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There is little significant work at the intersection of mathematical and computational epidemiology and detailed psychological processes, representations, and mechanisms. This is true despite general agreement in the scientific community and the general public that human behavior in its seemingly infinite variation and heterogeneity, susceptibility to bias, context, and habit is an integral if not fundamental component of what drives the dynamics of infectious disease. The COVID-19 pandemic serves as a close and poignant reminder. We offer a 10-year prospectus of kinds that centers around an unprecedented scientific approach: the integration of detailed psychological models into rigorous mathematical and computational epidemiological frameworks in a way that pushes the boundaries of both psychological science and population models of behavior.

Background: In the past decades, Greenland has changed from a hunter society to a more western lifestyle, causing less intake of traditional food, such as marine mammals, fish and seabirds. These changes in the living conditions and food habits might impact the maternal health in Greenland. Objectives: To describe lifestyle, reproductive factors and food intake in Greenlandic pregnant women, and to assess possible age and geographical differences. Design: Cross-sectional study of 189 Greenlandic pregnant women. Inclusion criteria were ≥18 years and lived >50% of their life in Greenland. Data were collected in 2010–2011, and information was obtained from lifestyle and food frequency questionnaires. Two age groups for comparison were given for the pregnant women (25.0 kg/m2, 46.3% were current smokers in the beginning of their pregnancy and few participants consumed alcohol during pregnancy. Women 50% in North, South and West had a higher alcohol intake during pregnancy. Women in North had the fewest breastfeeding plans. Women in Disko Bay had the lowest intake of terrestrial species. No significant geographical differences were found for intake of marine mammals or seabirds. Conclusions: The present study found relatively high BMI level and high smoking frequency in Greenlandic pregnant women. Age and region differences were found for alcohol consumption, breastfeeding plans and food intake profile. Further research is needed to implement relevant maternal health intervention programs in Greenland.

Background. The traditional diet of Inuit people comprises large amounts of fish and marine mammals that are rich in omega-3 polyunsaturated fatty acids (PUFAs). Results from in vitro studies, laboratory animal experiments and population studies suggest that omega-3 PUFA intake and a high omega-3/omega-6 ratio exert a positive effect on bone health. Objective. This longitudinal study was conducted to examine the relationship between omega-3 and omega-6 PUFA status and quantitative ultrasound (QUS) parameters in Greenlandic Inuit women. Methods. The study included 118 Inuit women from Nuuk (Greenland), aged 49–64 years, whose QUS parameters measured at baseline (year 2000), along with PUFA status and covariates, and follow-up QUS measurements 2 years later (year 2002). QUS parameters [speed of sound (SOS); broadband ultrasound attenuation (BUA)] were measured at the right calcaneus with a water-bath Lunar Achilles instrument. Omega-3 and omega-6 PUFA contents of erythrocyte membrane phospholipids were measured after transmethylation by gas chromatography coupled with a flame ionization detector. Relationships between QUS parameters and different PUFAs were studied in multiple linear regression models. Results. Increasing values of EPA, DHA and the omega-3/omega-6 PUFA ratio were associated with increased BUA values measured at follow-up (year 2002). These associations were still present in models adjusted for several confounders and covariates. We found little evidence of associations between PUFAs and SOS values. Conclusion. The omega-3 PUFA intake from marine food consumption seems to have a positive effect on bone intrinsic quality and strength, as revealed by higher BUA values in this group of Greenlandic Inuit women.

A series of six mono-, di-, and trivalent N,N’-diacetylchitobiose derivatives was conveniently prepared by employing a one-pot procedure for Cu(II)-catalyzed diazo transfer and Cu(I)-catalyzed azide–alkyne cycloaddition (CuAAC) starting from commercially available amines. These glycoclusters were probed for their binding potencies to the plant lectin wheat germ agglutinin (WGA) from Triticum vulgaris by an enzyme-linked lectin assay (ELLA) employing covalently immobilized N-acetylglucosamine (GlcNAc) as a reference ligand. IC50 values were in the low micromolar/high nanomolar range, depending on the linker between the two disaccharides. Binding enhancements β up to 1000 for the divalent ligands and 2800 for a trivalent WGA ligand, compared to N,N’-diacetylchitobiose as the corresponding monovalent ligand, were observed. Molecular modeling studies, in which the chitobiose moieties were fitted into crystallographically determined binding sites of WGA, correlate the binding enhancements of the multivalent ligands with their ability to bind to the protein in a chelating mode. The best WGA ligand is a trivalent cluster with an IC50 value of 220 nM. Calculated per mol of contained chitobiose, this is the best WGA ligand known so far.

Discrete dynamical systems are used to model various realistic systems in network science, from social unrest in human populations to regulation in biological networks. A common approach is to model the agents of a system as vertices of a graph, and the pairwise interactions between agents as edges. Agents are in one of a finite set of states at each discrete time step and are assigned functions that describe how their states change based on neighborhood relations. Full characterization of state transitions of one system can give insights into fundamental behaviors of other dynamical systems. In this paper, we describe a discrete graph dynamical systems (GDSs) application called GDSCalc for computing and characterizing system dynamics. It is an open access system that is used through a web interface. We provide an overview of GDS theory. This theory is the basis of the web application; i.e., an understanding of GDS provides an understanding of the software features, while abstracting away implementation details. We present a set of illustrative examples to demonstrate its use in education and research. Finally, we compare GDSCalc with other discrete dynamical system software tools. Our perspective is that no single software tool will perform all computations that may be required by all users; tools typically have particular features that are more suitable for some tasks. We situate GDSCalc within this space of software tools.

Kudoa thyrsites infection of marine fish typically results in myoliquefaction, which is only apparent 24 to 56 h post‐mortem. The traditional methods for the detection of K. thyrsites infected fish are time‐consuming and destructive, reducing its marketability. This poses a challenge for the fish industry to remove infected fish before it reaches the market or further processing activities. This study investigated the use of near‐infrared (NIR) spectroscopy, in combination with soft independent modelling of class analogy (SIMCA) and partial least square discriminant analysis (PLS‐DA), for discriminating K. thyrsites infected fish from uninfected fish. Performance of the classification models was evaluated by calculating the sensitivity, specificity and precision. A total of 334 fish samples (200 sardine, 64 hake and 70 kingklip) were used for this study. Infection of K. thyrsites was determined with the use of qPCR assays. Ninety per cent (90%) of the sardine samples, 78% of the hake samples and 37% of the kingklip samples were infected. Class groups of infected and uninfected fish samples were created for the purpose of generating SIMCA and PLS‐DA classification models for each species of fish, as well as for a species independent data set. Principal component analysis (PCA) of NIR spectra did not show any clustering for infected and uninfected samples. Calibration and test sample sets were generated for the purpose of building and testing the SIMCA and PLD‐DA classification models. SIMCA and PLS‐DA were unable to classify test samples correctly into the two classes. The number of misclassifications (NMC) was higher for the SIMCA models than for the PLS‐DA models, with more than 60% incorrectly classified. SIMCA classified most of the test samples into both classes. The precision for PLS‐DA were 89% for sardine, 81% for hake, 0% for kingklip and 87% for species independent models, however, most samples were classified at infected. The use of NIR spectroscopy and classification models such as SIMCA and PLS‐DA showed limited use as a method to distinguish between K. thyrsites infected and uninfected fish samples. Textural and chemical changes during extended frozen storage of the fish samples may have masked the effects associated with K. thyrsites infection. Further studies are suggested where NIR spectroscopy is used in combination with texture analysis and image spectroscopy. [ABSTRACT FROM AUTHOR]