bluuebunny/crossref_metadata_2025_split huggingface dataset:
PREDICTING UNPLANNED TRAUMA INTENSIVE CARE UNIT ADMISSIONS FOR INITIAL NONOPERATIVE, NON-ICU PATIENTS
Authors: Zander Tyler , Kendall Melissa A. , Grimsley Emily A. , Harry Shamir C. , Torikashvili Johnathan V. , Parikh Rajavi , Sujka Joseph , Kuo Paul C. 
Published: October 2024

ABSTRACT

Introduction: Unplanned intensive care unit (ICU) admissions are associated with increased morbidity and mortality. This study uses interpretable machine learning to predict unplanned ICU admissions for initial nonoperative trauma patients admitted to non-ICU locations. Methods: TQIP (2020–2021) was queried for initial nonoperative adult patients admitted to non-ICU locations. Univariable analysis compared patients who required an unplanned ICU admission to those who did not. Using variables that could be known at hospital admission, gradient boosting machines (CatBoost, LightGBM, XGBoost) were trained on 2021 data and tested on 2020 data. SHapley Additive exPlanations (SHAP) were used for interpretation. Results: The cohort had 1,107,822 patients; 1.6% had an unplanned ICU admission. Unplanned ICU admissions were older (71 [58–80] vs. 61 [39–76] years, P < 0.01), had a higher Injury Severity Score (ISS) (9 [8–13] vs. 9 [4–10], P < 0.01), longer length of stay (11 [7–17] vs. 4 [3–6] days, P < 0.01), higher rates of all complications, and most comorbidities and injuries (P < 0.05). All models had an AUC of 0.78 and an F1 score of 0.12, indicating poor performance in predicting the minority class. Mean absolute SHAP values revealed ISS (0.46), age (0.29), and absence of comorbidities (0.16) as most influential in predictions. Dependency plots showed greater SHAP values for greater ISS, age, and presence of comorbidities. Conclusions: Machine learning may outperform prior attempts at predicting the risk of unplanned ICU admissions in trauma patients while identifying unique predictors. Despite this progress, further research is needed to improve predictive performance by addressing class imbalance limitations.
MULTIPLE ORGAN FAILURE FOLLOWING SEVERE BATTLE INJURIES DURING RECENT CONFLICTS: A FRENCH RETROSPECTIVE COHORT STUDY
Authors: Schmitt Johan , Jacques Sébastien Cloé , Herzog Nicolas , Boutonnet Mathieu , Giacardi Christophe , Danguy des Déserts Marc , Martinez Thibault 
Published: October 2024

ABSTRACT

Introduction: Improvements in combat casualty care have increased survival rates, but these patients are at particular risk of developing multiple organ failure (MOF). We investigated the incidence and severity of MOF in a cohort of severe combat casualties. Materials and Methods: This retrospective study included all on-duty French land army war casualties with a severe combat injury requiring intensive care unit admission during 2009–2023. Demographic data, advanced life support interventions, and outcomes were collected. Each organ failure was then analyzed during a 7-day trauma course according to the Sequential Organ Failure Assessment score. Results: Of the 100 patients who met the inclusion criteria, those with persistent MOF at day 4 (MOF group) represented 22% of the total population (median Sequential Organ Failure Assessment score 6.0 [5.3–8.0]). Compared to those without persistent MOF, these patients were more severely injured (median Military Injury Severity Score 38.0 [interquartile range 33.0–56.8] vs. 26.5 [20.0–34.0], P < 0.001) by an explosive mechanism (68.2%) and sustained more traumatic brain injury (40.9% vs. 14.1%, P = 0.013). The MOF group also received significantly more blood units (median 14.0 [8.3–24.8] vs. 6.0 [0.0–12.0], P < 0.001) and massive transfusions (68.2% vs. 32.1%, P = 0.002). Pulmonary and cardiovascular dysfunction were the most frequently observed trauma outcomes. A multivariable logistic regression model showed that MOF persistence at day 4 was significantly associated (odds ratios [95% confidence intervals]) with severe injuries (1.5 [1–2.3], P = 0.042). Conclusion: A high number of severe lesions significantly and independently increased risk of MOF persistence at day 4 after combat-related trauma. These findings are particularly relevant to current and anticipated large-scale combat operations that will challenge battlefield casualty care and evacuation.
EUGENOL RESTRAINS ANGIOTENSIN II-INDUCED DEATH, INFLAMMATION AND FERROPTOSIS OF VASCULAR SMOOTH MUSCLE CELLS BY TARGETING STAT3/HMGB2 AXIS
Authors: Huang Birun , Chen Haiyan , Zhang Xiulan 
Published: October 2024

ABSTRACT

Background: Eugenol has been found to inhibit a variety of disease processes, including abdominal aortic aneurysm (AAA) formation. However, the specific role and the underlying molecular mechanism of Eugenol in AAA progression need to be further revealed. Methods: Vascular smooth muscle cells (VSMCs) were pretreated with Eugenol, followed by treated with Angiotensin II (Ang-II). VSMCs were transfected with HMGB2 siRNA or overexpression vector and treated with Ang-II to confirm the effect of HMGB2 on AAA progression. Cell proliferation and death were determined using cell counting kit 8 assay, 5-ethynyl-2′-deoxyuridine assay, and flow cytometry. Inflammatory factors were examined by ELISA. Fe2+, glutathione, and malondialdehyde levels were tested to evaluate cell ferroptosis. The protein levels of ferroptosis-related markers, high mobility group box 2 (HMGB2), and STAT3 were measured using western blot. Human AAA tissues and normal abdominal aortic tissues were collected to detect HMGB2 mRNA expression by quantitative real-time PCR. The interaction between HMGB2 and STAT3 was confirmed by chromatin immunoprecipitation assay and dual-luciferase reporter assay. Results: Eugenol enhanced VSMCs proliferation, while restrained Ang-II-induced death, inflammation, and ferroptosis. HMGB2 was upregulated in AAA tissues and Ang-II-induced VSMCs, and Eugenol significantly decreased HMGB2 expression. HMGB2 knockdown reduced Ang-II-induced VSMCs death, inflammation, and ferroptosis, Besides, HMGB2 overexpression abolished the effect of Eugenol on Ang-II-induced VSMCs injury. Transcription factor STAT3 bound to HMGB2 promoter region to increase its expression. In addition, Eugenol decreased STAT3 expression to regulate HMGB2. Conclusion: Eugenol could slow down the development of AAA, which might be achieved by regulating STAT3/HMGB2 axis.
Super Resolved Single-Cell Spatial Metabolomics from Multimodal Mass Spectrometry Imaging guided by Imaging Mass Cytometry
Authors: Ozturk Efe , Venkataraman Abhijeet , Rivera Moctezuma Felix G. , Coskun Ahmet F. 
Published: October 2024

AbstractMass spectrometry imaging (MSI) is a powerful technique for spatially resolved analysis of metabolites and other biomolecules within biological tissues. However, the inherent low spatial resolution of MSI often limits its ability to provide detailed cellular-level information. To address this limitation, we propose a guided super-resolution (GSR) approach that leverages high-resolution Imaging Mass Cytometry (IMC) images to enhance the spatial resolution of low-resolution MSI data. By using these detailed IMC images as guides, we improve the resolution of MSI images, creating high-resolution metabolite maps. This enhancement facilitates more precise analysis of cellular structures and tissue architectures, providing deeper insights into super-resolved spatial metabolomics at the single-cell level.
Establishment and Molecular Characterization of Patient-Derived Organoids for Primary Central Nervous System Lymphoma
Authors: Li Shengjie , Ren Jun , Wu Jianing , Xia Zuguang , Li Yingzhu , Li Chengxun , Cao Wenjun 
Published: October 2024

AbstractPrimary central nervous system lymphoma (PCNSL) exhibits substantial heterogeneity, both intra-tumoral and intertumoral, posing challenges in developing effective treatment methods. Existing in vitro models fail to simulate the inherent microenvironment and the cellular and mutational diversity of native tumors and require a prolonged generation time. To address this concern, we described an organoid culture method for patient-derived PCNSL organoids (CLOs) and evaluated them through extensive molecular characterization. These CLOs accurately mimicked the histological attributes, gene expression landscapes and mutational profiles of their original tumors through rigorous histopathological analysis, RNA sequencing and whole-exome sequencing. Notably, CLOs were generated within 2 weeks, demonstrating rapid development and reliability. Furthermore, therapeutic profiling was performed on three selected CLOs using four standard treatment drugs. High concordance was observed between the drug responses of patients and those observed in the CLOs, with specific sensitivity to ibrutinib and methotrexate and resistance to dexamethasone and rituximab. Taken together, these results emphasize that CLOs can effectively emulate the key characteristics of PCNSL, enhancing the understanding of the genetic landscape of this complex disease. CLOs provide a rapid and reliable platform for exploring individualized treatment strategies, potentially accelerating the transition of research findings to clinical practice.
Genetically Predicted Inflammatory Proteins Mediate the Association Between Gut Microbiota and Preterm Delivery: A Mendelian Randomization Study
Authors: Zhang Min , Chen Xiaodan , Zhang Yan , Huang Jia , Chen Ling 
Published: October 2024

AbstractAimsInflammatory proteins and unique gut microbiota profiles characterize preterm delivery (PTD). Nevertheless, the comprehensive understanding of gut microbiota and inflammatory proteins of PTD remains unclear. This study aimed to investigate the causal relationship between gut microbiota and PTD and identify the inflammatory proteins as potential mediators.Methods and resultsThe exposure genome-wide association studies (GWAS) data were sourced from the GWAS Catalog, while the outcome GWAS data were obtained from the Early Growth Genetics (EGG) Consortium. The study used 473 types of gut microbiota, 91 types of inflammatory proteins, and PTD from GWAS. We then performed two-sample Mendelian randomization (TSMR) and bidirectional Mendelian randomization (BDMR) analyses to explore the causal relationships between gut microbiota, inflammatory proteins, and PTD. Additionally, we conducted two-step Mendelian randomization (2SMR) to identify potential mediating inflammatory proteins in this process. MR analysis identified 26 gut microbiota and 6 types of inflammatory proteins causally associated with PTD. Furthermore, there was no strong evidence that genetically predicted PTD affected these gut microbiota and inflammatory proteins. Further, 2SMR analysis revealed that the association between Elusimicrobiaceae and PTD was mediated by the C-C motif chemokine 23 (CCL23), accounting for 5.09% (95%CI; 4.1%-8.7%) of the association. Similarly, the relationship between Thioalkalivibrionaceae and PTD was mediated by the Interleukin-20 receptor subunit alpha (IL-20RA), which accounted for 16.88% (95%CI; 12.77%-20.99%) of the association.ConclusionsOur results reveal that Elusimicrobiaceae and Thioalkalivibrionaceae were significantly associated with PTD, with mediation occurring via CCL23 and IL-20RA, respectively.Impact StatementThis study establishes a causal link between specific gut microbiota, inflammatory proteins, and PTD through MR analyses. The findings indicate that targeting the pathways involving Elusimicrobiaceae - CCL23 - PTD and Thioalkalivibrionaceae - IL20RA - PTD may provide promising interventions for preventing and treating PTD.
Alternative transcripts recode human genes to express overlapping, frameshifted microproteins
Authors: Su Haomiao , Katz Samuel G. , Slavoff Sarah A. 
Published: October 2024

AbstractOverlapping genes were thought to be essentially absent from the human genome until the discovery of abundant, frameshifted internal open reading frames (iORFs) nested within annotated protein coding sequences. However, it is currently unclear how many functional human iORFs exist and how they are expressed. We demonstrate that, in hundreds of cases, alternative transcript variants that bypass the start codon of annotated coding sequences (CDSs) can recode a human gene to express the iORF-encoded microprotein. While many human genes generate such non- coding alternative transcripts, they are poorly annotated. Here we develope a new analysis pipeline enabling the assignment of translated human iORFs to alternative transcripts, and provide long- read sequencing and molecular validation of their expression in dozens of cases. Finally, we demonstrate that a conservedDEDD2iORF switches the function of this gene from pro- to anti- apoptotic. This work thus demonstrates that alternative transcript variants can broadly reprogram human genes to express frameshifted iORFs, revealing new levels of complexity in the human transcriptome and proteome.
The Single-Stranded DNA-Binding Factor SUB1/PC4 Alleviates Replication Stress at Telomeres and is a Vulnerability of ALT Cancer Cells
Authors: Dubois Jean-Christophe , Bonnell Erin , Frion Julie , Zimmer Samuel , Khan Muhammad Riaz , Teplitz Gabriela M. , Casimir Lisa , Méthot Élie , Filion Amélie , Idrissou Mouhamed , Jacques Pierre-Étienne , Wellinger Raymund J. , Maréchal Alexandre 
Published: October 2024

AbstractTo achieve replicative immortality, cancer cells must activate telomere maintenance mechanisms. In 10-15% of cancers, this is enabled by recombination-based alternative lengthening of telomeres pathways (ALT). ALT cells display several hallmarks including heterogeneous telomere length, extrachromosomal telomeric repeats and ALT-associated PML bodies. ALT cells also have high telomeric replication stress (RS) enhanced by fork-stalling structures (R-loops, G4s) and altered chromatin states. In ALT cells, telomeric RS promotes telomere elongation but above a certain threshold becomes detrimental to cell survival. Manipulating RS at telomeres has thus been proposed as a therapeutic strategy against ALT cancers.Through analysis of genome-wide CRISPR fitness screens, we identified ALT-specific vulnerabilities and describe here our characterization of the roles of SUB1, a ssDNA-binding protein, as a novel regulator of telomere stability. SUB1 depletion further increases RS at ALT telomeres, profoundly impairing ALT cell growth without impacting telomerase-positive cancer cells. During RS, SUB1 is recruited to stalled forks and ALT telomeres via its ssDNA-binding domain. This recruitment is potentiated by RPA depletion, suggesting that these factors may compete for ssDNA. The viability of ALT cells and their resilience towards RS also requires ssDNA-binding by SUB1. SUB1 depletion accelerates cell death induced by FANCM depletion, triggering unsustainable levels of telomeric damage specifically in ALT cells. Finally, combining SUB1 depletion with RS-inducing drugs rapidly induces replication catastrophe in ALT cells. Altogether, our work identifies SUB1 as a new ALT susceptibility with important roles in the mitigation of RS at ALT telomeres and suggests new therapeutic strategies for a host of still poorly managed cancers.SignificanceStatementCurrently, there are few treatment options for ALT cancers with chemotherapy still occupying center stage despite often limited efficacy. ALT cancer cells experience high levels of replication stress at telomeres and its enhancement (e.g. via ATR inhibition) is a promising therapeutic strategy. Sensitivity to ATR inhibition varies amongst ALT cell lines/tumors warranting the development of additional ways to modulate telomeric replication stress. Here we identify SUB1, a single-stranded DNA-binding protein, as a vulnerability of ALT cells. SUB1 localizes to ALT telomeres and mitigates deleterious replication stress. SUB1 depletion synergizes with ATR inhibition and FANCM downregulation suggesting that co-targeting SUB1 with other regulators of replication stress at telomeres may kill ALT cancer cells more effectively.
Nicotine metabolite ratio as an informed biomarker to optimize acupuncture for smoking cessation: randomised controlled trial
Authors: Chen Shu-min , Ji Jia , xin Chai , Li Yang , Wuyuan  , Chang Jin , MiaoZhang  , Liu Zhen-yu , Tan Chao-ren , Yang Jin-sheng , Liu Zhao , Wang Ying-ying 
Published: October 2024

ABSTRACTObjectiveTo evaluate the effectiveness of using nicotine metabolite ratio (NMR) as an informed biomarker to optimize acupuncture for smoking cessation.MethodsThis was a prospective, two-arm, open-label randomized controlled trial. Participants were recruited and classified as slow or normal metabolizers based on their NMR values, and were randomly assigned to high-frequency or low-frequency acupuncture groups. Acupuncture sessions were held 3 to 5 times per week for 8 weeks. Minimum behavioral support was provided. The primary outcome was the 12-week continuous abstinence rate assessed by urine cotinine levels. Secondary outcomes included point abstinence, treatment adherence, and adverse reactions.ResultsBetween September 2018 and April 2022, 220 participants were included. Among them, 211 (95.9%) were male, and the mean (SD) age was 48.5 (11.6) years. With 0.31 as the NMR cut-off value, 70 (31.8%) were divided as normal metabolizers and 150 (68.2%) as slow metabolizers. The validated 3-month sustained abstinence was 17.3% (19/110) in the high-frequency acupuncture group, which was significantly higher than 8.2% (9/110) in the low-frequency acupuncture group (OR=3.89, 95% CI: 1.36, 8.11). In slow metabolizers, the validated 3-month sustained abstinence rate was 19.0% (15/79) in the high-frequency acupuncture, which was higher than 7.0% (5/71) in low-frequency acupuncture (OR=3.53, 95% CI: 1.03, 6.13). In normal metabolizers, the validated 3-month sustained abstinence rates were 12.9% (4/31) in the high-frequency acupuncture group and 10.3% (4/39) in the low-frequency acupuncture group, with high-frequency acupuncture non-inferior to low-frequency acupuncture (OR=1.11, 95% CI: 0.24, 5.17). Treatment adherence was high in both groups, and adverse reactions were infrequent. No serious adverse events were recorded.ConclusionThis pioneering study demonstrated that NMR might be used as a biomarker to optimize acupuncture treatments for smoking cessation, particularly among slow metabolizers. This study provides valuable insights into personalized smoking cessation strategies and highlights the potential of integrating acupuncture with other interventions for improved outcomes.Trial RegistrationChinese Clinical Trials Registry (No.ChiCTR1800018196), Registered 4 September 2018, (chictr.org.cn).
Efficient secretion of a plastic degrading enzyme from the green algaeChlamydomonas reinhardtii
Authors: Molino João Vitor Dutra , Saucedo Barbara , Kang Kalisa , Walsh Chloe , Diaz Crisandra Jade , Tessman Marissa , Mayfield Stephen 
Published: October 2024

AbstractPlastic pollution has become a global crisis, with microplastics contaminating every environment on the planet, including our food, water, and even our bodies. In response, there is a growing interest in developing plastics that biodegrade naturally, thus avoiding the creation of persistent microplastics. As a mechanism to increase the rate of polyester plastic degradation, we examined the potential of using the green microalgaChlamydomonas reinhardtiifor the expression and secretion of PHL7, an enzyme that breaks down post-consumer polyethylene terephthalate (PET) plastics. We engineeredC. reinhardtiito secrete active PHL7 enzyme and selected strains showing robust expression, by using agar plates containing a polyester polyurethane (PU) dispersion as an efficient screening tool. This method demonstrated the enzyme’s efficacy in degrading ester bond-containing plastics, such as PET and bio-based polyurethanes, and highlights the potential for microalgae to be implemented in environmental biotechnology. The effectiveness of algal-expressed PHL7 in degrading plastics was shown by incubating PET with the supernatant from engineered strains, resulting in substantial plastic degradation, confirmed by mass spectrometry analysis of terephthalic acid (TPA) formation from PET. Our findings demonstrate the feasibility of polyester plastic recycling using microalgae to produce plastic-degrading enzymes. This eco-friendly approach can support global efforts toward eliminating plastic in our environment, and aligns with the pursuit of low-carbon materials, as these engineered algae can also produce plastic monomer precursors. Finally, this data demonstratesC. reinhardtiicapabilities for recombinant enzyme production and secretion, offering a “green” alternative to traditional industrial enzyme production methods.Graphical Abstract
Automated segmentation of synchrotron-scanned fossils
Authors: During Melanie A. D. , Matelsky Jordan K. , Gustafsson Fredrik K. , Voeten Dennis F. A. E. , Chen Donglei , Wester Brock A. , Körding Konrad P. , Ahlberg Per E. , Schön Thomas B. 
Published: October 2024

AbstractComputed tomography has revolutionised the study of the internal three-dimensional structure of fossils. Historically, fossils typically spent years in preparation to be freed from the enclosing rock. Now, X-ray and synchrotron tomography reveal structure that is otherwise invisible and data acquisition can be fast. However, manual segmentation of these 3D volumes can still take months to years. This is especially challenging for resource-poor teams, as scanning may be free, but the computing power and (AI-assisted) segmentation software required to handle the resulting large data sets are complex to use and expensive.Here we present a free, browser-based segmentation tool that reduces computational overhead by splitting volumes into small chunks, allowing processing on low-memory, inexpensive hardware. Our tool also speeds up collaborative ground-truth generation and 3D visualization, all in-browser. We developed and evaluated our pipeline on various open-data scans of differing contrast, resolution, textural complexity, and size. Our tool successfully isolated theThrinaxodonandBroomistegapair from an Early Triassic burrow. It isolated cranial bones from the Cretaceous acipenseriformParapsephurus willybemision both 45.53µm and 13.67µm resolution scanning data. We also isolated bones of the Middle Triassic sauropterygianNothosaurusand a challenging scan of a squamate embryo inside an egg dating back to the Early Cretaceous. Our tool reliably reproduces expert-supervised segmentation at a fraction of the time and cost, offering greater accessibility than existing tools. Beyond the online tool, all our code is open source, enabling contributions from the palaeontology community to further this emerging machine learning ecosystem.