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The addition of molecular dopants into organic semiconductors (OSCs) is a ubiquitous augmentation strategy to enhance the electrical conductivity of OSCs. Although the importance of optimizing OSC–dopant interactions is well-recognized, chemically generalizable structure–function relationships are difficult to extract due to the sensitivity and dependence of doping efficiency on chemistry, processing conditions, and morphology. Computational modeling for an integrated OSC–dopant design is an attractive approach to systematically isolate fundamental relationships, but requires the challenging simultaneous treatment of molecular reactivity and morphology evolution. We present the first computational study to couple molecular reactivity with morphology evolution in a molecularly doped OSC. Reactive Monte Carlo is employed to examine the evolution of OSC–dopant morphologies and doping efficiency with respect to dielectric, the thermodynamic driving for the doping reaction, and dopant aggregation. We observe that for well-mixed systems with experimentally relevant dielectric constants, doping efficiency is near unity with a very weak dependence on the ionization potential and electron affinity of OSC and dopant, respectively. At experimental dielectric constants, reaction-induced aggregation is observed, corresponding to the well-known insolubility of solution-doped materials. Simulations are qualitatively consistent with a number of experimental studies showing a decrease of doping efficiency with increasing dopant concentration. Finally, we observe that the aggregation of dopants lowers doping efficiency and thus presents a rational design strategy for maximizing doping efficiency in molecularly doped OSCs. This work represents an important first step toward the systematic integration of molecular reactivity and morphology evolution into the characterization of multi-scale structure–function relationships in molecularly doped OSCs. [ABSTRACT FROM AUTHOR]

We employ deep kernel learning electronic coarse-graining (DKL-ECG) with approximate Gaussian processes as a flexible and scalable framework for learning heteroscedastic electronic property distributions as a smooth function of coarse-grained (CG) configuration. The appropriateness of the Gaussian prior on predictive CG property distributions is justified as a function of CG model resolution by examining the statistics of target distributions. The certainties of predictive CG distributions are shown to be limited by CG model resolution with DKL-ECG predictive noise converging to the intrinsic physical noise induced by the CG mapping operator for multiple chemistries. Further analysis of the resolution dependence of learned CG property distributions allows for the identification of CG mapping operators that capture CG degrees of freedom with strong electron–phonon coupling. We further demonstrate the ability to construct the exact quantum chemical valence electronic density of states (EDOS), including behavior in the tails of the EDOS, from an entirely CG model by combining iterative Boltzmann inversion and DKL-ECG. DKL-ECG provides a means of learning CG distributions of all-atom properties that are traditionally "lost" in CG model development, introducing a promising methodological alternative to backmapping algorithms commonly employed to recover all-atom property distributions from CG simulations. [ABSTRACT FROM AUTHOR]

The University of California (UC) implemented the Diabetes Prevention Program (DPP) to address diabetes and obesity risk. This project examined the reach and effectiveness of this university-based DPP delivery approach. This project compared 12-month weight change among three groups of UC beneficiaries with overweight/obesity: (1) those who received invitation letters and enrolled in UC DPP, (2) those mailed invitation letters but did not enroll, and (3) those who were not mailed letters and did not enroll (controls). Using 2012–2022 EHR, administrative and DPP cohort data, an interrupted time series was conducted in 2022–2023 to compare group differences in rate of weight change. Among 6,231 beneficiaries (132 UC DPP aware enrollees, 1,750 DPP aware non-enrollees, 4,349 controls), UC DPP enrollees were older (mean age 49), mostly women (76%), and more diverse (33% Asian, 8% Black, 20% Hispanic, 4% Multi/Other). Over 12 months of follow-up, UC DPP enrollee postenrollment rate of weight loss was −0.68 lbs./month. UC DPP enrollees had significantly greater weight change from pre- to post-enrollment than DPP aware non-enrollees (adjusted Δ-1.02 vs. Δ-0.07 lbs./month, difference= −0.95, p <0.001). Weight change among all participants who received letters with/without DPP enrollment was similar to controls. UC DPP reached a diverse group and was effective for weight loss at 12-month follow-up. However, UC DPP invitation letters to raise prediabetes and DPP awareness were not associated with significant weight change in the absence of DPP enrollment. University-based approaches to DPP delivery are effective and may enhance reach of DPP among at-risk adults. [ABSTRACT FROM AUTHOR]

Emerging photovoltaic technologies continue to march forward with power conversion efficiencies of lead halide perovskite solar cells (PSCs) nearing 26%, perovskite-Si tandems now exceeding the single junction detailed balance limit of 33%, and organic solar cells (OSCs) showing efficiencies nearing 20%. Yang and Yang[16] use transient absorption spectroscopy to investigate the recombination dynamics of photocarriers in a multilayer indium selenide nanofilm, showing that exciton-exciton annihilation is inefficient in multilayers due to weaker Coulomb interactions. [Extracted from the article]

This study describes a novel, distinct phenotype of urinary symptoms named "myofascial urinary frequency syndrome" (MUFS) present in one-third of individuals presenting with urinary frequency. In addition to a characteristic symptom constellation suggestive of myofascial dysfunction, MUFS subjects exhibit "persistency": a persistent feeling of needing to urinate regardless of urine volume. On examination, 97% of MUFS patients demonstrated pelvic floor hypertonicity with either global tenderness or myofascial trigger points, and 92% displayed evidence of impaired muscular relaxation, hallmarks of myofascial dysfunction. To confirm this symptom pattern was attributable to the pelvic floor musculature, we confirmed the presence of "persistency" in 68 patients with pelvic floor myofascial dysfunction established through comprehensive examination and electromyography and corroborated by improvement with pelvic floor myofascial release. These symptoms distinguish subjects with myofascial dysfunction from subjects with OAB, IC/BPS, and asymptomatic controls, confirming MUFS is a distinct LUTS symptom complex. [ABSTRACT FROM AUTHOR]

Despite growing interest in polymers under extreme conditions, most atomistic molecular dynamics simulations cannot describe the bond scission events underlying failure modes in polymer networks undergoing large strains. In this work, we propose a physics-based machine learning approach that can detect and perform bond breaking with near quantum-chemical accuracy on-the-fly in atomistic simulations. Particularly, we demonstrate that by coarse-graining highly correlated neighboring bonds, the prediction accuracy can be dramatically improved. By comparing with existing quantum mechanics/molecular mechanics methods, our approach is approximately two orders of magnitude more efficient and exhibits improved sensitivity toward rare bond breaking events at low strain. The proposed bond breaking molecular dynamics scheme enables fast and accurate modeling of strain hardening and material failure in polymer networks and can accelerate the design of polymeric materials under extreme conditions. [ABSTRACT FROM AUTHOR]

Interventions to better coordinate care for high-need high-cost (HNHC) Medicaid patients frequently fail to demonstrate changes in hospitalizations or emergency department (ED) use. Many of these interventions are modeled after practice-level complex care management (CCM) programs. The authors hypothesized that a national CCM program may be effective for some subgroups of HNHC patients, and the overall null effect may obfuscate subgroup-level impact. They used a previously published typology defining 6 subgroups of high-cost Medicaid patients and evaluated program impact by subgroup. The analysis used an individual-level interrupted time series with a comparison group. Intervention subjects were high-cost adult Medicaid patients who enrolled in 1 of 2 national CCM programs implemented by UnitedHealthcare (UHC) (n = 39,687). The comparators were patients who met CCM program criteria but were ineligible due to current enrollment in another UHC/Optum led program (N = 26,359). The intervention was a CCM program developed by UHC/Optum to provide "whole person care" delivering standardized interventions to address medical, behavioral, and social needs for HNHC Medicaid patients, and the outcome was probability of hospitalization or ED use in a given month, estimated at 12 months postenrollment. A reduction in risk of ED utilization for 4 of 6 subgroups was found. A reduction in risk of hospitalization for 1 of 6 subgroups was also found. The authors conclude that standardized health plan led CCM programs demonstrate effectiveness for certain subgroups of HNHC patients in Medicaid. This effectiveness is principally in reducing ED risk and may extend to the risk of hospitalization for a small number of patients. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to characterize the physiologic response of both eyelid and eyebrow position to increasing downward forces simulated by external weights. Methods: In this prospective observational study, both normal individuals and patients affected by ptosis were tested. External eyelid weights were placed on one upper eyelid with incrementally increasing weight from 0.2 to 2.4 g. The eyelid carrying the weight was randomly selected for normal subjects and patients with bilateral ptosis, whereas for unilateral ptosis, the ptotic eyelid was utilized. Photographs were obtained at baseline and with increasing weight until MRD1 reached 0 on the weighted side or, until 2.4 g was reached. Eyelid and brow position on the weighted and unweighted sides were digitally measured in millimeter. Primary outcome measures were change in the margin to reflex distance (MRD1) and pupil to brow distance (PTB) with weight on the weighted and unweighted sides for normal and ptosis subjects. Results: The weighted eyelid MRD1 decreased linearly with increasing weight. This was true for normal and ptosis subjects. The unweighted eyelid MRD1 increased linearly with increasing weight. This was also the case for both normal and ptosis subjects. With increasing weight, PTB increased linearly on the weighted side. No significant intergroup differences were noted. Conclusions: In normal and ptosis subjects, when external weight on the eyelid is incrementally increased, the weighted eyelid MRD1 decreases, the unweighted eyelid MRD1 increases, and both brows elevate in a linear fashion. [ABSTRACT FROM AUTHOR]

In this intervention article, we cultivate an anti- colonial critique of the ideational genealogy and conceptual materialisation of the social licence to operate (SLO) in the extractive industries in order to open a conversation about the racialised and colonial logics underlying its enactment and discursive practices. SLO functions to restrict the emergence of imaginary political potentials within communities impacted by extractive projects. We focus on the role of academics and social science researchers within and beyond the space of the university in engineering, shaping, and promoting dominant SLO frameworks, and endorsing the power and mythology of SLO. We do so in conversation with decolonial orientations that simultaneously analyse the colonial logics within corporate practice and galvanise epistemic justice beyond colonial and epistemic extractivism. The university, as a site for the refinement and promotion of hegemonic concepts like SLO, is an important space for post-extractive struggles. [ABSTRACT FROM AUTHOR]

A configurational sampling algorithm based on nested layerings of Markov chains (Layered Nested Markov Chain Monte Carlo or L-NMCMC) is presented for simulations of systems characterized by rugged free energy landscapes. The layerings are generated using a set of auxiliary potential energy surfaces. The implementation of the method is demonstrated in the context of a rugged, two-dimensional potential energy surface. The versatility of the algorithm is next demonstrated on a simple, many-body system, namely, a canonical Lennard-Jones fluid in the liquid state. In that example, different layering schemes and auxiliary potentials are used, including variable cutoff distances and excluded-volume tempering. In addition to calculating a variety of properties of the system, it is also shown that L-NMCMC, when combined with a free-energy perturbation formalism, provides a straightforward means to construct approximate free-energy surfaces at no additional computational cost using the sampling distributions of each auxiliary Markov chain. The proposed L-NMCMC scheme is general in that it could be complementary to any number of methods that rely on sampling from a target distribution or methods that exploit a hierarchy of time scales and/or length scales through decomposition of the potential energy. [ABSTRACT FROM AUTHOR]

Bottom-up methods for coarse-grained (CG) molecular modeling are critically needed to establish rigorous links between atomistic reference data and reduced molecular representations. For a target molecule, the ideal reduced CG representation is a function of both the conformational ensemble of the system and the target physical observable(s) to be reproduced at the CG resolution. However, there is an absence of algorithms for selecting CG representations of molecules from which complex properties, including molecular electronic structure, can be accurately modeled. We introduce continuously gated message passing (CGMP), a graph neural network (GNN) method for atomically decomposing molecular electronic structure sampled over conformational ensembles. CGMP integrates 3D-invariant GNNs and a novel gated message passing system to continuously reduce the atomic degrees of freedom accessible for electronic predictions, resulting in a one-shot importance ranking of atoms contributing to a target molecular property. Moreover, CGMP provides the first approach by which to quantify the degeneracy of "good" CG representations conditioned on specific prediction targets, facilitating the development of more transferable CG representations. We further show how CGMP can be used to highlight multiatom correlations, illuminating a path to developing CG electronic Hamiltonians in terms of interpretable collective variables for arbitrarily complex molecules. [ABSTRACT FROM AUTHOR]

We develop a lattice model utilizing coarse-grained molecular sites to study charge transport in molecular semiconducting materials. The model bridges atomistic descriptions and structureless lattice models by mapping molecular structure onto sets of spatial vectors isomorphic with spin vectors in a classical n-vector Heisenberg model. Specifically, this model incorporates molecular topologydependent orientational and intermolecular coupling preferences, including the direct inclusion of spatially correlated transfer integrals and site energy disorder. This model contains the essential physics required to explicitly simulate the interplay of molecular topology and correlated structural disorder, and their effect on charge transport. As a demonstration of its utility, we apply this model to analyze the effects of long-range orientational correlations, molecular topology, and intermolecular interaction strength on charge motion in bulk molecular semiconductors. [ABSTRACT FROM AUTHOR]

Background: Opioid (OPD), sedative (SDT), and antidepressant (ADM) prescribing has increased dramatically over the last 20 years. This study evaluated preoperative OPD, SDT, and ADM use on hospital costs in patients undergoing colorectal resection at a single institution. Methods: This study was a retrospective record review. The local ACS-NSQIP database was queried for adult patients (age ≥ 18 years) undergoing open/laparoscopic, partial/total colectomy, or proctectomy from January 1, 2013 to December 31, 2016. Individual patient medical records were reviewed to determine preoperative OPD, SDT, and AD use. Hospital cost data from index admission were captured by the hospital cost accounting system and matched to NSQIP query-identified cases. All ACS-NSQIP categorical patient characteristic, operative risk, and outcome variables were compared in medication groups using chi-square tests or Fisher's exact tests, and continuous variables were compared using Mann–Whitney U tests. Results: A total of 1185 colorectal procedures were performed by 30 different surgeons. Of these, 27.6% patients took OPD, 18.5% SDT, and 27.8% ADM preoperatively. Patients taking OPD, SDT, and ADM were found to have increased mean total hospital costs (MTHC) compared to non-users (30.8 vs 23.6 for OPD, 31.6 vs 24.4 for SDT, and 30.7 vs 23.8 for ADM). OPD and SDT use were identified as independent risk factors for increased MTHC on multivariable analysis. Conclusion: Preoperative OPD and SDT use can be used to predict increased MTHC in patients undergoing colorectal resections. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes can negatively impact long term health outcomes, healthcare costs and quality of life. However, intensive lifestyle interventions, including the Diabetes Prevention Program (DPP), can significantly lower risk of incident type 2 diabetes among overweight adults with prediabetes. Unfortunately, the majority of adults in the US who are at risk of developing diabetes do not engage in DPP-based lifestyle change programs. Increased adoption of evidence-based obesity and diabetes prevention interventions, such as the DPP, may help large employers reduce health risks and improve health outcomes among employees. In 2018, the University of California Office of thePresident (UCOP) implemented the UC DPP Initiative, a novel, multi-component program to address diabetes and obesity prevention across the UC system.Methods: The goal of our study is to conduct a multifaceted evaluation of the UC DPP Initiative using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Our evaluation will integrate unique and diverse UC data sources, including electronic health record (EHR) data, administrative claims, campus-based DPP cohort data, qualitative interviews and site visits. Our primary outcome of interest is the mean percent weight change among three groups of overweight/obese UC beneficiaries at risk for diabetes at 12-month follow-up. Secondary outcomes include mean percent weight change at 24-month follow-up, barriers and facilitators associated with implementatio, as well as  the degree of program adoption and maintenance.Discussion: Our study will help inform diabetes and obesity prevention efforts across the UC system. Findings from this evaluation will also be highly applicable to universities and large employers, as well as community organizers, healthcare organizations and insurers implementing the DPP and/or other health promotion interventions. [ABSTRACT FROM AUTHOR]

Introduction: Different endpoint criteria, different durations of follow-up and the completeness of follow-up can dramatically affect the perceived benefits of atrial fibrillation (AF) ablation.Methods: We defined three endpoints for recurrence of AF post ablation in a cohort of 200 patients with symptomatic AF, refractory to antiarrhythmic drugs (AADs). A 'Strict Endpoint' where patients were considered to have a recurrence with any symptomatic or documented recurrence for ≥30 seconds with no blanking period, and off their AADs, a 'Liberal Endpoint' where only documented recurrences after the blanking period, either on or off AADs were counted, and a 'Patient-defined Outcome endpoint' which was the same as the Liberal endpoint but allowed for up to two recurrences and one repeat ablation or DCCV during follow-up. We also surveyed 50 patients on the waiting list for an AF ablation and asked them key questions regarding what they would consider to be a successful result for them.Results: Freedom from recurrence of atrial tachyarrhythmias (AT) at 5 years was 62% for the Strict Endpoint, 73% for the Liberal Endpoint, and 80% for the Patient-defined Outcome endpoint (p<0.001). Of the 50 patients surveyed awaiting AF ablation, 70% said they would still consider the procedure a success if it required one repeat ablation or one DCCV (p=0.004), and 76% would be accepting of one or two recurrences during follow-up (p<0.001).Conclusion: In this study, the majority of patients still considered AF ablation a successful treatment if they had up to two recurrences of AF, one repeat procedure or one DCCV. Furthermore, a 'Patient-defined' definition of success lead to significantly different results in this AF ablation cohort when compared to conventionally used/guideline directed measures of success. [ABSTRACT FROM AUTHOR]

Background: Technological burden and medical complexity are significant drivers of clinician burnout. Electronic health record(EHR)-based population health management tools can be used to identify high-risk patient populations and implement prophylactic health practices. Their impact on clinician burnout, however, is not well understood. Our objective was to assess the relationship between ratings of EHR-based population health management tools and clinician burnout. Methods: We conducted cross-sectional analyses of 2018 national Veterans Health Administration(VA) primary care personnel survey, administered as an online survey to all VA primary care personnel (n = 4257, response rate = 17.7%), using bivariate and multivariate logistic regressions. Our analytical sample included providers (medical doctors, nurse practitioners, physicians' assistants) and nurses (registered nurses, licensed practical nurses). The outcomes included two items measuring high burnout. Primary predictors included importance ratings of 10 population health management tools (eg. VA risk prediction algorithm, recent hospitalizations and emergency department visits, etc.). Results: High ratings of 9 tools were associated with lower odds of high burnout, independent of covariates including VA tenure, team role, gender, ethnicity, staffing, and training. For example, clinicians who rated the risk prediction algorithm as important were less likely to report high burnout levels than those who did not use or did not know about the tool (OR 0.73; CI 0.61-0.87), and they were less likely to report frequent burnout (once per week or more) (OR 0.71; CI 0.60-0.84). Conclusions: Burned-out clinicians may not consider the EHR-based tools important and may not be using them to perform care management. Tools that create additional technological burden may need adaptation to become more accessible, more intuitive, and less burdensome to use. Finding ways to improve the use of tools that streamline the work of population health management and/or result in less workload due to patients with poorly managed chronic conditions may alleviate burnout. More research is needed to understand the causal directional of the association between burnout and ratings of population health management tools. [ABSTRACT FROM AUTHOR]

Background: Hospital readmission rates decreased for myocardial infarction (AMI), heart failure (CHF), and pneumonia with implementation of the first phase of the Hospital Readmissions Reduction Program (HRRP). It is not established whether readmissions fell for chronic obstructive pulmonary disease (COPD), an HRRP condition added in 2014. Objective: We sought to determine whether HRRP penalties influenced COPD readmissions among Medicare, Medicaid, or privately insured patients. Design: We analyzed a retrospective cohort, evaluating readmissions across implementation periods for HRRP penalties ("pre-HRRP" January 2010–April 2011, "implementation" May 2011–September 2012, "partial penalty" October 2012–September 2014, and "full penalty" October 2014–December 2016). Patients: We assessed discharged patients ≥ 40 years old with COPD versus those with HRRP Phase 1 conditions (AMI, CHF, and pneumonia) or non-HRRP residual diagnoses in the Nationwide Readmissions Database. Interventions: HRRP was announced and implemented during this period, forming a natural experiment. Measurements: We calculated differences-in-differences (DID) for 30-day COPD versus HRRP Phase 1 and non-HRRP readmissions. Key Results: COPD discharges for 1.2 million Medicare enrollees were compared with 22 million non-HRRP and 3.4 million HRRP Phase 1 discharges. COPD readmissions decreased from 19 to 17% over the study. This reduction was significantly greater than non-HRRP conditions (DID − 0.41%), but not HRRP Phase 1 (DID + 0.02%). A parallel trend was observed in the privately insured, with significant reduction compared with non-HRRP (DID − 0.83%), but not HRRP Phase 1 conditions (DID − 0.45%). Non-significant reductions occurred in Medicaid (DID − 0.52% vs. non-HRRP and − 0.21% vs. Phase 1 conditions). Conclusions: In Medicare, HRRP implementation was associated with reductions in COPD readmissions compared with non-HRRP controls but not versus other HRRP conditions. Parallel findings were observed in commercial insurance, but not in Medicaid. Condition-specific penalties may not reduce readmissions further than existing HRRP trends. [ABSTRACT FROM AUTHOR]

The article discusses the chemical design of polymers with target structural and/or functional properties represents a grand challenge in materials science. Topics include machine learning algorithms, enabled by preexisting experimental and computational data, have emerged as powerful tools for molecular property prediction and design; and the directed design of polymers with tailored composition or sequence has considerable potential in numerous application areas.

Introduction and Hypothesis: As interstitial cystitis/bladder pain syndrome (IC/BPS) likely represents multiple pathophysiologies, we sought to validate three clinical phenotypes of IC/BPS patients in a large, multi-center cohort using unsupervised machine learning (ML) analysis. Methods: Using the female Genitourinary Pain Index and O'Leary-Sant Indices, k-means unsupervised clustering was utilized to define symptomatic phenotypes in 130 premenopausal IC/BPS participants recruited through the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) research network. Patient-reported symptoms were directly compared between MAPP ML-derived phenotypic clusters to previously defined phenotypes from a single center (SC) cohort. Results: Unsupervised ML categorized IC/BPS participants into three phenotypes with distinct pain and urinary symptom patterns: myofascial pain, non-urologic pelvic pain, and bladder-specific pain. Defining characteristics included presence of myofascial pain or trigger points on examination for myofascial pain patients (p = 0.003) and bladder pain/burning for bladder-specific pain patients (p < 0.001). The three phenotypes were derived using only 11 features (fGUPI subscales and ICSI/ICPI items), in contrast to 49 items required previously. Despite substantial reduction in classification features, unsupervised ML independently generated similar symptomatic clusters in the MAPP cohort with equivalent symptomatic patterns and physical examination findings as the SC cohort. Conclusions: The reproducible identification of IC/BPS phenotypes, distinguishing bladder-specific pain from myofascial and genital pain, using independent ML analysis of a multicenter database suggests these phenotypes reflect true pathophysiologic differences in IC/BPS patients. [ABSTRACT FROM AUTHOR]

Responding to calls for increased attention to actions and reactions "from above" within the extractive industry, we offer a decolonial critique of the ways in which corporate entities and multinational institutions draw on racialized rhetoric of "local" suffering, "local" consultation, and "local" culpability in oil as development. Such rhetoric functions to legitimize extractive intervention within a set of practices that we call localwashing. Drawing from a decade of research on and along the Chad–Cameroon Oil Pipeline, we show how multiscalar actors converged to assert knowledge of, responsibility for, and collaborations with "local" people within a racialized politics of scale. These corporate representations of the racialized "local" are coded through long-standing colonial tropes. We identify three interrelated and overlapping flexian elite rhetoric(s) and practices of racialized localwashing: (1) anguishing, (2) arrogating, and (3) admonishing. These elite representations of a racialized "local" reveal diversionary efforts "from above" to manage public opinion, displace blame for project failures, and domesticate dissent in a context of persistent scrutiny and criticism from international and regional advocates and activists. Key Words: coloniality, decolonial, elite, extraction, racism. [ABSTRACT FROM AUTHOR]

Background: The most frequent complications from percutaneous electrophysiology procedures relate to vascular access. We sought to perform the first randomised controlled trial for femoral venous haemostasis utilising a simple and novel purse string suture (PSS) technique.Methods: We randomised 200 consecutive patients who were referred for electrophysiology procedures at two different hospitals to either 10minutes of manual pressure or a PSS over the femoral vein and determined the incidence of vascular access site complications.Results: The mean age was 61.8±12.1years and 138 (69%) were male. Bleeding requiring addition pressure or a FemStop (Abbott Laboratories, Abbott Park, IL, USA) for complete haemostasis occurred in 17/99 (17%) patients in the PSS arm and 19/101 (19%) patients in the manual pressure arm (p=0.72). There were no cases of haematoma prolonging hospital stay, arterio-venous fistula, pseudoaneurysm or retroperitoneal bleeding. The mean duration to achieve haemostasis was 45seconds in the PSS arm and 10minutes 44seconds in the manual pressure arm (p<0.001). Pain/discomfort associated with haemostasis occurred in 15/99 (15%) patients in the PSS arm and in 29/101 (29%) patients receiving manual pressure (p=0.03).Conclusions: In this randomised trial we demonstrate that an easy to perform PSS is as effective at achieving haemostasis as 10minutes of manual pressure for catheter ablation procedures. The PSS is considerably faster to perform and is more comfortable for patients than manual pressure. [ABSTRACT FROM AUTHOR]

Background Survival after heart transplantation (HTx) is limited by complications related to alloreactivity, immune suppression, and adverse effects of pharmacologic therapies. We hypothesize that time-dependent phenomapping of clinical and molecular data sets is a valuable approach to clinical assessments and guiding medical management to improve outcomes. Methods We analyzed clinical, therapeutic, biomarker, and outcome data from 94 adult HTx patients and 1,557 clinical encounters performed between January 2010 and April 2013. Multivariate analyses were used to evaluate the association between immunosuppression therapy, biomarkers, and the combined clinical end point of death, allograft loss, retransplantation, and rejection. Data were analyzed by K -means clustering ( K = 2) to identify patterns of similar combined immunosuppression management, and percentile slopes were computed to examine the changes in dosages over time. Findings were correlated with clinical parameters, human leucocyte antigen antibody titers, and peripheral blood mononuclear cell gene expression of the AlloMap (CareDx, Inc., Brisbane, CA) test genes. An intragraft, heart tissue gene coexpression network analysis was performed. Results Unsupervised cluster analysis of immunosuppressive therapies identified 2 groups, 1 characterized by a steeper immunosuppression minimization, associated with a higher likelihood for the combined end point, and the other by a less pronounced change. A time-dependent phenomap suggested that patients in the group with higher event rates had increased human leukocyte antigen class I and II antibody titers, higher expression of the FLT3 AlloMap gene, and lower expression of the MARCH8 and WDR40A AlloMap genes. Intramyocardial biomarker-related coexpression network analysis of the FLT3 gene showed an immune system–related network underlying this biomarker. Conclusions Time-dependent precision phenotyping is a mechanistically insightful, data-driven approach to characterize patterns of clinical care and identify ways to improve clinical management and outcomes. [ABSTRACT FROM AUTHOR]

Abstract: Background: Model of End‐Stage Liver Disease eXcluding INR (MELD‐XI) at cardiac transplant has demonstrated prognostic survival utility, but has not been specifically validated in adult congenital heart disease (ACHD) in a registry study. Methods: Adults undergoing first‐time orthotopic heart transplant from 2005 to 2015 in the United Network for Organ Sharing (UNOS) registry were examined in parallel: ACHD (n = 543), ischemic‐dilated cardiomyopathy (IDCM, n = 6954) and valvular heart disease (VHD, n = 355). Our primary endpoint was a composite of death, graft failure, and retransplantation assessed at 3 months (early), and those with freedom from early endpoint were reassessed at 5 years (late). Interactions between hepatorenal indices and waitlist time were examined. Secondary outcomes relating to long‐term morbidity were assessed at late endpoint. Freedom from endpoint analysis in ACHD at clinically relevant endpoints was also conducted. Results: Model of End‐Stage Liver Disease eXcluding INR score at transplant associated with an increased risk of early endpoint in all cohorts. At late endpoint, bilirubin level associated with increased risk uniquely in ACHD. Conclusions: Model of End‐Stage Liver Disease eXcluding INR holds prognostic application to ACHD in early time points and demonstrates unique waitlist interactions. Transplant bilirubin level may hold significance in long‐term risk stratification of the ACHD population. Time on waitlist is an important consideration to contextualize these values. [ABSTRACT FROM AUTHOR]

Subtle details about a polyelectrolyte's surrounding environment can dictate its structural features and potential applications. Atomic force microscopy (AFM), surface forces apparatus (SFA) measurements, and coarse-grained molecular dynamics simulations are combined to study the structure of planar polyelectrolyte brushes [poly(styrenesulfonate), PSS] in a variety of solvent conditions. More specifically, AFM images provide a first direct visualization of lateral inhomogeneities on the surface of polyelectrolyte brushes collapsed in solutions containing trivalent counterions. These images are interpreted in the context of a coarse-grained molecular model and are corroborated by accompanying interaction force measurements with the SFA. Our findings indicate that lateral inhomogeneities are absent from PSS brush layers collapsed in a poor solvent without multivalent ions. Together, AFM, SFA, and our molecular model present a detailed picture in which solvophobic and multivalent ion-induced effects work in concert to drive strong phase separation, with electrostatic bridging of polyelectrolyte chains playing an essential role in the collapsed structure formation. [ABSTRACT FROM AUTHOR]

The article reports changes in influenza vaccine uptake in the U.S. during the pandemic after COVID-19 vaccines became available. Topic discussed include data from Center for Disease Control and Prevention show changes in influenza vaccine uptake and data comparison that show that vaccine uptake remained relatively stable regardless of COVID-19 vaccine uptake.

Atrial myopathy may underlie the progression of atrial fibrillation (AF) from a treatable disease to an irreversible condition with poor ablation outcomes. Electrophysiological methods to unmask areas prone to re-entry initiation could be key to defining latent atrial myopathy. Consecutive patients referred for AF ablation were prospectively included at four institutions. Decrement evoked potential mapping (DEEP) was performed in eight left atrial sites and five right atrial sites, from two different pacing locations (endocardially from the left atrial appendage, epicardially from the proximal coronary sinus). The electrograms (EGMs) during S1 600 ms drive and after an extra stimulus (S2 at +30 ms above atrial refractoriness) were studied at each location and assessed for decremental properties. Follow-up was 12 months. Seventy-four patients were included and 85% had persistent AF. A total of 17,614 EGMs were individually analysed and measured. Nine percent of the EGMs showed DEEP properties (local delay of >10 ms after S2) with a mean decrement of 33±26 ms. DEEPs were more frequent in the left atrium than the right atrium (9.4% vs 8.0%; p<0.001) and more prevalent in persistent AF patients than paroxysmal AF patients (9.8% vs 4.6% p=0.001). Atrial DEEPs were more frequently unmasked in normal bipolar voltage areas and by epicardial pacing than endocardial pacing (9.6% vs 8.4%, respectively; p=0.004). Within the left atrium, the roof had the highest prevalence of DEEP EGMs. DEEP mapping of both atria is useful for highlighting areas with a tendency for unidirectional block and re-entry initiation. Those areas are more easily unmasked by epicardial pacing from the coronary sinus and more prevalent in persistent AF patients than in paroxysmal AF patients. [ABSTRACT FROM AUTHOR]

The theoretical description of the time-evolution of excitons requires, as an initial step, the calculation of their spectra, which has been inaccessible to most users due to the high computational scaling of conventional algorithms and accuracy issues caused by common density functionals. Previously (J. Chem. Phys.2016, 144, 204105), we developed a simple method that resolves these issues. Our scheme is based on a two-step calculation in which a linear-response TDDFT calculation is used to generate orbitals perturbed by the excitonic state, and then a second linear-response TDDFT calculation is used to determine the spectrum of excitations relative to the excitonic state. Herein, we apply this theory to study near-infrared absorption spectra of excitons in oligomers of the ubiquitous conjugated polymers poly(3-hexylthiophene) (P3HT), poly(2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene) (MEH-PPV), and poly(benzodithiophene-thieno[3,4-b]thiophene) (PTB7). For P3HT and MEH-PPV oligomers, the calculated intense absorption bands converge at the longest wavelengths for 10 monomer units, and show strong consistency with experimental measurements. The calculations confirm that the exciton spectral features in MEH-PPV overlap with those of the bipolaron formation. In addition, our calculations identify the exciton absorption bands in transient absorption spectra measured by our group for oligomers (1, 2, and 3 units) of PTB7. For all of the cases studied, we report the dominant orbital excitations contributing to the optically active excited state-excited state transitions, and suggest a simple rule to identify absorption peaks at the longest wavelengths. We suggest our methodology could be considered for further developments in theoretical transient spectroscopy to include nonadiabatic effects, coherences, and to describe the formation of species such as charge-transfer states and polaron pairs. [ABSTRACT FROM AUTHOR]

Aim: The complex interplay of externalizing and internalizing problems in substance use risk is not well understood. This study tested whether the relationship of conduct problems and several internalizing disorders with future substance use is redundant, incremental, or interactive in adolescents.Methods: Two semiannual waves of data from the Happiness and Health Study were used, which included 3383 adolescents (M age=14.1years old; 53% females) in Los Angeles who were beginning high school at baseline. Logistic regression models tested the likelihood of past six-month alcohol, tobacco, marijuana, and any substance use at follow-up conditional on baseline conduct problems, symptoms of one of several internalizing disorders (i.e., Social Phobia and Major Depressive, Generalized Anxiety, Panic, and Obsessive-Compulsive Disorder), and their interaction adjusting for baseline use and other covariates.Findings: Conduct problems were a robust and consistent risk factor of each substance use outcome at follow-up. When adjusting for the internalizing-conduct comorbidity, depressive symptoms were the only internalizing problem whose risk for alcohol, tobacco, and any substance use was incremental to conduct problems. With the exception of social phobia, antagonistic interactive relationships between each internalizing disorder and conduct problems were found when predicting any substance use; internalizing symptoms was a more robust risk factor for substance use in teens with low (vs. high) conduct problems.Conclusions: Although internalizing and externalizing problems both generally increase risk of substance use, a closer look reveals important nuances in these risk pathways, particularly among teens with comorbid externalizing and internalizing problems. [ABSTRACT FROM AUTHOR]

Background: This project aimed to study resource utilization and surgical outcomes after hepaticojejunostomy (HJ) for biliary injuries utilizing data from ACS NSQIP. Methods: Data from the Participant Use Data File containing surgical patients submitted to the ACS NSQIP during the period of 1/1/2005-12/31/2014 were analyzed. Results: During the study period, 320 patients underwent HJ. Mean age was 50 years, and 109 (34%) were male. Forty-four percent of patients met criteria for ASA class III-V. Forty patients (12.5%) developed one or more critical care complications (CCC). Eighty-one patients (25%) experienced morbidity with a perioperative mortality rate of 1.9%. The mean age of these patients was 52 years, and 62% were male. Age and preoperative elevated alkaline phosphatase were independent predictors of CCC (p < 0.001 and 0.042, OR 1.035, OR 4.337, respectively). Patients ASA class III, age, and preoperative hypoalbuminemia were found to increase risk for prolonged LOS (OR 1.87, p = 0.041, OR 1.02, p = 0.049, OR 2.63, p = 0.001). Discussion: The most significant predictors of morbidity and increased resource utilization after HJ include increasing age, ASA class III or above, and preoperative hypoalbuminemia. Age and ASA class are the strongest predictors of CCC in these patients. [ABSTRACT FROM AUTHOR]

Due to the nonperiodic nature of charge transport in disordered systems, generating insight into static charge transport networks, as well as analyzing the network dynamics, can be challenging. Here, we apply time-dependent network analysis to scrutinize the charge transport networks of two representative molecular semiconductors: a rigid n-type molecule, perylenediimide, and a flexible p-type molecule, bBDT(TDPP)2. Simulations reveal the relevant timescale for local transfer integral decorrelation to be ~100 fs, which is shown to be faster than that of a crystalline morphology of the same molecule. Using a simple graph metric, global network changes are observed over timescales competitive with charge carrier lifetimes. These insights demonstrate that static charge transport networks are qualitatively inadequate, whereas average networks often overestimate network connectivity. Finally, a simple methodology for tracking dynamic charge transport properties is proposed. [ABSTRACT FROM AUTHOR]

Marijuana is one of the most commonly used drugs in the United States, and use during adolescence--when the brain is still developing-- has been proposed as a cause of poorer neurocognitive outcome. Nonetheless, research on this topic is scarce and often shows conflicting results, with some studies showing detrimental effects of marijuana use on cognitive functioning and others showing no significant long-term effects. The purpose of the present study was to examine the associations of marijuana use with changes in intellectual performance in two longitudinal studies of adolescent twins (n = 789 and n = 2,277). We used a quasiexperimental approach to adjust for participants' family background characteristics and genetic propensities, helping us to assess the causal nature of any potential associations. Standardized measures of intelligence were administered at ages 9-12 y, before marijuana involvement, and again at ages 17-20 y. Marijuana use was self-reported at the time of each cognitive assessment as well as during the intervening period. Marijuana users had lower test scores relative to nonusers and showed a significant decline in crystallized intelligence between preadolescence and late adolescence. However, there was no evidence of a dose-response relationship between frequency of use and intelligence quotient (IQ) change. Furthermore, marijuana-using twins failed to show significantly greater IQ decline relative to their abstinent siblings. Evidence from these two samples suggests that observed declines in measured IQ may not be a direct result of marijuana exposure but rather attributable to familial factors that underlie both marijuana initiation and low intellectual attainment. [ABSTRACT FROM AUTHOR]

Coarse-grained models of polymer and biomolecular systems have enabled the computational study of cooperative phenomena, e.g., self-assembly, by lumping multiple atomistic degrees of freedom along the backbone of a polymer, lipid, or DNA molecule into one effective coarse-grained interaction center. Such a coarse-graining strategy leaves the number of molecules unaltered. In order to treat the surrounding solvent or counterions on the same coarse-grained level of description, one can also stochastically group several of those small molecules into an effective, coarse-grained solvent bead or “fluid element.” Such a procedure reduces the number of molecules, and we discuss how to compensate the concomitant loss of translational entropy by density-dependent interactions in spatially inhomogeneous systems. [ABSTRACT FROM AUTHOR]

It is well established that the amplitude of beta oscillations (∼13–30 Hz)—recorded over the sensorimotor cortex—distinctly change throughout movement. Specifically, a movement-related beta decrease (MRBD) occurs before and during movement, and a post-movement beta rebound (PMBR) follows. We investigated how the magnitude of the MRBD and PMBR vary when participants are put in an experimentally induced slow versus fast movement state. Individuals performed a task with blocks that elicited longer reaction times (RTs) and shorter RTs (SLOW and FAST blocks, respectively) while scalp-electroencephalography (EEG) was recorded. The timing of an upcoming movement was also modulated to create blocks with certain and uncertain response timing (FIXED and VARIED blocks, respectively). We found that beta modulation was reduced in SLOW blocks compared to FAST blocks (i.e., a less negative MRBD and less positive PMBR). For the movement certainty manipulation, we saw mixed behavioral and EEG results. Our primary finding of reduced beta modulation during an experimentally induced "slowed movement state" aligns with previous work showing reduced movement-related beta activity in patients with Parkinson's disease. • Beta oscillations over the sensorimotor cortex are modulated during movement. • Less urgent task blocks led to slowed reaction times in healthy participants. • Scalp-EEG showed reduced task-related beta power in less urgent blocks. • Response context, rather than reaction time, best explains our beta power results. • Our results suggest participants were in a "slowed movement state." [ABSTRACT FROM AUTHOR]

The two classic structural classifications of solid matter, crystalline and amorphous, are quite useful for inorganic solids, from antimony trichloride to zinc dibromide and beyond. However, for many molecular materials, especially those based on components containing ten or more non-hydrogen atoms, ordered single crystals are less common, and intermediate structures that are neither amorphous nor crystalline frequently dominate. Herein, we discuss several situations in which there is local (or partial) ordering in such molecular materials. These materials go beyond the standard concepts concerning polymers and must account for imperfect but substantial local ordering, such as that caused by weak intermolecular interactions (e.g., p stacking, H-bonding, and/or dispersion forces). This local ordering has important implications for, and applications in, materials properties : we specifically consider dielectric response, electron transport, and exciton transfer. Finally, we discuss the fundamental importance of the effective dimensionality of partially ordered domains in molecular materials. [ABSTRACT FROM AUTHOR]

With the abundant variety and increasing chemical complexity of conjugated polymers proliferating the field of organic semiconductors, it has become increasingly important to correlate the polymer molecular structure with its mesoscale conformational and morphological attributes. For instance, it is unknown which combinations of chemical moieties and periodicities predictably produce mesoscale ordering. Interestingly, not all ordered morphologies result in efficient devices. In this work we have parametrized accurate classical force-fields and used these to compute the conformational and aggregation characteristics of single strands of common conjugated polymers. Molecular dynamics trajectories are shown to reproduce experimentally observed polymeric ordering, concluding that efficient organic photovoltaic devices span a range of polymer conformational classes, and suggesting that the solution-phase morphologies have far-reaching effects. Encouragingly, these simulations indicate that despite the wide-range of conformational classes present in successful devices, local molecular ordering, and not long-range crystallinity, appears to be the necessary requirement for efficient devices. Finally, we examine what makes a "good" solvent for conjugated polymers, concluding that dispersive π-electron solvent-polymer interactions, and not the electrostatic potential of the backbone interacting with the solvent, are what primarily determine a polymer's solubility in a particular solvent, and consequently its morphological characteristics. [ABSTRACT FROM AUTHOR]

The two classic structural classifications of solid matter, crystalline and amorphous, are quite useful for inorganic solids, from antimony trichloride to zinc dibromide and beyond. However, for many molecular materials, especially those based on components containing ten or more non-hydrogen atoms, ordered single crystals are less common, and intermediate structures that are neither amorphous nor crystalline frequently dominate. Herein, we discuss several situations in which there is local (or partial) ordering in such molecular materials. These materials go beyond the standard concepts concerning polymers and must account for imperfect but substantial local ordering, such as that caused by weak intermolecular interactions (e.g., p stacking, H-bonding, and/or dispersion forces). This local ordering has important implications for, and applications in, materials properties : we specifically consider dielectric response, electron transport, and exciton transfer. Finally, we discuss the fundamental importance of the effective dimensionality of partially ordered domains in molecular materials. [ABSTRACT FROM AUTHOR]

Using a combination of classicalmolecular dynamics and symmetryadapted intermolecular perturbation theory, we develop a high-accuracycomputational method for examining the solubility energetics of nonelectrolytes.This approach is used to accurately compute the cohesive energy densityand Hildebrand solubility parameters of 26 molecular liquids. Theenergy decomposition of symmetry adapted perturbation theory is thenutilized to develop multicomponent Hansen-like solubility parameters.These parameters are shown to reproduce the solvent categorizations(nonpolar, polar aprotic, or polar protic) of all molecular liquidsstudied while lending quantitative rigor to these qualitative categorizationsvia the introduction of simple, easily computable parameters. Notably,we find that by monitoring the first-order exchange energy contributionto the total interaction energy, one can rigorously determine thehydrogen bonding character of a molecular liquid. Finally, this methodis applied to compute explicitly the Flory interaction parameter andthe free energy of mixing for two different small molecule mixtures,reproducing the known miscibilities. This methodology represents animportant step toward the prediction of molecular solubility fromfirst principles. [ABSTRACT FROM AUTHOR]

There are no established questionnaires that evaluate habitual sleep practices in the context of beliefs and attitudes about sleep. This study describes an effort to develop and evaluate a questionnaire that assesses habitual sleep; behaviors associated with sleep and potential sleep problems; sleep hygiene; social and environmental determinants of sleep; beliefs and attitudes about sleep as it relates to health, safety, and functioning; and knowledge about sleep. A total of 124 participants completed the final questionnaire. Overall, the questionnaire and subscales demonstrated moderate internal consistency, and concurrent and divergent validity were demonstrated by comparing various subscales to existing measures. Future studies may utilize the descriptive data to determine the role of behavioral, social, and environmental determinants of healthy sleep. [ABSTRACT FROM PUBLISHER]

Quantum-chemicalcomputation is a useful and widespread tool forunderstanding the electronic structure of conjugated polymers as wellas predicting new synthetic targets. In this work, we assess the validityof considering a single conformational or structural isomer as representativeof the entire conformational or structural distributions in ab-initiocomputations of figures-of-merit (dipole moment, HOMO, LUMO, and opticalgap). It is found from surveying numerous conjugated copolymers thatconsidering only a single conformational or structural isomer canhide significant deviations in frontier molecular orbital energiesand optical gaps as well as qualitative shifts in dipole moments.We discuss the limitations of not considering isomeric dispersionon the polymer’s computed electronic properties and the implicationsthese findings have on the rational design of conjugated polymers. [ABSTRACT FROM AUTHOR]

Sleep symptoms are associated with weight gain and cardiometabolic disease. The potential role of diet has been largely unexplored. Data from the 2007-2008 National Health and Nutrition Examination Survey ( NHANES) were used ( n = 4552) to determine which nutrients were associated with sleep symptoms in a nationally representative sample. Survey items assessed difficulty falling asleep, sleep maintenance difficulties, non-restorative sleep and daytime sleepiness. Analyses were adjusted for energy intake, other dietary factors, exercise, body mass index ( BMI) and sociodemographics. Population-weighted, logistic regression, with backwards-stepwise selection, examined which nutrients were associated with sleep symptoms. Odds ratios ( ORs) reflect the difference in odds of sleep symptoms associated with a doubling in nutrient. Nutrients that were associated independently with difficulty falling asleep included (in order): alpha-carotene ( OR = 0.96), selenium ( OR = 0.80), dodecanoic acid ( OR = 0.91), calcium ( OR = 0.83) and hexadecanoic acid ( OR = 1.10). Nutrients that were associated independently with sleep maintenance difficulties included: salt ( OR = 1.19), butanoic acid (0.81), carbohydrate ( OR = 0.71), dodecanoic acid ( OR = 0.90), vitamin D ( OR = 0.84), lycopene ( OR = 0.98), hexanoic acid ( OR = 1.25) and moisture ( OR = 1.27). Nutrients that were associated independently with non-restorative sleep included butanoic acid ( OR = 1.09), calcium ( OR = 0.81), vitamin C ( OR = 0.92), water ( OR = 0.98), moisture ( OR = 1.41) and cholesterol ( OR = 1.10). Nutrients that were associated independently with sleepiness included: moisture ( OR = 1.20), theobromine ( OR = 1.04), potassium ( OR = 0.70) and water ( OR = 0.97). These results suggest novel associations between sleep symptoms and diet/metabolism, potentially explaining associations between sleep and cardiometabolic diseases. [ABSTRACT FROM AUTHOR]

The aim of the current analysis was to investigate the relationship of daytime sleepiness with alcohol consumption and sleep duration using a population sample of adult Americans. Data was analyzed from adult respondents of the National Health and Nutritional Examination Survey (NHANES) 2007-2008 (n = 2919) using self-reported variables for sleepiness, sleep duration, and alcohol consumption (quantity and frequency of alcohol use). A heavy drinking episode was defined as the consumption of ⩾5 standard alcoholic beverages in a day. Logistic regression models adjusted for sociodemographic variables and insomnia covariates were used to evaluate the relationship between daytime sleepiness and an interaction of alcohol consumption variables with sleep duration. The results showed that daytime sleepiness was reported by 15.07% of the subjects. In univariate analyses adjusted for covariates, an increased probability of daytime sleepiness was predicted by decreased log drinks per day [OR = 0.74 (95% CI, 0.58-0.95)], a decreased log drinking frequency [0.90 (95% CI, 0.83-0.98)], and lower sleep duration [OR = 0.75 (95% CI, 0.67-0.84)]. An interaction between decreased sleep duration and an increased log heavy drinking frequency predicted increased daytime sleepiness (p = 0.004).Thus, the effect of sleep duration should be considered when evaluating the relationship between daytime sleepiness and heavy drinking. [ABSTRACT FROM AUTHOR]

Machine learning interatomic potentials have emerged as a powerful tool for bypassing the spatiotemporal limitations of ab initio simulations, but major challenges remain in their efficient parameterization. We present AL4GAP, an ensemble active learning software workflow for generating multicomposition Gaussian approximation potentials (GAP) for arbitrary molten salt mixtures. The workflow capabilities include: (1) setting up user-defined combinatorial chemical spaces of charge neutral mixtures of arbitrary molten mixtures spanning 11 cations (Li, Na, K, Rb, Cs, Mg, Ca, Sr, Ba and two heavy species, Nd, and Th) and 4 anions (F, Cl, Br, and I), (2) configurational sampling using low-cost empirical parameterizations, (3) active learning for down-selecting configurational samples for single point density functional theory calculations at the level of Strongly Constrained and Appropriately Normed (SCAN) exchange-correlation functional, and (4) Bayesian optimization for hyperparameter tuning of two-body and many-body GAP models. We apply the AL4GAP workflow to showcase high throughput generation of five independent GAP models for multicomposition binary-mixture melts, each of increasing complexity with respect to charge valency and electronic structure, namely: LiCl–KCl, NaCl–CaCl2, KCl–NdCl3, CaCl2–NdCl3, and KCl–ThCl4. Our results indicate that GAP models can accurately predict structure for diverse molten salt mixture with density functional theory (DFT)-SCAN accuracy, capturing the intermediate range ordering characteristic of the multivalent cationic melts. [ABSTRACT FROM AUTHOR]

The chemical variety present in the organic electronics literature has motivated us to investigate potential nonbonding interactions often incorporated into conformational “locking” schemes. We examine a variety of potential interactions, including oxygen–sulfur, nitrogen–sulfur, and fluorine–sulfur, using accurate quantum-chemical wave function methods and noncovalent interaction (NCI) analysis on a selection of high-performing conjugated polymers and small molecules found in the literature. In addition, we evaluate a set of nonbonding interactions occurring between various heterocyclic and pendant atoms taken from a group of representative π-conjugated molecules. Together with our survey and set of interactions, it is determined that while many nonbonding interactions possess weak binding capabilities, nontraditional hydrogen-bonding interactions, oxygen–hydrogen (CH···O) and nitrogen–hydrogen (CH···N), are alone in inducing conformational control and enhanced planarity along a polymer or small molecule backbone at room temperature. [ABSTRACT FROM AUTHOR]

Abstract: Short sleep duration is associated with weight gain and obesity, diabetes, cardiovascular disease, psychiatric illness, and performance deficits. Likewise, long sleep duration is also associated with poor physical and mental health. The role of a healthy diet in habitual sleep duration represents a largely unexplored pathway linking sleep and health. This study evaluated associations between habitual sleep parameters and dietary/nutritional variables obtained via the National Health and Nutrition Examination Survey (NHANES), 2007–2008. We hypothesized that habitual very short (<5h) short (5–6h) and long (9+h) sleep durations are associated with intake of a number of dietary nutrient variables. Overall, energy intake varied across very short (2036kcal), short (2201kcal), and long (1926kcal) sleep duration, relative to normal (2151kcal) sleep duration (p =0.001). Normal sleep duration was associated with the greatest food variety (17.8), compared to very short (14.0), short (16.5) and long (16.3) sleep duration (p <0.001). Associations between sleep duration were found across nutrient categories, with significant associations between habitual sleep duration and proteins, carbohydrates, vitamins and minerals. In stepwise analyses, significant contributors of unique variance included theobromine (long sleep RR=0.910, p <0.05), vitamin C (short sleep RR=0.890, p <0.05), tap water (short sleep RR=0.952, p <0.001; very short (<5h) sleep RR=0.941, p <0.05), lutein+zeaxanthin (short sleep RR=1.123, p <0.05), dodecanoic acid (long sleep RR=0.812, p <0.05), choline (long sleep RR=0.450, p =0.001), lycopene (very short (<5h) sleep RR=0.950, p <0.05), total carbohydrate (very short (<5h) sleep RR=0.494, p <0.05; long sleep RR=0.509, p <0.05), selenium (short sleep RR=0.670, p <0.01) and alcohol (long sleep RR=1.172, p <0.01). Overall, many nutrient variables were associated with short and/or long sleep duration, which may be explained by differences in food variety. Future studies should assess whether these associations are due to appetite dysregulation, due to short/long sleep and/or whether these nutrients have physiologic effects on sleep regulation. In addition, these data may help us better understand the complex relationship between diet and sleep and the potential role of diet in the relationship between sleep and obesity and other cardiometabolic risks. [Copyright &y& Elsevier]

The effects of structural constraints on the metal-to-ligandchargetransfer (MLCT) excited state structural dynamics of cuprous bis-2,9-diphenyl-phenanthroline([Cu(I)(dpp)2]+) in both coordinating acetonitrileand noncoordinating toluene were studied using X-ray transient absorption(XTA) spectroscopy and density functional theory (DFT) calculations.The phenyl groups attached to the phenanthroline ligands not onlyeffectively shield the Cu(I) center from solvent molecules, but alsoforce a flattened tetrahedral coordination geometry of the Cu(I) center.Consequently, the MLCT state lifetime in [Cu(I)(dpp)2]+is solvent-independent, unlike the previously studied 2,9-methylsubstituted bis-phenanthroline Cu(I) complex. The MLCT state of [Cu(I)(dpp)2]+still undergoes a “pseudo Jahn-Tellerdistortion,” with the angle between the two phenanthrolineligand planes decreased further by 7°. The XTA results indicatethat, in the MLCT excited state of [Cu(I)(dpp)2]+, the phenyls at the 2, 9 positions of the phenanthroline rotate,breaking the π–π interaction with the phenanthrolineligands without ever rotating in-plane with the phenanthroline ligands.Hence, the transferred electron density from the Cu(I) center is localizedon the phenanthroline moiety with no charge density present on thephenyl rings. The insight about the effect of the structural constraintson the MLCT state properties will guide the design of Cu(I) diiminecomplexes with suitable excited-state properties to function as earth-abundantdye sensitizers for solar electricity generation. [ABSTRACT FROM AUTHOR]

Existing research has demonstrated associations between sleep duration and obesity, diabetes, cardiovascular disease and mortality. Sleep disorders research has shown that sleep apnoea, insomnia and other sleep disorders confer risk for cardiometabolic disease, particularly in the presence of reduced sleep duration. The aim of the present study was to examine the associations between general sleep disturbance, operationalized as 'difficulty falling asleep, staying asleep, or sleeping too much' as measured in a large, nationally representative sample, and self-reported history of myocardial infarction, stroke, coronary artery disease, diabetes and obesity. Data from the Behavioral Risk Factor Surveillance System were analysed. Complete data were available for 138 201 individuals. A hierarchical logistic regression analysis examined associations before and after adjustment for demographic, socioeconomic, medical and psychological factors. After adjusting for demographic, socioeconomic and health risk factors, sleep duration was associated with obesity [odds ratio (OR) = 1.18, P < 0.0005), diabetes (OR = 1.18, P < 0.005), myocardial infarction (OR = 1.36, P < 0.0005), stroke (OR = 1.22, P < 0.05) and coronary artery disease (OR = 1.59, P < 0.0005). In fully adjusted models that included physical health, significant relationships remained for obesity (OR = 1.14, P < 0.0005), myocardial infarction (OR = 1.23, P < 0.005) and coronary artery disease (OR = 1.43, P < 0.0005). Sleep disturbance is a significant risk factor for obesity, diabetes, myocardial infarction, stroke and coronary artery disease, and effects for obesity, myocardial infarction and coronary artery disease are the most robust after adjustment. This study demonstrates that sleep disturbance is a novel risk factor that is potentially modifiable. Future research should determine whether sleep intervention could reduce the cardiometabolic consequences of sleep disturbance. [ABSTRACT FROM AUTHOR]