Benchmark Dose for Dioxin Based on Gestational Diabetes Mellitus Using Coexposure Statistical Methods and an Optimized Physiologically Based Toxicokinetic Model.

Tao Ying, Xin Liu, Lei Zhang, Wencheng Cao, Sheng Wen, Yongning Wu, Gengsheng He, Jingguang Li

Abstract read

In one paragraph

Article in Environment & health (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Tao YingSchool of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China.ORCID https://orcid.org/0009-0004-5916-4920

Xin LiuNHC Key Laboratory of Food Safety Risk Assessment, Chinese Academy of Medical Science Research Unit (No. 2019RU014), China National Center for Food Safety Risk Assessment, Beijing 100021, China.ORCID https://orcid.org/0000-0001-7689-1346

Lei ZhangNHC Key Laboratory of Food Safety Risk Assessment, Chinese Academy of Medical Science Research Unit (No. 2019RU014), China National Center for Food Safety Risk Assessment, Beijing 100021, China.

Wencheng CaoChina Hubei Provincial Center for Disease Control and Prevention, Hubei Provincial Academy of Preventive Medicine, Hubei 430023, China.

Sheng WenChina Hubei Provincial Center for Disease Control and Prevention, Hubei Provincial Academy of Preventive Medicine, Hubei 430023, China.

Yongning WuNHC Key Laboratory of Food Safety Risk Assessment, Chinese Academy of Medical Science Research Unit (No. 2019RU014), China National Center for Food Safety Risk Assessment, Beijing 100021, China.ORCID https://orcid.org/0000-0001-6430-1302

Gengsheng HeSchool of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China.ORCID https://orcid.org/0000-0002-8740-8935

Jingguang LiNHC Key Laboratory of Food Safety Risk Assessment, Chinese Academy of Medical Science Research Unit (No. 2019RU014), China National Center for Food Safety Risk Assessment, Beijing 100021, China.ORCID https://orcid.org/0000-0003-0525-7027

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dioxins are ubiquitous endocrine-disrupting substances, but determining the effects and benchmark doses in situations of coexposure is highly challenging. The objective of this study was to assess the relationship between dioxin andgestational diabetes mellitus (GDM), calculate the benchmark dose (BMD) of dioxin in coexposure scenarios, and derive a daily exposure threshold using an optimized physiologically based toxicokinetic (PBTK) model. Based on a nested case-control study including 77 cases with GDM and 154 controls, serum levels of 29 dioxin-like compounds (DLCs) along with 10 perfluoroalkyl acids (PFAAs), seven polybrominated diphenyl ethers (PBDEs), and five non-dioxin-like polychlorinated biphenyls (ndl-PCBs) were measured at 9-16 weeks of gestation. Bayesian machine kernel regression (BKMR) was employed to identify significant chemicals, and probit and logistic models were used to calculate BMD adjusted for significant chemicals. A physiologically based toxicokinetic (PBTK) model was optimized using polyfluorinated dibenzo-

Identifiers

PMID39512389

DOI10.1021/envhealth.4c00017

PMCPMC11540123

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.