bluuebunny/crossref_metadata_2025_split huggingface dataset:
Precision phenotyping from routine laboratory parameters for machine learning out-of-hospital survival prediction using 4D time-dependent SHAP plots in an all-comers prospective PCI registry
Authors: Călburean Paul-Adrian , Scurtu Anda-Cristina , Grebenisan Paul , Nistor Ioana-Andreea , Vacariu Victor , Drincal Reka-Katalin , Sulea Ioana Paula , Oltean Tiberiu , Hadadi László 
Published: September 2024

AbstractIntroductionOut-of-hospital mortality in coronary artery disease (CAD) is particularly high and established adverse event prediction tools are yet to be available. Our study aimed to investigate whether precision phenotyping can be performed using routine laboratory parameters for the prediction of out-of-hospital survival in a CAD population treated by percutaneous coronary intervention (PCI).Materials and methodsAll patients treated by PCI and discharged alive in a tertiary center between January 2016 – December 2022 that have been included prospectively in the local registry were analyzed. 115 parameters from the PCI registry and 266 parameters derived from routine laboratory testing were used. An extreme gradient-boosted decision tree machine learning (ML) algorithm was trained and used to predict all-cause and cardiovascular-cause survival.ResultsA total of 7186 PCI hospitalizations for 5797 patients were included with more than 610.000 laboratory values. All-cause and cardiovascular cause mortality was 17.5% and 12.2%, respectively, during a median follow-up time of 1454 (687 – 2072) days. The integrated area under the receiver operator characteristic curve for prediction of all-cause and cardiovascular cause mortality by the ML on the validation dataset was 0.844 and 0.837, respectively (all p<0.001). The integrated area under the precision-recall curve for prediction of all-cause and cardiovascular cause mortality by the ML on the validation dataset was 0.647 and 0.589, respectively (all p<0.001).ConclusionPrecise survival prediction in CAD can be achieved using routine laboratory parameters. ML outperformed clinical risk scores in predicting out-of-hospital mortality in a prospective all-comers PCI population.
Anti-cancer effect of memantine as adjunctive therapy in metastatic colon cancer: A pilot randomized controlled clinical trial
Authors: Jannesar Kosar , Roosta Yousef , Masoudi Naser , Asghari Rahim , Rasouli Javad , Soraya Hamid 
Published: September 2024

AbstractPurposeColon cancer, one of the three deadliest cancers worldwide, has a high prevalence, especially in developing societies. Recently, our preclinical study demonstrated the strong anti-tumor effects of memantine on colon cancer in rats. This study aimed to investigate the effects of memantine (an NMDA receptor antagonist) in patients with metastatic colon cancer.Patients and MethodsIn this randomized controlled clinical trial, 32 patients with metastatic colon cancer were randomized into two arms. The first arm received a chemotherapy regimen and the second arm received a chemotherapy regimen plus memantine 20 mg/day. The tumor size, metastasis, hematological parameters, CEA level, and N/L ratio were measured. Additionally, we assessed the safety and tolerability of this combination and its effect on the quality of life (QoL) of metastatic colon cancer patients.ResultsMemantine reduced the colon tumor size in comparison to the control group patients (P=0.04). Also, in the memantine group, the metastasis was lower than in the control group (50% vs 87.5% respectively). Moreover, the memantine-treated group demonstrated reduced levels of CEA (P=0.01) as well as improved some hematological parameters. Also, quality of life was partially improved and no serious adverse effects were reported.ConclusionsThree-month adjuvant therapy with memantine reduces tumor size, metastasis, CEA level, and the N/L ratio, and also causes relative improvement of hematological parameters as well as the quality of life without causing any serious adverse effects. Therefore, memantine could be suggested as an appropriate adjuvant therapy in metastatic colorectal cancer.
YOLOv8 Enables Automated Dragonfly Species Classification Using Wing Images
Authors: Kim Suyeon 
Published: September 2024

ABSTRACTThis study investigates the digitization of insect collections and the application of deep learning models to improve this process. During a one-hour filming session, 141 images of dragonfly specimens from the Cornell University Insect Collection were captured and preprocessed using five distinct methods: (1) adding box annotations around the wings, (2) adding polygon annotations to outline the forewings and hindwings, (3) removing vein system images, (4) retaining only the wing outline images, and (5) grouping by automatically measured wing size and classifying species within those groups. By comparing YOLOv8 models trained on datasets with these different preprocessing methods, the study revealed three key findings: (1) datasets with bounding box annotations result in shorter preprocessing times and superior model performance compared to polygon annotations; (2) although models trained with polygon annotations may have lower accuracy, they provide more detailed information on wing length and phenotypic traits; and (3) the wing vein system, rather than the wing outline, is the critical factor in classification accuracy.
Rapid precision targeting of nanoparticles to lung via caveolae pumping system in endothelium
Authors: Nayak Tapas R. , Chrastina Adrian , Valencia Jose , Yedidsion Robert , Buss Tim , Cederstrom Brittany , Koziol Jim , Levin Michael D. , Olenyuk Bogdan , Schnitzer Jan E. 
Published: September 2024

AbstractModern medicine seeks precision targeting, imaging and therapy to maximize efficacy and avoid toxicities. Nanoparticles (NPs) have tremendous, yet unmet clinical potential to carry and deliver imaging and therapeutic agents systemically with tissue precision. But their size contributes to unwanted rapid scavenging by the reticulo-endothelial system (RES) and poor penetration of key endothelial cell (EC) barriers, both limiting target-tissue uptake, safety and efficacy. Here, we discover the extraordinary yet size-dependent ability of the EC caveolae pumping system (CPS) to deliver NPs rapidly and specifically into lungs. Gold and dendritic NPs are conjugated to aminopeptidase-P2 antibodies targeting caveolae of lung microvascular endothelium. SPECT-CT imaging and biodistribution analyses reveal that rat lungs extract most of the intravenously injected dose within minutes to achieve rapid blood clearance, high lung tissue concentrations well beyond peak blood levels, and precision lung imaging and targeting. Active transcytosis by caveolae greatly outperforms passive transvascular delivery and can even outpace RES scavenging. These results reveal how much ECs can both limit and promote tissue penetration of NPs and the power and limitations of the CPS. This study provides a new retargeting paradigm for small NPs to avoid RES uptake and achieve unprecedented rapid precision nanodelivery for future diagnostic and therapeutic applications.
Cholesterol accumulation-induced impairment of AKT signaling in LPS-stimulated macrophages play a dispensable role in suppressing HIF-1α-dependent glycolysis
Authors: Ting Kenneth K.Y. , Cybulsky Myron I. 
Published: September 2024

AbstractThe formation of lipid-laden macrophages (Mφs) is a hallmark of atherosclerosis, yet how the accumulation of cholesterol in Mφs underlies the inflammatory process of atherogenesis remains unclear. It is well recognized that the reprogramming of metabolism in Mφs is critical for supporting their inflammatory responses, which may shed light on how the metabolism of Mφ foam cells is linked to inflammation. Indeed, recent research has now revealed Mφs that accumulate excess cholesterol adopt a distinct metabolic adaptation, a metabolic profile that is unexpectedly associated with a deactivated inflammatory response. Mechanistically, our group has previously shown that upon LPS stimulation, excess cholesterol accumulation in Mφs impaired their induction of AKT-dependent early glycolytic reprogramming and HIF-1α-dependent late glycolytic reprogramming. However, it remains unclear if these events are interconnected and synergistically contribute to the suppression of inflammation observed in these Mφs. Here, we demonstrated that cholesterol loading of Mφs impaired LPS-induced early glycolysis by reducing the phosphorylation of hexokinases, yet complete inhibition of AKT only modestly impaired HIF-1α-dependent glycolytic reprogramming. On the other hand, we confirmed that HIF-1α degradation, but not its reduced synthesis, is the primary mechanism that underlies its impaired expression in cholesterol loaded Mφs. Finally, we showed that cholesterol loading of Mφs alone was sufficient to induce oxidative stress, such as the production of 4-HNE, and deplete the levels of reduced KEAP1 proteins. Mφs lacking NRF2 resisted the effects of cholesterol loading on suppressing the expression of glycolytic and pro-inflammatory proteins.
Circular RNAs correlate with DNA damage in ageing human placental tissue and in stillbirth
Authors: Arthurs Anya L. , Jackson Matilda R. , McCullough Dylan , Scott Hamish S. , Barnett Christopher P. , Webb Stuart T. , Smith Melanie D. , Jankovic-Karasoulos Tanja , Dekker Gustaaf A. , Roberts Claire T. 
Published: September 2024

AbstractUnexplained stillbirth may occur due to premature placental ageing, with unexpected deterioration of placental function for gestational age. Circular RNAs (circRNAs) are enzyme-resistant RNA molecules that accumulate in ageing tissues. Furthermore, circRNAs bind gDNA directly, forming circRNA:DNA complexes which can induce DNA breaks. This study investigated circRNA accumulation with gestational age in healthy and stillbirth placentae and determined whether circRNAs directly interact with placental DNA causing DNA damage. Placenta samples (n=60 term uncomplicated; n=4 unexplained stillbirth) were assessed. Compared with earlier gestations (37, 38, 39, 40 weeks’), placental DNA damage and expression of 6 candidate circRNAs (circ_0009000, circ_0024157, circ_0061017, circ_0036877, circ_0054624 and circ_0111277), but not their linear transcripts, were increased in 40 and 41+ weeks’ gestation samples, and in stillbirth. DRIP-qPCR signal size was significantly larger in term placentae than in enzyme-treated controls, confirming that all candidate circRNA loci bind to placental DNA. Depletion of circ_0009000 by specific siRNA in HEK293T cells, significantly reduced DNA damage compared to control, and increased expression of senescence-associated genes.Stillbirth placentae show accelerated ageing with premature accumulation of candidate circRNAs at levels consistent with older gestation tissue. These circRNAs bind to DNA and circ_0009000 causes DNA breaks and senescence in placenta. Therefore, circRNAs play a role in placental ageing and associate with stillbirth, likely via DNA damage.Graphical Abstract
Disease-associated microglia and activation of CD8+T cells precede neuronal cell loss in a model of hereditary spastic paraplegia
Authors: Frolov A , Huang H , Schütz D , Köhne M , Blank-Stein N , Osei-Sarpong C , Büttner M , Elmzzahi T , Khundadze M , Becker M , Bonaguro L , Hübner CA , Händler K , Stumm R , Mass E , Beyer M 
Published: September 2024

AbstractIn central nervous system (CNS) diseases characterized by late-onset neurodegeneration, the interplay between innate and adaptive immune responses remains poorly understood. This knowledge gap is amplified by the prolonged nature of these diseases, complicating the delineation of brain-resident and infiltrating cells. Here, we conducted a comprehensive profiling of innate and adaptive immune cells across various CNS regions in a murine model of spastic paraplegia 15 (SPG15), a complicated form of hereditary spastic paraplegia (HSP). Using fate-mapping of bone marrow-derived cells via genetic labeling, we identified microgliosis and microglial MHC-II upregulation accompanied by infiltration and local expansion of T cells in the CNS ofSpg15-/-mice. Single-cell analysis revealed an increase of disease-associated microglia (DAM) and clonal expansion of effector CD8+T cells across CNS regions occurring prior to neuronal loss. Analysis of potential cell-cell communication pathways suggested bidirectional interactions between DAM and effector CD8+T cells potentially contributing to disease progression inSpg15-/-mice. In summary, we identified a shift in microglial phenotypes associated with recruitment and clonal expansion of T cells as a new characteristic ofSpg15-driven neuropathology. Targeting activated microglia, CD8+T cells and their communication represent promising avenues to prevent the loss of neuronal function in HSP.
Diurnal variation in skeletal muscle mitochondrial function dictates time of day-dependent differences in exercise capacity
Authors: Khatri Subhash , Das Souparno , Singh Anshit , Shabbir A , Kashiv Mohit , Laxman Sunil , Kolthur-Seetharam Ullas 
Published: September 2024

ABSTRACTExercise impinges on almost all physiological processes at an organismal level and is a potent intervention to treat various diseases. Exercise performance is well established to display diurnal rhythm, peaking during the late active phase. However, the underlying molecular/metabolic factors and mitochondrial energetics that possibly dictate time-of-day exercise capacity remain unknown. Here, we have unraveled the importance of diurnal variation in mitochondrial functions as a determinant of skeletal muscle exercise performance. Our results show that exercise-induced muscle metabolome and energetics are distinct at ZT3 and ZT15. Importantly, we have elucidated key diurnal differences in mitochondrial functions that are well correlated with disparate time-of-day dependent exercise capacity. Providing causal evidence, we illustrate that loss of Sirtuin4 (SIRT4), a well-known mitochondrial regulator, abrogates diurnal variation in mitochondrial functions and consequently abolishes time-of-day dependent exercise performance. Therefore, our findings unequivocally demonstrate the pivotal role of baseline skeletal-muscle mitochondrial functions in dictating diurnal exercise capacity.
Evaluating Cross-linking-driven integrative modeling in peptide-HLAII complexes prediction with insights for refining predictive accuracy
Authors: Di Ianni Andrea , Barbero Luca M. , Cowan Kyra , Riccardi Sirtori Federico 
Published: September 2024

ABSTRACTIn silicoprediction of peptide-HLAII (human leucocyte antigen class II) complexes has emerged as a crucial approach in bioinformatics for deciphering antigen presentation mechanisms. Severalin silicotools have been developed to predict peptide binding to HLAII alleles, trying to deconvolute the intricate peptide-HLAII binding specificity. These approaches integrate bases from molecular modeling, machine learning, and bioinformatics to predict peptide-HLAII interactions. Initially, structure-based methods relying on molecular docking algorithms were widespread, utilizing structural data of HLAII molecules and peptides to infer plausible binding conformations. These methods often faced challenges in accuracy due to the dynamic nature of peptide-HLAII interactions. Besides, the high flexibility of peptide sidechains makes their placement into the HLA-binding site even more complex. In recent years, machine learning techniques have drawn attention to peptide-HLAII binding predictions. Supervised learning algorithms, such as support vector machines (SVMs), neural networks, and ensemble methods, have been considerably applied to discriminate patterns from large datasets of experimentally validated peptide-HLAII binding affinities (like Immune Epitope Data Base, IEDB) and more recently mass spectrometry- eluted ligands from MHC-associated peptide proteomics (MAPPs) assay. The role of experiment- assisted integrative modeling in aiding peptide-HLAII complexes prediction still needs to be clarified. In this work, we benchmarked the use of AlphaLink2 (AlphaFold2 + cross-links restraints) and compared it to AlphaFold2 Multimer in predicting correct peptide binding motifs. These results can pave the way to an integrated strategy for vaccine development and protein deimmunization or autoimmunity mitigation.
How does obsolescence risk influence consumer resistance to smartwatches?
Authors: Acikgoz Fulya , Borulu Burak , Bölen Mehmet Cem 
Published: September 2024

PurposeDue to advances in both software and hardware, obsolescence risk refers to the fear that a product will soon become obsolete, which can be very high for technological products such as smartwatches or smartphones. Drawing on the perceived risk theory and innovation resistance, this study examines the effects of different obsolescence risks on consumer resistance to smartwatches.Design/methodology/approachA sequential explanatory approach using a mixed method was adopted in this study. In Study 1, we conducted semi-structured and in-depth face-to-face interviews with 16 individuals to identify the most important obsolescence risks affecting consumers’ resistance to smartwatches. This qualitative study develops a novel theoretical model based on interpretive results, including technological, economic, functional, and aesthetic obsolescence risks. In Study 2, we tested our theoretical model by applying partial least-squares structural equation modeling to a sample of 298 smartwatch users.FindingsThe results show that consumer resistance to smartwatches is affected by technological, economic, functional, and aesthetic obsolescence risks.Originality/valueAlthough most extant studies have focused on the factors influencing the adoption and use of consumer electronics, little is known about the role of obsolescence risk in consumers’ resistance to these products.
Financing options for logistics firms considering product quality loss
Authors: Bi Gongbing , Wu Yue , Xu Hang 
Published: September 2024

Purpose
This paper aims to investigate the impact of quality loss in transit on e-commerce supply chain pricing, production and financing decisions.

Design/methodology/approach
The authors consider a Stackelberg game model with a supplier, logistics firm and e-commerce platform. The logistics firm is capital-constrained and obtains funding from the e-commerce platform by debt financing or equity financing. Through backward induction, this paper first solves the equilibrium results under the two financing schemes and then reveals the financing preferences of all parties.

Findings
The results demonstrate that equity financing reduces financing costs and promotes production significantly. However, it may also lead to overproduction, particularly in markets with poor profitability and high cost factors. When the percentage of product quality loss is large, equity financing is preferable. With the increasing of transportation level, the benefits of debt finance are steadily growing. In addition, equity financing is the Pareto dominant scheme for all firms under certain circumstances. The extensions consider hybrid financing and another quality loss type.

Practical implications
The paper derives the equilibrium solutions and financing preferences, then specifies the threshold for applying financing schemes. Provide guidance for logistics firms’ finance model innovation and core enterprise involvement in the logistics industry.

Originality/value
The paper investigates how logistics firms’ financing strategies are impacted by product quality loss.
Employee disengagement: the catalytic role of leader-induced defensive cognitions and perceptual politics
Authors: Tahir Muhammad Zohaib , Mughal Farooq , Awan Tahir Mumtaz , Waheed Aamer 
Published: September 2024

PurposeThe study aims to attain insights into the role of destructive leadership and perceived organizational politics as catalysts for employee disengagement through the perspective of social identity theory. The research further considers employees’ defensive cognitions for a comprehensive understanding of these interrelated phenomena in the workplace.Design/methodology/approachIn order to ascertain the pertinence and contextual relevance of the proposed framework, literary review was complemented by a survey-based study encompassing 114 full-time employees purposively selected from the six systemically important banks of Pakistan.FindingsThe findings accentuate the significance of destructive leadership in inducing withdrawal behaviours among employees directly and indirectly through continuance commitment. The results also underline perceptions of politics as a significant work environment impediment amplifying employees’ propensity to undergo psychological withdrawal.Originality/valueThe study contributes to strategic human resource management literature by offering an identity-based explanation for employees’ disengagement, considering Pakistan’s power-distant and collectivist orientation. The research further introduces an empirical novelty by postulating a total effect moderation model.
Improved elastic full‐waveform inversion of ocean bottom node data
Authors: Wu Bo , Yao Gang , Zheng Qingqing , Niu Fenglin , Wu Di 
Published: September 2024

AbstractElastic full‐waveform inversion enables the quantitative inversion of multiple subsurface parameters, significantly enhancing the interpretation of subsurface lithology. Simultaneously, with the ongoing advancements in ocean bottom node technology, the application of elastic full‐waveform inversion to marine ocean bottom node data is receiving increasing attention. This is attributed to the capability of ocean bottom node to acquire high‐quality four‐component data. However, elastic full‐waveform inversion of ocean bottom node data typically encounters two challenges: First, the presence of low S‐wave velocity layers in the seabed leads to weak energy of converted S‐waves, resulting in significantly poorer inversion results for S‐wave velocity compared to those for P‐wave velocity; second, the cross‐talk effect of multiple parameters further exacerbates the difficulty in inverting S‐wave velocity. To effectively recover the S‐wave velocity using ocean bottom node data, we modify the S‐wave velocity gradient in conventional elastic full‐waveform inversion to alleviate the impact of cross‐talk from multiple parameters on the inversion of S‐wave velocity. Furthermore, to invert for density parameters, we adopt a two‐stage inversion strategy. In the first stage, P‐wave and S‐wave velocities are updated simultaneously with a single‐step length. Because the initial density model is far from the true one, density is updated using an empirical relationship derived from well‐log data. In the second stage, velocities and density are updated simultaneously with multi‐step length to further refine the models obtained in the first stage. The high effectiveness of the improved elastic full‐waveform inversion is validated by numerical examples.