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The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require large amounts of annotated data for training and validation. Furthermore, label noise introduced during the annotation process may impede the algorithms' performance. Unlike H&E, where identification of MFs is based mainly on morphological features, the mitosis-specific antibody phospho-histone H3 (PHH3) specifically highlights MFs. Counting MFs on slides stained against PHH3 leads to higher agreement among raters and has therefore recently been used as a ground truth for the annotation of MFs in H&E. However, as PHH3 facilitates the recognition of cells indistinguishable from H&E staining alone, the use of this ground truth could potentially introduce an interpretation shift and even label noise into the H&E-related dataset, impacting model performance. This study analyzes the impact of PHH3-assisted MF annotation on inter-rater reliability and object level agreement through an extensive multi-rater experiment. Subsequently, MF detectors, including a novel dual-stain detector, were evaluated on the resulting datasets to investigate the influence of PHH3-assisted labeling on the models' performance. We found that the annotators' object-level agreement significantly increased when using PHH3-assisted labeling (F1: 0.53 to 0.74). However, this enhancement in label consistency did not translate to improved performance for H&E-based detectors, neither during the training phase nor the evaluation phase. Conversely, the dual-stain detector was able to benefit from the higher consistency. This reveals an information mismatch between the H&E and PHH3-stained images as the cause of this effect, which renders PHH3-assisted annotations not well-aligned for use with H&E-based detectors. Based on our findings, we propose an improved PHH3-assisted labeling procedure., (© 2024. The Author(s).)

Chronic heart failure is associated with reduced myocardial β-adrenergic receptor expression and mitochondrial function. Since these data coincide with increased plasma catecholamine levels, we investigated the relation between myocardial β-receptor expression and mitochondrial respiratory activity under conditions of physiological catecholamine concentrations. This post hoc analysis used material of a prospective randomized, controlled study on 12 sexually mature (age 20-24 weeks) Early Life Stress or control pigs (weaning at day 21 and 28-35 after birth, respectively) of either sex. Measurements in anesthetized, mechanically ventilated, and instrumented animals comprised serum catecholamine (liquid-chromatography/tandem-mass-spectrometry) and 8-isoprostane levels, whole blood superoxide anion concentrations (electron spin resonance), oxidative DNA strand breaks (tail moment in the "comet assay"), post mortem cardiac tissue mitochondrial respiration, and immunohistochemistry (β 2 -adrenoreceptor, mitochondrial respiration complex, and nitrotyrosine expression). Catecholamine concentrations were inversely related to myocardial mitochondrial respiratory activity and β 2 -adrenoceptor expression, whereas there was no relation to mitochondrial respiratory complex expression. Except for a significant, direct, non-linear relation between DNA damage and noradrenaline levels, catecholamine concentrations were unrelated to markers of oxidative stress. The present study suggests that physiological variations of the plasma catecholamine concentrations, e.g., due to physical and/or psychological stress, may affect cardiac β 2 -adrenoceptor expression and mitochondrial respiration.

Although the Paralympic Games have been around for over 60 years, women remain underrepresented in almost all aspects of the Paralympic Movement. It has been suggested that a way to increase women's involvement is through the implementation of mixed-gender events. On paper, this approach makes sense. However, when it comes to the implementation of mixed-gender opportunities for women, it is less clear how effective these events are in increasing participation by women in Para sport. Through document analysis and interviews with athletes and organizers of mixed-gender Paralympic sport, we explore the various strategies that four mixed-gender sports have used to address the issue of gender parity. Using critical feminist theories, we illustrate how larger social, political, and cultural ideas about gender influence women's experiences within these events and discuss the potential of using mixed-gender initiatives to address gender parity within the Paralympic Movement.

The tumor-stroma ratio (TSR) has been repeatedly shown to be a prognostic factor for survival prediction of different cancer types. However, an objective and reliable determination of the tumor-stroma ratio remains challenging. We present an easily adaptable deep learning model for accurately segmenting tumor regions in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of colon cancer patients into five distinct classes (tumor, stroma, necrosis, mucus, and background). The tumor-stroma ratio can be determined in the presence of necrotic or mucinous areas. We employ a few-shot model, eventually aiming for the easy adaptability of our approach to related segmentation tasks or other primaries, and compare the results to a well-established state-of-the art approach (U-Net). Both models achieve similar results with an overall accuracy of 86.5% and 86.7%, respectively, indicating that the adaptability does not lead to a significant decrease in accuracy. Moreover, we comprehensively compare with TSR estimates of human observers and examine in detail discrepancies and inter-rater reliability. Adding a second survey for segmentation quality on top of a first survey for TSR estimation, we found that TSR estimations of human observers are not as reliable a ground truth as previously thought.

Background: Early Life Stress (ELS) may exert long-lasting biological effects, e.g., on PBMC energy metabolism and mitochondrial respiration. Data on its effect on brain tissue mitochondrial respiration is scarce, and it is unclear whether blood cell mitochondrial activity mirrors that of brain tissue. This study investigated blood immune cell and brain tissue mitochondrial respiratory activity in a porcine ELS model. Methods: This prospective randomized, controlled, animal investigation comprised 12 German Large White swine of either sex, which were weaned at PND (postnatal day) 28-35 (control) or PND21 (ELS). At 20-24 weeks, animals were anesthetized, mechanically ventilated and surgically instrumented. We determined serum hormone, cytokine, and "brain injury marker" levels, superoxide anion (O 2 • ¯) formation and mitochondrial respiration in isolated immune cells and immediate post mortem frontal cortex brain tissue. Results: ELS animals presented with higher glucose levels, lower mean arterial pressure. Most determined serum factors did not differ. In male controls, TNFα and IL-10 levels were both higher than in female controls as well as, no matter the gender in ELS animals. MAP-2, GFAP, and NSE were also higher in male controls than in the other three groups. Neither PBMC routine respiration and brain tissue oxidative phosphorylation nor maximal electron transfer capacity in the uncoupled state (ETC) showed any difference between ELS and controls. There was no significant relation between brain tissue and PBMC, ETC, or brain tissue, ETC, and PBMC bioenergetic health index. Whole blood O 2 • ¯ concentrations and PBMC O 2 • ¯ production were comparable between groups. However, granulocyte O 2 • ¯ production after stimulation with E. coli was lower in the ELS group, and this effect was sex-specific: increased O 2 • ¯ production increased upon stimulation in all control animals, which was abolished in the female ELS swine. Conclusion: This study provides evidence that ELS i ) may, gender-specifically, affect the immune response to general anesthesia as well as O 2 • ¯ radical production at sexual maturity, ii ) has limited effects on brain and peripheral blood immune cell mitochondrial respiratory activity, and iii ) mitochondrial respiratory activity of peripheral blood immune cells and brain tissue do not correlate., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Münz, Wolfschmitt, Zink, Abele, Hogg, Hoffmann, Gröger, Calzia, Waller, Radermacher and Merz.)

Neuroblastoma is the most common extracranial, malignant, solid tumor found in children. In more than one-third of cases, the tumor is in an advanced stage, with limited resectability. The treatment options include resection, with or without (neo-/) adjuvant therapy, and conservative therapy, the latter even with curative intent. Contrast-enhanced MRI is used for staging and therapy monitoring. Diffusion-weighted imaging (DWI) is often included. DWI allows for a calculation of the apparent diffusion coefficient (ADC) for quantitative assessment. Histological tumor characteristics can be derived from ADC maps. Monitoring the response to treatment is possible using ADC maps, with an increase in ADC values in cases of a response to therapy. Changes in the ADC value precede volume reduction. The usual criteria for determining the response to therapy can therefore be supplemented by ADC values. While these changes have been observed in neuroblastoma, early changes in the ADC value in response to therapy are less well described. In this study, we evaluated whether there is an early change in the ADC values in neuroblastoma under therapy; if this change depends on the form of therapy; and whether this change may serve as a prognostic marker. We retrospectively evaluated neuroblastoma cases treated in our institution between June 2007 and August 2014. The examinations were grouped as 'prestaging'; 'intermediate staging'; 'final staging'; and 'follow-up'. A classification of "progress", "stable disease", or "regress" was made. For the determination of ADC values, regions of interest were drawn along the borders of all tumor manifestations. To calculate ADC changes ( ∆ADC), the respective MRI of the prestaging was used as a reference point or, in the case of therapies that took place directly after previous therapies, the associated previous staging. In the follow-up examinations, the previous examination was used as a reference point. The ∆ADC were grouped into ∆ADCregress for regressive disease, ∆ADCstable for stable disease, and ∆ADC for progressive disease. In addition, examinations at 60 to 120 days from the baseline were grouped as er∆ADCregress , er∆ADCstable , and er∆ADCprogress . Any differences were tested for significance using the Mann-Whitney test (level of significance: p < 0.05). In total, 34 patients with 40 evaluable tumor manifestations and 121 diffusion-weighted MRI examinations were finally included. Twenty-seven patients had INSS stage IV neuroblastoma, and seven had INSS stage III neuroblastoma. A positive N-Myc expression was found in 11 tumor diseases, and 17 patients tested negative for N-Myc (with six cases having no information). 26 patients were assigned to the high-risk group according to INRG and eight patients to the intermediate-risk group. There was a significant difference in mean ADC values from the high-risk group compared to those from the intermediate-risk group, according to INRG. The differences between the mean ∆ADC values (absolute and percentage) according to the course of the disease were significant: between ∆ADCregress and ∆ADCstable , between ∆ADCprogress and ∆ADCstable , as well as between ∆ADCregress and ∆ADCprogress . The differences between the mean er∆ADC values (absolute and percentage) according to the course of the disease were significant: between er∆ADCregress and er∆ADCstable , as well as between er∆ADCregress and er∆ADCprogress . Forms of therapy, N-Myc status, and risk groups showed no further significant differences in mean ADC values and ∆ADC / er∆ADC . A clear connection between the ADC changes and the response to therapy could be demonstrated. This held true even within the first 120 days after the start of therapy: an increase in the ADC value corresponds to a probable response to therapy, while a decrease predicts progression. Minimal or no changes were seen in cases of stable disease.

Image analysis assistance with artificial intelligence (AI) has become one of the great promises over recent years in pathology, with many scientific studies being published each year. Nonetheless, and perhaps surprisingly, only few image AI systems are already in routine clinical use. A major reason for this is the missing validation of the robustness of many AI systems: beyond a narrow context, the large variability in digital images due to differences in preanalytical laboratory procedures, staining procedures, and scanners can be challenging for the subsequent image analysis. Resulting faulty AI analysis may bias the pathologist and contribute to incorrect diagnoses and, therefore, may lead to inappropriate therapy or prognosis. In this study, a pretrained AI assistance tool for the quantification of Ki-67, estrogen receptor (ER), and progesterone receptor (PR) in breast cancer was evaluated within a realistic study set representative of clinical routine on a total of 204 slides (72 Ki-67, 66 ER, and 66 PR slides). This represents the cohort with the largest image variance for AI tool evaluation to date, including 3 staining systems, 5 whole-slide scanners, and 1 microscope camera. These routine cases were collected without manual preselection and analyzed by 10 participant pathologists from 8 sites. Agreement rates for individual pathologists were found to be 87.6% for Ki-67 and 89.4% for ER/PR, respectively, between scoring with and without the assistance of the AI tool regarding clinical categories. Individual AI analysis results were confirmed by the majority of pathologists in 95.8% of Ki-67 cases and 93.2% of ER/PR cases. The statistical analysis provides evidence for high interobserver variance between pathologists (Krippendorff's α, 0.69) in conventional immunohistochemical quantification. Pathologist agreement increased slightly when using AI support (Krippendorff α, 0.72). Agreement rates of pathologist scores with and without AI assistance provide evidence for the reliability of immunohistochemical scoring with the support of the investigated AI tool under a large number of environmental variables that influence the quality of the diagnosed tissue images., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Meningiomas are the most common primary intracranial tumors, of which atypical meningiomas account for ~ 20%. A loss of NF2 has been proven to be an initial step for meningioma development; however, the role of non- NF2 alterations is unknown. Here we report a case of an atypical meningioma with a NF2 splice donor mutation and four recurrences. Using a custom NGS panel, further complex heterogenic molecular alterations were discovered. At first, one subclone of the initial tumor showed an additional PIK3CA variant, most likely of no pathogenic relevance. Then, the first and second recurrences no longer harbored the PIK3CA variant and no tumor heterogeneity was found. The tumor-driving NF2 mutation persisted, however. The latest, third recurrence showed a remarkable genetic heterogeneity with multiple, additional non- NF2 variants and a pathogenic PIKC3A mutation. In detail, one subclone showed a SUFU and two SMARCE1 variants. Another, geographically separate tumor subclone, in contrast, showed several different non- NF2 variants in SMO , PIK3CA and SUFU . Most important, one of the newly acquired PIK3CA alterations in the kinase domain (L1006F) is likely to be an additional tumor-driving mutation, which activates the PI3K-AKT-mTOR pathway. The reported genetic heterogeneity in meningiomas has been addressed in only a few studies. Although some of the detected variants in our case are expected to have biochemical consequences, these consequences are usually not likely to promote tumor development, when taking into account the suggested role of the altered proteins in tumorigenic pathways. However, the occurrence of a single oncogenic missense mutation in a subclone of the third recurrence may indicate a clonal change towards enhanced aggressiveness. Taken together, our case supports the need to perform in-depth studies to clarify the role of non- NF2 mutations for meningioma growth and development.

Digital pathology can be thought of as a model composed of 3 main elements; classification algorithm, Graphical User Interface (GUI) and the pathologists. Currently there is only a one way interaction from the classification algorithm to the pathologist. This paper, proposes an additional backward path which is a new feedback-based method, aimed to improve the performance of the classification algorithms by utilizing the feedback of the pathologists. The GUI developed for this purpose, is aimed to be simple and adaptive to different classification algorithms. The method showed significant improvement in the classification performance of the applied Convolutional Neural Network (CNN) algorithm. The 25% quantile of the probability score of the predictions increased from 0.48 to 0.89 and the median of the data increased from 0.95 to 0.99.