bluuebunny/crossref_metadata_2025 huggingface dataset:
Passive heating in sport: context-specific benefits, detriments, and considerations
Authors: Menzies Campbell , Clarke Neil D. , Pugh Christopher J.A. , Steward Charles J. , Thake C. Douglas , Cullen Tom
Published: January 2025

Exercise and passive heating share some acute physiological responses. These include increases in body temperature, sweat rate, blood flow, heart rate, and redistribution of plasma and blood volume. These responses can vary depending on the heating modality or dose (e.g., temperature, duration, body coverage) and are beneficial to athletes in specific scenarios. These scenarios include being applied to increase muscle or force production, induce rapid weight loss, stimulate thermoregulatory or cardiovascular adaptation, or to accelerate recovery. The rationale being to tailor the specific passive heating protocol to target the desired physiological response. However, some acute responses to passive heating may also be detrimental to sporting outcomes, such as exercising in the heat, having unintended residual negative effects on performance or perceptions of fatigue, or even resulting in hospitalisation if implemented inappropriately. Accordingly, the effects of passive heating should be carefully considered prior to implementation by athletes, coaches, and support staff. Therefore, the purpose of this review is to evaluate the physiological responses to different modes and doses of passive heating and explore the various sport contexts where these effects may either benefit or hinder athletes. Understanding these responses can aid the implementation of passive heating in sport and identify potential recommended heating protocols in each given scenario.
Shallow Foundation Load Testing on Natural Florida Limestone: Single Rock Layer and Rock-Over-Sand Subsurface
Authors: Yang Kunyu , McVay Michael , Rodgers Michael B , Wasman Scott , Tran Khiem , Faraone Michael , Herrera Rodrigo , Horhota David
Published: January 2025

This article presents three shallow foundation load tests under various layer conditions (single rock layer and rock-over-sand subsurface), rock strengths, and limestone formations. Rock coring with laboratory triaxial testing, standard penetration tests (SPT), seismic shear tests, and measuring while drilling (MWD) tests were performed to identify the representative mass bulk dry unit weight (γdt) and the spatial variability of γdt. The geometric mean and median γdt, together with seismic shear results, were used to characterize rock strength and stiffness. Each footing test was sized at 1.07–1.83 m to fit the 12.20 m load frame (8.01 MN capacity) using laboratory-assessed bilinear strength envelopes of the rock. Predicted bearing capacities with Florida bearing capacity equations provided reasonable estimates for three load tests.
Mean and differential settlement, including spatial variability for a single footing on a heterogeneous rock layer, were captured with the Fenton and Griffiths method. For the settlement prediction of rock-over-sand subsurface, a parametric study was conducted for typical footing size, rock thickness, and mass properties with the finite element method (FEM), and a Winkler approach with a stress-dependent weighted harmonic mean modulus (Eeq). The proposed method achieved good agreement with the FEM results and was validated with load tests.
Structural analysis of physical gel networks using graph neural networks
Authors: Gimperlein Matthias , Dominsky Felix , Schmiedeberg Michael
Published: January 2025

We employ graph neural networks (GNN) to analyse and classify physical gel networks obtained from Brownian dynamics simulations of particles with competing attractive and repulsive interactions. Conventionally such gels are characterized by their position in a state diagram spanned by the packing fraction and the strength of the attraction. Gel networks at different regions of such a state diagram are qualitatively different although structural differences are subtile while dynamical properties are more pronounced. However, using graph classification the GNN is capable of positioning complete or partial snapshots of such gel networks at the correct position in the state diagram based on purely structural input. Furthermore, we demonstrate that not only supervised learning but also unsupervised learning can be used successfully. Therefore, the small structural differences are sufficient to classify the gel networks. Even the trend of data from experiments with different salt concentrations is classified correctly if the GNN was only trained with simulation data. Finally, GNNs are used to compute backbones of gel networks. As the node features used in the GNN are computed in linear time

$$\mathcal {O}(N)$$

O
(
N
)

, the use of GNN significantly accelerates the computation of reduced networks on a particle level.

Graphic abstract
The physical nature of the event horizon in the Schwarzschild black hole solution
Authors: Vavryčuk Václav
Published: January 2025

This study explores the relationship between the Schwarzschild metric and alternative metrics used to describe the gravitational field of a black hole in free space. While it is well-established that an infinite number of coordinate systems can be employed in general relativity, we demonstrate that the black hole solution is unique when expressed in a physically meaningful (proper) coordinate system. Notably, this coordinate system differs from the Schwarzschild metric due to the distinction between the true physical distance R and the Schwarzschild coordinate distance r. Consequently, the event horizon, commonly associated with the Schwarzschild solution, is shown to be a coordinate artefact of the chosen covariant metric tensor rather than a coordinate-invariant physical feature. As a result, no boundary prevents outgoing photons from escaping the black hole’s vicinity. This finding challenges the mainstream interpretation but remains fully consistent with general relativity. Moreover, it is supported by numerical modelling of light rays near a black hole. By reconsidering the existence of event horizons, this work offers potential resolutions to long-standing issues in black hole formation theories and the emission of electromagnetic and gravitational waves from black holes.

Graphical abstract
Permeability Model for Fractal Porous Media with Rough Capillary Walls
Authors: Zhao Yibo
Published: January 2025

The pore space of a porous medium is typically considered to consist of a collection of curved capillaries with rough walls. A model describing roughness is established by applying fractal theory. As a result, a modified permeability model is derived theoretically, which is closely related to roughness. To validate this model, a new form of Kozeny–Carman (KC) equation is also developed for estimating permeability on a set of benchmark rock samples, and a good agreement was achieved in terms of small relative error between measured and predicted permeabilities. Therefore, we can conclude that pore roughness should not be ignored in predicting permeability. Although the improved KC equation can predict permeability effectively too, it is not practical as the KC constant is difficult to determine.
A computational investigation using the nonNewtonian Sisko model and finite element analysis to determine blood flow characteristics in trapezoidal stenosed arteries
Authors: Hussain Azad , Dar Muhammad Naveel Riaz , Arif Ahmed
Published: January 2025

Arterial stenosis, a narrowing of the artery, significantly impacts blood flow dynamics and heat transfer. Although this phenomenon has been studied broadly, there is very less study about the complex interactions between nonNewtonian blood behavior, complicated artery geometry and temperature fluctuations. Using the Sisko model to represent the nonNewtonian blood nature in a trapezoidally stenotic artery, this study looks to clarify impact of arterial stenosis on blood flow dynamics. This study specifically looks into the temperature, pressure and velocity profiles in these circumstances. A Sisko structural equation-based mathematical model is created to represent blood flow via a trapezoidally stenosed artery. The governing equations which include momentum, energy conservation and continuity are numerically solved with the proper boundary conditions. Under various parametric values, the study shows complex fluctuations in the temperature, pressure and velocity profiles within the stenosed artery. These profiles are greatly impacted by the nonNewtonian conduct of blood, especially in the stenosis zone. It is discovered that the degree of stenosis is important in determining heat transmission, shear stress and flow resistance. Important new information about the hemodynamics and thermal behavior of blood in stenosed arteries is provided by this study. The results increase our understanding of vascular disorders and have the potential to guide the creation of innovative diagnostic and medical techniques.
An Intelligent Ensemble Deep Learning Techniques with Improved Owl Search Algorithm-Aided Optimal Feature Selection for Predicting the Presence of Heart Diseases
Authors: Bhadane Deepak Yashwantrao , Borse Indrabhan S.
Published: January 2025

Cardiovascular disease evaluation and prediction are critical medical duties to ensure precise classification, which allows heart specialists to offer treatment to patients. Heart illness is one of the deadliest diseases, particularly a sudden cardiac arrest, which strikes an individual so suddenly that there is no opportunity to manage it, and this condition is extremely hard to detect. Numerous medical machine learning, as well as data mining methods, have been employed to extract significant information about coronary artery disease prognosis. However, the precision of the intended outcomes is not adequate. An effective deep learning-assisted heart disease prediction model is presented to solve the above difficulties. At first, the data are accumulated from a standard dataset. After this process, the features from the data are optimally selected using the Improved Owl Search Algorithm (IOSA). These features are further transferred to the prediction phase. Here, the heart disease is predicted by the Ensemble Deep Attention with Convolution Network (EDACNet), and this model is composed by the combination of “Long Short-Term Memory (LSTM)”, “Gated Recurrent Unit (GRU)”, “Deep Markov Random Field (Deep MRF)” and “1Dimensional Convolutional Neural Network (1DCNN)”. The prediction scores obtained from each structure are multiplied by an optimized weight, and it is subjected to a weighted averaging process. Here, the weight is optimized by the same IOSA. The final results after the weighted averaging process provide the final predicted outcomes over heart diseases. At last, the validation process is carried out to measure the usefulness of a designed prediction model. The result of the developed model achieves better performance in terms of accuracy and precision. It shows the value of accuracy to be 96 and also the precision attained the value of 97. Therefore, the entire validation developed a model that provides effective performance over existing techniques.
How Can Haptic Feedback Assist People with Blind and Low Vision (BLV): A Systematic Literature Review
Authors: Jiang Chutian , Kuang Emily , Fan Mingming
Published: January 2025

People who are blind and low vision (BLV) encounter numerous challenges in their daily lives and work. To support them, various haptic assistive tools have been developed. Despite these advancements, the effective utilization of these tools—including the optimal haptic feedback and on-body stimulation positions for different tasks along with their limitations—remains poorly understood. Recognizing these gaps, we conducted a systematic literature review spanning two decades (2004–2024) to evaluate the development of haptic assistive tools within the HCI community. Our findings reveal that these tools are primarily used for understanding graphical information, providing guidance and navigation, and facilitating education and training, among other life and work tasks. We identified three main limitations: hardware limitations, functionality limitations, and UX and evaluation methods limitations. Based on these insights, we discuss potential research avenues and offer suggestions for enhancing the effectiveness of future haptic assistive technologies.
Enhancing Quantum Algorithms for Quadratic Unconstrained Binary Optimization via Integer Programming
Authors: Wagner Friedrich , Nüßlein Jonas , Liers Frauke
Published: January 2025

To date, research in quantum computation promises potential for outperforming classical heuristics in combinatorial optimization. However, when aiming at provable optimality, one has to rely on classical exact methods like integer programming. State-of-the-art integer programming algorithms can compute strong relaxation bounds even for hard instances, but may have to enumerate a large number of subproblems for determining an optimum solution. If the potential of quantum computing is realized, it can be expected that in particular finding high-quality solutions for hard problems can be done fast. Still, near-future quantum hardware considerably limits the size of treatable problems. In this work, we go one step into integrating the potentials of quantum and classical techniques for combinatorial optimization. We propose a hybrid heuristic for the weighted maximum-cut problem and for quadratic unconstrained binary optimization. The heuristic employs a linear programming relaxation, rendering it well-suited for integration into exact branch-and-cut algorithms. For large instances, we reduce the problem size according to a linear relaxation such that the reduced problem can be handled by quantum machines of limited size. Moreover, we improve the applicability of depth-1 QAOA, a parameterized quantum algorithm, by deriving a parameter estimate for arbitrary instances. We present numerous computational results from real quantum hardware.
Engineering Digital Systems for Humanity: a Research Roadmap
Authors: Autili Marco , De Sanctis Martina , Inverardi Paola , Pelliccione Patrizio
Published: January 2025

As testified by new regulations like the European AI Act, worries about the human and societal impact of (autonomous) software technologies are becoming of public concern. Human, societal, and environmental values, alongside traditional software quality, are increasingly recognized as essential for sustainability and long-term well-being. Traditionally, systems are engineered taking into account business goals and technology drivers. Considering the growing awareness in the community, in this paper, we argue that engineering of systems should also consider human, societal, and environmental drivers. Then, we identify the macro and technological challenges by focusing on humans and their role while co-existing with digital systems. The first challenge considers humans in a proactive role when interacting with digital systems, i.e., taking initiative in making things happen instead of reacting to events. The second concerns humans having a reactive role in interacting with digital systems, i.e., humans interacting with digital systems as a reaction to events. The third challenge focuses on humans with a passive role, i.e., they experience, enjoy or even suffer the decisions and/or actions of digital systems. The fourth challenge concerns the duality of trust and trustworthiness, with humans playing any role. Building on the new human, societal, and environmental drivers and the macro and technological challenges, we identify a research roadmap of digital systems for humanity. The research roadmap is concretized in a number of research directions organized into four groups: development process, requirements engineering, software architecture and design, and verification and validation.
Generating High-Fidelity Clothed Human Dynamics with Temporal Diffusion
Authors: Zou Shihao , Xu Yuanlu , Sarafianos Nikolaos , Bogo Federica , Tung Tony , Si Weixin , Cheng Li
Published: January 2025

Clothed human modeling plays a crucial role in multimedia research, with applications spanning virtual reality, gaming, and fashion design. The goal is to learn clothed human dynamics from observations and then generate humans with high-fidelity clothing details for motion animation. Despite tremendous advancements in clothing shape analysis by existing approaches, the community still faces challenges in generating convincing visual effects of cloth dynamics, maintaining temporally smooth clothing details, and handling diverse clothing patterns. To address these challenges, we introduce ClothDiffuse, a temporal diffusion model that seamlessly integrates three key components into this task: temporal dynamics modeling, iterative refinement, and diversified generation. Our approach begins by using an encoder to extract high-level temporal features from input human body motions. These features are combined with a learnable pixel-aligned garment feature, serving as prior conditions for the shape decoder. The decoder then iteratively denoise Gaussian noise to produce clothing deformations over time on the input unclothed human bodies. To ensure that the results align with observations and adhere to physical plausibility for clothing shape inference, we propose two physics-inspired loss functions that preserve the intra-frame distances and inter-frame forces of clothing points. Additionally, the stochastic nature of the denoising process allows for the generation of diverse and plausible clothing shapes. Experiments show that our approach outperforms state-of-the-art methods in chamfer distance and visual effects, particularly for loose clothing such as dresses and skirts. Furthermore, our approach effectively adapts to out-of-domain clothing types and generate realistic clothes dynamics.
The Electroactive Species and Electrolyte Solution Chemistry Importance in Non-Aqueous Mg Electrochemical Systems
Authors: Dlugatch Ben , Kumar Yogendra , Attias Ran , Salama Michael , Btavo-Zhyvotovs Dmitry , Noked Malachi , Aurbach Doron
Published: January 2025

The chemistry of the electrolyte solutions that enable reversible Mg deposition is not trivial. Such solutions are currently limited to ethereal solvents and most of them contain chlorides complexes. These ionic complexes have important role in the performance. However, the presence of chlorides in these solutions complicates the cathode side because such solutions are not compatible with the commonly used metallic current collectors for cathodes. Consequently, it is questionable whether it is possible to synthesize fully functional Cl-free electrolyte solutions suitable commercial Mg-ion batteries. Noked et al. reported that by adding DME to the precursor electrolyte [Mg2Cl3*6THF]+ [Ph3AlCl]- in THF, it was possible to create a new electroactive complex Mg salt, namely, [Mg-3.DME]2+ 2[AlPh3Cl]-, which solution performs better than the precursor’s solution. This solution introduces a new case of chlorides free electrolyte solution, with stabilized Mg2+ cations and anions containing chloride ligands which cannot lead to corrosion phenomena. In this work a full evaluation of selected electrolyte solution was carried out, considering rigorously the role of the electroactive species and the anion complexes in the electrochemical process. In addition, we study the effect of the anion on the electrochemical performance by comparing this solution with other previously presented solutions.
Sex differences in aortic valve inflammation and remodeling in chronic severe aortic regurgitation
Authors: Tiraplegui Carolina , Garaikoetxea Mattie , Sádaba Alba , San Ildefonso-García Susana , Goñi-Olóriz Miriam , Fernández-Celis Amaya , Martín-Núñez Ernesto , Álvarez Virginia , Sádaba Rafael , Anand Vidhu , Jover Eva , Navarro Adela , López-Andrés Natalia
Published: January 2025

The pathogenesis of chronic aortic regurgitation (AR) is different in male and female. Female patients with AR showed less aortic valve inflammation and collagen accumulation as compared with male. Valvular cells from female patients secreted less inflammatory molecules and collagen and higher levels of proteoglycans. Valvular interstitial cells from females were more sensitive to transforming growth factor (TGF)-β-induced proteoglycans secretion. Our study opens a new perspective oriented toward sex-specific molecular pathways and therapeutic targets in chronic severe AR.
Strategic MARCOS Model for Optimizing Renewable Energy Investments Under Pythagorean Hesitant Fuzzy Assessments
Authors: Younis Muhammad , Ashraf Shahzaib , Abdullah Saleem , Shahid Tooba , K. C. Gokul
Published: January 2025

For sustainable growth, investments in renewable energy must be maximized. Maximizing investments in renewable energy opens the door to a more successful and environmentally friendly future. Analyzing technological viability, cost‐effectiveness, regulatory compliance, and environmental impact are all part of this optimization process. This paper delves into a sophisticated methodology designed to tackle uncertainties in decision‐making by leveraging the innovative concept of Pythagorean hesitant fuzzy sets (PHFSs). We defined aggregation operations and distance measures for PHFS. After that, we introduced Measurement of Alternatives and Ranking According to the Compromise Solution (MARCOS), a novel methodology under PHFS, it is a robust tool acknowledged for navigating complex decision scenarios with multiple criteria. Following that, we showcased a case study on enhancing renewable energy investments through an AI‐based strategy for sustainable development, utilizing the newly developed MARCOS algorithm. The study highlights the significance of its adaptability and efficiency in practical applications. Furthermore, we compared this methodology with the Technique for Establishing Order Performance by Similarity to the Ideal Solution (TOPSIS), offering insights into their respective strengths. This offers a concrete demonstration of its real‐world utility and potential impact in decision‐making scenarios. Finally, in the last, we conclude the whole study.
Predicting Resilient Modulus of Fine‐Grained Soils Using Support Vector Machine‐RBF and Random Forest
Authors: Tilahun Yonas , Qinghua Xiao , Ashango Argaw Asha , Dame Shume
Published: January 2025

The resilient modulus (Mr) of subgrade soils is an important element in road pavement structural design procedures. However, because of regional differences in soil parameters and the nature of test procedures, determining Mr in the laboratory has become cumbersome. The purpose of this study is to develop a reliable soft computing approach for forecasting Mr of subgrade soils using support vector machine‐based linear kernel (SVM‐LR), polynomial kernel (SVM‐Poly), radial basic function (SVM‐RBF), and random forest (RF) techniques. For this purpose, a dataset of 138 soil samples from diverse geographical locations in Ethiopia was gathered, and the models were trained and tested using an 85% training and 15% test data split. All of the recommended models used confining pressure (CP), notional maximum axial stress (NmaxAS), specific gravity, P#200, silt%, clay%, liquid limit (LL), plasticity index (PI), maximum dry density, Wopt, and swell as input variables. The correctness of the proposed models was assessed by comparing predicted and observed Mr values with various statistical approaches such as root means square error (RMSE), mean squared error (MSE), mean absolute error (MAE), and determination coefficient (R2). The support vector machine RBF model outperformed all other models in validation, with R2 values of 0.99 and 0.91, MAE of 0.1 and 1.76, MSE of 0.01 and 29.54, and RMSE of 0.1 and 5.43. The Taylor diagrams of the test and training datasets show that the SVM‐RBF model outperforms the other models. Sensitivity analysis was performed to explore the impact of input variable quantity on the output of Mr for the MPL model, and it was determined that the top five essential parameters are, in decreasing order, LL, P#200, silt%, PI, and clay%. In contrast, the nominal maximum axial stress and Gs have the least impact.
Autonomous Landing of a Fixed‐Wing UAV With RTK GNSS and MEMS IMU
Authors: Xia Lu , Li Jianqing
Published: January 2025

Autonomous landing system is an important part of unmanned aerial vehicle (UAV) autonomous flight. Large fixed‐wing UAVs often consume more onboard space and computing resources. With the improvement of system integration and the reduction of high‐performance global navigation satellite system (GNSS) costs, real‐time kinematic (RTK) GNSS has been widely used in small‐scale and low‐cost fixed‐wing UAVs. This article uses less onboard hardware and ground facility requirements to design an autonomous taking off and landing system suitable for general fixed‐wing UAVs. A modified gradient descent attitude estimator, based on microelectromechanical system (MEMS) inertial measurement unit (IMU) and RTK GNSS, and a guidance method based on a tracking differentiator for using in a high dynamic environment are proposed, and circular path following and vertical transient simulations are performed. The simulation results show that this method can improve attitude estimation accuracy, motion control accuracy, and altitudinal transient quality. Finally, the actual flight test verifies its feasibility in the actual environment. The flight test results prove that it is feasible to implement the autonomous landing process of fixed‐wing UAV with the proposed system and method.
Calcium Chloride Enhances Defense Response Against Diaporthe nobilis by Eliciting Reactive Oxygen Species in Kiwifruit
Authors: Li Huanhuan , Su Qian , Huang Zhipeng , Yu Shukun , Liu Yongsheng , Miao Min
Published: January 2025

Kiwifruit (Actinidia spp.) rot, caused by pathogenic fungi, represents the most severe disease during postharvest storage. The utilization of induced resistance against fungal pathogens in harvested fruit has been demonstrated as a promising strategy for controlling postharvest losses. In this study, the effect of calcium chloride (CaCl2) on induction of resistance to Diaporthe nobilis, one of the most epidemic pathogens of soft rot in kiwifruit, and the underlying mechanisms were investigated. Our data showed that the application of 3% CaCl2 resulted in smaller rotten lesion diameters after inoculation with the pathogen, induced expression of the respiratory burst oxidase homolog (RBOH) gene family, and increased accumulation of reactive oxygen species (ROS). Moreover, we found that the activity of three pathogenesis‐related antioxidant enzymes—peroxidase (POD), catalase (CAT), and superoxide dismutase (SOD)—as well as the expression of important defense‐related genes, was enhanced by CaCl2 treatment. The results of our study suggest that the application of CaCl2 treatment holds promise as a green and viable method for effectively preventing and safeguarding kiwifruit against postharvest decay.
Enhancement of High-Dose Chemotherapy and Autologous SCT with the PARP Inhibitor Olaparib for Refractory Lymphoma
Authors: Nieto Yago , Ramdial Jeremy , Valdez Benigno , Thall Peter F. , Bassett Roland , Barnett Melissa , Srour Samer , Hosing Chitra , Alousi Amin , Qazilbash Muzaffar , Popat Uday , Gulbis Alison , Shigle Terri Lynn , Ahmed Sairah , Guillermo Pacheco Maria , Champlin Richard , Shpall Elizabeth J. , Andersson Borje S.
Published: January 2025

Purpose:

More active high-dose chemotherapy (HDC) regimens are needed for autologous stem cell transplantation (ASCT) for refractory lymphomas. Seeking HDC enhancement with a PARP inhibitor, we observed marked synergy between olaparib and vorinostat/gemcitabine/busulfan/melphalan (GemBuMel) against lymphoma cell lines, mediated by the inhibition of DNA damage repair. Our preclinical work led us to clinically study olaparib/vorinostat/GemBuMel with ASCT.

Patients and Methods:

Patients ages 15 to 65 years with refractory lymphoma and adequate end-organ function were eligible for this phase I trial. The olaparib dosage was escalated from 25 mg orally twice a day on days −11 to −3, plus vorinostat (1,000 mg orally/day, days −10 to −3), gemcitabine (2,475 mg/m2/day i.v., days −8 and −3), busulfan (target AUC 4,000 µmol/L.minute−1/day i.v., days −8 to −5), melphalan (60 mg/m2/day i.v., days −3 and −2), and rituximab (CD20+ tumors; 375 mg/m2, day −10), with ASCT.

Results:

Fifty patients were enrolled (23 with Hodgkin lymphoma, 18 with diffuse large B-cell lymphoma, and 9 with T-cell non–Hodgkin lymphoma); the median age was 35 years (range, 20–61); patients received a median of three prior lines of therapy (range, 2–7); 17 patients had previously relapsed after chimeric antigen receptor T-cell therapy or other cellular immunotherapies; 23 patients had PET-positive tumors at HDC (9 in progression). An olaparib dosage of 150 mg orally twice a day was identified as the recommended phase II dosage. The main extramedullary toxicity was mucositis. The overall response rate and complete response rate were 100% and 90%, respectively. At the median follow-up of 30 (range, 12–56) months, the event-free survival and overall survival rates were 72% and 82% in all patients and 71% and 88% in patients with prior CAR T-cell failure, respectively.

Conclusions:

In this first trial combining a PARP inhibitor with HDC, olaparib/vorinostat/GemBuMel was safe and showed promising activity in refractory lymphomas, including post–CAR-T relapses.
Novel Combination Therapy Targeting Oncogenic Signaling Kinase P21-Activated Kinase 1 and Chemotherapeutic Drugs Against Triple-Negative Breast Cancer
Authors: Ezhil Inemai , Seetharaman Abirami , Kanumuri Rahul , Rajamani Barathidasan , Gangavarapu Ranga Rao , Venkatraman Ganesh , Rayala Suresh K.
Published: January 2025

Most of the triple-negative phenotypes or basal-like molecular subtypes of breast cancers are associated with aggressive clinical behavior and show poor disease prognosis. Current treatment options are constrained, emphasizing the need for novel combinatorial therapies for this particular tumor subtype. Our group has demonstrated that functionally active p21–activated kinase 1 (PAK1) exhibits significantly higher expression levels in clinical triple-negative breast cancer (TNBC) samples compared with other subtypes, as well as adjacent normal tissues. Low PAK1 expression in TNBC was significantly linked to better prognosis, with improved overall survival (P = 0.00236) and relapse-free survival (P = 0.0314), as shown by Gene expression–based Outcome for Breast cancer Online analysis. To confirm the role of PAK1 as a therapeutic target and to discover novel synergistic chemotherapy drug combinations, we conducted a drug combination screen using TNBC cell lines and a mouse metastatic tumor cell line. We identified the combined inhibition of PAK1 inhibitor NVS-PAK1 with doxorubicin/paclitaxel/methotrexate as a synergistic novel therapeutic approach for treating metastatic TNBC to improve overall survival. This study also indicated a reduction in the effective dosage of the chemotherapeutic drug when combined with NVS-PAK1. Our study demonstrates that combining NVS-PAK1 with each individual chemotherapeutic drug such as doxorubicin, paclitaxel, and methotrexate resulted in decreased colony formation, reduced wound-healing capability, and diminished migratory and invasive potential in both TNBC cell lines and 4T1 in vitro. These findings were further validated in orthotopic mouse mammary tumors, confirming that simultaneous PAK1 inhibition alongside chemotherapy significantly enhanced antitumor efficacy and reduced metastasis.
Supplementary Table S6 from Cancer Prevalence across Vertebrates
Authors: Compton Zachary T. , Mellon Walker , Harris Valerie K. , Rupp Shawn , Mallo Diego , Kapsetaki Stefania E. , Wilmot Mallory , Kennington Ryan , Noble Kathleen , Baciu Cristina , Ramirez Lucia N. , Peraza Ashley , Martins Brian , Sudhakar Sushil , Aksoy Selin , Furukawa Gabriela , Vincze Orsolya , Giraudeau Mathieu , Duke Elizabeth G. , Spiro Simon , Flach Edmund , Davidson Hannah , Li Christopher I. , Zehnder Ashley , Graham Trevor A. , Troan Brigid V. , Harrison Tara M. , Tollis Marc , Schiffman Joshua D. , Aktipis C. Athena , Abegglen Lisa M. , Maley Carlo C. , Boddy Amy M.
Published: January 2025

List of veterinarian diagnoses used as the data dictionary
Supplementary Table S4 from AMG 193, a Clinical Stage MTA-Cooperative PRMT5 Inhibitor, Drives Antitumor Activity Preclinically and in Patients with MTAP-Deleted Cancers
Authors: Belmontes Brian , Slemmons Katherine K. , Su Chun , Liu Siyuan , Policheni Antonia N. , Moriguchi Jodi , Tan Hong , Xie Fang , Aiello Daniel Andrew , Yang Yajing , Lazaro Raul , Aeffner Famke , Rees Matthew G. , Ronan Melissa M. , Roth Jennifer A. , Vestergaard Mikkel , Cowland Sanne , Andersson Jan , Sarvary Ian , Chen Qing , Sharma Pooja , Lopez Patricia , Tamayo Nuria , Pettus Liping H. , Ghimire-Rijal Sudipa , Mukund Susmith , Allen Jennifer R. , DeVoss Jason , Coxon Angela , Rodon Jordi , Ghiringhelli François , Penel Nicolas , Prenen Hans , Glad Sanne , Chuang Chen-Hua , Keyvanjah Kiana , Townsley Danielle M. , Butler John R. , Bourbeau Matthew P. , Caenepeel Sean , Hughes Paul E.
Published: January 2025

Supplementary Table S4: AMG 193 AUCs
Supplementary Table S3 from AMG 193, a Clinical Stage MTA-Cooperative PRMT5 Inhibitor, Drives Antitumor Activity Preclinically and in Patients with MTAP-Deleted Cancers
Authors: Belmontes Brian , Slemmons Katherine K. , Su Chun , Liu Siyuan , Policheni Antonia N. , Moriguchi Jodi , Tan Hong , Xie Fang , Aiello Daniel Andrew , Yang Yajing , Lazaro Raul , Aeffner Famke , Rees Matthew G. , Ronan Melissa M. , Roth Jennifer A. , Vestergaard Mikkel , Cowland Sanne , Andersson Jan , Sarvary Ian , Chen Qing , Sharma Pooja , Lopez Patricia , Tamayo Nuria , Pettus Liping H. , Ghimire-Rijal Sudipa , Mukund Susmith , Allen Jennifer R. , DeVoss Jason , Coxon Angela , Rodon Jordi , Ghiringhelli François , Penel Nicolas , Prenen Hans , Glad Sanne , Chuang Chen-Hua , Keyvanjah Kiana , Townsley Danielle M. , Butler John R. , Bourbeau Matthew P. , Caenepeel Sean , Hughes Paul E.
Published: January 2025

Supplementary Table S3: In vitro and in vivo potencies of AM-9747 and AMG 193
Supplementary Figures S1 - S69 from Cancer Prevalence across Vertebrates
Authors: Compton Zachary T. , Mellon Walker , Harris Valerie K. , Rupp Shawn , Mallo Diego , Kapsetaki Stefania E. , Wilmot Mallory , Kennington Ryan , Noble Kathleen , Baciu Cristina , Ramirez Lucia N. , Peraza Ashley , Martins Brian , Sudhakar Sushil , Aksoy Selin , Furukawa Gabriela , Vincze Orsolya , Giraudeau Mathieu , Duke Elizabeth G. , Spiro Simon , Flach Edmund , Davidson Hannah , Li Christopher I. , Zehnder Ashley , Graham Trevor A. , Troan Brigid V. , Harrison Tara M. , Tollis Marc , Schiffman Joshua D. , Aktipis C. Athena , Abegglen Lisa M. , Maley Carlo C. , Boddy Amy M.
Published: January 2025

All of the PGLS regressions done with the exception of the multivariate analysis. The multivariate analysis is included as a separate file S41
Supplementary Figure S41 from Cancer Prevalence across Vertebrates
Authors: Compton Zachary T. , Mellon Walker , Harris Valerie K. , Rupp Shawn , Mallo Diego , Kapsetaki Stefania E. , Wilmot Mallory , Kennington Ryan , Noble Kathleen , Baciu Cristina , Ramirez Lucia N. , Peraza Ashley , Martins Brian , Sudhakar Sushil , Aksoy Selin , Furukawa Gabriela , Vincze Orsolya , Giraudeau Mathieu , Duke Elizabeth G. , Spiro Simon , Flach Edmund , Davidson Hannah , Li Christopher I. , Zehnder Ashley , Graham Trevor A. , Troan Brigid V. , Harrison Tara M. , Tollis Marc , Schiffman Joshua D. , Aktipis C. Athena , Abegglen Lisa M. , Maley Carlo C. , Boddy Amy M.
Published: January 2025

Multivariate PGLS regression analysis
Supplementary Figure S6 from AMG 193, a Clinical Stage MTA-Cooperative PRMT5 Inhibitor, Drives Antitumor Activity Preclinically and in Patients with MTAP-Deleted Cancers
Authors: Belmontes Brian , Slemmons Katherine K. , Su Chun , Liu Siyuan , Policheni Antonia N. , Moriguchi Jodi , Tan Hong , Xie Fang , Aiello Daniel Andrew , Yang Yajing , Lazaro Raul , Aeffner Famke , Rees Matthew G. , Ronan Melissa M. , Roth Jennifer A. , Vestergaard Mikkel , Cowland Sanne , Andersson Jan , Sarvary Ian , Chen Qing , Sharma Pooja , Lopez Patricia , Tamayo Nuria , Pettus Liping H. , Ghimire-Rijal Sudipa , Mukund Susmith , Allen Jennifer R. , DeVoss Jason , Coxon Angela , Rodon Jordi , Ghiringhelli François , Penel Nicolas , Prenen Hans , Glad Sanne , Chuang Chen-Hua , Keyvanjah Kiana , Townsley Danielle M. , Butler John R. , Bourbeau Matthew P. , Caenepeel Sean , Hughes Paul E.
Published: January 2025

Supplementary Figure S6. AM-9747 treatment results in increased DNA damage and cellular senescence in BxPC-3 cells
Supplementary Figure S5 from AMG 193, a Clinical Stage MTA-Cooperative PRMT5 Inhibitor, Drives Antitumor Activity Preclinically and in Patients with MTAP-Deleted Cancers
Authors: Belmontes Brian , Slemmons Katherine K. , Su Chun , Liu Siyuan , Policheni Antonia N. , Moriguchi Jodi , Tan Hong , Xie Fang , Aiello Daniel Andrew , Yang Yajing , Lazaro Raul , Aeffner Famke , Rees Matthew G. , Ronan Melissa M. , Roth Jennifer A. , Vestergaard Mikkel , Cowland Sanne , Andersson Jan , Sarvary Ian , Chen Qing , Sharma Pooja , Lopez Patricia , Tamayo Nuria , Pettus Liping H. , Ghimire-Rijal Sudipa , Mukund Susmith , Allen Jennifer R. , DeVoss Jason , Coxon Angela , Rodon Jordi , Ghiringhelli François , Penel Nicolas , Prenen Hans , Glad Sanne , Chuang Chen-Hua , Keyvanjah Kiana , Townsley Danielle M. , Butler John R. , Bourbeau Matthew P. , Caenepeel Sean , Hughes Paul E.
Published: January 2025

Supplementary Figure S5. In vitro target validation, RNA-seq, and additional cell cycle data in WT and MTAP-deleted tumor cells
Supplementary Figure S1 from AMG 193, a Clinical Stage MTA-Cooperative PRMT5 Inhibitor, Drives Antitumor Activity Preclinically and in Patients with MTAP-Deleted Cancers
Authors: Belmontes Brian , Slemmons Katherine K. , Su Chun , Liu Siyuan , Policheni Antonia N. , Moriguchi Jodi , Tan Hong , Xie Fang , Aiello Daniel Andrew , Yang Yajing , Lazaro Raul , Aeffner Famke , Rees Matthew G. , Ronan Melissa M. , Roth Jennifer A. , Vestergaard Mikkel , Cowland Sanne , Andersson Jan , Sarvary Ian , Chen Qing , Sharma Pooja , Lopez Patricia , Tamayo Nuria , Pettus Liping H. , Ghimire-Rijal Sudipa , Mukund Susmith , Allen Jennifer R. , DeVoss Jason , Coxon Angela , Rodon Jordi , Ghiringhelli François , Penel Nicolas , Prenen Hans , Glad Sanne , Chuang Chen-Hua , Keyvanjah Kiana , Townsley Danielle M. , Butler John R. , Bourbeau Matthew P. , Caenepeel Sean , Hughes Paul E.
Published: January 2025

Supplementary Figure S1. SPR chaser characterization
Supplementary Figure 3 from Zongertinib (BI 1810631), an Irreversible HER2 TKI, Spares EGFR Signaling and Improves Therapeutic Response in Preclinical Models and Patients with HER2-Driven Cancers
Authors: Wilding Birgit , Woelflingseder Lydia , Baum Anke , Chylinski Krzysztof , Vainorius Gintautas , Gibson Neil , Waizenegger Irene C. , Gerlach Daniel , Augsten Martin , Spreitzer Fiona , Shirai Yukina , Ikegami Masachika , Tilandyová Sylvia , Scharn Dirk , Pearson Mark A. , Popow Johannes , Obenauf Anna C. , Yamamoto Noboru , Kondo Shunsuke , Opdam Frans L. , Bruining Annemarie , Kohsaka Shinji , Kraut Norbert , Heymach John V. , Solca Flavio , Neumüller Ralph A.
Published: January 2025

In vitro biomarker modulation of (phospho-)protein and mRNA levels post poziotinib or zongertinib treatment.
Supplementary Figure 1 from Zongertinib (BI 1810631), an Irreversible HER2 TKI, Spares EGFR Signaling and Improves Therapeutic Response in Preclinical Models and Patients with HER2-Driven Cancers
Authors: Wilding Birgit , Woelflingseder Lydia , Baum Anke , Chylinski Krzysztof , Vainorius Gintautas , Gibson Neil , Waizenegger Irene C. , Gerlach Daniel , Augsten Martin , Spreitzer Fiona , Shirai Yukina , Ikegami Masachika , Tilandyová Sylvia , Scharn Dirk , Pearson Mark A. , Popow Johannes , Obenauf Anna C. , Yamamoto Noboru , Kondo Shunsuke , Opdam Frans L. , Bruining Annemarie , Kohsaka Shinji , Kraut Norbert , Heymach John V. , Solca Flavio , Neumüller Ralph A.
Published: January 2025

Synthesis and in vivo DMPK profile of zongertinib
Supplementary Data Set 1 from Disparate Pathways for Extrachromosomal DNA Biogenesis and Genomic DNA Repair
Authors: Rose John C. , Belk Julia A. , Wong Ivy Tsz-Lo , Luebeck Jens , Horn Hudson T. , Daniel Bence , Jones Matthew G. , Yost Kathryn E. , Hung King L. , Kolahi Kevin S. , Curtis Ellis J. , Kuo Calvin J. , Bafna Vineet , Mischel Paul S. , Chang Howard Y.
Published: January 2025

sgRNA, primer, and probe sequences.
Supplementary Data Table 1 from Zongertinib (BI 1810631), an Irreversible HER2 TKI, Spares EGFR Signaling and Improves Therapeutic Response in Preclinical Models and Patients with HER2-Driven Cancers
Authors: Wilding Birgit , Woelflingseder Lydia , Baum Anke , Chylinski Krzysztof , Vainorius Gintautas , Gibson Neil , Waizenegger Irene C. , Gerlach Daniel , Augsten Martin , Spreitzer Fiona , Shirai Yukina , Ikegami Masachika , Tilandyová Sylvia , Scharn Dirk , Pearson Mark A. , Popow Johannes , Obenauf Anna C. , Yamamoto Noboru , Kondo Shunsuke , Opdam Frans L. , Bruining Annemarie , Kohsaka Shinji , Kraut Norbert , Heymach John V. , Solca Flavio , Neumüller Ralph A.
Published: January 2025

MANO method and results. Sheet 1: Primer sequence for the bar code amplification. Sheet 2: Primer sequence for next-generation sequencing analysis. Sheet 3: Raw data for zongertinib (BI 1810631 in table) drug sensitivity assay.
Supplementary Figures S1-10 from Neuro-Mesenchymal Interaction Mediated by a β2-Adrenergic Nerve Growth Factor Feedforward Loop Promotes Colorectal Cancer Progression
Authors: Kobayashi Hiroki , Iida Tadashi , Ochiai Yosuke , Malagola Ermanno , Zhi Xiaofei , White Ruth A. , Qian Jin , Wu Feijing , Waterbury Quin T. , Tu Ruhong , Zheng Biyun , LaBella Jonathan S. , Zamechek Leah B. , Ogura Atsushi , Woods Susan L. , Worthley Daniel L. , Enomoto Atsushi , Wang Timothy C.
Published: January 2025

Supplementary Figure S1 supports Figure 1 and shows stromal NGF expression and innervation in human colorectal cancer tissues. Supplementary Figure S2 supports Figure 1 and shows stromal NGF expression and innervation in mouse colorectal cancer tissues. Supplementary Figure S3 supports Figure 2 and shows that adrenergic stimulation induces fibroblast NGF upregulation via the β2-adrenergic receptor to promote innervation. Supplementary Figure S4 supports Figure 3 and shows that adrenergic stimulation increases mouse colon cancer organoid growth through ADRA2/Gi protein-mediated activation of YAP signaling. Supplementary Figure S5 supports Figure 3 and shows that adrenergic stimulation increases human colon cancer cell growth through ADRA2/Gi protein-mediated activation of YAP signaling. Supplementary Figure S6 supports Figure 3 and shows that chemical sympathectomy inhibits colon cancer growth and YAP activation. Supplementary Figure S7 supports Figure 4 and shows that stromal NGF increases innervation and colon cancer cell proliferation. Supplementary Figure S8 supports Figure 5 and shows that NGF increases colon cancer cell growth and stem-related gene expression. Supplementary Figure S9 supports Figure 6 and shows that Trk blockade decreases innervation, cancer cell proliferation, and Ngf expression. Supplementary Figure S10 supports Figure 7 and shows that high NGF expression is associated with poor patient outcomes, stroma-rich tumor subtypes, and enrichment for YAP and AKT pathways.
Supplementary Tables S1-S13 from Chromothripsis-Mediated Small Cell Lung Carcinoma
Authors: Rekhtman Natasha , Tischfield Sam E. , Febres-Aldana Christopher A. , Lee Jake June-Koo , Chang Jason C. , Herzberg Benjamin O. , Selenica Pier , Woo Hyung Jun , Vanderbilt Chad M. , Yang Soo-Ryum , Xu Fei , Bowman Anita S. , da Silva Edaise M. , Noronha Anne Marie , Mandelker Diana L. , Mehine Miika , Mukherjee Semanti , Blanco-Heredia Juan , Orgera John J. , Nanjangud Gouri J. , Baine Marina K. , Aly Rania G. , Sauter Jennifer L. , Travis William D. , Savari Omid , Moreira Andre L. , Falcon Christina J. , Bodd Francis M. , Wilson Christina E. , Sienty Jacklynn V. , Manoj Parvathy , Sridhar Harsha , Wang Lu , Choudhury Noura J. , Offin Michael , Yu Helena A. , Quintanal-Villalonga Alvaro , Berger Michael F. , Ladanyi Marc , Donoghue Mark T.A. , Reis-Filho Jorge S. , Rudin Charles M.
Published: January 2025

Supplementary Table S1. Integrated genomic and immunohistochemical results for TP53 and RB1 in aSCLC Supplementary Table S2. Demographic, clinicopathologic and immunohistochemical characteristics: Per patient data Supplementary Table S3. Samples and studies performed: Per sample data Supplementary Table S4. Clinicopathologic comparison aSCLC vs other SCLC Supplementary Table S5. MSK-IMPACT metrics and full results for all samples Supplementary Table S6. Full list of SNV by MSK-IMPACT in aSCLC Supplementary Table S7. Full list of CNA by MSK-IMPACT in aSCLC Supplementary Table S8. RB1 and TP53 non-coding variant annotation by WGS Supplementary Table S9. Full list of SV by WGS in aSCLC Supplementary Table S10. Full list of fusions by RNAseq in aSCLC Supplementary Table S11. Timing of amplifications by WGS: mutTimerR Supplementary Table S12. Immunohistochemical antibodies, protocols and scoring criteria Supplementary Table S13. List of covered genes by targeted NGS (MSK-IMPACT assay): somatic and germline.
Supplementary Figures S1-S13 from Chromothripsis-Mediated Small Cell Lung Carcinoma
Authors: Rekhtman Natasha , Tischfield Sam E. , Febres-Aldana Christopher A. , Lee Jake June-Koo , Chang Jason C. , Herzberg Benjamin O. , Selenica Pier , Woo Hyung Jun , Vanderbilt Chad M. , Yang Soo-Ryum , Xu Fei , Bowman Anita S. , da Silva Edaise M. , Noronha Anne Marie , Mandelker Diana L. , Mehine Miika , Mukherjee Semanti , Blanco-Heredia Juan , Orgera John J. , Nanjangud Gouri J. , Baine Marina K. , Aly Rania G. , Sauter Jennifer L. , Travis William D. , Savari Omid , Moreira Andre L. , Falcon Christina J. , Bodd Francis M. , Wilson Christina E. , Sienty Jacklynn V. , Manoj Parvathy , Sridhar Harsha , Wang Lu , Choudhury Noura J. , Offin Michael , Yu Helena A. , Quintanal-Villalonga Alvaro , Berger Michael F. , Ladanyi Marc , Donoghue Mark T.A. , Reis-Filho Jorge S. , Rudin Charles M.
Published: January 2025

Supplementary Figure S1. Detailed morphologic and immunohistochemical findings: Case A01. Supplementary Figure S2. Detailed morphologic and immunohistochemical findings: Case A08. Supplementary Figure S3. Detailed morphologic and immunohistochemical findings: Case A17. Supplementary Figure S4. Detailed morphologic and immunohistochemical findings: Case A20. Supplementary Figure S5. Mutational signatures in atypical SCLC (aSCLC), never-smoker SCLC with RB1–/TP53– (nsSCLC) and smoking-associated SCLC (sSCLC) analyzed by MSK-IMPACT. Supplementary Figure S6. Circos plots showing structural variants and copy number alterations across the genome from all cases with WGS. Supplementary Figure S7. Chromothripsis assessment by targeted NGS (MSK-IMPACT) versus WGS. Supplementary Figure S8. RNAseq for non-recurrently amplified (KRAS, ERBB3, KDM5A) or deleted (TGFBR2, ARID1A) genes on chromothriptic chromosomes and TERT. Supplementary Figure S9. Comparison of chromothripsis characteristics in aSCLC vs other major lung cancer types. Supplementary Figure S10. Chromothripsis architecture in all cases profiled by whole-genome sequencing. Supplementary Figure S11. Chromothripsis in multi-sample analysis and genomic alterations in samples with histotype heterogeneity. Supplementary Figure S12. Cell cycle and p53 pathway deregulation in aSCLC. Supplementary Figure S13. Expression of potential therapeutic markers in aSCLC.