Connection and disconnection as predictors of mental health and wellbeing

Despite the established literature on connection to others, and burgeoning research on self-connection, researchers have paid little attention to the equivalent experiences of disconnection that people can experience in their everyday lives. The current research examined connection and disconnection from oneself and others. Specifically, across two studies, participants listed up to twenty words or phrases that they experienced related to each form of (dis)connection. Study 1 focused on how these affected participants’ mental health (i.e. anxiety and depression), while study 2 examined positive forms of wellbeing (i.e., flourishing and life satisfaction). Results suggested that increased mental health was most strongly related to a greater experience of connection to others. Flourishing also increased as one’s experience of other-connection increased. By contrast, poorer wellbeing was related to a greater experience of disconnection from others. Finally, life satisfaction decreased when participants experienced greater self-disconnection. In all, these findings provide an initial test of and support for the continued examination of various forms of both connection and disconnection

Dark Sector Glueballs at the LHC

We study confining dark sectors where the lightest hadrons are glueballs. Such models can provide viable dark matter candidates and appear in some neutral naturalness scenarios. In this work, we introduce a new phenomenological model of dark glueball hadronization inspired by the Lund string model. This enables us to make realistic predictions for dark glueball phenomenology at the LHC for the first time. Our model reproduces the expected thermal distribution of hadron species as an emergent consequence of hadronization dynamics. The ability to predict the production of glueball states heavier than the lightest species significantly expands the reach of long-lived glueball searches in MATHUSLA compared to previous simplified estimates. We also characterize regions of parameter space where emerging and/or semivisible jets could arise from pure-glue dark sectors, thereby providing new benchmark models that motivate searches for these signatures.Comment: 27 pages + appendices + references, 11 + 4 figure

Early life metal dysregulation in amyotrophic lateral sclerosis

ObjectiveDeficiencies and excess of essential elements and toxic metals are implicated in amyotrophic lateral sclerosis (ALS), but the age when metal dysregulation appears remains unknown. This study aims to determine whether metal uptake is dysregulated during childhood in individuals eventually diagnosed with ALS.MethodsLaser ablation- inductively coupled plasma- mass spectrometry was used to obtain time series data of metal uptake using biomarkers in teeth from autopsies or dental extractions of ALS (n = 36) and control (n = 31) participants. Covariate data included sex, smoking, occupational exposures, and ALS family history. Case- control differences were identified in temporal profiles of metal uptake for individual metals using distributed lag models. Weighted quantile sum (WQS) regression was used for metals mixture analyses. Similar analyses were performed on an ALS mouse model to further verify the relevance of dysregulation of metals in ALS.ResultsMetal levels were higher in cases than in controls: 1.49 times for chromium (1.11- 1.82; at 15 years), 1.82 times for manganese (1.34- 2.46; at birth), 1.65 times for nickel (1.22- 2.01; at 8 years), 2.46 times for tin (1.65- 3.30; at 2 years), and 2.46 times for zinc (1.49- 3.67; at 6 years). Co- exposure to 11 elements indicated that childhood metal dysregulation was associated with ALS. The mixture contribution of metals to disease outcome was likewise apparent in tooth biomarkers of an ALS mouse model, and differences in metal distribution were evident in ALS mouse brains compared to brains from littermate controls.InterpretationOverall, our study reveals direct evidence that altered metal uptake during specific early life time windows is associated with adult- onset ALS.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155978/1/acn351006_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155978/2/acn351006.pd

The MATHUSLA Test Stand

The rate of muons from LHC $pp$ collisions reaching the surface above the ATLAS interaction point is measured and compared with expected rates from decays of $W$ and $Z$ bosons and $b$- and $c$-quark jets. In addition, data collected during periods without beams circulating in the LHC provide a measurement of the background from cosmic ray inelastic backscattering that is compared to simulation predictions. Data were recorded during 2018 in a 2.5 $\times$ 2.5 $\times$ 6.5~$\rm{m}^3$ active volume MATHUSLA test stand detector unit consisting of two scintillator planes, one at the top and one at the bottom, which defined the trigger, and six layers of RPCs between them, grouped into three $(x,y)$-measuring layers separated by 1.74 m from each other. Triggers selecting both upward-going tracks and downward-going tracks were used.Comment: 18 pages, 11 figures, 1 tabl

Early-Life Critical Windows of Susceptibility to Manganese Exposure and Sex-Specific Changes in Brain Connectivity in Late Adolescence

Background: Early-life environmental exposures during critical windows (CWs) of development can impact life course health. Exposure to neuroactive metals such as manganese (Mn) during prenatal and early postnatal CWs may disrupt typical brain development, leading to persistent behavioral changes. Males and females may be differentially vulnerable to Mn, presenting distinctive CWs to Mn exposure. Methods: We used magnetic resonance imaging to investigate sex-specific associations between early-life Mn uptake and intrinsic functional connectivity in adolescence. A total of 71 participants (15-23 years old; 53% female) from the Public Health Impact of Manganese Exposure study completed a resting-state functional magnetic resonance imaging scan. We estimated dentine Mn concentrations at prenatal, postnatal, and early childhood periods using laser ablation-inductively coupled plasma-mass spectrometry. We performed seed-based correlation analyses to investigate the moderating effect of sex on the associations between Mn and intrinsic functional connectivity adjusting for age and socioeconomic status. Results: We identified significant sex-specific associations between dentine Mn at all time points and intrinsic functional connectivity in brain regions involved in cognitive and motor function: 1) prenatal: dorsal striatum, occipital/frontal lobes, and middle frontal gyrus; 2) postnatal: right putamen and cerebellum; and 3) early childhood: putamen and occipital, frontal, and temporal lobes. Network associations differed depending on exposure timing, suggesting that different brain networks may present distinctive CWs to Mn. Conclusions: These findings suggest that the developing brain is vulnerable to Mn exposure, with effects lasting through late adolescence, and that females and males are not equally vulnerable to these effects. Future studies should investigate cognitive and motor outcomes related to these associations

The Oslo Health Study: The impact of self-selection in a large, population-based survey

BACKGROUND: Research on health equity which mainly utilises population-based surveys, may be hampered by serious selection bias due to a considerable number of invitees declining to participate. Sufficient information from all the non-responders is rarely available to quantify this bias. Predictors of attendance, magnitude and direction of non-response bias in prevalence estimates and association measures, are investigated based on information from all 40 888 invitees to the Oslo Health Study. METHODS: The analyses were based on linkage between public registers in Statistics Norway and the Oslo Health Study, a population-based survey conducted in 2000/2001 inviting all citizens aged 30, 40, 45, 59–60 and 75–76 years. Attendance was 46%. Weighted analyses, logistic regression and sensitivity analyses are performed to evaluate possible selection bias. RESULTS: The response rate was positively associated with age, educational attendance, total income, female gender, married, born in a Western county, living in the outer city residential regions and not receiving disability benefit. However, self-rated health, smoking, BMI and mental health (HCSL) in the attendees differed only slightly from estimated prevalence values in the target population when weighted by the inverse of the probability of attendance. Observed values differed only moderately provided that the non-attending individuals differed from those attending by no more than 50%. Even though persons receiving disability benefit had lower attendance, the associations between disability and education, residential region and marital status were found to be unbiased. The association between country of birth and disability benefit was somewhat more evident among attendees. CONCLUSIONS: Self-selection according to sociodemographic variables had little impact on prevalence estimates. As indicated by disability benefit, unhealthy persons attended to a lesser degree than healthy individuals, but social inequality in health by different sociodemographic variables seemed unbiased. If anything we would expect an overestimation of the odds ratio of chronic disease among persons born in non-western countries

Mesenchymal inflammation drives genotoxic stress in hematopoietic stem cells and predicts disease evolution in human pre-leukemia

Mesenchymal niche cells may drive tissue failure and malignant transformation in the hematopoietic system but the molecular mechanisms and their relevance to human disease remain poorly defined. Here, we show that perturbation of mesenchymal cells in a mouse model of the preleukemic disorder Shwachman-Diamond syndrome induces mitochondrial dysfunction, oxidative stress and activation of DNA damage responses in hematopoietic stem and progenitor cells. Massive parallel RNA sequencing of highly purified mesenchymal cells in the mouse model and a range of human preleukemic syndromes identified p53-S100A8/9-TLR inflammatory signaling as a common driving mechanism of genotoxic stress. Transcriptional activation of this signaling axis in the mesenchymal niche predicted leukemic evolution and progression-free survival in myelodysplastic syndrome, the principal leukemia predisposition syndrome. Collectively, our findings reveal a concept of mesenchymal niche-induced genotoxic stress in heterotypic stem and progenitor cells through inflammatory signaling as an actionable determinant of disease outcome in human preleukemia

Recent Progress and Next Steps for the MATHUSLA LLP Detector

We report on recent progress and next steps in the design of the proposed MATHUSLA Long Lived Particle (LLP) detector for the HL-LHC as part of the Snowmass 2021 process. Our understanding of backgrounds has greatly improved, aided by detailed simulation studies, and significant R&D has been performed on designing the scintillator detectors and understanding their performance. The collaboration is on track to complete a Technical Design Report, and there are many opportunities for interested new members to contribute towards the goal of designing and constructing MATHUSLA in time for HL-LHC collisions, which would increase the sensitivity to a large variety of highly motivated LLP signals by orders of magnitude.Comment: Contribution to Snowmass 2021 (EF09, EF10, IF6, IF9), 18 pages, 12 figures. v2: included additional endorser

Overcoming leakage in scalable quantum error correction

Leakage of quantum information out of computational states into higher energy states represents a major challenge in the pursuit of quantum error correction (QEC). In a QEC circuit, leakage builds over time and spreads through multi-qubit interactions. This leads to correlated errors that degrade the exponential suppression of logical error with scale, challenging the feasibility of QEC as a path towards fault-tolerant quantum computation. Here, we demonstrate the execution of a distance-3 surface code and distance-21 bit-flip code on a Sycamore quantum processor where leakage is removed from all qubits in each cycle. This shortens the lifetime of leakage and curtails its ability to spread and induce correlated errors. We report a ten-fold reduction in steady-state leakage population on the data qubits encoding the logical state and an average leakage population of less than $1 \times 10^{-3}$ throughout the entire device. The leakage removal process itself efficiently returns leakage population back to the computational basis, and adding it to a code circuit prevents leakage from inducing correlated error across cycles, restoring a fundamental assumption of QEC. With this demonstration that leakage can be contained, we resolve a key challenge for practical QEC at scale.Comment: Main text: 7 pages, 5 figure