bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resistance to complement-mediated lysis of parainfluenza virus 5-infected cells is acquired after transition from acute to persistent infection
Authors: Fox Candace R. , Yousef Nasser N. , Varudkar Namita , Shiffer Elisabeth M. , Aquino Jenna R. , Kedarinath Kritika , Parks Griffith D. 
Published: January 2025

ABSTRACT

Persistent viral infections can be an important medical problem, with persistently infected (PI) cells extending viral shedding, maintaining inflammation, and providing potential sources for new viral variants. Given that PI cells can acquire resistance to some innate immune pathways, we tested the hypothesis that complement (C’)-mediated lysis of parainfluenza virus 5 (PIV5)-infected cells would differ between acute-infected and PI cells. Biochemical and real-time cell viability assays showed effective C’-mediated lysis of A549 lung cells acutely infected with PIV5, through pathways that depended on C3 and C5, but largely independent of C6. A PIV5 PI cell line established by long-term culturing of acutely infected A549 cells showed a high-level persistent expression of PIV5 proteins and infectious virus. Under conditions that led to effective lysis of acute PIV5-infected cells, the PI cells were nearly completely resistant to C’-mediated killing. This lack of C’ killing was not due to failure to activate C’, since C’-treated PIV5 PI cells had extensive C3 and membrane attack complex deposition, as well as production of C3a and C5a. Transcriptomics analysis revealed the C’ cascade as the most significantly upregulated pathway in PIV5 PI cells versus acute infection. Biochemical analyses showed that resistance to C’ killing correlated with increased expression in PI cells of two major C’ inhibitors: complement factor H and Vitronectin. The finding of acquisition of C’ resistance after the transition from acute PIV5 infection to PI cells raises the potential to inform therapeutics for PIs based on modulating C’ pathways.

IMPORTANCE
A persistent infection (PI) with RNA viruses can extend virus shedding, prolong inflammation, and be a source of new viral variants. Since profound changes to innate immune pathways can occur in PI cells, it was important to test PI cells for changes in sensitivity to the complement (C') system, powerful innate immune pathways capable of lysing infected cells. Using parainfluenza virus 5 (PIV5) as a model system, we show that PI cells are nearly completely resistant to C'-mediated lysis, in stark contrast to high sensitivity of acute PIV5-infected cells to C' killing. A key finding was the upregulated expression in PI cells of two C' inhibitors: Vitronectin and complement factor H. These are important results with strong potential to inform therapeutics, given that polymorphisms in C' genes can correlate with severity of viral infections, and clinical trials are underway with new drugs that modulate C' responses.
Complete mitochondrial genome of
Rhaphidophora duxiu
(Orthoptera: Rhaphidophoridae: Rhaphidophorinae)
Authors: Yu Tingting , Yao Yuqing , Bian Xun , Zhang Bin 
Published: January 2025

ABSTRACT

We present the complete mitochondrial genome of
Rhaphidophora duxiu
from China. The mitogenome of
R. duxiu
is circular, AT-rich (75.3%), and 15,898 bp in length. It comprises 13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA genes. It is identical in gene content to
Rhaphidophora quadrispina
.
A murine model of
Trypanosoma brucei-
induced myocarditis and cardiac dysfunction
Authors: Crilly Nathan P. , Zita Marcelle Dina , Beaver Alexander K. , Sysa-Shah Polina , Bhalodia Aashik , Gabrielson Kathy , Adamo Luigi , Mugnier Monica R. 
Published: January 2025

ABSTRACT

Trypanosoma brucei
is a protozoan parasite that causes human and animal African trypanosomiases (HAT and AAT). Cardiac symptoms are commonly reported in HAT patients, and intracardiac parasites with accompanying myocarditis have been observed in both natural hosts and animal models of
T. brucei
infection. Despite the importance of
T. brucei
as a cause of cardiac dysfunction and the dramatic socioeconomic impact of African trypanosomiases in sub-Saharan Africa, there are currently no reproducible murine models of
T. brucei-
associated cardiomyopathy. We present the first clinically relevant, reproducible murine model of cardiac dysfunction in chronic
T. brucei
infection. Similar to humans, mice showed histological evidence of myocarditis and elevation of serum NT-proBNP with electrocardiographic abnormalities. Serum NT-proBNP levels were elevated prior to the development of severe ventricular dysfunction. On flow cytometry, myocarditis was associated with an increase of most myocardial immune cell populations, including multiple T cell and macrophage subsets, corroborating the notion that
T. brucei-
associated cardiac damage is an immune-mediated event. This novel mouse model represents a powerful and practical tool to investigate the pathogenesis of
T. brucei
-mediated heart damage and supports the development of therapeutic options for
T. brucei
-associated cardiac disease. In characterizing this model, we provide evidence that
T. brucei
causes cardiac disease, and we suggest that immunopathology is an important contributor to cardiac pathology. Along with other recent studies, our work demonstrates the importance of extravascular spaces, including the heart, for
T. brucei
pathogenesis.

IMPORTANCE
African trypanosomiasis is a neglected tropical disease affecting both people and cattle, which represents a major public health problem in sub-Saharan Africa with an enormous socioeconomic impact. Cardiac disease represents an underappreciated clinical manifestation of African trypanosomiasis that may lead to lifelong illness despite successful treatment of infection. However, this aspect of African trypanosomiasis remains poorly understood, partially due to a lack of well-characterized and practical animal models. In this study, we present the development and characterization of a novel, reproducible, and cost-effective mouse model of cardiac dysfunction in African trypanosomiasis. We demonstrate that this model recapitulates major features of cardiac dysfunction in natural infection, including the presence of parasites in the cardiac interstitial spaces, alterations of cardiac biomarkers, and functional changes. This model represents a resource to support the understanding of cardiac complications of trypanosomiasis and the development of new therapies to prevent and treat cardiac involvement in African trypanosomiasis.
Axisymmetric Poiseuille Flow with Temperature-Dependent Viscosity under Pressure and Temperature Gradients
Authors: Knyazev D. V. 
Published: January 2025

Abstract
The study of steady-state axisymmetric Poiseuille flow of a Newtonian fluid induced by streamwise pressure and temperature gradients in the case of the dynamic viscosity coefficient dependent on the temperature is reduced to finding solutions to a three-parameter boundary-value problem for a third-order ordinary differential equation. In the domain of the parameter space corresponding to negative axial temperature gradients, there exist two branches of solutions describing flows accompanied by heat removal from the fluid. When the branches meet, they form a boundary in the phase space beyond which no solutions to the Poiseuille-type problem exist. One of the branches can be continued into the domain of non-negative values of the streamwise temperature gradient and contains an isothermal Poiseuille solution. Along this branch, curve of the flow rate as a function of the dimensionless axial temperature gradient has a minimum in the domain of positive values of the latter. In this part of the parameter space, the heat exchange regime with the external medium depends on the relation between all three dimensionless numbers of the problem. The heat exchange regime affects the nature of flow, slowing down the flow near the rigid wall during heat transfer, and forming a more filled velocity profile when heat is absorbed by fluid.
Time to nursing home admission and death in people with dementia: systematic review and meta-analysis
Authors: Brück Chiara C , Mooldijk Sanne S , Kuiper Lieke M , Sambou Muhammed L , Licher Silvan , Mattace-Raso Francesco , Wolters Frank J 
Published: January 2025

Abstract

Objective
To summarise available evidence on time to nursing home admission and death among people with dementia, and to explore prognostic indicators.

Design
Systematic review and meta-analysis.

Data sources
Medline, Embase, Web of Science, Cochrane, and Google Scholar from inception to 4 July 2024.

Eligibility criteria for selecting studies
Longitudinal studies on survival or nursing home admission in people with dementia. Studies with fewer than 150 participants, recruitment during acute hospital admission, or less than one year of follow-up were excluded.

Results

19 307 articles were identified and 261 eligible studies included. 235 reported on survival among 5 553 960 participants and 79 reported on nursing home admission among 352 990 participants. Median survival from diagnosis appeared to be strongly dependent on age, ranging from 8.9 years at mean age 60 for women to 2.2 years at mean age 85 for men. Women overall had shorter survival than men (mean difference 4.1 years (95% confidence interval 2.1 to 6.1)), which was attributable to later age at diagnosis in women. Median survival was 1.2 to 1.4 years longer in Asia than in the US and Europe, and 1.4 years longer for Alzheimer’s disease compared with other types of dementia. Compared with studies before 2000, survival was longer in contemporary clinic based studies (P
trend
=0.02), but not in community based studies. Taken together, variation in reported clinical characteristics and study methodology explained 51% of heterogeneity in survival. Median time to nursing home admission was 3.3 years (interquartile range 1.9 to 4.0). 13% of people were admitted in the first year after diagnosis, increasing to 57% at five years, but few studies appropriately accounted for competing mortality risk when assessing admission rates.

Conclusions
The average life expectancy of people with dementia at time of diagnosis ranged from 5.7 years at age 65 to 2.2 at age 85 in men and from 8.0 to 4.5, respectively, in women. About one third of remaining life expectancy was lived in nursing homes, with more than half of people moving to a nursing home within five years after a dementia diagnosis. Prognosis after a dementia diagnosis is highly dependent on personal and clinical characteristics, offering potential for individualised prognostic information and care planning.

Systematic review registration
PROSPERO CRD42022341507.
Initial measurement of reactor antineutrino oscillation at SNO+
Authors:   SNO+ Collaboration, Allega A. , Anderson M. R. , Andringa S. , Askins M. , Asner D. M. , Auty D. J. , Bacon A. , Baker J. , Barão F. , Barros N. , Bayes R. , Beier E. W. , Bezerra T. S. , Bialek A. , Biller S. D. , Blucher E. , Caden E. , Callaghan E. J. , Chen M. , Cheng S. , Cleveland B. , Cookman D. , Corning J. , Cox M. A. , Dehghani R. , Deloye J. , Depatie M. M. , Di Lodovico F. , Dima C. , Dittmer J. , Dixon K. H. , Esmaeilian M. S. , Falk E. , Fatemighomi N. , Ford R. , Gaur A. , González-Reina O. I. , Gooding D. , Grant C. , Grove J. , Hall S. , Hallin A. L. , Hallman D. , Heintzelman W. J. , Helmer R. L. , Hewitt C. , Howard V. , Hreljac B. , Hu J. , Huang P. , Hunt-Stokes R. , Hussain S. M. A. , Inácio A. S. , Jillings C. J. , Kaluzienski S. , Kaptanoglu T. , Khan H. , Kladnik J. , Klein J. R. , Kormos L. L. , Krar B. , Kraus C. , Krauss C. B. , Kroupová T. , Lake C. , Lebanowski L. , Lefebvre C. , Lozza V. , Luo M. , Maio A. , Manecki S. , Maneira J. , Martin R. D. , McCauley N. , McDonald A. B. , Mills C. , Milton G. , Colina A. Molina , Morris D. , Morton-Blake I. , Mubasher M. , Naugle S. , Nolan L. J. , O’Keeffe H. M. , Orebi Gann G. D. , Ouyang S. , Page J. , Paleshi K. , Parker W. , Paton J. , Peeters S. J. M. , Pickard L. , Quenallata B. , Ravi P. , Reichold A. , Riccetto S. , Rose J. , Rosero R. , Semenec I. , Simms J. , Skensved P. , Smiley M. , Smith J. , Svoboda R. , Tam B. , Tseng J. , Vázquez-Jáuregui E. , Veinot J. G. C. , Virtue C. J. , Ward M. , Weigand J. J. , Wilson J. R. , Wilson J. D. , Wright A. , Yang S. , Yeh M. , Ye Z. , Yu S. , Zhang Y. , Zuber K. , Zummo A. 
Published: January 2025

Abstract
The SNO

$$+$$

+

collaboration reports its first spectral analysis of long-baseline reactor antineutrino oscillation using 114 tonne-years of data. Fitting the neutrino oscillation probability to the observed energy spectrum yields constraints on the neutrino mass-squared difference

$$\Delta m^2_{21}$$

Δ

m
21
2

. In the ranges allowed by previous measurements, the best-fit

$$\Delta m^2_{21}$$

Δ

m
21
2

is (

$$8.85^{+1.10}_{-1.33}$$

8
.

85

-
1.33

+
1.10

)

$$\times $$

×

$$10^{-5}$$

10

-
5

$$\hbox {eV}^2$$

eV
2

. This measurement is continuing in the next phases of SNO+ and is expected to surpass the present global precision on

$$\Delta m^2_{21}$$

Δ

m
21
2

with about three years of data.
Hybrid quantum neural networks: harnessing dressed quantum circuits for enhanced tsunami prediction via earthquake data fusion
Authors: Dutta Shivanya Shomir , Sandeep Sahil , D Nandhini , S Amutha 
Published: January 2025

AbstractTsunami is one of the deadliest natural disasters which can occur, leading to great loss of life and property. This study focuses on predicting tsunamis, using earthquake dataset from the year 1995 to 2023. The research introduces the Hybrid Quantum Neural Network (HQNN), an innovative model that combines Neural Network (NN) architecture with Parameterized Quantum Circuits (PmQC) to tackle complex machine learning (ML) problems where deep learning (DL) models struggle, aiming for higher accuracy in prediction while maintaining a compact model size. The hybrid model’s performance is compared with the classical model counterpart to investigate the quantum circuit’s effectivity as a layer in a DL model. The model has been implemented using 2-6 features through Principle Component Analysis (PCA) method. HQNN’s quantum circuit is a combination of Pennylane’s embedding (Angle Embedding (AE) and Instantaneous Quantum Polynomial (IQP) Embedding) and layer circuits (Basic Entangler Layers (BEL), Random Layers (RL), and Strongly Entangling Layers (SEL)), along with the classical layers. Results show that the proposed model achieved high performance, with a maximum accuracy up to 96.03% using 4 features with the combination of AE and SEL, superior to the DL model. Future research could explore the scalability and diverse applications of HQNN, as well as its potential to address practical ML challenges.
Viscoelastic wetting transition: beyond lubrication theory
Authors: Kansal Minkush , Datt Charu , Bertin Vincent , Snoeijer Jacco H. 
Published: January 2025

Abstract
The dip-coating geometry, where a solid plate is withdrawn from or plunged into a liquid pool, offers a prototypical example of wetting flows involving contact-line motion. Such flows are commonly studied using the lubrication approximation approach which is intrinsically limited to small interface slopes and thus small contact angles. Flows for arbitrary contact angles, however, can be studied using a generalized lubrication theory that builds upon viscous corner flow solutions. Here we derive this generalized lubrication theory for viscoelastic liquids that exhibit normal stress effects and are modelled using the second-order fluid model. We apply our theory to advancing and receding contact lines in the dip-coating geometry, highlighting the influence of viscoelastic normal stresses for contact line motion at arbitrary contact angle.
Enhancing predictive modeling of drug resistance in type 1 breast cancer through dynamic bayesian networks and machine learning integration
Authors: Arshad Arooba , Yousaf M. , Nutini Alessandro 
Published: January 2025

The emergence of drug resistance in Type 1 (T1) breast cancer poses a critical challenge to effective treatment and patient outcomes. Our study introduces an innovative framework that integrates Bayesian statistical methods with machine learning (ML) to advance predictive modeling of drug resistance mechanisms in T1 breast cancer. By uniting the strengths of dynamic Bayesian networks (DBNs) and ML, this approach enables the analysis of complex, multi-dimensional clinical data, including genomic, proteomic, and treatment response datasets. DBNs are employed to model the temporal evolution of resistance mechanisms, capturing time-dependent biological changes. ML algorithms complement this by uncovering intricate patterns and forecasting resistance trajectories under various therapeutic regimens. This synergistic combination not only identifies key biomarkers and resistance pathways but also addresses uncertainty and variability in patient responses, providing a robust predictive tool. The resulting model offers actionable insights to clinicians, aiding in the optimization of treatment strategies and improving patient outcomes. This work highlights the transformative potential of integrating Bayesian and ML methodologies to unravel complex biological phenomena, paving the way for advancements in precision oncology and personalized medicine.
The Frequency Spectrum of Rectilinearly Moving Point Sources in a Translation-Invariant Environment Applied to Edge Diffraction
Authors: Ochmann Martin 
Published: January 2025

In a translation-invariant environment, the three-dimensional sound field can be determined through spatial Fourier transform by superimposing two-dimensional sound fields. This technique is commonly referred to as the 2.5D method, due to the dimensional reduction that takes place. If the sound source is not stationary but moves along the axis of invariance, the calculation of the sound field generally becomes more complex. However, if a harmonically radiating point source moves uniformly at a constant speed along the invariance axis, the opposite is true, and the calculation is significantly simplified. Motivated by the form of the Green’s function in the free field, the so-called separation of variables, or product approach, reduces the problem to a purely two-dimensional one, the general solution of which is referred to in this work as the Product-Doppler formula. Constructing a Fourier integral over the wavenumber domain along the invariance axis is no longer necessary. It is shown that the Product-Doppler formula can be used to solve both interior and exterior problems. The sound field generated by a moving source inside a cylindrical tunnel, and the sound generated by an exterior moving source and scattered from an absorbing cylinder are analyzed. The complex problem of sound diffraction caused by a source moving along the edge of a wedge or a screen is studied in detail. A comparison with results from the literature shows strong agreement.
Electrochemical Characteristics of Sr(Ti0.3Fe0.7)O3–Based Electrodes in Solid Oxide Cells Operated in H2/H2O and CO/CO2 Mixtures
Authors: Geisendorfer Nicholas R , Pibulchinda Pattiya , Cox Dalton M , Barnett Scott A. 
Published: January 2025

Abstract
The electrochemical characteristics of SrTi0.3Fe0.7O3-δ (STF), Sr0.95Ti0.3Fe0.63Ni0.07 O3-δ (STFN), and Sr0.95Ti0.3Fe0.63Ru0.07 O3-δ (STFR) fuel electrodes were compared for a range of H2/H2O and CO/CO2 fuel mixtures. Electrodes prepared in symmetrical solid oxide cells were measured using impedance spectroscopy over a range of temperatures. Impedance spectra were fitted well in all cases using an equivalent circuit that featured three R-Q elements, but the response was generally dominated by a low frequency process associated with adsorption and charge transfer. The electrodes all yielded similar polarization resistances RP values at relatively high temperature ( 800°C) in H2/H2O, but STFN and STFR were substantially better than STF at lower temperatures. STFR yielded a much lower RP than the other electrodes when operating in CO/CO2. In full cells with these electrodes, STFR-based cells yielded superior power density and smaller polarization resistance compared to both STFN and STF cells, consistent with the symmetric cell results. It is suggested that the superior performance of STFR in CO/CO2 resulted from an enhancement of electrode processes in the presence of exsolved Ru-Fe nanoparticles.
The Dynamic Changes of COL11A1 Expression During the Carcinogenesis and Development of Breast Cancer and as a Candidate Diagnostic and Prognostic Marker
Authors: Wang Yuli , Wang Jing 
Published: January 2025

Purpose: Collagen type XI alpha 1 (COL11A1), a critical member of the collagen superfamily, is essential for tissue structure and integrity. This study aimed to validate previously identified variations in COL11A1 expression during breast cancer carcinogenesis and progression, as well as elucidate their clinical implications.Methods: COL11A1 mRNA expression levels were assessed using real‐time reverse transcription‐PCR (RT‐PCR) in 30 pairs of normal breast tissue and primary breast cancer, 30 pairs of primary breast cancer and lymph node metastases, 30 benign tumors, and 107 primary breast cancers. COL11A1 protein expression was evaluated by Western blot in six matched trios of normal tissue, primary cancer, and lymph node metastasis.Results: COL11A1 mRNA levels were significantly higher in primary breast cancer tissues (n = 30) than in adjacent normal breast tissues (p < 0.001). Conversely, lymph node metastases (n = 30) showed significantly lower COL11A1 mRNA levels compared to their primary breast cancer counterparts (p = 0.005). In a larger cohort, primary breast cancers (n = 107) had significantly elevated COL11A1 mRNA levels relative to adjacent normal tissues (n = 30) and benign tumors (n = 30) (p < 0.001). Benign tumors also demonstrated higher levels compared to normal tissues (p = 0.012). The protein expression patterns were consistent with the mRNA findings. Receiver operating characteristic (ROC) curve analysis confirmed the diagnostic relevance of COL11A1 expression levels. Significant associations were found between COL11A1 mRNA levels and clinical parameters including lymph node involvement (p = 0.046), clinical stage (p = 0.004), and progesterone receptor status (p = 0.048). Overexpression of COL11A1 was correlated with poor prognosis.Conclusions: COL11A1 expression varies during breast tumor initiation and progression, with elevated levels linked to worse prognoses. These findings underscore COL11A1’s potential as a biomarker in breast cancer, suggesting its assessment could enhance diagnostic and prognostic strategies for more personalized patient management.