Phenotypic stereotypes are traits, often polygenic, that have been stringently selected to conform to specific criteria. In dogs, Canis familiaris, stereotypes result from breed standards set for conformation, performance (behaviors), etc. As a consequence, phenotypic values measured on a few individuals are representative of the breed stereotype. We used DNA samples isolated from 148 dog breeds to associate SNP markers with breed stereotypes. Using size as a trait to test the method, we identified six significant quantitative trait loci (QTL) on five chromosomes that include candidate genes appropriate to regulation of size (e.g., IGF1, IGF2BP2 SMAD2, etc.). Analysis of other morphological stereotypes, also under extreme selection, identified many additional significant loci. Less well-documented data for behavioral stereotypes tentatively identified loci for herding, pointing, boldness, and trainability. Four significant loci were identified for longevity, a breed characteristic not under direct selection, but inversely correlated with breed size. The strengths and limitations of the approach are discussed as well as its potential to identify loci regulating the within-breed incidence of specific polygenic diseases.

Detailed examination of the water column, sediments, and interstitial waters was conducted in Balmer Lake, Ontario, Canada, in 1993-1994 and 1999 in order to assess the seasonal and interannual controls governing the behavior of As. High-resolution profiles of dissolved (<0.45 microm) Fe, Mn, SO4(2-), and sigmaH2S across the sediment-water interface indicate the presence of reducing conditions in close proximity to the benthic boundary during ice-free periods, which are characterized by fully oxygenated bottom waters. Dissolved As is remobilized as As(III) in suboxic sediment horizons via the redox-controlled dissolution of Fe (and perhaps Mn) oxide phases. During 1993-1994, As fluxes to the water column were relatively low (2-15 microg cm(-2) year(-1)) and contributed between 2 and 18% of the water column inventory. Dissolved As in the lake waters was derived primarily from external mining-related loadings during this period. Between 1993 and 1999, external loadings of As to Balmer Lake decreased while [As]aq within the lake increased, suggesting an increase in the proportion of sediment-derived As. Indeed, benthic dissolved As fluxes in 1999 ranged from 179 to 380 microg cm(-2) year(-1), representing approximately 33-60% of the water column burden. The relatively recent importance of sedimentary arsenic sources is suggested to reflect changes to sediment redox conditions associated with a postulated increase in lake primary productivity. Ironically, the increased contribution of dissolved arsenic to the water column appears to have resulted from an otherwise improvement in water quality. Reduced loadings of Cu, Zn, and Ni to the lake since 1994 appear to have allowed increased phytoplankton production that has stimulated arsenic release.

The deleterious effects of a disrupted copper metabolism are illustrated by hereditary diseases caused by mutations in the genes coding for the copper transporters ATP7A and ATP7B. Menkes disease, involving ATP7A, is a fatal neurodegenerative disorder of copper deficiency. Mutations in ATP7B lead to Wilson disease, which is characterized by a predominantly hepatic copper accumulation. The low incidence and the phenotypic variability of human copper toxicosis hamper identification of causal genes or modifier genes involved in the disease pathogenesis. The Labrador retriever was recently characterized as a new canine model for copper toxicosis. Purebred dogs have reduced genetic variability, which facilitates identification of genes involved in complex heritable traits that might influence phenotype in both humans and dogs. We performed a genome-wide association study in 235 Labrador retrievers and identified two chromosome regions containing ATP7A and ATP7B that were associated with variation in hepatic copper levels. DNA sequence analysis identified missense mutations in each gene. The amino acid substitution ATP7B:p.Arg1453Gln was associated with copper accumulation, whereas the amino acid substitution ATP7A:p.Thr327Ile partly protected against copper accumulation. Confocal microscopy indicated that aberrant copper metabolism upon expression of the ATP7B variant occurred because of mis-localization of the protein in the endoplasmic reticulum. Dermal fibroblasts derived from ATP7A:p.Thr327Ile dogs showed copper accumulation and delayed excretion. We identified the Labrador retriever as the first natural, non-rodent model for ATP7B-associated copper toxicosis. Attenuation of copper accumulation by the ATP7A mutation sheds an interesting light on the interplay of copper transporters in body copper homeostasis and warrants a thorough investigation of ATP7A as a modifier gene in copper-metabolism disorders. The identification of two new functional variants in ATP7A and ATP7B contributes to the biological understanding of protein function, with relevance for future development of therapy.

IMPORTANCE Compared with the treatment of physical conditions, the quality of care of mental health disorders remains poor and the rate of improvement in treatment is slow, a primary reason being the lack of objective and systematic methods for measuring the delivery of psychotherapy. OBJECTIVE To use a deep learning model applied to a large-scale clinical data set of cognitive behavioral therapy (CBT) session transcripts to generate a quantifiable measure of treatment delivered and to determine the association between the quantity of each aspect of therapy delivered and clinical outcomes. DESIGN, SETTING, AND PARTICIPANTS All data were obtained from patients receiving internet-enabled CBT for the treatment of a mental health disorder between June 2012 and March 2018 in England. Cognitive behavioral therapy was delivered in a secure online therapy room via instant synchronous messaging. The initial sample comprised a total of 17 572 patients (90 934 therapy session transcripts). Patients self-referred or were referred by a primary health care worker directly to the service. EXPOSURES All patients received National Institute for Heath and Care Excellence-approved disorder-specific CBT treatment protocols delivered by a qualified CBT therapist. MAIN OUTCOMES AND MEASURES Clinical outcomes were measured in terms of reliable improvement in patient symptoms and treatment engagement. Reliable improvement was calculated based on 2 severity measures: Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder 7-item scale (GAD-7), corresponding to depressive and anxiety symptoms respectively, completed by the patient at initial assessment and before every therapy session. RESULTS Treatment sessions from a total of 14 899 patients (10 882 women) aged between 18 and 94 years (median age, 34.8 years) were included in the final analysis. We trained a deep learning model to automatically categorize therapist utterances into 1 or more of 24 feature categories. The trained model was applied to our data set to obtain quantifiable measures of each feature of treatment delivered. A logistic regression revealed that increased quantities of a number of session features, including change methods (cognitive and behavioral techniques used in CBT), were associated with greater odds of reliable improvement in patient symptoms (odds ratio, 1.11; 95% CI, 1.06-1.17) and patient engagement (odds ratio, 1.20, 95% CI, 1.12-1.27). The quantity of nontherapy-related content was associated with reduced odds of symptom improvement (odds ratio, 0.89; 95% CI, 0.85-0.92) and patient engagement (odds ratio, 0.88, 95% CI, 0.84-0.92). CONCLUSIONS AND RELEVANCE This work demonstrates an association between clinical outcomes in psychotherapy and the content of therapist utterances. These findings support the principle that CBT change methods help produce improvements in patients' presenting symptoms. The application of deep learning to large clinical data sets can provide valuable insights into psychotherapy, informing the development of new tre...

Host anti-toxin immune responses play important roles in Clostridium difficile disease and outcome. The relationship between host immune and inflammatory responses during severe C. difficile infection (CDI) and the risk of mortality has yet to be defined. We aimed to investigate the host systemic IgG anti-toxin immune responses, the in vitro cytotoxicity of the infecting C. difficile ribotyped strain, and the host inflammatory markers and their relationship to CDI disease severity and risk of mortality. Inflammatory markers, co-morbidities and CDI outcomes were recorded in a prospective cohort of 150 CDI cases. Serum anti-cytotoxin A (TcdA) and anti-TcdB IgG titres were measured by ELISA and the infecting C. difficile isolate was ribotyped and the in vitro cytotoxin titre assessed. A low median anti-TcdA IgG titre was significantly associated with 30-day all-cause mortality (P,0.05). Ribotype 027 isolates were significantly more toxinogenic than other ribotypes (P,0.00001). High cytotoxin titres correlated with increased inflammatory markers but also higher anti-TcdA and -TcdB (P,0.05) IgG responses resulting in a lower risk of mortality. On multivariate analysis, predictors of mortality were peak white cell count .20¾10 9 l

Traits that have been stringently selected to conform to specific criteria in a closed population are phenotypic stereotypes. In dogs, Canis familiaris, such stereotypes have been produced by breeding for conformation, performance (behaviors), etc. We measured phenotypes on a representative sample to establish breed stereotypes. DNA samples from 147 dog breeds were used to characterize single nucleotide polymorphism allele frequencies for association mapping of breed stereotypes. We identified significant size loci (quantitative trait loci [QTLs]), implicating candidate genes appropriate to regulation of size (e.g., IGF1, IGF2BP2 SMAD2, etc.). Analysis of other morphological stereotypes, also under extreme selection, identified many additional significant loci. Behavioral loci for herding, pointing, and boldness implicated candidate genes appropriate to behavior (e.g., MC2R, DRD1, and PCDH9). Significant loci for longevity, a breed characteristic inversely correlated with breed size, were identified. The power of this approach to identify loci regulating the incidence of specific polygenic diseases is demonstrated by the association of a specific IGF1 haplotype with hip dysplasia, patella luxation, and pancreatitis.

The biogeochemical mechanisms of Se exchange between water and sediments in two contrasting lentic environments were assessed through examination of Se speciation in the water column, porewater, and sediment. High-resolution (7 mm) vertical profiles of <0.45 μm Se species across the sediment-water interface demonstrate that the behavior of dissolved Se(VI), Se(IV), and organo-Se are closely linked to redox conditions as revealed by porewater profiles of redox-sensitive species (dissolved O2, NO3-, Fe, Mn, SO4(2-), and ΣH2S). At both sites Se(VI) is removed from solution in suboxic near-surface porewaters demonstrating that the sediments are serving as diffusive sinks for Se. X-ray absorption near edge spectroscopy (XANES) of sediments suggests that elemental Se and organo-Se represent the dominant sedimentary sinks for dissolved Se. Dissolved Se(IV) and organo-Se are released to porewaters in the near-surface sediments resulting in the diffusive transport of these species into the water column, where between-site differences in the depths of release can be linked to differences in redox zonation. The presence or absence of emergent vegetation is proposed to present a dominant control on sedimentary redox conditions as well as on the recycling and persistence of reduced Se species in bottom waters.

Background and AimsPrediction of severe clinical outcomes in Clostridium difficile infection (CDI) is important to inform management decisions for optimum patient care. Currently, treatment recommendations for CDI vary based on disease severity but validated methods to predict severe disease are lacking. The aim of the study was to derive and validate a clinical prediction tool for severe outcomes in CDI.MethodsA cohort totaling 638 patients with CDI was prospectively studied at three tertiary care clinical sites (Boston, Dublin and Houston). The clinical prediction rule (CPR) was developed by multivariate logistic regression analysis using the Boston cohort and the performance of this model was then evaluated in the combined Houston and Dublin cohorts.ResultsThe CPR included the following three binary variables: age ≥ 65 years, peak serum creatinine ≥2 mg/dL and peak peripheral blood leukocyte count of ≥20,000 cells/μL. The Clostridium difficile severity score (CDSS) correctly classified 76.5% (95% CI: 70.87-81.31) and 72.5% (95% CI: 67.52-76.91) of patients in the derivation and validation cohorts, respectively. In the validation cohort, CDSS scores of 0, 1, 2 or 3 were associated with severe clinical outcomes of CDI in 4.7%, 13.8%, 33.3% and 40.0% of cases respectively.ConclusionsWe prospectively derived and validated a clinical prediction rule for severe CDI that is simple, reliable and accurate and can be used to identify high-risk patients most likely to benefit from measures to prevent complications of CDI.