bluuebunny/crossref_metadata_2025 huggingface dataset:
Challenges in Model Synchronization for Information Preservation Illustrated with the FACE and AADL Standards
Authors: Blouin Dominique , Bhobe Anish , Pautet Laurent
Published: December 2024

This article explores the challenges in Model Synchronization in Model Driven Engineering, focusing on Information Preservation. It introduces modern architecture description languages such as FACE and AADL and describes the challenges in reliably maintaining consistency of their models, as well as determining how to propagate changes of one model to the other. It describes ongoing efforts including improving Information Preservation in model synchronization approaches such as Triple Graph Grammars, as well as the required foundations and ideas for the establishing effective Model Management and Synchronization frameworks.
Reconfigurable and Scalable Honeynet for Cyber-physical Systems
Authors: Sousa Luís , Cecílio José , Ferreira Pedro M. , Oliveira de Sá Alan
Published: December 2024

Industrial Control Systems (ICS) constitute the backbone of contemporary industrial operations, ranging from modest heating, ventilation, and air conditioning systems to expansive national power grids. Given their pivotal role in critical infrastructure, there has been a concerted effort to enhance security measures and deepen our comprehension of potential cyber threats within this domain. To address these challenges, numerous implementations of Honeypots and Honeynets intended to detect and understand attacks have been employed for ICS. This approach diverges from conventional methods by focusing on making a scalable and reconfigurable honeynet for cyber-physical systems. It will also automatically generate attacks on the honeynet to test and validate it. With the development of a scalable and reconfigurable Honeynet and automatic attack generation tools, it is also expected that the system will serve as a basis for producing datasets for training algorithms for detecting and classifying attacks in cyberphysical honeynets.
Nano in Micro: Novel Concepts in Foodborne Pathogen Transmission and Pathogenesis
Authors: Liu Yue , Ma Xuchuan , Cazzaniga Monica , Gahan Cormac G.M. , den Besten Heidy M.W. , Abee Tjakko
Published: December 2024

In this article, we highlight novel components of foodborne pathogens that influence their response, physiology, adaptation, and survival in the face of diverse stresses, and consequently have implications for their transmission in the food chain and their pathogenesis. Recent insights into the role of bacteriophages/prophages, bacterial extracellular vesicles, and bacterial microcompartments, which make up the emerging field we coined as “nano in micro,” are presented, together with the role of understudied food-relevant substrates in pathogen fitness and virulence. These new insights also lead to reflections on generally adopted laboratory conditions in the long-standing research field of adaptive stress response in foodborne pathogens. In addition, selected examples of the impact of diet and microbiota on intestinal colonization and host invasion are discussed. A final section on risk assessment presents an overview of tools for (kinetic) data modeling and perspectives for the implementation of information derived from whole-genome sequencing, combined with advancements in dose-response models and exposure assessments.
Numerical Investigation of Heat Transfer and Flow Patterns of Supercritical CO2 in Six‐Start Spirally Fluted Tubes
Authors: Wu Hanghui , Chen Shanshan , Chen Zhoulin , Chen Xiaoping , Wu Weidong
Published: December 2024

This research numerically investigates the heat transfer and flow patterns of supercritical carbon dioxide (sCO2) in a six‐start spirally fluted tube. The research focuses on the geometrical optimization of the tube based on three key parameters: the groove depth (e1), the gap between the main tube and the outer sleeve (e2), and the thread pitch (p). The influence of these parameters on the heat transfer coefficient (h) and friction factor (f) was also investigated and analyzed. Furthermore, the study examined the overall impact of the gravity inclination angle (δ) on the thermal performance and flow velocity of the spirally fluted tube. The results indicated that the optimal geometrical parameters are as follows: e1/D = 0.33, e2/D = 0.04, and p/D = 8.33, yielding the highest values of h/h8/(f/f8) in the spirally fluted tub. The change in e2 has a more significant effect on turbulent kinetic energy (TKE) and thermal performance than the change in e1. The p value showed a more substantial effect on the f value compared with the h value. Furthermore, the h value was positively correlated with the gravity inclination angle δ in the region where Tb  < Tpc. In the region where Tb  > Tpc, increasing the gravity inclination angle δ led to a reduction in h value. When δ < 0°, the h value experienced a slight increase. However, the h value showed a substantial variation when δ > 0°, and the near‐wall fluid experienced a reduced flow velocity because of the combined effects of gravity and buoyancy, leading to a decrease in heat transfer. Larger gravity inclination angles led to a more pronounced deterioration in heat transfer. This study is anticipated to provide a theoretical basis for the optimized design of heat exchangers and the enhancement of energy conversion efficiency.
Highly Efficient DC–DC Boost Converter Achieved With Improved MPPT‐Based Raspberry Pi for Enhancing Photovoltaic System Generation
Authors: Alghaythi Mamdouh L. , Fathy Ahmed , Allehyani Ahmed , Alshammari Meshari S. , Atitallah Ahmed Ben , Rezk Hegazy , Gaafar Tamer S.
Published: December 2024

The operation of photovoltaic (PV) panels in partial shade (PS) conditions (PSCs) lowers the quantity of energy generated due to the hot spots that increase the power loss. In this scenario, a maximum power point tracker (MPPT) is necessary to monitor the power–voltage curve, which features multiple local peaks in addition to one global peak (GP). The GP could not be extracted from the panel at PSCs using traditional MPPT techniques such as hill climbing (HC), perturb and observe (P&O), and incremental conductance (IC). Therefore, this paper proposes a new construction of MPPT simulated via a Raspberry Pi 4 controller programed through a recent bald eagle search (BES) algorithm. Because of its substantially enhanced diversification, which aids in avoiding local peaks, the suggested BES can capture the global power of PV during PSCs. The Raspberry Pi 4‐BES MPPT in the recommended hardware adjusts the direct current (DC)–DC boost converter’s duty cycle based on its inputs, which are the voltage and current from the PV panel output. Eight shade patterns are studied, and the fetched results through the proposed BES are compared to other programed approaches of skill optimization algorithm (SOA), gray wolf optimizer (GWO), and particle swarm optimization (PSO). Additionally, the proposed tracker’s Simulink model is created and evaluated in relation to the experimental hardware. Moreover, the power errors and efficiencies of all considered approaches are calculated in both simulation and experimental analyses. The results revealed that the least errors are 0.0018% and 0.296% obtained through the proposed Raspberry Pi 4‐BES MPPT in simulation and experimental, respectively. Also, in the simulation and experimental setting, the recommended tracker yielded the highest efficiencies of 99.99% and 99.92%, respectively. The suggested Raspberry Pi 4‐BES MPPT is praised for being a useful tracker for monitoring the GP of PV panels at various PSCs.
Antifatigue Effects of Deer‐Hide Gelatin on Mice by Regulating Nrf2/Keap1 and AMPK/PGC1α Signaling Pathways and Intestinal Flora
Authors: Chang Yuan , Zhang Lulu , Nie Zixuan , Miao Yixiang , Jia Tianzhu , Shi Ji , Liu Pengpeng
Published: December 2024

Objective: This study investigated the antifatigue effects of deer‐hide gelatin (DHG) and its mechanism in mice through a weight‐loaded swimming experiment.

Methods: The subjects were assigned to the blank group (BC), positive group (PC), model group (MC), and high, medium, and low doses of DHG groups (HP, MP, and LP). After 4 weeks of treatment, the subjects were sacrificed to detect fatigue‐related biochemical indicators and the protein and mRNA expressions of Nrf2/Keap1 and AMPK/PGC1α pathways. The morphological changes of skeletal muscle were detected. High‐throughput sequencing technology was used to detect the changes in the relative abundance of intestinal flora and the content of short‐chain fatty acids (SCFAs) in tired subjects.

Results: Compared with MC, DHG could prolong the exhaustion time of weight‐loaded swimming mice; reduce the CK, BUN, lactic acid, MDA, 5‐HT, and GABA levels; and increase the LDH, SOD, CAT, Glycogen, MG, BG, ACH, and Glu levels. Moreover, DHG increased the protein and mRNA expression of Nrf2, HO‐1, AMPK, PGC1α, and P‐AMPK and reduced the protein and mRNA expression of Keap1. The 16S rDNA sequencing analysis also showed that DHG regulated the abundance of intestinal microbiota and the content of SCFAs and increased the growth of beneficial bacteria.

Conclusions: DHG exhibited antifatigue effects on mice by activating Nrf2/Keap1 and AMPK/PGC1α pathways, reducing oxidative stress damage, and enhancing mitochondrial energy supply. The study’s findings confirmed the considerable antioxidant and antifatigue activities of DHG, providing a preliminary foundation and practical theory for the further development of DHG as a nutritional supplement.
Supplementary figure 4 from Targeting NTRK1 Enhances Immune Checkpoint Inhibitor Efficacy in NTRK1 Wild-Type Non–Small Cell Lung Cancer
Authors: Smith Margaret R. , Dixon Caroline B. , Wang Yuezhu , Liu Yin , D’Agostino Ralph , Ruiz Jimmy , Oliver George , Miller Lance D. , Topaloglu Umit , Chan Michael D. , Farris Michael , Su Jing , Mileham Kathryn F. , Zhao Dawen , Li Wencheng , Sexton Tammy , Lycan Thomas , Haas Karen M. , Grayson Jason M. , Xing Fei
Published: December 2024

Supplementary figure 4
Table S4 from Fitness Screens Map State-Specific Glioblastoma Stem Cell Vulnerabilities
Authors: MacLeod Graham , Molaei Fatemeh , Haider Shahan , Almeida Maira P. , Lin Sichun , Kushida Michelle , Sureshkumar Haresh , Bhatti Jasmine K. , Lu Jack Q. , Schramek Daniel , Dirks Peter B. , Angers Stephane
Published: December 2024

normalized Bayes Factor scores, essentiality calls and subtype scores from GBM5K and TKOv3 screens
Supplementary data from Extracellular Vesicle–Packaged ACSL4 Induces Hepatocyte Senescence to Promote Hepatocellular Carcinoma Progression
Authors: Hou Pei-pei , Zheng Chong-ming , Wu Si-hong , Liu Xi-xiao , Xiang Guang-xin , Cai Wei-yang , Chen Gang , Lou Yong-liang
Published: December 2024

Supplementary materials and methods, supplementary figure legends, and supplementary table S1.
Table S2 from Fitness Screens Map State-Specific Glioblastoma Stem Cell Vulnerabilities
Authors: MacLeod Graham , Molaei Fatemeh , Haider Shahan , Almeida Maira P. , Lin Sichun , Kushida Michelle , Sureshkumar Haresh , Bhatti Jasmine K. , Lu Jack Q. , Schramek Daniel , Dirks Peter B. , Angers Stephane
Published: December 2024

Sequence of qPCR primers used in this study.
Figure S8 from B7-H3–Targeted CAR-Vδ1T Cells Exhibit Potent Broad-Spectrum Activity against Solid Tumors
Authors: Jiang Licui , You Fengtao , Wu Hai , Qi Changsong , Xiang Shufen , Zhang Ping , Meng Huimin , Wang Min , Huang Jiequn , Li Yafen , Chen Dan , An Gangli , Yang Nan , Zhang Bozhen , Shen Lin , Yang Lin
Published: December 2024

The supporting data of single-cell RNA sequencing between AQ-CAR-IL2-Vδ1T cells and AG-CAR-Vδ1T cells.
Figure S3 from B7-H3–Targeted CAR-Vδ1T Cells Exhibit Potent Broad-Spectrum Activity against Solid Tumors
Authors: Jiang Licui , You Fengtao , Wu Hai , Qi Changsong , Xiang Shufen , Zhang Ping , Meng Huimin , Wang Min , Huang Jiequn , Li Yafen , Chen Dan , An Gangli , Yang Nan , Zhang Bozhen , Shen Lin , Yang Lin
Published: December 2024

Functional comparison of various CAR structures carrying different cytokines in vitro
Supplementary figure 9 from Single-Cell Transcriptomic Analysis Identifies Senescent Osteocytes That Trigger Bone Destruction in Breast Cancer Metastasis
Authors: Kaur Japneet , Adhikari Manish , Sabol Hayley M. , Anloague Aric , Khan Sharmin , Kurihara Noriyoshi , Diaz-delCastillo Marta , Andreasen Christina Møller , Barnes Charles Lowry , Stambough Jeffrey B. , Palmieri Michela , Reyes-Castro Olivia , Zarrer Jennifer , Taipaleenmäki Hanna , Ambrogini Elena , Almeida Maria , O’Brien Charles A. , Nookaw Intawat , Delgado-Calle Jesus
Published: December 2024

Supplementary figure 9
Supplementary figure 8 from Single-Cell Transcriptomic Analysis Identifies Senescent Osteocytes That Trigger Bone Destruction in Breast Cancer Metastasis
Authors: Kaur Japneet , Adhikari Manish , Sabol Hayley M. , Anloague Aric , Khan Sharmin , Kurihara Noriyoshi , Diaz-delCastillo Marta , Andreasen Christina Møller , Barnes Charles Lowry , Stambough Jeffrey B. , Palmieri Michela , Reyes-Castro Olivia , Zarrer Jennifer , Taipaleenmäki Hanna , Ambrogini Elena , Almeida Maria , O’Brien Charles A. , Nookaw Intawat , Delgado-Calle Jesus
Published: December 2024

Supplementary figure 8
Supplementary figure 11 from Single-Cell Transcriptomic Analysis Identifies Senescent Osteocytes That Trigger Bone Destruction in Breast Cancer Metastasis
Authors: Kaur Japneet , Adhikari Manish , Sabol Hayley M. , Anloague Aric , Khan Sharmin , Kurihara Noriyoshi , Diaz-delCastillo Marta , Andreasen Christina Møller , Barnes Charles Lowry , Stambough Jeffrey B. , Palmieri Michela , Reyes-Castro Olivia , Zarrer Jennifer , Taipaleenmäki Hanna , Ambrogini Elena , Almeida Maria , O’Brien Charles A. , Nookaw Intawat , Delgado-Calle Jesus
Published: December 2024

Supplementary figure 11
Figure S7-10 and Table S1-2 from LTβR Agonism Promotes Antitumor Immune Responses via Modulation of the Tumor Microenvironment
Authors: An Disi , Chen Guoying , Cheng Wei-Yi , Mohrs Katja , Adler Christina , Gupta Namita T. , Atwal Gurinder S. , DiLillo David J. , Daly Christopher , Lin John C. , Kuhnert Frank
Published: December 2024

Supplementary Figure S7-10 and Table S1-2
Table S7 from Fitness Screens Map State-Specific Glioblastoma Stem Cell Vulnerabilities
Authors: MacLeod Graham , Molaei Fatemeh , Haider Shahan , Almeida Maira P. , Lin Sichun , Kushida Michelle , Sureshkumar Haresh , Bhatti Jasmine K. , Lu Jack Q. , Schramek Daniel , Dirks Peter B. , Angers Stephane
Published: December 2024

DESEQ2 analysis of control vs Ptk2 knockout mouse GBM tumor samples
Table S6 from Fitness Screens Map State-Specific Glioblastoma Stem Cell Vulnerabilities
Authors: MacLeod Graham , Molaei Fatemeh , Haider Shahan , Almeida Maira P. , Lin Sichun , Kushida Michelle , Sureshkumar Haresh , Bhatti Jasmine K. , Lu Jack Q. , Schramek Daniel , Dirks Peter B. , Angers Stephane
Published: December 2024

Normalized Bayes Factor Scores for GSC and GBM cell line screens
Table S5 from Fitness Screens Map State-Specific Glioblastoma Stem Cell Vulnerabilities
Authors: MacLeod Graham , Molaei Fatemeh , Haider Shahan , Almeida Maira P. , Lin Sichun , Kushida Michelle , Sureshkumar Haresh , Bhatti Jasmine K. , Lu Jack Q. , Schramek Daniel , Dirks Peter B. , Angers Stephane
Published: December 2024

qBF scores GSC screens vs Nonmalignant control screens
Table S3 from Fitness Screens Map State-Specific Glioblastoma Stem Cell Vulnerabilities
Authors: MacLeod Graham , Molaei Fatemeh , Haider Shahan , Almeida Maira P. , Lin Sichun , Kushida Michelle , Sureshkumar Haresh , Bhatti Jasmine K. , Lu Jack Q. , Schramek Daniel , Dirks Peter B. , Angers Stephane
Published: December 2024

GBM5K Library Composition. Gene list and Source for inclusion in library (see "Key" tab)
Data from Extracellular Vesicle–Packaged ACSL4 Induces Hepatocyte Senescence to Promote Hepatocellular Carcinoma Progression
Authors: Hou Pei-pei , Zheng Chong-ming , Wu Si-hong , Liu Xi-xiao , Xiang Guang-xin , Cai Wei-yang , Chen Gang , Lou Yong-liang
Published: December 2024

Abstract
Extracellular vesicles (EV) derived from cancer cells are crucial mediators of intercellular communication during tumor progression. The cargo in tumor-derived EVs that facilitates the establishment of a tumor-supportive microenvironment could serve as a therapeutic target to improve cancer treatment. Here, we demonstrated that hepatocellular carcinoma (HCC) cells secreted the acyl-CoA synthetase long-chain family member 4 (ACSL4) in large EVs (lEV) to modulate tumor–microenvironment interactions that promote HCC progression. HCC-derived lEV ACSL4 increased the intracellular abundance of polyunsaturated fatty acid–containing lipids and remodeled the lipid profile to potentiate lipid peroxidation in peritumoral hepatocytes, resulting in hepatocyte senescence accompanied by the senescence-associated secretory phenotype. Depletion of senescent hepatocytes by senolytic treatment suppressed tumor progression. In HCC cells, SREBP2-mediated transcriptional activation upregulated ACSL4 expression, and Akt-mediated phosphorylation of ACSL4 induced its packaging into lEVs by augmenting its interaction with Annexin A2. This study identified the critical regulatory function of ACSL4 secreted from HCC cells in inducing lipid remodeling and senescence in hepatocytes to support HCC progression, suggesting that targeting lEV ACSL4 is a potential therapeutic strategy for HCC.

Significance: Peritumoral hepatocyte senescence mediated by ACSL4 secreted from hepatocellular carcinoma cells in extracellular vesicles promotes tumor progression through a senescence secretome and represents a therapeutic target in liver cancer.
Supplementary Table S4 from Identification of High-Incidence Populations in the United States for Anti–Epstein-Barr Virus Serologic Screening for Nasopharyngeal Carcinoma
Authors: Clark Payton E. , Taparra Kekoa , Miller Jacob A.
Published: December 2024

Table S4. NPC Mortality Reduction and Cost-Effectiveness among Men for Serology-Based Screening Strategies (Once-Lifetime Screening). Data are reported for a hypothetical cohort of 50-year-old men who develop NPC in low, intermediate, or high-incidence populations under base case assumptions.
Supplementary Figure 1 from Identification of High-Incidence Populations in the United States for Anti–Epstein-Barr Virus Serologic Screening for Nasopharyngeal Carcinoma
Authors: Clark Payton E. , Taparra Kekoa , Miller Jacob A.
Published: December 2024

Supplementary Figure 1: Natural history Markov model of endemic nasopharyngeal carcinoma (NPC). Healthy adults could develop Epstein-Barr Virus-associated (EBV) stage I NPC and progress without detection to more advanced stages of undetected disease. This is the cohort of patients with prevalent undiagnosed NPC that can be screen-detected. Each undetected stage of NPC could present symptomatically or be detected by screening. A subset of healthy adults and those with each stage of preclinical NPC are biomarker positive or negative (for each of ten biomarker combinations). At the time of screening, participants who are biomarker positive (whether healthy or those with preclinical NPC) test positive and are found to be true positives or false positives. Similarly, participants who are biomarker negative are true negatives or false negatives. Each detected (incident) case of NPC is managed with radiotherapy and/or chemotherapy, and can either be cured or develop locoregional recurrence (LRR) or distant metastasis (DM) after treatment and die from their disease. Patients with stage IVC NPC receive chemotherapy until dying from their disease. In each state, there is also the risk of remaining within the same state or dying from other causes.
Supplementary Figure S2 from Racial, Ethnic, and Socioeconomic Disparities in Meeting Physical Activity Guidelines among Female Breast Cancer Survivors in the United States
Authors: Wojcik Kaitlyn M. , Wilson Oliver W.A. , Shiels Meredith S. , Sheppard Vanessa B. , Jayasekera Jinani
Published: December 2024

Supplementary Figure S2: Percentage of Breast Cancer Survivors Who Met Aerobic Guidelines and/or Muscle Strengthening Guidelines.
Supplementary Table S1 from High Gastric Cancer Mortality and Years of Life Lost in Nicaragua: A Population-Based Study 1997 to 2012
Authors: Peña-Galo Edgar M. , Palacios-Navarro Guillermo , Pastora-Membreño Javier , Torres-Herman Tatiana , Norwood Dalton A. , Montalvan-Sanchez Eleazar E. , Beasley Timothy , Bravo Luis E. , Morgan Douglas R.
Published: December 2024

Supplementary Table S1 illustrates the period rate ratios for gastric cancer mortality, detailing the rate ratio and its 95% confidence intervals across 5-year and year-by-year intervals, alongside the corresponding p-values indicating statistical significance.
Supplementary Table S1 from Social Determinants of Breast Cancer Screening: A Multilevel Analysis of Proximal and Distal Factors Related to the Practice of Mammography
Authors: Sarmiento Daiana Denis , Tumas Natalia , Pereyra Sofia Aynelen , Scruzzi Graciela Fabiana , Pou Sonia Alejandra
Published: December 2024

Supplementary Table S1 presents summary measures of the macro-contextual variables under study for 24 jurisdictions or provinces in Argentina during the period 2016 to 2018.
Supplementary Figure S1 from Social Determinants of Breast Cancer Screening: A Multilevel Analysis of Proximal and Distal Factors Related to the Practice of Mammography
Authors: Sarmiento Daiana Denis , Tumas Natalia , Pereyra Sofia Aynelen , Scruzzi Graciela Fabiana , Pou Sonia Alejandra
Published: December 2024

Supplementary Figure S1: this DAG visually depicts the key relationships among the variables selected as covariates (represented by white boxes) and the outcome (represented by the central grey box). At the distal level, the oval represents an unobserved dimension, with the variables connected by dotted arrows serving as proxy indicators. As illustrated, age, urban size, and the dimension of healthcare system quality are primary confounders in the complex pathways that may influence the timely practice of mammography in Argentina.
Supplemental Table 3 from Lifecourse Growth and Development Determinants of Mammographic Density in Black Women
Authors: Bigham Zahna , Holder Etienne X. , Rodday Angie Mae , Breeze Janis L. , Nelson Kerrie P. , Palmer Julie R. , Freund Karen M. , Bertrand Kimberly A.
Published: December 2024

Supplemental Table 3 shows linear regression analysis of growth and developmental factors with absolute measures of breast density, by age at mammogram.
Supplemental Table 2 from Lifecourse Growth and Development Determinants of Mammographic Density in Black Women
Authors: Bigham Zahna , Holder Etienne X. , Rodday Angie Mae , Breeze Janis L. , Nelson Kerrie P. , Palmer Julie R. , Freund Karen M. , Bertrand Kimberly A.
Published: December 2024

Supplemental Table 2 shows linear regression analysis of factors related to growth and development with mammographic density among current postmenopausal hormone therapy users
Supplementary Table S3 from High Incidence of Gastric Cancer in El Salvador: A National Multisectorial Study during 2000 to 2014
Authors: Ruiz de Campos Lisseth , Valdez de Cuellar Marisabel , Norwood Dalton A. , Carrasco Tiffany Y. , Montalvan-Sanchez Eleazar E. , Rodriguez Funes Maria-Virginia , Beasley Timothy , Dominguez Ricardo L. , Bravo Luis E. , Morgan Douglas R.
Published: December 2024

Supplementary Table S3 shows the detailed data availability for each type of contributing center by data source (Endoscopy, histology or endoscopy/histology).
Supplementary Table S2 from Population-Based Study of Gastric Cancer Survival and Associations in Rural Western Honduras
Authors: Dominguez Ricardo L. , Montalvan-Sanchez Eleazar E. , Norwood Dalton A. , Rodriguez-Murillo Aida , Dominguez Lucia , Estevez Ordoñez Dagoberto , Beasley Timothy , Bravo Luis E. , Morgan Douglas R.
Published: December 2024

Supplementary Table S2 reports the hazard ratios (HR) for various covariates in a gastric cancer survival study from Western Honduras. The crude hazard ratios (cHR) and adjusted hazard ratios (aHR) are presented alongside their respective 95% confidence intervals (CI) and p-values.
Supplementary Figure S1 from Population-Based Study of Gastric Cancer Survival and Associations in Rural Western Honduras
Authors: Dominguez Ricardo L. , Montalvan-Sanchez Eleazar E. , Norwood Dalton A. , Rodriguez-Murillo Aida , Dominguez Lucia , Estevez Ordoñez Dagoberto , Beasley Timothy , Bravo Luis E. , Morgan Douglas R.
Published: December 2024

Supplementary Figure S1 presents a series of plots assessing the proportionality assumption in a Cox proportional hazards model by examining the scaled Schoenfeld residuals plotted against time. Each plot corresponds to a different covariate included in the model. The residuals are displayed to investigate any systematic patterns that might suggest violations of the proportional hazards assumption. The lack of distinct trends or patterns across the series of plots supports the assumption's validity for the included covariates.
Supplementary Table 4 from Excess Mortality in Persons with Concurrent HIV and Cancer Diagnoses: A Retrospective Cohort Study
Authors: Lee Kamaria L. , Sarovar Varada , Lam Jennifer O. , Leyden Wendy A. , Alexeeff Stacey E. , Lea Alexandra N. , Hechter Rulin C. , Hu Haihong , Marcus Julia L. , Yuan Qing , Kramer Jennifer R. , Lin Lilie L. , Chiao Elizabeth Y. , Towner William J. , Horberg Michael A. , Silverberg Michael J.
Published: December 2024

Unadjusted and adjusted mortality rate differences and excess mortality rate for cancer groups, stratified by sex and race/ethnicity
Supplementary Table 1 from Excess Mortality in Persons with Concurrent HIV and Cancer Diagnoses: A Retrospective Cohort Study
Authors: Lee Kamaria L. , Sarovar Varada , Lam Jennifer O. , Leyden Wendy A. , Alexeeff Stacey E. , Lea Alexandra N. , Hechter Rulin C. , Hu Haihong , Marcus Julia L. , Yuan Qing , Kramer Jennifer R. , Lin Lilie L. , Chiao Elizabeth Y. , Towner William J. , Horberg Michael A. , Silverberg Michael J.
Published: December 2024

Number of prevalent and incident cancers by HIV status
Data from Racial, Ethnic, and Socioeconomic Disparities in Meeting Physical Activity Guidelines among Female Breast Cancer Survivors in the United States
Authors: Wojcik Kaitlyn M. , Wilson Oliver W.A. , Shiels Meredith S. , Sheppard Vanessa B. , Jayasekera Jinani
Published: December 2024

AbstractBackground:
Cancer survivors show low physical activity participation rates in the United States. However, there are limited national-level data on disparities in the prevalence of meeting physical activity guidelines among women with and without breast cancer. We aimed to evaluate national-level trends in meeting physical activity guidelines across demographic and socioeconomic characteristics of breast cancer survivors and women without cancer.
Methods:
Data for women ≥35 years of age with and without breast cancer were obtained from the 2004 to 2018 National Health Interview Survey. We used National Health Interview Survey sample weights to generate national-level prevalence estimates and calculate absolute and relative indices of disparity for breast cancer survivors and women without cancer meeting aerobic (150 minutes/week) and muscle-strengthening guidelines (2 sessions/week) stratified by demographic (e.g., race/ethnicity) and socioeconomic (e.g., homeownership) characteristics.
Results:
We included 5,845 breast cancer survivors and 160,162 women without cancer. The weighted percentage of breast cancer survivors meeting aerobic guidelines was 37.7% compared with 40.9% of women without cancer. Fewer women met muscle-strengthening guidelines. There were lower proportions of women who were younger (<50-years), were non-Hispanic Black, were Hispanic, worked 35+ hours/week, or rented their home among breast cancer survivors meeting aerobic guidelines compared with women without cancer meeting aerobic guidelines.
Conclusions:
Breast cancer survivors were less likely to meet physical activity guidelines compared with women without cancer. Demographic and socioeconomic disparities may exist among breast cancer survivors and women without cancer meeting physical activity guidelines.
Impact:
Targeted interventions may be necessary to address low physical activity participation among breast cancer survivors.
Data from The University of North Carolina Cancer Survivorship Cohort: A Resource for Collaborative Survivorship Research
Authors: Anderson Chelsea , Bensen Jeannette T. , Allott Emma H. , Basta Patricia V. , Irwin Debra E. , Gerstel Adrian , Farnan Laura , Tan Hung-Jui , Kent Erin E. , Kuo Tzy-Mey , Baggett Christopher D. , Olshan Andrew F. , Earp H. Shelton , Nichols Hazel B.
Published: December 2024

AbstractBackground:
Rapid growth in the number of US cancer survivors drives the need for ongoing research efforts to improve outcomes and experiences after cancer. In this study, we describe the University of North Carolina (UNC) Cancer Survivorship Cohort, a medical center–based cohort of adults with cancer that integrates medical record–abstracted cancer information, patient-reported outcomes, and biological specimens.
Methods:
Participants ages 18+ were recruited from UNC oncology clinics between April 2010 and August 2016. After enrollment, participants completed questionnaires on a range of topics including demographics, health history, healthcare access and utilization, quality of life, and symptoms. Blood samples and tumor tissue specimens were collected and processed by study staff, and cancer characteristics and other clinical data were abstracted from electronic medical records. Participants consented to recontact for future studies and linkage of their data with other data resources.
Results:
In total, 3,999 participants with a cancer diagnosis were enrolled in the cohort. The most common cancer types among those enrolled included breast (N = 866), uterine (N = 458), colorectal (N = 300), prostate (N = 296), and head and neck (N = 248) cancers. Blood specimens were collected for 3,027 participants (76%). Additional participants without cancer (N = 1,299) were also enrolled, and the majority (62%) provided biospecimen samples.
Conclusions:
We encourage a wide collaboration with investigators across institutions seeking to advance research in cancer survivorship. Procedures are in place to support proposals for use of existing or linked data and for proposals that require participant recontact or analysis of biospecimens.
Impact:
The UNC Cancer Survivorship Cohort is a unique resource for cancer survivorship research.
Data from Social Determinants of Breast Cancer Screening: A Multilevel Analysis of Proximal and Distal Factors Related to the Practice of Mammography
Authors: Sarmiento Daiana Denis , Tumas Natalia , Pereyra Sofia Aynelen , Scruzzi Graciela Fabiana , Pou Sonia Alejandra
Published: December 2024

AbstractBackground:
Mammography is crucial for early breast cancer detection. In Latin America, Argentina faces a significant breast cancer burden, with varying mammography rates. The social factors influencing mammography practices remain unclear. This study aimed to identify the proximal and distal social determinants of this practice among Argentinean women using a multilevel approach.
Methods:
This nationwide cross-sectional study included 4,924 women, ages 50 to 70, participating in the 2018 National Risk Factor Survey of Argentina. Two-level logistic models were used to estimate measures of association (ORs) between timely mammography practice (within the last 2 years) and selected covariates (sociodemographics, proximal environment, and distal-level variables). The intraclass correlation coefficient and proportional change in variance were calculated.
Results:
Of the total participants, 62.8% of women underwent timely mammography. Age [OR = 0.96; 95% confidence interval (CI), 0.94–0.97], health insurance (OR = 2.22; 95% CI, 1.87–2.63), education (OR = 2.1; 95% CI, 1.74–2.64), and income (OR = 1.56; 95% CI, 1.23–1.97) were associated with mammography practice. Women in nonmarital (OR = 0.61; 95% CI, 0.52–0.72) or larger households (OR = 0.61; 95% CI, 0.51–0.63) were less likely to have timely mammography; living in a larger city was positively associated with timely mammography (OR = 1.28; 95% CI, 1.12–1.46). Women in provinces with higher physician density (OR = 1.06; 95% CI, 1.01–1.11) and lower maternal mortality ratio (OR = 0.9; 95% CI, 0.87–0.96) had higher chances of timely mammography. The intraclass correlation coefficient and proportional change in variance suggested that the explored healthcare indicators largely explained the macro-contextual effect.
Conclusions:
Multilevel factors influenced mammography practices in Argentina. The results highlight disparities linked to sociodemographic characteristics and healthcare resources.
Impact:
Efforts to address social inequalities in breast cancer screening must consider multilevel determinants, including in healthcare settings.
Data from Lifecourse Growth and Development Determinants of Mammographic Density in Black Women
Authors: Bigham Zahna , Holder Etienne X. , Rodday Angie Mae , Breeze Janis L. , Nelson Kerrie P. , Palmer Julie R. , Freund Karen M. , Bertrand Kimberly A.
Published: December 2024

AbstractBackground:
High mammographic density is one of the strongest breast cancer risk factors; however, determinants of high mammographic density are understudied in Black women. We assessed growth and development factors across the lifecourse in relation to mammographic density.
Methods:
Within the Black Women’s Health Study, we used Cumulus software to assess percent mammographic density from digital screening mammograms for 5,905 women ages 40 to 74 years. We fit linear regression models to quantify the association of lifecourse characteristics including birthweight, childhood somatotype, age at menarche, body mass index (BMI) at age 18 years, height, BMI at mammography, and adulthood waist-to-hip ratio with density overall and by age. We also performed a path analysis to assess the total and mediating effects of the growth and development factors on density.
Results:
BMI at age 18 years, height, BMI at mammography, and waist-to-hip ratio were significantly and inversely associated with density. On path analysis, total effects of childhood somatotype (standardized β = −0.05, P < 0.001), BMI at age 18 years (standardized β = −0.13, P < 0.001), BMI at mammography (standardized β = −0.22, P < 0.001), and waist-to-hip ratio (standardized β = −0.04, P < 0.001) were associated with density.
Conclusions:
Several factors across the lifecourse—greater childhood somatotype, BMI at age 18 years, height, BMI at mammography, and waist-to-hip ratio—were associated with lower mammographic density in this cohort of Black women.
Impact:
Body size closer to the time of mammography may be more meaningful in determining mammographic density, though early-life adiposity also influences mammographic density.

See related In the Spotlight, p. 1541
Supplementary Table 5 from Nivolumab in Patients with Metastatic Castration-Resistant Prostate Cancer with and without DNA Repair Defects
Authors: Isaacsson Velho Pedro , Bastos Diogo Assed , Saint’ana Pedro Tofani , Rigatti Brenda , da Costa Emily Tonin , Muniz David Q.B. , Andreis Felipe , Ferreira Rafael Dal Ponte , Giongo Pedrotti Luana , Maistro Simone , Katayama Maria Lucia Hirata , Folgueira Maria Aparecida Azevedo Koike , Morelle Alessandra , Leal Alessandro , de Castro Gilberto
Published: December 2024

Supplementary Table 5: Detailed description of adverse events (n = 38).
Supplementary Table 4 from Nivolumab in Patients with Metastatic Castration-Resistant Prostate Cancer with and without DNA Repair Defects
Authors: Isaacsson Velho Pedro , Bastos Diogo Assed , Saint’ana Pedro Tofani , Rigatti Brenda , da Costa Emily Tonin , Muniz David Q.B. , Andreis Felipe , Ferreira Rafael Dal Ponte , Giongo Pedrotti Luana , Maistro Simone , Katayama Maria Lucia Hirata , Folgueira Maria Aparecida Azevedo Koike , Morelle Alessandra , Leal Alessandro , de Castro Gilberto
Published: December 2024

Supplementary Table 4: List of oncogenic or likely oncogenic mutations found in patients.
Supplementary Table 1 from Nivolumab in Patients with Metastatic Castration-Resistant Prostate Cancer with and without DNA Repair Defects
Authors: Isaacsson Velho Pedro , Bastos Diogo Assed , Saint’ana Pedro Tofani , Rigatti Brenda , da Costa Emily Tonin , Muniz David Q.B. , Andreis Felipe , Ferreira Rafael Dal Ponte , Giongo Pedrotti Luana , Maistro Simone , Katayama Maria Lucia Hirata , Folgueira Maria Aparecida Azevedo Koike , Morelle Alessandra , Leal Alessandro , de Castro Gilberto
Published: December 2024

Supplementary Table 1: 53-gene ctDNA panel. In grey, genes involved in DNA repair by any mechanism.
Supplementary Figure 4C from Nivolumab in Patients with Metastatic Castration-Resistant Prostate Cancer with and without DNA Repair Defects
Authors: Isaacsson Velho Pedro , Bastos Diogo Assed , Saint’ana Pedro Tofani , Rigatti Brenda , da Costa Emily Tonin , Muniz David Q.B. , Andreis Felipe , Ferreira Rafael Dal Ponte , Giongo Pedrotti Luana , Maistro Simone , Katayama Maria Lucia Hirata , Folgueira Maria Aparecida Azevedo Koike , Morelle Alessandra , Leal Alessandro , de Castro Gilberto
Published: December 2024

Supplementary Figure 4C: KM curve of OS in patients with and without PD-L1 expression.
Supplementary Figure 4A from Nivolumab in Patients with Metastatic Castration-Resistant Prostate Cancer with and without DNA Repair Defects
Authors: Isaacsson Velho Pedro , Bastos Diogo Assed , Saint’ana Pedro Tofani , Rigatti Brenda , da Costa Emily Tonin , Muniz David Q.B. , Andreis Felipe , Ferreira Rafael Dal Ponte , Giongo Pedrotti Luana , Maistro Simone , Katayama Maria Lucia Hirata , Folgueira Maria Aparecida Azevedo Koike , Morelle Alessandra , Leal Alessandro , de Castro Gilberto
Published: December 2024

Supplementary Figure 4A: KM curve of PSA-PFS in patients with and without PD-L1 expression.
Figure S3 from Characterization of FGFR Alterations and Activation in Patients with High-Risk Non–Muscle-Invasive Bladder Cancer
Authors: Eisner Joel R. , de Jong Florus C. , Shibata Yoichiro , Mayhew Gregory M. , Davison James M. , Carcione Jenna , Pappan Kirk L. , Thomas Shibu , Triantos Spyros , Santiago-Walker Ademi , Baig Mahadi , Milburn Michael V. , Beebe Kirk D. , Zuiverloon Tahlita C.M.
Published: December 2024

Figure S3
Supplementary Figure 2A from Nivolumab in Patients with Metastatic Castration-Resistant Prostate Cancer with and without DNA Repair Defects
Authors: Isaacsson Velho Pedro , Bastos Diogo Assed , Saint’ana Pedro Tofani , Rigatti Brenda , da Costa Emily Tonin , Muniz David Q.B. , Andreis Felipe , Ferreira Rafael Dal Ponte , Giongo Pedrotti Luana , Maistro Simone , Katayama Maria Lucia Hirata , Folgueira Maria Aparecida Azevedo Koike , Morelle Alessandra , Leal Alessandro , de Castro Gilberto
Published: December 2024

Supplementary Figure 2A: KM curve of PSA-PFS by TMB
Supplementary Table S3 from Synthetic Lethal Targeting of CDK12-Deficient Prostate Cancer with PARP Inhibitors
Authors: Chou Jonathan , Robinson Troy M. , Egusa Emily A. , Lodha Roshan , Zhang Meng , Badura Michelle , Mikayelyan Mane , Delavan Henry M. , Swinderman Jason , Wilson Chris , Zhu Jun , Das Rajdeep , Nguyen Minh , Loehr Andrea , Golsorkhi Tony , Simmons Andrew , Abida Wassim , Chinnaiyan Arul M. , Arkin Michelle R. , Small Eric J. , Quigley David A. , Yang Lixing , Kim Minkyu , Ashworth Alan , Feng Felix Y.
Published: December 2024

List of primers and oligonucleotides used for generating CDK12, CDK13, and CCNK KOs and CRISPRi knockdowns, and primers used for quantitative PCR (QPCR).
Supplementary Table S2 from Synthetic Lethal Targeting of CDK12-Deficient Prostate Cancer with PARP Inhibitors
Authors: Chou Jonathan , Robinson Troy M. , Egusa Emily A. , Lodha Roshan , Zhang Meng , Badura Michelle , Mikayelyan Mane , Delavan Henry M. , Swinderman Jason , Wilson Chris , Zhu Jun , Das Rajdeep , Nguyen Minh , Loehr Andrea , Golsorkhi Tony , Simmons Andrew , Abida Wassim , Chinnaiyan Arul M. , Arkin Michelle R. , Small Eric J. , Quigley David A. , Yang Lixing , Kim Minkyu , Ashworth Alan , Feng Felix Y.
Published: December 2024

List of CDK12 mutations in the “CDK12 mutated” patient cohort treated on the TRITON2 study. The exact mutation in allele 1 and allele 2 are indicated, along with the best PSA percent change from baseline. LOH indicates loss of heterozygosity, as inferred based on allele frequency of the detected mutated allele and absence of wildtype reads from the wildtype allele. Green denotes a decrease from baseline. Red denotes an increase from baseline.
Figure S1 from A Preoperative Window-of-Opportunity Study of Oral SERD, Imlunestrant, in Newly Diagnosed ER-Positive, HER2-Negative Early Breast Cancer: Results from the EMBER-2 Study
Authors: Neven Patrick , Stahl Nicole , Vidal Maria , Martín Miguel , Kaufman Peter A. , Harbeck Nadia , Hunt Kelly K. , Carter Stacey , Bidard Francois-Clement , Fasching Peter A. , Aftimos Philippe , Wheatley Duncan , Hamilton Erika , Aft Rebecca , Kulkarni Swati , Schmid Peter , Bhave Manali , Ismail-Khan Roohi , Karacsonyi Claudia , Estrem Shawn T. , Nguyen Bastien , Ozbek Umut , Yuen Eunice , Rodrik-Outmezguine Vanessa , Ciruelos Eva
Published: December 2024

Plasma imlunestrant concentrations at visit 2
Supplementary Table S9 from Determination of MYD88 and CXCR4 Mutations for Clinical Detection and Their Significance in Waldenström Macroglobulinemia
Authors: Yan Yuting , Yu Ying , Xiong Wenjie , Wang Jun , Yao Yao , Jia Yujiao , Huang Yanshan , Li Yuxi , Wang Tingyu , Lyu Rui , Sun Hao , Wang Haoxu , Wang Qi , Liu Wei , An Gang , Sui Weiwei , Xu Yan , Huang Wenyang , Yu Zhen , Zou Dehui , Hao Mu , Xiao Zhijian , Wang Jianxiang , Qiu Lugui , Yi Shuhua
Published: December 2024

Supplementary Table 9. The response rate by MYD88/CXCR4 genotype during first-line Rituximab/Bortezomib-based therapy.
Supplementary Figure S9 from Combinations of HDAC Inhibitor and PPAR Agonist Induce Ferroptosis of Leukemic Stem Cell–like Cells in Acute Myeloid Leukemia
Authors: Zhou Hui , Qin Dongmei , Xie Chendi , Zhou Jie , Jia Shuman , Zhou Ziwei , Qiu Yi , Xu Bing , Zha Jie
Published: December 2024

Supplementary Figure S9. (A-B) Representative data for flow cytometric analysis of mCD45/hCD34 staining in the spleen (A) and bone marrow (B). (C) Flow cytometry analysis of human CD34+ AML cells sorted from bone marrow of PDX#1 and PDX#2 mice by human CD34 Nanobeads.
Supplementary Figure S8 from Determination of MYD88 and CXCR4 Mutations for Clinical Detection and Their Significance in Waldenström Macroglobulinemia
Authors: Yan Yuting , Yu Ying , Xiong Wenjie , Wang Jun , Yao Yao , Jia Yujiao , Huang Yanshan , Li Yuxi , Wang Tingyu , Lyu Rui , Sun Hao , Wang Haoxu , Wang Qi , Liu Wei , An Gang , Sui Weiwei , Xu Yan , Huang Wenyang , Yu Zhen , Zou Dehui , Hao Mu , Xiao Zhijian , Wang Jianxiang , Qiu Lugui , Yi Shuhua
Published: December 2024

Supplementary Figure 8. The survival outcomes of patients with MYD88/CXCR4 mutation status according to the option of different first-line therapies. The progression free survival and overall survival in patients with cytotoxic therapy (A-B); in patients with Rtuximab/bortezomib-based therapy; (C-D); and in patients with BTKi-based therapy (E-F). *P < 0.05, **P < 0.01, ***P < 0.001.
Supplementary Figure S7 from Determination of MYD88 and CXCR4 Mutations for Clinical Detection and Their Significance in Waldenström Macroglobulinemia
Authors: Yan Yuting , Yu Ying , Xiong Wenjie , Wang Jun , Yao Yao , Jia Yujiao , Huang Yanshan , Li Yuxi , Wang Tingyu , Lyu Rui , Sun Hao , Wang Haoxu , Wang Qi , Liu Wei , An Gang , Sui Weiwei , Xu Yan , Huang Wenyang , Yu Zhen , Zou Dehui , Hao Mu , Xiao Zhijian , Wang Jianxiang , Qiu Lugui , Yi Shuhua
Published: December 2024

Supplementary Figure 7. The survival outcomes of patients with different CXCR4 mutation subtypes, mutation sites and clonality. The progression free survival (A) and overall survival (B) in patients of different CXCR4 mutation types; The progression free survival (C) and overall survival (D) in patients with different amino acid sites of CXCR4 mutations; The progression free survival (E) and overall survival (F) according to the clonality of CXCR4 mutations
Supplementary Figure 1 from Multidimensional Immunotyping of Human NF1-Associated Peripheral Nerve Sheath Tumors Uncovers Tumor-Associated Macrophages as Key Drivers of Immune Evasion in the Tumor Microenvironment
Authors: Zhang Lindy , Maalouf Alexandre , Makri Stavriani C. , Banerjee Jineta , Suru Aditya , Tam Ada J. , Calizo Ana , Pollard Kai , Wang Jiawan , Danilova Ludmila , Ioannou Maria , Levin Adam S. , Morris Carol D. , Rhee Daniel S. , Belzberg Allan J. , Blakeley Jaishri O. , Ladle Brian H. , Pardoll Drew M. , Lucas Calixto-Hope G. , Rodriguez Fausto J. , Gross John M. , Anders Robert A. , Pratilas Christine A. , Llosa Nicolas J.
Published: December 2024

Supplementary Figure 1
Table S3. Met alterations3 from Safety, Efficacy, and Biomarker Analysis of Crizotinib in MET-Mutated Non–Small Cell Lung Cancer—Results from the Drug Rediscovery Protocol
Authors: Verkerk Karlijn , van der Wel Tijmen J.W.T. , Zeverijn Laurien J. , Geurts Birgit S. , Spiekman Ilse A.C. , de Wit Gijs F. , Roepman Paul , Jansen Anne M.L. , van der Noort Vincent , Smit Egbert F. , Hoeben Ann , Hendriks Lizza E.L. , van den Heuvel Michel M. , Piet Berber , Herder Gerarda J.M. , Hashemi Sayed M.S. , Gelderblom Hans , Verheul Henk M.W. , Voest Emile E. , de Langen Adrianus J.
Published: December 2024

Type of Met alterations found by both inclusion diagnostics and WGS. Variants annotated according to the NM_000245 (MANE transcript). Abbreviations: NGS, next generation sequencing; PCR, polymerase chain reaction; WGS, whole genome sequencing.
Supplementary Table S7 from Botensilimab, an Fc-Enhanced Anti–CTLA-4 Antibody, Is Effective against Tumors Poorly Responsive to Conventional Immunotherapy
Authors: Chand Dhan , Savitsky David A. , Krishnan Shanmugarajan , Mednick Gabriel , Delepine Chloe , Garcia-Broncano Pilar , Soh Kah Teong , Wu Wei , Wilkens Margaret K. , Udartseva Olga , Vincent Sylvia , Joshi Bishnu , Keith Justin G. , Manrique Mariana , Marques Marilyn , Tanne Antoine , Levey Daniel L. , Han Haiyong , Ng Serina , Ridpath Jackson , Huber Olivia , Morin Benjamin , Galand Claire , Bourdelais Sean , Gombos Randi B. , Ward Rebecca , Qin Yu , Waight Jeremy D. , Costa Matthew R. , Sebastian-Yague Alvaro , Rudqvist Nils-Petter , Pupecka-Swider Malgorzata , Venkatraman Vignesh , Slee Andrew , Patel Jaymin M. , Grossman Joseph E. , Wilson Nicholas S. , Von Hoff Daniel D. , Stebbing Justin , Curiel Tyler J. , Buell Jennifer S. , O’Day Steven J. , Stein Robert B.
Published: December 2024

This dataset summarizes the clinical response and disease control rates of patients with advanced solid tumors treated in the ongoing phase 1 trial of botensilimab. These efficacy measures are crucial for assessing the therapeutic potential of botensilimab alone and in combination with balstilimab. Importantly, these data further highlight the therapeutic potential in patients who have progressed on prior immune checkpoint therapy, providing valuable insights into botensilimab's efficacy in this challenging-to-treat population.