SAHIS-Net: a spectral attention and feature enhancement network for microscopic hyperspectral cholangiocarcinoma image segmentation.

Cholangiocarcinoma (CCA) poses a significant clinical challenge due to its aggressive nature and poor prognosis. While traditional diagnosis relies on color-based histopathology, hyperspectral imaging (HSI) offers rich, high-dimensional data holding potential for more accurate diagnosis. However, extracting meaningful insights from this data remains challenging. This work investigates the application of deep learning for CCA segmentation in microscopic HSI images, and introduces two novel neural networks: (1) Histogram Matching U-Net (HM-UNet) for efficient image pre-processing, and (2) Spectral Attention based Hyperspectral Image Segmentation Net (SAHIS-Net) for CCA segmentation. SAHIS-Net integrates a novel Spectral Attention (SA) module for adaptively weighing spectral information, an improved attention-aware feature enhancement (AFE) mechanism for better providing the model with more discriminative features, and a multi-loss training strategy for effective early stage feature extraction. We compare SAHIS-Net against several general and CCA-specific models, demonstrating its superior performance in segmenting CCA regions. These results highlight the potential of our approach for segmenting medical HSI images.

Immunostimulatory CKb11 gene combined with immune checkpoint PD-1/PD-L1 blockade activates immune response and simultaneously overcomes the immunosuppression of cancer.

Immunosuppression tumor microenvironment (TME) seriously impedes anti-tumor immune response, resulting in poor immunotherapy effect of cancer. This study develops a folate-modified delivery system to transport the plasmids encoding immune stimulatory chemokine CKb11 and PD-L1 inhibitors to tumor cells, resulting in high CKb11 secretion from tumor cells, successfully activating immune cells and increasing cytokine secretion to reshape the TME, and ultimately delaying tumor progression. The chemokine CKb11 enhances the effectiveness of tumor immunotherapy by increasing the infiltration of immune cells in TME. It can cause high expression of IFN-γ, which is a double-edged sword that inhibits tumor growth while causing an increase in the expression of PD-L1 on tumor cells. Therefore, combining CKb11 with PD-L1 inhibitors can counterbalance the suppressive impact of PD-L1 on anti-cancer defense, leading to a collaborative anti-tumor outcome. Thus, utilizing nanotechnology to achieve targeted delivery of immune stimulatory chemokines and immune checkpoint inhibitors to tumor sites, thereby reshaping immunosuppressive TME for cancer treatment, has great potential as an immunogene therapy in clinical applications.

Segmentation of hyphae and yeast in fungi-infected tissue slice images and its application in analyzing antifungal blue light therapy.

Candida albicans is a pathogenic fungus that undergoes morphological transitions between hyphal and yeast forms, adapting to diverse environmental stimuli and exhibiting distinct virulence. Existing research works on antifungal blue light (ABL) therapy have either focused solely on hyphae or neglected to differentiate between morphologies, obscuring potential differential effects. To address this gap, we established a novel dataset of 150 C. albicans-infected mouse skin tissue slice images with meticulously annotated hyphae and yeast. Eleven representative convolutional neural networks were trained and evaluated on this dataset using seven metrics to identify the optimal model for segmenting hyphae and yeast in original high pixel size images. Leveraging the segmentation results, we analyzed the differential impact of blue light on the invasion depth and density of both morphologies within the skin tissue. U-Net-BN outperformed other models in segmentation accuracy, achieving the best overall performance. While both hyphae and yeast exhibited significant reductions in invasion depth and density at the highest ABL dose (180 J/cm2), only yeast was significantly inhibited at the lower dose (135 J/cm2). This novel finding emphasizes the importance of developing more effective treatment strategies for both morphologies.

We studied the effects of blue light therapy on hyphal and yeast forms of Candida albicans. Through image segmentation techniques, we discovered that the changes in invasion depth and density differed between these two forms after exposure to blue light.

Immunostimulatory gene therapy combined with checkpoint blockade reshapes tumor microenvironment and enhances ovarian cancer immunotherapy.

Immune evasion has made ovarian cancer notorious for its refractory features, making the development of immunotherapy highly appealing to ovarian cancer treatment. The immune-stimulating cytokine IL-12 exhibits excellent antitumor activities. However, IL-12 can induce IFN-γ release and subsequently upregulate PDL-1 expression on tumor cells. Therefore, the tumor-targeting folate-modified delivery system F-DPC is constructed for concurrent delivery of IL-12 encoding gene and small molecular PDL-1 inhibitor (iPDL-1) to reduce immune escape and boost anti-tumor immunity. The physicochemical characteristics, gene transfection efficiency of the F-DPC nanoparticles in ovarian cancer cells are analyzed. The immune-modulation effects of combination therapy on different immune cells are also studied. Results show that compared with non-folate-modified vector, folate-modified F-DPC can improve the targeting of ovarian cancer and enhance the transfection efficiency of pIL-12. The underlying anti-tumor mechanisms include the regulation of T cells proliferation and activation, NK activation, macrophage polarization and DC maturation. The F-DPC/pIL-12/iPDL-1 complexes have shown outstanding antitumor effects and low toxicity in peritoneal model of ovarian cancer in mice. Taken together, our work provides new insights into ovarian cancer immunotherapy. Novel F-DPC/pIL-12/iPDL-1 complexes are revealed to exert prominent anti-tumor effect by modulating tumor immune microenvironment and preventing immune escape and might be a promising treatment option for ovarian cancer treatment.

Tumor-Microenvironment-Activatable Nanoparticle Mediating Immunogene Therapy and M2 Macrophage-Targeted Inhibitor for Synergistic Cancer Immunotherapy.

Immunotherapy has achieved prominent clinical efficacy in combating cancer and has recently become a mainstream treatment strategy. However, achieving broad efficacy with a single modality is challenging, and the heterogeneity of the tumor microenvironment (TME) restricts the accuracy and effectiveness of immunotherapy strategies for tumors. Herein, a TME-responsive targeted nanoparticle to enhance antitumor immunity and reverse immune escape by codelivering interleukin-12 (IL-12) expressing gene and colony-stimulating factor-1 receptor (CSF-1R) inhibitor PLX3397 (PLX) is presented. The introduction of disulfide bonds and cyclo(Arg-Gly-Asp-d-Phe-Lys) (cRGD) peptides conferred reduction reactivity and tumor targeting to the nanoparticles, respectively. It is hypothesized that activating host immunity by the local expression of IL-12, while modulating the tumor-associated macrophages (TAM) function through blocking CSF-1/CSF-1R signaling, could constitute a feasible approach for cancer immunotherapy. The fabricated functional nanoparticle successfully ameliorated the TME by stimulating the proliferation and activation of T lymphocytes, promoting the repolarization of TAMs, reducing myeloid-derived suppressor cells (MDSCs), and promoting the maturation of dendritic cells (DC) as well as the secretion of antitumor cytokines, which efficiently suppressed tumor growth and metastasis. Finally, substantial changes in the TME were deciphered by single-cell analysis including infiltration of different cells, transcriptional states, secretory signaling and cell-cell communications. These findings provide a promising combinatorial immunotherapy strategy through immunomodulatory nanoparticles.

High-resolution ultrasonography for the diagnosis of brachial plexus root lesions.

The aim of this study was to investigate the feasibility of using high-resolution ultrasonography in the diagnosis of brachial plexus (BP) root lesions. A prospective study of ultrasonographic evaluation of BP nerve roots was performed in 37 patients with BP root lesions (29 with root injuries, 8 with tumors). The pre-operative ultrasonographic findings were compared with the surgical and pathohistological findings. All C5-7 roots were detected by ultrasonography in all patients, whereas 92% (68/74) of C8 and 51% (38/74) of T1 nerve roots were visualized. Among 29 patients with BP root avulsion, partial injuries or totally interrupted BP roots were detected in all patients. Cystic masses and neuromas were detected in 16 and 23 patients, respectively. In 8 patients with BP root tumors, 8 hypo-echoic masses were detected inside or partly outside of intervertebral foramina connecting to nerve roots. Surgical exploration revealed that there were 57 BP root avulsions in 29 patients. However, 2 T1 nerve root avulsions had been missed by pre-operative ultrasonography. Pathohistology revealed that all 8 BP root tumors pre-operatively diagnosed by ultrasonography were schwannomas. High-resolution ultrasonography can provide a convenient and accurate imaging modality for quick diagnosis and location of BP root lesions.