Global patterns of antigen receptor repertoire disruption across adaptive immune compartments in COVID-19.

Whereas pathogen-specific T and B cells are a primary focus of interest during infectious disease, we have used COVID-19 to ask whether their emergence comes at a cost of broader B cell and T cell repertoire disruption. We applied a genomic DNA-based approach to concurrently study the immunoglobulin-heavy (IGH) and T cell receptor (TCR) ß and δ chain loci of 95 individuals. Our approach detected anticipated repertoire focusing for the IGH repertoire, including expansions of clusters of related sequences temporally aligned with SARS-CoV-2-specific seroconversion, and enrichment of some shared SARS-CoV-2-associated sequences. No significant age-related or disease severity-related deficiencies were noted for the IGH repertoire. By contrast, whereas focusing occurred at the TCRß and TCRδ loci, including some TCRß sequence-sharing, disruptive repertoire narrowing was almost entirely limited to many patients aged older than 50 y. By temporarily reducing T cell diversity and by risking expansions of nonbeneficial T cells, these traits may constitute an age-related risk factor for COVID-19, including a vulnerability to new variants for which T cells may provide key protection.

Emerging Role of Scintigraphy Using Bone-Seeking Tracers for Diagnosis of Cardiac Amyloidosis: AJR Expert Panel Narrative Review.

Amyloidoses are a complex group of clinical diseases that result from progressive organ dysfunction due to extracellular protein misfolding and deposition. The two most common types of cardiac amyloidosis are transthyretin amyloidosis (ATTR) and light-chain (AL) amyloidosis. Diagnosis of ATTR cardiomyopathy (ATTR-CM) is challenging owing to its phenotypic similarity to other more common cardiac conditions, the perceived rarity of the disease, and unfamiliarity with its diagnostic algorithms; endomyocardial biopsy was historically required for diagnosis. However, myocardial scintigraphy using bone-seeking tracers has shown high accuracy for detection of ATTR-CM and has become a key noninvasive diagnostic test for the condition, receiving support from professional society guidelines and transforming prior diagnostic paradigms. This AJR Expert Panel Narrative Review describes the role of myocardial scintigraphy using bone-seeking tracers in the diagnosis of ATTR-CM. The article summarizes available tracers, acquisition techniques, interpretation and reporting considerations, diagnostic pitfalls, and gaps in the current literature. The critical need for monoclonal testing of patients with positive scintigraphy results to differentiate ATTR-CM from AL cardiac amyloidosis is highlighted. Recent updates in guideline recommendations that emphasize the importance of a qualitative visual assessment are also discussed.

Exploiting Vector Pattern Diversity of Molecular Scaffolds for Cheminformatics Tasks in Drug Discovery.

Chemical diversity is challenging to describe objectively. Despite this, various notions of chemical diversity are used throughout the medicinal chemistry optimization process in drug discovery. In this work, we show the usefulness of considering exploited vectors during different phases of the drug design process to provide a quantitative and objective description of chemical diversity. We have developed a concise and fast approach to enumerate and analyze the exploited vector patterns (EVPs) of molecular compound series, which can then be used in archetypal compound selection tasks, from hit matter identification to hit expansion and lead optimization. We first show that EVPs can be used to assess the progressibility of compounds in a fragment library design exercise. By considering EVPs, we then show how a set of compounds can be prioritized for hit expansion using EVP-based, customizable diversity sampling approaches, reducing the time taken and mitigating human biases. We also show that EVPs are a useful tool to analyze SAR data, offering the chance to uncover correlations between different vectors without predetermining the molecular scaffold structures. The codes used to perform these tasks are presented as easy-to-use Jupyter notebooks, which can be readily adapted for further related tasks.

Machine learning for molecular and materials science.

Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.

Mechanical properties and peculiarities of molecular crystals.

In the last century, molecular crystals functioned predominantly as a means for determining the molecular structures via X-ray diffraction, albeit as the century came to a close the response of molecular crystals to electric, magnetic, and light fields revealed that the physical properties of molecular crystals were as rich as the diversity of molecules themselves. In this century, the mechanical properties of molecular crystals have continued to enhance our understanding of the colligative responses of weakly bound molecules to internal frustration and applied forces. Here, the authors review the main themes of research that have developed in recent decades, prefaced by an overview of the particular considerations that distinguish molecular crystals from traditional materials such as metals and ceramics. Many molecular crystals will deform themselves as they grow under some conditions. Whether they respond to intrinsic stress or external forces or interactions among the fields of growing crystals remains an open question. Photoreactivity in single crystals has been a leading theme in organic solid-state chemistry; however, the focus of research has been traditionally on reaction stereo- and regio-specificity. However, as light-induced chemistry builds stress in crystals anisotropically, all types of motions can be actuated. The correlation between photochemistry and the responses of single crystals-jumping, twisting, fracturing, delaminating, rocking, and rolling-has become a well-defined field of research in its own right: photomechanics. The advancement of our understanding requires theoretical and high-performance computations. Computational crystallography not only supports interpretations of mechanical responses, but predicts the responses itself. This requires the engagement of classical force-field based molecular dynamics simulations, density functional theory-based approaches, and the use of machine learning to divine patterns to which algorithms can be better suited than people. The integration of mechanics with the transport of electrons and photons is considered for practical applications in flexible organic electronics and photonics. Dynamic crystals that respond rapidly and reversibly to heat and light can function as switches and actuators. Progress in identifying efficient shape-shifting crystals is also discussed. Finally, the importance of mechanical properties to milling and tableting of pharmaceuticals in an industry still dominated by active ingredients composed of small molecule crystals is reviewed. A dearth of data on the strength, hardness, Young's modulus, and fracture toughness of molecular crystals underscores the need for refinement of measurement techniques and conceptual tools. The need for benchmark data is emphasized throughout.

IFN-γ-dependent interactions between tissue-intrinsic γδ T cells and tissue-infiltrating CD8 T cells limit allergic contact dermatitis.

BACKGROUND: Elicitation of allergic contact dermatitis (ACD), an inflammatory type 4 hypersensitivity disease, induces skin infiltration by polyclonal effector CD8 αß T cells and precursors of tissue-resident memory T (TRM) cells. Because TRM have long-term potential to contribute to body-surface immunoprotection and immunopathology, their local regulation needs a fuller understanding. OBJECTIVE: We sought to investigate how TRM-cell maturation might be influenced by innate-like T cells pre-existing within many epithelia. METHODS: This study examined CD8+ TRM-cell maturation following hapten-induced ACD in wild-type mice and in strains harboring altered compartments of dendritic intraepidermal γδ T cells (DETCs), a prototypic tissue-intrinsic, innate-like T-cell compartment that reportedly regulates ACD, but by no elucidated mechanism. RESULTS: In addition to eliciting CD8 TRM, ACD induced DETC activation and an intimate coregulatory association of the 2 cell types. This depended on DETC sensing IFN-γ produced by CD8 cells and involved programmed death-ligand 1 (PD-L1). Thus, in mice lacking DETC or lacking IFN-γ receptor solely on γδ cells, ACD-elicited CD8 T cells showed enhanced proliferative and effector potentials and reduced motility, collectively associated with exaggerated ACD pathology. Comparable dysregulation was elicited by PD-L1 blockade in vitro, and IFN-γ-regulated PD-L1 expression was a trait of human skin-homing and intraepithelial γδ T cells. CONCLUSIONS: The size and quality of the tissue-infiltrating CD8 T-cell response during ACD can be profoundly regulated by local innate-like T cells responding to IFN-γ and involving PD-L1. Thus, interindividual and tissue-specific variations in tissue-intrinsic lymphocytes may influence responses to allergens and other challenges and may underpin inflammatory pathologies such as those repeatedly observed in γδ T-cell-deficient settings.

The validity of Engagement and Feedback Assessments (EFAs): identifying students at risk of failing.

BACKGROUND: Imperial College School of Medicine, London UK, introduced a new curriculum in 2019, with a focus on the GMC outcomes for graduates, and pedagogy best practice. The new curriculum included formative assessments, named engagement and feedback assessments (EFAs), to support learning, and attainment in the summative examinations. The aims of this study were to assess the validity of EFAs and to determine whether they have utility as a modified form of programmatic assessment to inform decision-making regarding possible interventions by measuring and analysing attendance at and performance in these formative events. METHODS: Seven hundred and sixty-one students were included in the study and assessment results were included for academic years 2019/20 to 2020/21. Forty-one data points per student, (27 in Year 1 and 14 in Year 2) were used, to compare EFA scores with the summative performance. Attendance was monitored through engagement with the EFAs. RESULTS: Cohort 1 (enrolled 2019): In year 1, EFAs were associated with summative exam scores (overall r = 0.63, p < 0.001). Year 2, EFA scores were also associated with summative scores (overall r = 0.57, p < 0.001), including the clinical practical assessment (r = 0.45, p < 0.001). Missing two or more EFAs was associated with a significant increase in the likelihood of failing one or more summative examinations in the first year (OR: 7.97, 95% CI 2.65-34.39) and second year (OR: 3.20, 95% CI 1.74-5.95). Missing more than two EFAs in their first year was also associated with a higher risk of failing a summative examination in the second year (OR: 2.47, 95% CI 1.33-4.71). Students who increased their attendance between year 1 and 2 fared better in summative assessment than those who maintained poor attendance, whereas those that reduced their attendance fared worse than those that maintained high attendance. Cohort 2 (enrolled 2020): Analysis of cohort 2 supported these findings and in this cohort missing two or more EFAs was again associated with an increased likelihood of failing a summative examination (OR = 4.00, 95% CI = 2.02-7.90). CONCLUSION: Our EFA model has validity in predicting performance in summative assessments and can inform prospective interventions to support students' learning. Enhancing attendance and engagement can improve outcomes.

BMAT's predictive validity for medical school performance: A retrospective cohort study.

BACKGROUND: Although used widely, there is limited evidence of the BioMedical Admissions Test's (BMAT) predictive validity and incremental validity over prior educational attainment (PEA). We investigated BMAT's predictive and incremental validity for performance in two undergraduate medical schools, Imperial College School of Medicine (ICSM), UK, and Lee Kong Chian School of Medicine (LKCMedicine), Singapore. Our secondary goal was to compare the evidence collected with published evidence relating to comparable tools. METHODS: This was a retrospective cohort study of four ICSM (1188 students, entering 2010-2013) and three LKCMedicine cohorts (222 students, 2013-2015). We investigated associations between BMAT Section 1 ('Thinking Skills'), Section 2 ('Scientific Knowledge and Applications') and Section 3a ('Writing Task') scores, with written and clinical assessment performance across all programme years. Incremental validity was investigated over PEA (A-levels) in a subset of ICSM students. RESULTS: When BMAT sections were investigated independently, Section 2 scores predicted performance on all written assessments in both institutions with mainly small effect sizes (standardised coefficient ranges: ICSM: 0.08-0.19; LKCMedicine: 0.22-0.36). Section 1 scores predicted Years 5 and 6 written assessment performance at ICSM (0.09-0.14) but nothing at LKCMedicine. Section 3a scores only predicted Year 5 clinical assessment performance at ICSM with a coefficient <0.1. There were no positive associations with standardised coefficients >0.1 between BMAT performance and clinical assessment performance. Multivariable regressions confirmed that Section 2 scores were the most predictive. We found no clear evidence of incremental validity for any BMAT section scores over A-level grades. DISCUSSION: Schools who wish to assess scientific knowledge independently of A-levels may find BMAT Section 2 useful. Comparison with previous studies indicates that, overall, BMAT seems less useful than comparable tools. Larger scale studies are needed. Broader questions regarding why institutions adopt certain admissions tests, including those with little evidence, need consideration.

"More than just a medical student": a mixed methods exploration of a structured volunteering programme for undergraduate medical students.

BACKGROUND: As a result of the COVID-19 pandemic Imperial College School of Medicine developed a structured volunteering programme involving 398 medical students, across eight teaching hospitals. This case study aims to explore the relationship between the processes, context, participant experiences and impacts of the programme so that lessons can be learned for future emergencies and service-learning programmes. METHODS: Using an illuminative approach to evaluation we invited all volunteers and supervisors to complete a mixed-methods survey. This explored differences in experience across demographics and contextual factors, correlations between aspects of induction, supervision and overall experience, and reviewed the impacts of the programme. Quantitative responses were statistically analysed and qualitative reflections were thematically coded to triangulate and explain quantitative findings. Follow up interviews were carried out to check back findings and co-create conclusions. RESULTS: We received responses from 61 students and 17 supervisors. Student participants described predominantly altruistic motivations and transformational changes to their professional identity driven by feeling included, having responsibility, and engaging in authentic workplace-based learning afforded by freedom from the assessed curriculum. They reported new perspectives on their future professional role within the multidisciplinary team and the value of workplace-based learning. They reported increases in wellbeing and self-esteem related to feeling included and valued, and positively contributing to service provision at a time of need. Significantly higher overall satisfaction was associated with a personalised induction, active supervision, earlier stage of training, and male gender. Gender-related differences were not explained through our data but have been reported elsewhere and warrant further study. The duration, intensity and type of role that volunteers performed was similar across demographics and did not appear to modulate their overall experience. CONCLUSIONS: Whilst acknowledging the uniqueness of emergency volunteering and the survey response rate of 15% of volunteers, we suggest the features of a successful service-learning programme include: a learner-centred induction, regular contact with engaged and appreciative supervisors, and roles where students feel valued. Programmes in similar settings may find that service learning is most impactful earlier in medical students' training and that students with altruistic motivations and meaningful work may flourish without formal outcomes and assessments.

Safety and immunogenicity of one versus two doses of the COVID-19 vaccine BNT162b2 for patients with cancer: interim analysis of a prospective observational study.

BACKGROUND: The efficacy and safety profiles of vaccines against SARS-CoV-2 in patients with cancer is unknown. We aimed to assess the safety and immunogenicity of the BNT162b2 (Pfizer-BioNTech) vaccine in patients with cancer. METHODS: For this prospective observational study, we recruited patients with cancer and healthy controls (mostly health-care workers) from three London hospitals between Dec 8, 2020, and Feb 18, 2021. Participants who were vaccinated between Dec 8 and Dec 29, 2020, received two 30 µg doses of BNT162b2 administered intramuscularly 21 days apart; patients vaccinated after this date received only one 30 µg dose with a planned follow-up boost at 12 weeks. Blood samples were taken before vaccination and at 3 weeks and 5 weeks after the first vaccination. Where possible, serial nasopharyngeal real-time RT-PCR (rRT-PCR) swab tests were done every 10 days or in cases of symptomatic COVID-19. The coprimary endpoints were seroconversion to SARS-CoV-2 spike (S) protein in patients with cancer following the first vaccination with the BNT162b2 vaccine and the effect of vaccine boosting after 21 days on seroconversion. All participants with available data were included in the safety and immunogenicity analyses. Ongoing follow-up is underway for further blood sampling after the delayed (12-week) vaccine boost. This study is registered with the NHS Health Research Authority and Health and Care Research Wales (REC ID 20/HRA/2031). FINDINGS: 151 patients with cancer (95 patients with solid cancer and 56 patients with haematological cancer) and 54 healthy controls were enrolled. For this interim data analysis of the safety and immunogenicity of vaccinated patients with cancer, samples and data obtained up to March 19, 2021, were analysed. After exclusion of 17 patients who had been exposed to SARS-CoV-2 (detected by either antibody seroconversion or a positive rRT-PCR COVID-19 swab test) from the immunogenicity analysis, the proportion of positive anti-S IgG titres at approximately 21 days following a single vaccine inoculum across the three cohorts were 32 (94%; 95% CI 81-98) of 34 healthy controls; 21 (38%; 26-51) of 56 patients with solid cancer, and eight (18%; 10-32) of 44 patients with haematological cancer. 16 healthy controls, 25 patients with solid cancer, and six patients with haematological cancer received a second dose on day 21. Of the patients with available blood samples 2 weeks following a 21-day vaccine boost, and excluding 17 participants with evidence of previous natural SARS-CoV-2 exposure, 18 (95%; 95% CI 75-99) of 19 patients with solid cancer, 12 (100%; 76-100) of 12 healthy controls, and three (60%; 23-88) of five patients with haematological cancers were seropositive, compared with ten (30%; 17-47) of 33, 18 (86%; 65-95) of 21, and four (11%; 4-25) of 36, respectively, who did not receive a boost. The vaccine was well tolerated; no toxicities were reported in 75 (54%) of 140 patients with cancer following the first dose of BNT162b2, and in 22 (71%) of 31 patients with cancer following the second dose. Similarly, no toxicities were reported in 15 (38%) of 40 healthy controls after the first dose and in five (31%) of 16 after the second dose. Injection-site pain within 7 days following the first dose was the most commonly reported local reaction (23 [35%] of 65 patients with cancer; 12 [48%] of 25 healthy controls). No vaccine-related deaths were reported. INTERPRETATION: In patients with cancer, one dose of the BNT162b2 vaccine yields poor efficacy. Immunogenicity increased significantly in patients with solid cancer within 2 weeks of a vaccine boost at day 21 after the first dose. These data support prioritisation of patients with cancer for an early (day 21) second dose of the BNT162b2 vaccine. FUNDING: King's College London, Cancer Research UK, Wellcome Trust, Rosetrees Trust, and Francis Crick Institute.

Structures and Spin States of Iron(II) Complexes of Isomeric 2,6-Di(1,2,3-triazolyl)pyridine Ligands.

Iron(II) complex salts of 2,6-di(1,2,3-triazol-1-yl)pyridine (L1) are unexpectedly unstable in undried solvent. This is explained by the isolation of [Fe(L1)4(H2O)2][ClO4]2 and [Fe(NCS)2(L1)2(H2O)2]·L1, containing L1 bound as a monodentate ligand rather than in the expected tridentate fashion. These complexes associate into 44 grid structures through O-H···N hydrogen bonding; a solvate of a related 44 coordination framework, catena-[Cu(µ-L1)2(H2O)2][BF4]2, is also presented. The isomeric ligands 2,6-di(1,2,3-triazol-2-yl)pyridine (L2) and 2,6-di(1H-1,2,3-triazol-4-yl)pyridine (L3) bind to iron(II) in a more typical tridentate fashion. Solvates of [Fe(L3)2][ClO4]2 are low-spin and diamagnetic in the solid state and in solution, while [Fe(L2)2][ClO4]2 and [Co(L3)2][BF4]2 are fully high-spin. Treatment of L3 with methyl iodide affords 2,6-di(2-methyl-1,2,3-triazol-4-yl)pyridine (L4) and 2-(1-methyl-1,2,3-triazol-4-yl)-6-(2-methyl-1,2,3-triazol-4-yl)pyridine (L5). While salts of [Fe(L5)2]2+ are low-spin in the solid state, [Fe(L4)2][ClO4]2·H2O is high-spin, and [Fe(L4)2][ClO4]2·3MeNO2 exhibits a hysteretic spin transition to 50% completeness at T1/2 = 128 K (ΔT1/2 = 6 K). This transition proceeds via a symmetry-breaking phase transition to an unusual low-temperature phase containing three unique cation sites with high-spin, low-spin, and 1:1 mixed-spin populations. The unusual distribution of the spin states in the low-temperature phase reflects "spin-state frustration" of the mixed-spin cation site by an equal number of high-spin and low-spin nearest neighbors. Gas-phase density functional theory calculations reproduce the spin-state preferences of these and some related complexes. These highlight the interplay between the σ-basicity and π-acidity of the heterocyclic donors in this ligand type, which have opposing influences on the molecular ligand field. The Brønsted basicities of L1-L3 are very sensitive to the linkage isomerism of their triazolyl donors, which explains why their iron complex spin states show more variation than the better-known iron(II)/2,6-dipyrazolylpyridine system.

Modulation of π-stacking modes and photophysical properties of an organic semiconductor through isosteric cocrystallization.

We report on the control of π-stacking modes (herringbone vs slipped-stack) and photophysical properties of 9,10-bis((E)-2-(pyridin-4-yl)vinyl)anthracene (BP4VA), an anthracene-based organic semiconductor (OSC), by isosteric cocrystallization (i.e., the replacement of one functional group in a coformer with another of "similar" electronic structure) with 2,4,6-trihalophenols (3X-ph-OH, where X = Cl, Br, and I). Specifically, BP4VA organizes as slipped-stacks when cocrystallized with 3Cl-ph-OH and 3Br-ph-OH, while cocrystallization with 3I-ph-OH results in a herringbone mode. The photoluminescence and molecular frontier orbital energy levels of BP4VA were effectively modulated by the presence of 3X-ph-OH through cocrystallization. We envisage that the cocrystallization of OSCs with minimal changes in cocrystal formers can provide access to convenient structural and property diversification for advanced single-crystal electronics.

Usability and Reliability of an Accessible Patient-Reported Outcome Measure (PROM) Software: The Pediatric Evaluation of Disability Inventory-Patient-Reported Outcome (PEDI-PRO).

IMPORTANCE: Patient-reported outcome measures (PROMs) are used in rehabilitation to evaluate outcomes. We integrated a new PROM for transition-age youth with intellectual and/or developmental disabilities (IDD), the Pediatric Evaluation of Disability Inventory-Patient-Reported Outcome (PEDI-PRO), with a computer-delivered survey platform (Accessible Testing Learning and Assessment System) to enhance cognitive accessibility. OBJECTIVE: To evaluate the usability of the PEDI-PRO software and to investigate its reliability and acceptability to transition-age youth with IDD. DESIGN: Clinical field testing and a survey; repeated-observation test-retest design. SETTING: Clinicians evaluated the PEDI-PRO's usability in school and health care contexts; research staff conducted reliability and acceptability testing in natural settings. PARTICIPANTS: Occupational therapists (n = 12) and physical therapists (n = 2) administered the PEDI-PRO to 39 youths with IDD. Fifty-five transition-age youth with IDD (M age = 19.7) completed the PEDI-PRO twice. OUTCOMES AND MEASURES: Clinicians completed the System Usability Survey (SUS) and open-ended feedback. Youth provided feedback via a brief survey. RESULTS: The mean SUS rating was 84.00 (SD = 11.68), exceeding the industry standard. Intraclass correlations ranged from .80 to .83 across the three PEDI-PRO domains. Internal reliability (α) was .86-.90 across domains. Youth reported that they liked the accessibility features: interface images, button sounds, read-aloud audio, and rating category choices (M = 88.8%, SD = 5.1%). CONCLUSIONS AND RELEVANCE: The PEDI-PRO supported transition-age youth with IDD to reliably report perceived functional performance. The accessible software was favorably perceived by both clinicians and youth. WHAT THIS ARTICLE ADDS: Design features of the PEDI-PRO make it easy to use in practice with transition-age youth with IDD. The PEDI-PRO's cognitively accessible administrative design, including step-by-step instructions for teaching PROM use and a self-reflective questioning technique, could serve as a training model for this and other PROMs.

A Reversible Structural Phase Transition by Electrochemically-Driven Ion Injection into a Conjugated Polymer.

We find that conjugated polymers can undergo reversible structural phase transitions during electrochemical oxidation and ion injection. We study poly[2,5-bis(thiophenyl)-1,4-bis(2-(2-(2-methoxyethoxy)ethoxy)ethoxy)benzene] (PB2T-TEG), a conjugated polymer with glycolated side chains. Using grazing incidence wide-angle X-ray scattering (GIWAXS), we show that, in contrast to previously known polymers, this polymer switches between two structurally distinct crystalline phases associated with electrochemical oxidation/reduction in an aqueous electrolyte. Importantly, we show that this unique phase change behavior has important physical consequences for ion-polaron pair transport. Notably, using moving front experiments visualized by both optical microscopy and super-resolution photoinduced force microscopy (PiFM), we show that a laterally propagating ion-polaron pair front in PB2T-TEG exhibits non-Fickian transport, retaining a sharp step-edge profile, in stark contrast to the Fickian diffusion more commonly observed in polymers like P3MEEMT. This structural phase transition is reminiscent of those accompanying ion uptake in inorganic materials like LiFePO4. We propose that the engineering of similar properties in future conjugated polymers may enable the realization of new materials with superior performance in electrochemical energy storage or neuromorphic memory applications.

Modeling the dielectric constants of crystals using machine learning.

The relative permittivity of a crystal is a fundamental property that links microscopic chemical bonding to macroscopic electromagnetic response. Multiple models, including analytical, numerical, and statistical descriptions, have been made to understand and predict dielectric behavior. Analytical models are often limited to a particular type of compound, whereas machine learning (ML) models often lack interpretability. Here, we combine supervised ML, density functional perturbation theory, and analysis based on game theory to predict and explain the physical trends in optical dielectric constants of crystals. Two ML models, support vector regression and deep neural networks, were trained on a dataset of 1364 dielectric constants. Analysis of Shapley additive explanations of the ML models reveals that they recover correlations described by textbook Clausius-Mossotti and Penn models, which gives confidence in their ability to describe physical behavior, while providing superior predictive power.

Super- and Ferroelastic Organic Semiconductors for Ultraflexible Single-Crystal Electronics.

Like silicon, single crystals of organic semiconductors are pursued to attain intrinsic charge transport properties. However, they are intolerant to mechanical deformation, impeding their application in flexible electronic devices. Such contradictory properties, namely exceptional molecular ordering and mechanical flexibility, are unified in this work. We found that bis(triisopropylsilylethynyl)pentacene (TIPS-P) crystals can undergo mechanically induced structural transitions to exhibit superelasticity and ferroelasticity. These properties arise from cooperative and correlated molecular displacements and rotations in response to mechanical stress. By utilizing a bending-induced ferroelastic transition of TIPS-P, flexible single-crystal electronic devices were obtained that can tolerate strains (ϵ) of more than 13 % while maintaining the charge carrier mobility of unstrained crystals (µ>0.7 µ0 ). Our work will pave the way for high-performance ultraflexible single-crystal organic electronics for sensors, memories, and robotic applications.

Reducing future fears by suppressing the brain mechanisms underlying episodic simulation.

Imagining future events conveys adaptive benefits, yet recurrent simulations of feared situations may help to maintain anxiety. In two studies, we tested the hypothesis that people can attenuate future fears by suppressing anticipatory simulations of dreaded events. Participants repeatedly imagined upsetting episodes that they feared might happen to them and suppressed imaginings of other such events. Suppressing imagination engaged the right dorsolateral prefrontal cortex, which modulated activation in the hippocampus and in the ventromedial prefrontal cortex (vmPFC). Consistent with the role of the vmPFC in providing access to details that are typical for an event, stronger inhibition of this region was associated with greater forgetting of such details. Suppression further hindered participants' ability to later freely envision suppressed episodes. Critically, it also reduced feelings of apprehensiveness about the feared scenario, and individuals who were particularly successful at down-regulating fears were also less trait-anxious. Attenuating apprehensiveness by suppressing simulations of feared events may thus be an effective coping strategy, suggesting that a deficiency in this mechanism could contribute to the development of anxiety.

Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder.

Major depressive disorder (MDD) is clinically heterogeneous with prevalence rates twice as high in women as in men. There are many possible sources of heterogeneity in MDD most of which are not measured in a sufficiently comparable way across study samples. Here, we assess genetic heterogeneity based on two fundamental measures, between-cohort and between-sex heterogeneity. First, we used genome-wide association study (GWAS) summary statistics to investigate between-cohort genetic heterogeneity using the 29 research cohorts of the Psychiatric Genomics Consortium (PGC; N cases = 16,823, N controls = 25,632) and found that some of the cohort heterogeneity can be attributed to ascertainment differences (such as recruitment of cases from hospital vs. community sources). Second, we evaluated between-sex genetic heterogeneity using GWAS summary statistics from the PGC, Kaiser Permanente GERA, UK Biobank, and the Danish iPSYCH studies but did not find convincing evidence for genetic differences between the sexes. We conclude that there is no evidence that the heterogeneity between MDD data sets and between sexes reflects genetic heterogeneity. Larger sample sizes with detailed phenotypic records and genomic data remain the key to overcome heterogeneity inherent in assessment of MDD.

Materials discovery by chemical analogy: role of oxidation states in structure prediction.

The likelihood of an element to adopt a specific oxidation state in a solid, given a certain set of neighbours, might often be obvious to a trained chemist. However, encoding this information for use in high-throughput searches presents a significant challenge. We carry out a statistical analysis of the occurrence of oxidation states in 16 735 ordered, inorganic compounds and show that a large number of cations are only likely to exhibit certain oxidation states in combination with particular anions. We use this data to build a model that ascribes probabilities to the formation of hypothetical compounds, given the proposed oxidation states of their constituent species. The model is then used as part of a high-throughput materials design process, which significantly narrows down the vast compositional search space for new ternary metal halide compounds. Finally, we employ a machine learning analysis of existing compounds to suggest likely structures for a small subset of the candidate compositions. We predict two new compounds, MnZnBr4 and YSnF7, that are thermodynamically stable according to density functional theory, as well as four compounds, MnCdBr4, MnRu2Br8, ScZnF5 and ZnCoBr4, which lie within the window of metastability.

Sub-region expression of brain-derived neurotrophic factor in the dorsal hippocampus and amygdala is Affected by mild traumatic brain injury and stress in male rats.

The US population suffers 1.5 million head injuries annually, of which mild traumatic brain injuries (mTBI) comprise 75%. Many individuals subsequently experience long-lasting negative symptoms, including anxiety. Previous rat-based work in our laboratory has shown that mTBI changes neuronal counts in the hippocampus and amygdala, regions associated with anxiety. Specifically, mTBI increased neuronal death in the dorsal CA1 sub-region of the hippocampus, but attenuated it in the medial (MeA) and the basolateral nuclei of the amygdala nine days following injury, which was associated with greater anxiety. We have also shown that glucocorticoid receptor (GR) antagonism prior to concomitant stress and mTBI extinguishes anxiety-like behaviors. Using immunohistochemistry, this study examines the expression of brain-derived neurotrophic factor (BDNF) following social defeat and mTBI, and whether this is affected by prior glucocorticoid receptor antagonism as a potential mechanism behind these anxiety and neuronal differences. Here, stress and mTBI upregulate BDNF in the MeA, and both GR and mineralocorticoid receptor antagonism downregulate BDNF in the dorsal hippocampal CA1 and dentate gyrus, as well as the central nucleus of the amygdala. These findings suggest BDNF plays a role in the mechanism underlying neuronal changes following mTBI in amygdalar and hippocampal subregions, and may participate in stress elicited changes to neural plasticity in these regions. Taken together, these results suggest an essential role for BDNF in the development of anxiety behaviors following concurrent stress and mTBI.