Tear glucose sensing for diabetes management has long been sought as an alternative to more invasive self-monitoring of blood glucose (SMBG). However, tear glucose sensors were known to have limitations, including correlation issues with blood glucose due to low sample volume, low concentration of glucose in the tear fluid, and evaporation of the tear sample. An engineering design approach to solve these problems led to the development of an integrated device capable of collecting the tear sample from the ocular surface with little to no stress on the eye, with an extremely low limit of detection, broad dynamic range, and rapid detection and analysis of sample. Here we present the development of a prototypical self-monitoring of tear glucose (SMTG) sensor, summarizing bench studies on the enzymes and their specificity, the development of the fluid capture device and its manufacture and performance and results of system testing in an animal study where safety, lag time and tear glucose to blood glucose correlation were assessed.

Aims: To analyze outcomes in primary anorectal melanoma, a rare disease with limited data and treatment guidelines. Materials & methods: We analyzed 305 subjects in the National Cancer Database from 2004 to 2015. The primary end point was overall survival (OS). Results: Surgery was predictive of OS (median 2.24 vs 1.18 years; p = 0.009) with no survival difference between local and transabdominal approaches (p = 0.77). No OS benefit was seen with chemotherapy (p = 0.16), radiotherapy (p = 0.31) or adjuvant therapy post surgery (p > 0.05 for all groups). Targeted therapy trended toward higher survival in metastatic patients (1.33 vs 0.55 years; p = 0.06). Conclusion: In nonmetastatic patients, surgery of any method is associated with a survival benefit. The trend for improved survival following targeted therapy in metastatic patients merits further exploration.

This work represents a preliminary proof-of-concept design and verification of a 3D-printed glucose biosensor. The proof of concept presented is the first example of glucose dehydrogenase sensor fabricated by a 3D-printer while maintaining similar features to current lab-industry standards. The sensor was verified to detect physiological glucose concentrations between 0 and 400 mg/dL with a linear coefficient as high as .97. This study showed that it was possible to use 3D-printed technology to create a biosensor sensitive to glucose detection. As availability and functionality of 3D-printers expands, this technology has the potential to be an option for diabetes management. This preliminary study shows that the 3D-printed sensor platform holds promise for sensitive glucose detection.