Advanced Cell Diagnostics (United States)

Implantable cardioverter-defibrillators (ICDs) are the cornerstone of sudden cardiac death prevention in cardiomyopathies, but disease-specific structural and electrophysiological substrates profoundly affect device performance and outcomes. Understanding these distinctions is critical for tailoring therapy and improving patient safety. This review examines current evidence and practical experience regarding ICD implantation, programming, and management in hypertrophic cardiomyopathy (HCM), arrhythmogenic right ventricular cardiomyopathy (ARVC), and cardiac amyloidosis (CA). We performed a structured narrative synthesis to identify phenotype-specific technical challenges, programming strategies, and complication trends. For HCM, lead placement and programming to minimize inappropriate therapies are emphasized; for ARVC, issues of lead instability, oversensing, and ATP efficacy are explored; and for CA, defibrillation thresholds, sensing difficulties, and individualized indications are discussed. ICD therapy in cardiomyopathies must be individualized, balancing arrhythmic protection against disease-specific risks and device-related complications. Tailored programming, careful system selection, and remote monitoring are key to improving outcomes. Emerging technologies such as modular and extravascular ICD systems promise safer and more phenotype-driven care.

Quantum biosensors, which harness quantum effects to detect biomarkers, could address the urgent need for more sensitive rapid diagnostics. Lateral flow tests using nitrogen-vacancy centres in nanodiamond labels offer high sensitivity and robustness by controlling the spin-dependent fluorescence to remove background. This is particularly important in complex and variable clinical samples. However, to date only model systems have been studied with few clinical samples. Here we show results of a clinical evaluation of a spin-enhanced nanodiamond test for SARS-CoV-2 antigen with 103 upper respiratory tract swab samples. We find 95.1% sensitivity (Ct ≤ 30) and 100% specificity benchmarked against RT-qPCR, with no cross-reactivity to influenza A, RSV, and Rhinovirus. Modelling with patient data yields a mean of 2.0-days earlier detection compared to conventional gold-nanoparticle tests (just 0.6 days after RT-qPCR) with 2.2-fold more patients detected on the first day of symptom onset, potentially reducing the transmission risk and protecting populations.

In many malignancies, an increased number of tumor-infiltrating lymphocytes (TILs) is recognized as a favorable prognostic factor, with exceptions such as renal cell carcinoma. However, the clinical significance of TIL size remains unclear. T-cell activation by mitogens increases cell size, partly via c-myc expression, suggesting that larger T cells may be more activated. We hypothesized that TIL size might be prognostically relevant in cancer patients. Here, we examined the relationship between the size and number of tumor-infiltrating CD8 + T cells and patient prognosis in 96 cases of esophageal squamous cell carcinoma (ESCC). We employed artificial intelligence (AI) analysis to quantify the mean size of intratumoral CD8+ T cells in each sample. Patients were then divided into "Large" and "Small" CD8+ T cell groups according to the median T-cell size. Similarly, we classified cases into "High" and "Low" groups based on CD8 + T-cell numbers. We found that patients in the Large CD8+ T cell group had significantly better overall survival than those in the Small CD8+ T cell group by a univariate analysis (p = 0.039), but the difference did not reach statistical significance in a multivariate analysis (p = 0.054). Patients in the High CD8 + T cell group had better outcomes than those in the Low CD8+ T cell group. There was no significant correlation between CD8+ T cell size and count, and their combination (Large/High) identified a subgroup of patients with the most favorable prognosis. Our findings suggest that CD8+ T cell size could serve as an independent prognostic marker in ESCC.

Manufacturing is experiencing a historic transformation from labor-intensive manual assembly toward intelligent, interconnected, and autonomous production. The increasing deployment of industrial robots, multifunctional machines (MFMs), and humanoid systems, combined with artificial intelligence (AI), is enabling the concept of “lights-off” factories that can operate continuously with minimal human intervention. This paper traces the evolution of assembly automation, from Henry Ford’s moving line and Toyota’s lean principles to Tesla’s high-automation journey, Apple’s precision robotics ecosystem, and FANUC’s fully autonomous “lights-off” plant. Lessons learned from these pioneers inform the design of future factories facilities that combine human intelligence with robotic precision, flexibility, and resilience.

BackgroundAdvances in spatial biology have enhanced the comprehension of signaling networks by allowing the investigation of tissue architectures and cellular interactions. Techniques such as multiplexed immunofluorescence (mIF) and RNA in situ hybridization (ISH) allow simultaneous detection of multiple protein and RNA biomarkers, therefore providing a comprehensive overview of cellular functions and signaling networks.Combining spatial assays on the same tissue section is essential to increase our knowledge of tissue biology. In complex tissues such as tumor microenvironments or neural tissues, extracting precise information on cellular interconnections or neuronal connectivity and signaling activity is key for understanding the biological processes involved in development and disease.Here, we present a novel fully automated approach that integrates the RNAscope™ HiPlexPro assay1 and sequential immunofluorescence (seqIF™)2 protocols for the co-detection of RNA and protein targets on the same tissue section on the COMET™ platform. The multiomics protocol was applied to mouse tissues and frozen sections for the first time, demonstrating the versatility and robustness of the approach.MethodsWe employed the COMET™ platform, an advanced tissue staining and imaging system, to automate and integrate RNAscope™ and seqIF™ protocols for the simultaneous detection of RNA and protein biomarkers. The system ensures precise temperature control and reagent distribution, critical for maintaining the integrity of frozen sections.Through this automated assay, protocols with up to three cycles of RNAscope™ detection (using four fluorescent channels per cycle) were combined with up to twelve cycles of seqIF™, detecting two protein markers each. Thus, resulting in a combined multiplexing capability of up to 12-plex RNA and 24-plex protein targets.ResultsIn this study, we demonstrated that the combination of RNAscope™ and seqIF™ protocols on COMET™ enables the simultaneous detection of RNA and protein biomarkers on sensitive frozen tissue sections, while ensuring high reproducibility and minimal user intervention.Here, RNAscope™ probes targeting biomarkers relevant to neuronal function, including neurotransmitters and receptors, and other glial cells, were combined to selected protein markers profiling multiple cell types in their microenvironment, including several types of infiltrating immune cells (such as CD3+, F4/80+, CD11c+, or CD56+ cells).ConclusionsOur findings demonstrate the successful application of the combined RNAscope™ and seqIF™ protocols on the COMET™ platform to analyze delicate and high autofluorescence tissue sections and tissues of non-human origin. These results demonstrate the versatility and robustness of the approach and opens door to potential new applications in the immuno-oncology field, including biomarker and drug development.ReferencesWang F, Flanagan J, Su N, et al. RNAscope: a novel in situ RNA Analysis platform for formalin-fixed paraffin-embedded tissues. Journal of Molecular Diagnostics 2012;14:22-29.Rivest F, Eroglu D, Pelz B, et al. Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics. Scientific Reports 2023;13,16994.

BackgroundProtein-protein interaction (PPI) is one of the many mechanisms where individual cells understand and modulate the surrounding environment through communication with nearby cells or extracellular matrix. In many diseases including cancer, some PPIs have been identified to adversely impact immune response. One well-known example is the interaction between programmed cell death ligand 1 (PD-L1) and programmed cell death protein 1 (PD-1). Tumor cells utilize PD-1/PD-L1 interaction to evade immune cell activities. While many immunotherapies targeting PD-1/PD-L1 blockade have been approved by FDA, there is a critical need for biomarkers that are more predictive of clinical outcomes than PD-L1 immunohistochemistry. Direct detection of PD-1/PD-L1 interactions in patient tissues in the context of a multiomic readout is likely to have better correlation to the therapeutic effect of checkpoint inhibitors than PD-L1 test alone and pinpoint specific tumor-immune cell interactions from accidental proximity.We have developed a fully automated workflow that can visualize PPI with multiomic context of tumor-immune microenvironment (TIME) on a single FFPE tissue section. We observed PD-1/PD-L1 interaction, individual proteins, and mRNA at high spatial resolution in tumor tissues using new workflow enabled by high sensitivity and specificity of RNAscopeTM technology.MethodsOligonucleotide-conjugated anti-PD-1 and anti-PD-L1 primary antibodies or secondary antibodies were prepared to integrate the detection of PD-1/PD-L1 interaction or protein-protein proximity into RNAscopeTM Multiomic LS assay. The protease-free workflow is fully automated and performed on BOND Rx instrument. New 6-plex workflow allows imaging of one PPI and combination of up to 5 protein and mRNA targets of interest with tyramide signal amplification.ResultsOn human normal and cancer tissues, we show microenvironment surrounding the PD-1/PD-L1 interaction signals using oligonucleotide-conjugated primary anti-PD-1 and anti-PD-L1 antibodies, cell phenotyping protein markers for immune and tumor cells (CD4, CD8, CD68, and PanCK), as well as mRNA markers for secreted proteins such as chemokines, cytokines, or enzymes (CXCL9, CXCL10, IFNG or GZMK). The PPI signals appear as a group of punctate dots enabling semi-quantitative analysis. This assay is also capable of visualizing other protein-protein interaction or proximity using oligonucleotide-conjugated secondary antibodies.ConclusionsNew protease-free RNAscopeTM multiomics workflow is a powerful technique to resolve protein-protein proximity including PPI in the context of TIME. Spatial multiomic analyses of PPI will expand our knowledge of tumor immune evasion strategies and potentially offer new patient stratification strategy for checkpoint inhibitor immunotherapies.

Miranda, Elijah E. MS1; Hoffman, William R. MD1,2,3; Bongers, Herwin ATPL4; Snyder, Quay MD, MSPH5,6; Worley, Sandie Y. MD3; Yuan, Tony PhD, MS1,8; Tvaryanas, Anthony MD, PhD, MPH&TM7 Author Information