Shelf Transport Pathways Adjacent to the East Australian Current Reveal Sources of Productivity for Coastal Reefs

The region where the East Australian Current (EAC) separates from the coast is dynamic and the shelf circulation is impacted by the interplay of the western boundary current and its eddy field with the coastal ocean. This interaction can drive upwelling, retention or export. Hence understanding the connection between offshore waters and the inner shelf is needed as it influences the productivity potential of valuable coastal rocky reefs. Near urban centres, artificial reefs enhance fishing opportunities in coastal waters, however these reefs are located without consideration of the productivity potential of adjacent waters. Here we identify three dominant modes of mesoscale circulation in the EAC separation region (~31.5−34.5°S); the ‘EAC mode’ which dominates the flow in the poleward direction, and two eddy modes, the ‘EAC eddy mode’ and the ‘Eddy dipole mode’, which are determined by the configuration of a cyclonic and anticyclonic eddy and the relationship with the separated EAC jet. We use a Lagrangian approach to reveal the transport pathways across the shelf to understand the impact of the mesoscale circulation modes and to explore the productivity potential of the coastal waters. We investigate the origin (position and depth) of the water that arrives at the inner-mid shelf over a 21-day period (the plankton productivity timescale). We show that the proportion of water that is upwelled from below the euphotic zone varies spatially, and with each mesoscale circulation mode. Additionally, shelf transport timescales and pathways are also impacted by the mesoscale circulation. The highest proportion of upwelling (70%) occurs upstream of 32.5°S, associated with the EAC jet separation, with vertical displacements of 70–120 m. From 33 to 33.5°S, water comes from offshore above the euphotic layer, and shelf transport timescales are longest. The region of highest retention over the inner shelf is immediately downstream of the EAC separation region. The position of the EAC jet and the location of the cyclonic eddy determines the variability in shelf-ocean interactions and the productivity of shelf waters. These results are useful for understanding productivity of temperate rocky reefs in general and specifically for fisheries enhancements along an increasingly urbanised coast

Vertical-external-cavity surface-emitting lasers and quantum dot lasers

The use of cavity to manipulate photon emission of quantum dots (QDs) has been opening unprecedented opportunities for realizing quantum functional nanophotonic devices and also quantum information devices. In particular, in the field of semiconductor lasers, QDs were introduced as a superior alternative to quantum wells to suppress the temperature dependence of the threshold current in vertical-external-cavity surface-emitting lasers (VECSELs). In this work, a review of properties and development of semiconductor VECSEL devices and QD laser devices is given. Based on the features of VECSEL devices, the main emphasis is put on the recent development of technological approach on semiconductor QD VECSELs. Then, from the viewpoint of both single QD nanolaser and cavity quantum electrodynamics (QED), a single-QD-cavity system resulting from the strong coupling of QD cavity is presented. A difference of this review from the other existing works on semiconductor VECSEL devices is that we will cover both the fundamental aspects and technological approaches of QD VECSEL devices. And lastly, the presented review here has provided a deep insight into useful guideline for the development of QD VECSEL technology and future quantum functional nanophotonic devices and monolithic photonic integrated circuits (MPhICs).Comment: 21 pages, 4 figures. arXiv admin note: text overlap with arXiv:0904.369

Performance of Different Diagnostic PD-L1 Clones in Head and Neck Squamous Cell Carcinoma

Background: The approval of immune checkpoint inhibitors in combination with specific diagnostic biomarkers presents new challenges to pathologists as tumor tissue needs to be tested for expression of programmed death-ligand 1 (PD-L1) for a variety of indications. As there is currently no requirement to use companion diagnostic assays for PD-L1 testing in Germany different clones are used in daily routine. While the correlation of staining results has been tested in various entities, there is no data for head and neck squamous cell carcinomas (HNSCC) so far. Methods: We tested five different PD-L1 clones (SP263, SP142, E1L3N, 22-8, 22C3) on primary HNSCC tumor tissue of 75 patients in the form of tissue microarrays. Stainings of both immune and tumor cells were then assessed and quantified by pathologists to simulate real-world routine diagnostics. The results were analyzed descriptively and the resulting staining pattern across patients was further investigated by principal component analysis and non-negative matrix factorization clustering. Results: Percentages of positive immune and tumor cells varied greatly. Both the resulting combined positive score as well as the eligibility for certain checkpoint inhibitor regimens was therefore strongly dependent on the choice of the antibody. No relevant co-clustering and low similarity of relative staining patterns across patients was found for the different antibodies. Conclusions: Performance of different diagnostic anti PD-L1 antibody clones in HNSCC is less robust and interchangeable compared to reported data from other tumor entities. Determination of PD-L1 expression is critical for therapeutic decision making and may be aided by back-to-back testing of different PD-L1 clones

Submonolayer Quantum Dots for High Speed Surface Emitting Lasers

We report on progress in growth and applications of submonolayer (SML) quantum dots (QDs) in high-speed vertical-cavity surface-emitting lasers (VCSELs). SML deposition enables controlled formation of high density QD arrays with good size and shape uniformity. Further increase in excitonic absorption and gain is possible with vertical stacking of SML QDs using ultrathin spacer layers. Vertically correlated, tilted or anticorrelated arrangements of the SML islands are realized and allow QD strain and wavefunction engineering. Respectively, both TE and TM polarizations of the luminescence can be achieved in the edge-emission using the same constituting materials. SML QDs provide ultrahigh modal gain, reduced temperature depletion and gain saturation effects when used in active media in laser diodes. Temperature robustness up to 100 °C for 0.98 μm range vertical-cavity surface-emitting lasers (VCSELs) is realized in the continuous wave regime. An open eye 20 Gb/s operation with bit error rates better than 10−12has been achieved in a temperature range 25–85 °Cwithout current adjustment. Relaxation oscillations up to ∼30 GHz have been realized indicating feasibility of 40 Gb/s signal transmission

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

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

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

Nonlinear optics and saturation behavior of quantum dot samples under continuous wave driving

The nonlinear optical response of self-assembled quantum dots is relevant to the application of quantum dot based devices in nonlinear optics, all-optical switching, slow light and self-organization. Theoretical investigations are based on numerical simulations of a spatially and spectrally resolved rate equation model, which takes into account the strong coupling of the quantum dots to the carrier reservoir created by the wetting layer states. The complex dielectric susceptibility of the ground state is obtained. The saturation is shown to follow a behavior in between the one for a dominantly homogeneously and inhomogeneously broadened medium. Approaches to extract the nonlinear refractive index change by fringe shifts in a cavity or self-lensing are discussed. Experimental work on saturation characteristic of InGa/GaAs quantum dots close to the telecommunication O-band (1.24-1.28 mm) and of InAlAs/GaAlAs quantum dots at 780 nm is described and the first demonstration of the cw saturation of absorption in room temperature quantum dot samples is discussed in detail

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.Sinonasal tumour diagnosis can be complicated by the heterogeneity of disease and classification systems. Here, the authors use machine learning to classify sinonasal undifferentiated carcinomas into 4 molecular classe with differences in differentiation state and clinical outcome.Berliner Krebsgesellschaft e.V. Robert-Koch-Platz 7 10115 Berlin German