Factors influencing delayed high-dose methotrexate excretion and its correlation with adverse reactions after treatment in children with malignant hematological tumors.

Background: High-dose methotrexate (HDMTX) is crucial in treating pediatric malignant hematological tumors. However, its use is often complicated by delayed excretion and associated adverse reactions, which can significantly affect treatment outcomes and patient safety. Identifying risk factors is essential for safer, more effective therapy. This study aimed to investigate the influencing factors for delayed excretion and their correlation with adverse reactions in children with malignant hematological tumors after receiving HDMTX chemotherapy. Methods: From April to October 2021, the clinical information of children who had undergone HDMTX chemotherapy and had their blood tested for drug concentration was gathered by the Department of Hematology and Oncology at Shanghai Children's Medical Center. Via univariate and multivariate logistic regression, the factors affecting the delayed excretion of HDMTX were examined, and the relationship between delayed excretion and unfavorable effects in children was determined. Results: This study included 99 patients comprising 199 courses of HDMTX. The occurrence rate of HDMTX delayed excretion was 20.1%. Age ≥9 years and a 24-hour methotrexate (MTX) concentration of 64 µmol/L were independent risk factors for delayed MTX excretion according to multivariate logistic regression analysis (P<0.05). Negative side effects, such as fever, infection, mucositis, gastrointestinal response, and decreased platelet count in children with delayed excretion were statistically significant when compared to those of children with normal excretion. White blood cell reduction, hemoglobin levels below 65 g/L, MTX excretion delay, and concomitant etoposide treatment were all independent risk factors for infection in children. Conclusions: To estimate the risk of delayed MTX excretion during HDMTX therapy, patient laboratory data should be scrutinized, especially for patients ≥9 years or those with a 24-hour MTX concentration of greater than 64 µmol/L.

High-dose methotrexate pharmacokinetics and its impact on prognosis of paediatric acute lymphoblastic leukaemia patients: A population pharmacokinetic study.

This study delivers a comprehensive evaluation of the efficacy and pharmacokinetics of high-dose methotrexate (HDMTX) in a large cohort of Chinese paediatric acute lymphoblastic leukaemia patients. A total of 533 patients were included in the prognostic analysis. An association was observed between lower steady-state MTX concentrations (<56 µmol/L) and poorer outcomes in intermediate-/high-risk (IR/HR) patients. Subgroup analysis further revealed that this relationship between concentrations and prognosis was even more pronounced in patients with MLL rearrangements. In contrast, such an association did not emerge within the low-risk patient group. Additionally, utilizing population pharmacokinetic modelling (6051 concentrations from 815 patients), we identified the significant impact of physiological maturation, estimated glomerular filtration rate, sex and concurrent dasatinib administration on MTX pharmacokinetics. Simulation-based recommendations include a reduced dosage regimen for those with renal insufficiency and a specific 200 mg/kg dosage for infants under 1 year. The findings underscore the critical role of HDMTX in treating IR/HR populations and call for a reassessment of its application in lower-risk groups. An individualized pharmacokinetic dosage regimen could achieve the most optimal results, ensuring the largest proportion of steady-state concentrations within the optimal range.

Neutron penumbral image reconstruction with a convolution neural network using fast Fourier transform.

In Inertial Confinement Fusion (ICF), the asymmetry of a hot spot is an important influence factor in implosion performance. Neutron penumbral imaging, which serves as an encoded-aperture imaging technique, is one of the most important diagnostic methods for detecting the shape of a hot spot. The detector image is a uniformly bright range surrounded by a penumbral area, which presents the strength distribution of hot spots. The present diagnostic modality employs an indirect imaging technique, necessitating the reconstruction process to be a pivotal aspect of the imaging protocol. The accuracy of imaging and the applicable range are significantly influenced by the reconstruction algorithm employed. We develop a neural network named Fast Fourier transform Neural Network (FFTNN) to reconstruct two-dimensional neutron emission images from the penumbral area of the detector images. The FFTNN architecture consists of 16 layers that include a FFT layer, convolution layer, fully connected layer, dropout layer, and reshape layer. Due to the limitations in experimental data, we propose a phenomenological method for describing hot spots to generate datasets for training neural networks. The reconstruction performance of the trained FFTNN is better than that of the traditional Wiener filtering and Lucy-Richardson algorithm on the simulated dataset, especially when the noise level is high as indicated by the evaluation metrics, such as mean squared error and structure similar index measure. This proposed neural network provides a new perspective, paving the way for integrating neutron imaging diagnosis into ICF.

Analysis of bioactive components and synergistic action mechanism of ShuGan-QieZhi Capsule for treating non-alcoholic fatty liver disease.

BACKGROUND: ShuGan-QieZhi capsule (SGQZC) is a traditional Chinese preparation used to treat hyperlipidemia and obesity, even non-alcoholic fatty liver disease (NAFLD). However, its therapeutic effects, main bioactive ingredients, as well as potential mechanisms for NAFLD are still unclear. PURPOSE: To investigate the pharmacological effect, main active ingredients, and mechanisms of SGQZC against high-fat diet (HFD)-induced NAFLD in mice. METHODS: NAFLD models were established by feeding C57BL/6 J mice an HFD for 24 weeks. From the 12th week, HFD-fed mice received daily gavage of either SGQZC or silibinin for 12 weeks. Hepatic hypertrophy parameters, along with hepatic and systemic lipid metabolism changes in NAFLD mice, were assessed. Oil red O and histopathological staining techniques determined lipid accumulation and liver injury severity. qRT-PCR analysis measured the expression of genes tied to liver lipid metabolism and inflammation. HPLC-MS/MS identified the primary components of SGQZC in the serum. Human normal hepatocytes (LO2) and hepatic stellate cells (LX-2) were used to screen SGQZC's bioactive ingredients. Network pharmacological analysis, transcriptomics, and western blotting delved into SGQZC's synergistic mechanisms against NAFLD. RESULTS: SGQZC ameliorated abnormal lipid metabolism and liver hypertrophy in mice with HFD-induced NAFLD, consequently reducing hepatic lipid accumulation, inflammatory cell infiltration, and liver impairment. Eight crucial components of SGQZC were detected in serum using HPLC-MS/MS and were found to effectively attenuate lipid accumulation and inflammation in liver cells. Further investigation indicated that SGQZC modulates MAPK pathway and AKT/NF-κB pathway, subsequently improving lipid metabolism and inflammation. CONCLUSION: SGQZC alleviates NAFLD by synergistically modulating the MAPK-mediated lipid metabolism and inhibiting AKT/NF-κB pathways-mediated inflammation. Our findings reveal the enormous potential of SGQZC for the treatment of NAFLD, providing a possible new clinical therapeutic strategy.

The effect of Shengmai injection in patients with coronary heart disease in real world and its personalized medicine research using machine learning techniques.

Objective: Shengmai injection is a common treatment for coronary heart disease. The accurate dose regimen is important to maximize effectiveness and minimize adverse reactions. We aim to explore the effect of Shengmai injection in patients with coronary heart disease based on real-world data and establish a personalized medicine model using machine learning and deep learning techniques. Methods: 211 patients were enrolled. The length of hospital stay was used to explore the effect of Shengmai injection in a case-control study. We applied propensity score matching to reduce bias and Wilcoxon rank sum test to compare results between the experimental group and the control group. Important variables influencing the dose regimen of Shengmai injection were screened by XGBoost. A personalized medicine model of Shengmai injection was established by XGBoost selected from nine algorithm models. SHapley Additive exPlanations and confusion matrix were used to interpret the results clinically. Results: Patients using Shengmai injection had shorter length of hospital stay than those not using Shengmai injection (median 10.00 days vs. 11.00 days, p = 0.006). The personalized medicine model established via XGBoost shows accuracy = 0.81 and AUC = 0.87 in test cohort and accuracy = 0.84 and AUC = 0.84 in external verification. The important variables influencing the dose regimen of Shengmai injection include lipid-lowering drugs, platelet-lowering drugs, levels of GGT, hemoglobin, prealbumin, and cholesterol at admission. Finally, the personalized model shows precision = 75%, recall rate = 83% and F1-score = 79% for predicting 40 mg of Shengmai injection; and precision = 86%, recall rate = 79% and F1-score = 83% for predicting 60 mg of Shengmai injection. Conclusion: This study provides evidence supporting the clinical effectiveness of Shengmai injection, and established its personalized medicine model, which may help clinicians make better decisions.

Decoupling of nutrient stoichiometry in Suaeda glauca (Bunge) senesced leaves under salt treatment.

The stoichiometry of senesced leaves is pivotal in nutrient cycling and can be significantly influenced by soil salinization, a rising global issue threatening the functionality of ecosystems. However, the impacts of soil salinization on senesced leaf stoichiometry are not fully understood. In this study, we conducted a pot experiment with varying soil salt concentrations to examine their influence on the concentrations and stoichiometric ratios of nitrogen (N), phosphorus (P), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), and zinc (Zn) in the senesced leaves of Suaeda glauca (Bunge). Compared to the control group, salt treatments significantly enhanced Na concentration while diminishing the concentrations of K, Ca, Mg, Zn, N, and P. Interestingly, as salinity levels escalated, N concentration maintained stability, whereas P concentration exhibited an increasing trend. Moreover, K, Ca, and Mg significantly declined as salt levels rose. Salt treatments brought about significant changes in stoichiometric ratios, with the N:P, K:Na, N:Na, N:Mg, and Ca : Mg ratios dropping and the N:Ca and N:K ratios rising, illustrating the varying nutrient coupling cycles under different salt conditions. These findings shed light on the plasticity of stoichiometric traits in S. glauca senesced leaves in response to soil salinization shifts, which could potentially offer insights into nutrient cycling reactions to soil salinization.

Lensless computationally defined confocal incoherent imaging with a Fresnel zone plane as coded aperture.

We present a Fresnel zone plate (FZP) mask-based system for single-shot lensless confocal imaging. The system uses an FZP as coded aperture, which allows each point source to cast a unique pattern onto the sensor, representing their horizontal and axial positions. This results in a 2D sensor measurement comprising a series of FZP patterns, which records the spatial intensity distribution of the incoherent illuminant. The reconstruction process is facilitated by an algorithm based on compress sensing (CS) theory and the use of the nuclear norm of gradient scanning and hologram segmentation technology for autofocusing. The simulative and experimental results of this study align well with the expectation that every layered scene can be accurately recovered at the corresponding depth, without undesirable signals from other layers. Additionally, we analyze the deviation of the reconstruction results in the experiment, which emphasizes the need to consider the thickness of the FZP for a precise forward propagation model.

Vancomycin population pharmacokinetics analysis in Chinese paediatric patients with varying degrees of renal function and ages: development of new practical dosing recommendations.

OBJECTIVES: To describe the pharmacokinetics of vancomycin in a large Chinese paediatric cohort with varying degrees of renal function and ages and to develop practical dosing guidelines. PATIENTS AND METHODS: We conducted a retrospective population pharmacokinetic study using data from paediatric patients who received vancomycin between June 2013 and June 2022. A non-linear mixed-effect modelling approach with a one-compartment model structure was applied. Monte Carlo simulations were used to stimulate an optimal dosage regimen to achieve the target of AUC24/MIC between 400 and 650. RESULTS: We analysed a total of 673 paediatric patients and 1547 vancomycin serum concentrations. Covariate analysis revealed that physiological maturation, renal function, albumin and cardiothoracic surgery (CTS) significantly affected vancomycin pharmacokinetics. The typical clearance and volume of distribution, standardized to 70 kg, were 7.75 L/h (2.3% relative standard error, RSE) and 36.2 L (1.7% RSE), respectively. Based on the model, we proposed an optimal dosing regimen that considers the patient's age and estimate glomerular filtration rate (eGFR) to achieve a target AUC24/MIC for CTS and non-CTS patients. We also found that a loading dose of 20 mg/kg can help patients with an eGFR of <60 mL/min/1.73 m2 achieve the target AUC on the first day of treatment. CONCLUSIONS: We established vancomycin pharmacokinetic parameters in Chinese paediatric patients and proposed a dosing guideline integrating eGFR, age and CTS status, potentially improving clinical outcomes and reducing nephrotoxicity risk.

A LC-MS/MS Method for Quantifying the Schisandrin B and Exploring Its Intracellular Exposure Correlating Antitumor Effect.

Schisandrin B (Sch.B) shows antineoplastic activity in colorectal cancer, but the mechanism is still obscure. The intracellular spatial distribution may be helpful in elucidating the mechanism. To investigate the intracellular drug distribution of Sch.B in cancer cells, a simple, rapid, and sensitive ultra-highperformance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method was established for the determination of Sch.B in colorectal cancer cells. Warfarin was utilized as an internal standard. The sample pretreatment was carried out with protein precipitation using methanol. The analyte was separated on an Atlantis T3-C18 column (3 µm, 2.1∗100 mm) using gradient elution with a mobile phase comprised of methanol and 0.2% formic acid in water. The flow rate was 0.4 mL/min. The linear range of Sch.B was 20.0-1000.0 ng/mL with a correlation coefficient (R) more than 0.99. The matrix effect and recovery ranged from 88.01% to 94.59% and from 85.25% to 91.71%; the interday and intraday precision and accuracy, stability, specificity, carryover, matrix effect, and recovery all conformed to the requirements of pharmacopoeia. Cell viability and apoptosis assays demonstrated that Sch.B has an inhibitory effect in a dose-dependent way on HCT116 proliferation and achieved significant suppression at 75 µM (IC50). It was found that in HCT116 cell, nucleus, and mitochondria, exposure levels of Sch.B peaked at 36 h and then decreased, and mitochondria possessed more Sch.B than nucleus. These results may help to elucidate the antitumor effect of Sch.B.

Forms of nitrogen inputs regulate the intensity of soil acidification.

Soil acidification induced by reactive nitrogen (N) inputs can alter the structure and function of terrestrial ecosystems. Because different N-transformation processes contribute to the production and consumption of H+ , the magnitude of acidification likely depends on the relative amounts of organic N (ON) and inorganic N (IN) inputs. However, few studies have explicitly measured the effects of N composition on soil acidification. In this study, we first conducted a meta-analysis to test the effects of ON or IN inputs on soil acidification across 53 studies in grasslands. We then compared soil acidification across five different ON:IN ratios and two input rates based on long-term field N addition experiments. The meta-analysis showed that ON had weaker effects on soil acidification than IN when the N addition rate was above 20 g N m-2 year-1 . The field experiment confirmed the findings from meta-analysis: N addition with proportions of ON ≥ 20% caused less soil acidification, especially at a high input rate (30 g N m-2 year-1 ). Structural equation model analysis showed that this result was largely due to a relatively low rate of H+ production from ON as NH3 volatilization and uptake of ON and NH4 + by the dominant grass species Leymus chinensis (which are both lower net contributors to H+ production) result in less NH4 + available for nitrification (which is a higher net contributor to H+ production). These results indicate that the evaluation of soil acidification induced by N inputs should consider N forms and manipulations of relative composition of N inputs may provide an effective approach to alleviate the N-induced soil acidification.

Evaluation of in vivo antibacterial drug efficacy using Caenorhabditis elegans infected with carbapenem-resistant Klebsiella pneumoniae as a model host.

Objective: This study was developed to assess the in vivo antimicrobial activity of specific drugs using a model system consisting of Caenorhabditis elegans (C. elegans) infected with Carbapenem-resistant Klebsiella pneumoniae (CRKP) in an effort to identify promising drugs for CRKP-infected patient treatment. Methods: A C. elegans-CRKP liquid assay platform was developed and used to conduct limited in vivo screening for antimicrobial agents with potential activity against CRKP. Time curves for 10 different concentrations of tested antimicrobial agents were tested in this model system at 0, 2, 6, 8, and 12 h after treatment. The protective effects of these different antimicrobial agents were compared at different time points. Furthermore, ten CRKP strains samples were isolated from clinical specimens to demonstrate the applicability of the nematode model method, and two typical clinical cases are presented. Results: CRKP bacteria were sufficient to induce C. elegans death in a dose- and time-dependent fashion, while effective antimicrobial agents improved the survival of these nematodes in a dose-dependent manner. Notably, PB and TGC exhibited robust antibacterial protection within 12 h even at low tested concentrations, and clear efficacy remained evident for high doses of CAZ at this same time point as mediators of improved nematode survival. The results of C. elegans model method were well consistent with that using the Kirby-Bauer method in 10 CRKP strains samples, and two typical clinical cases showed applicability, reliability and efficacy of C. elegans model method. Conclusion: Overall, nematode models in drug sensitivity testing have shown advantages in clinical settings. Our results highlight the value of C. elegans model systems as tools for the simultaneous screening of different agents for in vivo antibacterial efficacy and are deserved further study.

Gandi Capsule Improved Podocyte Lipid Metabolism of Diabetic Nephropathy Mice through SIRT1/AMPK/HNF4A Pathway.

Podocyte lipid accumulation is a potential therapeutic target for diabetic nephropathy (DN). This study was aimed at clarifying the mechanism of Gandi capsule (GDC) ameliorating DN by regulating the lipid metabolism of podocytes. Network pharmacology methods were performed to screen the key molecules and potential targets of GDC for constructing the molecular-protein interaction network of GDC and conducting signal pathway enrichment analysis. GDC was predicted to ameliorate DN through SIRT1/AMPK/HNF4A pathway. Our results showed that GDC improved renal function in db/db mice. Besides, GDC exhibited effectiveness in relieving kidney tissue damage and renal lipid accumulation in db/db mice, and same effects were present in GDC-active ingredient baicalin. We further proved the new role of HNF4A in the lipid metabolism of DN mediated by SIRT1 and AMPK signaling pathways. The results suggested decreased expression of SIRT1 and p-AMPKα in the kidney tissue and increased expression of HNF4A of db/db mice compared with the control group. GDC and baicalin could reverse these expression changes. Furthermore, similar expression changes were observed in the murine podocyte cell line (MPC-5) treated with different concentrations of GDC and baicalin. Our research suggested that GDC and its active ingredient baicalin could alleviate the abnormal lipid metabolism in the kidney of db/db mice and might exert renal protection through the SIRT1/AMPK/HNF4A pathway.

Case Report: Monitoring Vancomycin Concentrations and Pharmacokinetic Parameters in Continuous Veno-Venous Hemofiltration Patients to Guide Individualized Dosage Regimens: A Case Analysis.

There are limited pharmacokinetic (PK) studies on vancomycin in patients treated with continuous renal replacement therapy (CRRT), and the results have been inconsistent. Because of individual differences, proposing a definite recommendation for the clinical regimen is not possible. Rapidly reaching target vancomycin concentrations will facilitate effective treatment for critically ill patients treated with CRRT. In this study, to understand the dynamic change in drug clearance rates in vivo, analyze the effect of PK changes on drug concentrations, and recommend loading and maintenance dosage regimens, we monitored the blood concentrations of vancomycin and calculated the area under the curve in two critically ill patients treated with vancomycin and continuous veno-venous hemofiltration (CVVH). On the basis of real-time therapeutic drug monitoring results and PK parameters, an individualized vancomycin regimen was developed for patients with CVVH. Good clinical efficacy was achieved, which provided support and reference for empirical vancomycin therapy in these patients.

The relationship between vancomycin AUC/MIC and trough concentration, age, dose, renal function in Chinese critically ill pediatric patients.

To assess the pharmacokinetic parameters of vancomycin in Chinese critically ill pediatric patients, children treated with vancomycin, hospitalized in the intensive care unit were included. Samples to determine peak and trough serum concentrations were obtained on the third day of treatment. Half-life was significantly longer in neonates and showed a decreasing trend in infants and children. In patients aged ≥1 month, AUC24 /MIC ≥400 was achieved in 31.8% at the dose of 40 mg/kg/d, and in 48.7% at the dose of 60 mg/kg/d with an assumed MIC of 1 mg/L. Augmented renal clearance (ARC) was present in 27.3% of children, which was associated with higher vancomycin clearance and lower AUC values. A good correlation was observed between trough concentration and AUC24 , and the trough concentration that correlated with AUC24 of 400 were varied according to the dosage regimens, 8.42 mg/L for 6-hintervals, and 6.63 mg/L for 8-h intervals. To conclude, vancomycin trough concentration that related to the AUC24 of 400 was much lower in critically ill children than that in adults. The dosage of 60 mg/kg/day did not enough for producing AUC24 in the range of 400-600 mg h/L in critically ill children, especially in those with ARC.

Oxidation Mechanism of Al-Sn Bearing Alloys.

Oxidation of Al-Sn bearing alloy occurs during production, processing and use, which reduces both alloy performance and performance of coatings applied to the alloy surface. Therefore, the oxidation mechanism of Al-Sn bearing alloy is studied at 25, 180, 300, and 500 °C. The oxidation morphologies of the alloy were observed by scanning electron microscopy (SEM), and the oxidation products were determined by X-ray diffraction (XRD). The oxidation weight gain curves were obtained by thermogravimetric analysis. The experimental results show that: Al-Sn bearing alloy is oxidized quickly to form Al2O3. As the oxidation temperature increases, Sn phase start to precipitate along the grain boundary and form networked spheroids of Sn on the alloy surface. The amount of precipitation increases with further increase of the oxidation temperature. Cracks and holes are left in the alloy. The oxide layer is mainly composed of Sn, SnO2, and Al2O3. At 25 °C, oxidation rate of Al-Sn alloy approach zero. At 180, 300, and 500 °C, the oxidation rate increases quickly conforming to a power function, and eventually remains stable at about 3 × 10-6 mg·mm-2·s-1.

An Ensemble Model for Prediction of Vancomycin Trough Concentrations in Pediatric Patients.

PURPOSE: This study aimed to establish an optimal model to predict vancomycin trough concentrations by using machine learning. PATIENTS AND METHODS: We enrolled 407 pediatric patients (age < 18 years) who received vancomycin intravenously and underwent therapeutic drug monitoring from June 2013 to April 2020 at Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine. The median (interquartile range) age and weight of the patients were 2 (0.63-5) years and 12 (7.8-19) kg. Vancomycin trough concentrations were considered as the target variable, and eight different algorithms were used for predictive performance comparison. The whole dataset (407 cases) was divided into training group and testing group at the ratio of 80%: 20%, which were 325 and 82 cases, respectively. RESULTS: Ultimately, five algorithms (XGBoost, GBRT, Bagging, ExtraTree and decision tree) with high R 2 (0.657, 0.514, 0.468, 0.425 and 0.450, respectively) were selected and further ensembled to establish the final model and achieve an optimal result. For missing data, through filling the missing values and model ensemble, we obtained R 2 =0.614, MAE=3.32, MSE=24.39, RMSE=4.94 and a prediction accuracy of 51.22% (predicted trough concentration within ±30% of the actual trough concentration). In comparison with the pharmacokinetic models (R 2 =0.3), the machine learning model works better in model fitting and has better prediction accuracy. CONCLUSION: Therefore, the ensemble model is useful for the vancomycin concentration prediction, especially in the population of children with great individual variation. As machine learning methods evolve, the clinical value of the ensemble model will be demonstrated in the clinical practice.

Prediction of vancomycin dose on high-dimensional data using machine learning techniques.

OBJECTIVES: Despite therapeutic vancomycin is regularly monitored, its dose requirements vary considerably between individuals. Various innovative vancomycin dosing strategies have been developed for dose optimization; however, the utilization of individual factors and extensibility is insufficient. We aimed to develop an optimal dosing algorithm for vancomycin based on the high-dimensional data using the proposed variable engineering and machine-learning methods. METHODS: This study proposed a variable engineering process that automatically generates second-order variable interactions. We performed an initial examination of independent variables and interactive variables using eXtreme Gradient Boosting. The vancomycin dose prediction model was established based on the derived variables. RESULTS: Based on the evaluation of the model performance in the validation cohort, our algorithm accounted for 67.5% of variations in the vancomycin doses. Subgroup analysis showed better performance in patients with medium and high body weight (with the ideal predictive percentage of 72.7% and 73.7%), and low and medium levels of serum creatinine (with the ideal predictive percentage of 77.8% and 73.1%) than in other groups. CONCLUSION: The new vancomycin dose prediction model is potentially useful for patients whose population profiles are similar to those of our patients and yielded desired reference of clinical indicators with specific breakpoints.