Aggregation of Votes with Multiple Positions on Each Issue

We consider the problem of aggregating votes cast by a society on a fixed set of issues, where each member of the society may vote for one of several positions on each issue, but the combination of votes on the various issues is restricted to a set of feasible voting patterns. We require the aggregation to be supportive, i.e. for every issue $j$ the corresponding component $f_j$ of every aggregator on every issue should satisfy $f_j(x_1, ,\ldots, x_n) \in \{x_1, ,\ldots, x_n\}$. We prove that, in such a set-up, non-dictatorial aggregation of votes in a society of some size is possible if and only if either non-dictatorial aggregation is possible in a society of only two members or a ternary aggregator exists that either on every issue $j$ is a majority operation, i.e. the corresponding component satisfies $f_j(x,x,y) = f_j(x,y,x) = f_j(y,x,x) =x, \forall x,y$, or on every issue is a minority operation, i.e. the corresponding component satisfies $f_j(x,x,y) = f_j(x,y,x) = f_j(y,x,x) =y, \forall x,y.$ We then introduce a notion of uniformly non-dictatorial aggregator, which is defined to be an aggregator that on every issue, and when restricted to an arbitrary two-element subset of the votes for that issue, differs from all projection functions. We first give a characterization of sets of feasible voting patterns that admit a uniformly non-dictatorial aggregator. Then making use of Bulatov's dichotomy theorem for conservative constraint satisfaction problems, we connect social choice theory with combinatorial complexity by proving that if a set of feasible voting patterns $X$ has a uniformly non-dictatorial aggregator of some arity then the multi-sorted conservative constraint satisfaction problem on $X$, in the sense introduced by Bulatov and Jeavons, with each issue representing a sort, is tractable; otherwise it is NP-complete

DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer

Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 BRCA1 pathogenic mutation carriers, 65 BRCAx (BRCA1-wild type), 38 BRCA1 test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (BACH2, C8orf31, and LOC654342) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set). Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G>A (IVS 19-12 G>A) (P>0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of BRCA1 variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity

Modulation of porcine β-defensins 1 and 2 upon individual and combined Fusarium toxin exposure in a swine jejunal epithelial cell line

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Exploring how family carers of a person with dementia manage pre-death grief: A mixed methods study

Objectives Many family carers of a person with dementia experience pre-death grief. We aimed to identify strategies that help carers manage pre-death grief. We hypothesised that emotion and problem focussed styles would be associated with lower, and dysfunctional coping with higher grief intensity. Methods Mixed methods observational study using structured and semi-structured interviews with 150 family carers of people with dementia living at home or in a care home. Most participants were female (77%), caring for a parent (48%) or partner/spouse (47%) with mild (25%), moderate (43%) or severe (32%) dementia. They completed the Marwit-Meuser Caregiver Grief Inventory Short Form and the Brief Coping Orientation to Problems Experienced (Brief-COPE) questionnaire. We asked carers to identify strategies used for managing grief. We recorded field notes for 150 interviews and audio-recorded additional interviews with a sub-sample of 16 participants. Results Correlations indicated that emotion-oriented coping was associated with lower grief (R = −0.341), and dysfunctional coping with higher grief (R = 0.435), with a small association with problem-focused strategies (R = −0.109), partly supporting our hypothesis. Our qualitative themes broadly match the three Brief-COPE styles. Unhelpful strategies of denial and avoidance align with dysfunctional coping strategies. Psychological strategies (including acceptance and humour) and seeking support were consistent with emotion-focused strategies, but we did not identify a theme relating to problem-focused strategies. Conclusion Most carers identified multiple strategies for processing grief. Carers could readily identify supports and services that they found helpful for managing pre-death grief, yet current services appear under-resourced to meet growing demand. (ClinicalTrials.gov ID: NCT03332979)

Is preparation for end of life associated with pre-death grief in caregivers of people with dementia?

OBJECTIVES: Family caregivers of people with dementia can experience loss and grief before death. We hypothesized that modifiable factors indicating preparation for end of life are associated with lower pre-death grief in caregivers. DESIGN: Cross-sectional. SETTING: Caregivers of people with dementia living at home or in a care home. PARTICIPANTS: In total, 150 caregivers, 77% female, mean age 63.0 (SD = 12.1). Participants cared for people with mild (25%), moderate (43%), or severe dementia (32%). MEASUREMENTS: Primary outcome: Marwit-Meuser Caregiver Grief Inventory Short Form (MMCGI-SF). We included five factors reflecting preparation for end of life: (1) knowledge of dementia, (2) social support, (3) feeling supported by healthcare providers, (4) formalized end of life documents, and (5) end-of-life discussions with the person with dementia. We used multiple regression to assess associations between pre-death grief and preparation for end of life while controlling for confounders. We repeated this analysis with MMCGI-SF subscales ("personal sacrifice burden"; "heartfelt sadness"; "worry and felt isolation"). RESULTS: Only one hypothesized factor (reduced social support) was strongly associated with higher grief intensity along with the confounders of female gender, spouse, or adult child relationship type and reduced relationship closeness. In exploratory analyses of MMCGI-SF subscales, one additional hypothesized factor was statistically significant; higher dementia knowledge was associated with lower "heartfelt sadness." CONCLUSION: We found limited support for our hypothesis. Future research may benefit from exploring strategies for enhancing caregivers' social support and networks as well as the effectiveness of educational interventions about the progression of dementia (ClinicalTrials.gov ID: NCT03332979)

Finding Crush: Environmental DNA Analysis as a Tool for Tracking the Green Sea Turtle Chelonia mydas in a Marine Estuary

Environmental DNA (eDNA) analysis is a rapid, non-invasive method for species detection and distribution assessment using DNA released into the surrounding environment by an organism. eDNA analysis is recognised as a powerful tool for detecting endangered or rare species in a range of ecosystems. Although the number of studies using eDNA analysis in marine systems is continually increasing, there appears to be no published studies investigating the use of eDNA analysis to detect sea turtles in natural conditions. We tested the efficacy of two primer pairs known to amplify DNA fragments of differing lengths (488 and 253 bp) from Chelonia mydas tissues for detecting C. mydas eDNA in water samples. The capture, extraction, and amplification of C. mydas eDNA from aquaria (Sea World, San Diego, CA, United States) and natural water (San Diego Bay, CA, United States) were successful using either primer set. The primer pair providing the shorter amplicon, LCMint2/H950g, demonstrated the ability to distinguish cross-reactive species by melt curve analysis and provided superior amplification metrics compared to the other primer set (LTCM2/HDCM2); although primer dimer was observed, warranting future design refinement. Results indicated that water samples taken from deeper depths might improve detection frequency, consistent with C. mydas behaviour. Overall, this pilot study suggests that with refinement of sampling methodology and further assay optimisation, eDNA analysis represents a promising tool to monitor C. mydas. Potential applications include rapid assessment across broad geographical areas to pinpoint promising locations for further evaluation with traditional methods

Self-regulation learning as active inference: dynamic causal modeling of an fMRI neurofeedback task

Introduction: Learning to self-regulate brain activity by neurofeedback has been shown to lead to changes in the brain and behavior, with beneficial clinical and non-clinical outcomes. Neurofeedback uses a brain-computer interface to guide participants to change some feature of their brain activity. However, the neural mechanism of self-regulation learning remains unclear, with only 50% of the participants succeeding in achieving it. To bridge this knowledge gap, our study delves into the neural mechanisms of self-regulation learning via neurofeedback and investigates the brain processes associated with successful brain self-regulation. Methods: We study the neural underpinnings of self-regulation learning by employing dynamical causal modeling (DCM) in conjunction with real-time functional MRI data. The study involved a cohort of 18 participants undergoing neurofeedback training targeting the supplementary motor area. A critical focus was the comparison between top-down hierarchical connectivity models proposed by Active Inference and alternative bottom-up connectivity models like reinforcement learning. Results: Our analysis revealed a crucial distinction in brain connectivity patterns between successful and non-successful learners. Particularly, successful learners evinced a significantly stronger top-down effective connectivity towards the target area implicated in self-regulation. This heightened top-down network engagement closely resembles the patterns observed in goal-oriented and cognitive control studies, shedding light on the intricate cognitive processes intertwined with self-regulation learning. Discussion: The findings from our investigation underscore the significance of cognitive mechanisms in the process of self-regulation learning through neurofeedback. The observed stronger top-down effective connectivity in successful learners indicates the involvement of hierarchical cognitive control, which aligns with the tenets of Active Inference. This study contributes to a deeper understanding of the neural dynamics behind successful self-regulation learning and provides insights into the potential cognitive architecture underpinning this process