bluuebunny/crossref_metadata_2025_split huggingface dataset:
AHRR and SFRP2 in primary versus recurrent high-grade serous ovarian carcinoma and their prognostic implication
Authors: Monjé Nanna , Dragomir Mihnea P. , Sinn Bruno V. , Hoffmann Inga , Makhmut Anuar , Simon Tincy , Kunze Catarina A. , Ihlow Jana , Schmitt Wolfgang D. , Pohl Jonathan , Piwonski Iris , Marchenko Sofya , Keunecke Carlotta , Calina Teodor G. , Tiso Francesca , Kulbe Hagen , Kreuzinger Caroline , Cacsire Castillo-Tong Dan , Sehouli Jalid , Braicu Elena I. , Denkert Carsten , Darb-Esfahani Silvia , Kübler Kirsten , Capper David , Coscia Fabian , Morkel Markus , Horst David , Sers Christine , Taube Eliane T. 
Published: February 2024

Abstract
Background
The aim of this study was to analyse transcriptomic differences between primary and recurrent high-grade serous ovarian carcinoma (HGSOC) to identify prognostic biomarkers.

Methods
We analysed 19 paired primary and recurrent HGSOC samples using targeted RNA sequencing. We selected the best candidates using in silico survival and pathway analysis and validated the biomarkers using immunohistochemistry on a cohort of 44 paired samples, an additional cohort of 504 primary HGSOCs and explored their function.

Results
We identified 233 differential expressed genes. Twenty-three showed a significant prognostic value for PFS and OS in silico. Seven markers (AHRR, COL5A2, FABP4, HMGCS2, ITGA5, SFRP2 and WNT9B) were chosen for validation at the protein level. AHRR expression was higher in primary tumours (p < 0.0001) and correlated with better patient survival (p < 0.05). Stromal SFRP2 expression was higher in recurrent samples (p = 0.009) and protein expression in primary tumours was associated with worse patient survival (p = 0.022). In multivariate analysis, tumour AHRR and SFRP2 remained independent prognostic markers. In vitro studies supported the anti-tumorigenic role of AHRR and the oncogenic function of SFRP2.

Conclusions
Our results underline the relevance of AHRR and SFRP2 proteins in aryl-hydrocarbon receptor and Wnt-signalling, respectively, and might lead to establishing them as biomarkers in HGSOC.
Transactivation of Met signaling by oncogenic Gnaq drives the evolution of melanoma in Hgf-Cdk4 mice
Authors: Mengoni Miriam , Braun Andreas Dominik , Seedarala Sahithi , Bonifatius Susanne , Kostenis Evi , Schanze Denny , Zenker Martin , Tüting Thomas , Gaffal Evelyn 
Published: February 2024

AbstractRecent pan-cancer genomic analyses have identified numerous oncogenic driver mutations that occur in a cell-type and tissue-specific distribution. For example, oncogenic mutations in Braf and Nras genes arise predominantly in melanocytic neoplasms of the epidermis, while oncogenic mutations in Gnaq/11 genes arise mostly in melanocytic lesions of the dermis or the uvea. The mechanisms promoting cell-type and tissue-specific oncogenic events currently remain poorly understood. Here, we report that Gnaq/11 hotspot mutations occur as early oncogenic drivers during the evolution of primary melanomas in Hgf-Cdk4 mice. Additional single base substitutions in the Trp53 gene and structural chromosomal aberrations favoring amplifications of the chromosomal region containing the Met receptor gene accumulate during serial tumor transplantation and in cell lines established in vitro. Mechanistically, we found that the GnaqQ209L mutation transactivates the Met receptor. Overexpression of oncogenic GnaqQ209L in the immortalized melanocyte cell line promoted in vivo growth that was enhanced by transgenic Hgf expression in the tumor microenvironment. This cross-signaling mechanism explains the selection of oncogenic Gnaq/11 in primary Hgf-Cdk4 melanomas and provides an example of how oncogenic driver mutations, intracellular signaling cascades, and microenvironmental cues cooperate to drive cancer development in a tissue-specific fashion.
Antibody and antibody fragments site-specific conjugation using new Q-tag substrate of bacterial transglutaminase
Authors: El Alaoui Meddy , Sivado Eva , Jallas Anne-Catherine , Mebarki Lamia , Dyson Michael R. , Perrez Franck , Valsesia-Wittmann Sandrine , El Alaoui Said 
Published: February 2024

AbstractDuring the last few years Antibody-Drug Conjugates (ADCs) have become one of the most active and very promising therapeutic weapons. Lessons learned from the traditional chemical conjugations (via lysine or cysteine residues of the antibodies) and the clinical studies of the developed ADCs have recently paved the way to the improvement of the conjugation technologies. Use of site-specific conjugation is considered as the promising path for improving the design and development of homogeneous ADCs with controlled Drug-Antibody ratio (DAR). Moreover, some of these conjugations can be applied to antibody fragments such as Fab, scfv and VHH for which random and chemical conjugation showed significant limitations. In this study, we identified a novel small peptide substrate (Q-tag) with high affinity and specificity of bacterial transglutaminase which can be genetically fused to different formats of antibodies of interest for the development of enzymatic site-specific conjugation we named “CovIsolink” platform. We describe the synthesis of chemically defined drugs conjugation in which the site and stoichiometry of conjugation are controlled using a genetically encoded Q-tag peptide with specific amino acids which serves as a substrate of bacterial transglutaminase. This approach has enabled the generation of homogeneous conjugates with DAR 1,7 for full IgG and 0,8 drug ratio for Fab, scfv and VHH antibody fragments without the presence of significant amounts of unconjugated antibody and fragments. As a proof of concept, Q-tagged anti Her-2 (human IgG1 (Trastuzumab) and the corresponding fragments (Fab, scfv and VHH) were engineered and conjugated with different aminated-payloads. The corresponding Cov-ADCs were evaluated in series of in vitro and in vivo assays, demonstrating similar tumor cell killing potency as Trastuzumab emtansine (Kadcyla®) even with lower drug-to-antibody ratio (DAR).
Restrained Mitf-associated autophagy by Mulberroside A ameliorates osteoclastogenesis and counteracts OVX-Induced osteoporosis in mice
Authors: Xue Hong , Feng Zhenhua , Yuan Putao , Qiao Li , Lou Qiliang , Zhao Xiangde , Ma Qingliang , Wang Shiyu , Shen Yang , Ye Huali , Cheng Jiao , Wang Jiying , Wan Shuanglin , Zhang Boya , Shi Peihua , Sun Xuewu 
Published: February 2024

AbstractBone and mineral metabolism homeostasis accounts for the maintenance of normal skeletal remodeling. However, with aging and changes in hormone levels, over-activated osteoclasts disrupt homeostasis, induce osteoporosis, and even cause osteoporotic fractures, leading to an enormous economic burden. Despite the rapid development of pharmacological therapy for osteoporosis, safer and more effective treatments remain to be explored. Here, we demonstrate that Mulberroside A (Mul-A), a natural component extracted from mulberry bark and branches, effectively suppresses osteoclastogenesis in vitro and counteracts bone loss caused by ovariectomy (OVX). The mechanism underlying this effect involves the repression of autophagic flux during osteoclastogenesis by Mul-A, which can be attributed to the restrained expression of microphthalmia-related transcription factor (Mitf) and its nuclear translocation. Importantly, Mitf overexpression partially reverses the inhibitory effects of Mul-A on autophagy and osteoclastogenesis. Moreover, applying two autophagy agonizts, rapamycin and Torin 1, attenuates the osteoclastogenic regulatory role of Mul-A. Collectively, our study demonstrates that Mul-A damages osteoclast differentiation and ameliorates osteoporosis caused by estrogen deficiency by modulation of Mitf-associated autophagy, indicating its therapeutic potential against osteoporosis.
Perturbative solution of fermionic sign problem in quantum Monte Carlo computations
Authors: Iskakov Sergei , Katsnelson Mikhail I. , Lichtenstein Alexander I. 
Published: February 2024

AbstractWe have developed a strong-coupling perturbation scheme for a general doped Hubbard model around a particle-hole-symmetric reference system, which is free from the fermionic sign problem. Our approach is based on the lattice determinantal Quantum Monte Carlo (QMC) method in both continuous and discrete time versions for large periodic clusters in a fermionic bath. By considering the first-order perturbation in the shift of the chemical potential and the second-neighbor hopping, we are able to obtain an accurate electronic spectral function for a range of parameters that correspond to optimally doped cuprate systems at temperatures of up to T = 0.1t, which are challenging to access using straightforward lattice QMC calculations. We also discuss the formation of the pseudogap and the nodal-antinodal dichotomy for a doped Hubbard system with the interaction parameter U equal to the bandwidth and the optimal value of the next-nearest-neighbor hopping parameter $${t}^{{\prime} }$$

t

′

for high-temperature superconducting cuprates.
Distinctive CD56dim NK subset profiles and increased NKG2D expression in blood NK cells of Parkinson’s disease patients
Authors: Weber Stephen , Menees Kelly B. , Park Jieun , Agin-Liebes Julian , Lin Chih-Chun , Alcalay Roy N. , Lee Jae-Kyung 
Published: February 2024

AbstractMounting data suggest an important role for the immune system in Parkinson’s disease (PD). Previous evidence of increased natural killer (NK) cell populations in PD suggests a potential role of NK cells in the pathogenesis of the disease. Previous studies have analyzed NK cell populations using aggregation by variable expression of CD56 and CD16. It remains unknown what differences may exist between NK cell subpopulations when stratified using more nuanced classification. Here, we profile NK cell subpopulations and elucidate the expressions of activating, NKG2D, inhibitory, NKG2A, and homing, CX3CR1, receptors on NK cell subpopulations in PD and healthy controls (HC). We analyzed cryopreserved PMBC samples using a 10-color flow cytometry panel to evaluate NK cell subpopulations in 31 individuals with sporadic PD and 27 HC participants. Here we identified significant differences in the CD56dim NK subset that changes with disease severity in PD. Furthermore, the expressions of NKG2D in all three NK cell subsets were significantly elevated in PD patients compared to HC. Notably, NKG2A expression in the CD56bright NK subset increased in PD patients with longer disease duration but there were no changes in CX3CR1. In summary, our data suggests that changes in NK cells may be influenced by the clinical severity and duration of PD.
Accurate and sensitive mutational signature analysis with MuSiCal
Authors: Jin Hu , Gulhan Doga C. , Geiger Benedikt , Ben-Isvy Daniel , Geng David , Ljungström Viktor , Park Peter J. 
Published: February 2024

AbstractMutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. Here we present Mutational Signature Calculator (MuSiCal), a rigorous analytical framework with algorithms that solve major problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing more than 2,700 cancer genomes, we provide an improved catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous ‘flat’ signatures and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.
Dual view deep learning for enhanced breast cancer screening using mammography
Authors: Kebede Samuel Rahimeto , Waldamichael Fraol Gelana , Debelee Taye Girma , Aleme Muluberhan , Bedane Wubalem , Mezgebu Bethelhem , Merga Zelalem Chimdesa 
Published: February 2024

AbstractBreast cancer has the highest incidence rate among women in Ethiopia compared to other types of cancer. Unfortunately, many cases are detected at a stage where a cure is delayed or not possible. To address this issue, mammography-based screening is widely accepted as an effective technique for early detection. However, the interpretation of mammography images requires experienced radiologists in breast imaging, a resource that is limited in Ethiopia. In this research, we have developed a model to assist radiologists in mass screening for breast abnormalities and prioritizing patients. Our approach combines an ensemble of EfficientNet-based classifiers with YOLOv5, a suspicious mass detection method, to identify abnormalities. The inclusion of YOLOv5 detection is crucial in providing explanations for classifier predictions and improving sensitivity, particularly when the classifier fails to detect abnormalities. To further enhance the screening process, we have also incorporated an abnormality detection model. The classifier model achieves an F1-score of 0.87 and a sensitivity of 0.82. With the addition of suspicious mass detection, sensitivity increases to 0.89, albeit at the expense of a slightly lower F1-score of 0.79.
Continuous and discontinuous compressible flows in a converging–diverging channel solved by physics-informed neural networks without exogenous data
Authors: Liang Hong , Song Zilong , Zhao Chong , Bian Xin 
Published: February 2024

AbstractPhysics-informed neural networks (PINNs) are employed to solve the classical compressible flow problem in a converging–diverging nozzle. This problem represents a typical example described by the Euler equations, a thorough understanding of which serves as a guide for solving more general compressible flows. Given a geometry of the channel, analytical solutions for the steady states do indeed exist, and they depend on the ratio between the back pressure of the outlet and the stagnation pressure of the inlet. Moreover, in the diverging region, the solution may branch into subsonic flow, supersonic flow, or a mixture of both with a discontinuous transition where a normal shock occurs. Classical numerical schemes with shock fitting and capturing methods have been developed to solve this type of problem effectively, whereas the original PINNs are unable to predict the flows correctly. We make a first attempt to exploit the power of PINNs to solve this problem directly by adjusting the weights of different components of the loss function to acquire physical solutions and in the meantime, avoid trivial solutions. With a universal setting yet no exogenous data, we are able to solve this problem accurately; that is, for different given pressure ratios, PINNs provide different branches of solutions at both steady and unsteady states, some of which are discontinuous in nature. For an inverse problem such as unknown specific-heat ratio, it works effectively as well.
On the spin dependence of detection times and the nonmeasurability of arrival times
Authors: Goldstein Sheldon , Tumulka Roderich , Zanghì Nino 
Published: February 2024

AbstractAccording to a well-known principle of quantum physics, the statistics of the outcomes of any quantum experiment are governed by a Positive-Operator-Valued Measure (POVM). In particular, for experiments designed to measure a specific physical quantity, like the time of a particle’s first arrival at a surface, this principle establishes that if the probability distribution of that quantity does not arise from a POVM, no such experiment exists. Such is the case with the arrival time distributions proposed by Das and Dürr, due to the nature of their spin dependence.
BAMLET administration via drinking water inhibits intestinal tumor development and promotes long-term health
Authors: Tran Hien Thi , Wan Murphy Lam Yim , Ambite Ines , Cavalera Michele , Grossi Mario , Háček Jaromir , Esmaeili Parisa , Carneiro António N. B. M. , Chaudhuri Arunima , Ahmadi Shahram , Svanborg Catharina 
Published: February 2024

AbstractThough new targeted therapies for colorectal cancer, which progresses from local intestinal tumors to metastatic disease, are being developed, tumor specificity remains an important problem, and side effects a major concern. Here, we show that the protein-fatty acid complex BAMLET (bovine alpha-lactalbumin made lethal to tumor cells) can act as a peroral treatment for colorectal cancer. ApcMin/+ mice, which carry mutations relevant to hereditary and sporadic human colorectal cancer, that received BAMLET in the drinking water showed long-term protection against tumor development and decreased expression of tumor growth-, migration-, metastasis- and angiogenesis-related genes. BAMLET treatment via drinking water inhibited the Wnt/β-catenin and PD-1 signaling pathways and prolonged survival without evidence of toxicity. Systemic disease in the lungs, livers, spleens, and kidneys, which accompanied tumor progression, was inhibited by BAMLET treatment. The metabolic response to BAMLET included carbohydrate and lipid metabolism, which were inhibited in tumor prone ApcMin/+ mice and weakly regulated in C57BL/6 mice, suggesting potential health benefits of peroral BAMLET administration in addition to the potent antitumor effects. Together, these findings suggest that BAMLET administration in the drinking water maintains antitumor pressure by removing emergent cancer cells and reprogramming gene expression in intestinal and extra-intestinal tissues.
Generative adversarial reduced order modelling
Authors: Coscia Dario , Demo Nicola , Rozza Gianluigi 
Published: February 2024

AbstractIn this work, we present GAROM, a new approach for reduced order modeling (ROM) based on generative adversarial networks (GANs). GANs attempt to learn to generate data with the same statistics of the underlying distribution of a dataset, using two neural networks, namely discriminator and generator. While widely applied in many areas of deep learning, little research is done on their application for ROM, i.e. approximating a high-fidelity model with a simpler one. In this work, we combine the GAN and ROM framework, introducing a data-driven generative adversarial model able to learn solutions to parametric differential equations. In the presented methodology, the discriminator is modeled as an autoencoder, extracting relevant features of the input, and a conditioning mechanism is applied to the generator and discriminator networks specifying the differential equation parameters. We show how to apply our methodology for inference, provide experimental evidence of the model generalization, and perform a convergence study of the method.
Quantitative assessments of honeybee colony’s response to an artificial vibrational pulse resulting in non-invasive measurements of colony’s overall mobility and restfulness
Authors: Bencsik Martin , McVeigh Adam , Claeys Bouuaert David , Capela Nuno , Penny Frederick , Newton Michael Ian , Sousa José Paulo , de Graaf Dirk C. 
Published: February 2024

AbstractIn this work we aim to provide a quantitative method allowing the probing of the physiological status of honeybee colonies by providing them with a gentle, short, external artificial vibrational shockwave, and recording their response. The knock is provided by an external electromagnetic shaker attached to the outer wall of a hive, driven by a computer with a 0.1 s long, monochromatic vibration at 340Hz set to an amplitude that occasionally yields a mild response from the bees, recorded by an accelerometer placed in the middle of the central frame of the colony. To avoid habituation, the stimulus is supplied at randomised times, approximately every hour. The method is pioneered with a pilot study on a single colony hosted indoors, then extended onto eight outdoors colonies. The results show that we can quantitatively sense the colony’s overall mobility, independently from another physiological aspect, which is phenomenologically explored. Using this, a colony that is queenless is easily discriminated from the others.
Biaxial strain tuned upconversion photoluminescence of monolayer WS2
Authors: Roy Shrawan , Yang Xiaodong , Gao Jie 
Published: February 2024

AbstractMonolayer tungsten disulfide (1L-WS2) is a direct bandgap atomic-layered semiconductor material with strain tunable optical and optoelectronic properties among the monolayer transition metal dichalcogenides (1L-TMDs). Here, we demonstrate biaxial strain tuned upconversion photoluminescence (UPL) from exfoliated 1L-WS2 flakes transferred on a flexible polycarbonate cruciform substrate. When the biaxial strain applied to 1L-WS2 increases from 0 to 0.51%, it is observed that the UPL peak position is redshifted by up to 60 nm/% strain, while the UPL intensity exhibits exponential growth with the upconversion energy difference varying from − 303 to − 120 meV. The measured power dependence of UPL from 1L-WS2 under biaxial strain reveals the one photon involved multiphonon-mediated upconversion mechanism. The demonstrated results provide new opportunities in advancing TMD-based optical upconversion devices for future flexible photonics and optoelectronics.
Agreement between invasive and noninvasive measurement of tear film breakup time
Authors: Szczesna-Iskander Dorota H. , Llorens-Quintana Clara 
Published: February 2024

AbstractThe agreement between fluorescein breakup time (FBUT) estimates and noninvasive breakup time (NIBUT) estimates automatically acquired using two videokeratoscopes was assessed. Small-cone (E300, Medmont) and large-bowl (K5M, OCULUS) Placido-ring–based videokeratoscopes were utilized for automated NIBUT estimation and fluorescein strip method was used for FBUT estimation. 33 subjects completed the study. Clear instructions were given regarding the blink before measurements. Bland–Altman analysis was used to test the agreement between tear film breakup time estimates and repeated measure analysis of variance was used to test the differences between measurement types. In comparison to FBUT, E300 NIBUT estimate was shorter (− 0.6 ± 2.6 s), whereas K5M NIBUT estimate was longer (3.3 ± 2.4 s). Limits of agreement for FBUT vs. E300 was 29.8 s, for FBUT vs. K5M 26.4 s, and 31.4 s for E300 vs. K5M. There were significant differences between tear film breakup times (F = 3.59,df = 2,P = 0.032). E300 and K5M NIBUT measurements have poor agreement with FBUT, even when blinking is precisely clarified. Agreement was better for shorted break up times than that for longer ones but in general NIBUT measurements are not interchangeable.
Inequalities in regional excess mortality and life expectancy during the COVID-19 pandemic in Europe
Authors: Hajdu Tamás , Krekó Judit , Tóth Csaba G. 
Published: February 2024

AbstractUsing data for 201 regions (NUTS 2) in Europe, we examine the mortality burden of the COVID-19 pandemic and how the mortality inequalities between regions changed between 2020 and 2022. We show that over the three years of the pandemic, not only did the level of excess mortality rate change considerably, but also its geographical distribution. Focusing on life expectancy as a summary measure of mortality conditions, we find that the variance of regional life expectancy increased sharply in 2021 but returned to the pre-pandemic level in 2022. The 2021 increase was due to a much higher-than-average excess mortality in regions with lower pre-pandemic life expectancy. While the life expectancy inequality has returned to its pre-pandemic level in 2022, the observed life expectancy in almost all regions is far below that expected without the pandemic.