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Families of mixtures of multivariate power exponential (MPE) distributions have already been introduced and shown to be competitive for cluster analysis in comparison to other mixtures of elliptical distributions, including mixtures of Gaussian distributions. A family of mixtures of multivariate skewed power exponential distributions is proposed that combines the flexibility of the MPE distribution with the ability to model skewness. These mixtures are more robust to variations from normality and can account for skewness, varying tail weight, and peakedness of data. A generalized expectation-maximization approach, which combines minorization-maximization and optimization based on accelerated line search algorithms on the Stiefel manifold, is used for parameter estimation. These mixtures are implemented both in the unsupervised and semi-supervised classification frameworks. Both simulated and real data are used for illustration and comparison to other mixture families. [ABSTRACT FROM AUTHOR]

In children, digital media, lifestyle, and the COVID pandemic have impacted sunlight exposure, exercise, and diet patterns - cues that entrain the circadian clock. We hypothesized that low morning cortisol reflects a weak circadian clock, impacting the pro-inflammatory state. The primary objective was to test relationships between diurnal cortisol fluctuations and the inflammatory state in children as a means of providing indirect support for this hypothesis. The Cardiovascular Health Intervention Program (CHIP) was a population-based cross-sectional and longitudinal study of circadian health in public elementary school children in Southern Maine, USA (recruitment period 2012–2017). Participants were 689 students in 4th grade (baseline; age=9.2 ± 0.4 years), and 647 students in 5th grade (age=10.5 ± 0.5 years). Nine salivary cortisol measures per child (2 awakening and 1 prior to bed for 3 sequential days) (n = 1336 child phenotype days; n = 7987 cortisol assays), 10 cytokines measured in morning and evening saliva samples (n = 202 child phenotype days), and lipids were measured. Clinical outcomes were blood pressure, weight and height (body mass index [BMI]; BMI = kg/m2), among others. Upon-waking cortisol levels were 0.28 ± 0.13 µg/dL, 30-minute post-waking 0.33 ± 0.15 µg/dL, and evening 0.08 ± 0.10 µg/dL. Salivary cytokine levels (n = 202) showed interleukins (IL) IL-1β and IL-8 were highest in early morning (upon awakening; AM), and IL-6 and tumor necrosis factor (TNF) TNF-α highest before bed (PM) (IL-1β AM > PM [−4.02 fold; p < 0.001]; IL-8 AM > PM [−1.36 fold; p < 0.001]; IL-6 AM < PM [+1.49 fold; p < 0.001]; TNF-α AM < PM [+1.73 fold; p = 0.03]. Regression modeling showed high morning cortisol was associated with high morning IL-1β (p = 3.82 ×10−6), but low evening IL-1β (p = 6.27 ×10−4). Regression modeling of BMI z-score as the response variable showed the expected significant relationships to high density lipoprotein (HDL) (negative; p < 0.001), mean arterial pressure (positive; p < 0.001), and morning cortisol (negative; p = 0.01) but only weak relationships to either evening cortisol (p = 0.1) or cytokine (positive; p = 0.02; from the model with smallest Rsquared) levels. We provide preliminary data on diurnal fluctuations of inflammatory cytokines in saliva in a population-based cohort of children. Correlation of morning and evening cortisol levels with inflammatory cytokines in the same saliva samples showed that high morning cortisol was associated with high morning IL-1β and low evening IL-1β. Future studies may test the hypothesis that strong diurnal cycling of IL-1β may serve as a homeostatic mechanism keeping the immune system in check, and that low morning cortisol (possible circadian misalignment) may lead to less stringent control of inflammatory networks. • First population-based study in school children, exploring associations of circadian misalignment with inflammatory cytokines. • Utilized metabolic syndrome measures and cortisol to determine pro-inflammatory factor relationships in children. • Explored the potential of non-invasive biofluid, saliva in biomarker research • Findings suggest strong correlation between cortisol rhythm and pro-inflammatory conditions in children. • Cortisol dysregulation might be linked with higher incidences of cardiovascular diseases and allergies in adulthood. [ABSTRACT FROM AUTHOR]

Whole genome duplication (WGD), the doubling of the nuclear DNA of a species, contributes to biological innovation by creating genetic redundancy. One mode of WGD is allopolyploidization, wherein each genome from two ancestral species becomes a 'subgenome' of a polyploid descendant species. The evolutionary trajectory of a duplicated gene that arises from WGD is influenced both by natural selection that may favour redundant, new or partitioned functions, and by gene silencing (pseudogenization). Here, we explored how these two phenomena varied over time and within allopolyploid genomes in several allotetraploid clawed frog species (Xenopus). Our analysis demonstrates that, across these polyploid genomes, purifying selection was greatly relaxed compared to a diploid outgroup, was asymmetric between each subgenome, and that coding regions are shorter in the subgenome with more relaxed purifying selection. As well, we found that the rate of gene loss was higher in the subgenome under weaker purifying selection and that this rate has remained relatively consistent over time after WGD. Our findings provide perspective from recently evolved vertebrates on the evolutionary forces that likely shape allopolyploid genomes on other branches of the tree of life. [ABSTRACT FROM AUTHOR]

A family of parsimonious Gaussian cluster-weighted models is presented. This family concerns a multivariate extension to cluster-weighted modelling that can account for correlations between multivariate responses. Parsimony is attained by constraining parts of an eigen-decomposition imposed on the component covariance matrices. A sufficient condition for identifiability is provided and an expectation-maximization algorithm is presented for parameter estimation. Model performance is investigated on both synthetic and classical real data sets and compared with some popular approaches. Finally, accounting for linear dependencies in the presence of a linear regression structure is shown to offer better performance, vis-à-vis clustering, over existing methodologies. [ABSTRACT FROM AUTHOR]

Lateral gene transfer is an important mechanism for evolution among bacteria. Here, genome-wide gene insertion and deletion rates are modeled in a maximum-likelihood framework with the additional flexibility of modeling potential missing data. The performance of the models is illustrated using simulations and a data set on gene family phyletic patterns from Gardnerella vaginalis that includes an ancient taxon. A novel application involving pseudogenization/genome reduction magnitudes is also illustrated, using gene family data from Mycobacterium spp. Finally, an R package called indelmiss is available from the Comprehensive R Archive Network at https://cran.r-project.org/package=indelmiss, with support documentation and examples. [ABSTRACT FROM AUTHOR]

An expanded family of mixtures of multivariate power exponential distributions is introduced. While fitting heavy-tails and skewness have received much attention in the model-based clustering literature recently, we investigate the use of a distribution that can deal with both varying tail-weight and peakedness of data. A family of parsimonious models is proposed using an eigen-decomposition of the scale matrix. A generalized expectation-maximization algorithm is presented that combines convex optimization via a minorization-maximization approach and optimization based on accelerated line search algorithms on the Stiefel manifold. Lastly, the utility of this family of models is illustrated using both toy and benchmark data. [ABSTRACT FROM AUTHOR]

Vaccination can delay the peak of a pandemic influenza wave by reducing the number of individuals initially susceptible to influenza infection. Emerging evidence indicates that susceptibility to severe secondary bacterial infections following a primary influenza infection may vary seasonally, with peak susceptibility occurring in winter. Taken together, these two observations suggest that vaccinating to prevent a fall pandemic wave might delay it long enough to inadvertently increase influenza infections in winter, when primary influenza infection is more likely to cause severe outcomes. This could potentially cause a net increase in severe outcomes. Most pandemic models implicitly assume that the probability of severe outcomes does not vary seasonally and hence cannot capture this effect. Here we show that the probability of intensive care unit (ICU) admission per influenza infection in the 2009 H1N1 pandemic followed a seasonal pattern. We combine this with an influenza transmission model to investigate conditions under which a vaccination program could inadvertently shift influenza susceptibility to months where the risk of ICU admission due to influenza is higher. We find that vaccination in advance of a fall pandemic wave can actually increase the number of ICU admissions in situations where antigenic drift is sufficiently rapid or where importation of a cross-reactive strain is possible. Moreover, this effect is stronger for vaccination programs that prevent more primary influenza infections. Sensitivity analysis indicates several mechanisms that may cause this effect. We also find that the predicted number of ICU admissions changes dramatically depending on whether the probability of ICU admission varies seasonally, or whether it is held constant. These results suggest that pandemic planning should explore the potential interactions between seasonally varying susceptibility to severe influenza outcomes and the timing of vaccine-altered pandemic influenza waves. [ABSTRACT FROM AUTHOR]

Abstract: Birth rates have been declining in higher-income countries since the middle of the 19th century. A growing number of other countries have entered this demographic transition to lower fertility, as socioeconomic development continues. Analyses of this demographic transition vary widely, but most analyze individual populations in isolation from others, and most come from fields outside the biological sciences. Here, we develop a population biological model of population dynamics in higher-income countries. Individual countries evolve through density-regulated growth, where gradual evolution toward higher population densities boosts productivity (and hence socioeconomic growth) through economics of agglomeration and scale, in turn reducing birth rates. The exchange of technology and capital between countries can further boost productivity gains in any given country, thus contributing to its demographic transition. As a result, countries can down-regulate one another''s population growth through mutual improvements in productivity. The model is fitted to time series data on population size, GDP per capita, and birth rates for the United States, the United Kingdom, and France. The metapopulation dynamics are also characterized across a range of parameter values close to the fitted values. This work may help advance population biological approaches to understanding the implications of the fertility demographic transition for modern human populations. This is relevant to developing long-term predictions of the earth''s total population size, which must be based upon a model that incorporates underlying mechanisms. [Copyright &y& Elsevier]

Continuous-time Markov chain models with finite state space are routinely used for analysis of discrete character data on phylogenetic trees. Examples of such discrete character data include restriction sites, gene family presence/absence, intron presence/absence and gene family size data. While models with constrained substitution rate matrices have been used to good effect, more biologically realistic models have been increasingly implemented in the recent literature combining, e.g., site rate variation, site partitioning, branch-specific rates, allowing for nonstationary prior root probabilities, correcting for sampling bias, etc. to name a few. Here, a flexible and fast R package is introduced that infers evolutionary rates of discrete characters on a tree within a probabilistic framework. The package, markophylo, fits maximum-likelihood models using Markov chains on phylogenetic trees. The package is efficient, with the workhorse functions written in C++ and the interface in user-friendly R. [ABSTRACT FROM AUTHOR]

Human genetic variation (polymorphisms) in genes coding proteins involved in the absorption, distribution, metabolism, and elimination (ADME) of drugs can have a strong effect on drug exposure and downstream efficacy and safety outcomes. Vamorolone, a dissociative steroidal anti‐inflammatory drug for treating Duchenne muscular dystrophy (DMD), primarily undergoes oxidation by CYP3A4 and CYP3A5 and glucuronidation by UDP‐glucuronosyltransferases. This work assesses the pharmacokinetics (PKs) of vamorolone and sources of interindividual variability (IIV) in 81 steroid‐naïve boys with DMD aged 4 to <7 years old considering the genetic polymorphisms of CYPS3A4 (CYP3A4*22, CYP3A4*1B), CYP3A5 (CYP3A5*3), and UGT1A1 (UGT1A1*60) utilizing population PK modeling. A one‐compartment model with zero‐order absorption (Tk0, duration of absorption), linear clearance (CL/F), and volume (V/F) describes the plasma PK data for boys with DMD receiving a wide range of vamorolone doses (0.25–6 mg/kg/day). The typical CL/F and V/F values of vamorolone were 35.8 L/h and 119 L, with modest IIV. The population Tk0 was 3.14 h yielding an average zero‐order absorption rate (k0) of 1.16 mg/kg/h with similar absorption kinetics across subjects at the same vamorolone dose (i.e., no IIV on Tk0). The covariate analysis showed that none of the genetic covariates had any significant impact on the PKs of vamorolone in boys with DMD. Thus, the PKs of vamorolone is very consistent in these young boys with DMD. [ABSTRACT FROM AUTHOR]

Duchenne muscular dystrophy is initiated by dystrophin deficiency, but downstream pathophysiological pathways such as membrane instability, NFĸB activation, mitochondrial dysfunction, and induction of TGFβ fibrosis pathways are thought to drive the disability. Dystrophin replacement strategies are hopeful for addressing upstream dystrophin deficiency; however, all methods to date use semi-functional dystrophin proteins that are likely to trigger downstream pathways. Thus, combination therapies that can target multiple downstream pathways are important in treating DMD, even for dystrophin-replacement strategies. We sought to define blood pharmacodynamic biomarkers of drug response in the mdx mouse model of Duchenne muscular dystrophy using a series of repurposed drugs. Four-week-old mdx mice were treated for four weeks with four different drugs singly and in combination: vehicle, prednisolone, vamorolone, rituximab, β-aminoisobutyric acid (BAIBA) (11 treatment groups; n = 6/group). Blood was collected via cardiac puncture at study termination, and proteomic profiling was carried out using SOMAscan aptamer panels (1,310 proteins assayed). Prednisolone was tested alone and in combination with other drugs. It was found to have a good concordance of prednisolone-responsive biomarkers (56 increased by prednisolone, 39 decreased) focused on NFκB and TGFβ cascades. Vamorolone shared 45 (80%) of increased biomarkers and 13 (33%) of decreased biomarkers with prednisolone. Comparison of published human corticosteroid-responsive biomarkers to our mdx data showed 14% (3/22) concordance between mouse and human. Rituximab showed fewer drug-associated biomarkers, with the most significant being human IgG. On the other hand, BAIBA treatment (high and low dose) showed a drug-associated increase in 40 serum proteins and decreased 5 serum proteins. Our results suggest that a biomarker approach could be employed for assessing drug combinations in both mouse and human studies. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer-related death in the Unites States, and approximately 85% of all lung cancers are classified as non-small cell lung cancer (NSCLC), which is extremely difficult to treat and its survival rate is low. After decades of clinical trials, the most effective treatments are still those that implement the first-generation platinum anticancer agent cisplatin (CDDP) in combination with other drugs. We previously demonstrated that the naturally-occurring compound phenethyl isothiocyanate (PEITC) can be used to sensitize NSCLC cells to CDDP. Furthermore, co-encapsulation of PEITC and CDDP in liposomes enhances their toxicity toward NSCLC cells. We here optimize liposomal-PEITC-CDDP, demonstrate the release of PEITC and CDDP from the nanoparticle, and show that liposomal-PEITC-CDDP is much more toxic toward both A549 and H596 human NSCLC cell lines than toward WI-38 and BEAS-2B human normal lung cell lines. Thus, we have prepared an efficacious therapy that has significantly higher toxicity toward cancer cell lines than normal cell lines. [ABSTRACT FROM AUTHOR]

Highlights • Vancomycin AUC thresholds were assessed using two-point pharmacokinetic monitoring. • AUC thresholds for success and nephrotoxicity were ≥297 mg·h/L and ≥710 mg·h/L. • Rates of clinical failure (18.2%) and nephrotoxicity (13.0%) were low. • These data support evidence to target a vancomycin AUC range of 400–600 mg·h/L. • Adoption of AUC-based vancomycin monitoring may improve safety and efficacy. ABSTRACT Limited evidence exists evaluating pharmacokinetic thresholds for vancomycin efficacy and nephrotoxicity using non-Bayesian methods. The objective of this study was to evaluate the 24-h steady-state vancomycin area under the concentration–time curve (AUC 24) thresholds for efficacy and nephrotoxicity in patients with methicillin-resistant Staphylococcus aureus bacteraemia (MRSA-B) after implementing two-point pharmacokinetic therapeutic drug monitoring. A single-centre, retrospective cohort study was performed including adult patients admitted between 1 June 2016 and 1 January 2018 with MRSA-B treated with vancomycin for ≥72 h. The AUC 24 was calculated using peak and trough vancomycin serum concentrations. Clinical success was defined as defervescence and blood culture sterilisation by Day 7. Nephrotoxicity was defined as an increase in serum creatinine of >0.5 mg/dL (or ≥50%) from baseline. Classification and regression tree (CART) analyses were performed to identify AUC 24 thresholds for efficacy and nephrotoxicity. Forty-six patients were included in the study. Clinical success and nephrotoxicity were observed in 81.8% and 13.0%, respectively. The CART-derived vancomycin AUC 24 thresholds for clinical success and nephrotoxicity were ≥297 mg·h/L and ≥710 mg·h/L, respectively. Patients with an AUC 24 ≥297 mg·h/L had a >2.7-fold increase in clinical success compared with those who did not (89.5% vs. 33.3%, respectively; P = 0.01), and patients with an AUC 24 ≥710 mg·h/L had a >7-fold increase in nephrotoxicity compared with those with an AUC 24 <710 mg·h/L (66.7% vs. 9.3%, respectively; P = 0.04). This study supports current recommendations to target vancomycin AUC 24 values of 400–600 mg·h/L when calculated using two-point pharmacokinetics, although a wider range may exist. [ABSTRACT FROM AUTHOR]

[Display omitted] • Pharmacodynamic biomarkers after a single 0.2 mg/kg dose in volunteers were studied. • Acute serum time series on both circadian day and drug day were analyzed. • Broad suppression of adrenal steroids by 3 h after dosing was shown. • IL-10 was observed to increase while IL-8 decreased. • Beta-2 microglobulin, TNFSF15, TSH, CST3, NBL1 showed time-related decreases. Pharmacological glucocorticoids are the most prescribed anti-inflammatory medications, and are chemical variants of cortisol, the circadian and stress hormone. Both endogenous and pharmacological glucocorticoids bind the glucocorticoid receptor (NR3C1) with high affinity, and both then bind downstream gene promoter elements (GRE) to drive positive gene transcription of many proteins. Glucocorticoid/GR complexes also bind distinct negative gene promoter elements (nGRE) to inhibit expression of genes involved in NF-κB innate immunity signaling. We sought to define the acute response of a single dose of prednisone (0.2 mg/kg) in young adult volunteers, with blood samples taken at baseline, 2, 3, 4 and 6 h post-oral dose. To control for circadian morning cortisol hitting the same molecular pathways, a day of blood draws was done without oral prednisone (same time of day), one day prior to drug day. Serum samples were processed for steroid hormone profiles (mass spectrometry; 9 steroidal hormones), proteomics (SOMAscan aptamer panels, 1,305 proteins), and inflammatory markers (Meso Scale Discovery; 10 pro-inflammatory cytokines). The pharmacological effect of the prednisone dose was shown by significant declines of adrenal steroids by 3 h after dosing. IL-10 showed drug-related increase to 4 hrs, then decrease to 6 hrs. IL-8 showed drug-related decrease in serum by 4 h, consistent with direct negative action of GR/ligand on IL-8 gene promoter. Proteomics data showed beta-2 microglobulin, TNFSF15, TSH, CST3, NBL1 to show time-related decreases with prednisone, while CXCL13 showed increases, although these require validation. In summary, a single low dose of prednisone leads to broad suppression of the adrenal axis within 3 h, and down-regulation of inflammatory serum proteins by 6 h. [ABSTRACT FROM AUTHOR]

Duchenne muscular dystrophy (DMD) is a progressive muscle disease involving complex skeletal muscle pathogenesis. The pathogenesis is triggered by sarcolemma instability due to the lack of dystrophin protein expression, leading to Ca2+ influx, muscle fiber apoptosis, inflammation, muscle necrosis, and fibrosis. Our lab recently used two high-throughput multiplexing techniques (e.g., SomaScan® aptamer assay and tandem mass tag-(TMT) approach) and identified a series of serum protein biomarkers tied to different pathobiochemical pathways. In this study, we focused on validating the circulating levels of three proinflammatory chemokines (CCL2, CXCL10, and CCL18) that are believed to be involved in an early stage of muscle pathogenesis. We used highly specific and reproducible MSD ELISA assays and examined the association of these chemokines with DMD pathogenesis, age, disease severity, and response to glucocorticoid treatment. As expected, we confirmed that these three chemokines were significantly elevated in serum and muscle samples of DMD patients relative to age-matched healthy controls (p-value < 0.05, CCL18 was not significantly altered in muscle samples). These three chemokines were not significantly elevated in Becker muscular dystrophy (BMD) patients, a milder form of dystrophinopathy, when compared in a one-way ANOVA to a control group but remained significantly elevated in the age-matched DMD group (p < 0.05). CCL2 and CCL18 but not CXCL10 declined with age in DMD patients, whereas all three chemokines remained unchanged with age in BMD and controls. Only CCL2 showed significant association with time to climb four steps in the DMD group (r = 0.48, p = 0.038) and neared significant association with patients' reported outcome in the BMD group (r = 0.39, p = 0.058). Furthermore, CCL2 was found to be elevated in a serum of the mdx mouse model of DMD, relative to wild-type mouse model. This study suggests that CCL2 might be a suitable candidate biomarker for follow-up studies to demonstrate its physiological significance and clinical utility in DMD. [ABSTRACT FROM AUTHOR]

Prednisone (Pred) and Deflazacort (Dfz) are commonly used glucocorticoids (GCs) for Duchenne muscular dystrophy (DMD) treatment and management. While GCs are known to delay the loss of ambulation and motor abilities, chronic use can result in onerous side effects, e.g., weight gain, growth stunting, loss of bone density, etc. Here, we use the CINRG Duchenne natural history study to gain insight into comparative safety of Pred versus Dfz treatment through GC-responsive pharmacodynamic (PD) biomarkers. Longitudinal trajectories of SOMAscan® protein data obtained on serum of DMD boys aged 4 to 10 (Pred: n = 7; Dfz: n = 8) were analyzed after accounting for age and time on treatment. Out of the pre-specified biomarkers, seventeen candidate proteins were differentially altered between the two drugs (p < 0.05). These include IGFBP-2 and AGER associated with diabetes complications, and MMP-3 associated with extracellular remodeling. As a follow-up, IGFBP-2, MMP-3, and IGF-I were quantified with an ELISA using a larger sample size of DMD biosamples (Dfz: n = 17, Pred: n = 12; up to 76 sera samples) over a longer treatment duration. MMP-3 and IGFBP-2 validated the SOMAscan® signal, however, IGF-I did not. This study identified GC-responsive biomarkers, some associated with safety, that highlight differential PD response between Dfz and Pred. [ABSTRACT FROM AUTHOR]

Extensive biomarker discoveries for DMD have occurred in the past 7 years, and a vast array of these biomarkers were confirmed in independent cohorts and across different laboratories. In these previous studies, glucocorticoids and age were two major confounding variables. In this new study, using SomaScan technology and focusing on a subset of young DMD patients who were not yet treated with glucocorticoids, we identified 108 elevated and 70 decreased proteins in DMD relative to age matched healthy controls (p value < 0.05 after adjusting for multiple testing). The majority of the elevated proteins were muscle centric followed by cell adhesion, extracellular matrix proteins and a few pro-inflammatory proteins. The majority of decreased proteins were of cell adhesion, however, some had to do with cell differentiation and growth factors. Subsequent treatment of this group of DMD patients with glucocorticoids affected two major groups of pharmacodynamic biomarkers. The first group consisted of 80 serum proteins that were not associated with DMD and either decreased or increased following treatment with glucocorticoids, and therefore were reflective of a broader effect of glucocorticoids. The second group consisted of 17 serum proteins that were associated with DMD and these tended to normalize under treatment, thus reflecting physiologic effects of glucocorticoid treatment in DMD. In summary, we have identified a variety of circulating protein biomarkers that reflect the complex nature of DMD pathogenesis and response to glucocorticoids. [ABSTRACT FROM AUTHOR]