Miracle-dz/UniFAR-FTUs huggingface dataset:
Eliciting End-State Comfort Planning in Children With and Without Developmental Coordination Disorder Using a Hammer Task: A Pilot Study

The end-state comfort (ESC) effect refers to the consistent tendency of healthy adults to end their movements in a comfortable end posture. In children with and without developmental coordination disorder (DCD), the results of studies focusing on ESC planning have been inconclusive, which is likely to be due to differences in task constraints. The present pilot study focused on the question whether children with and without DCD were able to change their planning strategy and were more likely to plan for ESC when demanded by complex object manipulations at the end of a task. To this end, we examined ESC planning in 18 children with and without DCD (aged 5–11years) using the previously used sword-task and the newly developed hammer-task. In the sword-task, children had to insert a sword in a wooden block, which could be relatively easily completed with an uncomfortable end-posture. In the hammer-task, children had to strike down a nail in a wooden pounding bench, which required additional force and speed demands, making it relatively difficult to complete the movement with an uncomfortable end-posture. In line with our hypothesis, the results demonstrated that children with and without DCD were more likely to plan for ESC on the hammer-task compared with the sword-task. Thus, while children with and without DCD show inconsistent ESC planning on many previously used tasks, the present pilot study shows that many of them are able to take into account the end-state of their movements if demanded by task constraints.
Comparison of Intraoperative Ultrasound B-Mode and Strain Elastography for the Differentiation of Glioblastomas From Solitary Brain Metastases. An Automated Deep Learning Approach for Image Analysis

Background The differential diagnosis of glioblastomas (GBM) from solitary brain metastases (SBM) is essential because the surgical strategy varies according to the histopathological diagnosis. Intraoperative ultrasound elastography (IOUS-E) is a relatively novel technique implemented in the surgical management of brain tumors that provides additional information about the elasticity of tissues. This study compares the discriminative capacity of intraoperative ultrasound B-mode and strain elastography to differentiate GBM from SBM. Methods We performed a retrospective analysis of patients who underwent craniotomy between March 2018 to June 2020 with glioblastoma (GBM) and solitary brain metastases (SBM) diagnoses. Cases with an intraoperative ultrasound study were included. Images were acquired before dural opening, first in B-mode, and then using the strain elastography module. After image pre-processing, an analysis based on deep learning was conducted using the open-source software Orange. We have trained an existing neural network to classify tumors into GBM and SBM via the transfer learning method using Inception V3. Then, logistic regression (LR) with LASSO (least absolute shrinkage and selection operator) regularization, support vector machine (SVM), random forest (RF), neural network (NN), and k-nearest neighbor (kNN) were used as classification algorithms. After the models’ training, ten-fold stratified cross-validation was performed. The models were evaluated using the area under the curve (AUC), classification accuracy, and precision. Results A total of 36 patients were included in the analysis, 26 GBM and 10 SBM. Models were built using a total of 812 ultrasound images, 435 of B-mode, 265 (60.92%) corresponded to GBM and 170 (39.8%) to metastases. In addition, 377 elastograms, 232 (61.54%) GBM and 145 (38.46%) metastases were analyzed. For B-mode, AUC and accuracy values of the classification algorithms ranged from 0.790 to 0.943 and from 72 to 89%, respectively. For elastography, AUC and accuracy values ranged from 0.847 to 0.985 and from 79% to 95%, respectively. Conclusion Automated processing of ultrasound images through deep learning can generate high-precision classification algorithms that differentiate glioblastomas from metastases using intraoperative ultrasound. The best performance regarding AUC was achieved by the elastography-based model supporting the additional diagnostic value that this technique provides.
Self-Reported Voluntary Blame-Taking: Kinship Before Friendship and No Effect of Incentives

Inspired by theories of prosocial behavior, we tested the effect of relationship status and incentives on intended voluntary blame-taking in two experiments (Experiment 2 was pre-registered). Participants (NE1 = 211 and NE2 = 232) imagined a close family member, a close friend, or an acquaintance and read a scenario that described this person committing a minor traffic offense. The person offered either a monetary, social, or no incentive for taking the blame. Participants indicated their willingness to take the blame and reasons for and against blame-taking. Overall, a sizable proportion of participants indicated to be willing to take the blame (E1: 57.8%; E2: 34.9%). Blame-taking rates were higher for family members than close friends or acquaintances in both experiments, as expected. Unexpectedly, there was no difference between a close friend and an acquaintance in Experiment 2. Social incentives did not have an effect on voluntary blame-taking in either experiment. Neither did we find an interaction between relationship status and incentives. The results highlight the importance of kin relationships in the context of voluntary blame-taking.
Harnessing Neuroimaging to Reduce Socioeconomic Disparities in Chronic Disease: A Conceptual Framework for Improving Health Messaging

Socioeconomic status (SES)-related health disparities persist for numerous chronic diseases, with lower-SES individuals exhibiting greater risk of morbidity and mortality compared to their higher-SES counterparts. One likely contributor is disparities in health messaging efforts, which are currently less effective for motivating health behavior change among those lower in SES. Drawing on communication neuroscience and social neuroscience research, we describe a conceptual framework to improve health messaging effectiveness in lower SES communities. The framework is based on evidence that health-message-induced activity in the ventral striatum (VS) and subdivisions of the medial pre-frontal cortex (MPFC) predicts behavior change. Additionally, we draw from social neuroscience work showing that activity in these regions during valuation and the processing of self-related vs. social information, differs as a function of SES. Bringing together these previously disparate lines of work, we argue that health messages emphasizing the benefits to close others (vs. the self) of engaging in behavior change will be more effective among lower SES individuals. We also outline a research agenda based on our framework. Ultimately, we hope that this framework utilizing a “brain-as-predictor” approach generates novel insights about the neural underpinnings of message-induced behavior change among lower SES individuals, and helps to close the gap in SES-based health disparities by harnessing the power of neuroimaging.
The Regenerating Adult Zebrafish Retina Recapitulates Developmental Fate Specification Programs

Adult zebrafish possess the remarkable capacity to regenerate neurons. In the damaged zebrafish retina, Müller glia reprogram and divide to produce neuronal progenitor cells (NPCs) that proliferate and differentiate into both lost neuronal cell types and those unaffected by the damage stimulus, which suggests that developmental specification/differentiation programs might be recapitulated during regeneration. Quantitative real-time polymerase chain reaction revealed that developmental competence factors are expressed following photoreceptor damage induced by intense light or in a genetic rod photoreceptor cell ablation model. In both light- and N-Methyl-D-aspartic acid (NMDA)-damaged adult zebrafish retinas, NPCs, but not proliferating Müller glia, expressed fluorescent reporters controlled by promoters of ganglion (atoh7), amacrine (ptf1a), bipolar (vsx1), or red cone photoreceptor cell competence factors (thrb) in a temporal expression sequence. In both damage paradigms, atoh7:GFP was expressed first, followed by ptf1a:EGFP and lastly, vsx1:GFP, whereas thrb:Tomato was observed in NPCs at the same time as ptf1a:GFP following light damage but shifted alongside vsx1:GFP in the NMDA-damaged retina. Moreover, HuC/D, indicative of ganglion and amacrine cell differentiation, colocalized with atoh7:GFP prior to ptf1a:GFP expression in the ganglion cell layer, which was followed by Zpr-1 expression (red/green cone photoreceptors) in thrb:Tomato-positive cells in the outer nuclear layer in both damage paradigms, mimicking the developmental differentiation sequence. However, comparing NMDA- to light-damaged retinas, the fraction of PCNA-positive cells expressing atoh7:GFP increased, that of thrb:Tomato and vsx1:GFP decreased, and that of ptf1a:GFP remained similar. To summarize, developmental cell specification programs were recapitulated during retinal regeneration, which adapted to account for the cell type lost.
Recent Consanguinity and Outbred Autozygosity Are Associated With Increased Risk of Late-Onset Alzheimer’s Disease

Prior work in late-onset Alzheimer’s disease (LOAD) has resulted in discrepant findings as to whether recent consanguinity and outbred autozygosity are associated with LOAD risk. In the current study, we tested the association between consanguinity and outbred autozygosity with LOAD in the largest such analysis to date, in which 20 LOAD GWAS datasets were retrieved through public databases. Our analyses were restricted to eight distinct ethnic groups: African–Caribbean, Ashkenazi–Jewish European, European–Caribbean, French–Canadian, Finnish European, North-Western European, South-Eastern European, and Yoruba African for a total of 21,492 unrelated subjects (11,196 LOAD and 10,296 controls). Recent consanguinity determination was performed using FSuite v1.0. 3, according to subjects’ ancestral background. The level of autozygosity in the outbred population was assessed by calculating inbreeding estimates based on the proportion (FROH) and the number (NROH) of runs of homozygosity (ROHs). We analyzed all eight ethnic groups using a fixed-effect meta-analysis, which showed a significant association of recent consanguinity with LOAD (N = 21,481; OR = 1.262, P = 3.6 × 10–4), independently of APOE∗4 (N = 21,468, OR = 1.237, P = 0.002), and years of education (N = 9,257; OR = 1.274, P = 0.020). Autozygosity in the outbred population was also associated with an increased risk of LOAD, both for FROH (N = 20,237; OR = 1.204, P = 0.030) and NROH metrics (N = 20,237; OR = 1.019, P = 0.006), independently of APOE∗4 [(FROH, N = 20,225; OR = 1.222, P = 0.029) (NROH, N = 20,225; OR = 1.019, P = 0.007)]. By leveraging the Alzheimer’s Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data, we determined that LOAD subjects do not show an enrichment of rare, risk-enhancing minor homozygote variants compared to the control population. A two-stage recessive GWAS using ADSP data from 201 consanguineous subjects in the discovery phase followed by validation in 10,469 subjects led to the identification of RPH3AL p.A303V (rs117190076) as a rare minor homozygote variant increasing the risk of LOAD [discovery: Genotype Relative Risk (GRR) = 46, P = 2.16 × 10–6; validation: GRR = 1.9, P = 8.0 × 10–4]. These results confirm that recent consanguinity and autozygosity in the outbred population increase risk for LOAD. Subsequent work, with increased samples sizes of consanguineous subjects, should accelerate the discovery of non-additive genetic effects in LOAD.
2D Graphene-TiO2 Composite and Its Photocatalytic Application in Water Pollutants

To solve the global water shortages and serious water pollution problems, research on semiconductor photocatalysts has generated significant research attention. The degradation of pollutants by titanium dioxide (TiO2) exceeds other semiconductor materials. However, its wide bandgap restricts the photocatalytic reaction under visible light. The large specific surface area and good thermal conductivity of graphene yielded an effective graphene-TiO2 catalyst combination effective under visible light. 2D graphene-TiO2 composites (2D-GTC) have shown promise, so a study of the preparation methods, mechanism and catalytic effect of different pollutants on this material was undertaken. In this current review, the characteristics of different graphene and TiO2 composites and their preparation methods, as well as the effects of different synthesis methods on the catalyst are introduced. The reaction mechanism of 2D-GTC catalysts, the degradation effects of different pollutants in water are all reviewed.
Effects of a Coordinative Ability Training Program on Adolescents’ Cognitive Functioning

The purpose of this randomized controlled study was to investigate the effects of a 12-week coordinative ability training program on adolescents’ cognitive functioning, using evaluation tests of visuospatial perception, attention, and working memory. We randomly assigned 60 public school students (14–15 years) to either an experimental coordinative abilities training (∼40 min twice/week) group (n = 30) or a control group (n = 30) who received general psycho-physical wellness training (∼40 min., twice a week). At baseline and after training we used two standardized motor tests and a single cognitive measure (Corsi’s Block-tapping test) to assess students’ visuospatial perception, attention, and working memory. We found a significant Time x Group interaction for the Throwing and Catching Test and Corsi’s Block-Tapping test, reflecting a meaningful experimental group improvement (p < 0.001), and there were no significant pre-post changes found in the control group. Thus, a 12-week program of coordinative abilities was able to improve not only coordination skills but aspects of cognitive functioning relevant to academic achievement.
Advances in Human Immune System Mouse Models for Studying Human Hematopoiesis and Cancer Immunotherapy

Immunotherapy has established itself as a promising tool for cancer treatment. There are many challenges that remain including lack of targets and some patients across various cancers who have not shown robust clinical response. One of the major problems that have hindered the progress in the field is the dearth of appropriate mouse models that can reliably recapitulate the complexity of human immune-microenvironment as well as the malignancy itself. Immunodeficient mice reconstituted with human immune cells offer a unique opportunity to comprehensively evaluate immunotherapeutic strategies. These immunosuppressed and genetically modified mice, with some overexpressing human growth factors, have improved human hematopoietic engraftment as well as created more functional immune cell development in primary and secondary lymphoid tissues in these mice. In addition, several new approaches to modify or to add human niche elements to further humanize these immunodeficient mice have allowed a more precise characterization of human hematopoiesis. These important refinements have opened the possibility to evaluate not only human immune responses to different tumor cells but also to investigate how malignant cells interact with their niche and most importantly to test immunotherapies in a more preclinically relevant setting, which can ultimately lead to better success of these drugs in clinical trials.
Multisite Autism Spectrum Disorder Classification Using Convolutional Neural Network Classifier and Individual Morphological Brain Networks

Autism spectrum disorder (ASD) is a range of neurodevelopmental disorders with behavioral and cognitive impairment and brings huge burdens to the patients’ families and the society. To accurately identify patients with ASD from typical controls is important for early detection and early intervention. However, almost all the current existing classification methods for ASD based on structural MRI (sMRI) mainly utilize the independent local morphological features and do not consider the covariance patterns of these features between regions. In this study, by combining the convolutional neural network (CNN) and individual structural covariance network, we proposed a new framework to classify ASD patients with sMRI data from the ABIDE consortium. Moreover, gradient-weighted class activation mapping (Grad-CAM) was applied to characterize the weight of features contributing to the classification. The experimental results showed that our proposed method outperforms the currently used methods for classifying ASD patients with the ABIDE data and achieves a high classification accuracy of 71.8% across different sites. Furthermore, the discriminative features were found to be mainly located in the prefrontal cortex and cerebellum, which may be the early biomarkers for the diagnosis of ASD. Our study demonstrated that CNN is an effective tool to build the framework for the diagnosis of ASD with individual structural covariance brain network.
Sustainable Development Goal 11 and a New Urban Agenda for Caribbean Small Island Developing States: Policy, Practice, and Action

Many Caribbean Small Island Developing States face the daunting task of fulfilling the United Nations Sustainable Development Goals by 2030. As signatories to the United Nations Sustainable Development Goals, their governments committed to embark on a roadmap to achieve sustainable development within this time frame. In this context, Caribbean Small Island Developing States have embraced Sustainable Development Goal 11 in pursuit of creating inclusive, safe, resilient, and sustainable cities as articulated in various governance, spatial, socio-economic, and environmental policies. Notwithstanding this commitment, a tension exists between policy and practice. Several barriers to policy implementation have stymied efforts to make progress in fulfilling Goal 11. Enabling the impact of sound policy through well-informed practice is pivotal, if these states are to make advancements in ensuring that their population has access to basic services and live in safe, resilient, and sustainable cities without leaving any citizen behind. This paper firstly seeks to critically review existing policies and practice that impact on the attainment of Sustainable Development Goal 11. It highlights the drivers of unsustainable urbanization that are undermining progress in achieving this key sustainable development goal. In keeping with the United Nations declaration of a Decade for Action, this paper secondly makes recommendations for action that are fundamental to putting Caribbean Small Island Developing States on a trajectory leading to the fulfillment of Goal 11. It specifically recommends strategic actions within the context of a New Urban Agenda that are relevant to Caribbean Small Island Developing States that are encountering similar challenges. The experience of Trinidad is drawn upon to provide a narrative of gaps between policy and practice, and to distill key actions for attaining SDG 11 by 2030 and beyond.
Test-Retest Reliability of Neural Correlates of Response Inhibition and Error Monitoring: An fMRI Study of a Stop-Signal Task

Response inhibition (RI) and error monitoring (EM) are important processes of adaptive goal-directed behavior, and neural correlates of these processes are being increasingly used as transdiagnostic biomarkers of risk for a range of neuropsychiatric disorders. Potential utility of these purported biomarkers relies on the assumption that individual differences in brain activation are reproducible over time; however, available data on test-retest reliability (TRR) of task-fMRI are very mixed. This study examined TRR of RI and EM-related activations using a stop signal task in young adults (n = 56, including 27 pairs of monozygotic (MZ) twins) in order to identify brain regions with high TRR and familial influences (as indicated by MZ twin correlations) and to examine factors potentially affecting reliability. We identified brain regions with good TRR of activations related to RI (inferior/middle frontal, superior parietal, and precentral gyri) and EM (insula, medial superior frontal and dorsolateral prefrontal cortex). No subcortical regions showed significant TRR. Regions with higher group-level activation showed higher TRR; increasing task duration improved TRR; within-session reliability was weakly related to the long-term TRR; motion negatively affected TRR, but this effect was abolished after the application of ICA-FIX, a data-driven noise removal method.
Reduction in Nesfatin-1 Levels in the Cerebrospinal Fluid and Increased Nigrostriatal Degeneration Following Ventricular Administration of Anti-nesfatin-1 Antibody in Mice

Nesfatin-1 is one of several brain-gut peptides that have a close relationship with the central dopaminergic system. Our previous studies have shown that nesfatin-1 is capable of protecting nigral dopaminergic neurons against 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced neurotoxicity. A recent study also revealed a reduced blood level of nesfatin-1 in patients with Parkinson’s disease (PD). The current study was designed to investigate whether reduced nesfatin-1 in cerebrospinal fluid (CSF) induces nigrostriatal system degeneration. An intra-cerebroventricular (ICV) injection technique was used to administer anti-nesfatin-1 antibody directly into the lateral ventricle of the brain. Enzyme-linked immunosorbent assay (ELISA) results showed that ICV injection of anti-nesfatin-1 antibody into the lateral ventricle of the brain once daily for 2 weeks caused a significant reduction in nesfatin-1 levels in the CSF (93.1%). Treatment with anti-nesfatin-1 antibody resulted in a substantial loss (23%) of TH-positive (TH+) dopaminergic neurons in the substantia nigra pars compacta (SNpc), as shown by immunofluorescence staining, a depletion in dopamine and its metabolites in the striatum detected by high-performance liquid chromatography (HPLC), and obvious nuclear shrinkage and mitochondrial lesions in dopaminergic neurons in the SNpc detected by transmission electron microscopy (TEM). Furthermore, the results from our Western blot and ELISA experiments demonstrated that anti-nesfatin-1 antibody injection induced an upregulation of caspase-3 activation, increased the expression of p-ERK, and elevated brain-derived neurotrophic factor (BDNF) levels in the SNpc. Taken together, these observations suggest that reduced nesfatin-1 in the brain may induce nigrostriatal dopaminergic system degeneration; this effect may be mediated via mitochondrial dysfunction-related apoptosis. Our data support a role of nesfatin-1 in maintaining the normal physiological function of the nigrostriatal dopaminergic system.