Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

A prospective study on tumour response assessment methods after neoadjuvant endocrine therapy in early oestrogen receptor-positive breast cancer.

BACKGROUND: Neoadjuvant endocrine therapy (NET) in oestrogen receptor-positive (ER+) /HER2-negative (HER2-) breast cancer allows real-time evaluation of drug efficacy as well as investigation of the biological and molecular changes that occur after estrogenic deprivation. Clinical and pathological evaluation after NET may be used to obtain prognostic and predictive information of tumour response to decide adjuvant treatment. In this setting, clinical scales developed to evaluate response after neoadjuvant chemotherapy are not useful and there are not validated biomarkers to assess response to NET beyond Ki67 levels and preoperative endocrine prognostic index score (mPEPI). METHODS: In this prospective study, we extensively analysed radiological (by ultrasound scan (USS) and magnetic resonance imaging (MRI)) and pathological tumour response of 104 postmenopausal patients with ER+ /HER2- resectable breast cancer, treated with NET for a mean of 7 months prior to surgery. We defined a new score, tumour cellularity size (TCS), calculated as the product of the residual tumour cellularity in the surgical specimen and the tumour pathological size. RESULTS: Our results show that radiological evaluation of response to NET by both USS and MRI underestimates pathological tumour size (path-TS). Tumour size [mean (range); mm] was: path-TS 20 (0-80); radiological-TS by USS 9 (0-31); by MRI: 12 (0-60). Nevertheless, they support the use of MRI over USS to clinically assess radiological tumour response (rad-TR) due to the statistically significant association of rad-TR by MRI, but not USS, with Ki67 decrease (p = 0.002 and p = 0.3, respectively) and mPEPI score (p = 0.002 and p = 0.6, respectively). In addition, we propose that TCS could become a new tool to standardize response assessment to NET given its simplicity, reproducibility and its good correlation with existing biomarkers (such as ΔKi67, p = 0.001) and potential added value. CONCLUSION: Our findings shed light on the dynamics of tumour response to NET, challenge the paradigm of the ability of NET to decrease surgical volume and point to the utility of the TCS to quantify the scattered tumour response usually produced by endocrine therapy. In the future, these results should be validated in independent cohorts with associated survival data.

A standardized approach to evaluation and reporting of synovial histopathology in two surgically induced murine models of osteoarthritis.

OBJECTIVE: Synovial pathology has been linked to osteoarthritis (OA) pain in patients. Microscopic grading systems for synovial changes in human OA have been described, but a standardized approach for murine models of OA is needed. We sought to develop a reproducible approach and set of minimum recommendations for reporting of synovial histopathology in mouse models of OA. METHODS: Coronal and sagittal sections from male mouse knee joints subjected to destabilization of medial meniscus (DMM) or partial meniscectomy (PMX) were collected as part of other studies. Stains included Hematoxylin and Eosin (H&E), Toluidine Blue (T-Blue), and Safranin O/Fast Green (Saf-O). Four blinded readers graded pathological features (hyperplasia, cellularity, and fibrosis) at specific anatomic locations. Inter-reader agreement of each feature score was determined. RESULTS: There was acceptable to very good agreement when using 3-4 individual readers. After DMM and PMX, expected medial predominant changes in hyperplasia and cellularity were observed, with fibrosis noted at 12 weeks post-PMX. Synovial changes were consistent from section to section in the mid-joint area. When comparing stains, H&E and T-blue resulted in better agreement compared to Saf-O stain. CONCLUSIONS: To account for the pathologic and anatomic variability in synovial pathology and allow for a more standardized evaluation that can be compared across studies, we recommend evaluating a minimum set of 3 pathological features at standardized anatomic areas. Further, we suggest reporting individual feature scores separately before relying on a single summed "synovitis" score. H&E or T-blue are preferred, inter-reader agreement for each feature should be considered.

Liquid-based cytology specimens for next-generation sequencing in lung adenocarcinoma: challenges and evaluation of targeted therapy.

BACKGROUND: To explore challenges of liquid-based cytology (LBC) specimens for next-generation sequencing (NGS) in lung adenocarcinoma and evaluate the efficacy of targeted therapy. METHODS: A retrospective analysis was conducted on the NGS test of 357 cases of advanced lung adenocarcinoma LBC specimens and compared with results of histological specimens to assess the consistency. The impact of tumor cellularity on NGS test results was evaluated. The utility of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) was collected. Clinical efficacy evaluation was performed and survival curve analysis was conducted using the Kaplan-Meier method. RESULTS: There were 275 TKI-naive and 82 TKI-treated specimens, the mutation rates of cancer-related genes detected in both groups were similar (86.2% vs. 86.6%). The EGFR mutation rate in the TKI treated group was higher than that in the TKI-naive group (69.5% > 54.9%, P = 0.019). There was no significant difference in the EGFR mutation frequency among different tumor cellularity in the TKI-naive group. However, in the TKI treated group, the frequency of EGFR sensitizing mutation and T790M resistance mutation in specimens with < 20% tumor cellularity was significantly lower than that in specimens with ≥ 20% tumor cellularity. Among 22 cases with matched histological specimens, 72.7% (16/22) of LBC specimens were completely consistent with results of histological specimens. Among 92 patients with EGFR-mutant lung adenocarcinoma treated with EGFR-TKIs in the two cohorts, 88 cases experienced progression, and the median progression-free survival (PFS) was 12.1 months. CONCLUSIONS: Cytological specimens are important sources for gene detection of advanced lung adenocarcinoma. When using LBC specimens for molecular testing, it is recommended to fully evaluate the tumor cellularity of the specimens.

Early morphological and neurochemical changes of the bed nucleus of stria terminalis (BNST) in gestational protein-restricted male offspring.

BACKGROUND: The bed nucleus of the stria terminalis (BNST) is a structure with a peculiar neurochemical composition involved in modulating anxietylike behavior and fear. AIM: The present study investigated the effects on the BNST neurochemical composition and neuronal structure in critical moments of the postnatal period in gestational protein-restricted male rats' offspring. METHODS: Dams were maintained during the pregnancy on isocaloric rodent laboratory chow with standard protein content [NP, 17%] or low protein content [LP, 6%]. BNST from male NP and age-matched LP offspring was studied using the isotropic fractionator method, Neuronal 3D reconstruction, dendritic-tree analysis, blotting analysis, and high-performance liquid chromatography. RESULTS: Serum corticosterone levels were higher in male LP offspring than NP rats in 14-day-old offspring, without any difference in 7-day-old progeny. The BNST total cell number and anterodorsal BNST division volume in LP progeny were significantly reduced on the 14th postnatal day compared with NP offspring. The BNST HPLC analysis from 7 days-old LP revealed increased norepinephrine levels compared to NP progeny. The BNST blot analysis from 7-day-old LP revealed reduced levels of GR and BDNF associated with enhanced CRF1 expression compared to NP offspring. 14-day-old LP offspring showed reduced expression of MR and 5HT1A associated with decreased DOPAC and DOPA turnover levels relative to NP rats. In Conclusion, the BNST cellular and neurochemical changes may represent adaptation during development in response to elevated fetal exposure to maternal corticosteroid levels. In this way, gestational malnutrition alters the BNST content and structure and contributes to already-known behavioral changes.

Diagnostic implication of thyroid spherules for cytological diagnosis of thyroid nodules.

OBJECTIVE: Thyroid fine-needle aspiration (FNA) is a principal diagnostic procedure for thyroid nodules. A specific cytomorphological structure, known as the thyroid spherule, is often seen in FNA specimens. The clinical significance of these spherules in terms of diagnosis and prevalence remains largely unexplored. METHODS: We performed a retrospective study on 310 thyroid FNA specimens and categorized them according to the Bethesda System for Reporting Thyroid Cytopathology. The presence, size and number of thyroid spherules in each specimen were examined and these data were subsequently correlated with the clinicopathological features. RESULTS: Thyroid spherules were almost exclusively detected in benign cases, comprising 7.6% of all benign diagnoses. The average diameter of spherules in benign cases was 84.9 µm. Benign cases and cases with atypia of undetermined significance cases primarily exhibited low cellularity, while follicular neoplasms and malignant cases typically showed moderate to high cellularity. In the subgroup of FNA cases with moderate to high cellularity, spherules were identified in 12 (20%) of 59 benign FNA cases. Within this group, the sensitivity and specificity of thyroid spherules for detecting benign FNA cases were 20% and 100%, respectively. CONCLUSIONS: Our results suggest that the presence of thyroid spherules in FNA specimens can serve as a highly specific marker for benign thyroid conditions. The prevalence of spherule detection is strongly influenced by the cellularity. In cases with moderate to high cellularity, the identification of spherules can assist the cytopathologists in diagnosing thyroid FNA cases as benign.

MarrowQuant 2.0: A Digital Pathology Workflow Assisting Bone Marrow Evaluation in Experimental and Clinical Hematology.

Bone marrow (BM) cellularity assessment is a crucial step in the evaluation of BM trephine biopsies for hematologic and nonhematologic disorders. Clinical assessment is based on a semiquantitative visual estimation of the hematopoietic and adipocytic components by hematopathologists, which does not provide quantitative information on other stromal compartments. In this study, we developed and validated MarrowQuant 2.0, an efficient, user-friendly digital hematopathology workflow integrated within QuPath software, which serves as BM quantifier for 5 mutually exclusive compartments (bone, hematopoietic, adipocytic, and interstitial/microvasculature areas and other) and derives the cellularity of human BM trephine biopsies. Instance segmentation of individual adipocytes is realized through the adaptation of the machine-learning-based algorithm StarDist. We calculated BM compartments and adipocyte size distributions of hematoxylin and eosin images obtained from 250 bone specimens, from control subjects and patients with acute myeloid leukemia or myelodysplastic syndrome, at diagnosis and follow-up, and measured the agreement of cellularity estimates by MarrowQuant 2.0 against visual scores from 4 hematopathologists. The algorithm was capable of robust BM compartment segmentation with an average mask accuracy of 86%, maximal for bone (99%), hematopoietic (92%), and adipocyte (98%) areas. MarrowQuant 2.0 cellularity score and hematopathologist estimations were highly correlated (R2 = 0.92-0.98, intraclass correlation coefficient [ICC] = 0.98; interobserver ICC = 0.96). BM compartment segmentation quantitatively confirmed the reciprocity of the hematopoietic and adipocytic compartments. MarrowQuant 2.0 performance was additionally tested for cellularity assessment of specimens prospectively collected from clinical routine diagnosis. After special consideration for the choice of the cellularity equation in specimens with expanded stroma, performance was similar in this setting (R2 = 0.86, n = 42). Thus, we conclude that these validation experiments establish MarrowQuant 2.0 as a reliable tool for BM cellularity assessment. We expect this workflow will serve as a clinical research tool to explore novel biomarkers related to BM stromal components and may contribute to further validation of future digitalized diagnostic hematopathology workstreams.

Human papillomavirus testing using HPV APTIMA® assay and an external cellularity control in self-collected samples.

In cervical cancer screening programs, the detection of high-risk human papillomavirus (HR-HPV) is now widely implemented on physician-collected samples and has expanded to include self-collected samples. The use of a cellularity control (CC) is needed to reduce false-negative HPV results. An external mRNA CC for the HPV APTIMA® assay was assessed for its analytical performance and the results were compared with both cervix cytobrush samples taken by physicians and self-collected vaginal samples from 148 women. The performance of the CC was adjusted to control for the presence of cellular mRNA in the ThinPrep® and Multitest® transport media. This CC is user-friendly but implies to perform two independent assays on PANTHER® automate. Self-collected vaginal sampling gives a lower median CC results (13.2 vs. 16.9 min) but a higher risk of negative CC results (3.3 vs. 0%). The usefulness of the CC for the HR-HPV assay may be optimized by the definition of a threshold for a minimum cell number to be tested to increase confidence in HPV-negative results. The systematic use of an RNA CC increases confidence for HPV RNA assays on self-collected vaginal samples.

DKI can distinguish high-grade gliomas from IDH1-mutant low-grade gliomas and correlate with their different nuclear-to-cytoplasm ratio: a localized biopsy-based study.

OBJECTIVES: To explore whether differences in diffusional kurtosis imaging (DKI) between therapy-naïve high-grade gliomas (HGGs) and low-grade gliomas (LGGs) are related to the cellularity and/or the nuclear-to-cytoplasmic (N/C) ratio. METHODS: We analyzed 44 and 40 diffuse glioma samples that were pathologically confirmed as HGGs and IDH1-mutant LGGs, respectively. The DKI parameters included kurtosis metrics (mean kurtosis [MK], axial kurtosis [K//], and radial kurtosis [K⊥]), and the diffusional metrics (fractional anisotropy [FA], mean diffusion [MD], axial diffusion [λ//], and radial diffusion [λ⊥]). The cellularity and the N/C ratio were compared within LGGs and HGGs using the Mann-Whitney U test (significant level, p < 0.007 [0.05/7]); Bonferroni correction). Spearman's correlation analysis was used to calculate the correlation coefficients among DKI metrics, cellularity, and the N/C ratio at a significant level of p = 0.05. RESULTS: Excluding FA, all DKI metrics showed significant differences between HGGs and LGGs (all p ≤ 0.001). The N/C ratio of HGGs was significantly higher than that of LGGs; however, differences in cellularity were not significant between the two glioma groups (p = 0.525). Similarly, excluding FA, all DKI metrics were significantly correlated with the N/C ratio in LGGs, with correlation coefficients of - 0.365 (MD), - 0.313 (λ//), - 0.376 (λ⊥), 0.859 (MK), 0.772 (K//), and 0.842 (K//). There was a non-significant correlation between any DKI parameters and the cellularity in LGGs. Additionally, the cellularity and N/C ratios in HGGs did not correlate with any DKI metrics. CONCLUSIONS: DKI differentiate LGGs from HGGs associated with their different N/C ratios. CLINICAL RELEVANCE STATEMENT: This study shows that DKI differentiates LGGs from HGGs may correlated with their different N/C ratios, this could provide a possible histopathological mechanism about why DKI can DKI differentiate LGGs from HGGs. KEY POINTS: • Excluding FA, all DKI metrics showed a significant difference between high-grade gliomas and IDH1-mutant low-grade gliomas. • The nuclear-to-cytoplasm ratios in high-grade gliomas were significantly more extensive than that in IDH1-mutant low-grade gliomas, but not the cellularity. • Significant associations were seen between DKI measures and the N/C ratio; a non-significant correlation was noted between any DKI metric and cellularity in glioma specimens.

Bone marrow adipose cells - cellular interactions and changes with obesity.

The bone marrow is a spatially restricted niche, housing cells of the hematopoietic and mesenchymal lineages in various hierarchical commitment states. Although highly localized, cells within this niche are also subject to regulation by environmental and/or circulatory changes through extensive vascularization. Bone marrow adipocytes, derived from mesenchymal stem cells and once known as marrow space fillers, are a heterogeneous population. These cells reside in distinct niches within the bone marrow and interact with proximal cells, such as hematopoietic precursors and lineage-committed cells. In this diverse cellular milieu, bone marrow adipocytes influence commitment decisions and cellular lineage selection by interacting with stem and progenitor cells. In addition, bone marrow adipocytes respond to environmental changes, such as obesity, by undergoing hypertrophy, hyperplasia or adoption of characteristics resembling those of peripheral brown, beige or white adipocytes. Here, we review recent findings and concepts on the influence of bone marrow adipocytes on hematopoietic and other cellular lineages within this niche. We discuss how changes in local, systemic, cellular and secreted signals impact on mesenchymal stem cell expansion, differentiation and lineage commitment. Furthermore, we highlight that bone marrow adipocytes may be intermediaries conveying environmental cues to influence hematopoietic cellular survival, proliferation and preferential differentiation.

A collaborative workflow between pathologists and deep learning for the evaluation of tumour cellularity in lung adenocarcinoma.

AIMS: The reporting of tumour cellularity in cancer samples has become a mandatory task for pathologists. However, the estimation of tumour cellularity is often inaccurate. Therefore, we propose a collaborative workflow between pathologists and artificial intelligence (AI) models to evaluate tumour cellularity in lung cancer samples and propose a protocol to apply it to routine practice. METHODS AND RESULTS: We developed a quantitative model of lung adenocarcinoma that was validated and tested on 50 cases, and a collaborative workflow where pathologists could access the AI results and adjust their original tumour cellularity scores (adjusted-score) that we tested on 151 cases. The adjusted-score was validated by comparing them with a ground truth established by manual annotation of haematoxylin and eosin slides with reference to immunostains with thyroid transcription factor-1 and napsin A. For training, validation, testing the AI and testing the collaborative workflow, we used 40, 10, 50 and 151 whole slide images of lung adenocarcinoma, respectively. The sensitivity and specificity of tumour segmentation were 97 and 87%, respectively, and the accuracy of nuclei recognition was 99%. One pathologist's visually estimated scores were compared to the adjusted-score, and the pathologist's scores were altered in 87% of cases. Comparison with the ground truth revealed that the adjusted-score was more precise than the pathologists' scores (P < 0.05). CONCLUSION: We proposed a collaborative workflow between AI and pathologists as a model to improve daily practice and enhance the prediction of tumour cellularity for genetic tests.

Plant-based diets fed to juvenile meagre Argyrosomus regius with low methionine and taurine supplementation led to an overall reduction in fish performance and to an increase in muscle fibre recruitment.

Methionine and taurine are amino acids (AA) that are usually deficient when fish meal is replaced by plant proteins. In this study, three diets were tested in juvenile meagre (initial weight: 13.4 g) for 8 weeks. The D1 diet had 0.2% methionine and 1% taurine supplementation; the D2 and D3 diets had 0.6% methionine and 1% and 2% taurine supplementation, respectively. The results showed that meagre fed the D1 diet had lower specific growth rate (2.2 to 2.5), lower feed efficiency (0.9 to 1.2) and higher food conversion rate (FCR, 1.1 to 0.8) as well as a lower activity of the alanine aminotransferase (ALAT) enzyme. Furthermore, a higher recruitment of muscle fibres (46% compared to 36%) as well as a higher fibre density was observed (1019 compared to 870 fibres mm-2 ). This study shows that meagre requires a sufficient quantity of methionine in plant-based diets to avoid a reduction in fish performance. Furthermore, taurine supplementation in the D1 diet was not able to mitigate the effects of methionine deficiency. A higher taurine supplementation did not improve meagre performance.

Correlation between MRI morphological response patterns and histopathological tumor regression after neoadjuvant endocrine therapy in locally advanced breast cancer: a randomized phase II trial.

PURPOSE: To correlate MRI morphological response patterns with histopathological tumor regression grading system based on tumor cellularity in locally advanced breast cancer (LABC)-treated neoadjuvant with third-generation aromatase inhibitors. METHODS: Fifty postmenopausal patients with ER-positive/HER-2-negative LABC treated with neoadjuvant letrozole and exemestane given sequentially in an intra-patient cross-over regimen for at least 4 months with MRI response monitoring at baseline as well as after at least 2 and 4 months on treatment. The MRI morphological response pattern was classified into 6 categories: 0/complete imaging response; I/concentric shrinkage; II/fragmentation; III/diffuse; IV/stable; and V/progressive. Histopathological tumor regression was assessed based on the recommendations from The Royal College of Pathologists regarding tumor cellularity. RESULTS: Following 2 and 4 months with therapy, the most common MRI pattern was pattern II (24/50 and 21/50, respectively). After 4 months on therapy, the most common histopathological tumor regression grade was grade 3 (21/50). After 4 months an increasing correlation is observed between MRI patterns and histopathology. The overall correlation, between the largest tumor diameter obtained from MRI and histopathology, was moderate and positive (r = 0.50, P-value = 2e-04). Among them, the correlation was highest in type IV (r = 0.53). CONCLUSION: The type II MRI pattern "fragmentation" was more frequent in the histopathological responder group; and types I and IV in the non-responder group. Type II pattern showed the best endocrine responsiveness and a relatively moderate correlation between sizes obtained from MRI and histology, whereas type IV pattern indicated endocrine resistance but the strongest correlation between MRI and histology.

Diastolic dysfunction in a pre-clinical model of diabetes is associated with changes in the cardiac non-myocyte cellular composition.

BACKGROUND: Diabetes is associated with a significantly elevated risk of cardiovascular disease and its specific pathophysiology remains unclear. Recent studies have changed our understanding of cardiac cellularity, with cellular changes accompanying diabetes yet to be examined in detail. This study aims to characterise the changes in the cardiac cellular landscape in murine diabetes to identify potential cellular protagonists in the diabetic heart. METHODS: Diabetes was induced in male FVB/N mice by low-dose streptozotocin and a high-fat diet for 26-weeks. Cardiac function was measured by echocardiography at endpoint. Flow cytometry was performed on cardiac ventricles as well as blood, spleen, and bone-marrow at endpoint from non-diabetic and diabetic mice. To validate flow cytometry results, immunofluorescence staining was conducted on left-ventricles of age-matched mice. RESULTS: Mice with diabetes exhibited hyperglycaemia and impaired glucose tolerance at endpoint. Echocardiography revealed reduced E:A and e':a' ratios in diabetic mice indicating diastolic dysfunction. Systolic function was not different between the experimental groups. Detailed examination of cardiac cellularity found resident mesenchymal cells (RMCs) were elevated as a result of diabetes, due to a marked increase in cardiac fibroblasts, while smooth muscle cells were reduced in proportion. Moreover, we found increased levels of Ly6Chi monocytes in both the heart and in the blood. Consistent with this, the proportion of bone-marrow haematopoietic stem cells were increased in diabetic mice. CONCLUSIONS: Murine diabetes results in distinct changes in cardiac cellularity. These changes-in particular increased levels of fibroblasts-offer a framework for understanding how cardiac cellularity changes in diabetes. The results also point to new cellular mechanisms in this context, which may further aid in development of pharmacotherapies to allay the progression of cardiomyopathy associated with diabetes.

Heterogeneity analysis of MRI T2 maps for measurement of early tumor response to radiotherapy.

External beam radiotherapy (XRT) is a widely used cancer treatment, yet responses vary dramatically among patients. These differences are not accounted for in clinical practice, partly due to a lack of sensitive early response biomarkers. We hypothesize that quantitative magnetic resonance imaging (MRI) measures reflecting tumor heterogeneity can provide a sensitive and robust biomarker of early XRT response. MRI T2 mapping was performed every 72 hours following 10 Gy dose XRT in two models of pancreatic cancer propagated in the hind limb of mice. Interquartile range (IQR) of tumor T2 was presented as a potential biomarker of radiotherapy response compared with tumor growth kinetics, and biological validation was performed through quantitative histology analysis. Quantification of tumor T2 IQR showed sensitivity for detection of XRT-induced tumor changes 72 hours after treatment, outperforming T2-weighted and diffusion-weighted MRI, with very good robustness. Histological comparison revealed that T2 IQR provides a measure of spatial heterogeneity in tumor cell density, related to radiation-induced necrosis. Early IQR changes were found to correlate to subsequent tumor volume changes, indicating promise for treatment response prediction. Our preclinical findings indicate that spatial heterogeneity analysis of T2 MRI can provide a translatable method for early radiotherapy response assessment. We propose that the method may in future be applied for personalization of radiotherapy through adaptive treatment paradigms.

Pretransplant bone marrow cellularity and blood count recovery are not associated with relapse or survival risk following allogeneic stem cell transplant for AML in CR.

INTRODUCTION: Allogeneic hematopoietic cell transplantation (HCT) can be curative for acute myeloid leukemia (AML). Novel therapies may render patients' bone marrow hypocellularity and lead to prolonged post-therapy pancytopenia. Patients' bone marrow cellularity (BMC) at pretransplant assessment and post-treatment pancytopenia (classification CR-incomplete [CRi]) may manifest AML persistence. METHODOLOGY: We retrospectively examined the impact of BMC and ELN response (ELNr) on a single-center cohort of 337 patients who underwent allogeneic HCT for AML in CR1. RESULTS: Median follow-up was 33 months. Overall survival (OS) for the whole cohort was 55.8% at 2 years, while cumulative incidence of relapse (CIR) was 20.8%, and non-relapse mortality was 27.5%. OS and CIR were not significantly different between BMC groups; and neither was ELNr. ELNr CRi was associated with BMC aplastic and hypocellular marrow states (P < 2.6e-8). Multivariate analysis confirmed neither BMC nor attainment of ELNr CR vs CRi affected OS or relapse. Significant factors for survival included age at transplant, cytogenetic risk, development of acute Gr II-IV GvHD, and moderate-severe chronic GvHD, while cytogenetic risk and chronic GvHD affected relapse. CONCLUSION: Neither ELNr status nor pretransplant BMC influenced relapse post-HCT or OS. Hypocellularity and CRi are not negative prognostic factors for post-HCT outcomes of AML.

Screening For Bone Marrow Cellularity Changes in Cynomolgus Macaques in Toxicology Safety Studies Using Artificial Intelligence Models.

Many compounds affect the cellularity of hematolymphoid organs including bone marrow. Toxicologic pathologists are tasked with their evaluation as part of safety studies. An artificial intelligence (AI) tool could provide diagnostic support for the pathologist. We looked at the ability of a deep-learning AI model to evaluate whole slide images of macaque sternebrae to identify and enumerate bone marrow hematopoietic cells. The AI model was trained and able to differentiate the hematopoietic cells from the other sternebrae tissues. We compared the model to severity scores in a study with decreased hematopoietic cellularity. The mean cells/mm2 from the model was lower for each increase in severity score. The AI model was trained by 1 pathologist, providing proof of concept that AI model generation can be fast and agile, without the need of a cross disciplinary team and significant effort. We see great potential for the role of AI-based bone marrow screening.

Quantitative magnetic resonance imaging for determining bone marrow fat fraction at 1.5 T and 3.0 T: a technique to noninvasively assess cellularity and potential malignancy of the bone marrow.

BACKGROUND: Pediatric bone marrow assessment by MRI is challenging and primarily experiential and qualitative, with a paucity of clinically useful quantitative imaging techniques. OBJECTIVE: MRI fat fraction (MRI-FF) is a technique used to quantify the degree of fat in other organ systems. The purpose of this study was to assess whether MRI-FF accurately measures bone marrow composition. MATERIALS AND METHODS: This two-part study included a validation phase, followed by an application phase. For the validation phase, the MRI-FF of piglet bones (6 long bones, 8 axial bones) was performed at 1.5 tesla (T) and 3.0 T, and correlated to the histological fat fraction (H-FF). We used Bland-Altman plots to compare MRI-FF at 1.5 tesla T and 3.0 T. For the application phase, five children with malignant marrow disease were recruited along with seven age- and gender-matched control subjects. The MRI-FF in the children was correlated to the H-FF. Boxplots were used to compare the MRI-FF of patients and control subjects. RESULTS: For the validation animal study, the MRI-FF of piglet bones at both 1.5 T and 3.0 T demonstrated moderate positive correlation to H-FF (r=0.41 and 0.42, respectively). MRI-FF at 1.5 T and 3.0 T were in good agreement, on average 7.7% apart. For the application phase, we included 5 children (4 with leukemia, 1 rhabdomyosarcoma) with median age 7 years, range (3-10 years). All children had MRI-FF and H-FF below 10%. The MRI-FF in patients (3.8±1.2) was significantly lower than that of control subjects (46.1±12.3%) (P<0.01). CONCLUSION: MRI-FF is a valid technique to assess bone marrow fat fraction at both 1.5 T and 3.0 T. The MRI-FF in children with malignant marrow processes is significantly lower than in control subjects with normal marrow.

The Effect of 17α-Ethynilestradiol and GPER1 Activation on Body and Muscle Growth, Muscle Composition and Growth-Related Gene Expression of Gilthead Seabream, Sparus aurata L.

Endocrine-disrupting chemicals include natural and synthetic estrogens, such as 17α-ethynilestradiol (EE2), which can affect reproduction, growth and immunity. Estrogen signalling is mediated by nuclear or membrane estrogen receptors, such as the new G-protein-coupled estrogen receptor 1 (GPER1). The present work studies the effect of EE2 and G1 (an agonist of GPER1) on body and muscle parameters and growth-related genes of 54 two-year-old seabreams. The fish were fed a diet containing EE2 (EE2 group) and G1 (G1 group) for 45 days and then a diet without EE2 or G1 for 122 days. An untreated control group was also studied. At 45 days, the shortest body length was observed in the G1 group, while 79 and 122 days after the cessation of treatments, the shortest body growth was observed in the EE2 group. Hypertrophy of white fibers was higher in the EE2 and G1 groups than it was in the control group, whereas the opposite was the case with respect to hyperplasia. Textural hardness showed a negative correlation with the size of white fibers. At the end of the experiment, all fish analyzed in the EE2 group showed a predominance of the gonadal ovarian area. In addition, the highest expression of the mafbx gene (upregulated in catabolic signals) and mstn2 (myogenesis negative regulator) was found in EE2-exposed fish.

The Coevolution of Cellularity and Metabolism Following the Origin of Life.

The emergence of cellular organisms occurred sometime between the origin of life and the evolution of the last universal common ancestor and represents one of the major transitions in evolutionary history. Here we describe a series of artificial life simulations that reveal a close relationship between the evolution of cellularity, the evolution of metabolism, and the richness of the environment. When environments are rich in processing energy, a resource that the digital organisms require to both process their genomes and replicate, populations evolve toward a state of non-cellularity. But when processing energy is not readily available in the environment and organisms must produce their own processing energy from food puzzles, populations always evolve both a proficient metabolism and a high level of cellular impermeability. Even between these two environmental extremes, the population-averaged values of cellular impermeability and metabolic proficiency exhibit a very strong correlation with one another. Further investigations show that non-cellularity is selectively advantageous when environmental processing energy is abundant because it allows organisms to access the available energy, while cellularity is selectively advantageous when environmental processing energy is scarce because it affords organisms the genetic fidelity required to incrementally evolve efficient metabolisms. The selection pressures favoring either non-cellularity or cellularity can be reversed when the environment transitions from one of abundant processing energy to one of scarce processing energy. These results have important implications for when and why cellular organisms evolved following the origin of life.