Deterministic coupling of a single silicon-vacancy color center to a photonic crystal cavity in diamond

Deterministic coupling of single solid-state emitters to nanocavities is the key for integrated quantum information devices. We here fabricate a photonic crystal cavity around a preselected single silicon-vacancy color center in diamond and demonstrate modification of the emitters internal population dynamics and radiative quantum efficiency. The controlled, room-temperature cavity coupling gives rise to a resonant Purcell enhancement of the zero-phonon transition by a factor of 19, coming along with a 2.5-fold reduction of the emitter's lifetime

Evaluation of nitrogen- and silicon-vacancy defect centres as single photon sources in quantum key distribution

We demonstrate a quantum key distribution (QKD) testbed for room temperature single photon sources based on defect centres in diamond. A BB84 protocol over a short free-space transmission line is implemented. The performance of nitrogen-vacancy (NV) as well as silicon-vacancy defect (SiV) centres is evaluated and an extrapolation for next-generation sources with enhanced efficiency is discussed.Comment: 14 pages, 5 figure

Visible-to-telecom quantum frequency conversion of light from a single quantum emitter

Quantum frequency conversion (QFC), a nonlinear optical process in which the frequency of a quantum light field is altered while conserving its non-classical correlations, was first demonstrated 20 years ago. Meanwhile, it is considered an essential tool for the implementation of quantum repeaters since it allows for interfacing quantum memories with telecom-wavelength photons as quantum information carriers. Here we demonstrate efficient (>30%) QFC of visible single photons (711 nm) emitted by a quantum dot (QD) to a telecom wavelength (1,313 nm). Analysis of the first and second-order coherence before and after wavelength conversion clearly proves that important properties, such as the coherence time and photon antibunching, are fully conserved during the frequency translation process. Our findings underline the great potential of single photon sources on demand in combination with QFC as a promising technique for quantum repeater schemes.Comment: 11 pages, 4 figure

MYO5B, STX3, and STXBP2 mutations reveal a common disease mechanism that unifies a subset of congenital diarrheal disorders:A mutation update

Microvillus inclusion disease (MVID) is a rare but fatal autosomal recessive congenital diarrheal disorder caused by MYO5B mutations. In 2013, we launched an open-access registry for MVID patients and their MYO5B mutations (www.mvid-central.org). Since then, additional unique MYO5B mutations have been identified in MVID patients, but also in non-MVID patients. Animal models have been generated that formally prove the causality between MYO5B and MVID. Importantly, mutations in two other genes, STXBP2 and STX3, have since been associated with variants of MVID, shedding new light on the pathogenesis of this congenital diarrheal disorder. Here, we review these additional genes and their mutations. Furthermore, we discuss recent data from cell studies that indicate that the three genes are functionally linked and, therefore, may constitute a common disease mechanism that unifies a subset of phenotypically linked congenital diarrheal disorders. We present new data based on patient material to support this. To congregate existing and future information on MVID geno-/phenotypes, we have updated and expanded the MVID registry to include all currently known MVID-associated gene mutations, their demonstrated or predicted functional consequences, and associated clinical information.</p

Genetic and epigenetic characterization of posterior pituitary tumors

Pituicytoma (PITUI), granular cell tumor (GCT), and spindle cell oncocytoma (SCO) are rare tumors of the posterior pituitary. Histologically, they may be challenging to distinguish and have been proposed to represent a histological spectrum of a single entity. We performed targeted next-generation sequencing, DNA methylation profiling, and copy number analysis on 47 tumors (14 PITUI; 12 GCT; 21 SCO) to investigate molecular features and explore possibilities of clinically meaningful tumor subclassification. We detected two main epigenomic subgroups by unsupervised clustering of DNA methylation data, though the overall methylation differences were subtle. The largest group (n = 23) contained most PITUIs and a subset of SCOs and was enriched for pathogenic mutations within genes in the MAPK/PI3K pathways (12/17 [71%] of sequenced tumors: FGFR1 (3), HRAS (3), BRAF (2), NF1 (2), CBL (1), MAP2K2 (1), PTEN (1)) and two with accompanying TERT promoter mutation. The second group (n = 16) contained most GCTs and a subset of SCOs, all of which mostly lacked identifiable genetic drivers. Outcome analysis demonstrated that the presence of chromosomal imbalances was significantly associated with reduced progression-free survival especially within the combined PITUI and SCO group (p = 0.031). In summary, we observed only subtle DNA methylation differences between posterior pituitary tumors, indicating that these tumors may be best classified as subtypes of a single entity. Nevertheless, our data indicate differences in mutation patterns and clinical outcome. For a clinically meaningful subclassification, we propose a combined histo-molecular approach into three subtypes: one subtype is defined by granular cell histology, scarcity of identifiable oncogenic mutations, and favorable outcome. The other two subtypes have either SCO or PITUI histology but are segregated by chromosomal copy number profile into a favorable group (no copy number changes) and a less favorable group (copy number imbalances present). Both of the latter groups have recurrent MAPK/PI3K genetic alterations that represent potential therapeutic targets

DNA methylation-based classification of sinonasal tumors

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs