bluuebunny/crossref_metadata_2025 huggingface dataset:
Word order and prosody in the expression of information structure
Authors: Laleko Oksana
Published: February 2025

The chapter presents experimental data probing the interactions between word order and prosody in the formal encoding of information structure in homeland and heritage Russian. Contrary to traditional accounts that emphasize the primacy of word order in the marking of givenness and newness in Slavic, neither heritage nor homeland speakers favored the word order strategy (“place given constituents before new constituents”) over the prosodic strategy (“new information focus realizes stress”), lending evidence against theoretical accounts that assume a direct mapping between word order and information structure in Russian. The chapter offers an account of heritage language word order change in terms of change in the degree of prosodic and word order plasticity (Vallduví and Engdahl 1995) in ways that broadly parallel micro-variation observed across Slavic languages (Šimík and Wierzba 2017). An important advantage of this approach is that it is more explicit than most traditional accounts of heritage language change in approaching all grammars under analysis as internally consistent, even if differently configured, systems. In this regard, the chapter advances the position that heritage languages are a valid and essential empirical resource for linguistic theory building.
Realism, the English School, and the Survival of States
Authors: Lemke Douglas
Published: February 2025

In this chapter, I contrast realist and English school expectations about how states protect themselves from dying. Realists focus on power maximization. The English school focuses on international society. I find strong support for the English school because the members of international society (sovereign states) are much less likely to die than are states excluded from international society (territorial contenders). I find no support for realist expectations; no matter how I structure the analysis, powerful states are never consistently associated with longer state survival. Rules for membership in international society changed around 1960. The differing time periods offer a critical experiment for differentiating between realism and the English school. The English school is supported in the critical experiment, while realism is again rejected.
Conclusions
Authors: Lemke Douglas
Published: February 2025

In this chapter, I draw together the preceding analyses to differentiate between theories with strong support, weak support, and no support. In the bulk of the chapter, I present two main implications of the book. The first is that we really cannot understand international relations (IR) more broadly (e.g., not just state death) unless we widen our focus to include both sovereign states and territorial contenders. The second, which I label “intranational IR,” suggests we will not fully appreciate IR until we study all anarchical relationships. Sometimes those exist within the borders of a state. When they do, they are excluded by most IR researchers as domestic politics. I conclude that widening the range of actors and behaviors we study is necessary for IR’s continued advance as a science.
The Double Life of Mens Rea
Authors: Kelly Erin I
Published: February 2025

This chapter examines why establishing a defendant’s mental state at the time of the criminal act should be considered a basic requirement of justice for criminal law. It is tempting to account for the importance of “mens rea” to criminal justice through a retributive theory of punishment. According to retributivists, morally culpable criminal wrongdoers deserve to be punished, and mens rea is evidence of moral culpability. By contrast, this chapter argues that the mental state elements of criminal law represent fair-notice and fair opportunity limits on the measures a state may justly take to protect the rights of victims. These fairnesss limits provided by the mens rea element of criminal liability do not depend on a theory of retributive justice or moral desert. The chapter then addresses what a defendant’s accountability comes to in the interpersonal morality of redress, both its agential presuppositions and its interpersonal point, which is elaborated through the idea of restorative justice. The central ideas is that we should relinquish retributive aspirations for mens rea and adopt the less punitive and more flexible approach to interpersonal moral accountability offered by restorative justice.
Returning a Kindness
Authors: Macnamara Coleen
Published: February 2025

The most often-encountered characterization of a returned kindness is a characterization of what it is not. A returned kindness, we are told, is not a payment or compensation for the original kind act. This seems exactly right, but it prompts a question: If a returned kindness is not a form of payment, what is it? How should we construe the “returning the kindness” element of a grateful response? This chapter aims to propose positive characterization of returning a kindness. I urge that a returned kindness is an expression of the emotion of gratitude in the sense that it is a demonstration of the reciprocal caring orientation that in part constitutes or directly results from an episode of gratitude.
Supporting older people through Hospital at Home care: a systematic review of patient, carer and healthcare professionals’ perspectives
Authors: Wong Anita , Cooper Claudia , Evans Catherine J , Rawle Mark James , Walters Kate , Conroy Simon Paul , Davies Nathan
Published: February 2025

Introduction

Hospital at Home provides hospital-level type care at home, both remote and face-to-face by a multidisciplinary team of healthcare professionals. In practice, various different models are employed, but we do not know what older people, their family carers (carers) and healthcare professionals think of what works best for them. This review aimed to describe the various Hospital at Home models and synthesise literature exploring patient, carer and staff perspectives of Hospital at Home care for older people.

Methods and analysis

A systematic review of UK studies. Medline, Embase and CINAHL and grey literature were searched from 1991 to 2024, using predetermined inclusion and exclusion criteria; data were extracted from included papers. Tabulation, thematic grouping and concept mapping of themes were used to narratively synthesise the literature.

Results

Twenty studies met eligibility. Hospital at Home models included admission avoidance and early discharge. Studies were largely positive regarding Hospital at Home, with benefits including home familiarity, enabling person-centred care and shared decision-making and provision of family carer support. Challenges included staff accessibility, patient and carer anxieties regarding the safety of virtual wards, coordination across sectors and older people using technology.

Conclusion

Provision of holistic, accessible and continuous care for older people in Hospital at Home services facilitated patient and carer empowerment, dignity and autonomy. There are gaps in our understanding and evidence surrounding paid care workers and informal carers’ perspectives in UK settings, especially within rigorous Hospital at Home literature.
A comprehensive review of deep learning-based approaches for drug–drug interaction prediction
Authors: Xia Yan , Xiong An , Zhang Zilong , Zou Quan , Cui Feifei
Published: February 2025

Deep learning models have made significant progress in the biomedical field, particularly in the prediction of drug–drug interactions (DDIs). DDIs are pharmacodynamic reactions between two or more drugs in the body, which may lead to adverse effects and are of great significance for drug development and clinical research. However, predicting DDI through traditional clinical trials and experiments is not only costly but also time-consuming. When utilizing advanced Artificial Intelligence (AI) and deep learning techniques, both developers and users face multiple challenges, including the problem of acquiring and encoding data, as well as the difficulty of designing computational methods. In this paper, we review a variety of DDI prediction methods, including similarity-based, network-based, and integration-based approaches, to provide an up-to-date and easy-to-understand guide for researchers in different fields. Additionally, we provide an in-depth analysis of widely used molecular representations and a systematic exposition of the theoretical framework of models used to extract features from graph data.
Do protein language models learn phylogeny?
Authors: Tule Sanjana , Foley Gabriel , Bodén Mikael
Published: February 2025

Deep machine learning demonstrates a capacity to uncover evolutionary relationships directly from protein sequences, in effect internalising notions inherent to classical phylogenetic tree inference. We connect these two paradigms by assessing the capacity of protein-based language models (pLMs) to discern phylogenetic relationships without being explicitly trained to do so. We evaluate ESM2, ProtTrans, and MSA-Transformer relative to classical phylogenetic methods, while also considering sequence insertions and deletions (indels) across 114 Pfam datasets. The largest ESM2 model tends to outperform other pLMs (including the multimodal ESM3) by recovering phylogenetic relationships among homologous protein sequences in both low- and high-gap settings. pLMs agree with conventional phylogenetic methods in general, but more so for protein families with fewer implied indels, highlighting indels as a key factor differentiating classical phylogenetics from pLMs. We find that pLMs preferentially capture broader as opposed to finer evolutionary relationships within a specific protein family, where ESM2 has a sweet spot for highly divergent sequences, at remote distance. Less than 10% of neurons are sufficient to broadly recapitulate classical phylogenetic distances; when used in isolation, the difference between the paradigms is further diminished. We show these neurons are polysemantic, shared among different homologous families but never fully overlapping. We highlight the potential of ESM2 as a complementary tool for phylogenetic analysis, especially when extending to remote homologs that are difficult to align and imply complex histories of insertions and deletions. Implementations of analyses are available at https://github.com/santule/pLMEvo.
ESM-BBB-Pred: a fine-tuned ESM 2.0 and deep neural networks for the identification of blood–brain barrier peptides
Authors: Naseem Ansar , Alturise Fahad , Alkhalifah Tamim , Khan Yaser Daanial
Published: February 2025

Blood–brain barrier peptides (BBBP) could significantly improve the delivery of drugs to the brain, paving the way for new treatments for central nervous system (CNS) disorders. The primary challenge in treating CNS disorders lies in the difficulty pharmaceutical agent’s face in crossing the BBB. Almost 98% of small molecule drugs and nearly all large molecule drugs fail to penetrate the BBB effectively. Thus, identifying these peptides is vital for advancements in healthcare. This study introduces an enhanced intelligent computational model called BBB-PEP- Evolutionary Scale Modeling (ESM), designed to identify BBBP. The relative positions, reverse position and statistical moment-based features have been utilized on the existing benchmark dataset. For classification purpose, six deep classifiers such as fully connected networks, convolutional neural network, simple recurrent neural networks, long short-term memory (LSTM), bidirectional LSTM, and gated recurrent unit have been utilized. In addition to harnessing the effectiveness of the pre-trained model, a protein language model ESM 2.0 has been fine-tuned on a benchmark dataset for BBBP classification. Three tests such as self-consistency, independent set testing, and five-fold cross-validation have been utilized for evaluation purposes with evaluation metrics includes accuracy, specificity, sensitivity, and Matthews correlation coefficient. The fine-tuned model ESM 2.0 has shown superior results as compared to employed classifiers and surpasses the existing benchmark studies. This system will support future research and the scientific community in the computational identification of BBBP.
DECA: harnessing interpretable transformer model for cellular deconvolution of chromatin accessibility profile
Authors: Luo Shijie , Zhu Ming , Lin Liquan , Xie Jiajing , Lin Shihao , Chen Ying , Zhu Jiali , Huang Jialiang
Published: February 2025

The assay for transposase-accessible chromatin with sequencing (ATAC-seq) identifies chromatin accessibility across the genome, crucial for gene expression regulating. However, bulk ATAC-seq obscures cellular heterogeneity, while single-cell ATAC-seq suffers from issues such as sparsity and costliness. To this end, we introduce DECA, a sophisticated deep learning model based on vision transformer to deconvolve cell type information from bulk chromatin accessibility profiles, utilizing single-cell ATAC-seq datasets as reference for enhanced precision and resolution. Notably, patch attention generated by DECA’s multi-head attention mechanism aligns with chromatin interactions detected by Hi-C. Additionally, DECA predicted lineage-specific cell composition changes due to genetic perturbation. The chromatin accessibility signatures predicted by DECA are enriched with cell-type specific genetic variations. Ultimately, we applied DECA on pan-cancer ATAC-seq datasets and demonstrated its capability to deconvolve cell type proportions with clinical significance. Taken together, DECA deconvolves cellular proportions and predicts their chromatin accessibility profiles from bulk chromatin accessibility data, which enable exploring the gene regulatory programs in development and diseases.
Single cell multiome analysis of the bovine placenta identifies gene regulatory networks in trophoblast differentiation
Authors: Davenport Kimberly M , Lowke Makenzie T , Ortega M Sofia , Kelleher Andrew M , Warren Wesley C , Spencer Thomas E
Published: February 2025

A central determinant of successful reproduction is pregnancy establishment and maintenance that relies on proper development of the conceptus (embryo/fetus and associated extraembryonic membranes including the placenta). Pregnancy loss in cattle can be caused by inadequate development and differentiation of the placenta. However, the cellular and molecular mechanisms regulating bovine placenta development and, particularly, trophoblast differentiation are not well understood. Recent single-cell RNA-seq analyses revealed dynamic changes in cell populations and gene expression patterns during bovine placental development. Here, the chromatin accessibility landscape across diverse cell populations was determined in the developing (day 40) and mature (day 170) bovine placenta using the 10X Genomics multiome (snRNA-seq and snATAC-seq) platform. Analyses revealed distinct trophoblast, mesenchyme, endothelial, immune, and epithelial cell populations characterized by unique gene expression and chromatin accessibility signatures. ATAC-seq peaks defined open chromatin regions, facilitating the identification of transcription factor binding sites and candidate gene regulatory networks (GRN) involved with trophoblast differentiation. Several transcription factors, known for their involvement in trophoblast differentiation in other mammalian species, were identified as candidate regulators of uninucleate (UNC) to binucleate (BNC) trophoblast differentiation. This study adds to our foundational understanding of gene regulation and expression in the placenta, offering insights into the mechanisms governing pregnancy loss in cattle.
Suppression of FOXO3 by BMP signaling contribute to the different primordial germ cell proliferation between layers and broilers
Authors: Ma Yuxiao , Meng Lu , Wei Jiahui , Wu Wenhui , Zhang Yun , Wang Xuzhao , Guo Xiaotong , Wang Feiyi , Mao Yong , Zhu Guiyu
Published: February 2025

Although all domestic chicken breeds originate from their wild relatives, the red junglefowl, they have been selectively bred for high yields in egg or meat production， or both. Some breeds are highly efficient in egg production, while others perform poorly, due to long-term selection aimed for different purposes. Female primordial germ cells (PGCs) are the precursors of eggs and the population size of PGCs will ultimately determine ovarian reserve of hens. In this study, we observed that the layers exhibit greater proliferation capacity and a higher number of PGCs compared to the broilers before meiosis. By comparing the PGC transcriptomes between layers and broilers, we identified potential genes that regulate cell proliferation. We further confirmed that FOXO3 expression is higher in broilers, where it inhibits the PGC proliferation both in vivo and in vitro. However, in layers, the upstream BMP signaling stimulate the phosphorylation of AKT and suppress FOXO3 activity. Consequently, the elevated BMP signaling and reduced FOXO3 co-operatively promote more robust PGC proliferation in layers compared to broilers and result in a greater number of PGCs in layers. Our data not only reveal molecular mechanisms underlying PGC growth, but also provide new clues to improve the laying performance in chicken.
Differences in uterine and serum metabolome associated with clinical cure failure of metritis in dairy cows
Authors: Pereira F N S , Martelo Pereira A , Galvão K N , Bisinotto R S , Figueiredo C C
Published: February 2025

This study investigated differences in uterine and serum metabolome associated with clinical cure failure of metritis in dairy cows. Metritis was diagnosed in lactating Holstein cows from two Florida dairies and defined by the presence of fetid, watery, reddish-brown vaginal discharge from 4 to 12 days postpartum (dpp). Cows with metritis (n = 24) were paired with cows without metritis of similar parity and dpp (n = 24). On the day of metritis diagnosis (day 0), all cows with metritis received antimicrobial therapy. The continued presence of the fetid, watery, reddish-brown discharge on day 5 (n = 16) was defined as clinical cure failure, whereas clinical cure was defined by its absence (n = 8). Metabolome analyses of uterine lavage (days 0 and 5) and serum samples (day 0) were conducted using untargeted gas chromatography time-of-flight mass spectrometry. Normalized data were analyzed using partial least squares–discriminant analysis and ANOVA, adjusting P-values for multiple comparisons. Differences in the uterine metabolome on day 0 associated with clinical cure failure were linked to carbohydrate, amino acid, and lipid metabolism. Greater concentrations of arachidonic acid, ribose, and glutaric acid were associated with clinical cure failure, suggesting a greater degree of tissue lesion and inflammation. No differences in the serum metabolome were associated with cure failure. No differences in uterine metabolome were associated with clinical cure failure on day 5. The findings suggest that clinical cure failure is associated with a greater uterine inflammatory process that did not persist until cure assessment day.
Epigenetic age acceleration in peripheral blood correlates with brain-MRI age acceleration
Authors: Sant'Anna Barbosa Ferreira Pedro , van Dongen Jenny , den Braber Anouk , Boomsma Dorret I , de Geus Eco J C , van ‘t Ent Dennis
Published: February 2025

As the world's population ages, more and more people are expected to suffer from age-related diseases. Biological aging markers derived from DNA methylation and brain structure show promise in predicting health outcomes. Understanding the relationship between these biomarkers can promote the development of effective health interventions.

In a sample of 254 participants from the Netherlands Twin Register (20-84 years), we investigated associations between DNA methylation age acceleration based on five epigenetic biomarkers (Hannum, Horvath, PhenoAge, GrimAge, and DunedinPACE) and brain age acceleration based on neuroimaging (brainageR). Furthermore, we applied bivariate twin models to examine the contribution of genetic and environmental factors to the associations (cross-twin cross-trait correlations and within monozygotic-twin pair differences).

We observed relationships with brain age acceleration for DNA methylation age acceleration based on the Hannum and GrimAge clocks that were supported by within MZ twin pair difference modelling. Cross-twin cross-trait modelling confirmed a non-shared environmental etiology.

Twin analyses highlight the importance of the environment in accelerated aging, raising the possibility for interventions such as lifestyle modification.
Advances in engineered organoid models of skin for biomedical research
Authors: Zeng Dongao , Li Shikai , Du Fangzhou , Xia Yuchen , Zhang Jingzhong , Yu Shuang , Qin Jianhua
Published: February 2025

In recent years, significant progress has been made in the development of organoids, which offer promising opportunities for developmental and translational research. With advances in cell biology and bioengineering techniques, skin models are evolving from conventional multilayered structures to appendage-bearing spheroids or 3D biomimetic models. This comprehensive review aims to provide an in-depth understanding of organoid models of the skin, covering topics such as skin development, construction strategies and key elements, types of organoid models, biomedical applications, and challenges. Embryonic skin development is briefly introduced to provide a foundational understanding of construction principles. Current engineering strategies are outlined, highlighting key elements such as cell sources, bioengineering techniques, 3D scaffolds, and crucial signaling pathways. Furthermore, recent advances in generating organoids with structural and functional parallels to native skin are meticulously summarized. These developments facilitate the utilization of organoids in diverse applications, such as modeling skin disorders, developing regenerative solutions, and understanding skin development. Finally, the challenges and prospects in the field are discussed. The integration of state-of-the-art bioengineering techniques with a deep understanding of skin biology is promoting the production and biomedical application of these organoid models.
“The FBI has no politics”: COMINFIL radio-TV and the suppression of dissent
Authors: Stabile Carol A , Tokos Lauren , Yousaf Miriam
Published: February 2025

In the second half of the 1940s, the Federal Bureau of Investigation initiated an investigation of the broadcasting industry that had far-reaching consequences for the future of television. This investigation, COMINFIL Radio-TV (short for Communist Infiltration of Radio-TV) provided justification and resources for the Bureau’s surveillance of progressives and efforts to attack and undermine progressive reforms in the postwar era. This article shows how the Bureau used the threat of communist infiltration to infiltrate trade unions, broadcast networks, and progressive organizations. In doing so, this article begins to address a crucial gap in Cold War media historiography—the Bureau’s interventions into broadcasting at a particularly critical moment in the development of television—by documenting government suppression of dissent and censorship.
Arm’s length or joined at the hip? Public service media’s coverage of Gaza
Authors: Forde Sydney L , Freedman Des
Published: February 2025

Critiquing normative articulations of a public versus commercial media binary, we explore the contradictory juxtaposition of democratic expectations assigned to public service media (PSM) broadly, alongside actual PSM reporting. We examine US and UK PSM coverage of two major events related to the bombardment of Gaza and subsequent humanitarian crisis in the months following the Hamas attacks on October 7, 2023. Contextualized within the UK, US and Israel’s historical and ongoing colonial violence within Palestine over the past 75 years, we assess coverage that stands in contradiction to the often fetishized notion of PSM’s role in serving a broadly conceived and normatively accepted “public,” and challenge the independence afforded to existing PSM structures via a critique of the notion that PSM organizations operate at “arm’s length” from government. Throughout our analysis, we find evidence of systematic failures and highlight PSM’s use as an instrument perpetuating state power and control.
Executive Summary: State-of-the-Art Review: Data and Trust to Improve Care for Transgender and Gender-Diverse Patients
Authors: Van Sickels Nicholas , Wong Jennifer W H , Villacorta-Cari Evelyn , Lee Steph E , Fallin-Bennett Keisa
Published: February 2025

As active medical and surgical providers of gender-affirming care, we aim to share lived experiences of our patients and outline best practices in gender-affirming medicine in this review.
Renal functional reserve in living kidney donors
Authors: Rinne Ana González , Sorensen Cristian Acosta , Reseghetti Elia , Viera Yaiza Rivero , Rincón Marian Stefany , Izquierdo Edduin Martín , Bethencourt Alejandro Alonso , Morales Adelaida , Moya Elisa Cabello , González Selene , Cabrera Faina González , Hernández Arminda Fariña , Lima Sergio Luis , Martín Laura Díaz , Escamilla Beatriz , Cruz Coriolano , Rinne Federico González , Tamajón Lourdes Pérez , Gaspari Flavio , Marrero Domingo Hernández , Porrini Esteban
Published: February 2025

Background

Factors associated with renal functional reserve (RFR)—presence or absence—are not completely clear and remain under-investigated.

Methods

In this observational study, we evaluated the characteristics associated with the presence or absence of RFR in healthy subjects—living kidney donors—before donation. Renal function was assessed with measured glomerular filtration rate (GFR)—the clearance of iohexol—and RFR with the infusion of amino acids. An increase in GFR > 10% after amino acid infusion indicated the presence of RFR. We defined a priori three groups of donors: without, with, and using RFR. Subject using RFR had baseline GFR >100 ml/min but without an increase in GFR after stimulation.

Results

Subjects without RFR were predominantly women (81%) with the lowest body surface area (BSA) (1.71 ± 0.17 m2), and basal GFR (85 ± 9 ml/min). Subjects with RFR were also mostly women (85%), with a higher BSA (1.83 ± 0.18 m2; p 0.039) and basal GFR (93 ± 15 ml/min). Subjects using RFR were mostly males (56%) and had the highest BSA (1.94 ± 0.18 m2; P < 0.0001 vs without RFR; p ns vs with RFR), basal GFR (123 ± 20 ml/min; P < 0.0001 vs subjects without RFR; P < 0.0001 vs with RFR), and weight (82.1 ± 13.2 Kg; P < 0.0001 vs without RFR; p ns vs with RFR).

Conclusions

The presence or absence of RFR was associated to differences in gender, weight, BMI, BSA, and basal GFR. Women with small BSA may have lower GFR and no RFR, indicating possibly a lower renal endowment even in the normal range of renal function. The use of RFR may indicate a response to a higher metabolic demand in subjects with higher renal endowment.
An investigation into the causes of race bias in AI-based cine CMR segmentation
Authors: Lee Tiarna , Puyol-Antón Esther , Ruijsink Bram , Roujol Sebastien , Barfoot Theodore , Ogbomo-Harmitt Shaheim , Shi Miaojing , King Andrew
Published: February 2025

Aims

Artificial intelligence (AI) methods are being used increasingly for the automated segmentation of cine cardiac magnetic resonance (CMR) imaging. However, these methods have been shown to be subject to race bias, i.e. they exhibit different levels of performance for different races depending on the (im)balance of the data used to train the AI model. In this paper we investigate the source of this bias, seeking to understand its root cause(s).

Methods and Results

We trained AI models to perform race classification on cine CMR images and/or segmentations from White and Black subjects from the UK Biobank and found that the classification accuracy for images was higher than for segmentations. Interpretability methods showed that the models were primarily looking at non-heart regions. Cropping images tightly around the heart caused classification accuracy to drop to almost chance level. Visualising the latent space of AI segmentation models showed that race information was encoded in the models. Training segmentation models using cropped images reduced but did not eliminate the bias. A number of possible confounders for the bias in segmentation model performance were identified for Black subjects but none for White subjects.

Conclusions

Distributional differences between annotated CMR data of White and Black races, which can lead to bias in trained AI segmentation models, are predominantly image-based, not segmentation-based. Most of the differences occur in areas outside the heart, such as subcutaneous fat. These findings will be important for researchers investigating performance of AI models on different races.
The Intergenerational Transmission of Welfare Dependency
Authors: de Haan Monique , Schreiner Ragnhild C
Published: February 2025

Exploiting rich administrative data from Norway, we estimate nonparametric bounds around the average causal effect of parental welfare participation on children’s welfare participation for children that grew up in welfare-dependent families. We find upper bounds well below the intergenerational association and substantially below existing LATE estimates in the literature. Our results show that a substantial portion of the observed intergenerational correlation in welfare dependency is due to selection, and that there is important heterogeneity in the intergenerational effects both between participants (and their children) within a welfare program, as well as across different welfare programs.
A comment on buyers’ miscoordination, entry, and downstream competition
Authors: Sevük Barış
Published: February 2025

Fumagalli and Motta (The Economic Journal, 2008) argue that competition among downstream buyers limits the ability of a dominant upstream firm to deter entry by a more efficient competitor. This comment demonstrates that the impact of downstream competition is, in fact, more complex. In particular, competition can motivate buyers to favor the incumbent due to a ‘raising rivals’ costs’ effect.
Morality in the Making: The Collaborative Relationship Between Formal Caregivers, Informal Caregivers and Nursing Home Residents
Authors: Dohmen Marleen D W , Visser Mandy , Huijg Johanna M , Groot Barbara C , Abma Tineke A
Published: February 2025

BACKGROUND AND OBJECTIVES

Collaboration between formal and informal caregivers is essential for providing good care to nursing home residents. Yet, ambiguity regarding mutual roles and responsibilities often impedes effective collaboration. To address this issue, we examined how formal caregivers, informal caregivers, and residents establish a moral understanding of their responsibilities, and how these understandings affect their triadic relationship.

RESEARCH DESIGN AND METHODS

We conducted a responsive evaluation including 28 semi-structured interviews with formal caregivers, informal caregivers, and residents. Walker’s expressive-collaborative model of morality (2007) was used as a theoretical lens to identify identities, values and roles in the triad.

RESULTS

Formal caregivers were assigned more moral responsibilities in the care process than residents and informal caregivers, particularly regarding decision-making authority. Formal caregivers considered this justified, while informal caregivers generally desired more influence. The attitude of residents on this matter remained relatively unclear. The diverging views on moral responsibilities between formal and informal caregivers led to relational tensions, impacting mutual trust and recognition between them.

DISCUSSION AND IMPLICATIONS

Walker’s model of morality provides a deeper understanding of the moral dynamics underlying the collaboration between formal caregivers, informal caregivers, and residents. Traditional hierarchies and a mismatch between healthcare and family ethics are implied to hinder informal caregiver involvement. Our findings call for practical and cultural adaptations on different levels within and outside nursing home organizations to improve the triadic collaborative relationship.
Probabilistic Deconvolution of SS waves for Imaging Fine Mantle Stratification (SHARP-SS)
Authors: Zhang Ziqi , Olugboji Tolulope , Kim Doyeon
Published: February 2025

Long-period underside SS wave reflections have been widely used to furnish global constraints on the presence and depth of mantle discontinuities and to document evidence for their origins, e.g., mineral phase-transformations in the transition zone, compositional changes in the mid-mantle, and dehydration-induced melting above and below the transition zone. For higher-resolution imaging, it is necessary to separate the signature of the source wavelet (SS arrival) from that of the distortion caused by the mantle reflectivity (SS precursors). Classical solutions to the general deconvolution problem include frequency-domain or time-domain deconvolution. However, these algorithms do not easily generalize when (1) the reflectivity series is of a much shorter period compared to the source wavelet, (2) the bounce point sampling is sparse, or (3) the source wavelet is noisy or hard to estimate. To address these problems, we propose a new technique called SHARP-SS: Sparse High-Resolution Algorithm for Reflection Profiling with SS waves. SHARP-SS is a Bayesian deconvolution algorithm that makes minimal a-priori assumptions on the noise model, source signature, and reflectivity structure. We test SHARP-SS using real data examples beneath the NoMelt Pacific Ocean region. We recover a low-velocity discontinuity at a depth of ∼69 ± 4 km which marks the base of the oceanic lithosphere, consistent with previous work derived from surface waves, body wave conversions, and ScS reverberations. We anticipate high-resolution fine mantle stratification imaging using SHARP-SS at locations where seismic stations are sparsely distributed.
Research on intelligent detection method of high-voltage circuit breaker based on PSO–CNN
Authors: Hua Xufen , Liu Zhigang
Published: February 2025

Through the intelligent detection of high-voltage circuit breakers, equipment faults can be detected and diagnosed in time, which can effectively prevent power accidents and ensure the safe operation of the power grid. In this paper, a detection method based on particle swarm optimization (PSO) and convolutional neural network (CNN) is proposed, and the parameter setting of CNN is optimized by PSO. The feature of vibration signal is extracted and the feature sample set is constructed. On this basis, the sample set is constructed and the experiment is carried out. The experimental results show that the proposed method has significant advantages in precision, recall rate, and F1 score compared with the traditional method; the precision can reach 0.926, the recall can reach 0.913, and the F1 score can reach 0.919. Future research could optimize the training process to reduce running time, as well as introduce more advanced data preprocessing techniques to improve data quality.
Research on industrial carbon emission prediction method based on CNN–LSTM under dual carbon goals
Authors: Xia Xuwei , Zhu Dongge , Sha Jiangbo , Ma Rui , Kang Wenni
Published: February 2025

In order to achieve the dual carbon goal, a prediction method of industrial carbon emissions based on CNN–LSTM was studied. The extended Kaya identity is used to measure the emissions, and the LMDI decomposition method is used to determine the influencing factors. The model inputs historical emission data, extracts spatial features through CNN, and then makes time series prediction by LSTM, and finally outputs the prediction results. Experiments show that this method can effectively predict carbon emissions in different scenarios and provide support for the goal of double carbon.
Implementation of artificial intelligence techniques in electric vehicles for battery management system
Authors: Sudhapriya K , Jaisiva S
Published: February 2025

The hybrid AI-based battery management system (HAI-BMS) is proposed to solve the complex problem of electric vehicle (EV) battery management. It combines conventional manipulation processes with system-gaining knowledge of neural networks and reinforcement learning algorithms. This simulation showcases the capability of AI-based BMS to transform electric-powered transportation by demonstrating substantial improvements to battery performance, lifespan, and average vehicle efficiency. By incorporating AI techniques into the BMSs of electric automobiles, the HAI-BMS is paving the manner for future transportation options that are sensible, bendy, and eco-friendly.
Research on the optimization strategy for shared energy storage configuration in new energy stations considering hydrogen production from renewable energy
Authors: Zhang Huaqing , Yang Yu , Qun Li , Zhe Zhang , Kuiyuan Liu , Di Chang
Published: February 2025

Renewable energy development and advanced storage technologies are key to reducing fossil fuel dependence and enabling the green transition. This study proposes a shared energy storage strategy for renewable energy station clusters to address fossil fuel dependence and support the green energy transition. By leveraging the spatiotemporal complementarities of storage demands, the approach improves system performance and output tracking. A cooperative investment model accommodates various energy storage technologies, reducing costs and enhancing efficiency. Case studies show the model strengthens station alliances, optimizes energy storage, and offers a cost-effective solution for renewable energy integration and increased hydrogen production profitability.
Architectural design of high-density urban vacant land plots on the basis of thermal environment analysis: the case of Macau BT8 and BT9 plots
Authors: Yang Shuai , Chen Yile , Zheng Liang
Published: February 2025

The purpose of this study is to use thermal environment analysis to investigate architectural design strategies for vacant land in high-density cities. Researchers used Rhino to construct a 3D model of the Macau BT8 and BT9 plots and imported the collected data, including terrain, meteorology, and surrounding buildings, into the model to accurately replicate the actual spatial environment. Moreover, we used Ladybug analysis to determine the sunshine distribution of the plot at a specific time. Finally, a design solution with a visual rendering effect was proposed by combining the upper-level planning constraints with the thermal environment simulation analysis results.
StomaGAN: Improving image-based analysis of stomata through Generative Adversarial Networks
Authors: Gibbs Jonathon A , Gibbs Alexandra J
Published: February 2025

Stomata regulate gas exchange between plants and the atmosphere, but analysing their morphology is challenging due to anatomical variability and artifacts during image acquisition. Deep learning (DL) can address these challenges but often requires large and diverse datasets, which are costly and error prone to produce. Generative adversarial networks (GANs) offer a solution by generating artificial data via unsupervised learning. However, GANs often suffer from problems including mode collapse, vanishing gradients, and network failure, particularly with small datasets. Here, we present StomaGAN, a deep convolutional GAN (DCGAN) with tailored modifications to address common GAN issues. We collected 559 stomatal impressions of field, or faba bean (Vicia faba) consisting of ~3,000 stoma, 80% of which were used to train StomaGAN. Evaluation metrics, including generator and discriminator loss progression and a mean Fréchet Inception Distance (FID) score of 61.4 across eight experimental runs confirms successful training. To validate StomaGAN, we generated artificial images to train a deep convolutional neural network (DCNN) based on the DeepLabV3 framework for stomata detection from real, unseen images. The DCNN achieved a mean Interception over Union (IoU) of 0.95 on artificial training images and a 0.91 on real, unseen, images across varying magnifications. Our results demonstrate that StomaGAN effectively generates high-quality synthetic datasets, enabling reliable stomatal detection and enhancing phenotypic analysis. This approach reduces the need for extensive manual data collection and simplifies complex morphological assessments.
Wide-ranging organic nitrogen diets of freshwater picocyanobacteria
Authors: Druce Elliot , Maberly Stephen C , Sánchez-Baracaldo Patricia
Published: February 2025

Freshwater picocyanobacteria (Syn/Pro clade) contribute substantially to the primary production of inland waters, especially when nitrogen is limiting or co-limiting. Nevertheless, they remain poorly understood ecologically and genomically, with research on their nitrogen acquisition mainly focused on inorganic sources. However, dissolved organic nitrogen is often a major component of the freshwater nitrogen pool and it is increasingly evident that many forms are bioavailable. Comparative genomic analyses, axenic growth assays, and proteomic analyses were used here to investigate organic nitrogen acquisition mechanisms in the Syn/Pro clade. Comparative analysis of the genomes of 295 freshwater and marine strains of picocyanobacteria identified a large diversity of amino acid transporters, the absence of degradation pathways for five amino acids (asparagine, phenylalanine, serine, tryptophan, and tyrosine), and alternative mechanisms for chitin assimilation (direct chitin catabolism vs initial acetylation to chitosan and subsequent degradation). Growth assays demonstrated the widespread bioavailability of amino acids, including basic amino acids though the known basic amino acid transporter is not encoded. This suggests further genetic components are involved, either through extracellular catabolism or the presence of novel transporters. Proteomic analysis demonstrates the dual utilization of nitrogen and carbon from the amino acid substrate and provides evidence for a mild stress response through the up-regulation of lysine biosynthesis and FtsH1, potentially caused by accumulation of secondary metabolites. Our results are relevant to understanding how picocyanobacteria have come to thrive in dissolved organic nitrogen-rich oligotrophic environments and explores how their different molecular capabilities may influence communities between habitats.
Carbon dioxide enhances Akkermansia muciniphila fitness and anti-obesity efficacy in high-fat diet mice
Authors: Wang Xiangfeng , Yang Qianqian , Shi Changping , Wang Yuyang , Guo Dingming , Wan Xuchun , Dong Pengyuan , Zhang Qianyao , Hu Yueyan , Zhang Ruilin , Yang Hongju , Chen Weihua , Liu Zhi
Published: February 2025

Numerous studies and clinical applications have underscored the therapeutic potential of the indigenous gut bacterium Akkermansia muciniphila in various diseases. However, our understanding of how A. muciniphila senses and responds to host gastrointestinal signals remains limited. Here, we demonstrate that A. muciniphila exhibits rapid growth, facilitated by its self-produced carbon dioxide, with key enzymes such as glutamate decarboxylase, carbonic anhydrase, and pyruvate ferredoxin oxidoreductase playing pivotal roles. Additionally, we design a novel delivery system, comprising calcium carbonate, inulin, A. muciniphila, and sodium alginate, which enhances A. muciniphila growth and facilitates the expression of part probiotic genes in mice intestinal milieu. Notably, the administration of this delivery system induces weight loss in mice fed high-fat diets. Furthermore, we elucidate the significant impact of carbon dioxide on the composition and functional genes of the human gut microbiota, with genes encoding carbonic anhydrase and amino acid metabolism enzymes exhibiting heightened responsiveness. These findings reveal a novel mechanism by which gut commensal bacteria sense and respond to gaseous molecules, thereby promoting growth. Moreover, they suggest the potential for designing rational therapeutic strategies utilizing live bacterial delivery systems to enhance probiotic growth and ameliorate gut microbiota-related diseases.
Promoter choice for XKS1 overexpression impacts xylose metabolism in Saccharomyces cerevisiae
Authors: de Souza Brenda Cristina , Vargas Beatriz de Oliveira , Seguchi Gustavo , Carazzolle Marcelo F , Guimarães Pereira Gonçalo Amarante , de Mello Fellipe da Silveira Bezerra
Published: February 2025

Aims

The impact of promoter selection on the overexpression of the XKS1 gene in Saccharomyces cerevisiae is investigated with a focus on optimizing xylose metabolism for second-generation ethanol production. The goal was to identify how different promoters affect the fermentation performance of laboratory and industrial yeast strains under various media conditions.

Methods and Results

Four constitutive promoters—TEF1p, ADH1p, PGK1p, and TDH3p—were tested to overexpress XKS1 in two strains of S. cerevisiae, one laboratory strain (BY4742) and one industrial strain (PE-2B), both engineered with a heterologous xylose isomerase pathway. The strains were evaluated in defined (YNB) and complex (YPDX) media, as well as a synthetic sugarcane hydrolysate, over a 144-hour fermentation period. Promoter choice significantly influenced cell growth, xylose consumption and ethanol production. In the laboratory strain, TEF1p yielded the highest ethanol production in YPDX, while TDH3p promoted higher biomass formation. In the industrial strain, ADH1p, TEF1p, and PGK1p led to high ethanol yields in YPDX, with ADH1p showing superior performance in the synthetic hydrolysate. RT-qPCR reveals lower XKS1 expression levels render a better trait for BY4742, while the opposite is observed for PE-2B.

Conclusions

It is demonstrated that promoter selection is crucial for optimizing XKS1 expression and xylose metabolism in S. cerevisiae. Promoters must be carefully tailored to the yeast strain and fermentation conditions to maximize ethanol production, providing strategic insights for enhancing the industrial fermentation of lignocellulosic biomass.
Karyotype evolution and speciation in Orthoptera
Authors: Palacios-Gimenez Octavio M , Castillo Elio R D , Schielzeth Holger
Published: February 2025

Karyotype evolution might fuel speciation and can thereby contribute to species diversity. To test the hypothesis that speciation and karyotype change are linked, we estimated anagenetic and cladogenetic rates of karyotype evolution as well as speciation rates in Orthoptera. We compiled the male diploid chromosome number and the number of visible chromosome arms (the fundamental number) from published sources for 1,541 species. Chromosome-associated speciation rates were estimated by jointly modeling cladogenetic and anagenetic character evolution and the phylogenetic birth-death process in a Bayesian statistical framework using a subset of 516 species from 14 families. Our findings unveiled heterogeneity among orthopteran families in the pace of karyotype evolution and whether it was linked to speciation. In 6/14 clades we found evidence supporting speciation-associated (cladogenetic) karyotype changes, while in 6/14 clades karyotype evolution was primarily anagenetic. The remaining clades (2/14) showed uncertainty in favor of either model. We further analysed whether flightless phenotype, and thus less mobile species, showed higher rates of karyotype evolution. We showed that the flightless phenotype is associated with the rate of chromosome loss. The finding indicates contrasting patterns of karyotype evolution within specific orthopteran lineages, thus emphasizing substantial diversity in the pace of this evolutionary process. It also implies that substantial changes in chromosome number, arising from instances of chromosomal gains and losses, are recurring events in orthopterans that are associated with reproductive isolation and speciation, at least in some groups.