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Author Correction: A simple model for Behavioral Time Scale Synaptic Plasticity (BTSP) provides content addressable memory with binary synapses and one-shot learning
Characterization of language abilities and semantic networks in very preterm children at school-age
It has been widely assessed that very preterm children (<32 weeks gestational age) present language and memory impairments compared with full-term children. However, differences in their underlying semantic memory structure have not been studied yet. Nevertheless, the way concepts are learned and organized across development relates to children’s capacities in retrieving and using information later. Therefore, the semantic memory organization could underlie several cognitive deficits existing in very preterm children. Computational mathematical models offer the possibility to characterize semantic networks through three coefficients calculated on spoken language: average shortest path length (i.e., distance between concepts), clustering (i.e., local interconnectivity), and modularity (i.e., compartmentalization into small sub-networks). Here we assessed these coefficients in 38 very preterm schoolchildren (aged 8–10 years) compared with 38 full-term schoolchildren (aged 7–10 years) based on a verbal fluency task. Using semantic network analysis, very preterm children showed a longer distance between concepts and a lower interconnectivity at a local level than full-term children. In addition, we found a trend for a higher modularity at a global in very preterm children compared with full-term children. These findings provide preliminary evidence that very preterm children demonstrate subtle impairments in the organization of their semantic network, encouraging the adaptation of the support and education they receive.
Transforming CCTV cameras into NO2 sensors at city scale for adaptive policymaking
Abstract Air pollution in cities, especially NO2, is linked to numerous health problems, ranging from mortality to mental health challenges and attention deficits in children. While cities globally have initiated policies to curtail emissions, real-time monitoring remains challenging due to limited environmental sensors and their inconsistent distribution. This gap hinders the creation of adaptive urban policies that respond to the sequence of events and daily activities affecting pollution in cities. Here, we demonstrate how city CCTV cameras can act as a pseudo-NO2 sensors. Using a predictive graph deep model, we utilised traffic flow from London’s cameras in addition to environmental and spatial factors, generating NO2 predictions from over 133 million frames. Our analysis of London’s mobility patterns unveiled critical spatiotemporal connections, showing how specific traffic patterns affect NO2 levels, sometimes with temporal lags of up to 6 h. For instance, if trucks only drive at night, their effects on NO2 levels are most likely to be seen in the morning when people commute. These findings cast doubt on the efficacy of some of the urban policies currently being implemented to reduce pollution. By leveraging existing camera infrastructure and our introduced methods, city planners and policymakers could cost-effectively monitor and mitigate the impact of NO2 and other pollutants.
Scientists flock to DeepSeek: how they’re using the blockbuster AI model
Single cell profiling of circulating autoreactive CD4 T cells from patients with autoimmune liver diseases suggests tissue imprinting
Abstract Autoimmune liver diseases (AILD) involve dysregulated CD4 T cell responses against liver self-antigens, but how these autoreactive T cells relate to liver tissue pathology remains unclear. Here we perform single-cell transcriptomic and T cell receptor analyses of circulating, self-antigen-specific CD4 T cells from patients with AILD and identify a subset of liver-autoreactive CD4 T cells with a distinct B-helper transcriptional profile characterized by PD-1, TIGIT and HLA-DR expression. These cells share clonal relationships with expanded intrahepatic T cells and exhibit transcriptional signatures overlapping with tissue-resident T cells in chronically inflamed environments. Using a mouse model, we demonstrate that, following antigen recognition in the liver, CD4 T cells acquire an exhausted phenotype, play a crucial role in liver damage, and are controlled by immune checkpoint pathways. Our findings thus suggest that circulating autoreactive CD4 T cells in AILD are imprinted by chronic antigen exposure to promote liver inflammation, thereby serving as a potential target for developing biomarkers and therapies for AILD.
Rural-urban disparity in uptaking skilled antenatal care visits by pregnant women in Bangladesh: Zero and One Inflated Poisson regression model
Background Utilization of maternal health care services, specifically, antenatal care services from skilled health providers have been given utmost priority in low- and middle-income countries over years with a view of mitigating complications during pregnancy as well as safeguarding the health and survival of both mother and newborn. However, there is a general tendency of pregnant mothers in Bangladesh of receiving skilled antenatal care (SANC) service once, or even never which refrains us to ensure World Health Organization (WHO) recommended eight plus SANC visits, additionally, to meet Sustainable Development Goal (SDG) number three. Objectives The study aims at assessing how the average number of SANC visits taken by the reproductive women in Bangladesh changes over the time in rural and urban areas together with finding out the potential demographic and socio-economic factors associated with SANC visits by addressing possible accumulation of zero and one counts in SANC visits. Methods In this study, data have been retrieved from last four waves of Bangladesh Demographic and Health Surveys ranging from 2011 to 2022 and later combined together to form a pooled dataset. Non-parametric Kruskal-Wallis test has been performed for exploring unadjusted association of covariates with the response and Mann-Whitney U test has been conducted for multiple comparison in case of significant association for a covariate having more than two categories. For checking the existence of concurrent inflation at zero and one in the pooled dataset, partial score test has been performed. Based on the results of score test, Zero and One Inflated Poisson regression model has been fitted to the pooled dataset, where an interaction term between area of residence and survey year has been considered for trend analysis. Results The study highlights that the rate of mean SANC visits is rapidly rising with time among pregnant women not only from the urban areas but also from the rural areas of Bangladesh. However, the rate of change in uptaking the SANC visits is higher in rural area compared to urban area. It was observed that for a given survey year, the rate of mean SANC visits was higher among women from urban areas compared to that among women from rural areas of Bangladesh. This study provides the evidence of 17.2% extra zero counts and 1.1% extra one counts in the pooled dataset. Conclusion The study results depict that inequity in SANC services based on area of residence prevails in Bangladesh. However, the gap in the rate of mean SANC visits in rural areas compared to urban areas has gradually reduced over time. Based on the results, the study comes up with some recommendations to facilitate the policy makers in improvising strategies and ensuring sustainable rise in SANC counts as well as WHO recommended positive pregnancy experience in the country to meet SDGs.
Halofuginone prevents inflammation and proliferation of high-altitude pulmonary hypertension by inhibiting the TGF-β1/Smad signaling pathway
Diffusion-driven transient hydrogenation in metal superhydrides at extreme conditions
Evaluation of anti-inflammatory and wound healing properties of Tinospora cordifolia extract
Tinospora cordifolia extract exhibits diverse benefits—anti-arthritis, anti-malarial, anti-allergic, anti-diabetic, antihepatotoxic, and antipyretic effects. Its specific anti-inflammatory and healing capacities remain unexplored, prompting a study utilizing a mouse skin wound model and direct T. cordifolia extraction. UV-Vis spectroscopy depicted an absorption range of 200–400 nm, while FTIR analysis identified alcohols, phenols, amines, amides, aldehydes, ketones, alkanes, and alkenes. GC-MS analysis revealed the presence of components: 5methyl-5-Hexen-2-Ol, n-hexadecenoic acid, cholesta-4,6-dien-3beta-ol, stigmasterol, β-sitosterol, stearate which are present in the extract. Histopathological examination confirmed accelerated wound healing, showcasing reduced inflammation, restored blood vessels, collagen fibers, and swift epidermal closure. T. cordifolia extract exhibits promise in enhancing wound healing through its antibacterial, anti-inflammatory properties.
The study of mechanical properties and fracture evolution of coal-rock masses under hard roof-soft floor conditions
Genetically-encoded targeted protein degradation technology to remove endogenous condensation-prone proteins and improve crop performance
Personal, environmental and behavioral predictors associated with online fraud victimization among adults
Background Online malicious attempts such as scamming continue to proliferate across the globe, aided by the ubiquitous nature of technology that makes it increasingly easy to dupe individuals. This study aimed to identify the predictors for online fraud victimization focusing on Personal, Environment and Behavior (PEB). Methods Social Cognitive Theory (SCT) was used as a guide in developing the PEB framework. Specifically, three factors were identified—Self-awareness (Personal), Attitude (Personal and Environment) and Safe Practice (Behavior) as the potential predictors for online fraud victimization. A self-reporting questionnaire was developed based on the PEB framework and used to collect data targeting Malaysian adults. The study reports result from two separate datasets collected across two separate timelines. Study I involved data collection in January 2023 (n = 820) whereas Study II was conducted with a modified questionnaire from November 2023 –January 2024 (n = 629). Study I identified the online fraud victimization predictors through an Exploratory Factor Analysis (EFA) and a hierarchical binary logistic regression. The dataset from Study II was used to validate the online fraud victimization model derived from Study I by executing another round of hierarchical binary logistic regression. Results Results from both the samples show that most of the respondents are aware of digital privacy. EFA from Study I yielded a five-factor solution with a total variance of 60.6%, namely, Self-awareness, Safe Practice, Bank Trust, Overconfidence and Social Influence. Hierarchical binary logistic regression results from both the studies were found to be consistent. Specifically, Overconfidence (β = 0.374; OR = 1.453; 95% CI [1.119, 1.887]; p = 0.005) and Social Influence (β = 0.332; OR = 1.225; 95% CI [1.077, 1.512]; p = 0.006) were found to significantly predict online fraud victimization as well as gender (β = 0.364; OR = 1.440; 95% CI [1.008, 2.016]; p = 0.045) with females exhibiting higher risks to victimization. Implications The emergence of Overconfidence and Social Influence as significant predictors can guide the development of targeted online fraud awareness campaigns and/or tools emphasizing critical thinking and skepticism. Policymakers can leverage this knowledge to implement regulations that reduce deceptive practices online, promote digital literacy programs, and mandate clearer consumer protections to mitigate the impact of social manipulation and overconfidence on fraud victimization. Conclusion This study identifies online fraud victimization predictors, hence improving our understanding of the factors behind this phenomenon—allowing for the development of effective preventive measures and policies to safeguard individuals and improve digital security. For instance, gender- specific educational campaigns can be developed to enhance awareness and equip women with strategies to detect and avoid scams. Additionally, addressing systemic factors like social norms and digital literacy gaps is crucial for creating equitable and effective solutions to reduce online fraud victimization.
Mechanical properties and piecewise constitutive model of fine sandstone in mining area of western China
Author Correction: MADS-box encoding gene Tunicate1 positively controls maize yield by increasing leaf number above the ear
Modes of embodiment for an immersed experience in museums: The Royal Tank Museum
This study examines how exhibits at the Royal Tank Museum (RTM) engage visitors through bodily experiences. The goal is to understand RTM’s visitor interaction and engagement. This research fills a gap in the literature on Jordanian museums by documenting some experiential characteristics of museum exhibits and establishing a framework for evaluating embodied museum encounters. A detailed RTM episode analysis, online survey, visitor behavior observations, structured interviews, and a comprehensive questionnaire are used. Al-Karameh Hall offers embodied experiences using sensory and physical tools, while Jerusalem Hall and the Battle of Al-Latrun fall short due to fractured narratives and inadequate sensory engagement. According to the study, boosting the clarity of narratives, adding personal belongings, and strengthening the spatial connection between exhibitions and their surrounds can greatly enhance visitors’ embodied experiences.
Exploring the Association Between Overactive Bladder (OAB) and Cognitive decline: mediation by depression in elderly adults, a NHANES weighted analysis
Oligoclonality of TRBC1 and TRBC2 in T cell lymphomas as mechanism of primary resistance to TRBC-directed CAR T cell therapies
Neonatal outcomes and resuscitation practices following the addition of heart rate-guidance to basic resuscitation
Aim To evaluate the impact of heart rate-guided basic resuscitation compared to Helping Babies Breathe on neonatal outcomes and resuscitation practices in the Democratic Republic of the Congo. Methods We conducted a pre-post clinical trial comparing heart rate-guided basic resuscitation to Helping Babies Breathe in three facilities, enrolling in-born neonates ≥28 weeks gestation. We collected observational data during a convenience sample of resuscitations and extracted clinical data from the medical record for all participants. We evaluated our primary outcome of effective breathing at three minutes after birth among newborns not breathing well at 30 seconds after birth employing generalized linear models using maximum likelihood estimation. Results Among 1,284 newborns with observational data, there was no difference in the proportion effectively breathing at three minutes (adjusted relative risk 1.08 [95% CI 0.81, 1.45]). Among 145 receiving bag mask ventilation, time to bag mask ventilation decreased 64.3 seconds during heart rate-guided resuscitation (p<0.001). Among 10,906 enrolled in the trial, perinatal mortality was unchanged (adjusted relative risk 1.19 [95% CI 0.96, 1.48]) and death before discharge increased (adjusted relative risk 1.43 [95% CI 1.03, 1.99]). Expert review of stillborn cases demonstrated a stillbirth misclassification rate of 33.3% during Helping Babies Breathe versus 5.9% in heart rate-guided resuscitation. Conclusion During heart rate-guided basic resuscitation, time to bag mask ventilation was reduced by greater than one minute. The increase in death before discharge and unchanged perinatal mortality may be due to resuscitation of newborns with a higher risk of mortality who were previously presumed stillborn. A cluster-randomized trial of heart rate-guided basic resuscitation is needed to evaluate its impact on neonatal mortality in low-resource settings.