This study demonstrated the fabrication of alginate microfibers using a modular microfluidic system for magnetic-responsive controlled drug release and cell culture. A novel two-dimensional fluid-focusing technique with multi-inlets and junctions was used to spatiotemporally control the continuous laminar flow of alginate solutions. The diameter of the manufactured microfibers, which ranged from 211 µm to 364 µm, could be well controlled by changing the flow rate of the continuous phase. While the model drug, diclofenac, was encapsulated into microfibers, the drug release profile exhibited the characteristic of a proper and steady release. Furthermore, the diclofenac release kinetics from the magnetic iron oxide-loaded microfibers could be controlled externally, allowing for a rapid drug release by applying a magnetic force. In addition, the successful culture of glioblastoma multiforme cells in the microfibers demonstrated a good structural integrity and environment to grow cells that could be applied in drug screening for targeting cancer cells. The proposed microfluidic system has the advantages of ease of fabrication, simplicity, and a fast and low-cost process that is capable of generating functional microfibers with the potential for biomedical applications, such as drug controlled release and cell culture.

We conclude that the PLS-ANN classification algorithm based on autofluorescence spectroscopy at 330-nm excitation is useful for in vivo diagnosis of OSF as well as oral premalignant and malignant lesions.

We conclude that time-resolved autofluorescence spectroscopy at 633 nm under 410-nm excitation, based on two-component lifetime calculation and FDA, is a very sensitive technique for in vivo diagnosis of oral premalignant lesions. .

A probability-based multivariate statistical algorithm combining partial least-squares (PLS) and logistic regression was developed to identify the development stages of oral cancer through analysis of autofluorescence spectra of oral tissues. Tissues were taken from a 7,12-dimethylbenz[alanthracene-induced hamster buccal pouch carcinogenesis model. Analyses were conducted at various excitation wavelengths, ranging from 280 n m to 400 nm in 20 nm increments, to assess classification performance at different excitations. For each excitation the PLS analysis and logistic regression were combined, on the basis of cross validation, to calculate the posterior probabilities of samples belonging to four stages of cancer development: normal tissues, hyperplasia, dysplasia and early cancers and frankly invasive cancers. Results showed that the 320 nm excitation wavelength optimally classified the cancer development stages: the accuracy rates for identifying samples at that excitation were 91.7%, 83.3%, 66.7% and 83.3% for the four respective stages. The average accuracy rate was 81.3%. These results suggest that the algorithm described in this study might be useful for the detection of human oral cancers.

No abstract