bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proinflammatory dietary pattern and risk of total and subtypes of breast cancer among US women
Authors: Romanos-Nanclares Andrea , Willett Walter C , Rosner Bernard , Stover Daniel G , Sardesai Sagar D , Holmes Michelle D , Chen Wendy Y , Tamimi Rulla M , Tabung Fred K , Eliassen A Heather 
Published: November 2024

Abstract

Background
Dietary patterns promoting chronic inflammation, including the empirical dietary inflammatory pattern (EDIP), have been associated with certain cancers. Investigating whether this dietary pattern is associated with breast cancer—where the role of inflammation is less well-defined—could provide valuable insights and potentially improve strategies for preventing this cancer.

Methods
We prospectively followed 76 386 women from Nurses’ Health Study (NHS, 1984-2018) and 92 886 women from Nurses’ Health Study II (NHSII, 1991-2019). Diet was assessed by food frequency questionnaires every 4 years, starting at baseline. The inflammatory potential of diet was evaluated using the validated EDIP based on plasma C-reactive protein, interleukin-6, and tumor necrosis factor α-R2. Higher scores indicate higher dietary inflammatory potential. Hazard ratios (HRs) and 95% confidence intervals (CIs) of overall and subtypes of breast cancer were estimated using multivariable-adjusted Cox regression models.

Results
During 4 490 842 person-years of follow-up, we documented 11 026 breast cancer cases. Women in the highest compared with the lowest EDIP quintile were at higher breast cancer risk (HRQ5vsQ1 = 1.12, 95% CI = 1.05 to 1.19; Ptrend &lt; .001). The association was stronger for estrogen receptor negative tumors (HRQ5vsQ1 = 1.29, 95% CI = 1.09 to 1.53; Ptrend = .003). Also, we observed that the association of EDIP with breast cancer risk differed by molecular subtype, with the strongest association observed with basal-like tumors (HRQ5vsQ1 = 1.80, 95% CI = 1.20 to 2.71; Ptrend = .004).

Conclusions
Higher EDIP scores were associated with a modestly increased risk of breast cancer, which was more pronounced for estrogen receptor negative and basal-like breast tumors. These results support the hypothesis that diet-related inflammation plays a role in breast cancer etiology, particularly tumors lacking hormone receptors.
Roflumilast mitigates cisplatin-induced nephrotoxicity by regulating TNF-α/TNFR1/TNFR2/Fas/Caspase mediated apoptosis and inflammatory signals
Authors: Patel Priyal , Patel Sandip , Patel Yash , Chudasama Piyush , Soni Shailesh , Patel Samir , Raval Manan 
Published: November 2024

Abstract

Purpose
The study aimed to evaluate the effect of roflumilast on modulating TNF-α/Caspase mediated cellular signals in cisplatin-induced nephrotoxicity in rats.

Methods
The rats (Male Wistar) were divided into five groups: normal control, disease control (cisplatin: 7 mg/kg i.p.), and cisplatin + roflumilast (0.25, 0.5, and 1 mg/kg b.w., p.o.). Cisplatin was administrated to rats on 0 day, and roflumilast treatment was started from the 6th–15th days. Blood and tissue were collected. Tissue was used to measure oxidative stress, such as malondialdehyde, superoxide dismutase, and catalase. Gene expression study involved real-time PCR of key genes linked with inflammation and apoptosis, i.e. Tnf-α, Tnfr1, Tnfr2, Fas, Nfkb, Casp3, Casp8, and Nrf2.

Findings
Cisplatin showed decreased serum creatinine and urea, high albumin, and total protein. Cisplatin elevated the malondialdehyde and reduced superoxide dismutase and catalase activity. Cisplatin also attributed an overexpression of Tnf-α, Tnfr1, Tnfr2, Nfkb, Fas, Casp3, and Casp8, and a decrease in the Nrf2 gene. Roflumilast decreased creatinine and urea and increased albumin and total protein levels. Roflumilast also downregulated the expression of Tnf-α, Tnfr1, Tnfr2, Nfkb, Fas, Casp3, and Casp8 and upregulated the Nrf2 gene expression.

Conclusion
Roflumilast manifested as a potential reno-protective agent against cisplatin-induced nephrotoxicity.
Object oriented data analysis of surface motion time series in peatland landscapes
Authors: Mitchell Emily G , Dryden Ian L , Fallaize Christopher J , Andersen Roxane , Bradley Andrew V , Large David J , Sowter Andrew 
Published: November 2024

Abstract
Peatlands account for 10% of UK land area, 80% of which are degraded to some degree, emitting carbon at a similar magnitude to oil refineries or landfill sites. A lack of tools for rapid and reliable assessment of peatland condition has limited monitoring of vast areas of peatland and prevented targeting areas urgently needing action to halt further degradation. Measured using interferometric synthetic aperture radar (InSAR), peatland surface motion is highly indicative of peatland condition, largely driven by the eco-hydrological change in the peatland causing swelling and shrinking of the peat substrate. The computational intensity of recent methods using InSAR time series to capture the annual functional structure of peatland surface motion becomes increasingly challenging as the sample size increases. Instead, we utilize the behaviour of the entire peatland surface motion time series using object oriented data analysis to assess peatland condition. Bayesian cluster analysis based on the functional structure of the surface motion time series finds areas indicative of soft/wet peatlands, drier/shrubby peatlands, and thin/modified peatlands. The posterior distribution of the assigned peatland types enables the scale of peatland degradation to be assessed, which will guide future cost-effective decisions for peatland restoration.
The Influence of Neck Pain and Sleep Quantity on Headache Burden in Service Members With and Without Mild Traumatic Brain Injury: An Observational Study
Authors: Reid Matthew W , Lu Lisa H , Hershaw Jamie N , Kennedy Jan E 
Published: November 2024

ABSTRACT

Introduction
Headache is the most overwhelmingly reported symptom following mild traumatic brain injury (mTBI). The upper cervical spine has been implicated in headache etiology, and cervical dysfunction may result in neck pain that influences the experience of headache. Sleep problem is the second most reported symptom following mTBI. We explored the contribution of neck pain (as a potential proxy for cervical dysfunction) on headache burden along with the contribution of sleep quantity following mTBI.

Materials and Methods
Retrospective data from a repository consisting of service members recruited from primary care, with (N = 493) and without a history of mTBI (N = 63), was used for analysis. Portions of the Neurobehavioral Symptom Inventory, Pittsburgh Sleep Quality Index, and Orebro Musculoskeletal Pain Questionnaire were used for headache, sleep, and neck pain measures.

Results
Demographic and military characteristics that differed between groups were treated as covariates in analyses. Group comparisons revealed significant differences in the expected direction on all measures: mTBI &gt; controls on headache and neck pain; controls &gt; mTBI on sleep quantity. Regression revealed that neck pain accounted for the most variance in headache score, followed by group membership and sleep quantity. When analyzing groups separately, no difference in the pattern of results was revealed in the mTBI group. In the control group, variance in headache score was only significantly related to neck pain.

Conclusions
Amongst service members who sought service from primary care, neck pain explains more variance in headache burden than mTBI history or sleep quantity, supporting that cervical dysfunction may be a salient factor associated with headache. Neck functioning may be a potential area of intervention in the management of headaches.
ExoMol line lists – LXIV. Empirical rovibronic spectra of phosphorous mononitride (PN) covering the IR and UV regions
Authors: Semenov Mikhail , El-Kork Nayla , Yurchenko Sergei N , Tennyson Jonathan 
Published: November 2024

ABSTRACT
A new phosphorous mononitride ($^{31}$P$^{14}$N and ${}^{31}$P${}^{15}$N) line list PaiN covering infrared, visible, and ultraviolet regions is presented. The PaiN line list extending to the $A\, {}^{1}\Pi$–$X\, {}^{1}\Sigma ^{+}$ vibronic band system replaces the previous YYLT ExoMol line list for PN. A thorough analysis of high-resolution experimental spectra from the literature involving the $X\, {}^{1}\Sigma ^{+}$ and $A\, {}^{1}\Pi$ states is conducted, and many perturbations to the $A\, {}^{1}\Pi$ energies are considered as part of a comprehensive MARVEL (Measured-Active-Rotational-Vibrational-Energy-Levels) study. Ab initio potential energy and coupling curves from the previous work are refined by fitting their analytical representations to 1224 empirical energy levels determined using the MARVEL procedure. The PaiN line list is compared to previously observed spectra, recorded and calculated lifetimes, and previously calculated partition functions. The ab initio transition dipole moment curve for the A–X band is scaled to match experimentally measured lifetimes. The line list is suitable for temperatures up to 5000 K and wavelengths longer than 121 nm. PaiN is available from www.exomol.com.
Digital Image Processing to Detect Adaptive Evolution
Authors: Amin Md Ruhul , Hasan Mahmudul , DeGiorgio Michael 
Published: November 2024

Abstract
In recent years, advances in image processing and machine learning have fueled a paradigm shift in detecting genomic regions under natural selection. Early machine learning techniques employed population-genetic summary statistics as features, which focus on specific genomic patterns expected by adaptive and neutral processes. Though such engineered features are important when training data are limited, the ease at which simulated data can now be generated has led to the recent development of approaches that take in image representations of haplotype alignments and automatically extract important features using convolutional neural networks. Digital image processing methods termed α-molecules are a class of techniques for multiscale representation of objects that can extract a diverse set of features from images. One such α-molecule method, termed wavelet decomposition, lends greater control over high-frequency components of images. Another α-molecule method, termed curvelet decomposition, is an extension of the wavelet concept that considers events occurring along curves within images. We show that application of these α-molecule techniques to extract features from image representations of haplotype alignments yield high true positive rate and accuracy to detect hard and soft selective sweep signatures from genomic data with both linear and nonlinear machine learning classifiers. Moreover, we find that such models are easy to visualize and interpret, with performance rivaling those of contemporary deep learning approaches for detecting sweeps.
Natural variation of magnesium stable isotopes in human kidney stones
Authors: Liu Jinke , Han Guilin , Tian Yu , Qu Rui , Wang Di , Shen Yanan 
Published: November 2024

Abstract
Kidney stones, as typical biominerals produced within the human body, pose a significant threat to human health, affecting over 12% of the global population. However, the exact mechanisms underlying their formation are not fully understood. Recent metal isotopic analysis provides a new way to study the roles of metal cations in biological processes within organisms. Here, we report the Mg isotope ratios of human kidney stones for the first time. The total range of measured values for δ26Mg in kidney stones is 1.05‰, from −1.12‰ to −0.07‰. Our data exhibit a significant 24Mg enrichment compared with the values calculated from density functional theory. We suggest that the Mg-isotopic fractionations in vivo are linked to active Mg transport mediated by proteins during intestinal absorption and preferential renal reabsorption of ionized Mg2+ via tight junctional proteins. Our results indicate that the inhibitory effect of Mg on kidney stones is related to the kink-blocking mechanism, and the incorporation of hydrated Mg lessens the extent of inhibition and the magnitude of isotope discrimination. We show that metal isotopes provide new insights into the underlying biological processes and human health.
Antisense transcription is associated with expression of metal resistance determinants in Cupriavidus metallidurans CH34
Authors: Große Cornelia , Grau Jan , Herzberg Martin , Nies Dietrich H 
Published: November 2024

Abstract
Cupriavidus metallidurans is able to thrive in metal-rich environments but also survives metal starvation. Expression of metal resistance determinants in C. metallidurans was investigated on a global scale. Cupriavidus metallidurans was challenged with a MultiTox metal mix specifically designed for the wildtype strain CH34 and its plasmid-free derivative AE104, including treatment with ethylenediamintetraacetate (EDTA), or without challenge. The sense and antisense transcripts were analyzed in both strains and under all three conditions by RNASeq. A total of 10 757 antisense transcripts (ASTs) were assigned to sense signals from genes and untranslated regions, and 1 319 of these ASTs were expressed and were longer than 50 bases. Most of these (82%) were dual-use transcripts that contained antisense and sense regions, but ASTs (16%) were also observed that had no sense regions. Especially in metal-treated cells of strains CH34 and AE104, up- or down-regulated sense transcripts were accompanied by antisense transcription activities that were also regulated. The presence of selected asRNAs was verified by reverse transcription polymerase chain reaction (RT-PCR). Following metal stress, expression of genes encoding components of the respiratory chain, motility, transcription, translation, and protein export were down-regulated. This should also affect the integration of the metal efflux pumps into the membrane and the supply of the energy required to operate them. To solve this dilemma, transcripts for the metal efflux pumps may be stabilized by interactions with ASTs to allow their translation and import into the membrane. Alternatively, metal stress possibly causes recruitment of RNA polymerase from housekeeping genes for preferential expression of metal resistance determinants.
ECOD: integrating classifications of protein domains from experimental and predicted structures
Authors: Schaeffer R Dustin , Medvedev Kirill E , Andreeva Antonina , Chuguransky Sara Rocio , Pinto Beatriz Lazaro , Zhang Jing , Cong Qian , Bateman Alex , Grishin Nick V 
Published: November 2024

Abstract
The evolutionary classification of protein domains (ECOD) classifies protein domains using a combination of sequence and structural data (http://prodata.swmed.edu/ecod). Here we present the culmination of our previous efforts at classifying domains from predicted structures, principally from the AlphaFold Database (AFDB), by integrating these domains with our existing classification of PDB structures. This combined classification includes both domains from our previous, purely experimental, classification of domains as well as domains from our provisional classification of 48 proteomes in AFDB predicted from model organisms and organisms of concern to global health. ECOD classifies over 1.8 M domains from over 1000 000 proteins collectively deposited in the PDB and AFDB. Additionally, we have changed the F-group classification reference used for ECOD, deprecating our original ECODf library and instead relying on direct collaboration with the Pfam sequence family database to inform our classification. Pfam provides similar coverage of ECOD with family classification while being more accurate and less redundant. By eliminating duplication of effort, we can improve both classifications. Finally, we discuss the initial deployment of DrugDomain, a database of domain-ligand interactions, on ECOD and discuss future plans.
Harmonizome 3.0: integrated knowledge about genes and proteins from diverse multi-omics resources
Authors: Diamant Ido , Clarke Daniel J B , Evangelista John Erol , Lingam Nathania , Ma’ayan Avi 
Published: November 2024

Abstract
By processing and abstracting diverse omics datasets into associations between genes and their attributes, the Harmonizome database enables researchers to explore and integrate knowledge about human genes from many central omics resources. Here, we introduce Harmonizome 3.0, a significant upgrade to the original Harmonizome database. The upgrade adds 26 datasets that contribute nearly 12 million associations between genes and various attribute types such as cells and tissues, diseases, and pathways. The upgrade has a dataset crossing feature to identify gene modules that are shared across datasets. To further explain significantly high gene set overlap between dataset pairs, a large language model (LLM) composes a paragraph that speculates about the reasons behind the high overlap. The upgrade also adds more data formats and visualization options. Datasets are downloadable as knowledge graph (KG) assertions and visualized with Uniform Manifold Approximation and Projection (UMAP) plots. The KG assertions can be explored via a user interface that visualizes gene–attribute associations as ball-and-stick diagrams. Overall, Harmonizome 3.0 is a rich resource of processed omics datasets that are provided in several AI-ready formats. Harmonizome 3.0 is available at https://maayanlab.cloud/Harmonizome/.
InterPro: the protein sequence classification resource in 2025
Authors: Blum Matthias , Andreeva Antonina , Florentino Laise Cavalcanti , Chuguransky Sara Rocio , Grego Tiago , Hobbs Emma , Pinto Beatriz Lazaro , Orr Ailsa , Paysan-Lafosse Typhaine , Ponamareva Irina , Salazar Gustavo A , Bordin Nicola , Bork Peer , Bridge Alan , Colwell Lucy , Gough Julian , Haft Daniel H , Letunic Ivica , Llinares-López Felipe , Marchler-Bauer Aron , Meng-Papaxanthos Laetitia , Mi Huaiyu , Natale Darren A , Orengo Christine A , Pandurangan Arun P , Piovesan Damiano , Rivoire Catherine , Sigrist Christian J A , Thanki Narmada , Thibaud-Nissen Françoise , Thomas Paul D , Tosatto Silvio C E , Wu Cathy H , Bateman Alex 
Published: November 2024

Abstract
InterPro (https://www.ebi.ac.uk/interpro) is a freely accessible resource for the classification of protein sequences into families. It integrates predictive models, known as signatures, from multiple member databases to classify sequences into families and predict the presence of domains and significant sites. The InterPro database provides annotations for over 200 million sequences, ensuring extensive coverage of UniProtKB, the standard repository of protein sequences, and includes mappings to several other major resources, such as Gene Ontology (GO), Protein Data Bank in Europe (PDBe) and the AlphaFold Protein Structure Database. In this publication, we report on the status of InterPro (version 101.0), detailing new developments in the database, associated web interface and software. Notable updates include the increased integration of structures predicted by AlphaFold and the enhanced description of protein families using artificial intelligence. Over the past two years, more than 5000 new InterPro entries have been created. The InterPro website now offers access to 85 000 protein families and domains from its member databases and serves as a long-term archive for retired databases. InterPro data, software and tools are freely available.
CATH v4.4: major expansion of CATH by experimental and predicted structural data
Authors: Waman Vaishali P , Bordin Nicola , Lau Andy , Kandathil Shaun , Wells Jude , Miller David , Velankar Sameer , Jones David T , Sillitoe Ian , Orengo Christine 
Published: November 2024

Abstract
CATH (https://www.cathdb.info) is a structural classification database that assigns domains to the structures in the Protein Data Bank (PDB) and AlphaFold Protein Structure Database (AFDB) and adds layers of biological information, including homology and functional annotation. This article covers developments in the CATH classification since 2021. We report the significant expansion of structural information (180-fold) for CATH superfamilies through classification of PDB domains and predicted domain structures from the Encyclopedia of Domains (TED) resource. TED provides information on predicted domains in AFDB. CATH v4.4 represents an expansion of ∼64 844 experimentally determined domain structures from PDB. We also present a mapping of ∼90 million predicted domains from TED to CATH superfamilies. New PDB and TED data increases the number of superfamilies from 5841 to 6573, folds from 1349 to 2078 and architectures from 41 to 77. TED data comprises predicted structures, so these new folds and architectures remain hypothetical until experimentally confirmed. CATH also classifies domains into functional families (FunFams) within a superfamily. We have updated sequences in FunFams by scanning FunFam-HMMs against UniProt release 2024_02, giving a 276% increase in FunFams coverage. The mapping of TED structural domains has resulted in a 4-fold increase in FunFams with structural information.
The PLSDB 2025 update: enhanced annotations and improved functionality for comprehensive plasmid research
Authors: Molano Leidy-Alejandra G , Hirsch Pascal , Hannig Matthias , Müller Rolf , Keller Andreas 
Published: November 2024

Abstract
Plasmids are extrachromosomal DNA molecules in bacteria and archaea, playing critical roles in horizontal gene transfer, antibiotic resistance, and pathogenicity. Since its first release in 2018, our database on plasmids, PLSDB, has significantly grown and enhanced its content and scope. From 34 513 records contained in the 2021 version, PLSDB now hosts 72 360 entries. Designed to provide life scientists with convenient access to extensive plasmid data and to support computer scientists by offering curated datasets for artificial intelligence (AI) development, this latest update brings more comprehensive and accurate information for plasmid research, with interactive visualization options. We enriched PLSDB by refining the identification and classification of plasmid host ecosystems and host diseases. Additionally, we incorporated annotations for new functional structures, including protein-coding genes and biosynthetic gene clusters. Further, we enhanced existing annotations, such as antimicrobial resistance genes and mobility typing. To accommodate these improvements and to host the increase plasmid sets, the webserver architecture and underlying data structures of PLSDB have been re-reconstructed, resulting in decreased response times and enhanced visualization of features while ensuring that users have access to a more efficient and user-friendly interface. The latest release of PLSDB is freely accessible at https://www.ccb.uni-saarland.de/plsdb2025.