Miracle-dz/UniFAR-FTUs huggingface dataset:
Skin Temperatures of Back or Neck Are Better Than Abdomen for Indication of Average Proximal Skin Temperature During Sleep of School-Aged Children

Purpose The tight association between sleep, body temperature regulation, and patterns of skin temperature change highlights the necessity for accurate and valid assessment of skin temperatures during sleep. With increased interest in this functional relationship in infants and children, it is important to identify where to best measure proximal skin temperature and whether it is possible to reduce the number of sites of measures, in order to limit the experimental effects in natural settings. Thus, the aim of this study was to determine the most suitable single skin temperature sites for representation of average proximal skin temperature during sleep of school aged children. Methods Statistical analyses were applied to skin temperature data of 22 children, aged 6 to 12 years, measured over four consecutive school nights in their home settings, to compare single site measures of abdomen, back, neck, forehead and subclavicular skin temperatures (local temperatures) with average proximal skin temperatures. Results Abdomen and forehead skin temperatures were significantly different (respectively higher and lower) to the other local proximal temperatures and to average proximal skin temperatures. Moreover, the time pattern of forehead temperature was very different from that of the other local temperatures. Conclusions Local forehead and abdomen skin temperatures are least suitable as single site representations of average proximal skin temperatures in school aged children when considering both the level and the time course pattern of the temperature across the night. Conversely, back and neck temperatures provide most fitting representation of average proximal skin temperatures.
Snowball ICA: A Model Order Free Independent Component Analysis Strategy for Functional Magnetic Resonance Imaging Data

In independent component analysis (ICA), the selection of model order (i.e., number of components to be extracted) has crucial effects on functional magnetic resonance imaging (fMRI) brain network analysis. Model order selection (MOS) algorithms have been used to determine the number of estimated components. However, simulations show that even when the model order equals the number of simulated signal sources, traditional ICA algorithms may misestimate the spatial maps of the signal sources. In principle, increasing model order will consider more potential information in the estimation, and should therefore produce more accurate results. However, this strategy may not work for fMRI because large-scale networks are widely spatially distributed and thus have increased mutual information with noise. As such, conventional ICA algorithms with high model orders may not extract these components at all. This conflict makes the selection of model order a problem. We present a new strategy for model order free ICA, called Snowball ICA, that obviates these issues. The algorithm collects all information for each network from fMRI data without the limitations of network scale. Using simulations and in vivo resting-state fMRI data, our results show that component estimation using Snowball ICA is more accurate than traditional ICA. The Snowball ICA software is available at https://github.com/GHu-DUT/Snowball-ICA.
Conspiracy Beliefs, Rejection of Vaccination, and Support for hydroxychloroquine: A Conceptual Replication-Extension in the COVID-19 Pandemic Context

Many conspiracy theories appeared along with the COVID-19 pandemic. Since it is documented that conspiracy theories negatively affect vaccination intentions, these beliefs might become a crucial matter in the near future. We conducted two cross-sectional studies examining the relationship between COVID-19 conspiracy beliefs, vaccine attitudes, and the intention to be vaccinated against COVID-19 when a vaccine becomes available. We also examined how these beliefs predicted support for a controversial medical treatment, namely, chloroquine. In an exploratory study 1 (N = 409), two subdimensions of COVID-19 conspiracy beliefs were associated with negative attitudes toward vaccine science. These results were partly replicated and extended in a pre-registered study 2 (N = 396). Moreover, we found that COVID-19 conspiracy beliefs (among which, conspiracy beliefs about chloroquine), as well as a conspiracy mentality (i.e., predisposition to believe in conspiracy theories) negatively predicted participants’ intentions to be vaccinated against COVID-19 in the future. Lastly, conspiracy beliefs predicted support for chloroquine as a treatment for COVID-19. Interestingly, none of the conspiracy beliefs referred to the dangers of the vaccines. Implications for the pandemic and potential responses are discussed.
Epidemiological and Genomic Analysis of SARS-CoV-2 in 10 Patients From a Mid-Sized City Outside of Hubei, China in the Early Phase of the COVID-19 Outbreak

A novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing Coronavirus Disease 2019 (COVID-19) pandemic. In this study, we performed a comprehensive epidemiological and genomic analysis of SARS-CoV-2 genomes from 10 patients in Shaoxing (Zhejiang Province), a mid-sized city outside of the epicenter Hubei province, China, during the early stage of the outbreak (late January to early February, 2020). We obtained viral genomes with >99% coverage and a mean depth of 296X demonstrating that viral genomic analysis is feasible via metagenomics sequencing directly on nasopharyngeal samples with SARS-CoV-2 Real-time PCR Ct values <28. We found that a cluster of four patients with travel history to Hubei shared the exact same virus with patients from Wuhan, Taiwan, Belgium, and Australia, highlighting how quickly this virus spread to the globe. The virus from another cluster of two family members living together without travel history but with a sick contact of a confirmed case from another city outside of Hubei accumulated significantly more mutations (9 SNPs vs. average 4 SNPs), suggesting a complex and dynamic nature of this outbreak. Our findings add to the growing knowledge of the epidemiological and genomic characteristics of SARS-CoV-2 and offers a glimpse into the early phase of this viral infection outside of Hubei, China.
Effect of Population Lockdown on Pediatric Emergency Room Demands in the Era of COVID-19

Objectives: The aim of this study was to assess the impact of the COVID-19 pandemic and population lockdown on pediatric ED consultations. Methods: A cross-sectional study on pediatric emergency department consultations before and during the current COVID-19 pandemic (March–May 2019 vs. March–May 2020) was performed in two hospitals in the Campania region (Southern Italy) [i.e., Salerno University Hospital (Salerno) and Pediatric Regional Referral Emergency Hub “AORN Santobono-Pausillipon” (Naples)]. Results: 29,368 consecutive ED pediatric patients (13,430 females; mean age ± SD = 5.4 ± 4.7 years) were seen in March–May 2019 and 9,133 (4,494 females; mean age ± SD = 5.9 ± 4.2 years) in March–May 2020. Resuscitation/emergency and urgent care pediatric ED consultations were 1,388 (4.7%, 95% CI 4.5–4.9) in the 2019 trimester, while they were 648 (7.1%, 95% CI 6.6–7.6) in the 2020 trimester (p < 0.01). Mean pediatric ED daily consultations were 326.3 (95% CI 299.9–352.7) in the considered period of 2019 and 101.4 (95%CI 77.9–124.9) in the same period of 2020 (p < 0.001). COVID-19 nasal swabs were performed for 385 children; of those, six resulted positive and four of them were hospitalized. Conclusions: This work provides a unique snapshot of the pediatric EDs demands in the era of COVID-19. We witnessed a significant reduction of non-urgent health care demands during the pandemic but an increase of more severe urgent cases. The COVID-19 pandemic and the following lockdown unveiled the inappropriateness of the majority of pediatric ED consultations. Nevertheless, the current scenario highlighted the need for appropriate and timely clinical evaluations in the pediatric primary care to tackle late and more severe diagnoses in EDs.
GLT25D2 Is Critical for Inflammatory Immune Response to Promote Acetaminophen-Induced Hepatotoxicity by Autophagy Pathway

Acetaminophen (APAP) overdose induces hepatocyte necrosis and causes liver hepatotoxicity. Currently, the role of galactosyltransferase in APAP-induced liver injury is still unclear. This study assessed the contribution of the GLT25D2 gene, a kind of collagen galactosyltransferase, to the development of APAP-induced liver injury. This study found that the expression of GLT25D2 markedly increased first and then decreased in the liver of mice treated with APAP, however, it downregulated in the liver of APAP overdose-patients compared with normal controls. Knockout of GLT25D2 significantly ameliorated the liver injury, meanwhile, it downregulated the proinflammatory cytokines (IL-6, TNF-α) and chemokines (CXCL-10, MIG and CXCL-1) levels, however, and upregulated the anti-inflammatory cytokines (IL-22, IL-10) levels. Mechanistic explorations showed that (1) GLT25D2 knockout promoted autophagy pathway; and (2) the GLT25D2 knockout-induced autophagy selected to clear damaged mitochondria in APAP-induced liver injury by mitophagy; and (3) the autophagy intervention by Atg 7 siRNA cancelled liver protection by knockout of GLT25D2 through regulating liver inflammation. In conclusion, our study proves that the upregulated expression of GLT25D2 decreased autophagy contributing to APAP-induced hepatotoxicity by mediating the inflammatory immune regulatory mechanism.
Neuromorphic Computing Using NAND Flash Memory Architecture With Pulse Width Modulation Scheme

A novel operation scheme is proposed for high-density and highly robust neuromorphic computing based on NAND flash memory architecture. Analog input is represented with time-encoded input pulse by pulse width modulation (PWM) circuit, and 4-bit synaptic weight is represented with adjustable conductance of NAND cells. Pulse width modulation scheme for analog input value and proposed operation scheme is suitably applicable to the conventional NAND flash architecture to implement a neuromorphic system without additional change of memory architecture. Saturated current-voltage characteristic of NAND cells eliminates the effect of serial resistance of adjacent cells where a pass bias is applied in a synaptic string and IR drop of metal wire resistance. Multiply–accumulate (MAC) operation of 4-bit weight and width-modulated input can be performed in a single input step without additional logic operation. Furthermore, the effect of quantization training (QT) on the classification accuracy is investigated compared with post-training quantization (PTQ) with 4-bit weight. Lastly, a sufficiently low current variance of NAND cells obtained by the read–verify–write (RVW) scheme achieves satisfying accuracies of 98.14 and 89.6% for the MNIST and CIFAR10 images, respectively.
Identifying Clinically and Functionally Distinct Groups Among Healthy Controls and First Episode Psychosis Patients by Clustering on EEG Patterns

Objective The mismatch negativity (MMN) is considered as a promising biomarker that can inform future therapeutic studies. However, there is a large variability among patients with first episode psychosis (FEP). Also, most studies report a single electrode site and on comparing case–control group differences. Few have taken advantage of the full wealth of multi-channel EEG signals to examine observable patterns. None, to our knowledge, have used machine learning (ML) approaches to investigate neurophysiological derived subgroups with distinct cognitive and functional outcome characteristics. In this study, we applied ML to empirically stratify individuals into homogeneous subgroups based on multi-channel MMN data. We then characterized the functional, cognitive, and clinical profiles of these neurobiologically derived subgroups. We also explored the underlying low frequency range responses (delta, theta, alpha) during MMN. Methods Clinical, neurocognitive, functioning data of 33 healthy controls and 20 FEP patients were collected. 90% of the patients had 6-month follow-up data. Neurocognition, social cognition, and functioning measures were assessed using the NCCB Cognitive Battery, the Awareness of Social Inference Test, UCSD Performance-Based Skills Assessment, and Multnomah Community Ability Scale. Symptom severity was collected using the PANSS. MMN amplitude and single-trial derived low frequency activity across 24 frontocentral channels were used as main variables in the ML k-means clustering analyses. Results We found a consistent pattern of two distinctive subgroups. We labeled them as “better functioning” and “poorer functioning” clusters, respectively. Each subgroup can be mapped onto either better or poorer clinical, cognitive, and functioning profiles. Also, we identified two subgroups of patients: one showed improved MMN and one showed worsening of MMN over time. Patients with improved MMN had better follow-up clinical, cognitive, and functioning profile than those with worsening MMN. Among the low frequency bands, delta frequency appeared to be the most relevant to the observed MMN responses in all individuals. However, higher delta responses were not necessarily associated with a better functioning profile, suggesting that delta frequency alone may not be useful in clinical characterization. Conclusions The ML approach could be a robust tool to explore heterogeneity and facilitate the identification of neurobiological homogeneous subgroups in FEP.
Macrophage TLR4 and PAR2 Signaling: Role in Regulating Vascular Inflammatory Injury and Repair

Macrophages play a central role in dictating the tissue response to infection and orchestrating subsequent repair of the damage. In this context, macrophages residing in the lungs continuously sense and discriminate among a wide range of insults to initiate the immune responses important to host-defense. Inflammatory tissue injury also leads to activation of proteases, and thereby the coagulation pathway, to optimize injury and repair post-infection. However, long-lasting inflammatory triggers from macrophages can impair the lung's ability to recover from severe injury, leading to increased lung vascular permeability and neutrophilic injury, hallmarks of Acute Lung Injury (ALI). In this review, we discuss the roles of toll-like receptor 4 (TLR4) and protease activating receptor 2 (PAR2) expressed on the macrophage cell-surface in regulating lung vascular inflammatory signaling.
Personality Traits Modulate the Impact of Emotional Stimuli During a Working Memory Task: A Near-Infrared Spectroscopy Study

The purpose of the present study was to examine the influence of personality traits on the impact of emotional stimuli focusing on n-back task performance and brain activity changes. Previous neuroimaging studies have reported that individual differences in emotional processing can be attributed to personality traits, which is linked to the hemisphere-specific activity of the dorsolateral prefrontal cortex (DLPFC) in response to emotional stimuli. Thirty right-handed healthy young male participants were recruited in this study and classified into two groups, the behavioral inhibition system (BIS) group and behavioral activation system (BAS) group, based on their scores on the BIS/BAS scale. Participants saw six emotional images (two each with negative, neutral, and positive valence), which were selected from the International Affective Picture System and validated in a preliminary experiment. Then, a dual 2-back task that simultaneously employed auditory-verbal and visuospatial stimuli was conducted. Additionally, the concentration of oxygenated hemoglobin (Oxy-Hb) changes in the DLPFC was measured during the image presentation and dual 2-back task by near-infrared spectroscopy (NIRS). The task performance showed a significantly increased reaction time (RT) in the negative valence independent of personality traits. The results of Oxy-Hb changes showed a significant interaction between personality traits and emotional valence. Further, the hemisphere-subgroup analysis revealed that the right DLPFC activity was significantly higher in the negative valence than in the neutral valence in the BIS group; the right DLPFC activity was also significantly higher in the BIS group than in the BAS group in the positive valence. There was no main effect or interaction in the left DLPFC activity. These findings suggest the importance of considering personality traits when examining the impact of emotional stimuli. Further studies with large sample sizes warranted to examine the influence emotional stimuli exert on working memory performance, considering the personality traits to better understand individual differences in emotional processing.
A Dual Nanosensor Approach to Determine the Cytosolic Concentration of ATP in Astrocytes

Adenosine triphosphate (ATP) is the central energy carrier of all cells and knowledge on the dynamics of the concentration of ATP ([ATP]) provides important insights into the energetic state of a cell. Several genetically encoded fluorescent nanosensors for ATP were developed, which allow following the cytosolic [ATP] at high spatial and temporal resolution using fluorescence microscopy. However, to calibrate the fluorescent signal to [ATP] has remained challenging. To estimate basal cytosolic [ATP] ([ATP]0) in astrocytes, we here took advantage of two ATP nanosensors of the ATeam-family (ATeam1.03; ATeam1.03YEMK) with different affinities for ATP. Altering [ATP] by external stimuli resulted in characteristic pairs of signal changes of both nanosensors, which depend on [ATP]0. Using this dual nanosensor strategy and epifluorescence microscopy, [ATP]0 was estimated to be around 1.5 mM in primary cultures of cortical astrocytes from mice. Furthermore, in astrocytes in acutely isolated cortical slices from mice expressing both nanosensors after stereotactic injection of AAV-vectors, 2-photon microscopy revealed [ATP]0 of 0.7 mM to 1.3 mM. Finally, the change in [ATP] induced in the cytosol of cultured cortical astrocytes by application of azide, glutamate, and an increased extracellular concentration of K+ were calculated as −0.50 mM, −0.16 mM, and 0.07 mM, respectively. In summary, the dual nanosensor approach adds another option for determining the concentration of [ATP] to the increasing toolbox of fluorescent nanosensors for metabolites. This approach can also be applied to other metabolites when two sensors with different binding properties are available.
Prediction of Self-Perception of Patient in Rheumatoid Arthritis With the Key RNAs Expression Profiles

Self-perception in patients is their self-response to sensory stimuli. It is an important aspect of the existence and quality of life among patients. However, the inherent relationship between self-perception and the cellular activity at the molecular level is elusive. In this study, we aimed to explore the association of self-perception with RNA expression profile in patients with rheumatoid arthritis (RA) through computational analysis. We recruited 30 patients clinically diagnosed with RA and to age- and sex-matched controls without previous clinical history. In total, 5 self-perception measures and 30 RNA expression measures were derived from RA patients and control groups. A correlation analysis based on Spearman correlation and Logistic-regression methods was adopted to assess the correlation between self-perception and RNA expression. Quantitative analysis revealed that RA patients with poor self-perception were closely associated with RNAs expression, In addition, 3 key molecules including AC019117.2, LINC00638, and hsa_circ_0003972 could be used to predict self-perception changes in RA patients. Herein, our results will provide new insights in RA diagnosis however, the underlying mechanisms need to be further explored.
The Impact of the Digital Home Environment on Kindergartners’ Language and Early Literacy

We examined whether a digital home literacy environment could be distinguished from a (traditional) analog home literacy environment, and whether both were related to kindergartners’ language and literacy levels, taking parental expectations into account. Caregivers of 71 kindergarteners filled out a questionnaire on the home environment (expectations, activities, and materials), and the children were assessed on language (vocabulary and grammar) and literacy (begin phoneme awareness, segmentation skill, and grapheme knowledge) skills. Results showed that a digital environment could be distinguished from an analog environment. However, only the analog environment was related to children’s language abilities. Parental expectations were related directly to both language and literacy abilities. The fact that there was no relation between the digital home environment and language and literacy outcomes might indicate large variation in the quality of the digital home environment. More attention is needed to this part of daily life when growing up in a digital society.
Insomnia Is Associated With Frequency of Suicidal Ideation Independent of Depression: A Replication and Extension of Findings From the National Health and Nutrition Examination Survey

Objective Insomnia is associated with suicidality, although the mechanisms of this association are unclear. This study sought to replicate previous findings showing that insomnia symptoms but not sleep duration are associated with frequency of suicidal ideation in adults. We further investigated whether depression or sleep duration moderates the association between insomnia symptoms and frequency of suicidal ideation. Materials and Methods We used the 2005–2006 cycle of the National Health and Nutrition Examination Survey to replicate previously reported findings from the 2007–2008 cycle. We used ordered logistic regression to determine whether insomnia symptoms were associated with frequency of suicidal ideation independently of depression and other potential confounds. To extend these findings, we tested whether depression or sleep duration moderated the association between insomnia symptoms and frequency of suicidal ideation. We further replicated these findings in parallel analyses using the combined data from the 2005–2006 and 2007–2008 cycles. Results This study replicated previous results showing that insomnia symptoms are associated with frequency of suicidal ideation in the NHANES 2005–2006 cycle (OR = 1.09, p < 0.05), even after adjusting for potentially confounding variables, including depression. Neither depression nor sleep duration moderated this association. Difficulty with sleep maintenance insomnia symptoms were most robustly associated with frequency of suicidal ideation (OR ≥ 1.97, p < 0.05). Sleep duration was not robustly associated with suicidal ideation. Conclusions In this study, we found that insomnia symptoms were uniquely associated with frequency of suicidal ideation. This association cannot be explained by the shared association with depression or sleep duration.