Artificial Intelligence-Based Mitosis Scoring in Breast Cancer: Clinical Application.

In recent years, artificial intelligence (AI) has demonstrated exceptional performance in mitosis identification and quantification. However, the implementation of AI in clinical practice needs to be evaluated against the existing methods. This study is aimed at assessing the optimal method of using AI-based mitotic figure scoring in breast cancer (BC). We utilized whole slide images from a large cohort of BC with extended follow-up comprising a discovery (n = 1715) and a validation (n = 859) set (Nottingham cohort). The Cancer Genome Atlas of breast invasive carcinoma (TCGA-BRCA) cohort (n = 757) was used as an external test set. Employing automated mitosis detection, the mitotic count was assessed using 3 different methods, the mitotic count per tumor area (MCT; calculated by dividing the number of mitotic figures by the total tumor area), the mitotic index (MI; defined as the average number of mitotic figures per 1000 malignant cells), and the mitotic activity index (MAI; defined as the number of mitotic figures in 3 mm2 area within the mitotic hotspot). These automated metrics were evaluated and compared based on their correlation with the well-established visual scoring method of the Nottingham grading system and Ki67 score, clinicopathologic parameters, and patient outcomes. AI-based mitotic scores derived from the 3 methods (MCT, MI, and MAI) were significantly correlated with the clinicopathologic characteristics and patient survival (P < .001). However, the mitotic counts and the derived cutoffs varied significantly between the 3 methods. Only MAI and MCT were positively correlated with the gold standard visual scoring method used in Nottingham grading system (r = 0.8 and r = 0.7, respectively) and Ki67 scores (r = 0.69 and r = 0.55, respectively), and MAI was the only independent predictor of survival (P < .05) in multivariate Cox regression analysis. For clinical applications, the optimum method of scoring mitosis using AI needs to be considered. MAI can provide reliable and reproducible results and can accurately quantify mitotic figures in BC.

Head-to-head: Should Ki67 proliferation index be included in the formal classification of pulmonary neuroendocrine neoplasms?

The reporting of lung neuroendocrine neoplasms (NENs) according to the 2021 World Health Organisation (WHO) is based on mitotic count per 2 mm2, necrosis assessment and a constellation of cytological and immunohistochemical details. Accordingly, typical carcinoid and atypical carcinoid are low- to intermediate-grade neuroendocrine tumours (NETs), while large-cell neuroendocrine carcinoma (NEC) and small-cell lung carcinoma are high-grade NECs. In small-sized diagnostic material (cytology and biopsy), the noncommittal term of carcinoid tumour/NET not otherwise specified (NOS) and metastatic carcinoid NOS have been introduced with regard to primary and metastatic diagnostic settings, respectively. Ki-67 antigen, a well-known marker of cell proliferation, has been included in the WHO classification as a non-essential but desirable criterion, especially to distinguish NETs from high-grade NECs and to delineate the provisional category of carcinoid tumours/NETs with elevated mitotic counts (> 10 mitoses per mm2) and/or Ki-67 proliferation index (≥ 30%). However, a wider use of this marker in the spectrum of lung NENs continues to be highly reported and debated, thus witnessing a never-subsided attention. Therefore, the arguments for and against incorporating Ki-67 in the classification and clinical practice of these neoplasms are discussed herein in detail.

Mitotic activity: A systematic literature review of the assessment methodology and prognostic value in canine tumors.

One of the most relevant prognostic indices for tumors is cellular proliferation, which is most commonly measured by the mitotic activity in routine tumor sections. The goal of this systematic review was to analyze the methods and prognostic relevance of histologically measuring mitotic activity that have been reported for canine tumors in the literature. A total of 137 articles that correlated the mitotic activity in canine tumors with patient outcome were identified through a systematic (PubMed and Scopus) and nonsystematic (Google Scholar) literature search and eligibility screening process. Mitotic activity methods encompassed the mitotic count (MC, number of mitotic figures per tumor area) in 126 studies, presumably the MC (method not specified) in 6 studies, and the mitotic index (MI, number of mitotic figures per number of tumor cells) in 5 studies. A particularly high risk of bias was identified based on the available details of the MC methods and statistical analyses, which often did not quantify the prognostic discriminative ability of the MC and only reported P values. A significant association of the MC with survival was found in 72 of 109 (66%) studies. However, survival was evaluated by at least 3 studies in only 7 tumor types/groups, of which a prognostic relevance is apparent for mast cell tumors of the skin, cutaneous melanoma, and soft tissue tumor of the skin and subcutis. None of the studies using the MI found a prognostic relevance. This review highlights the need for more studies with standardized methods and appropriate analysis of the discriminative ability to prove the prognostic value of the MC and MI in various tumor types. Future studies are needed to evaluate the influence of the performance of individual pathologists on the appropriateness of prognostic thresholds and investigate methods to improve interobserver reproducibility.

Mitotic activity: A systematic literature review of the assessment methodology and prognostic value in feline tumors.

Increased proliferation is a driver of tumorigenesis, and quantification of mitotic activity is a standard task for prognostication. This systematic review is an analysis of all available references on mitotic activity in feline tumors to provide an overview of the assessment methods and prognostic value. A systematic literature search in PubMed and Scopus and a nonsystematic search in Google Scholar were conducted. All articles on feline tumors that correlated mitotic activity with patient outcome were identified. Data analysis revealed that of the 42 eligible articles, mitotic count (MC, mitotic figures/tumor area) was evaluated in 39 studies, and mitotic index (MI, mitotic figures/tumor cells) in 3 studies. The risk of bias was considered high for most studies (26/42, 62%) based on small study populations, insufficient details of the MC/MI methods, and lack of statistical measures for diagnostic accuracy or effect on outcome. The MC/MI methods varied between studies. A significant association of MC with survival was determined in 20 of 28 (71%) studies (10 studies evaluated other outcome metrics or provided individual patient data), while 1 study found an inverse effect. Three tumor types had at least 4 studies, and a prognostic association with survival was found in 5 of 6 studies on mast cell tumors, 5 of 5 on mammary tumors, and 3 of 4 on soft-tissue sarcomas. MI was shown to correlate with survival for mammary tumors by 2 research groups; however, comparisons to MC were not conducted. Further studies with standardized mitotic activity methods and appropriate statistical analysis for discriminant ability of patient outcome are needed to infer the prognostic value of MC and MI.

Prognostic impact of Ki-67 in canine splenic hemangiosarcoma: A preliminary study.

Canine splenic hemangiosarcoma has a high metastatic rate and short survival time. Currently, the main prognostic parameters are tumor stage and therapy, while data on histologic parameters, such as grade and Ki-67 expression, are scarce. The aims of this study were to compare two methods of assessment of Ki-67, verify their prognostic impact, and define a threshold value based on survival. Thirty-one cases of histologically diagnosed canine splenic hemangiosarcoma, which were treated with splenectomy and had full staging and follow-up information, were collected. Three were stage I, 17 stage II, and 11 stage III. The mean mitotic count (MC) was 23.9 (standard deviation [SD]: 22.1) and the median was 15 (range, 1-93). Immunohistochemistry for Ki-67 was performed, the Ki-67 labeling index (Ki-67LI) was assessed as a percentage of positive neoplastic nuclei per ≥500 cell, and the Ki-67 count (KI-67C) was defined as the average number of positive nuclei using a 1 cm2 optical grid performed in 5, 40× fields. The mean Ki-67LI and Ki-67C were 56.4% (SD: 38.7) and 27.2 (SD: 12.9) and medians were 51% (range, 8.2-55.2) and 26 (range, 5.5-148), respectively. Using a cut-off of 56% and 9, respectively, Kaplan-Meier survival curves showed an association of overall survival with Ki-67LI and MC. In addition to clinical stage, Ki-67LI maintained its prognostic value on multivariate analysis, supporting the role of Ki-67LI as an independent prognostic parameter. Based on these results, we propose a diagnostically applicable cut-off value of 56% for Ki-67LI as a prognostic parameter for canine splenic hemangiosarcoma.

True Mitotic Count Prediction in Gastrointestinal Stromal Tumors: Bayesian Network Model and PROMETheus (Preoperative Mitosis Estimator Tool) Application Development.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) present a complex clinical landscape, where precise preoperative risk assessment plays a pivotal role in guiding therapeutic decisions. Conventional methods for evaluating mitotic count, such as biopsy-based assessments, encounter challenges stemming from tumor heterogeneity and sampling biases, thereby underscoring the urgent need for innovative approaches to enhance prognostic accuracy. OBJECTIVE: The primary objective of this study was to develop a robust and reliable computational tool, PROMETheus (Preoperative Mitosis Estimator Tool), aimed at refining patient stratification through the precise estimation of mitotic count in GISTs. METHODS: Using advanced Bayesian network methodologies, we constructed a directed acyclic graph (DAG) integrating pertinent clinicopathological variables essential for accurate mitotic count prediction on the surgical specimen. Key parameters identified and incorporated into the model encompassed tumor size, location, mitotic count from biopsy specimens, surface area evaluated during biopsy, and tumor response to therapy, when applicable. Rigorous testing procedures, including prior predictive simulations, validation utilizing synthetic data sets were employed. Finally, the model was trained on a comprehensive cohort of real-world GIST cases (n=80), drawn from the repository of the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, with a total of 160 cases analyzed. RESULTS: Our computational model exhibited excellent diagnostic performance on synthetic data. Different model architecture were selected based on lower deviance and robust out-of-sample predictive capabilities. Posterior predictive checks (retrodiction) further corroborated the model's accuracy. Subsequently, PROMETheus was developed. This is an intuitive tool that dynamically computes predicted mitotic count and risk assessment on surgical specimens based on tumor-specific attributes, including size, location, surface area, and biopsy-derived mitotic count, using posterior probabilities derived from the model. CONCLUSIONS: The deployment of PROMETheus represents a potential advancement in preoperative risk stratification for GISTs, offering clinicians a precise and reliable means to anticipate mitotic counts on surgical specimens and a solid base to stratify patients for clinical studies. By facilitating tailored therapeutic strategies, this innovative tool is poised to revolutionize clinical decision-making paradigms, ultimately translating into improved patient outcomes and enhanced prognostic precision in the management of GISTs.

Digital image analysis of Ki67 hotspot detection and index counting in gastroenteropancreatic neuroendocrine neoplasms.

The Ki-67 proliferative index plays a pivotal role in the subclassification of neuroendocrine neoplasm (NEN) according to the WHO Classification of Digestive System Tumors (5th edition), which designates neuroendocrine tumor (NET) grades 1, 2, and 3 for Ki-67 proliferative index of <3 %, 3-20 %, and >20 %, respectively. Proliferative index calculation must be performed in the hotspot, traditionally selected by visual scanning at low-power magnification. Recently, gradient map visualization has emerged as a tool for various purposes, including hotspot selection. This study includes 97 cases of gastrointestinal neuroendocrine neoplasms, with hotspots selected by bare eye and gradient map visualization (GM). Each hotspot was analyzed using three methods: eye estimation (EE), digital image analysis (DIA), and manual counting. Of the NENs studied, 91 % were NETs (26 % for G1, 55 % for G2, and 10 % for G3). Only 9 cases were neuroendocrine carcinoma (NEC). Between two hotspot selection methods, GM resulted in a higher grade in 14.77 % of cases, primarily upgrading from NET G1 to G2. Among the counting methods, DIA demonstrated substantial agreement with manual counting, both for pathologist and resident. Grading by other methods tended to result in a higher grade than MC (26.99 % with EE and 8.52 % with DIA). Given its clinical and statistical significance, this study advocates for the application of GM in hotspot selection to identify higher-grade tumors. Furthermore, DIA provides accurate grading, offering time efficiency over MC.

PROTECTIVE EFFECT OF A NEW SUPEROXIDE-PRODUCING ENZYME COMPLEX FROM RASPBERRY IN RATS WITH THIRD-DEGREE THERMAL BURNS.

Thermal burns are the most common type of burn injuries. Medical treatment for burns is crucial, especially for third-degree burns and when a significant surface area of the body is affected. One of the most pressing issues in modern medicine is the search for new effective means to accelerate the healing of burn wounds. Oxygen radicals play a significant role in maintaining homeostasis, forming the body's resistance to infection, and ensuring the regeneration of organs and tissues. In this study, a superoxide (O2-)-producing enzyme (SPE) from raspberries was applied (topically to the skin, injected under the wound surface, with solution concentrations of 12.75% and 5%) after a third-degree thermal burn to determine its reparative effects on the skin. To assess the condition of the animals that had suffered burn injuries and the healing process, blood parameters were analyzed, and cytogenetic indices of bone marrow from the femur of the animals were studied: mitotic index, number of polyploid cells, and chromosomal aberrations. When analyzing hematological, cytogenetic, and histological parameters, significant differences were found between the «clean burn¼ groups and the groups in which SPE was used in different concentrations and methods of application. The use of SPE in both concentrations contributed to a reduction in the area of burn wounds compared to a «clean burn¼. The survival rate of animals for 30 days (before the end of the experiment) was 100% when using a 12.75% SPE solution and 50% when using a 5% SPE solution. The use of SPE led to significant differences in hematological parameters from the «clean burn¼ group throughout the entire duration of the experiment, showing a tendency to normalize the parameters. Under the influence of the 12.75% SPE solution, there was a tendency toward normalization of the mitotic index, along with a significant reduction in the percentage of polyploid cells and chromosomal aberrations, which may indicate its beneficial effects. This study found that a 12.75% SPE solution derived from raspberries was more effective and had healing properties on third-degree thermal burns, promoting rapid healing of the burn wound.

Combined proliferation and apoptosis index provides better risk stratification in breast cancer.

AIMS: Breast cancer (BC) risk stratification is critical for predicting behaviour and guiding management decision-making. Despite the well-established prognostic value of cellular proliferation in BC, the interplay between proliferation and apoptosis remains to be defined. In this study, we hypothesised that the combined proliferation and apoptosis indices can provide a more accurate in-vivo growth rate measure and a precise prognostic predictor. METHODS AND RESULTS: Apoptotic and mitotic figures were counted in whole slide images (WSI) generated from haematoxylin and eosin-stained sections of 1545 BC cases derived from two well-defined BC cohorts. Counts were carried out visually within defined areas. There was a significant correlation between mitosis and apoptosis scores. High apoptotic counts were associated with features of aggressive behaviour, including high grade, high pleomorphism score and hormonal receptor negativity. Although the mitotic index (MI) and apoptotic index (AI) were independent prognostic indicators, the prognostic value was synergistically higher when combined. BC patients with a high combined AI and MI had the shortest survival. Replacing the mitosis score with the mitosis-apoptosis index in the Nottingham grading system revealed that the modified grade with the new score had a higher significant association with BC-specific survival with a higher hazard ratio. CONCLUSION: Apoptotic figures count provides additional prognostic value in BC when combined with MI; such a combination can be implemented to assess the behaviour of BC and provides an accurate prognostic indicator. This can be considered when using artificial intelligence algorithms to assess proliferation in BC.

Improving mitotic cell counting accuracy and efficiency using phosphohistone-H3 (PHH3) antibody counterstained with haematoxylin and eosin as part of breast cancer grading.

BACKGROUND: Mitotic count in breast cancer is an important prognostic marker. Unfortunately, substantial inter- and intraobserver variation exists when pathologists manually count mitotic figures. To alleviate this problem, we developed a new technique incorporating both haematoxylin and eosin (H&E) and phosphorylated histone H3 (PHH3), a marker highly specific to mitotic figures, and compared it to visual scoring of mitotic figures using H&E only. METHODS: Two full-face sections from 97 cases were cut, one stained with H&E only, and the other was stained with PHH3 and counterstained with H&E (PHH3-H&E). Counting mitoses using PHH3-H&E was compared to traditional mitoses scoring using H&E in terms of reproducibility, scoring time, and the ability to detect mitosis hotspots. We assessed the agreement between manual and image analysis-assisted scoring of mitotic figures using H&E and PHH3-H&E-stained cells. The diagnostic performance of PHH3 in detecting mitotic figures in terms of sensitivity and specificity was measured. Finally, PHH3 replaced the mitosis score in a multivariate analysis to assess its significance. RESULTS: Pathologists detected significantly higher mitotic figures using the PHH3-H&E (median ± SD, 20 ± 33) compared with H&E alone (median ± SD, 16 ± 25), P < 0.001. The concordance between pathologists in identifying mitotic figures was highest when using the dual PHH3-H&E technique; in addition, it highlighted mitotic figures at low power, allowing better agreement on choosing the hotspot area (k = 0.842) in comparison with standard H&E (k = 0.625). A better agreement between image analysis-assisted software and the human eye was observed for PHH3-stained mitotic figures. When the mitosis score was replaced with PHH3 in a Cox regression model with other grade components, PHH3 was an independent predictor of survival (hazard ratio [HR] 5.66, 95% confidence interval [CI] 1.92-16.69; P = 0.002), and even showed a more significant association with breast cancer-specific survival (BCSS) than mitosis (HR 3.63, 95% CI 1.49-8.86; P = 0.005) and Ki67 (P = 0.27). CONCLUSION: Using PHH3-H&E-stained slides can reliably be used in routine scoring of mitotic figures and integrating both techniques will compensate for each other's limitations and improve diagnostic accuracy, quality, and precision.

In vitro cytogenotoxic evaluation of aripiprazole on human peripheral lymphocytes and computational molecular docking analysis.

Two different drug groups, typical (classic) and atypical (new), are used in the treatment of schizophrenia. Aripiprazole, an atypical antipsychotic chemical, is the active ingredient of the drug Abilify. This study was conducted to determine the possible genotoxic effect of aripiprazole. For this purpose, four different doses of aripiprazole (5; 10; 20, and 40 µg/mL) were examined with Chromosome Abnormality (CA), Sister Chromatid Exchange (SCE), Micronucleus (MN) tests. Based on these tests, Proliferation Index (PI), Percent Abnormal Cells (AC), Mitotic Index (MI), Micronuclear Binuclear Cell (MNBN), and Nuclear Division Index (NDI) levels were determined in human peripheral lymphocytes treated for 24 and 48 hours. Also, to determine possible binding sites of Aripiprazole on B-DNA molecular docking analysis was performed using AutoDock 4.0 (B-DNA dodecamer, PDB code: 1BNA). Aripiprazole binds to B-DNA with a very significant free binding energy (-11.88 Kcal/mol). According to our study, aripiprazole did not significantly change SCE, CA, AC percentage, MN frequencies when compared with control. According to these results, aripiprazole does not have a genotoxic effect. At the same time, no significant change was observed in the PI, MI, and NDI frequencies when compared with the control. In line with these results, it was observed that the use of aripiprazole in the treatment of schizophrenia did not pose any acute genotoxic and cytotoxic risk.

A rare case of sclerosing meningioma with immunohistochemical features.

To identify histological types of Meningiomas', immunohistochemically markers are used. We present Phosphohistone-H3 (PHH-3) staining for the first time. The patient's case notes were retrospectively reviewed. PHH-3 staining revealed sparse mitotically active cells. PHH-3 staining can be used to grade sclerosing meningioma.

Prediction of the mitotic index and preoperative risk stratification of gastrointestinal stromal tumors with CT radiomic features.

OBJECTIVE: The objective is to develop a mitotic prediction model and preoperative risk stratification nomogram for gastrointestinal stromal tumor (GIST) based on computed tomography (CT) radiomic features. METHODS: A total of 267 GIST patients from 2009.07 to 2015.09 were retrospectively collected and randomly divided into (6:4) training cohort and validation cohort. The 2D-tumor region of interest was delineated from the portal-phase images on contrast-enhanced (CE)-CT, and radiomic features were extracted. Lasso regression method was used to select valuable features to establish a radiomic model for predicting mitotic index in GIST. Finally, the nomogram of preoperative risk stratification was constructed by combining the radiomic features and clinical risk factors. RESULTS: Four radiomic features closely related to the level of mitosis were obtained, and a mitotic radiomic model was constructed. The area under the curve (AUC) of the radiomics signature model used to predict mitotic levels in training and validation cohorts (training cohort AUC = 0.752; 95% confidence interval [95%CI] 0.674-0.829; validation cohort AUC = 0.764; 95% CI 0.667-0.862). Finally, the preoperative risk stratification nomogram combining radiomic features was equivalent to the clinically recognized gold standard AUC (0.965 vs. 0.983) (p = 0.117). The Cox regression analysis found that the nomogram score was one of the independent risk factors for the long-term prognosis of the patients. CONCLUSION: Preoperative CT radiomic features can effectively predict the level of mitosis in GIST, and combined with preoperative tumor size, accurate preoperative risk stratification can be performed to guide clinical decision-making and individualized treatment.

Different miRNAs Related to FBXW7 Mutations or High Mitotic Indices Contribute to Rectal Neuroendocrine Tumors: A Pilot Study.

Recent studies suggest that miRNA may be involved in the development of rectal neuroendocrine tumors (NETs). We explored the frequency of clinicopathologically relevant mutations and miRNA expression in rectal NETs to examine molecular profiles related to prognosis and behavior. Twenty-four eligible specimens with endoscopically excised rectal NETs were selected. Next-generation sequencing and an miRNA expression assay were used to evaluate the expression profile relevant to common genetic mutations in rectal NETs. Kyoto Encyclopedia of Genes and Genomes analysis predicted that the possible target signaling pathways were correlated with dysregulated miRNAs. Nineteen rectal NETs harbored more than one mutation in the 24 cancer-related genes. Seven miRNAs (hsa-miR-769-5p, hsa-miR-221-3p, hsa-miR-34a-5p, hsa-miR-181c-5p, hsa-miR-1246, hsa-miR-324-5p, and hsa-miR-361-3p) were significantly down-regulated in tumors harboring the FBWX7 mutation. Unsupervised hierarchical clustering analysis showed that up-regulation of these seven miRNAs may result in high mitotic indices, indicating the role of miRNAs in tumor progression. Among the down-regulated miRNAs, hsa-miR-769-5p was strongly correlated with extracellular matrix-receptor interaction and lysine degradation. Among the clinicopathological factors, up-regulated hsa-miR-3934-5p was linked to an increased mitotic count. No change in miRNA expression was associated with a tumor size >1 cm, lymphovascular invasion, or Ki-67 index. In summary, we identified different miRNA signatures involved in FBXW7 mutations or high mitotic indices in rectal NETs, which may play a critical role in tumor behavior.

The Role of Insulin-like Growth Factor-Axis and Mitotic Index in South Indian Neonates with Small for Gestational Age.

OBJECTIVE: IGF-axis and mitotic capacity of cells play a vital role in fetal growth. We compared IGF1, IGF2, and IGFBP3 protein levels, mitotic indices, IGFR1 and IGFR2 mRNA expression in appropriate for gestational age (AGA) and small for gestational age (SGA) neonates of Indian women. METHODS: Cord blood (n = 80) and placental samples (n = 40) were collected from AGA and SGA neonates. Plasma IGF1, IGF2, and IGFBP3 proteins were measured by ELISA. IGFR1 and IGFR2 mRNA expression in the placenta were analyzed by qRT-PCR. Cord blood was cultured in vitro and mitotic index was obtained. RESULTS: IGF1 (p = 1), and IGF2 (p = 0.69) protein levels did not differ, whereas IGFBP3 (p = 0.02) was significantly less in SGA compared to AGA neonates. Down-regulation of IGFR1 (3.9-folds) and IGFR2 (2.8-folds) mRNA and reduced mitotic index of lymphocytes was observed in SGA (p = 0.001) compared to AGA neonates. CONCLUSION: Our results showed that, SGA neonates displayed down-regulated IGFR1 and IGFR2 mRNA, decreased IGFBP3 protein and mitotic index.

Correlation of Endoscopic Ultrasonography Features with the Mitotic Index in 2- to 5-cm Gastric Gastrointestinal Stromal Tumors.

BACKGROUND: Predicting the malignancy potential of gastrointestinal stromal tumor (GIST) before resection could improve patient management strategies as gastric GISTs with a low malignancy potential can be safely treated endoscopically, but surgical resection is required for those tumors with a high malignancy potential. This study aimed to evaluate endoscopic ultrasound (EUS) features of 2- to 5-cm gastric GISTs that might be used to predict their mitotic index using surgical specimens as the gold standard. PATIENTS AND METHODS: Forty-nine patients (30 females and 19 males; mean age 55.1 ± 12.7 years) who underwent EUS examinations, followed by surgical resections of 2- to 5-cm gastric GISTs, were retrospectively reviewed. RESULTS: The mean tumor size was 3.44 ± 0.97 (range 2.1-5.0) cm. A univariate analysis revealed no significant differences in age, sex, and tumor location in the low mitotic index and high mitotic index groups (all p > 0.05). In terms of EUS features, there were no significant differences in the mitotic indexes with respect to the shape, surface lobulation, border regularity, echogenicity, homogeneity, growth patterns, presence of mucosal ulceration, hyperechogenic foci, anechoic spaces, and hypoechoic halos (all p > 0.05). However, the tumor size was larger in the high mitotic index group than that in the low mitotic index group (3.97 ± 1.05 vs. 3.27 ± 0.9 cm, p = 0.03). CONCLUSION: Conventional EUS features are not reliable for predicting the mitotic index of 2- to 5-cm gastric GISTs. Further modalities for predicting the mitotic index are needed to prevent unnecessary surgical resections in patients with a low risk of malignancy.

Cytogenotoxicity assessment in Allium cepa roots exposed to methyl orange treated with Oedogonium subplagiostomum AP1.

The present study is an attempt to assess the cytogenotoxic effect of untreated and methyl orange treated with Oedogonium subplagiostomum AP1 on Allium cepa roots. On the fifth day, root growth, root length, mitotic index, mitotic inhibition/depression, and chromosomal abnormalities were measured in root cells of Allium cepa subjected to untreated and treated methyl orange dye solutions. Roots exposed to treated dye solution exhibited maximum root growth, root length and mitotic index, whereas roots exposed to untreated dye solution had the most mitotic inhibition and chromosomal abnormalities. Allium cepa exposed to untreated dye solution revealed chromosomal aberrations such as disoriented and abnormal chromosome grouping, vagrant and laggard chromosomes, chromosomal loss, sticky chain and disturbed metaphase, pulverised and disturbed anaphase, chromosomal displacement in anaphase, abnormal telophase, and chromosomal bridge at telophase, spindle disturbances and binucleate cells. The comet test was used to quantify DNA damage in the root cells of A. cepa subjected to untreated and treated methyl orange solutions in terms of tail DNA (percent) and tail length. The results concluded that A. cepa exposed to methyl orange induced DNA damage whereas meager damage was noted in the treated dye solution. As a result, the research can be used as a biomarker to detect the genotoxic effects of textile dyes on biota.

Use of Artificial Intelligence in the Prediction of Malignant Potential of Gastric Gastrointestinal Stromal Tumors.

BACKGROUND AND AIMS: This study aimed to investigate whether AI via a deep learning algorithm using endoscopic ultrasonography (EUS) images could predict the malignant potential of gastric gastrointestinal stromal tumors (GISTs). METHODS: A series of patients who underwent EUS before surgical resection for gastric GISTs were included. A total of 685 images of GISTs from 55 retrospectively included patients were used as the training data set for the AI system. Convolutional neural networks were constructed to build a deep learning model. After applying the synthetic minority oversampling technique, 70% of the generated images were used for AI training and 30% were used to test AI diagnoses. Next, validation was performed using 153 EUS images of 15 patients with GISTs. In addition, conventional EUS features of 55 patients in the training cohort were evaluated to predict the malignant potential of GISTs and mitotic index. RESULTS: The overall sensitivity, specificity, and accuracy of the AI system for predicting malignancy risk were 83%, 94%, and 82% in the training dataset, and 75%, 73%, and 66% in the validation cohort, respectively. When patients were divided into low-risk and high-risk groups, sensitivity, specificity, and accuracy increased to 99% in the training dataset and 99.7%, 99.7%, and 99.6%, respectively, in the validation cohort. No conventional EUS features were found to be associated with either malignant potential or mitotic index (P > 0.05). CONCLUSIONS: AI via a deep learning algorithm using EUS images could predict the malignant potential of gastric GISTs with high accuracy.

Retrospective study of the clinicopathological characteristics and prognostic factors of gastrointestinal stromal tumors in Chinese patients.

The purpose of this study was to investigate the clinicopathological characteristics and prognostic factors of patients with gastrointestinal stromal tumors (GISTs) in mainland China. We retrospectively analyzed the clinicopathological characteristics and survival data of 149 patients with GISTs admitted to Shengjing Hospital of China Medical University from July 2011 to October 2017. The following details were collected from all patients: sex, age, symptoms, preoperative examination, pathology, surgical procedures, and follow-up data. Recurrence-free survival (RFS) and overall survival (OS) were used to assess survival outcomes. The Kaplan-Meier method was performed to draw survival curves and calculate the survival rate. The log-rank test was performed for univariate analysis, and the significant factors were included in multivariate analysis using a Cox proportional hazards model to determine prognostic factors. The 5-year RFS rate was 78.5 % and 5-year OS rate was 83.2 %. The univariate analysis showed that the following prognostic factors could significantly predict 5-year RFS and OS: tumor size, initial status, modified NIH classification, mitotic index, CD117 expression, Ki67 index, and surgical procedure (P < 0.05). The multivariate analysis showed that mitotic index, CD117, and Ki67 index were independent prognostic factors associated with 5-year RFS and 5-year OS. This study provides a reference for the clinicopathological characteristics and prognostic factors of patients with GISTs in mainland China, and the results suggest that focusing on immunohistochemical markers in clinical practice may be more reliable for the prediction of clinical outcomes.

Cytotoxic and genotoxic effects induced by associated commercial glyphosate and 2,4-D formulations using the Allium cepa bioassay.

Studies assessing the toxicity of glyphosate and 2,4-dichlorophenoxyacetic acid mixture are scarce. The aim of this study was to evaluate the cytotoxicity and genotoxicity of the mixture of these herbicides using Allium cepa. Roots were exposed to glyphosate (1.56 and 11.66 mg mL-1), 2,4-D (0.28 and 17.5 mg mL-1) and mixture for 24 h, based on the average concentration applied in the field and the acute reference dose (ARfD) established in Brazil. Both isolated and associated herbicides induced a significative decrease in mitotic index (MI) (P < 0.0001) in all tested concentrations. Regarding the genotoxicity results, 2,4-D and the mixture showed, at concentrations applied in the field, a significative increase of chromosomal anomalies (CA) index compared to control (P < 0.0001) and glyphosate (P = 0.024 and P = 0.0002, respectively). All tested groups from the ARfD showed a significative difference compared to the control group (P < 0.0001), as well as glyphosate and 2,4-D isolated compared to the mixture (P = 0.0005 and P < 0.0001, respectively). The most observed CA were apoptotic bodies, giant cells, and nuclear erosions. We emphasize the need for further studies assessing the toxicity of these herbicides' mixture due to the distinct effects caused in different organisms.