bluuebunny/crossref_metadata_2025_split huggingface dataset:
Expired blood transfusion and mortality outcomes in combat trauma patients
Authors: Riley Brian C. , Phuong Jimmy , Hasan Rida A. , Stansbury Lynn G. , Hess John R. , Roubik Daniel J. 
Published: July 2024

AbstractBackgroundExpired blood can be transfused if clinically indicated but outcome data do not exist. We hypothesized that modestly outdated blood can effectively support a hemorrhaging patient until surgical control is achieved. This study assessed whether expired blood was associated with mortality in combat trauma patients.Study Design and MethodsA retrospective analysis of Armed Services Blood Program and Department of Defense Trauma Registry databases evaluated combat casualty records (2001–2023). The intervention of interest was transfusion of at least one unit of whole blood (WB), red blood cells (RBC), or platelets within one week past expiration. The outcome of interest was mortality at discharge. A control cohort that only received in‐date blood was matched to the treatment cohort for logistic regression analysis.ResultsOne hundred patients received expired RBCs (86), WB (11), and platelets (3). Mortality at discharge was 11.6% for expired RBC recipients and 13.4% for the control cohort (p = .97). After adjustment for injury severity, expired RBCs were not associated with mortality (OR = 0.40 [95% CI, 0.14–1.16]; p = .09). Of 10 patients who received the most expired RBCs by volume or storage duration, two were deceased at discharge. All 14 expired WB and platelet recipients were alive at discharge, but sample sizes were underpowered for regression analysis.DiscussionTransfusion of modestly outdated RBCs was not associated with mortality in combat trauma patients. Expired WB and platelet recipients did well, but sample sizes were too small to draw significant conclusions. Expired blood should be further investigated for possible use in extenuating circumstances.
E-Fuels as Reduced Carbon Emission Options
Authors: Huey Carolyn , Metghalchi Hameed , Levendis Yiannis 
Published: July 2024

Abstract
Synthetic “E-fuels,” or electro-fuels, have been introduced as a potential reduced carbon emissions energy source for power generation and vehicle propulsion applications. Environmental change is needed, with the transportation sector alone producing approximately a quarter of global greenhouse gas (GHG) emissions. Hydrogen, produced from electrolysis to avoid GHG production, is used along with CO2 or nitrogen to generate these electro-fuels, through the Fischer–Tropsch process. Direct air capture (DAC) of atmospheric carbon dioxide or biomass combustion effluents can provide sources for these gases to be combined with hydrogen to generate synthetic methanol, methane, or ammonia—the three most widely discussed E-fuels. In addition, “ER-fuels,” or electrically reformed fuels, are a similar option to E-fuels, where refinery fuel gases, such as ethane or propane, are reformed before synthesis to produce the final fuel. E-fuels, on the other hand, are generated from hydrogen and carbon either captured or produced, not from existing fuels. Redox couples, such as vanadium, can additionally be used as zero emission fuels; they are “electrically rechargeable” in that, through electrolysis, the reducing agent is produced, and then using a fuel cell (FC), the reverse occurs, and electrons plus the oxidizing agent are produced. These synthetic fuels are approximately carbon neutral when the hydrogen is sourced from renewable powered electrolysis, mainly solar and wind energy, as the amount of carbon dioxide consumed is roughly equivalent to the amount produced upon their combustion or FC energy conversion. Combustion in gas turbines or reciprocating piston-cylinder engines and FC electricity generation are the two main uses for extracting energy from E-fuels. Fuel cells are shown to have higher efficiency, but combustion provides fewer infrastructure changes and easier implementation. Both options provide a method for controlling carbon emissions using E-fuels as opportunities for energy storage.
Devonian plutons in the eastern Meguma terrane, Nova Scotia, Canada: zircon U–Pb, Lu–Hf, and O isotopic compositions, age, and petrogenetic implications
Authors: Archibald Donnelly B. , Barr Sandra M. , White Chris E. , Nickerson Shae J. , Stern Richard A. , Luo Yan , Pearson Graham D. 
Published: July 2024

Abundant granitic plutons intruded the eastern Meguma terrane of Nova Scotia in the middle- to late Devonian. Less voluminous diorite–tonalite and gabbro intrusions are associated with the granitic plutons along the northern margin of the terrane adjacent to the Cobequid–Chedabucto fault zone. All plutons contain metasedimentary xenoliths, and the mafic plutons show magma mingling textures with their adjacent granitic plutons. New U–Pb zircon data from autocrystic zircon in 13 samples indicate coeval emplacement of mafic and granitic plutons between ca. 382 and 368 Ma. However, the zircon grains contain numerous inherited domains that range in age from Palaeoproterozoic to Devonian. These inherited ages correspond to detrital zircon U–Pb dates from the Cambrian to Ordovician metasedimentary host rocks. Zircon oxygen isotopic data (δ18O) are between +7.4 ± 0.2‰ and +9.3 ± 0.3‰ indicating significant involvement of the crust as the magma source or contaminant. If the high δ18Ozrn values are a result of contamination, the contaminant was likely the metasedimentary rocks of the Meguma terrane. Hafnium isotopic data from autocrystic zircon have εHf( t) between −6.0 ± 1.5 and +2.1 ± 2.5. The new zircon U–Pb, O, and Hf isotopic data from plutons in the eastern Meguma terrane are indistinguishable from published data from the South Mountain Batholith. The data suggest that Devonian magmatism in the Meguma terrane post-dated the main orogenic event that caused folding and regional metamorphism and involved the same magma source and/or contaminants throughout the terrane.
Signature flips in time-varying $$\Lambda (t)$$ cosmological models with observational data
Authors: Myrzakulov Yerlan , Koussour M. , Karimov M. , Rayimbaev J. 
Published: July 2024

AbstractIn this study, we investigate signature flips within the framework of cosmological models featuring a time-varying vacuum energy term $$\Lambda (t)$$

Λ
(
t
)

. Specifically, we consider the power-law form of $$\Lambda =\alpha H^n$$

Λ
=
α

H
n

, where $$\alpha $$
α
and n are constants. To constrain the model parameters, we use the MCMC technique, allowing for effective exploration of the model’s parameters. We apply this approach to analyze 31 points of observational Hubble Data (OHD), 1048 points from the Pantheon data, and additional CMB data. We consider three scenarios: when n is a free parameter (Case I), when $$n=0$$

n
=
0

(Case II), and when $$n=1$$

n
=
1

(Case III). In our analysis across all three cases, we observe that our model portrays the universe’s evolution from a matter-dominated decelerated epoch to an accelerated epoch, as indicated by the corresponding deceleration parameter. In addition, we investigate the physical behavior of total energy density, total EoS parameter, and jerk parameter. Our findings consistently indicate that all cosmological parameters predict an accelerated expansion phase of the universe for all three cases ($$q_0<0$$

q
0

<
0

, $$\omega _0<-\frac{1}{3}$$

ω
0

<
-

1
3

, $$j_0>0$$

j
0

>
0

). Furthermore, our analysis reveals that the Om(z) diagnostics for Cases I and III align with the quintessence region, while Case II corresponds to the $$\Lambda $$
Λ
CDM model.
From Pursuit of the Universal AGI Architecture to Systematic Approach to Heterogeneous AGI (SAGI): Addressing Alignment, Energy & AGI Grand Challenges
Authors: Kurshan Eren 
Published: July 2024

Artificial intelligence (AI) faces a trifecta of grand challenges: the Energy Wall, the Alignment Problem and the Leap from Narrow AI to AGI. Contemporary AI solutions consume unsustainable amounts of energy during model training and daily operations. Making things worse, the amount of computation required to train each new AI model has been doubling every 2 months since 2020, directly translating to unprecedented increases in energy consumption. The leap from AI to AGI requires multiple functional subsystems operating in a balanced manner, which requires a system architecture. However, the current approach to AI lacks system design; even though system characteristics play a key role in the human brain; from the way it processes information to how it makes decisions. In this paper, we posit that system design is the missing piece in overcoming current AI the grand challenges. We present a Systematic Approach to AGI (SAGI) that utilizes system design principles to overcome the energy wall and the alignment challenges. This paper asserts that artificial intelligence can be realized through a multiplicity of design-specific pathways, rather than a singular, overarching AGI architecture. AGI systems may exhibit diverse architectural configurations and capabilities, contingent upon their intended use cases. We argue that AI alignment, the most difficult among the grand challenges, is not attainable without a way to reflect the complexity of the human moral system and its subsystems in the AGI architectures. We claim that AGI approaches such as symbolicism, connectionism and others are not fundamental to AGI but emergent from the system design processes. Hence, we focus on employing system design principles as a guiding framework, rather than solely concentrating on a universal AGI architecture.
Single-cell genomics details the maturation block in BCP-ALL and identifies therapeutic vulnerabilities in DUX4-r cases
Authors: Thorsson Hanna , Henningsson Rasmus , Puente-Moncada Noelia , Peña-Martínez Pablo , Sjöström Ludvig , Ågerstam Helena , Sandén Carl , Rissler Marianne , Castor Anders , Marquart Hanne , Modvig Signe , Paulsson Kajsa , Pronk Cornelis Jan , Schmiegelow Kjeld , Hyrenius-Wittsten Axel , Orsmark-Pietras Christina , Lilljebjörn Henrik , Fioretos Thoas 
Published: July 2024

Abstract
B-cell progenitor acute lymphoblastic leukemia (BCP-ALL) is the most common childhood malignancy and is driven by multiple genetic alterations that cause maturation arrest and accumulation of abnormal progenitor B cells. Current treatment protocols with chemotherapy have led to favorable outcomes but are associated with significant toxicity and risk of side effects, highlighting the necessity for highly effective, less toxic, targeted drugs, even in subtypes with a favorable outcome. Here, we used multimodal single-cell sequencing to delineate the transcriptional, epigenetic, and immunophenotypic characteristics of 23 childhood BCP-ALLs belonging to the BCR::ABL1+, ETV6::RUNX1+, high hyperdiploid, and recently discovered DUX4-rearranged (DUX4-r) subtypes. Projection of the ALL cells along the normal hematopoietic differentiation axis revealed a diversity in the maturation pattern between the different BCP-ALL subtypes. Although the BCR::ABL1+, ETV6::RUNX1+, and high hyperdiploidy cells mainly showed similarities to normal pro-B cells, DUX4-r ALL cells also displayed transcriptional signatures resembling mature B cells. Focusing on the DUX4-r subtype, we found that the blast population displayed not only multilineage priming toward nonhematopoietic cells, myeloid, and T-cell lineages, but also an activation of phosphatidylinositol 3-kinase (PI3K)/AKT signaling that sensitized the cells to PI3K inhibition in vivo. Given the multilineage priming of DUX4-r blasts with aberrant expression of myeloid marker CD371 (CLL-1), we generated chimeric antigen receptor T cells, which effectively eliminated DUX4-r ALL cells in vivo. These results provide a detailed characterization of BCP-ALL at the single-cell level and reveal therapeutic vulnerabilities in the DUX4-r subtype, with implications for the understanding of ALL biology and new therapeutic strategies.
A single-sample workflow for joint metabolomic and proteomic analysis of clinical specimens
Authors: Gegner Hagen M. , Naake Thomas , Aljakouch Karim , Dugourd Aurelien , Kliewer Georg , Müller Torsten , Schilling Dustin , Schneider Marc A. , Kunze-Rohrbach Nina , Grünewald Thomas G.P. , Hell Rüdiger , Saez-Rodriguez Julio , Huber Wolfgang , Poschet Gernot , Krijgsveld Jeroen 
Published: July 2024

AbstractUnderstanding the interplay of the proteome and the metabolome helps to understand cellular regulation and response. To enable robust inferences from such multi-omics analyses, we introduced and evaluated a workflow for combined proteome and metabolome analysis starting from a single sample. Specifically, we integrated established and individually optimized protocols for metabolomic and proteomic profiling (EtOH/MTBE and autoSP3, respectively) into a unified workflow (termed MTBE-SP3), and took advantage of the fact that the protein residue of the metabolomic sample can be used as a direct input for proteome analysis. We particularly evaluated the performance of proteome analysis in MTBE-SP3, and demonstrated equivalence of proteome profiles irrespective of prior metabolite extraction. In addition, MTBE-SP3 combines the advantages of EtOH/MTBE and autoSP3 for semi-automated metabolite extraction and fully automated proteome sample preparation, respectively, thus advancing standardization and scalability for large-scale studies. We showed that MTBE-SP3 can be applied to various biological matrices (FFPE tissue, fresh-frozen tissue, plasma, serum and cells) to enable implementation in a variety of clinical settings. To demonstrate applicability, we applied MTBE-SP3 and autoSP3 to a lung adenocarcinoma cohort showing consistent proteomic alterations between tumour and non-tumour adjacent tissue independent of the method used. Integration with metabolomic data obtained from the same samples revealed mitochondrial dysfunction in tumour tissue through deregulation of OGDH, SDH family enzymes and PKM. In summary, MTBE-SP3 enables the facile and reliable parallel measurement of proteins and metabolites obtained from the same sample, benefiting from reduced sample variation and input amount. This workflow is particularly applicable for studies with limited sample availability and offers the potential to enhance the integration of metabolomic and proteomic datasets.
Graphical Abstract
Molecular Characterization of Lineage-IV Peste Des Petits Ruminants Virus and the Development of In-House Indirect Enzyme-Linked Immunosorbent Assay (IELISA) for its Rapid Detection”
Authors: Kamal Tahira , Khan Saeed-ul-Hassan , Hassan Fariha , Zahoor Amir-bin- , Ullah Amman , Andrabi S. Murtaza Hassan , Ali Ghulam Muhammad , Afsar Tayyaba , Husain Fohad Mabood , Shafique Huma , Razak Suhail 
Published: July 2024

AbstractPeste des petits ruminants (PPRV), a highly contagious viral disease, causes significant economic losses concerning sheep and goats. Recently, PPR viruses (PPRVs), have adopted new hosts and lineage IV of PPRVs represents genetic diversity within the same lineage. 350 samples, including blood, swabs, and tissues from sheep/goats, were collected during the 2020–2021 disease outbreaks in Pakistan. These samples were analysed through RT-PCR and three isolates of PPRV with accession numbers, MW600920, MW600921, and MW600922, were submitted to GenBank, based on the partial N-gene sequencing. This analysis provides a better understanding of genetic characterizations and a targeted RT-PCR approach for rapid PPRV diagnosis. An IELISA test was developed using the semi-purified antigen MW600922 isolate grown in Vero cells. The PPRV isolates currently present high divergence with the Turkish strain; conversely, similarities equivalent to 99.73% were observed for isolates collected from Pakistan. The developed indirect ELISA (IELISA) test demonstrated antibody detection rates at dilutions of 1:200 for antibodies (serum) and 1:32 for antigens. In comparison to cELISA, high specificity (85.23%) and sensitivity (90.60%) rates were observed. In contrast to the virus neutralization test (VNT), IELISA was observed to be 100% specific and 82.14% sensitive in its results. Based on these results, serological surveys conducted for PPR antibodies using IELISA can be a more effective strategy on a larger scale. Furthermore, our results demonstrate a significant breakthrough in the research in terms of cost-effectiveness and storage efficiency, and the developed IELISA test is highly recommended for use in developing countries.
Comparative genome analysis of the genus Marivirga and proposal of two novel marine species: Marivirga arenosa sp. nov., and Marivirga salinae sp. nov.
Authors: Muhammad Neak , Avila Forbes , Kim Song-Gun 
Published: July 2024

Abstract
Background
The phylum Bacteroidota represents a significant proportion of heterotrophic bacteria found in marine ecosystems. Members of the phylum Bacteroidota are actively involved in the degradation of biopolymers such as polysaccharides and proteins. Bacteroidota genomes exhibit a significant enrichment of various enzymes, including carbohydrate-active enzymes (CAZymes), carboxypeptidases, esterases, isomerases, peptidases, phosphatases, and sulfatases. The genus Marivirga, a member of the family Marivirgaceae within the phylum Bacteroidota, comprises six documented species. During a microbial diversity study, three novel Marivirga strains (BKB1-2 T, ABR2-2, and BDSF4-3 T) were isolated from the West Sea, Republic of Korea.

Results
To explore the taxonomic status and genomic characteristics of the novel isolates, we employed a polyphasic taxonomic approach, which included phylogenetic, chemotaxonomic and comprehensive genome analysis. The three isolates were Gram-stain-negative, aerobic, rod-shaped, moderately halophilic, and had a gliding motility. The average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values among the two isolates, BKB1-2 T and BDSF4-3 T, and the six reference strains were 70.5–76.5% for ANI and 18.1–25.7% for dDDH. Interestingly, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the strains harbor genes for a comprehensive pathway for dissimilatory nitrate reduction to ammonium (DNRA), as well as other nitrogen pathways for the reduction of nitrite, nitric oxide, and nitrous oxide. Additionally, the antiSMASH analysis indicated that the strains contained three to eight biosynthetic gene clusters (BGCs) associated with the synthesis of secondary metabolites. Furthermore, the strains carried a high number of CAZyme ranging from 53 to 152, which was also demonstrated by an in vitro analysis of degradation of the polysaccharide cellulose, chitin, laminarin, starch, and xylan. Additionally, all the strains carried genes for the metabolism of heavy metals, and exhibited tolerance to heavy metals, with minimum inhibitory concentrations (MICs) in millimoles (mM) in ranges of Co2+ (3–6), Cu2+ (0.2–0.4), Ni2+ (3–5), Zn2+ (2–4), Mn2+ (20–50), and Hg2+ (0.3).

Conclusions
Based on polyphasic taxonomic approach, the three isolated strains represent two novel species names Marivirga arenosa sp. nov. (BKB1-2 T = KCTC 82989 T = InaCC B1618T), and Marivirga salinae sp. nov. (BDSF4-3 T = KCTC 82973 T = InaCC B1619T).
A novel approach to terminate roof-dependent atrial flutter with epicardial conduction through septopulmonary bundle
Authors: Zhou Dongchen , Zhang Biqi , Zeng Cong , Yin Xiang , Guo Xiaogang 
Published: July 2024

AbstractAtrial flutter, a prevalent cardiac arrhythmia, is primarily characterized by reentrant circuits in the right atrium. However, atypical forms of atrial flutter present distinct challenges in terms of diagnosis and treatment. In this study, we examine three noteworthy clinical cases of atypical atrial flutter, which offer compelling evidence indicating the implication of the lesser-known Septopulmonary Bundle (SPB). This inference is based on the identification of distinct electrocardiographic patterns observed in these patients and their favorable response to catheter ablation, which is a standard treatment for atrial flutter. Remarkably, in each case, targeted ablation at the anterior portion of the left atrial roof effectively terminated the arrhythmia, thus providing further support for the hypothesis of SPB involvement. These insightful observations shed light on the potential significance of the SPB in the etiology of atypical atrial flutter and introduce a promising therapeutic target. We anticipate that this paper will stimulate further exploration into the role of the SPB in atrial flutter and pave the way for the development of targeted ablation strategies.
Phenogrouping heart failure with preserved or mildly reduced ejection fraction using electronic health record data
Authors: Soltani Fardad , Jenkins David A. , Kaura Amit , Bradley Joshua , Black Nicholas , Farrant John P. , Williams Simon G. , Mulla Abdulrahim , Glampson Benjamin , Davies Jim , Papadimitriou Dimitri , Woods Kerrie , Shah Anoop D. , Thursz Mark R. , Williams Bryan , Asselbergs Folkert W. , Mayer Erik K. , Herbert Christopher , Grant Stuart , Curzen Nick , Squire Iain , Johnson Thomas , O’Gallagher Kevin , Shah Ajay M. , Perera Divaka , Kharbanda Rajesh , Patel Riyaz S. , Channon Keith M. , Lee Richard , Peek Niels , Mayet Jamil , Miller Christopher A. 
Published: July 2024

Abstract
Background
Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data.

Methods
2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups.

Results
Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF.

Conclusions
Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles.