Toward Waveguide-Based Optical Chromatography

We report analytical expressions for optical forces acting on particles inside waveguides. The analysis builds on our previously reported Fourier Transform method to obtain Beam Shape Coefficients for any beam. Here we develop analytical expressions for the Beam Shape Coefficients in cylindrical and rectangular metallic waveguides. The theory is valid for particle radius a ranging from the Rayleigh regime to large microparticles, such as aerosols like virus loaded droplets. The theory is used to investigate how optical forces within hollow waveguides can be used to sort particles in “optical chromatography” experiments in which particles are optically propelled along a hollow-core waveguide. For Rayleigh particles, the axial force is found to scale with a6, while the radial force, which prevents particles from crashing into the waveguide walls, scales with a3. For microparticles, narrow Mie resonances create a strong wavelength dependence of the optical force, enabling more selective sorting. Several beam parameters, such as power, wavelength, polarization state and waveguide modes can be tuned to optimize the sorting performance. The analysis focuses on cylindrical waveguides, where meter-long liquid waveguides in the form of hollow-core photonic crystal fibers are readily available. The modes of such fibers are well-approximated by the cylindrical waveguide modes considered in the theory.</jats:p

Axial optical trapping efficiency through a dielectric interface

Axial trapping through a dielectric interface is investigated in the framework of the angular spectrum representation and of the generalized Lorenz-Mie theory. We determine the optical force for an arbitrarily polarized non-paraxial, strongly aberrated, axially symmetric focusing beam and apply this description to the case of an arbitrarily positioned dielectric microsphere, commonly employed in optical tweezers, not taking into account the contribution of evanescent waves at the interface. We derive the analytical expression of the force profile, finding that the incident polarization does not affect the axial optical force. In addition, we derive an approximated expression for the axial force as a function of beam displacement just outside the microsphere and we show how the information provided by the ripple structure of the optical trapping efficiency versus sphere displacement curve, due to the aberration effect, could be exploited to calibrate the bead axial position versus the experimental beam positioning controls.766

Raman, hyper-Raman, hyper-Rayleigh, two-photon luminescence and morphology-dependent resonance modes in a single optical tweezers system

We present a setup of optical tweezers combined with linear and nonlinear microspectroscopies that enhances the capabilities of capture and analysis of both techniques. We can use either a continuous-wave (cw) Ti:sapphire laser for Raman measurements or a pulsed femtosecond Ti:sapphire laser that permitted the observation of nonlinear results such as hyper-Raman, hyper-Rayleigh, and two-photon luminescence. Only the high peak intensity of the femtosecond laser allows the observation of all these nonlinear spectroscopies. The sensitivity of our system also permitted the observation of morphology-dependent resonance (MDR) modes of a single stained trapped microsphere of 6 mu m. The possibility of performing spectroscopy in a living microorganism optically trapped in any desired neighborhood would mean that one can dynamically observe the chemical reactions and/or mechanical properties changing in real time.721

Machine learning can identify newly diagnosed patients with CLL at high risk of infection

Infections have become the major cause of morbidity and mortality among patients with chronic lymphocytic leukemia (CLL) due to immune dysfunction and cytotoxic CLL treatment. Yet, predictive models for infection are missing. In this work, we develop the CLL Treatment-Infection Model (CLL-TIM) that identifies patients at risk of infection or CLL treatment within 2 years of diagnosis as validated on both internal and external cohorts. CLL-TIM is an ensemble algorithm composed of 28 machine learning algorithms based on data from 4,149 patients with CLL. The model is capable of dealing with heterogeneous data, including the high rates of missing data to be expected in the real-world setting, with a precision of 72% and a recall of 75%. To address concerns regarding the use of complex machine learning algorithms in the clinic, for each patient with CLL, CLL-TIM provides explainable predictions through uncertainty estimates and personalized risk factors

The Emergence of a Lanthanide-rich Kilonova Following the Merger of Two Neutron Stars

We report the discovery and monitoring of the near-infrared counterpart (AT2017gfo) of a binary neutron-star merger event detected as a gravitational wave source by Advanced LIGO/Virgo (GW170817) and as a short gamma-ray burst by Fermi/GBM and Integral/SPI-ACS (GRB170817A). The evolution of the transient light is consistent with predictions for the behaviour of a "kilonova/macronova", powered by the radioactive decay of massive neutron-rich nuclides created via r-process nucleosynthesis in the neutron-star ejecta. In particular, evidence for this scenario is found from broad features seen in Hubble Space Telescope infrared spectroscopy, similar to those predicted for lanthanide dominated ejecta, and the much slower evolution in the near-infrared Ks-band compared to the optical. This indicates that the late-time light is dominated by high-opacity lanthanide-rich ejecta, suggesting nucleosynthesis to the 3rd r-process peak (atomic masses A~195). This discovery confirms that neutron-star mergers produce kilo-/macronovae and that they are at least a major - if not the dominant - site of rapid neutron capture nucleosynthesis in the universe

Lipopolysaccharides Impair Insulin Gene Expression in Isolated Islets of Langerhans via Toll-Like Receptor-4 and NF-κB Signalling

BACKGROUND:Type 2 diabetes is characterized by pancreatic β-cell dysfunction and is associated with low-grade inflammation. Recent observations suggest that the signalling cascade activated by lipopolysaccharides (LPS) binding to Toll-Like Receptor 4 (TLR4) exerts deleterious effects on pancreatic β-cell function; however, the molecular mechanisms of these effects are incompletely understood. In this study, we tested the hypothesis that LPS alters insulin gene expression via TLR4 and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) in islets. METHODOLOGY/PRINCIPAL FINDINGS:A 24-h exposure of isolated human, rat and mouse islets of Langerhans to LPS dose-dependently reduced insulin gene expression. This was associated in mouse and rat islets with decreased mRNA expression of pancreas-duodenum homebox-1 (PDX-1) and mammalian homologue of avian MafA/l-Maf (MafA). Accordingly, LPS exposure also decreased glucose-induced insulin secretion. LPS repression of insulin, PDX-1 and MafA expression, as well as its inhibition of insulin secretion, were not observed in islets from TLR4-deficient mice. LPS inhibition of β-cell gene expression in rat islets was prevented by inhibition of the NF-κB pathway, but not the p38 mitogen-activated protein kinase (p38 MAPK) pathway. CONCLUSIONS/SIGNIFICANCE:Our findings demonstrate that LPS inhibit β-cell gene expression in a TLR4-dependent manner and via NF-κB signaling in pancreatic islets, suggesting a novel mechanism by which the gut microbiota might affect pancreatic β-cell function