Unsupervised augmentation optimization for few-shot medical image segmentation

The augmentation parameters matter to few-shot semantic segmentation since they directly affect the training outcome by feeding the networks with varying perturbated samples. However, searching optimal augmentation parameters for few-shot segmentation models without annotations is a challenge that current methods fail to address. In this paper, we first propose a framework to determine the ``optimal'' parameters without human annotations by solving a distribution-matching problem between the intra-instance and intra-class similarity distribution, with the intra-instance similarity describing the similarity between the original sample of a particular anatomy and its augmented ones and the intra-class similarity representing the similarity between the selected sample and the others in the same class. Extensive experiments demonstrate the superiority of our optimized augmentation in boosting few-shot segmentation models. We greatly improve the top competing method by 1.27\% and 1.11\% on Abd-MRI and Abd-CT datasets, respectively, and even achieve a significant improvement for SSL-ALP on the left kidney by 3.39\% on the Abd-CT dataset

FairAdaBN: Mitigating unfairness with adaptive batch normalization and its application to dermatological disease classification

Deep learning is becoming increasingly ubiquitous in medical research and applications while involving sensitive information and even critical diagnosis decisions. Researchers observe a significant performance disparity among subgroups with different demographic attributes, which is called model unfairness, and put lots of effort into carefully designing elegant architectures to address unfairness, which poses heavy training burden, brings poor generalization, and reveals the trade-off between model performance and fairness. To tackle these issues, we propose FairAdaBN by making batch normalization adaptive to sensitive attribute. This simple but effective design can be adopted to several classification backbones that are originally unaware of fairness. Additionally, we derive a novel loss function that restrains statistical parity between subgroups on mini-batches, encouraging the model to converge with considerable fairness. In order to evaluate the trade-off between model performance and fairness, we propose a new metric, named Fairness-Accuracy Trade-off Efficiency (FATE), to compute normalized fairness improvement over accuracy drop. Experiments on two dermatological datasets show that our proposed method outperforms other methods on fairness criteria and FATE.Comment: Accepted by MICCAI 202

Seroprevalence of Toxoplasma gondii infection in dairy goats in Shaanxi Province, Northwestern China

<p>Abstract</p> <p>Background</p> <p><it>Toxoplasma gondii </it>is an important zoonotic pathogen causing significant human and animal health problems. Infection in dairy goats not only results in significant reproductive losses, but also represents an important source of human infection due to consumption of infected meat and milk. In the present study we report for the first time seroprevalence of <it>T. gondii </it>infection in Guanzhong and Saanen dairy goats in Shaanxi province, Northwestern China.</p> <p>Results</p> <p>Sera from 751 dairy goats from 9 farms in 6 counties were examined for <it>T. gondii </it>antibodies with an indirect haemagglutination (IHA) test. Antibodies to <it>T. gondii </it>were detected in 106 (14.1%) serum samples, with antibody titres ranging from 1:64 to 1:1024. Seropositive goats were found in all 9 farms and seroprevalences in Guanzhong (16.3%, 75/461) and Saanen (10.7%, 31/290) dairy goats were not statistically significantly different. All the factors (sex, age and location) reported in the present study affected prevalence of infection, and seroprevalence increased with age, suggesting postnatal acquisition of <it>T. gondii </it>infection.</p> <p>Conclusions</p> <p>The results of the present survey indicate that infection by <it>T. gondii </it>is widely prevalent in dairy goats in Shaanxi province, Northwestern China, and this has implications for prevention and control of toxoplasmosis in this province.</p

Spatial Pathomics Toolkit for Quantitative Analysis of Podocyte Nuclei with Histology and Spatial Transcriptomics Data in Renal Pathology

Podocytes, specialized epithelial cells that envelop the glomerular capillaries, play a pivotal role in maintaining renal health. The current description and quantification of features on pathology slides are limited, prompting the need for innovative solutions to comprehensively assess diverse phenotypic attributes within Whole Slide Images (WSIs). In particular, understanding the morphological characteristics of podocytes, terminally differentiated glomerular epithelial cells, is crucial for studying glomerular injury. This paper introduces the Spatial Pathomics Toolkit (SPT) and applies it to podocyte pathomics. The SPT consists of three main components: (1) instance object segmentation, enabling precise identification of podocyte nuclei; (2) pathomics feature generation, extracting a comprehensive array of quantitative features from the identified nuclei; and (3) robust statistical analyses, facilitating a comprehensive exploration of spatial relationships between morphological and spatial transcriptomics features.The SPT successfully extracted and analyzed morphological and textural features from podocyte nuclei, revealing a multitude of podocyte morphomic features through statistical analysis. Additionally, we demonstrated the SPT's ability to unravel spatial information inherent to podocyte distribution, shedding light on spatial patterns associated with glomerular injury. By disseminating the SPT, our goal is to provide the research community with a powerful and user-friendly resource that advances cellular spatial pathomics in renal pathology. The implementation and its complete source code of the toolkit are made openly accessible at https://github.com/hrlblab/spatial_pathomics

Identification, Characterization, and Effects of Xenopus laevis PNAS-4 Gene on Embryonic Development

Apoptosis plays an important role in embryonic development. PNAS-4 has been demonstrated to induce apoptosis in several cancer cells. In this study, we cloned Xenopus laevis PNAS-4 (xPNAS-4), which is homologous to the human PNAS-4 gene. Bioinformatics analysis for PNAS-4 indicated that xPNAS-4 shared 87.6% identity with human PNAS-4 and 85.5% with mouse PNAS-4. The phylogenetic tree of PNAS-4 protein was also summarized. An analysis of cellular localization using an EGFP-fused protein demonstrated that xPNAS-4 was localized in the perinuclear region of the cytoplasm. RT-PCR analysis revealed that xPNAS-4, as a maternally expressed gene, was present in all stages of early embryo development. Whole-mount in situ hybridization showed that xPNAS-4 was mainly expressed in ectoderm and mesoderm. Furthermore, microinjection of xPNAS-4 mRNA in vivo caused developmental defects manifesting as a small eye phenotype in the Xenopous embryos, and as a small eye or one-eye phenotype in developing zebrafish embryos. In addition, embryos microinjected with xPNAS-4 antisense morpholino oligonucleotides (MOs) exhibited a failure of head development and shortened axis

Franck-Condon Effect in Central Spin System

We study the quantum transitions of a central spin surrounded by a collective-spin environment. It is found that the influence of the environmental spins on the absorption spectrum of the central spin can be explained with the analog of the Franck-Condon (FC) effect in conventional electron-phonon interaction system. Here, the collective spins of the environment behave as the vibrational mode, which makes the electron to be transitioned mainly with the so-called "vertical transitions" in the conventional FC effect. The "vertical transition" for the central spin in the spin environment manifests as, the certain collective spin states of the environment is favored, which corresponds to the minimal change in the average of the total spin angular momentum.Comment: 8 pages, 8 figure

Dysregulation of hepatic microRNA expression in C57BL/6 mice affected by excretory-secretory products of Fasciola gigantica

The excretory-secretory products released by the liver fluke Fasciola gigantica (FgESPs) play important roles in regulating the host immune response during the infection. Identification of hepatic miRNAs altered by FgESPs may improve our understanding of the pathogenesis of F. gigantica infection. In this study, we investigated the alterations in the hepatic microRNAs (miRNAs) in mice treated with FgESPs using high-throughput small RNA (sRNA) sequencing and bioinformatics analysis. The expression of seven miRNAs was confirmed by quantitative stem-loop reverse transcription quantitative PCR (qRT-PCR). A total of 1,313 miRNAs were identified in the liver of mice, and the differentially expressed (DE) miRNAs varied across the time lapsed post exposure to FgESPs. We identified 67, 154 and 53 dysregulated miRNAs at 1, 4 and 12 weeks post-exposure, respectively. 5 miRNAs (miR-126a-3p, miR-150-5p, miR-155-5p, miR-181a-5p and miR-362-3p) were commonly dysregulated at the three time points. We also found that most of the DE miRNAs were induced by FgESPs in the mouse liver after 4 weeks of exposure. These were subjected to Gene Ontology (GO) enrichment analysis, which showed that the predicted targets of the hepatic DE miRNAs of mice 4 weeks of FgESPs injection were enriched in GO terms, including cell membrane, ion binding, cellular communication, organelle and DNA damage. KEGG analysis indicated that the predicted targets of the most downregulated miRNAs were involved in 15 neural activity-related pathways, 6 digestion-related pathways, 20 immune response-related pathways and 17 cancer-related pathways. These data provide new insights into how FgESPs can dysregulate hepatic miRNAs, which play important roles in modulating several aspects of F. gigantica pathogenesis

Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging

The segment anything model (SAM) was released as a foundation model for image segmentation. The promptable segmentation model was trained by over 1 billion masks on 11M licensed and privacy-respecting images. The model supports zero-shot image segmentation with various segmentation prompts (e.g., points, boxes, masks). It makes the SAM attractive for medical image analysis, especially for digital pathology where the training data are rare. In this study, we evaluate the zero-shot segmentation performance of SAM model on representative segmentation tasks on whole slide imaging (WSI), including (1) tumor segmentation, (2) non-tumor tissue segmentation, (3) cell nuclei segmentation. Core Results: The results suggest that the zero-shot SAM model achieves remarkable segmentation performance for large connected objects. However, it does not consistently achieve satisfying performance for dense instance object segmentation, even with 20 prompts (clicks/boxes) on each image. We also summarized the identified limitations for digital pathology: (1) image resolution, (2) multiple scales, (3) prompt selection, and (4) model fine-tuning. In the future, the few-shot fine-tuning with images from downstream pathological segmentation tasks might help the model to achieve better performance in dense object segmentation

Lycium barbarum Polysaccharides Attenuate Cisplatin-Induced Hair Cell Loss in Rat Cochlear Organotypic Cultures

The aim of the present study was to investigate the effects of Lycium barbarum polysaccharides (LBP) on cisplatin-induced hair cell damage in the organ of Corti explant. The neonatal (P2–3) rat organ of Corti explant was exposed to cisplatin (20 μM; 48 h) with or without LBP pretreatment (150 and 600 μg/mL; 24 h). Hair cell loss was indicated by FITC-labeled phalloidin staining. The level of reactive oxygen species (ROS) and alteration of mitochondrial membrane potential (ΔΨm) in hair cells were analyzed using fluorescent probes 2′,7′-dichlorofluorescein diacetate and JC-1, respectively. The results showed that LBP significantly attenuated hair cell loss (p < 0.01). Hair cells pretreated with LBP showed significant reduction in ROS production and the decline of ΔΨm compared with cisplatin alone group (p < 0.01), indicating the protective effect of LBP on cisplatin-induced hair cell loss. Taken together, these results indicate that LBP was effective in attenuating cisplatin-induced hair cell loss by reducing the production of ROS and maintaining mitochondrial ΔΨm