Unsupervised domain adaptation for histopathology image segmentation with incomplete labels.

Stain variations pose a major challenge to deep learning segmentation algorithms in histopathology images. Current unsupervised domain adaptation methods show promise in improving model generalization across diverse staining appearances but demand abundant accurately labeled source domain data. This paper assumes a novel scenario, namely, unsupervised domain adaptation based segmentation task with incompletely labeled source data. This paper propose a Stain-Adaptive Segmentation Network with Incomplete Labels (SASN-IL). Specifically, the algorithm consists of two stages. The first stage is an incomplete label correction stage, involving reliable model selection and label correction to rectify false-negative regions in incomplete labels. The second stage is the unsupervised domain adaptation stage, achieving segmentation on the target domain. In this stage, we introduce an adaptive stain transformation module, which adjusts the degree of transformation based on segmentation performance. We evaluate our method on a gastric cancer dataset, demonstrating significant improvements, with a 10.01% increase in Dice coefficient compared to the baseline and competitive performance relative to existing methods.

CrossU-Net: Dual-modality cross-attention U-Net for segmentation of precancerous lesions in gastric cancer.

Gastric precancerous lesions (GPL) significantly elevate the risk of gastric cancer, and precise diagnosis and timely intervention are critical for patient survival. Due to the elusive pathological features of precancerous lesions, the early detection rate is less than 10%, which hinders lesion localization and diagnosis. In this paper, we provide a GPL pathological dataset and propose a novel method for improving the segmentation accuracy on a limited-scale dataset, namely RGB and Hyperspectral dual-modal pathological image Cross-attention U-Net (CrossU-Net). Specifically, we present a self-supervised pre-training model for hyperspectral images to serve downstream segmentation tasks. Secondly, we design a dual-stream U-Net-based network to extract features from different modal images. To promote information exchange between spatial information in RGB images and spectral information in hyperspectral images, we customize the cross-attention mechanism between the two networks. Furthermore, we use an intermediate agent in this mechanism to improve computational efficiency. Finally, we add a distillation loss to align predicted results for both branches, improving network generalization. Experimental results show that our CrossU-Net achieves accuracy and Dice of 96.53% and 91.62%, respectively, for GPL lesion segmentation, providing a promising spectral research approach for the localization and subsequent quantitative analysis of pathological features in early diagnosis.

Long-Term Transcriptomic Changes and Cardiomyocyte Hyperpolyploidy after Lactose Intolerance in Neonatal Rats.

Many cardiovascular diseases originate from growth retardation, inflammation, and malnutrition during early postnatal development. The nature of this phenomenon is not completely understood. Here we aimed to verify the hypothesis that systemic inflammation triggered by neonatal lactose intolerance (NLI) may exert long-term pathologic effects on cardiac developmental programs and cardiomyocyte transcriptome regulation. Using the rat model of NLI triggered by lactase overloading with lactose and the methods of cytophotometry, image analysis, and mRNA-seq, we evaluated cardiomyocyte ploidy, signs of DNA damage, and NLI-associated long-term transcriptomic changes of genes and gene modules that differed qualitatively (i.e., were switched on or switched off) in the experiment vs. the control. Our data indicated that NLI triggers the long-term animal growth retardation, cardiomyocyte hyperpolyploidy, and extensive transcriptomic rearrangements. Many of these rearrangements are known as manifestations of heart pathologies, including DNA and telomere instability, inflammation, fibrosis, and reactivation of fetal gene program. Moreover, bioinformatic analysis identified possible causes of these pathologic traits, including the impaired signaling via thyroid hormone, calcium, and glutathione. We also found transcriptomic manifestations of increased cardiomyocyte polyploidy, such as the induction of gene modules related to open chromatin, e.g., "negative regulation of chromosome organization", "transcription" and "ribosome biogenesis". These findings suggest that ploidy-related epigenetic alterations acquired in the neonatal period permanently rewire gene regulatory networks and alter cardiomyocyte transcriptome. Here we provided first evidence indicating that NLI can be an important trigger of developmental programming of adult cardiovascular disease. The obtained results can help to develop preventive strategies for reducing the NLI-associated adverse effects of inflammation on the developing cardiovascular system.

HPV Type Distribution in Benign, High-Grade Squamous Intraepithelial Lesions and Squamous Cell Cancers of the Anus by HIV Status.

The incidence of anal cancer is increasing, especially in high-risk groups, such as PLWH. HPV 16, a high-risk (HR) HPV genotype, is the most common genotype in anal high-grade squamous intraepithelial lesions (HSIL) and squamous cell carcinoma (SCC) in the general population. However, few studies have described the distribution of HR HPV genotypes other than HPV 16 in the anus of PLWH. HPV genotyping was performed by DNA amplification followed by dot-blot hybridization to identify the HR and low-risk (LR) genotypes in benign anal lesions (n = 34), HSIL (n = 30), and SCC (n = 51) of PLWH and HIV-negative individuals. HPV 16 was the most prominent HR HPV identified, but it was less common in HSIL and SCC from PLWH compared with HIV-negative individuals, and other non-HPV 16 HR HPV (non-16 HR HPV) types were more prevalent in samples from PLWH. A higher proportion of clinically normal tissues from PLWH were positive for one or more HPV genotypes. Multiple HPV infection was a hallmark feature for all tissues (benign, HSIL, SCC) of PLWH. These results indicate that the development of anal screening approaches based on HPV DNA testing need to include non-16 HR HPVs along with HPV 16, especially for PLWH. Along with anal cytology, these updated screening approaches may help to identify and prevent anal disease progression in PLWH.

An international comparability study to determine the sources of uncertainty associated with a non-competitive sandwich fluorescent ELISA.

BACKGROUND: Immunoassays allow the specific detection and quantitation of biological molecules in complex samples at physiologically relevant concentrations. However, there are concerns over the comparability of such techniques when the same assay is performed by different operators or laboratories. An international intercomparison study was performed to assess the uncertainty involved in the estimation of a protein cytokine concentration using a fluorescent ELISA. METHODS: The intercomparison study method was based on a non-competitive sandwich immunoassay with an enhancement step to generate a fluorescent readout. The intercomparison was performed in two phases, with the uncertainty of the instrument determined separately from that of the assay. The 11 laboratories participating in the study represented national metrology institutes or nominated expert laboratories. RESULTS: Participants were asked to determine an undisclosed concentration of interferon using a supplied standard. The mean participant estimate and experimental standard deviation of the mean was 3.54+/-0.22 mg/L, with the spread of data ranging around +/-35% of the mean. The quantitation range of the ELISA and of participants' instruments displayed large variation that contributed to the overall uncertainty. CONCLUSIONS: Identified sources of uncertainty within the ELISA methodology included pipetting, data fitting, model selection and instrument/plate variation.

Hepatitis C virus core protein transforms murine fibroblasts by promoting genomic instability.

The oncogenic potential of hepatitis C virus (HCV) core protein has been demonstrated, but the precise mechanism of cell transformation triggered by HCV core is still unclear. This study shows that constitutive expression of HCV core protein (core) in NIH 3T3 murine fibroblasts triggers malignant transformation. At the preneoplastic stage, clones that expressed HCV core constitutively demonstrated genomic instability seen as disruption of the mitotic spindle cell checkpoint leading to increased ploidy. Transformation was completed by the loss of DNA and resistance to apoptosis induced by serum starvation. Simultaneously, cells acquired a capacity for anchorage independent growth and absence of contact inhibition. Inoculation of these transformed cells into severe combined immune deficiency (SCID) mice led to formation of solid core-expressing tumors. Transformation and tumorigenicity of core-expressing cell lines coincided with a 5- to 10-fold repression of endogenous p53 transactivation. Thus, long-term HCV core expression alone is sufficient for complete transformation of immortal fibroblasts that can then induce tumors in a susceptible host. This data suggests that malignant transformation by HCV core may occur through primary stress, induction of genomic instability, and further HCV core-induced rescue of surviving mutated cells.