Confined placental mosaicism: placental size and function evaluated on magnetic resonance imaging.

OBJECTIVES: Evidence regarding placental function in pregnancies complicated by confined placental mosaicism (CPM) is conflicting. We aimed to compare placental function between CPM and non-CPM pregnancies prenatally and at birth. A secondary objective was to evaluate the relationship between placental function and chromosomal subtype of CPM. METHODS: This was a retrospective study of pregnancies with CPM and control pregnancies delivered at a tertiary hospital in Denmark between 2014 and 2017. Placental volume and placental transverse relaxation time (T2*) were estimated on magnetic resonance imaging (MRI), fetal weight and uterine artery pulsatility index (UtA-PI) were estimated on ultrasound and fetoplacental ratio was assessed on MRI and at birth. These estimates of placental function were adjusted for gestational age and compared between groups using the Wilcoxon rank-sum test. Within the group of CPM pregnancies, measures of placental function were compared between those at high risk (chromosome numbers 2, 3, 7, 13 and 16) and those at low risk (chromosome numbers 5, 18 and 45X). RESULTS: A total of 90 pregnancies were included, of which 12 had CPM and 78 were controls. MRI and ultrasound examinations were performed at a median gestational age of 32.6 weeks (interquartile range, 24.7-35.3 weeks). On MRI assessment, CPM placentae were characterized by a lower placental T2* Z-score (P = 0.004), a lower fetoplacental ratio (P = 0.03) and a higher UtA-PI Z-score (P = 0.03), compared with non-CPM placentae. At birth, the fetoplacental ratio was significantly lower (P = 0.02) and placental weight Z-score was higher (P = 0.01) in CPM pregnancies compared with non-CPM pregnancies. High-risk CPM pregnancies showed a reduced placental T2* Z-score (P = 0.003), lower birth-weight Z-score (P = 0.041), earlier gestational age at delivery (P = 0.019) and higher UtA-PI Z-score (P = 0.028) compared with low-risk CPM pregnancies. Low-risk CPM pregnancies did not differ in any of these parameters from non-CPM pregnancies. CONCLUSIONS: CPM pregnancies are characterized by an enlarged and dysfunctional placenta. Placental function was highly related to the chromosomal type of CPM; placental dysfunction was seen predominantly in high-risk CPM pregnancies in which chromosomes 2, 3, 7, 13 or 16 were involved. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Detection of low numbers of bacterial cells in a pharmaceutical drug product using Raman spectroscopy and PLS-DA multivariate analysis.

Sterility testing is a laborious and slow process to detect contaminants present in drug products. Raman spectroscopy is a promising label-free tool to detect microorganisms and thus gaining relevance as a future alternative culture-free method for sterility testing in the pharmaceutical industry. However, reaching detection limits similar to standard procedures while keeping a high accuracy remains challenging, due to weak bacterial Raman signals. In this work, we show a new non-invasive approach focusing on detection of different bacteria in concentrations below 100 CFU per ml within drug product containers using Raman spectroscopy and multivariate data analysis. Even though Raman spectra from drug product with and without bacteria are similar, a partial least squared discriminant analysis (PLS-DA) model shows great performance to distinguish samples with bacterial contaminants in concentrations down to 10 CFU per ml. We used spiked samples with bacterial spores for model validation achieving a detection accuracy of 99%. Our results indicate the great potential of this rapid, and cost-effective approach to be used in quality control in the pharmaceutical industry.

Nitro-fatty acids decrease type I interferons and monocyte chemoattractant protein 1 in ex vivo models of inflammatory arthritis.

BACKGROUND: Inflammatory arthritis including rheumatoid arthritis (RA) and spondyloarthritis (SpA) is characterized by inflammation and destruction of the joints. Approximately one third of patients do not respond to first-line treatments. Nitro-fatty acids are bioactive lipids with anti-inflammatory properties and tissue-protective functions. The nitro-fatty acid 10-NO2-oleic acid (10-NO2-OA) is being tested in clinical trials for patients with fibrotic and inflammatory conditions. Here, we tested whether 10-NO2-OA could inhibit immune reactions involved in the inflammatory and joint destructive processes in inflammatory arthritis. METHODS: Synovial fluid and blood samples were obtained from 14 patients with active RA or SpA. The in vitro models consisted of synovial fluid mononuclear cells (SFMCs) cultured for 48 h, SFMCs cultured for 21 days, and fibroblast-like synovial cells (FLSs) co-cultured with peripheral blood mononuclear cells (PBMCs) for 48 h. Cells were treated with or without 10-NO2-OA or the tumor necrosis factor alpha (TNFα) inhibitor etanercept. Supernatants were analyzed for type I interferon, monocyte chemoattractant protein-1 (MCP-1), matrix metalloproteinase 3 (MMP3) and tartrate resistant acid phosphatase (TRAP). RESULTS: In SFMCs cultured for 48 h, 10-NO2-OA dose-dependently decreased the secretion of bioactive type I interferons and MCP-1 but not MMP3 (P = 0.032, P = 0.0001, and P = 0.58, respectively). Both MCP-1 and MMP3 were decreased by etanercept (P = 0.0031 and P = 0.026, respectively). In SFMCs cultured for 21 days, 10-NO2-OA significantly decreased the production of MCP-1 but not TRAP (P = 0.027 and P = 0.1523, respectively). Etanercept decreased the production of TRAP but not MCP-1 (P < 0.001 and P = 0.84, respectively). In co-cultures of FLSs and PBMCs, 10-NO2-OA decreased the production of MCP-1 (P < 0.0001). This decrease in MCP-1 production was not seen with etanercept treatment (P = 0.47). CONCLUSION: 10-NO2-OA decreased the release of MCP-1 in three models of inflammatory arthritis. Of particular interest, 10-NO2-OA inhibited type I interferon, and 10-NO2-OA was more effective in reducing MCP-1 production in cultures dominated by FLSs compared with etanercept. Our results encourage clinical investigations of 10-NO2-OA in patients with inflammatory arthritis.

Ignoring genotype by environment interaction in the genetic evaluation of dairy cattle reduces accuracy but may increase selection intensity.

Genotype by environment interaction (G×E) may exist for traits that are expressed in different environments. The G×E is often ignored in the genetic evaluation of selection candidates. We hypothesized that genetic gain in 2 environments is always higher when the true value of the genetic correlation (rg) between traits expressed in different environments is considered in the genetic evaluation. We tested this hypothesis by stochastic simulation of dairy cattle breeding programs in a mainstream and a niche environment. The rg was varied from 0 to 1 in steps of 0.1. We simulated the following 3 scenarios: 1Trait_1Index, 2Traits_1Index, and 2Traits_2Indices. The G×E was ignored in the genetic evaluation in the scenario with 1Trait and included in scenarios with 2Traits. Selection was based on the mainstream selection index in both environments in scenarios with 1Index. Selection in the mainstream environment was based on the mainstream selection index and selection in the niche environment was based on the niche selection index in the scenario with 2Indices. With moderate G×E (rg between 0.6 and 0.9), the highest genetic gain was achieved in the niche environment by selecting for the mainstream selection index and ignoring G×E. At lower rg, the highest genetic gain was achieved when considering G×E and selecting for the niche selection index. For the mainstream environment, it was never an advantage to ignore G×E. Therefore, although our hypothesis was confirmed in most cases, there were cases where ignoring G×E was the better option, and using the correct evaluation led to inferior genetic gain. The results of the current study can be used in animal breeding programs that encompass multiple environments.

Phase II trial of carboplatin and bevacizumab in patients with breast cancer brain metastases.

BACKGROUND: We aimed to examine the safety and efficacy of bevacizumab and carboplatin in patients with breast cancer brain metastases. METHODS: We enrolled patients with breast cancer and > 1 measurable new or progressive brain metastasis. Patients received bevacizumab 15 mg/kg intravenously (IV) on cycle 1 day 1 and carboplatin IV AUC = 5 on cycle 1 day 8. Patients with HER2-positive disease also received trastuzumab. In subsequent cycles, all drugs were administered on day 1 of each cycle. Contrast-enhanced brain MRI was performed at baseline, 24-96 h after the first bevacizumab dose (day + 1), and every 2 cycles. The primary endpoint was objective response rate in the central nervous system (CNS ORR) by composite criteria. Associations between germline VEGF single nucleotide polymorphisms (rs699947, rs2019063, rs1570360, rs833061) and progression-free survival (PFS) and overall survival (OS) were explored, as were associations between early (day + 1) MRI changes and outcomes. RESULTS: Thirty-eight patients were enrolled (29 HER2-positive, 9 HER2-negative); all were evaluable for response. The CNS ORR was 63% (95% CI, 46-78). Median PFS was 5.62 months and median OS was 14.10 months. As compared with an Eastern Cooperative Oncology Group performance status (ECOG PS) of 0, patients with ECOG PS 1-2 had significantly worse PFS and OS (all P < 0.01). No significant associations between VEGF genotypes or early MRI changes and clinical outcomes were observed. CONCLUSIONS: The combination of bevacizumab and carboplatin results in a high rate of durable objective response in patients with brain metastases from breast cancer. This regimen warrants further investigation. TRIAL REGISTRATION: NCT01004172 . Registered 28 October 2009.

Textural features of hypoxia PET predict survival in head and neck cancer during chemoradiotherapy.

PURPOSE: The aim of this study was to investigate whether textural features of tumour hypoxia, assessed with serial [18F]fluoromisonidazole (FMISO)-PET, were able to predict clinical outcome in patients with head and neck squamous cell carcinoma (HNSCC, T1-4, N+, M0) during chemoradiotherapy (CRT). METHODS: In a preliminary evaluation of a prospective trial, tumour hypoxia was evaluated in 29 patients via serial FMISO-PET before and during CRT. All patients received an initial [18F]fluorodeoxyglucose (FDG)-PET before CRT, and tumour regions were defined on this FDG-PET. The first-order metrics tumour-to-background ratio (TBRmean, TBRmax, TBRpeak), coefficient of variation, total lesion uptake and integral non-uniformity were calculated for all scans. Further, 3 second-order (textural) features from two grey-level matrices were calculated, as well as differential non-uniformity (udiff). Prognostic value was examined by median split for group separation (GS) in Kaplan-Meier estimates and correlated with overall survival (OS), quantified via log-rank tests (p ≤ 0.05) and group-relative hazard ratios (HR). RESULTS: Within a median follow-up of 29.6 months (95% CI: 16.8-48.0 months), no first-order metrics predicted OS with a significant GS (all p > 0.05) on any FMISO-PET scan. Only udiff before and in week 2 during CRT (p = 0.03, HR = 10.8 and p = 0.05, HR = 5.2) and non-uniformity from grey-level run length matrix in week 2 separated prognostic groups (p = 0.05, HR = 5.3); lower values were correlated with better OS. Further, the decrease in udiff from before CRT to week 2 was correlated with better OS (p = 0.04, HR = 9.4). FDG-PET before CRT did not predict outcome in any measure. CONCLUSIONS: Textural features on FMISO-PET scans before CRT, in week 2 and, to a limited degree, the change of features during CRT, were able to identify head and neck squamous cell carcinoma patients with better OS, suggesting that a higher homogeneity of the degree of hypoxia in tumours could correlate with a better outcome after CRT.

Twenty years with diabetes and amputations: a retrospective population-based cohort study.

AIM: To investigate the trends in non-traumatic lower limb amputation in people with and without diabetes. METHODS: From the Danish National Patient Register, all people with either type 1 or type 2 diabetes (n = 462 743) as well as a group of people without diabetes from the general population (n = 1 388 886) were identified and separated into three groups based on diabetes type. Among these, 17 265 amputations were identified between 1997 and 2017 and stratified into trans-femoral amputations, trans-tibial amputations and amputations below the ankle using surgical codes. Annual changes were described using least-squares linear regression. RESULTS: The yearly mean decrease in incidence rate of amputation per 1000 person-years was -0.032 [95% CI: -0.062, -0.001], -0.022 [-0.032, -0.012] and -0.006 [-0.009, -0.003] for trans-femoral amputation, -0.072 [-0.093, -0.052], -0.090 [-0.102, -0.078] and -0.015 [-0.016, -0.013] for trans-tibial amputation, and -0.055 [-0.080, -0.020], -0.075 [-0.090, -0.060] and -0.011 [-0.014, -0.007] for amputation below the ankle in people with type 1 diabetes, people with type 2 diabetes and people without diabetes, respectively. CONCLUSIONS: Over recent decades, the incidence of amputation has decreased significantly in people with diabetes and in the general population without diabetes.

Novel approach to incorporate information about recessive lethal genes increases the accuracy of genomic prediction for mortality traits.

The genetic underpinnings of calf mortality can be partly polygenic and partly due to deleterious effects of recessive lethal alleles. Prediction of the genetic merits of selection candidates should thus take into account both genetic components contributing to calf mortality. However, simultaneously modeling polygenic risk and recessive lethal allele effects in genomic prediction is challenging due to effects that behave differently. In this study, we present a novel approach where mortality risk probabilities from polygenic and lethal allele components are predicted separately to compute the total risk probability of an individual for its future offspring as a basis for selection. We present methods for transforming genomic estimated breeding values of polygenic effect into risk probabilities using normal density and cumulative distribution functions and show computations of risk probability from recessive lethal alleles given sire genotypes and population recessive allele frequencies. Simulated data were used to test the novel approach as implemented in probit, logit, and linear models. In the simulation study, the accuracy of predicted risk probabilities was computed as the correlation between predicted mortality probabilities and observed calf mortality for validation sires. The results indicate that our novel approach can greatly increase the accuracy of selection for mortality traits compared with the accuracy of predictions obtained without distinguishing polygenic and lethal gene effects.

Effect of genomic selection and genotyping strategy on estimation of variance components in animal models using different relationship matrices.

BACKGROUND: The traditional way to estimate variance components (VC) is based on the animal model using a pedigree-based relationship matrix (A) (A-AM). After genomic selection was introduced into breeding programs, it was anticipated that VC estimates from A-AM would be biased because the effect of selection based on genomic information is not captured. The single-step method (H-AM), which uses an H matrix as (co)variance matrix, can be used as an alternative to estimate VC. Here, we compared VC estimates from A-AM and H-AM and investigated the effect of genomic selection, genotyping strategy and genotyping proportion on the estimation of VC from the two methods, by analyzing a dataset from a commercial broiler line and a simulated dataset that mimicked the broiler population. RESULTS: VC estimates from H-AM were severely overestimated with a high proportion of selective genotyping, and overestimation increased as proportion of genotyping increased in the analysis of both commercial and simulated data. This bias in H-AM estimates arises when selective genotyping is used to construct the H-matrix, regardless of whether selective genotyping is applied or not in the selection process. For simulated populations under genomic selection, estimates of genetic variance from A-AM were also significantly overestimated when the effect of genomic selection was strong. Our results suggest that VC estimates from H-AM under random genotyping have the expected values. Predicted breeding values from H-AM were inflated when VC estimates were biased, and inflation differed between genotyped and ungenotyped animals, which can lead to suboptimal selection decisions. CONCLUSIONS: We conclude that VC estimates from H-AM are biased with selective genotyping, but are close to expected values with random genotyping.VC estimates from A-AM in populations under genomic selection are also biased but to a much lesser degree. Therefore, we recommend the use of H-AM with random genotyping to estimate VC for populations under genomic selection. Our results indicate that it is still possible to use selective genotyping in selection, but then VC estimation should avoid the use of genotypes from one side only of the distribution of phenotypes. Hence, a dual genotyping strategy may be needed to address both selection and VC estimation.

Optical detection of radio waves through a nanomechanical transducer.

Low-loss transmission and sensitive recovery of weak radio-frequency and microwave signals is a ubiquitous challenge, crucial in radio astronomy, medical imaging, navigation, and classical and quantum communication. Efficient up-conversion of radio-frequency signals to an optical carrier would enable their transmission through optical fibres instead of through copper wires, drastically reducing losses, and would give access to the set of established quantum optical techniques that are routinely used in quantum-limited signal detection. Research in cavity optomechanics has shown that nanomechanical oscillators can couple strongly to either microwave or optical fields. Here we demonstrate a room-temperature optoelectromechanical transducer with both these functionalities, following a recent proposal using a high-quality nanomembrane. A voltage bias of less than 10 V is sufficient to induce strong coupling between the voltage fluctuations in a radio-frequency resonance circuit and the membrane's displacement, which is simultaneously coupled to light reflected off its surface. The radio-frequency signals are detected as an optical phase shift with quantum-limited sensitivity. The corresponding half-wave voltage is in the microvolt range, orders of magnitude less than that of standard optical modulators. The noise of the transducer--beyond the measured 800 pV Hz-1/2 Johnson noise of the resonant circuit--consists of the quantum noise of light and thermal fluctuations of the membrane, dominating the noise floor in potential applications in radio astronomy and nuclear magnetic imaging. Each of these contributions is inferred to be 60 pV Hz-1/2 when balanced by choosing an electromechanical cooperativity of ~150 with an optical power of 1 mW. The noise temperature of the membrane is divided by the cooperativity. For the highest observed cooperativity of 6,800, this leads to a projected noise temperature of 40 mK and a sensitivity limit of 5 pV Hz-1/2. Our approach to all-optical, ultralow-noise detection of classical electronic signals sets the stage for coherent up-conversion of low-frequency quantum signals to the optical domain.

Quantification of Tumor Oxygenation Based on FMISO PET: Influence of Location and Oxygen Level of the Well-Oxygenated Reference Region.

Tumor hypoxia may play a fundamental role in determining the radiotherapy outcome for several cancer types. Functional imaging with hypoxia specific radiotracers offers a way to visualize and quantify regions of increased radioresistance, which may benefit from dose escalation strategies. Conversion of the uptake in positron emission tomography (PET) images into oxygenation maps offers a way to quantitatively characterize the microenvironment. However, normalization of the uptake with respect to a well-oxygenated reference volume (WOV), which should be properly selected, is necessary when using conversion functions. This study aims at assessing the sensitivity of quantifying tumor oxygenation based on 18F-fluoromisonidazole (FMISO) PET with respect to the choice of the location and the oxygenation level of the WOV in head and neck cancer patients. WOVs varying not only in shape and location but also with respect to the assigned pO2 level were considered. pO2 values other than the standard 60 mmHg were selected according to the specific tissue type included in the volume. For comparison, the volume which would be considered as hypoxic based on a tissue-to-muscle ratio equal to 1.4 was also delineated, as conventionally done in clinical practice. Hypoxia mapping strategies are found highly sensitive to selection of the location of well-oxygenated region, but also on its assigned oxygenation level, which is crucial for hypoxia-guided adaptive dose escalation strategies.

Genotyping more cows increases genetic gain and reduces rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies.

Both small dairy cattle populations and dairy cattle populations with a low level of linkage disequilibrium (LD) suffer from low reliability of genomic prediction. In this study, we investigated whether adding more genotyped cows to the reference population influences the rate of genetic gain and rate of inbreeding by affecting the reliability. A standard breeding program with a large reference population and high LD, which mimicked a breeding program for Danish Holstein population, was simulated as a reference. A Danish Jersey population with a small reference population and high LD and a Red Dairy Cattle population with a large reference population and low LD were also simulated. Two additional breeding programs were simulated for Danish Jersey and Red Dairy Cattle populations, where 2,000 additional genotyped cows were included in the population for genomic selection. All 5 simulated breeding programs were initiated by a founder population to generate LD resembling the real LD pattern, followed by a 20-yr conventional progeny-testing scheme with 1,000 or 10,000 genotyped progeny-tested bulls and a 10-yr genomic selection scheme with or without 2,000 additional genotyped cows. Evaluation criteria were annual monetary genetic gain and rate of true inbreeding. Our results showed that adding more genotyped cows to the reference in dairy cattle populations has the potential to increase genetic gain and reduce the rate of inbreeding, regardless of reference population size and level of LD. However, it is still not possible to reach the same genetic gain as in the simulated Danish Holstein population with either a small reference population or low LD. Our results also showed that in a small reference population with high LD, it is difficult to manage inbreeding because of lower accuracy compared with the simulated Danish Holstein population and a smaller number of relevant families to select from. Therefore, breeding strategies need to be chosen to match population size and structure. The rate of true inbreeding is always underestimated by pedigree inbreeding and even more in genomic breeding programs, indicating that some forms of genome-wide inbreeding, instead of pedigree-based inbreeding, should be used to monitor inbreeding when genomic selection is implemented.

Possibilities for a specific breeding program for organic dairy production.

Organic dairy production differs from conventional dairy production in many aspects. However, breeding programs for the 2 production systems are the same in most countries. Breeding goals (BG) might be different for the 2 production systems and genotype × environment interaction may exist between organic and conventional dairy production, both of which have an effect on genetic gain in different breeding strategies. Other aspects also need to be considered, such as the application of multiple ovulation and embryo transfer (MOET), which is not allowed in organic dairy production. The general aim of this research was to assess different environment-specific breeding strategies for organic dairy production. The specific aim was to study differences in BG weights and include the effect of genotype × environment interaction, MOET, and the selection of breeding bulls from the conventional environment. Different scenarios were simulated. In the current scenario, the present-day situation for dairy production in Denmark was emulated as much as possible. The BG was based on a conventional dairy production system, MOET was applied in both environments, and conventional bulls could be selected as breeding bulls in the organic environment. Four alternative scenarios were simulated, all with a specific organic BG in the organic breeding program but differences in the usage of MOET and the selection of conventional bulls as breeding bulls. Implementation of a specific BG in organic dairy production slightly increased genetic gain in the aggregate genotype compared with the breeding program that is currently implemented in organic dairy production. Not using embryo transfer or only selecting breeding bulls from the organic environment decreased genetic gain in the aggregate genotype by as much as 24%. However, the use of embryo transfer is debatable because this is not allowed according to current regulations for organic dairy production. Assessing genetic gain on trait levels showed that a significant increase for functional traits was possible compared with the current breeding program in the organic environment without a decrease in genetic gain in the aggregate genotype. This difference on trait level was even more present when selection of conventional bulls as breeding bulls in the organic environment was not possible. This finding is very relevant when breeding for the desired cow in organic dairy production.

Innate and adaptive immune responses against human Puumala virus infection: immunopathogenesis and suggestions for novel treatment strategies for severe hantavirus-associated syndromes.

Two related hyperinflammatory syndromes are distinguished following infection of humans with hantaviruses: haemorrhagic fever with renal syndrome (HFRS) seen in Eurasia and hantavirus pulmonary syndrome (HPS) seen in the Americas. Fatality rates are high, up to 10% for HFRS and around 35%-40% for HPS. Puumala virus (PUUV) is the most common HFRS-causing hantavirus in Europe. Here, we describe recent insights into the generation of innate and adaptive cell-mediated immune responses following clinical infection with PUUV. First described are studies demonstrating a marked redistribution of peripheral blood mononuclear phagocytes (MNP) to the airways, a process that may underlie local immune activation at the site of primary infection. We then describe observations of an excessive natural killer (NK) cell activation and the persistence of highly elevated numbers of NK cells in peripheral blood following PUUV infection. A similar vigorous CD8 Tcell response is also described, though Tcell responses decline with viraemia. Like MNPs, many NK cells and CD8 T cells also localize to the lung upon acute PUUV infection. Following this, findings demonstrating the ability of hantaviruses, including PUUV, to cause apoptosis resistance in infected target cells, are described. These observations, and associated inflammatory cytokine responses, may provide new insights into HFRS and HPS disease pathogenesis. Based on similarities between inflammatory responses in severe hantavirus infections and other hyperinflammatory disease syndromes, we speculate whether some therapeutic interventions that have been successful in the latter conditions may also be applicable in severe hantavirus infections.

18F FDG-PET/CT has poor diagnostic accuracy in diagnosing shoulder PJI.

PURPOSE: Chronic low-grade periprosthetic joint infection (PJI) of a shoulder replacement can be challenging to diagnose. 18F-FDG PET/CT is suggested as a modality to diagnose lower-limb PJI, but no studies on shoulder replacements exist. The aim of this study was therefore to determine the diagnostic accuracy of 18F-FDG PET/CT in diagnosing chronic PJI of the shoulder. METHODS: Patients evaluated for a failed shoulder replacement during a 3-year period were prospectively included in the study. All patients underwent pre-operative 18F-FDG PET/CT, and were evaluated for signs of infection by three independent reviewers using shoulder-specific criteria. Interrater-agreement was calculated between the reviewers. If the patient had revision surgery, biopsy specimens were obtained and cultured with bacterial growth in the cultures serving as gold standard of infection. RESULTS: A total of 86 patients were included in the study. Nine patients were 18F-FDG PET/CT positive for infection, with only three true positive. Using the gold standard, infection was diagnosed after revision surgery in 22 cases. All infections were chronic and caused by low-virulent microbes. The sensitivity of 18F-FDG PET/CT was 0.14 95% CI (0.03-0.36), specificity 0.91 95% CI (0.81-0.97), positive predictive value was 0.40 95% CI (0.15-0.71) and negative predictive value 0.71 95% CI (0.67-0.75). The inter-observer agreement was 0.56 (Fleiss' kappa), indicating moderate agreement of the visual FDG-PET evaluation using the shoulder-specific criteria. CONCLUSION: 18F-FDG PET/CT has poor diagnostic accuracy in diagnosing low-grade PJI of the shoulder. 18F-FDG PET/CT cannot be recommended as a part of the routine preoperative workup to diagnose low-grade infection of a shoulder replacement.

Pedigree relationships to control inbreeding in optimum-contribution selection realise more genetic gain than genomic relationships.

BACKGROUND: We tested the premise that optimum-contribution selection with pedigree relationships to control inbreeding (POCS) realises at least as much true genetic gain as optimum-contribution selection with genomic relationships (GOCS) at the same rate of true inbreeding. METHODS: We used stochastic simulation to estimate rates of true genetic gain realised by POCS and GOCS at a 0.01 rate of true inbreeding in three breeding schemes with best linear unbiased predictions of breeding values based on pedigree (PBLUP) and genomic (GBLUP) information. The three breeding schemes differed in number of matings and litter size. Selection was for a single trait with a heritability of 0.2. The trait was controlled by 7702 biallelic quantitative-trait loci (QTL) that were distributed across a 30-M genome. The genome contained 54,218 biallelic markers that were used in GOCS and GBLUP. A total of 6012 identity-by-descent loci were placed across the genome in base populations. Unique alleles at these loci were used to calculate rates of true inbreeding. Breeding schemes were run for 10 discrete generations. Selection candidates were genotyped and phenotyped before selection. RESULTS: POCS realised more true genetic gain than GOCS at a 0.01 rate of true inbreeding in all combinations of breeding scheme and prediction method. POCS realised 14 to 33% more true genetic gain than GOCS with PBLUP in the three breeding schemes. It realised 1.5 to 5.7% more true genetic gain than GOCS with GBLUP. CONCLUSIONS: POCS realised more true genetic gain than GOCS because it managed expected genetic drift without restricting selection at QTL. By contrast, GOCS penalised changes in allele frequencies at markers that were generated by genetic drift and selection. Because these marker alleles were in linkage disequilibrium with QTL alleles, GOCS restricted changes in allele frequencies at QTL. This provides little incentive to use GOCS and highlights that we have more to learn before we can control inbreeding using genomic relationships in selective-breeding schemes. Until we can do so, POCS remains a worthy method of optimum-contribution selection because it realises more true genetic gain than GOCS at the same rate of true inbreeding.

Dissipative production of a maximally entangled steady state of two quantum bits.

Entangled states are a key resource in fundamental quantum physics, quantum cryptography and quantum computation. Introduction of controlled unitary processes--quantum gates--to a quantum system has so far been the most widely used method to create entanglement deterministically. These processes require high-fidelity state preparation and minimization of the decoherence that inevitably arises from coupling between the system and the environment, and imperfect control of the system parameters. Here we combine unitary processes with engineered dissipation to deterministically produce and stabilize an approximate Bell state of two trapped-ion quantum bits (qubits), independent of their initial states. Compared with previous studies that involved dissipative entanglement of atomic ensembles or the application of sequences of multiple time-dependent gates to trapped ions, we implement our combined process using trapped-ion qubits in a continuous time-independent fashion (analogous to optical pumping of atomic states). By continuously driving the system towards the steady state, entanglement is stabilized even in the presence of experimental noise and decoherence. Our demonstration of an entangled steady state of two qubits represents a step towards dissipative state engineering, dissipative quantum computation and dissipative phase transitions. Following this approach, engineered coupling to the environment may be applied to a broad range of experimental systems to achieve desired quantum dynamics or steady states. Indeed, concurrently with this work, an entangled steady state of two superconducting qubits was demonstrated using dissipation.

Genomic selection improves the possibility of applying multiple breeding programs in different environments.

One joint breeding program (BP) for different dairy cattle environments can be advantageous for genetic gain depending on the genetic correlation between environments (rg). The break-even correlation (rb) refers to the specific rg where genetic gain with 1 joint BP is equal to the genetic gain of 2 environment-specific BP. One joint BP has the highest genetic gain if rg is higher than rb, whereas 2 environment-specific BP have higher genetic gain if rg is lower than rb. Genetic gain in this context is evaluated from a breeding company's perspective that aims to improve genetic gain in both environments. With the implementation of genomic selection, 2 types of collaboration can be identified: exchanging breeding animals and exchanging genomic information. The aim of this study was to study genetic gain in multiple environments with different breeding strategies with genomic selection. The specific aims were (1) to find rb when applying genomic selection; (2) to assess how much genetic gain is lost when applying a suboptimal breeding strategy; (3) to study the effect of the reliability of direct genomic values, number of genotyped animals, and environments of different size on rb and genetic gain; and (4) to find rb from each environment's point of view. Three breeding strategies were simulated: 1 joint BP for both environments, 2 environment-specific BP with selection of bulls across environments, and 2 environment-specific BP with selection of bulls within environments. The rb was 0.65 and not different from rb with progeny-testing breeding programs when compared at the same selection intensity. The maximum loss in genetic gain in a suboptimal breeding strategy was 24%. A higher direct genomic value reliability and an increased number of genotyped selection candidates increased genetic gain, and the effect on rb was not large. A different size in 2 environments decreased rb by, at most, 0.10 points. From a large environment's point of view, 1 joint BP was the optimal breeding strategy in most scenarios. From a small environment's point of view, 1 joint BP was only the optimal breeding strategy at high rg. When the exchange of breeding animals between environments was restricted, genetic gain could still increase in each environment. This was due to the exchange of genomic information between environments, even when rg between environments were as low as 0.4. Thus, genomic selection improves the possibility of applying environment-specific BP.

Phonon Decoherence of Quantum Dots in Photonic Structures: Broadening of the Zero-Phonon Line and the Role of Dimensionality.

We develop a general microscopic theory describing the phonon decoherence of quantum dots and indistinguishability of the emitted photons in photonic structures. The coherence is found to depend fundamentally on the dimensionality of the structure resulting in vastly different performance for quantum dots embedded in a nanocavity (0D), waveguide (1D), slab (2D), or bulk medium (3D). In bulk, we find a striking temperature dependence of the dephasing rate scaling as T^{11} implying that phonons are effectively "frozen out" for T≲4 K. The phonon density of states is strongly modified in 1D and 2D structures leading to a linear temperature scaling for the dephasing strength. The resulting impact on the photon indistinguishability can be important even at sub-Kelvin temperatures. Our findings provide a comprehensive understanding of the fundamental limits to photon indistinguishability in photonic structures.

Understanding the potential bias of variance components estimators when using genomic models.

BACKGROUND: Genomic models that link phenotypes to dense genotype information are increasingly being used for infering variance parameters in genetics studies. The variance parameters of these models can be inferred using restricted maximum likelihood, which produces consistent, asymptotically normal estimates of variance components under the true model. These properties are not guaranteed to hold when the covariance structure of the data specified by the genomic model differs substantially from the covariance structure specified by the true model, and in this case, the likelihood of the model is said to be misspecified. If the covariance structure specified by the genomic model provides a poor description of that specified by the true model, the likelihood misspecification may lead to incorrect inferences. RESULTS: This work provides a theoretical analysis of the genomic models based on splitting the misspecified likelihood equations into components, which isolate those that contribute to incorrect inferences, providing an informative measure, defined as [Formula: see text], to compare the covariance structure of the data specified by the genomic and the true models. This comparison of the covariance structures allows us to determine whether or not bias in the variance components estimates is expected to occur. CONCLUSIONS: The theory presented can be used to provide an explanation for the success of a number of recently reported approaches that are suggested to remove sources of bias of heritability estimates. Furthermore, however complex is the quantification of this bias, we can determine that, in genomic models that consider a single genomic component to estimate heritability (assuming SNP effects are all i.i.d.), the bias of the estimator tends to be downward, when it exists.