An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases.

Identifying disease-causing variants in Rare Disease patients' genome is a challenging problem. To accomplish this task, we describe a machine learning framework, that we called "Suggested Diagnosis", whose aim is to prioritize genetic variants in an exome/genome based on the probability of being disease-causing. To do so, our method leverages standard guidelines for germline variant interpretation as defined by the American College of Human Genomics (ACMG) and the Association for Molecular Pathology (AMP), inheritance information, phenotypic similarity, and variant quality. Starting from (1) the VCF file containing proband's variants, (2) the list of proband's phenotypes encoded in Human Phenotype Ontology terms, and optionally (3) the information about family members (if available), the "Suggested Diagnosis" ranks all the variants according to their machine learning prediction. This method significantly reduces the number of variants that need to be evaluated by geneticists by pinpointing causative variants in the very first positions of the prioritized list. Most importantly, our approach proved to be among the top performers within the CAGI6 Rare Genome Project Challenge, where it was able to rank the true causative variant among the first positions and, uniquely among all the challenge participants, increased the diagnostic yield of 12.5% by solving 2 undiagnosed cases.

Go beyond the limits of genetic algorithm in daily covariate selection practice.

Covariate identification is an important step in the development of a population pharmacokinetic/pharmacodynamic model. Among the different available approaches, the stepwise covariate model (SCM) is the most used. However, SCM is based on a local search strategy, in which the model-building process iteratively tests the addition or elimination of a single covariate at a time given all the others. This introduces a heuristic to limit the searching space and then the computational complexity, but, at the same time, can lead to a suboptimal solution. The application of genetic algorithms (GAs) for covariate selection has been proposed as a possible solution to overcome these limitations. However, their actual use during model building is limited by the extremely high computational costs and convergence issues, both related to the number of models being tested. In this paper, we proposed a new GA for covariate selection to address these challenges. The GA was first developed on a simulated case study where the heuristics introduced to overcome the limitations affecting currently available GA approaches resulted able to limit the selection of redundant covariates, increase replicability of results and reduce convergence times. Then, we tested the proposed GA on a real-world problem related to remifentanil. It obtained good results both in terms of selected covariates and fitness optimization, outperforming the SCM.

Traumatic sheep myiasis: A review of the current understanding.

Myiasis, or the infestation of live humans and vertebrate animals by dipterous larvae, is a health issue worldwide. The economic impact and potential threat to animal health and wellbeing of this disease under the animal husbandry sector is considerable. Sheep are a highly vulnerable livestock category exposed to myiasis (sheep strike), due to several unique predisposing factors that attract flies. The successful mitigation of this disease relies on a thorough understanding of fly population dynamics associated with the change in weather patterns and the evaluation of this disease through different branches of science such as chemistry, molecular biology, and microbiology. The present review provides a summary of the existing knowledge of strike in sheep, discussed in relation to the application of volatile organic compounds, metagenomics, and molecular biology, and their use regarding implementing fly control strategies such as traps, and to increase the resilience of sheep to this disease through improving their health and wellbeing.

Space Flight-Promoted Insulin Resistance as a Possible Disruptor of Wound Healing.

During space flight, especially when prolonged, exposure to microgravity results in a number of pathophysiological changes such as bone loss, muscle atrophy, cardiovascular and metabolic changes and impaired wound healing, among others. Interestingly, chronic low-grade inflammation and insulin resistance appear to be pivotal events linking many of them. Interestingly, real and experimental microgravity is also associated to altered wound repair, a process that is becoming increasingly important in view of prolonged space flights. The association of insulin resistance and wound healing impairment may be hypothesized from some dysmetabolic conditions, like the metabolic syndrome, type 2 diabetes mellitus and abdominal/visceral obesity, where derangement of glucose and lipid metabolism, greater low-grade inflammation, altered adipokine secretion and adipocyte dysfunction converge to produce systemic effects that also negatively involve wound healing. Indeed, wound healing impairment after traumatic events and surgery in space remains a relevant concern for space agencies. Further studies are required to clarify the molecular connection between insulin resistance and wound healing during space flight, addressing the ability of physical, endocrine/metabolic, and pharmacological countermeasures, as well as nutritional strategies to prevent long-term detrimental effects on tissue repair linked to insulin resistance. Based on these considerations, this paper discusses the pathophysiological links between microgravity-associated insulin resistance and impaired wound healing.

Osteocalcin-expressing endothelial progenitor cells and serum osteocalcin forms are independent biomarkers of coronary atherosclerotic disease severity in male and female patients.

PURPOSE: Osteocalcin (OC), an osteoblast-derived regulator of metabolic processes, and circulating early endothelial progenitor cells (EPC, CD34 - /CD133 + /KDR +) expressing OC (OC +) are potential candidates linking bone metabolism and the vasculature and might be involved in vascular atherosclerotic calcification. This study aimed at assessing the association of circulating levels of different OC forms and of EPCs count with disease severity in patients with documented coronary atherosclerosis (CAD). METHODS: Patients (n = 59) undergoing coronary angiography were divided, according to stenosis severity, into (1) early coronary atherosclerosis (ECA) (n = 22), and (2) late coronary atherosclerosis (LCA) (n = 37). Total OC (TOC), carboxylated OC (cOC), undercarboxylated OC (unOC) were quantified by ELISA. EPC OC + count was assessed by flow cytometry. RESULTS: EPC OC + counts showed significant differences between ECA and LCA groups. unOC and unOC/TOC ratio were inversely correlated with EPC OC + count. A significant decrease in TOC and unOC plasma levels was associated with higher cardiovascular risk factors (CVRFs) number. EPC OC + count was correlated with LDL-C, total cholesterol, and triglycerides, with a greater significance in the LCA group. No association between the different forms of circulating OC (TOC, ucOC, cOC) and severity of CAD was found. CONCLUSION: This study showed a significant association between EPCs (CD34 - /CD133 + /KDR + /OC +), CAD severity and CVRFs, suggesting an active role for EPC OC + in the development of CAD. An inverse correlation between TOC, ucOC, and number of CVRFs was observed, suggesting that OC, regardless of its carboxylation status, may be developed as a further cardiovascular risk biomarker.

A translational model-based approach to inform the choice of the dose in phase 1 oncology trials: the case study of erdafitinib.

PURPOSE: Erdafitinib (JNJ-42756493, BALVERSA) is a tyrosine kinase inhibitor indicated for the treatment of advanced urothelial carcinoma. In this work, a translational model-based approach to inform the choice of the doses in phase 1 trials is illustrated. METHODS: A pharmacokinetic (PK) model was developed to describe the time course of erdafitinib plasma concentrations in mice and rats. Data from multiple xenograft studies in mice and rats were analyzed using the Simeoni tumor growth inhibition (TGI) model. The model parameters were used to derive a range of erdafitinib exposures that might inform the choice of the doses in oncology phase 1 trials. Conversion of exposures to doses was based on preliminary PK assessments from the first-in human (FIH) study. RESULTS: A one-compartment PK disposition model, with linear absorption and dose-dependent clearance, adequately described the PK data in both mice and rats via an allometric scaling approach. The TGI model was able to describe tumor growth dynamics, providing quantitative measurements of erdafitinib antitumor potency in mice and rats. Based on these estimates, ranges of efficacious unbound concentration were identified for erdafitinib in mice (0.642-5.364 µg/L) and rats (0.782-2.565 µg/L). Based on the FIH data, it was possible to transpose exposures into doses and doses of above 4 mg/day provided erdafitinib exposures associated with significant TGI in animals. The findings were in agreement with the results of the FIH trial, in which the first hints of clinical activities were observed at 6 mg. CONCLUSION: The successful modeling exercise of erdafitinib preclinical data showed how translational PK-PD modeling might be a tool to help to inform the choice of the doses in FIH studies.

Feasibility study of hospital antimicrobial stewardship analytics using electronic health records.

BACKGROUND: Hospital antimicrobial stewardship (AMS) programmes are multidisciplinary initiatives to optimize antimicrobial use. Most hospitals depend on time-consuming manual audits to monitor clinicians' prescribing. But much of the information needed could be sourced from electronic health records (EHRs). OBJECTIVES: To develop an informatics methodology to analyse characteristics of hospital AMS practice using routine electronic prescribing and laboratory records. METHODS: Feasibility study using electronic prescribing, laboratory and clinical coding records from adult patients admitted to six specialities at Queen Elizabeth Hospital, Birmingham, UK (September 2017-August 2018). The study involved: (i) a review of AMS standards of care; (ii) their translation into concepts measurable from commonly available EHRs; and (iii) a pilot application in an EHR cohort study (n = 61679 admissions). RESULTS: We developed data modelling methods to characterize antimicrobial use (antimicrobial therapy episode linkage methods, therapy table, therapy changes). Prescriptions were linked into antimicrobial therapy episodes (mean 2.4 prescriptions/episode; mean length of therapy 5.8 days), enabling several actionable findings. For example, 22% of therapy episodes for low-severity community-acquired pneumonia were congruent with prescribing guidelines, with a tendency to use broader-spectrum antibiotics. Analysis of therapy changes revealed IV to oral therapy switching was delayed by an average 3.6 days (95% CI: 3.4-3.7). Microbial cultures were performed prior to treatment initiation in just 22% of antibacterial prescriptions. The proposed methods enabled fine-grained monitoring of AMS practice down to specialities, wards and individual clinical teams by case mix, enabling more meaningful peer comparison. CONCLUSIONS: It is feasible to use hospital EHRs to construct rapid, meaningful measures of prescribing quality with potential to support quality improvement interventions (audit/feedback to prescribers), engagement with front-line clinicians on optimizing prescribing, and AMS impact evaluation studies.

Effect of Type of Tissue on the Development of Chrysomya rufifacies (Diptera: Calliphoridae) in Sri Lanka.

Chrysomya rufifacies (Macquart), the hairy maggot blow fly, is of great importance for the field of forensic entomology due to its habit as an early colonizer of decomposing vertebrate remains and myiasis producer. Development studies on this species have been conducted in scattered regions of the world, using types of tissue from several species of animals as a rearing medium. Despite the commonality of C. rufifacies in Sri Lanka, developmental studies have never been performed in this region. As well, the effects of diet on development have not been tested. In the current study, C. rufifacies immatures were reared on skeletal muscle, liver, and heart from domestic swine, with flies from colonies maintained at 25 and 28°C. The minimum time needed to complete each stage at 25°C on liver (224.14 h) was fastest followed by skeletal muscle (249.33 h) and heart (251.64 h) respectively, whereas at 28°C, fly development was quickest on heart muscle (178.27 h) followed by liver (178.50 h) and skeletal muscle (186.17 h) respectively. A significant difference in total development time was determined for temperature, while the rearing medium was not significant. Temperature also showed a significant effect on the length and the width of the larvae, while the type of tissue statistically impacted only the width.

A Population Dynamic Energy Budget-Based Tumor Growth Inhibition Model for Etoposide Effects on Wistar Rats.

PURPOSE: This work aimed to develop a population PK/PD tumor-in-host model able to describe etoposide effects on both tumor cells and host in Walker-256 tumor-bearing rats. METHODS: Etoposide was investigated on thirty-eight Wistar rats randomized in five arms: two groups of tumor-free animals receiving either placebo or etoposide (10 mg/kg bolus for 4 days) and three groups of tumor-bearing animals receiving either placebo or etoposide (5 or 10 mg/kg bolus for 8 or 4 days, respectively). To analyze experimental data, a tumor-in-host growth inhibition (TGI) model, based on the Dynamic Energy Budget (DEB) theory, was developed. Total plasma and free-interstitial tumor etoposide concentrations were assessed as driver of tumor kinetics. RESULTS: The model simultaneously describes tumor and host growths, etoposide antitumor effect as well as cachexia phenomena related to both the tumor and the drug treatment. The schedule-dependent inhibitory effect of etoposide is also well captured when the intratumoral drug concentration is considered as the driver of the tumor kinetics. CONCLUSIONS: The DEB-based TGI model capabilities, up to now assessed only in mice, are fully confirmed in this study involving rats. Results suggest that well designed experiments combined with a mechanistic modeling approach could be extremely useful to understand drug effects and to describe all the dynamics characterizing in vivo tumor growth studies.

Modeling tumor growth inhibition and toxicity outcome after administration of anticancer agents in xenograft mice: A Dynamic Energy Budget (DEB) approach.

Host features, such as cell proliferation rates, caloric intake, metabolism and energetic conditions, significantly influence tumor growth; at the same time, tumor growth may have a dramatic impact on the host conditions. For example, in clinics, at certain stages of the tumor growth, cachexia (body weight reduction) may become so relevant to be considered as responsible for around 20% of cancer deaths. Unfortunately, anticancer therapies may also contribute to the development of cachexia due to reduced food intake (anorexia), commonly observed during the treatment periods. For this reason, cachexia is considered one of the major toxicity findings to be evaluated also in preclinical studies. However, although various pharmacokinetic-pharmacodynamic (PK-PD) tumor growth inhibition (TGI) models are currently available, the mathematical modeling of cachexia onset and TGI after an anticancer administration in preclinical experiments is still an open issue. To cope with this, a new PK-PD model, based on a set of tumor-host interaction rules taken from Dynamic Energy Budget (DEB) theory and a set of drug tumor inhibition equations taken from the well-known Simeoni TGI model, was developed. The model is able to describe the body weight reduction, splitting the cachexia directly induced by tumor and that caused by the drug treatment under study. It was tested in typical preclinical studies, essentially designed for efficacy evaluation and routinely performed as a part of the industrial drug development plans. For the first time, both the dynamics of tumor and host growth could be predicted in xenograft mice untreated or treated with different anticancer agents and following different schedules. The model code is freely available for downloading at http://repository.ddmore.eu (model number DDMODEL00000274).

Body composition and metabolic changes during a 520-day mission simulation to Mars.

PURPOSE: The "Mars-500 project" allowed to evaluate the changes in psychological/physiological adaptation over a prolonged confinement, in order to gather information for future missions. Here, we evaluated the impact of confinement and isolation on body composition, glucose metabolism/insulin resistance and adipokine levels. METHODS: The "Mars-500 project" consisted of 520 consecutive days of confinement from June 3, 2010 to Nov 4, 2011. The crew was composed of six male subjects (three Russians, two Europeans, and one Chinese) with a median age of 31 years (range 27-38 years). RESULTS: During the 520-day confinement, total body mass and BMI progressively decreased, reaching a significant difference at the end (417 days) of the observation period (- 9.2 and - 5.5%, respectively). Fat mass remained unchanged. A progressive and significant increase of fasting plasma glucose was observed between 249 and 417 days (+ 10/+ 17% vs baseline), with a further increase at the end of confinement (up to + 30%). Median plasma insulin showed a non-significant early increment (60 days; + 86%). Total adiponectin halved (- 47%) 60 days after hatch closure, remaining at this nadir (- 51%) level for a further 60 days. High molecular weight adiponectin remained significantly lower from 60 to 168 days. CONCLUSIONS: Based on these data, countermeasures may be envisioned to balance the potentially harmful effects of prolonged confinement, including a better exercise program, with accurate monitoring of (1) the individual activity and (2) the relationship between body composition and metabolic derangement.

Effects of Zostera marina on the patterns of spatial distribution of sediments and macrozoobenthos in the boreal lagoon of Furen (Hokkaido, Japan).

Understanding patterns of spatial variations in benthic seagrass assemblages is a central issue in seagrass ecology. However, how patterns of spatial variations in macrozoobenthos and associated sediments differ between vegetated and unvegetated areas remain largely unexplored. In the present study, two different habitats represented by dense Zostera marina beds (Zostera) and unvegetated sediments (Bare) were compared at three locations, 100's meters apart, located at progressive distance from the Furen river in the boreal lagoon of Furen (Hokkaido, Japan). We tested the hypothesis that Z. marina influences the patterns of spatial distribution of abiotic and biotic components along an environmental (estuarine) gradient. The results showed considerable differences between Zostera and Bare, as well as between and within locations, in the distribution of both sediment variables (mud, total organic carbon [TOC] and total nitrogen, acid volatile sulfide, chlorophyll-a and pheopigments) and macrozoobenthic assemblage metrics (total number of species [S], Shannon-Weiner diversity index [H'], total abundance and abundance of dominant species). TOC content, associated to a high mud content, was highest in Bare irrespective of differences between locations (all being above a critical TOC threshold of 3.6%), while S and H' were higher in Zostera than in Bare at all locations. Significant location x habitat effects were found in the abundance of dominant species, represented mainly by mollusks and crustaceans. Furthermore, the proportions of spatial variance were greater at the scale of replicates (meters apart) than at the scale of stations (10's meters apart) for both sediment variables and the dominant species. Importantly, for the dominant species the spatial variance at the smaller scale was much higher in Zostera than in Bare, indicating that at the scale of meters Zostera beds increase the patchiness in the spatial distribution of individuals compared to bare sediments. Overall, our results demonstrate that Z. marina has a strong effect on the spatial heterogeneity in the intensity of the ecological processes influencing patterns of sediment and macrozoobenthos distribution along an environmental gradient. The present study provides a general framework to evaluate patterns of spatial distribution across various scales within several hundreds of meters in seagrass-dominated, eutrophic coastal lagoons.

Model-Based Assessment of Alternative Study Designs in Pediatric Trials. Part II: Bayesian Approaches.

This study presents a pharmacokinetic-pharmacodynamic based clinical trial simulation framework for evaluating the performance of a fixed-sample Bayesian design (BD) and two alternative Bayesian sequential designs (BSDs) (i.e., a non-hierarchical (NON-H) and a semi-hierarchical (SEMI-H) one). Prior information was elicited from adult trials and weighted based on the expected similarity of response to treatment between the pediatric and adult populations. Study designs were evaluated in terms of: type I and II errors, sample size per arm (SS), trial duration (TD), and estimate precision. No substantial differences were observed between NON-H and SEMI-H. BSDs require, on average, smaller SS and TD compared to the BD, which, on the other hand, guarantees higher estimate precision. When large differences between children and adults are expected, BSDs can return very large SS. Bayesian approaches appear to outperform their frequentist counterparts in the design of pediatric trials even when little weight is given to prior information from adults.

Model-Based Assessment of Alternative Study Designs in Pediatric Trials. Part I: Frequentist Approaches.

Alternative designs can increase the feasibility of pediatric trials when compared to classical parallel designs (PaD). In this work we present a model-based approach based on clinical trial simulations for the comparison of PaD with the alternative sequential, crossover, and randomized withdrawal (RWD) designs. Study designs were evaluated in terms of: type I and II errors, sample size per arm (SS), trial duration (TD), treatment exposures, and parameter estimate precision (EP). The crossover requires the lowest SS and TD, although it implies higher placebo and no treatment exposures. RWD maximizes exposure to active treatment while minimizing that to placebo, but requires the largest SS. SS of sequential designs can sometimes be smaller than the crossover one, although with poorer EP. This pharmacometric framework allows a multiscale comparison of alternative study designs that can be used for design selection in future pediatric trials.

Temporal distribution of intertidal macrozoobenthic assemblages in a Nanozostera noltii-dominated area (Lagoon of Venice).

We describe the temporal distribution of intertidal macrozoobenthic assemblages in a small marsh pond of the Lagoon of Venice colonized by the seagrass Nanozostera noltii (Hornemman) Tomlinson et Posluzny. Three stations ranging in the degree of N. noltii cover were selected about 100 m apart and sampled 9 times at regular intervals from March 1996 to March 1997. We applied the concepts of resistance and resilience to "natural stress" (e.g. extent of protection from seagrass meadows, exposure of macrozoobenthic assemblages to high temperatures in summer) with the aim to assess the stability of a community along a gradient of seagrass coverage. Results showed that the most structured and taxa-rich macrozoobenthic assemblage occurred at the station covered by a continuous stand of N. noltii, where permanent taxa (i.e. found in 100% of samples) were almost double than those found at the other stations. During the annual cycle, the macrozoobenthic assemblages showed a cyclical pattern, with temporal fluctuations increasing as they moved further away from the seagrass beds. We propose the role of N. noltii offering structural complexity and stability as the more probable explanation to the observed differences between stations in the intertidal assemblages.

Pharmacometrics Markup Language (PharmML): Opening New Perspectives for Model Exchange in Drug Development.

The lack of a common exchange format for mathematical models in pharmacometrics has been a long-standing problem. Such a format has the potential to increase productivity and analysis quality, simplify the handling of complex workflows, ensure reproducibility of research, and facilitate the reuse of existing model resources. Pharmacometrics Markup Language (PharmML), currently under development by the Drug Disease Model Resources (DDMoRe) consortium, is intended to become an exchange standard in pharmacometrics by providing means to encode models, trial designs, and modeling steps.

Mathematical modeling of growth and death dynamics of mouse embryonic stem cells irradiated with γ-rays.

Following ionizing radiation, mouse embryonic stem cells (mESCs) undergo both apoptosis and block at G2/M phase of the cell cycle. The dynamics of cell growth and the transition through the apoptotic phases cannot be directly inferred from experimental data, limiting the understanding of the biological response to the treatment. Here, we propose a semi-mechanistic mathematical model, defined by five compartments, able to describe the time curves of untreated and γ-rays irradiated mESCs and to extract the information therein embedded. To this end, mESCs were irradiated with 2 or 5 Gy γ-rays, collected over a period of 48 h and, at each time point, analyzed for apoptosis by using the Annexin V assay. When compared to unirradiated mESCs, the model estimates an additional 0.2 probability to undergo apoptosis for the 5 Gy-treated cells, and only a 0.07 (not statistically significantly different from zero) when a 2 Gy-irradiation dose is administered. Moreover, the model allows us to estimate the duration of the overall apoptotic process and also the time length of its early, intermediate, and late apoptotic phase.

A review of mixed-effects models of tumor growth and effects of anticancer drug treatment used in population analysis.

Population modeling of tumor size dynamics has recently emerged as an important tool in pharmacometric research. A series of new mixed-effects models have been reported recently, and we present herein a synthetic view of models with published mathematical equations aimed at describing the dynamics of tumor size in cancer patients following anticancer drug treatment. This selection of models will constitute the basis for the Drug Disease Model Resources (DDMoRe) repository for models on oncology.

Testing the saprobity hypothesis in a Mediterranean lagoon: effects of confinement and organic enrichment on benthic communities.

The macrobenthic community was compared at four sites characterized by varying degrees of freshwater input, organic enrichment and confinement in the Cabras lagoon (Sardinia, Italy). Three sites, riverine (C1), confined (C2) and seaward (C3), were studied on two dates of summer 2010 and on two dates of winter 2011. A fourth site (C12), representative of the central sector of the Cabras lagoon, was included in this study using the extensive historical datasets at our disposal from previously published work. We aimed to test the hypothesis that (1) the benthos is distributed according to the recently proposed concept of habitat saprobity for coastal lagoons that unifies the Pearson-Rosenberg (sensu organic enrichment) and Guélorget-Perthuisot (sensu confinement) models, and (2) indicator species of different saprobic levels can be identified among dominant species occurring along the saprobity gradient. Salinity was also considered as an additional agent of selection in brackish environments. Irrespective of significant seasonal changes within each site, our results highlighted major environmental and biotic differences between sites. At the northward riverine site (C1), most affected by freshwater input and with limited organic matter (OM) enrichment, Corophium orientale was the single dominant species. The most confined site (C2) was characterized by the highest levels of sedimentary OM and benthic Chlorophyll-a and by mesohaline conditions; the site was inhabited mainly by the halolimnobic Hediste diversicolor and Hydrobia spp. Site C12, characterized by a high OM load and high residence time, was dominated by the opportunistic detritivorous Alitta succinea and Polydora ciliata. At the southernmost seaward site (C3) the considerable seawater renewal, resulting in high salinity (only in summer) and limited OM load, favored a much more diverse macrobenthic assemblage, essentially composed of both marine species, such as Corophium insidiosum, Gammarus aequicauda, and brackish-water species, such as Lekanesphaera hookeri and Idotea chelipes. We conclude that the biotic and abiotic characteristics of the Cabras lagoon can be represented by a succession of spatial zones along two main gradients determined by salinity and saprobity. The salinity gradient proved to be the main structural feature in the oligohaline pole, while in the range of variable salinity, saprobity appeared to be the main selection factor. To illustrate our findings, we provide a graphical representation summarizing the changes in environmental parameters and indicator species along the salinity and saprobity gradients.