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The incidental detection of pancreatic cysts, an opportunity for the early detection of pancreatic cancer, is increasing, owing to an aging population and improvements in imaging technology. The classification of pancreatic cystic precursors currently relies on imaging and cyst fluid evaluations, including cytology and protein and genomic analyses. However, there are persistent limitations that obstruct the accuracy and quality of information for clinicians, including the limited volume of the complex, often acellular, and proteinaceous milieu that comprises pancreatic cyst fluid. The constraints of currently available clinical assays lead clinicians to the subjective and inconsistent application of diagnostic tools, which can contribute to unnecessary surgery and missed pancreatic cancers. Herein, we describe the pathway toward pancreatic cyst classification and diagnosis, the volume requirements for several clinically available diagnostic tools, and some analytical and diagnostic limitations for each assay. We then discuss current and future work on novel markers and methods, and how to expand the utility of clinical pancreatic cyst fluid samples. Results of ongoing studies applying SERS as a detection mode suggest that 50 μL of pancreatic cyst fluid is more than sufficient to accurately rule out non-mucinous pancreatic cysts with no malignant potential from further evaluation. This process is expected to leave sufficient fluid to analyze a follow-up, rule-in panel of markers currently in development that can stratify grades of dysplasia in mucinous pancreatic cysts and improve clinical decision-making.

Hepatitis C virus (HCV) infection is a significant global health concern, affecting millions of individuals worldwide and often leading to severe liver disease if left untreated. Laboratory testing plays a crucial role in the screening, diagnosis, and management of HCV, serving as the first step in identifying infected individuals and guiding treatment decisions. Current practices primarily involve a two-step testing process, beginning with serological assays to detect antibodies against HCV, followed by confirmatory tests for HCV RNA to ascertain active infection. The Centers for Disease Control and Prevention (CDC) recommends routine screening for all adults and at-risk populations to facilitate early detection and treatment. Recent innovations in laboratory testing have significantly improved the efficiency and accessibility of hepatitis C screening. Point-of-care (POC) testing has emerged as a transformative approach, allowing for rapid results in various settings, thus enhancing patient engagement and facilitating immediate linkage to care. Automated laboratory systems have streamlined testing processes, while advances in molecular techniques, such as polymerase chain reaction (PCR) and next-generation sequencing (NGS), have increased sensitivity and specificity in detecting HCV. Despite these advancements, challenges remain, including barriers to access, cost considerations, and the stigma associated with hepatitis C. Addressing these issues is essential for improving screening rates and ensuring that individuals receive timely care. The integration of new technologies, such as telemedicine and digital health tools, offers promising avenues for enhancing screening efforts and expanding access to testing. This review highlights the critical role of laboratory testing in hepatitis C screening, examining current practices and innovations that are reshaping the landscape of HCV diagnosis and management. By focusing on improving testing accessibility and efficiency, public health initiatives can play a pivotal role in reducing the burden of hepatitis C globally and improving health outcomes for affected individuals. [ABSTRACT FROM AUTHOR]

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Summary: This article investigates the devise issue of a practical finite‐time output‐tracking control for uncertain nonlinear nonstrict‐feedback systems subject simultaneously to time‐varying output constraints (TVOC), actuator saturation, and bounded unmatched disturbances. An adaptive fuzzy approximator‐based control system is devised using the dynamic surface control (DSC) concept. System output constraints are addressed by employing an appropriate barrier Lyapunov function. Adaptive fuzzy disturbance observers are constructed to practically deal with time‐varying unmatched but bounded disturbances. It is verified via Lyapunov stability analysis and simulation experiments that all closed‐loop signals remain bounded, the output tracking error practically converges in finite time to a tiny but adjustable neighborhood around the origin, and the system output stays within its required time‐varying bounds. [ABSTRACT FROM AUTHOR]