bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neutrino oscillations in matter using the adjugate of the Hamiltonian
Authors: Abdullahi Asli , Parke Stephen J. 
Published: July 2024

AbstractWe revisit neutrino oscillations in constant matter density for a number of different scenarios: three flavors with the standard Wolfenstein matter potential, four flavors with standard matter potential and three flavors with non-standard matter potentials. To calculate the oscillation probabilities for these scenarios one must determine the eigenvalues and eigenvectors of the Hamiltonians. We use a method for calculating the eigenvalues that is well known, determination of the zeros of determinant of matrix $$(\lambda I -H)$$

(
λ
I
-
H
)

, where H is the Hamiltonian, I the identity matrix and $$\lambda $$
λ
is a scalar. To calculate the associated eigenvectors we use a method that is little known in the particle physics community, the calculation of the adjugate (transpose of the cofactor matrix) of the same matrix, $$(\lambda I -H)$$

(
λ
I
-
H
)

. This method can be applied to any Hamiltonian, but provides a very simple way to determine the eigenvectors for neutrino oscillation in matter, independent of the complexity of the matter potential. This method can be trivially automated using the Faddeev–LeVerrier algorithm for numerical calculations. For the above scenarios we derive a number of quantities that are invariant of the matter potential, many are new such as the generalization of the Naumov–Harrison–Scott identity for four or more flavors of neutrinos. We also show how these matter potential independent quantities become matter potential dependent when off-diagonal non-standard matter effects are included.
Single charged Higgs pair production in exclusive processes at the LHC
Authors: Duarte Laura , Gonçalves Victor P. , Martins Daniel E. , Melo Téssio B. de 
Published: July 2024

AbstractThe production of a single charged Higgs boson pair by photon–photon interactions in pp collisions at the LHC is investigated in this exploratory study. We focus on the exclusive production, which is characterized by intact protons and two-rapidity gaps in the final state, and assume the type-I two-Higgs-doublet model, which still allows a light charged Higgs. Assuming the leptonic $$H^{\pm }\rightarrow [\tau \nu _{\tau }]$$

H
±

→

[
τ

ν
τ

]

decay mode, we derive predictions for the transverse momentum, rapidity and invariant mass distributions of the $$\tau ^+ \tau ^-$$

τ
+

τ
-

pair for different values of the charged Higgs mass. The contributions of different background processes are also estimated. Our results indicate that the contribution of the exclusive $$H^+ H^-$$

H
+

H
-

production for the $$[\tau ^{+}\nu _{\tau }][\tau ^{-} \nu _{\tau }]$$

[

τ
+

ν
τ

]

[

τ
-

ν
τ

]

final state is non-negligible and can, in principle, be used to searching for a light charged Higgs.
Noise and Parameter Mismatch in a Ring Network for Sensing Extremely Low Electric Fields
Authors: Palacios Antonio , Tamez Jacinto , Amani Mani , In Visarath 
Published: July 2024

Over the past years, we have exploited the bistability features that are commonly found in many individual sensors to develop a network-based [ Acebrón et al. , 2003 ; Bulsara et al. , 2004 ; In et al. , 2003a ; In et al. , 2003b ; In et al. , 2005 ; In et al. , 2006 ; In et al. , 2012 ; Palacios et al. , 2005 ] approach to modeling, designing, and fabricating extremely sensitive magnetic- and electric-field sensors capable of resolving field changes as low as 150[Formula: see text]pT and 100[Formula: see text]fAmps, respectively. Higher sensitivity is achieved by exploiting the symmetry of the network to create infinite-period bifurcations that render the ensuing oscillations highly sensitive to symmetry-breaking effects from external signals. In this paper, we study the effects of noise on the response of a network-based electric-field sensor as well as the effects of parameter mismatch, which appear naturally due to material imperfections and noise. The results show that Signal-to-Noise Ratio (SNR) increases sharply near the onset of the infinite-period bifurcation, and they increase further as the coupling strength in the network increases while passing the threshold that leads to oscillatory behavior. Overall, the SNR indicates that the negative effects of highly contaminated signals are well-mitigated by the sensitivity response of the system. In addition, computer simulations show the network-based system to be robust enough to mismatches in system parameters, while the deviations from the nominal parameter values form regions where the oscillations persist. Noise has a smoothing effect over the boundaries of these regions.
USING IFS TO REVEAL BIASES IN THE DISTRIBUTION OF PRIME NUMBERS
Authors: BROTHERS HARLAN J. 
Published: July 2024

It was long assumed that the pseudorandom distribution of prime numbers was free of biases. Specifically, while the prime number theorem gives an asymptotic measure of the probability of finding a prime number and Dirichlet’s theorem on arithmetic progressions tells us about the distribution of primes across residue classes, there was no reason to believe that consecutive primes might “know” anything about each other — that they might, for example, tend to avoid ending in the same digit. Here, we show that the Iterated Function System method (IFS) can be a surprisingly useful tool for revealing such unintuitive results and for more generally studying structure in number theory. Our experimental findings from a study in 2013 include fractal patterns that reveal “repulsive” phenomena among primes in a wide range of classes having specific congruence properties. Some of the phenomena shown in our computations and interpretation relate to more recent work by Lemke Oliver and Soundararajan on biases between consecutive primes. Here, we explore and extend those results by demonstrating how IFS points to the precise manner in which such biases behave from a dynamic standpoint. We also show that, surprisingly, composite numbers can exhibit a notably similar bias.
The future of geoenergy – a perspective
Authors: Gluyas J. G. , Fowler N. 
Published: July 2024

Energy from Earth resources (geoenergy) in the form of coal, oil and gas has fuelled the global society since the Industrial Revolution began. Amongst the consequences of fuelling society and associated population growth, is climate change, driven by the emission of greenhouse gases liberated through unabated combustion of fossil fuels.
There is much more to Earth energy systems, however, than just coal oil and gas. The Earth contains, in human terms, an unlimited supply of accessible heat and pressure (differences), as well as copious quantities of storage space, non-hydrocarbon gases and valuable solutes. These resources can be targeted to provide sustainable energy sources with low to zero carbon footprints.
This report does not contain any new radical technologies that will deliver energy free from all environmental impacts but it does show that, when considering geoenergy, society needs to look at the whole system, which combines chemical, thermal, potential, kinetic, gravitational and other energy forms that could be used from individual developments to minimize waste, maximize efficiency and reduce unwanted impacts.
We demonstrate that geoenergy will continue to play a key role in decarbonized energy systems for centuries to come.
Optimization Applications as Quantum Performance Benchmarks
Authors: Lubinski Thomas , Coffrin Carleton , McGeoch Catherine , Sathe Pratik , Apanavicius Joshua , Bernal Neira David , Quantum Economic Development Consortium(QED-C) Collaboration  
Published: July 2024

Combinatorial optimization is anticipated to be one of the primary use cases for quantum computation in the coming years. The Quantum Approximate Optimization Algorithm and Quantum Annealing can potentially demonstrate significant run-time performance benefits over current state-of-the-art solutions. Inspired by existing methods to characterize classical optimization algorithms, we analyze the solution quality obtained by solving Max-cut problems using gate-model quantum devices and a quantum annealing device. This is used to guide the development of an advanced benchmarking framework for quantum computers designed to evaluate the trade-off between run-time execution performance and the solution quality for iterative hybrid quantum-classical applications. The framework generates performance profiles through compelling visualizations that show performance progression as a function of time for various problem sizes and illustrates algorithm limitations uncovered by the benchmarking approach. As an illustration, we explore the factors that influence quantum computing system throughput, using results obtained through execution on various quantum simulators and quantum hardware systems.
Mesenchymal Stem Cell–Conditioned Media Modulate HUVEC Response to H2O2: Impact on Gene Expression and Potential for Atherosclerosis Intervention
Authors: Alqasoumi Abdulmajeed , Alsharidah Mansour , Mahmood Amer , Elsafadi Mona , Al Rugaie Osamah , Mohany Khalid M. , Al-Regaiey Khalid A. , Alyahya Khaleel I. , Alanteet Alaa A. , Algarzae Norah K. , AlGhibiwi Hanan K. , AlHomaidi Adel , Abumaree Mohammad 
Published: July 2024

Background: We studied the potential of human bone marrow–derived mesenchymal stem cell conditioned media (hBMSC CM) in protecting endothelial cell properties (viability, proliferation, and migrations) from the deleterious effects produced by the inflammatory environment of H2O2. Additionally, we investigated their impact on the endothelial cells’ gene expression of some inflammatory‐related genes, namely, TGF‐β1, FOS, ATF3, RAF‐1, and SMAD3.Methods: Human umbilical vein endothelial cells (HUVECs) were cultured individually under three conditions: alone, with varying concentrations of H2O2, or with varying concentrations of H2O2 and hBMSC CM. HUVEC adhesion, proliferation, and migration were evaluated using the xCELLigence system. The HUVECs’ gene expressions were evaluated by real‐time polymerase chain reaction (RT–PCR).Results: Generally, we observed enhanced HUVEC viability, proliferation, and migration when cultured in media supplemented with H2O2 and hBMSC CM. Furthermore, the CM modulated the expressions of the studied inflammatory‐related genes in HUVECs, promoting a more robust cellular response.Conclusion: This study has illuminated the protective role of hBMSC CM in mitigating the damaging effects of H2O2 on endothelial cell function. Our data demonstrate that hBMSC CM enhances the viability, proliferation, and migration of HUVECs even under oxidative stress conditions. Additionally, the conditioned medium was found to modulate the gene expression of pivotal markers related to inflammation, suggesting a favorable influence on cellular response mechanisms.
Association between Long-term Energy Balance–Related Factors and Survival in Colorectal Cancer Overall and by Metabolic Warburg-Subtypes
Authors: Offermans Kelly , Jenniskens Josien C.A. , Simons Colinda C.J.M. , Samarska Iryna , Fazzi Gregorio E. , Smits Kim M. , Schouten Leo J. , Weijenberg Matty P. , Grabsch Heike I. , van den Brandt Piet A. 
Published: July 2024

Abstract

Background:
Long-term energy balance–related factors (i.e., lifestyle and physiologic factors that influence the equilibrium between energy intake and energy expenditure over an extended period) such as body mass index (BMI) are linked to colorectal cancer risk, but their impact on colorectal cancer survival is unclear. We explored associations between these long-term energy balance–related factors and survival and examined potential differences across metabolic Warburg-subtypes.

Methods:
Associations between long-term energy balance–related factors and survival in the total series of patients with colorectal cancer (n = 2,347) obtained from the prospective Netherlands Cohort Study, as well as according to Warburg-subtype (Warburg-low: n = 652, Warburg-moderate: n = 802, Warburg-high: n = 797), were investigated using Cox regression analysis.

Results:
Among the long-term energy balance–related factors studied, only increasing prediagnostic BMI was associated with a borderline significant poorer overall survival in patients with colorectal cancer [HR5kg/m2, 1.07; 95% confidence interval (CI), 0.99–1.15]. Stratified analyses showed that prediagnostic weight gain (HR5kg, 1.04; 95% CI, 0.99–1.09) and potentially increased height (HR5cm, 1.04; 95% CI, 0.98–1.11) were associated with poor overall survival only in patients with Warburg-high colorectal cancer. Increasing prediagnostic BMI was associated with poor survival only in patients with Warburg-moderate colorectal cancer (colorectal cancer–specific: HR5kg/m2, 1.12; 95% CI, 0.96–1.32; overall: HR5kg/m2, 1.20; 95% CI, 1.05–1.36). No consistent patterns were observed across energy restriction proxies.

Conclusions:
Maintaining a healthy prediagnostic BMI may be beneficial for colorectal cancer survival. Moreover, associations between prediagnostic BMI, weight change, early-life energy restriction, height, and colorectal cancer survival differed according to Warburg-subtypes.

Impact:
Understanding the biologic pathways involved in associations between energy balance–related factors and colorectal cancer survival could help refine prevention strategies in the future.
Targeting AKR1B10 by Drug Repurposing with Epalrestat Overcomes Chemoresistance in Non–Small Cell Lung Cancer Patient-Derived Tumor Organoids
Authors: Suvilesh Kanve N. , Manjunath Yariswamy , Nussbaum Yulia I. , Gadelkarim Mohamed , Raju Murugesan , Srivastava Akhil , Li Guangfu , Warren Wesley C. , Shyu Chi-Ren , Gao Feng , Ciorba Matthew A. , Mitchem Jonathan B. , Rachagani Satyanarayana , Kaifi Jussuf T. 
Published: July 2024

Abstract

Purpose:
Systemic treatments given to patients with non–small cell lung cancer (NSCLC) are often ineffective due to drug resistance. In the present study, we investigated patient-derived tumor organoids (PDTO) and matched tumor tissues from surgically treated patients with NSCLC to identify drug repurposing targets to overcome resistance toward standard-of-care platinum-based doublet chemotherapy.

Experimental Design:
PDTOs were established from 10 prospectively enrolled patients with non-metastatic NSCLC from resected tumors. PDTOs were compared with matched tumor tissues by histopathology/immunohistochemistry, whole exome sequencing, and transcriptome sequencing. PDTO growths and drug responses were determined by measuring 3D tumoroid volumes, cell viability, and proliferation/apoptosis. Differential gene expression analysis identified drug-repurposing targets. Validations were performed with internal/external data sets of patients with NSCLC. NSCLC cell lines were used for aldo-keto reductase 1B10 (AKR1B10) knockdown studies and xenograft models to determine the intratumoral bioavailability of epalrestat.

Results:
PDTOs retained histomorphology and pathological biomarker expression, mutational/transcriptomic signatures, and cellular heterogeneity of the matched tumor tissues. Five (50%) PDTOs were chemoresistant toward carboplatin/paclitaxel. Chemoresistant PDTOs and matched tumor tissues demonstrated overexpression of AKR1B10. Epalrestat, an orally available AKR1B10 inhibitor in clinical use for diabetic polyneuropathy, was repurposed to overcome chemoresistance of PDTOs. In vivo efficacy of epalrestat to overcome drug resistance corresponded to intratumoral epalrestat levels.

Conclusions:
PDTOs are efficient preclinical models recapitulating the tumor characteristics and are suitable for drug testing. AKR1B10 can be targeted by repurposing epalrestat to overcome chemoresistance in NSCLC. Epalrestat has the potential to advance to clinical trials in patients with drug-resistant NSCLC due to favorable toxicity, pharmacological profile, and bioavailability.
Precision Oncology and Systemic Targeted Therapy in Pseudomyxoma Peritonei
Authors: Martínez-Quintanilla Jordi , Cabot Débora , Sabia Doménico , Arqués Oriol ,   for the PMPnet Group, Vergés Jordi , Chicote Irene , Bijelic Lana ,   for the PMPnet Group, Cabellos Laia , Alcántara Anna M. , Ramos Isabel , Barrios Pedro , Crusellas Oriol , Palacio Lina M. ,   for the PMPnet Group, Cámara Juan A. , Barriuso Jorge ,   for the PMPnet Group, Jiménez Juan J. , Muñoz-Torres Pau , Nonell Lara , Flores Raquel , Médico Enzo , Guaglio Marcello ,   for the PMPnet Group, Ros Javier , Élez Elena , Tabernero Josep , Aziz Omer , Deraco Marcello , Palmer Héctor G. ,   for the PMPnet Group,   PMPnet Group, Giovanna Chiorino , Francesco Mazzarotto , Manuela Gariboldi , Luca Varinelli , Tommaso Cavalleri , Bipasha Chakrabarty , Raghavendar Nagaraju , Patrick Caswell , Milly McAllister 
Published: July 2024

Abstract

Purpose:
Pseudomyxoma peritonei (PMP) is a rare and poorly understood malignant condition characterized by the accumulation of intra-abdominal mucin produced from peritoneal metastases. Currently, cytoreductive surgery remains the mainstay of treatment but disease recurrence and death after relapse frequently occur in patients with PMP. New therapeutic strategies are therefore urgently needed for these patients.

Experimental Design:
A total of 120 PMP samples from 50 patients were processed to generate a collection of 50 patient-derived organoid (PDO) and xenograft (PDX) models. Whole exome sequencing, immunohistochemistry analyses, and in vitro and in vivo drug efficacy studies were performed.

Results:
In this study, we have generated a collection of PMP preclinical models and identified druggable targets, including BRAFV600E, KRASG12C, and KRASG12D, that could also be detected in intra-abdominal mucin biopsies of patients with PMP using droplet digital PCR. Preclinical models preserved the histopathological markers from the original patient sample. The BRAFV600E inhibitor encorafenib reduced cell viability of BRAFV600E PMP-PDO models. Proof-of-concept in vivo experiments showed that a systemic treatment with encorafenib significantly reduced tumor growth and prolonged survival in subcutaneous and orthotopic BRAFV600E-PMP-PDX mouse models.

Conclusions:
Our study demonstrates for the first time that systemic targeted therapies can effectively control PMP tumors. BRAF signaling pathway inhibition represents a new therapeutic opportunity for patients with BRAFV600E PMP who have a poor prognosis. Importantly, our present data and collection of preclinical models pave the way for evaluating the efficacy of other systemic targeted therapies toward extending the promise of precision oncology to patients with PMP.
The Tumor Microbiome as a Predictor of Outcomes in Patients with Metastatic Melanoma Treated with Immune Checkpoint Inhibitors
Authors: Dravillas Caroline E. , Coleman Samuel S. , Hoyd Rebecca , Caryotakis Griffin , Denko Louis , Chan Carlos H.F. , Churchman Michelle L. , Denko Nicholas , Dodd Rebecca D. , Eljilany Islam , Hardikar Sheetal , Husain Marium , Ikeguchi Alexandra P. , Jin Ning , Ma Qin , McCarter Martin D. , Osman Afaf E.G. , Robinson Lary A. , Singer Eric A. , Tinoco Gabriel , Ulrich Cornelia M. , Zakharia Yousef , Spakowicz Daniel , Tarhini Ahmad A. , Tan Aik Choon ,   for the exORIEN Consortium
Published: July 2024

Abstract

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and its potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICI). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA sequencing (RNA-seq) was conducted on the formalin-fixed, paraffin-embedded and fresh frozen tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival ≥24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The age of the 71 patients with metastatic melanoma ranged from 24 to 83 years, 59% were male, and 55% survived &gt;24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy-responsive versus nonresponsive tumors. Responders showed significant enrichment of bacteriophages in the phylum Uroviricota, and nonresponders showed enrichment of several bacteria, including Campylobacter jejuni. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs.

Significance:
We analyzed the tumor microbiome and interactions with genes and pathways in metastatic melanoma treated with immunotherapy and identified several microbes associated with immunotherapy response and immune-related gene expression signatures. Machine learning models that combined microbe abundances and gene expression outperformed models using either dataset alone in predicting immunotherapy responses.
An innovative approach for detecting buildings and construction anomalies in Zenata City
Authors: Ait Moulay Maryem , Salbi Adil , Bouganssa Issam , Masmoudi Mohamed-Salim , Lasfar Abdelali 
Published: July 2024

<p>Rapid urban development in Morocco has led to increased construction activities and significant environmental concerns. Recently Zenata city has undergone significant urban development, marking a crucial step in its trajectory toward a modern smart city. As a part of this growth, our research incorporates an innovative method within the You Only Look Once version 8 (YOLOv8) model, representing a significant advance over conventional methods. The YOLO algorithm has been updated with new features and improvements that infuse our work with a dash of innovation. YOLOv8 integration improves construction and irregular construction detection accuracy beyond what is possible with traditional applications. We trained our algorithm using orthophoto captured by DJI MATRICE 300 RTK drone split into georeferenced tiles and annotated using LabelImg software. Through this process, we were able to create a solid 742 image dataset for training, testing, and validation purposes related to construction. Utilizing drone imagery and the YOLOv8 object detection algorithm, buildings and construction irregularities are detected with high accuracy after 300 training epochs on Kaggle's GPU P100. Insights for early detection and effective building site management are provided by this all-encompassing strategy, which supports Zenata City's sustainable urban growth.</p><div> </div>