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Despite increasing interest in the dynamics of functional brain networks, most studies focus on the changing relationships over time between spatially static networks or regions. Here we propose an approach to study dynamic spatial brain networks in human resting state functional magnetic resonance imaging (rsfMRI) data and evaluate the temporal changes in the volumes of these 4D networks. Our results show significant volumetric coupling (i.e., synchronized shrinkage and growth) between networks during the scan, that we refer to as dynamic spatial network connectivity (dSNC). We find that several features of such dynamic spatial brain networks are associated with cognition, with higher dynamic variability in these networks and higher volumetric coupling between network pairs positively associated with cognitive performance. We show that these networks are modulated differently in individuals with schizophrenia versus typical controls, resulting in network growth or shrinkage, as well as altered focus of activity within a network. Schizophrenia also shows lower spatial dynamical variability in several networks, and lower volumetric coupling between pairs of networks, thus upholding the role of dynamic spatial brain networks in cognitive impairment seen in schizophrenia. Our data show evidence for the importance of studying the typically overlooked voxel‐wise changes within and between brain networks. [ABSTRACT FROM AUTHOR]

Background Aims Patients/Methods Results Conclusions Patients can have different reasons for seeking cheek augmentation; while some are in need of volume augmentation, others may request projection and lifting. A treatment guide can be useful for treating clinicians in choosing the most suitable product.This 8‐week, multicenter study was conducted to evaluate the effectiveness and safety of cheek augmentation using a treatment guide to choose between study products HACON and HALYF.Female subjects intending to undergo cheek augmentation were treated according to primary need for treatment—HACON for contouring or HALYF for projection. Treatments were performed according to approved labels. Assessments included Global Aesthetic Improvement Scale (GAIS) evaluations, subject satisfaction, subject‐perceived age (FACE‐Q), naturalness of facial expressions, 3D imaging analysis, and safety assessments.All subjects (n = 60) were assessed as aesthetically improved by the investigators 4 and 8 weeks after last injection. For all subjects, contouring or projection was achieved as planned with natural‐looking results. Subject satisfaction was high in both study groups. Volume change of the cheek area was statistically significant from baseline to Week 4 (p < 0.001), in both treatment groups and on both sides of the face. Overall, treatments were well tolerated with mainly mild adverse events related to treatment.The proposed guide for product selection of HACON or HALYF for treatment of the cheek area was useful to achieve the primary treatment goal for both products. Treatments were well tolerated and associated with improved aesthetic appearance of the cheeks as well as high subject satisfaction. [ABSTRACT FROM AUTHOR]

Testosterone levels sharply rise during the transition from childhood to adolescence and these changes are known to be associated with changes in human brain structure. During this same developmental window, there are also robust changes in the neural oscillatory dynamics serving verbal working memory processing. Surprisingly, whereas many studies have investigated the effects of chronological age on the neural oscillations supporting verbal working memory, none have probed the impact of endogenous testosterone levels during this developmental period. Using a sample of 89 youth aged 6–14 years‐old, we collected salivary testosterone samples and recorded magnetoencephalography during a modified Sternberg verbal working memory task. Significant oscillatory responses were identified and imaged using a beamforming approach and the resulting maps were subjected to whole‐brain ANCOVAs examining the effects of testosterone and sex, controlling for age, during verbal working memory encoding and maintenance. Our primary results indicated robust testosterone‐related effects in theta (4–7 Hz) and alpha (8–14 Hz) oscillatory activity, controlling for age. During encoding, females exhibited weaker theta oscillations than males in right cerebellar cortices and stronger alpha oscillations in left temporal cortices. During maintenance, youth with greater testosterone exhibited weaker alpha oscillations in right parahippocampal and cerebellar cortices, as well as regions across the left‐lateralized language network. These results extend the existing literature on the development of verbal working memory processing by showing region and sex‐specific effects of testosterone, and are the first results to link endogenous testosterone levels to the neural oscillatory activity serving verbal working memory, above and beyond the effects of chronological age. [ABSTRACT FROM AUTHOR]

In this article I offer an analysis of harms associated with sexual objectification. Objectification can be benign, but harm tends to occur in three circumstances: (i) when objectification is non‐consensual, (ii) when a phenomenon that I term 'context‐creeping' occurs, and (iii) when the objectification is also enacting or reinforcing some kind of oppression. I defend the view that objectification is not always harmful, and I explain the popular intuition to the contrary by demonstrating that these three harm‐generating circumstances are especially prevalent. The phenomenon of 'context‐creeping' objectification is introduced to capture what is intuitively wrong with much objectification in media and advertising. This phenomenon describes when instances of sexual objectification (which may be, in themselves, benign) regularly occur outside sexual contexts, in a way that reinforces particular rape myths and thereby contributes to harms. This means that the ubiquity of discussion of pornography in the objectification literature is misleading, and a shift in focus to other media is warranted. I end with a warning, though: we should be very careful in how we respond to these problems, as attempts to mitigate any harms associated with objectifying media can badly misfire. [ABSTRACT FROM AUTHOR]

A study published in Clinical & Translational Medicine examines the connection between mitochondrial dysfunction, immune suppression, and the progression of BRAF V600E-mutated metastatic melanoma. The researchers analyzed proteomic data from 127 melanoma metastasis samples and discovered significant changes in mitochondrial function and immune response in BRAF V600E-mutated tumors. These findings indicate that targeting these adaptive pathways could lead to more effective treatment strategies. The study also emphasizes the important relationship between mitochondrial function and immune response in aggressive melanoma behavior. The article presents the results of a study that aimed to understand the molecular mechanisms underlying mitochondrial translation in melanoma. The researchers conducted bioinformatics analyses and found that high levels of mitochondrial ribosome proteins (MRPs) were associated with increased mitochondrial metabolic activities and compromised immune surveillance, which could facilitate tumor evasion. Conversely, tumors with lower levels of MRPs were enriched for proteins involved in extracellular matrix organization. The study suggests that targeting mitochondrial functions and combining them with immune checkpoint inhibitors could be a potential approach for treating metastatic melanoma. However, the study acknowledges the limitations of its small sample size and the need for further validation and functional studies. [Extracted from the article]

The minimizing Delta Debugging (DDMIN) was among the first algorithms designed to automate the task of reducing test cases. Its popularity is based on the characteristics that it works on any kind of input, without knowledge about the input structure. Several studies proved that smaller outputs can be produced faster with more advanced techniques (e.g., building a tree representation of the input and reducing that data structure); however, if the structure is unknown or changing frequently, maintaining the descriptors might not be resource‐efficient. Therefore, in this paper, we focus on the evaluation of the novel fixed‐point iteration of minimizing Delta Debugging (DDMIN*) on publicly available test suites related to software engineering. Our experiments show that DDMIN* can help reduce inputs further by 48.08% on average compared to DDMIN (using lines as the units of the reduction). Although the effectiveness of the algorithm improved, it comes with the cost of additional testing steps. This study shows how the characteristics of the input affect the results and when it pays off using DDMIN*. [ABSTRACT FROM AUTHOR]

The MHC class I region contains crucial genes for the innate and adaptive immune response, playing a key role in susceptibility to many autoimmune and infectious diseases. Genome‐wide association studies have identified numerous disease‐associated SNPs within this region. However, these associations do not fully capture the immune‐biological relevance of specific HLA alleles. HLA imputation techniques may leverage available SNP arrays by predicting allele genotypes based on the linkage disequilibrium between SNPs and specific HLA alleles. Successful imputation requires diverse and large reference panels, especially for admixed populations. This study employed a bioinformatics approach to call SNPs and HLA alleles in multi‐ethnic samples from the 1000 genomes (1KG) dataset and admixed individuals from Brazil (SABE), utilising 30X whole‐genome sequencing data. Using HIBAG, we created three reference panels: 1KG (n = 2504), SABE (n = 1171), and the full model (n = 3675) encompassing all samples. In extensive cross‐validation of these reference panels, the multi‐ethnic 1KG reference exhibited overall superior performance than the reference with only Brazilian samples. However, the best results were achieved with the full model. Additionally, we expanded the scope of imputation by developing reference panels for non‐classical, MICA, MICB and HLA‐H genes, previously unavailable for multi‐ethnic populations. Validation in an independent Brazilian dataset showcased the superiority of our reference panels over the Michigan Imputation Server, particularly in predicting HLA‐B alleles among Brazilians. Our investigations underscored the need to enhance or adapt reference panels to encompass the target population's genetic diversity, emphasising the significance of multiethnic references for accurate imputation across different populations. [ABSTRACT FROM AUTHOR]

Test weight (TW) is a unit of bulk density that is influenced by several factors, including both genetics and environment. A subset of the trials in the Uniform Soybean Tests—Southern States was used to correlate seed composition traits of oil and protein percentages, and seed weight (SW) with TW to investigate the interaction of these traits in multi‐environments for four different maturity group (MG) tests. The results indicate that environment (location and year combination) had a larger impact on TW than genetic effect in all MG tests. This difference was greater in the earlier MGs, compared to MG VI and MG VII. In all tests across four MGs, the genotype interaction with environment effect was significant, but practically was not as important as genotype or environment effects. Significant negative correlations between TW and SW (MG V, VI, and VII tests), and TW and oil (MG V and VI tests) were observed but not consistent in all environments within these tests. TW and protein correlations were inconsistent with a negative relationship in MG V but a positive relationship in MG VII. As anticipated, the inconsistencies in the relationships across MGs for TW and seed composition traits suggest that selection strategies for improving TW will differ across soybean breeding programs. In the future, a similar study using a diverse panel of cultivars that do not change from year to year may shed more light on the influence of seed composition and environmental conditions on TW. Core Ideas: Soybean test weights are heritable.Test weight and seed trait correlations differ across maturity groups.Test weight values across Uniform Soybean Test—Southern States were lower than the standard 60 lb bu‐1. [ABSTRACT FROM AUTHOR]

The brain mechanisms underlying the risk of cannabis use disorder (CUD) are poorly understood. Several studies have reported changes in functional connectivity (FC) in CUD, although none have focused on the study of time‐varying patterns of FC. To fill this important gap of knowledge, 39 individuals at risk for CUD and 55 controls, stratified by their score on a self‐screening questionnaire for cannabis‐related problems (CUDIT‐R), underwent resting‐state functional magnetic resonance imaging. Dynamic functional connectivity (dFNC) was estimated using independent component analysis, sliding‐time window correlations, cluster states and meta‐state indices of global dynamics and were compared among groups. At‐risk individuals stayed longer in a cluster state with higher within and reduced between network dFNC for the subcortical, sensory‐motor, visual, cognitive‐control and default‐mode networks, relative to controls. More globally, at‐risk individuals had a greater number of meta‐states and transitions between them and a longer state span and total distance between meta‐states in the state space. Our findings suggest that the risk of CUD is associated with an increased dynamic fluidity and dynamic range of FC. This may result in altered stability and engagement of the brain networks, which can ultimately translate into altered cortical and subcortical function conveying CUD risk. Identifying these changes in brain function can pave the way for early pharmacological and neurostimulation treatment of CUD, as much as they could facilitate the stratification of high‐risk individuals. [ABSTRACT FROM AUTHOR]

Soybean oil is an abundant commodity crop that has garnered attention for its use as a feedstock for sustainable materials. Soybean oil is high in polyunsaturated fatty acid content, which can promote undesirable properties in biodiesel and lubricant applications. In this work, we characterized the fatty acid composition of commercial soybean oil along with two other soybean oil varieties, Ellis and TN18‐4110. Ellis and commercial soybean oils had similar fatty acid compositions, while TN18‐4110 was enriched in the monounsaturated oleic acid. Biodiesel and estolides were prepared from the three varieties and the relevant physical properties were measured. In comparison to commercial soybean diesel, both Ellis and TN18‐4110 exhibited unique advantages. As estolide‐based lubricants, all three varieties had advantageous cold flow properties, but TN18‐4110 also possessed excellent oxidative stability and lower viscosity. The physical properties and structural property relationships of the biodiesel and estolides are discussed. [ABSTRACT FROM AUTHOR]

Schizophrenia (SZ) is a debilitating mental illness characterized by adolescence or early adulthood onset of psychosis, positive and negative symptoms, as well as cognitive impairments. Despite a plethora of studies leveraging functional connectivity (FC) from functional magnetic resonance imaging (fMRI) to predict symptoms and cognitive impairments of SZ, the findings have exhibited great heterogeneity. We aimed to identify congruous and replicable connectivity patterns capable of predicting positive and negative symptoms as well as cognitive impairments in SZ. Predictable functional connections (FCs) were identified by employing an individualized prediction model, whose replicability was further evaluated across three independent cohorts (BSNIP, SZ = 174; COBRE, SZ = 100; FBIRN, SZ = 161). Across cohorts, we observed that altered FCs in frontal‐temporal‐cingulate‐thalamic network were replicable in prediction of positive symptoms, while sensorimotor network was predictive of negative symptoms. Temporal‐parahippocampal network was consistently identified to be associated with reduced cognitive function. These replicable 23 FCs effectively distinguished SZ from healthy controls (HC) across three cohorts (82.7%, 90.2%, and 86.1%). Furthermore, models built using these replicable FCs showed comparable accuracies to those built using the whole‐brain features in predicting symptoms/cognition of SZ across the three cohorts (r =.17–.33, p <.05). Overall, our findings provide new insights into the neural underpinnings of SZ symptoms/cognition and offer potential targets for further research and possible clinical interventions. [ABSTRACT FROM AUTHOR]

The SNP‐HLA Reference Consortium (SHLARC), a component of the 18th International HLA and Immunogenetics Workshop, is aimed at collecting diverse and extensive human leukocyte antigen (HLA) data to create custom reference panels and enhance HLA imputation techniques. Genome‐wide association studies (GWAS) have significantly contributed to identifying genetic associations with various diseases. The HLA genomic region has emerged as the top locus in GWAS, particularly in immune‐related disorders. However, the limited information provided by single nucleotide polymorphisms (SNPs), the hallmark of GWAS, poses challenges, especially in the HLA region, where strong linkage disequilibrium (LD) spans several megabases. HLA imputation techniques have been developed using statistical inference in response to these challenges. These techniques enable the prediction of HLA alleles from genotyped GWAS SNPs. Here we present the SHLARC activities, a collaborative effort to create extensive, and multi‐ethnic reference panels to enhance HLA imputation accuracy. [ABSTRACT FROM AUTHOR]

Human genomics has quickly evolved, powering genome‐wide association studies (GWASs). SNP‐based GWASs cannot capture the intense polymorphism of HLA genes, highly associated with disease susceptibility. There are methods to statistically impute HLA genotypes from SNP‐genotypes data, but lack of diversity in reference panels hinders their performance. We evaluated the accuracy of the 1000 Genomes data as a reference panel for imputing HLA from admixed individuals of African and European ancestries, focusing on (a) the full dataset, (b) 10 replications from 6 populations, and (c) 19 conditions for the custom reference panels. The full dataset outperformed smaller models, with a good F1‐score of 0.66 for HLA‐B. However, custom models outperformed the multiethnic or population models of similar size (F1‐scores up to 0.53, against up to 0.42). We demonstrated the importance of using genetically specific models for imputing populations, which are currently underrepresented in public datasets, opening the door to HLA imputation for every genetic population. [ABSTRACT FROM AUTHOR]

The clinical development of Natural Killer (NK) cell‐mediated immunotherapy marks a milestone in the development of new cancer therapies and has gained traction due to the intrinsic ability of the NK cell to target and kill tumor cells. To fully harness the tumor killing ability of NK cells, we need to improve NK cell persistence and to overcome suppression of NK cell activation in the tumor microenvironment. The trans‐membrane, protein tyrosine phosphatase CD45, regulates NK cell homeostasis, with the genetic loss of CD45 in mice resulting in increased numbers of mature NK cells. This suggests that CD45‐deficient NK cells might display enhanced persistence following adoptive transfer. However, we demonstrate here that adoptive transfer of CD45‐deficiency did not enhance NK cell persistence in mice, and instead, the homeostatic disturbance of NK cells in CD45‐deficient mice stemmed from a developmental defect in the progenitor population. The enhanced maturation within the CD45‐deficient NK cell compartment was intrinsic to the NK cell lineage, and independent of the developmental defect. CD45 is not a conventional immune checkpoint candidate, as systemic loss is detrimental to T and B cell development, compromising the adaptive immune system. Nonetheless, this study suggests that inhibition of CD45 in progenitor or stem cell populations may improve the yield of in vitro generated NK cells for adoptive therapy. [ABSTRACT FROM AUTHOR]

Introduction: The anterior pituitary gland (PG) is a potential locus of hypothalamic–pituitary–adrenal (HPA) axis responsivity to early life stress, with documented associations between dehydroepiandrosterone (DHEA) levels and anterior PG volumes. In adults, elevated anxiety/depressive symptoms are related to diminished DHEA levels, and studies have shown a positive relationship between DHEA and anterior pituitary volumes. However, specific links between responses to stress, DHEA levels, and anterior pituitary volume have not been established in developmental samples. Methods: High‐resolution T1‐weighted MRI scans were collected from 137 healthy youth (9–17 years; Mage = 12.99 (SD = 1.87); 49% female; 85% White, 4% Indigenous, 1% Asian, 4% Black, 4% multiracial, 2% not reported). The anterior and posterior PGs were manually traced by trained raters. We examined the mediating effects of salivary DHEA on trauma‐related symptoms (i.e., anxiety, depression, and posttraumatic) and PG volumes as well as an alternative model examining mediating effects of PG volume on DHEA and trauma‐related symptoms. Results: DHEA mediated the association between anxiety symptoms and anterior PG volume. Specifically, higher anxiety symptoms related to lower DHEA levels, which in turn were related to smaller anterior PG. Conclusions: These results shed light on the neurobiological sequelae of elevated anxiety in youth and are consistent with adult findings showing suppressed levels of DHEA in those with greater comorbid anxiety and depression. Specifically, adolescents with greater subclinical anxiety may exhibit diminished levels of DHEA during the pubertal window, which may be associated with disruptions in anterior PG growth. [ABSTRACT FROM AUTHOR]

The transition from childhood to adolescence is associated with an influx of sex hormones, which not only facilitates physical and behavioral changes, but also dramatic changes in neural circuitry. While previous work has shown that pubertal hormones modulate structural and functional brain development, few of these studies have focused on the impact that such hormones have on spontaneous cortical activity, and whether these effects are modulated by sex during this critical developmental window. Herein, we examined the effect of endogenous testosterone on spontaneous cortical activity in 71 typically‐developing youth (ages 10–17 years; 32 male). Participants completed a resting‐state magnetoencephalographic (MEG) recording, structural MRI, and provided a saliva sample for hormone analysis. MEG data were source‐reconstructed and the power within five canonical frequency bands (delta, theta, alpha, beta, and gamma) was computed. The resulting power spectral density maps were analyzed via vertex‐wise ANCOVAs to identify spatially specific effects of testosterone and sex by testosterone interactions, while covarying out age. We found robust sex differences in the modulatory effects of testosterone on spontaneous delta, beta, and gamma activity. These interactions were largely confined to frontal cortices and exhibited a stark switch in the directionality of the correlation from the low (delta) to high frequencies (beta/gamma). For example, in the delta band, greater testosterone related to lower relative power in prefrontal cortices in boys, while the reverse pattern was found for girls. These data suggest testosterone levels are uniquely related to the development of spontaneous cortical dynamics during adolescence, and such levels are associated with different developmental patterns in males and females within regions implicated in executive functioning. [ABSTRACT FROM AUTHOR]

The examination of multivariate brain morphometry patterns has gained attention in recent years, especially for their powerful exploratory capabilities in the study of differences between patients and controls. Among the many existing methods and tools for the analysis of brain anatomy based on structural magnetic resonance imaging data, data‐driven source‐based morphometry (SBM) focuses on the exploratory detection of such patterns. Here, we implement a semi‐blind extension of SBM, called constrained source‐based morphometry (constrained SBM), which enables the extraction of maximally independent reference‐alike sources using the constrained independent component analysis (ICA) approach. To do this, we combine SBM with a set of reference components covering the full brain, derived from a large independent data set (UKBiobank), to provide a fully automated SBM framework. This also allows us to implement a federated version of constrained SBM (cSBM) to allow analysis of data that is not locally accessible. In our proposed decentralized constrained source‐based morphometry (dcSBM), the original data never leaves the local site. Each site operates constrained ICA on its private local data using a common distributed computation platform. Next, an aggregator/master node aggregates the results estimated from each local site and applies statistical analysis to estimate the significance of the sources. Finally, we utilize two additional multisite patient data sets to validate our model by comparing the resulting group difference estimates from both cSBM and dcSBM. [ABSTRACT FROM AUTHOR]

This work proposes a novel generative multimodal approach to jointly analyze multimodal data while linking the multimodal information to colors. We apply our proposed framework, which disentangles multimodal data into private and shared sets of features from pairs of structural (sMRI), functional (sFNC and ICA), and diffusion MRI data (FA maps). With our approach, we find that heterogeneity in schizophrenia is potentially a function of modality pairs. Results show (1) schizophrenia is highly multimodal and includes changes in specific networks, (2) non‐linear relationships with schizophrenia are observed when interpolating among shared latent dimensions, and (3) we observe a decrease in the modularity of functional connectivity and decreased visual‐sensorimotor connectivity for schizophrenia patients for the FA‐sFNC and sMRI‐sFNC modality pairs, respectively. Additionally, our results generally indicate decreased fractional corpus callosum anisotropy, and decreased spatial ICA map and voxel‐based morphometry strength in the superior frontal lobe as found in the FA‐sFNC, sMRI‐FA, and sMRI‐ICA modality pair clusters. In sum, we introduce a powerful new multimodal neuroimaging framework designed to provide a rich and intuitive understanding of the data which we hope challenges the reader to think differently about how modalities interact. [ABSTRACT FROM AUTHOR]

Brain networks extracted by independent component analysis (ICA) from magnitude‐only fMRI data are usually denoised using various amplitude‐based thresholds. By contrast, spatial source phase (SSP) or the phase information of ICA brain networks extracted from complex‐valued fMRI data, has provided a simple yet effective way to perform the denoising using a fixed phase change. In this work, we extend the approach to magnitude‐only fMRI data to avoid testing various amplitude thresholds for denoising magnitude maps extracted by ICA, as most studies do not save the complex‐valued data. The main idea is to generate a mathematical SSP map for a magnitude map using a mapping framework, and the mapping framework is built using complex‐valued fMRI data with a known SSP map. Here we leverage the fact that the phase map derived from phase fMRI data has similar phase information to the SSP map. After verifying the use of the magnitude data of complex‐valued fMRI, this framework is generalized to work with magnitude‐only data, allowing use of our approach even without the availability of the corresponding phase fMRI datasets. We test the proposed method using both simulated and experimental fMRI data including complex‐valued data from University of New Mexico and magnitude‐only data from Human Connectome Project. The results provide evidence that the mathematical SSP denoising with a fixed phase change is effective for denoising spatial maps from magnitude‐only fMRI data in terms of retaining more BOLD‐related activity and fewer unwanted voxels, compared with amplitude‐based thresholding. The proposed method provides a unified and efficient SSP approach to denoise ICA brain networks in fMRI data. [ABSTRACT FROM AUTHOR]

Programmed cell death pathways play an important role in innate immune responses to infection. Activation of intrinsic apoptosis promotes infected cell clearance; however, comparatively little is known about how this mode of cell death is regulated during infections and whether it can induce inflammation. Here, we identify that the pro‐survival BCL‐2 family member, A1, controls activation of the essential intrinsic apoptotic effectors BAX/BAK in macrophages and monocytes following bacterial lipopolysaccharide (LPS) sensing. We show that, due to its tight transcriptional and post‐translational regulation, A1 acts as a molecular rheostat to regulate BAX/BAK‐dependent apoptosis and the subsequent NLRP3 inflammasome‐dependent and inflammasome‐independent maturation of the inflammatory cytokine IL‐1β. Furthermore, induction of A1 expression in inflammatory monocytes limits cell death modalities and IL‐1β activation triggered by Neisseria gonorrhoeae‐derived outer membrane vesicles (NOMVs). Consequently, A1‐deficient mice exhibit heightened IL‐1β production in response to NOMV injection. These findings reveal that bacteria can induce A1 expression to delay myeloid cell death and inflammatory responses, which has implications for the development of host‐directed antimicrobial therapeutics. Synopsis: Cell death and inflammatory signalling crosstalk is critical for innate immune responses to pathogens. This study identifies the BCL‐2 family member A1 as a temporal regulator of these processes in myeloid cells upon bacterial recognition. LPS‐induced A1 expression in macrophages and monocytes delays apoptosis and NLRP3 inflammasome activation.Monocyte survival upon pathogen sensing is regulated by the short‐lived pro‐survival proteins MCL‐1 and A1.A1‐deficient myeloid cells can engage necroptotic signalling when apoptotic caspase activity is compromised.A1‐deficiency enhances IL‐1β responses to Neisseria gonorrhoeae‐derived outer membrane vesicles (NOMVs). [ABSTRACT FROM AUTHOR]

In recent years, Model‐Based Systems Engineering (MBSE) practices have been applied in various industries to design, simulate and verify complex systems. The verification and validation (V&V) of such systems engineering models are crucial to develop high‐quality systems. However, this is a challenging problem due to the complexity of the models and semantic differences in how different tools interpret the models, which can undermine the validity of the obtained results if they go undiscovered. To address these issues, we propose (i) a subset of the SysML language for which the practical semantic integrity of tools can be achieved and (ii) a cloud‐based V&V framework for this subset, lifting verification to an industrial scale. We demonstrate the feasibility of our approach on an industrial‐scale model from the aerospace domain and summarize the lessons learned during transitioning formal verification tools to an industrial context. [ABSTRACT FROM AUTHOR]

In this article, we focus on estimating the joint relationship between structural magnetic resonance imaging (sMRI) gray matter (GM), and multiple functional MRI (fMRI) intrinsic connectivity networks (ICNs). To achieve this, we propose a multilink joint independent component analysis (ml‐jICA) method using the same core algorithm as jICA. To relax the jICA assumption, we propose another extension called parallel multilink jICA (pml‐jICA) that allows for a more balanced weight distribution over ml‐jICA/jICA. We assume a shared mixing matrix for both the sMRI and fMRI modalities, while allowing for different mixing matrices linking the sMRI data to the different ICNs. We introduce the model and then apply this approach to study the differences in resting fMRI and sMRI data from patients with Alzheimer's disease (AD) versus controls. The results of the pml‐jICA yield significant differences with large effect sizes that include regions in overlapping portions of default mode network, and also hippocampus and thalamus. Importantly, we identify two joint components with partially overlapping regions which show opposite effects for AD versus controls, but were able to be separated due to being linked to distinct functional and structural patterns. This highlights the unique strength of our approach and multimodal fusion approaches generally in revealing potentially biomarkers of brain disorders that would likely be missed by a unimodal approach. These results represent the first work linking multiple fMRI ICNs to GM components within a multimodal data fusion model and challenges the typical view that brain structure is more sensitive to AD than fMRI. [ABSTRACT FROM AUTHOR]

In this paper we develop a model for the capabilities required by principals for effective Science, Technology, Engineering and Mathematics (STEM) leadership. The model underpinned a large national cross-sectional research and development project across Australian states in both primary and secondary schools. This model is developed via synthesis of research literature across leadership and STEM education. The model consists of five dimensions of principals' STEM capability: (1) STEM discipline-specific and integrated knowledge and practices; (2) contexts; (3) dispositions; (4) tools; and (5) critical orientation. These dimensions represent distinct, but interrelated, capacities required by principals to establish and maintain positive STEM learning cultures within schools. Elaborations have been provided, in the form of capabilities, for each of these dimensions. The model has the potential for shaping principals' STEM leadership development trajectories and structuring targeted professional learning programmes for principals, teachers and other members of the school community. [ABSTRACT FROM AUTHOR]

Control systems are typically tightly embedded into their environment to enable adaptation to environmental effects. As the complexity of such adaptive systems is rapidly increasing, there is a strong need for coherent tool‐centric approaches to aid their systematic development. This paper proposes an end‐to‐end component‐based specification, design and verification approach for adaptive systems based on the integration of a high‐level scenario language (sequence chart variant) and an adaptation definition language (statechart extension) in the open source Gamma tool. The scenario language supports high‐level constructs for specifying contracts and the adaptation definition language supports the flexible activation and deactivation of static contracts and managed elements (state‐based components) based on internal changes (e.g., faults), environmental changes (e.g., varying context) or interactions. The approach supports linking managed elements to static contracts to formally verify their adherence to the specified behavior at design time using integrated model checkers. Implementation can be derived from the adaptation model automatically, which can be tested using automated test generation and verified at runtime by contract‐based monitors. [ABSTRACT FROM AUTHOR]

Cotton (Gossypium hirsutum L.) germplasm lines BARBREN‐713‐8 (Reg. no. GP‐1138, PI 701080), BARBREN‐713‐11 (Reg. no. GP‐1131, PI 701073), BARBREN‐713‐13 (Reg. no. GP‐1132, PI 701074), BARBREN‐713‐25 (Reg. no. GP‐1133, PI 701075), BARBREN‐713‐32 (Reg. no. GP‐1134, PI 701076), BARBREN‐713‐33 (Reg. no. GP‐1135, PI 701077), BARBREN‐713‐41 (Reg. no. GP‐1136, PI 701078), and BARBREN‐713‐48 (Reg. no. GP‐1137, PI 701079) were developed and released by the USDA‐ARS, Texas A&M AgriLife Research, and Cotton Incorporated in 2014. The objective of the release was to provide breeders with agronomically elite germplasm that is resistant to reniform nematode (Rotylenchulus reniformis). Four lines (BARBREN‐713‐8, ‐32, ‐33, and ‐48) also have simple sequence repeat (SSR) DNA markers for the Mi‐1 or Mi‐2 gene for resistance to root‐knot nematode [Meloidogyne incognita (Kolfoid & White) Chitwood]. The lines have excellent seedling vigor in fields infested with both nematodes and fungal root‐rot pathogens. Resistance to reniform nematode was transferred from G. barbadense GB713 (PI 608139) and is associated primarily with the Ren2GB713 gene on chromosome 21. This gene could be detected with the codominant SSR marker BNL3279_105 or the single nucleotide polymorphism marker GI‐187401. In controlled environment assays, these lines reported here suppressed numbers of reniform nematode eggs by 74–92% compared with 'FiberMax FM966'. The lines outyielded and had fiber quality equal to or greater than several commercial cultivars. Core Ideas: Germplasm sources that combine elite agronomic performance with nematode resistance are needed.Developed lines have resistance to reniform nematode and elite agronomic performance even in absence of nematodes.SSR genotyping was used to develop SNP DNA markers to locate the Ren2GB713 gene.Incorporation of Ren2 markers into breeding lines improves agronomic performance and nematode resistance.These lines should allow use of resistance to nematodes in all areas where they are problematic. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to examine the intergenerational effects of maternal adverse childhood experiences (ACEs) and child mental health outcomes in rural Uganda, as well as the potentially mediating role of maternal depression in this pathway. Additionally, we sought to test the extent to which maternal social group membership attenuated the mediating effect of maternal depression on child mental health. Methods: Data come from a population‐based cohort of families living in the Nyakabare Parish, a rural district in southwestern Uganda. Between 2016 and 2018, mothers completed surveys about childhood adversity, depressive symptoms, social group membership, and their children's mental health. Survey data were analyzed using causal mediation and moderated‐mediation analysis. Results: Among 218 mother–child pairs, 61 mothers (28%) and 47 children (22%) showed symptoms meeting cutoffs for clinically significant psychological distress. In multivariable linear regression models, maternal ACEs had a statistically significant association with severity of child conduct problems, peer problems, and total child difficulty scores. Maternal depression mediated the relationship between maternal ACEs and conduct problems, peer problems, and total difficulty, but this mediating effect was not moderated by maternal group membership. Conclusions: Maternal depression may act as a potential mechanism linking maternal childhood adversity with poor child mental health in the next generation. Within a context of elevated rates of psychiatric morbidity, high prevalence of childhood adversity, and limited healthcare and economic infrastructures across Uganda, these results emphasize the prioritization of social services and mental health resources for rural Ugandan families. [ABSTRACT FROM AUTHOR]

BrainForge is a cloud‐enabled, web‐based analysis platform for neuroimaging research. This website allows users to archive data from a study and effortlessly process data on a high‐performance computing cluster. After analyses are completed, results can be quickly shared with colleagues. BrainForge solves multiple problems for researchers who want to analyze neuroimaging data, including issues related to software, reproducibility, computational resources, and data sharing. BrainForge can currently process structural, functional, diffusion, and arterial spin labeling MRI modalities, including preprocessing and group level analyses. Additional pipelines are currently being added, and the pipelines can accept the BIDS format. Analyses are conducted completely inside of Singularity containers and utilize popular software packages including Nipype, Statistical Parametric Mapping, the Group ICA of fMRI Toolbox, and FreeSurfer. BrainForge also features several interfaces for group analysis, including a fully automated adaptive ICA approach. [ABSTRACT FROM AUTHOR]

Because connectivity is such a basic concept in graph theory, extremal problems concerning the average order of the connected induced subgraphs of a graph have been of notable interest. A particularly resistant open problem is whether or not, for a connected graph G $G$ of order n $n$, all of whose vertices have degree at least 3, this average is at least n ∕ 2 $n\unicode{x02215}2$. It is shown in this paper that if G $G$ is a connected, vertex transitive graph, then the average order of the connected induced subgraphs of G $G$ is at least n ∕ 2 $n\unicode{x02215}2$.The extremal graph theory problems mentioned above lead to a broader theory. The concept of a Union‐Intersection System (UIS) S ≔(P , B ) ${\mathscr{S}}:= (P,{\rm{ {\mathcal B} }})$ is introduced, P $P$ being a finite set of points and B ${\rm{ {\mathcal B} }}$ a set of subsets of P $P$ called blocks satisfying the following simple property for all A , B ∈ B $A,B\in {\rm{ {\mathcal B} }}$: if A ∩ B ∈ B $A\cap B\in {\rm{ {\mathcal B} }}$, then A ∪ B ∈ B $A\cup B\in {\rm{ {\mathcal B} }}$. To generalize results on the average order of a connected induced subgraph of a graph, it is conjectured that if a UIS is, in various senses, “connected and regular,” then the average size of a block is at least half the number of points. We prove that if a union‐intersection set system is regular, completely irreducible, and nonredundant, then the average size of a block is at least half the number of points. [ABSTRACT FROM AUTHOR]

Diffusion and movement of subcutaneously injected biologics and high‐concentration immunoglobulin G (IgG) therapeutics away from the injection site and through the subcutaneous (SC) tissue may be concentration dependent. This possibility was confirmed by in situ measurement of diffusion coefficients of unlabeled bovine IgG in phosphate‐buffered saline within an in vitro hyaluronic acid matrix that represents the SC electrostatic environment. Diffusion decreased from 2.67 to 0.05 × 10−7 cm2/s when IgG concentration increased from 25 to 73 mg/mL. The results demonstrated that in situ detection of unlabeled proteins within an in vitro SC environment provides another useful tool for the preclinical characterization of injectable biologics. [ABSTRACT FROM AUTHOR]

Gene co‐expression network analysis is an efficient systems biology approach for the discovery of novel gene functions and trait‐associated gene modules. To identify clusters of functionally related genes involved in soybean nodule formation and development, we performed a weighted gene co‐expression network analysis. Two nodule‐specific modules (NSM‐1 and NSM‐2, containing 304 and 203 genes, respectively) were identified. The NSM‐1 gene promoters were significantly enriched in cis‐binding elements for ERF, MYB, and C2H2‐type zinc transcription factors, whereas NSM‐2 gene promoters were enriched in cis‐binding elements for TCP, bZIP, and bHLH transcription factors, suggesting a role of these regulatory factors in the transcriptional activation of nodule co‐expressed genes. The co‐expressed gene modules included genes with potential novel roles in nodulation, including those involved in xylem development, transmembrane transport, the ethylene signalling pathway, cytoskeleton organization, cytokinesis and regulation of the cell cycle, regulation of meristem initiation and growth, transcriptional regulation, DNA methylation, and histone modifications. Functional analysis of two co‐expressed genes using TILLING mutants provided novel insight into the involvement of unsaturated fatty acid biosynthesis and folate metabolism in nodule formation and development. The identified gene co‐expression modules provide valuable resources for further functional genomics studies to dissect the genetic basis of nodule formation and development in soybean. [ABSTRACT FROM AUTHOR]

HLA‐B is among the most variable gene in the human genome. This gene encodes a key molecule for antigen presentation to CD8+ T lymphocytes and NK cell modulation. Despite the myriad of studies evaluating its coding region (with an emphasis on exons 2 and 3), few studies evaluated introns and regulatory sequences in real population samples. Thus, HLA‐B variability is probably underestimated. We applied a bioinformatics pipeline tailored for HLA genes on 5347 samples from 80 different populations, which includes more than 1000 admixed Brazilians, to evaluate the HLA‐B variability (SNPs, indels, MNPs, alleles, and haplotypes) in exons, introns, and regulatory regions. We observed 610 variable sites throughout HLA‐B; the most frequent variants are shared worldwide. However, the haplotype distribution is geographically structured. We detected 920 full‐length haplotypes (exons, introns, and untranslated regions) encoding 239 different protein sequences. HLA‐B gene diversity is higher in admixed populations and Europeans while lower in African ancestry individuals. Each HLA‐B allele group is associated with specific promoter sequences. This HLA‐B variation resource may improve HLA imputation accuracy and disease‐association studies and provide evolutionary insights regarding HLA‐B genetic diversity in human populations. [ABSTRACT FROM AUTHOR]

Background: COVID‐19 is a life‐threatening virus which has circulated the globe resulting in unprecedented effects on the daily lives of people across the world. Countries across the globe have advocated measures, including self‐isolation and maintaining social distance to reduce the spread of COVID‐19. The pandemic has seen an increase in the use of information and communication technology (ICT) for many aspects of life. This study aimed to find out from people with intellectual disabilities what it was like using ICT during COVID‐19 and how this affected their lives. Method: Interviews and focus groups were conducted with 19 people with learning disabilities throughout the COVID pandemic. The qu/alitative data gathered was analysed using longitudinal thematic framework analysis to identify the main ways technology use had impacted on people's lives and the challenges and facilitators of technology use during this time. Findings: Technology played an important role in the lives of the people with learning disabilities who took part in the study. Technology facilitated continuation and maintenance of important daily activities and roles in people's lives (e.g., jobs, getting support and leisure), keeping people meaningfully occupied and maintaining social contact which reduced feelings of loneliness and isolation. People adapted and learned new skills, with help from friends, family and support staff, which boosted self‐confidence. Despite some identified barriers, prior technology use, tenacity and a positive attitude towards ICT supported learning new skills and adaptation to increased ICT use. Conclusions: Supporting the development of digital competence, confidence and persistence in people with learning disabilities was important during this international crisis and has had a fundamental positive effect on wellbeing. Accessible summary: COVID‐19 restrictions means that things that used to happen face‐to‐face now happen using technology online.We talked to 19 people to find out their experiences of using technology during COVID‐19.They told us that though they would be lost without it. It helped people to keep doing things but keeping in touch using technology was not the same.Experience, education, support from other people, being positive and not giving up helped people use technology during COVID‐19. [ABSTRACT FROM AUTHOR]

The validity and reliability of diagnoses in psychiatry is a challenging topic in mental health. The current mental health categorization is based primarily on symptoms and clinical course and is not biologically validated. Among multiple ongoing efforts, neurological observations alongside clinical evaluations are considered to be potential solutions to address diagnostic problems. The Bipolar‐Schizophrenia Network on Intermediate Phenotypes (B‐SNIP) has published multiple papers attempting to reclassify psychotic illnesses based on biological rather than symptomatic measures. However, the effort to investigate the relationship between this new categorization approach and other neuroimaging techniques, including resting‐state fMRI data, is still limited. This study focused on investigating the relationship between different psychotic disorders categorization methods and resting‐state fMRI‐based measures called dynamic functional network connectivity (dFNC) using state‐of‐the‐art artificial intelligence (AI) approaches. We applied our method to 613 subjects, including individuals with psychosis and healthy controls, which were classified using both the Diagnostic and Statistical Manual of Mental Disorders (DSM‐IV) and the B‐SNIP biomarker‐based (Biotype) approach. Statistical group differences and cross‐validated classifiers were performed within each framework to assess how different categories. Results highlight interesting differences in occupancy in both DSM‐IV and Biotype categorizations compared to healthy individuals, which are distributed across specific transient connectivity states. Biotypes tended to show less distinctiveness in occupancy level and included fewer cellwise differences. Classification accuracy obtained by DSM‐IV and Biotype categories were both well above chance. Results provided new insights and highlighted the benefits of both DSM‐IV and biology‐based categories while also emphasizing the importance of future work in this direction, including employing further data types. [ABSTRACT FROM AUTHOR]

Lynch syndrome (LS) is the most common inherited cancer syndrome. It is inherited via a monoallelic germline variant in one of the DNA mismatch repair (MMR) genes. LS carriers have a broad 30% to 80% risk of developing various malignancies, and more precise, individual risk estimations would be of high clinical value, allowing tailored cancer prevention and surveillance. Due to MMR deficiency, LS cancers are characterized by the accumulation of frameshift mutations leading to highly immunogenic frameshift peptides (FSPs). Thus, immune surveillance is proposed to inhibit the outgrowth of MMR‐deficient cell clones. Recent studies have shown that immunoediting during the evolution of MMR‐deficient cancers leads to a counter‐selection of highly immunogenic antigens. The immunogenicity of FSPs is dependent on the antigen presentation. One crucial factor determining antigen presentation is the HLA genotype. Hence, a LS carrier's HLA genotype plays an important role in the presentation of FSP antigens to the immune system, and may influence the likelihood of progression from precancerous lesions to cancer. To address the challenge of clarifying this possibility including diverse populations with different HLA types, we have established the INDICATE initiative (Individual cancer risk by HLA type, http://indicate-lynch.org/), an international network aiming at a systematic evaluation of the HLA genotype as a possible cancer risk modifier in LS. Here we summarize the current knowledge on the role of HLA type in cancer risk and outline future research directions to delineate possible association in the scenario of LS with genetically defined risk population and highly immunogenic tumors. [ABSTRACT FROM AUTHOR]

Parasitic absorption in the front window layers of transparent conductive oxide (TCO) films and carrier selective collection layers and the optical shading losses from the metallic finger grid mainly limit the current generation in silicon heterojunction (SHJ) solar cells. In this work, we demonstrate an improved short‐circuit current density (Jsc) of 40.24 mA/cm2 through a combination of novel window layers composed of transition metal doped indium oxide (IMO) and hydrogenated nanocrystalline silicon oxide (nc‐SiOx:H) films and Cu plating for SHJ solar cells. By introducing water vapor during direct current (DC) magnetron sputtering deposition process, IMO films show a large optical band gap (Eg) of about 3.88 eV and high mobility up to 83.2 cm2/V·s, while maintaining a low carrier concentration, which leads to high transparency and low near‐infrared (NIR) free carrier absorption (FCA). In addition to its high deposition rate and crystalline volume fraction, we found that nc‐SiOx:H films deposited by very high frequency (VHF) excited plasma‐enhanced chemical vapor deposition (PECVD) show an excellent surface passivation quality, which not only improves the open circuit voltage (Voc) of SHJ cells but also increases the Jsc through improved carrier selective collection. The quantified Jsc breakdown analysis was performed to identify the room for improvement, and it showed that the front shading loss (about 1.32 mA/cm2) is the largest portion. By combining the benefits of these window layer enhancements with the further use of fine line width and conductivity of Cu plating, SHJ solar cells, with a Jsc improvement of 0.57 mA/cm2 and a certified efficiency of 25.54%, were achieved on a total area of 274.5 cm2 using in‐house pilot production line equipment. [ABSTRACT FROM AUTHOR]

Resting‐state functional network connectivity (rsFNC) has shown utility for identifying characteristic functional brain patterns in individuals with psychiatric and mood disorders, providing a promising avenue for biomarker development. However, several factors have precluded widespread clinical adoption of rsFNC diagnostics, namely a lack of standardized approaches for capturing comparable and reproducible imaging markers across individuals, as well as the disagreement on the amount of data required to robustly detect intrinsic connectivity networks (ICNs) and diagnostically relevant patterns of rsFNC at the individual subject level. Recently, spatially constrained independent component analysis (scICA) has been proposed as an automated method for extracting ICNs standardized to a chosen network template while still preserving individual variation. Leveraging the scICA methodology, which solves the former challenge of standardized neuroimaging markers, we investigate the latter challenge of identifying a minimally sufficient data length for clinical applications of resting‐state fMRI (rsfMRI). Using a dataset containing rsfMRI scans of individuals with schizophrenia and controls (M = 310) as well as simulated rsfMRI, we evaluated the robustness of ICN and rsFNC estimates at both the subject‐ and group‐level, as well as the performance of diagnostic classification, with respect to the length of the rsfMRI time course. We found individual estimates of ICNs and rsFNC from the full‐length (5 min) reference time course were sufficiently approximated with just 3–3.5 min of data (r = 0.85, 0.88, respectively), and significant differences in group‐average rsFNC could be sufficiently approximated with even less data, just 2 min (r = 0.86). These results from the shorter clinical data were largely consistent with the results from validation experiments using longer time series from both simulated (30 min) and real‐world (14 min) datasets, in which estimates of subject‐level FNC were reliably estimated with 3–5 min of data. Moreover, in the real‐world data we found rsFNC and ICN estimates generated across the full range of data lengths (0.5–14 min) more reliably matched those generated from the first 5 min of scan time than those generated from the last 5 min, suggesting increased influence of "late scan" noise factors such as fatigue or drowsiness may limit the reliability of FNC from data collected after 10+ min of scan time, further supporting the notion of shorter scans. Lastly, a diagnostic classification model trained on just 2 min of data retained 97%–98% classification accuracy relative to that of the full‐length reference model. Our results suggest that, when decomposed with scICA, rsfMRI scans of just 2–5 min show good clinical utility without significant loss of individual FNC information of longer scan lengths. [ABSTRACT FROM AUTHOR]

The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time‐resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time‐resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U‐shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State‐based statistical summary measures presented robust and significant group differences that also showed significant age‐related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time‐resolved brain state trajectories. [ABSTRACT FROM AUTHOR]

Clinical trials generate key evidence to inform decision making, and also benefit participants directly. However, clinical trials frequently fail, often struggle to enroll participants, and are expensive. Part of the problem with trial conduct may be the disconnected nature of clinical trials, preventing rapid data sharing, generation of insights and targeted improvement interventions, and identification of knowledge gaps. In other areas of healthcare, a learning health system (LHS) has been proposed as a model to facilitate continuous learning and improvement. We propose that an LHS approach could greatly benefit clinical trials, allowing for continuous improvements to trial conduct and efficiency. A robust trial data sharing system, continuous analysis of trial enrollment and other success metrics, and development of targeted trial improvement interventions are potentially key components of a Trials LHS reflecting the learning cycle and allowing for continuous trial improvement. Through the development and use of a Trials LHS, clinical trials could be treated as a system, producing benefits to patients, advancing care, and decreasing costs for stakeholders. [ABSTRACT FROM AUTHOR]

The study of human brain connectivity, including structural connectivity (SC) and functional connectivity (FC), provides insights into the neurophysiological mechanism of brain function and its relationship to human behavior and cognition. Both types of connectivity measurements provide crucial yet complementary information. However, integrating these two modalities into a single framework remains a challenge, because of the differences in their quantitative interdependencies as well as their anatomical representations due to distinctive imaging mechanisms. In this study, we introduced a new method, joint connectivity matrix independent component analysis (cmICA), which provides a data‐driven parcellation and automated‐linking of SC and FC information simultaneously using a joint analysis of functional magnetic resonance imaging (MRI) and diffusion‐weighted MRI data. We showed that these two connectivity modalities produce common cortical segregation, though with various degrees of (dis)similarity. Moreover, we show conjoint FC networks and structural white matter tracts that directly link these cortical parcellations/sources, within one analysis. Overall, data‐driven joint cmICA provides a new approach for integrating or fusing structural connectivity and FC systematically and conveniently, and provides an effective tool for connectivity‐based multimodal data fusion in brain. [ABSTRACT FROM AUTHOR]

Absolute pitch (AP) refers to the naming of musical tone without external reference. The influential two‐component model states that AP is limited by the late‐emerging pitch labeling process only and not the earlier perceptual and memory processes. Over the years, however, support for this model at the neural level has been mixed with various methodological limitations. Here, the electroencephalography responses of 27 AP possessors and 27 non‐AP possessors were recorded. During both name verification and passive listening, event‐related potential analyses showed a difference between AP and non‐AP possessors at about 200 ms in their response toward tones compared with noise stimuli. Multivariate pattern analyses suggested that pitch naming was subserved by a series of transient processes for the first 250 ms, followed by a stage‐like process for both AP and non‐AP possessors with no group differences between them. These findings are inconsistent with the predictions of the two‐component model, and instead suggest the existence of an early perceptual locus of AP. Absolute pitch (AP) is a skill that is of high interest to musicians, and the existing model of AP suggested a late locus associated with tone labeling. Using an event‐related design contrasting AP and non‐AP musicians with noise control, we found an AP‐sensitive ERP effect at about 200 ms, which supported the existence of an early perceptual locus of AP. Our finding calls for a revision of the current theoretical model of AP. [ABSTRACT FROM AUTHOR]

Single‐use plastics (SUPs) are increasingly polluting terrestrial, coastal, and marine habits, contributing to the creeping "plastic crisis." The COVID‐19 pandemic provided a window of opportunity for decision makers to change the degree of urgency and responsiveness to this crisis and for policy entrepreneurs and industry who are against reducing plastic consumption to influence decision makers to change their position on various plastic‐related issues. Hygiene/health concerns have been used as a justification by governments and industry to increase the use of SUPs resulting in a reversal in, or a reprioritization of, policy decisions. Through the Multiple Streams Framework (MSF), I examine how creeping crises become secondary to urgent crises through agenda setting that is influenced and leveraged by policy entrepreneurs. I explore examples of such plastic policy decisions finding that they have been politically driven and influenced by entrepreneurs and industry rather than being primarily based on health concerns. Related Articles: Diaz‐Kope, Luisa, and John C. Morris. 2022. "Why Collaborate? Exploring the Role of Organizational Motivations in Cross‐sector Watershed Collaboration." Politics & Policy 50(3): 516–39. https://doi.org/10.1111/polp.12470. Gerlach, John David, Laron K. Williams, and Colleen E. Forcina. 2013. "The Science‐Natural Resource Policy Relationship: How Aspects of Diffusion Theory Explain Data Selection for Making Biodiversity Management Decisions." Politics & Policy 41(3): 326–54. https://doi.org/10.1111/polp.12017. Neill, Katharine A., and John C. Morris. 2012. "A Tangled Web of Principals and Agents: Examining the Deepwater Horizon Oil Spill through a Principal–Agent Lens." Politics & Policy 40(4): 629–56. https://doi.org/10.1111/j.1747‐1346.2012.00371.x. [ABSTRACT FROM AUTHOR]

A parallel automated track collector is integrated with a rationally designed centrifugal spinning head to collect aligned polyacrylonitrile (PAN) nanofibers. Centrifugal spinning is an extremely promising nanofiber fabrication technology due to high production rates. However, continuous oriented fiber collection and processing presents challenges. Engineering solutions to these two challenges are explored in this study. A 3D‐printed head design, optimized through a computational fluid dynamics simulation approach, is utilized to limit unwanted air currents that disturb deposited nanofibers. An automated track collecting device has pulled deposited nanofibers away from the collecting area. This results in a continuous supply of individual aligned nanofibers as opposed to the densely packed nanofiber mesh ring that is deposited on conventional static post collectors. The automated track collector allows for simple integration of the postdraw processing step that is critical to polymer fiber manufacturing for enhancing macromolecular orientation and mechanical properties. Postdrawing has enhanced the mechanical properties of centrifugal spun PAN nanofibers, which have different crystalline properties compared with conventional PAN microfiber. These technological developments address key limitations of centrifugal spinning that can facilitate high production rate commercial fabrication of highly aligned, high‐performance polymer nanofibers. [ABSTRACT FROM AUTHOR]

The postdrawing process is poorly understood for polymer nanofibers due to the difficulty of manipulating nanofiber structures. Here, an angled track system facilitates postdrawing of individual nanofibers with control of parameters including molecular weight, draw rate, draw ratio, and solvent evaporation time. In this study, the effects of molecular weight, draw rate, and relative residual solvent content on final nanofiber properties are investigated. Molecular weight is first investigated to clarify any influence polymer chain length can have on drawing in facilitating or hindering chain extensibility. Polyacrylonitrile nanofibers with 50 and 150 kDa molecular weights behave similarly with postdrawing resulting in reduced diameters and enhanced mechanics. Since solvent quantity during drawing is a time sensitive component it is meaningful to assess the impact of draw rate on the chemical and structural makeup of postdrawn fibers. Chemical bond vibrations and chain orientation are sensitive to draw rate when polycaprolactone nanofibers are dried for 3 minutes prior to postdrawing, but this dependency to draw rate is not observed when fibers are postdrawn immediately upon collection. These findings demonstrate that the amount of retained solvent at collection is relevant to this postprocessing approach, and highlights the dynamics of solvent evaporation during postdrawing. [ABSTRACT FROM AUTHOR]

Characterizing neuropsychiatric disorders is challenging due to heterogeneity in the population. We propose combining structural and functional neuroimaging and genomic data in a multimodal classification framework to leverage their complementary information. Our objectives are two‐fold (i) to improve the classification of disorders and (ii) to introspect the concepts learned to explore underlying neural and biological mechanisms linked to mental disorders. Previous multimodal studies have focused on naïve neural networks, mostly perceptron, to learn modality‐wise features and often assume equal contribution from each modality. Our focus is on the development of neural networks for feature learning and implementing an adaptive control unit for the fusion phase. Our mid fusion with attention model includes a multilayer feed‐forward network, an autoencoder, a bi‐directional long short‐term memory unit with attention as the features extractor, and a linear attention module for controlling modality‐specific influence. The proposed model acquired 92% (p <.0001) accuracy in schizophrenia prediction, outperforming several other state‐of‐the‐art models applied to unimodal or multimodal data. Post hoc feature analyses uncovered critical neural features and genes/biological pathways associated with schizophrenia. The proposed model effectively combines multimodal neuroimaging and genomics data for predicting mental disorders. Interpreting salient features identified by the model may advance our understanding of their underlying etiological mechanisms. [ABSTRACT FROM AUTHOR]

Introduction: Advances in natural language processing (NLP), speech recognition, and machine learning (ML) allow the exploration of linguistic and acoustic changes previously difficult to measure. We developed processes for deriving lexical‐semantic and acoustic measures as Alzheimer's disease (AD) digital voice biomarkers. Methods: We collected connected speech, neuropsychological, neuroimaging, and cerebrospinal fluid (CSF) AD biomarker data from 92 cognitively unimpaired (40 Aβ+) and 114 impaired (63 Aβ+) participants. Acoustic and lexical‐semantic features were derived from audio recordings using ML approaches. Results: Lexical‐semantic (area under the curve [AUC] = 0.80) and acoustic (AUC = 0.77) scores demonstrated higher diagnostic performance for detecting MCI compared to Boston Naming Test (AUC = 0.66). Only lexical‐semantic scores detected amyloid‐β status (p = 0.0003). Acoustic scores associated with hippocampal volume (p = 0.017) while lexical‐semantic scores associated with CSF amyloid‐β (p = 0.007). Both measures were significantly associated with 2‐year disease progression. Discussion: These preliminary findings suggest that derived digital biomarkers may identify cognitive impairment in preclinical and prodromal AD, and may predict disease progression. Highlights: This study derived lexical‐semantic and acoustics features as Alzheimer's disease (AD) digital biomarkers.These features were derived from audio recordings using machine learning approaches.Voice biomarkers detected cognitive impairment and amyloid‐β status in early stages of AD.Voice biomarkers may predict Alzheimer's disease progression.These markers significantly mapped to functional connectivity in AD‐susceptible brain regions. [ABSTRACT FROM AUTHOR]

Summary: Background: Tofacitinib is an oral Janus kinase (JAK) inhibitor and is registered for the treatment of ulcerative colitis (UC). The effectiveness of tofacitinib has been evaluated up to 12 months of treatment. Aim: The aim of this study was to assess the effectiveness and safety of 24 months of tofacitinib use in UC patients in the Netherlands. Methods: Patients initiating tofacitinib treatment were included in the ICC Registry, a nationwide, observational registry. Patients were prospectively evaluated for up to 24 months. The primary outcome was corticosteroid‐free clinical remission (CSFR, Simple Clinical Colitis Activity Index [SCCAI] ≤2) at week 104. Secondary outcomes included biochemical remission (C‐reactive protein (CRP) ≤5 mg/L and faecal calprotectin (FC) ≤250 μg/g), safety, and discontinuation rate. Results: We included 110 patients of whom 104 (94.5%) were anti‐TNF experienced. After 104 weeks of tofacitinib, 31.8% (34/107) were in CSFR, 23.4% (25/107) in biochemical remission and 18.7% (20/107) in combined clinical and biochemical remission. Of the patients in CSFR at week 52, 76.5% (26/34) remained so after 104 weeks of treatment. Sixty‐one patients (55.5%) discontinued tofacitinib after a median duration of 13 weeks (IQR 7–34). The main reasons for discontinuation were non‐response (59%), loss of response (14.8%), and adverse events (18%). There were 33.9 possible tofacitinib‐related adverse events per 100 patient‐years during follow‐up. Adverse events most probably related to tofacitinib were skin reactions and headaches. There were 6.4 herpes zoster infections per 100 patient‐years. Conclusion: Tofacitinib was effective in 31.8% of patients after 24 months of treatment. [ABSTRACT FROM AUTHOR]

Concomitant neuropsychiatric symptoms (NPS) are associated with accelerated Alzheimer's disease (AD) progression. Identifying multimodal brain imaging patterns associated with NPS may help understand pathophysiology correlates AD. Based on the AD continuum, a supervised learning strategy was used to guide four‐way multimodal neuroimaging fusion (Amyloid, Tau, gray matter volume, brain function) by using NPS total score as the reference. Loadings of the identified multimodal patterns were compared across the AD continuum. Then, regression analyses were performed to investigate its predictability of longitudinal cognition performance. Furthermore, the fusion analysis was repeated in the four NPS subsyndromes. Here, an NPS‐associated pathological–structural–functional covaried pattern was observed in the frontal‐subcortical limbic circuit, occipital, and sensor‐motor region. Loading of this multimodal pattern showed a progressive increase with the development of AD. The pattern significantly correlates with multiple cognitive domains and could also predict longitudinal cognitive decline. Notably, repeated fusion analysis using subsyndromes as references identified similar patterns with some unique variations associated with different syndromes. Conclusively, NPS was associated with a multimodal imaging pattern involving complex neuropathologies, which could effectively predict longitudinal cognitive decline. These results highlight the possible neural substrate of NPS in AD, which may provide guidance for clinical management. [ABSTRACT FROM AUTHOR]