bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations of Immune Checkpoint Predictive Biomarkers (MHC-I and MHC-II) with Clinical and Molecular Features in a Diverse Breast Cancer Cohort
Authors: Sun Xiaopeng , Kennedy Laura C. , Gonzalez-Ericsson Paula I. , Sanchez Violeta , Sanders Melinda , Perou Charles M. , Troester Melissa A. , Balko Justin M. , Reid Sonya A. 
Published: July 2024

Abstract

Purpose:
Immunotherapy (IO) in triple-negative breast cancer (TNBC) has improved survival outcomes, with promising improvements in pCR rates among early high-risk hormone receptor (HR)+/HER2− breast cancers. However, biomarkers are needed to select patients likely to benefit from IO. MHC-I and tumor-specific MHC-II (tsMHC-II) expression are candidate biomarkers for PD-(L)1 checkpoint inhibition but existing data from clinical trials included limited racial/ethnic diversity.

Experimental Design:
We performed multiplexed immunofluorescence assays in the Carolina Breast Cancer Study (CBCS; n = 1,628, 48% Black, 52% non-Black). Intrinsic subtype and P53 mutant-like status were identified using RNA-based multigene assays. We ranked participants based on tumoral MHC-I intensity (top 33% categorized as “MHC-Ihigh”) and MHC-II+ (≥5% of tumor cells as tsMHC-II+). MHC-I/II were evaluated in association with clinicopathological features by race.

Results:
Black participants had higher frequency of TNBC (25% vs. 12.5%, P ≤ 0.001) and basal-like (30% vs. 14%, P ≤ 0.001) tumors overall, and higher frequency of basal-like (11% vs. 5.5%, P = 0.002) and TP53 mutant tumors (26% vs. 17%, P = 0.002) among HR+/HER2−. The frequency of tsMHC-II+ was higher in HR+/HER2− Black participants (7.9% vs. 4.9%, P = 0.04). Black participants also had higher frequency of MHC-Ihigh (38.7% vs. 28.2%, P &lt; 0.001), which was significant among HR+/HER2− (28.2% vs. 22.1%, P = 0.02).

Conclusions:
In this diverse study population, MHC-I and MHC-II tumor cell expression were more highly expressed in HR+/HER2− tumors from Black women, underscoring the importance of diverse and equitable enrollment in future IO trials.
NETosis Impact on Tumor Biology, Radiation, and Systemic Therapy Resistance
Authors: Mowery Yvonne M. , Luke Jason J. 
Published: July 2024

SummaryNeutrophil extracellular trap (NET)osis via lytic neutrophil death or neutrophil activation is associated with standard cancer therapies, notably including radiotherapy; is immunosuppressive; and may enhance metastasis and treatment resistance. This emerging area of research should be prioritized in drug development and standard of care treatment paradigms including radiation therapy, chemotherapy, and immunotherapy.See related article by Teijeira et al., p. 4131
Predicted Cardiovascular Risk by the PREVENT Equations in US Adults With Stage 1 Hypertension
Authors: Muntner Paul , Jaeger Byron C. , Foti Kathryn , Ghazi Lama , Bundy Joshua D. , Chen Ligong , Safford Monika M. 
Published: July 2024

BACKGROUND:
The 2017 American College of Cardiology/American Heart Association blood pressure guideline recommends initiation of antihypertensive medication for adults with stage 1 hypertension (systolic blood pressure, 130–139 mm Hg, or diastolic blood pressure, 80–89 mm Hg) and 10-year atherosclerotic cardiovascular disease (ASCVD) risk ≥10% estimated by the pooled cohort equations (PCEs). In 2023, the American Heart Association published the predicting risk of cardiovascular disease events (PREVENT) equations to estimate ASCVD and total cardiovascular disease risk.

METHODS:
We analyzed US National Health and Nutrition Examination Survey data from 2013 to 2020 for 1703 adults aged 30 to 79 years without self-reported cardiovascular disease with stage 1 hypertension. We estimated 10-year ASCVD risk by the PCEs and 10-year ASCVD and total cardiovascular disease risk by the base PREVENT equations. Analyses were weighted to represent noninstitutionalized US adults with stage 1 hypertension.

RESULTS:
Mean 10-year ASCVD risk was 5.4% (95% CI, 5.0%–5.9%) and 2.9% (95% CI, 2.7%–3.1%) using the PCEs and PREVENT equations, respectively. The proportion with 10-year ASCVD risk of 10% to <15% and ≥15% was 8.1% and 7.8% estimated by the PCEs, respectively, and 3.0% and 0.3% estimated by the PREVENT equations, respectively. No participants had a 10-year ASCVD risk ≥10% on the PREVENT equations and <10% on the PCEs, while 12.5% had a 10-year ASCVD risk ≥10% on the PCEs and <10% on the PREVENT equations. The mean 10-year total cardiovascular disease risk estimated by the PREVENT equations was lower than the mean 10-year ASCVD risk on the PCEs.

CONCLUSIONS:
Among US adults with stage 1 hypertension, the 10-year predicted ASCVD risk estimated by the PREVENT equations was approximately half the risk estimated by the PCEs.
Improving laminar fMRI specificity by reducing macrovascular bias revealed by respiration effects
Authors: Chai Yuhui , Morgan A. Tyler , Handwerker Daniel A. , Li Linqing , Huber Laurentius , Sutton Bradley P. , Bandettini Peter A. 
Published: July 2024

Abstract
Functional MRI (fMRI) time series are inherently susceptible to the influence of respiratory variations. While many studies treat respiration as a source of noise in fMRI, this study employs natural respiratory variations during high resolution (0.8 mm) fMRI at 7T to formulate a respiration effect related map and then use this map to reduce macrovascular bias for a more laminar-specific fMRI measurement. Our results indicate that respiratory-related signal changes are modulated by breath phase (breathing in/out or in the transition between breath in and out) during fMRI acquisition, with distinct patterns across various brain regions. We demonstrate that respiration maps generated from normal fMRI runs, such as task-oriented sessions, closely resemble those from deep-breath and breath-hold experiments. These maps show a significant correlation with the macro-vasculature automatically segmented based on susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM) images. Most crucially, by removing voxels most responsive to respiratory variations, we can refine high-resolution fMRI measurements to be more layer-specific, improving the accuracy of laminar fMRI analysis.
Winter Targeted Observing Periods during the Year of Polar Prediction in the Southern Hemisphere (YOPP-SH)
Authors: Bromwich David H. , Gorodetskaya Irina V. , Carpentier Scott , Alexander Simon , Bazile Eric , Heinrich Victoria J. , Massonnet Francois , Powers Jordan G. , Carrasco Jorge F. , Cayette Arthur , Choi Taejin , Chyhareva Anastasiia , Colwell Steven R. , Cordeira Jason M. , Cordero Raul R. , Doerenbecher Alexis , Durán-Alarcón Claudio , French W. John R. , Gonzalez-Herrero Sergi , Guyot Adrien , Haiden Thomas , Hirasawa Naohiko , Imazio Paola Rodriguez , Kawzenuk Brian , Krakovska Svitlana , Lazzara Matthew A. , Litell Mariana Fontolan , Manning Kevin W. , Norris Kimberley , Park Sang-Jong , Ralph F. Martin , Rowe Penny M. , Sun Qizhen , Vitale Vito , Wille Jonathan D. , Zhang Zhenhai , Zou Xun 
Published: July 2024

Abstract
The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven targeted observing periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5–10-day duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed-phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high-time-resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The Sea Ice Prediction Network South (SIPN South) analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase.
Should We Conserve Entropy or Energy when Computing CAPE with Mixed-Phase Precipitation Physics?
Authors: Peters John M. 
Published: July 2024

Abstract
The rapidly increasing resolution of global atmospheric reanalysis and climate model datasets necessitates finding methods for computing convective available potential energy (CAPE) both efficiently and accurately. To this end, this article compares two common methods for computing CAPE which conserve either energy or entropy. Inaccuracies in these computations arise from both physical and numerical errors. For instance, computing CAPE with entropy conserved results in physical errors from nonequilibrium phase transitions but minimizes numerical errors because solutions are analytic at each height. In contrast, computing CAPE with energy conserved avoids these physical errors, but accumulates numerical errors that are grid-resolution-dependent because the numerical integration of a differential equation is required. Analysis of CAPE computed with large databases of soundings from the tropical Amazon and midlatitude storm environments shows that physical errors from the entropy method are typically 1%–3% as large as CAPE, which is comparable to the numerical errors from conserving energy with grid spacing of 25 and 250 m using explicit first-order and second-order integration schemes, respectively. Errors in entropy-based CAPE calculations are also insensitive to vertical grid spacing, in contrast to energy-based calculations whose error strongly scales with the grid spacing. It is shown that entropy-based methods are advantageous when intercomparing datasets with differing vertical resolution because they produce accurate and reasonably fast results that are insensitive to grid resolution, whereas a second-order energy-based method is advantageous when analyzing data with a consistent vertical resolution because of its superior computational efficiency.

Significance Statement
Convective available potential energy (CAPE) is a measure of instability in the atmosphere that helps forecasters and researchers understand when and where thunderstorms will form. The purpose of this article is to identify the most efficient and accurate methods for computing CAPE. Two methods are considered here, one that relates to the entropy (a measure of thermodynamic disorder) of an air parcel and one that relates to the energy of an air parcel. Results indicate that the entropy method is most accurate and insensitive to the resolution of the data used for the calculation (which can vary considerably), whereas the energy method uses the least computation time.
Path Tracking Controller Design of Automated Parking Systems via NMPC with an Instructible Solution
Authors: Chen Liang , Qin Zhaobo , Hu Manjiang , Bian Yougang , Peng Xiaoyan 
Published: July 2024

AbstractParking difficulties have become a social issue that people have to solve. Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents. The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method (RF-LNMPC) in order to improve the overall path tracking accuracy in parking conditions. Firstly, A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively. Secondly, the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization, of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution. Thirdly, the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented. The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically. Finally, the proposed RF-LNMPC is implemented on a self-driving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions. The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.
Vibration Control of the Rail Grinding Vehicle with Abrasive Belt Based on Structural Optimization and Lightweight Design
Authors: Fan Wengang , Zhang Shuai , Wu Zhiwei , Liu Yi , Yu Jiangnan 
Published: July 2024

AbstractAs a new grinding and maintenance technology, rail belt grinding shows significant advantages in many applications. The dynamic characteristics of the rail belt grinding vehicle largely determines its grinding performance and service life. In order to explore the vibration control method of the rail grinding vehicle with abrasive belt, the vibration response changes in structural optimization and lightweight design are respectively analyzed through transient response and random vibration simulations in this paper. Firstly, the transient response simulation analysis of the rail grinding vehicle with abrasive belt is carried out under operating conditions and non-operating conditions. Secondly, the vibration control of the grinding vehicle is implemented by setting vibration isolation elements, optimizing the structure, and increasing damping. Thirdly, in order to further explore the dynamic characteristics of the rail grinding vehicle, the random vibration simulation analysis of the grinding vehicle is carried out under the condition of the horizontal irregularity of the American AAR6 track. Finally, by replacing the Q235 steel frame material with 7075 aluminum alloy and LA43M magnesium alloy, both vibration control and lightweight design can be achieved simultaneously. The results of transient dynamic response analysis show that the acceleration of most positions in the two working conditions exceeds the standard value in GB/T 17426-1998 standard. By optimizing the structure of the grinding vehicle in three ways, the average vibration acceleration of the whole car is reduced by about 55.1% from 15.6 m/s2 to 7.0 m/s2. The results of random vibration analysis show that the grinding vehicle with Q235 steel frame does not meet the safety conditions of $$3\sigma$$

3
σ

. By changing frame material, the maximum vibration stress of the vehicle can be reduced from 240.7 MPa to 160.0 MPa and the weight of the grinding vehicle is reduced by about 21.7% from 1500 kg to 1175 kg. The modal analysis results indicate that the vibration control of the grinding vehicle can be realized by optimizing the structure and replacing the materials with lower stiffness under the premise of ensuring the overall strength. The study provides the basis for the development of lightweight, diversified and efficient rail grinding equipment.
Impact Force Localization and Reconstruction via ADMM-based Sparse Regularization Method
Authors: Wang Yanan , Chen Lin , Liu Junjiang , Qiao Baijie , He Weifeng , Chen Xuefeng 
Published: July 2024

AbstractIn practice, simultaneous impact localization and time history reconstruction can hardly be achieved, due to the ill-posed and under-determined problems induced by the constrained and harsh measuring conditions. Although $$\ell_{1}$$

ℓ
1

regularization can be used to obtain sparse solutions, it tends to underestimate solution amplitudes as a biased estimator. To address this issue, a novel impact force identification method with $$\ell_{p}$$

ℓ
p

regularization is proposed in this paper, using the alternating direction method of multipliers (ADMM). By decomposing the complex primal problem into sub-problems solvable in parallel via proximal operators, ADMM can address the challenge effectively. To mitigate the sensitivity to regularization parameters, an adaptive regularization parameter is derived based on the K-sparsity strategy. Then, an ADMM-based sparse regularization method is developed, which is capable of handling $$\ell_{p}$$

ℓ
p

regularization with arbitrary p values using adaptively-updated parameters. The effectiveness and performance of the proposed method are validated on an aircraft skin-like composite structure. Additionally, an investigation into the optimal p value for achieving high-accuracy solutions via $$\ell_{p}$$

ℓ
p

regularization is conducted. It turns out that $$\ell_{0.6}$$

ℓ

0.6

regularization consistently yields sparser and more accurate solutions for impact force identification compared to the classic $$\ell_{1}$$

ℓ
1

regularization method. The impact force identification method proposed in this paper can simultaneously reconstruct impact time history with high accuracy and accurately localize the impact using an under-determined sensor configuration.
Intelligent Diagnosis Method for Typical Co-frequency Vibration Faults of Rotating Machinery Based on SAE and Ensembled ResNet-SVM
Authors: Zhang Xiancheng , Pan Xin , Zeng Hao , Zhou Haofu 
Published: July 2024

AbstractIntelligent fault diagnosis is an important method in rotating machinery fault diagnosis and equipment health management. To deal with co-frequency vibration faults, a type of typical fault in rotating machinery, this paper proposes a fault diagnosis method based on the stacked autoencoder (SAE) and ensembled ResNet-SVM. Furthermore, the time- and frequency-domain features of several co-frequency vibration faults are summarized based on the mechanism analysis and calculated using actual vibration data. To realize and validate the high-precision diagnosis method of rotating equipment with co-frequency faults proposed in this study, the following three criteria are required: First, to improve the effectiveness and robustness of the ensembled model and the sliding window using data augmentation, adding noise, autoencoder (AE) and SAE methods are analyzed in terms of principle and practical effects. Second, ResNet is used as the feature extractor for the ensembled ResNet-SVM model. Feature extraction is carried out twice, and the extracted co-frequency fault features are more comprehensive. Finally, the data augmentation method and ensemble ResNet-SVM are combined for fault diagnosis and compared with other methods. The experimental results show that the accuracy of the proposed method can exceed 99.9%.
Velocity-Incorporated Wear Model of Rolling Guide Shoe Material Selection
Authors: Chen Longye , Yan Lingyu , Liu Chengliang , Zhang Zhinan 
Published: July 2024

AbstractTo ensure an accurate selection of rolling guide shoe materials, an analysis of the intricate relationship between linear speed and wear is imperative. Finite element simulations and experimental measurements are employed to evaluate four distinct types of materials: polyurethane, rubber, polytetrafluoroethylene (PTFE), and nylon. The speed-index of each material is measured, serving as a preparation for subsequent analysis. Furthermore, the velocity-wear factor is determined, providing insights into the resilience and durability of the material across varying speeds. Additionally, a wear model tailored specifically for viscoelastic bodies is explored, which is pivotal in understanding the wear mechanisms within the material. Leveraging this model, wear predictions are made under higher speed conditions, facilitating the choice of material for rolling guide shoes. To validate the accuracy of the model, the predicted degree of wear is compared with experimental data, ensuring its alignment with both theoretical principles and real-world performance. This comprehensive analysis has verified the effectiveness of the model in the selection of materials under high-speed conditions, thereby offering confidence in its reliability and ensuring optimal performance.
Inflammatory response of leptomeninges to a single cortical spreading depolarization
Authors: Karan Anna A. , Gerasimov Konstantin A. , Spivak Yulia S. , Suleymanova Elena M. , Vinogradova Lyudmila V. 
Published: July 2024

Abstract
Background
Neurogenic meningeal inflammation is regarded as a key driver of migraine headache. Multiple evidence show importance of inflammatory processes in the dura mater for pain generation but contribution of the leptomeninges is less clear. We assessed effects of cortical spreading depolarization (CSD), the pathophysiological mechanism of migraine aura, on expression of inflammatory mediators in the leptomeninges.

Methods
A single CSD event was produced by a focal unilateral microdamage of the cortex in freely behaving rats. Three hours later intact cortical leptomeninges and parenchyma of ipsi-lesional (invaded by CSD) and sham-treated contra-lesional (unaffected by CSD) hemispheres were collected and mRNA levels of genes associated with inflammation (Il1b, Tnf, Ccl2; Cx3cl1, Zc3h12a) and endocannabinoid CB2 receptors (Cnr2) were measured using qPCR.

Results
Three hours after a single unilateral CSD, most inflammatory factors changed their expression levels in the leptomeninges, mainly on the side of CSD. The meninges overlying affected cortex increased mRNA expression of all proinflammatory cytokines (Il1b, Tnf, Ccl2) and anti-inflammatory factors Zc3h12a and Cx3cl1. Upregulation of proinflammatory cytokines was found in both meninges and parenchyma while anti-inflammatory markers increased only meningeal expression.

Conclusion
A single CSD is sufficient to produce pronounced leptomeningeal inflammation that lasts for at least three hours and involves mostly meninges overlying the cortex affected by CSD. The prolonged post-CSD inflammation of the leptomeninges can contribute to mechanisms of headache generation following aura phase of migraine attack.
Antimicrobial efficacy of nano-particles for crop protection and sustainable agriculture
Authors: Jali Pallavi , Acharya Srinivas , Mahalik Gyanranjan 
Published: July 2024

AbstractPlant diseases cause colossal crop loss worldwide and are the major yield constraining component in agriculture. Nanotechnology, which has the possible to revolutionize numerous fields of science, innovation, drug, and agriculture. Nanotechnology can be utilized for combating the plant infectious diseases and nano-materials can be utilized as transporter of dynamic elements of pesticides, host defense etc. to the pathogens. The analysis of diseases, finding of pathogens may turn out to be substantially more precise and fast with the utilization of nanosensors. As worldwide demand for food production raises against an evolving atmosphere, nanotechnology could reasonably alleviate numerous challenges in disease managing by diminishing chemical inputs and advancing quick recognition of pathogens. The major goal of this review is to increase growth and productivity using supplements with nanoparticles. (i.e., metals, metal oxides, and carbon) to treat crop diseases and make agricultural practices more productive and sustainable. Prominently, this improved crop may not only be straight connected to the diminished occurrence of pathogenic microorganisms, yet in might possibly add nutritional benefits of the nanoparticles themselves, particularly for the micronutrients important for generating host resistance.