Phosphorus-based soil prophylactics for managing Pb contamination in soil: Slow-release kinetics and microbiological effects.

Soil remediation poses significant challenges due to its spatial heterogeneity, surpassing the complexities of atmospheric and water remediation. This study introduces an innovative approach to prevent soil heavy metal pollution by developing three phosphorus slow-release heavy metal soil prophylactic agents (SLPs) - Sap-11, Sap-12, and Sap-21. At a liquid-to-solid ratio of 1:20, the three types of SLPs achieve phosphorus sustained slow release amounts of 1.586 g/L, 4.259 g/L, and 1.444 g/L within 30 days, respectively. Over a cultivation period of 120 days, after amendment with the three SLPs, the surface soil demonstrates stabilization capacities for Pb of 29.56 mg/g, 46.24 mg/g, and 25.77 mg/g, respectively, representing enhancements of 283.64 %, 500.12 %, and 250.74 % compared to the control. Firstly, the direct contribution of P (up to 3.778 mg/g) released from SLPs chemically binding with Pb, and secondly, a significant proportion of the indirect contribution originating from the microbial activity and soil organic matter. In summary, SLP emerges as an effective strategy for soil heavy metal management, stabilizing heavy metals by stimulating the soil's inherent physiological and biochemical reactions. This approach provides a practical solution for the application of P-containing materials and introduces novel perspectives for soil heavy metal management strategies.

Effect of the mitochondrial uncoupling agent BAM15 against the Toxoplasma gondii RH strain and Prugniaud strain.

BACKGROUND: Toxoplasmosis is a zoonotic disease caused by the infection of the protozoa Toxoplasma gondii (T. gondii), and safe and effective therapeutic drugs are lacking. Mitochondria, is an important organelle that maintains T. gondii survival, however, drugs targeting mitochondria are lacking. METHODS: The cytotoxicity of BAM15 was detected by CCK-8 and the in vitro effects of BAM15 was detected by qPCR, plaque assay and flow cytometry. Furthermore, the ultrastructural changes of T. gondii after BAM15 treatment were observed by transmission electron microscopy, and further the mitochondrial membrane potential (ΔΨm), ATP level and reactive oxygen species (ROS) of T. gondii after BAM15 treatment were detected. The pharmacokinetic experiments and in vivo infection assays were performed in mice to determine the in vivo effect of BAM15. RESULTS: BAM15 had excellent anti-T. gondii activity in vitro and in vivo with an EC50 value of 1.25 µM, while the IC50 of BAM15 in Vero cells was 27.07 µM. Notably, BAM15 significantly inhibited proliferation activity of T. gondii RH strain and Prugniaud strain (PRU), caused T. gondii death. Furthermore, BAM15 treatment induced T. gondii mitochondrial vacuolation and autolysis by TEM. Moreover, the decrease in ΔΨm and ATP level, as well as the increase in ROS production further confirmed the changes CONCLUSIONS: Our study identifies a useful T. gondii mitochondrial inhibitor, which may also serve as a leading molecule to develop therapeutic mitochondrial inhibitors in toxoplasmosis.'

Effect of the pseudomonas metabolites HQNO on the Toxoplasma gondii RH strain in vitro and in vivo.

Toxoplasmosis is a widespread disease in humans and animals. Currently, toxoplasmosis chemotherapy options are limited due to severe side effects. There is an urgent need to develop new drugs with better efficacy and few side effects. HQNO, a cytochrome bc1 and type II NADH inhibitor in eukaryotes and bacteria, possesses extensive bioactivity. In this study, the cytotoxicity of HQNO was evaluated in Vero cells. The in vitro effects of HQNO were determined by plaque assay and qPCR assay. To determine the in vivo effect of HQNO, pharmacokinetic experiments and in vivo infection assays were performed in mice. The changes in tachyzoites after HQNO exposure were examined by transmission electron microscopy (TEM), MitoTracker Red CMXRos staining, ROS detection and ATP detection. HQNO inhibited T. gondii invasion and proliferation with an EC50 of 0.995 µM. Pharmacokinetic experiments showed that the Cmax of HQNO (20 mg/kg·bw) was 3560 ± 1601 ng/mL (13.73 µM) in healthy BALB/c mouse plasma with no toxicity in vivo. Moreover, HQNO induced a significant decrease in the parasite burden load of T. gondii in mouse peritoneum. TEM revealed alterations in the mitochondria of T. gondii. Further assays verified that HQNO also decreased the mitochondrial membrane potential (ΔΨm) and ATP levels and enhanced the level of reactive oxygen species (ROS) in T. gondii. Hence, HQNO exerted anti-T. gondii activity, which may be related to the damage to the mitochondrial electron transport chain (ETC).

IVIM using convolutional neural networks predicts microvascular invasion in HCC.

OBJECTIVES: The study aimed to investigate the diagnostic performance of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) using convolutional neural networks (CNNs). METHODS: This retrospective study included 114 patients with pathologically confirmed HCC from December 2014 to August 2021. All patients underwent MRI examination including IVIM sequence with 9 b-values preoperatively. First, 9 b-value images were superimposed in the channel dimension, and a b-value volume with a shape of 32 × 32 × 9 dimension was obtained. Secondly, an image resampling method was performed for data augmentation to generate more samples for training. Finally, deep features to predict MVI in HCC were directly derived from a b-value volume based on the CNN. Moreover, a deep learning model based on parameter maps and a fusion model combined with deep features of IVIM, clinical characteristics, and IVIM parameters were also constructed. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance for MVI prediction in HCC. RESULTS: Deep features directly extracted from IVIM-DWI (0.810 (range 0.760, 0.829)) using CNN yielded better performance for prediction of MVI than those from IVIM parameter maps (0.590 (range 0.555, 0.643)). Furthermore, the performance of the fusion model combined with deep features of IVIM-DWI, clinical features (α-fetoprotein (AFP) level and tumor size), and apparent diffusion coefficient (ADC) (0.829 (range 0.776, 0.848)) was slightly improved. CONCLUSIONS: Deep learning with CNN based on IVIM-DWI can be conducive to preoperative prediction of MVI in patients with HCC. KEY POINTS: • Deep learning assessment of IVIM data for prediction of MVI in HCC can overcome the unstable and low performance of IVIM parameters. • Deep learning model based on IVIM performs better than parameter values, clinical features, and deep learning model based on parameter maps. • The fusion model combined with deep features of IVIM, clinical characteristics, and ADC yields better performance for prediction of MVI than the model only based on IVIM.

Determination and pharmacokinetics study of UK-5099 in mouse plasma by LC-MS/MS.

BACKGROUND: UK-5099 is a potent mitochondrial acetone carrier inhibitor, that exhibits anticancer activity. Recently, the anti-Toxoplasma gondii activity of UK-5099 was proposed, and in vivo studies of its pharmacokinetics in BALB/c mice are necessary to further evaluate the clinical effect of UK-5099. METHODS AND RESULTS: A simple and fast high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis method was established and verified in terms of its linearity, matrix effect, accuracy, precision, recovery and stability. The analytes were separated by an Agilent ZORBAX XDB-C18 column (2.1 × 50 mm, 3.5 µm) at 30 °C. A gradient mobile phase consisting of water with 0.1% formic acid (FA) (phase A) and acetonitrile (ACN) (phase B) was delivered at a flow rate of 0.40 mL·min-1 with an injection volume of 5 µL. A good linear response was obtained in a concentration range of 5-5000 ng·mL-1 (r2 = 0.9947). The lower limit of quantification (LLOQ) was 5 ng·mL-1. The extraction recovery of UK-5099 was greater than 95%. The inter- and intra-day accuracy and precision of the method showed relative standard deviations (RSDs) of less than 15%. This method has been successfully applied to the pharmacokinetic evaluation of UK-5099 in mouse plasma. In health mice, the main pharmacokinetic parameters of UK-5099 after intraperitoneal administration were measured using a noncompartmental model, in which the AUC0-t was 42,103 ± 12,072 ng·h·mL-1 and the MRT0-t was 0.857 ± 0.143 h. The peak concentration (Cmax) was 82,500 ± 20,745 ng·h·mL-1, which occurred at a peak time (Tmax) = 0.250 ± 0.000 h. CONCLUSIONS: A fast and sensitive HPLC-MS/MS method was developed, validated and successfully used for the determination of UK-5099 levels in mice after intraperitoneal administration. This study was the first report of the pharmacokinetic parameters of UK-5099 in mice, which will help to further study the administration of UK-5099 in animals and humans.

hsa_circ_0119412 overexpression promotes cervical cancer progression by targeting miR-217 to upregulate anterior gradient 2.

BACKGROUND: Mounting evidence summarizes that circRNA is closely implicated in the development of numerous cancers. Our study aimed to investigate the role of circ_0119412 whose function was not explored in cervical cancer. METHODS: RT-qPCR analysis was utilized for the expression analysis of circ_0119412, miR-217, and anterior gradient 2 (AGR2). CCK-8 assay, transwell assay, and MTT assay were employed to assess cell proliferation, migration, and adhesion, respectively. Animal study was performed to check the role of circ_0119412 in vivo. Bioinformatics analysis was applied to predict the downstream targets of circ_0119412. RIP assay was utilized to examine miRNAs potentially bound by circ_0119412. The interplays between miR-217 and circ_0119412 or AGR2 were validated by dual-luciferase reporter assay. RESULTS: circ_0119412 expression was highly enhanced in cervical tumor tissues and cancer cells. circ_0119412 overexpression aggravated cervical cancer cell proliferation, migration, and adhesion, and its overexpression was also conducive to tumor formation and growth in animal models. AGR2 was upregulated in cervical cancer by the public bioinformatics data. circ_0119412 bound to miR-217, and miR-217 bound to AGR 3'UTR. The promoting effects of circ_0119412 overexpression on cancer cell malignant phenotypes were reversed by miR-217 enrichment. In addition, increased expression of miR-217 suppressed AGR2 expression, thus weakening the functional effects of AGR2. CONCLUSION: circ_0119412 functioned as an oncogenic driver to promote the malignant development of cervical cancer by targeting the miR-217/AGR2 pathway.

An attention-based deep learning model for predicting microvascular invasion of hepatocellular carcinoma using an intra-voxel incoherent motion model of diffusion-weighted magnetic resonance imaging.

The intra-voxel incoherent motion model of diffusion-weighted magnetic resonance imaging (IVIM-DWI) with a series of images with differentb-values has great potential as a tool for detecting, diagnosing, staging, and monitoring disease progression or the response to treatment. The current clinical tumour characterisation using IVIM-DWI is based on the parameter values derived from the IVIM model. On the one hand, the calculation accuracy of such parameter values is susceptible to deviations due to noise and motion; on the other hand, the performance of the parameter values is rather limited with respect to tumour characterisation. In this article, we propose a deep learning approach to directly extract spatiotemporal features from a series ofb-value images of IVIM-DWI using a deep learning network for lesion characterisation. Specifically, we introduce an attention mechanism to select dominant features from specificb-values, channels, and spatial areas of the multipleb-value images for better lesion characterisation. The experimental results for clinical hepatocellular carcinoma (HCC) when using IVIM-DWI demonstrate the superiority of the proposed deep learning model for predicting the microvascular invasion (MVI) of HCC. In addition, the ablation study reflects the effectiveness of the attention mechanism for improving MVI prediction. We believe that the proposed model may be a useful tool for the lesion characterisation of IVIM-DWI in clinical practice.

Enhanced visible-light photocatalysis of clofibric acid using graphitic carbon nitride modified by cerium oxide nanoparticles.

Recently, the emerging pharmaceutical micropollutants have become an environmental concern. Herein, we report an efficient elimination of clofibric acid (CA) using visible light-driven g-C3N4/CeO2 prepared by hydrothermal method. Among the catalysts with different compound ratios, g-C3N4/CeO2-3 (1.2 g g-C3N4 with 3 mmol Ce(NO3)3∙6H2O) exhibited the best photocatalytic performance. The effect of catalyst dosage was investigated and the optimal value was determined as 0.5 g L-1. The effect of initial pH (pH0) showed CA elimination decreased with increasing pH0. The underlying mechanism for CA oxidation was proposed based on synthetical analysis of photoluminescence emission spectra, transient photocurrent responses, electron paramagnetic resonance, chemical quenching experiments and band edge potential of g-C3N4 and CeO2. Photogenerated hole was primarily responsible for CA elimination while singlet oxygen played an auxiliary role. The products of CA oxidation were detected using liquid chromatography mass spectrometry (LC-MS) method and a possible pathway was put forward. Various organics were used as target contaminants to assess photocatalytic performance of g-C3N4/CeO2 heterojunction under acidic and alkaline pH conditions. The analysis of relationship between the oxidation peak potential (EOP) and the reaction rate constant indicated that photocatalysis using as prepared g-C3N4/CeO2-3 heterojunction is apt to oxidize contaminants with electron withdrawing group under acid condition.