Preadolescents’ relationships with pet dogs: Relationship continuity and associations with adjustment

Research on human–animal interaction in children has been studied in isolation rather than integrated with core theories of children’s relationships. This study is one of the first to examine how children’s relationships with pet dogs are related to their human relationships (parent–child attachments, friendships) and to child adjustment, and to include observational assessment of children’s interactions with their pet dog. Children (9 to 11 years old, n = 99) completed questionnaires regarding relationships with pet dogs, parents, and friends. Half the children were observed interacting with their pet dog. Children and teachers reported children’s adjustment. Children who felt closer to their dogs were more securely attached to mothers and fathers and reported more positive qualities and less conflict with friends. Children with more secure attachments to mothers, and greater companionship with dogs, interacted more with their dogs. Parental attachment and friendship quality, but not the pet dog relationship, were related to child adjustment.     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.     

Trace elements in rock salt and their bioavailability estimated from solubility in acid

In this study, 18 partly commercially available samples of rock salt from Austria, Germany, Pakistan, Poland, Switzerland, and Ukraine were investigated with respect to their content of trace elements using instrumental neutron activation analysis. Elements detected were Al, Ba, Br, Ca, Ce, Cl, Co, Cr, Cs, Eu, Fe, Hf, La, Mn, Na, Rb, Sb, Sc, Sm, Sr, Ta, Tb, Th, and Zn, some of them only in individual cases. An estimation of the bioavailability of these trace elements was performed by dissolving an equivalent of the sodium chloride samples in diluted hydrochloric acid (simulating stomach acid), filtering off the insoluble components, and analyzing the evaporated filtrate. It could be shown that in most cases bioactive trace elements like Fe can be found in rock salt in the form of almost insoluble compounds and are therefore not significantly bioavailable, whereas thorium, for example, was partly bioavailable in two cases. A significant contribution to the recommended daily intake of metal trace elements by using rock salt for nutrition can be excluded.     

Considering Future Potential Regarding Structural Diversity in Selection of Forest Reserves

A rich structural diversity in forests promotes biodiversity. Forests are dynamic and therefore it is crucial to consider future structural potential when selecting reserves, to make robust conservation decisions. We analyzed forests in boreal Sweden based on 17,599 National Forest Inventory (NFI) plots with the main aim to understand how effectiveness of reserves depends on the time dimension in the selection process, specifically by considering future structural diversity. In the study both the economic value and future values of 15 structural variables were simulated during a 100 year period. To get a net present structural value (NPSV), a single value covering both current and future values, we used four discounting alternatives: (1) only considering present values, (2) giving equal importance to values in each of the 100 years within the planning horizon, (3) applying an annual discount rate considering the risk that values could be lost, and (4) only considering the values in year 100. The four alternatives were evaluated in a reserve selection model under budget-constrained and area-constrained selections. When selecting young forests higher structural richness could be reached at a quarter of the cost over almost twice the area in a budget-constrained selection compared to an area-constrained selection. Our results point to the importance of considering future structural diversity in the selection of forest reserves and not as is done currently to base the selection on existing values. Targeting future values increases structural diversity and implies a relatively lower cost. Further, our results show that a re-orientation from old to young forests would imply savings while offering a more extensive reserve network with high structural qualities in the future. However, caution must be raised against a drastic reorientation of the current old-forest strategy since remnants of ancient forests will need to be prioritized due to their role for disturbance-sensitive species.     

Gross intestinal morphometry and allometry in primates

Although it is generally assumed that among mammals and within mammal groups, those species that rely on diets consisting of greater amounts of plant fiber have larger gastrointestinal tracts (GIT), statistical evidence for this simple claim is largely lacking. We compiled a dataset on the length of the small intestine, caecum, and colon in 42 strepsirrhine, platyrrhine, and catarrhine primate species, using specimens with known body mass (BM). We tested the scaling of intestine length with BM, and whether dietary proxies (percentage of leaves and a diet quality index) were significant covariates in these scaling relationships, using two sets of models: one that did not account for the phylogenetic structure of the data, and one that did. Intestine length mainly scaled geometrically at exponents that included 0.33 in the confidence interval; Strepsirrhini exhibited particularly long caeca, while those of Catarrhini were comparatively short. Diet proxies were only significant for the colon and the total large intestine (but not for the small intestine or the caecum), and only in conventional statistics (but not when accounting for phylogeny), indicating the pattern occurred across but not within clades. Compared to terrestrial Carnivora, primates have similar small intestine lengths, but longer large intestines. The data on intestine lengths presented here corroborate recent results on GIT complexity, suggesting that diet, as currently described, does not exhaustively explain GIT anatomy within primate clades.     

Antibody responses to galectin-8, TARP and TRAP1 in prostate cancer patients treated with a GM-CSF-secreting cellular immunotherapy

A critical factor in clinical development of cancer immunotherapies is the identification of tumor-associated antigens that may be related to immunotherapy potency. In this study, protein microarrays containing >8,000 human proteins were screened with serum from prostate cancer patients (N = 13) before and after treatment with a granulocyte–macrophage colony-stimulating factor (GM-CSF)-secreting whole cell immunotherapy. Thirty-three proteins were identified that displayed significantly elevated (P ≤ 0.05) signals in post-treatment samples, including three proteins that have previously been associated with prostate carcinogenesis, galectin-8, T-cell alternative reading frame protein (TARP) and TNF-receptor-associated protein 1 (TRAP1). Expanded analysis of antibody induction in metastatic, castration-resistant prostate cancer (mCRPC) patients (N = 92) from two phase 1/2 trials of prostate cancer immunotherapy, G-9803 and G-0010, indicated a significant (P = 0.03) association of TARP antibody induction and median survival time (MST). Antibody induction to TARP was also significantly correlated (P = 0.036) with an increase in prostate-specific antigen doubling time (PSADT) in patients with a biochemical (PSA) recurrence following prostatectomy or radiation therapy (N = 19) from in a previous phase 1/2 trial of prostate cancer immunotherapy, G-9802. RNA and protein encoding TARP and TRAP1 was up-regulated in prostate cancer tissue compared to matched normal controls. These preliminary findings suggest that antibody induction to TARP may represent a possible biomarker for treatment response to GM-CSF secreting cellular immunotherapy in prostate cancer patients and demonstrates the utility of using protein microarrays for the high-throughput screening of patient-derived antibody responses.     

Validation and Application of a Custom-Designed Targeted Next-Generation Sequencing Panel for the Diagnostic Mutational Profiling of Solid Tumors

The inevitable switch from standard molecular methods to next-generation sequencing for the molecular profiling of tumors is challenging for most diagnostic laboratories. However, fixed validation criteria for diagnostic accreditation are not in place because of the great variability in methods and aims. Here, we describe the validation of a custom panel of hotspots in 24 genes for the detection of somatic mutations in non-small cell lung carcinoma, colorectal carcinoma and malignant melanoma starting from FFPE sections, using 14, 36 and 5 cases, respectively. The targeted hotspots were selected for their present or future clinical relevance in solid tumor types. The target regions were enriched with the TruSeq approach starting from limited amounts of DNA. Cost effective sequencing of 12 pooled libraries was done using a micro flow cell on the MiSeq and subsequent data analysis with MiSeqReporter and VariantStudio. The entire workflow was diagnostically validated showing a robust performance with maximal sensitivity and specificity using as thresholds a variant allele frequency >5% and a minimal amplicon coverage of 300. We implemented this method through the analysis of 150 routine diagnostic samples and identified clinically relevant mutations in 16 genes including KRAS (32%), TP53 (32%), BRAF (12%), APC (11%), EGFR (8%) and NRAS (5%). Importantly, the highest success rate was obtained when using also the low quality DNA samples. In conclusion, we provide a workflow for the validation of targeted NGS by a custom-designed pan-solid tumor panel in a molecular diagnostic lab and demonstrate its robustness in a clinical setting.