bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and validation of pyroptosis patterns in AML via comprehensive bioinformatics analysis
Authors: Zhang Huifang , Deng Zeyu , Huang Zineng , Wang Peilong , Cheng Zhao , Peng Hongling 
Published: November 2023

Abstract
Background
Pyroptosis, a new type of programmed cell death, was associated with inflammation, immunity, and the development of tumor. However, the prognostic roles of pyroptosis-related genes and the correlation between pyroptosis and immunity in acute myeloid leukemia (AML) remains to be unrevealed.
Methods
This study analyzed the expression level and prognostic roles of 40 pyroptosis-related genes in AML patients. Clinical subtypes of AML were identified by nonnegative matrix factorization method (NMF) according to the expression level of pyroptosis-related genes. We also comprehensively explore the enrichment score (ES) of immunologic gene sets in different subtypes of AML by gene set variation analysis (GSVA). Least absolute shrinkage and selection operator method (LASSO) were used to seek prognostic immunologic gene sets and protein-protein interaction network was constructed to identify hub gens.
Results
32 pyroptosis-related genes were differently expressed between AML and the healthy, and 9 pyroptosis-related genes were significantly associated with the prognosis of AML patients. We identified two clinically relevant subtypes of AML and patients with subtype 1 had a better overall survival. The ES of immunologic gene sets were significantly different in two subtypes of AML and four were associated with the prognosis of AML patients. Notably, MF enrichment and Reactome pathway indicated that four prognostic immunologic gene sets were mainly associated with terms of cell adhesion molecule binding, ubiquitin protein ligase binding, cytokine activity in MF, and interferon signaling, class I MHC mediated antigen processing & presentation. Finally, 9 hub genes were found from the four prognostic immunologic gene sets.
Conclusions
We demonstrated the important role of pyroptosis in AML and identified two AML subtypes. This provides additional useful data for the development of clinical therapy for AML.
Wave-particle duality in the asymmetrical double-slit interference experiments
Authors: Van Thuan Vo , Duc Vinh Vu , Thanh Hung Nguyen , Quang Thieu Dang 
Published: November 2023

Abstract

We perform spectral analysis based on a suitable theoretical correlation between V-wave visibility and D-particle distinguishability following the complemen-tarity principle to verify wave-particle duality in the asymmetrical double-slit experiments. The selective interference spectra obtained in the experiments ensure the single-photon approximation in the Fraunhofer far-field condition. The results show that the theoretical interpretation following wave-particle complementarity may not be consistent with the experimental data, especially at the first main minima of the optical diffraction distributions. A dilemma would arise when one tries to revise the theoretical explanations for preserving the complementarity principle.
Sample Size Determination For Multidimensional Parameters And The A-Optimal Subsampling In A Big Data Linear Regression Model
Authors: Zhang Sheng , Tan Fei , Peng Hanxiang 
Published: November 2023

Abstract
To fast approximate the least squares estimator (LSE) efficiently in a Big Data linear regression by a subsampling LSE, numerous optimal sampling distributions are derived based on the criterion of minimizing the sum of the component variances of the subsampling LSE. We discuss truncation of the distributions, and construct the Scoring Algorithm with far less running time for implementing the subsampling LSE than for the full-sample LSE. The subsampling LSE is proved to be almost surely asymptotically normal for an arbitrary sampling distribution under suitable conditions. Motivated by subsampling and data-splitting in machine learning, sample size determination for multidimensional parameters is investigated. We conduct a comprehensive evaluation of our proposed approach through various numerical studies and compare it with the uniform sampling. Our results in both simulated and real data indicate that our approach substantially outperforms the uniform and the Algorithm significantly reduces the computational time required for implementing the full-sample LSE.
Modeling of Amplified Spontaneous Emission Noise for Quantum Communication Applications
Authors: Udvary Eszter 
Published: November 2023

Abstract

There is an increasing need for quantum communication applications, including true random numbers and quantum key distribution. The Amplified Spontaneous Emission (ASE) is a quantum physics process, which can play a significant role in both cases. A physical model for detecting and acquiring the ASE noise is developed. The photon probability is calculated, and the relationship with system parameters is presented. Experimental results quantitatively validate the physical model; the simulation results all significantly fit the corresponding experimental data well.
Modular geodesics and wedge domains in non-compactly causal symmetric spaces
Authors: Morinelli Vincenzo , Neeb Karl-Hermann , Gestur´Olafsson Gestur´OlafssonGestur´ 
Published: November 2023

Abstract
We continue our investigation of the interplay between causal structures on symmetric spaces and geometric aspects of Algebraic Quantum Field Theory. We adopt the perspective that the geometric implementation of the modular group is given by the flow generated by an Euler element of the Lie algebra (an element defining a 3-grading). Since any Euler element of a semisimple Lie algebra specifies a canonical non-compactly causal symmetric space M = G/H, we turn in this paper to the geometry of this flow. Our main results concern the positivity region W of the flow (the corresponding wedge region): If G has trivial center, then W is connected, it coincides with the so-called observer domain, specified by a trajectory of the modular flow which at the same time is a causal geodesic. It can also be characterized in terms of a geometric KMS condition, and it has a natural structure of an equivariant fiber bundle over a Riemannian symmetric space that exhibits it as a real form of the crown domain of G/K. Among the tools that we need for these results are two observations of independent interest: a polar decomposition of the positivity domain and a convexity theorem for G-translates of open H-orbits in the minimal flag manifold specified by the 3-grading.
MSC 2010: Primary 22E45; Secondary 81R05, 81T05
Three South African silcrete sources can be identified regardless of heat treatment using solution ICP-MS and LA-ICP-MS
Authors: Hirniak Jayde N. , Murray John K. , Zipkin Andrew M. 
Published: November 2023

Abstract
Silcrete is widely used for stone tool manufacture throughout various parts of the world and is sometimes heat-treated to improve flaking quality. Properly sourcing this raw material can provide insight into exchange networks and mobility patterns of early human populations, however, we only have a minor understanding of how heat treatment impacts the geochemistry of silcrete and how this varies between and within sources. This is particularly important in South Africa where heat-treated silcrete artifacts are common during the later Middle Stone Age. Here, we examine how heat treatment affects the geochemical composition of silcrete from three sources near the Pinnacle Point site complex in South Africa. We selected five unheated and five experimentally heat-treated silcrete samples from each source (n = 30) for solution ICP-MS analysis. We also test whether laser ablation ICP-MS is a viable method for sourcing silcrete since sample preparation for solution analyses can be challenging (i.e., use of harsh chemicals, issues digesting the sample). Our results suggest that all sources can be distinguished regardless of the treatment state and for both analytical approaches. The results of this study will help inform future provenience studies of silcrete artifacts to better understand how early humans living near Pinnacle Point interacted with the landscape.
Revisiting Named Entity Recognition in Food Computing: Enhancing Performance and Robustness
Authors: Akujuobi Uchenna , Liu Shuhong , Besold Tarek R. 
Published: November 2023

Abstract

In the ever-evolving domain of food computing, Named Entity Recognition (NER) presents transformative potential that extends far beyond mere word tagging in recipes. Its implications encompass intelligent recipe recommendations, health analysis, and personalization. Nevertheless, existing NER models in food computing encounter challenges stemming from variations in recipe input standards, limited annotations, and dataset quality. This article addresses the specific problem of ingredient NER and introduces two innovative models: SINERA, an efficient and robust model, and SINERAS, a semi-supervised variant that leverages a Gaussian Mixture Model (GMM) to learn from untagged ingredient list entries.
To mitigate issues associated with data quality and availability in food computing, we introduce the SINERA dataset, a diverse and comprehensive repository of ingredient lines. Additionally, we identify and tackle a pervasive challenge---spurious correlations between entity positions and predictions. To address this, we propose a set of data augmentation rules tailored for food NER. Extensive evaluations conducted on the SINERA dataset and a revised TASTEset dataset underscore the performance of our models. They outperform several state-of-the-art benchmarks and rival the BERT model while maintaining smaller parameter sizes and reduced training times.
Multiparametric magnetic resonance imaging in preoperative assessment of follicular thyroid neoplasm
Authors: Song Bin , Zheng Tingting , Wang Hao , Tang Lang , Xie Xiaoli , Fu Qingyin , Liu Weiyan , Wu Pu-Yeh , Zeng Mengsu 
Published: November 2023

Abstract
Objectives
To examine multiparametric magnetic resonance imaging for differentiating follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN).
Methods
Seven hundred two thyroid nodules, postoperatively confirmed by pathology, were retrospectively investigated and divided into two cohorts: training (n = 482) and validation (n = 220). The 133 FTNs were split into two groups: BFTN (n = 116) and MFTN (n = 17). Univariate and multivariate logistic regression analysis were used to identify independent predictors of FTN and MFTN. An nomogram for FTN and a risk score system for MFTN were constructed based on the results of multivariable analysis. Nomogram’ performance was evaluated based on discrimination, calibration, and clinical utility. The diagnostic performance of the risk score system for MFTN was compared with the performance of the Thyroid Imaging Reporting and Data System (TIRADS).
Results
The nomogram, which incorporated independent predictors, demonstrated good discrimination and calibration for differentiating FTN and non-FTN both in the training cohort (AUC = 0.947, Hosmer-Lemeshow P = 0.698) and the validation cohort (AUC = 0.927, Hosmer-Lemeshow P = 0.088). Tumor size, restricted diffusion, and cystic degeneration were risk factors for differentiating MFTN from BFTN. The AUC of the risk score system for MFTN prediction was 0.902 (95% CI 0.811–0.993), and the sensitivity, specificity, accuracy, and positive and negative predictive values of the risk score system at the optimal cutoff value were 76.5%, 94%, 91.8%, 65%, and 96.5%, respectively, which was better performance than five TIRADS.
Conclusions
The models based on MRI features had favorable diagnostic performance for preoperative prediction of FTN and MFTN. These models may aid in reducing unnecessary invasive biopsy or surgery.
Flexural behavior of reinforced concrete beams with steel and GFRP reinforcement
Authors: Kinjawadekar Trupti Amit , Patil Shantharam , Nayak Gopinatha , Kumar Saish 
Published: November 2023

Abstract

The use of alternative reinforcement in concrete structures in the form of glass fiber-reinforced polymer (GFRP) is a favorable option to the traditional reinforcement of steel. These bars possess unique features, including resistance to corrosion, an impressive tensile strength by weight ratio, and electromagnetic transparency, making them particularly appealing to the construction sector and structural engineers. The brittleness of GFRP bars significantly lowers the concrete beams’ ductility. Moreover, the significant deformations observed during the post-cracking phase is the effect of lower elastic modulus of these bars. The aim of this research study is to gain a deeper insight into the behaviour of structural members in flexure that are reinforced with GFRP bars. The failure modes were observed. The outcomes of load‒deflection performance are discussed. The fracture patterns observed in beams subjected to two point loading conditions have been documented for beams made of reinforced concrete that use both steel and GFRP as reinforcement. A finite element nonlinear analysis is performed using ABAQUS, to explore the exact response of specimens observed in experimental studies. A comparative study was performed between the experimental and numerical results.
Evaluation of the effect of Drimia Maritima and curcumin extracts in changes in the expression of Bax, Bcl-2, and P53 genes in lung cancer non-small cell
Authors: Sepehr Negin Noori , Soleimanifar Fatemeh , Dehaghi Nafiseh Khosravi , Mahboudi Hossein , zare Fereshteh , Tavasoli Afsaneh , Sameni Fatemeh , Kashani Hamed Haddad 
Published: November 2023

Abstract
Introduction:
Lung cancer is one of the most common malignancies in the world, with a very high mortality rate. Surgery and chemotherapy are among the first approaches to cancer treatment, which are associated with severe side effects, so more research has been done in the field of using medicinal plants with less toxicity. In the present study, we investigated the simultaneous effect of Drimia maritima plant extract (proscillaridin A), a cardiac glycoside, and turmeric plant extract (curcumin) in inducing apoptosis of non-small cell lung cancer cells.
Methods and Materials
Treatment of cancerous and non-cancerous cells with plant extracts was done by the MTT method, and the RNA of the samples was extracted using an extraction kit, and then cDNAs were synthesized using a special kit. Specific primers were designed for the sequence of P53, Bax, Bcl-2, and Gapdh genes, and the expression levels of the desired genes were checked and analyzed using the real-time PCR method. Cell cycle changes and apoptosis rates were also checked using the flow cytometry method.
Results
The results of investigating the simultaneous effect of proscillaridin and curcumin extracts on non-small cell lung cancer cells showed that we did not witness the synergistic power of the extracts together with each other, but we saw an increase in the survival of cancerous and non-cancerous cells, which, of course, in the case of non-cancerous cells were more impressive, and the two extracts seem to have neutralized each other's effect. The results indicate that the effect of each extract alone on cell lines (especially Calu-3 compared to A549) was greater.
Conclusions
Therefore, according to the research, it is possible that the use of extracts along with a suitable chemotherapy drug has a more significant effect on the life of normal or non-cancerous cells, which reduces the side effects of the drug and can increase the penetration rate of the chemotherapy drug, so in this field, more studies are needed.
Regulatory Science: The Maturation of an Evolving Scientific Discipline
Authors: Moghissi A. Alan , Steen Tomoko , Calderone Richard , Auffret Jean Pierre , Jaeger Lisa , Xu Liwei Sarah , Wixson McBride Carolyn , McBride Dennis 
Published: November 2023

Regulatory science encompasses the participation of a large array of scientific disciplines involved in the regulatory process. Although each discipline addresses different phenomenology and exploits different methodologies, the common scientific core is the same: objective pursuit of verifiable and useful knowledge. This paper updates the definition and scope of the practice of regulatory science, starting with a concise historical overview. It then examines the different phases of regulatory science applications: initial, exploratory, and standard operating. The paper also reviews the definitions of regulatory science used by various agencies and provides abbreviated scientific definitions. The paper summarizes Best Available Regulatory Science (BARS) and Metrics for Evaluation of Scientific Claims (MERSC), along with key elements and tools of regulatory science: peer review; regulatory science ethics, including the so-called Jeffersonian principle; mathematical models; cost benefit analysis; and stakeholder participation. The paper concludes with a brief description of these key tools and elements, highlighting their importance in the field of regulatory science.
Protein Species of Origin Determination By NMR Relaxometry
Authors: Webster Gregory K. 
Published: November 2023

Aims:
The aim of this project was to develop a QC friendly and efficient method of protein
species of origin identification to replace more costly mass spectrometric based methods currently
being used for this testing.

Background:
NMR relaxation measurements with proteins in aqueous solutions exploit the fast
chemical exchange between water and exposed NH and OH protons of amino acid side chains in
the folded protein structure unique to each biologic drug. Implementation of this technique has led
to routine testing for authentication and forensics of biopharmaceuticals, determination of moisture
content in lyophilized protein formulations and aggregation of proteins in solution. For small
molecule applications, TD-NMR can detect if solvents are received neat or tainted with moisture,
impurities, or denaturants.

Objective:
The objective of this study was to evaluate the ability of NMR Relaxation measurements
to differentiate between sources of Albumin proteins as a rapid QC test. Evaluation of differences
in molecular mobility between components in a solution as reflected in the longitudinal
(T1) and transverse (T2) relaxation times of protons demonstrate that NMR relaxation techniques
can distinguish between different albumin sources of origin.

Methods:
Representative albumin proteins from differing sources of origin were studied. Using
bovine serum albumin (BSA) as the target species of origin, NMR relaxation techniques as well as
chemometric modeling were used to evaluate the use of this technique for protein source of origin
identification.

Results:
NMR Relaxation using benchtop instrumentation showed that the bovine albumin species
of origin can be distinguished from porcine, chicken egg white and sheep sources of origin. Goat
albumin selectivity remained questionable and BSA cannot be distinguished from human or rabbit
sources of origin within the representative variability.

:
T2 transverse relaxation results were significantly more discriminating for protein source identification
than the T1 longitudinal relaxation result by itself. The T1 longitudinal relaxation result did
not contribute significantly to this investigation. However, fusing the T1 data with the T2 transverse
relaxation results and using larger data sets merit further evaluation in the hope of achieving
additional selectivity.

Conclusion:
While additional lots are needed for more definitive results, this preliminary evaluation
of using NMR Relaxation demonstrated the capability for the source of origin species discrimination
and identification using benchtop NMR instrumentation.
The Relationship Between Sarcopenia And Proteinuria, What Do We
Know?
Authors: Gungor Ozkan , Ulu Sena , Inci Ayca , Topal Kenan , Kalantar-Zadeh Kamyar 
Published: November 2023

Abstract:
Sarcopenia is one of the most common geriatric syndromes in the elderly. It is defined
as a decrease in muscle mass and function, and it can lead to physical disability, falls, poor
quality of life, impaired immune system, and death. It is known that, the frequency of sarcopenia
increases in the kidney patient population compared to healthy individuals. Although it is known
that kidney disease can lead to sarcopenia; our knowledge of whether sarcopenia causes kidney
disease is limited. Prior studies have suggested that protein energy wasting may be a risk of de
novo CKD. Proteinuria is an important manifestation of kidney disease and there is a relationship
between sarcopenia and proteinuria in diabetes, geriatric population, kidney transplant, and
nephrotic syndrome. Does proteinuria cause sarcopenia or vice versa? Are they both the results
of common mechanisms? This issue is not clearly known. In this review, we examined the relationship
between sarcopenia and proteinuria in the light of other studies.
Open-Source, Step-Counting Algorithm for Smartphone Data Collected in Clinical and Nonclinical Settings: Algorithm Development and Validation Study
Authors: Straczkiewicz Marcin , Keating Nancy L , Thompson Embree , Matulonis Ursula A , Campos Susana M , Wright Alexi A , Onnela Jukka-Pekka 
Published: November 2023

Background
Step counts are increasingly used in public health and clinical research to assess well-being, lifestyle, and health status. However, estimating step counts using commercial activity trackers has several limitations, including a lack of reproducibility, generalizability, and scalability. Smartphones are a potentially promising alternative, but their step-counting algorithms require robust validation that accounts for temporal sensor body location, individual gait characteristics, and heterogeneous health states.

Objective
Our goal was to evaluate an open-source, step-counting method for smartphones under various measurement conditions against step counts estimated from data collected simultaneously from different body locations (“cross-body” validation), manually ascertained ground truth (“visually assessed” validation), and step counts from a commercial activity tracker (Fitbit Charge 2) in patients with advanced cancer (“commercial wearable” validation).

Methods
We used 8 independent data sets collected in controlled, semicontrolled, and free-living environments with different devices (primarily Android smartphones and wearable accelerometers) carried at typical body locations. A total of 5 data sets (n=103) were used for cross-body validation, 2 data sets (n=107) for visually assessed validation, and 1 data set (n=45) was used for commercial wearable validation. In each scenario, step counts were estimated using a previously published step-counting method for smartphones that uses raw subsecond-level accelerometer data. We calculated the mean bias and limits of agreement (LoA) between step count estimates and validation criteria using Bland-Altman analysis.

Results
In the cross-body validation data sets, participants performed 751.7 (SD 581.2) steps, and the mean bias was –7.2 (LoA –47.6, 33.3) steps, or –0.5%. In the visually assessed validation data sets, the ground truth step count was 367.4 (SD 359.4) steps, while the mean bias was –0.4 (LoA –75.2, 74.3) steps, or 0.1%. In the commercial wearable validation data set, Fitbit devices indicated mean step counts of 1931.2 (SD 2338.4), while the calculated bias was equal to –67.1 (LoA –603.8, 469.7) steps, or a difference of 3.4%.

Conclusions
This study demonstrates that our open-source, step-counting method for smartphone data provides reliable step counts across sensor locations, measurement scenarios, and populations, including healthy adults and patients with cancer.