Longitudinal blood pressure changes in relation to urinary toxic/essential metals and metal mixtures - Margaret C. Weiss; Jiehuan Sun; Brian P. Jackson; Mary E. Turyk; Luyu Wang; Eric L. Brown; David Aguilar; Sharon A. Brown; Craig L. Hanis; Maria Argos; Robert M. Sargis (Environmental Research, 2026)

Maternal and early-life arsenic exposure and relative telomere length in children: Findings from the BiRCH cohort - Lydia Lichtiger; Shohreh F. Farzan; Tariqul Islam; Syed Emdadul Haque; Mohammad H. Shahriar; Golam Sarwar; Alauddin Ahmed; Chunyu Liu; Brandon L. Pierce; Farzana Jasmine; Muhammad G. Kibriya; Habibul Ahsan; et al. (Environmental Research, 2026)

Corrigendum to “Quality-assurance of heat-flow data: the new structure and evaluation scheme of the IHFC Global Heat Flow Database” [Tectonophysics 863 (2023) / 229976] - Sven Fuchs; Ben Norden; Florian Neumann; Norbert Kaul; Akiko Tanaka; Ilmo T. Kukkonen; Christophe Pascal; Rodolfo Christiansen; Gianluca Gola; Jan Šafanda; Orlando Miguel Espinoza-Ojeda; Ignacio Marzan; et al. (Tectonophysics, 2026)

Combination and summary of ATLAS dark matter searches interpreted in a 2HDM with a pseudo-scalar mediator using 139 fb−1 of s = 13 TeV pp collision data - G. Aad; B. Abbott; K. Abeling; N.J. Abicht; S.H. Abidi; A. Aboulhorma; H. Abramowicz; H. Abreu; Y. Abulaiti; A.C. Abusleme Hoffman; B.S. Acharya; C. Adam Bourdarios; et al. (Science Bulletin, 2024)

Air quality and cancer risk in the All of Us Research Program - Andrew Craver; Jiajun Luo; Muhammad G. Kibriya; Nina Randorf; Kendall Bahl; Elizabeth Connellan; Johnny Powell; Paul Zakin; Rena R. Jones; Maria Argos; Joyce Ho; Karen Kim; et al. (Cancer Causes & Control, 2024)
Introduction The NIH All of Us Research Program has enrolled over 544,000 participants across the US with unprecedented racial/ethnic diversity, offering opportunities to investigate myriad exposures and diseases. This paper aims to investigate the association between PM 2.5 exposure and cancer risks. Materials and methods This work was performed on data from 409,876 All of Us Research Program participants using the All of Us Researcher Workbench. Cancer case ascertainment was performed using data from electronic health records and the self-reported Personal Medical History questionnaire. PM 2.5 exposure was retrieved from NASA’s Earth Observing System Data and Information Center and assigned using participants’ 3-digit zip code prefixes. Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Generalized additive models (GAMs) were used to investigate non-linear relationships. Results A total of 33,387 participants and 46,176 prevalent cancer cases were ascertained from participant EHR data, while 20,297 cases were ascertained from self-reported survey data from 18,133 participants; 9,502 cancer cases were captured in both the EHR and survey data. Average PM 2.5 level from 2007 to 2016 was 8.90 μg/m 3 (min 2.56, max 15.05). In analysis of cancer cases from EHR, an increased odds for breast cancer (OR 1.17, 95% CI 1.09–1.25), endometrial cancer (OR 1.33, 95% CI 1.09–1.62) and ovarian cancer (OR 1.20, 95% CI 1.01–1.42) in the 4th quartile of exposure compared to the 1st. In GAM, higher PM 2.5 concentration was associated with increased odds for blood cancer, bone cancer, brain cancer, breast cancer, colon and rectum cancer, endocrine system cancer, lung cancer, pancreatic cancer, prostate cancer, and thyroid cancer. Conclusions We found evidence of an association of PM 2.5 with breast, ovarian, and endometrial cancers. There is little to no prior evidence in the literature on the impact of PM 2.5 on risk of these cancers, warranting further investigation.

Quality-assurance of heat-flow data: The new structure and evaluation scheme of the IHFC Global Heat Flow Database - Sven Fuchs; Ben Norden; Florian Neumann; Norbert Kaul; Akiko Tanaka; Ilmo T. Kukkonen; Christophe Pascal; Rodolfo Christiansen; Gianluca Gola; Jan Šafanda; Orlando Miguel Espinoza-Ojeda; Ignacio Marzan; et al. (Tectonophysics, 2023)

Relationships Between Urinary Metals and Diabetes Traits Among Mexican Americans in Starr County, Texas, USA - Margaret C. Weiss; Yu-Hsuan Shih; Molly Scannell Bryan; Brian P. Jackson; David Aguilar; Craig L. Hanis; Maria Argos; Robert M. Sargis (Biological Trace Element Research, 2023)

Rice Intake and Emerging Concerns on Arsenic in Rice: a Review of the Human Evidence and Methodologic Challenges - Margaret R. Karagas; Tracy Punshon; Matt Davis; Catherine M. Bulka; Francis Slaughter; Despina Karalis; Maria Argos; Habibul Ahsan (Current Environmental Health Reports, 2019)

The contribution of parent-to-offspring transmission of telomeres to the heritability of telomere length in humans - Dayana A. Delgado; Chenan Zhang; Kevin Gleason; Kathryn Demanelis; Lin S. Chen; Jianjun Gao; Shantanu Roy; Justin Shinkle; Mekala Sabarinathan; Maria Argos; Lin Tong; Alauddin Ahmed; et al. (Human Genetics, 2019)

Screening for gene–environment (G×E) interaction using omics data from exposed individuals: an application to gene-arsenic interaction - Maria Argos; Lin Tong; Shantanu Roy; Mekala Sabarinathan; Alauddin Ahmed; Md. Tariqul Islam; Tariqul Islam; Muhammad Rakibuz-Zaman; Golam Sarwar; Hasan Shahriar; Mahfuzar Rahman; Md. Yunus; et al. (Mammalian Genome, 2018)

Applying the dark diversity concept to nature conservation - Rob J. Lewis; Francesco de Bello; Jonathan A. Bennett; Pavel Fibich; Genevieve E. Finerty; Lars Götzenberger; Inga Hiiesalu; Liis Kasari; Jan Lepš; Maria Májeková; Ondřej Mudrák; Kersti Riibak; et al. (Conservation Biology, 2017)
Linking diversity to biological processes is central for developing informed and effective conservation decisions. Unfortunately, observable patterns provide only a proportion of the information necessary for fully understanding the mechanisms and processes acting on a particular population or community. We suggest conservation managers use the often overlooked information relative to species absences and pay particular attention to dark diversity (i.e., a set of species that are absent from a site but that could disperse to and establish there, in other words, the absent portion of a habitat‐specific species pool). Together with existing ecological metrics, concepts, and conservation tools, dark diversity can be used to complement and further develop conservation prioritization and management decisions through an understanding of biodiversity relativized by its potential (i.e., its species pool). Furthermore, through a detailed understanding of the population, community, and functional dark diversity, the restoration potential of degraded habitats can be more rigorously assessed and so to the likelihood of successful species invasions. We suggest the application of the dark diversity concept is currently an underappreciated source of information that is valuable for conservation applications ranging from macroscale conservation prioritization to more locally scaled restoration ecology and the management of invasive species.

Arsenic Exposure and Epigenetic Alterations: Recent Findings Based on the Illumina 450K DNA Methylation Array - Maria Argos (Current Environmental Health Reports, 2015)