bluuebunny/crossref_metadata_2025_split huggingface dataset:
RAGE inhibitor TTP488 (Azeliragon) suppresses metastasis in triple-negative breast cancer
Authors: Magna Melinda , Hwang Gyong Ha , McIntosh Alec , Drews-Elger Katherine , Takabatake Masaru , Ikeda Adam , Mera Barbara J. , Kwak Taekyoung , Miller Philip , Lippman Marc E. , Hudson Barry I. 
Published: July 2023

AbstractTriple-negative breast cancer (TNBC) is a highly aggressive and metastatic cancer subtype, which is generally untreatable once it metastasizes. We hypothesized that interfering with the Receptor for Advanced Glycation End-products (RAGE) signaling with the small molecule RAGE inhibitors (TTP488/Azeliragon and FPS-ZM1) would impair TNBC metastasis and impair fundamental mechanisms underlying tumor progression and metastasis. Both TTP488 and FPS-ZM1 impaired spontaneous and experimental metastasis of TNBC models, with TTP488 reducing metastasis to a greater degree than FPS-ZM1. Transcriptomic analysis of primary xenograft tumor and metastatic tissue revealed high concordance in gene and protein changes with both drugs, with TTP488 showing greater potency against metastatic driver pathways. Phenotypic validation of transcriptomic analysis by functional cell assays revealed that RAGE inhibition impaired TNBC cell adhesion to multiple extracellular matrix proteins (including collagens, laminins, and fibronectin), migration, and invasion. Neither RAGE inhibitor impaired cellular viability, proliferation, or cell cycle in vitro. Proteomic analysis of serum from tumor-bearing mice revealed RAGE inhibition affected metastatic driver mechanisms, including multiple cytokines and growth factors. Further mechanistic studies by phospho-proteomic analysis of tumors revealed RAGE inhibition led to decreased signaling through critical BC metastatic driver mechanisms, including Pyk2, STAT3, and Akt. These results show that TTP488 impairs metastasis of TNBC and further clarifies the signaling and cellular mechanisms through which RAGE mediates metastasis. Importantly, as TTP488 displays a favorable safety profile in human studies, our study provides the rationale for evaluating TTP488 in clinical trials to treat or prevent metastatic TNBC.
Cortex-wide topography of 1/f-exponent in Parkinson’s disease
Authors: Helson Pascal , Lundqvist Daniel , Svenningsson Per , Vinding Mikkel C. , Kumar Arvind 
Published: July 2023

AbstractParkinson’s disease (PD) is a progressive and debilitating brain disorder. Besides the characteristic movement-related symptoms, the disease also causes decline in sensory and cognitive processing. The extent of symptoms and brain-wide projections of neuromodulators such as dopamine suggest that many brain regions are simultaneously affected in PD. To characterise brain-wide disease-related changes in neuronal function, we analysed resting state magnetoencephalogram (MEG) from two groups: PD patients and healthy controls. Besides standard spectral analysis, we quantified the aperiodic components (κ, λ) of the neural activity by fitting a power law κ/fλ – f is the frequency, κ and λ are the fitting parameters—to the MEG power spectrum and studied its relationship with age and Unified Parkinson’s Disease Rating Scale (UPDRS). Consistent with previous results, the most significant spectral changes were observed in the high theta/low-alpha band (7–10 Hz) in all brain regions. Furthermore, analysis of the aperiodic part of the spectrum showed that in all but frontal regions λ was significantly larger in PD patients than in control subjects. Our results indicate that PD is associated with significant changes in aperiodic activity across the whole neocortex. Surprisingly, even early sensory areas showed a significantly larger λ in patients than in healthy controls. Moreover, λ was not affected by the Levodopa medication. Finally, λ was positively correlated with patient age but not with UPDRS-III. Because λ is closely associated with excitation-inhibition balance, our results propose new hypotheses about neural correlates of PD in cortical networks.
Profound structural conservation of chemically cross-linked HIV-1 envelope glycoprotein experimental vaccine antigens
Authors: Martin Gregory M. , Russell Rebecca A. , Mundsperger Philip , Harris Scarlett , Jovanoska Lu , Trajano Luiza Farache , Schiffner Torben , Fabian Katalin , Tolazzi Monica , Scarlatti Gabriella , McFarlane Leon , Cheeseman Hannah , Aldon Yoann , Schermer Edith E. , Breemen Marielle , Sliepen Kwinten , Katinger Dietmar , Kunert Renate , Sanders Rogier W. , Shattock Robin , Ward Andrew B. , Sattentau Quentin J. 
Published: July 2023

AbstractChemical cross-linking is used to stabilize protein structures with additional benefits of pathogen and toxin inactivation for vaccine use, but its use has been restricted by the potential for local or global structural distortion. This is of particular importance when the protein in question requires a high degree of structural conservation for inducing a biological outcome such as the elicitation of antibodies to conformationally sensitive epitopes. The HIV-1 envelope glycoprotein (Env) trimer is metastable and shifts between different conformational states, complicating its use as a vaccine antigen. Here we have used the hetero-bifunctional zero-length reagent 1-Ethyl-3-(3-Dimethylaminopropyl)-Carbodiimide (EDC) to cross-link two soluble Env trimers, selected well-folded trimer species using antibody affinity, and transferred this process to good manufacturing practice (GMP) for experimental medicine use. Cross-linking enhanced trimer stability to biophysical and enzyme attack. Cryo-EM analysis revealed that cross-linking retained the overall structure with root-mean-square deviations (RMSDs) between unmodified and cross-linked Env trimers of 0.4–0.5 Å. Despite this negligible distortion of global trimer structure, we identified individual inter-subunit, intra-subunit, and intra-protomer cross-links. Antigenicity and immunogenicity of the trimers were selectively modified by cross-linking, with cross-linked ConS retaining bnAb binding more consistently than ConM. Thus, the EDC cross-linking process improves trimer stability whilst maintaining protein folding, and is readily transferred to GMP, consistent with the more general use of this approach in protein-based vaccine design.
A placental model of SARS-CoV-2 infection reveals ACE2-dependent susceptibility and differentiation impairment in syncytiotrophoblasts
Authors: Chen J. , Neil J. A. , Tan J. P. , Rudraraju R. , Mohenska M. , Sun Y. B. Y. , Walters E. , Bediaga N. G. , Sun G. , Zhou Y. , Li Y. , Drew D. , Pymm P. , Tham W. H. , Wang Y. , Rossello F. J. , Nie G. , Liu X. , Subbarao K. , Polo J. M. 
Published: July 2023

AbstractSARS-CoV-2 infection causes COVID-19. Several clinical reports have linked COVID-19 during pregnancy to negative birth outcomes and placentitis. However, the pathophysiological mechanisms underpinning SARS-CoV-2 infection during placentation and early pregnancy are not clear. Here, to shed light on this, we used induced trophoblast stem cells to generate an in vitro early placenta infection model. We identified that syncytiotrophoblasts could be infected through angiotensin-converting enzyme 2 (ACE2). Using a co-culture model of vertical transmission, we confirmed the ability of the virus to infect syncytiotrophoblasts through a previous endometrial cell infection. We further demonstrated transcriptional changes in infected syncytiotrophoblasts that led to impairment of cellular processes, reduced secretion of HCG hormone and morphological changes vital for syncytiotrophoblast function. Furthermore, different antibody strategies and antiviral drugs restore these impairments. In summary, we have established a scalable and tractable platform to study early placental cell types and highlighted its use in studying strategies to protect the placenta.
The benefits and struggles of FAIR data: the case of reusing plant phenotyping data
Authors: Papoutsoglou Evangelia A. , Athanasiadis Ioannis N. , Visser Richard G. F. , Finkers Richard 
Published: July 2023

AbstractPlant phenotyping experiments are conducted under a variety of experimental parameters and settings for diverse purposes. The data they produce is heterogeneous, complicated, often poorly documented and, as a result, difficult to reuse. Meeting societal needs (nutrition, crop adaptation and stability) requires more efficient methods toward data integration and reuse. In this work, we examine what “making data FAIR” entails, and investigate the benefits and the struggles not only of reusing FAIR data, but also making data FAIR using genotype by environment and QTL by environment interactions for developmental traits in potato as a case study. We assume the role of a scientist discovering a phenotypic dataset on a FAIR data point, verifying the existence of related datasets with environmental data, acquiring both and integrating them. We report and discuss the challenges and the potential for reusability and reproducibility of FAIRifying existing datasets, using metadata standards such as MIAPPE, that were encountered in this process.
Chromosome-level genome assembly of the sea cucumber Apostichopus japonicus
Authors: Sun Lina , Jiang Chunxi , Su Fang , Cui Wei , Yang Hongsheng 
Published: July 2023

AbstractSea cucumber is a morphologically diverse and ecologically important clade of echinoderms. The sea cucumber Apostichopus japonicus is the most economically valuable species of sea cucumber. The initial assembly of the A. japonicus genome was released in 2017. However, this genome assembly is fragmented and lacks relative position information of genes on chromosomes. In this study, we produced a high-quality chromosome-level genome of A. japonicus using Pacbio HiFi long-reads and Hi-C sequencing data. The assembled A. japonicus genome spanned 671.60 Mb with a contig N50 size of 17.20 Mb and scaffold N50 size of 29.65 Mb. A total of 99.9% of the assembly was anchored to 23 chromosomes. In total, 19,828 genes were annotated, and 97.2% of BUSCO genes were fully represented. This high-quality genome of A. japonicus will not only aid in the development of sustainable aquaculture practices, but also lay a foundation for a deeper understanding of their genetic makeup, evolutionary history, and ecological adaptation.
Individual-level precision diagnosis for coronavirus disease 2019 related severe outcome: an early study in New York
Authors: Huang Chaorui C. , Xu Hong 
Published: July 2023

AbstractBecause of inadequate information provided by the on-going population level risk analyses for Coronavirus disease 2019 (COVID-19), this study aimed to evaluate the risk factors and develop an individual-level precision diagnostic method for COVID-19 related severe outcome in New York State (NYS) to facilitate early intervention and predict resource needs for patients with COVID-19. We analyzed COVID-19 related hospital encounter and hospitalization in NYS using Statewide Planning and Research Cooperative System hospital discharge dataset. Logistic regression was performed to evaluate the risk factors for COVID-19 related mortality. We proposed an individual-level precision diagnostic method by taking into consideration of the different weights and interactions of multiple risk factors. Age was the greatest risk factor for COVID-19 related fatal outcome. By adding other demographic variables, dyspnea or hypoxemia and multiple chronic co-morbid conditions, the model predictive accuracy was improved to 0.85 (95% CI 0.84–0.85). We selected cut-off points for predictors and provided a general recommendation to categorize the levels of risk for COVID-19 related fatal outcome, which can facilitate the individual-level diagnosis and treatment, as well as medical resource prediction. We further provided a use case of our method to evaluate the feasibility of public health policy for monoclonal antibody therapy.
Extremely large Lamb shift in a deep-strongly coupled circuit QED system with a multimode resonator
Authors: Ao Ziqiao , Ashhab Sahel , Yoshihara Fumiki , Fuse Tomoko , Kakuyanagi Kosuke , Saito Shiro , Aoki Takao , Semba Kouichi 
Published: July 2023

AbstractWe report experimental and theoretical results on the extremely large Lamb shift in a multimode circuit quantum electrodynamics (QED) system in the deep-strong coupling (DSC) regime, where the qubit-resonator coupling strength is comparable to or larger than the qubit and resonator frequencies. The system comprises a superconducting flux qubit (FQ) and a quarter-wavelength coplanar waveguide resonator ($$\lambda /4$$

λ
/
4

CPWR) that are coupled inductively through a shared edge that contains a Josephson junction to achieve the DSC regime. Spectroscopy is performed around the frequency of the fundamental mode of the CPWR, and the spectrum is fitted by the single-mode quantum Rabi Hamiltonian to obtain the system parameters. Since the qubit is also coupled to a large number of higher modes in the resonator, the single-mode fitting does not provide the bare qubit energy but a value that incorporates the renormalization from all the other modes. We derive theoretical formulas for the Lamb shift in the multimode resonator system. As shown in previous studies, there is a cut-off frequency $$\omega _{\textrm{cutoff}}$$

ω
cutoff

for the coupling between the FQ and the modes in the CPWR, where the coupling grows as $$\sqrt{\omega _n}$$

ω
n

for $$\omega _n/\omega _{\textrm{cutoff}}\ll 1$$

ω
n

/

ω
cutoff

≪
1

and decreases as $$1/\sqrt{\omega _n}$$

1
/

ω
n

for $$\omega _n/\omega _{\textrm{cutoff}}\gg 1$$

ω
n

/

ω
cutoff

≫
1

. Here $$\omega _n$$

ω
n

is the frequency of the nth mode. The cut-off effect occurs because the qubit acts as an obstacle for the current in the resonator, which suppresses the current of the modes above $$\omega _{\textrm{cutoff}}$$

ω
cutoff

at the location of the qubit and results in a reduced coupling strength. Using our observed spectrum and theoretical formulas, we estimate that the Lamb shift from the fundamental mode is 82.3% and the total Lamb shift from all the modes is 96.5%. This result illustrates that the coupling to the large number of modes in a CPWR yields an extremely large Lamb shift but does not suppress the qubit energy to zero, which would happen in the absence of a high-frequency cut-off.
Comparative hydrodynamic and nanoscale imaging study on the interactions of teicoplanin-A2 and bovine submaxillary mucin as a model ocular mucin
Authors: Chun Taewoo , Pattem Jacob , Gillis Richard B. , Dinu Vlad T. , Yakubov Gleb E. , Corfield Anthony P. , Harding Stephen E. 
Published: July 2023

AbstractGlycopeptide antibiotics are regularly used in ophthalmology to treat infections of Gram-positive bacteria. Aggregative interactions of antibiotics with mucins however can lead to long exposure and increases the risk of resistant species. This study focuses on the evaluation of potential interactions of the last line of defence glycopeptide antibiotic teicoplanin with an ocular mucin model using precision matrix free hydrodynamic and microscopic techniques: sedimentation velocity in the analytical ultracentrifuge (SV-AUC), dynamic light scattering (DLS) and atomic force microscopy (AFM). For the mixtures of teicoplanin at higher doses (1.25 mg/mL and 12.5 mg/mL), it was shown to interact and aggregate with bovine submaxillary mucin (BSM) in the distributions of both sedimentation coefficients by SV-AUC and hydrodynamic radii by DLS. The presence of aggregates was confirmed by AFM for higher concentrations. We suggest that teicoplanin eye drop formulations should be delivered at concentrations of < 1.25 mg/mL to avoid potentially harmful aggregations.
Region of interest (ROI) selection using vision transformer for automatic analysis using whole slide images
Authors: Hossain Md Shakhawat , Shahriar Galib Muhammad , Syeed M. M. Mahbubul , Uddin Mohammad Faisal , Hasan Mahady , Shivam Shingla , Advani Suresh 
Published: July 2023

AbstractSelecting regions of interest (ROI) is a common step in medical image analysis across all imaging modalities. An ROI is a subset of an image appropriate for the intended analysis and identified manually by experts. In modern pathology, the analysis involves processing multidimensional and high resolution whole slide image (WSI) tiles automatically with an overwhelming quantity of structural and functional information. Despite recent improvements in computing capacity, analyzing such a plethora of data is challenging but vital to accurate analysis. Automatic ROI detection can significantly reduce the number of pixels to be processed, speed the analysis, improve accuracy and reduce dependency on pathologists. In this paper, we present an ROI detection method for WSI and demonstrated it for human epidermal growth factor receptor 2 (HER2) grading for breast cancer patients. Existing HER2 grading relies on manual ROI selection, which is tedious, time-consuming and suffers from inter-observer and intra-observer variability. This study found that the HER2 grade changes with ROI selection. We proposed an ROI detection method using Vision Transformer and investigated the role of image magnification for ROI detection. This method yielded an accuracy of 99% using 20 × WSI and 97% using 10 × WSI for the ROI detection. In the demonstration, the proposed method increased the diagnostic agreement to 99.3% with the clinical scores and reduced the time to 15 seconds for automated HER2 grading.
Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data
Authors: Zakariaee Seyed Salman , Naderi Negar , Ebrahimi Mahdi , Kazemi-Arpanahi Hadi 
Published: July 2023

AbstractSince the beginning of the COVID-19 pandemic, new and non-invasive digital technologies such as artificial intelligence (AI) had been introduced for mortality prediction of COVID-19 patients. The prognostic performances of the machine learning (ML)-based models for predicting clinical outcomes of COVID-19 patients had been mainly evaluated using demographics, risk factors, clinical manifestations, and laboratory results. There is a lack of information about the prognostic role of imaging manifestations in combination with demographics, clinical manifestations, and laboratory predictors. The purpose of the present study is to develop an efficient ML prognostic model based on a more comprehensive dataset including chest CT severity score (CT-SS). Fifty-five primary features in six main classes were retrospectively reviewed for 6854 suspected cases. The independence test of Chi-square was used to determine the most important features in the mortality prediction of COVID-19 patients. The most relevant predictors were used to train and test ML algorithms. The predictive models were developed using eight ML algorithms including the J48 decision tree (J48), support vector machine (SVM), multi-layer perceptron (MLP), k-nearest neighbourhood (k-NN), Naïve Bayes (NB), logistic regression (LR), random forest (RF), and eXtreme gradient boosting (XGBoost). The performances of the predictive models were evaluated using accuracy, precision, sensitivity, specificity, and area under the ROC curve (AUC) metrics. After applying the exclusion criteria, a total of 815 positive RT-PCR patients were the final sample size, where 54.85% of the patients were male and the mean age of the study population was 57.22 ± 16.76 years. The RF algorithm with an accuracy of 97.2%, the sensitivity of 100%, a precision of 94.8%, specificity of 94.5%, F1-score of 97.3%, and AUC of 99.9% had the best performance. Other ML algorithms with AUC ranging from 81.2 to 93.9% had also good prediction performances in predicting COVID-19 mortality. Results showed that timely and accurate risk stratification of COVID-19 patients could be performed using ML-based predictive models fed by routine data. The proposed algorithm with the more comprehensive dataset including CT-SS could efficiently predict the mortality of COVID-19 patients. This could lead to promptly targeting high-risk patients on admission, the optimal use of hospital resources, and an increased probability of survival of patients.
A longitudinal transcriptomic analysis from unfed to post-engorgement midguts of adult female Ixodes scapularis
Authors: Lu Stephen , Martins Larissa A. , Kotál Jan , Ribeiro José M. C. , Tirloni Lucas 
Published: July 2023

AbstractThe hematophagy behavior has evolved independently several times within the Arthropoda phylum. Interestingly, the process of acquiring a blood meal in ticks is considerably distinct from that observed in other blood-feeding arthropods. Instead of taking seconds to minutes to complete a blood meal, an adult female Ixodes scapularis tick can remain attached to its host for numerous days. During this extended feeding period, the tick undergoes drastic morphological changes. It is well established that the tick midgut plays a pivotal role not only in blood meal digestion but also in pathogen acquisition and transmission. However, our understanding of the underlying molecular mechanisms involved in these events remains limited. To expedite tick research, we conducted a comprehensive longitudinal RNA-sequencing of the tick midgut before, during, and after feeding. By collecting ticks in different feeding stages (unfed, slow feeding, rapid feeding, and early post-detached), we obtained a comprehensive overview of the transcripts present in each stage and the dynamic transcriptional changes that occur between them. This provides valuable insights into tick physiology. Additionally, through unsupervised clustering, we identified transcripts with similar patterns and stage-specific sequences. These findings serve as a foundation for selecting targets in the development of anti-tick control strategies and facilitate a better understanding of how blood feeding and pathogen infection impact tick physiology.
Pre-ceramic polymer-assisted nucleation and growth of copper sulfide nanoplates
Authors: Loughney Patricia A. , Martin Kara L. , Cuillier Paul , Trigg Edward B. , Posey Nicholas D. , Dickerson Matthew B. , Pruyn Timothy L. , Doan-Nguyen Vicky 
Published: July 2023

AbstractPolymer-derived ceramics derived from pre-ceramic polymers (PCPs), have access to several form factors and are highly tunable systems. Tunability can be further expanded with the incorporation of functional nanoparticle fillers throughout the matrix for advanced nanocomposite polymer-derived ceramic development. However, capping ligands used in nanoparticle syntheses mix unfavorably with PCPs, giving aggregated filler material and diminished properties. To control dispersion, secondary nanoparticle processing is performed by adhering PCP-miscible caps to the surface after synthesis. This often sacrifices size control established for small nanoparticles (<10 nm). Herein, we successfully eliminate the need for extra nanoparticle processing through the development of a one-pot, copper sulfide synthesis in which a PCP assists the stable formation of nanoparticles and serves as the final graft molecule. We monitor the success of this methodology and the PCP’s role in the reaction through several characterization methods probing both the nanoparticle core and polymer graft.