We have demonstrated a high-energy Q-switched double-clad thulium-doped fiber laser (TDFL) using a graphene-oxide-deposited tapered fiber (GODTF) device as a saturable absorber operating at a wavelength of 2 μm for the first time. Because of the side-interaction of the graphene-oxide with the evanescent field on the taper waist, the GODTF devices have potential for offering high laser damage threshold. Using a 788 nm laser diode as the pump source, the TDFL generated stable single transverse mode Q-switched pulses with a single pulse energy of 6.71 μJ (corresponding to an average power of 302 mW) at a wavelength of 2032 nm. This is significantly higher than the highest pulse energy/average power from any rare-earth-doped fiber lasers employing a graphene or graphene-oxide based Q-switch so far. The demonstrated TDFL in this paper represents an encouraging step towards the practical applications of graphene or graphene-oxide based Q-switched 2 μm TDFLs.
As cancer is increasingly considered a metabolic disorder, it is postulated that serum metabolite profiling can be a viable approach for detecting the presence of cancer. By multiplexing mass spectrometry fingerprints from two independent nanostructured matrixes through machine learning for highly sensitive detection and high throughput analysis, we report a laser desorption/ionization (LDI) mass spectrometry-based liquid biopsy for pan-cancer screening and classification. The Multiplexed Nanomaterial-Assisted LDI for Cancer Identification (MNALCI) is applied in 1,183 individuals that include 233 healthy controls and 950 patients with liver, lung, pancreatic, colorectal, gastric, thyroid cancers from two independent cohorts. MNALCI demonstrates 93% sensitivity at 91% specificity for distinguishing cancers from healthy controls in the internal validation cohort, and 84% sensitivity at 84% specificity in the external validation cohort, with up to eight metabolite biomarkers identified. In addition, across those six different cancers, the overall accuracy for identifying the tumor tissue of origin is 92% in the internal validation cohort and 85% in the external validation cohort. The excellent accuracy and minimum sample consumption make the high throughput assay a promising solution for non-invasive cancer diagnosis.
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