cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc24t448
title: CCDC 1990359: Experimental Crystal Structure Determination

description: Related Article: Еlena А. Malinina, Svetlana E. Korolenko, Alexey S. Kubasov, Grigorii A. Buzanov, Alexey V. Golubev, Lyudmila V. Goeva, Nikolay P. Simonenko, Varvara V. Avdeeva, Nikolay T. Kuznetsov|2021|J.Solid State Chem.|302|122413|doi:10.1016/j.jssc.2021.122413
DOI: 10.5517/ccdc.csd.cc24t459
title: CCDC 1990360: Experimental Crystal Structure Determination

description: Related Article: Еlena А. Malinina, Svetlana E. Korolenko, Alexey S. Kubasov, Grigorii A. Buzanov, Alexey V. Golubev, Lyudmila V. Goeva, Nikolay P. Simonenko, Varvara V. Avdeeva, Nikolay T. Kuznetsov|2021|J.Solid State Chem.|302|122413|doi:10.1016/j.jssc.2021.122413
DOI: 10.5517/ccdc.csd.cc26gvn6
title: CCDC 2040068: Experimental Crystal Structure Determination

description: Related Article: Muge Shele, Xinyu Tian, Menghe Baiyin|2021|J.Solid State Chem.|302|122401|doi:10.1016/j.jssc.2021.122401
DOI: 10.5517/ccdc.csd.cc26t7hs
title: CCDC 2050045: Experimental Crystal Structure Determination

description: Related Article: Cai He, Xiang‐Long Chen, Shi‐Yi Zhuang, Yan‐Dong Wu, Bo‐Cheng Tang, An‐Xin Wu|2021|Adv.Synth.Catal.|363|3476|doi:10.1002/adsc.202100401
DOI: 10.5517/ccdc.csd.cc26xd0k
title: CCDC 2053068: Experimental Crystal Structure Determination

description: Related Article: Hasnain Mehmood, Muhammad Khalid, Muhammad Haroon, Tashfeen Akhter, Muhammad Ashfaq, Muhammad Nawaz Tahir, Muhammad Usman Khan, Muhammad Imran, Ataualpa Albert Carmo Braga, Simon Woodward|2021|J.Mol.Struct.|1245|131043|doi:10.1016/j.molstruc.2021.131043
DOI: 10.5517/ccdc.csd.cc26yq85
title: CCDC 2054347: Experimental Crystal Structure Determination

description: Related Article: Xiao-Yu Jiang, Xin-Yuan Chen, Hang Xiao, Xiao-Yuan Wu, Zhi-Gang Zhang, Lang Lin, Ming-Di Xu, Rong-Guo Chen, Min-Feng Zheng, Zhu-Wu Jiang|2021|Inorg.Chem.Commun.|131|108754|doi:10.1016/j.inoche.2021.108754
DOI: 10.5517/ccdc.csd.cc2736k4
title: CCDC 2058665: Experimental Crystal Structure Determination

description: Related Article: Wei-Wei Fan, Dan Yang, Zhong-Quan Cheng, Feng-Qing Xu, Fa-Wu Dong, Xiao-Yong Wei, Jiang-Miao Hu|2021|Phytochemistry|190|112858|doi:10.1016/j.phytochem.2021.112858
DOI: 10.5517/ccdc.csd.cc276tz8
title: CCDC 2062150: Experimental Crystal Structure Determination

description: Related Article: Muge Shele, Xinyu Tian, Menghe Baiyin|2021|J.Solid State Chem.|302|122401|doi:10.1016/j.jssc.2021.122401
DOI: 10.5517/ccdc.csd.cc27fl3d
title: CCDC 2068633: Experimental Crystal Structure Determination

description: Related Article: Zhi-Kun Liu, Zi-Shuo Yao, Jun Tao|2021|Inorg.Chem.|60|10291|doi:10.1021/acs.inorgchem.1c00727
DOI: 10.5517/ccdc.csd.cc27fl4f
title: CCDC 2068634: Experimental Crystal Structure Determination

description: Related Article: Zhi-Kun Liu, Zi-Shuo Yao, Jun Tao|2021|Inorg.Chem.|60|10291|doi:10.1021/acs.inorgchem.1c00727
DOI: 10.5517/ccdc.csd.cc27fl5g
title: CCDC 2068635: Experimental Crystal Structure Determination

description: Related Article: Zhi-Kun Liu, Zi-Shuo Yao, Jun Tao|2021|Inorg.Chem.|60|10291|doi:10.1021/acs.inorgchem.1c00727
DOI: 10.5517/ccdc.csd.cc27fl6h
title: CCDC 2068636: Experimental Crystal Structure Determination

description: Related Article: Zhi-Kun Liu, Zi-Shuo Yao, Jun Tao|2021|Inorg.Chem.|60|10291|doi:10.1021/acs.inorgchem.1c00727
DOI: 10.5517/ccdc.csd.cc27fl7j
title: CCDC 2068637: Experimental Crystal Structure Determination

description: Related Article: Zhi-Kun Liu, Zi-Shuo Yao, Jun Tao|2021|Inorg.Chem.|60|10291|doi:10.1021/acs.inorgchem.1c00727
DOI: 10.5517/ccdc.csd.cc27fl8k
title: CCDC 2068638: Experimental Crystal Structure Determination

description: Related Article: Zhi-Kun Liu, Zi-Shuo Yao, Jun Tao|2021|Inorg.Chem.|60|10291|doi:10.1021/acs.inorgchem.1c00727
DOI: 10.5517/ccdc.csd.cc27fl9l
title: CCDC 2068639: Experimental Crystal Structure Determination

description: Related Article: Zhi-Kun Liu, Zi-Shuo Yao, Jun Tao|2021|Inorg.Chem.|60|10291|doi:10.1021/acs.inorgchem.1c00727
DOI: 10.5517/ccdc.csd.cc27h6nm
title: CCDC 2070200: Experimental Crystal Structure Determination

description: Related Article: Jiarong Shi, Lianggui Li, Chunhui Shan, Zhonghong Chen, Liang Dai, Min Tan, Yu Lan, Yang Li|2021|J.Am.Chem.Soc.|143|10530|doi:10.1021/jacs.1c04389
DOI: 10.5517/ccdc.csd.cc27h6qp
title: CCDC 2070202: Experimental Crystal Structure Determination

description: Related Article: Jiarong Shi, Lianggui Li, Chunhui Shan, Zhonghong Chen, Liang Dai, Min Tan, Yu Lan, Yang Li|2021|J.Am.Chem.Soc.|143|10530|doi:10.1021/jacs.1c04389
DOI: 10.5517/ccdc.csd.cc27hh5f
title: CCDC 2070464: Experimental Crystal Structure Determination

description: Related Article: Thaddäus Thorwart, Daniel Roth, Lutz Greb|2021|Chem.-Eur.J.|27|10422|doi:10.1002/chem.202101138
DOI: 10.5517/ccdc.csd.cc27hh6g
title: CCDC 2070465: Experimental Crystal Structure Determination

description: Related Article: Thaddäus Thorwart, Daniel Roth, Lutz Greb|2021|Chem.-Eur.J.|27|10422|doi:10.1002/chem.202101138
DOI: 10.5517/ccdc.csd.cc27hh7h
title: CCDC 2070466: Experimental Crystal Structure Determination

description: Related Article: Thaddäus Thorwart, Daniel Roth, Lutz Greb|2021|Chem.-Eur.J.|27|10422|doi:10.1002/chem.202101138
DOI: 10.25345/c5q25m
title: MassIVE MSV000087877 - test 1 - penicillium part 1 xxxxxxxxxx
title: fungal extract obtained from plant tissue. fungal extract obtained from plant tissue.
DOI: 10.6084/m9.figshare.15047952.v1
title: Supplementary Table 2 from The influence of jaw-muscle fibre-type phenotypes on estimating maximum muscle and bite forces in primates

description: Maximum jaw-muscle and bite force estimates for P. troglodytes. The top row reports muscle force (MF) estimates using a specific tension of 35 N cm-2 [Eng et al., 2013]. The bottom row reports MF estimates based on our MF %CSA. The same muscle PCSAs and in-lever and out-lever estimates are used in both estimates of MF.
DOI: 10.6084/m9.figshare.15047958.v1
title: Supplementary Table 1 from The influence of jaw-muscle fibre-type phenotypes on estimating maximum muscle and bite forces in primates

description: Specimen-level information which includes species, sex and provenience. Data used to calculate %MF are included for each specimen such as PCSA and %CSA and specific tension for each fibre type present.
DOI: 10.6084/m9.figshare.15047952
title: Supplementary Table 2 from The influence of jaw-muscle fibre-type phenotypes on estimating maximum muscle and bite forces in primates

description: Maximum jaw-muscle and bite force estimates for P. troglodytes. The top row reports muscle force (MF) estimates using a specific tension of 35 N cm-2 [Eng et al., 2013]. The bottom row reports MF estimates based on our MF %CSA. The same muscle PCSAs and in-lever and out-lever estimates are used in both estimates of MF.
DOI: 10.5517/ccdc.csd.cc27hh8j
title: CCDC 2070467: Experimental Crystal Structure Determination

description: Related Article: Thaddäus Thorwart, Daniel Roth, Lutz Greb|2021|Chem.-Eur.J.|27|10422|doi:10.1002/chem.202101138
DOI: 10.5517/ccdc.csd.cc27hh9k
title: CCDC 2070468: Experimental Crystal Structure Determination

description: Related Article: Thaddäus Thorwart, Daniel Roth, Lutz Greb|2021|Chem.-Eur.J.|27|10422|doi:10.1002/chem.202101138
DOI: 10.5517/ccdc.csd.cc27hhbl
title: CCDC 2070469: Experimental Crystal Structure Determination

description: Related Article: Thaddäus Thorwart, Daniel Roth, Lutz Greb|2021|Chem.-Eur.J.|27|10422|doi:10.1002/chem.202101138
DOI: 10.5517/ccdc.csd.cc27jc27
title: CCDC 2071298: Experimental Crystal Structure Determination

description: Related Article: Irina A. Lutsenko, Dmitriy S. Yambulatov, Mikhail A. Kiskin, Yulia V. Nelyubina, Petr V. Primakov, Nikolay N. Efimov, Konstantin A. Babeshkin, Andrey V. Khoroshilov, Yurii V. Maksimov, Sergey V. Novichikhin, Ekaterina M. Zueva, Alexey A. Sidorov, Igor L. Eremenko|2021|Polyhedron|206|115354|doi:10.1016/j.poly.2021.115354
DOI: 10.5517/ccdc.csd.cc27jc38
title: CCDC 2071299: Experimental Crystal Structure Determination

description: Related Article: Irina A. Lutsenko, Dmitriy S. Yambulatov, Mikhail A. Kiskin, Yulia V. Nelyubina, Petr V. Primakov, Nikolay N. Efimov, Konstantin A. Babeshkin, Andrey V. Khoroshilov, Yurii V. Maksimov, Sergey V. Novichikhin, Ekaterina M. Zueva, Alexey A. Sidorov, Igor L. Eremenko|2021|Polyhedron|206|115354|doi:10.1016/j.poly.2021.115354
DOI: 10.5517/ccdc.csd.cc27k0qk
title: CCDC 2071938: Experimental Crystal Structure Determination

description: Related Article: Huiyeong Ju, Miki Iwase, Hikari Sako, Hiroki Horita, Shiori Koike, Eunji Lee, Mari Ikeda, Shunsuke Kuwahara, Yoichi Habata|2021|J.Org.Chem.|86|9847|doi:10.1021/acs.joc.1c00737
DOI: 10.5517/ccdc.csd.cc27my50
title: CCDC 2074742: Experimental Crystal Structure Determination

description: Related Article: Yanmei Hu, Yuming Zhang, Weiguo Han, Jian Li, Xingwen Pu, Di Wu, Zhengyang Bin, Jingsong You|2022|Chem.Eng.Journal|428|131186|doi:10.1016/j.cej.2021.131186
DOI: 10.5517/ccdc.csd.cc27mz51
title: CCDC 2074773: Experimental Crystal Structure Determination

description: Related Article: Yanmei Hu, Yuming Zhang, Weiguo Han, Jian Li, Xingwen Pu, Di Wu, Zhengyang Bin, Jingsong You|2022|Chem.Eng.Journal|428|131186|doi:10.1016/j.cej.2021.131186
DOI: 10.5517/ccdc.csd.cc27qgk0
title: CCDC 2077172: Experimental Crystal Structure Determination

description: Related Article: Mengmeng Xu, Min Hou, Haibing He, Shuanhu Gao|2021|Angew.Chem.,Int.Ed.|60|16655|doi:10.1002/anie.202105395
DOI: 10.5517/ccdc.csd.cc27qgn3
title: CCDC 2077175: Experimental Crystal Structure Determination

description: Related Article: Mengmeng Xu, Min Hou, Haibing He, Shuanhu Gao|2021|Angew.Chem.,Int.Ed.|60|16655|doi:10.1002/anie.202105395
DOI: 10.5517/ccdc.csd.cc27qgq5
title: CCDC 2077177: Experimental Crystal Structure Determination

description: Related Article: Mengmeng Xu, Min Hou, Haibing He, Shuanhu Gao|2021|Angew.Chem.,Int.Ed.|60|16655|doi:10.1002/anie.202105395
DOI: 10.5517/ccdc.csd.cc27wwfg
title: CCDC 2082376: Experimental Crystal Structure Determination

description: Related Article: Xiongfei Zheng, Ili Zulkifly, Andreas Heilmann, Caitilín McManus, Simon Aldridge|2021|Angew.Chem.,Int.Ed.|60|16416|doi:10.1002/anie.202106413
DOI: 10.5517/ccdc.csd.cc27wwgh
title: CCDC 2082377: Experimental Crystal Structure Determination

description: Related Article: Xiongfei Zheng, Ili Zulkifly, Andreas Heilmann, Caitilín McManus, Simon Aldridge|2021|Angew.Chem.,Int.Ed.|60|16416|doi:10.1002/anie.202106413
DOI: 10.5517/ccdc.csd.cc27wwhj
title: CCDC 2082378: Experimental Crystal Structure Determination

description: Related Article: Xiongfei Zheng, Ili Zulkifly, Andreas Heilmann, Caitilín McManus, Simon Aldridge|2021|Angew.Chem.,Int.Ed.|60|16416|doi:10.1002/anie.202106413
DOI: 10.5517/ccdc.csd.cc27wwjk
title: CCDC 2082379: Experimental Crystal Structure Determination

description: Related Article: Xiongfei Zheng, Ili Zulkifly, Andreas Heilmann, Caitilín McManus, Simon Aldridge|2021|Angew.Chem.,Int.Ed.|60|16416|doi:10.1002/anie.202106413
DOI: 10.5517/ccdc.csd.cc27wwkl
title: CCDC 2082380: Experimental Crystal Structure Determination

description: Related Article: Xiongfei Zheng, Ili Zulkifly, Andreas Heilmann, Caitilín McManus, Simon Aldridge|2021|Angew.Chem.,Int.Ed.|60|16416|doi:10.1002/anie.202106413
DOI: 10.5517/ccdc.csd.cc27wwlm
title: CCDC 2082381: Experimental Crystal Structure Determination

description: Related Article: Xiongfei Zheng, Ili Zulkifly, Andreas Heilmann, Caitilín McManus, Simon Aldridge|2021|Angew.Chem.,Int.Ed.|60|16416|doi:10.1002/anie.202106413
DOI: 10.5517/ccdc.csd.cc27wwmn
title: CCDC 2082382: Experimental Crystal Structure Determination

description: Related Article: Xiongfei Zheng, Ili Zulkifly, Andreas Heilmann, Caitilín McManus, Simon Aldridge|2021|Angew.Chem.,Int.Ed.|60|16416|doi:10.1002/anie.202106413
DOI: 10.5517/ccdc.csd.cc280dnc
title: CCDC 2085762: Experimental Crystal Structure Determination

description: Related Article: Mauro Mato, Marc Montesinos-Magraner, Arnau R. Sugranyes, Antonio M. Echavarren|2021|J.Am.Chem.Soc.|143|10760|doi:10.1021/jacs.1c05422
DOI: 10.5517/ccdc.csd.cc280dpd
title: CCDC 2085763: Experimental Crystal Structure Determination

description: Related Article: Mauro Mato, Marc Montesinos-Magraner, Arnau R. Sugranyes, Antonio M. Echavarren|2021|J.Am.Chem.Soc.|143|10760|doi:10.1021/jacs.1c05422
DOI: 10.6084/m9.figshare.14838901
title: Cohort profile and heritability assessment of familial pancreatic cancer: a nation-wide study

description: Familial Pancreatic Cancer (FPC) is responsible for up to 10% of all cases of pancreatic ductal adenocarcinoma (PDAC). Individuals predisposed for FPC have an estimated lifetime risk of 16–39% of developing PDAC. While heritability of PDAC has been estimated to be 36% in a Nordic twin study, no heritability estimate specific on FPC has been reported. A national cohort of Danish families with predisposition for FPC is currently included in a screening program for PDAC at Odense University Hospital. Family members included in the screening program were interviewed for pedigree data including: cases of PDAC among first-degree relatives (FDRs) and number of affected/unaffected siblings. Heritability for FPC in the predisposed families was assessed by doubling the estimated intra-class correlation coefficient (ICC) from a random intercept logistic model fitted to data on FDRs. Among families with predisposition for FPC, 83 cases of PDAC were identified. The median age at diagnosis of PDAC was 66 years, and median time from diagnosis to death was 7.6 months. A total of 359 individuals were found as unaffected FDRs of the 83 PDAC cases. The retrieved FDRs included a total of 247 individuals in sibship and 317 individuals in parent-offspring relatedness. We estimated an ICC of 0.25, corresponding to a narrow sense additive heritability estimate of 0.51 in the FPC family cohort. We have established a nation-wide cohort of FPC families to facilitate clinical and genetic studies on FPC. The estimated heritability of 51% prominently underlines a strong genetic background of FPC.
DOI: 10.6084/m9.figshare.14838901.v1
title: Cohort profile and heritability assessment of familial pancreatic cancer: a nation-wide study

description: Familial Pancreatic Cancer (FPC) is responsible for up to 10% of all cases of pancreatic ductal adenocarcinoma (PDAC). Individuals predisposed for FPC have an estimated lifetime risk of 16–39% of developing PDAC. While heritability of PDAC has been estimated to be 36% in a Nordic twin study, no heritability estimate specific on FPC has been reported. A national cohort of Danish families with predisposition for FPC is currently included in a screening program for PDAC at Odense University Hospital. Family members included in the screening program were interviewed for pedigree data including: cases of PDAC among first-degree relatives (FDRs) and number of affected/unaffected siblings. Heritability for FPC in the predisposed families was assessed by doubling the estimated intra-class correlation coefficient (ICC) from a random intercept logistic model fitted to data on FDRs. Among families with predisposition for FPC, 83 cases of PDAC were identified. The median age at diagnosis of PDAC was 66 years, and median time from diagnosis to death was 7.6 months. A total of 359 individuals were found as unaffected FDRs of the 83 PDAC cases. The retrieved FDRs included a total of 247 individuals in sibship and 317 individuals in parent-offspring relatedness. We estimated an ICC of 0.25, corresponding to a narrow sense additive heritability estimate of 0.51 in the FPC family cohort. We have established a nation-wide cohort of FPC families to facilitate clinical and genetic studies on FPC. The estimated heritability of 51% prominently underlines a strong genetic background of FPC.
DOI: 10.6084/m9.figshare.15047976.v1
title: Supplementary Material from Power laws in the Roman Empire: a survival analysis

description: The Roman Empire shaped western civilization, and many Roman principles are embodied in modern institutions. Although its political institutions proved both resilient and adaptable, allowing it to incorporate diverse populations, the Empire suffered from many conflicts. Indeed, most emperors died violently, from assassination, suicide or in battle. These conflicts produced patterns in the length of time that can be identified by statistical analysis. In this paper, we study the underlying patterns associated with the reign of the Roman emperors by using statistical tools of survival data analysis. We consider all the 175 Roman emperors and propose a new power-law model with change points to predict the time-to-violent-death of the Roman emperors. This model encompasses data in the presence of censoring and long-term survivors, providing more accurate predictions than previous models. Our results show that power-law distributions can also occur in survival data, as verified in other data types from natural and artificial systems, reinforcing the ubiquity of power-law distributions. The generality of our approach paves the way to further related investigations not only in other ancient civilizations but also in applications in engineering and medicine.
DOI: 10.6084/m9.figshare.15047976
title: Supplementary Material from Power laws in the Roman Empire: a survival analysis

description: The Roman Empire shaped western civilization, and many Roman principles are embodied in modern institutions. Although its political institutions proved both resilient and adaptable, allowing it to incorporate diverse populations, the Empire suffered from many conflicts. Indeed, most emperors died violently, from assassination, suicide or in battle. These conflicts produced patterns in the length of time that can be identified by statistical analysis. In this paper, we study the underlying patterns associated with the reign of the Roman emperors by using statistical tools of survival data analysis. We consider all the 175 Roman emperors and propose a new power-law model with change points to predict the time-to-violent-death of the Roman emperors. This model encompasses data in the presence of censoring and long-term survivors, providing more accurate predictions than previous models. Our results show that power-law distributions can also occur in survival data, as verified in other data types from natural and artificial systems, reinforcing the ubiquity of power-law distributions. The generality of our approach paves the way to further related investigations not only in other ancient civilizations but also in applications in engineering and medicine.
DOI: 10.15151/esrf-es-459569882
title: Biomimetic self-assembling peptides as an advanced, innovative treatment for hypomineralised dental enamel

description: Dental enamel formation occurs via organic-matrix mediated nucleation and crystal growth resulting in highly oriented, aligned apatite crystallites. Molar incisor hypomineralisation (MIH) is an enamel pathology with low mineral density, disordered and misaligned crystallites. It has as relatively high prevalence in populations world-wide and is challenging to treat. Our patented biomimetic self-assembling peptides (SAPs) are able to direct de novo crystallite nucleation and growth in enamel affected by demineralisation, therefore may guide oriented and aligned mineral growth in hypomineralised enamel. We will characterise the crystallographic preferred orientation and spatial distribution of alignment in MIH enamel with or without SAP treatment and related this to mineral concentration, to reveal whether our novel SAPs offer an advanced, innovative clinical treatment pathway for hypomineralised enamel.
DOI: 10.15151/esrf-es-459578554
title: X-Ray diffraction and equation of state of hydrohalite, a major component of water-rich planetary bodies.

description: Observations from space probes strongly support the presence of dissolved ionic species (e.g. Mg, Na, Cl, SO4) in deep oceans of icy moons like Ganymede, Europa, Enceladus and Titan to pressures of several GPa. Eutectic salt saturated phases (e.g. hydrohalite for H2O-NaCl) are expected at the surface and interior of these planetary bodies through their thermal evolution. Accurate P-V-T equations of state (EoS) of relevant materials are of capital importance to better constrain the structure, dynamic and evolution of icy worlds. Even if predicted as a major specie at the surface and interior of icy worlds , no equation of states for hydrohalite exists to date due to the very limited amount of data available in the litterature. We propose to run high-pressure, low temperatures single crystal and powder X-Ray diffraction experiment to characterize the volumes hydrohalite NaCl•2(H2O), in the 50K – 300K and 0 – 2200MPa range.
DOI: 10.6084/m9.figshare.15047958
title: Supplementary Table 1 from The influence of jaw-muscle fibre-type phenotypes on estimating maximum muscle and bite forces in primates

description: Specimen-level information which includes species, sex and provenience. Data used to calculate %MF are included for each specimen such as PCSA and %CSA and specific tension for each fibre type present.
DOI: 10.5281/zenodo.5131522
title: Split root Poa annua grass

description: This dataset shows plant mass for Poa annua plants grown under high and low light and N, with N supplied equally or unqually to the roots
DOI: 10.5281/zenodo.5131521
title: Split root Poa annua grass

description: This dataset shows plant mass for Poa annua plants grown under high and low light and N, with N supplied equally or unqually to the roots
DOI: 10.6084/m9.figshare.15048003
title: Clinical_information_gene_expression

description: This dataset contains clinical information and expression data of 1904 breast cancer patients from the METABRIC study and 1080 patients from the TCGA database.
DOI: 10.6084/m9.figshare.15048003.v2
title: Clinical_information_gene_expression

description: This dataset contains clinical information and expression data of 1904 breast cancer patients from the METABRIC study and 1080 patients from the TCGA database.
DOI: 10.6084/m9.figshare.15048003.v1
title: Clinical_information_gene_expression_metabric_risk_score.txt

description: This dataset contains clinical information and expression data of 1904 breast cancer patients from the METABRIC study.
DOI: 10.6084/m9.figshare.15048008.v1
title: Health effects of WiFi radiation: a review based on systematic quality evaluation

description: Although WiFi contributes little to total radiofrequency electromagnetic field (RF-EMF) exposure in our everyday environment, concern has raised whether this specific type of modulated RF-EMF causes health problems. The aim of this review is to evaluate all types of studies that investigated biological and health effects of WiFi exposure and fulfilled basic quality criteria. Eligible for inclusion were epidemiological, human experimental, <i>in vivo</i> and <i>in vitro</i> studies using realistic WiFi exposure settings. We conducted a systematic literature search for all papers published between January 1997 and August 2020 followed by a quality review addressing blinding and dosimetry in experimental studies and various types of biases in epidemiological studies. All studies fulfilling the quality criteria were descriptively summarized in terms of observation or absence of associations. From 1385 articles identified by the literature search, 23 fulfilled basic quality criteria: 6 epidemiological papers, 6 human experimental articles, 9 <i>in vivo</i> articles, and 2 <i>in vitro</i> articles. Whereas <i>in vivo</i> and <i>in vitro</i> studies applied exposure levels up to 4 W/kg, human studies dealt with exposure levels several orders of magnitude below the ICNIRP guidelines, which are typical for WiFi exposure situations in the everyday environment. Numerous outcomes ranging from biological markers to symptoms were mostly found not to be associated with WiFi exposure. Sporadic findings were not consistent in terms of outcomes or exposure-response associations. This review based on a systematic literature search and quality evaluation does not suggest detrimental health effects from WiFi exposure below regulatory limits.