy and AUC of the deep learning radiomics model are the highest. The Delong test showed that the differences between any two models did not reach statistical significance. Conclusion:The feature fusion model can be used for the differential diagnosis of normal and inner ear malformations, and its diagnostic performance is superior to radiomics or deep learning models alone.
Subject(s)
Deep Learning , Ear, Inner , Temporal Bone , Tomography, X-Ray Computed , Humans , Temporal Bone/diagnostic imaging , Temporal Bone/abnormalities , Ear, Inner/diagnostic imaging , Ear, Inner/abnormalities , Retrospective Studies , Tomography, X-Ray Computed/methods , Male , Female , Sensitivity and Specificity , ROC Curve , RadiomicsABSTRACT
Enhanced protein synthesis is a crucial molecular mechanism that allows cancer cells to survive, proliferate, metastasize, and develop resistance to anti-cancer treatments, and often arises as a consequence of increased signaling flux channeled to mRNA-bearing eukaryotic initiation factor 4F (eIF4F). However, the post-translational regulation of eIF4A1, an ATP-dependent RNA helicase and subunit of the eIF4F complex, is still poorly understood. Here, we demonstrate that IBTK, a substrate-binding adaptor of the Cullin 3-RING ubiquitin ligase (CRL3) complex, interacts with eIF4A1. The non-degradative ubiquitination of eIF4A1 catalyzed by the CRL3IBTK complex promotes cap-dependent translational initiation, nascent protein synthesis, oncogene expression, and cervical tumor cell growth both in vivo and in vitro. Moreover, we show that mTORC1 and S6K1, two key regulators of protein synthesis, directly phosphorylate IBTK to augment eIF4A1 ubiquitination and sustained oncogenic translation. This link between the CRL3IBTK complex and the mTORC1/S6K1 signaling pathway, which is frequently dysregulated in cancer, represents a promising target for anti-cancer therapies.
Subject(s)
Eukaryotic Initiation Factor-4A , Mechanistic Target of Rapamycin Complex 1 , Protein Biosynthesis , Ribosomal Protein S6 Kinases, 70-kDa , Signal Transduction , Ubiquitination , Animals , Humans , Mice , Cell Line, Tumor , Eukaryotic Initiation Factor-4A/metabolism , Eukaryotic Initiation Factor-4A/genetics , Mechanistic Target of Rapamycin Complex 1/metabolism , Mechanistic Target of Rapamycin Complex 1/genetics , Ribosomal Protein S6 Kinases, 70-kDa/metabolism , Ribosomal Protein S6 Kinases, 70-kDa/geneticsABSTRACT
The behavior of As is closely related to trans(formation) of ferrihydrite, which often coprecipitates with extracellular polymeric substances (EPS), forming EPS-mineral aggregates in natural environments. While the effect of EPS on ferrihydrite properity, mineralogy reductive transformation, and associated As fate in sulfate-reducing bacteria (SRB)-rich environments remains unclear. In this research, ferrihydrite-EPS aggregates were synthesized and batch experiments combined with spectroscopic, microscopic, and geochemical analyses were conducted to address these knowledge gaps. Results indicated that EPS blocked micropores in ferrihydrite, and altered mineral surface area and susceptibility. Although EPS enhanced Fe(III) reduction, it retarded ferrihydrite transformation to magnetite by inhibiting Fe atom exchange in systems with low SO42-. As a result, 16% of the ferrihydrite was converted into magnetite in the Fh-0.3 treatment, and no ferrihydrite transformation occurred in the Fh-EPS-0.3 treatment. In systems with high SO42-, however, EPS promoted mackinawite formation and increased As mobilization into the solution. Additionally, the coprecipitated EPS facilitated As(V) reduction to more mobilized As(III) and decreased conversion of As into the residual phase, enhancing the potential risk of As contamination. These findings advance our understanding on biogeochemistry of elements Fe, S, and As and are helpful for accurate prediction of As behavior.