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BackgroundThe rotational activation created by spiral waves may be a mechanism for atrial fibrillation (AF), yet it is unclear how activation patterns obtained from endocardial baskets are influenced by the 3D geometric curvature of the atrium or 'unfolding' into 2D maps. We develop algorithms that can visualize spiral waves and their tip locations on curved atrial geometries. We use these algorithms to quantify differences in AF maps and spiral tip locations between 3D basket reconstructions, projection onto 3D anatomical shells and unfolded 2D surfaces.MethodsWe tested our algorithms in N = 20 patients in whom AF was recorded from 64-pole baskets (Abbott, CA). Phase maps were generated by non-proprietary software to identify the tips of spiral waves, indicated by phase singularities. The number and density of spiral tips were compared in patient-specific 3D shells constructed from the basket, as well as 3D maps from clinical electroanatomic mapping systems and 2D maps.ResultsPatients (59.4±12.7 yrs, 60% M) showed 1.7±0.8 phase singularities/patient, in whom ablation terminated AF in 11/20 patients (55%). There was no difference in the location of phase singularities, between 3D curved surfaces and 2D unfolded surfaces, with a median correlation coefficient between phase singularity density maps of 0.985 (0.978-0.990). No significant impact was noted by phase singularities location in more curved regions or relative to the basket location (p>0.1).ConclusionsAF maps and phase singularities mapped by endocardial baskets are qualitatively and quantitatively similar whether calculated by 3D phase maps on patient-specific curved atrial geometries or in 2D. Phase maps on patient-specific geometries may be easier to interpret relative to critical structures for ablation planning.

Abstract Background The rising number of children identified with autism has led to exponential growth in for-profit applied behavior analysis (ABA) agencies and the use of highly structured approaches that may not be developmentally appropriate for young children. Multiple clinical trials support naturalistic developmental behavior interventions (NDBIs) that integrate ABA and developmental science and are considered best practices for young autistic children. The Early Start Denver Model (ESDM) is a comprehensive NDBI shown to improve social communication outcomes for young autistic children in several controlled efficacy studies. However, effectiveness data regarding NDBI use in community-based agencies are limited. Methods This study uses a community-partnered approach to test the effectiveness of ESDM compared to usual early behavioral intervention (EBI) for improving social communication and language in autistic children served by community agencies. This is a hybrid type 1 cluster-randomized controlled trial with 2 conditions: ESDM and EBI. In the intervention group, supervising providers will receive training in ESDM; in the control group, they will continue EBI as usual. We will enroll and randomize 100 supervisors (50 ESDM, 50 EBI) by region. Each supervisor enrolls 3 families of autistic children under age 5 (n = 300) and accompanying behavior technicians (n = 200). The primary outcome is child language and social communication at 6 and 12 months. Secondary outcomes include child adaptive behavior, caregiver use of ESDM strategies, and provider intervention fidelity. Child social motivation and caregiver fidelity will be tested as mediating variables. ESDM implementation determinants will be explored using mixed methods. Discussion This study will contribute novel knowledge on ESDM effectiveness, the variables that mediate and moderate child outcomes, and engagement of its mechanisms in community use. We expect results from this trial to increase community availability of this model and access to high-quality intervention for young autistic children, especially those who depend on publicly funded intervention services. Understanding implementation determinants will aid scale-up of effective models within communities. Trail registration Clinicaltrials.gov identifier number NCT06005285. Registered on August 21, 2023. Protocol version Issue date 6 August 2024; Protocol amendment number: 02.

Mapping sea ice in the Arctic is essential for maritime navigation, and growing vessel traffic highlights the necessity of the timeliness and accuracy of sea ice charts. In addition, with the increased availability of satellite imagery, automation is becoming more important. The AutoICE Challenge investigates the possibility of creating deep learning models capable of mapping multiple sea ice parameters automatically from spaceborne synthetic aperture radar (SAR) imagery and assesses the current state of the automatic-sea-ice-mapping scientific field. This was achieved by providing the tools and encouraging participants to adopt the paradigm of retrieving multiple sea ice parameters rather than the current focus on single sea ice parameters, such as concentration. The paper documents the efforts and analyses, compares, and discusses the performance of the top-five participants’ submissions. Participants were tasked with the development of machine learning algorithms mapping the total sea ice concentration, stage of development, and floe size using a state-of-the-art sea ice dataset with dual-polarised Sentinel-1 SAR images and 22 other relevant variables while using professionally labelled sea ice charts from multiple national ice services as reference data. The challenge had 129 teams representing a total of 179 participants, with 34 teams delivering 494 submissions, resulting in a participation rate of 26.4 %, and it was won by a team from the University of Waterloo. Participants were successful in training models capable of retrieving multiple sea ice parameters with convolutional neural networks and vision transformer models. The top participants scored best on the total sea ice concentration and stage of development, while the floe size was more difficult. Furthermore, participants offered intriguing approaches and ideas that could help propel future research within automatic sea ice mapping, such as applying high downsampling of SAR data to improve model efficiency and produce better results.

Live cell imaging is a standard technique in experimental biology that enables the observation of isolated cells and tissue slices in real time and the testing of cellular responses to changes in buffer composition. However, most live cell imaging devices require the use of dedicated microscopes and/or specialised stage adaptors, and come at a reasonably high cost. We employed 3D printing technology to create a low-cost imaging chamber with side ports to exchange fluids, to be used on upright microscopes. The chamber increased the functionality of a standard upright epifluorescent microscope to allow dynamic, real-time calcium imaging of cultured hypothalamic astrocytes from mice, and to test the effects of ATP stimulation upon calcium signalling. It was also used on slices obtained from the mouse brain using a brain matrix slicer. The advantages of this chamber include a very simple design that can be used with upright epifluorescence microscopes, does not require any special stage adaptor, and includes ports to permit fluid exchange during imaging. This chamber is ideal for educational settings with undergraduate laboratories that do not have access to dedicated inverted fluorescent microscopes for tissue culture experiments.

Bicultural stress, adolescents' appraisal of intergenerational conflict and discrimination from peers, can strain youths' capacity for functional coping and positive adaptation. Conversely, internal assets (IAs; i.e., positive identity and social competencies) promote thriving and resilience. We assessed associations between bicultural stress and past 30-day bullying victimization and perpetration and the protective effects of IAs among Hispanic and Somali youth. Results of multilevel mixed effects models indicate that bicultural stress was associated with higher frequency of past 30-day bullying victimization ([beta] = 2.14, SE = 0.26) and perpetration ([beta] = 0.79, SE = 0.17) however, youth with high IAs had the lowest frequency of bullying behaviors even at elevated levels of bicultural stress (p's < 0.001; adjusting for family functioning, parent/caregiver reported SES, marital status, and number of children). Results underscore the promise of fostering immigrant origin youths' positive identity and social competencies to facilitate healthy developmental and well-being over the life course.

Abstract Background There is no gold standard patient-reported outcome measure (PROM) in hand surgery. As a result, a diverse array of PROM instruments have been utilized across centers over time. Lack of score interchangeability limits the ability to compare or conglomerate scores when new instruments are introduced. Our aim was to develop a linkage for the PROMIS UE CAT v1.2 and PROMIS PF CAT scores and develop crosswalk tables for interconversion between these PROMs. Methods Retrospective review was conducted to identify adult (≥ 18y) patients seen by orthopaedic hand surgeons at a single academic tertiary care hospital who had completed PROMIS UE CAT v1.2 and PROMIS PF CAT score at the same visit. For those with multiple visits, only one randomly selected visit was included in the analyses. Pearson’s correlation was calculated to determine the linear relationship between the scores. Linkage from PF to UE was performed utilizing several commonly utilized equating models (identity, mean, linear, equipercentile and circle-arc methods). The performance of the models was assessed using intraclass correlation (ICC) between observed PROMIS UE CAT v1.2 and estimated PROMIS UE CAT v1.2 scores generated using the model as well as Root Mean Square Error (RMSE). The model chosen as the ‘best’ was further assessed for population invariance using root expected mean squared difference (REMSD) where

Background/objectiveTo examine the cognitive benefits of 6 months of prescribed intermittent exercise (10-min bouts totaling 150 weekly minutes) in community-dwelling older adults, comparing effects of low-intensity movement (LIM) and moderate-intensity aerobic exercise (aerobic exercise; AE) training; and exploring biological mechanisms of exercise-related cognitive improvement.MethodTwenty-five adults (>60 years old) participated in a 6-month controlled trial and were randomized into LIM or AE intermittent training. Cognition was assessed using a neuropsychological test battery including the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), California Verbal Learning Test, 2nd Edition (CVLT-II), and Delis-Kaplan Executive Function System (D-KEFS). Neuroimaging measures were collected using a 7 T human MRI scanner. Serologic neurotrophic and inflammatory factors were analyzed using Luminex multiplex assays [brain derived neurotrophic factor (BDNF); vascular endothelial growth factor (VEGF)]; interleukin-6 (IL-6), C-reactive protein (CRP), plasminogen activator inhibitor (PAI-1).ResultsLIM and AE intermittent training had dissociable effects on cognition, with LIM resulting in improved learning and memory and AE resulting in improved executive functioning. Intervention groups differed on change in cognitive performance on CVLT-II learning and D-KEFS trail making test. Increase in right dorsolateral prefrontal cortex (DLPFC) surface area was linked to executive improvement (i.e., phonemic fluency) regardless of intervention group. A decline in circulating PAI-1 was linked to learning and memory improvement in response to LIM over 6 months.ConclusionModerate-intensity AE and LIM intermittent training likely have distinct cognitive benefits, though low-intensity activity is often included as a control group in exercise trials in aging.

Measures of physical growth, such as weight and height have long been the predominant outcomes for monitoring child health and evaluating interventional outcomes in public health studies, including those that may impact neurodevelopment. While physical growth generally reflects overall health and nutritional status, it lacks sensitivity and specificity to brain growth and developing cognitive skills and abilities. Psychometric tools, e.g., the Bayley Scales of Infant and Toddler Development, may afford more direct assessment of cognitive development but they require language translation, cultural adaptation, and population norming. Further, they are not always reliable predictors of future outcomes when assessed within the first 12–18 months of a child’s life. Neuroimaging may provide more objective, sensitive, and predictive measures of neurodevelopment but tools such as magnetic resonance (MR) imaging are not readily available in many low and middle-income countries (LMICs). MRI systems that operate at lower magnetic fields (< 100mT) may offer increased accessibility, but their use for global health studies remains nascent. The UNITY project is envisaged as a global partnership to advance neuroimaging in global health studies. Here we describe the UNITY project, its goals, methods, operating procedures, and expected outcomes in characterizing neurodevelopment in sub-Saharan Africa and South Asia.

Abstract In oxygen (O2)‐controlled cell culture, an indispensable tool in biological research, it is presumed that the incubator setpoint equals the O2 tension experienced by cells (i.e., pericellular O2). However, it is discovered that physioxic (5% O2) and hypoxic (1% O2) setpoints regularly induce anoxic (0% O2) pericellular tensions in both adherent and suspension cell cultures. Electron transport chain inhibition ablates this effect, indicating that cellular O2 consumption is the driving factor. RNA‐seq analysis revealed that primary human hepatocytes cultured in physioxia experience ischemia‐reperfusion injury due to cellular O2 consumption. A reaction‐diffusion model is developed to predict pericellular O2 tension a priori, demonstrating that the effect of cellular O2 consumption has the greatest impact in smaller volume culture vessels. By controlling pericellular O2 tension in cell culture, it is found that hypoxia vs. anoxia induce distinct breast cancer transcriptomic and translational responses, including modulation of the hypoxia‐inducible factor (HIF) pathway and metabolic reprogramming. Collectively, these findings indicate that breast cancer cells respond non‐monotonically to low O2, suggesting that anoxic cell culture is not suitable for modeling hypoxia. Furthermore, it is shown that controlling atmospheric O2 tension in cell culture incubators is insufficient to regulate O2 in cell culture, thus introducing the concept of pericellular O2‐controlled cell culture.

Abstract SAG21/LEA5 is an unusual late embryogenesis abundant protein in Arabidopsis thaliana, that is primarily mitochondrially located and may be important in regulating translation in both chloroplasts and mitochondria. SAG21 expression is regulated by a plethora of abiotic and biotic stresses and plant growth regulators indicating a complex regulatory network. To identify key transcription factors regulating SAG21 expression, yeast-1-hybrid screens were used to identify transcription factors that bind the 1685 bp upstream of the SAG21 translational start site. Thirty-three transcription factors from nine different families bound to the SAG21 promoter, including members of the ERF, WRKY and NAC families. Key binding sites for both NAC and WRKY transcription factors were tested through site directed mutagenesis indicating the presence of cryptic binding sites for both these transcription factor families. Co-expression in protoplasts confirmed the activation of SAG21 by WRKY63/ABO3, and SAG21 upregulation elicited by oligogalacturonide elicitors was partially dependent on WRKY63, indicating its role in SAG21 pathogen responses. SAG21 upregulation by ethylene was abolished in the erf1 mutant, while wound-induced SAG21 expression was abolished in anac71 mutants, indicating SAG21 expression can be regulated by several distinct transcription factors depending on the stress condition.

Abstract Background Massive amounts of sewage sludge are generated during biological sewage treatment and are commonly subjected to anaerobic digestion, land application, and landfill disposal. Concurrently, persistent organic pollutants (POPs) are frequently found in sludge treatment and disposal systems, posing significant risks to both human health and wildlife. Metabolically versatile microorganisms originating from sewage sludge are inevitably introduced to sludge treatment and disposal systems, potentially affecting the fate of POPs. However, there is currently a dearth of comprehensive assessments regarding the capability of sewage sludge microbiota from geographically disparate regions to attenuate POPs and the underpinning microbiomes. Results Here we report the global prevalence of organohalide-respiring bacteria (OHRB) known for their capacity to attenuate POPs in sewage sludge, with an occurrence frequency of ~50% in the investigated samples (605 of 1186). Subsequent laboratory tests revealed microbial reductive dechlorination of polychlorinated biphenyls (PCBs), one of the most notorious categories of POPs, in 80 out of 84 sludge microcosms via various pathways. Most chlorines were removed from the para- and meta-positions of PCBs; nevertheless, ortho-dechlorination of PCBs also occurred widely, although to lower extents. Abundances of several well-characterized OHRB genera (Dehalococcoides, Dehalogenimonas, and Dehalobacter) and uncultivated Dehalococcoidia lineages increased during incubation and were positively correlated with PCB dechlorination, suggesting their involvement in dechlorinating PCBs. The previously identified PCB reductive dehalogenase (RDase) genes pcbA4 and pcbA5 tended to coexist in most sludge microcosms, but the low ratios of these RDase genes to OHRB abundance also indicated the existence of currently undescribed RDases in sewage sludge. Microbial community analyses revealed a positive correlation between biodiversity and PCB dechlorination activity although there was an apparent threshold of community co-occurrence network complexity beyond which dechlorination activity decreased. Conclusions Our findings that sludge microbiota exhibited nearly ubiquitous dechlorination of PCBs indicate widespread and nonnegligible impacts of sludge microbiota on the fate of POPs in sludge treatment and disposal systems. The existence of diverse OHRB also suggests sewage sludge as an alternative source to obtain POP-attenuating consortia and calls for further exploration of OHRB populations in sewage sludge. Video Abstract

Abstract PHF6 mutations (PHF6 MT) are identified in various myeloid neoplasms (MN). However, little is known about the precise function and consequences of PHF6 in MN. Here we show three main findings in our comprehensive genomic and proteomic study. Firstly, we show a different pattern of genes correlating with PHF6 MT in male and female cases. When analyzing male and female cases separately, in only male cases, RUNX1 and U2AF1 are co-mutated with PHF6. In contrast, female cases reveal co-occurrence of ASXL1 mutations and X-chromosome deletions with PHF6 MT. Next, proteomics analysis reveals a direct interaction between PHF6 and RUNX1. Both proteins co-localize in active enhancer regions that define the context of lineage differentiation. Finally, we demonstrate a negative prognostic role of PHF6 MT, especially in association with RUNX1. The negative effects on survival are additive as PHF6 MT cases with RUNX1 mutations have worse outcomes when compared to cases carrying single mutation or wild-type.

Caffeine is recognized as one of the most effective dietary ergogenic aids in sports, yet its evidence-based effectiveness in esports is unclear. This study investigated the effects of two different doses of caffeine on the shooting performance and reaction time of 24 first-person shooter (FPS) esports players (22 men, 2 women; age = 22.29 ± 2.91 years). Participants completed three experimental trials in which they consumed either a water control (CON), a 1 mg·kg−1 BM (CAF1) or a 3 mg·kg−1 BM (CAF3) dose of caffeine. Performance measures (e.g., score, accuracy (%), hit rate (hits/sec), and shots fired) were assessed in a static clicking and reactive tracking style task on the KovaaK's FPS aim trainer. Reaction time was used to assess vigilance on the psychomotor vigilance test (PVT). Performance was measured at four time points in each trial: pre-treatment (PRE), 60 min (POST1), 80 min (POST2), and 100 min (POST3) post-treatment. Significant differences were identified using repeated-measures analysis of variances. Caffeine, irrespective of dose, significantly improved performance compared to CON for static clicking score and hit rate, reactive tracking accuracy, and reaction time on the PVT. Significant interactions between treatment and time were identified and post hoc analyses showed that compared to CON, CAF1 significantly improved static clicking score at POST1 and POST3, static clicking hit rate at POST1, reactive tracking accuracy at POST1, POST2, and POST3, and reaction time on the PVT at POST1 and POST2. Post hoc analysis also showed that compared to CON, CAF3 significantly improved static clicking score, reactive tracking accuracy, and reaction time on the PVT at all time points, in addition to static clicking hit rate at POST1 and POST3. In summary, caffeine supplementation enhances the shooting performance and reaction time of FPS esports players.

Abstract Objectives Patients hospitalized for COVID‐19 frequently develop hypoxemia and acute respiratory distress syndrome (ARDS) after admission. In non‐COVID‐19 ARDS studies, admission to hospital wards with subsequent transfer to intensive care unit (ICU) is associated with worse outcomes. We hypothesized that initial admission to the ward may affect outcomes in patient with COVID‐19 ARDS. Methods This was a retrospective study of consecutive adults admitted for COVID‐19 ARDS between March 2020 and March 2021 at Stanford Health Care. Mortality scores at hospital admission (Coronavirus Clinical Characterization Consortium Mortality Score [4C score]) and ICU admission (Simplified Acute Physiology Score III [SAPS‐III]) were calculated, as well as ROX index for patients on high flow nasal oxygen. Patients were classified by emergency department (ED) disposition (ward‐first vs. ICU‐direct), and 28‐ and 60‐day mortality and highest level of respiratory support within 1 day of ICU admission were compared. A second cohort (April 2021‒July 2022, n = 129) was phenotyped to validate mortality outcome. Results A total of 157 patients were included, 48% of whom were first admitted to the ward (n = 75). Ward‐first patients had more comorbidities, including lung disease. Ward‐first patients had lower 4C and similar SAPS‐III score, yet increased mortality at 28 days (32% vs. 17%, hazard ratio [HR] 2.0, 95% confidence interval [95% CI] 1.0‒3.7, p = 0.039) and 60 days (39% vs. 23%, HR 1.83, 95% CI 1.04‒3.22, p = 0.037) compared to ICU‐direct patients. More ward‐first patients escalated to mechanical ventilation on day 1 of ICU admission (36% vs. 14%, p = 0.002) despite similar ROX index. Ward‐first patients who upgraded to ICU within 48 h of ED presentation had the highest mortality. Mortality findings were replicated in a sensitivity analysis. Conclusion Despite similar baseline risk scores, ward‐first patients with COVID‐19 ARDS had increased mortality and escalation to mechanical ventilation compared to ICU‐direct patients. Ward‐first patients requiring ICU upgrade within 48 h were at highest risk, highlighting a need for improved identification of this group at ED admission.

ABSTRACT The human gut teems with a diverse ecosystem of microbes, yet non-bacterial portions of that community are overlooked in studies of metabolic diseases firmly linked to gut bacteria. Type 2 diabetes mellitus (T2D) is associated with compositional shifts in the gut bacterial microbiome and the mycobiome, the fungal portion of the microbiome. However, whether T2D and/or metformin treatment underpins fungal community changes is unresolved. To differentiate these effects, we curated a gut mycobiome cohort spanning 1,000 human samples across five countries and validated our findings in a murine experimental model. We use Bayesian multinomial logistic normal models to show that T2D and metformin both associate with shifts in the relative abundance of distinct gut fungi. T2D is associated with shifts in the Saccharomycetes and Sordariomycetes fungal classes, while the genera Fusarium and Tetrapisipora most consistently associate with metformin treatment. We confirmed the impact of metformin on individual gut fungi by administering metformin to healthy mice. Thus, metformin and T2D account for subtle, but significant and distinct variation in the gut mycobiome across human populations. This work highlights for the first time that metformin can confound associations of gut fungi with T2D and warrants the need to consider pharmaceutical interventions in investigations of linkages between metabolic diseases and gut microbial inhabitants.IMPORTANCEThis is the largest to-date multi-country cohort characterizing the human gut mycobiome, and the first to investigate potential perturbations in gut fungi from oral pharmaceutical treatment. We demonstrate the reproducible effects of metformin treatment on the human and murine gut mycobiome and highlight a need to consider metformin as a confounding factor in investigations between type 2 diabetes mellitus and the gut microbial ecosystem.

IntroductionOlder adults are not protected from obesity, which has been linked to frailty, cognitive impairment, and other aging-related factors. Intensive lifestyle interventions have been shown to be effective for weight loss in older adults; however, these have typically been highly intensive and less feasible for dissemination. This analysis describes weight loss in a large-scale, commercially available, digital intervention in a subset of older adults.MethodsOlder adults (N = 20,443, males = 6,238; females = 14,205) between 65 and 85 years of age with overweight (43.3%) or obesity (46.7%) participated in an online, self-directed weight loss program. Behavioral-based content was delivered through weekly video lessons within an online platform that included weight and physical activity tracking, an online community, a reference library, and access to coaching support. Self-reported measures taken at the time of entry into the program were used for this analysis (demographics, height, body weight, and health status). Weight was reported across weeks of engagement in the curriculum.ResultsThe average weight loss was −3.15 kg (95% CI: [−3.20, −3.11]) at 15.5 weeks. Weight loss was significantly greater in male individuals (−3.79 kg [95% CI: −3.89, −3.71]) versus female individuals (−2.87 kg [95% CI: −2.94, −2.82]) (p < 0.001), with a similar engagement in curriculum weeks. Percent weight loss was statistically significant for all age categories (p < 0.05) and self-reported health conditions (p < 0.05).DiscussionShort-term weight loss was observed in older adults exposed to a low-touch, self-guided, and digital behavioral-based weight loss program. Weight loss was also observed even in the presence of various chronic health conditions.

As the rates of Autism Spectrum Disorder (ASD) increase and early screening efforts intensify, more toddlers with high likelihood of ASD are entering the United States' (US') publicly funded early intervention system. Early intervention service delivery for toddlers with ASD varies greatly based on state resources and regulations. Research recommends beginning ASD-specific evidence-based practices (EBP), especially caregiver-implemented intervention, as early as possible to facilitate the development of social-communication skills and general learning. Translating EBP into practice has been challenging, especially in low-resourced areas. The main goal of this study was to obtain a more comprehensive understanding of public early intervention system structure, service delivery practices, and factors influencing EBP use for children with ASD in the US. Participants (N = 133) included 8 early intervention state coordinators in 7 states, 29 agency administrators in those states, 57 early intervention providers from those agencies, and 39 caregivers of children with ASD receiving services from those providers. Online surveys gathered stakeholder and caregiver perspectives on early intervention services as well as organizational factors related to EBP implementation climate and culture. Stakeholders identified key intervention needs for young children with ASD. In general, both agency administrators and direct providers reported feeling "somewhat effective" or "very effective" in addressing most needs of children with ASD. They reported the most difficulty addressing eating, sleeping, family stress, and stereotyped behaviors. Data indicate that children from families with higher income received significantly higher service intensity. While administrators and providers reported high rates of high-quality caregiver coaching (>60%), caregivers reported low rates (23%). Direct providers with more favorable attitudes toward EBP had greater EBP use. In turn, provider attitudes toward EBP were significantly associated with implementation leadership and culture at their agency. Results suggest that publicly funded early intervention programs in the US require additional resources and training for providers and leaders to support improved implementation climate and attitudes toward ASD EBPs. Results also suggest that more state system support is needed to increase use of ASD-specific EBP use, including high-quality caregiver coaching, to better serve toddlers with ASD. Recommendations for implementation strategies are addressed.

This paper explores two-phase immersion cooling using sealed enclosures of dielectric fluid as a technique to achieve compact, power dense converters on a single printed circuit board (PCB). The proposed approach employs passive circulation of the fluid and does not introduce system complexity beyond a heat exchanger required to condense the vapour. A test apparatus representing six 650 V, 150 A semiconductor switches in an inverter rejecting heat to a 65$\,^{\circ }$C water cooling loop is developed. Pool boiling experiments on a flat surface in Novec 7000 dielectric fluid demonstrate critical heat flux of 43 W cm$^{-2}$ at a saturation temperature of 94$\,^{\circ }$C and a corresponding pressure of 593 kPa. By augmenting the surface with pin fins (representative of a heat spreader attached to a switch) and grit blasting to improve the surface micro-geometry, the maximum heat transfer coefficient increased from 1.5 W cm$^{-2}$ K$^{-1}$ to 3.4 W cm$^{-2}$ K$^{-1}$ with a corresponding reduction in switch temperature from 125$\,^{\circ }$C to 107$\,^{\circ }$C at the total power dissipation of 186 W. A practical implementation with comparable thermal performance to the experimental apparatus but minimised volume of 0.12 L is presented. This yields a Cooling System Performance Index of 37 WL$^{-1}$ K$^{-1}$, including the heat exchanger and printed circuit board with switches, decoupling capacitors and gate drivers.

This paper introduces a distributed secondary control scheme for achieving current sharing and average voltage regulation objectives in a DC microgrid. The proposed scheme employs a dynamic diffusion algorithm (DDA) instead of the consensus algorithm to enable distributed communication among converters. To help understand DDA, the relation of DDA and other diffusion algorithms is discussed in detail and its superiority is shown by comparison with diffusion and consensus algorithms. Furthermore, considering the discrete nature and different sampling time of the digital controller and communication network, a z-domain model of the entire DC microgrid is established. The influence of communication and secondary control parameters on the system stability is investigated. Based on the established model, the tolerable communication rates are obtained. Real-time simulations conducted on the OPAL-RT platform validate the effectiveness of the proposed scheme, showcasing its advantages in terms of convergence speed and stability.

Abstract We compared circulating miRNA profiles of hospitalized COVID-positive patients (n = 104), 27 with acute respiratory distress syndrome (ARDS) and age- and sex-matched healthy controls (n = 18) to identify miRNA signatures associated with COVID and COVID-induced ARDS. Meta-analysis incorporating data from published studies and our data was performed to identify a set of differentially expressed miRNAs in (1) COVID-positive patients versus healthy controls as well as (2) severe (ARDS+) COVID vs moderate COVID. Gene ontology enrichment analysis of the genes these miRNAs interact with identified terms associated with immune response, such as interferon and interleukin signaling, as well as viral genome activities associated with COVID disease and severity. Additionally, we observed downregulation of a cluster of miRNAs located on chromosome 14 (14q32) among all COVID patients. To predict COVID disease and severity, we developed machine learning models that achieved AUC scores between 0.81–0.93 for predicting disease, and between 0.71–0.81 for predicting severity, even across diverse studies with different sample types (plasma versus serum), collection methods, and library preparations. Our findings provide network and top miRNA feature insights into COVID disease progression and contribute to the development of tools for disease prognosis and management.

Abstract Background Women from migrant and refugee backgrounds living in high-income countries have increased risk of adverse perinatal outcomes and report lower satisfaction with perinatal healthcare. In Sydney, Australia, a new service known as the Cross Cultural Workers (CCWs) in Maternity and Child and Family Health Service (the CCW Service) was implemented to support such women and families from pregnancy to the early parenting period. This study aimed to ascertain the experiences of women and their partners engaging with the CCW Service. Methods A survey study was undertaken. Women accessing the CCW Service were recruited during pregnancy and were asked to complete surveys at three time points: in the third trimester of pregnancy, at 6 and 12 months postpartum. Their partners were invited to complete a survey at 6 months postpartum. Survey data were analysed to compare satisfaction, usefulness, number of CCW interactions, cultural sensitivity, and service improvement recommendations across all three survey timepoints. Results A total of 231 surveys were received: 113 during pregnancy, 50 at 6-months postpartum, 44 at 12-months postpartum, and 24 partner surveys. Participants in all surveys reported the CCW Service to be useful (84–94%), stating that it increased their understanding of pregnancy, birth and parenting (95–100%), and that they would recommend the CCW Service (92–98%). Participants experienced a high level of satisfaction (88–95%) irrespective of the number of CCW interactions (p = 0.42). Thoughts on becoming a mother or parent were more positive after meeting the CCW than before for both women (p = 0.01) and partners (p = 0.12). Suggestions for CCW Service improvement were to 1) increase the provision of information, specifically financial entitlements, postnatal depression, and support services, 2) increase involvement of partners in care, 3) increase the CCW workforce/or number of CCWs. Conclusion The CCW Service was associated with positive experiences and high rates of satisfaction at all timepoints. This service has the potential to inform the implementation of similar models of care that improve accessibility, the perinatal experience, and respond to the unique needs of women and families from migrant and refugee backgrounds.

Abstract Quantum information processing promises to revolutionise computing; quantum algorithms have been discovered that address common tasks significantly more efficiently than their classical counterparts. For a physical system to be a viable quantum computer it must be possible to initialise its quantum state, to realise a set of universal quantum logic gates, including at least one multi-qubit gate, and to make measurements of qubit states. Molecular Electron Spin Qubits (MESQs) have been proposed to fulfil these criteria, as their bottom-up synthesis should facilitate tuning properties as desired and the reproducible production of multi-MESQ structures. Here we explore how to perform a two-qubit entangling gate on a multi-MESQ system, and how to readout the state via quantum state tomography. We propose methods of accomplishing both procedures using multifrequency pulse Electron Paramagnetic Resonance (EPR) and apply them to a model MESQ structure consisting of two nitroxide spin centres. Our results confirm the methodological principles and shed light on the experimental hurdles which must be overcome to realise a demonstration of controlled entanglement on this system.

Abstract Storage or transportation temperature is very important for preserving the quality of fruit. However, low temperature in sensitive fruit such as peach can induce loss of quality. Fruit exposed to a specific range of temperatures and for a longer period can show chilling injury (CI) symptoms. The susceptibility to CI at low temperature varies among cultivars and genetic backgrounds. Along with agronomic management, appropriate postharvest management can limit quality losses. The importance of correct temperature management during postharvest handling has been widely demonstrated. Nowadays, due to long-distance markets and complex logistics that require multiple actors, the management of storage/transportation conditions is crucial for the quality of products reaching the consumer. Peach fruit exposed to low temperatures activate a suite of physiological, metabolomic, and molecular changes that attempt to counteract the negative effects of chilling stress. In this review an overview of the factors involved, and plant responses is presented and critically discussed. Physiological disorders associated with CI generally only appear after the storage/transportation, hence early detection methods are needed to monitor quality and detect internal changes which will lead to CI development. CI detection tools are assessed: they need to be easy to use, and preferably non-destructive to avoid loss of products. Graphical Abstract

Hypoxia is a major factor shaping the immune landscape, and several cancer models have been developed to emulate hypoxic tumors. However, to date, they still have several limitations, such as the lack of reproducibility, inadequate biophysical cues, limited immune cell infiltration, and poor oxygen (O2) control, leading to non-pathophysiological tumor responses. Therefore, it is essential to develop better cancer models that mimic key features of the tumor extracellular matrix and recreate tumor-associated hypoxia while allowing cell infiltration and cancer-immune cell interactions. Herein, hypoxia-inducing cryogels (HICs) have been engineered using hyaluronic acid (HA) to fabricate three-dimensional microtissues and model a hypoxic tumor microenvironment. Specifically, tumor cell-laden HICs have been designed to deplete O2 locally and induce long-standing hypoxia. HICs promoted changes in hypoxia-responsive gene expression and phenotype, a metabolic adaptation to anaerobic glycolysis, and chemotherapy resistance. Additionally, HIC-supported tumor models induced dendritic cell (DC) inhibition, revealing a phenotypic change in the plasmacytoid DC (pDC) subset and an impaired conventional DC (cDC) response in hypoxia. Lastly, our HIC-based melanoma model induced CD8+ T cell inhibition, a condition associated with the downregulation of pro-inflammatory cytokine secretion, increased expression of immunomodulatory factors, and decreased degranulation and cytotoxic capacity of T cells. Overall, these data suggest that HICs can be used as a tool to model solid-like tumor microenvironments and has great potential to deepen our understanding of cancer-immune cell relationship in low O2 conditions and may pave the way for developing more effective therapies.

Apple cultivars ‘Annurca’ and ‘Limoncella’ are grown locally in the Campania region of Italy and are valued for their distinctive flavour and characteristics, including a high content of nutritionally important bioactive compounds. However, apples are typically stored chilled for several months before consumption, so it is important to assess if the valuable characteristics are still present after postharvest storage. Here, we compare the quality, nutritional parameters, and aroma of these two cultivars with two widely grown international cultivars, ‘Golden Delicious’ and ‘Fuji’, after 60 days of storage. The aroma profiles of all four apples were analysed using thermal desorption and gas chromatography–time-of-flight mass spectrometry. We show that the local cultivars are distinct from the international cultivars in their bioactive compound content and their antioxidant activity. ‘Limoncella’ shows high sugar content, which may be acting as a cryoprotectant during storage, and high total phenolics in the flesh, which is of nutritional interest. We identified 104 volatile organic compounds (VOCs) and showed that the overall aroma profile is distinct for each cultivar, containing 11 published odorant compounds. The ‘Annurca’ profile is uniquely low in esters. Seven VOCs retain good discrimination across the four cultivars and, together with the quality and nutritional data, separate the two local cultivars from the international cultivars by hierarchical clustering. Overall, the data emphasize the unique characteristics of the two local cultivars and their value.

Foods high in phenolics such as prunes have been shown to exert protective effects on bone mineral density (BMD), but only certain individuals experience these benefits. This post-hoc analysis of a 12-month randomized controlled trial aimed to identify the relationship among the gut microbiome, immune responses, and bone protective effects of prunes on postmenopausal women. Subjects who consumed 50–100 g prunes daily were divided into responders (n = 20) and non-responders (n = 32) based on percent change in total hip bone mineral density (BMD, ≥1% or ≤−1% change, respectively). DXA scans were used to determine body composition and BMD. Immune markers were measured using immunoassays and flow cytometry. Targeted phenolic metabolites were analyzed using ultra performance liquid chromatography-tandem mass spectrometry. The fecal microbiota was characterized through 16S rRNA gene PCR amplicon sequencing. After 12 months of prune consumption, anti-inflammatory markers showed responders had significantly lower levels of IL-1β and TNF-α. QIIME2 sequence analysis showed that microbiomes of responders and non-responders differed in alpha (Shannon and Faith PD, Kruskal-Wallis p < 0.05) and beta diversity (unweighted Unifrac, PERMANOVA p < 0.04) metrics both before and after prune treatment. Furthermore, responders had a higher abundance of bacterial families Oscillospiraceae and Lachnospiraceae (ANCOM-BC p < 0.05). These findings provide evidence that postmenopausal women with initial low BMD can benefit from prunes if they host certain gut microbes. These insights can guide precision nutrition strategies to improve BMD tailored to diet and microbiome composition.

Esports research lacks game-based metrics platforms appropriate for adequately capturing esports performance. The aim of this pilot study was to assess the reliability of the KovaaK's first-person shooter (FPS) aim trainer as a metrics platform for assessing shooting proficiency in esports players. Ten FPS esports players completed two identical experimental trials (T) separated by three to five days. Each trial included four rounds (R) of testing, evaluating four shooting tasks: Micro Flicking, Macro Flicking, Strafe Tracking, and Wall Peeking. Reliability of performance outcomes (e.g., accuracy, headshot accuracy, hits per second, and total shots hit) were assessed using the intraclass correlation coefficient (ICC) and their 95% confidence intervals (CI), and significant differences were identified using repeated-measures analysis of variance (RM-ANOVA). Results indicated excellent, or good to excellent reliability for all outcome variables with the ICC estimates ranging between 0.947–0.995, with lower and upper bound 95% CIs ranging between 0.876–0.988, and 0.984–0.999, respectively. Significant improvements were seen between experimental trials in the Macro Flicking task for accuracy (p = .005) and hits per second (p = .009) only. Significant interactions between trial and round were identified in the Micro Flicking task for accuracy (p = .006), with post hoc analysis showing accuracy was significantly higher in T1R1 compared to T2R1 (87.74 ± 3.13 vs. 85.99 ± 3.05, respectively, p = .02), and in T2R4 compared to T2R2 (87.99 ± 2.89 vs. 84.70 ± 4.25, respectively, p = .049). Significant interactions were also identified in the Strafe Tracking task for headshot accuracy (p = .002), with post hoc analysis showing headshot accuracy was significantly higher in T1R2 compared to T2R2 (78.48 ± 8.15 vs. 76.79 ± 12.16, respectively, p = .003), and in T1R2 compared to T1R1 (78.48 ± 8.15 vs. 73.68 ± 17.94, respectively, p = .023). In summary, this study demonstrates that KovaaK's provides a reliable metrics platform for assessing shooting proficiency in esports, however, some variability in performance was observed.

Abstract Background Chronic levels of inflammation are associated with higher risk of many chronic diseases. Physical activity (PA) lowers the risk of cancer, cardiovascular disease (CVD), diabetes and others. One mechanism for PA-induced protection may be through the immune system. We investigated the association between leisure-time PA and peripheral immune cell populations in a large nationally representative sample of the US general population. Methods A total of 17,093 participants [mean (SE) age of 41.6 (0.3) years] of the National Health and Nutrition Examination Survey 1999–2018 were included. Self-reported leisure-time PA was converted to metabolic equivalent of task hours per week (MET-hrs/wk). White blood cell (WBC) count, WBC ratios, and platelet count were derived. Multivariable linear regression analyses were used to estimate associations between leisure-time PA level and peripheral immune cell populations. Multivariable logistic regression analyses were used to estimate associations between leisure-time PA and metrics of WBC count and neutrophil-to-lymphocyte ratio (NLR) which may predict mortality. Results A higher leisure-time PA level was associated with a lower WBC count (> 14.0 vs. 14.0 vs. 8.1 × 109 cells/L; odds ratio [OR] = 0.76, 95% CI = 0.66–0.88) and high NLR (> 2.68; OR = 0.84, 95% CI = 0.72–0.99), which may predict CVD and all-cause mortality. The highest leisure-time PA level also linked to a lower probability of a high WBC count (≥ 8.3 × 109 cells/L; OR = 0.76, 95% CI = 0.66–0.88), which may predict cancer mortality. Conclusions We observed an inverse association between leisure-time PA level, WBC count, and NLR, particularly for neutrophil levels. These results suggest that participants at higher levels of leisure-time PA may have lower levels of inflammation, which may be important for future chronic disease outcomes.

Abstract Anti-vaccine content and other kinds of misinformation are hypothesized to be more heavily monetized than other kinds of online content. We test this hypothesis by applying several novel and scalable measures of website monetization strategies to more than 400,000 links shared by 261 anti-vaccine Facebook pages and 190 pro-vaccine ones. Contrary to expectations, websites promoted in pro-vaccine venues do more to monetize attention than those promoted in anti-vaccine venues. This is a consequence of how intensely monetized news websites are—pro-vaccine venues share more links to news. The specific news sites shared by anti-vaccine venues are rated less credible by fact-checking organizations, but we find little substantive difference in their monetization strategies. These results emphasize the need to interpret measures of monetization within the context of the broader “attention economy”.

Background: Segmenting computed tomography (CT) is crucial in various clinical applications, such as tailoring personalized cardiac ablation for managing cardiac arrhythmias. Automating segmentation through machine learning (ML) is hindered by the necessity for large, labeled training data, which can be challenging to obtain. This article proposes a novel approach for automated, robust labeling using domain knowledge to achieve high-performance segmentation by ML from a small training set. The approach, the domain knowledge-encoding (DOKEN) algorithm, reduces the reliance on large training datasets by encoding cardiac geometry while automatically labeling the training set. The method was validated in a hold-out dataset of CT results from an atrial fibrillation (AF) ablation study. Methods: The DOKEN algorithm parses left atrial (LA) structures, extracts “anatomical knowledge” by leveraging digital LA models (available publicly), and then applies this knowledge to achieve high ML segmentation performance with a small number of training samples. The DOKEN-labeled training set was used to train a nnU-Net deep neural network (DNN) model for segmenting cardiac CT in N = 20 patients. Subsequently, the method was tested in a hold-out set with N = 100 patients (five times larger than training set) who underwent AF ablation. Results: The DOKEN algorithm integrated with the nn-Unet model achieved high segmentation performance with few training samples, with a training to test ratio of 1:5. The Dice score of the DOKEN-enhanced model was 96.7% (IQR: 95.3% to 97.7%), with a median error in surface distance of boundaries of 1.51 mm (IQR: 0.72 to 3.12) and a mean centroid–boundary distance of 1.16 mm (95% CI: −4.57 to 6.89), similar to expert results (r = 0.99; p < 0.001). In digital hearts, the novel DOKEN approach segmented the LA structures with a mean difference for the centroid–boundary distances of −0.27 mm (95% CI: −3.87 to 3.33; r = 0.99; p < 0.0001). Conclusions: The proposed novel domain knowledge-encoding algorithm was able to perform the segmentation of six substructures of the LA, reducing the need for large training data sets. The combination of domain knowledge encoding and a machine learning approach could reduce the dependence of ML on large training datasets and could potentially be applied to AF ablation procedures and extended in the future to other imaging, 3D printing, and data science applications.

Despite the growing availability of sensing and data in general, we remain unable to fully characterize many in-service engineering systems and structures from a purely data-driven approach. The vast data and resources available to capture human activity are unmatched in our engineered world, and, even in cases where data could be referred to as “big,” they will rarely hold information across operational windows or life spans. This paper pursues the combination of machine learning technology and physics-based reasoning to enhance our ability to make predictive models with limited data. By explicitly linking the physics-based view of stochastic processes with a data-based regression approach, a derivation path for a spectrum of possible Gaussian process models is introduced and used to highlight how and where different levels of expert knowledge of a system is likely best exploited. Each of the models highlighted in the spectrum have been explored in different ways across communities; novel examples in a structural assessment context here demonstrate how these approaches can significantly reduce reliance on expensive data collection. The increased interpretability of the models shown is another important consideration and benefit in this context.

Measurements of chemical abundances in high- z star-forming (SF) galaxies place important constraints on the enrichment histories of galaxies and the physical conditions in the early Universe. The James Webb Space Telescope (JWST) is beginning to enable direct chemical abundance measurements in galaxies at z > 2 via the detection of the faint T _e -sensitive auroral line [O iii ] λ 4364. However, abundances of other elements (e.g., S and Ar) in high- z galaxies remain unconstrained owing to a lack of T _e data and wavelength coverage. Here we present multiple direct abundances in Q2343-D40, a galaxy at z = 2.9628 ± 0.0001 observed with JWST/NIRSpec as part of the CECILIA program. We report the first simultaneous measurement of T _e [O iii ] and T _e [S iii ] in a high- z galaxy, finding good agreement with the temperature trends in local SF systems. We measure a gas-phase metallicity of 12+log(O/H) = 8.07 ± 0.06, and the N/O abundance, log(N/O) = −1.37 ± 0.21, is indicative of primary nucleosynthesis. The S/O and Ar/O relative abundances, log(S/O) = −1.88 ± 0.10 and log(Ar/O) = −2.80 ± 0.12, are both >0.3 dex lower than the solar ratios. However, the relative Ar ^2+ /S ^2+ abundance is consistent with the solar ratio, suggesting that the relative S-to-Ar abundance does not evolve significantly with redshift. Recent nucleosynthesis models find that significant amounts of S and Ar are produced in Type Ia supernovae, such that the S/O and Ar/O abundances in Q2343-D40 could be the result of predominantly core-collapse supernova enrichment. Future JWST observations of high- z galaxies will uncover whether S/O and Ar/O are sensitive to the timescales of these different enrichment mechanisms.

Introduction Headache is a common chief complaint of children presenting to emergency departments (EDs). Approximately 0.5%–1% will have emergent intracranial abnormalities (EIAs) such as brain tumours or strokes. However, more than one-third undergo emergent neuroimaging in the ED, resulting in a large number of children unnecessarily exposed to radiation. The overuse of neuroimaging in children with headaches in the ED is driven by clinician concern for life-threatening EIAs and lack of clarity regarding which clinical characteristics accurately identify children with EIAs. The study objective is to derive and internally validate a stratification model that accurately identifies the risk of EIA in children with headaches based on clinically sensible and reliable variables.Methods and analysis Prospective cohort study of 28 000 children with headaches presenting to any of 18 EDs in the Pediatric Emergency Care Applied Research Network (PECARN). We include children aged 2–17 years with a chief complaint of headache. We exclude children with a clear non-intracranial alternative diagnosis, fever, neuroimaging within previous year, neurological or developmental condition such that patient history or physical examination may be unreliable, Glasgow Coma Scale score

Abstract Background Two acute respiratory distress syndrome (ARDS) trials showed no benefit for statin therapy, though secondary analyses suggest inflammatory subphenotypes may have a differential response to simvastatin. Statin medications decrease cholesterol levels, and low cholesterol has been associated with increased mortality in critical illness. We hypothesized that patients with ARDS and sepsis with low cholesterol could be harmed by statins. Methods Secondary analysis of patients with ARDS and sepsis from two multicenter trials. We measured total cholesterol from frozen plasma samples obtained at enrollment in Statins for Acutely Injured Lungs from Sepsis (SAILS) and Simvastatin in the Acute Respiratory Distress Syndrome (HARP-2) trials, which randomized subjects with ARDS to rosuvastatin versus placebo and simvastatin versus placebo, respectively, for up to 28 days. We compared the lowest cholesterol quartile (

BackgroundSegmentation of computed tomography (CT) is important for many clinical procedures including personalized cardiac ablation for the management of cardiac arrhythmias. While segmentation can be automated by machine learning (ML), it is limited by the need for large, labeled training data that may be difficult to obtain. We set out to combine ML of cardiac CT with domain knowledge, which reduces the need for large training datasets by encoding cardiac geometry, which we then tested in independent datasets and in a prospective study of atrial fibrillation (AF) ablation.MethodsWe mathematically represented atrial anatomy with simple geometric shapes and derived a model to parse cardiac structures in a small set of N = 6 digital hearts. The model, termed “virtual dissection,” was used to train ML to segment cardiac CT in N = 20 patients, then tested in independent datasets and in a prospective study.ResultsIn independent test cohorts (N = 160) from 2 Institutions with different CT scanners, atrial structures were accurately segmented with Dice scores of 96.7% in internal (IQR: 95.3%–97.7%) and 93.5% in external (IQR: 91.9%–94.7%) test data, with good agreement with experts (r = 0.99; p

The COVID-19 pandemic has highlighted the need for relevant metrics describing the resources and community attributes that affect the impact of communicable disease outbreaks. Such tools can help inform policy, assess change, and identify gaps to potentially reduce the negative outcomes of future outbreaks. The present review was designed to identify available indices to assess communicable disease outbreak preparedness, vulnerability, or resilience, including articles describing an index or scale developed to address disasters or emergencies which could be applied to addressing a future outbreak. This review assesses the landscape of indices available, with a particular focus on tools assessing local-level attributes. This systematic review yielded 59 unique indices applicable to assessing communicable disease outbreaks through the lens of preparedness, vulnerability, or resilience. However, despite the large number of tools identified, only 3 of these indices assessed factors at the local level and were generalizable to different types of outbreaks. Given the influence of local resources and community attributes on a wide range of communicable disease outcomes, there is a need for local-level tools that can be applied broadly to various types of outbreaks. Such tools should assess both current and long-term changes in outbreak preparedness with the intent to identify gaps, inform local-level decision makers, public policy, and future response to current and novel outbreaks.

The specialized functions of each hemisphere of the vertebrate brain are summarized together with the current evidence of lateralized behavior in farm and companion animals, as shown by the eye or ear used to attend and respond to stimuli. Forelimb preference is another manifestation of hemispheric lateralization, as shown by differences in behavior between left- and right-handed primates, left- and right-pawed dogs and cats, and left- and right-limb-preferring horses. Left-limb preference reflects right hemisphere use and is associated with negative cognitive bias. Positive cognitive bias is associated with right-limb and left-hemisphere preferences. The strength of lateralization is also associated with behavior. Animals with weak lateralization of the brain are unable to attend to more than one task at a time, and they are more easily stressed than animals with strong lateralization. This difference is also found in domesticated species with strong vs. weak limb preferences. Individuals with left-limb or ambilateral preference have a bias to express functions of the right hemisphere, heightened fear and aggression, and greater susceptibility to stress. Recognition of lateralized behavior can lead to improved welfare by detecting those animals most likely to suffer fear and distress and by indicating housing conditions and handling procedures that cause stress.

We compare the switching losses of four equivalent silicon and wide-bandgap 650 V power transistors operated in a hard-switched half-bridge configuration, switching 400 V at 40 A. Each transistor is mounted on an identical PCB and driven by a gate drive circuit matched to its requirements. Switching speed is maximised by a PCB design featuring very low parasitic inductance and the use of zero external gate resistance (where possible). Switching losses are measured electrically using a Double Pulse Test (DPT) method. However, high-bandwidth electrical measurements are prone to error and so we assess the gain accuracy, offset accuracy, and the bandwidth requirements of the DPT measurements, and then verify the DPT results by calorimetry. The electrical and calorimetric measurements are shown to agree to within 5%. Comprehensive plots of gate-source voltage, drain-source voltage, and source current are provided for all transistors over a junction temperature range of 50–150°C. The ratio of the total half-bridge switching losses is 1:3.2:14:31 for the GaN HEMT, SiC MOSFET, Si IGBT, and Si superjunction MOSFET, respectively.

Abstract Background Cell stress promotes degradation of mitochondria which release danger-associated molecular patterns that are catabolized to N-formylmethionine. We hypothesized that in critically ill adults, the response to N-formylmethionine is associated with increases in metabolomic shift-related metabolites and increases in 28-day mortality. Methods We performed metabolomics analyses on plasma from the 428-subject Correction of Vitamin D Deficiency in Critically Ill Patients trial (VITdAL-ICU) cohort and the 90-subject Brigham and Women’s Hospital Registry of Critical Illness (RoCI) cohort. In the VITdAL-ICU cohort, we analyzed 983 metabolites at Intensive Care Unit (ICU) admission, day 3, and 7. In the RoCI cohort, we analyzed 411 metabolites at ICU admission. The association between N-formylmethionine and mortality was determined by adjusted logistic regression. The relationship between individual metabolites and N-formylmethionine abundance was assessed with false discovery rate correction via linear regression, linear mixed-effects, and Gaussian graphical models. Results Patients with the top quartile of N-formylmethionine abundance at ICU admission had a significantly higher adjusted odds of 28-day mortality in the VITdAL-ICU (OR, 2.4; 95%CI 1.5–4.0; P = 0.001) and RoCI cohorts (OR, 5.1; 95%CI 1.4–18.7; P = 0.015). Adjusted linear regression shows that with increases in N-formylmethionine abundance at ICU admission, 55 metabolites have significant differences common to both the VITdAL-ICU and RoCI cohorts. With increased N-formylmethionine abundance, both cohorts had elevations in individual short-chain acylcarnitine, branched chain amino acid, kynurenine pathway, and pentose phosphate pathway metabolites. Conclusions The results indicate that circulating N-formylmethionine promotes a metabolic shift with heightened mortality that involves incomplete mitochondrial fatty acid oxidation, increased branched chain amino acid metabolism, and activation of the pentose phosphate pathway. Graphic Abstract

Abstract Background Intellectual disability affects approximately one third of individuals with autism spectrum disorder (autism). Yet, a major unresolved neurobiological question is what differentiates autistic individuals with and without intellectual disability. Intelligence quotients (IQs) are highly variable during childhood. We previously identified three subgroups of autistic children with different trajectories of intellectual development from early (2–3½ years) to middle childhood (9–12 years): (a) persistently high: individuals whose IQs remained in the normal range; (b) persistently low: individuals whose IQs remained in the range of intellectual disability (IQ < 70); and (c) changers: individuals whose IQs began in the range of intellectual disability but increased to the normal IQ range. The frontoparietal (FPN) and default mode (DMN) networks have established links to intellectual functioning. Here, we tested whether brain regions within the FPN and DMN differed volumetrically between these IQ trajectory groups in early childhood. Methods We conducted multivariate distance matrix regression to examine the brain regions within the FPN (11 regions x 2 hemispheres) and the DMN (12 regions x 2 hemispheres) in 48 persistently high (18 female), 108 persistently low (32 female), and 109 changers (39 female) using structural MRI acquired at baseline. FPN and DMN regions were defined using networks identified in Smith et al. (Proc Natl Acad Sci U S A 106:13040–5, 2009). IQ trajectory groups were defined by IQ measurements from up to three time points spanning early to middle childhood (mean age time 1: 3.2 years; time 2: 5.4 years; time 3: 11.3 years). Results The changers group exhibited volumetric differences in the DMN compared to both the persistently low and persistently high groups at time 1. However, the persistently high group did not differ from the persistently low group, suggesting that DMN structure may be an early predictor for change in IQ trajectory. In contrast, the persistently high group exhibited differences in the FPN compared to both the persistently low and changers groups, suggesting differences related more to concurrent IQ and the absence of intellectual disability. Conclusions Within autism, volumetric differences of brain regions within the DMN in early childhood may differentiate individuals with persistently low IQ from those with low IQ that improves through childhood. Structural differences in brain networks between these three IQ-based subgroups highlight distinct neural underpinnings of these autism sub-phenotypes.

Abstract Introduction We describe a protocol for FIRE CORAL, an observational cohort study that examines the recovery from COVID-19 disease following acute hospitalization with an emphasis on functional, imaging, and respiratory evaluation. Methods and analysis FIRE CORAL is a multicenter prospective cohort study of participants recovering from COVID-19 disease with in-person follow-up for functional and pulmonary phenotyping conducted by the National Heart, Lung and Blood Institute (NHLBI) Prevention and Early Treatment of Acute Lung Injury (PETAL) Network. FIRE CORAL will include a subset of participants enrolled in Biology and Longitudinal Epidemiology of PETAL COVID-19 Observational Study (BLUE CORAL), an NHLBI-funded prospective cohort study describing the clinical characteristics, treatments, biology, and outcomes of hospitalized patients with COVID-19 across the PETAL Network. FIRE CORAL consists of a battery of in-person assessments objectively measuring pulmonary function, abnormalities on lung imaging, physical functional status, and biospecimen analyses. Participants will attend and perform initial in-person testing at 3 to 9 months after hospitalization. The primary objective of the study is to determine the feasibility of longitudinal assessments investigating multiple domains of recovery from COVID-19. Secondarily, we will perform descriptive statistics, including the prevalence and characterization of abnormalities on pulmonary function, chest imaging, and functional status. We will also identify potential clinical and biologic factors that predict recovery or the occurrence of persistent impairment of pulmonary function, chest imaging, and functional status. Ethics and dissemination FIRE CORAL is approved via the Vanderbilt University central institutional review board (IRB) and via reliance agreement with the site IRBs. Results will be disseminated via the writing group for the protocol committee and reviewed by the PETAL Network publications committee prior to publication. Data obtained via the study will subsequently be made publicly available via NHLBI’s biorepository. Strengths and limitations of the study Strengths: First US-based multicenter cohort of pulmonary and functional outcomes in patients previously hospitalized for COVID-19 infection Longitudinal biospecimen measurement allowing for biologic phenotyping of abnormalities Geographically diverse cohort allowing for a more generalizable understanding of post-COVID pulmonary sequela Limitations: Selected cohort given proximity to a participating center Small cohort which may be underpowered to identify small changes in pulmonary function

There is a genetic component to the risk of severe COVID-19, but the genetic effects are difficult to separate from social constructs that covary with genetic ancestry. To address this, the authors identify determinants of COVID-19 severity using admixture mapping, viral phylodynamics, and host immune and metagenomic sequencing.