Browse Articles

Telomere-to-telomere DNA replication timing profiling using single-molecule sequencing with Nanotiming

Abstract Current temporal studies of DNA replication are either low-resolution or require complex cell synchronisation and/or sorting procedures. Here we introduce Nanotiming, a single-molecule, nanopore sequencing-based method producing high-resolution, telomere-to-telomere replication timing (RT) profiles of eukaryotic genomes by interrogating changes in intracellular dTTP concentration during S phase through competition with its analogue bromodeoxyuridine triphosphate (BrdUTP) for incorporation into replicating DNA. This solely demands the labelling of asynchronously growing cells with an innocuous dose of BrdU during one doubling time followed by BrdU quantification along nanopore reads. We demonstrate in S. cerevisiae model eukaryote that Nanotiming reproduces RT profiles generated by reference methods both in wild-type and mutant cells inactivated for known RT determinants. Nanotiming is simple, accurate, inexpensive, amenable to large-scale analyses, and has the unique ability to access RT of individual telomeres, revealing that Rif1 iconic telomere regulator selectively delays replication of telomeres associated with specific subtelomeric elements.

Research on the risk spillover effect between China’s national carbon emissions trading market and crude oil futures market

The development of China’s National Carbon Market has strengthened the inherent link between the carbon market and the broader energy market, providing a potential for cross-market risk transmission resonance. Studying the risk spillover effects between China’s National Carbon Market and the crude oil futures market is of significant practical importance, both in terms of carbon market development and carbon risk management. Based on the Maximal Overlap Discrete Wavelet Transform (MODWT), the price series are decomposed across multiple scales, and the risk spillover effects between the carbon market and the crude oil futures market are examined from both the time domain and the frequency domain. Methods such as wavelet energy decomposition, wavelet correlation, lead-lag analysis, and wavelet coherence are used to explore the mean spillover effects and volatility spillover effects (collectively referred to as risk spillover effects) across various scales. The study finds that China’s National Carbon Market exhibits a clear compliance-driven effect, with relatively low market liquidity. The crude oil futures market experiences frequent price fluctuations, primarily driven by long-term factors. In the time domain, the risk transmission resonance between the carbon market and the crude oil futures market is high, with significant positive correlations observed at the D1 to D4 scales, and noticeable mean spillover effects. In the frequency domain, at the D3 to D4 scales, the carbon market and the crude oil futures market exhibit similar volatility frequencies, indicating strong volatility spillover effects. Based on these findings, it is recommended that the trading volume of the carbon market be gradually increased to improve market liquidity. Furthermore, the risk monitoring and early warning mechanisms of China’s National Carbon Market should be improved. For carbon-emitting companies, enhancing awareness of carbon asset management and making informed investment and hedging decisions based on the correlation between the two markets is crucial.

Biological, environmental, and psychological stress and the human gut microbiome in healthy adults

AbstractEmerging research suggests that the gut microbiome plays a crucial role in stress. We assess stress-microbiome associations in two samples of healthy adults across three stress domains (perceived stress, stressful life events, and biological stress /Respiratory Sinus Arrhythmia; RSA). Study 1 (n = 62; mean-age = 37.3 years; 68% female) and Study 2 (n = 74; mean-age = 41.6 years; female only) measured RSA during laboratory stressors and used 16S rRNA pyrosequencing to classify gut microbial composition from fecal samples. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States was used to predict functional pathways of metagenomes. Results showed differences in beta diversity between high and low stressful life events groups across both studies. Study 1 revealed differences in beta diversity between high and low RSA groups. In Study 1, the low perceived stress group was higher in alpha diversity than the high perceived stress group. Levels of Clostridium were negatively associated with RSA in Study 1 and levels Escherichia/Shigella were positively associated with perceived stress in Study 2. Associations between microbial functional pathways (L-lysine production and formaldehyde absorption) and RSA are discussed. Findings suggest that certain features of the gut microbiome are differentially associated with each stress domain.

MIL-53(Al)-derived bimetallic Pd–Co catalysts for the selective hydrogenation of 1,3-butadiene at low temperature

Integrating genetic subtypes with PET scan monitoring to predict outcome in diffuse large B-cell lymphoma

The impact of village heads’ educational levels on adolescent academic performance: Evidence from rural China

This study investigates the relationship between the educational level of village heads and the academic performance of adolescents, using data from the China Family Panel Studies (CFPS). The analysis reveals that village chiefs with well-educated significantly enhance the academic outcomes of adolescents within their communities. This positive effect remains robust even after controlling for endogeneity through instrumental variables and conducting various robustness checks. Further investigation shows that these well-educated village leaders contribute to an increased provision of public goods, thereby improving the village’s external environment, which in turn supports academic performance. Additionally, well-educated village chiefs serve as role models within the community’s social network, positively influencing parental educational aspirations and enhancing adolescents’ academic results. Notably, the impact of well-educated village chiefs is more pronounced among girls and adolescents from low-income families, underscoring its significance in promoting gender equity in education and breaking cycles of intergenerational poverty.

Trabecular meshwork ultrastructural changes in primary and secondary glaucoma

AbstractTo examine ultrastructural changes in the trabecular meshwork (TM) in patients with primary and secondary glaucoma using scanning electron microscopy (SEM). This was a qualitative descriptive hospital-based study on the ultrastructure of the TM. Pure TM samples were collected after microincisional trabeculectomy from 26 patients with primary or secondary glaucoma and 10 control samples from eye bank donor corneas. SEM was used to analyze structural changes in the TM beams, corneoscleral meshwork (CSM), and juxtacanalicular (JCT) regions. Morphological features were compared between groups and correlated with histopathological findings. SEM revealed flattened and broadened TM beams in the JCT, resembling controls, often with a dumbbell configuration. Histopathological examination (HPE) and SEM showed rounded TM beams with considerable thinning, especially in primary angle-closure glaucoma (PACG), compared to primary open-angle (POAG) and pseudoexfoliation glaucoma (XFG). Maximum thinning in all primary glaucoma occurred in the CSM region, with minimal changes in the JCT region despite a reduction in cellularity in both regions. In steroid glaucoma, amorphous, glistening material was found on the TM beams in the JCT and CSM. XFG eyes displayed vesicular bodies adjacent to fibrillar material scattered diffusely over the TM beams, particularly in the CSM, differing from the platelet clumps seen in regular blood clots. TM beam thinning in primary glaucoma primarily affects the CSM region, sparing the JCT region. Amorphous deposits or vesicular bodies, seen only in steroid-induced glaucoma and XFG, suggest different mechanisms of TM damage in these glaucoma types.

Empathy is associated with older adults’ social behaviors and verbal emotional expressions throughout the day

Abstract Empathy plays a crucial role in promoting older adults’ interpersonal experiences, but it remains unclear how these benefits of empathy occur. To address this gap, we examined associations between empathy and how older adults behave and express emotions during their daily interpersonal encounters. Participants included 268 adults aged 65+ (46% men, n = 124) from the Daily Experiences and Well-being Study. They reported background characteristics and empathy in baseline interviews and indicated interpersonal encounters every 3 hours across 5 to 6 days. Participants wore electronically activated recorders (EAR), an app that captured 30-second snippets of ambient sounds every 7 minutes. Verbatim transcripts were coded for positive and negative social behaviors (e.g., praise, complain) and text was analyzed via Linguistic Inquiry and Word Count (LIWC) software for verbal expressions of positive and negative emotions (e.g., happy, hope, hate, hurt). Multilevel models showed that greater empathy was associated with greater variety in positive social behaviors throughout the day. More empathic older adults expressed more positive emotions while engaging in positive behaviors and less negative emotions when engaging in negative behaviors. This study innovatively draws on naturalistic data to delineate how more empathic older adults may have more positive and less negative social experiences than their less empathic counterparts. Findings may inform interventions that can incorporate empathy training to target those at higher risk of poor interpersonal experiences and outcomes (e.g., social isolation).

Multi-modal conditional diffusion model using signed distance functions for metal-organic frameworks generation

The right way to ride the wrong bike: An exploration of Klein’s ‘unridable’ bicycle

Professor Richard Klein and his students built a bicycle with a rather interesting feature: no one was able to ride it. A prize was offered. Hundreds of students and cycling enthusiasts attempted it. Years passed, and the prize money grew. Klein’s rear-steered bicycle became a canonical example of how non-minimum phase systems can be difficult and sometimes nearly impossible to control. It has been lauded as a particularly effective educational example in which students can experience the loss of controllability in a seemingly simple, albeit unorthodox bicycle. The primary result of the work reported here is a demonstration that it is possible for a human of modest athletic ability to ride Klein’s unridable bicycle, to keep it balanced, and to control its direction of travel. There is a secret to riding Klein’s rear-steer bicycle. The secret is revealed through an exploration of the dynamics and control of the bike that contains three elements: (1) modeling the physics of the actively steered bicycle as an inverted pendulum riding atop a carriage; (2) recognizing that the steer kinematics leads to competing physical mechanisms which an aspiring rider might exploit; and (3) examining limitations of controllability and stabilizability of the system from a state space perspective. From this vantage point, one can devise a novel strategy, based on a component of lateral acceleration that dominates at low speed, for riding the so-called “unridable” bike and solving Klein’s puzzle. The work adds a new chapter on the dynamics and control of the rear-steered bicycle, a problem of academic interest.

Perceived social support, marital satisfaction, and resilience in women with abortion experience through structural equation modeling

Development and application of microcapsules based on rice husk and metallurgical sludge to improve soil fertility

Pt/IrOx enables selective electrochemical C-H chlorination at high current

Single-cell data reveal heterogeneity of investment in ribosomes across a bacterial population

Dropping the baton: Cognitive biases in emergency physicians

Introduction Clinical medicine is becoming more complex and increasingly requires a team-based approach to deliver healthcare needs. This dispersion of cognitive reasoning across individuals, teams and systems (termed “distributed cognition”) means that our understanding of cognitive biases and errors must expand beyond traditional “in-the-head” individual mental models and focus on a broader “out-in-the-world” context instead. To our knowledge, no qualitative studies thus far have examined cognitive biases in clinical settings from a team-based sociocultural perspective. Our study therefore seeks to explore how cognitive biases and errors among emergency physicians (EPs) arise due to sociocultural influences and lapses in team cognition. Methodology Our study team comprised four EPs of different seniorities from three different institutions and local and international academics who provided qualitative methodological guidance. We adopted a constructivist paradigm and employed a reflexive thematic analysis approach which acknowledged our researcher reflexivity. We conducted seven focus group discussions with 25 EPs who were purposively sampled for maximum variation. Our research question was: How do sociocultural factors lead to cognitive biases and medical errors among EPs? Results Our themes coalesce around sociocultural pressures related to team psychology. In theme one, the EP is compelled by sociocultural pressures to blindly trust colleagues. In the second, the EP is obliged by cultural norms to be “nice” and neatly summarise cases into illness scripts during handovers. In the last, the EP is under immense pressure to follow conventional wisdom, comply with clinical protocols and not challenge inpatient specialists. Conclusion Cognitive biases and errors in clinical decision-making can arise due to lapses in distributed team cognition. Although this study focuses on emergency medicine, these pitfalls in team-based cognition are relevant across the entire continuum of care and across all specialties of medicine. The hyperacute nature of emergency medicine merely exacerbates and condenses these into a compressed timeframe. Indeed, similar relays are run every day in every discipline of medicine, with the same unified goal of doing the best for our patients while not committing cognitive errors and dropping the baton.

Estimating the prevalence of six common respiratory viral infections in Zhangzhou, China using nasopharyngeal swabs in adults and throat swabs in Children

SLC35A2 is a novel prognostic biomarker and promotes cell proliferation and metastasis via Wnt/β-catenin/EMT signaling pathway in breast cancer

Generalized cue reactivity in rat dopamine neurons after opioids

AbstractCue reactivity is the maladaptive neurobiological and behavioral response upon exposure to drug cues and is a major driver of relapse. A widely accepted assumption is that drugs of abuse result in disparate dopamine responses to cues that predict drug vs. natural rewards. The leading hypothesis is that drug-induced dopamine release represents a persistently positive reward prediction error that causes runaway enhancement of dopamine responses to drug cues, leading to their pathological overvaluation. However, this hypothesis has not been directly tested. Here, we develop Pavlovian and operant procedures in male rats to measure firing responses within the same dopamine neurons to drug versus natural reward cues, which we find to be similarly enhanced compared to cues predicting natural rewards in drug-naive controls. This enhancement is associated with increased behavioral reactivity to the drug cue, suggesting that dopamine neuronal activity may still be relevant to cue reactivity, albeit not as previously hypothesized. These results challenge the prevailing hypothesis of cue reactivity, warranting revised models of dopaminergic function in opioid addiction, and provide insights into the neurobiology of cue reactivity with potential implications for relapse prevention.

The global RNA-binding protein RbpB is a regulator of polysaccharide utilization in Bacteroides thetaiotaomicron

AbstractParamount to human health, symbiotic bacteria in the gastrointestinal tract rely on the breakdown of complex polysaccharides to thrive in this sugar-deprived environment. Gut Bacteroides are metabolic generalists and deploy dozens of polysaccharide utilization loci (PULs) to forage diverse dietary and host-derived glycans. The expression of the multi-protein PUL complexes is tightly regulated at the transcriptional level. However, how PULs are orchestrated at translational level in response to the fluctuating levels of their cognate substrates is unknown. Here, we identify the RNA-binding protein RbpB and a family of noncoding RNAs as key players in post-transcriptional PUL regulation. We demonstrate that RbpB interacts with numerous cellular transcripts, including a paralogous noncoding RNA family comprised of 14 members, the FopS (family of paralogous sRNAs). Through a series of in-vitro and in-vivo assays, we reveal that FopS sRNAs repress the translation of SusC-like glycan transporters when substrates are limited—an effect antagonized by RbpB. Ablation of RbpB in Bacteroides thetaiotaomicron compromises colonization in the mouse gut in a diet-dependent manner. Together, this study adds to our understanding of RNA-coordinated metabolic control as an important factor contributing to the in-vivo fitness of predominant microbiota species in dynamic nutrient landscapes.

Incident duration prediction through integration of uncertainty and risk factor evaluation: A San Francisco incidents case study

Predicting incident duration and understanding incident types are essential in traffic management for resource optimization and disruption minimization. Precise predictions enable the efficient deployment of response teams and strategic traffic rerouting, leading to reduced congestion and enhanced safety. Furthermore, an in-depth understanding of incident types helps in implementing preventive measures and formulating strategies to alleviate their influence on road networks. In this paper, we present a comprehensive framework for accurately predicting incident duration, with a particular emphasis on the critical role of street conditions and locations as major incident triggers. To demonstrate the effectiveness of our framework, we performed an in-depth case study using a dataset from San Francisco. We introduce a novel feature called "Risk" derived from the Risk Priority Number (RPN) concept, highlighting the significance of the incident location in both incident occurrence and prediction. Additionally, we propose a refined incident categorization through fuzzy clustering methods, delineating a unique policy for identifying boundary clusters that necessitate further modeling and testing under varying scenarios. Each cluster undergoes a Multiple Criteria Decision-Making (MCDM) process to gain deeper insights into their distinctions and provide valuable managerial insights. Finally, we employ both traditional Machine Learning (ML) and Deep Learning (DL) models to perform classification and regression tasks. Specifically, incidents residing in boundary clusters are predicted utilizing the scenarios outlined in this study. Through a rigorous analysis of feature importance using top-performing predictive models, we identify the "Risk" factor as a critical determinant of incident duration. Moreover, variables such as distance, humidity, and hour demonstrate significant influence, further enhancing the predictive power of the proposed model.