Hasil untuk "Cytology"

Erik K. Alexander, Giulia C. Kennedy, Z. Baloch et al.

E. Weibel

M. White

E. Weibel, G. Kistler, W. Scherle

Stereological principles provide efficient and reliable tools for the determination of quantitative parameters of tissue structure on sections. Some principles which allow the estimation of volumetric ratios, surface areas, surface-to-volume ratios, thicknesses of tissue or cell sheets, and the number of structures are reviewed and presented in general form; means for their practical application in electron microscopy are outlined. The systematic and statistical errors involved in such measurements are discussed.

Y. Nikiforov, S. Carty, S. Chiosea et al.

Background: Fine-needle aspiration (FNA) cytology is a common approach to evaluate thyroid nodules. It offers definitive diagnosis of a benign or malignant nodule in the majority of cases. However, 10–25% of nodules yield one of three indeterminate cytologic diagnoses, leading to suboptimal management of these patients. Atypia of undetermined significance/follicular lesion of undermined significance (AUS/FLUS) is a common indeterminate diagnosis, with the cancer risk ranging from 6% to 48%. This study assessed whether a multi-gene next-generation sequencing (NGS) assay can offer significant improvement in diagnosis in AUS/FLUS nodules. Methods: From May 2014 to March 2015, 465 consecutive FNA samples with the cytologic diagnosis of AUS/FLUS underwent prospective molecular testing using the ThyroSeq v2.1 panel. The panel included 14 genes analyzed for point mutations and 42 types of gene fusions occurring in thyroid cancer. In addition, eight genes were assessed for expression in order to evaluate the cell composition of FNA samples. Ninety-eight (21%) of these nodules had definitive surgical (n = 96) or nonsurgical (n = 2) follow-up and were used to determine the assay performance. Results: Among 465 AUS/FLUS nodules, three were found to be composed of parathyroid cells and 462 of thyroid follicular cells. Of the latter, 31 (6.7%) were positive for mutations. The most frequently mutated genes were NRAS and HRAS, and overall point mutations in seven different genes and five types of gene fusions were identified in these nodules. Among 98 nodules with known outcome, histologic analysis revealed 22 (22.5%) cancers. ThyroSeq v2.1 was able to classify 20/22 cancers correctly, showing a sensitivity of 90.9% [confidence interval (CI) 78.8–100], specificity of 92.1% [CI 86.0–98.2], positive predictive value of 76.9% [CI 60.7–93.1], and negative predictive value of 97.2% [CI 78.8–100], with an overall accuracy of 91.8% [CI 86.4–97.3]. Conclusions: The results of the study demonstrate that the ThyroSeq v2.1 multi-gene NGS panel of molecular markers provides both high sensitivity and high specificity for cancer detection in thyroid nodules with AUS/FLUS cytology, which should allow improved management for these patients.

Yonghao Si, Xingyuan Zeng, Zhao Chen et al.

High-quality annotated datasets are crucial for advancing machine learning in medical image analysis. However, a critical gap exists: most datasets either offer a single, clean ground truth, which hides real-world expert disagreement, or they provide multiple annotations without a separate gold standard for objective evaluation. To bridge this gap, we introduce CytoCrowd, a new public benchmark for cytology analysis. The dataset features 446 high-resolution images, each with two key components: (1) raw, conflicting annotations from four independent pathologists, and (2) a separate, high-quality gold-standard ground truth established by a senior expert. This dual structure makes CytoCrowd a versatile resource. It serves as a benchmark for standard computer vision tasks, such as object detection and classification, using the ground truth. Simultaneously, it provides a realistic testbed for evaluating annotation aggregation algorithms that must resolve expert disagreements. We provide comprehensive baseline results for both tasks. Our experiments demonstrate the challenges presented by CytoCrowd and establish its value as a resource for developing the next generation of models for medical image analysis.

E. Hoster, A. Rosenwald, F. Berger et al.

Yasmine Aramon, Andrea Pieragostini, Pierre Jean Francin et al.

Abstract The outcome of multiple myeloma (MM) has tremendously improved over the past decade, due to the development of efficient chemotherapy and mostly immunotherapy. Yet, some patients still display poor responses and outcome. This could be in part related to the presence of peripheral plasma cells, at levels not compatible with a diagnosis of plasma‐cell leukaemia. Some recent publications have highlighted the prognostic influence of low levels of such cells which is around 0.1%. Automated blood cell analysers now include fluorescent staining, allowing to identify cells with higher levels or nucleic acids such as activated B‐lymphocytes/plasma cells with highly active ribosomal activity related to antibody production. Here, a prospective evaluation of peripheral high fluorescent lymphoid cell (HFLC) levels was carried out on samples from patients with newly diagnosed MM, and data computed with regard to patient evolution. HFLC above a 0.1% threshold were identified as strongly correlated with poorer response in a cohort of 127 patients. The 74 patients with low HFLC had a significantly better PFS both in univariate (p = 0.0017) and multivariate (p = 0.0007) analyses. This simple test provides a significant prognostic value for patients with MM and could eventually lead clinicians to consider more aggressive strategies for patients with peripheral HFLC above 0.1%. Trial Registration: The authors have confirmed clinical trial registration is not needed for this submission

Rafeeq P. H. Ahmed, Onur Kanisicak, Perwez Alam

<b>Background</b>: The limited regenerative capacity of adult mammalian cardiomyocytes (CMs) poses a significant challenge for cardiac repair following myocardial infarction. In contrast to adult mammals, CMs in zebrafish and newt hearts retain a lifelong capacity for proliferation and cardiac regeneration. Likewise, neonatal mice exhibit a brief postnatal period, during which CMs retain the ability to proliferate and contribute to myocardial repair, which markedly diminishes within the first week of life. Emerging evidence indicates that adult CM cell cycle progression is critically influenced by oxidative stress. Adult mammalian CMs possess a high mitochondrial content to meet their substantial energy demands. However, this also leads to elevated reactive oxygen species (ROS) production, resulting in DNA damage and subsequent cell cycle arrest. We hypothesize that reducing the mitochondrial content in adult CMs will mitigate ROS production, thereby facilitating cell cycle progression. <b>Methods</b>: Adult CMs were isolated from adult rats (≥12 weeks old). To induce mitophagy, adult CMs were transfected with parkin-expressing plasmid and then treated with carbonyl cyanide 3-chlorophenylhydrazone (CCCP), a mitochondrial protonophore, for 7 days. Post-treatment assessments included the quantification of adult CM proliferation, mitochondrial content, and ROS levels. <b>Results</b>: CCCP-treated adult CMs exhibited a significant increase in proliferation markers, including EdU incorporation, KI67, phospho-histone H3, and Aurora B. Furthermore, CCCP treatment significantly reduced the mitochondrial content, as evidenced by decreased MitoTracker, TMRM, and Tom20 staining compared to controls. This was accompanied by electron microscopy analysis, which showed a significant reduction in the mitochondrial number in the adult CM after CCCP treatment. Moreover, our results also demonstrate a marked reduction in oxidative stress, demonstrated by lower 123-dihydro-rhodamine (123-DHR), CellROX signals, and VDAC. <b>Conclusions</b>: Our findings demonstrate that CCCP-mediated mitochondrial depletion reduces oxidative stress and promotes cell cycle re-entry in adult CM. This study provides direct experimental evidence and substantiates the role of elevated mitochondria and ROS levels in adult CM cell cycle exit.

Hanan Hendawy, Ahmed Farag, Asmaa Elhaieg et al.

Effective bladder reconstruction remains a significant challenge in urology, particularly for conditions requiring partial or complete bladder replacement. In this study, the efficacy is evaluated of two types of scaffolds, silk fibroin (SF) and adipose-derived stem cells (ADSCs-SF), in promoting bladder regeneration and their associated outcomes. A rat model was used to compare the surgical outcomes and morphological recovery of bladder tissues implanted with SF and ADSCs-SF scaffolds. Post-operative recovery, including voiding ability and complication rates, was assessed. The morphological and histological changes of the regenerated bladder tissue were evaluated at multiple time points (2, 4, 8, and 12 weeks) using gross tissue analysis, histometric assessments, and immunohistochemical staining. Both scaffold types demonstrated successful integration into the bladder wall with no significant differences in body weight or voiding issues. The SF scaffold group exhibited graft shrinkage and a 41.6% incidence of bladder calculus formation. In contrast, the ADSCs-SF scaffold facilitated superior morphological restoration, with bladder tissue progressively adopting a more normal shape and no incidence of bladder calculus. Histological analysis revealed that the ADSCs-SF scaffold significantly promoted the regeneration of a more organized urothelium layer and smooth muscle tissue. It also resulted in higher vessel density and reduced infiltration of inflammatory cells when compared to the SF scaffold alone. Additionally, the ADSCs-SF group exhibited enhanced expression of key markers, including uroplakin III, a urothelial marker, and α-SMA, a smooth muscle cell marker. These findings suggest that the ADSCs-SF scaffold not only supports the structural integrity of the bladder but also improves tissue regeneration and reduces adverse inflammatory responses, offering a promising approach for bladder repair and reconstruction.

Claire Delehouzé, Melodie Mallais, Arnaud Comte et al.

Abstract In the past two decades, various non-apoptotic pathways of regulated cell death have been identified; a small subset of these, including necroptosis and ferroptosis, manifests the phenotypic features of necrotic death. These two regulated necroses are being extensively studied because of their putative roles in severe acute and chronic pathologies. Moreover, as these regulated necrotic pathways are coactivated in a number of common pathologies, the development of multi-target directed ligands (that is, the use of a polypharmacological strategy) is a path-breaking avenue of research. In this study, we determined that the 7-azaindole derivative, sibiriline, inhibited both RIPK1-driven necroptosis (induced by Tumor Necrosis Factor-α) and ferroptosis (triggered by various classes of ferroptosis inducers), with EC50s against each in the µM range. We next performed a combined large-scale transcriptomic study in order to determine the molecular mechanisms of action of sibiriline. We identified the stress response protein heme oxygenase-1 (HMOX1) as the main biomarker of ferroptosis inhibition by sibiriline. We hypothesized that this compound reacts as an antioxidant to block ferroptosis; indeed, we found that sibiriline inhibits lipid peroxidation by trapping phospholipid-derived peroxyl radicals as a radical-trapping antioxidant (RTA). Taken together, these results show that sibiriline is a new dual inhibitor of necroptosis and ferroptosis cell death pathways; it works by inhibition of both RIPK1 kinase and (phospho)lipid peroxidation. We also demonstrate the in vitro efficacy of sibiriline to inhibit cell death in cell-based models of Parkinson’s disease and cystic fibrosis. These findings shed light on the high therapeutic potency of RIPK1 inhibitors with RTA activity.

Xindong Wei, Anfeng Si, Shuai Zhao et al.

Abstract Background Circular (circ)RNAs have emerged as crucial contributors to cancer progression. Nonetheless, the expression regulation, biological functions, and underlying mechanisms of circRNAs in mediating hepatocellular carcinoma (HCC) progression remain insufficiently elucidated. Methods We identified circUCK2(2,3) through circRNA sequencing, RT–PCR, and Sanger sequencing. CircUCK2(2,3) levels were measured in two independent HCC cohorts using quantitative real-time PCR (qRT–PCR). We explored the functions of circUCK2(2,3) using gain- and loss-of-function assays. Techniques such as RNA-sequencing, RNA immunoprecipitation (RIP), polysome fractionation, RNA pulldown, dual luciferase reporter assay, inhibitors of EGFR downstream signaling, CRISPR–Cas9, and medium transfer assays were employed to investigate the regulatory mechanisms and the protumoral activities of circUCK2(2,3). Additionally, in vitro cytotoxic assays and patient-derived xenograft (PDX) models assessed the effects of circUCK2(2,3) on the cytotoxic synergy of lenvatinib and EGFR inhibitors. Results CircUCK2(2,3) is upregulated in HCC tissues and serves as an independent risk factor for poor recurrence-free survival. The expression of circUCK2(2,3) is independent on its host gene, UCK2, but is regulated by its upstream promoter and flanking inverted complementary sequences. Functionally, circUCK2(2,3) enhances HCC proliferation, migration, and invasion, both in vitro and in vivo. Mechanistically, by sponging miR-149-5p, circUCK2(2,3) increases CNIH4 levels, which in turn amplifies TGFα secretion, resulting in the activation of EGFR and downstream pAKT and pERK signaling pathways. Moreover, circUCK2(2,3) overexpression sensitizes HCC cells to EGFR inhibitors, and increases the synergistic cytotoxicity of combined lenvatinib and EGFR inhibitor treatment. Conclusions CircUCK2(2,3) regulates a novel oncogenic pathway, miR-149-5p–CNIH4–TGFα–EGFR, in HCC, presenting a viable therapeutic target and biomarker for the precision treatment of HCC. Graphical Abstract

Love Panta, Suraj Prasai, Karishma Malla Vaidya et al.

Cervical cancer remains a significant health challenge, with high incidence and mortality rates, particularly in transitioning countries. Conventional Liquid-Based Cytology(LBC) is a labor-intensive process, requires expert pathologists and is highly prone to errors, highlighting the need for more efficient screening methods. This paper introduces an innovative approach that integrates low-cost biological microscopes with our simple and efficient AI algorithms for automated whole-slide analysis. Our system uses a motorized microscope to capture cytology images, which are then processed through an AI pipeline involving image stitching, cell segmentation, and classification. We utilize the lightweight UNet-based model involving human-in-the-loop approach to train our segmentation model with minimal ROIs. CvT-based classification model, trained on the SIPaKMeD dataset, accurately categorizes five cell types. Our framework offers enhanced accuracy and efficiency in cervical cancer screening compared to various state-of-art methods, as demonstrated by different evaluation metrics.

Marco Acerbis, Swarnadip Chatterjee, Christophe Avenel et al.

Computational cytology faces two major challenges: i) instance-level labels are unreliable and prohibitively costly to obtain, ii) witness rates are extremely low. We propose SLAM-AGS, a Slide-Label-Aware Multitask pretraining framework that jointly optimizes (i) a weakly supervised similarity objective on slide-negative patches and (ii) a self-supervised contrastive objective on slide-positive patches, yielding stronger performance on downstream tasks. To stabilize learning, we apply Adaptive Gradient Surgery to tackle conflicting task gradients and prevent model collapse. We integrate the pretrained encoder into an attention-based Multiple Instance Learning aggregator for bag-level prediction and attention-guided retrieval of the most abnormal instances in a bag. On a publicly available bone-marrow cytology dataset, with simulated witness rates from 10% down to 0.5%, SLAM-AGS improves bag-level F1-Score and Top 400 positive cell retrieval over other pretraining methods, with the largest gains at low witness rates, showing that resolving gradient interference enables stable pretraining and better performance on downstream tasks. To facilitate reproducibility, we share our complete implementation and evaluation framework as open source: https://github.com/Ace95/SLAM-AGS.

Marco Acerbis, Nataša Sladoje, Joakim Lindblad

Accurate and efficient cell detection is crucial in many biomedical image analysis tasks. We evaluate the performance of several Deep Learning (DL) methods for cell detection in Papanicolaou-stained cytological Whole Slide Images (WSIs), focusing on accuracy of predictions and computational efficiency. We examine recentoff-the-shelf algorithms as well as custom-designed detectors, applying them to two datasets: the CNSeg Dataset and the Oral Cancer (OC) Dataset. Our comparison includes well-established segmentation methods such as StarDist, Cellpose, and the Segment Anything Model 2 (SAM2), alongside centroid-based Fully Convolutional Regression Network (FCRN) approaches. We introduce a suitable evaluation metric to assess the accuracy of predictions based on the distance from ground truth positions. We also explore the impact of dataset size and data augmentation techniques on model performance. Results show that centroid-based methods, particularly the Improved Fully Convolutional Regression Network (IFCRN) method, outperform segmentation-based methods in terms of both detection accuracy and computational efficiency. This study highlights the potential of centroid-based detectors as a preferred option for cell detection in resource-limited environments, offering faster processing times and lower GPU memory usage without compromising accuracy.

Stephanie Bond, Renaud Léguillette

Abstract Background Nebulized administration of dexamethasone on cytokine regulation in horses with moderate asthma has not been investigated. Objective To investigate the changes in expression of inflammatory cytokine mRNA after nebulized administration of dexamethasone treatment of horses with moderate asthma. Animals Horses with naturally occurring moderate asthma (n = 16) and healthy control horses (n = 4). All horses were kept in a dusty environment during the study. Methods Prospective, parallel, randomized, controlled, blinded clinical trial. Blood endogenous cortisol, tracheal mucus, and bronchoalveolar lavage (BAL) were sampled before and after 13 days treatment with either nebulized administration of dexamethasone (15 mg once daily) or 0.9% saline (3 mL). Treatment groups were randomly allocated via randomization function (Microsoft Excel). Amplification of target mRNA in BAL fluid (IL‐1β, IL‐4, IL‐5, IL‐6, IL‐8, IL‐10, IL‐12, IL‐17, IL‐23, IFN‐γ, Eotaxin‐2, and TNF‐α) was achieved by qPCR, and the relative expression software tool was used to analyze BAL inflammatory cytokine mRNA. Results Horses treated with nebulized administration of dexamethasone had increased relative expression of IL‐5 (1.70‐fold), IL‐6 (1.71‐fold), IL‐17 (3.25‐fold), IL‐12 (1.66‐fold), and TNF‐α (1.94‐fold), and decreased relative expression of IL‐23 (1.76‐fold; P = .04) in samples collected on Day 14, in comparison to samples collected on Day 0 (all P < .05). Horses treated with nebulized administration of saline had no significant difference in the relative expression of any gene (all P > .05). Conclusions and Clinical Importance Nebulized administration of dexamethasone was associated with increased expression of inflammatory cytokine mRNA. There was no improvement in inflammatory airway cytology associated with either dexamethasone or saline treatment.

Anja Levis, Markus Huber, Déborah Mathis et al.

Ketone bodies (KBs) are energy-efficient substrates utilized by the heart depending on its metabolic demand and substrate availability. Levels of circulating KBs have been shown to be elevated in acute and chronic cardiovascular disease and are associated with severity of disease in patients with heart failure and functional outcome after myocardial infarction. To investigate whether this pattern similarly applies to patients undergoing cardiac surgery involving cardiopulmonary bypass (CPB), we analysed prospectively collected pre- and postoperative blood samples from 192 cardiac surgery patients and compared levels and perioperative changes in total KBs with Troponin T as a marker of myocardial cell injury. We explored the association of patient characteristics and comorbidities for each of the two biomarkers separately and comparatively. Median levels of KBs decreased significantly over the perioperative period and inversely correlated with changes observed for Troponin T. Associations of patient characteristics with ketone body perioperative course showed notable differences compared to Troponin T, possibly highlighting factors acting as a “driver” for the change in the respective biomarker. We found an inverse correlation between perioperative change in ketone body levels and changes in troponin, indicating a marked decrease in ketone body concentrations in patients exhibiting greater myocardial cell injury. Further investigations aimed at better understanding the role of KBs on perioperative changes are warranted.

Wenyi Lian, Joakim Lindblad, Christina Runow Stark et al.

Oral cancer is a global health challenge. It is treatable if detected early, but it is often fatal in late stages. There is a shift from the invasive and time-consuming tissue sampling and histological examination, toward non-invasive brush biopsies and cytological examination. Reliable computer-assisted methods are essential for cost-effective and accurate cytological analysis, but the lack of detailed cell-level annotations impairs model effectiveness. This study aims to improve AI-based oral cancer detection using multimodal imaging and deep fusion. We combine brightfield and fluorescence whole slide microscopy imaging to analyze Papanicolaou-stained liquid-based cytology slides of brush biopsies collected from both healthy and cancer patients. Due to limited cytological annotations, we utilize a weakly supervised deep learning approach using only patient-level labels. We evaluate various multimodal fusion strategies, including early, late, and three recent intermediate fusion methods. Our results show: (i) fluorescence imaging of Papanicolaou-stained samples provides substantial diagnostic information; (ii) multimodal fusion enhances classification and cancer detection accuracy over single-modality methods. Intermediate fusion is the leading method among the studied approaches. Specifically, the Co-Attention Fusion Network (CAFNet) model excels with an F1 score of 83.34% and accuracy of 91.79%, surpassing human performance on the task. Additional tests highlight the need for precise image registration to optimize multimodal analysis benefits. This study advances cytopathology by combining deep learning and multimodal imaging to enhance early, non-invasive detection of oral cancer, improving diagnostic accuracy and streamlining clinical workflows. The developed pipeline is also applicable in other cytological settings. Our codes and dataset are available online for further research.

Ching-Kai Lin, Di-Chun Wei, Yun-Chien Cheng

This study presents a computer-aided diagnosis (CAD) system to assist early detection of lung metastases during endobronchial ultrasound (EBUS) procedures, significantly reducing follow-up time and enabling timely treatment. Due to limited cytology images and morphological similarities among cells, classifying lung metastases is challenging, and existing research rarely targets this issue directly.To overcome data scarcity and improve classification, the authors propose a few-shot learning model using a hybrid pretrained backbone with fine-grained classification and contrastive learning. Parameter-efficient fine-tuning on augmented support sets enhances generalization and transferability. The model achieved 49.59% accuracy, outperforming existing methods. With 20 image samples, accuracy improved to 55.48%, showing strong potential for identifying rare or novel cancer types in low-data clinical environments.

Kin-Wai Tam, Cheuk-Yin Wong, Kenneth Lap-Kei Wu et al.

The in vitro derivation of Schwann cells from human bone marrow stromal cells (hBMSCs) opens avenues for autologous transplantation to achieve remyelination therapy for post-traumatic neural regeneration. Towards this end, we exploited human induced pluripotent stem-cell-derived sensory neurons to direct Schwann-cell-like cells derived from among the hBMSC-neurosphere cells into lineage-committed Schwann cells (hBMSC-dSCs). These cells were seeded into synthetic conduits for bridging critical gaps in a rat model of sciatic nerve injury. With improvement in gait by 12-week post-bridging, evoked signals were also detectable across the bridged nerve. Confocal microscopy revealed axially aligned axons in association with MBP-positive myelin layers across the bridge in contrast to null in non-seeded controls. Myelinating hBMSC-dSCs within the conduit were positive for both MBP and human nucleus marker HuN. We then implanted hBMSC-dSCs into the contused thoracic cord of rats. By 12-week post-implantation, significant improvement in hindlimb motor function was detectable if chondroitinase ABC was co-delivered to the injured site; such cord segments showed axons myelinated by hBMSC-dSCs. Results support translation into a protocol by which lineage-committed hBMSC-dSCs become available for motor function recovery after traumatic injury to both peripheral and central nervous systems.