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Soil pollution with cadmium (Cd) poses serious health and environmental consequences. The study investigated the incubation of several soil samples and conducted quantitative soil characterization to assess the influence of biochar (BC) on Cd adsorption. The aim was to develop predictive models for Cd concentrations using statistical and modeling approaches dependent on soil characteristics. The potential risk linked to the transformation and immobilization of Cd adsorption by BC in the soil could be conservatively assessed by pH, clay, cation exchange capacity, organic carbon, and electrical conductivity. In this study, Long Short-Term Memory (LSTM), Bidirectional Gated Recurrent Unit (BiGRU), and 5-layer CNN Convolutional Neural Networks (CNNs) were applied for risk assessments to establish a framework for evaluating Cd risk in BC amended soils to predict Cd transformation. In the case of control soils (CK), the BiGRU model showed commendable performance, with an R 2 value of 0.85, indicating an approximate 85.37% variance in the actual Cd. The LSTM model, which incorporates sequence data, produced less accurate results ( R 2 = 0.84) , while the 5-layer CNN model had an R2 value of 0.91, indicating that the CNN model could account for over 91% of the variation in actual Cd levels. In the case of BC-applied soils, the BiGRU model demonstrated a strong correlation between predicted and actual values with R 2 (0.93), indicating that the model explained 93.21% of the variance in Cd concentrations. Similarly, the LSTM model showed a notable increase in performance with BC-treated soil data. The R 2 value for this model stands at a robust R 2   (0.94) , reflecting its enhanced ability to predict Cd levels with BC incorporation. Outperforming both recurrent models, the 5-layer CNN model attained the highest precision with an R 2 value of 0.95, suggesting that 95.58% of the variance in the actual Cd data can be explained by the CNN model's predictions in BC-amended soils. Consequently, this study suggests developing ecological soil remediation strategies that can effectively manage heavy metal pollution in soils for environmental sustainability. [ABSTRACT FROM AUTHOR]

Purpose: To construct a venous thromboembolism (VTE) risk assessment model specifically for inpatients with cancer. Method: Patients were included according to the inclusion criteria. Univariate and multivariate analyses of all variables were included to develop a VTE risk assessment model applicable to the derivation cohort. Hosmer–Lemeshow test and receiver operating characteristic (ROC) curve were used to test the fit degree and identification validity of the model. The patient data from separate validation cohorts verified the external population. Result: A total of 944 cancer patients were included in this study. Alfalfa-inpatient-CAT model, a risk assessment model for VTE in hospitalized cancer patients, was established, which mainly includes hypertension, surgical history (nearly one month), history of VTE, peripherally inserted central venous catheters (PICC), chemotherapy, PT < 12.85 s, D-dimer ≥ 1.805 μg/mL, hemoglobin ≤ 114.5 g/L, CRP ≥ 7.575 mg/L. Hosmer–Lemeshow test results showed P = 0.353 > 0.05, (χ2 = 8.872, Df = 8). The area under ROC curve was 0.906 [95%CI (0.881–0.930), P < 0.001]. The authenticity evaluation in the model database showed that the risk of thrombosis in the high-risk group (score ≥ 3) was 72.63%, significantly higher than that in the low-risk group (score 0–2) (27.37%) [χ2 = 144.00, Df = 1, P < 0.001]. Conclusion: This study developed a new VTE risk assessment model – Alfalfa-inpatient-CAT model – for hospitalized cancer patients at high risk of thrombosis. This model has a good fitting degree and discriminant validity. It is expected to provide some reference for the clinical treatment of inpatients with cancer through continuous optimization. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the genetic polymorphisms of related gene loci (CYP2C9*3, VKORC1-1639G > A) based on demographic and clinical factors, and use the maximum a posterior Bayesian method to construct a warfarin individualized dose prediction model in line with the Chinese Han population. Finally, the built model is compared and analyzed with the widely used models at home and abroad. In this study, a total of 5467 INR measurements are collected from 646 eligible subjects in our hospital, and the maximum a posterior Bayesian method is used to construct a warfarin dose prediction that conforms to the Chinese Han population on the basis of the Hamberg model. The model is verified and compared with foreign models. This study finds that body weight and concomitant use of amiodarone have a significant effect on the anticoagulant effect of warfarin. The model can provide an effective basis for individualized and rational dosing of warfarin in Han population more accurately. In the performance of comparison with different warfarin dose prediction models, the new model has the highest prediction accuracy, and the prediction percentage is as high as 72.56%. The dose predicted by the Huang model is the closest to the actual dose of warfarin. The population pharmacokinetics and pharmacodynamics model established in this study can better reflect the distribution characteristics of INR values after warfarin administration in the Han population, and performs better than the models reported in the literature. [ABSTRACT FROM AUTHOR]

Most studies have focused on complex strategies for materials preparation instead of industrial wastewater treatment due to emergency treatment requirements for metal pollution. This study evaluated sodium polyacrylate (PSA) as a carbon skeleton and FeS as a functional material to synthesize PSA-nFeS material. The characteristics and interactions of PSA-nFeS composites treated with hexavalent chromium were analyzed by means of various techniques, such as scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDS), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectrometry (FTIR), and atomic absorption spectroscopy (AAS). Adsorption-coupled reduction was observed to be the predominant mechanism of Cr(VI) removal. The feasibility of PSA-nFeS composites in reducing toxicity and removing of Cr(VI) from real effluents was investigated through column studies and material properties evaluation. The continuous column studies were conducted using tannery effluents to optimize feed flow rates, initial feed Cr(VI) concentration, and column bed height. The results revealed that PSA-nFeS composites are ideal for filling materials in portable filtration devices due to their lightweight and compact size. [ABSTRACT FROM AUTHOR]

Background: Poor anticoagulation management of warfarin may lead to patient admission, prolonged hospital stays, and even death due to anticoagulation-related adverse events. Traditional non-web-based outpatient clinics struggle to provide ideal anticoagulation management services for patients, and there is a need to explore a safer, more effective, and more convenient mode of warfarin management., Objective: This study aimed to compare differences in the quality of anticoagulation management and clinical adverse events between a web-based management model (via a smartphone app) and the conventional non-web-based outpatient management model., Methods: This study is a prospective cohort research that includes multiple national centers. Patients meeting the nadir criteria were split into a web-based management group using the Alfalfa app or a non-web-based management group with traditional outpatient management, and they were then monitored for a 6-month follow-up period to collect coagulation test results and clinical events. The effectiveness and safety of the 2 management models were assessed by the following indicators: time in therapeutic range (TTR), bleeding events, thromboembolic events, all-cause mortality events, cumulative event rates, and the distribution of the international normalized ratio (INR)., Results: This national multicenter cohort study enrolled 522 patients between June 2019 and May 2021, with 519 (99%) patients reaching the follow-up end point, including 260 (50%) in the non-web-based management group and 259 (50%) in the web-based management group. There were no observable differences in baseline characteristics between the 2 patient groups. The web-based management group had a significantly higher TTR than the non-web-based management group (82.4% vs 71.6%, P<.001), and a higher proportion of patients received effective anticoagulation management (81.2% vs 63.5%, P<.001). The incidence of minor bleeding events in the non-web-based management group was significantly higher than that in the web-based management group (12.1% vs 6.6%, P=.048). Between the 2 groups, there was no statistically significant difference in the incidence of severe bleeding and thromboembolic and all-cause death events. In addition, compared with the non-web-based management group, the web-based management group had a lower proportion of INR in the extreme subtreatment range (17.6% vs 21.3%) and severe supertreatment range (0% vs 0.8%) and a higher proportion in the treatment range (50.4% vs 43.1%), with statistical significance., Conclusions: Compared with traditional non-web-based outpatient management, web-based management via the Alfalfa app may be more beneficial because it can enhance patient anticoagulation management quality, lower the frequency of small bleeding events, and improve INR distribution., (©Wenfei Chen, Jiana Chen, Shaojun Jiang, Chunhua Wang, Jinhua Zhang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 29.07.2024.)