bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systemic longitudinal immune profiling identifies proliferating Treg cells as predictors of immunotherapy benefit: biomarker analysis from the phase 3 CONTINUUM and DIPPER trials
Authors: Huang Sai-Wei , Jiang Wei , Xu Sha , Zhang Yuan , Du Juan , Wang Ya-Qin , Yang Kun-Yu , Zhang Ning , Liu Fang , Zou Guo-Rong , Jin Feng , Wu Hai-Jun , Zhou Yang-Ying , Zhu Xiao-Dong , Chen Nian-Yong , Xu Cheng , Qiao Han , Liu Na , Sun Ying , Ma Jun , Liang Ye-Lin , Liu Xu 
Published: October 2024

AbstractThe identification of predictors for immunotherapy is often hampered by the absence of control groups in many studies, making it difficult to distinguish between prognostic and predictive biomarkers. This study presents biomarker analyses from the phase 3 CONTINUUM trial (NCT03700476), the first to show that adding anti-PD-1 (aPD1) to chemoradiotherapy (CRT) improves event-free survival (EFS) in patients with locoregionally advanced nasopharyngeal carcinoma. A dynamic single-cell atlas was profiled using mass cytometry on peripheral blood mononuclear cell samples from 12 pairs of matched relapsing and non-relapsing patients in the aPD1-CRT arm. Using a supervised representation learning algorithm, we identified a Ki67+ proliferating regulatory T cells (Tregs) population expressing high levels of activated and immunosuppressive molecules including FOXP3, CD38, HLA-DR, CD39, and PD-1, whose abundance correlated with treatment outcome. The frequency of these Ki67+ Tregs was significantly higher at baseline and increased during treatment in patients who relapsed compared to non-relapsers. Further validation through flow cytometry (n = 120) confirmed the predictive value of this Treg subset. Multiplex immunohistochemistry (n = 249) demonstrated that Ki67+ Tregs in tumors could predict immunotherapy benefit, with aPD1 improving EFS only in patients with low baseline levels of Ki67+ Tregs. These findings were further validated in the multicenter phase 3 DIPPER trial (n = 262, NCT03427827) and the phase 3 OAK trial of anti-PD-L1 immunotherapy in NSCLC, underscoring the predictive value of Ki67+ Treg frequency in identifying the beneficiaries of immunotherapy and potentially guiding personalized treatment strategies.
Stress relaxation and improved fracture toughness of metal bonding using flexible monolith sheets and an epoxy adhesive
Authors: Kamo Yoshiyuki , Matsumoto Akikazu 
Published: October 2024

Abstract
While epoxy resins exhibit excellent mechanical and insulating properties as well as excellent stability against heat and chemicals, epoxy adhesives also have drawbacks such as brittleness and stress concentration. Rubber-based materials are often added to epoxy adhesives to increase toughness, but they are sensitive to heat and moisture, limiting their effectiveness in harsh environments. In this study, we propose a new sheet-type adhesive consisting of a conventional liquid epoxy adhesive and an epoxy monolith sheet with internal continuous pores, using the advantageous properties of the flexibility and toughness of the epoxy monolith to avoid stress concentration. We evaluated the adhesion strength for metal bonding using the sheet-type epoxy adhesives via a lap-shear tensile adhesion test at various temperatures. The total destruction energy was also estimated via a tapered double cantilever beam test. Furthermore, a heat cycle adhesion test was conducted using two types of metallic materials with different coefficients of thermal expansion to elucidate the effect of the monolith sheet on the improvement of interfacial failure induced by stress concentration.
Direct observation of deformation and resistance to damage accumulation during shock loading of stabilized nanocrystalline Cu-Ta alloys
Authors: Hornbuckle B. C. , Koju R. K. , Kennedy G. , Jannotti P. , Lorenzo N. , Lloyd J. T. , Giri A. , Solanki K. , Thadhani N. N. , Mishin Y. , Darling K. A. 
Published: October 2024

AbstractEnergy absorption by matter is fundamental to natural and man-made processes. However, despite this ubiquity, developing materials capable of withstanding severe energy fluxes without degradation is a significant challenge in materials science and engineering. Despite recent advances in creating alloys resistant to energy fluxes, mitigating the damage caused by the absorption and transfer of mechanical energy remains a critical obstacle in both fundamental science and technological applications. This challenge is especially prominent when the mechanical energy is transferred to the material by shock loading. This study demonstrates a phenomenon in which microstructurally stabilized nanocrystalline Cu-Ta alloys can undergo reversal or nearly complete recovery of the dislocation structure after multiple shock-loading impacts, unlike any other known metallic material. The microstructure of these alloys can withstand repeated shock-wave interactions at pressures up to 12 GPa without any significant microstructural damage or deterioration, demonstrating an extraordinary capacity to be virtually immune to the detrimental effects of shock loading.
Community successional patterns and inter-kingdom interactions during granular biofilm development
Authors: de Celis Miguel , Modin Oskar , Arregui Lucía , Persson Frank , Santos Antonio , Belda Ignacio , Wilén Britt-Marie , Liébana Raquel 
Published: October 2024

AbstractAerobic granular sludge is a compact and efficient biofilm process used for wastewater treatment which has received much attention and is currently being implemented worldwide. The microbial associations and their ecological implications occurring during granule development, especially those involving inter-kingdom interactions, are poorly understood. In this work, we monitored the prokaryote and eukaryote community composition and structure during the granulation of activated sludge for 343 days in a sequencing batch reactor (SBR) and investigated the influence of abiotic and biotic factors on the granule development. Sludge granulation was accomplished with low-wash-out dynamics at long settling times, allowing for the microbial communities to adapt to the SBR environmental conditions. The sludge granulation and associated changes in microbial community structure could be divided into three stages: floccular, intermediate, and granular. The eukaryotic and prokaryotic communities showed parallel successional dynamics, with three main sub-communities identified for each kingdom, dominating in each stage of sludge granulation. Although inter-kingdom interactions were shown to affect community succession during the whole experiment, during granule development random factors like the availability of settlement sites or drift acquired increasing importance. The prokaryotic community was more affected by deterministic factors, including reactor conditions, while the eukaryotic community was to a larger extent shaped by biotic interactions (including inter-kingdom interactions) and stochasticity.
Quantum chemical calculation dataset for representative protein folds by the fragment molecular orbital method
Authors: Takaya Daisuke , Ohno Shu , Miyagishi Toma , Tanaka Sota , Okuwaki Koji , Watanabe Chiduru , Kato Koichiro , Tian Yu-Shi , Fukuzawa Kaori 
Published: October 2024

AbstractThe function of a biomacromolecule is not only determined by its three-dimensional structure but also by its electronic state. Quantum chemical calculations are promising non-empirical methods available for determining the electronic state of a given structure. In this study, we used the fragment molecular orbital (FMO) method, which applies to biopolymers such as proteins, to provide physicochemical property values on representative structures in the SCOP2 database of protein families, a subset of the Protein Data Bank. Our dataset was constructed by over 5,000 protein structures, including over 200 million inter-fragment interaction energies (IFIEs) and their energy components obtained by pair interaction energy decomposition analysis (PIEDA) using FMO-MP2/6-31 G*. Moreover, three basis sets, 6-31 G*, 6-31 G**, and cc-pVDZ, were used for the FMO calculations of each structure, making it possible to compare the energies obtained with different basis functions for the same fragment pair. The total data size is approximately 6.7 GB. Our dataset will be useful for functional analyses and machine learning based on the physicochemical property values of proteins.
CRITID: enhancing CRITIC with advanced independence testing for robust multi-criteria decision-making
Authors: Zhang Qiang , Fan Jiahui , Gao Chaobang 
Published: October 2024

AbstractIn multi-criteria decision-making and model evaluation, determining the weight of criteria is crucial. With the rapid development of information technology and the advent of the big data era, the need for complex problem analysis and decision-making has intensified. Traditional CRiteria Importance Through Intercriteria Correlation (CRITIC) methods rely on Pearson correlation, which may not adequately address nonlinearity in some scenarios. This study aims to refine the CRITIC method to better accommodate nonlinear relationships and enhance its robustness. We have developed a novel method named CRiteria Importance Through Intercriteria Dependence (CRITID), which leverages cutting-edge independence testing methods such as distance correlation among others. This approach enhances the assessment of intercriteria relationships. Upon application across diverse data distributions, the CRITID method has demonstrated enhanced rationality and robustness relative to the traditional CRITIC method. These improvements significantly benefit multi-criteria decision-making and model evaluation, providing a more accurate and dependable framework for analyzing complex datasets.
Large language model use in clinical oncology
Authors: Carl Nicolas , Schramm Franziska , Haggenmüller Sarah , Kather Jakob Nikolas , Hetz Martin J. , Wies Christoph , Michel Maurice Stephan , Wessels Frederik , Brinker Titus J. 
Published: October 2024

AbstractLarge language models (LLMs) are undergoing intensive research for various healthcare domains. This systematic review and meta-analysis assesses current applications, methodologies, and the performance of LLMs in clinical oncology. A mixed-methods approach was used to extract, summarize, and compare methodological approaches and outcomes. This review includes 34 studies. LLMs are primarily evaluated on their ability to answer oncologic questions across various domains. The meta-analysis highlights a significant performance variance, influenced by diverse methodologies and evaluation criteria. Furthermore, differences in inherent model capabilities, prompting strategies, and oncological subdomains contribute to heterogeneity. The lack of use of standardized and LLM-specific reporting protocols leads to methodological disparities, which must be addressed to ensure comparability in LLM research and ultimately leverage the reliable integration of LLM technologies into clinical practice.
Bacterial live therapeutics for human diseases
Authors: Frutos-Grilo Elisabet , Ana Yamile , Gonzalez-de Miguel Javier , Cardona-i-Collado Marcel , Rodriguez-Arce Irene , Serrano Luis 
Published: October 2024

AbstractThe genomic revolution has fueled rapid progress in synthetic and systems biology, opening up new possibilities for using live biotherapeutic products (LBP) to treat, attenuate or prevent human diseases. Among LBP, bacteria-based therapies are particularly promising due to their ability to colonize diverse human tissues, modulate the immune system and secrete or deliver complex biological products. These bacterial LBP include engineered pathogenic species designed to target specific diseases, and microbiota species that promote microbial balance and immune system homeostasis, either through local administration or the gut-body axes. This review focuses on recent advancements in preclinical and clinical trials of bacteria-based LBP, highlighting both on-site and long-reaching strategies.
Enhanced QSVM with elitist non‐dominated sorting genetic optimisation algorithm for breast cancer diagnosis
Authors: P Jose , Hariharan Shanmugasundaram , Madhivanan Vimaladevi , N Sujaudeen , Krisnamoorthy Murugaperumal , Cherukuri Aswani Kumar 
Published: October 2024

AbstractMachine learning has emerged as a promising method for predicting breast cancer using quantum computation techniques. Quantum machine learning algorithms, such as quantum support vector machines (QSVMs), are demonstrating superior efficiency and economy in tackling complex problems compared to traditional machine learning methods. When compared with classical support vector machine, the quantum machine produces remarkably accurate results. The suggested quantum SVM model in this study effectively resolved the binary classification problem for diagnosing malignant breast cancer. This work introduces an enhanced approach to breast cancer diagnosis by integrating QSVM with elitist non‐dominated sorting genetic optimization (ENSGA), leveraging the strengths of both techniques to achieve more accurate and efficient classification results. ENSGA plays a crucial role in optimising QSVM parameters, ensuring that the model attains the best possible classification accuracy while considering multiple objectives simultaneously. Moreover, the quantum kernel estimation method demonstrated exceptional performance by achieving high accuracy within an impressive execution time of 0.14 in the IBM QSVM simulator. The seamless integration of quantum computation techniques with optimisation strategies such as ENSGA highlights the potential of quantum machine learning in revolutionising the field of healthcare, particularly in the domain of breast cancer diagnosis.
Detecting and sizing the Earth with PLATO: A feasibility study based on solar data
Authors: Krenn A. F. , Lendl M. , Sulis S. , Deleuil M. , Hofmeister S. J. , Jannsen N. , Fossati L. , De Ridder J. , Seynaeve D. , Jarolim R. , Veronig A. M. 
Published: October 2024

Context. The PLAnetary Transits and Oscillations of stars (PLATO) mission will observe the same area of the sky continuously for at least two years in an effort to detect transit signals of an Earth-like planet orbiting a solar-like star.
Aims. We aim to study how short-term solar-like variability caused by oscillations and granulation would affect PLATO’s ability to detect and size Earth if PLATO were to observe the Solar System itself. We also compare different approaches to mitigate noise caused by short-term solar-like variability and perform realistic transit fitting of transit signals in PLATO-like light curves.
Methods. We injected Earth-like transit signals onto real solar data taken by the Helioseismic and Magnetic Imager (HMI) instrument on board the Solar Dynamics Observatory (SDO). We isolated short-term stellar variability in the HMI observations by removing any variability with characteristic timescales longer than five hours using a smooth Savitzky-Golay filter. We then added a noise model for a variety of different stellar magnitudes computed by PlatoSim assuming an observation by all 24 normal cameras. We first compared four different commonly used treatments of correlated noise in the time domain by employing them in a transit fitting scheme. We then tried to recover pairs of transit signals using an algorithm similar to the transit least squares algorithm. Finally, we performed transit fits using realistic priors on planetary and stellar parameters and assessed how accurately the pair of two injected transits was recovered.
Results. We find that short-term solar-like variability affects the correct retrieval of Earth-like transit signals in PLATO data. Variability models accounting for variations with typical timescales at the order of one hour are sufficient to mitigate these effects. We find that when the limb-darkening coefficients of the host star are properly constrained, the impact parameter does not negatively affect the detectability of a transit signal or the retrieved transit parameters, except for high values (b > 0.8). For bright targets (8.5–10.5 mag), the transit signal of an Earth analogue can reliably be detected in PLATO data. For faint targets a detection is still likely, though the results of transit search algorithms have to be verified by transit-fitting algorithms to avoid false positive detections being flagged. For bright targets (V-mag ≤ 9.5), the radius of an Earth-like planet orbiting a solar-like star can be correctly determined at a precision of 3% or less, assuming that at least two transit events are observed and the characteristics of the host star are well understood.
Successful Repair of Esophageal Atresia with Tracheoesophageal Fistula and Interrupted Inferior Vena Cava: A Rare Case Report
Authors: Mu Xiao Long , Wang Junqiu 
Published: October 2024

AbstractEsophageal atresia (EA) with tracheoesophageal fistula (TEF) is a congenital anomaly that can present complex surgical challenges, especially when accompanied by rare vascular conditions like an interrupted inferior vena cava (IVC). The division of the azygos vein is a common part of TEF repair, but in the presence of an interrupted IVC, this can lead to life-threatening complications. We report the case of a newborn diagnosed with EA, TEF, and interrupted IVC, successfully treated through thoracotomy. This case underscores the importance of prenatal and postnatal imaging to diagnose vascular anomalies prior to TEF repair, ensuring the preservation of the azygos vein to prevent fatal outcomes. Raising awareness of this rare association is crucial to optimizing surgical planning and outcomes.
Sleep Quality in Parkinson Disease: Clinical Insights and PSQI Reliability Assessment
Authors: Pezzini Julia Valle , Trevisan Dante Diniz , Dominiak Soares Victor Henrique , Gauer Luís Eduardo , Lima Marcelo M. S. 
Published: October 2024

AbstractSleep disturbances are prevalent in Parkinson disease (PD), encompassing a spectrum from parasomnias like REM sleep behavior disorder to symptoms of sleep-wake cycle dysregulation, such as insomnia and daytime sleepiness. This research investigates sleep quality in PD patients compared with a matched healthy control group and explores the relationships between PD clinical characteristics and sleep parameters. Additionally, the study assesses the reliability of the Pittsburgh Sleep Quality Index (PSQI) for PD patients by examining internal consistency. The study comprises 52 participants, 27 in the PD group and 25 in the healthy control group, matched for sex and age. Sleep quality revealed that PD patients experienced significantly poorer sleep quality than the control group (p = 0.009). Weak correlations were found between PSQI scores and the modified Hoehn and Yahr scale (p = 0.062), with no correlation observed with the daily equivalent dose of levodopa (L-DOPA). The prevalence of poor sleep quality (PSQI score > 5) was 85.1% for PD patients and 68% for the control group. The internal consistency analysis of the PSQI yielded a Cronbach's
α of 0.588 for the PD group. While the PSQI demonstrates utility in detecting general sleep abnormalities and gauging patient perceptions of sleep quality in PD, its limitation as a global score is emphasized. The index prioritizes sleep habits and may not fully capture important sleep disorders in this population. These findings underscore the complex relationship between PD and sleep quality, suggesting the need for a comprehensive approach to assess and address sleep disturbances in PD patients.
Voltage-induced rearrangement in silver nanoparticles spatial distribution produced by EAFD method and its LSPR optimization
Authors: Amirdadi Ehsan , Masheli Milad Habibi , Mostafavi Amjad Jafar 
Published: October 2024

Abstract
This paper presents a voltage-induced and thermal annealing rearrangement (VITAR) method based on modified electric field assisted film dissolution method as a flexible and powerful tool for manipulating nanoparticles spatial distribution based on drift and diffusion mechanisms that occur due to external DC voltage and thermal annealing processes. Different samples with various arrangements of external DC voltage and thermal annealing processes have been produced. The extinction and attenuated total reflection (ATR) spectra, as well as atomic force microscope (AFM) images, have been employed to investigate their optical and morphological properties. Four cases with arrangements of DV-Anl, DV-Anl-DV, DV-Anl-IV, and DV-IV-Anl have been studied. The AFM images show that by applying secondary voltage (direct or inverse voltage), it is possible to drift nanoparticles and change its morphology (size and shape) as well as surface and volume distributions. As a result, by applying a secondary direct voltage (in the DV-Anl-DV case), the surface density of nanoparticles decreases due to direct drift force. It is notable that in this case, the extinction peak and ATR depth have not significantly changed. By applying a secondary inverse voltage (in the DV-Anl-IV, and DV-IV-Anl cases), an increase in the surface density of the nanoparticles has been observed. Also, the extinction peak has increased, and the ATR depth has decreased in the DV-Anl-IV case, but in the DV-IV-Anl case, due to the uniform size of surface nanoparticles, the resonance power has shown a significant increase in both extinction and ATR spectra compared to other cases. The resulting changes in extinction and ATR spectra show that by using the VITAR process, the surface structure, morphology and its optical properties can be optimized and this method provides a great opportunity to enhance Localized Surface Plasmon Resonance effects, which can be employed in nano-optical devices.