bluuebunny/crossref_metadata_2025_split huggingface dataset:
Remote Incisions as an Alternative to Mastectomy Scars for Breast Tissue Expander-to-Implant Exchange: A Propensity Score-Matched Analysis
Authors: Elmorsi Rami , Barrera Jose E. , Mericli Alexander F. , Schaverien Mark V. , Baumann Donald P. , Olenczak J. Bryce 
Published: December 2024

Background:
Two-stage prosthetic breast reconstruction involves the exchange of tissue expanders for implants, but complications of this procedure can necessitate revision surgeries and implant removal. The choice between remote incision (RI) and traditional access via existing mastectomy scars (MS) for this exchange remains underexplored. RIs offer potential benefits by placing the incision at a region of higher quality tissue, prompting our comparative analysis of complications between RI and MS.

Methods:
We retrospectively analysed patients undergoing expander-to-implant exchange via RI or MS access during 2018 through 2023. Data on demographics, comorbidities, cancer characteristics, surgeries, therapies, and outcomes were collected from the electronic medical record, and complication rates were compared between RI and MS exchange procedures.

Results:
In propensity-score matched cohorts, overall complications (10% for MS and 7.5% for RI, p = 0.58), infection (5.0% for MS vs. 2.5% for RI, p = 0.68), seroma (2.5% for both, p>0.99), dehiscence (2.5% for both, p>0.99), implant exposure (2.5% for MS vs. 1.2% for RI, p>0.99), and implant explantation (7.5% for MS vs. 6.2% for RI, p=0.75) were similar or lower in the RI group. Overall complications, infection, seroma, dehiscence, implant exposure, and explantation were also lower in radiated patients receiving RI compared to MS exchanges, though statistically insignificant. Transaxillary and inframammary incisions showed comparable outcomes, albeit the latter having a higher incidence of infections.

Conclusions:
RIs represent a safe alternative to MS exchanges in selected, high-risk patients undergoing post-mastectomy implant-based breast reconstruction.
Prediction of Local Tumor Progression After Thermal Ablation of Colorectal Cancer Liver Metastases Based on Magnetic Resonance Imaging Δ-Radiomics
Authors: Zhu Xiucong , Zhu Jinke , Sun Chenwen , Zhu Fandong , Wu Bing , Mao Jiaying , Zhao Zhenhua 
Published: December 2024

Purpose
This study aimed to enhance the predictability of local tumor progression (LTP) postthermal ablation in patients with colorectal cancer liver metastases (CRLMs). A sophisticated approach integrating magnetic resonance imaging (MRI) Δ-radiomics and clinical feature-based modeling was employed.

Materials and Methods
In this retrospective study, 37 patients with CRLM were included, encompassing a total of 57 tumors. Radiomics features were derived by delineating the images of lesions pretreatment and images of the ablation zones posttreatment. The change in these features, termed Δ-radiomics, was calculated by subtracting preprocedure values from postprocedure values. Three models were developed using the least absolute shrinkage and selection operators (LASSO) and logistic regression: the preoperative lesion model, the postoperative ablation area model, and the Δ model. Additionally, a composite model incorporating identified clinical features predictive of early treatment success was created to assess its prognostic utility for LTP.

Results
LTP was observed in 20 out of the 57 lesions (35%). The clinical model identified, tumor size (P = 0.010), and ΔCEA (P = 0.044) as factors significantly associated with increased LTP risk postsurgery. Among the three models, the Δ model demonstrated the highest AUC value (T2WI AUC in training, 0.856; Delay AUC, 0.909; T2WI AUC in testing, 0.812; Delay AUC, 0.875), whereas the combined model yielded optimal performance (T2WI AUC in training, 0.911; Delay AUC, 0.954; T2WI AUC in testing, 0.847; Delay AUC, 0.917). Despite its superior AUC values, no significant difference was noted when comparing the performance of the combined model across the two sequences (P = 0.6087).

Conclusions
Combined models incorporating clinical data and Δ-radiomics features serve as valuable indicators for predicting LTP following thermal ablation in patients with CRLM.
Identification and verification of feature biomarkers associated with choline metabolism in sepsis-induced cardiomyopathy
Authors: Pei Meng-Qin , Sun Zhen-Dong , Yang Yu-Shen , Fang Yu-Ming , Zeng Ya-Fen , He He-Fan 
Published: December 2024

Abstract

Background: Sepsis-induced cardiomyopathy (SIC), one of the most common complications of sepsis, seriously affects the prognosis of critically ill patients. Choline metabolism is an important biological process in the organism, and the mechanism of its interaction with SIC is unclear. The aim of this study was to reveal the choline metabolism genes (CMGs) associated with SIC and to provide effective targets for the treatment of SIC.

Methods: Through a comprehensive analysis of the microarray dataset GSE79962 (comprising 20 SIC patients and 11 healthy controls) from the GEO database, suspected co-expression modules and differentially expressed genes (DEGs) in SIC were identified. Hub CMGs were obtained by intersecting choline metabolism database with DEGs and key model genes. Afterward, hub CMGs most significantly involved in prognosis were further analyzed for the verification of major pathways of enrichment analysis. Finally, the expression of hub CMGs in in vivo and in vitro SIC model was verified by immunohistochemistry staining and quantitative real-time polymerase chain reaction analysis (qPCR).

Results: WGCNA identified 1 hub gene panel and 3867 hub genes, which were intersected with DEGs and CMGs to obtain the same 3 hub CMGs:HIF-1α, DGKD and PIK3R1. Only HIF-1α shows significant association with mortality (P = 0.009). Subsequent differential analysis based on the high and low HIF-1α expression yielded 63 DEGs and then they were uploaded into Cytoscape software to construct a protein-protein interaction (PPI) network and 6 hub genes with the highest priority were obtained (CISH, THBS1, IMP1, MYC, SOCS3 and VCAN). Finally, a multifactorial COX analysis revealed a significant correlation between HIF-1α and survival in SIC patients, which was further validated by in vitro and in vivo experiments.

Conclusion: Our findings will provide new insights into the pathogenesis of SIC, and HIF-1α may have important applications as a potential biomarker for early detection and therapeutic intervention in SIC.
Pioneering the retroperitoneal approach: Indocyanine green fluorescence-guided embolization in totally endophytic renal masses during robot-assisted partial nephrectomy
Authors: Chiang Ting-Yi , Tsai I-Chen , Hsieh Chia-Chih , Tseng Wen-Hsin , Wu Reng-Hong , Huang Steven K. , Chiu Allen W. 
Published: December 2024

Purpose:
This study aimed to evaluate the feasibility and outcomes of utilizing superselective transarterial indocyanine green (ICG)-lipiodol delivery to arterial branches supplying renal masses. Retroperitoneal robot-assisted partial nephrectomy (RAPN) was performed on 8 patients, and the characteristics of the patients, operative outcomes, and renal function results were assessed.

Materials and methods:
A preoperative procedure involved the transarterial delivery of an ICG-lipiodol mixture into tertiary-order arterial branches supplying renal masses. Retroperitoneal RAPN was performed on 8 patients, with detailed assessments of patient characteristics, operative outcomes, and renal function results.

Results:
The tumors were predominantly on the left side (mean size, 2.5 cm; RENAL nephrometry score, 7.3). The operative outcomes were favorable, with minimal ischemia time, no complications, and 100% margin-free resections. Individual renal functions showed a mild decrease in the estimated glomerular filtration rate, emphasizing the safety of ICG.

Conclusion:
The findings of this study support the effectiveness of retroperitoneal RAPN for challenging endophytic renal masses and introduce a novel approach with superselective transarterial ICG-lipiodol delivery, demonstrating favorable operative outcomes and successful preservation of renal function.
The association between consumption of dairy products and risk of type 2 diabetes
Authors: Fathi Soroor , Vahdat Mahsa , Saeedirad Zahra , Hassanpour Ardekanizadeh Naeemeh , Mousavi Mele Mahdi , Shekari Soheila , Mobarakeh Khadijeh Abbasi , Shafaei Hanieh , Mosavi Jarrahi Alireza , Rajabi Harsini Asma , Khoshdooz Sara , Gholamalizadeh Maryam , YazdiMoghaddam Hamideh , Doaei Saeid 
Published: December 2024

Background
The effects of dairy products on type 2 diabetes mellitus (T2DM) are unclear. Some studies have revealed the beneficial effects, whereas others found harmful effects of dairy products on the risk of T2DM. The objective of the present study was to investigate the association of different types of dairy products with risk of T2DM in Iranian adults.

Methods
This cross-sectional study included a total of 4241 individuals. Among these participants, 1804 were diagnosed with T2DM or prediabetes, whereas the remaining 2437 individuals were without T2DM. A validated food frequency questionnaire was used to assess the consumption of different types of dairy products.

Results
A positive association was found between T2DM with dietary intake of milk [odds ratio (OR): 1.16, 95% confidence interval (CI): 1.11–1.23, P = 0.008] and cheese (OR: 1.90, 95% CI: 1.41–2.29, P = 0.001) after adjustment for age, sex, physical activity, BMI, education level, energy, and fat intake. There was no significant association between T2DM and dietary intake of total dairy, yogurt, ayran (yogurt drink), and curd.

Conclusion
A positive association was found between the consumption of some dairy products including milk and cheese and the risk of T2DM. Further longitudinal studies are warranted to approve this finding.
LITERATURE REVIEW THE RELATIONSHIP BETWEEN NURSES RESILIENCE AND SOCIAL SUPPORT : PHILOSOPHY OF NURSING
Authors: Ernawati Naya , Pandin Moses Glorino Rumambo , Yusuf Ah 
Published: December 2024

AbstractIntroductionThe purpose of this study is to examine the philosophy of social support from the perspective of the resilience.MethodsThis study used a literature review using the PICOS framework. There are 11 articles in it, articleswere searched from 4 databases namely Sciencedirect, Scopus, PubMed, CINAHL. The keywords used in the literature search were resilience AND social support, AND nurses AND hospital. The search was limited to 2019-2024 publications, full articles, not review articles. The strategy used to search for articlesusing the PICOS framework. Then selected using the PRISMA diagram andobtained eleven articles. Quality assessment of eleven articles using the JBI CriticalAppraisal tool.ResultsTen articles describing the relationship between social support and resilience. Social Support can be used improve resilience in nurses at hospital.ConclusionSocial support is related to psychological resilience. Building resilience and social support can help reduce nurses’ vulnerability. Policymakers must develop and implement appropriate strategies to increase nurses’ social support and resilience to improve the quality of nursing care.
Cutaneous human papillomavirus E6 impairs the cGAS-STING pathway
Authors: Tolbert Emily , Dacus Dalton , Pollina Rose , Wallace Nicholas A. 
Published: December 2024

AbstractBeta genus human papillomaviruses (β-HPVs) are ubiquitous double stranded DNA (dsDNA) viruses that may promote skin cancers by destabilizing the host genome. Supporting this, expression of the E6 gene from a β-HPV (β-HPV 8 E6) results in increased micronuclei that should induce an innate immune response that eliminates these cells. Yet, β-HPV 8 E6 promotes rather than restricts proliferation. We hypothesize that β-HPV 8 E6 accomplishes this by attenuating the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway, an innate immune pathway that becomes activated in response to cytosolic micronuclear dsDNA. Here, we show that in response to stimulation by transfection of pLVX-GFP plasmid, β-HPV 8 E6 reduced the magnitude and intensity of cGAS-STING pathway activation in immunoblot experiments. These data also demonstrate that impairment of the cGAS-STING pathway is strongest downstream of STING phosphorylation. Further, RNA-sequencing suggests that β-HPV 8 E6 downregulates other innate immune pathways. We also show that cGAS is recruited to micronuclei induced by β-HPV 8 E6. These data suggest a mechanism by which β-HPV 8 E6 facilitates proliferation of cells destabilized by micronuclei and support the hypothesis that the prevalence of β-HPV infections is in part due to the impairment of the cGAS-STING innate immune response.
Spatial single cell transcriptomic analysis of a novel DICER1 Syndrome GEMM informs the cellular origin and developmental hierarchy of associated sarcomas
Authors: Kommoss Felix K.F. , Zhang Joyce , Lynch Branden J. , Chen Shary Yuting , Senz Janine , Moscovitz Yana , Hill Lesley Ann , Scott Wilder , Bush Jonathan , Chen Kenneth S. , von Deimling Andreas , Foulkes William D. , Morin Gregg , Underhill T. Michael , Wang Yemin , Huntsman David G. 
Published: December 2024

AbstractDICER1 syndrome predisposes children and young adults to tumor development across various organs. Many of these cancers are sarcomas, which uniquely express the RNase IIIb domain-deficient form of DICER1 and exhibit consistent histological and molecular similarities regardless of their anatomical origins. To uncover their cellular origin and developmental hierarchy, we established a lineage-traceable genetically engineered mouse model that allows for precise activation ofDicer1mutations in Hic1+mesenchymal stromal cells. This model resulted in the development of renal tumors closely mirroring human DICER1 sarcoma histologically and molecularly. Single-cell transcriptomics coupled with targeted spatial gene expression analysis revealed a Hic1+progenitor population marked byPdgfra,Dpt, andMfap4,corresponding to universal fibroblasts of steady-state kidneys. These fibroblastic progenitors exhibit the capacity to undergo rhabdomyoblastic differentiation or transition to highly proliferative anaplastic sarcoma. Investigation of patient samples identified analogous cell states. This study uncovers a fibroblastic origin for DICER1 sarcoma and provides a faithful model for mechanistic investigation and therapeutic development for tumors within the rhabdomyosarcoma spectrum.
Interactions betweenBrassica carinataand its pollinators is shaped by managed beehives and neonicotinoid seed treatment
Authors: Nottebrock Henning , Stiles Shane , Lundgren Jonathan G. , Fenster Charles B. 
Published: December 2024

AbstractBrassica carinatais a biofuel and animal feed crop with expanding global production. Although there is much research on common farming practices to improve yield, there is almost a complete absence of data on the dependency of yield through pollination services. Reciprocally, we lack information on whetherB. carinataoffers ecosystem services to pollinators. We observed almost 4000 pollinator visits, quantified different plant functional traits, including floral resources and examined the effect of supplementing fields with honey bee hives and the use of neonicotinoid seed treatment on seed yield and honey bee health. Data was collected from 35 0.404-ha sites with more than 800 focalB. carinataindividuals across 2 years in the Prairie Coteau region of the Northern Great Plains. We found that pollinators (n = 28 species) are attracted to floral resources at different spatial scales. High visitation rates by pollinator species were associated with double the seed set inB. carinatarelative to the lowest visitation rates.Brassica carinataadds floral resources to the agricultural ecosystem and therefore has the potential to increase pollinator health. However, species interactions are influenced by the use of insecticides and the presence of honey bees by managed beehives. In particular, insecticides alter the role of pollinators on crop pollination by reducing the positive impact of floral resources on pollinator-mediated yield and honey bee health.
Identifying Effect Modification of Latent Population Characteristics on Risk Factors with a Sparse Varying Coefficient Regression
Authors: Wang Ruofan , Fang Lei , Wang Yue , Jin Jin 
Published: December 2024

AbstractLeveraging observational data to understand the associations between risk factors and disease outcomes and conduct disease risk prediction is a common task in epidemiology. While traditional linear regression and other machine learning models have been extensively implemented for this task, the associations between risk factors and disease outcomes are typically deemed fixed. In many cases, however, such associations may vary by some underlying features of the individuals, which may involve certain subpopulation characteristics and environmental factors. While data for these latent features may not be available, the observed data on risk factors may have captured some proportion of the variation in these features. Thus extracting latent factors from risk factors and incorporating this effect modification into the model may better capture the underlying data structure and improve inference. We develop a novel regression model with some coefficients varying as functions of latent features extracted from the risk factors. We have demonstrated the superiority of our approach in various data settings via simulation studies. An application on a dataset for lung cancer patients from The Cancer Genome Atlas (TCGA) Program showed that our approach led to a 6% - 118% increase in (AUC-0.5) for distinguishing between different lung cancer stages compared to the classic lasso and elastic net regressions and identified interesting latent effect modifications associated with certain gene pathways.
Flow transport and not ejection fraction determines left ventricular stasis in patients with impaired systolic function
Authors: Martinez-Legazpi Pablo , Bermejo Javier , del Alamo Juan C. 
Published: December 2024

AbstractBackgroundImpaired left ventricular (LV) systolic function is a major risk factor for mural thrombosis and embolism, but LV ejection fraction (EF) poorly predicts these events, suggesting the existence of additional sources of variability. Advances in multi-dimensional flow imaging and patient-specific simulations have sparked the derivation of diverse metrics to assess blood stasis and transit efficiency. However, simple models to interpret these metrics and their dependence on chamber function are lacking.MethodsWe introduce queue models of LV blood transit connecting two common metrics of LV efficiency: flow component analysis and residence time (RT) mapping. These models yield closed-form expressions for the average RT of blood in the LV as a function of EF, direct flow (DF) —blood entering and leaving the LV in one cardiac cycle, and residual volume (RV) — blood persisting in the LV for >2 cycles. Models’ performance was tested against RT obtained from vector flow mapping in 332 subjects, including controls and patients with acute myocardial infarction (AMI), hypertrophic (HCM) and dilated (DCM) cardiomyopathy.ResultsQueue models revealed RT is increasingly sensitive to DF as EF decreases, contradicting the traditional view of large DF as a teleological advantage. Instead, RT is minimized when blood transits in a first-in-first-out (FIFO) manner, while DF short-circuits the FIFO pattern, prolonging RT for other flow components. FIFO models show a good performance to assess RT in the studied subjects, especially when accounting for patient-specific DF and RV, with R: 0.62 for the pooled data, 0.70 for control, and 0.60, 0.80 and 0.40 for AMI, DCM and HCM groups respectively.ConclusionBy developing queue models of LV blood transit, and testing them on a large clinical database, we show large DF may contribute to increased blood stasis when EF is low. These models also explain why EF is a poor thrombosis risk marker in AMI and DCM.
Amino Acid Transfer Free Energies Reveal Thermodynamic Driving Forces in Biomolecular Condensate Formation
Authors: Rekhi Shiv , Mittal Jeetain 
Published: December 2024

AbstractThe self-assembly of intrinsically disordered proteins into biomolecular condensates shows a dependence on the primary sequence of the protein, leading to sequence-dependent phase separation. Methods to investigate this sequence-dependent phase separation rely on effective residue-level interaction potentials that quantify the propensity for the residues to remain in the dilute phase versus the dense phase. The most direct measure of these effective potentials are the distribution coefficients of the different amino acids between the two phases, but due to the lack of availability of these coefficients, proxies, most notably hydropathy, have been used. However, recent work has demonstrated the limitations of the assumption of hydropathy-driven phase separation. In this work, we address this fundamental gap by calculating the transfer free energies associated with transferring each amino acid side chain analog from the dilute phase to the dense phase of a model biomolecular condensate. We uncover an interplay between favorable protein-mediated and unfavorable water-mediated contributions to the overall free energies of transfer. We further uncover an asymmetry between the contributions of positive and negative charges in the driving forces for condensate formation. The results presented in this work provide an explanation for several non-trivial trends observed in the literature and will aid in the interpretation of experiments aimed at elucidating the sequence-dependent driving forces underlying the formation of biomolecular condensates.
Local Haplotype Classifiers enable Efficient, Flexible, and Secure Genotype Imputation and Downstream Analyses
Authors: Cheema Muhammad Nadeem , Nazir Anam , Moon Jungho , Oh Yongwoo , Naseri Ardalan , Zhi Degui , Jiang Xiaoqian , Kim Miran , Harmanci Arif 
Published: December 2024

AbstractThe decreasing cost of genotyping technologies led to abundant availability and usage of genetic data. Although it offers many potentials for improving health and curing diseases, genetic data is highly intrusive in many aspects of individual privacy. Secure genotype analysis methods have been developed to perform numerous tasks such as genome-wide association studies, meta-analysis, kinship inference, and genotype imputation outsourcing. Here we present a new approach for using lightweight haplotype classifier models to use predicted haplotype information in a flexible privacy-preserving framework to perform genotype imputation and downstream tasks. Compared to the previous secure methods that rely main on linear models, our approach utilizes efficient models that rely on utilizing haplotypic information, which improves accuracy and increases the throughput of imputation by performing multiple imputations per model evaluation.