Search Results (409)

Resistance to cytarabine (Ara-C) remains a major obstacle to the successful treatment of acute myeloid leukemia (AML). Therefore, modulating Ara-C resistance is indispensable for improving clinical outcomes. We previously demonstrated that sodium caseinate (SC), a salt derived from casein, the principal milk protein, inhibits proliferation and modulates the expression of Ara-C resistance-related genes in chemoresistant cells. However, it remains unclear whether the combination of SC with antineoplastic agents enhances apoptosis, modulates chemoresistance-related genes, and prolongs the survival of tumor-bearing mice implanted with chemoresistant cells. Here, we investigated the effects of SC in combination with Ara-C or daunorubicin (DNR) on cell proliferation, apoptosis, the expression of chemoresistance-associated genes, and the survival of tumor-bearing mice. Crystal violet assays, quantitative reverse transcription polymerase chain reaction (qRT-PCR), immunofluorescence, flow cytometry, and Kaplan–Meier survival curves were used to evaluate the effects of combinations in chemoresistant cells. We demonstrate that the IC₂₅ concentration of SC, when combined with antileukemic agents, increases the sensitivity of chemoresistant WEHI-CR50 cells to Ara-C by downregulating SIRT1 and MDR1, upregulating the expression of ENT1 and dCK, enhancing apoptosis, and prolonging the survival of WEHI-CR50 tumor-bearing mice. Our data suggest that SC in combination with antileukemic agents could be an effective adjuvant for Ara-C-resistant AML. Full article

A State of Health (SOH) estimation of lithium-ion batteries is a core function of battery management systems, directly affecting the safe operation, lifetime prediction, and economic efficiency of batteries. However, existing methods still face challenges in balancing feature robustness and model generalization ability; for instance, some studies rely on features whose physical correlation with SOH lacks strict verification, or the models struggle to simultaneously capture the temporal dynamics of health factors and nonlinear mapping relationships. To address this, this paper proposes an SOH estimation method based on incremental capacity (IC) curves and a Temporal Convolutional Network—Relevance Vector Machine (TCN-RVM) model, with core innovations reflected in two aspects. Firstly, five health factors are extracted from IC curves, and the strong correlation between these features and SOH is verified using both Pearson and Spearman coefficients, ensuring the physical rationality and statistical significance of feature selection. Secondly, the TCN-RVM model is constructed to achieve complementary advantages. The dilated causal convolution of TCN is used to extract temporal local features of health factors, addressing the insufficient capture of long-range dependencies in traditional models; meanwhile, the Bayesian inference framework of RVM is integrated to enhance the nonlinear mapping capability and small-sample generalization, avoiding the overfitting tendency of complex models. Experimental validation is conducted using the lithium-ion battery dataset from the University of Maryland. The results show that the mean absolute error of the SOH estimation using the proposed method does not exceed 0.72%, which is significantly superior to comparative models such as CNN-GRU, KELM, and SVM, demonstrating higher accuracy and reliability compared with other models. Full article

Accurate and reliable detection of coal mine gases is the key to ensuring the safe service of coal mine production. Fourier Transform Infrared (FTIR) spectroscopy, due to its high sensitivity, non-destructive nature, and potential for online monitoring, has emerged as a key technique in gas detection. However, the complex underground environment often causes baseline drift in IR spectra. Furthermore, the variety of gas species and uneven distribution of concentrations make it difficult to achieve precise and reliable online analysis using existing quantitative methods. This paper aims to perform a quantitative analysis of coal mine gases by FTIR. It utilized the adaptive smoothness parameter penalized least squares method to correct the drifted spectra. Subsequently, based on the infrared spectral distribution characteristics of coal mine gases, they could be classified into gases with mutually distinct absorption peaks and gases with overlapping absorption peaks. For gases with distinct absorption peaks, three spectral lines, including the absorption peak and its adjacent troughs, were selected for quantitative analysis. Spline fitting, polynomial fitting, and other curve fitting methods are used to establish a functional relationship between characteristic parameters and gas concentration. For gases with overlapping absorption peaks, a wavelength selection method bassed on the impact values of variables and population analysis was applied to select variables from the spectral data. The selected variables were then used as input features for building a model with a backpropagation (BP) neural network. Finally, the proposed method was validated using standard gases. Experimental results show detection limits of 0.5 ppm for CH₄, 1 ppm for C₂H₆, 0.5 ppm for C₃H₈, 0.5 ppm for n-C₄H₁₀, 0.5 ppm for i-C₄H₁₀, 0.5 ppm for C₂H₄, 0.2 ppm for C₂H₂, 0.5 ppm for C₃H₆, 1 ppm for CO, 0.5 ppm for CO₂, and 0.1 ppm for SF₆, with quantification limits below 10 ppm for all gases. Experimental results show that the absolute error is less than 0.3% of the full scale (F.S.) and the relative error is within 10%. These results demonstrate that the proposed infrared spectral quantitative analysis method can effectively analyze mine gases and achieve good predictive performance. Full article

The inevitable decline in battery performance presents a major barrier to its widespread industrial application. Adaptive and accurate estimation of battery capacity is paramount for battery operation, maintenance, and residual value evaluation. In this paper, we propose a novel battery capacity estimation method based on an approximate open circuit voltage curve. The proposed method is rigorously tested using both lithium–iron–phosphate (LFP) and nickel–cobalt–manganese (NCM) battery packs at multiple charging rates under varied aging conditions. To further enhance capacity estimation accuracy, a voltage correction strategy is implemented utilizing the incremental capacity (IC) curve. This strategy also verifies the potential benefits of increasing the charging rate to shorten the overall test duration. Eventually, the capacity estimation error is consistently controlled within 2%. With optimal state of charge (SOC) interval selection, the estimation error can be further reduced to 1%. Clearly, our proposed method exhibits excellent compatibility across diverse battery materials and degradation states. This adaptability holds substantial scientific value and practical importance. It contributes to the safe and economic utilization of Li-ion batteries throughout their entire lifespan. Full article

This study aims to predict the purpose of the use of IC card data in LRT immediately after its opening by means of a questionnaire survey and to understand the changes in the number of commuters to better understand the growth in LRT commuter ridership, which has not been fully clarified in Japan. Furthermore, to assess long-term commuter retention for LRT systems, the analysis revealed the following three points. First, a discriminant analysis based on a national PT survey revealed that commuting and leisure or business activities can be classified with high accuracy. Second, it was found that commuter numbers increased immediately after opening, while the number of leisure or business users decreased in the first few months after opening and then leveled off. Third, the increase in the number of commuters was modeled using a logistic curve, and the annual rate of change in ridership was predicted to be less than 1% in the first three to four years after opening. Full article

TXS 0506+056 is a blazar associated with neutrino events. The study on its variation mechanics and periodicity analysis is meaningful to understand other BL Lac objects. The local cross-correlation function (LCCF) analysis presents a 3$\sigma$ correlation in both the $\gamma$-ray versus optical and optical versus radio light curves. The time lag analysis suggests that the optical and $\gamma$-ray band share the same emission region, located upstream of the radio band in the jet. We use both the weighted wavelet Z-transform and generalized Lomb–Scargle methods to analyze the periodicity. We find two plausible quasi-periodic oscillations (QPOs) at ${506}_{-56}^{+133}$ days and ${175}_{-7}^{+15}$ days for the light curve of the optical band. For the $\gamma$-ray band, we find that the spectrum varies with the softer when brighter (SWB) trend, which could be explained naturally if a stable very high energy component exists. For the optical band, TXS 0506+056 exhibits a harder when brighter (HWB) trend. We discover a trend transition from HWB to SWB in the X-ray band, which could be modeled by the shift in peak frequency assuming that the X-ray emission is composed of the synchrotron and the inverse Compton (IC) components. The flux correlations of $\gamma$-ray and optical bands behave anomalously during the period of neutrino events, indicating that there are possible other hadronic components associated with neutrino. Full article

How to use efficient and accurate methods to estimate the capacity of lithium batteries has always been an important research topic. Traditional capacity estimation methods are time-consuming and require strict experimental conditions, making them unsuitable for real-time applications. This article introduces the concept of the inflection point of the charge/discharge curve in the SOC-V curve and proposes a fast estimation method for battery capacity by combining the advantages of the IC curve peak and SOC inflection point methods. By analyzing the charge and discharge data of grouped batteries, it was found that there is a certain correspondence between the inflection point of the SOC-V curve and the peak point of the IC curve. This relationship remains stable during battery aging and can provide a reliable basis for battery SOH evaluation, further improving the estimation accuracy of SOH. This method significantly reduces experimental time, is more suitable for practical applications, and provided an efficient and practical technical means for battery performance evaluation. Full article

The development of lightweight de-icing equipment for partial transmission lines in a microtopography area has become a hot research topic. However, the existing local line de-icing methods pay less attention to the mechanical damage caused by unequal tension on the tower, and there is a lack of safe de-icing strategies. This study has proposed a methodology integrating an orthogonal experimental design and finite element mechanical analysis to assess the impact of localized line de-icing on the structural stability of transmission tower-line systems. Taking the ±800 kV transmission line as an example, the refined finite element model of the transmission tower-line system has been established, the influence of each conductor and ground wire defrosting on the tower has been analyzed, and a scientific de-icing strategy has been formulated. Thus, the critical ice thickness and wind speed curves for tower failure have been calculated. The research results show that the de-icing of conductor 1, 5, 6, and ground wires 11 and 12 has a higher impact on the failure of the entire tower-line system. Ice melting on the windward side and ice covering on the leeward side will cause the unbalanced tension of the tower to be greater. The findings provide actionable guidelines for the formulation of a transmission line de-icing strategy and reduce the damage caused by ice. Full article

Glaciers worldwide are in retreat, and their meltwater can modulate mountain aquifers. We examined whether mass loss of the Juncal Norte Glacier (central Chile) has affected groundwater storage in the Juncal River basin between 1990 and 2022. Recession-curve modeling of daily streamflow shows no statistically significant trend in basin-scale groundwater reserves (τ = 0.06, p > 0.05). In contrast, glacier volume declined significantly (−3.8 hm³/yr, p < 0.05), and precipitation at the nearby Riecillos station fell sharply during the 2008–2017 megadrought (p < 0.05) but exhibited no significant change beforehand. Given the simultaneous decreases in meteoric inputs (rain + snow) and glacier mass, one would expect groundwater storage to decline; its observed stability therefore suggests that enhanced glacier-melt recharge may be temporarily offsetting drier conditions. Isotopic evidence from comparable Andean catchments supports such glacio-groundwater coupling, although time lags of months to years complicate detection with recession models alone. Hence, while our results do not yet demonstrate a direct glacier–groundwater link, they are consistent with the hypothesis that ongoing ice loss is buffering aquifer storage. Longer records and tracer studies are required to verify this mechanism and to inform sustainable water resources planning. Full article

This study, based on the vessel position data of pump-suction beam trawlers and the integrated species distribution model (ISDM), deeply analyzes the spatio-temporal distribution characteristics of the habitat of Antarctic krill and the contributions of key environmental factors. The Convolutional Neural Network–attention model (CNN–attention model) was used to identify the fishing status of the vessel position data of Norwegian pump-suction beam trawlers for Antarctic krill during the fishing seasons from 2021 to 2023. Variables of marine environment, including sea surface temperature (SST), sea surface height (SSH), chlorophyll concentration (CHL), sea ice concentration (SIC), sea surface salinity (SSS), and spatial factor Geographical Offshore Linear Distance (GLD) were combined and input into the ISDM for simulating and predicting the spatial distribution of the habitat. The model results show that the Area Under the Curve (AUC) and True Skill Statistic (TSS) indices for all months exceed 0.9, with an average AUC of 0.997 and a TSS of 0.973, indicating extremely high accuracy of the model in habitat prediction. Further analysis of environmental factors reveals that Geographical Offshore Linear Distance (GLD) and chlorophyll concentration (CHL) are the main factors affecting habitat suitability, contributing 34.9% and 25.2%, respectively, and their combined contribution exceeds 60%. In addition, factors such as sea surface height (SSH), sea surface temperature (SST), sea ice concentration (SIC), and sea surface salinity (SSS) have impacts on the habitat distribution to varying degrees, and each factor exhibits different suitability response characteristics in different seasons and sub-regions. There is no significant correlation between the habitat area of Antarctic krill and catch (p > 0.05), while there is a significant positive correlation between the fishing duration and the catch (p < 0.001), indicating that a longer fishing duration can effectively increase the Antarctic krill catch. Full article

The declining trend of battery aging has strong nonlinearity and volatility, which poses great challenges to the prediction of battery’s state of health (SOH). In this research, an innovative framework is initially put forward for SOH prediction. First, partial incremental capacity analysis (PICA) is carried out to analyze the performance degradation within a specific voltage range. Subsequently, the height of the peak, the position of the peak, and the area beneath the peak of the IC curves are retrieved and used as health features (HFs). Moreover, improved ensemble empirical mode decomposition based on fractal dimension (FEEMD) is first proposed and utilized to decompose HFs to reduce the nonlinearity and fluctuations. Additionally, a bidirectional gated recurrent unit with an attention mechanism (BiGRU-AM) is constructed for the prognosis of these sub-layers. Finally, the effectiveness and robustness of the proposed prognosis framework are validated using two battery datasets. The results of three groups of comparative experiments demonstrate that the maximum root mean squared error (RMSE) and mean absolute error (MAE) values reach merely 0.55% and 0.59%, respectively. This further demonstrates that the proposed FEEMD outperforms other benchmark models and can offer a reliable foundation for the health prognosis of lithium-ion batteries. Full article

Background/Objectives: A case-control study was conducted to determine the association of the −238 G>A and −308 G>A TNF-alpha (TNFA) promoter polymorphisms with mRNA and protein expression in 180 Systemic Lupus Erythematosus (SLE) patients and 186 control subjects (CS) from western Mexico. Methods: Genotyping was performed using the PCR-RFLP method. TNFA mRNA expression was assessed by real-time quantitative PCR, and soluble TNF-α (sTNF-α) levels were quantified by ELISA. For comparison groups, Chi-square, Mann–Whitney U, or Kruskal–Wallis tests were used. Spearman’s rank correlation coefficient determined the correlation between variables. The Area Under the Curve was used to determine the diagnosing performance of sTNF-α. Results: No differences were found in the genotype distribution of −238 G>A and −308 G>A TNFA polymorphisms between SLE patients and CS. However, the −238A allele was associated with increased SLE susceptibility (OR 1.18 CI 95% 1.02–3.50, p = 0.037). Also, logistic regression analysis showed that LN risk was significantly higher in carriers of the −308A allele (OR 3.11 IC95% 1.15–6.43; p = 0.002). On the other hand, the TNFA mRNA expression was 3.3-fold higher in SLE compared to CS. SLE patients with −308 GG genotype showed higher TNFA mRNA expression compared to GA+AA genotype carriers (p < 0.01). Regarding sTNFa levels, SLE patients showed higher concentration than CS, mainly in lupus nephritis (LN), with a weak negative correlation with estimated Glomerular Filtration Rate and an acceptable accuracy for diagnosing SLE and LN, with areas under the curve of 0.61 and 0.65, respectively. Conclusions: The −238 A allele and −308 A allele of the TNFA gene are linked to a higher risk of susceptibility to SLE and LN in the western Mexican population. Additionally, SLE patients exhibited increased TNF-alpha gene expression and sTNF-α, particularly in LN, demonstrating acceptable diagnostic performance. Full article

Background and Objectives: Osteosarcoma is a primary malignant bone tumor characterized by the proliferation of malignant mesenchymal cells and primarily affects children and adolescents. Hesperidin (Hes) interacts with various cellular targets and inhibits cancer cell proliferation by inducing apoptosis. However, the precise mechanisms underlying Hes-induced cell death in osteosarcoma cells remain unclear. This study aimed to investigate the effects of Hes and cisplatin (Cis) on the Bax/Bcl-2 apoptotic pathway in osteosarcoma cells. Materials and Methods: The human osteosarcoma cell line U2OS (Uppsala 2 Osteosarcoma) was treated with IC₅₀ concentrations of Hes and Cis for 48 h. Changes in the mRNA expression levels of Bax, Bcl-2, Caspase-3, and Survivin—key regulators of apoptosis—were analyzed using quantitative real-time PCR (qPCR). The synergistic and/or antagonistic interactions of the Hes and Cis combination were evaluated using Combenefit v2.021 software (Cambridge, UK). Results: The dose–response curve for Hes revealed a gradual reduction in cell viability, with an IC₅₀ value of 106 µM, while the IC₅₀ value for Cis was 4.83 µM. The levels of the inflammatory cytokines IL-1β, TNF-α, and IFN-γ were significantly decreased in the treatment groups compared to the control (p = 0.01). IL-6 levels also showed a marked decrease, particularly in the Hes and Cis groups, with high statistical significance (p = 0.002). Treatment with Hes and Cis significantly upregulated the mRNA expression of Bax and Caspase-3, while significantly downregulating Bcl-2 and Survivin mRNA levels (p < 0.05). Notably, Bax expression was highest in the Hes + Cis combination group. The combination treatment exhibited enhanced cytotoxicity, especially at higher concentrations, indicating a synergistic effect between the two compounds. Conclusions: This study is the first to demonstrate that Hes induces apoptosis in U2OS osteosarcoma cells and that its combination with Cis may enhance anticancer efficacy by activating apoptosis-related cell death pathways. Given the growing focus on combination therapies and cell death mechanisms in cancer research, these findings provide valuable insights into potential novel strategies for osteosarcoma treatment. Full article

Background: Human African trypanosomiasis (HAT), caused by Trypanosoma brucei, is a neglected tropical disease with limited treatments, highlighting the pressing need for new drugs. Cell division cycle-2-related kinase 12 (CRK12), a pivotal protein involved in the cell cycle regulation of T. brucei, has emerged as a promising therapeutic target for HAT, yet effective CRK12 inhibitors remain lacking. Methods: An integrated strategy combining computational modeling, virtual screening, molecular dynamics (MD) simulations, and experimental validation was adopted to discover potential inhibitors against CRK12. By using the predicted and refined 3D structure of CRK12 from AlphaFold2 and MD simulation, over 1.5 million compounds were screened based on multiple-scale molecular docking, and 26 compounds were selected for evaluation of biological activity based on anti-T. brucei bioassays. Dose–response curves were generated for the most potent inhibitors, and the interaction mechanism between the top four compounds and CRK12 was explored by MD simulations and MM/GBSA binding free energy analysis. Results: Of the 26 compounds, six compounds demonstrated sub-micromolar to low-micromolar IC₅₀ values (0.85–3.50 µM). The top four hits, F733-0072, F733-0407, L368-0556, and L439-0038, exhibited IC₅₀ values of 1.11, 1.97, 0.85, and 1.66 µM, respectively. Binding free energy and energy decomposition analyses identified ILE335, VAL343, PHE430, ALA433, and LEU482 as hotspot residues for compound binding. Hydrogen bonding analysis demonstrated that these compounds can form stable hydrogen bonds with the hinge residue ALA433, ensuring their stable binding within the active site. Conclusions: This study establishes a robust and cost-effective pipeline for CRK12 inhibitor discovery, identifying several novel inhibitors demonstrating promising anti-HAT activity. The newly discovered scaffolds exhibit structural diversity distinct from known CRK12 inhibitors, providing valuable lead compounds for anti-trypanosomal drug development. Full article

Diclofenac, a nonsteroidal anti-inflammatory drug widely used worldwide, has been detected in waterbodies at concentrations ranging from ng L⁻¹ to µg L⁻¹. Although diclofenac is not a persistent compound, aquatic organisms may be exposed to this drug for extended periods due to its incorporation into the environment by continuous release from hospitals and municipal discharges. This study aimed to evaluate the toxic effects of diclofenac on the microalga Pseudokirchneriella subcapitata, the cladoceran Daphnia curvirostris, and zebrafish embryos (Danio rerio). Toxicity bioassays for the microalga were performed according to the OECD 201 protocol with diclofenac concentrations of 0, 6.25, 12.5, 25, 50, 75, and 100 mg L⁻¹. For the determination of acute toxicity in the cladoceran (48 h), concentrations of 0, 10, 20, 30, 40, 50, and 60 mg L⁻¹ were tested; in subchronic bioassays, the effect of the drug on the reproductive parameters of D. curvirostris was determined for 21 days with sublethal concentrations of 10.3, 14.4, 17.2, and 21.3 mg L⁻¹. Toxicity bioassays on zebrafish embryos were performed according to the OECD 236 protocol, using concentrations of 0, 1, 2, 4, 6, 8, and 10 mg L⁻¹ of diclofenac. The results confirmed the toxic effects of the drug. The IC₅₀ for the microalga was 16.57 mg L⁻¹, while the LC₅₀ for D. curvirostris and D. rerio was 32.29 and 6.27 mg L⁻¹, respectively. In the microalga, chlorophyll-a and carotenoids increased at a concentration of 3.62 mg L⁻¹ of diclofenac; however, chlorophyll-b decreased at the highest drug concentration (13.51 mg L⁻¹). Protein and lipid concentrations in P. subcapitata exposed to all concentrations were higher than in the control. Chronic diclofenac exposure did not affect the survival of D. curvirostris; however, the cumulative progeny and number of clutches significantly decreased, and the age of first reproduction was delayed at all drug concentrations. Protein concentration in D. curvirostris hatchlings was higher at all diclofenac concentrations; in contrast, the amount of lipids and carbohydrates decreased significantly. In D. rerio, the hatching rate decreased by 40, 51.6, and 80% at concentrations of 6, 8, and 10 mg L⁻¹ diclofenac, respectively, and exposure to the drug caused lethal effects such as coagulation at 24 and 48 hpf; sublethal effects such as edema and curved tail were also observed at concentrations of 2 to 10 mg L⁻¹, and the effects increased with increasing concentration up to 144 hpf. The results demonstrate the vulnerability of aquatic organisms to the toxic effects of diclofenac, suggesting that discharging it into water bodies should be regulated to prevent potential ecological impacts on the various trophic levels of freshwater biota. Full article