Spectroscopy and Biosensing with Optically Resonant Dielectric Nanostructures

Resonant dielectric nanoparticles (RDNs) made of materials with large positive dielectric permittivity, such as Si, GaP, GaAs, have become a powerful platform for modern light science, enabling various fascinating applications in nanophotonics and quantum optics. In addition to light localization at the nanoscale, dielectric nanostructures provide electric and magnetic resonant responses throughout the visible and infrared spectrum, low dissipative losses and optical heating, low doping effect and absence of quenching, which are interesting for spectroscopy and biosensing applications. In this review, we present state-of-the-art applications of optically resonant high-index dielectric nanostructures as a multifunctional platform for light-matter interactions. Nanoscale control of quantum emitters and applications for enhanced spectroscopy including fluorescence spectroscopy, surface-enhanced Raman scattering (SERS), biosensing, and lab-on-a-chip technology are surveyed. We describe the theoretical background underlying these effects, overview realizations of specific resonant dielectric nanostructures and hybrid excitonic systems, and outlook the challenges in this field, which remain open to future research

Impaired perceptual learning in a mouse model of Fragile X syndrome is mediated by parvalbumin neuron dysfunction and is reversible.

To uncover the circuit-level alterations that underlie atypical sensory processing associated with autism, we adopted a symptom-to-circuit approach in the Fmr1-knockout (Fmr1-/-) mouse model of Fragile X syndrome. Using a go/no-go task and in vivo two-photon calcium imaging, we find that impaired visual discrimination in Fmr1-/- mice correlates with marked deficits in orientation tuning of principal neurons and with a decrease in the activity of parvalbumin interneurons in primary visual cortex. Restoring visually evoked activity in parvalbumin cells in Fmr1-/- mice with a chemogenetic strategy using designer receptors exclusively activated by designer drugs was sufficient to rescue their behavioral performance. Strikingly, human subjects with Fragile X syndrome exhibit impairments in visual discrimination similar to those in Fmr1-/- mice. These results suggest that manipulating inhibition may help sensory processing in Fragile X syndrome

Bias in Online Freelance Marketplaces: Evidence from TaskRabbit and Fiverr

Online freelancing marketplaces have grown quickly in recent years. In theory, these sites offer workers the ability to earn money without the obligations and potential social biases associated with traditional employment frameworks. In this paper, we study whether two prominent online freelance marketplaces - TaskRabbit and Fiverr - are impacted by racial and gender bias. From these two platforms, we collect 13,500 worker profiles and gather information about workers' gender, race, customer reviews, ratings, and positions in search rankings. In both marketplaces, we find evidence of bias: we find that gender and race are significantly correlated with worker evaluations, which could harm the employment opportunities afforded to the workers. We hope that our study fuels more research on the presence and implications of discrimination in online environments

The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016

The 2016 speaker recognition evaluation (SRE'16) is the latest edition in the series of benchmarking events conducted by the National Institute of Standards and Technology (NIST). I4U is a joint entry to SRE'16 as the result from the collaboration and active exchange of information among researchers from sixteen Institutes and Universities across 4 continents. The joint submission and several of its 32 sub-systems were among top-performing systems. A lot of efforts have been devoted to two major challenges, namely, unlabeled training data and dataset shift from Switchboard-Mixer to the new Call My Net dataset. This paper summarizes the lessons learned, presents our shared view from the sixteen research groups on recent advances, major paradigm shift, and common tool chain used in speaker recognition as we have witnessed in SRE'16. More importantly, we look into the intriguing question of fusing a large ensemble of sub-systems and the potential benefit of large-scale collaboration.Peer reviewe

Transcriptome Analysis during Human Trophectoderm Specification Suggests New Roles of Metabolic and Epigenetic Genes

In humans, successful pregnancy depends on a cascade of dynamic events during early embryonic development. Unfortunately, molecular data on these critical events is scarce. To improve our understanding of the molecular mechanisms that govern the specification/development of the trophoblast cell lineage, the transcriptome of human trophectoderm (TE) cells from day 5 blastocysts was compared to that of single day 3 embryos from our in vitro fertilization program by using Human Genome U133 Plus 2.0 microarrays. Some of the microarray data were validated by quantitative RT-PCR. The TE molecular signature included 2,196 transcripts, among which were genes already known to be TE-specific (GATA2, GATA3 and GCM1) but also genes involved in trophoblast invasion (MUC15), chromatin remodeling (specifically the DNA methyltransferase DNMT3L) and steroid metabolism (HSD3B1, HSD17B1 and FDX1). In day 3 human embryos 1,714 transcripts were specifically up-regulated. Besides stemness genes such as NANOG and DPPA2, this signature included genes belonging to the NLR family (NALP4, 5, 9, 11 and 13), Ret finger protein-like family (RFPL1, 2 and 3), Melanoma Antigen family (MAGEA1, 2, 3, 5, 6 and 12) and previously unreported transcripts, such as MBD3L2 and ZSCAN4. This study provides a comprehensive outlook of the genes that are expressed during the initial embryo-trophectoderm transition in humans. Further understanding of the biological functions of the key genes involved in steroidogenesis and epigenetic regulation of transcription that are up-regulated in TE cells may clarify their contribution to TE specification and might also provide new biomarkers for the selection of viable and competent blastocysts

A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

<p>Abstract</p> <p>Background</p> <p>Because insulin is the main regulator of glucose homeostasis, quantitative models describing the dynamics of glucose-induced insulin secretion are of obvious interest. Here, a computational model is introduced that focuses not on organism-level concentrations, but on the quantitative modeling of local, cellular-level glucose-insulin dynamics by incorporating the detailed spatial distribution of the concentrations of interest within isolated avascular pancreatic islets.</p> <p>Methods</p> <p>All nutrient consumption and hormone release rates were assumed to follow Hill-type sigmoid dependences on local concentrations. Insulin secretion rates depend on both the glucose concentration and its time-gradient, resulting in second-and first-phase responses, respectively. Since hypoxia may also be an important limiting factor in avascular islets, oxygen and cell viability considerations were also built in by incorporating and extending our previous islet cell oxygen consumption model. A finite element method (FEM) framework is used to combine reactive rates with mass transport by convection and diffusion as well as fluid-mechanics.</p> <p>Results</p> <p>The model was calibrated using experimental results from dynamic glucose-stimulated insulin release (GSIR) perifusion studies with isolated islets. Further optimization is still needed, but calculated insulin responses to stepwise increments in the incoming glucose concentration are in good agreement with existing experimental insulin release data characterizing glucose and oxygen dependence. The model makes possible the detailed description of the intraislet spatial distributions of insulin, glucose, and oxygen levels. In agreement with recent observations, modeling also suggests that smaller islets perform better when transplanted and/or encapsulated.</p> <p>Conclusions</p> <p>An insulin secretion model was implemented by coupling local consumption and release rates to calculations of the spatial distributions of all species of interest. The resulting glucose-insulin control system fits in the general framework of a sigmoid proportional-integral-derivative controller, a generalized PID controller, more suitable for biological systems, which are always nonlinear due to the maximum response being limited. Because of the general framework of the implementation, simulations can be carried out for arbitrary geometries including cultured, perifused, transplanted, and encapsulated islets.</p