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.

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.

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.

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.

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.

[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.

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.

Revisiting the mutagenicity and genotoxicity of N-nitroso propranolol in bacterial and human in vitro assays.

Propranolol is a widely used ß-blocker that can generate a nitrosated derivative, N-nitroso propranolol (NNP). NNP has been reported to be negative in the bacterial reverse mutation test (the Ames test) but genotoxic in other in vitro assays. In the current study, we systematically examined the in vitro mutagenicity and genotoxicity of NNP using several modifications of the Ames test known to affect the mutagenicity of nitrosamines, as well as a battery of genotoxicity tests using human cells. We found that NNP induced concentration-dependent mutations in the Ames test, both in two tester strains that detect base pair substitutions, TA1535 and TA100, as well as in the TA98 frameshift-detector strain. Although positive results were seen with rat liver S9, the hamster liver S9 fraction was more effective in bio-transforming NNP into a reactive mutagen. NNP also induced micronuclei and gene mutations in human lymphoblastoid TK6 cells in the presence of hamster liver S9. Using a panel of TK6 cell lines that each expresses a different human cytochrome P450 (CYP), CYP2C19 was identified as the most active enzyme in the bioactivation of NNP to a genotoxicant among those tested. NNP also induced concentration-dependent DNA strand breakage in metabolically competent 2-dimensional (2D) and 3D cultures of human HepaRG cells. This study indicates that NNP is genotoxic in a variety of bacterial and mammalian systems. Thus, NNP is a mutagenic and genotoxic nitrosamine and a potential human carcinogen.

Growth and development of oncology nursing in Asia.

Oncology nursing is increasingly recognized around the world as being vitally important for an effective cancer control system. Granted, there is variation between and among countries/regions regarding the strength and nature of that recognition, but oncology nursing is clearly seen as a specialty practice and as a priority for development in cancer control plans, especially for high resource countries/regions. Many countries/regions are beginning to recognize that nurses are vitally important to their cancer control efforts and nurses require specialized education and infrastructure support to make a substantial contribution. The purpose of this paper is to highlight the growth and development of cancer nursing in Asia. Several brief summaries are presented by nurse leaders in cancer care from several Asian countries/regions. Their descriptions reflect illustrations of the leadership nurses are providing in cancer control practice, education, and research in their respective countries/regions. The illustrations also reflect the potential for future development and growth of oncology nursing as a specialty given the many challenges nurses face across Asia. The development of relevant education programs following basic nursing preparation, the establishment of specialty organizations for oncology nurses, and engagement by nurses in policy activity have been influential factors in the growth of oncology nursing in Asia.

Case report: Pathological and genetic features of pancreatic undifferentiated carcinoma with osteoclast-like giant cells.

Objectives: Pancreatic undifferentiated carcinoma accounts for 2%-7% of pancreatic carcinomas. We aimed to investigate the pathological and genetic characteristics of pancreatic undifferentiated carcinoma with osteoclast-like giant cells and the key points of treatment. Methods: The clinical data and follow-up results of four patients diagnosed with pancreatic undifferentiated carcinoma with osteoclast-like giant cells between May 2015 and May 2020 at the First Affiliated Hospital of Xi'an Jiaotong University were retrospectively analyzed. Results: Chief complaints included "pain and discomfort in the upper abdomen" (2/4), "nausea and vomiting" (1/4) or no symptoms (1/4). Preoperative mildly elevated tumor markers included carcinoembryonic antigen (1/4) and CA19-9 (1/4). The tumors were located in the tail of the pancreas in three patients and the head and neck in one patient. Tumor metastasis was found in pancreatic adipose tissue in two patients and lymph node metastasis in one patient, with microscopic heterogeneous mononuclear cells and scattered osteoclast-like giant cells of various sizes. One patient (1/4) had a mucinous cystic tumor of the pancreas, and two patients (2/4) had adenocarcinoma of the pancreatic duct. Only one patient received postoperative gemcitabine combined with albumin-bound paclitaxel chemotherapy. Conclusion: Currently, treatment guidelines are lacking for PUC-OGC, and prognosis varies markedly. More cases must be reported to clarify its origination. The long-term follow-up of diagnosed patients and genetic mutation testing can also contribute to improving treatment and prognosis of this disease.

High-throughput micronucleus assay using three-dimensional HepaRG spheroids for in vitro genotoxicity testing.

The in vitro micronucleus (MN) assay is a component of most test batteries used in assessing potential genotoxicity. Our previous study adapted metabolically competent HepaRG cells to the high-throughput (HT) flow-cytometry-based MN assay for genotoxicity assessment (Guo et al. in J Toxicol Environ Health A 83:702-717, 2020b, https://doi.org/10.1080/15287394.2020.1822972 ). We also demonstrated that, compared to HepaRG cells grown as two-dimensional (2D) cultures, 3D HepaRG spheroids have increased metabolic capacity and improved sensitivity in detecting DNA damage induced by genotoxicants using the comet assay (Seo et al. in ALTEX 39:583-604, 2022, https://doi.org/10.14573/altex.22011212022 ). In the present study, we have compared the performance of the HT flow-cytometry-based MN assay in HepaRG spheroids and 2D HepaRG cells by testing 34 compounds, including 19 genotoxicants or carcinogens and 15 compounds that show different genotoxic responses in vitro and in vivo. 2D HepaRG cells and spheroids were exposed to the test compounds for 24 h, followed by an additional 3- or 6-day incubation with human epidermal growth factor to stimulate cell division. The results demonstrated that HepaRG spheroids showed generally higher sensitivity in detecting several indirect-acting genotoxicants (require metabolic activation) compared to 2D cultures, with 7,12-dimethylbenzanthracene and N-nitrosodimethylamine inducing higher % MN formation along with having significantly lower benchmark dose values for MN induction in 3D spheroids. These data suggest that 3D HepaRG spheroids can be adapted to the HT flow-cytometry-based MN assay for genotoxicity testing. Our findings also indicate that integration of the MN and comet assays improved the sensitivity for detecting genotoxicants that require metabolic activation. These results suggest that HepaRG spheroids may contribute to New Approach Methodologies for genotoxicity assessment.

High CX3CR1 expression predicts poor prognosis in paediatric acute myeloid leukaemia undergoing hyperleukocytosis.

INTRODUCTION: Paediatric AML patients with hyperleukocytosis have a poor prognosis and higher early mortality. Therefore, more studies are needed to explore relevant prognostic indicators and develop effective prevention strategies for this type of childhood AML. METHODS: All original data were obtained from the TARGET database. First, we explored meaningful differentially expressed genes (DEGs) between the hyperleukocytosis group and the non-hyperleukocytosis group. Next, we screened and identified valuable target genes using univariate Cox regression, Cytoscape software, and Kaplan-Meier survival curves. Finally, the coexpressed genes, functional networks, and immune-related activities associated with the target gene were deeply analysed by the GeneMANIA, LinkedOmics, GEPIA2021, TISIDB, and GSCA databases. RESULTS: We selected 1229 DEGs between the hyperleukocytosis group and the non-hyperleukocytosis group in paediatric AML patients. Among them, 495 DEGs were significantly linked with the overall survival of paediatric AML patients. Further, we discovered that CX3CR1 was a promising target gene. Meanwhile, we identified CX3CR1 as an independent prognostic predictor. Besides, we showed that CX3CR1 had strong physical interactions with CX3CL1. Additionally, functional network analysis suggested that CX3CR1 and its coexpressed genes modulated immune response pathways. Subsequent analysis found that immune cells with a high median value of CX3CR1 were monocytes, resting NK cells and CD8 T cells. Finally, we observed that CX3CR1 expression correlated with infiltrating levels of immune cells and immune signatures. CONCLUSION: Elevated CX3CR1 expression may be an adverse prognostic indicator in paediatric AML patients undergoing hyperleukocytosis. Moreover, CX3CR1 may serve as an immunotherapeutic target for AML with hyperleukocytosis in children.

Effect of aerobic exercise on physical function indices in the elderly / Efeito do exercício aeróbico nos índices de função física dos idosos / Efecto del ejercicio aeróbico en los índices de la función física de las personas mayores

ABSTRACT Introduction China is currently experiencing the problem of population aging, and the health status of the elderly has become a major focus of social attention. Objective Study the effect of aerobic exercise on the indices of physical function in the elderly. Methods 40 elderly people performed aerobic exercise 5 times a week for 8 weeks. Each exercise lasted 60 minutes, including 10 minutes of warm-up, 40 minutes of aerobic exercise (running, brisk walking, square dancing, among other activities), and 10 minutes of final cool-down. Data measurement included body indices, cardiopulmonary function, blood markers, and exercise capacity. Results Aerobic exercise can effectively improve the body shape, cardiopulmonary function, and blood lipid content of the elderly, and improve their flexibility and physical quality, enhancing their activities of daily living. Conclusion The results of this study show that aerobic exercise can effectively improve the body performance of the elderly in activities of daily living, effectively optimizing cardiopulmonary and lipid indexes. Engaging the elderly to participate in aerobic exercise should be considered by community social workers. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

RESUMO Introdução A China enfrenta atualmente o problema do envelhecimento populacional, e o estado de saúde dos idosos tornou-se um dos principais focos de atenção social. Objetivo Estudar o efeito do exercício aeróbico nos índices da função física nos idosos. Métodos 40 idosos executaram exercícios aeróbicos 5 vezes por semana durante 8 semanas. Cada exercício teve duração de 60 minutos, incluindo 10 minutos de aquecimento, 40 minutos de exercício aeróbico (corrida, caminhada rápida, dança de quadrilha, entre outras atividades) e 10 minutos de relaxamento final. A mensuração dos dados incluiu índices corporais, função cardiopulmonar, marcadores sanguíneos e capacidade de exercício. Resultados O exercício aeróbico pode efetivamente melhorar a forma corporal, a função cardiopulmonar e o conteúdo lipídico sanguíneo do idoso, além de melhorar a sua flexibilidade e a qualidade física, aprimorando suas atividades de vida diárias. Conclusão Os resultados deste estudo mostram que o exercício aeróbico pode melhorar efetivamente o desempenho corporal dos idosos nas atividades de vida diária, otimizando efetivamente os índices cardiopulmonares e lipídicos. O engajamento dos idosos na participação em exercícios aeróbicos deve ser considerada pelos assistentes sociais comunitários. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

RESUMEN Introducción China se enfrenta actualmente al problema del envejecimiento de la población, y el estado de salud de las personas mayores se ha convertido en un importante foco de atención social. Objetivo Estudiar el efecto del ejercicio aeróbico sobre los índices de función física en los ancianos. Métodos 40 ancianos realizaron ejercicio aeróbico 5 veces por semana durante 8 semanas. Cada ejercicio duró 60 minutos, incluyendo 10 minutos de calentamiento, 40 minutos de ejercicio aeróbico (correr, caminar rápido, bailar, entre otras actividades) y 10 minutos de relajación final. La medición de datos incluía índices corporales, función cardiopulmonar, marcadores sanguíneos y capacidad de ejercicio. Resultados El ejercicio aeróbico puede mejorar eficazmente la forma del cuerpo, la función cardiopulmonar y el contenido de lípidos en la sangre de los ancianos, y mejorar su flexibilidad y calidad física, potenciando sus actividades de la vida diaria. Conclusión Los resultados de este estudio muestran que el ejercicio aeróbico puede mejorar eficazmente el rendimiento corporal de los ancianos en las actividades de la vida diaria, optimizando efectivamente los índices cardiopulmonares y lipídicos. Los trabajadores sociales de la comunidad deberían considerar el compromiso de los ancianos de participar en el ejercicio aeróbico. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.

Corrigendum: Serum cytokine levels for predicting immune-related adverse events and the clinical response in lung cancer treated with immunotherapy.

[This corrects the article DOI: 10.3389/fonc.2022.923531.].

A dual-branch hybrid dilated CNN model for the AI-assisted segmentation of meningiomas in MR images.

BACKGROUND AND OBJECTIVE: Treatment for meningiomas usually includes surgical removal, radiation therapy, and chemotherapy. Accurate segmentation of tumors significantly facilitates complete surgical resection and precise radiotherapy, thereby improving patient survival. In this paper, a deep learning model is constructed for magnetic resonance T1-weighted Contrast Enhancement (T1CE) images to develop an automatic processing scheme for accurate tumor segmentation. METHODS: In this paper, a novel Convolutional Neural Network (CNN) model is proposed for the accurate meningioma segmentation in MR images. It can extract fused features in multi-scale receptive fields of the same feature map based on MR image characteristics of meningiomas. The attention mechanism is added as a helpful addition to the model to optimize the feature information transmission. RESULTS AND CONCLUSIONS: The results were evaluated on two internal testing sets and one external testing set. Mean Dice Similarity Coefficient (DSC) values of 0.886, 0.851, and 0.874 are demonstrated, respectively. In this paper, a deep learning approach is proposed to segment tumors in T1CE images. Multi-center testing sets validated the effectiveness and generalization of the method. The proposed model demonstrates state-of-the-art tumor segmentation performance.