bluuebunny/crossref_metadata_2025 huggingface dataset:
Personality changes during adolescence predict young adult psychosis proneness and mediate gene–environment interplays of schizophrenia risk
Authors: Antonucci Linda A. , Raio Alessandra , Kikidis Gianluca Christos , Bertolino Alessandro , Rampino Antonio , Banaschewski Tobias , Bokde Arun L.W. , Desrivières Sylvane , Flor Herta , Grigis Antoine , Garavan Hugh , Heinz Andreas , Martinot Jean-Luc , Paillère Martinot Marie-Laure , Artiges Eric , Nees Frauke , Papadopoulos Orfanos Dimitri , Poustka Luise , Hohmann Sarah , Fröhner Juliane H. , Smolka Michael N. , Vaidya Nilakshi , Walter Henrik , Whelan Robert , Schumann Gunter , Hartman Catharina A. , Pergola Giulio ,   the IMAGEN Consortium
Published: October 2024

Background

Psychotic symptoms in adolescence are associated with social adversity and genetic risk for schizophrenia. This gene–environment interplay may be mediated by personality, which also develops during adolescence. We hypothesized that (i) personality development predicts later Psychosis Proneness Signs (PPS), and (ii) personality traits mediate the association between genetic risk for schizophrenia, social adversities, and psychosis.

Methods

A total of 784 individuals were selected within the IMAGEN cohort (Discovery Sample-DS: 526; Validation Sample-VS: 258); personality was assessed at baseline (13–15 years), follow-up-1 (FU1, 16–17 years), and FU2 (18–20 years). Latent growth curve models served to compute coefficients of individual change across 14 personality variables. A support vector machine algorithm employed these coefficients to predict PPS at FU3 (21–24 years). We computed mediation analyses, including personality-based predictions and self-reported bullying victimization as serial mediators along the pathway between polygenic risk score (PRS) for schizophrenia and FU3 PPS. We replicated the main findings also on 1132 adolescents recruited within the TRAILS cohort.

Results

Growth scores in neuroticism and openness predicted PPS with 65.6% balanced accuracy in the DS, and 69.5% in the VS Mediations revealed a significant positive direct effect of PRS on PPS (confidence interval [CI] 0.01–0.15), and an indirect effect, serially mediated by personality-based predictions and victimization (CI 0.006–0.01), replicated in the TRAILS cohort (CI 0.0004–0.004).

Conclusions

Adolescent personality changes may predate future experiences associated with psychosis susceptibility. PPS personality-based predictions mediate the relationship between PRS and victimization toward adult PPS, suggesting that gene–environment correlations proposed for psychosis are partly mediated by personality.
Indicting the Athenians in the Melian dialogue
Authors: James Jesse
Published: October 2024

It is widely agreed that Thucydides’ Melian dialogue presents the Athenian invasion of Melos, and the Athenian justification, in a negative light. Attention tends to focus on the immorality of ‘the rule of the stronger’ that the Athenians present in the dialogue. This essay argues that another feature of the dialogue triggering negative judgements of the Athenians is their criticism of the Melians’ resistance: it is voiced by the Athenians themselves and therefore provokes in readers a ‘speaker-relative’ normative judgement of the Athenians. Philosophers have explored how our normative judgements about statements often depend on the speaker. Because the Athenians have deliberately put the Melians into their perilous situation, and because part of Athenian self-mythology was heroic resistance against overwhelming numbers in the Persian Wars, Athenian criticism of the Melians is hypocritical and applies an asymmetrical ethics to the Athenians and the Melians. Reaction against these features of the dialogue exacerbates the moral abhorrence of the Athenians felt by many readers. Hence I disagree with Bosworth’s view of the dialogue as primarily critical of the Melians. Instead we see Thucydides here condemning not only the Athenian imperial project but also the rhetoric used to defend and sustain it.
Resource-rational contractualism: A triple theory of moral cognition
Authors: Levine Sydney , Chater Nick , Tenenbaum Joshua B. , Cushman Fiery
Published: October 2024

It is widely agreed upon that morality guides people with conflicting interests towards agreements of mutual benefit. We therefore might expect numerous proposals for organizing human moral cognition around the logic of bargaining, negotiation, and agreement. Yet, while “contractualist” ideas play an important role in moral philosophy, they are starkly underrepresented in the field of moral psychology. From a contractualist perspective, ideal moral judgments are those that would be agreed to by rational bargaining agents—an idea with wide-spread support in philosophy, psychology, economics, biology, and cultural evolution. As a practical matter, however, investing time and effort in negotiating every interpersonal interaction is unfeasible. Instead, we propose, people use abstractions and heuristics to efficiently identify mutually beneficial arrangements. We argue that many well-studied elements of our moral minds, such as reasoning about others’ utilities (“consequentialist” reasoning) or evaluating intrinsic ethical properties of certain actions (“deontological” reasoning), can be naturally understood as resource-rational approximations of a contractualist ideal. Moreover, this view explains the flexibility of our moral minds—how our moral rules and standards get created, updated and overridden and how we deal with novel cases we have never seen before. Thus, the apparently fragmentary nature of our moral psychology—commonly described in terms of systems in conflict—can be largely unified around the principle of finding mutually beneficial agreements under resource constraint. Our resulting “triple theory” of moral cognition naturally integrates contractualist, consequentialist and deontological concerns.
Two tiers, not one: Different sources of extrinsic mortality have opposing effects on life history traits
Authors: Ellis Bruce J. , Reid Brie M. , Kramer Karen L.
Published: October 2024

Guided by concepts from life history (LH) theory, a large human research literature has tested the hypothesis that exposures to extrinsic mortality (EM) promote the development of faster LH strategies (e.g., earlier/faster reproduction, higher offspring number). A competing model proposes that, because EM in the past was intimately linked to energetic constraints, such exposures specifically led to the development of slower LH strategies. We empirically address this debate by examining (1) LH variation among small-scale societies under different environmental conditions; (2) country-, regional- and community-level correlations between ecological conditions, mortality, maturational timing, and fertility; (3) individual-level correlations between this same set of factors; and (4) natural experiments leveraging the impact of externally-caused changes in mortality on LH traits. Partially supporting each model, we found that harsh conditions encompassing energetic stress and ambient cues to EM (external cues received through sensory systems) have countervailing effects on the development of LH strategies, both delaying pubertal maturation and promoting an accelerated pace of reproduction and higher offspring number. We conclude that, although energetics are fundamental to many developmental processes, providing a first tier of environmental influence, this first tier alone cannot explain these countervailing effects. An important second tier of environmental influence is afforded by ambient cues to EM. We advance a 2-tiered model that delineates this second tier and its central role in regulating development of LH strategies. Consideration of the first and second tier together is necessary to account for the observed countervailing shifts toward both slower and faster LH traits.
Contingent Attachment: Long-term Lived Experience in the Redevelopment of a Third Front Neighbourhood
Authors: Jin Yi
Published: October 2024

Employing the concept of “contingent attachment” as its key point, this paper investigates the transformation of residents’ neighbourhood attachment during the redevelopment of a neighbourhood originally established during the Third Front construction period. By framing neighbourhood attachment as contingent, this paper seeks to highlight that the different directions of neighbourhood attachment hinge upon several factors: the entities mobilizing the narrative, the varying treatment of residents across different phases of the relocation, and residents’ perceptions regarding the changes brought about by the relocation process. Special attention within this paper is paid towards the long-term lived experiences of residents since the onset of the Third Front construction to show how these experiences are woven into diverse narratives associated with residents’ neighbourhood attachments.
Carbon pricing and household welfare: evidence from Uganda
Authors: Aggarwal Raavi , Ayhan Sinem H. , Jakob Michael , Steckel Jan Christoph
Published: October 2024

Policymakers frequently voice concerns that carbon pricing could impair economic development in the short run, especially in low-income countries such as Uganda. Using a consumer demand system for energy and food items, we assess how households’ welfare, and demand for food and energy, would respond to a carbon price of USD40/tCO2. We find welfare losses of 0.2–12 per cent of household expenditure on food and fuel, due to the carbon price. Average demand for electricity and kerosene decline by 11 and 20 per cent respectively, while firewood demand rises by 10 per cent on average. We observe shifts within food consumption baskets, with declines in the demand for meat & fish, and vegetables, alongside an increase in cereal consumption. Household nutrition is adversely impacted, with declines in protein and micronutrient intake across the population. Complementary social protection policies such as cash transfers are therefore required to ease adverse effects on economic development in Uganda.
Adoption of clean energy cooking technologies in rural households: the role of women
Authors: Tornel-Vázquez Rossana , Iglesias Eva , Loureiro Maria
Published: October 2024

Ensuring energy access for rural households is crucial for global sustainable development. Technologies like liquefied petroleum gas, biogas, and efficient cookers are touted as solutions, yet their adoption remains limited despite their potential health, economic, and environmental benefits. We conducted a meta-analysis of 50 studies in developing countries, integrating contextual factors to explore gender and other determinants impacting rural energy transition. Our findings underscore socioeconomic status, social capital, environmental concerns, and gender dynamics as pivotal factors. Notably, women's involvement boosts adoption rates by 7.90 per cent, yet cultural barriers often sideline them from these processes. Thus, our recommendations stress addressing women's roles as energy technology users to foster inclusive energy transitions.
Constraining the driving mechanism of galaxy-scale winds with emission line spectra
Authors: Stern Jonathan , Oñorbe Jose , Richings Alexander J. , Johnson Sean D. , Faucher-Giguère Claude-André
Published: October 2024

Using hydrodynamic simulations and photoionization calculations, we demonstrate that quasar emission line spectra contain information on the driving mechanism of galaxy-scale outflows. Outflows driven by a hot shocked bubble are expected to exhibit LINER-like optical line ratios, while outflows driven by radiation pressure are expected to exhibit Seyfert-like line ratios. Driving by radiation pressure also has a distinct signature in the narrow UV lines, which is detected in an HST-COS spectrum of a nearby quasar hosting a large-scale wind.
Updated Calculations of the Spectral-Line Radiation Force & Mass-Loss Rates for AGN Outflows
Authors: Lattimer Aylecia S. , Cranmer Steven
Published: October 2024

Photon-driven flows have been studied for almost a century, and a quantitative description of the radiative forces on atoms and ions is important for understanding a wide variety of systems, including active galactic nuclei (AGN). The colloquially-termed “radiation pressure” of line-driven winds plays an important role in driving outflows in these environments. Quantifying the associated forces is crucial to understanding how these flows enable interactive mechanisms within these environments, such as AGN feedback. Here we provide new calculations of the dimensionless line strength parameter due to radiation driving. For representative AGN, we calculate the photoionization balance at each step along the line of sight (LOS) to the proposed wind-launching region above the accretion disk. We then use a recently compiled database of approximately 5.6 million spectral lines to compute the strength of the line-driving force on the gas and the mass-loss rates resulting from these outflows. We also introduce a “shielding factor’’ that increases the magnitude of the accretion disk column density prior to the launch radius. This shielding factor simulates a proposed inner “failed wind” region that is thought to shield the outflowing gas from becoming over-ionized by the central source. We also revisit and formalize the role of the commonly-used ionization parameter in setting the properties of the accelerating gas.
Large-Scale Features of the CON Galaxy NGC4418 with MUSE
Authors: Wethers Clare F. , Aalto Susanne , Privon G. C. , Stanley F. , Gallagher J. , Gorski M. , König S. , Onishi K. , Yang C.
Published: October 2024

Compact obscured nuclei (CONs) are relatively common in the centers of local (U)LIRGs, yet their nature remains unknown. Both AGN activity and extreme nuclear starbursts have been suggested as plausible nuclear power sources. The prevalence of outflows in these systems suggest that CONs represent a key phase in the nuclear feedback cycle, in which material is ejected from the central regions of the galaxy. Here, we present results from MUSE for the confirmed local CON galaxy NGC4418. For the first time we spatially map the spectral features and kinematics of the galaxy in the optical, revealing several previously unknown structures. In particular, we discover a bilateral outflow along the minor axis, an outflowing bubble, several knot structures and a receding outflow partially obscured by the galactic disk. Based on the properties of these features, we conclude that the CON in NGC4418 is most likely powered by an AGN.
Photon scattering in a relativistic outflow having velocity shear: a novel mechanism of generation for high energy power-law spectra
Authors: Vyas Mukesh Kumar , Pe’er Asaf
Published: October 2024

. We show that an extragalactic jet with a velocity shear gives rise to Fermi like acceleration process for photons scattering withing the shear layers of the jet. Such photons then gain energy to produce a high energy power law. These power law spectra at high energies are frequently observed in several extragalactic objects such as Gamma Ray Bursts (GRBs). We implement the model on GRBs to show that the obtained range of the photon indices are well within their observed values. The analytic results are confirmed with numerical simulations following Monte Carlo approach.
Interpretation of IR variability of AGNs in the hollow bi-conical dust outflow model
Authors: Oknyansky Victor L. , Gaskell C. Martin
Published: October 2024

We show that, contrary to simple predictions, most AGNs show at best only a small increase of lags with increasing wavelength in the J, H, K, and L bands. We suggest that a possible cause of this near simultaneity from the near-IR to the mid-IR is that the hot dust is in a hollow bi-conical outflow of which we preferentially see the near side. In the proposed model sublimation or re-creation of dust (with some delay relative luminosity variations) along our line of sight in the hollow cone as the flux varies could be a factor in explaining the AGN changing-look phenomenon (CL). Variations in the dust obscuration can help explain changes in relationship of Hβ time delay on Luv variability. The relative wavelength independence of IR lags simplifies the use of IR lags for estimating cosmological parameters.
Effect of center-pivot and subsurface drip irrigation systems on growth and evapotranspiration of volunteer corn in corn, soybean, and sorghum
Authors: Singh Mandeep , Irmak Suat , Kukal Meetpal S. , Kumar Vipan , Lindquist John L. , Knezevic Stevan Z. , Pitla Santosh , Jhala Amit J.
Published: October 2024

Volunteer corn (Zea mays L.) is a competitive weed in corn-based cropping systems. Scientific literature does not exist about the water use of volunteer corn grown in different crops and irrigation systems. The objectives of this study were to characterize the growth and evapotranspiration (ETa) of volunteer corn in corn, soybean [Glycine max (L). Merr.], and sorghum [Sorghum bicolor (L.) Moench] under center-pivot irrigation (CPI) and subsurface drip irrigation (SDI) systems. Field experiments were conducted in south-central Nebraska in 2021 and 2022. Soil moisture sensors were installed at depths of 0 to 0.30, 0.30 to 0.60, and 0.60 to 0.90 m to track soil water balance and quantify seasonal total ETa. Corn was the most competitive, as volunteer corn had the lowest biomass, leaf area, and plant height compared with the fallow. Soybean was the least competitive with volunteer corn, as the plant height, biomass, and leaf area of volunteer corn in soybean were similar to fallow at 15, 30, 45, and 60 d after transplanting (DATr). Averaged across crop treatments, irrigation type did not affect volunteer corn growth at 15 to 45 DATr. Soil water depletion and ETa were similar across crop treatments with and without volunteer corn, as water was not a limiting factor in this study. The ETa of volunteer corn was the highest in soybean (623 mm), followed by sorghum (622 mm), and corn (617 mm) under CPI. The SDI had higher irrigation efficiency, because without affecting crop yield, it had 3%, 6%, and 8% lower ETa in soybean (605 mm), sorghum (585 mm), and corn (571 mm), respectively. Although soil water use did not differ with volunteer corn infestation, a soybean yield loss of 27% was observed, which suggests that volunteer corn may not compete for moisture under fully irrigated conditions; however, it can impact the crop yield potential due to competition for factors other than soil moisture.
Multiple-resistance evolution to ACCase inhibitors and glyphosate in sourgrass (Digitaria insularis) is attributed to diverse polymorphisms in the herbicide target sites
Authors: Moisinho Ivana Santos , Ferreira Luiz Augusto Inojosa , Krzyzaniak Fabrício , Albrecht Alfredo Junior Paiola , Albrecht Leandro Paiola , Brunharo Caio
Published: October 2024

Sourgrass [Digitaria insularis (L.) Mez ex Ekman] is considered the most troublesome weed in agronomic crops in South America. Overreliance on glyphosate has selected for resistant populations, although the resistance mechanisms remain unknown. Recently, populations were identified that exhibited multiple resistance to 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) and acetyl-CoA carboxylase (ACCase) inhibitors, posing a significant challenge due to the lack of alternative control options. This project aimed to identify the resistance patterns and levels to glyphosate and ACCase inhibitors of three suspected resistant populations (P1, P2, and P3), and elucidate the resistance mechanisms. We performed dose–response experiments with clethodim, fluazifop-P-butyl, glyphosate, and pinoxaden to identify the possibility of cross- and multiple resistance and to quantify the resistance levels. We sequenced the ACCase and EPSPS genes to test the hypothesis that target-site mutations were involved in the resistance mechanisms, given the resistance patterns observed. Our results indicated that two of the tested populations, P1 and P2, were multiple resistant to glyphosate and all ACCase-inhibitor classes, while P3 was resistant to glyphosate only. Resistance levels varied by herbicide, with resistance indices ranging from 2.7- to nearly 2,000-fold. We identified an amino acid substitution in ACCase at position 2078 (Asp-2078-Gly), homozygous for both P1 and P2, corroborating the resistance patterns observed. Interestingly, EPSPS sequencing identified multiple heterozygous DNA polymorphisms that resulted in amino acid substitutions at positions 106 (P1 and P2) or at both 102 and 106 (P3), indicating multiple evolutionary origins of glyphosate-resistance evolution. We show for the first time the genetic mechanisms of multiple resistance to glyphosate and ACCase in D. insularis, and provide a thorough discussion of the evolutionary and management implications of our work.
Interpretable Transformer Neural Network Prediction of Diverse Environmental Time Series Using Weather Forecasts
Authors: Orozco López Enrique , Kaplan David , Linhoss Anna
Published: October 2024

Transformer neural networks (TNNs) have caused a paradigm shift in deep learning domains like natural language processing, gathering immense interest due to their versatility in other fields such as time series forecasting (TSF). Most current TSF applications of TNNs use only historic observations to predict future events, ignoring information available in weather forecasts to inform better predictions, and with little attention given to the interpretability of the model's use of explanatory inputs. This work explores the potential for TNNs to perform TSF across multiple environmental variables (streamflow, stage, water temperature, and salinity) in two ecologically important regions: the Peace River watershed (Florida) and the northern Gulf of Mexico (Louisiana). The TNN was tested and its prediction uncertainty quantified for each response variable from one‐to fourteen‐day‐ahead forecasts using past observations and spatially distributed weather forecasts. A sensitivity analysis (SA) was performed on the trained TNNs' attention weights to identify the relative influence of each input variable on each response variable across prediction windows. Overall model performance ranged from good to very good (0.78 < NSE < 0.99 for all variables and forecast horizons). Through the SA, we found that the TNN was able to learn the physical patterns behind the data, adapt the use of input variables to each forecast, and increasingly use weather forecast information as prediction windows increased. The TNN's excellent performance and flexibility, along with the intuitive interpretability highlighting the logic behind the models' forecasting decision‐making process, provide evidence for the applicability of this architecture to other TSF variables and locations.
A New Efficient Approach to Model Stiff Biogeochemical Reactive Transport Scenarios Across Groundwater Systems
Authors: Bu Xiaochuang , Dai Heng , Yuan Songhu , Ye Ming , Dai Zhenxue , Reza Soltanian Mohamad , Wen Zhang , Guadagnini Alberto
Published: October 2024

Biogeochemical reactive transport models (RTMs) are key for understanding the evolution of the quality of groundwater systems and their interaction with anthropogenic activities. The inherent stiffness of these models, within which bio‐geochemical reactions and transport processes take place simultaneously across diverse time scales, poses significant computational challenges. The development of current RTMs is characterized by a tradeoff between accuracy and computational efficiency. Our study introduces a novel approach grounded on Computational Singular Perturbation (CSP) with the aim of efficiently solving stiff biogeochemical RTMs in groundwater systems. We integrate the CSP concept and algorithm with a reactive transport model associated with a groundwater system. Our results document that this yields a significant improvement in terms of efficiency while maintaining accuracy. For demonstration and evaluation purposes, we apply the approach to a collection of typical groundwater biogeochemical RTMs including H2O2 production/consumption, Cr(VI) adsorption‐desorption equilibrium, and denitrification processes within riparian aquifers. The new approach is then evaluated against traditional apparent rate (AR) and Equilibrium‐kinetic (EK) methods. Our results reveal that the new approach effectively identifies fast species and simplifies reaction networks, thus significantly reducing stiffness and computational costs while maintaining remarkable accuracy. Overall, our approach offers a robust and efficient solution for modeling stiff biogeochemical processes in groundwater systems. Its successful application to diverse reaction networks highlights its potential for broad implementation in environmental and engineering contexts, paving the way for accurate and computationally feasible groundwater quality assessments.
Impact of the Indian Ocean Dipole Mode on Planetary Boundary Layer Ozone in China
Authors: Jiang Zhongjing , Li Jing , Liu Guanyu , Zhang Chongzhao
Published: October 2024

The Indian Ocean Dipole (IOD) mode exerts distinct impacts on the climate in China and can further affect tropospheric ozone. Using long‐term GEOS‐Chem simulations, we found distinct changes in planetary boundary layer ozone throughout China during positive and negative phases of IOD. In summer, ozone shows synchronized increases except in southern China during positive IOD; the ozone increases are dominated by chemical production and transport in northern and western China, respectively. The increased precursor from biogenic emissions contributed to ozone chemical formation in the northern region, and the increased precipitation and decreased solar radiation hindered ozone production in southern China. Ozone changes show good symmetry over most regions during negative IOD. In autumn, the ozone reduction in southern China shares the same reason as summer, while the chemical increase over northern China is affected more by changes in solar radiation and relative humidity than in the precursor emission.
Scale‐Dependent Drivers of Air‐Sea CO2 Flux Variability
Authors: Fay Amanda R. , Carroll Dustin , McKinley Galen A. , Menemenlis Dimitris , Zhang Hong
Published: October 2024

In climate studies, it is crucial to distinguish between changes caused by natural variability and those resulting from external forcing. Here we use a suite of numerical experiments based on the ECCO‐Darwin ocean biogeochemistry model to separate the impact of the atmospheric carbon dioxide (CO2) growth rate and climate on the ocean carbon sink — with a goal of disentangling the space‐time variability of the dominant drivers. When globally integrated, the variable atmospheric growth rate and climate exhibit similar magnitude impacts on ocean carbon uptake. At local scales, interannual variability in air‐sea CO2 flux is dominated by climate. The implications of our study for real‐world ocean observing systems are clear: in order to detect future changes in the ocean sink due to slowing atmospheric CO2 growth rates, better observing systems and constraints on climate‐driven ocean variability are required.
An Adaptive X‐Ray Dynamic Image Estimation Method Based on OMNI Solar Wind Parameters and SXI Simulated Observations
Authors: Wang R. C. , Jorgensen Anders M. , Li Dalin , Sun Tianran , Yang Zhen , Peng Xiaodong
Published: October 2024

Observations of the overall interactions between solar wind and the Earth's magnetosphere are crucial for space weather monitoring. Upcoming missions like the Solar Wind Magnetosphere Ionosphere Link Explorer (SMILE) and the Lunar Environment heliosphere X‐ray Imager (LEXI) aim to make comprehensive global imaging of Earth's magnetosphere using soft X‐ray imager (SXI) in order to understand its dynamic response to solar wind impact. Short‐duration X‐ray images have a low signal‐to‐noise ratio (SNR), limited by cosmic background and Poisson noise. Longer integration times provide better SNR of magnetospheric structures but fail to capture the short‐term dynamics during the integration. Our study introduces a neural network method which is able to estimate the short‐term dynamics during a long integration, driven by OMNI solar wind data and simulated soft X‐ray images. Specifically, an adaptive X‐ray image estimator and a spatio‐temporal discriminator are used. It leverages X‐ray models like Magnetohydrodynamic (MHD) and Jorgensen & Sun model, driven by OMNI data to provide high‐temporal‐resolution prior information on magnetosphere motion, with SXI observation images acting as a posterior constraint on the magnetosphere's state. Experimental validation demonstrates apparent improvements in Peak signal‐to‐noise ratio (PSNR) and Structural Similarity (SSIM) compared to traditional linear and optical flow interpolation methods. The method's flexibility, considering input‐output consistency, enables easy extension to any interval (>3 min), meeting diverse application needs. In conclusion, our study presents a new approach to soft X‐ray image estimation based on neural networks, providing insights into magnetospheric dynamics as observed in soft X‐rays.
Trends and Drivers of Water Temperature Extremes in Mountain Rivers
Authors: van Hamel A. , Brunner M. I.
Published: October 2024

Water temperature extremes can pose serious threats to the aquatic ecosystems of mountain rivers. These rivers are influenced by snow and glaciermelt, which change with climate. As a result, the frequency and severity of water temperature extremes may change. While previous studies have documented changes in non‐extreme water temperature, it is yet unclear how extreme water temperatures change in a warming climate and how their hydro‐meteorological drivers differ from those of non‐extremes. This study aims to assess temporal changes and spatial variability in water temperature extremes and enhance our understanding of the driving processes across European mountain rivers in the current climate, at both a regional and continental scale. First, we describe the characteristics of extreme events and explore their relationships with catchment characteristics. Second, we assess trends in water temperature extremes and compare them with trends in mean water temperature. Third, we use random forest models to identify the main driving processes of water temperature extremes. Last, we conduct a co‐occurrence analysis to examine the relationship between water temperature extremes and hydro‐climatic extremes. Our results show that mean water temperature has increased by °C per decade, leading to more extreme events at high elevations in spring and summer. While non‐extreme water temperatures are mainly driven by air temperature, water temperature extremes are also importantly influenced by soil moisture, baseflow, and meltwater. Our study highlights the complexity of water temperature dynamics in mountain rivers at the regional and continental scale, especially during water temperature extremes.
Ultrastructural investigation of the posterior hyaloid membrane in posterior vitreous detachment
Authors: Nixon Thomas R. W. , Hayes Matthew J. , Snead David , Snead Martin P.
Published: October 2024

Background

Separation of the posterior hyaloid membrane (PHM) from the retina in posterior vitreous detachment (PVD) is a fundamental, but poorly understood, process underlying vitreoretinal disorders including retinal detachment and macular hole. We performed electron microscopy studies of the PHM after PVD to investigate its ultrastructure, associated cellular structures and relationship to the internal limiting membrane (ILM).

Methods

Post-mortem human eyes were collected from recently deceased patients over 70 years of age. A posterior scleral button was trephined to identify PVD status, and the PHM and vitreous prepared for analysis with transmission and scanning electron microscopy.

Results

Twelve eyes from six patients were collected. Seven eyes had PVD; five eyes had attached vitreous. PHM was isolated from seven of seven eyes with PVD. The PHM in eyes with PVD is a laminar lacy sheet, distinct from the disorganised fibres of vitreous gel. Eyes without PVD had vitreous encased in internal limiting membrane which had separated en bloc from the retina. Cells embedded in the PHM (laminocytes) were identified in five of seven eyes with PVD, with strands stretching into the membrane.

Conclusions

PHM isolated from eyes with PVD is distinct from artefactual separation of the ILM from the retina during dissection. PHM is ultrastructurally distinct from vitreous gel and is a separate entity. The en face appearance of PHM is similar to that of ILM, suggesting that in PVD, PHM forms from separation of an inner layer of ILM. Laminocytes may play a role in the pathogenesis of vitreoretinal disease.
Long-term carbon storage in shelf sea sediments reduced by intensive bottom trawling
Authors: Zhang Wenyan , Porz Lucas , Yilmaz Rümeysa , Wallmann Klaus , Spiegel Timo , Neumann Andreas , Holtappels Moritz , Kasten Sabine , Kuhlmann Jannis , Ziebarth Nadja , Taylor Bettina , Ho-Hagemann Ha Thi Minh , Bockelmann Frank-Detlef , Daewel Ute , Bernhardt Lea , Schrum Corinna
Published: October 2024

Bottom trawling represents the most widespread anthropogenic physical disturbance to seafloor sediments on continental shelves. While trawling-induced changes to benthic ecology have been widely recognized, the impacts on long-term organic carbon storage in marine sediments remains uncertain. Here we combined datasets of sediment and bottom trawling for a heavily trawled region, the North Sea, to explore their potential mutual dependency. A pattern emerges when comparing the surface sediment organic carbon-to-mud ratio with the trawling intensity represented by the multi-year averaged swept area ratio. The organic carbon-to-mud ratio exhibits a systematic response to trawling where the swept area ratio is larger than 1 yr−1. Three-dimensional physical–biogeochemical simulation results suggest that the observed pattern is attributed to the correlated dynamics of mud and organic carbon during transport and redeposition in response to trawling. Both gain and loss of sedimentary organic carbon may occur in weakly trawled areas, whereas a net reduction of sedimentary organic carbon is found in intensely trawled grounds. Cessation of trawling allows restoration of sedimentary carbon stock and benthic biomass, but their recovery occurs at different timescales. Our results point out a need for management of intensely trawled grounds to enhance the CO2 sequestration capacity in shelf seas.
Medical image segmentation with UNet-based multi-scale context fusion
Authors: Yuan Yongqi , Cheng Yong
Published: October 2024

Histopathological examination holds a crucial role in cancer grading and serves as a significant reference for devising individualized patient treatment plans in clinical practice. Nevertheless, the distinctive features of numerous histopathological image targets frequently contribute to suboptimal segmentation performance. In this paper, we propose a UNet-based multi-scale context fusion algorithm for medical image segmentation, which extracts rich contextual information by extracting semantic information at different encoding stages and assigns different weights to the semantic information at different scales through TBSFF module to improve the learning ability of the network for features. Through multi-scale context fusion and feature selection networks, richer semantic features and detailed information are extracted. The target can be more accurately segmented without significantly increasing the extra overhead. The results demonstrate that our algorithm achieves superior Dice and IoU scores with a relatively small parameter count. Specifically, on the GlaS dataset, the Dice score is 90.56, and IoU is 83.47. For the MoNuSeg dataset, the Dice score is 79.07, and IoU is 65.98.
Leveraging ML for profiling lipidomic alterations in breast cancer tissues: a methodological perspective
Authors: Shahnazari Parisa , Kavousi Kaveh , Minuchehr Zarrin , Goliaei Bahram , Salek Reza M
Published: October 2024

In this study, a comprehensive methodology combining machine learning and statistical analysis was employed to investigate alterations in the metabolite profiles, including lipids, of breast cancer tissues and their subtypes. By integrating biological and machine learning feature selection techniques, along with univariate and multivariate analyses, a notable lipid signature was identified in breast cancer tissues. The results revealed elevated levels of saturated and monounsaturated phospholipids in breast cancer tissues, consistent with external validation findings. Additionally, lipidomics analysis in both the original and validation datasets indicated lower levels of most triacylglycerols compared to non-cancerous tissues, suggesting potential alterations in lipid storage and metabolism within cancer cells. Analysis of cancer subtypes revealed that levels of PC 30:0 were relatively reduced in HER2(−) samples that were ER(+) and PR(+) compared to those that were ER(−) and PR(−). Conversely, HER2(+) tumors, which were ER(−) and PR(−), exhibited increased concentrations of PC 30:0. This increase could potentially be linked to the role of Stearoyl-CoA-Desaturase 1 in breast cancer. Comprehensive metabolomic analyses of breast cancer can offer crucial insights into cancer development, aiding in early detection and treatment evaluation of this devastating disease.
Adversarial robustness improvement for X-ray bone segmentation using synthetic data created from computed tomography scans
Authors: Fok Wai Yan Ryana , Fieselmann Andreas , Huemmer Christian , Biniazan Ramyar , Beister Marcel , Geiger Bernhard , Kappler Steffen , Saalfeld Sylvia
Published: October 2024

Deep learning-based image analysis offers great potential in clinical practice. However, it faces mainly two challenges: scarcity of large-scale annotated clinical data for training and susceptibility to adversarial data in inference. As an example, an artificial intelligence (AI) system could check patient positioning, by segmenting and evaluating relative positions of anatomical structures in medical images. Nevertheless, data to train such AI system might be highly imbalanced with mostly well-positioned images being available. Thus, we propose the use of synthetic X-ray images and annotation masks forward projected from 3D photon-counting CT volumes to create realistic non-optimally positioned X-ray images for training. An open-source model (TotalSegmentator) was used to annotate the clavicles in 3D CT volumes. We evaluated model robustness with respect to the internal (simulated) patient rotation $$\alpha$$
α
on real-data-trained models and real&synthetic-data-trained models. Our results showed that real&synthetic- data-trained models have Dice score percentage improvements of 3% to 15% across different $$\alpha$$
α
groups compared to the real-data-trained model. Therefore, we demonstrated that synthetic data could be supplementary used to train and enrich heavily underrepresented conditions to increase model robustness.
Critical assessment of anti-amyloid-β monoclonal antibodies effects in Alzheimer’s disease: a systematic review and meta-analysis highlighting target engagement and clinical meaningfulness
Authors: Avgerinos Konstantinos I. , Manolopoulos Apostolos , Ferrucci Luigi , Kapogiannis Dimitrios
Published: October 2024

Despite most monoclonal antibodies against Aβ in Alzheimer’s failed to demonstrate efficacy, the newest antibodies showed statistically significant clinical effects. We conducted a systematic review and meta-analysis to assess the efficacy, target engagement, and safety of anti-Aβ antibodies in sporadic AD including phase III RCTs published up to November 28, 2023. Antibodies as a drug class, attenuated worsening on the clinical scales CDR-SB and ADAS-Cog by very small effect sizes and reduced amyloid on PET by a very large effect size. Reduction of amyloid on PET was moderately correlated with CDR-SB and ADAS-Cog reductions. However, antibodies increased risk of ARIA-E and ARIA-H by a very large and moderate effect size, respectively. In subgroup analyses by individual drug, Donanemab and Lecanemab induced the largest benefits. In subgroup analyses by binding affinity, antibodies without binding to monomers were associated with the most favorable effects. Despite statistical significance for improvement on clinical measures, antibody effects were below the threshold of clinically meaningful change during the period they were studied. However, the newest antibodies demonstrably interfere with the underlying ΑD pathophysiology and therefore their benefit could be cumulative over time leading to larger clinical effects in subsequent years. PROSPERO registration no. CRD42022381334.
In-silico and in-vitro study of novel antimicrobial peptide AM1 from Aegle marmelos against drug-resistant Staphylococcus aureus
Authors: Awdhesh Kumar Mishra Rudra , Kodiveri Muthukaliannan Gothandam
Published: October 2024

Antimicrobial peptides have garnered increasing attention as potential alternatives due to their broad-spectrum antimicrobial activity and low propensity for developing resistance. This is for the first time; proteome sequences of Aegle marmelos were subjected to in-silico digestion and AMP prediction were performed using DBAASP server. After screening the peptides on the basis of different physiochemical property, peptide sequence GKEAATKAIKEWGQPKSKITH (AM1) shows the maximum binding affinity with − 10.2 Kcal/mol in comparison with the standard drug (Trimethoprim) with − 7.4 kcal/mol and − 6.8 Kcal/mol for DHFR and SaTrmK enzyme respectively. Molecular dynamics simulation performed for 300ns, it has been found that peptide was able to stabilize the protein more effectively, analysed by RMSD, RMSF, and other statistical analysis. Free binding energy for DHFR and SaTrmK interaction from MMPBSA analysis with peptide was found to be -47.69 and − 44.32 Kcal/mol and for Trimethoprim to be -13.85 Kcal/mol and − 11.67 Kcal/mol respectively. Further in-vitro study was performed against Methicillin Susceptible Staphylococcus aureus (MSSA), Methicillin Resistant Staphylococcus aureus (MRSA), Multi-Drug Resistant Staphylococcus aureus (MDR-SA) strain, where MIC values found to be 2, 4, and 8.5 µg/ml lesser in comparison to trimethoprim which has higher MIC values 2.5, 5, and 9.5 µg/ml respectively. Thus, our study provides the insight for the further in-vivo study of the peptides against multi-drug resistant S. aureus.
Potential of pre-diagnostic metabolomics for colorectal cancer risk assessment or early detection
Authors: Seum Teresa , Frick Clara , Cardoso Rafael , Bhardwaj Megha , Hoffmeister Michael , Brenner Hermann
Published: October 2024

This systematic review investigates the efficacy of metabolite biomarkers for risk assessment or early detection of colorectal cancer (CRC) and its precursors, focusing on pre-diagnostic biospecimens. Searches in PubMed, Web of Science, and SCOPUS through December 2023 identified relevant prospective studies. Relevant data were extracted, and the risk of bias was assessed with the QUADAS-2 tool. Among the 26 studies included, significant heterogeneity existed for case numbers, metabolite identification, and validation approaches. Thirteen studies evaluated individual metabolites, mainly lipids, while eleven studies derived metabolite panels, and two studies did both. Nine panels were internally validated, resulting in an area under the curve (AUC) ranging from 0.69 to 0.95 for CRC precursors and 0.72 to 1.0 for CRC. External validation was limited to one panel (AUC = 0.72). Metabolite panels and lipid-based biomarkers show promise for CRC risk assessment and early detection but require standardization and extensive validation for clinical use.
Phosphorylation of P-stalk proteins defines the ribosomal state for interaction with auxiliary protein factors
Authors: Filipek Kamil , Blanchet Sandra , Molestak Eliza , Zaciura Monika , Wu Colin Chih-Chien , Horbowicz-Drożdżal Patrycja , Grela Przemysław , Zalewski Mateusz , Kmiecik Sebastian , González-Ibarra Alan , Krokowski Dawid , Latoch Przemysław , Starosta Agata L , Mołoń Mateusz , Shao Yutian , Borkiewicz Lidia , Michalec-Wawiórka Barbara , Wawiórka Leszek , Kubiński Konrad , Socała Katarzyna , Wlaź Piotr , Cunningham Kyle W , Green Rachel , Rodnina Marina V , Tchórzewski Marek
Published: October 2024

Ribosomal action is facilitated by the orchestrated work of trans-acting factors and ribosomal elements, which are subject to regulatory events, often involving phosphorylation. One such element is the ribosomal P-stalk, which plays a dual function: it activates translational GTPases, which support basic ribosomal functions, and interacts with the Gcn2 kinase, linking the ribosomes to the ISR pathway. We show that P-stalk proteins, which form a pentamer, exist in the cell exclusively in a phosphorylated state at five C-terminal domains (CTDs), ensuring optimal translation (speed and accuracy) and may play a role in the timely regulation of the Gcn2-dependent stress response. Phosphorylation of the CTD induces a structural transition from a collapsed to a coil-like structure, and the CTD gains conformational freedom, allowing specific but transient binding to various protein partners, optimizing the ribosome action. The report reveals a unique feature of the P-stalk proteins, indicating that, unlike most ribosomal proteins, which are regulated by phosphorylation in an on/off manner, the P-stalk proteins exist in a constantly phosphorylated state, which optimizes their interaction with auxiliary factors.
Diagnosing and engineering gut microbiomes
Authors: Cappio Barazzone Elisa , Diard Médéric , Hug Isabelle , Larsson Louise , Slack Emma
Published: October 2024

The microbes, nutrients and toxins that we are exposed to can have a profound effect on the composition and function of the gut microbiome. Thousands of peer-reviewed publications link microbiome composition and function to health from the moment of birth, right through to centenarians, generating a tantalizing glimpse of what might be possible if we could intervene rationally. Nevertheless, there remain relatively few real-world examples where successful microbiome engineering leads to beneficial health effects. Here we aim to provide a framework for the progress needed to turn gut microbiome engineering from a trial-and-error approach to a rational medical intervention. The workflow starts with truly understanding and accurately diagnosing the problems that we are trying to fix, before moving on to developing technologies that can achieve the desired changes.
Matrix Biology: ECM Turnover and Temporal Fluctuation
Authors: Tran Quyen , Ogle Brenda M.
Published: October 2024

The extracellular matrix (ECM) provides structural scaffolding for cells as well as crucial biochemical and biomechanical cues. The environment created by ECM is diverse and is different for each type of tissue depending on its role within the body. The ECM environment is also dynamic during development to a mature state. The healthy, mature state can be disrupted during disease. In this chapter we explore the spatial and temporal expression of ECM within the mammalian heart during development and with disease. When possible, we also evaluate how the expression of ECM proteins, in particular in location and time, affect cell behavior with emphasis on the in-vivo environment. We show that the study of cell-ECM interactions of heart tissues evolves over time from: 1) descriptive analyses of structure; to 2) dissected ECM-linked cell behaviors; to more recent work to unravel 3) the mechanistic underpinnings of ECM-linked cell behaviors. We suspect this experimental progression is reflected in tissues other than those of the heart, though the kinetics may differ.