Conditional linear-optical measurement schemes generate effective photon nonlinearities

We provide a general approach for the analysis of optical state evolution under conditional measurement schemes, and identify the necessary and sufficient conditions for such schemes to simulate unitary evolution on the freely propagating modes. If such unitary evolution holds, an effective photon nonlinearity can be identified. Our analysis extends to conditional measurement schemes more general than those based solely on linear optics.Comment: 16 pages, 2 figure

From Linear Optical Quantum Computing to Heisenberg-Limited Interferometry

The working principles of linear optical quantum computing are based on photodetection, namely, projective measurements. The use of photodetection can provide efficient nonlinear interactions between photons at the single-photon level, which is technically problematic otherwise. We report an application of such a technique to prepare quantum correlations as an important resource for Heisenberg-limited optical interferometry, where the sensitivity of phase measurements can be improved beyond the usual shot-noise limit. Furthermore, using such nonlinearities, optical quantum nondemolition measurements can now be carried out at the single-photon level.Comment: 10 pages, 5 figures; Submitted to a Special Issue of J. Opt. B on "Fluctuations and Noise in Photonics and Quantum Optics" (Herman Haus Memorial Issue); v2: minor change

Photon wave functions, wave-packet quantization of light, and coherence theory

The monochromatic Dirac and polychromatic Titulaer-Glauber quantized field theories (QFTs) of electromagnetism are derived from a photon-energy wave function in much the same way that one derives QFT for electrons, that is, by quantization of a single-particle wave function. The photon wave function and its equation of motion are established from the Einstein energy-momentum-mass relation, assuming a local energy density. This yields a theory of photon wave mechanics (PWM). The proper Lorentz-invariant single-photon scalar product is found to be non-local in coordinate space, and is shown to correspond to orthogonalization of the Titulaer-Glauber wave-packet modes. The wave functions of PWM and mode functions of QFT are shown to be equivalent, evolving via identical equations of motion, and completely describe photonic states. We generalize PWM to two or more photons, and show how to switch between the PWM and QFT viewpoints. The second-order coherence tensors of classical coherence theory and the two-photon wave functions are shown to propagate equivalently. We give examples of beam-like states, which can be used as photon wave functions in PWM, or modes in QFT. We propose a practical mode converter based on spectral filtering to convert between wave packets and their corresponding biorthogonal dual wave packets.Comment: 34 pages, 3 figures, minor correction

Simultaneous quantitative assessment of circulating cell-free mitochondrial and nuclear DNA by multiplex real-time PCR

Quantification of circulating nucleic acids in plasma and serum could be used as a non-invasive diagnostic tool for monitoring a wide variety of diseases and conditions. We describe here a rapid, simple and accurate multiplex real-time PCR method for direct synchronized analysis of circulating cell-free (ccf) mitochondrial (mtDNA) and nuclear (nDNA) DNA in plasma and serum samples. The method is based on one-step multiplex real-time PCR using a FAM-labeled MGB probe and primers to amplify the mtDNA sequence of the ATP 8 gene, and a VIC-labeled MGB probe and primers to amplify the nDNA sequence of the glycerinaldehyde-3-phosphate-dehydrogenase (GAPDH) gene, in plasma and serum samples simultaneously. The efficiencies of the multiplex assays were measured in serial dilutions. Based on the simulation of the PCR reaction kinetics, the relative quantities of ccf mtDNA were calculated using a very simple equation. Using our optimised real-time PCR conditions, close to 100% efficiency was obtained from the two assays. The two assays performed in the dilution series showed very good and reproducible correlation to each other. This optimised multiplex real-time PCR protocol can be widely used for synchronized quantification of mtDNA and nDNA in different samples, with a very high rate of efficiency

Excessive Neutrophil Activity in Gestational Diabetes Mellitus: Could It Contribute to the Development of Preeclampsia?

Gestational diabetes mellitus is a transient form of glucose intolerance occurring during pregnancy. Pregnancies affected by gestational diabetes mellitus are at risk for the development of preeclampsia, a severe life threatening condition, associated with significant feto-maternal morbidity and mortality. It is a risk factor for long-term health in women and their offspring. Pregnancy has been shown to be associated with a subliminal degree of neutrophil activation and tightly regulated generation of neutrophil extracellular traps (NETs). This response is excessive in cases with preeclampsia, leading to the presence of large numbers of NETs in affected placentae. We have recently observed that circulatory neutrophils in cases with gestational diabetes mellitus similarly exhibit an excessive pro-NETotic phenotype, and pronounced placental presence, as detected by expression of neutrophil elastase. Furthermore, exogenous neutrophil elastase liberated by degranulating neutrophils was demonstrated to alter trophoblast physiology and glucose metabolism by interfering with key signal transduction components. In this review we examine whether additional evidence exists suggesting that altered neutrophil activity in gestational diabetes mellitus may contribute to the development of preeclampsia

Extending the scope of pooled analyses of individual patient biomarker data from heterogeneous laboratory platforms and cohorts using merging algorithms

Background: A common challenge in medicine, exemplified in the analysis of biomarker data, is that large studies are needed for sufficient statistical power. Often, this may only be achievable by aggregating multiple cohorts. However, different studies may use disparate platforms for laboratory analysis, which can hinder merging. Methods: Using circulating placental growth factor (PIGF), a potential biomarker for hypertensive disorders of pregnancy (HDP) such as preeclampsia, as an example, we investigated how such issues can be overcome by inter-platform standardization and merging algorithms. We studied 16,462 pregnancies from 22 study cohorts. PIGF measurements (gestational age >= 20 weeks) analyzed on one of four platforms: R & Systems, Alere (R) Triage, Roche (R) Elecsys or Abbott (R) Architect, were available for 13,429 women. Two merging algorithms, using Z-Score and Multiple of Median transformations, were applied. Results: Best reference curves (BRC), based on merged, transformed PIGF measurements in uncomplicated pregnancy across six gestational age groups, were estimated. Identification of HDP by these PIGF-BRCS was compared to that of platform-specific curves. Conclusions: We demonstrate the feasibility of merging PIGF concentrations from different analytical platforms. Overall BRC identification of HDP performed at least as well as platform-specific curves. Our method can be extended to any set of biomarkers obtained from different laboratory platforms in any field. Merged biomarker data from multiple studies will improve statistical power and enlarge our understanding of the pathophysiology and management of medical syndromes. (C) 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.Peer reviewe

A cohort evaluation on arterial stiffness and hypertensive disorders in pregnancy

10.1186/1471-2393-12-160BMC Pregnancy and Childbirth12-BPCM

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe