Showing papers by "University of Copenhagen published in 2023"

Hjelmslev, a forerunner of the semantic maps method in linguistic typology?

Abstract: In this paper, we show that Hjelmslev’s approach to language description and crosslinguistic comparison, on the one hand, and the semantic maps model used in linguistic typology, on the other, differ significantly. Although Hjelmslev paved the way for employing graphic representations as a means to show how each language of the world subdivides the semantic continuum in its own way, he can hardly be considered as a forerunner of the semantic maps tradition. In a nutshell, Hjelmslev’s schemas are meant to compare the specific organisation of individual linguistic systems, but the semantic maps method aims at unveiling semantic regularities across languages. The former targets the particular ‘grid’ imposed by each language on a given semantic space, but the latter abstracts away from specific linguistic systems and posits universal atoms of sense that can be organised in cross-linguistically valid networks.

Decoding of the speech envelope from EEG using the VLAAI deep neural network

Abstract: To investigate the processing of speech in the brain, commonly simple linear models are used to establish a relationship between brain signals and speech features. However, these linear models are ill-equipped to model a highly-dynamic, complex non-linear system like the brain, and they often require a substantial amount of subject-specific training data. This work introduces a novel speech decoder architecture: the Very Large Augmented Auditory Inference (VLAAI) network. The VLAAI network outperformed state-of-the-art subject-independent models (median Pearson correlation of 0.19, p < 0.001), yielding an increase over the well-established linear model by 52%. Using ablation techniques, we identified the relative importance of each part of the VLAAI network and found that the non-linear components and output context module influenced model performance the most (10% relative performance increase). Subsequently, the VLAAI network was evaluated on a holdout dataset of 26 subjects and a publicly available unseen dataset to test generalization for unseen subjects and stimuli. No significant difference was found between the default test and the holdout subjects, and between the default test set and the public dataset. The VLAAI network also significantly outperformed all baseline models on the public dataset. We evaluated the effect of training set size by training the VLAAI network on data from 1 up to 80 subjects and evaluated on 26 holdout subjects, revealing a relationship following a hyperbolic tangent function between the number of subjects in the training set and the performance on unseen subjects. Finally, the subject-independent VLAAI network was finetuned for 26 holdout subjects to obtain subject-specific VLAAI models. With 5 minutes of data or more, a significant performance improvement was found, up to 34% (from 0.18 to 0.25 median Pearson correlation) with regards to the subject-independent VLAAI network.

Disruption of day‐to‐night changes in circadian gene expression with chronic tendinopathy

Abstract: Overuse injury in tendon tissue (tendinopathy) is a frequent and costly musculoskeletal disorder and represents a major clinical problem with unsolved pathogenesis. Studies in mice have demonstrated that circadian clock-controlled genes are vital for protein homeostasis and important in the development of tendinopathy. We performed RNA sequencing, collagen content and ultrastructural analyses on human tendon biopsies obtained 12 h apart in healthy individuals to establish whether human tendon is a peripheral clock tissue and we performed RNA sequencing on patients with chronic tendinopathy to examine the expression of circadian clock genes in tendinopathic tissues. We found time-dependent expression of 280 RNAs including 11 conserved circadian clock genes in healthy tendons and markedly fewer (23) differential RNAs with chronic tendinopathy. Further, the expression of COL1A1 and COL1A2 was reduced at night but was not circadian rhythmic in synchronised human tenocyte cultures. In conclusion, day-to-night changes in gene expression in healthy human patellar tendons indicate a conserved circadian clock as well as the existence of a night reduction in collagen I expression. KEY POINTS: Tendinopathy is a major clinical problem with unsolved pathogenesis. Previous work in mice has shown that a robust circadian rhythm is required for collagen homeostasis in tendons. The use of circadian medicine in the diagnosis and treatment of tendinopathy has been stifled by the lack of studies on human tissue. Here, we establish that the expression of circadian clock genes in human tendons is time dependent, and now we have data to corroborate that circadian output is reduced in diseased tendon tissues. We consider our findings to be of significance in advancing the use of the tendon circadian clock as a therapeutic target or preclinical biomarker for tendinopathy.

Insulin resistance in patients with cancer: a systematic review and meta-analysis

Abstract: Background Insulin resistance is a critical cause of metabolic dysfunctions. Metabolic dysfunction is common in patients with cancer and is associated with higher cancer recurrence rates and reduced overall survival. Yet, insulin resistance is rarely considered in the clinic and thus it is uncertain how frequently this condition occurs in patients with cancer.Methods To address this knowledge gap, we performed a systematic review and a meta-analysis guided by the Preferred Items for Systematic Review and Meta-Analyses (PRISMA) statement. We included studies assessing insulin resistance in patients with various cancer diagnoses, using the gold-standard hyperinsulinemic–euglycemic clamp method. Studies eligible for inclusion were as follows: (1) included cancer patients older than 18 years of age; (2) included an age-matched control group consisting of individuals without cancer or other types of neoplasms; (3) measured insulin sensitivity using the hyperinsulinemic–euglycemic clamp method. We searched the databases MEDLINE, Embase, and Cochrane Central Register of Controlled Trials for articles published from database inception through March 2023 with no language restriction, supplemented by backward and forward citation searching. Bias was assessed using funnel plot.Findings Fifteen studies satisfied the criteria. The mean insulin-stimulated rate of glucose disposal (Rd) was 7.5 mg/kg/min in control subjects (n = 154), and 4.7 mg/kg/min in patients with a cancer diagnosis (n = 187). Thus, the Rd mean difference was −2.61 mg/kg/min [95% confidence interval, −3.04; −2.19], p<.01). Heterogeneity among the included studies was insignificant (p=.24).Interpretation These findings suggest that patients with a cancer diagnosis are markedly insulin resistant. As metabolic dysfunction in patients with cancer associates with increased recurrence and reduced overall survival, future studies should address if ameliorating insulin resistance in this population can improve these outcomes thereby improving patient care.Key pointsMetabolic dysfunction increases cancer recurrence rates and reduces survival for patients with cancer.Insulin resistance is a critical cause of metabolic dysfunctions.To date, no comprehensive compilation of research investigating insulin resistance in cancer patients has been produced.In this meta-analysis, we found that patients with various cancers were markedly insulin-resistant.

Risk of Type 1 Diabetes in Children Is Not Increased After SARS-CoV-2 Infection: A Nationwide Prospective Study in Denmark

Abstract: OBJECTIVE It has been hypothesized that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children can increase risk of developing type 1 diabetes. RESEARCH DESIGN AND METHODS We undertook a prospective, register-based analysis of children in Denmark by investigating the association between SARS-CoV-2 infection and subsequent risk of type 1 diabetes. During the pandemic, Denmark had one of the highest test rates per capita in the world, and 90% of all Danish children were tested. RESULTS Compared with children with a history of only negative SARS-CoV-2 tests, we did not observe a higher risk of first-time diagnosis of type 1 diabetes in children 30 days or more after a positive SARS-CoV-2 test (hazard ratio 0.85; 95% CI 0.70–1.04). CONCLUSIONS Our data do not support that SARS-CoV-2 infection is associated with type 1 diabetes or that type 1 diabetes should be a special focus after a SARS-CoV-2 infection in children.

Commissioning of the novel Continuous Angle Multi-energy Analysis spectrometer at the Paul Scherrer Institut

Abstract: We report on the commissioning results of the cold neutron multiplexing secondary spectrometer CAMEA (\textbf{C}ontinuous \textbf{A}ngle \textbf{M}ulti-\textbf{E}nergy \textbf{A}nalysis) at the Swiss Spallation Neutron Source (SINQ) at the Paul Scherrer Institut, Switzerland. CAMEA is optimized for an efficient data acquisition of scattered neutrons in the horizontal scattering plane, allowing for detailed and rapid mapping of low-energy excitations under extreme sample environment conditions.

Non-Hermitian Hamiltonian deformations in quantum mechanics

Abstract: A bstract The construction of exactly-solvable models has recently been advanced by considering integrable $$ T\overline{T} $$ T T ¯ deformations and related Hamiltonian deformations in quantum mechanics. We introduce a broader class of non-Hermitian Hamiltonian deformations in a nonrelativistic setting, to account for the description of a large class of open quantum systems, which includes, e.g., arbitrary Markovian evolutions conditioned to the absence of quantum jumps. We relate the time evolution operator and the time-evolving density matrix in the undeformed and deformed theories in terms of integral transforms with a specific kernel. Non-Hermitian Hamiltonian deformations naturally arise in the description of energy diffusion that emerges in quantum systems from time-keeping errors in a real clock used to track time evolution. We show that the latter can be related to an inverse $$ T\overline{T} $$ T T ¯ deformation with a purely imaginary deformation parameter. In this case, the integral transforms take a particularly simple form when the initial state is a coherent Gibbs state or a thermofield double state, as we illustrate by characterizing the purity, Rényi entropies, logarithmic negativity, and the spectral form factor. As the dissipative evolution of a quantum system can be conveniently described in Liouville space, we further study the spectral properties of the Liouvillians, i.e., the dynamical generators associated with the deformed theories. As an application, we discuss the interplay between decoherence and quantum chaos in non-Hermitian deformations of random matrix Hamiltonians and the Sachdev-Ye-Kitaev model.

Loss of <i>Adgra3</i> causes obstructive azoospermia with high penetrance in male mice

Abstract: The adhesion receptor ADGRA3 (GPR125) is a known spermatogonial stem cell marker, but its impact on male reproduction and fertility has not been examined. Using a mouse model lacking Adgra3 (Adgra3-/- ), we show that 55% of the male mice are infertile from puberty despite having normal spermatogenesis and epididymal sperm count. Instead, male mice lacking Adgra3 exhibited decreased estrogen receptor alpha expression and transient dilation of the epididymis. Combined with an increased estradiol production, this indicates a post-pubertal hormonal imbalance and fluid retention. Dye injection revealed a blockage between the ejaculatory duct and the urethra, which is rare in mice suffering from infertility, thereby mimicking the etiologies of obstructive azoospermia found in human male infertility. To summarize, male reproductive tract development is dependent on ADGRA3 function that in concert with estrogen signaling may influence fluid handling during sperm maturation and storage.

Classification of aluminum scrap by laser induced breakdown spectroscopy (LIBS) and RGB + D image fusion using deep learning approaches

Abstract: Integrating multi-sensor systems to sort and monitor complex waste streams is one of the most recent innovations in the recycling industry. The complementary strengths of Laser-Induced Breakdown Spectroscopy (LIBS) and computer vision systems offer a novel multi-sensor solution for the complex task of sorting aluminum (Al) post-consumer scrap into alloy groups. This study presents two novel methods for fusing RGB and Depth images with LIBS using Deep Learning models. The first method is a single-output model that combines LIBS UNET and two DenseNets in a late fusion framework. The second method is a multiple-output model that uses the structure of the single-output model to enhance learning and avoid overfitting. In particular, the network has two outputs that enable the regularization of the individual sensors. A data set of 773 aluminum scrap pieces was created with two sets of ground truth-values, corresponding to the two envisaged sorting tasks, to train and evaluate the developed models. The first sorting task is separating Cast and Wrought (C&W) aluminum. The second is the division of the post-consumer aluminum scrap into three commercially interesting fractions. The single-output model performs best for separating C&W, with a Precision, Recall, and F1-score of 99%. The multiple-output model performs best for classifying the three selected commercial fractions, with a Precision, Recall, and F-score of 86%, 83%, and 84%, respectively. The presented data fusion method for LIBS and computer vision images encompasses the great potential for sorting post-consumer aluminum scrap. By sorting mixed post-consumer aluminum scrap in alloy groups, more wrought-to-wrought recycling can occur, and quality losses can be mitigated during recycling.

Close, but not too close: a mesoscopic description of (a)symmetry and membrane shaping mechanisms

Abstract: Biomembranes are fundamental to our understanding of the cell, the basic building block of all life. An intriguing aspect of membranes is their ability to assume a variety of shapes, which is crucial for cell function. Here, we review various membrane shaping mechanisms with special focus on the current understanding of how local curvature and local rigidity induced by membrane proteins leads to emerging forces and consequently large-scale membrane deformations. We also argue that describing the interaction of rigid proteins with membranes purely in terms of local membrane curvature is incomplete and that changes in the membrane rigidity moduli must also be considered.

On the Justified Use of AI Decision Support in Evidence-Based Medicine: Validity, Explainability, and Responsibility

Abstract: When is it justified to use opaque artificial intelligence (AI) output in medical decision-making? Consideration of this question is of central importance for the responsible use of opaque machine learning (ML) models, which have been shown to produce accurate and reliable diagnoses, prognoses, and treatment suggestions in medicine. In this article, I discuss the merits of two answers to the question. According to the Explanation View, clinicians must have access to an explanation of why an output was produced. According to the Validation View, it is sufficient that the AI system has been validated using established standards for safety and reliability. I defend the Explanation View against two lines of criticism, and I argue that within the framework of evidence-based medicine mere validation seems insufficient for the use of AI output. I end by characterizing the epistemic responsibility of clinicians and point out how a mere AI output cannot in itself ground a practical conclusion about what to do.

The dawn of the functional genomics era in muscle physiology

Abstract: Skeletal muscle is the most abundant component of the mature mammalian phenotype. Designed to generate contractile force and movement, skeletal muscle is crucial for organism health, function and development. One of the great interests for muscle biologists is in understanding how skeletal muscle adapts during periods of stress and stimuli, such as disease, disuse and ageing. To this end, genomic-based experimental and analytical approaches offer one of the most powerful approaches for comprehensively mapping the molecular paradigms that regulate skeletal muscle. With the power, applicability, and robustness of 'omic' technologies continually being developed, we are now in a position to investigate these molecular mechanisms in skeletal muscle to an unprecedented level of accuracy and precision, heralding the dawn of a new era of functional genomics in the field of muscle physiology.

Eye-tracking methodology in research on visual politics

Abstract: Chapter 3: Scholars interested in the perception and impact of visual political information are increasingly applying eye-tracking methodology to understand how (and why) citizens allocate attention to political content. Today's modern media environment presents individuals with an unmanageable amount of stimuli; in order to understand the effects of mediated messages for politically relevant behaviour, scholars require insights into the conditions and processes that affect the amount of visual attention that citizens devote to these stimuli. Eye-tracking methodology, although often time- and cost-intensive in implementation, can be of great value in this context. This chapter provides a brief overview on the physiological background of eye-movements and their measurement and discusses their application in research. It further outlines the most common independent and dependent variables used in eye-tracking studies on visual politics and presents recent findings from state-of-the-art methodological designs. Two case studies highlight the opportunities and challenges associated with the method, and the chapter concludes with a discussion on possible directions for future research.

Chemical and visual characterisation of EGRIP glacial ice and cloudy bands within

Abstract: Abstract. Impurities in polar ice play a critical role in ice flow, deformation, and the integrity of the ice core record. Especially cloudy bands, visible layers with high impurity concentrations are prominent features in ice from the last glacial. Their physical and chemical properties are poorly understood, highlighting the need to analyse them in more detail. We bridge the gap between decimetre and micrometre scales by combining the visual stratigraphy line scanner, fabric analyser, microstructure mapping, Raman spectroscopy, and laser ablation inductively coupled plasma mass spectrometry 2D impurity imaging. We classified almost 1300 cloudy bands from glacial ice from the East Greenland Ice-core Project (EGRIP) ice core into seven different types. We determine the localisation and mineralogy of more than 1000 micro-inclusions at 13 depths. The majority of the found minerals are related to terrestrial dust, such as quartz, feldspar, mica, and hematite. We further found carbonaceous particles, dolomite, and gypsum in high abundance. Rare minerals are e.g., rutile, anatase, epidote, titanite, and grossular. 2D impurity imaging with 20 μm resolution revealed that Na, Mg and Sr are mainly at grain boundaries. Dust-related analytes, such as Al, Fe, and Ti, are also located in the grain interior forming clusters of insoluble impurities. Cloudy bands are thus clearly distinguishable in the chemical data. We present novel vast micron-resolution insights into cloudy bands and describe the differences within and outside these bands. Combining the visual and chemical data results in new insights into the formation of different cloudy band types and could be the starting point for future in-depth studies on impurity signal integrity and internal deformation.

Can remnant cholesterol (triglyceride-rich lipoproteins) reclassify estimated risk of atherosclerotic cardiovascular disease?

Abstract: To summarize recent studies analyzing reclassification of estimated risk of myocardial infarction (MI) and ischemic heart disease (IHD) by inclusion of remnant cholesterol (= cholesterol content in triglyceride-rich lipoproteins) in primary and secondary prevention settings.For individuals in a primary prevention setting with remnant cholesterol levels at least 95th percentile (≥1.6 mmol/l, 61 mg/dl), 23% of MI and 21% of IHD events developed later were reclassified correctly from below to above 5% for 10-year occurrence when remnant cholesterol levels were added to models based on conventional risk factors, whereas no events were reclassified incorrectly. Overall improved reclassification of MI was also observed for remnant cholesterol levels as low as at least 50th percentile (≥0.6 mmol/l, 25 mg/dl); however, the addition of remnant cholesterol over the entire concentration range yielded insignificant improvements of NRI for MI but slightly improved reclassification of NRI for IHD. In a secondary prevention setting, addition of remnant cholesterol over the entire concentration range to a conventional risk model improved reclassification.Elevated remnant cholesterol levels considerably improves reclassification of individuals who later develop MI and IHD, in primary as well as in secondary prevention settings.

Information, involvement, self-care and support—The needs of caregivers of people with stroke: A grounded theory approach

Abstract: Background Globally, stroke is a leading cause of death and disability, with most care undertaken by caregivers who are generally family and friends without prior experience of care. The lack of experience or unpreparedness results in feelings of uncertainty, burnout, anxiety, burden, etc. Hence, it is necessary to identify the needs of caregivers to better support them in their caregiving journey and improve the quality of care delivered. Methods The study employed a grounded theory methodology that utilizes information gathered from literature reviews and social media to represent the needs and create a storyline visually. The storyline is further refined and evaluated using an online survey of 72 participants recruited through online stroke caregiving communities. Results The study identified four core categories of needs: (i) Information: sufficient information delivered in layman’s terms based on the individual situation of the caregiver and survivor through oral and hands-on demonstrations, (ii) Involvement: inclusion in the decision-making processes at different stages of recovery through face-to-face communication at the hospital, (iii) Self-care: ability to engage in work and leisure activities, (iv) Support: receive support in the form of resources, services and finances from different other stakeholders. Conclusions There is a need to create a caregiver-centered approach in stroke recovery to ensure limited obstruction to care and reduced uncertainty in stroke recovery. Moreover, through the inclusion of caregivers in stroke recovery, it may be possible to reduce the burden of care to the caregiver and ensure the satisfaction of the healthcare system throughout stroke recovery.

Optimal investment strategies for asset-liability management with affine diffusion factor processes and HARA preferences

Abstract: This paper investigates an optimal asset-liability management problem within the expected utility maximization framework. The general hyperbolic absolute risk aversion (HARA) utility is adopted to describe the risk preference of the asset-liability manager. The financial market comprises a risk-free asset and a risky asset. The market price of risk depends on an affine diffusion factor process, which includes, but is not limited to, the constant elasticity of variance (CEV), Stein-Stein, Schöbel and Zhu, Heston, 3/2, 4/2 models, and some non-Markovian models, as exceptional examples. The accumulative liability process is featured by a generalized drifted Brownian motion with possibly unbounded and non-Markovian drift and diffusion coefficients. Due to the sophisticated structure of HARA utility and the non-Markovian framework of the incomplete financial market, a backward stochastic differential equation (BSDE) approach is adopted. By solving a recursively coupled BSDE system, closed-form expressions for both the optimal investment strategy and optimal value function are derived. Moreover, explicit solutions to some particular cases of our model are provided. Finally, numerical examples are presented to illustrate the effect of model parameters on the optimal investment strategies in several particular cases.

Modeling the radiative, thermal and chemical microenvironment of 3D scanned corals

Abstract: Abstract Reef building corals are efficient biological collectors of solar radiation and consist of a thin stratified tissue layer spread over a light scattering calcium carbonate skeleton surface that together construct complex three dimensional (3D) colony structures forming the foundation of coral reefs. They exhibit a vast diversity of structural forms to maximize photosynthesis of their dinoflagellate endosymbionts (Symbiodiniaceae), while simultaneously minimizing photodamage. The symbiosis takes place in the presence of dynamic gradients of light, temperature and chemical species that are affected by the interaction of incident irradiance and water flow with the coral colony. We developed a multiphysics modelling approach to simulate microscale spatial distribution of light, temperature and O 2 in coral fragments with accurate morphology determined by 3D scanning techniques. Model results compared well with spatial measurements of light, O 2 and temperature under similar flow and light conditions. The model enabled us to infer the effect of coral morphology and light scattering in tissue and skeleton on the internal light environment experienced by the endosymbionts, as well as the combined contribution of light, water flow and ciliary movement on O 2 and temperature distributions in the coral. The multiphysics modeling approach is general enough to enable simulation of external and internal light, O 2 and temperature microenvironments in 3D scanned coral species with varying degrees of branching and morphology under different environmental conditions. This approach is also relevant for simulating structure-function relationships in other benthic systems such as photosynthetic biofilms and aquatic plant tissue, and can also be adapted to other sessile organisms such as symbiont-bearing giant clams, ascidians, jellyfish or foraminifera. The model could also be useful in more applied research such as optimization of 3D bioprinted constructs where different designs can be evaluated and optimized.

To Filter or Not to Filter? Impact on Stability of Delay-Difference and Neutral Equations With Multiple Delays

Abstract: For control systems where the closed-loop system description is governed by linear delay-differential equations of neutral type, it is known that stability may be fragile, in the sense of sensitive to infinitesimal perturbations to parameters in the system model or arbitrarily small errors in the implementation of the controller. A natural approach to resolve this problem of ill-posedness and to break down the underlying instability mechanisms, rooted in characteristic roots moving from the left plane to the right one via the point at infinity, consists of including a low-pass filter in the control loop, provided the inclusion preserves stability. Independently of the particular control problem, the addition of a low-pass filter essentially boils down to a “regularization” of delay-difference equations and delay equations of neutral type in terms of parametrized delay equations of retarded type, where the parameter can be interpreted as the inverse of the filter's cut-off frequency. In this paper, the stability properties of these parametrized delay equations are analyzed in a general, multi-delay setting, with focus on the transition to the original delay-difference or neutral equations. It is illustrated that the spectral abscissa may not be continuous at the transition, which may impact stability. Hence, conditions for preservation of stability in terms of a robustified stability indicator called filtered spectral abscissa are presented, for which mathematical characterizations and a computationally tractable expression are provided. The application of a PD controller to a time-delay system with relative degree one is used to motivate the structure of the equations studied throughout the paper, and to explicate the implications of the presented results on control design, discussed in the last section.

Elucidation of the Molecular Mechanism of Bovine Milk γ-Glutamyltransferase Catalyzed Formation of γ-Glutamyl-Valyl-Glycine

Abstract: γ-Glu-Val-Gly (γ-EVG) is a potent kokumi peptide that can be synthesized through the transpeptidase reaction catalyzed by γ-glutamyl transferase from bovine milk (BoGGT). To explore the molecular mechanism between BoGGT and l-glutamine, γ-glutamyl peptides were generated through the transpeptidase reaction catalyzed by BoGGT at various reaction conditions. Quantitation of γ-glutamyl peptides, structure prediction of BoGGT, molecular docking, and molecular dynamic simulations were performed. Membrane-free BoGGT had a higher transpeptidase activity with Val-Gly as an acceptor than membrane BoGGT. The suitable conditions for γ-EVG production using BoGGT were 100 mM Val-Gly, 20 mM Gln, 1.2 U/mL BoGGT, pH 8.5, and 37 °C, and 13.1 mM γ-EVG was produced. The hydrogen bonds are mainly formed between residues from the light subunit of BoGGT (Thr380, Thr398, Ser450, Ser451, Met452, and Gly473) and the l-glutamine donor. NaCl might inhibit the transpeptidase activity by destroying the hydrogen bonds between BoGGT and l-glutamine, thereby increasing the distance between the hydroxyl oxygen atom on Thr380 of BoGGT and the amide carbon atom on l-glutamine.

A Tractable Class of Multivariate Phase-Type Distributions for Loss Modeling

Abstract: Phase-type (PH) distributions are a popular tool for the analysis of univariate risks in numerous actuarial applications. Their multivariate counterparts (MPH∗), however, have not seen such a proliferation because of a lack of explicit formulas and complicated estimation procedures. A simple construction of multivariate phase-type distributions––mPH––is proposed for the parametric description of multivariate risks, leading to models of considerable probabilistic flexibility and statistical tractability. The main idea is to start different Markov processes at the same state and allow them to evolve independently thereafter, leading to dependent absorption times. By dimension augmentation arguments, this construction can be cast under the umbrella of MPH∗ class but enjoys explicit formulas that the general specification lacks, including common measures of dependence. Moreover, it is shown that the class is still rich enough to be dense on the set of multivariate risks supported on the positive orthant, and it is the smallest known subclass to have this property. In particular, the latter result provides a new short proof of the denseness of the MPH∗ class. In practice, this means that the mPH class allows for the modeling of bivariate risks with any given correlation or copula. We derive an expectation-maximization algorithm for its statistical estimation and illustrate it on bivariate insurance data. Extensions to more general settings are outlined.

Neutrophil gelatinase‐associated lipocalin ( <scp>NGAL</scp> ) as a potential biomarker for Equine Asthma

Abstract: Background Studies in people have found neutrophil gelatinase-associated lipocalin (NGAL) concentrations are increased in asthma and can be used to distinguish between asthma sub-types. Neutrophil gelatinase-associated lipocalin has not yet been investigated in equine asthma (EA). Objectives To investigate the ability of NGAL concentrations in bronchoalveolar lavage (BAL) fluid and serum to distinguish between control horses, horses with mild-moderate EA (MEA) and horses with severe EA (SEA). Study design Retrospective cross-sectional study. Methods Details of endoscopic examination including tracheal mucus score (TMS, scale 0-5) and BAL cytology performed on 227 horses were extracted from records and NGAL concentrations were measured on stored serum and BAL fluid samples. The horses were divided into groups (control group n=73, MEA n=98, SEA n=56) based on clinical signs and BAL cytology results. Differences between groups were evaluated with the Mann-Whitney test and correlation between BAL NGAL, serum NGAL and BAL cytology were evaluated using Spearman´s correlation. Results BAL NGAL concentrations were higher in EA than in control horses (median: 25.6 μg/L and 13.3 μg/L, respectively, p<0.001). Concentrations of NGAL in BAL differed between groups, with higher concentrations in MEA than in control horses (median: 18.5 μg/L and 13.3 μg/L, respectively, p<0.001), and higher concentrations in SEA than in MEA horses (median: 54.1 μg/L and 18.5 μg/L, respectively, p<0.001). BAL NGAL concentration differed between horses with TMS ≤2 and >2 (median 15.6 and 21.1 μg/L respectively, p = 0.004). No differences were found in serum NGAL concentration between any of the groups. Main limitation Only 66 of the 227 (29 %) horses had haematology and serum NGAL measured. Conclusion BAL NGAL concentration differed between control and EA and reflected severity of disease. These results justify further research into the potential of NGAL as a biomarker of EA.