Development and Validation of the Interprofessional Collaboration Practice Competency Scale (IPCPCS) for Clinical Nurses.

Interprofessional collaborative practice is a core competency and is the key to strengthening health practice systems in order to deliver safe and high-quality nursing practice. However, there is no Interprofessional Collaboration Practice Competency Scale (IPCPCS) for clinical nurses in Taiwan. Therefore, the purposes of this study were to develop an IPCPCS and to verify its reliability and validity. This was a psychometric study with a cross-sectional survey using convenience sampling to recruit nurses from the seven hospitals of a medical foundation. A self-designed structured IPCPCS was rolled out via a Google survey. The data were analyzed using descriptive statistics, principal-axis factoring (PAF) with Promax rotation, Pearson correlation, reliability analysis, and one-way ANOVA. PAF analysis found that three factors could explain 77.76% of cumulative variance. These were collaborative leadership and interprofessional conflict resolution, interprofessional communication and team functioning, and role clarification and client-centered care. The internal consistency of the three factors (Cronbach's α) was between 0.970 to 0.978, and the Pearson correlation coefficients were between 0.814 to 0.883. Significant differences were presented in the IPCPCS score by age, education level, total years of work experience, position on the nursing clinical ladder, and participation in interprofessional education. In conclusion, the three factors used in the IPCPCS have good reliability and construct validity. This scale can be used as an evaluation tool of in-service interprofessional education courses for clinical nurses.

Effects of narrow-wide row planting patterns on canopy photosynthetic characteristics, bending resistance and yield of soybean in maize‒soybean intercropping systems.

With the improvements in mechanization levels, it is difficult for the traditional intercropping planting patterns to meet the needs of mechanization. In the traditional maize‒soybean intercropping, maize has a shading effect on soybean, which leads to a decrease in soybean photosynthetic capacity and stem bend resistance, resulting in severe lodging, which greatly affects soybean yield. In this study, we investigated the effects of three intercropping ratios (four rows of maize and four rows of soybean; four rows of maize and six rows of soybean; six rows of maize and six rows of soybean) and two planting patterns (narrow-wide row planting pattern of 80-50 cm and uniform-ridges planting pattern of 65 cm) on soybean canopy photosynthesis, stem bending resistance, cellulose, hemicellulose, lignin and related enzyme activities. Compared with the uniform-ridge planting pattern, the narrow-wide row planting pattern significantly increased the LAI, PAR, light transmittance and compound yield by 6.06%, 2.49%, 5.68% and 5.95%, respectively. The stem bending resistance and cellulose, hemicellulose, lignin and PAL, TAL and CAD activities were also significantly increased. Compared with those under the uniform-ridge planting pattern, these values increased by 7.74%, 3.04%, 8.42%, 9.76%, 7.39%, 10.54% and 8.73% respectively. Under the three intercropping ratios, the stem bending resistance, cellulose, hemicellulose, lignin content and PAL, TAL, and CAD activities in the M4S6 treatment were significantly greater than those in the M4S4 and M6S6 treatments. Compared with the M4S4 treatment, these variables increased by 12.05%, 11.09%, 21.56%, 11.91%, 18.46%, 16.1%, and 16.84%, respectively, and compared with the M6S6 treatment, they increased by 2.06%, 2.53%, 2.78%, 2.98%, 8.81%, 4.59%, and 4.36%, respectively. The D-M4S6 treatment significantly improved the lodging resistance of soybean and weakened the negative impact of intercropping on soybean yield. Therefore, based on the planting pattern of narrow-wide row maize‒soybean intercropping planting pattern, four rows of maize and six rows of soybean were more effective at improving the lodging resistance of soybean in the semiarid region of western China.

Evaluating the mutagenicity of N-nitrosodimethylamine in 2D and 3D HepaRG cell cultures using error-corrected next generation sequencing.

Human liver-derived metabolically competent HepaRG cells have been successfully employed in both two-dimensional (2D) and 3D spheroid formats for performing the comet assay and micronucleus (MN) assay. In the present study, we have investigated expanding the genotoxicity endpoints evaluated in HepaRG cells by detecting mutagenesis using two error-corrected next generation sequencing (ecNGS) technologies, Duplex Sequencing (DS) and High-Fidelity (HiFi) Sequencing. Both HepaRG 2D cells and 3D spheroids were exposed for 72 h to N-nitrosodimethylamine (NDMA), followed by an additional incubation for the fixation of induced mutations. NDMA-induced DNA damage, chromosomal damage, and mutagenesis were determined using the comet assay, MN assay, and ecNGS, respectively. The 72-h treatment with NDMA resulted in concentration-dependent increases in cytotoxicity, DNA damage, MN formation, and mutation frequency in both 2D and 3D cultures, with greater responses observed in the 3D spheroids compared to 2D cells. The mutational spectrum analysis showed that NDMA induced predominantly A:T → G:C transitions, along with a lower frequency of G:C → A:T transitions, and exhibited a different trinucleotide signature relative to the negative control. These results demonstrate that the HepaRG 2D cells and 3D spheroid models can be used for mutagenesis assessment using both DS and HiFi Sequencing, with the caveat that severe cytotoxic concentrations should be avoided when conducting DS. With further validation, the HepaRG 2D/3D system may become a powerful human-based metabolically competent platform for genotoxicity testing.

Proposed mechanisms of electron uptake in metal-corroding methanogens and their potential for CO2 bioconversion applications.

Some methanogens are electrotrophic bio-corroding microbes that can acquire electrons from solid surfaces including metals. In the laboratory, pure cultures of methanogenic cells oxidize iron-based materials including carbon steel, stainless steel, and Fe0. For buried or immersed pipelines or other metallic structures, methanogens are often major components of corroding biofilms with complex interspecies relationships. Models explaining how these microbes acquire electrons from solid donors are multifaceted and include electron transfer via redox mediators such as H2 or by direct contact through membrane proteins. Understanding the electron uptake (EU) routes employed by corroding methanogens is essential to develop efficient strategies for corrosion prevention. It is also beneficial for the development of bioenergy applications relying on methanogenic EU from solid donors such as bioelectromethanogenesis, hybrid photosynthesis, and the acceleration of anaerobic digestion with electroconductive particles. Many methanogenic species carrying out biocorrosion are the same ones forming the extensive abiotic-biological interfaces at the core of these bio-applications. This review will discuss the interactions between corrosive methanogens and metals and how the EU capability of these microbes can be harnessed for different sustainable biotechnologies.

Use of Lentivirus-Based Method for Establishing TK6 Human Cell Lines Expressing Cytochrome P450 and its Applications in Genotoxicity Testing.

The human lymphoblastoid cell line TK6 stands out as the most widely employed human cell line in genotoxicity testing, as recommended by various testing guidelines for in vitro assessments. Nevertheless, like many testing cell lines, TK6 lacks functional phase I drug-metabolizing enzymes crucial for chemical genotoxicity evaluations. This protocol introduces a lentivirus-based methodology for establishing a panel of TK6-derived cell lines, each expressing one of 14 cytochrome P450s (CYP1A1, CYP1A2, CYP1B1, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C18, CYP2C19, CYP2D6, CYP2E1, CYP3A4, CYP3A5, and CYP3A7). The utilization of a lentiviral expression system ensures stable transduction, offering notable advantages such as sustained transgene expression, high transduction efficiency, positive selection feasibility, and user-friendly application. Additionally, we present a detailed procedure for validating the enhanced expression of each CYP in the established cell lines through real-time PCR, western blotting, and mass spectrometry analysis. Lastly, we exemplify the application of these CYP-expressing TK6 cell lines in genotoxicity testing, employing a flow-cytometry-based in vitro micronucleus test. Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Basic Protocol 1: Lentivirus production and transduction for TK6 cells Support Protocol: Selecting a single clone of CYP-expressing TK6 cells Basic Protocol 2: Validation of CYP expression in TK6 cell lines Basic Protocol 3: Application of transduced cell lines in flow-cytometry-based micronucleus assay.

[Pollution Source Apportionment of Heavy Metals in Cultivated Soil Around a Red Mud Yard Based on APCS-MLR and PMF Models].

In order to explore the characteristics and sources of heavy metal pollution in cultivated soil around a red mud yard in Chongqing， the content and spatial distribution characteristics of eight heavy metal elements （Cd， Cr， Hg， Ni， Pb， As， Cu， and Zn） in the soil were analyzed， and the single factor pollution index method and Nemerow comprehensive pollution index method were used to evaluate the characteristics of heavy metal pollution in soil. On the basis of correlation analysis， the APCS-MLR and PMF models were used to quantitatively analyze the sources of heavy metals. The results showed that the average contents of the other seven heavy metal elements were higher than the background values of Chongqing soil， except for that of Cr. The heavy metals Cd， Hg， and As were moderately polluted， and Pb， Cu， Ni， and Zn were mildly polluted. The spatial distribution pattern of Cr， Ni， Pb， Cu， and Zn in the soil was similar， and there was a very significant positive correlation between them （P < 0.01）. The spatial distribution characteristics of Cd， Hg， and As were significantly different， and there was no significant correlation between them （P > 0.05）. The source apportionment showed that the sources of heavy metals in the soil in the study area were relatively complex， and the APCS-MLR and PMF models could identify the same four pollution sources， namely red mud yard percolation emission and natural sources， thermal power generation emission sources， agricultural activities and natural sources， and non-ferrous metal smelting emission sources. There was little difference in the results of source apportionment between the two models. The contribution rates of the four pollution sources in the APCS-MLR model were 51.8%， 18.0%， 15.9%， and 14.3%， respectively， whereas those in the PMF model were 45.9%， 12.8%， 21.5%， and 19.8%， respectively.

Evaluation of weak genotoxicity of hydroxychloroquine in human TK6 cells.

Hydroxychloroquine (HCQ), a derivative of chloroquine (CQ), is an antimalarial and antirheumatic drug. Since there is limited data available on the genotoxicity of HCQ, in the current study, we used a battery of in vitro assays to systematically examine the genotoxicity of HCQ in human lymphoblastoid TK6 cells. We first showed that HCQ is not mutagenic in TK6 cells up to 80 µM with or without exogenous metabolic activation. Subsequently, we found that short-term (3-4 h) HCQ treatment did not cause DNA strand breakage as measured by the comet assay and the phosphorylation of histone H2A.X (γH2A.X), and did not induce chromosomal damage as determined by the micronucleus (MN) assay. However, after 24-h treatment, both CQ and HCQ induced comparable and weak DNA damage and MN formation in TK6 cells; upregulated p53 and p53-mediated DNA damage responsive genes; and triggered apoptosis and mitochondrial damage that may partially contribute to the observed MN formation. Using a benchmark dose (BMD) modeling analysis, the lower 95% confidence limit of BMD50 values (BMDL50) for MN induction in TK6 cells were about 19.7 µM for CQ and 16.3 µM for HCQ. These results provide additional information for quantitative genotoxic risk assessment of these drugs.

Heavy metal pollution in agricultural soils from surrounding industries with low emissions: Assessing contamination levels and sources.

The potential for heavy metal (HM) pollution in agricultural soils adjacent to industries with elevated HM emissions has long been recognized. However, industries with relatively lower levels of HM emissions, such as alumina smelting and glass production, may still contribute to the pollution of surrounding agricultural soils through continuous, albeit low-level, emissions. Despite this, this issue has not garnered adequate attention thus far. Therefore, this study aimed to assess the extent of HM pollution in agricultural soils adjacent to an alumina smelting and a glass production factory, identifying contamination levels and potential sources through the analysis of input fluxes, isotope fingerprints, and receptor models. Results showed moderate cadmium (Cd) contamination in surface soil, exceeding standards at a rate of 86.36 %. Further analysis revealed that atmospheric deposition was the primary route for Cd input in both paddy fields (89.20 %) and dryland soils (91.61 %). Additionally, the δ114/110Cd values in surface soils indicated that dust played a role in influencing Cd levels in distant surface soils, while raw materials and slags were identified as primary sources near the factory. Industrial sources were considered the primary contributors of Cd in soil accounting for approximately 73.38 % and 82.67 %, respectively, according to the positive matrix factorization model (PMF) and absolute principal component scores-multiple linear regression model (APCS-MLR). Overall, this study underscores the importance of monitoring HMs from industries with relatively low emissions and provides a scientific basis for effectively managing HMs pollution in agricultural soils, ensuring the preservation of agricultural soil quality.

Prediction of human epidermal growth factor receptor 2 (HER2) status in breast cancer by mammographic radiomics features and clinical characteristics: a multicenter study.

OBJECTIVES: To preoperatively evaluate the human epidermal growth factor 2 (HER2) status in breast cancer using mammographic radiomics features and clinical characteristics on a multi-vendor and multi-center basis. METHODS: This multi-center study included a cohort of 1512 Chinese female with invasive ductal carcinoma of no special type (IDC-NST) from two different hospitals and five devices (1332 from Institution A, used for training and testing the models, and 180 women from Institution B, as the external validation cohort). The Gradient Boosting Machine (GBM) was employed to establish radiomics and multiomics models. Model efficacy was evaluated by the area under the curve (AUC). RESULTS: The number of HER2-positive patients in the training, testing, and external validation cohort were 245(26.3%), 105 (26.3.8%), and 51(28.3%), respectively, with no statistical differences among the three cohorts (p = 0.842, chi-square test). The radiomics model, based solely on the radiomics features, achieved an AUC of 0.814 (95% CI, 0.784-0.844) in the training cohort, 0.776 (95% CI, 0.727-0.825) in the testing cohort, and 0.702 (95% CI, 0.614-0.790) in the external validation cohort. The multiomics model, incorporated radiomics features with clinical characteristics, consistently outperformed the radiomics model with AUC values of 0.838 (95% CI, 0.810-0.866) in the training cohort, 0.788 (95% CI, 0.741-0.835) in the testing cohort, and 0.722 (95% CI, 0.637-0.811) in the external validation cohort. CONCLUSIONS: Our study demonstrates that a model based on radiomics features and clinical characteristics has the potential to accurately predict HER2 status of breast cancer patients across multiple devices and centers. CLINICAL RELEVANCE STATEMENT: By predicting the HER2 status of breast cancer reliably, the presented model built upon radiomics features and clinical characteristics on a multi-vendor and multi-center basis can help in bolstering the model's applicability and generalizability in real-world clinical scenarios. KEY POINTS: • The mammographic presentation of breast cancer is closely associated with the status of human epidermal growth factor receptor 2 (HER2). • The radiomics model, based solely on radiomics features, exhibits sub-optimal performance in the external validation cohort. • By combining radiomics features and clinical characteristics, the multiomics model can improve the prediction ability in external data.

Bacteria-Based Nanoprobes for Cancer Therapy.

Surgical removal together with chemotherapy and radiotherapy has used to be the pillars of cancer treatment. Although these traditional methods are still considered as the first-line or standard treatments, non-operative situation, systemic toxicity or resistance severely weakened the therapeutic effect. More recently, synthetic biological nanocarriers elicited substantial interest and exhibited promising potential for combating cancer. In particular, bacteria and their derivatives are omnipotent to realize intrinsic tumor targeting and inhibit tumor growth with anti-cancer agents secreted and immune response. They are frequently employed in synergistic bacteria-mediated anticancer treatments to strengthen the effectiveness of anti-cancer treatment. In this review, we elaborate on the development, mechanism and advantage of bacterial therapy against cancer and then systematically introduce the bacteria-based nanoprobes against cancer and the recent achievements in synergistic treatment strategies and clinical trials. We also discuss the advantages as well as the limitations of these bacteria-based nanoprobes, especially the questions that hinder their application in human, exhibiting this novel anti-cancer endeavor comprehensively.

Distinct MRI characteristics of spinal cord diffuse midline glioma, H3 K27-altered in comparison to spinal cord glioma without H3 K27-alteration and demyelination disorder.

BACKGROUND: An applicable magnetic resonance imaging (MRI) biomarker for diffuse midline glioma (DMG), H3 K27-altered of the spinal cord is important for non-invasive diagnosis. PURPOSE: To evaluate the efficacy of conventional MRI (cMRI) in distinguishing between DMGs, H3 K27-altered, gliomas without H3 K27-alteration, and demyelinating lesions in the spinal cord. MATERIAL AND METHODS: Between January 2017 and February 2023, patients with pathology-confirmed spinal cord gliomas (including ependymomas) with definite H3 K27 status and demyelinating diseases diagnosed by recognized criteria were recruited as the training set for this retrospective study. Morphologic parameter assessment was performed by two neuroradiologists on T1-weighted, T2-weighted, and contrast-enhanced T1-weighted imaging. Variables with high inter- and intra-observer agreement were included in univariable correlation analysis and multivariable logistic regression. The performance of the final model was verified by internal and external testing sets. RESULTS: The training cohort included 21 patients with DMGs (13 men; mean age = 34.57 ± 13.489 years), 21 with wild-type gliomas (10 men; mean age = 46.76 ± 17.017 years), and 20 with demyelinating diseases (5 men; mean age = 49.50 ± 18.872 years). A significant difference was observed in MRI features, including cyst(s), hemorrhage, pial thickening with enhancement, and the maximum anteroposterior diameter of the spinal cord. The prediction model, integrating age, age2, and morphological characteristics, demonstrated good performance in the internal and external testing cohort (accuracy: 0.810 and 0.800, specificity: 0.810 and 0.720, sensitivity: 0.872 and 0.849, respectively). CONCLUSION: Based on cMRI, we developed a model with good performance for differentiating among DMGs, H3 K27-altered, wild-type glioma, and demyelinating lesions in the spinal cord.

Multicenter Study of the Utility of Convolutional Neural Network and Transformer Models for the Detection and Segmentation of Meningiomas.

PURPOSE: This study aimed to investigate the effectiveness and practicality of using models like convolutional neural network and transformer in detecting and precise segmenting meningioma from magnetic resonance images. METHODS: The retrospective study on T1-weighted and contrast-enhanced images of 523 meningioma patients from 3 centers between 2010 and 2020. A total of 373 cases split 8:2 for training and validation. Three independent test sets were built based on the remaining 150 cases. Six convolutional neural network detection models trained via transfer learning were evaluated using 4 metrics and receiver operating characteristic analysis. Detected images were used for segmentation. Three segmentation models were trained for meningioma segmentation and were evaluated via 4 metrics. In 3 test sets, intraclass consistency values were used to evaluate the consistency of detection and segmentation models with manually annotated results from 3 different levels of radiologists. RESULTS: The average accuracies of the detection model in the 3 test sets were 97.3%, 93.5%, and 96.0%, respectively. The model of segmentation showed mean Dice similarity coefficient values of 0.884, 0.834, and 0.892, respectively. Intraclass consistency values showed that the results of detection and segmentation models were highly consistent with those of intermediate and senior radiologists and lowly consistent with those of junior radiologists. CONCLUSIONS: The proposed deep learning system exhibits advanced performance comparable with intermediate and senior radiologists in meningioma detection and segmentation. This system could potentially significantly improve the efficiency of the detection and segmentation of meningiomas.

The involvement of hepatic cytochrome P450s in the cytotoxicity of lapatinib.

Lapatinib, an oral tyrosine kinase inhibitor used as a first-line treatment for HER2-positive breast cancer, has been reported to be associated with hepatotoxicity; however, the underlying mechanisms remain unclear. In this study, we report that lapatinib causes cytotoxicity in multiple types of hepatic cells, including primary human hepatocytes, HepaRG cells, and HepG2 cells. A 24-h treatment with lapatinib induced cell cycle disturbances, apoptosis, and DNA damage, and decreased the protein levels of topoisomerase in HepG2 cells. We investigated the role of cytochrome P450 (CYP)-mediated metabolism in lapatinib-induced cytotoxicity using our previously established HepG2 cell lines, which express each of 14 CYPs (1A1, 1A2, 1B1, 2A6, 2B6, 2C8, 2C9, 2C18, 2C19, 2D6, 2E1, 3A4, 3A5, and 3A7). We demonstrate that lapatinib is metabolized by CYP1A1, 3A4, 3A5, and 3A7. Among these, lapatinib-induced cytotoxicity and DNA damage were attenuated in cells overexpressing CYP3A5 or 3A7. Additionally, we measured the production of three primary metabolites of lapatinib (O-dealkylated lapatinib, N-dealkylated lapatinib, and N-hydroxy lapatinib) in CYP1A1-, 3A4-, 3A5-, and 3A7-overexpressing HepG2 cells. We compared the cytotoxicity of lapatinib and its 3 metabolites in primary human hepatocytes, HepaRG cells, and HepG2 cells and demonstrated that N-dealkylated lapatinib is more toxic than the parent drug and the other metabolites. Taken together, our results indicate that lapatinib-induced cytotoxicity involves multiple mechanisms, such as apoptosis and DNA damage; that N-dealkylated lapatinib is a toxic metabolite contributing to the toxic effect of lapatinib; and that CYP3A5- and 3A7-mediated metabolism plays a role in attenuating the cytotoxicity of lapatinib.

Modified Stabilization Test to Diagnose Chronic Syndesmotic Injuries Based on Posture Control.

BACKGROUND: To propose and validate a modified noninvasive method for the diagnosis of chronic syndesmotic injuries. METHODS: This study included 16 patients with chronic ankle instability. Herein, we propose the Modified Stabilization Test, a new measurement for use in the diagnosis of chronic syndesmotic injury, as determined by wearing a 60-kPa pneumatic brace. The test combines the center of pressure and sensory organization test to measure postural control. For comparison, we also measured the tibiofibular clear space, tibiofibular overlap, and medial clear space using anteroposterior radiograph; a line marked horizontally above the tibial plaque using computed tomography (CT) to measure the syndesmotic gap and fibular rotation angle; and magnetic resonance imaging (MRI) scans to determine the presence of the λ sign. The distance of syndesmosis was confirmed in 16 individuals through arthroscopy, and the results of the examination were used to determine the diagnostic efficacy of each index. RESULTS: Receiver operating characteristic curve analysis revealed that the optimal cut-off value, sensitivity, and specificity of the Modified Stabilization Test for the diagnosis of chronic syndesmotic injuries were 0.80, 100%, and 87.5%, respectively. The area under the curve (AUC) of the Modified Stabilization Test was 0.906 (95% CI 0.656, 0.993; P < .001), which was superior to imaging indices such as radiography, CT, and MRI (AUC = 0.516-0.891). CONCLUSION: We developed the Modified Stabilization Test-a noninvasive diagnostic tool for the screening of chronic syndesmotic injuries. The test showed high sensitivity and specificity for the identification of chronic syndesmotic injuries and is helpful in the identification of chronic syndesmotic injuries. LEVEL OF EVIDENCE: Level II, diagnostic-investigating a diagnostic test.

Microbial taxa related to natural hydrogen and methane emissions in serpentinite-hosted hyperalkaline springs of New Caledonia.

The southeastern part of New Caledonia main island (Grande Terre) is the location of a large ophiolitic formation that hosts several hyperalkaline springs discharging high pH (∼11) and warm (<40°C) fluids enriched in methane (CH4) and hydrogen (H2). These waters are produced by the serpentinization of the ultrabasic rock formations. Molecular surveys had previously revealed the prokaryotic diversity of some of these New Caledonian springs, especially from the submarine chimneys of Prony Bay hydrothermal field. Here we investigate the microbial community of hyperalkaline waters from on-land springs and their relationships with elevated concentrations of dissolved H2 (21.1-721.3 µmol/L) and CH4 (153.0-376.6 µmol/L). 16S rRNA gene analyses (metabarcoding and qPCR) provided evidence of abundant and diverse prokaryotic communities inhabiting hyperalkaline fluids at all the collected springs. The abundance of prokaryotes was positively correlated to the H2/CH4 ratio. Prokaryotes consisted mainly of bacteria that use H2 as an energy source, such as microaerophilic Hydrogenophaga/Serpentinimonas (detected in all sources on land) or anaerobic sulfate-reducing Desulfonatronum, which were exclusively found in the most reducing (Eh ref H2 ∼ -700 mV) and the most H2-enriched waters discharging at the intertidal spring of the Bain des Japonais. The relative abundance of a specific group of uncultured Methanosarcinales that thrive in serpentinization-driven ecosystems emitting H2, considered potential H2-consuming methanogens, was positively correlated with CH4 concentrations, and negatively correlated to the relative abundance of methylotrophic Gammaproteobacteria. Firmicutes were also numerous in hyperalkaline waters, and their relative abundance (e.g., Gracilibacter or Dethiobacter) was proportional to the dissolved H2 concentrations, but their role in the H2 budget remains to be assessed. The prokaryotic communities thriving in New Caledonia hyperalkaline waters are similar to those found in other serpentinite-hosted high-pH waters worldwide, such as Lost City (North Atlantic) and The Cedars (California).

Predicting peritumoral edema development after gamma knife radiosurgery of meningiomas using machine learning methods: a multicenter study.

OBJECTIVES: Edema is a complication of gamma knife radiosurgery (GKS) in meningioma patients that leads to a variety of consequences. The aim of this study is to construct radiomics-based machine learning models to predict post-GKS edema development. METHODS: In total, 445 meningioma patients who underwent GKS in our institution were enrolled and partitioned into training and internal validation datasets (8:2). A total of 150 cases from multicenter data were included as the external validation dataset. In each case, 1132 radiomics features were extracted from each pre-treatment MRI sequence (contrast-enhanced T1WI, T2WI, and ADC maps). Nine clinical features and eight semantic features were also generated. Nineteen random survival forest (RSF) and nineteen neural network (DeepSurv) models with different combinations of radiomics, clinical, and semantic features were developed with the training dataset, and evaluated with internal and external validation. A nomogram was derived from the model achieving the highest C-index in external validation. RESULTS: All the models were successfully validated on both validation datasets. The RSF model incorporating clinical, semantic, and ADC radiomics features achieved the best performance with a C-index of 0.861 (95% CI: 0.748-0.975) in internal validation, and 0.780 (95% CI: 0.673-0.887) in external validation. It stratifies high-risk and low-risk cases effectively. The nomogram based on the predicted risks provided personalized prediction with a C-index of 0.962 (95%CI: 0.951-0.973) and satisfactory calibration. CONCLUSION: This RSF model with a nomogram could represent a non-invasive and cost-effective tool to predict post-GKS edema risk, thus facilitating personalized decision-making in meningioma treatment. CLINICAL RELEVANCE STATEMENT: The RSF model with a nomogram built in this study represents a handy, non-invasive, and cost-effective tool for meningioma patients to assist in better counselling on the risks, appropriate individual treatment decisions, and customized follow-up plans. KEY POINTS: • Machine learning models were built to predict post-GKS edema in meningioma. The random survival forest model with clinical, semantic, and ADC radiomics features achieved excellent performance. • The nomogram based on the predicted risks provides personalized prediction with a C-index of 0.962 (95%CI: 0.951-0.973) and satisfactory calibration and shows the potential to assist in better counselling, appropriate treatment decisions, and customized follow-up plans. • Given the excellent performance and convenient acquisition of the conventional sequence, we envision that this non-invasive and cost-effective tool will facilitate personalized medicine in meningioma treatment.

Glioblastomas with and without peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintensity present morphological and microstructural differences on conventional MR images.

OBJECTIVES: Glioblastoma (GB) without peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintensity is atypical and its characteristics are barely known. The aim of this study was to explore the differences in pathological and MRI-based intrinsic features (including morphologic and first-order features) between GBs with peritumoral FLAIR hyperintensity (PFH-bearing GBs) and GBs without peritumoral FLAIR hyperintensity (PFH-free GBs). METHODS: In total, 155 patients with pathologically diagnosed GBs were retrospectively collected, which included 110 PFH-bearing GBs and 45 PFH-free GBs. The pathological and imaging data were collected. The Visually AcceSAble Rembrandt Images (VASARI) features were carefully evaluated. The first-order radiomics features from the tumor region were extracted from FLAIR, apparent diffusion coefficient (ADC), and T1CE (T1-contrast enhanced) images. All parameters were compared between the two groups of GBs. RESULTS: The pathological data showed more alpha thalassemia/mental retardation syndrome X-linked (ATRX)-loss in PFH-free GBs compared to PFH-bearing ones (p < 0.001). Based on VASARI evaluation, PFH-free GBs had larger intra-tumoral enhancing proportion and smaller necrotic proportion (both, p < 0.001), more common non-enhancing tumor (p < 0.001), mild/minimal enhancement (p = 0.003), expansive T1/FLAIR ratio (p < 0.001) and solid enhancement (p = 0.009), and less pial invasion (p = 0.010). Moreover, multiple ADC- and T1CE-based first-order radiomics features demonstrated differences, especially the lower intensity heterogeneity in PFH-free GBs (for all, adjusted p < 0.05). CONCLUSIONS: Compared to PFH-bearing GBs, PFH-free ones demonstrated less immature neovascularization and lower intra-tumoral heterogeneity, which would be helpful in clinical treatment stratification. CLINICAL RELEVANCE STATEMENT: Glioblastomas without peritumoral FLAIR hyperintensity show less immature neovascularization and lower heterogeneity leading to potential higher treatment benefits due to less drug resistance and treatment failure. KEY POINTS: • The study explored the differences between glioblastomas with and without peritumoral FLAIR hyperintensity. • Glioblastomas without peritumoral FLAIR hyperintensity showed less necrosis and contrast enhancement and lower intensity heterogeneity. • Glioblastomas without peritumoral FLAIR hyperintensity had less immature neovascularization and lower tumor heterogeneity.

Genotoxicity assessment of eight nitrosamines using 2D and 3D HepaRG cell models.

N-nitrosamine impurities have been increasingly detected in human drugs. This is a safety concern as many nitrosamines are mutagenic in bacteria and carcinogenic in rodent models. Typically, the mutagenic and carcinogenic activity of nitrosamines requires metabolic activation by cytochromes P450 enzymes (CYPs), which in many in vitro models are supplied exogenously using rodent liver homogenates. There are only limited data on the genotoxicity of nitrosamines in human cell systems. In this study, we used metabolically competent human HepaRG cells, whose metabolic capability is comparable to that of primary human hepatocytes, to evaluate the genotoxicity of eight nitrosamines [N-cyclopentyl-4-nitrosopiperazine (CPNP), N-nitrosodibutylamine (NDBA), N-nitrosodiethylamine (NDEA), N-nitrosodimethylamine (NDMA), N-nitrosodiisopropylamine (NDIPA), N-nitrosoethylisopropylamine (NEIPA), N-nitroso-N-methyl-4-aminobutyric acid (NMBA), and N-nitrosomethylphenylamine (NMPA)]. Under the conditions we used to culture HepaRG cells, three-dimensional (3D) spheroids possessed higher levels of CYP activity compared to 2D monolayer cells; thus the genotoxicity of the eight nitrosamines was investigated using 3D HepaRG spheroids in addition to more conventional 2D cultures. Genotoxicity was assessed as DNA damage using the high-throughput CometChip assay and as aneugenicity/clastogenicity in the flow-cytometry-based micronucleus (MN) assay. Following a 24-h treatment, all the nitrosamines induced DNA damage in 3D spheroids, while only three nitrosamines, NDBA, NDEA, and NDMA, produced positive responses in 2D HepaRG cells. In addition, these three nitrosamines also caused significant increases in MN frequency in both 2D and 3D HepaRG models, while NMBA and NMPA were positive only in the 3D HepaRG MN assay. Overall, our results indicate that HepaRG spheroids may provide a sensitive, human-based cell system for evaluating the genotoxicity of nitrosamines.

Oligodendrocyte Transcription Factor 2 as a Potential Prognostic Biomarker of Glioblastoma: Kaplan-Meier Analysis and the Development of a Binary Predictive Model Based on Visually Accessible Rembrandt Image and Magnetic Resonance Imaging Radiomic Features.

OBJECTIVE: Oligodendrocyte transcription factor 2 (OLIG2) is universally expressed in human glioblastoma (GB). Our study explores whether OLIG2 expression impacts GB patients' overall survival and establishes a machine learning model for OLIG2 level prediction in patients with GB based on clinical, semantic, and magnetic resonance imaging radiomic features. METHODS: Kaplan-Meier analysis was used to determine the optimal cutoff value of the OLIG2 in 168 GB patients. Three hundred thirteen patients enrolled in the OLIG2 prediction model were randomly divided into training and testing sets in a ratio of 7:3. The radiomic, semantic, and clinical features were collected for each patient. Recursive feature elimination (RFE) was used for feature selection. The random forest (RF) model was built and fine-tuned, and the area under the curve was calculated to evaluate the performance. Finally, a new testing set excluding IDH-mutant patients was built and tested in a predictive model using the fifth edition of the central nervous system tumor classification criteria. RESULTS: One hundred nineteen patients were included in the survival analysis. Oligodendrocyte transcription factor 2 was positively associated with GB survival, with an optimal cutoff of 10% ( P = 0.00093). One hundred thirty-four patients were eligible for the OLIG2 prediction model. An RFE-RF model based on 2 semantic and 21 radiomic signatures achieved areas under the curve of 0.854 in the training set, 0.819 in the testing set, and 0.825 in the new testing set. CONCLUSIONS: Glioblastoma patients with ≤10% OLIG2 expression tended to have worse overall survival. An RFE-RF model integrating 23 features can predict the OLIG2 level of GB patients preoperatively, irrespective of the central nervous system classification criteria, further guiding individualized treatment.

[Characteristics and Risk Evaluation of Heavy Metal Contamination in Paddy Soils in the Three Gorges Reservoir Area].

Soil Cd, Hg, Pb, As, Cr, Cu, Zn, and Ni of 12 districts in the Three Gorges Reservoir area (Chongqing section) were analyzed, and different evaluation methods were used to assess the degree of contamination, potential ecological risk, and human health risk of soil heavy metals in paddy soils. The results showed that the average values of all heavy metals except Cr in paddy soils in the Three Gorges Reservoir area exceeded the background values of soils in the Three Gorges Reservoir area, and the contents of Cd, Cu, and Ni in 12.32%, 4.35%, and 2.54% of the soil samples exceeded the screening values, respectively. The variation coefficients of the eight heavy metals were 29.08%-56.43%, which belonged to the medium and above-intensity variation levels and were influenced by anthropogenic activities. The eight heavy metals were contaminated in the soil, and 16.30%, 6.52%, and 2.90% of the soil Cd, Hg, and Pb were heavily contaminated. At the same time, the potential ecological risk of soil Hg and Cd were in the medium risk level on the whole. Wuxi County and Wushan County had relatively high pollution levels among the 12 districts, the Nemerow pollution index showed a moderate pollution level, and the comprehensive potential ecological risks were also at a moderate ecological hazard level. The results of the health risk evaluation showed that hand-mouth intake was the main exposure path of non-carcinogenic risk and carcinogenic risk. Soil heavy metals presented no non-carcinogenic risk for adults (HI<1), but 12.68% of the sites had non-carcinogenic risk for children (HI>1). As and Cr were the main influencing factors for non-carcinogenic and carcinogenic risks in the study area, and their total contributions to non-carcinogenic and carcinogenic risks were more than 75% and 95%, respectively, which was cause for concern.