No abstract

The quantitative analysis of tear analytes in point‐of‐care settings can enable early diagnosis of ocular diseases. Here, a fluorescent scleral lens sensor is developed to quantitatively measure physiological levels of pH, Na+, K+, Ca2+, Mg2+, and Zn2+ ions. Benzenedicarboxylic acid, a pH probe, displays a sensitivity of 0.12 pH units within pH 7.0–8.0. Crown ether derivatives exhibit selectivity to Na+ and K+ ions within detection ranges of 0–100 and 0–50 mmol L−1, and selectivities of 15.6 and 8.1 mmol L−1, respectively. A 1,2 bis(o‐aminophenoxy)ethane‐N,N,‐N',N'‐tetraacetic‐acid‐based probe allows Ca2+ ion sensing with 0.02–0.05 mmol L−1 sensitivity within 0.50–1.25 mmol L−1 detection range. 5‐Oxazolecarboxylic acid senses Mg2+ ions, exhibiting a sensitivity of 0.10–0.44 mmol L−1 within the range of 0.5–0.8 mmol L−1. The N‐(2‐methoxyphenyl)iminodiacetate Zn2+ ion sensor has a sensitivity of 1 µmol L−1 within the range of 10–20 µmol L−1. The fluorescent sensors are subsequently multiplexed in the concavities of an engraved scleral lens. A handheld ophthalmic readout device comprising light‐emitting diodes (LEDs) and bandpass filters is fabricated to excite as well as read the scleral sensor. A smartphone camera application and an user interface are developed to deliver quantitative measurements with data deconvolution. The ophthalmic system enables the assessment of dry eye severity stages and the differentiation of its subtypes.

We demonstrate that the integration of complex human synovial organ cultures in a lab-on-a-chip provides reproducible and reliable information on how systemic stress factors affect synovial tissue architectures using light scatter biosensing.

Complete blood count and differentiation of leukocytes (DIFF) belong to the most frequently performed laboratory diagnostic tests. Here, a flow cytometry‐based method for label‐free DIFF of untouched leukocytes by digital holographic microscopy on the rich phase contrast of peripheral leukocyte images, using highly controlled 2D hydrodynamic focusing conditions is reported. Principal component analysis of morphological characteristics of the reconstructed images allows classification of nine leukocyte types, in addition to different types of leukemia and demonstrates disappearance of acute myeloid leukemia cells in remission. To exclude confounding effects, the classification strategy is tested by the analysis of 20 blinded clinical samples. Here, 70% of the specimens are correctly classified with further 20% classifications close to a correct diagnosis. Taken together, the findings indicate a broad clinical applicability of the cytometry method for automated and reagent‐free diagnosis of hematological disorders.