The Gleason grading system, currently the most powerful prognostic predictor of prostate cancer, is based solely on the tumor’s histological architecture and has high inter-observer variability. We propose an automated Gleason scoring system based on deep neural networks for diagnosis of prostate core needle biopsy samples. To verify its efficacy, the system was trained using 1133 cases of prostate core needle biopsy samples and validated on 700 cases. Further, system-based diagnosis results were compared with reference standards derived from three certified pathologists. In addition, the system’s ability to quantify cancer in terms of tumor length was also evaluated via comparison with pathologist-based measurements. The results showed a substantial diagnostic concordance between the system-grade group classification and the reference standard (0.907 quadratic-weighted Cohen’s kappa coefficient). The system tumor length measurements were also notably closer to the reference standard (correlation coefficient, R = 0.97) than the original hospital diagnoses (R = 0.90). We expect this system to assist pathologists to reduce the probability of over- or under-diagnosis by providing pathologist-level second opinions on the Gleason score when diagnosing prostate biopsy, and to support research on prostate cancer treatment and prognosis by providing reproducible diagnosis based on the consistent standards.

In histopathology, acquiring subcellular-level three-dimensional (3D) tissue structures efficiently and without damaging the tissues during serial sectioning and staining remains a formidable challenge. We address this by integrating holotomography with deep learning and creating 3D virtual hematoxylin and eosin (H&E) images from label-free thick cancer tissues. This method involves measuring the tissues’ 3D refractive index (RI) distribution using holotomography, followed by processing with a deep learning-based image translation framework to produce virtual H&E staining in 3D. Applied to colon cancer tissues up to 50 µm thick—far surpassing conventional slide thickness—this technique provides direct methodological validation through chemical H&E staining. It reveals quantitative 3D microanatomical structures of colon cancer with subcellular resolution. Further validation of our method’s repeatability and scalability is demonstrated on gastric cancer samples across different institutional settings. This innovative 3D virtual H&E staining method enhances histopathological efficiency and reliability, marking a significant advancement in extending histopathology to the 3D realm and offering substantial potential for cancer research and diagnostics.

Recent advances in spatial transcriptomics (ST) technologies have transformed our ability to profile gene expression while preserving crucial spatial context within tissues. However, existing ST platforms are constrained by high costs, long turnaround times, low resolution, limited gene coverage and inherently small tissue capture areas, which hinder their broad applications. Here we present iSCALE, a method that reconstructs large-scale, super-resolution gene expression landscapes and automatically annotates cellular-level tissue architecture in samples exceeding capture areas of current ST platforms. The performance of iSCALE was assessed by comprehensive evaluations involving benchmarking experiments, immunohistochemistry staining and manual annotations by pathologists. When applied to multiple sclerosis human brain samples, iSCALE uncovered lesion-associated cellular characteristics undetectable by conventional ST experiments. Our results demonstrate the utility of iSCALE in analyzing large tissues by enabling unbiased annotation, resolving cell type composition, mapping cellular microenvironments and revealing spatial features beyond the reach of standard ST analysis or routine histopathological assessment.

Cancer is a major cause of mortality and morbidity in Korea. However, there has been no previous nursing literature review on the phenomenon of resilience among cancer patients in Korea. The purpose of this study was to identify information about theories, instruments, correlates, and outcomes of resilience in the cancer experiences of Korean adults. This was a scoping review that searched Ovid MEDLINE, CINAHL, Google Scholar, DBpia, and the Korean Studies Information Service System between 2000 and 2016 in order to identify English and Korean research reports. The review yielded 17 quantitative studies, including 2 resilience theories and 6 resilience-specific instruments. The factors self-efficacy, hope, social supports, self-esteem, anxiety, and depression were associated with resilience, regardless of the type of cancer. Quality of life and coping were commonly investigated outcome variables for resilience. This review suggests that a nursing theory reflecting Korean culture and qualitative research concerning the phenomenon of resilience should be conducted as research priorities as the foundation for developing culturally appropriate tools for resilience. This will lead to enhanced quality of life among Korean cancer patients, which is the core of palliative nursing care.

Hepatic steatosis renders hepatocytes vulnerable to injury, resulting in the progression of preexisting liver disease. Previous animal and cell culture studies implicated mammalian target of rapamycin (mTOR), signal transducer and activator of transcription-3 (STAT3), extracellular signal-regulated kinase (ERK) and estrogen-receptor α in the pathogenesis of hepatic steatosis and disease progression. However, to date there have been few studies performed using human liver tissue to study hepatic steatosis. We examined the expression patterns of mTOR, STAT3, ERK and estrogen-receptor α in liver tissues from patients diagnosed with hepatic steatosis. We reviewed the clinical and histomorphological features of 29 patients diagnosed with hepatic steatosis: 18 with non-alcoholic fatty liver disease (NAFLD), 11 with alcoholic fatty acid disease (AFLD), and a control group (16 biliary cysts and 22 hepatolithiasis). Immunohistochemistry was performed on liver tissue using an automated immunostainer. The histologic severity of hepatic steatosis was evaluated by assessing four key histomorphologic parameters common to NAFLD and AFLD: steatosis, lobular inflammation, ballooning degeneration and fibrosis. mTOR, phosphorylated STAT3, phosphorylated pERK, estrogen-receptor α were found to be more frequently expressed in the hepatic steatosis group than in the control group. Specifically, mTOR was expressed in 78% of hepatocytes, and ERK in 100% of hepatic stellate cells, respectively, in patients with NAFLD. Interestingly, estrogen-receptor α was diffusely expressed in hepatocytes in all NALFD cases. Phosphorylated (active) STAT3 was expressed in 73% of hepatocytes and 45% of hepatic stellate cells in patients with AFLD, and phosphorylated (active) ERK was expressed in hepatic stellate cells in all AFLD cases. Estrogen-receptor α was expressed in all AFLD cases (focally in 64% of AFLD cases, and diffusely in 36%). Phosphorylated STAT3 expression in hepatocytes and hepatic stellate cells correlated with severe lobular inflammation, severe ballooning degeneration and advanced fibrosis, whereas diffusely expressed estrogen-receptor α correlated with a mild stage of fibrosis. Our data indicate ERK activation and estrogen-receptor α may be relevant in the development of hepatic steatosis. However, diffuse expression of estrogen-receptor α would appear to impede disease progression, including hepatic fibrosis. Finally, phosphorylated STAT3 may also contribute to disease progression.