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Superconducting qubits provide a promising approach to large-scale fault-tolerant quantum computing. However, qubit connectivity on a planar surface is typically restricted to only a few neighboring qubits. Achieving longer-range and more flexible connectivity, which is particularly appealing in light of recent developments in error-correcting codes, however, usually involves complex multilayer packaging and external cabling, which is resource intensive and can impose fidelity limitations. Here, we propose and realize a high-speed on-chip quantum processor that supports reconfigurable all-to-all coupling with a large on-off ratio. We implement the design in a four-node quantum processor, built with a modular design comprising a wiring substrate coupled to two separate qubit-bearing substrates, each including two single-qubit nodes. We use this device to demonstrate reconfigurable controlled-Z gates across all qubit pairs, with a benchmarked average fidelity of 96.00%±0.08% and best fidelity of 97.14%±0.07%, limited mainly by dephasing in the qubits. We also generate multiqubit entanglement, distributed across the separate modules, demonstrating GHZ-3 and GHZ-4 states with fidelities of 88.15%±0.24% and 75.18%±0.11%, respectively. This approach promises efficient scaling to larger-scale quantum circuits and offers a pathway for implementing quantum algorithms and error-correction schemes that benefit from enhanced qubit connectivity.

ObjectiveTo analyze the local field potentials (LFPs) in patients with focal drug-resistant epilepsy (DRE) from the anterior nucleus of the thalamus (ANT) during inter-ictal state and seizure state.MethodANT stereotactic EEG (SEEG) recordings were studied in four patients with focal temporal lobe epilepsy. SEEG data was classified as inter-ictal and ictal state and sub-categorized into electrographic (ESz), focal aware seizure (FAS), focal with impaired awareness (FIA), or focal to bilateral tonic-clonic seizure (FBTC). LFP was analyzed at 4 Hz, 8 Hz, 16 Hz, 32 Hz, high gamma (100 Hz), and ripples (200 Hz) using spectrogram analysis and a statistical comparison of normalized power spectral density (PSD) averaged during seizures versus pre-ictal baseline segments.ResultThe LFP recordings were analyzed for 162 seizures (127 ESz, 23 FAS, 6 FIA, and 6 FBTC). Based on time-frequency data (spectrogram), a broad band of activity, occurring between 2 and 6 Hz and centered at 4 Hz, and thin-band activity occurring specifically at 8 Hz on the frequency spectrogram were observed during the inter-ictal state. Statistically significant changes in LFP-PSD were seen for FAS, FIA, and FBTC. We observed a significant gain in LFP at the lower frequency band during FAS at 4 Hz, FIA, and FBTC at 4, 8, and 16 Hz while also observing increases at higher frequencies during FBTC at 100 and 200 Hz and a decrease during FAS seizures at 32 Hz. In contrast, no significant change in LFP power was seen for electrographic seizures.InterpretationOur observations from a limited dataset indicate that all clinical seizure types, but not electrographic seizures, caused a change in ANT-LFP based on the magnitude of the associated power spectral density (PSD). Future work will be needed to validate the use of ANT-LFP at these frequencies as accurate measurements of seizure occurrence and severity. This work represents a first step toward understanding ANT thalamic LFP patterns during focal seizures and developing adaptive DBS strategies.

This paper presents a novel approach to address computational challenges in predicting flow features by employing a Graph Neural Network (GNN), which is proficient in predicting flow domain values. Traditional Computational Fluid Dynamics (CFD) simulations, although effective, often require substantial computational resources and time, limiting their applicability in time-sensitive scenarios and optimization studies necessitating extensive case studies. The main objective was to evaluate the feasibility of employing node classification on a graph generated from a 2D baffle flow system to segment the domain based on relative fluid age. A second objective was to compare the computational time required for CFD simulations with the inference time of the network to quantify the efficiency gains achieved by utilizing the network. Results demonstrate the potential of utilizing graph convolutional networks for domain segmentation to predict regions of holdup and bypass. The GNN achieved 97% and 92% accuracy in predicting recirculation regions in single and double baffle cases, particularly excelling in high Reynolds number scenarios. Importantly, the proposed GNN-based approach reduces computation time by over 2100%, showcasing significant efficiency gains. Results here highlight the promise of employing graph convolutional networks for flow feature prediction, offering substantial computational efficiency improvements over traditional CFD simulations.

BackgroundNasopharyngeal carcinoma (NPC) has an extremely high incidence rate in Southern China, resulting in a severe disease burden for the local population. Current EBV serologic screening is limited by false positives, and there is opportunity to integrate polygenic risk scores for personalized screening which may enhance cost-effectiveness and resource utilization.MethodsA Markov model was developed based on epidemiological and genetic data specific to endemic areas of China, and further compared polygenic risk-stratified screening [subjects with a 10-year absolute risk (AR) greater than a threshold risk underwent EBV serological screening] to age-based screening (EBV serological screening for all subjects). For each initial screening age (30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64, and 65–69 years), a modeled cohort of 100,000 participants was screened until age 69, and then followed until age 79.ResultsAmong subjects aged 30 to 54 years, polygenic risk-stratified screening strategies were more cost-effective than age-based screening strategies, and almost comprised the cost-effectiveness efficiency frontier. For men, screening strategies with a 1-year frequency and a 10-year absolute risk (AR) threshold of 0.7% or higher were cost-effective, with an incremental cost-effectiveness ratio (ICER) below the willingness to pay (¥203,810, twice the local per capita GDP). Specifically, the strategies with a 10-year AR threshold of 0.7% or 0.8% are the most cost-effective strategies, with an ICER ranging from ¥159,752 to ¥201,738 compared to lower-cost non-dominated strategies on the cost-effectiveness frontiers. The optimal strategies have a higher probability (29.4–35.8%) of being cost-effective compared to other strategies on the frontier. Additionally, they reduce the need for nasopharyngoscopies by 5.1–27.7% compared to optimal age-based strategies. Likewise, for women aged 30–54 years, the optimal strategy with a 0.3% threshold showed similar results. Among subjects aged 55 to 69 years, age-based screening strategies were more cost-effective for men, while no screening may be preferred for women.ConclusionOur economic evaluation found that the polygenic risk-stratified screening could improve the cost-effectiveness among individuals aged 30–54, providing valuable guidance for NPC prevention and control policies in endemic areas of China.

The present study is focused on investigating the feasibility of additive manufacturing of single crystal nickel components using MIG processed wire arc additive manufacturing (WAAM) technique. The feasibility was validated by depositing the material first on 99.999 % pure polycrystalline nickel substrate and then onto a 99.995 % pure single crystal nickel specimen oriented in direction. Optical microscopy and EBSD results prove the possibility for regions of single crystal to be deposited. The process yielded distinct regions of single crystal. Columnar and equiaxed grains occurred in a region with the highest local thermal gradient and slowest solidification rate. EBSD analysis confirmed that the single crystal region revealed in optical microscopy was in one orientation and the etchant was effective in highlighting individual grain boundaries.

Abstract Background Widely reported by bipolar disorder (BD) patients, cognitive symptoms, including deficits in executive function, memory, attention, and timing are under-studied. Work suggests that individuals with BD show impairments in interval timing tasks, including supra-second, sub-second, and implicit motor timing compared to the neuronormative population. However, how time perception differs within individuals with BD based on disorder sub-type (BDI vs II), depressed mood, or antipsychotic medication-use has not been thoroughly investigated. The present work administered a supra-second interval timing task concurrent with electroencephalography (EEG) to patients with BD and a neuronormative comparison group. As this task is known to elicit frontal theta oscillations, signal from the frontal (Fz) lead was analyzed at rest and during the task. Results Results suggest that individuals with BD show impairments in supra-second interval timing and reduced frontal theta power during the task compared to neuronormative controls. However, within BD sub-groups, neither time perception nor frontal theta differed in accordance with BD sub-type, depressed mood, or antipsychotic medication use. Conclusions This work suggests that BD sub-type, depressed mood status or antipsychotic medication use does not alter timing profile or frontal theta activity. Together with previous work, these findings point to timing impairments in BD patients across a wide range of modalities and durations indicating that an altered ability to assess the passage of time may be a fundamental cognitive abnormality in BD.

BackgroundARDS is a heterogeneous syndrome with distinct clinical phenotypes. Here we investigate whether the presence or absence of large pulmonary ultrasonographic consolidations can categorize COVID-19 ARDS patients requiring mechanical ventilation into distinct clinical phenotypes.MethodsThis is a retrospective study performed in a tertiary-level intensive care unit in Israel between April and September 2020. Data collected included lung ultrasound (LUS) findings, respiratory parameters, and treatment interventions. The primary outcome was a composite of three ARDS interventions: prone positioning, high PEEP, or a high dose of inhaled nitric oxide.ResultsA total of 128 LUS scans were conducted among 23 patients. The mean age was 65 and about two-thirds were males. 81 scans identified large consolidation and were classified as "C-type", and 47 scans showed multiple B-lines with no or small consolidation and were classified as "B-type". The presence of a "C-type" study had 2.5 times increased chance of receiving the composite primary outcome of advanced ARDS interventions despite similar SOFA scores, Pao2/FiO2 ratio, and markers of disease severity (OR = 2.49, %95CI 1.40-4.44).ConclusionThe presence of a "C-type" profile with LUS consolidation potentially represents a distinct COVID-19 ARDS subphenotype that is more likely to require aggressive ARDS interventions. Further studies are required to validate this phenotype in a larger cohort and determine causality, diagnostic, and treatment responses.

The rate of incidentally discovered unruptured intracranial aneurysms has increased with the broad availability of neuroimaging. The determination of the risk of rupture of brain aneurysms is challenging. Several clinical scales for aneurysm rupture prediction have been developed. The most common scales are PHASES, ELAPSS, and UIATS. These scales are not routinely used in clinical practice due to inherent shortcomings. In this review, we analyze the risk factors used in generating these scales and the performance of these scales in clinical studies. We also discuss new potential biomarkers and tools to predict aneurysm rupture.

Introduction High resolution vessel wall imaging (HR‐VWI) enables accurate visualization of intracranial atherosclerotic plaques. Radiomics can be utilized as an objective quantification method of plaque appearance and shape. We aimed to analyze the radiomics features (RFs) obtained from 7T‐HR‐VWI to differentiate between culprit and non‐culprit plaques in patients with intracranial atherosclerotic disease (ICAD). Methods Patients with ICAD as stroke etiology undergoing HR‐VWI were included in the study. Culprit plaques in the vascular territory of the stroke were identified. The degree of stenosis, area degree of stenosis and plaque burden were calculated. Three‐dimensional segmentation of the plaque was performed, and RFs were extracted. We then evaluated multiple machine learning models to predict and identify culprit plaques using significantly different RFs. The dataset was then randomly divided into training and testing datasets, and the trained model was evaluated on the independent testing dataset. Results The study included 33 patients with ICAD as the cause of stroke. Univariate analysis revealed 38 significantly different RFs between culprit and non‐culprit plaques in pre‐contrast MRI, 39 in post‐contrast MRI and 25 RFs that were different between pre and post contrast MRIs. Additionally, seven shape‐based RFs exhibited significant distinctions between the two plaque types. The random forest model achieved an accuracy rate of 81% (88% sensitivity and 75% specificity) in identifying culprit plaques in the independent testing dataset. This model successfully identified the culprit plaque in 7 out of 8 cases during the testing phase. Conclusion In this study symptomatic culprit plaques had a different signature RFs compared to other plaque within the same subject. A machine learning model built with RFs successfully identified the symptomatic atherosclerotic plaques in most cases. Radiomics is a promising tool for stratification of plaques in patients with ICAD.

Background Plaque enhancement after gadolinium contrast administration may assess plaque instability and response to medical therapy. We used high‐resolution vessel wall imaging to evaluate changes in plaque morphologic pattern and enhancement after treatment with high‐intensity statins. Methods Patients with a history of stroke or transient ischemic attack attributable to intracranial atherosclerotic disease underwent 7‐T high‐resolution vessel wall imaging. T1 and T1+gadolinium sequences were obtained at baseline. Follow‐up images were acquired at a minimum of 6 months after the initial scan. Low‐density lipoprotein levels were also recorded at baseline and at follow‐up, after maximal medical therapy was started. Plaque burden, degree of stenosis, and area degree of stenosis were calculated at baseline and follow‐up. Gadolinium enhancement was quantified using a 3‐dimensional pipeline for plaque analysis. Results Five patients were included. The mean age was 56 years, and the average time to follow‐up imaging was 17.7 months. Low‐density lipoprotein decreased from a mean of 122 to 111 mg/dL at follow‐up. Plaque burden decreased from μ=76% to 60%, area degree of stenosis decreased from μ=61% to 56%, and gadolinium uptake decreased from a mean of μ=4.11 to 3.76. Furthermore, a lower low‐density lipoprotein at follow‐up was correlated with decreased plaque burden (r=0.86), lower area degree of stenosis (r=0.8), and less gadolinium uptake (r=0.82). Conclusions Plaque morphologic pattern and gadolinium uptake changed at follow‐up with high‐intensity statin therapy. High‐resolution vessel wall imaging shows promise in assessing plaque response to medical therapy.

Abstract Background Epstein-Barr Virus (EBV)-associated nasopharyngeal carcinoma (NPC) exhibits unusual geographic restriction despite ubiquitous lifelong infection. Screening programs can detect most NPC cases at an early stage, but existing EBV diagnostics are limited by false positives and low positive predictive value (PPV), leading to excess screening endoscopies, MRIs, and repeated testing. Recent EBV genome-wide association studies (GWAS) suggest that EBV BALF2 variants account for more than 80% of attributable NPC risk. We therefore hypothesized that high-risk BALF2 variants could be readily detected in plasma for once-lifetime screening triage. Methods We designed and validated a multiplex genotyping assay to detect EBV BALF2 polymorphisms in human plasma. Targeted next-generation sequencing was used to validate this assay, conduct association studies with clinical phenotype, and longitudinally genotype plasma to assess within-host haplotype stability. We examined the association between NPC and BALF2 haplotypes in a large non-endemic population and three prior EBV GWAS. Finally, we estimated NPC mortality reduction, resource utilization, and cost-effectiveness of BALF2 variant-informed screening using a previously-validated cohort model. Results Following analytical validation, the BALF2 genotyping assay had 99.3% concordance with sequencing in a cohort of 24 NPC cases and 155 non-NPC controls. BALF2 haplotype was highly associated with NPC in this non-endemic population (I613V: odds ratio [OR] 7.9; V317M: OR 178.8). No other candidate BALF2 polymorphisms were significantly associated with NPC or hematologic disorders. Longitudinal genotyping revealed 97.8% within-host haplotype concordance, indicative of lifelong latent infection. In a meta-analysis of 755 NPC cases and 981 non-NPC controls, BALF2 I613V and V317M were significantly associated with NPC in both endemic and non-endemic populations. Modeled variant-informed screening strategies achieved a 46% relative increase in PPV with 7% decrease in effective screening sensitivity, thereby averting nearly half of screening endoscopies/MRIs among endemic populations in east/southeast Asia. Conclusions EBV BALF2 haplotypes are temporally stable within hosts and can be readily detected in plasma via an inexpensive multiplex genotyping assay that offers near-perfect sequencing concordance. In endemic and non-endemic populations, I613V and V317M were highly associated with NPC and could be leveraged to develop variant-informed screening programs that mitigate false positives with small reductions in screening sensitivity.

Abstract Background We investigated the relationship between mindfulness and compassion in a broader way than is typically done by (a) using a recent, comprehensive conceptualization of mindfulness as a manifold of self-awareness, self-regulation, and self-transcendence, and (b) by casting a wide net of compassion measures [i.e., the Compassionate Love for Humanity Scale (Sprecher and Fehr in J Soc Pers Relatsh 22(5):629–651, 2005); Compassion Scale (Martins et al. in J Health Care Poor Underserved 24:1235–1246, 2013); Compassion Scale (Pommier in Assessment 27:21–39, 2020); Relational Compassion Scale (Hacker in The relational compassion scale: Development and validation of a new self-rated scale for the assessment of self-other compassion, University of Glasgow, 2008); and the SOCS-O scale (Gu et al. in Clin Psychol Rev 37:1–12, 2020)]. Additionally, we examined the interplay between mindfulness, compassion, and ethical sensitivities by assessing the influence of the moral foundations (individualizing and binding) on compassion, and the influence of mindfulness, the moral foundations, and compassion on awareness of privilege. Methods We surveyed 407 undergraduate students. Factor analysis was used to examine the dimensionality of the compassion measures; path analysis to examine the relationships between all variables. Results Factor analysis revealed distinct affective (empathy, indifference), cognitive (common humanity, recognizing suffering), and motivational (willingness to act) aspects of compassion. Mindfulness, under its aspects of reflective awareness, self-compassion, and self-transcendence, was associated with compassion, with reflective awareness predicting multiple aspects of compassion over and beyond the normal mechanisms of the mindfulness manifold and the moral foundations. Individualizing was associated with all aspects of compassion; binding was only connected to recognizing suffering and a willingness to act. Awareness of privilege was positively connected to mindfulness through individualizing and the recognition of common humanity; it was also directly negatively related to the moral foundation of binding. Conclusions Mindfulness and compassion have synergistic and distinct positive effects on ethical sensitivities. Given that both compassion and ethical sensitivities have roots in mindfulness, mindfulness interventions might be one possible venue to enhance these positive aspects of individuals’ psychology.

Introduction The severity of internal carotid artery (ICA) atherosclerosis is assessed through measurements of degree of stenosis. This approach does not factor in mechanisms compensating for reduced distal perfusion, such as collateral circulation. An alternative approach is evaluating severity of carotid stenosis based on downstream changes in ocular perfusion. Laser speckle flowgraphy (LSFG) is a non‐invasive tool that quantifies intraocular blood flow. This pilot study investigated whether LSFG metrics could be surrogates for degree of stenosis. Additionally, we quantified changes in flow through the stenosed vessel before and after stenting usingsyngoiFlow (iFlow). Methods Fourteen patients had stents placed to treat symptomatic carotid stenosis. LSFG metrics were obtained before and after stenting. Mean blur rate (MBR), an index of ocular blood velocity, and associated waveform parameters were extracted from the optic nerve head (ONH) region of the eye. iFlow quantified time to peak (TTP), an index of peak cerebral contrast flow, by transforming digital subtraction angiography (DSA) images into perfusion heat maps.TTPswere extracted for seven regions of interest (ROIs) by two raters. Results Two LSFG waveform parameters were significantly negatively correlated with degree of stenosis. These parameters, flow acceleration index (FAI) and rising rate (RR), also increased significantly after stenting. Intraclass correlation coefficients calculated for TTPs showed substantial agreement across all ROIs. Significant decreases in TTP after stenting were observed in ROIs placed in the high cervical ICA, cavernous segment of the ICA, and brain parenchyma. Conclusions LSFG provides biometrics that can accurately measure the impact of ICA stenosis by quantifying distal perfusion. Indices of ocular blood flow acceleration may serve as surrogate metrics for degree of stenosis. iFlow is a sensitive tool to quantify changes in flow after stenting. Non‐invasive flow‐dependent methods are promising in the assessment of patients with ICA stenosis.

Introduction Aneurysmal subarachnoid hemorrhage (aSAH) can lead to life‐threatening complications such as vasospasm and hydrocephalus. The incidence of these events is influenced by the volume of intracranial hemorrhage. The Fisher score is a subjective adjudication of SAH volume. We developed an objective semi‐automated method to quantify the volume of intracranial hemorrhage. Moreover, we evaluated the association of aSAH volume with vasospasm and hydrocephalus. Methods A custom semi‐automated image segmentation algorithm quantifying aSAH volume was implemented in MATLAB. The volume of hemorrhage was retrospectively measured from non‐contrast brain CT scans with Fisher grade ≥ 2. The algorithm utilized region‐growing and 3D k‐means clustering. Performance was validated against the average of two sets of hemorrhage volumes manually measured. These measurements were obtained from two independent raters who selected regions of interest spanning areas of hemorrhage. The association between blood volume and clinical outcome (hydrocephalus or vasospasm) was evaluated using ROC analysis. Results Fifty‐seven patients were included in this study and 10 patients were used for validation of our method. The ICC between raters for manual measurements of hemorrhage in the validation group was 0.988 (CI: (0.911, 0.997), p < 0.001). Validation of semi‐automated versus manual methods resulted in an ICC of 0.961 (CI: (0.756, 0.991), p < 0.001). Bland‐Altman analysis revealed that the algorithm slightly underestimated blood volume (mean difference = ‐4.11 mL). Hemorrhage volume discriminated for the development of vasospasm (AUC = 0.781) and hydrocephalus (AUC = 0.776). Conclusions Volume of hemorrhage is a key factor that influences the incidence of complications in aSAH. We developed and validated a semi‐automated algorithm for quantifying the volume of aSAH. Vasospasm and hydrocephalus were associated with greater amounts of intracranial blood. Objective measurements of aSAH volume can aid in adjudicating risk of complications among patients with aSAH.

Summary: Biomass conversion to fuels and chemicals is crucial to decarbonization, but choosing an advantageous upgrading pathway out of many options is challenging. Rigorously evaluating all candidate pathways (process simulation, product property testing) requires a prohibitive amount of research effort; even simple upgrading schemes have hundreds of possible permutations. We present a method enabling high-throughput screening by approximating upgrading unit operations and drop-in compatibility of products (e.g., fuel properties) and apply it to volatile fatty acid (VFA) conversion to liquid transportation fuels via a MATLAB script, VFA Upgrading to Liquid Transportation fUels Refinery Estimation (VULTURE). VULTURE selects upgrading configurations that maximize fuel blend bio-derived content. We validate VULTURE’s approximations through surrogate fuel property testing and process simulation. Techno-economic and life cycle analyses suggest that VFA upgrading processes down-selected by VULTURE are profitable and have low carbon intensities, demonstrating the potential for the strategy to accelerate process development timelines at decreased costs.

Tertiary sulci are shallow cortical folds that emerge late in gestation. Here the authors link prefrontal tertiary sulcal depth with reasoning scores in children and adolescents.

Pooled nucleic acid amplification tests for severe acute respiratory syndrome coronavirus 2 could increase availability of testing at decreased cost. However, the effect of dilution on analytical sensitivity through sample pooling has not been well characterized. We tested 1,648 prospectively pooled specimens by using 3 nucleic acid amplification tests for severe acute respiratory syndrome coronavirus 2: a laboratory-developed real-time reverse transcription PCR targeting the envelope gene, and 2 commercially available Panther System assays targeting open reading frame 1ab. Positive percent agreement (PPA) of pooled versus individual testing ranged from 71.7% to 82.6% for pools of 8 and from 82.9% to 100.0% for pools of 4. We developed and validated an independent stochastic simulation model to estimate effects of dilution on PPA and efficiency of a 2-stage pooled real-time reverse transcription PCR testing algorithm. PPA was dependent on the proportion of tests with positive results, cycle threshold distribution, and assay limit of detection.

Sociohydrology is a recent effort to integrate coupled human-water systems to understand the dynamics and co-evolution of the system in a holistic sense. However, due to the complexity and uncertainty involved in coupled human-water systems, the feedbacks and interactions are inherently difficult to model. Part of this complexity is due to the multi-scale nature across space and time at which different hydrologic and social processes occur and the varying scale at which data is available. This systematic review seeks to comprehensively collect those documents that conduct analysis within the sociohydrology framework to quantify the spatial-temporal scale(s) and the types of variables and datasets that were used. Overall, a majority of sociohydrology studies reviewed were primarily published in hydrological journals and contain more established hydrological, rather than social, models. The spatial extents varied by political and natural boundaries with the most common being cities and watersheds. Temporal extents also varied from event-based to millennial timescales where decadal and yearly were the most common. In addition to this, current limitations of sociohydrology research, notably the absence of an interdisciplinary unity, future directions, and implications for scholars doing sociohydrology are discussed.

Myotonic dystrophy type 1 is the most common form of muscular dystrophy in adults, and is primarily characterized by muscle weakness and myotonia, yet some of the most disabling symptoms of the disease are cognitive and behavioral. Here we evaluated several of these non-motor symptoms from a cross-sectional time-point in one of the largest longitudinal studies to date, including full-scale intelligence quotient, depression, anxiety, apathy, sleep, and cerebral white matter fractional anisotropy in a group of 39 adult-onset myotonic dystrophy type 1 participants (27 female) compared to 79 unaffected control participants (46 female). We show that intelligence quotient was significantly associated with depression (P < 0.0001) and anxiety (P = 0.018), but not apathy (P < 0.058) or hypersomnolence (P = 0.266) in the DM1 group. When controlling for intelligence quotient, cerebral white matter fractional anisotropy was significantly associated with apathy (P = 0.042) and hypersomnolence (P = 0.034), but not depression (P = 0.679) or anxiety (P = 0.731) in the myotonic dystrophy type 1 group. Finally, we found that disease duration was significantly associated with apathy (P < 0.0001), hypersomnolence (P < 0.001), IQ (P = 0.038), and cerebral white matter fractional anisotropy (P < 0.001), but not depression (P = 0.271) or anxiety (P = 0.508). Our results support the hypothesis that cognitive deficits, hypersomnolence, and apathy, are due to the underlying neuropathology of myotonic dystrophy type 1, as measured by cerebral white matter fractional anisotropy and disease duration. Whereas elevated symptoms of depression and anxiety in myotonic dystrophy type 1 are secondary to the physical symptoms and the emotional stress of coping with a chronic and debilitating disease. Results from this work contribute to a better understanding of disease neuropathology and represent important therapeutic targets for clinical trials.

Purpose: We assessed the effectiveness of a virtual networking session tailored for third- and fourth-year medical students interested in radiation oncology, and report students’ concerns about applying to radiation oncology during the pandemic. Methods and Materials: A multi-institutional networking session was hosted on Zoom and included medical students, faculty, and residents from across the country. The breakout room feature was used to divide participants into smaller groups. Participants were randomly shuffled into new groups every 10 to 15 minutes. Students completed pre- and post-session surveys. Results: Among the 134 students who registered, 69 students participated in the session, and 53 students completed a post-session survey. Most students reported the session was valuable or very valuable (79%), and it was easy or very easy to network through the virtual format (66%). After the session, 18 (33.9%) students reported their interest in radiation oncology increased, and 34 (64.2%) reported their interest remained the same. Most students believed COVID-19 (55%) and virtual interviews and platforms (55%) negatively or somewhat negatively affected their ability to select a residency program. Most students (62%) were concerned they will be inaccurately evaluated as an interviewee on a virtual platform. Although 30% agreed or strongly agreed the cost-savings and convenience of virtual interviews outweigh potential downsides, 66% of students were planning to visit cities of interest in person before rank list submission. Conclusions: Medical students reported significant concerns with their ability to be accurately evaluated and to choose among residency programs on a virtual platform. Students found the networking session to be a valuable resource for most students, and programs could continue similar efforts during the residency application cycle to better represent their program while maintaining certain financial and geographic advantages of a virtual environment.

The inference of cortical sulcal labels often focuses on deep (primary and secondary) sulcal regions, whereas shallow (tertiary) sulcal regions are largely overlooked in the literature due to the scarcity of manual/well-defined annotations and their large neuroanatomical variability. In this paper, we present an automated framework for regional labeling of both primary/secondary and tertiary sulci of the dorsal portion of lateral prefrontal cortex (LPFC) using spherical convolutional neural networks. We propose two core components that enhance the inference of sulcal labels to overcome such large neuroanatomical variability: (1) surface data augmentation and (2) context-aware training. (1) To take into account neuroanatomical variability, we synthesize training data from the proposed feature space that embeds intermediate deformation trajectories of spherical data in a rigid to non-rigid fashion, which bridges an augmentation gap in conventional rotation data augmentation. (2) Moreover, we design a two-stage training process to improve labeling accuracy of tertiary sulci by informing the biological associations in neuroanatomy: inference of primary/secondary sulci and then their spatial likelihood to guide the definition of tertiary sulci. In the experiments, we evaluate our method on 13 deep and shallow sulci of human LPFC in two independent data sets with different age ranges: pediatric (N=60) and adult (N=36) cohorts. We compare the proposed method with a conventional multi-atlas approach and spherical convolutional neural networks without/with rotation data augmentation. In both cohorts, the proposed data augmentation improves labeling accuracy of deep and shallow sulci over the baselines, and the proposed context-aware training offers further improvement in the labeling of shallow sulci over the proposed data augmentation. We share our tools with the field and discuss applications of our results for understanding neuroanatomical-functional organization of LPFC and the rest of cortex (https://github.com/ilwoolyu/SphericalLabeling).

Existing literature demonstrates a strong relationship between childhood experiences and adult health outcomes. The Differential Susceptibility to Environment Theory suggests that there are several factors, including personality, that affect a child's sensitivity to adverse and advantageous experiences. A sample of 246 adults (ages 19–57) were asked questions about extroverted personality characteristics, adverse and advantageous childhood experiences (ACEs and counter-ACEs), and several indicators of adult health, including executive functioning, perceived stress levels, depression, and past smoking habits. The sample was then stratified based on level of extroversion scores with the top quartile being labeled as “extroverts”, the bottom quartile as “introverts”, and those in between as “ambiverts”. Regression analyses were then used to assess the relationship between childhood experiences and each adult health outcome. The results of the study showed that the relationship between childhood experiences and adult health was generally stronger among extroverted individuals. These results suggest that extroverts may be more sensitive to environmental influences in childhood as compared to introverts and ambiverts. More research is needed to understand the neurobiological mechanisms that increase environmental sensitivity among extroverts.

In the last 20 years there has been a turn toward the emotional and affective in contemporary social theory and in human geography, including urban political ecology. This article offers a methodology for approximating emotion and affect in everyday geographies of consumption, taking the shopping mall as a special case due to its ability to manipulate these aspects of the visitor experience. Focusing on an ethnographic study of the Mall Paseo Chiloé and its context of rapid social-spatial change, this article describes the methods used for this kind of research, as well as offering some reflections on my experience using these methods as a way of highlighting the kinds of challenges that can arise during fieldwork. This article also includes some results from the fieldwork that highlight the potential of this methodology. As there is already a vast literatura on affect and emotion in the social sciences, this article focuses on the fieldwork and the methodological approach for carrying out such a study. As such, the emphasis is on the details around using fundamental methods like participant observation, as well as more innovative methods like mobile interviews and photo elicitation.

The purpose of this study was to explore the physical, social, and mental health correlates of executive functioning in adults. Our sample consisted of 250 adults aged 18–55 years who participated in a survey. Participants reported on their physical health behaviors, family closeness, and mental health. Using hierarchical linear regression, the final model explained 41 percent of executive functioning in adults. Dispositional forgiveness of situations, stress, and living in a single-family home were the only significant correlates of executive functioning. These results are useful for better understanding possible mechanisms through which to improve executive functioning in adults.

There is a critical need for the public to have trusted sources of vaccine information. A longitudinal online study assessed trust in COVID-19 vaccine information from 10 sources. A factor analysis for data reduction revealed two factors. The first factor contained politically conservative sources (PCS) of information. The second factor included eight news sources representing mainstream sources (MS). Multivariable logistic regression models were used. Trust in Dr. Fauci was also examined. High trust in MS was associated with intention to encourage family members to get COVID-19 vaccines, altruistic beliefs that more vulnerable people should have vaccine priority, and belief that racial minorities with higher rates of COVID-19 deaths should have priority. High trust in PCS was associated with intention to discourage friends from getting vaccinated. Higher trust in PCS was also associated with participants more likely to disagree that minorities with higher rates of COVID-19 deaths should have priority for a vaccine. High trust in Dr. Fauci as a source of COVID-19 vaccine information was associated with factors similar to high trust in MS. Fair, equitable, and transparent access and distribution are essential to ensure trust in public health systems’ abilities to serve the population.