bluuebunny/crossref_metadata_2025 huggingface dataset:
RGMU: A High-flexibility and Low-cost Reconfigurable Galois Field Multiplication Unit Design Approach for CGRCA
Authors: Jiang Danping , Dai Zibin , Liu Yanjiang , Zhang Zongren
Published: January 2024

Finite field multiplication is a non-linear transformation operator that appears in the majority of symmetric cryptographic algorithms. Numerous specified finite field multiplication units have been proposed as a fundamental module in the coarse-grained reconfigurable cipher logic array to support more cryptographic algorithms; however, it will introduce low flexibility and high overhead, resulting in reduced performance of the coarse-grained reconfigurable cipher logic array. In this article, a high-flexibility and low-cost reconfigurable Galois field multiplication unit (RGMU) is proposed to balance the tradeoffs between the function, delay, and area. All the finite field multiplication operations, including maximum distance separable matrix multiplication, parallel update of Fibonacci linear feedback shift register, parallel update of Galois linear feedback shift register, and composite field multiplication, are analyzed and two basic operation components are abstracted. Further, a reconfigurable finite field multiplication computational model is established to demonstrate the efficacy of reconfigurable units and guide the design of RGMU with high performance. Finally, the overall architecture of RGMU and two multiplication circuits are introduced. Experimental results show that the RGMU can not only reduce the hardware overhead and power consumption but also has the unique advantage of satisfying all the finite field multiplication operations in symmetric cryptography algorithms.
Hemoptysis and Unilateral Pulmonary Infiltrates due to Severe Acute Mitral Regurgitation from Papillary Muscle Rupture
Authors: Wieckowska Joanna , Diloreto Nicholas , Hood Shannon , Chojnacki Isabella , Zakri Dalia
Published: January 2024

Acute mitral regurgitation typically presents with dyspnea, chest pain, and hemodynamic instability. It is an uncommon cause of hemoptysis. We present a case of a patient presenting with dyspnea and hemoptysis without hemodynamic instability along with right-sided infiltrate on chest radiography a few days after an acute inferolateral STEMI who was found to have posterior papillary muscle rupture resulting in acute mitral regurgitation. Our case illustrates that the aforementioned symptoms and signs should raise concern for acute mitral regurgitation and prompt cardiac evaluation in the appropriate clinical setting as they may mimic acute pulmonary processes and delay critical diagnosis and treatment.
Prevalence of Esophageal Eosinophilia, Eosinophilic Esophagitis, and Lymphocytic Gastritis in Children with Celiac Disease: A Saudi Tertiary Center Experience
Authors: Alaifan Meshari A. , Khayat Ammar , Bokhary Rana Y. , Ibrahim Abdulhameed , Bin-Taleb Yagoub , Alhussaini Bakr H. , Saadah Omar I.
Published: January 2024

Background. Celiac disease (CD) is an immune-mediated enteropathy that has been associated with other immune-related gastrointestinal disorders, such as eosinophilic esophagitis (EoE) and lymphocytic gastritis (LG). To our knowledge, this is the first study in Saudi Arabia that has described such an association. Aim. To evaluate the prevalence of EoE and LG in children and adolescents with CD. Methods. This was a retrospective cross-sectional study of all pediatric patients (aged 0–18 years) with CD following up at King Abdulaziz University Hospital, between January, 2014, and December, 2021. The study examined clinical, demographic, endoscopic, and histopathological data. Results. Seventy-five patients with CD were included in the analysis. The median age was 12 years (range, 2–18 years). Male constituted 54.7% of the overall cohort (n = 41). The most common clinical symptoms were short stature (54.7%), weight loss (34.7%), abdominal pain (33.3%), abdominal distension (29.3%), anorexia (29.3%), diarrhea (24%), and vomiting (21.3%). The esophageal biopsy results reported were basal cell hyperplasia in 24 patients (32.9%), esophageal eosinophilia in 23 patients (31.5%), and EoE in 3 patients (4.1%). The gastric biopsy results were normal in 40 patients (53.3%). The most common abnormality was chronic inactive gastritis with no Helicobacter pylori (HP) infection (16%). LG was found in 3 patients (4%). Conclusions. The prevalence of EoE in this cohort of patients with CD was lower than the prevalence recorded in a number of other studies. Further studies are needed to determine the effects of a gluten-free diet (GFD) on EOE and LG.
Chronic Appendicitis: Possible Differential Diagnosis in Patients with Chronic Abdominal Pain
Authors: Ljubas Iva , Jurca Ivana , Grgić Dora
Published: January 2024

In the emergency department, patients frequently present with abdominal pain, with a variety of different causes ranging from intra‐abdominal to extra‐abdominal and retroperitoneal pathologies which can affect all age groups. Chronic appendicitis is a rare medical condition characterized by less severe and continuous abdominal pain and a clinical picture lasting longer than 1‐2 days and extending over months, even years, and it is not always possible to consider it as a preliminary diagnosis. We represent a case report of chronic appendicitis where the patient’s clinical picture led the diagnostics and treatment in different directions and delayed the diagnosis. Namely, our patient was radiologically diagnosed with a collection of denser content retroperitoneally in the right lower quadrant of the abdomen, which in the first place was not related to possible appendicitis, regarding complaints. The existence of chronic appendicitis is a diagnosis unfamiliar to many clinicians and has no official diagnostic criteria. After diagnosis, treatment usually begins with antibiotics, and the next most common step is surgery. The optimal treatment for this condition is unknown. With this case report, we wish to draw attention to chronic appendicitis as a possible differential diagnosis in patients with chronic abdominal pain.
Spatial and Seasonal Patterns of Tick Infestations in Kassena‐Nankana Livestock
Authors: Offei Addo Seth , Essah Bentil Ronald , Olivia Ama Baako Bernice , Ansah-Owusu Jane , Nii Laryea Tawiah-Mensah Christopher , Behene Eric , Asoala Victor , Dunford James C. , Asiedu Larbi John , Kweku Baidoo Philip , David Wilson Michael , Diclaro Joseph W. , Dadzie Samuel K.
Published: January 2024

The ability of ticks to adapt to different ecological zones, coupled with the spread of infectious pathogens negatively affects livestock production and thus, there is a need for better control strategies. However, control measures within a geographical region can only be effective if there is available information on tick population dynamics and ecology. This study focused on ticks infesting livestock in the Kassena‐Nankana Districts of the Upper East Region of Ghana. The ticks were morphologically identified, variables such as season, animal host, and predilection sites were recorded, and the data were analyzed using STATA version 13. Out of 448 livestock examined, tick infestation in cattle was (78.60%), followed by sheep (25%) and goats (5.88%). A total of 1,550 ticks including nymphs (303) and adults (1,247) were collected. Adult ticks were found to be significantly associated with season (p < 0.001), with a high burden in the wet season. The nymph burden and body parts of livestock hosts were significantly associated with more nymphs collected from male animals than females (p < 0.001). Three genera of ticks, Amblyomma (62.97%), Hyalomma (18.71%), and Rhipicephalus (18.32%) were morphologically identified with the most predominant tick species recorded as Amblyomma variegatum (62.97%). Matured A. variegatum was sampled primarily in the wet season with their predilection site as the udder/scrotum (p < 0.001). However, adult Hyalomma truncatum was observed to have a significant association with the anal region (p < 0.001). Findings from this study are essential for formulating tick control measures to prevent the spread of infectious pathogens.
Table S2 from Direct Medical Spending on Young and Average-Age Onset Colorectal Cancer before and after Diagnosis: a Population-Based Costing Study
Authors: Garg Ria , Sayre Eric C. , Pataky Reka , McTaggart-Cowan Helen , Peacock Stuart , Loree Jonathan M. , McKenzie Michael , Brown Carl J. , Yeung Shirley S.T. , De Vera Mary A.
Published: January 2024

Unit Cost Price List for Publicly Funded Cancer therapy Agents
Supplementary Table 5 from Incident Cardiovascular Disease Risk among Older Asian, Native Hawaiian and Pacific Islander Breast Cancer Survivors
Authors: Hashibe Mia , Wei Mei , Lee Catherine J. , Tao Randa , Koric Alzina , Wang Jing , Daud Anees , Tay Djin , Shen Jincheng , Lee Yuan-chin A. , Chang Chun-Pin E.
Published: January 2024

This table shows the percentage of breast cancer patients in ANHPI groupings who were diagnosed with CVD outcomes, by age group
Supplementary Table 4 from Incident Cardiovascular Disease Risk among Older Asian, Native Hawaiian and Pacific Islander Breast Cancer Survivors
Authors: Hashibe Mia , Wei Mei , Lee Catherine J. , Tao Randa , Koric Alzina , Wang Jing , Daud Anees , Tay Djin , Shen Jincheng , Lee Yuan-chin A. , Chang Chun-Pin E.
Published: January 2024

This table shows the number of incident CVD diagnosed after cancer diagnosis, stratified by follow up period
Supplementary Table 8 from Male-Pattern Vertex Baldness Trajectories, Chest Hair Patterns, and Odds of Overall and Aggressive Prostate Cancer
Authors: Salmon Charlotte , Mesidor Miceline , Rousseau Marie-Claude , Richard Hugues , Weiss Deborah , Spence Andrea R. , Parent Marie-Elise
Published: January 2024

Supplementary Table 8. Association between baldness trajectories and odds of prostate cancer, according to cancer aggressiveness (Gleason score <8, Gleason score ≥ 8), Prostate Cancer & Environment Study, Montreal, Canada, 2005–2012
Supplementary Table 5 from Male-Pattern Vertex Baldness Trajectories, Chest Hair Patterns, and Odds of Overall and Aggressive Prostate Cancer
Authors: Salmon Charlotte , Mesidor Miceline , Rousseau Marie-Claude , Richard Hugues , Weiss Deborah , Spence Andrea R. , Parent Marie-Elise
Published: January 2024

Supplementary Table 5. Association between vertex baldness trajectories and odds of prostate cancer, overall and by cancer aggressiveness, after restricting to participants who had been screened for prostate cancer in the 2 years preceding the index date, Prostate Cancer & Environment Study, Montreal, Canada, 2005–2012
Supplementary Figure 3 from Incident Cardiovascular Disease Risk among Older Asian, Native Hawaiian and Pacific Islander Breast Cancer Survivors
Authors: Hashibe Mia , Wei Mei , Lee Catherine J. , Tao Randa , Koric Alzina , Wang Jing , Daud Anees , Tay Djin , Shen Jincheng , Lee Yuan-chin A. , Chang Chun-Pin E.
Published: January 2024

Supplementary Figure 3 shows the clinical characteristics of ANHPI subgroups of older breast cancer patients and older NHW breast cancer patients in SEER Medicare.
Supplementary Table 4 from Male-Pattern Vertex Baldness Trajectories, Chest Hair Patterns, and Odds of Overall and Aggressive Prostate Cancer
Authors: Salmon Charlotte , Mesidor Miceline , Rousseau Marie-Claude , Richard Hugues , Weiss Deborah , Spence Andrea R. , Parent Marie-Elise
Published: January 2024

Supplementary Table 4. Association between joint exposure of baldness and chest hair amount, and odds of prostate cancer, overall and by cancer aggressiveness, after restricting to participants who had been screened for prostate cancer in the 2 years preceding the index date, Prostate Cancer & Environment Study, Montreal, Canada, 2005–2012
Supplementary Figure 2 from Incident Cardiovascular Disease Risk among Older Asian, Native Hawaiian and Pacific Islander Breast Cancer Survivors
Authors: Hashibe Mia , Wei Mei , Lee Catherine J. , Tao Randa , Koric Alzina , Wang Jing , Daud Anees , Tay Djin , Shen Jincheng , Lee Yuan-chin A. , Chang Chun-Pin E.
Published: January 2024

Supplementary Figure 2 shows the characteristics of ANHPI subgroups of older breast cancer patients and older NHW breast cancer patients in SEER-Medicare. (Highest education = census tract <5% non high school grads; highest income = census tract income $90,000+; highest SES = census tract Yost Index Quintile 5)
Supplementary Figure 1 from Incident Cardiovascular Disease Risk among Older Asian, Native Hawaiian and Pacific Islander Breast Cancer Survivors
Authors: Hashibe Mia , Wei Mei , Lee Catherine J. , Tao Randa , Koric Alzina , Wang Jing , Daud Anees , Tay Djin , Shen Jincheng , Lee Yuan-chin A. , Chang Chun-Pin E.
Published: January 2024

Supplementary Figure 1 shows the exclusion criteria and the number of patients excluded due to the criteria for the ANHPI and NHW breast cancer cohort in SEER-Medicare
Table S8 from Investigating Causal Effects of Hematologic Traits on Lung Cancer: A Mendelian Randomization Study
Authors: Yang Zhanghuan , He Hao , He Guangxu , Zeng Chudai , Hu Qian
Published: January 2024

Causal Effects of Identified Traits in Lung Cancer in Ever/Never Smokers Estimated via Seven Methods for Each Association
Supplementary Figure 3 from Male-Pattern Vertex Baldness Trajectories, Chest Hair Patterns, and Odds of Overall and Aggressive Prostate Cancer
Authors: Salmon Charlotte , Mesidor Miceline , Rousseau Marie-Claude , Richard Hugues , Weiss Deborah , Spence Andrea R. , Parent Marie-Elise
Published: January 2024

Supplementary Figure 3. Vertex baldness severity trajectories, using controls only, Prostate Cancer & Environment Study, Montreal, Canada, 2005–2012.
Figure shows results from the group-based trajectory modeling of the changes in the degree of baldness severity over time, from age 30 to 70, using the control population only. Letters A to H represent increasing vertex baldness severity levels, with A and B indicative of no baldness.
Supplementary Figure 1 from Male-Pattern Vertex Baldness Trajectories, Chest Hair Patterns, and Odds of Overall and Aggressive Prostate Cancer
Authors: Salmon Charlotte , Mesidor Miceline , Rousseau Marie-Claude , Richard Hugues , Weiss Deborah , Spence Andrea R. , Parent Marie-Elise
Published: January 2024

Supplementary Figure 1. Directed acyclic graph of the association between male pattern baldness and prostate cancer.
In green, variables of interest. In orange, potential confounding factors.
Table S2 from Investigating Causal Effects of Hematologic Traits on Lung Cancer: A Mendelian Randomization Study
Authors: Yang Zhanghuan , He Hao , He Guangxu , Zeng Chudai , Hu Qian
Published: January 2024

Description of Hematological Traits Evaluated in This MR Analysis
Supplementary Table 3 from Abbreviated Score to Assess Adherence to the 2018 WCRF/AICR Cancer Prevention Recommendations and Risk of Cancer in the UK Biobank
Authors: Malcomson Fiona C. , Parra-Soto Solange , Ho Frederick K. , Celis-Morales Carlos , Sharp Linda , Mathers John C.
Published: January 2024

Associations between abbreviated score and risk of all cancers combined and of cancer at individual anatomical sites, stratified according to smoking status
Table S16 from Investigating Causal Effects of Hematologic Traits on Lung Cancer: A Mendelian Randomization Study
Authors: Yang Zhanghuan , He Hao , He Guangxu , Zeng Chudai , Hu Qian
Published: January 2024

Heterogeneity Test and Pleiotropy Test for Association With FDR < 0.1 in Subgroup Analysis
Supplementary Table 2 from Abbreviated Score to Assess Adherence to the 2018 WCRF/AICR Cancer Prevention Recommendations and Risk of Cancer in the UK Biobank
Authors: Malcomson Fiona C. , Parra-Soto Solange , Ho Frederick K. , Celis-Morales Carlos , Sharp Linda , Mathers John C.
Published: January 2024

Comparisons of number of participants and incident cancer cases between previous analyses with total score and present analyses with abbreviated score
Table S13 from Investigating Causal Effects of Hematologic Traits on Lung Cancer: A Mendelian Randomization Study
Authors: Yang Zhanghuan , He Hao , He Guangxu , Zeng Chudai , Hu Qian
Published: January 2024

Phenotype Covariance Matrix Estimated by metaCCA Method
Table S10 from Investigating Causal Effects of Hematologic Traits on Lung Cancer: A Mendelian Randomization Study
Authors: Yang Zhanghuan , He Hao , He Guangxu , Zeng Chudai , Hu Qian
Published: January 2024

SNPs used in MVMR with adjustment for smoking and bilirubin
Figure S3 from Investigating Causal Effects of Hematologic Traits on Lung Cancer: A Mendelian Randomization Study
Authors: Yang Zhanghuan , He Hao , He Guangxu , Zeng Chudai , Hu Qian
Published: January 2024

Leave-one-out plot for hematocrit on lung carcinoma.
Supplemental Table 7 from Mobile Phone Use and Risks of Overall and 25 Site-Specific Cancers: A Prospective Study from the UK Biobank Study
Authors: Zhang Yanjun , Zhang Yuanyuan , Ye Ziliang , Yang Sisi , Liu Mengyi , Wu Qimeng , Zhou Chun , He Panpan , Gan Xiaoqin , Qin Xianhui
Published: January 2024

Supplemental Table 7. Associations of mobile phone use status (users vs. non-users) with incident site-specific cancers in women.
Figure S2 from Investigating Causal Effects of Hematologic Traits on Lung Cancer: A Mendelian Randomization Study
Authors: Yang Zhanghuan , He Hao , He Guangxu , Zeng Chudai , Hu Qian
Published: January 2024

Leave-one-out plot for reticulocyte count on lung carcinoma.
Supplementary Table 2 from Association between Dietary Anthocyanidins and Biliary Cancer Risk in 98,458 Participants: Results from a Prospective Study
Authors: Xiang Ling , Wu Dabin , Xu Zhiquan , Tang Yunhao , He Hongmei , Wang Yaxu , Gu Haitao , Peng Linglong
Published: January 2024

Supplementary Table 2. Association of Standardized total anthocyanidins with the risk of biliary cancer.
Supplemental Table 11 from Mobile Phone Use and Risks of Overall and 25 Site-Specific Cancers: A Prospective Study from the UK Biobank Study
Authors: Zhang Yanjun , Zhang Yuanyuan , Ye Ziliang , Yang Sisi , Liu Mengyi , Wu Qimeng , Zhou Chun , He Panpan , Gan Xiaoqin , Qin Xianhui
Published: January 2024

Supplemental Table 11. Associations of mobile phone use behaviors with incident overall cancer, nonmelanoma skin cancer, prostate cancer and urinary tract cancer in men, among mobile phone users.
Supplementary Table 1 from Association between Dietary Anthocyanidins and Biliary Cancer Risk in 98,458 Participants: Results from a Prospective Study
Authors: Xiang Ling , Wu Dabin , Xu Zhiquan , Tang Yunhao , He Hongmei , Wang Yaxu , Gu Haitao , Peng Linglong
Published: January 2024

Supplementary Table 1. Distribution of variables with missing data before and after imputation.
Supplementary Figure 1 from Association between Dietary Anthocyanidins and Biliary Cancer Risk in 98,458 Participants: Results from a Prospective Study
Authors: Xiang Ling , Wu Dabin , Xu Zhiquan , Tang Yunhao , He Hongmei , Wang Yaxu , Gu Haitao , Peng Linglong
Published: January 2024

Supplementary Figure 1. The timeline of the study.
Supplemental Table 1 from Mobile Phone Use and Risks of Overall and 25 Site-Specific Cancers: A Prospective Study from the UK Biobank Study
Authors: Zhang Yanjun , Zhang Yuanyuan , Ye Ziliang , Yang Sisi , Liu Mengyi , Wu Qimeng , Zhou Chun , He Panpan , Gan Xiaoqin , Qin Xianhui
Published: January 2024

Supplemental Table 1. Baseline characteristics of study participants by cancer status in men and women.
Supplemental Figure S2 from Patient Willingness to Use a Pharmacy-Based Colorectal Cancer Screening Service: A National Survey of U.S. Adults
Authors: Shah Parth D. , Wangen Mary , Rohweder Catherine L. , Waters Austin R. , Odebunmi Olufeyisayo O. , Marciniak Macary W. , Ferrari Renée M. , Wheeler Stephanie B. , Brenner Alison T.
Published: January 2024

Measurement model for latent variable willingness to use PharmFIT.
Supplemental Figure 5 from Mobile Phone Use and Risks of Overall and 25 Site-Specific Cancers: A Prospective Study from the UK Biobank Study
Authors: Zhang Yanjun , Zhang Yuanyuan , Ye Ziliang , Yang Sisi , Liu Mengyi , Wu Qimeng , Zhou Chun , He Panpan , Gan Xiaoqin , Qin Xianhui
Published: January 2024

Supplemental Figure 5. Association of mobile phone use status (users vs. non-users) with incident site-specific cancers in men, excluding the cases identified during the first 2 years of follow-up.
Supplemental Figure S1 from Patient Willingness to Use a Pharmacy-Based Colorectal Cancer Screening Service: A National Survey of U.S. Adults
Authors: Shah Parth D. , Wangen Mary , Rohweder Catherine L. , Waters Austin R. , Odebunmi Olufeyisayo O. , Marciniak Macary W. , Ferrari Renée M. , Wheeler Stephanie B. , Brenner Alison T.
Published: January 2024

Measurement model for Diffusion of Innovation latent variables relative advantage, compatibility, and complexity.
Supplemental Figure 4 from Mobile Phone Use and Risks of Overall and 25 Site-Specific Cancers: A Prospective Study from the UK Biobank Study
Authors: Zhang Yanjun , Zhang Yuanyuan , Ye Ziliang , Yang Sisi , Liu Mengyi , Wu Qimeng , Zhou Chun , He Panpan , Gan Xiaoqin , Qin Xianhui
Published: January 2024

Supplemental Figure 4. Sensitivity analyses on the association of mobile phone use status (users vs. non-users) with incident site-specific cancers in men (A) and women (B), by further adjusting for the year of enrollment.
Supplemental Figure 2 from Mobile Phone Use and Risks of Overall and 25 Site-Specific Cancers: A Prospective Study from the UK Biobank Study
Authors: Zhang Yanjun , Zhang Yuanyuan , Ye Ziliang , Yang Sisi , Liu Mengyi , Wu Qimeng , Zhou Chun , He Panpan , Gan Xiaoqin , Qin Xianhui
Published: January 2024

Supplemental Figure 2. Stratified analyses on the association of mobile phone use with the risk of incident overall cancer, nonmelanoma skin cancer, prostate cancer and urinary tract cancer in men, according to different age groups.
Supplemental Table 4 from Adiposity, Weight Change, and Urinary Melatonin Levels among Men in the Multiethnic Cohort
Authors: Chowdhury-Paulino Ilkania M. , Vaselkiv Jane B. , Cheng Iona , Schernhammer Eva S. , Lin Zhike , Haiman Christopher A. , Le Marchand Loïc , Valdimarsdóttir Unnur , Wilkens Lynne R. , Markt Sarah C. , Mucci Lorelei A.
Published: January 2024

Supplemental Table 4: Associations between race/ethnicity and 6-sulfatoxymelatonin levels, in minimally and fully adjusted models and with and without adjustment for BMI
Supplementary Table S8 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S8 shows the results of weighted multiple linear regression analysis of log-transformed urinary nicotine N’-oxide with study covariates
Supplementary Table S5 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S5 shows the results of weighted multiple linear regression analysis of log-transformed urinary cotinine with study covariates
Supplementary Figure 3 from A Population-Based Family Case–Control Study of Sun Exposure and Follicular Lymphoma Risk
Authors: Odutola Michael K. , van Leeuwen Marina T. , Bruinsma Fiona , Turner Jennifer , Hertzberg Mark , Seymour John F. , Prince H. Miles , Trotman Judith , Verner Emma , Roncolato Fernando , Opat Stephen , Lindeman Robert , Tiley Campbell , Milliken Samuel T. , Underhill Craig R. , Benke Geza , Giles Graham G. , Vajdic Claire M.
Published: January 2024

Supplementary Figure 3 shows the distribution of total hours per week at four decade years
Supplementary Table S40 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S40 shows regression coefficients of time since last smoked a cigarette referenced to “within the last hour” from weighted multiple linear regression analysis of log-transformed urinary biomarkers for each evaluated in this study and the intra-class correlation coefficients from this alternative model
Table S5. from Adherence to 2018 WCRF/AICR Cancer Prevention Recommendations and Risk of Cancer: The Melbourne Collaborative Cohort Study
Authors: Peng Yang , Bassett Julie K. , Hodge Allison M. , Melaku Yohannes Adama , Afshar Nina , Hopper John L. , MacInnis Robert J. , Lynch Brigid M. , Smith-Warner Stephanie A. , Giles Graham G. , Milne Roger L. , Jayasekara Harindra
Published: January 2024

Hazard ratiosa for WCRF/AICR diet and lifestyle scores and total, alcohol-, obesity- and smoking-related, and digestive tract cancer risk for men in the Melbourne Collaborative Cohort Study
Supplementary Table S39 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S39 shows the results of weighted multiple linear regression analysis of log-transformed urinary lead with study covariates
Supplementary Table S38 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S38 shows the results of weighted multiple linear regression analysis of log-transformed urinary cadmium with study covariates
Supplementary Table S36 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S36 shows the results of weighted multiple linear regression analysis of log-transformed urinary mandelic acid (MADA) with study covariates
Supplementary Table S34 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S34 shows the results of weighted multiple linear regression analysis of log-transformed urinary N‐acetyl‐S‐(2‐hydroxypropyl)‐L‐cysteine (2HPMA) with study covariates
Supplementary Table S3 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S3 shows the reference biomarker levels in smoking and nonsmoking populations
Supplementary Table S5 from Effects of KRAS Genetic Interactions on Outcomes in Cancers of the Lung, Pancreas, and Colorectum
Authors: Grabski Isabella N. , Heymach John V. , Kehl Kenneth L. , Kopetz Scott , Lau Ken S. , Riely Gregory J. , Schrag Deborah , Yaeger Rona , Irizarry Rafael A. , Haigis Kevin M.
Published: January 2024

Supplementary Table S5: Adjusted p-values (Benjamini-Hochberg) and coefficients for testing differential mutation status for each gene in each cluster, compared to all other clusters, in univariate logistic regressions for NSCLC, CRC, and PDAC.
Supplementary Table S29 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S29 shows the results of weighted multiple linear regression analysis of log-transformed urinary N‐acetyl‐S‐(3‐hydroxypropyl‐1‐methyl)‐L‐cysteine (3HMPMA) with study covariates
Supplementary Table S28 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S28 shows the results of weighted multiple linear regression analysis of log-transformed urinary N‐acetyl‐S‐(2‐carboxyethyl)‐L‐cysteine (2CoEMA) with study covariates
Supplementary Figure S3 from Effects of KRAS Genetic Interactions on Outcomes in Cancers of the Lung, Pancreas, and Colorectum
Authors: Grabski Isabella N. , Heymach John V. , Kehl Kenneth L. , Kopetz Scott , Lau Ken S. , Riely Gregory J. , Schrag Deborah , Yaeger Rona , Irizarry Rafael A. , Haigis Kevin M.
Published: January 2024

Supplementary Figure S3: CONSORT diagram depicting the number of included and excluded samples, and the reasons for exclusion, at each step of analysis for the PDAC cohort.
Supplementary Table S25 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S25 shows the results of weighted multiple linear regression analysis of log-transformed urinary N‐acetyl‐S‐(4‐hydroxy‐2‐buten‐1‐yl)‐L-cysteine (4HBeMA) with study covariates
Supplementary Table S1 from Racial and Ethnic Disparities in the Use of Robot-Assisted Surgery and Minimally Invasive Surgery in Pelvic Cancer Treatment: A Systematic Review
Authors: Mao Jialin , Genkinger Jeanine M. , Rundle Andrew G. , Wright Jason D. , Aryal Suvekshya , Liebeskind Alexander Y. , Tehranifar Parisa
Published: January 2024

Other relevant information for studies included in the systematic review.
Supplementary Table S16 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S16 shows the results of weighted multiple linear regression analysis of log-transformed urinary 2-hydroxyphenanthrene/3-hydroxyphenanthrene with study covariates
Supplementary Table S15 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S15 shows the results of weighted multiple linear regression analysis of log-transformed urinary N’-nitrosoanatabine with study covariates
Supplementary Table S12 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S12 shows the results of weighted multiple linear regression analysis of log-transformed urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) with study covariates
Supplementary Table S11 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S11 shows the results of weighted multiple linear regression analysis of log-transformed urinary anatabine with study covariates
Supplementary Table S10 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

Supplementary Table S10 shows the results of weighted multiple linear regression analysis of log-transformed urinary anabasine with study covariates
Supplementary Figure 1 from A Population-Based Family Case–Control Study of Sun Exposure and Follicular Lymphoma Risk
Authors: Odutola Michael K. , van Leeuwen Marina T. , Bruinsma Fiona , Turner Jennifer , Hertzberg Mark , Seymour John F. , Prince H. Miles , Trotman Judith , Verner Emma , Roncolato Fernando , Opat Stephen , Lindeman Robert , Tiley Campbell , Milliken Samuel T. , Underhill Craig R. , Benke Geza , Giles Graham G. , Vajdic Claire M.
Published: January 2024

Supplementary Figure 1 shows the exclusions for cases and controls during the recruitment processes
Data from The Breast Microbiome in Breast Cancer Risk and Progression: A Narrative Review
Authors: Peters Brandilyn A. , Kelly Libusha , Wang Tao , Loudig Olivier , Rohan Thomas E.
Published: January 2024

Abstract
A decade ago, studies in human populations first revealed the existence of a unique microbial community in the breast, a tissue historically viewed as sterile, with microbial origins seeded through the nipple and/or translocation from other body sites. Since then, research efforts have been made to characterize the microbiome in healthy and cancerous breast tissues. The purpose of this review is to summarize the current evidence for the association of the breast microbiome with breast cancer risk and progression. Briefly, while many studies have examined the breast microbiome in patients with breast cancer, and compared it with the microbiome of benign breast disease tissue or normal breast tissue, these studies have varied widely in their sample sizes, methods, and quality of evidence. Thus, while several large and rigorous cross-sectional studies have provided key evidence of an altered microbiome in breast tumors compared with normal adjacent and healthy control tissue, there are few consistent patterns of perturbed microbial taxa. In addition, only one large prospective study has provided evidence of a relationship between the breast tumor microbiota and cancer prognosis. Future research studies featuring large, well-characterized cohorts with prospective follow-up for breast cancer incidence, progression, and response to treatment are warranted.
Data from Adiposity, Weight Change, and Urinary Melatonin Levels among Men in the Multiethnic Cohort
Authors: Chowdhury-Paulino Ilkania M. , Vaselkiv Jane B. , Cheng Iona , Schernhammer Eva S. , Lin Zhike , Haiman Christopher A. , Le Marchand Loïc , Valdimarsdóttir Unnur , Wilkens Lynne R. , Markt Sarah C. , Mucci Lorelei A.
Published: January 2024

AbstractBackground:
Low levels of 6-sulfatoxymelatonin, the primary urinary metabolite of melatonin, have been linked to cancer and cardiometabolic outcomes in White and female populations.
Methods:
We examined the association between adulthood adiposity and 6-sulfatoxymelatonin levels in a racially and ethnically diverse population. Our study included 4,078 men in the Multiethnic Cohort with adiposity measurements at enrollment (1993–1996) and biomarkers measured in urines collected in 1995 and 2005. Multivariable linear regression models were used to estimate the percent change in 6-sulfatoxymelatonin levels and 95% confidence intervals (CI). Associations were examined separately by racial/ethnic group.
Results:
The prevalence of obesity varied by race and ethnicity, from 10% for Japanese American men to 34% for Native Hawaiian men. Compared with men with normal body mass index (BMI), men who were overweight (−7.8%; 95% CI, −11.9 to −3.5%) and obese (−18.1%; 95% CI, −23.2 to −12.6%) had significantly lower 6-sulfatoxymelatonin levels adjusting for potential confounding factors. Increasing weight gain in adulthood was also associated with lower 6-sulfatoxymelatonin (Ptrend < 0.0001). The inverse associations for BMI and weight change were qualitatively similar across racial and ethnic groups.
Conclusions:
Obesity is inversely associated with melatonin in a racially diverse population. This finding is relevant given higher rates of obesity among Black, Native Hawaiian, and Latino men, as well as potential racial and ethnic differences in circadian function.
Impact:
Melatonin may be a relevant biomarker among obesity-associated malignancies and could shed light on a potential mechanism of cancer disparities.
Data from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study
Authors: Ashley David L. , Zhu Wanzhe , Bhandari Deepak , Wang Lanqing , Feng Jun , Wang Yuesong , Meng Lei , Xia Baoyun , Jarrett Jeffery M. , Chang Cindy M. , Kimmel Heather L. , Blount Benjamin C.
Published: January 2024

AbstractBackground:
Biomarkers of exposure are tools for understanding the impact of tobacco use on health outcomes if confounders like demographics, use behavior, biological half-life, and other sources of exposure are accounted for in the analysis.
Methods:
We performed multiple regression analysis of longitudinal measures of urinary biomarkers of alkaloids, tobacco-specific nitrosamines, polycyclic aromatic hydrocarbons, volatile organic compounds (VOC), and metals to examine the sample-to-sample consistency in Waves 1 and 2 of the Population Assessment of Tobacco and Health (PATH) Study including demographic characteristics and use behavior variables of persons who smoked exclusively. Regression coefficients, within- and between-person variance, and intra-class correlation coefficients (ICC) were compared with biomarker smoking/nonsmoking population mean ratios and biological half-lives.
Results:
Most biomarkers were similarly associated with sex, age, race/ethnicity, and product use behavior. The biomarkers with larger smoking/nonsmoking population mean ratios had greater regression coefficients related to recency of exposure. For VOC and alkaloid metabolites, longer biological half-life was associated with lower within-person variance. For each chemical class studied, there were biomarkers that demonstrated good ICCs.
Conclusions:
For most of the biomarkers of exposure reported in the PATH Study, for people who smoke cigarettes exclusively, associations are similar between urinary biomarkers of exposure and demographic and use behavior covariates. Biomarkers of exposure within-subject consistency is likely associated with nontobacco sources of exposure and biological half-life.
Impact:
Biomarkers measured in the PATH Study provide consistent sample-to-sample measures from which to investigate the association of adverse health outcomes with the characteristics of cigarettes and their use.
Data from A Population-Based Family Case–Control Study of Sun Exposure and Follicular Lymphoma Risk
Authors: Odutola Michael K. , van Leeuwen Marina T. , Bruinsma Fiona , Turner Jennifer , Hertzberg Mark , Seymour John F. , Prince H. Miles , Trotman Judith , Verner Emma , Roncolato Fernando , Opat Stephen , Lindeman Robert , Tiley Campbell , Milliken Samuel T. , Underhill Craig R. , Benke Geza , Giles Graham G. , Vajdic Claire M.
Published: January 2024

AbstractBackground:
Epidemiologic evidence suggests an inverse association between sun exposure and follicular lymphoma risk.
Methods:
We conducted an Australian population-based family case–control study based on 666 cases and 459 controls (288 related, 171 unrelated). Participants completed a lifetime residence and work calendar and recalled outdoor hours on weekdays, weekends, and holidays in the warmer and cooler months at ages 10, 20, 30, and 40 years, and clothing types worn in the warmer months. We used a group-based trajectory modeling approach to identify outdoor hour trajectories over time and examined associations with follicular lymphoma risk using logistic regression.
Results:
We observed an inverse association between follicular lymphoma risk and several measures of high lifetime sun exposure, particularly intermittent exposure (weekends, holidays). Associations included reduced risk with increasing time outdoors on holidays in the warmer months [highest category OR = 0.56; 95% confidence interval (CI), 0.42–0.76; Ptrend < 0.01], high outdoor hours on weekends in the warmer months (highest category OR = 0.71; 95% CI, 0.52–0.96), and increasing time outdoors in the warmer and cooler months combined (highest category OR = 0.66; 95% CI, 0.50–0.91; Ptrend 0.01). Risk was reduced for high outdoor hour maintainers in the warmer months across the decade years (OR = 0.71; 95% CI, 0.53–0.96).
Conclusions:
High total and intermittent sun exposure, particularly in the warmer months, may be protective against the development of follicular lymphoma.
Impact:
Although sun exposure is not recommended as a cancer control policy, confirming this association may provide insights regarding the future control of this intractable malignancy.
Data from Racial and Ethnic Disparities in the Use of Robot-Assisted Surgery and Minimally Invasive Surgery in Pelvic Cancer Treatment: A Systematic Review
Authors: Mao Jialin , Genkinger Jeanine M. , Rundle Andrew G. , Wright Jason D. , Aryal Suvekshya , Liebeskind Alexander Y. , Tehranifar Parisa
Published: January 2024

Abstract
Surgical innovations for cancer treatment may penetrate differentially across racial and ethnic groups and contribute to disparities in health and health care quality. We summarized the current evidence of racial and ethnic disparities in robot-assisted surgery (RAS) and minimally invasive surgery (MIS) use in four major pelvic cancer treatments. We identified studies related to racial and ethnic disparities in RAS and/or MIS use in the treatment of prostate, endometrial, bladder, and rectal cancers during 2001 to 2022 from PubMed, EMBASE, and the Cochrane database. Twenty-eight studies were selected (prostate = 7, endometrial = 14, bladder = 1, rectal = 5, multiple cancers = 1) and all were retrospective. Thirteen and 23 studies examined racial and ethnic differences in individual patients’ receipt of RAS and MIS, respectively. Black patients were less likely to receive RAS/MIS than White patients in most studies. Hispanic patients were less likely to receive RAS/MIS than White patients in just over half of the studies. Studies of Asian patients were few and reported mixed results. Three studies examined disparities on the center level and found that racial and ethnic minority prostate cancer patients were less likely to be treated at RAS-performing or high-technology facilities. More work is needed to improve understanding of the mechanisms underlying racial and ethnic disparities in RAS and MIS use and their impact on disparities in health outcomes.
Abstract A005: Enhanced DNA damage and disruption of repair by iodinated thymidine analogues with Tipiracil for clinical radiation sensitization
Authors: Grindrod Scott , Velana Alfredo , Rich Tyvin , Jung Mira , Pang Dalong , Dritschilo Anatoly
Published: January 2024

IUdR incorporation into cellular DNA enhances radiation induced DNA damage and impairs repair pathways. IUdR has been explored as a clinical radiation sensitizer in Phase I and II clinical trials of sarcomas and gliomas, showing clinical activity. A major barrier to acceptance of this therapy has been the poor pharmacokinetic (PK) profile of IUdR which has a blood plasma half-life of less than 10 minutes. Continuous IV infusion of IUdR has been used to achieve clinically relevant DNA incorporation into tumor cells, but technical limitations of delivery and acute toxicities in rapidly proliferating normal tissues presented barriers to advancing this approach. To improve the PK profile of IUdR, a prodrug strategy has been employed leading to the development of ropidoxuridine (IPdR), which improved the PK profile, demonstrated oral bioavailability of the active metabolite IUdR, showed less normal tissue toxicity, and provided tumor radiation sensitization. IPdR plus XRT has been tested in Phase 0 and Phase 1 clinical trials and a phase II trial is proposed for glioblastoma treatment. We report here a second approach to improve the PK profile of orally administered IUdR by combining these iodinated thymidine analogs with the metabolism inhibitor, Tipiracil (TPI) which inhibits thymidine phosphorylase, the primary enzyme responsible for irreversible IUdR degradation, and is currently used in the FDA approved combination drug Lonsurf. Oral co-administration of IUdR and TPI in rats dramatically improved the PK profile of IUdR, increasing the half-life of the compound to 1.5 hours and boosting the maximum plasma concentration by approximately 8-fold. We studied the effects of Tipiracil on the metabolism of IUdR by varying the molecular ratio of IUdR/TPI from 2:1 up to a ratio of 10:1 and discovered that the plasma concentration of IUdR plateaued between a ratio of 5:1 and 10:1. This new combination therapy of IUdR/TPI yields a PK profile of IUdR that is relevant to clinical treatment in combination with RT and offers to expand potential clinical radiation sensitizer applications.

Citation Format: Scott Grindrod, Alfredo Velana, Tyvin Rich, Mira Jung, Dalong Pang, Anatoly Dritschilo. Enhanced DNA damage and disruption of repair by iodinated thymidine analogues with Tipiracil for clinical radiation sensitization [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr A005.