bluuebunny/crossref_metadata_2025 huggingface dataset:
Learning decouples accuracy and reaction time for rapid decisions in a transitive inference task
Authors: Munoz Fabian , Jensen Greg , Shinn Maxwell , Alkan Yelda , Murray John D. , Terrace Herbert S. , Ferrera Vincent P.
Published: February 2025

The accumulation of evidence over time formalized in the drift diffusion model (DDM), has become one of the most prevalent models of deliberative decision-making. To better understand the role of latent variables during a serial learning task, in which decisions were made rapidly and did not show typical accuracy and response time patterns, we fit behavioral data with a DDM using PyDDM (Shinn et al., 2020). We trained macaque monkeys (N = 3) on a transitive inference transfer task in which they learned the implied order in a ranked list of 7 novel pictures in each behavioral session, indicating their choices by making saccadic eye movements. They reliably learned each new list order within 200-300 trials with asymptotic accuracy of around 80-90% correct. Their responses showed a symbolic distance effect, with 60% accuracy for adjacent list items and 90% accuracy for the largest symbolic distance. Although performance accuracy improved with learning and symbolic distance, reaction times were nearly constant. Nevertheless, accuracy and reaction time were well fit by the generalized drift- diffusion model. The fits were achieved by simultaneously increasing both the evidence accumulation rate and a collapsing bound to capture the shape of the reaction time distributions. These results indicate that decision-making during learning and transfer in a TI task may be characterized by a “variable collapsing bound” DDM.
A dendritic guidance receptor functions in both ligand dependent and independent modes
Authors: Reddy Anay R , Machera Sebastian J , Cook Zoe T , Özkan Engin , Shen Kang
Published: February 2025

The formation of an appropriately shaped dendritic arbor is critical for a neuron to receive information. Dendritic morphogenesis is a dynamic process involving growth, branching, and retraction. How the growth and stabilization of dendrites are coordinated at the molecular level remains a key question in developmental neurobiology. The highly arborized and stereotyped dendritic arbors of theCaenorhabditis elegansPVD neuron are shaped by the transmembrane DMA-1 receptor through its interaction with a tripartite ligand complex consisting of SAX-7, MNR-1, and LECT-2. However, receptor null mutants exhibit strongly reduced dendrite outgrowth, whereas ligand null mutants show disordered branch patterns, suggesting a ligand-independent function of the receptor. To test this idea, we identified point mutations indma-1that disrupt receptor-ligand binding and introduced corresponding mutations into the endogenous gene. We show that the ligand-free receptor is sufficient to drive robust, disordered dendritic branch formation but results in a complete loss of arbor shape. This disordered outgrowth program utilizes similar downstream effectors as the stereotyped outgrowth program, further arguing that ligand binding is not necessary for outgrowth. Finally, we demonstrate that ligand binding is required to maintain higher-order dendrites after development is complete. Taken together, our findings support a surprising model in which ligand-free and ligand-bound DMA-1 receptors have distinct functions: the ligand-free receptor promotes stochastic outgrowth and branching, whereas the ligand-bound receptor guides stereotyped dendrite morphology by stabilizing arbors at target locations.
Annotation Comparison Explorer (ACE): connecting brain cell types across studies of health and Alzheimer’s Disease
Authors: Miller Jeremy A. , Travaglini Kyle J. , Luquez Tain , Hostetler Rachel E. , Oster Aaron , Daniel Scott , Tasic Bosiljka , Menon Vilas
Published: February 2025

Single-cell multiomic technologies have allowed unprecedented access to gene profiles of individual cells across species and organ systems, including >1000 papers focused on brain cell types alone. The Allen Institute has created foundational atlases characterizing mammalian brain cell types in the adult mouse brain and the neocortex of aged humans with and without Alzheimer’s disease (AD). With so many public cell type classifications (or ‘taxonomies’) available and many groups choosing to define their own, linking cell types and associated knowledge between studies remains a major challenge. Here, we introduce Annotation Comparison Explorer (ACE), a web application for comparing cell type assignments and other cell-based annotations (e.g., donor demographics, anatomic locations, batch variables, and quality control metrics). ACE allows filtering of cells and includes an interactive set of tools for comparing two or more taxonomy annotations alongside collected knowledge (e.g., increased abundance in disease conditions, cell type aliases, or other information about a specific cell type). We present three primary use cases for ACE. First, we demonstrate how a user can assign cell type labels from the Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) taxonomy to cells from their own study and compare these cell type mappings to existing cell type assignments and cell metadata. Second, we extend this approach to ten published human AD studies which we previously reprocessed through a common data analysis pipeline. This allowed us to compare brain taxonomies across otherwise incomparable studies and identify congruent cell type abundance changes in AD, including a decrease in abundance of subsets of somatostatin interneurons. Finally, ACE includes translation tables between different mouse and human brain cell type taxonomies publicly accessible on Allen Brain Map, from initial studies in individual neocortical areas to more recent studies spanning the whole brain. ACE can be freely and publicly accessed as a web application (https://sea-ad.shinyapps.io/ACEapp/) and on GitHub (github.com/AllenInstitute/ACE).
ML-MAGES: A machine learning framework for multivariate genetic association analyses with genes and effect size shrinkage
Authors: Liu Xiran , Crawford Lorin , Ramachandran Sohini
Published: February 2025

A fundamental goal of genetics is to identify which and how genetic variants are associated with a trait, often using the regression results from genome-wide association (GWA) studies. Important methodological challenges are accounting for inflation in GWA effect estimates as well as investigating more than one trait simultaneously. We leverage machine learning approaches for these two challenges, developing a computationally efficient method called ML-MAGES. First, we shrink the inflation in GWA effect sizes caused by non-independence among variants using neural networks. We then cluster variant associations among multiple traits via variational inference. We compare the performance of shrinkage via neural networks to regularized regression and fine-mapping, two approaches used for addressing inflated effects but dealing with variants in focal regions of different sizes. Our neural network shrinkage outperforms both methods in approximating the true effect sizes in simulated data. Our infinite mixture clustering approach offers a flexible, data-driven way to distinguish different types of associations—trait-specific, shared across traits, or spurious—among multiple traits based on their regularized effects. Clustering applied to our neural network shrinkage results also produces consistently higher precision and recall for distinguishing gene-level associations in simulations. We demonstrate the application of ML-MAGES on association analyses of two quantitative traits and two binary traits in the UK Biobank. Our identified associated genes from single-trait enrichment tests overlap with those having known relevant biological processes to the traits. Besides trait-specific associations, ML-MAGES identifies several variants with shared multi-trait associations, suggesting putative shared genetic architecture.
In harmony? A scoping review of methods to combine multiple 16S amplicon data sets
Authors: Li Zone , Chen Yingan , Sun Yage , McArthur Kristen , Carnes Megan , Liu Tiange , Mueller Noel T. , Page Grier P. , Rossman Lori , Smirnova Ekaterina , White Julie D. , Kress Amii M. , Debelius Justine W
Published: February 2025

Robust evidence on relationships between the human microbiome and health are critical for understanding and improving the human condition. However, there is little information about methodological approaches to combine and analyze multiple microbiome data sets. To address this gap, we conducted a scoping review of studies that combine sequencing data from multiple data sets to understand the study objectives, data sources and selection, feature -table assembly methods, and analyses. References were identified through a systematic search of literature published between 2011 and 2022. Our final review included 60 articles. Despite the wide-spread use of the word “meta-analysis,” we found that only 24 studies used a systematic process to select their data sets, suggesting multiple meanings of the term within the field. While more than two thirds of studies used at least one publicly available data source, 19 had to request data from the original authors. Most studies (60%) combined data sets from multiple disjoint hypervariable regions. The number of hypervariable regions combined was not associated with the table construction method, but feature table construction method and the number of hypervariable regions influenced analytical resolution. Our results suggest the microbiome community needs to examine the use of terminology and analytic approaches for combining data sets; that additional work is needed to explore the impact of data source on bias in combined studies; and invite an independent evaluation of the methods used for feature table construction across disjoint regions.
Spike sorting AI agent
Authors: Lin Zuwan , Marin-Llobet Arnau , Baek Jongmin , He Yichun , Lee Jaeyong , Wang Wenbo , Zhang Xinhe , Lee Ariel J. , Liang Ningyue , Du Jin , Ding Jie , Li Na , Liu Jia
Published: February 2025

Spike sorting is a fundamental process for decoding neural activity, involving preprocessing, spike detection, feature extraction, clustering, and validation. However, conventional spike sorting methods are highly fragmented, labor-intensive, and heavily reliant on expert manual curation, limiting their scalability and reproducibility. This challenge has become more pressing with advances in neural recording technology, such as high-density Neuropixels for large-scale neural recording or flexible electrodes for long-term stable recording over months to years. The volume and complexity of these datasets make manual curation infeasible, requiring an automated and scalable solution. Here, we introduce SpikeAgent, a multimodal large language model (LLM)-based AI agent that automates and standardizes the entire spike sorting pipeline. Unlike traditional approaches, SpikeAgent integrates multiple LLM backends, coding functions, and established algorithms, autonomously performing spike sorting with reasoning-based decision-making and real-time interaction with intermediate results. It generates interpretable reports, providing transparent justifications for each sorting decision, enhancing transparency and reliability. We benchmarked SpikeAgent against human experts across various neural recording technology, demonstrating its versatility and ability to achieve curation consistency that are equal to, or even higher than human experts. It also drastically reduces the expertise barrier and accelerates the curation and validation time by orders of magnitude. Moreover, it enables automated interpretability of the neural spiking data, which cannot be achieved by any conventional methods. SpikeAgent presents a paradigm shift in processing signals for neuroscience and brain-computer interfaces, while laying the ground for AI agent-augmented science across various domains.
RNA-binding proteins: it's better to play in a band
Authors: Jeong Joshua , Hertel Klemens J. , Shi Yongsheng
Published: February 2025

Alternative splicing (AS) is regulated by a myriad of RNA-binding proteins (RBPs) in a coordinated manner. However, most studies characterize RBPs individually. In this issue ofGenes & Development, Peyda and colleagues (doi:10.1101/gad.352105.124) revealed how the LASR complex, consisting of multiple RBPs, regulates AS by recognizing multipart sequences. Their approach may be applicable to studying the combinatorial effects of other RBPs, which is critical for cracking the splicing code.
The role of transposon activity in shapingcis-regulatory element evolution after whole genome duplication
Authors: Monsen Oystein , Gronvold Lars , Datsomor Alex , Harvey Thomas Nelson , Kijas James , Suh Alexander Sang-Jae , Hvidsten Torgeir Rhoden , Sandve Simen Rod
Published: February 2025

Whole-genome duplications (WGD) and transposable element (TE) activity can act synergistically in genome evolution. WGDs can increase TE activity directly through cellular stress or indirectly by relaxing selection against TE insertions in functionally redundant, duplicated regions. Because TEs can function as, or evolve into, TE-derivedcis-regulatory elements (TE-CREs), bursts of TE activity following WGD are therefore likely to impact evolution of gene regulation. Yet, the role of TEs in genome regulatory evolution after WGDs is not well understood. Here we used Atlantic salmon as a model system to explore how TE activity after the salmonid WGD ~100MYA shaped CRE evolution. We identified 55,080 putative TE-CREs using chromatin accessibility data from liver and brain. Retroelements were both the dominant source of TE-CREs and had higher regulatory activity in MPRA experiments compared to DNA elements. A minority of TE-subfamilies (16%) accounted for 46% of TE-CREs, but these "CRE-superspreaders" were mostly active prior to the WGD. Analysis of individual TE insertions, however, revealed enrichment of TE-CREs originating from WGD-associated TE activity, particularly for the DTT (Tc1-Mariner) DNA elements. Furthermore, coexpression analyses supported the presence of TE-driven gene regulatory network evolution, including DTT elements active at the time of WGD. In conclusion, our study supports a scenario where TE activity has been important in genome regulatory evolution, either through relaxed selective constraints, or strong selection to recalibrate optimal gene expression phenotypes, during a transient period following genome doubling.
Gravitationally sensitive structured x-ray optics using nuclear resonances
Authors: Lee Shin-Yu , Ahrens Sven , Liao Wen-Te
Published: February 2025

Einstein's general theory of relativity not only revolutionized our understanding of the universe but also led to numerous gravitational applications on large spatial scales, such as gravitational-wave astronomy and the operation of the global positioning system. On Earth, the gravitational redshift has been experimentally observed over spatial scales ranging from a few millimeters to thousands of kilometers. However, finding an application of gravitational effects in a quantum system at small spatial extensions on Earth remains a challenge. Along this line, we introduce a structured x-ray waveguide that serves as an x-ray mode converter, and its performance is influenced by an altitude change in the order of millimeters or even microns. Our results suggest that the gravitational redshift can be another way to fine adjust the x-ray detuning for any devices using a nuclear clock transition.

Published by the American Physical Society
2025
Improving the performance of phase-change microcapsules for application in single spaces in hot climates
Authors: Diab Esraa , Motawa Ibrahim , Elshikh Mohamed
Published: February 2025

Purpose

This study aims to design a high-performance building envelope system with a focus on evaluating energy savings considering the hot climate.

Design/methodology/approach

A thermal energy storage approach based on inorganic phase change material (PCM) was adopted to regulate both temperature and humidity conditions when added to building envelopes. The microencapsulation technology was used to form new PCM microcapsules by combining a humidity agent material with thermal conduction accelerating material to encapsulate an inorganic PCM. The relevant parameters of the thermophysical characteristics of the synthesized PCM microcapsules were tested and analyzed. Also, a numerical validation was done for the energy-saving evaluation of the new synthesized PCM microcapsules when used in a building envelope.

Findings

The study results showed that the new synthesized PCM microcapsules have high latent heat capacities and enhanced thermal conduction values. The simulation results conducted by the Conduction Finite Difference solution algorithm (CondFD) approved the efficiency of the proposed PCM compositions when added to a building envelope.

Research limitations/implications

Due to applying the PCM to the building envelope composition by the addition instead of the replacement method, the proposed design solutions are not suitable for improving the performance of lightweight construction.

Originality/value

This study provides a promising energy-efficient system for building envelopes. The study originality is represented in adding carbon nanoparticles as a shell material to overcome the low thermal conduction issue of PCMs. In addition to testing the impacts of different doses of the carbon shell material on the thermal performance of inorganic PCM microcapsules.
A moderated mediation model of relationship between artificial intelligence awareness and withdrawal behaviors
Authors: Nguyen Thi Phuong Linh , Nguyen Dinh Trung
Published: February 2025

Purpose

This study aims to explore the relationship between artificial intelligence (AI) awareness and physical and psychological withdrawal behaviors of enterprises employees through the mediating roles of job security and emotional exhaustion as well as the moderating role of emotional intelligence.

Design/methodology/approach

Data were collected through a self-administered questionnaire from six fields with the highest level of AI application with a sample of 1,129 Vietnamese enterprises employees. Data were analyzed using SmartPLS, a bootstrapping technique was used to analyze the data. The mediating effect of job security and emotional exhaustion and the moderating effect of emotional intelligence were performed.

Findings

The research showed that the proposed moderated mediation model was accepted because the relationships between the constructs were statistically significant. The results of the data analysis supported a positive relationship between AI awareness and physical and psychological withdrawal behaviors, as well as a mediating effect of job security and emotional exhaustion. The findings also confirmed that there is a moderating effect of emotional intelligence between AI awareness and job security, emotional exhaustion, physical and psychological withdrawal behaviors.

Research limitations/implications

Sample data was only collected at a few Vietnamese enterprises in six fields with the highest level of AI application which are e-commerce, transportation and logistics, education, real estate, finance and agriculture, which may be limiting generalizability of research results.

Practical implications

This study offers several practical and useful management implications, such as anticipating negative attitudes, feelings and behaviors of employees to prepare a response plan; conducting interviews, investigate employees’ AI awareness and do their best to minimize its negative effects on employees’ psychological states and behaviors; and paying attention to recruiting and selecting employees with good emotional intelligence.

Originality/value

This study contributes to the growing literature on AI by elucidating the mediating roles of job insecurity and emotional exhaustion in the relationship between AI awareness and physical and psychological withdrawal behavior. This study also makes a significant step forward in examining the moderating mechanisms of emotional intelligence in attenuating the effects of AI awareness on job insecurity, emotional exhaustion, physical and psychological withdrawal behavior.
Unlocking AI capabilities: exploring strategic fit, innovation ambidexterity and digital entrepreneurial intent in driving digital transformation
Authors: Ahmad Zeshan
Published: February 2025

Purpose

The insurgence of the COVID-19 pandemic insinuated that family-owned small hotels (F-OSH) should adopt AI capabilities and innovation activities and digitize their operations to survive. This study examines the potential of AI capabilities to digitally transform F-OSHs by leveraging innovation ambidexterity, preparing them for future disasters proactively. Additionally, it sheds light on how the impact of AI capabilities on innovation ambidexterity varies based on strategic fit. In addition, this research explores the influence of digital entrepreneurial intention on fostering innovation ambidexterity, essential for digital transformation in F-OSHs.

Design/methodology/approach

The study collected primary data from 318 descendant entrepreneurs designated as chairpersons or managing directors in F-OSH and analyzed the data using the partial least structural equation modeling technique.

Findings

This study found a positive association of AI capabilities, and digital entrepreneurial intention with the digital transformation of F-OSHs, while strategic fit does not have an association with innovation ambidexterity. Innovation ambidexterity mediates the relationship between AI capabilities and digital transformation in F-OSHs. Moreover, a strong strategic fit increases the effect of AI capabilities on innovation ambidexterity. Furthermore, a high intention for digital entrepreneurship reduces the impact of innovation ambidexterity on the digital transformation of F-OSHs.

Practical implications

The combination of AI capabilities and innovation ambidexterity has transformed F-OSHs' digital transformation. This proactive approach to dealing with economic recessions such as COVID-19 is also influenced by digital entrepreneurial intention and strategic fit.

Originality/value

Anchored on the dynamic capability theory, this study provides valuable insights and novel empirical evidence by investigating the mediating mechanism of innovation ambidexterity and boundary condition of strategic fit and digital entrepreneurial intention between AI capabilities and digital transformation in F-OSHs.
ChatGPT technology contribution in business innovation, policy and management
Authors: Alzoubi Yehia Ibrahim , Mishra Alok
Published: February 2025

Purpose

This paper aims to discuss a novel artificial intelligence (AI) model known as Generative Pretrained Transformer (GPT), specifically ChatGPT, and its potential applications in the corporate sphere. It highlights the significance of ChatGPT in the realms of corporate innovation, management and policymaking.

Design/methodology/approach

ChatGPT is explained as an AI language model produced by OpenAI, using the GPT framework and extensive training on natural language data. This paper addresses the model’s capabilities to respond to natural language queries resembling human interactions by reviewing the available literature as well as the professional websites.

Findings

This paper discusses the advantages of ChatGPT in a business context, emphasizing its potential benefits. It also critically examines the limitations of ChatGPT, including ethical considerations, data interpretation challenges, reliability and privacy-related issues.

Originality/value

This paper contributes to the discourse surrounding ChatGPT’s role in business innovation, management and policymaking. It highlights both the potential and limitations of this AI technology, offering insights into its implications and future research directions for corporate applications.
A Clinical Isolate of Human Parainfluenza Virus 3 (Fukushima/O695/2019) Contains a Mutation in the Serial Guanosines in the RNA Editing Site of the P Gene and Produces an Atypical Number of Nongenomic Guanosine Insertions During RNA Editing
Authors: Shirato Kazuya , Kawase Miyuki , Suwa Reiko , Kakizaki Masatoshi , Sugimoto Satoko , Kume Yohei , Chishiki Mina , Ono Takashi , Okabe Hisao , Norito Sakurako , Hosoya Mitsuaki , Ujike Makoto , Hashimoto Koichi
Published: February 2025

Human parainfluenza virus 3 (HPIV3) contains a purine‐rich RNA editing site, allowing multiple viral proteins to be produced from a single gene by the posttranscriptional addition of G nucleotides. The Fukushima/O695/2019 (O695) HPIV3 clinical isolate has a G‐to‐A substitution at the last position of five serial G residues in the RNA editing site. This study evaluates the effects of this substitution in the RNA editing site on the biological character of HPIV3. Our results show that O695 has slightly reduced viral replication compared with viruses with an intact RNA editing site. The number of G nucleotides inserted into the RNA editing site in HPIV3 isolates with an intact RNA editing site was 5 or fewer in most cases, giving a total of 10 serial G bases (5 + 5). In contrast, the number of G nucleotides inserted into the RNA editing site in O695 showed an atypical pattern, with six or fewer in most cases. This resulted in a total of 10 (4 + 6), suggesting the additional insertion of one more nongenomic G to the mRNA of the P gene of O695 compared with viruses carrying no mutations in the RNA editing site. Phylogenetic analysis reveals that mutations in the RNA editing site occur sporadically with various mutation patterns, suggesting that these mutations are routinely selected for during the life cycle of HPIV3.
The Effectiveness of Macroprudential Policies on Credit Growth in Vietnam
Authors: Dinh Thi Thu Hong , Huu Nguyen Tuan
Published: February 2025

This study presents a comprehensive analysis of the effectiveness of macroprudential policies on credit growth in Vietnam. It introduces an advanced approach to create a macroprudential index (MPI) that measures the state of macroprudential policy. The MPI is then applied to a high‐frequency database on a monthly basis to estimate its impact on real credit growth and the country's credit growth cycle. The study's comprehensive nature is evident in the manual survey of the policies of the State Bank of Vietnam and the information published by commercial banks from January 1999 to June 2023. The findings reveal that, unlike flexible monetary policy, macroprudential policy tools have gained prominence and have been tightened since 1999. Moreover, empirical evidence suggests that tightening macroprudential policies in Vietnam has helped reduce real credit growth, although they have not been effective in smoothing real credit growth cycles.
The Dutch Exile Community in King's Lynn: A Forgotten Moment in Anglo‐Dutch Contact
Authors: JOBY CHRISTOPHER
Published: February 2025

Before, during and after the start of the Dutch Revolt, thousands of people, principally Calvinists, left the Low Countries for England. They established communities in more than twenty towns including the borough of King's Lynn in west Norfolk. Exiles from Flanders and Holland began arriving in Lynn in 1567, and they soon established a Calvinist church community there. A 1571 census indicates that the exile community had more than 200 members, many of whom worked in the textile trade. In 1572, in the early months of the Dutch Revolt, the minister returned to the Low Countries. Thereafter, we have little information on the exile church in Lynn, although exiles did continue to produce textiles, which were sealed in Norwich. This article analyses the history of the exile community and church in Lynn. It addresses questions such as where the exiles came from, why they moved to Lynn and the practices and positions they adopted and networks they created. Furthermore, it explores the relationship between the exile communities in Lynn and Norwich. Several of the church leaders returned to the Low Countries. The article therefore explores their role in building the Reformed Church there. Finally, it challenges previous historiography on Calvinist exiles in Norfolk by suggesting that attention should be paid not only to the exile communities in Norwich but also to those in other Norfolk towns such as Lynn.
Relapse in substance‐induced psychosis and associated risk factors. A Nationwide register‐linkage study from Sweden
Authors: Ellilä Venla , Taipale Heidi , Tiihonen Jari , Mittendorfer‐Rutz Ellenor , Niemelä Solja
Published: February 2025

Background and Aims

Substance‐induced psychoses (SIP) have the potential to relapse and convert into schizophrenia‐spectrum disorders. However, risk factors associated with SIP relapse remain unknown. The aim of this study was to measure the incidence and risk of SIP relapse and associating risk factors.

Design, setting and participants

Population based register study that identified people with first‐time SIP between 2006 and 2016 (n = 7320) from Swedish nation‐wide registers to examine incidence of relapse and associated risk factors during 2‐year follow‐up. Participants were censored to death, emigration and the diagnosis of other psychotic illness. Risk factors associated with relapse were studied using multivariable Cox models.

Measurements

SIP was measured via related diagnostic codes (ICD‐10: F1x.5) collected from the National Patient Register (NPR). SIP relapse was measured as hospitalization due to SIP during 2‐year follow‐up also collected from the NPR. Potential risk factors included demographic characteristics, psychiatric comorbidities, sickness absence and disability pension collected from nationwide registers.

Findings

Of the study population (n = 7320), 20.0% (n = 1463) had a SIP relapse during the follow‐up (median time 126 days, interquartile range 56–321) and 83.3% had the same type of SIP as their first SIP. Relapse was most common for those whose first SIP was induced by cannabis (25.7%), followed by multi‐substance use (23.8%) and (meth)amphetamine (19.7%). Factors associated with SIP relapse were previous substance use disorder [hazard ratio (HR) = 1.37, 95% confidence interval (CI) = 1.20–1.56], younger age (16–29 years, HR = 1.29, 95% CI = 1.05–1.58, versus 50–65), being born abroad (HR = 1.23, 95% CI = 1.07–1.41), attention deficit hyperactivity disorder (HR = 1.21, 95% CI = 1.05–1.39), having had 1–90 days sick leave during the previous year (HR = 1.19, 95% CI = 1.01–1.44), and cannabis‐ (HR = 2.42, 95% CI = 1.98–2.96), (meth)amphetamine‐ (HR = 1.49, 95% CI = 1.23–1.81) or multi‐substance‐ (HR = 1.81, 95% CI = 1.52–2.15) induced psychosis compared with alcohol‐induced psychosis.

Conclusions

In Sweden, 20% of people with substance‐induced psychosis between 2006 and 2016 had a relapse within 2 years follow‐up. Cannabis‐induced psychosis had the shortest time lapse between episodes. Risk factors for relapse included attention deficit hyperactivity disorder, substance‐use disorder, younger age, previous sickness absence and being born outside Sweden.
Gender differences in circumstances associated with cannabis use
Authors: Martin Erin L. , Baker Nathaniel L. , Ramakrishnan Viswanathan , Neelon Brian , Saladin Michael E. , McRae‐Clark Aimee L.
Published: February 2025

Background and Objectives

Identifying circumstances associated with cannabis use is critical to the development of effective interventions for cannabis use disorder (CUD) and circumstances may differ by gender. The Inventory of Drug Taking Situations (IDTS) assesses the types of situations in which individuals most often use drugs through eight subscales: dealing with (1) Unpleasant Emotions; (2) Physical Discomfort; (3) Pleasant Emotions; (4) Testing Personal Control; (5) Urges/Temptations; (6) Conflict with Others; (7) Social Pressure; and (8) Pleasant Times with Others. The aims of this study were to determine if IDTS scores varied by gender in individuals with CUD, and to ascertain if behavioral factors such as cannabis use or stress were differentially associated with IDTS scores by gender.

Methods

Baseline data were obtained from a study of 148 nontreatment‐seeking individuals with CUD. Data included demographic characteristics, IDTS scores, self‐reported past 90‐day substance use, and measures of past‐month and childhood stress.

Results

Women reported using cannabis more than men in negative affective contexts, namely when experiencing conflict with others, testing personal control, physical discomfort, and unpleasant emotions. IDTS subscale scores associated with negative affect and pleasant emotions were positively associated with past 90‐day cannabis use sessions across genders, use when experiencing negative affect was associated with childhood stress across genders, and use when experiencing unpleasant emotions was differentially associated with recent stress by gender.

Conclusion and Scientific Significance

Findings suggest gender differences in circumstances associated with cannabis use with implications for therapeutic development for CUD.
“It was never about money!”: Articulating a Commoning Anticapitalist Strategy in German Common Economies
Authors: Amaduzzi Lee , Ruiz Cayuela Sergio
Published: February 2025

In this paper, we delve into a contentious issue within commoning literature: the role of money in anticapitalist strategy and praxis. Focusing on German Gemeinsame Ökonomie (“Common Economies”), income sharing groups in the radical left, we examine the boundaries of money as a transformative tool and the social relations cultivated through commoning money. By militantly engaging with individuals who pool their finances into shared bank accounts, the paper explores the operational dynamics and underlying rationale of Common Economies along three analytical and political categories that form our proposed commoning anticapitalist strategy. First, individual commoners and processes of subjectivation that can potentially reconfigure common senses. Second, communities and the very contentious process of boundary‐making as a balance between subsistence and political potential. And third, the accumulation of collective capacities and their deployment to articulate a commons autonomy aiming to overcome the capitalist organisation of life. Situating money commoning within the framework of reproductive commoning, we argue that Common Economies do not see money sharing as an end in‐itself, but as a means that allows them to liberate collective work and direct it towards radical anticapitalist action. Finally, we analyse the shortcomings of Common Economies as a commoning anticapitalist strategy: a lack of internal diversity of the groups, the challenge of upscaling, and the inherent contradictions of using money in trying to overcome capitalism. This investigation contributes to a nuanced understanding of money as a capitalist tool that can be hacked to rebuild reproductive commons in the Global North.
Hunting and Habitat Destruction Drive Widespread Functional Declines of Top Predators in a Global Deforestation Hotspot
Authors: Romero‐Muñoz Alfredo , Bleyhl Benjamin , Benítez‐López Ana , Camino Micaela , Decarre Julieta , Nanni A. Sofía , Noss Andrew , Giordano Anthony J. , Quiroga Verónica A. , Torres Ricardo , Thompson Jeffrey J. , Villalba Laura , Nuñez Regueiro Mauricio M. , De Angelo Carlos , Kuemmerle Tobias
Published: February 2025

Aim

We investigated the effects of habitat destruction and hunting on the functional decline of top predators, specifically jaguar and puma, in the Gran Chaco.

Location

The 1.1 million km2 South American Gran Chaco.

Methods

We used spatially explicit, individual‐based models for jaguars and pumas, incorporating detailed information on habitat suitability and hunting pressure. We parameterized our models with literature data and calibrated them through a Delphi expert‐elicitation process. We simulated population trajectories under a hypothetical, threat‐free, baseline versus different threat scenarios.

Results

Under combined threats of hunting and habitat loss, jaguar and puma populations declined by 88% and 80%, respectively, compared to range contractions of 48% and 35%, respectively. Both species remained regionally viable, particularly due to large protected areas, which acted as population sources but were surrounded by strong sinks. We observed a widespread weakening of the top carnivore guild function, with at least one species extirpated across 67% of the Chaco and strong declines (> 80%; considered here as functional loss) for both species concurrently across 61% of their area of historical co‐occurrence. Hunting was a much stronger driver of population declines (88% and 77% for jaguars and pumas, respectively) compared to habitat destruction (26% and 22%).

Main Conclusions

Large predators play key functional roles in ecosystems. Our findings reveal that these functions can be lost over vast areas due to the combined effects of habitat destruction and hunting, with functional loss extending far beyond the areas of species' extirpation. Very large protected areas, like Kaa‐Iya in Bolivia, are crucial for maintaining viable populations of top predators, highlighting the pressing need for increased protection and connectivity in the Chaco to prevent further trophic downgrading. More generally, our research underscores the value of spatially detailed, mechanistic models for disentangling the complex dynamics of multiple threats on ecological functioning at broad scales.
Optimising Resource Use Through Low‐Precision Feature Selection: A Performance Analysis of Logarithmic Division and Stochastic Rounding
Authors: Suárez‐Marcote Samuel , Morán‐Fernández Laura , Bolón‐Canedo Verónica
Published: February 2025

The growth in the number of wearable devices has increased the amount of data produced daily. Simultaneously, the limitations of such devices has also led to a growing interest in the implementation of machine learning algorithms with low‐precision computation. We propose green and efficient modifications of state‐of‐the‐art feature selection methods based on information theory and fixed‐point representation. We tested two potential improvements: stochastic rounding to prevent information loss, and logarithmic division to improve computational and energy efficiency. Experiments with several datasets showed comparable results to baseline methods, with minimal information loss in both feature selection and subsequent classification steps. Our low‐precision approach proved viable even for complex datasets like microarrays, making it suitable for energy‐efficient internet‐of‐things (IoT) devices. While further investigation into stochastic rounding did not yield significant improvements, the use of logarithmic division for probability approximation showed promising results without compromising classification performance. Our findings offer valuable insights into resource‐efficient feature selection that contribute to IoT device performance and sustainability.
Intercellular mitochondrial transfer contributes to microenvironmental redirection of cancer cell fate
Authors: Bjerring Julie Sofie , Khodour Yara , Peterson Emilee Anne , Sachs Patrick Christian , Bruno Robert David
Published: February 2025

The mammary microenvironment has been shown to suppress tumor progression by redirecting cancer cells to adopt a normal mammary epithelial progenitor fate in vivo. However, the mechanism(s) by which this alteration occurs has yet to be defined. Here, we test the hypothesis that mitochondrial transfer from normal mammary epithelial cells to breast cancer cells plays a role in this redirection process. We evaluate mitochondrial transfer in 2D and 3D organoids using our unique 3D bioprinting system to produce chimeric organoids containing normal and cancer cells. We demonstrate that breast cancer tumoroid growth is hindered following interaction with mammary epithelial cells in both 2D and 3D environments. Furthermore, we show mitochondrial transfer occurs between donor mammary epithelial cells and recipient cancer cells primarily through tunneling nanotubes (TNTs) with minimal amounts seen from extracellular transfer of mitochondria, likely via extracellular vesicles (EVs). This organelle exchange results in various cellular and metabolic alterations within cancer cells, reducing their proliferative potential, and making them susceptible to microenvironmental control. Our results demonstrate that mitochondrial transfer contributes to microenvironmental redirection of cancer cells through alteration of metabolic and molecular functions of the recipient cancer cells. To the best of our knowledge, this is the first description of a 3D bioprinter‐assisted organoid system for studying mitochondrial transfer. These studies are also the first mechanistic insights into the process of mammary microenvironmental redirection of cancer and provide a framework for new therapeutic strategies to control cancer.
Past, present, and future strategies for detecting and quantifying circular RNA variants
Authors: Lin He , Conn Vanessa M. , Conn Simon J.
Published: February 2025

Circular RNAs (circRNAs) are a family of covalently closed RNA transcripts ubiquitous across the eukaryotic kingdom. CircRNAs are generated by a class of alternative splicing called backsplicing, with the resultant circularization of a part of parental RNA producing the characteristic backsplice junction (BSJ). Because of the noncontiguous sequence of the BSJ with respect to the DNA genome, circRNAs remained hidden in plain sight through over a decade of RNA next‐generation sequencing, yet over 3 million unique circRNA transcripts have been illuminated in the past decade alone. CircRNAs are expressed in a cell type‐specific manner, are highly stable, with many examples of circRNAs being evolutionarily conserved and/or functional in specific contexts. However, circRNAs can be very lowly expressed and predictions of the circRNA context from BSJ‐spanning reads alone can confound extrapolation of the exact sequence composition of the circRNA transcript. For these reasons, specific and ultrasensitive detection, combined with enrichment, bespoke bioinformatics pipelines and, more recently, long‐read, highly processive sequencing is becoming critical for complete characterization of all circRNA variants. Concomitantly, the need for targeted detection and quantification of specific circRNAs has sparked numerous laboratory‐based and commercial approaches to visualize circRNAs in cells and quantify them in biological samples, including biospecimens. This review focuses on advancements in the detection and quantification of circRNAs, with a particular focus on recent next‐generation sequencing approaches to bolster detection of circRNA variants and accurately normalize between sequencing libraries.
Microlearning for Green Skills Development in Ghana: A Pathway to Sustainability and Just Transitions
Authors: Owusu‐Agyeman Yaw
Published: February 2025

There have been calls for society to embrace lower‐carbon production and consumption practices to address the growing environmental concerns, which include pollution, biodiversity loss, and environmental deterioration. This call is also linked to the achievement of the United Nations sustainable development goals (SDGs) and the need for countries to create a society that seeks to preserve the health and well‐being of current and future generations. However, a global transition to a low‐carbon economy that is inclusive, equitable, and socially responsible can be achieved through the contributions of individuals who are equipped with green skills to support the SDGs. Using a qualitative research approach and qualitative content analysis (QCA), the current study examined how microlearning could serve as a strong instructional approach and tool to promote the development of green skills among individuals and the green skills ecosystem. The findings show that microlearning, which is characterised by technology‐mediated processes, multi‐facilitation approaches, and bite‐sized pieces of information, could be effectively and adequately used to support the development of green skills across businesses and substantially reduce pollution, biodiversity loss, and environmental deterioration. The study concludes by arguing that by leveraging the important features of microlearning, such as the brevity of learning experiences, clarity of content, easy accessibility to learning resources, and the ability of trainees to combine their work schedules with the training programme, many individuals will be equipped with green skills to contribute to the achievement of the SDGs.
Impact of Pre‐Infection COVID‐19 Vaccination on the Incidence and Severity of Long COVID: A Retrospective Case–Control Study
Authors: Barado Elena , Carlos Silvia , Moreno‐Galarraga Laura , Amer Fares , Escrivá Nicolás , Torres María Gabriela , Reina Gabriel , Fernandez‐Montero Alejandro
Published: February 2025

Long COVID is an emerging condition with an important impact on the quality of life of affected individuals. This study aims to analyse the association between complete vaccination prior to SARS‐CoV‐2 infection and the subsequent development of long COVID, including its symptoms and their frequency through a retrospective case–control study. Cases included participants with long COVID, while controls were participants without long COVID but who had a SARS‐CoV‐2 infection. Data were collected through a self‐reported survey. The study demonstrates a significant association between vaccination and a lower incidence of long COVID, adjusted for sex, age, university education, body mass index, physical activity, race, tobacco use, alcohol intake, adherence to Mediterranean diet, previous illness, flu vaccination, health care worker, high‐risk COVID worker and sleep hours and sedentarism (OR 0.49, CI 95% 0.28–0.87). Furthermore, there is a statistically significant association between vaccination and reduced symptoms such as anosmia, dysgeusia, myalgia or arthralgia, as well as a lower overall number, adjusted for the aforementioned variables. These findings suggest that the vaccine could be associated not only to a milder course of SARS‐CoV‐2 infection but also with an improvement in the state of long COVID and its symptoms.
Synthesis of superhydrophobic crack‐free monolithic silica aerogels via a vacuum freeze‐drying process
Authors: Ma Yu , Zhu Zhenting , Zhang Huangshuai , Kallel Mohamed , Yang Zihao , Ren Juanna , El‐Bahy Salah M. , Chen Zhe , El‐Bahy Zeinhom M. , Zhang Hang , Guo Zhanhu
Published: February 2025

Freeze‐drying is a promising method for drying gels, but it is considered incapable of preparing bulk inorganic oxide aerogels. Herein, using tert‐butanol/water co‐solvent as the freeze‐drying solvent, large‐size crack‐free monolithic silica aerogels with different absolute ethyl alcohol to tetraethylorthosilicate molar ratios were successfully synthesized via a vacuum freeze‐drying process. Superhydrophobicity was then obtained through an efficient chemical vapor deposition hydrophobic modification process. As the molar ratio increased from 8 to 16, the density, linear shrinkage, specific surface area (SSA), and mechanical properties decreased, while the thermal conductivity decreased first and then increased. The freeze‐dried silica aerogels show the lowest density of 0.078 g/cm3, the lowest linear shrinkage of 4.6%, the highest SSA of 962 m2/g, the highest Young's modulus of 904.3 kPa, and a lowest thermal conductivity of 0.026 W/(m·K). Despite the formed fine ice crystals compressing the gel skeleton to some extent in the freeze‐drying process, the developed mesoporous skeleton structure is basically preserved, which ensures excellent thermal insulation and mechanical performance. This study demonstrates that high‐quality monolithic inorganic oxide aerogels can be effectively prepared by the freeze‐drying method, which provides them with another efficient drying method independent of supercritical fluid drying and ambient pressure drying methods.