American Journal of Pathology最新文献

Lung cancer is an increasingly serious health problem worldwide, and early detection and diagnosis are crucial for successful treatment. With the development of artificial intelligence and the growth of data volume, machine learning techniques can play a significant role in improving the accuracy of early detection in lung cancer. This study proposes a deep learning-based segmentation algorithm for rapid on-site cytopathological evaluation (ROSE) to enhance the diagnostic efficiency of endobronchial ultrasound-guided transbronchial needle aspiration biopsy (EBUS-TBNA) during surgery. By utilizing the CUNet3+ network model, cell clusters, including cancer cell clusters, can be accurately segmented in ROSE-stained pathological sections. The model demonstrated high accuracy, with an F1-score of 0.9604, recall of 0.9609, precision of 0.9654, and accuracy of 0.9834 on the internal testing data set. It also achieved an area under the receiver-operating characteristic curve of 0.9972 for cancer identification. The proposed algorithm saved time for on-site diagnosis, improved EBUS-TBNA efficiency, and outperformed classical segmentation algorithms in accurately identifying lung cancer cell clusters in ROSE-stained images. It effectively reduced over-segmentation, decreased network parameters, and enhanced computational efficiency, making it suitable for real-time patient evaluation during surgical procedures.

Accumulating evidence has substantiated the potential of ambient particulate matter (PM) to elicit detrimental health consequences in the respiratory system, notably airway inflammation. Macrophages, a pivotal component of the innate immune system, assume a crucial function in responding to exogenous agents. However, the roles and detailed mechanisms in regulating PM-induced airway inflammation remain unclear. The current study revealed that PM had the ability to stimulate the formation of macrophage extracellular traps (METs) both in vitro and in vivo. This effect was dependent on peptidylarginine deiminase type 4 (PAD4)–mediated histone citrullination. Additionally, reactive oxygen species were involved in the formation of PM-induced METs, in parallel with PAD4. Genetic deletion of PAD4 in macrophages resulted in an up-regulation of inflammatory cytokine expression. Moreover, mice with PAD4-specific knockout in myeloid cells exhibited exacerbated PM-induced airway inflammation. Mechanistically, inhibition of METs suppressed the phagocytic ability in macrophages, leading to airway epithelial injuries and an aggravated PM-induced airway inflammation. The present study demonstrates that METs play a crucial role in promoting the phagocytosis and clearance of PM by macrophages, thereby suppressing airway inflammation. Furthermore, it suggests that activation of METs may represent a novel therapeutic strategy for PM-related airway disorders.

Bifidobacterium bifidum strain BB1 causes a strain-specific enhancement in intestinal epithelial tight junction (TJ) barrier. Tumor necrosis factor (TNF)-α induces an increase in intestinal epithelial TJ permeability and promotes intestinal inflammation. The major purpose of this study was to delineate the protective effect of BB1 against the TNF-α–induced increase in intestinal TJ permeability and to unravel the intracellular mechanisms involved. TNF-α produces an increase in intestinal epithelial TJ permeability in Caco-2 monolayers and in mice. Herein, the addition of BB1 inhibited the TNF-α increase in Caco-2 intestinal TJ permeability and mouse intestinal permeability in a strain-specific manner. BB1 inhibited the TNF-α–induced increase in intestinal TJ permeability by interfering with TNF-α–induced enterocyte NF-κB p50/p65 and myosin light chain kinase (MLCK) gene activation. The BB1 protective effect against the TNF-α–induced increase in intestinal permeability was mediated by toll-like receptor-2/toll-like receptor-6 heterodimer complex activation of peroxisome proliferator-activated receptor γ (PPAR-γ) and PPAR-γ pathway inhibition of TNF-α–induced inhibitory kappa B kinase α (IKK-α) activation, which, in turn, resulted in a step-wise inhibition of NF-κB p50/p65, MLCK gene, MLCK kinase activity, and MLCK-induced opening of the TJ barrier. In conclusion, these studies unraveled novel intracellular mechanisms of BB1 protection against the TNF-α–induced increase in intestinal TJ permeability. The current data show that BB1 protects against the TNF-α–induced increase in intestinal epithelial TJ permeability via a PPAR-γ–dependent inhibition of NF-κB p50/p65 and MLCK gene activation.

Local tetanus develops when limited amounts of tetanus neurotoxin (TeNT) are released by Clostridium tetani generated from spores inside a necrotic wound. Within days, a spastic paralysis restricted to the muscles of the affected anatomical area develops. This paralysis follows the retrograde transport of TeNT inside the axons of motoneurons and its uptake by inhibitory interneurons with cleavage of a vesicle-associated membrane protein required for neurotransmitter release. Consequently, incontrollable excitation of motoneurons causes contractures of innervated muscles and leads to local spastic paralysis. Here, the initial events occurring close to the site of TeNT release were investigated in a mouse model of local tetanus. A peripheral flaccid paralysis was found to occur, before or concurrent to the spastic paralysis. At variance from the confined TeNT proteolytic activity taking place within motor neuron terminals, central protein cleavage was detected within inhibitory interneurons controlling motor neuron efferents innervating muscle groups distant from the site of TeNT release. These results indicate peripheral activity of TeNT in tetanus and explains why the spastic paralysis observed in local tetanus, although confined to single limbs, generally affects multiple muscles. The initial TeNT neuroparalytic activity can be detected by measuring the compound muscle action potential, providing a very early diagnosis and therapy, thus preventing the ensuing life-threatening generalized tetanus.

This review focuses on the dual role of platelets in atherosclerosis and thrombosis, exploring their involvement in inflammation, angiogenesis, and plaque formation, as well as their hemostatic and prothrombotic functions. Beyond their thrombotic functions, platelets engage in complex interactions with diverse cell types, influencing disease resolution and progression. The contribution of platelet degranulation helps in the formation of atheromatous plaque, whereas the reciprocal interaction with monocytes adds complexity. Alterations in platelet membrane receptors and signaling cascades contribute to advanced atherosclerosis, culminating in atherothrombotic events. Understanding these multifaceted roles of platelets will lead to the development of targeted antiplatelet strategies for effective cardiovascular disease prevention and treatment. Understanding platelet functions in atherosclerosis and atherothrombosis at different stages of disease will be critical for designing targeted treatments and medications to prevent or cure the disease Through this understanding, platelets can be targeted at specific times in the atherosclerosis process, possibly preventing the development of atherothrombosis.

The placenta plays a crucial role in pregnancy success. ΔNp63α (p63), a transcription factor from the TP53 family, is highly expressed in villous cytotrophoblasts (CTBs), the epithelial stem cells of the human placenta, and is involved in CTB maintenance and differentiation. We examined the mechanisms of action of p63 by identifying its downstream targets. Gene expression changes were evaluated following overexpression and knockdown of p63 in the JEG3 choriocarcinoma cell line, using microarray-based RNA profiling. High-temperature requirement A4 (HTRA4), a placenta-specific serine protease involved in trophoblast differentiation and altered in preeclampsia, was identified as a gene reciprocally regulated by p63, and its expression was characterized in primary human placental tissues by RNA-sequencing and in situ hybridization. Potential p63 DNA-binding motifs were identified in the HTRA4 promoter, and p63 occupancy at some of these sites was confirmed using chromatin immunoprecipitation, followed by quantitative PCR in both JEG3 and trophoblast stem cells. These data begin to identify members of the transcriptional network downstream of p63, thus laying the groundwork for probing mechanisms by which this important transcription factor regulates trophoblast stemness and differentiation.

Conjunctival fibrosis is a common postoperative complication of glaucoma filtration surgery, resulting in uncontrolled intraocular pressure and surgery failure. Therefore, there is an urgent need to understand the molecular mechanisms underlying conjunctival fibrosis and to explore novel pharmacologic anti-fibrosis therapies for glaucoma filtration surgery. Herein, the 4-dimensional data-independent acquisition (4D-DIA) quantitative proteomic results, coupled with experimental data, revealed the activation of the Wnt/β-catenin pathway in transforming growth factor (TGF)-β1–induced human conjunctival fibroblasts (HConFs). Treatment with ICG-001, a Wnt/β-catenin inhibitor, effectively inhibited cell proliferation and migration in TGFβ1-treated HConFs. ICG-001 treatment alleviated the increased generation of extracellular matrix proteins induced by TGFβ1. In addition, ICG-001 reduced the expression level of α smooth muscle actin (α-SMA) and inhibited cell contractility in TGFβ1-treated HConFs. Proteomics data further suggested that αB-crystallin (CRYAB) was a downstream target of Wnt/β-catenin, which was up-regulated by TGFβ1 and down-regulated by ICG-001. Immunoblotting assay also indicated that ICG-001 reduced the expressions of ubiquitin and β-catenin in TGFβ1-treated HConFs, implying that CRYAB stabilized β-catenin by inhibiting its ubiquitination degradation. Exogenous CRYAB promoted cell viability, increased extracellular matrix protein levels, and up-regulated α-SMA expression of HConFs under TGFβ1 stimulation. CRYAB rescued TGFβ1-induced fibrotic responses that were suppressed by ICG-001. In conclusion, this study elucidates the regulatory mechanism of the Wnt/β-catenin/CRYAB pathway in conjunctival fibrosis, offering promising therapeutic targets for mitigating bleb scarring after glaucoma filtration surgery.

Endometrial cancer is the fourth most common cancer in women in the United States, with a lifetime risk of approximately 2.8%. Precise histologic evaluation and molecular classification of endometrial cancer are important for effective patient management and determining the best treatment options. This study introduces EndoNet, which uses convolutional neural networks for extracting histologic features and a vision transformer for aggregating these features and classifying slides into high- and low-grade cases. The model was trained on 929 digitized hematoxylin and eosin–stained whole-slide images of endometrial cancer from hysterectomy cases at Dartmouth-Health. It classifies these slides into low-grade (endometrioid grades 1 and 2) and high-grade (endometrioid carcinoma International Federation of Gynecology and Obstetrics grade 3, uterine serous carcinoma, or carcinosarcoma) categories. EndoNet was evaluated on an internal test set of 110 patients and an external test set of 100 patients from The Cancer Genome Atlas database. The model achieved a weighted average F1 score of 0.91 (95% CI, 0.86 to 0.95) and an area under the curve of 0.95 (95% CI, 0.89 to 0.99) on the internal test, and 0.86 (95% CI, 0.80 to 0.94) for F1 score and 0.86 (95% CI, 0.75 to 0.93) for area under the curve on the external test. Pending further validation, EndoNet has the potential to support pathologists without the need of manual annotations in classifying the grades of gynecologic pathology tumors.

Liver resection is one of the best treatments for small hepatocellular carcinoma (HCC), but post-resection recurrence is frequent. Biotherapies have emerged as an efficient adjuvant treatment, making the identification of patients at high risk of recurrence critical. Microvascular invasion (mVI), poor differentiation, pejorative macrotrabecular architectures, and vessels encapsulating tumor clusters architectures are the most accurate histologic predictors of recurrence, but their evaluation is time-consuming and imperfect. Herein, a supervised deep learning–based approach with ResNet34 on 680 whole slide images (WSIs) from 107 liver resection specimens was used to build an algorithm for the identification and quantification of these pejorative architectures. This model achieved an accuracy of 0.864 at patch level and 0.823 at WSI level. To assess its robustness, it was validated on an external cohort of 29 HCCs from another hospital, with an accuracy of 0.787 at WSI level, affirming its generalization capabilities. Moreover, the largest connected areas of the pejorative architectures extracted from the model were positively correlated to the presence of mVI and the number of tumor emboli. These results suggest that the identification of pejorative architectures could be an efficient surrogate of mVI and have a strong predictive value for the risk of recurrence. This study is the first step in the construction of a composite predictive algorithm for early post-resection recurrence of HCC, including artificial intelligence–based features.