Recent advances in microfluidic technology of arterial thrombosis investigations.

Microfluidic technology has emerged as a powerful tool in studying arterial thrombosis, allowing researchers to construct artificial blood vessels and replicate the hemodynamics of blood flow. This technology has led to significant advancements in understanding thrombosis and platelet adhesion and aggregation. Microfluidic models have various types and functions, and by studying the fabrication methods and working principles of microfluidic chips, applicable methods can be selected according to specific needs. The rapid development of microfluidic integrated system and modular microfluidic system makes arterial thrombosis research more diversified and automated, but its standardization still needs to be solved urgently. One key advantage of microfluidic technology is the ability to precisely control fluid flow in microchannels and to analyze platelet behavior under different shear forces and flow rates. This allows researchers to study the physiological and pathological processes of blood flow, shedding light on the underlying mechanisms of arterial thrombosis. In conclusion, microfluidic technology has revolutionized the study of arterial thrombosis by enabling the construction of artificial blood vessels and accurately reproducing hemodynamics. In the future, microfluidics will place greater emphasis on versatility and automation, holding great promise for advancing antithrombotic therapeutic and prophylactic measures.

What is the context? To study the mechanism of arterial thrombosis, including the platelet adhesion and aggregation behavior and the coagulation process.Microfluidic technology is commonly used to study thrombosis. Microfluidic technology can simulate the real physiological environment on the microscopic scale in vitro, with high throughput, low cost, and fast speed.As an innovative experimental platform, microfluidic technology has made remarkable progress and has found applications in the fields of biology and medicine.What is new? This review summarizes the different fabrication methods of microfluidics and compares the advantages and disadvantages of these methods. Recent developments in microfluidic integrated systems and modular microfluidic systems have led to more diversified and automated microfluidic chips in the future.The different types and functions of microfluidic models are summarized. Platelet adhesion aggregation and coagulation processes, as well as arterial thrombus-related shear force changes and mechanical behaviors, were investigated by constructing artificial blood vessels and reproducing hemodynamics.Microfluidics can provide a basis for the development of personalized thrombosis treatment strategies. By analyzing the mechanism of action of existing drugs, using microfluidic technology for high-throughput screening of drugs and evaluating drug efficacy, more drug therapy possibilities can be developed.What is the impact?This review utilizes microfluidics to further advance the study of arterial thrombosis, and microfluidics is also expected to play a greater role in the biomedical field in the future.

Cerebrospinal fluid-induced stable and reproducible SERS sensing for various meningitis discrimination assisted with machine learning.

Cerebrospinal fluid (CSF)-based pathogen or biochemical testing is the standard approach for clinical diagnosis of various meningitis. However, misdiagnosis and missed diagnosis always occur due to the shortages of unusual clinical manifestations and time-consuming shortcomings, low sensitivity, and poor specificity. Here, for the first time, we propose a simple and reliable CSF-induced SERS platform assisted with machine learning (ML) for the diagnosis and identification of various meningitis. Stable and reproducible SERS spectra are obtained within 30 s by simply mixing the colloidal silver nanoparticles (Ag NPs) with CSF sample, and the relative standard deviation of signal intensity is achieved as low as 2.1%. In contrast to conventional salt agglomeration agent-induced irreversible aggregation for achieving Raman enhancement, a homogeneous and dispersed colloidal solution is observed within 1 h for the mixture of Ag NPs/CSF (containing 110-140 mM chloride), contributing to excellent SERS stability and reproducibility. In addition, the interaction processes and potential enhancement mechanisms of different Ag colloids-based SERS detection induced by CSF sample or conventional NaCl agglomeration agents are studied in detail through in-situ UV-vis absorption spectra, SERS analysis, SEM and optical imaging. Finally, an ML-assisted meningitis classification model is established based on the spectral feature fusion of characteristic peaks and baseline. By using an optimized KNN algorithm, the classification accuracy of autoimmune encephalitis, novel cryptococcal meningitis, viral meningitis, or tuberculous meningitis could be reached 99%, while an accuracy value of 68.74% is achieved for baseline-corrected spectral data. The CSF-induced SERS detection has the potential to provide a new type of liquid biopsy approach in the fields of diagnosis and early detection of various cerebral ailments.