bluuebunny/crossref_metadata_2025 huggingface dataset:
MCAD-MM: a benchmark dataset and method for multi-channel acoustic detection of marine mammals
Authors: Li Nan , Shi Zhensheng , Shao Yuqi , Sun Naizhe , Zheng Bing , Zheng Haiyong
Published: January 2025

Marine mammals play an important role in maintaining the balance of marine ecosystems. A thorough understanding of their living habits, distribution, and environmental interaction is critical to formulating effective protection strategies. Traditional direct observation and sampling methods are limited in range, and it is challenging to cover the vast sea area because of the difficulties in operation and high cost. Passive acoustic monitoring (PAM) is an efficient and noninvasive technology to collect and analyze the sound signals of marine mammals via underwater deployment of hydrophones. However, the existing PAM studies are often limited by their focus on specific species or regions and need more universality. Moreover, the datasets and methods used need a unified benchmark, and the research results are difficult to integrate and share. This study proposes a novel approach based on deep learning (DL) to construct a common and systematic benchmark dataset and method for acoustic detection of marine mammals. The dataset is processed and analyzed via the combined use of the research data provided by the DCLDE Oahu dataset and the DL technology, covering acoustic signals and seawater ambient noises of various marine mammals, providing new data support and methodology guidance for research in related fields. The overall study involves a series of tasks: data acquisition, processing, labeling, methodology, experimental verification, and result analysis. We also use a Mamba-based state-space model for the detection of marine mammal vocalizations from the Mel-spectrogram representation of their acoustic signals. To the best of our knowledge, this is the first DL-based benchmark study on acoustic detection of marine mammals. This study not only provides a framework for the construction of a benchmark dataset and method based on a data-driven DL approach but also implements a unified process for data processing and quality assurance, laying a solid foundation for subsequent work and notably contributing to a broader understanding of marine biodiversity and conservation thereof.
Introducing youth to clinical research: Development and pilot implementation of a children’s activity book
Authors: Cadzow Renee , Strohmeier Andy , Carnes Erin , Quattrin Teresa
Published: January 2025

Introduction:

Children continue to be an underrepresented population in research and clinical trials due to difficulties encountered in recruitment, assenting, and retention processes. “Sofia Learns About Research” is a children’s activity book that introduces youth to clinical research and basic elements of clinical trials.

Methods:

Development of the activity book began in 2016, with publication of the first paper version in 2017 and an online version adapted for computer and tablet users in 2019. In 2019, we developed internal review board-approved pre/post surveys with five statements (written at ≤ 3rd-grade level) reflecting key concepts covered in the book. Participants were asked to indicate whether they agreed, disagreed, or were not sure about each of the statements and if they would ever want to be part of a research study. Preliminary analyses included descriptive statistics and cross-tabulations with chi squares.

Results:

Despite delays in dissemination and outreach due to the COVID-19 pandemic, we obtained feedback from over 170 diverse persons across a spectrum of communities and community partners. After book exposure, more participants knew that both children and parents have to assent/consent and that participants can withdraw from a study at any time.

Conclusions:

The book is an important advocacy tool with a long-term aim of increasing children’s knowledge and awareness about clinical research, ultimately leading to enhanced participation in clinical research and trials.
Assessing Mental Health Effects of Eastern Kentucky Households After the State’s Deadliest Flood: Using a Community Assessment for Public Health Emergency Response (CASPER)
Authors: Johnson Oshea , Balasuriya Lilanthi , Riley Tammy , Lockard Anthony Scott , Raleigh Angela , Ellis Martha , Schnall Amy Helene , Hanchey Arianna , Thoroughman Doug
Published: January 2025

Objectives

On July 28, 2022, eastern Kentucky experienced the state’s deadliest flood in recorded history. In response to ongoing mental health concerns from community members who survived the flood, local health department directors in affected communities requested technical assistance from the Kentucky Department for Public Health and the Centers for Disease Control and Prevention.

Methods

Two simultaneous Community Assessments for Public Health Emergency Response (CASPERs) were conducted 6 weeks after the flood. Four counties were assessed in each CASPER. EpiInfo7 was used to calculate the unweighted and weighted frequencies and percentages to estimate the number and percentage of households with a particular response in each CASPER.

Results

Approximately a third (30.5%) of households in CASPER 1 and approximately 40% of households in CASPER 2 reported experiencing ≥1 mental health problems. Individual-level mental health questions from a modified 3-stage CASPER found approximately 15% of persons in both CASPERs reported a Patient Health Questionnaire-2 (PHQ-2) score ≥3 and approximately 20% of persons in both CASPERs reported Generalized Anxiety Disorder-2 (GAD-2) score ≥3.

Conclusions

These findings indicated households experienced mental health problems after the flood. Depression and anxiety were prevalent among persons living in flood-affected areas. If ever needed, households preferred to receive mental health services in-person and locally.
Mediation Analysis in Bayesian Extended Redundancy Analysis with Mixed Outcome Variables
Authors: Choi Ji Yeh , Kyung Minjung , Park Ju-Hyun
Published: January 2025

Extended redundancy analysis (ERA) is a statistical approach to component-based multivariate regression modeling that explores interrelationships among multiple sets of while incorporating regression with a data-reduction technique. The extant models that utilize ERA have assumed the outcome variables with the same data type. Also, ERA models focused on estimating direct pathways only without explicitly addressing mediation effects. In this paper, ERA is extended to handle multiple mediators and mixed types of outcome variables by adopting a Bayesian framework, taking into account correlation structure among all of the outcome variables. The proposed method develops an algorithm that derives the joint posterior distribution of parameters using a Markov chain Monte Carlo algorithm. Simulations and an empirical dataset are provided to illustrate the usefulness of the proposed method.
Every Trait Counts: Marginal Maximum Likelihood Estimation for Novel Multidimensional Count Data Item Response Models with Rotation or
$\boldsymbol{\ell}_{\mathbf{1}}$
–Regularization for Simple Structure
Authors: Beisemann Marie , Holling Heinz , Doebler Philipp
Published: January 2025

Multidimensional item response theory (MIRT) offers psychometric models for various data settings, most popularly for dichotomous and polytomous data. Less attention has been devoted to count responses. A recent growth in interest in count item response models (CIRM)—perhaps sparked by increased occurrence of psychometric count data, e.g., in the form of process data, clinical symptom frequency, number of ideas or errors in cognitive ability assessment—has focused on unidimensional models. Some recent unidimensional CIRMs rely on the Conway–Maxwell–Poisson distribution as the conditional response distribution which allows conditionally over-, under-, and equidispersed responses. In this article, we generalize to the multidimensional case, introducing the Multidimensional Two-Parameter Conway–Maxwell–Poisson Model (M2PCMPM). Using the expectation-maximization (EM) algorithm, we develop marginal maximum likelihood estimation methods, primarily for exploratory M2PCMPMs. The resulting discrimination matrices are rotationally indeterminate. Recently, regularization of the discrimination matrix has been used to obtain a simple structure (i.e., a sparse solution) for dichotomous and polytomous data. For count data, we also (1) rotate or (2) regularize the discrimination matrix. We develop an EM algorithm with lasso (

$\ell _1$

) regularization for the M2PCMPM and compare (1) and (2) in a simulation study. We illustrate the proposed model with an empirical example using intelligence test data.
Identifiability of Polychoric Models with Latent Elliptical Distributions
Authors: Cheng Che , Yang Hau-Hung , Hsu Yung-Fong
Published: January 2025

The family of polychoric models (PM) categories ordinal data with latent multivariate normal variables. This modeling framework is commonly used to study the association between ordinal variables, often leading to a polychoric correlation model (PCM). Moreover, PM subsumes several well-known psychometric models, such as the structural equation modeling (SEM) with ordinal data. That said, the identifiability of PM has not been addressed in the literature. Meanwhile, in recent years researchers have suggested that the latent variables underlying PM could be generalized to the family of elliptical distributions, such as the multivariate logistic and t distributions. This article concerns the identifiability of PM and PCM with latent elliptical distributions, for which we show that PM is not identifiable and PCM is identifiable. In particular, we prove the identifiability of the polychoric t correlation model based on the copula representation. We then move on to find the set of identifiability constraints of PM through an “equivalence-classes approach of identifiability,” and demonstrate its use in two applications: one concerns the identifiability of PM on Likert scales and on comparative judgment, and the other concerns the identifiability of ordinal SEM and item factor analysis. Possible implications induced by these identifiability constraints are discussed.
The Sum Score Model: Specifying and Testing Equally Weighted Composites Using Structural Equation Modeling
Authors: Schuberth Florian , Schamberger Tamara , Kemény Ildikó , Henseler Jörg
Published: January 2025

In principle, structural equation modeling (SEM) is capable of emulating all approaches based on the general linear model. Yet, modeling sum scores in a structural equation model is not straightforward. Existing approaches to studying sum scores in a structural equation model are limited in terms either of model specification or of model assessment. This paper introduces a specification to SEM that allows for directly modeling sum scores and that overcomes existing approaches’ limitations in dealing with sum scores in the SEM context. The sum score model we present builds on the recently proposed refined Henseler–Ogasawara (H–O) specification of composites. It allows us to estimate models with sum scores in an integrative way. It can mimic the results of existing approaches and provides a means of assessing whether a sum score fully transmits the effects of or on the variables that make up the sum score. In addition, it allows for taking into account random measurement error in the variables that form the sum score. Consequently, this model specification offers researchers an improved way of judging and defending the use of sum scores empirically and conceptually.
Assumptions and Properties of Two-Level Nonparametric Item Response Theory Models
Authors: Koopman Letty , Zijlstra Bonne J. H. , van der Ark L. Andries
Published: January 2025

Nonparametric item response theory (IRT) models consist of assumptions that restrict the joint item-score distribution. These assumptions imply stochastic ordering properties that allow ordering of respondents and items using the simple sum score and item mean score, respectively, and imply observable data properties that are useful for investigating model fit. In this paper, we investigate these properties for two-level nonparametric IRT. We introduce four two-level nonparametric IRT models. Two models pertain to respondents nested in groups: The MHM-1, useful for ordering respondents and groups, and the DMM-1, useful for ordering respondents, groups, and items. Two models pertain to groups rated by multiple respondents: The MHM-2, useful for ordering groups, and the DMM-2, useful for ordering groups and items. We define the model assumptions, derive implied stochastic ordering properties, and derive observable data properties that are useful for model fit investigation. Relations between models and properties are also presented.
Robust approximate constraint following control design for collaborative robots system and experimental validation
Authors: Liu Haohua , Zhen Shengchao , Liu Xiaoli , Zheng Hongmei , Gao Liansheng , Chen Ye-Hwa
Published: January 2025

The paper presents a novel control method aimed at enhancing the trajectory tracking accuracy of two-link mechanical systems, particularly nonlinear systems that incorporate uncertainties such as time-varying parameters and external disturbances. Leveraging the Udwadia–Kalaba equation, the algorithm employs the desired system trajectory as a servo constraint. First, the system’s constraints to construct its dynamic equation and apply generalized constraints from the constraint equation to an unconstrained system. Second, we design a robust approximate constraint tracking controller for manipulator control and establish its stability using Lyapunov’s law. Finally, we numerically simulate and experimentally validate the controller on a collaborative platform using model-based design methods.
Gender representation in undergraduate music technology education: case studies from Aotearoa/New Zealand
Authors: Hoad Catherine , Johnson Henry , Rogerson-Berry Megan , Wilson Oli , Ellery Josh
Published: January 2025

This article explores the relationship between gender inequities in undergraduate music technology education and the widespread imbalances that permeate the professional music technology workforce. We present evidence concerning the relationship between tertiary training and industry outcomes by focusing on three music technology degree-level offerings in Aotearoa/New Zealand. In doing so, we critically examine the ways in which higher education in Aotearoa/New Zealand may be seen to perpetuate international trends concerning the underrepresentation of women in music technology fields. Firstly, the article offers an overview of extant scholarship on gender and music technology training. From here, it examines national data on music enrolments that show gender imbalances across music degrees. It then analyses three music technology degree-level offerings in Aotearoa as case studies. These reveal how gender inequities are amplified in areas relating to music technology. Datasets are then considered in relation to gender representation within the music industry in Aotearoa. The article concludes by offering reflections on key areas for interventions and avenues for further research.
Neural Voices of Patients with Severe Brain Injury?
Authors: Owen Matthew , Hight Darren , Hudetz Anthony G.
Published: January 2025

Studies have shown that some covertly conscious brain-injured patients, who are behaviorally unresponsive, can reply to simple questions via neuronal responses. Given the possibility of such neuronal responses, Andrew Peterson et al. have argued that there is warrant for some covertly conscious patients being included in low-stakes medical decisions using neuronal responses, which could protect and enhance their autonomy. The justification for giving credence to alleged neuronal responses must be analyzed from various perspectives, including neurology, bioethics, law, and as we suggest, philosophy of mind. In this article, we analyze the warrant for giving credence to neuronal responses from two different views in philosophy of mind. We consider how nonreductive physicalism’s causal exclusion problem elicits doubt about interpreting neural activity as indicating a conscious response. By contrast, such an interpretation is supported by the mind-body powers model of neural correlates of consciousness inspired by hylomorphism.
Ethical Considerations and Implications of Multi-Cancer Early Detection Screening: Reliability, Access and Cost to Test and Treat
Authors: Sempere Lorenzo F.
Published: January 2025

This essay focuses on the ethical considerations and implications of providing a universal multi-cancer screening test as the best approach to reduce societal cancer burden in a society with limited funds, resources, and infrastructure. With 1.9 million cancer diagnoses each year in the United States, with 86% of all cancers diagnosed in individuals over the age of 50, and with screening tools approved for only four cancer types (breast, cervical, colorectal, and lung cancer), it seems that a multi-cancer screening test to detect most cancer early that is easy to administer, and is accurate and cost-effective, would be worth considering. Whole-body magnetic resonance imaging and a multi-marker blood test are the two main technologies that we will discuss as a universal screening test. However, to understand and appreciate the societal and clinical breakthrough of such a screening test, we must first consider the accessibility and efficacy of current screening methods. We conclude with a closer examination of the ethical implications of implementing the Galleri test as a multi-cancer detection screening tool as adamantly advocated by the company that developed this blood-based test.
Contiguous Xp21 deletion involving Duchenne muscular dystrophy and McLeod neuroacanthocytosis syndrome results in rapidly progressive and fatal cardiomyopathy
Authors: Blackstone William Z. , Malaguit Seth E. , Shwaish Natalie S. , Frandsen Erik L.
Published: January 2025

Dilated cardiomyopathy is an expected manifestation and common cause of death in patients with Duchenne muscular dystrophy. We present an unusually rapid progression of cardiomyopathy in a boy with Duchenne muscular dystrophy. Expanded genetic testing revealed a contiguous Xp21 deletion involving dystrophin and XK genes, responsible for Duchenne muscular dystrophy and McLeod neuroacanthocytosis syndrome, respectively, resulting in a more severe cardiac phenotype.
The Interpretation of Karakoram Anomaly by High Karakoram Ice Core Record
Authors: Wang Jiajia , Xu Baiqing , Li Zhen , Nasir Jawad , Farhan Suhaib Bin , Wang Mo , Xie Ying , Yang Song , Cauquoin Alexandre , Hussain Azfar
Published: January 2025

Glacier mass in the Karakoram region has increased since the mid‐1990s in contrast to Himalayan glaciers. The scarcity and brevity of observations, including in situ observations and weather station data, limit our understanding of the Karakoram anomaly. Here, we present the stable water isotopes and snow accumulation records of Karakoram's first shallow ice core, covering 1998 to 2018. The decreased δ18O suggests an overall cooling trend in the Karakoram region for the early 21st century. In contrast, snow accumulation shows a significant increasing trend, which reveals that the Karakoram glacier has been getting more and more precipitation supplies recently. Using correlation field analysis and a backward trajectory model, we find that the decreased temperature and increased precipitation in the Karakoram are related to weakening westerlies. The northward shift of westerlies will transport colder water vapor from the North Atlantic to Karakoram, decreasing temperature and increasing precipitation in Karakoram. Our results indicated a trend of temperature cooling and precipitation increase trend in the Karakoram related to the weakened westerlies and the North Atlantic, which might explain the Karakoram anomaly that occurred in the Pamir‐Karakoram‐Kunlun region under the present climate change background. These results can provide new insights for predicting the changes in glacier mass in Karakoram and evaluating the variations in Asian water towers.
Enhancing Urban Thermal Environment and Energy Sustainability With Temperature‐Adaptive Radiative Roofs
Authors: Zhang Keer , Zhao Lei , Oleson Keith , Li Xinchang “Cathy” , Lee Xuhui
Published: January 2025

Urban overheating presents significant challenges to public health and energy sustainability. Conventional radiative cooling strategies, such as cool roofs with high albedo, lead to undesired winter cooling and increased space heating demand for cities with cold winters, a phenomenon known as heating energy penalty. A novel roof coating with high albedo and temperature‐adaptive emissivity (TAE)—low emissivity during cold conditions and high emissivity during hot conditions—has the potential to mitigate winter heating energy penalty. In this study, we implement this roof coating in a global climate model to evaluate its impact on air temperature and building energy demand for space heating and cooling in global cities. Adopting roofs with TAE increases global urban air temperature by up to +0.54°C in the winter (99th percentile; mean change +0.16°C) but has negligible effects on summer urban air temperature (mean change +0.05°C). Combining TAE with high albedo effectively provides summer cooling and does not increase building energy demand in the winter, particularly for mid‐latitude cities. Sensitivities of air temperature to changes in emissivity and albedo are associated with local “apparent” net longwave radiation and incoming solar radiation, respectively. We propose a simple parameterization of air temperature responses to emissivity and albedo to facilitate the development of city‐specific radiative mitigation strategies. This study emphasizes the necessity of developing mitigation approaches specific to local cloudiness.
Heat and Drought Events Alter Biogenic Capacity to Balance CO2 Budget in South‐Western Europe
Authors: Segura‐Barrero R. , Lauvaux T. , Lian J. , Ciais P. , Badia A. , Ventura S. , Bazzi H. , Abbessi E. , Fu Z. , Xiao J. , Li X. , Villalba G.
Published: January 2025

Heat and drought events are increasing in frequency and intensity, posing significant risks to natural and agricultural ecosystems with uncertain effects on the net ecosystem CO2 exchange (NEE). The current Vegetation Photosynthesis and Respiration Model (VPRM) was adjusted to include soil moisture impacts on the gross ecosystem exchange (GEE) and respiration (RECO) fluxes to assess the temporal variability of NEE over south‐western Europe for 2001–2022. Warming temperatures lengthen growing seasons, causing an increase in GEE, which is mostly compensated by a similar increment in RECO. As a result, there is a modest increase in the net carbon sink of 0.69 gC m−2 yr−1 but with high spatial and annual variability. The heatwave of 2022 reduced net carbon uptake by 91.7 TgC, a 26.4% decrease from the mean. The interannual variability of NEE is more influenced by drought in temperate humid regions than in Mediterranean semi‐arid regions. These results emphasize the vulnerability of the net carbon sink as drying trends could revert the NEE trends, as it is happening for croplands in the French Central Massif.
An Investigation Into Far‐Flank Magnetic Reconnection at Earth's Magnetopause
Authors: Sullivan K. M. , Fuselier S. A. , Trattner K. J. , Petrinec S. M. , Burch J. L. , Gershman D. J.
Published: January 2025

Magnetospheric Multiscale (MMS) observations have revealed that reconnection occurs along the flanks of Earth's magnetopause, near and past the terminator when the interplanetary magnetic field is southward. However, the question remains how common this reconnection is. Previous research has indicated that reconnection may be suppressed in the far‐flank regions due to the high velocity shear between the plasma in the magnetosheath and the plasma in the magnetosphere. This study investigates far‐flank reconnection by looking for evidence of reconnection in crossings of the far‐flank magnetopause. Forty‐one magnetopause crossing events were found that satisfied certain criteria and 35 of these events showed identifiable signs of reconnection. Based on these findings, reconnection is not suppressed along the magnetospheric flanks due to the velocity shear during southward IMF.
Barotropic Trends Through the Barents Sea Opening for the Period 1975–2021
Authors: Jahanmard Vahidreza , Löptien Ulrike , Sandø Anne Britt , Gierisch Andrea M. U. , Dietze Heiner , Lien Vidar , Delpeche‐Ellmann Nicole , Hordoir Robinson
Published: January 2025

We analyze the output of a regional ocean model that comprises the North Atlantic and the Arctic Ocean for the period 1975–2021. We focus on the flow through the cross sections closing the Nordic Sea basin. The simulated flow at Barents Sea Opening (BSO) shows a clear positive trend. To understand the origin of this trend, we reconstruct the BSO flow based on wind time series over the Nordic Seas using deep learning. To explore potential links between the results from this reconstruction and the major atmospheric modes, we perform a suite of idealized experiments where the ocean model is forced with wind field anomalies that refer to known changes in the leading modes of atmospheric circulation over the North Atlantic and Arctic Oceans. Known changes in the major atmospheric wind patterns over the North Atlantic have a weak impact on the simulated BSO flow, and the sign is not consistent with the overall trend of the full simulation. The latter holds as well for the known temporal changes in the intensity of the Arctic dipole mode. The weak temporal changes in the Arctic oscillation are consistent with the trend in the BSO flow but could not explain its amplitude. Ultimately, we could not establish a clear link between the BSO flow trend and changes in the major atmospheric modes. We conclude that the atmospheric pattern responsible for the BSO flow trend does not project directly on the leading modes of atmospheric variability over the North Atlantic and the Arctic.
Modeling Spatial Distributions of Salt Marsh Blue Carbon Using Morphometric Parameters From Lidar
Authors: Turek B. , Teng W. , Yu Q. , Yellen B. , Woodruff J.
Published: January 2025

Salt marshes sequester large amounts of carbon, mainly within their deep soils. Several nationwide assessments have indicated that spatial variability of marsh soil carbon is minimal, however there's a need to further reduce carbon stock uncertainties by exploring finer‐scale variation using a process‐based modeling approach. Marsh soil properties vary spatially with several parameters, including marsh platform elevation, which controls inundation depth, and proximity to the marsh edge and tidal creek network, which control variability in relative sediment supply. We used lidar to extract these morphometric parameters from salt marshes to map soil organic carbon across a marsh at the meter scale. Soil samples were collected in 2021 from four northeast U.S. salts marshes with distinctive geomorphologies. Tidal creeks were delineated from 1‐m resolution topobathy lidar data using a semi‐automated workflow in GIS. Log‐linear multivariate regression models were developed to predict soil organic matter, bulk density, and carbon density as a function of predictive metrics at each site and across sites. Distance from tidal creeks was the most significant model predictor. Modeling marsh soil characteristics worked best in marshes with single channel hydrology. Addition of distance to the inlet and tidal range as regional metrics significantly improved cross‐site modeling. Our mechanistic approach reveals important meter‐level variation in soil characteristics across a marsh and provides motivation to continue rigorous mapping of soil carbon at fine spatial resolutions. Furthermore, carbon density values used to calculate total marsh carbon stocks should be carefully selected depending on project scale, marsh geomorphology, and desired accuracy.
Real‐Time Flood Inundation Modeling With Flow Resistance Parameter Learning
Authors: Young Alexander , Albertson John D. , Moretti Giovanni , Orlandini Stefano
Published: January 2025

Emergency response to flood plain inundations requires real‐time forecasts of flow depth, velocity, and arrival time. Detailed and rapid flood inundation forecasts can be obtained from numerical solution of 2D unsteady flow equations based on high‐resolution topographic data and geomorphologically informed unstructured meshes. However, flow resistance parameters representing the effects of land surface topography unresolved by digital terrain model data remain uncertain. In the present study, flow resistance parameters representing the effects of roughness, vegetation, and buildings are determined hydraulically in real‐time using flow depth observations. A detailed numerical reproduction of a real flood has been largely corroborated by observations and subsequently used as a surrogate of the ground truth target. In synthetic numerical experiments, flow depth observations are obtained from a network of in‐situ flow depth sensors assigned to hydraulically relevant locations in the flood plain. Starting from a generic resistance parameter set, the capability of a tandem 2D surface flow model and Bayesian optimization technique to achieve convergence to the target resistance parameter set is tested. Convergence to the target resistance parameter set was obtained with 50 or fewer tandem flow + optimization iterations for each forecasting cycle in which the difference between simulated and observed flow depths is minimized. The flood arrival time errors across a 52  flood plain inundation area were reduced by 3.13 hr with respect to results obtained without optimization from a fixed range of flow resistance parameters. Performance metrics like critical success index and probability of detection reach values above 90% across the flood plain.
Magmatic Fluids and Melts May Lie Beneath Dormant German Volcanoes
Authors: Stanley Sarah
Published: January 2025

New processing strategies applied to old seismic data reveal potential pockets of magmatic fluids or melts from the upper mantle.
Exposure to childhood maltreatment is associated with specific epigenetic patterns in sperm
Authors: Tuulari Jetro J. , Bourgery Matthieu , Iversen Jo , Koefoed Thomas Gade , Ahonen Annukka , Ahmedani Ammar , Kataja Eeva-Leena , Karlsson Linnea , Barrès Romain , Karlsson Hasse , Kotaja Noora
Published: January 2025

Childhood maltreatment exposure (CME) increases the risk of adverse long-term health consequences for the exposed individual. Animal studies suggest that CME may also influence the health and behaviour in the next generation offspring through CME-driven epigenetic changes in the germ line. Here we investigated the associated between early life stress on the epigenome of sperm in humans with history of CME. We measured paternal CME using the Trauma and Distress Scale (TADS) questionnaire and mapped sperm-borne sncRNAs expression by small RNA sequencing (small RNA-seq) and DNA methylation (DNAme) in spermatozoa by reduced-representation bisulfite sequencing (RRBS-seq) in males from the FinnBrain Birth Cohort Study. The study design was a (nested) case-control study, high-TADS (TADS ≥ 39, n = 25 for DNAme and n = 14 for small RNA-seq) and low-TADS (TADS ≤ 10, n = 30 for DNAme and n = 16 for small RNA-seq). We identified 3 genomic regions with differential methylation between low and high-TADS and 68 tRNA-derived small RNAs (tsRNAs) and miRNAs with different levels in males with high CME (False discovery rate, FDR corrected p < 0.05). Of potential interest, we identified differential expression of miRNA hsa-mir-34c-5p and differential methylation levels near the CRTC1 and GBX2 genes, which are documented to control brain development. Our results provide further evidence that early life stress influences the paternal germline epigenome and supports a possible effect in modulating the development of the central nervous system of the next generation.
Dynamic tracking of objects in the macaque dorsomedial frontal cortex
Authors: Rajalingham Rishi , Sohn Hansem , Jazayeri Mehrdad
Published: January 2025

A central tenet of cognitive neuroscience is that humans build an internal model of the external world and use mental simulation of the model to perform physical inferences. Decades of human experiments have shown that behaviors in many physical reasoning tasks are consistent with predictions from the mental simulation theory. However, evidence for the defining feature of mental simulation – that neural population dynamics reflect simulations of physical states in the environment – is limited. We test the mental simulation hypothesis by combining a naturalistic ball-interception task, large-scale electrophysiology in non-human primates, and recurrent neural network modeling. We find that neurons in the monkeys’ dorsomedial frontal cortex (DMFC) represent task-relevant information about the ball position in a multiplexed fashion. At a population level, the activity pattern in DMFC comprises a low-dimensional neural embedding that tracks the ball both when it is visible and invisible, serving as a neural substrate for mental simulation. A systematic comparison of different classes of task-optimized RNN models with the DMFC data provides further evidence supporting the mental simulation hypothesis. Our findings provide evidence that neural dynamics in the frontal cortex are consistent with internal simulation of external states in the environment.
Tuning the selectivity of NH3 oxidation via cooperative electronic interactions between platinum and copper sites
Authors: Chen Lu , Guan Xuze , Fei Zhaofu , Asakura Hiroyuki , Zhang Lun , Wang Zhipeng , Su Xinlian , Yao Zhangyi , Keenan Luke L. , Hayama Shusaku , van Spronsen Matthijs A. , Karagoz Burcu , Held Georg , Allen Christopher S. , Hopkinson David G. , Decarolis Donato , Callison June , Dyson Paul J. , Wang Feng Ryan
Published: January 2025

Selective catalytic oxidation (SCO) of NH3 to N2 is one of the most effective methods used to eliminate NH3 emissions. However, achieving high conversion over a wide operating temperature range while avoiding over-oxidation to NOx remains a significant challenge. Here, we report a bi-metallic surficial catalyst (PtSCuO/Al2O3) with improved Pt atom efficiency that overcomes the limitations of current catalysts. It achieves full NH3 conversion at 250 °C with a weight hourly space velocity of 600 ml NH3·h−1·g−1, which is 50 °C lower than commercial Pt/Al2O3, and maintains high N2 selectivity through a wide temperature window. Operando XAFS studies reveal that the surface Pt atoms in PtSCuO/Al2O3 enhance the redox properties of the Cu species, thus accelerating the Cu2+ reduction rate and improving the rate of the NH3-SCO reaction. Moreover, a synergistic effect between Pt and Cu sites in PtSCuO/Al2O3 contributes to the high selectivity by facilitating internal selective catalytic reduction.
Robust proteome profiling of cysteine-reactive fragments using label-free chemoproteomics
Authors: Biggs George S. , Cawood Emma E. , Vuorinen Aini , McCarthy William J. , Wilders Harry , Riziotis Ioannis G. , van der Zouwen Antonie J. , Pettinger Jonathan , Nightingale Luke , Chen Peiling , Powell Andrew J. , House David , Boulton Simon J. , Skehel J. Mark , Rittinger Katrin , Bush Jacob T.
Published: January 2025

Identifying pharmacological probes for human proteins represents a key opportunity to accelerate the discovery of new therapeutics. High-content screening approaches to expand the ligandable proteome offer the potential to expedite the discovery of novel chemical probes to study protein function. Screening libraries of reactive fragments by chemoproteomics offers a compelling approach to ligand discovery, however, optimising sample throughput, proteomic depth, and data reproducibility remains a key challenge. We report a versatile, label-free quantification proteomics platform for competitive profiling of cysteine-reactive fragments against the native proteome. This high-throughput platform combines SP4 plate-based sample preparation with rapid chromatographic gradients. Data-independent acquisition performed on a Bruker timsTOF Pro 2 consistently identified ~23,000 cysteine sites per run, with a total of ~32,000 cysteine sites profiled in HEK293T and Jurkat lysate. Crucially, this depth in cysteinome coverage is met with high data completeness, enabling robust identification of liganded proteins. In this study, 80 reactive fragments were screened in two cell lines identifying >400 ligand-protein interactions. Hits were validated through concentration-response experiments and the platform was utilised for hit expansion and live cell experiments. This label-free platform represents a significant step forward in high-throughput proteomics to evaluate ligandability of cysteines across the human proteome.
Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function
Authors: Valo Erkka , Richmond Anne , Mutter Stefan , Dahlström Emma H. , Campbell Archie , Porteous David J. , Wilson James F. ,   FinnDiane Study Group, Mutter Stefan , Groop Per-Henrik , Hayward Caroline , Sandholm Niina
Published: January 2025

Dissecting the genetic mechanisms underlying urinary metabolite concentrations can provide molecular insights into kidney function and open possibilities for causal assessment of urinary metabolites with risk factors and disease outcomes. Proton nuclear magnetic resonance metabolomics provides a high-throughput means for urinary metabolite profiling, as widely applied for blood biomarker studies. Here we report a genome-wide association study meta-analysed for 3 European cohorts comprising 8,011 individuals, covering both people with type 1 diabetes and general population settings. We identify 54 associations (p < 9.3 × 10−10) for 19 of 54 studied metabolite concentrations. Out of these, 33 were not reported previously for relevant urinary or blood metabolite traits. Subsequent two-sample Mendelian randomization analysis suggests that estimated glomerular filtration rate causally affects 13 urinary metabolite concentrations whereas urinary ethanolamine, an initial precursor for phosphatidylcholine and phosphatidylethanolamine, was associated with higher eGFR lending support for a potential protective role. Our study provides a catalogue of genetic associations for 53 metabolites, enabling further investigation on how urinary metabolites are linked to human health.
Degradation bottlenecks and resource competition in transiently and stably engineered mammalian cells
Authors: Gabrielli Jacopo , Di Blasi Roberto , Kontoravdi Cleo , Ceroni Francesca
Published: January 2025

Degradation tags, otherwise known as degrons, are portable sequences that can be used to alter protein stability. Here, we report that degron-tagged proteins compete for cellular degradation resources in engineered mammalian cells leading to coupling of the degradation rates of otherwise independently expressed proteins when constitutively targeted human degrons are adopted. We show the effect of this competition to be dependent on the context of the degrons. By considering different proteins, degron position and cellular hosts, we highlight how the impact of the degron on both degradation strength and resource coupling changes, with identification of orthogonal combinations. By adopting inducible bacterial and plant degrons we also highlight how controlled uncoupling of synthetic construct degradation from the native machinery can be achieved. We then build a genomically integrated capacity monitor tagged with different degrons and confirm resource competition between genomic and transiently expressed DNA constructs. This work expands the characterisation of resource competition in engineered mammalian cells to protein degradation also including integrated systems, providing a framework for the optimisation of heterologous expression systems to advance applications in fundamental and applied biological research.
The global RNA-binding protein RbpB is a regulator of polysaccharide utilization in Bacteroides thetaiotaomicron
Authors: Rüttiger Ann-Sophie , Ryan Daniel , Spiga Luisella , Lamm-Schmidt Vanessa , Prezza Gianluca , Reichardt Sarah , Langford Madison , Barquist Lars , Faber Franziska , Zhu Wenhan , Westermann Alexander J.
Published: January 2025

Paramount 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.
A Y chromosome-linked genome editor for efficient population suppression in the malaria vector Anopheles gambiae
Authors: Tolosana Ignacio , Willis Katie , Gribble Matthew , Phillimore Lee , Burt Austin , Nolan Tony , Crisanti Andrea , Bernardini Federica
Published: January 2025

Genetic control – the deliberate introduction of genetic traits to control a pest or vector population – offers a powerful tool to augment conventional mosquito control tools that have been successful in reducing malaria burden but that are compromised by a range of operational challenges. Self-sustaining genetic control strategies have shown great potential in laboratory settings, but hesitancy due to their invasive and persistent nature may delay their implementation. Here, instead, we describe a self-limiting strategy, designed to have geographically and temporally restricted effect, based on a Y chromosome-linked genome editor (YLE). The YLE comprises a CRISPR-Cas9 construct that is always inherited by males yet generates an autosomal dominant mutation that is transmitted to over 90% of the offspring and results in female-specific sterility. To our knowledge, our system represents a pioneering approach in the engineering of the Y chromosome to generate a genetic control strain for mosquitoes. Mathematical modelling shows that this YLE technology is up to seven times more efficient for population suppression than optimal versions of other self-limiting strategies, such as the widely used Sterile Insect Technique or the Release of Insects carrying a Dominant Lethal gene.
Effects of seven days’ fasting on physical performance and metabolic adaptation during exercise in humans
Authors: Kolnes Kristoffer J. , Nilsen Emelie T. F. , Brufladt Steffen , Meadows Allison M. , Jeppesen Per B. , Skattebo Øyvind , Johansen Egil I. , Birk Jesper B. , Højlund Kurt , Hingst Janne , Skålhegg Bjørn S. , Kjøbsted Rasmus , Griffin Julian L. , Kolnes Anders J. , O’Rahilly Stephen , Wojtaszewski Jørgen F. P. , Jensen Jørgen
Published: January 2025

Humans have, throughout history, faced periods of starvation necessitating increased physical effort to gather food. To explore adaptations in muscle function, 13 participants (7 males and 6 females) fasted for seven days. They lost 4.6 ± 0.3 kg lean and 1.4 ± 0.1 kg fat mass. Maximal isometric and isokinetic strength remained unchanged, while peak oxygen uptake decreased by 13%. Muscle glycogen was halved, while expression of electron transport chain proteins was unchanged. Pyruvate dehydrogenase kinase 4 (PDK4) expression increased 13-fold, accompanied by inhibitory pyruvate dehydrogenase phosphorylation, reduced carbohydrate oxidation and decreased exercise endurance capacity. Fasting had no impact on 5’ AMP-activated protein kinase (AMPK) activity, challenging its proposed role in muscle protein degradation. The participants maintained muscle strength and oxidative enzymes in skeletal muscle during fasting but carbohydrate oxidation and high-intensity endurance capacity were reduced.
Carbon nitride caught in the act of artificial photosynthesis
Authors: Cruz Daniel , Żółtowska Sonia , Savateev Oleksandr , Antonietti Markus , Giusto Paolo
Published: January 2025

Covalent semiconductors of the carbon nitride family are among the most promising systems to realize “artificial photosynthesis”, that is exploiting synthetic materials which use sunlight as an energy source to split water into its elements or converting CO2 into added value chemicals. However, the role of surface interactions and electronic properties on the reaction mechanism remain still elusive. Here, we use in-situ spectroscopic techniques that enable monitoring surface interactions in carbon nitride under artificial photosynthetic conditions. We show that the water adsorption and light illumination cause changes of the surface electron density, which activate the photocatalyst and enable the water splitting process. Our results reveal critical details on the photocatalytic mechanism, which proceeds through proton-coupled electron transfer, and provide key information to design more efficient photocatalyst for artificial photosynthesis.
In vivo spontaneous Ca2+ activity in the pre-hearing mammalian cochlea
Authors: De Faveri Francesca , Ceriani Federico , Marcotti Walter
Published: January 2025

The refinement of neural circuits towards mature function is driven during development by patterned spontaneous calcium-dependent electrical activity. In the auditory system, this sensory-independent activity arises in the pre-hearing cochlea and regulates the survival and refinement of the auditory pathway. However, the origin and interplay of calcium signals during cochlear development is unknown in vivo. Here we show how calcium dynamics in the cochlear neuroepithelium of live pre-hearing mice shape the activity of the inner hair cells (IHCs) and their afferent synapses. Both IHCs and supporting cells (SCs) generate spontaneous calcium-dependent activity. Calcium waves from SCs synchronise the activity of nearby IHCs, which then spreads longitudinally recruiting several additional IHCs via a calcium wave-independent mechanism. This synchronised IHC activity in vivo increases the probability of afferent terminal recruitment. Moreover, the modiolar-to-pillar segregation in sound sensitivity of mature auditory nerve fibres appears to be primed at pre-hearing ages.