Search Results (74)

Background/Objectives: Paclitaxel (PTX) is widely used in the treatment of a variety of solid tumours due to its broad-spectrum anti-tumour activity, but its use in brain gliomas is limited by insufficient blood–brain tumour barrier (BBTB) penetration and systemic toxicity. The aim of this study was to develop a Solutol HS-15-based micellar nanoparticle (PSM) to enhance the brain glioma targeting of PTX and reduce toxicity. Methods: PSMs were prepared by solvent injection and characterised for particle size, encapsulation rate, haemolysis rate and in vitro release properties. A C6 in situ glioma mouse model was used to assess the brain targeting and anti-tumour effects of the PSM by in vivo imaging, tissue homogenate fluorescence analysis and bioluminescence monitoring. Meanwhile, its safety was evaluated by weight monitoring, serum biochemical indexes and histopathological analysis. Results: The particle size of PSMs was 13.45 ± 0.70 nm, with an encapsulation rate of 96.39%, and it demonstrated excellent cellular uptake. In tumour-bearing mice, PSMs significantly enhanced brain tumour targeting with a brain drug concentration 5.94 times higher than that of free PTX. Compared with Taxol, PSMs significantly inhibited tumour growth (terminal luminescence intensity <1 × 10⁶ p/s/cm²/Sr) and did not cause significant liver or kidney toxicity or body weight loss. Conclusions: PSMs achieve an efficient accumulation of brain gliomas through passive targeting and EPR effects while significantly reducing the systemic toxicity of PTX. Its simple preparation process and excellent therapeutic efficacy support its use as a potential clinically translational candidate for glioma treatment. Full article

Wildfires critically affect ecosystems, carbon cycles, and public health. COVID-19 restrictions provided a unique opportunity to study human activity’s role in wildfire regimes. This study presents a comprehensive evaluation of pandemic-induced wildfire regime changes across global fire-prone regions. Using MODIS data (2010–2022), we analyzed fire patterns during the pandemic (2020–2022) against pre-pandemic baselines. Key findings include: (a) A 22% global decline in wildfire hotspots during 2020–2022 compared to 2015–2019, with the most pronounced reduction occurring in 2022; (b) Contrasting regional trends: reduced fire activity in tropical zones versus intensified burning in boreal regions; (c) Stark national disparities, exemplified by Russia’s net increase of 59,990 hotspots versus Australia’s decrease of 60,380 in 2020; (d) Seasonal shifts characterized by December declines linked to mobility restrictions, while northern summer fires persisted due to climate-driven factors. Notably, although climatic factors predominantly govern fire regimes in northern latitudes, anthropogenic ignition sources such as agricultural burning and accidental fires substantially contribute to both fire incidence and associated emissions. The pandemic period demonstrated that while human activity restrictions reduced ignition sources in tropical regions, fire activity in boreal ecosystems during these years exhibited persistent correlations with climatic variables, reinforcing climate’s pivotal—though not exclusive—role in shaping fire regimes. This underscores the need for integrated wildfire management strategies that address both human and climatic factors through regionally tailored approaches. Future research should explore long-term shifts and adaptive management frameworks. Full article

Due to the characteristics of high salt and high acidity of the electrolyte and the chemical reaction between thiourea (Tu) and metal ions, it is still a problem to quickly and accurately detect Tu concentration in copper electrolyte. An improved spectrophotometric method has been proposed by simplifying the extraction steps of the traditional extraction–spectrophotometry and reducing the dosage of extractant and buffer. The improved method, with a favorable R² of 0.9991, great precision of 1.67% and excellent spiked recovery of 102.19%, was not affected by the presence of gelatin and copper ions. Moreover, based on the spectrophotometry, a colorimetric method for rapid detection of Tu concentration in copper electrolyte was proposed. Using the standard color card produced enabled the expeditious determination of the concentration range of Tu in copper electrolyte. Since the gray value of the standard color card is linearly related to the Tu concentration, it is feasible to determine the Tu concentration by measuring the gray value of the test strip, and its accuracy was verified by spectrophotometry. The colorimetric method has satisfactory results in industrial practice. This study provides a novel approach for the rapid detection of Tu concentration in the copper electrolysis industry. Full article

Granular samples are often used to characterize the pore structure of shale. To systematically analyze the influence of particle size on pore characteristics, case studies were performed on two groups of organic-rich deep shale samples. Multiple methods, including small-angle neutron scattering (SANS), low-pressure nitrogen gas adsorption (LP-N₂GA), low-pressure carbon dioxide gas adsorption (LP-CO₂GA), and XRD analysis, were adopted to investigate how the crushing process would affect pore structure parameters and the fractal features of deep shale samples. The research indicates that with the decrease in particle size, the measurements from nitrogen adsorption and SANS experiments significantly increase, with relative effects reaching 95.09% and 51.27%, respectively. However, the impact on carbon dioxide adsorption measurements is minor, with a maximum of only 8.97%. This suggests that the comminution process primarily alters the macropore structure, with limited influence on the micropores. Since micropores contribute the majority of the specific surface area in deep shale, the effect of particle size variation on the specific surface area is negligible, averaging only 16.52%. Shales exhibit dual-fractal characteristics. The distribution range of the mass fractal dimension of the experimental samples is 2.658–2.961, which increases as the particle size decreases. The distribution range of the surface fractal dimension is 2.777–2.834, which decreases with the decrease in particle size. Full article

Shale gas is a critical energy resource, and estimating its ultimate recoverable reserves (EUR) is a key indicator for evaluating the development potential and effectiveness of gas wells. To address the challenges in accurately predicting shale gas EUR, this study analyzed production data from 200 wells in the CN block. Sixteen potential factors influencing EUR were considered, and key geological, engineering, and production factors were identified using Spearman correlation analysis and mutual information methods to exclude highly linearly correlated variables. An attention mechanism was introduced to weight input features prior to model training, enhancing the interpretability of feature contributions. The hyperparameters of the model were optimized using the Rabbit Optimization Algorithm (ROA), and 10-fold cross-validation was employed to improve the stability and reliability of model evaluation, mitigating overfitting and bias. The performance of four machine learning models was compared, and the optimal model was selected. The results indicated that the ROA-CatBoost-AM model exhibited superior performance in both fitting accuracy and prediction effectiveness. This model was subsequently applied for EUR prediction and for identifying the primary factors controlling productivity, providing effective guidance for development practices. The dominant factors and production forecasts determined by the model offer valuable references for optimizing block development strategies. Full article

Background: Colorectal cancer (CRC) is one of the common malignant tumors. Chemotherapeutic agents represented by doxorubicin (DOX) are common adjuvant therapies for patients with advanced CRC. However, DOX suffers from dose-dependent cardiotoxicity and myelosuppression due to a lack of targeting and specificity, which severely limits its clinical application. Methods: Herein, we constructed a zeolitic imidazolate framework-8 (ZIF-8) modified by a novel peptide (LT peptide) to deliver the chemotherapeutic drug doxorubicin (DOX) for the targeted treatment of CRC. Results: In this study, LT-PEG@DOX@ZIF-8 nanoparticles were prepared by a simple method with suitable particle size and zeta potential, which were also capable of pH-responsive drug release. In vitro assays exhibited that LT-PEG@DOX@ZIF-8 nanoparticles were effectively taken up by C26 cells, significantly inhibited cell proliferation, and induced apoptosis. Furthermore, in mice models with colorectal tumors, LT-PEG@DOX@ZIF-8 nanoparticles also displayed specific tumor aggregation and exerted anti-tumor effects to prolong the survival of the mice. Conclusions: In conclusion, LT-PEG@DOX@ZIF-8 provides a promising strategy for the delivery of DOX to effectively treat CRC. Full article

It is important to explore the hot deformation behavior and establish the hot processing map of steel to design and optimize the hot rolling process. In this paper, 50CrVA spring steel was used as the experimental material. Single-pass compression tests were performed at 850–1150 °C and 0.01–5 s⁻¹ on an MMS-300 thermo-mechanical simulation testing machine to investigate the hot deformation behavior and establish the hot processing map. The results show that as the strain rate increases and the deformation temperature decreases, the flow stress of 50CrVA spring steel increases. The constitutive equation of 50CrVA spring steel is $\dot{\epsilon }=1.01\times {10}^{14}{[\sinh (0.0094{\sigma }_p)]}^{4.53}\exp (-{\displaystyle \frac{364,470}{RT}})$. The dynamic recrystallization critical strain model is ${\epsilon }_c=4.19\times {10}^{-3}{Z}^{7.31\times {10}^{-2}}$. A hot processing map of 50CrVA spring steel was constructed to determine the plastic instability region and optimal hot working region. Full article

With the development of shale gas horizontal well-filling technology, by drilling infill wells between wells, the well spacing is continuously reduced to make shale reservoir reconstruction more effective. However, in shale gas reservoirs in China, the problem of inter-well interference is becoming increasingly serious, which not only affects the production of well groups but also causes wellbore damage. Currently, the process of interference in the production process is unclear. This study addresses the inter-well interference issue in deep shale gas reservoirs. An integrated numerical simulation method combining the Discrete Fracture Network, Finite Element Method, and Finite Difference Method is proposed. A comprehensive reservoir numerical model considering the production process is proposed. According to the actual reservoir model parameters and operation parameters, a multi-factor analysis model under multiple production conditions was established. Cumulative gas production and inter-well interference were analyzed. Finally, a field model was established, and the history matching of formation pressure was carried out. According to the history-matching results, the pressure expansion range in the production stage was analyzed. These research results provide a scientific basis and practical suggestions for the effective management and mitigation of inter-well interference and are expected to play an important role in practical engineering applications. Full article

Bivalve mollusks, comprising animals enclosed in two shell valves, are well-adapted to benthic life in many intertidal zones. Clams have evolved the buried lifestyle, which depends on their unique soft tissue structure and their wedge-shaped muscular foot and long extendible siphons. However, molecular mechanisms of adaptative phenotype evolution remain largely unknown. In the present study, we obtain the high-quality chromosome-level genome of Manila clam R. philippinarum, an economically important marine bivalve in many coastal areas. The genome is constructed by the Hi-C assisted assembly, which yields 19 chromosomes with a total of 1.17 Gb and BUSCO integrity of 92.23%. The de novo assembled genome has a contig N50 length of 307.7 kb and scaffold N50 of 59.5 Mb. Gene family expansion analysis reveals that a total of 24 single-copy gene families have undergone the significant expansion or contraction, including E3 ubiquitin ligase and dynein heavy chain. The significant expansion of transposable elements has been also identified, including long terminal repeats (LTR) and non-LTR retrotransposons. The comparative transcriptomics among different clam tissues reveals that extracellular matrix (ECM) receptors and neuroactive ligand receptors may play the important roles in tissue structural support and neurotransmission during their infaunal life. These findings of gene family expansion and tissue-specific expression may reflect the unique soft tissue structure of clams, suggesting the evolution of lineage-specific morphological novelties. The high-quality genome and transcriptome data of R. philippinarum will not only facilitate the genetic studies on clams but will also provide valuable information on morphological novelties in mollusks. Full article

Deep-learning-based (DL-based) seismic inversion has emerged as one of the state-of-the-art research areas in exploration geophysics with the development of artificial intelligence technology. Due to its good portability and high computational efficiency, this method has emerged as a data-driven approach for estimating subsurface properties. However, most of the current DL-based methods rely solely on seismic data, lacking the incorporation of prior information. In addition, these methods are usually performed trace-by-trace, resulting in insufficient horizontal constraints. These limitations make traditional methods less robust, particularly when dealing with high noise levels or limited data. To address these challenges, we propose a multi-input deep learning network for pre-stack inversion, which combines data-driven and model-driven approaches for optimization. The proposed method separately extracts features from the model and data, merging them to improve feature utilization. Moreover, by adopting a 2-D training unit, rather than a trace-by-trace approach, the method improves the horizontal continuity of the results. Tests on synthetic and real seismic data confirmed the robustness and improved stability of the proposed method, even under challenging conditions. This dual-driven approach significantly enhances the reliability of seismic inversion. Full article

Forest fire is one of the dominant disturbances in the forests of Heilongjiang Province, China, and is one of the most rapid response predictors that indicate the impact of climate change on forests. This study calculated the Canadian FWI (Fire Weather Index) and its components from meteorological record over past years, and a linear model was built from the monthly mean FWI and monthly fire numbers. The significance test showed that fire numbers and FWI had a very pronounced correlation, and monthly mean FWI was suitable for predicting the monthly fire numbers in this region. Then FWI and its components were calculated from the SRES (IPCC Special Report on Emission Scenarios) A2 and B2 climatic scenarios, and the linear model was rebuilt to be suitable for the climatic scenarios. The results indicated that fire numbers would increase by 2.98–129.97% and −2.86–103.30% in the A2 and B2 climatic scenarios during 2020–2090, respectively. The monthly variation tendency of the FWI components is similar in the A2 and B2 climatic scenarios. The increasing fire risk is uneven across months in these two climatic scenarios. The monthly analysis showed that the FFMC (Fine Fuel Moisture Code) would increase dramatically in summer, and the decreasing precipitation in summer would contribute greatly to this tendency. The FWI would increase rapidly from the spring fire season to the autumn fire season, and the FWI would have the most rapid increase in speed in the spring fire season. DMC (Duff Moisture Code) and DC (Drought Code) have relatively balanced rates of increasing from spring to autumn. The change in the FWI in this region is uneven in space as well. In early 21st century, the FWI of the north of Heilongjiang Province would increase more rapidly than the south, whereas the FWI of the middle and south of Heilongjiang Province would gradually catch up with the increasing speed of the north from the middle of 21st century. The changes in the FWI across seasons and space would influence the fire management policy in this region, and the increasing fire numbers and variations in the FWI scross season and space suggest that suitable development of the management of fire sources and forest fuel should be conducted. Full article

This study aimed to explore the longitudinal associations between healthy eating habits, resilience, insomnia, and Internet addiction by using a cross-lagged panel analysis of Chinese college students. Overall, 807 Chinese college students completed questionnaires on healthy eating habits, resilience, insomnia, and Internet addiction from August 2020 (time 1, T1) to November 2020 (time 2, T2), and were selected for the data analyses. Healthy eating habits (T1) had significant effects on resilience (T2; β = 0.064, p < 0.05) and insomnia (T2; β = −0.064, p < 0.05), but not Internet addiction (T2; β = −0.028, p > 0.05). Insomnia (T1) negatively predicted resilience (T2; β = −0.098, p < 0.01). Insomnia was bidirectionally associated with Internet addiction (Internet addiction at T1 to insomnia at T2: β = 0.085, p < 0.01; insomnia at T1 to Internet addiction at T2: β = 0.070, p < 0.05). Additionally, Internet addiction (T1) significantly predicted resilience (T2; β = −0.075, p < 0.05). This study further expanded the understanding of the longitudinal associations between healthy eating habits, resilience, insomnia, and Internet addiction, which provided higher-level evidence and important implications for the interventions for reducing college students’ Internet addiction, developing healthy eating habits, and improving resilience and sleep health. Full article

In this study examining the effects of temperature and dissolved oxygen (DO) on arsenic (As) release at the sediment–water interface (SWI), it was found that an increase in temperature promoted the formation of an anaerobic environment and the reduction and desorption of As fractions within the sediments. A temperature of 32 °C was the most favorable condition for As release at the SWI, and low DO conditions aggravated this process. Even under high DO conditions, the release of sediment As was significantly accelerated under high-temperature conditions, allowing dissolved As to rapidly migrate to the overlying water. In this process, the release of As from sediments was a consequence of the transformation of As fractions in the sediments. Full article

Stimulated emission depletion (STED) microscopy, as a popular super-resolution imaging technique, has been widely used in bio-structure analysis and resolving the dynamics of biological processes beyond the diffraction limit. The performance of STED critically depends on the optical properties of the fluorescent probes. Ideally, the probe should process high brightness and good photostability, and exhibit a sensitive response to the depletion beam. Organic dyes and fluorescent proteins, as the most widely used STED probes, suffer from low brightness and exhibit rapid photobleaching under a high excitation power. Recently, luminescent nanoparticles (NPs) have emerged as promising fluorescent probes in biological imaging due to their high brightness and good photostability. STED imaging using various kinds of NPs, including quantum dots, polymer dots, carbon dots, aggregation-induced emission dots, etc., has been demonstrated. This review will comprehensively review recent advances in fluorescent NP-based STED probes, discuss their advantages and pitfalls, and outline the directions for future development. Full article