Notes

A singular truncating different within the FGD1 gene connected with Aarskog-Scott affliction in a family members previously diagnosed with Phon Hashomer camptodactyly.
In contrast to Hg, temporal correspondence was observed between Se concentrations in brine shrimp and those in all water samples regardless of filtering and depth, with maxima and minima at higher-than-seasonal frequency. The data suggest a spatially diffuse source of bioavailable mercury to the shallow brine that responds to seasonal influences, for which the underlying deep brine, surficial sediments, and overlying atmosphere were evaluated in terms of potential temporal correspondence to shallow brine and brine shrimp Hg concentrations, as well as potential to mix across the extent of the shallow brine. Bioaccumulation factors were at the low end of those reported for marine systems, and decreased at higher trace element concentrations in water.The funeral industry is a potential reservoir of antibiotic resistance. The occurrence, human exposure and health risks of antibiotic resistance in the funeral industry were examined. The funeral industry harbours antibiotic resistance to multiple common and last-resort antibiotics, hence constitutes the 'thanato-resistome'. learn more Hydrological processes, air-borne particulates and vectors disseminate antibiotic resistance, while horizontal gene transfer circulates antibiotic resistance among resistomes, forming a complex network. Ingestion, inhalation of air-borne particulates, dermal intake and clothes of workers contribute to human exposure. Human health risks include; development of drug resistance in previously susceptible pathogens, and increased morbidity and mortality caused by increased pathogenicity and outbreaks of multi-drug resistant infections. Ecological risks include the proliferation of resistant organisms at the expense of susceptible ones, thereby disrupting ecosystem structure and function, including biogeochemical cycles. Barring inferential data, quantitative evidence linking antibiotic resistance to human infections is weak. This reflects the lack of systematic quantitative studies, rather than the absence of such health risks. Quantitative risk assessment is constrained by lack of quantitative data on antibiotic resistance in various reservoirs and exposure routes. A framework for risk assessment and mitigation is proposed. Finally, ten hypotheses and emerging tools such as genomics, in silico techniques and big data analytics are highlighted.Stereopsis is a powerful depth cue for humans, which may also contribute to object recognition. In particular, we surmise that face identification would benefit from the availability of stereoscopic depth cues, since facial perception may be based on three-dimensional (3D) representations. In this study, a virtual reality (VR) headset with integrated eye-tracking was used to present stereoscopic images of faces. As a monoscopic contrast condition, identical images of faces were displayed to the two eyes. We monitored the participants' gaze behavior and pupil diameters while they performed a sample-to-match face identification task. We found that accuracy was superior in the stereoscopic condition compared to the monoscopic condition for frontal and intermediate views, but not profiles. Moreover, pupillary diameters were smaller when identifying stereoscopically seen faces than when viewing them without stereometric cues, which we interpret as lower processing load for the former than the latter conditions. The analysis of gaze showed that participants tended to focus on regions of the face rich in volumetric information, more so in the stereoscopic condition than the monoscopic condition. Together, these findings suggest that a 3D representation of faces may be the natural format used by the visual system when assessing face identity. Stereoscopic information, by providing depth information, assists the construction of robust facial representations in memory.Consistent associations have been shown between self-reported peer victimisation and internalising symptoms. In distinct literature, anxious and depressed youth have been shown to interpret ambiguous social stimuli in a manner consistent with social threat and rejection. The aim of the current study was to determine whether this sensitivity to social threat among anxious/depressed youth explains significant variance in the relationship between self-reports of peer victimisation and internalising symptoms. Two hundred and sixty-seven students in grades seven and eight (M age = 12.62, SD = 0.65) completed measures of their own symptoms of anxiety and depression as well as their experiences of being physically or relationally victimised by their peers. They also read descriptions of 10 hypothetical ambiguous social interactions and provided responses indicating whether they interpreted each scenario as indicating social threat (rejection/negative evaluation) and the extent to which they perceived it as victimisation. As expected, anxiety and depression were positively correlated with self-reported peer victimisation and with interpretations consistent with social threat and victimisation (social threat sensitivity). In turn, social threat sensitivity was positively correlated with both self-reported relational and physical victimisation, but moreso with the former. However, the relationship between anxiety and depression and victimisation remained significant, even after controlling for social threat sensitivity. Results suggest that a sensitivity toward social threat can influence self-reports of peer victimisation among anxious and depressed youth, but that the relationship between internalising and victimisation goes beyond this sensitivity.Avoidance towards innocuous stimuli is a key characteristic across anxiety-related disorders and chronic pain. Insights into the relevant learning processes of avoidance are often gained via laboratory procedures, where individuals learn to avoid stimuli or movements that have been previously associated with an aversive stimulus. Typically, statistical analyses of data gathered with conditioned avoidance procedures include frequency data, for example, the number of times a participant has avoided an aversive stimulus. Here, we argue that further insights into the underlying processes of avoidance behavior could be unraveled using computational models of behavior. We then demonstrate how computational models could be used by reanalysing a previously published avoidance data set and interpreting the key findings. We conclude our article by listing some challenges in the direct application of computational modeling to avoidance data sets.
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