bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advanced hybrid LSTM-transformer architecture for real-time multi-task prediction in engineering systems
Authors: Cao Kangjie , Zhang Ting , Huang Jueqiao 
Published: February 2024

AbstractIn the field of engineering systems—particularly in underground drilling and green stormwater management—real-time predictions are vital for enhancing operational performance, ensuring safety, and increasing efficiency. Addressing this niche, our study introduces a novel LSTM-transformer hybrid architecture, uniquely specialized for multi-task real-time predictions. Building on advancements in attention mechanisms and sequence modeling, our model integrates the core strengths of LSTM and Transformer architectures, offering a superior alternative to traditional predictive models. Further enriched with online learning, our architecture dynamically adapts to variable operational conditions and continuously incorporates new field data. Utilizing knowledge distillation techniques, we efficiently transfer insights from larger, pretrained networks, thereby achieving high predictive accuracy without sacrificing computational resources. Rigorous experiments on sector-specific engineering datasets validate the robustness and effectiveness of our approach. Notably, our model exhibits clear advantages over existing methods in terms of predictive accuracy, real-time adaptability, and computational efficiency. This work contributes a pioneering predictive framework for targeted engineering applications, offering actionable insights into.
Assessing the impact of three feeding stages on rumen bacterial community and physiological characteristics of Japanese Black cattle
Authors: Lee Huseong , Kim Minji , Masaki Tatsunori , Ikuta Kentaro , Iwamoto Eiji , Nishihara Koki , Nonaka Itoko , Ashihara Akane , Baek Youlchang , Lee Sungdae , Uemoto Yoshinobu , Haga Satoshi , Terada Fuminori , Roh Sanggun 
Published: February 2024

AbstractIn Japan, Japanese Black cattle, known for their exceptional meat quality owing to their abundant intramuscular fat, undergo a unique three-stage feeding system with varying concentrate ratios. There is limited research on physiological and rumen microbial changes in Japanese Black cattle during these stages. Therefore, this study aimed to examine Japanese Black steers in these three stages: early (T1, 12–14 months), middle (T2, 15–22 months), and late (T3, 23–30 months). The rumen bacteria of 21 cattle per phase was analyzed using 16S rRNA gene sequencing. Rumen bacterial diversity was significantly higher in T1, with a distinct distribution, than in T2 and T3. Specific phyla and genera were exclusive to each stage, reflecting the shifts in feed composition. Certain genera dominated each stage: T1 had Flexilinea, Streptococcus, Butyrivibrio, Selenomonas, and Kandleria; T2 had Bifidobacterium, Shuttleworthia, and Sharpea; and T3 had Acetitomaculum, Mycoplasma, Atopobium, and Howardella. Correlation analysis revealed significant associations between certain microbial populations and physiological parameters. These findings indicate that changes in energy content and feed composition are associated with physiological and ruminal alterations. This study may guide strategies to improve rumen health and productivity in Japanese Black cattle by modifying diets to specific fattening stages.
Development and validation of a simplified risk prediction model for preterm birth: a prospective cohort study in rural Ethiopia
Authors: Kassahun Eskeziaw Abebe , Gebreyesus Seifu Hagos , Tesfamariam Kokeb , Endris Bilal Shikur , Roro Meselech Assegid , Getnet Yalemwork , Hassen Hamid Yimam , Brusselaers Nele , Coenen Samuel 
Published: February 2024

AbstractPreterm birth is one of the most common obstetric complications in low- and middle-income countries, where access to advanced diagnostic tests and imaging is limited. Therefore, we developed and validated a simplified risk prediction tool to predict preterm birth based on easily applicable and routinely collected characteristics of pregnant women in the primary care setting. We used a logistic regression model to develop a model based on the data collected from 481 pregnant women. Model accuracy was evaluated through discrimination (measured by the area under the Receiver Operating Characteristic curve; AUC) and calibration (via calibration graphs and the Hosmer–Lemeshow goodness of fit test). Internal validation was performed using a bootstrapping technique. A simplified risk score was developed, and the cut-off point was determined using the “Youden index” to classify pregnant women into high or low risk for preterm birth. The incidence of preterm birth was 19.5% (95% CI:16.2, 23.3) of pregnancies. The final prediction model incorporated mid-upper arm circumference, gravidity, history of abortion, antenatal care, comorbidity, intimate partner violence, and anemia as predictors of preeclampsia. The AUC of the model was 0.687 (95% CI: 0.62, 0.75). The calibration plot demonstrated a good calibration with a p-value of 0.713 for the Hosmer–Lemeshow goodness of fit test. The model can identify pregnant women at high risk of preterm birth. It is applicable in daily clinical practice and could contribute to the improvement of the health of women and newborns in primary care settings with limited resources. Healthcare providers in rural areas could use this prediction model to improve clinical decision-making and reduce obstetrics complications.
Influence of university agricultural technology extension on efficient and sustainable agriculture
Authors: Dai Zhaoli , Wang Qing , Jiang Jiyu , Lu Yan 
Published: February 2024

AbstractAgricultural extension, as an important part of modern agriculture, can promote the scientific transformation of the traditional agricultural production model. This paper analysed the impact of university agricultural technology extension on efficient and sustainable agriculture using difference-in-differences model (DID). The results showed that university agricultural technology extension plays a facilitating role by influencing the coordinated development and green development dimensions in efficient and sustainable agriculture; there is a moderating effect of modern agricultural industrial parked in university agricultural technology extension and efficient and sustainable agriculture; there are significant differences in the impact of university agricultural technology extension on efficient and sustainable agriculture across regions and different levels of development. The findings have important implications for evaluating the effectiveness of current university agricultural extension policies and how to further promote university agricultural extension. The study also established an evaluation index system for efficient and sustainable agriculture, explored the mechanism of university agricultural extension in promoting efficient and sustainable agriculture, and enriched relevant theoretical research.
Convection-permitting climate models offer more certain extreme rainfall projections
Authors: Fosser Giorgia , Gaetani Marco , Kendon Elizabeth J. , Adinolfi Marianna , Ban Nikolina , Belušić Danijel , Caillaud Cécile , Careto João A. M. , Coppola Erika , Demory Marie-Estelle , de Vries Hylke , Dobler Andreas , Feldmann Hendrik , Goergen Klaus , Lenderink Geert , Pichelli Emanuela , Schär Christoph , Soares Pedro M. M. , Somot Samuel , Tölle Merja H. 
Published: February 2024

AbstractExtreme precipitation events lead to dramatic impacts on society and the situation will worsen under climate change. Decision-makers need reliable estimates of future changes as a basis for effective adaptation strategies, but projections at local scale from regional climate models (RCMs) are highly uncertain. Here we exploit the km-scale convection-permitting multi-model (CPM) ensemble, generated within the FPS Convection project, to provide new understanding of the changes in local precipitation extremes and related uncertainties over the greater Alpine region. The CPM ensemble shows a stronger increase in the fractional contribution from extreme events than the driving RCM ensemble during the summer, when convection dominates. We find that the CPM ensemble substantially reduces the model uncertainties and their contribution to the total uncertainties by more than 50%. We conclude that the more realistic representation of local dynamical processes in the CPMs provides more reliable local estimates of change, which are essential for policymakers to plan adaptation measures.
Modular tissue-in-a-CUBE platform to model blood-brain barrier (BBB) and brain interaction
Authors: Koh Isabel , Hagiwara Masaya 
Published: February 2024

AbstractWith the advent of increasingly sophisticated organoids, there is growing demand for technology to replicate the interactions between multiple tissues or organs. This is challenging to achieve, however, due to the varying culture conditions of the different cell types that make up each tissue. Current methods often require complicated microfluidic setups, but fragile tissue samples tend not to fare well with rough handling. Furthermore, the more complicated the human system to be replicated, the more difficult the model becomes to operate. Here, we present the development of a multi-tissue chip platform that takes advantage of the modularity and convenient handling ability of a CUBE device. We first developed a blood-brain barrier-in-a-CUBE by layering astrocytes, pericytes, and brain microvascular endothelial cells in the CUBE, and confirmed the expression and function of important tight junction and transporter proteins in the blood-brain barrier model. Then, we demonstrated the application of integrating Tissue-in-a-CUBE with a chip in simulating the in vitro testing of the permeability of a drug through the blood-brain barrier to the brain and its effect on treating the glioblastoma brain cancer model. We anticipate that this platform can be adapted for use with organoids to build complex human systems in vitro by the combination of multiple simple CUBE units.
Deficiency in PHD2-mediated hydroxylation of HIF2α underlies Pacak-Zhuang syndrome
Authors: Ferens Fraser G. , Taber Cassandra C. , Stuart Sarah , Hubert Mia , Tarade Daniel , Lee Jeffrey E. , Ohh Michael 
Published: February 2024

AbstractPacak-Zhuang syndrome is caused by mutations in the EPAS1 gene, which encodes for one of the three hypoxia-inducible factor alpha (HIFα) paralogs HIF2α and is associated with defined but varied phenotypic presentations including neuroendocrine tumors and polycythemia. However, the mechanisms underlying the complex genotype-phenotype correlations remain incompletely understood. Here, we devised a quantitative method for determining the dissociation constant (Kd) of the HIF2α peptides containing disease-associated mutations and the catalytic domain of prolyl-hydroxylase (PHD2) using microscale thermophoresis (MST) and showed that neuroendocrine-associated Class 1 HIF2α mutants have distinctly higher Kd than the exclusively polycythemia-associated Class 2 HIF2α mutants. Based on the co-crystal structure of PHD2/HIF2α peptide complex at 1.8 Å resolution, we showed that the Class 1 mutated residues are localized to the critical interface between HIF2α and PHD2, adjacent to the PHD2 active catalytic site, while Class 2 mutated residues are localized to the more flexible region of HIF2α that makes less contact with PHD2. Concordantly, Class 1 mutations were found to significantly increase HIF2α-mediated transcriptional activation in cellulo compared to Class 2 counterparts. These results reveal a structural mechanism in which the strength of the interaction between HIF2α and PHD2 is at the root of the general genotype-phenotype correlations observed in Pacak-Zhuang syndrome.
Membrane lipids drive formation of KRAS4b-RAF1 RBDCRD nanoclusters on the membrane
Authors: Shrestha Rebika , Carpenter Timothy S. , Van Que N. , Agamasu Constance , Tonelli Marco , Aydin Fikret , Chen De , Gulten Gulcin , Glosli James N. , López Cesar A. , Oppelstrup Tomas , Neale Chris , Gnanakaran Sandrasegaram , Gillette William K. , Ingólfsson Helgi I. , Lightstone Felice C. , Stephen Andrew G. , Streitz Frederick H. , Nissley Dwight V. , Turbyville Thomas J. 
Published: February 2024

AbstractThe oncogene RAS, extensively studied for decades, presents persistent gaps in understanding, hindering the development of effective therapeutic strategies due to a lack of precise details on how RAS initiates MAPK signaling with RAF effector proteins at the plasma membrane. Recent advances in X-ray crystallography, cryo-EM, and super-resolution fluorescence microscopy offer structural and spatial insights, yet the molecular mechanisms involving protein-protein and protein-lipid interactions in RAS-mediated signaling require further characterization. This study utilizes single-molecule experimental techniques, nuclear magnetic resonance spectroscopy, and the computational Machine-Learned Modeling Infrastructure (MuMMI) to examine KRAS4b and RAF1 on a biologically relevant lipid bilayer. MuMMI captures long-timescale events while preserving detailed atomic descriptions, providing testable models for experimental validation. Both in vitro and computational studies reveal that RBDCRD binding alters KRAS lateral diffusion on the lipid bilayer, increasing cluster size and decreasing diffusion. RAS and membrane binding cause hydrophobic residues in the CRD region to penetrate the bilayer, stabilizing complexes through β-strand elongation. These cooperative interactions among lipids, KRAS4b, and RAF1 are proposed as essential for forming nanoclusters, potentially a critical step in MAP kinase signal activation.
Generation of human iPSC-derived phrenic-like motor neurons to model respiratory motor neuron degeneration in ALS
Authors: Thiry Louise , Sirois Julien , Durcan Thomas M. , Stifani Stefano 
Published: February 2024

AbstractThe fatal motor neuron (MN) disease Amyotrophic Lateral Sclerosis (ALS) is characterized by progressive MN degeneration. Phrenic MNs (phMNs) controlling the activity of the diaphragm are prone to degeneration in ALS, leading to death by respiratory failure. Understanding of the mechanisms of phMN degeneration in ALS is limited, mainly because human experimental models to study phMNs are lacking. Here we describe a method enabling the derivation of phrenic-like MNs from human iPSCs (hiPSC-phMNs) within 30 days. This protocol uses an optimized combination of small molecules followed by cell-sorting based on a cell-surface protein enriched in hiPSC-phMNs, and is highly reproducible using several hiPSC lines. We show further that hiPSC-phMNs harbouring ALS-associated amplification of the C9orf72 gene progressively lose their electrophysiological activity and undergo increased death compared to isogenic controls. These studies establish a previously unavailable protocol to generate human phMNs offering a disease-relevant system to study mechanisms of respiratory MN dysfunction.
GlPRMT5 inhibits GlPP2C1 via symmetric dimethylation and regulates the biosynthesis of secondary metabolites in Ganoderma lucidum
Authors: Wang Zi , Qiu Hao , Li Yefan , Zhao Mingwen , Liu Rui 
Published: February 2024

AbstractPRMT5, a type II arginine methyltransferase, is involved in transcriptional regulation, RNA processing and other biological processes and signal transduction. Secondary metabolites are vital pharmacological compounds in Ganoderma lucidum, and their content is an important indicator for evaluating the quality of G. lucidum. Here, we found that GlPRMT5 negatively regulates the biosynthesis of secondary metabolites. In further in-depth research, GlPP2C1 (a type 2C protein phosphatase) was identified out as an interacting protein of GlPRMT5 by immunoprecipitation-mass spectrometry (IP-MS). Further mass spectrometry detection revealed that GlPRMT5 symmetrically dimethylates the arginine 99 (R99) and arginine 493 (R493) residues of GlPP2C1 to weaken its activity. The symmetrical dimethylation modification of the R99 residue is the key to affecting GlPP2C1 activity. Symmetrical demethylation-modified GlPP2C1 does not affect the interaction with GlPRMT5. In addition, silencing GlPP2C1 clearly reduced GA content, indicating that GlPP2C1 positively regulates the biosynthesis of secondary metabolites in G. lucidum. In summary, this study reveals the molecular mechanism by which GlPRMT5 regulates secondary metabolites, and these studies provide further insights into the target proteins of GlPRMT5 and symmetric dimethylation sites. Furthermore, these studies provide a basis for the mutual regulation between different epigenetic modifications.
Discovery of late Quaternary giant magnetofossils in the Bay of Bengal
Authors: Kadam Nitin , Badesab Firoz , Lascu Ioan , Wagner Courtney L. , Gaikwad Virsen , Saha Abhishek , Sangode Satish , Venkateshwarlu Mamilla 
Published: February 2024

AbstractUnusually large and enigmatic giant magnetofossils are well-documented in sediments deposited during and surrounding climatic events such as the Paleocene-Eocene Thermal Maximum (~56 Ma) and Middle Eocene Climatic Optimum (~40 Ma). However, the absence of giant magnetofossil modern analogues raises intriguing questions about their origin and formation mechanism. In this study, we report the discovery of giant magnetofossils within late Quaternary sediments retrieved from the Bay of Bengal (BoB), the youngest giant magnetofossils yet reported. First-order reversal curve diagrams of BoB sediments display a central ridge feature, a characteristic magnetic signature of non-interacting single domain magnetofossils. Scanning electron microscopy examinations reveal giant magnetofossils with needle, spindle, bullet, and spearhead shapes. We use high-resolution transmission electron microscopy, with electron diffraction and energy dispersive spectrometry, to confirm their distinctive morphologies and magnetite crystal structure. Our environmental magnetic and geochemical data suggest that an influx of fluvially derived reactive iron and organic carbon, combined with persistent suboxic conditions, supported the proliferation of giant magnetofossil-producing organisms. The discovery of a modern analogue to ancient giant magnetofossils expands our understanding of their temporal distribution within the geological record and is a promising step toward elucidating the nature of the organisms responsible for their formation.
Defining national net zero goals is critical for food and land use policy
Authors: Bishop George , Duffy Colm , Prudhomme Rémi , Cowie Annette , O’Donoghue Cathal , Cain Michelle , Lanigan Gary J. , Styles David 
Published: February 2024

AbstractThe identification of agriculture and land use configurations that achieve net zero (NZ) greenhouse gas emissions is critical to inform appropriate land use and food policy, yet national NZ targets lack consistent definitions. Here, 3000 randomised scenarios projecting future agricultural production and compatible land use combinations in Ireland were screened using ten NZ definitions. When aggregating carbon dioxide, methane, and nitrous oxide emissions using various methods, 1–85% of scenarios met NZ criteria. Despite considerable variation, common actions emerged across definitions, including high rates of afforestation, organic soil re-wetting, and cattle destocking. Ambitious technical abatement of agricultural emissions moderated, but could not substitute, these actions. With abatement, 95th percentile milk output varied from 11–91% of 2021 output, but was associated with reductions of up to 98% in suckler-beef production, and a 47–387% increase in forest cover. Achieving NZ will thus require transformation of Ireland’s land sector. Lagging land use change effects require urgent action, but sustaining a just transition will require visioning of future NZ land use combinations supporting a sustainable and resilient food system, alongside an expanding circular bioeconomy. We provide new insight into the sensitivity of such visioning to NZ definitions, pointing to an urgent need for international consensus on the accounting of methane emissions in NZ targets.
Socioeconomic deprivation and illness trajectory in the Scottish population after COVID-19 hospitalization
Authors: Morrow Andrew J. , Sykes Robert , Saleh Merna , Zahra Baryab , MacIntosh Alasdair , Kamdar Anna , Bagot Catherine , Bayes Hannah K. , Blyth Kevin G. , Bulluck Heerajnarain , Carrick David , Church Colin , Corcoran David , Findlay Iain , Gibson Vivienne B. , Gillespie Lynsey , Grieve Douglas , Barrientos Pauline Hall , Ho Antonia , Lang Ninian N. , Lowe David J. , Lennie Vera , Macfarlane Peter W. , Mayne Kaitlin J. , Mark Patrick B. , McConnachie Alex , McGeoch Ross , Nordin Sabrina , Payne Alexander , Rankin Alastair J. , Robertson Keith , Ryan Nicola , Roditi Giles , Sattar Naveed , Stobo David , Allwood-Spiers Sarah , Touyz Rhian M. , Veldtman Gruschen , Weeden Sarah , Weir Robin , Watkins Stuart , Welsh Paul , Mangion Kenneth , Berry Colin 
Published: February 2024

Abstract
Background
The associations between deprivation and illness trajectory after hospitalisation for coronavirus disease-19 (COVID-19) are uncertain.

Methods
A prospective, multicentre cohort study was conducted on post-COVID-19 patients, enrolled either in-hospital or shortly post-discharge. Two evaluations were carried out: an initial assessment and a follow-up at 28–60 days post-discharge. The study encompassed research blood tests, patient-reported outcome measures, and multisystem imaging (including chest computed tomography (CT) with pulmonary and coronary angiography, cardiovascular and renal magnetic resonance imaging). Primary and secondary outcomes were analysed in relation to socioeconomic status, using the Scottish Index of Multiple Deprivation (SIMD). The EQ-5D-5L, Brief Illness Perception Questionnaire (BIPQ), Patient Health Questionnaire-4 (PHQ-4) for Anxiety and Depression, and the Duke Activity Status Index (DASI) were used to assess health status.

Results
Of the 252 enrolled patients (mean age 55.0 ± 12.0 years; 40% female; 23% with diabetes), deprivation status was linked with increased BMI and diabetes prevalence. 186 (74%) returned for the follow-up. Within this group, findings indicated associations between deprivation and lung abnormalities (p = 0.0085), coronary artery disease (p = 0.0128), and renal inflammation (p = 0.0421). Furthermore, patients with higher deprivation exhibited worse scores in health-related quality of life (EQ-5D-5L, p = 0.0084), illness perception (BIPQ, p = 0.0004), anxiety and depression levels (PHQ-4, p = 0.0038), and diminished physical activity (DASI, p = 0.002). At the 3-month mark, those with greater deprivation showed a higher frequency of referrals to secondary care due to ongoing COVID-19 symptoms (p = 0.0438). However, clinical outcomes were not influenced by deprivation.

Conclusions
In a post-hospital COVID-19 population, socioeconomic deprivation was associated with impaired health status and secondary care episodes. Deprivation influences illness trajectory after COVID-19.