A universal immunohistochemistry analyzer for generalizing AI-driven assessment of immunohistochemistry across immunostains and cancer types.

Immunohistochemistry (IHC) is the common companion diagnostics in targeted therapies. However, quantifying protein expressions in IHC images present a significant challenge, due to variability in manual scoring and inherent subjective interpretation. Deep learning (DL) offers a promising approach to address these issues, though current models require extensive training for each cancer and IHC type, limiting the practical application.

System-level interventions for fall risk assessment, fall prevention and fall injury prevention in long-term care facilities: a scoping review.

Objectives: Older adults living in long-term care facilities (LTCFs) are at high risk for falls. Interventions to prevent falls and fall-related injury in this population may be individual-level or system-focused interventions. However, relatively little attention has been given to research on system-focused interventions.

Person-focused interventions for fall risk assessment, fall prevention and fall injury prevention in long-term care facilities: a scoping review.

Objective: Falls are a significant concern in long-term care facilities (LTCFs) as fall-related injuries can result in functional impairment, disability and death. Older adults living in LTCFs are at greater risk for falls than those in the community. Using scoping review methodology, we aimed to synthesise evidence examining intervention effects of person-focused interventions for risk assessment and prevention in LTCFs in order to identify evidence-based practices in LTCFs.

Prognostic Significance of the Immune Microenvironment in Endometrial Cancer.

This study used artificial intelligence (AI)-based analysis to investigate the immune microenvironment in endometrial cancer (EC). We aimed to evaluate the potential of AI-based immune metrics as prognostic biomarkers. In total, 296 cases with EC were classified into 4 molecular subtypes: polymerase epsilon ultramutated (POLEmut), mismatch repair deficiency (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP).

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

Aims: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity.

Methods And Results: An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.

Augmented interpretation of HER2, ER, and PR in breast cancer by artificial intelligence analyzer: enhancing interobserver agreement through a reader study of 201 cases.

Background: Accurate classification of breast cancer molecular subtypes is crucial in determining treatment strategies and predicting clinical outcomes. This classification largely depends on the assessment of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) status. However, variability in interpretation among pathologists pose challenges to the accuracy of this classification.

Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.

Background: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types.

The Perceived Meaning of Traumatic Brain Injury for Older Adults: A Longitudinal-Multiple Case Study.

Purpose: The aim of this study was to explore the perceived meaning of traumatic brain injury (TBI) over the first-year postinjury among older adults and to explore if and how meaning changes.

Design: A longitudinal multiple-case study design was used.

Methods: Semistructured face-to-face interviews were completed at 1 week and 1, 3, 6, and 12 months postinjury.

Kidney Donor Perspectives on Acute Postoperative Pain Management.

This study employed a qualitative descriptive approach to examine living kidney donor's experience of postoperative pain. Thirteen living kidney donors aged 46.5 (±14.

Social integration: A concept analysis.

Background: In recent decades, social isolation has been increasingly linked to serious health conditions. However, social integration (SI) is a complex concept that has not been systematically explored or defined in nursing. It is essential for nurses and healthcare providers to have a clearer concept of SI to better provide holistic care to support optimal health.

Artificial Intelligence-Powered Whole-Slide Image Analyzer Reveals a Distinctive Distribution of Tumor-Infiltrating Lymphocytes in Neuroendocrine Neoplasms.

Despite the importance of tumor-infiltrating lymphocytes (TIL) and PD-L1 expression to the immune checkpoint inhibitor (ICI) response, a comprehensive assessment of these biomarkers has not yet been conducted in neuroendocrine neoplasm (NEN). We collected 218 NENs from multiple organs, including 190 low/intermediate-grade NENs and 28 high-grade NENs. TIL distribution was derived from Lunit SCOPE IO, an artificial intelligence (AI)-powered hematoxylin and eosin (H&E) analyzer, as developed from 17,849 whole slide images.

Artificial intelligence-powered programmed death ligand 1 analyser reduces interobserver variation in tumour proportion score for non-small cell lung cancer with better prediction of immunotherapy response.

Background: Manual evaluation of programmed death ligand 1 (PD-L1) tumour proportion score (TPS) by pathologists is associated with interobserver bias.

Objective: This study explored the role of artificial intelligence (AI)-powered TPS analyser in minimisation of interobserver variation and enhancement of therapeutic response prediction.

Methods: A prototype model of an AI-powered TPS analyser was developed with a total of 802 non-small cell lung cancer (NSCLC) whole-slide images.

Ischemic Stroke Risk Among Adult Brain Tumor Survivors: Evidence to Guide Practice.

INTRODUCTION: Primary brain tumors are the leading cause of cancer mortality in the United States affecting approximately 90,000 Americans each year. A major complication for brain tumor survivors is acute ischemic stroke (AIS). Currently, there are limited research to provide guidelines for AIS prevention and management in adult brain tumor survivors.

Predicting pressure injury using nursing assessment phenotypes and machine learning methods.

Objective: Pressure injuries are common and serious complications for hospitalized patients. The pressure injury rate is an important patient safety metric and an indicator of the quality of nursing care. Timely and accurate prediction of pressure injury risk can significantly facilitate early prevention and treatment and avoid adverse outcomes.

High Paip1 Expression as a Potential Prognostic Marker in Hepatocellular Carcinoma.

Background/aim: Translation plays an important role in the carcinogenesis of various human tumors. Paip1 and eIF4A1 are translation-associated proteins that mediate the function of eukaryotic initiation factor 4F complex. This study aimed to analyse the relationship between the expression status of Paip1 and eIF4A1 and clinicopathologic features in hepatocellular carcinoma (HCC).

Effects of abutment screw preload in two implant connection systems: A 3D finite element study.

Statement Of Problem: Finite element analysis (FEA) has been used to evaluate the biomechanical behaviors of dental implants. However, in some FEA studies, the influence of the preload condition has been omitted to simplify the analysis. This might affect the results of biomechanical analysis significantly.

High expression of DEK is associated with poor prognosis in hepatocellular carcinoma.

DEK is an oncogene that has been identified as part of the DEK-CAN fusion gene. DEK plays a role in carcinogenesis through WNT signaling and induces cell proliferation through cyclin-dependent kinase signaling. DEK overexpression has been reported in HCC, but the clinical significance is unclear.

Early prediction of neurological outcome after barbiturate coma therapy in patients undergoing brain tumor surgery.

After a difficult brain tumor surgery, refractory intracranial hypertension (RICH) may occur due to residual tumor or post-operative complications such as hemorrhage, infarction, and aggravated brain edema. We investigated which predictors are associated with prognosis when using barbiturate coma therapy (BCT) as a second-tier therapy to control RICH after brain tumor surgery. The study included adult patients who underwent BCT after brain tumor surgery between January 2010 and December 2016.

Clinical and genomic landscape of gastric cancer with a mesenchymal phenotype.

Gastric cancer is a heterogeneous cancer, making treatment responses difficult to predict. Here we show that we identify two distinct molecular subtypes, mesenchymal phenotype (MP) and epithelial phenotype (EP), by analyzing genomic and proteomic data. Molecularly, MP subtype tumors show high genomic integrity characterized by low mutation rates and microsatellite stability, whereas EP subtype tumors show low genomic integrity.

Expression and prognostic significance of programmed death protein 1 and programmed death ligand-1, and cytotoxic T lymphocyte-associated molecule-4 in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignancies and causes of death worldwide. In this study, we assessed the correlation between clinicopathologic factors with programmed cell death protein 1 (PD-1) and programmed cell death ligand-1 (PD-L1), and cytotoxic T lymphocyte-associated molecule-4 (CTLA-4) expressions. Furthermore, we analyzed the prognostic significance of these proteins in a subgroup of patients.

SIRT7, H3K18ac, and ELK4 Immunohistochemical Expression in Hepatocellular Carcinoma.

Background: SIRT7 is one of the histone deacetylases and is NAD-dependent. It forms a complex with ETS-like transcription factor 4 (ELK4), which deacetylates H3K18ac and works as a transcriptional suppressor. Overexpression of SIRT7 and deacetylation of H3K18ac have been shown to be associated with aggressive clinical behavior in some cancers, including hepatocellular carcinoma (HCC).

Genomic Copy Number Signatures Uncovered a Genetically Distinct Group from Adenocarcinoma and Squamous Cell Carcinoma in Non-Small Cell Lung Cancer.

Adenocarcinoma (AC) and squamous cell carcinoma (SCC) of non-small cell lung carcinoma (NSCLC) have different clinical presentations, morphologies, treatments, and prognoses. Recent studies suggested that fundamental genetic alterations related to carcinogenesis of each tumor type may be different. In this study, we investigated the genomic alterations of 47 primary NSCLC samples (22 ACs and 25 SCCs) as well as the corresponding normal tissue using array comparative genomic hybridization.