cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3159895
title: Generalized Fiducial Inference: A Review and New Results

description: R. A. Fisher, the father of modern statistics, proposed the idea of fiducial inference during the first half of the 20th century. While his proposal led to interesting methods for quantifying uncertainty, other prominent statisticians of the time did not accept Fisher’s approach as it became apparent that some of Fisher’s bold claims about the properties of fiducial distribution did not hold up for multi-parameter problems. Beginning around the year 2000, the authors and collaborators started to reinvestigate the idea of fiducial inference and discovered that Fisher’s approach, when properly generalized, would open doors to solve many important and difficult inference problems. They termed their generalization of Fisher’s idea as generalized fiducial inference (GFI). The main idea of GFI is to carefully transfer randomness from the data to the parameter space using an inverse of a data-generating equation without the use of Bayes’ theorem. The resulting generalized fiducial distribution (GFD) can then be used for inference. After more than a decade of investigations, the authors and collaborators have developed a unifying theory for GFI, and provided GFI solutions to many challenging practical problems in different fields of science and industry. Overall, they have demonstrated that GFI is a valid, useful, and promising approach for conducting statistical inference. The goal of this article is to deliver a timely and concise introduction to GFI, to present some of the latest results, as well as to list some related open research problems. It is authors’ hope that their contributions to GFI will stimulate the growth and usage of this exciting approach for statistical inference. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.3159895.v2
title: Generalized Fiducial Inference: A Review and New Results

description: R. A. Fisher, the father of modern statistics, proposed the idea of fiducial inference during the first half of the 20th century. While his proposal led to interesting methods for quantifying uncertainty, other prominent statisticians of the time did not accept Fisher’s approach as it became apparent that some of Fisher’s bold claims about the properties of fiducial distribution did not hold up for multi-parameter problems. Beginning around the year 2000, the authors and collaborators started to reinvestigate the idea of fiducial inference and discovered that Fisher’s approach, when properly generalized, would open doors to solve many important and difficult inference problems. They termed their generalization of Fisher’s idea as generalized fiducial inference (GFI). The main idea of GFI is to carefully transfer randomness from the data to the parameter space using an inverse of a data-generating equation without the use of Bayes’ theorem. The resulting generalized fiducial distribution (GFD) can then be used for inference. After more than a decade of investigations, the authors and collaborators have developed a unifying theory for GFI, and provided GFI solutions to many challenging practical problems in different fields of science and industry. Overall, they have demonstrated that GFI is a valid, useful, and promising approach for conducting statistical inference. The goal of this article is to deliver a timely and concise introduction to GFI, to present some of the latest results, as well as to list some related open research problems. It is authors’ hope that their contributions to GFI will stimulate the growth and usage of this exciting approach for statistical inference. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.3159895.v1
title: Generalized Fiducial Inference: A Review and New Results

description: R. A. Fisher, the father of modern statistics, proposed the idea of fiducial inference during the first half of the 20th century. While his proposal led to interesting methods for quantifying uncertainty, other prominent statisticians of the time did not accept Fisher’s approach as it became apparent that some of Fisher’s bold claims about the properties of fiducial distribution did not hold up for multi-parameter problems. Beginning around the year 2000, the authors and collaborators started to re-investigate the idea of fiducial inference and discovered that Fisher’s approach, when properly generalized, would open doors to solve many important and difficult inference problems. They termed their generalization of Fisher’s idea as generalized fiducial inference (GFI). The main idea of GFI is to carefully transfer randomness from the data to the parameter space using an inverse of a data generating equation without the use of Bayes theorem. The resulting generalized fiducial distribution (GFD) can then be used for inference. After more than a decade of investigations, the authors and collaborators have developed a unifying theory for GFI, and provided GFI solutions to many challenging practical problems in different fields of science and industry. Overall, they have demonstrated that GFI is a valid, useful, and promising approach for conducting statistical inference. The goal of this paper is to deliver a timely and concise introduction to GFI, to present some of the latest results, as well as to list some related open research problems. It is the authors’ hope that their contributions to GFI will stimulate the growth and usage of this exciting approach for statistical inference.
DOI: 10.18462/iir.rankine.2020.1145
title: Enabling power production from challenging industrial off-gas – model-based investigation of a novel heat recovery concept.
DOI: 10.6084/m9.figshare.3159880
title: Estrogen receptor alpha is cell cycle-regulated and regulates the cell cycle in a ligand-dependent fashion

description: Estrogen receptor alpha (ERα) has been implicated in several cell cycle regulatory events and is an important predictive marker of disease outcome in breast cancer patients. Here, we aimed to elucidate the mechanism through which ERα influences proliferation in breast cancer cells. Our results show that ERα protein is cell cycle-regulated in human breast cancer cells and that the presence of 17-β-estradiol (E2) in the culture medium shortened the cell cycle significantly (by 4.5 hours, <i>P</i> &lt; 0.05) compared with unliganded conditions. The alterations in cell cycle duration were observed in the S and G<sub>2</sub>/M phases, whereas the G<sub>1</sub> phase was indistinguishable under liganded and unliganded conditions. In addition, ERα knockdown in MCF-7 cells accelerated mitotic exit, whereas transfection of ERα-negative MDA-MB-231 cells with exogenous ERα significantly shortened the S and G<sub>2</sub>/M phases (by 9.1 hours, <i>P</i> &lt; 0.05) compared with parental cells. Finally, treatment of MCF-7 cells with antiestrogens revealed that tamoxifen yields a slower cell cycle progression through the S and G<sub>2</sub>/M phases than fulvestrant does, presumably because of the destabilizing effect of fulvestrant on ERα protein. Together, these results show that ERα modulates breast cancer cell proliferation by regulating events during the S and G<sub>2</sub>/M phases of the cell cycle in a ligand-dependent fashion. These results provide the rationale for an effective treatment strategy that includes a cell cycle inhibitor in combination with a drug that lowers estrogen levels, such as an aromatase inhibitor, and an antiestrogen that does not result in the degradation of ERα, such as tamoxifen.
DOI: 10.6084/m9.figshare.3159880.v2
title: Estrogen receptor alpha is cell cycle-regulated and regulates the cell cycle in a ligand-dependent fashion

description: Estrogen receptor alpha (ERα) has been implicated in several cell cycle regulatory events and is an important predictive marker of disease outcome in breast cancer patients. Here, we aimed to elucidate the mechanism through which ERα influences proliferation in breast cancer cells. Our results show that ERα protein is cell cycle-regulated in human breast cancer cells and that the presence of 17-β-estradiol (E2) in the culture medium shortened the cell cycle significantly (by 4.5 hours, <i>P</i> &lt; 0.05) compared with unliganded conditions. The alterations in cell cycle duration were observed in the S and G<sub>2</sub>/M phases, whereas the G<sub>1</sub> phase was indistinguishable under liganded and unliganded conditions. In addition, ERα knockdown in MCF-7 cells accelerated mitotic exit, whereas transfection of ERα-negative MDA-MB-231 cells with exogenous ERα significantly shortened the S and G<sub>2</sub>/M phases (by 9.1 hours, <i>P</i> &lt; 0.05) compared with parental cells. Finally, treatment of MCF-7 cells with antiestrogens revealed that tamoxifen yields a slower cell cycle progression through the S and G<sub>2</sub>/M phases than fulvestrant does, presumably because of the destabilizing effect of fulvestrant on ERα protein. Together, these results show that ERα modulates breast cancer cell proliferation by regulating events during the S and G<sub>2</sub>/M phases of the cell cycle in a ligand-dependent fashion. These results provide the rationale for an effective treatment strategy that includes a cell cycle inhibitor in combination with a drug that lowers estrogen levels, such as an aromatase inhibitor, and an antiestrogen that does not result in the degradation of ERα, such as tamoxifen.
DOI: 10.6084/m9.figshare.3159871
title: Mitophagy receptor FUNDC1 regulates mitochondrial dynamics and mitophagy

description: Mitochondrial fragmentation due to imbalanced fission and fusion of mitochondria is a prerequisite for mitophagy, however, the exact “coupling” of mitochondrial dynamics and mitophagy remains unclear. We have previously identified that FUNDC1 recruits MAP1LC3B/LC3B (LC3) through its LC3-interacting region (LIR) motif to initiate mitophagy in mammalian cells. Here, we show that FUNDC1 interacts with both DNM1L/DRP1 and OPA1 to coordinate mitochondrial fission or fusion and mitophagy. OPA1 interacted with FUNDC1 via its Lys70 (K70) residue, and mutation of K70 to Ala (A), but not to Arg (R), abolished the interaction and promoted mitochondrial fission and mitophagy. Mitochondrial stress such as selenite or FCCP treatment caused the disassembly of the FUNDC1-OPA1 complex while enhancing DNM1L recruitment to the mitochondria. Furthermore, we observed that dephosphorylation of FUNDC1 under stress conditions promotes the dissociation of FUNDC1 from OPA1 and association with DNM1L. Our data suggest that FUNDC1 regulates both mitochondrial fission or fusion and mitophagy and mediates the “coupling” across the double membrane for mitochondrial dynamics and quality control.
DOI: 10.6084/m9.figshare.3159880.v1
title: Estrogen Receptor Alpha is Cell Cycle-Regulated and Regulates the Cell Cycle in a Ligand-Dependent Fashion

description: Estrogen receptor alpha (ERα) has been implicated in several cell cycle regulatory events and is an important predictive marker of disease outcome in breast cancer patients. Here, we aimed to elucidate the mechanism through which ERα influences proliferation in breast cancer cells. Our results show that ERα protein is cell cycle-regulated in human breast cancer cells and that the presence of 17-β-estradiol (E2) in the culture medium shortened the cell cycle significantly (by 4.5 hours, <i>P</i> &lt; 0.05) compared with unliganded conditions. The alterations in cell cycle duration were observed in the S and G<sub>2</sub>/M phases, whereas the G<sub>1</sub> phase was indistinguishable under liganded and unliganded conditions. In addition, ERα knockdown in MCF-7 cells accelerated mitotic exit, whereas transfection of ERα-negative MDA-MB-231 cells with exogenous ERα significantly shortened the S and G<sub>2</sub>/M phases (by 9.1 hours, <i>P</i> &lt; 0.05) compared with parental cells. Finally, treatment of MCF-7 cells with antiestrogens revealed that tamoxifen yields a slower cell cycle progression through the S and G<sub>2</sub>/M phases than fulvestrant does, presumably because of the destabilizing effect of fulvestrant on ERα protein. Together, these results show that ERα modulates breast cancer cell proliferation by regulating events during the S and G<sub>2</sub>/M phases of the cell cycle in a ligand-dependent fashion. These results provide the rationale for an effective treatment strategy that includes a cell cycle inhibitor in combination with a drug that lowers estrogen levels, such as an aromatase inhibitor, and an antiestrogen that does not result in the degradation of ERα, such as tamoxifen.
DOI: 10.6084/m9.figshare.3159859
title: Distinct temporal requirements for autophagy and the proteasome in yeast meiosis

description: Meiosis is a special type of cellular renovation that involves 2 successive cell divisions and a single round of DNA replication. Two major degradation systems, the autophagy-lysosome and the ubiquitin-proteasome, are involved in meiosis, but their roles have yet to be elucidated. Here we show that autophagy mainly affects the initiation of meiosis but not the nuclear division. Autophagy works not only by serving as a dynamic recycling system but also by eliminating some negative meiotic regulators such as Ego4 (Ynr034w-a). In a quantitative proteomics study, the proteasome was found to be significantly upregulated during meiotic divisions. We found that proteasomal activity is essential to the 2 successive meiotic nuclear divisions but not for the initiation of meiosis. Our study defines the roles of autophagy and the proteasome in meiosis: Autophagy mainly affects the initiation of meiosis, whereas the proteasome mainly affects the 2 successive meiotic divisions.
DOI: 10.6084/m9.figshare.3159862
title: Identification of modulators of autophagic flux in an image-based high content siRNA screen

description: Autophagy is the primary process for recycling cellular constituents through lysosomal degradation. In addition to nonselective autophagic engulfment of cytoplasm, autophagosomes can recognize specific cargo by interacting with ubiquitin-binding autophagy receptors such as SQSTM1/p62 (sequestosome 1). This selective form of autophagy is important for degrading aggregation-prone proteins prominent in many neurodegenerative diseases. We carried out a high content image-based siRNA screen (4 to 8 siRNA per gene) for modulators of autophagic flux by monitoring fluorescence of GFP-SQSTM1 as well as colocalization of GFP-SQSTM1 with LAMP2 (lysosomal-associated membrane protein 2)-positive lysosomal vesicles. GFP-SQSTM1 and LAMP2 phenotypes of primary screen hits were confirmed in 2 cell types and profiled with image-based viability and MTOR signaling assays. Common seed analysis guided siRNA selection for these assays to reduce bias toward off-target effects. Confirmed hits were further validated in a live-cell assay to monitor fusion of autophagosomes with lysosomes. Knockdown of 10 targets resulted in phenotypic profiles across multiple assays that were consistent with upregulation of autophagic flux. These hits include modulators of transcription, lysine acetylation, and ubiquitination. Two targets, <i>KAT8</i> (K[lysine] acetyltransferase 8) and <i>CSNK1A1</i> (casein kinase 1, α 1), have been implicated in autophagic regulatory feedback loops. We confirmed that <i>CSNK1A1</i> knockout (KO) cell lines have accelerated turnover of long-lived proteins labeled with <sup>14</sup>C-leucine in a pulse-chase assay as additional validation of our screening assays. Data from this comprehensive autophagy screen point toward novel regulatory pathways that might yield new therapeutic targets for neurodegeneration.
DOI: 10.6084/m9.figshare.3159871.v1
title: Mitophagy receptor FUNDC1 regulates mitochondrial dynamics and mitophagy

description: Mitochondrial fragmentation due to imbalanced fission and fusion of mitochondria is a prerequisite for mitophagy, however, the exact “coupling” of mitochondrial dynamics and mitophagy remains unclear. We have previously identified that FUNDC1 recruits MAP1LC3B/LC3B (LC3) through its LC3-interacting region (LIR) motif to initiate mitophagy in mammalian cells. Here, we show that FUNDC1 interacts with both DNM1L/DRP1 and OPA1 to coordinate mitochondrial fission or fusion and mitophagy. OPA1 interacted with FUNDC1 via its Lys70 (K70) residue, and mutation of K70 to Ala (A), but not to Arg (R), abolished the interaction and promoted mitochondrial fission and mitophagy. Mitochondrial stress such as selenite or FCCP treatment caused the disassembly of the FUNDC1-OPA1 complex while enhancing DNM1L recruitment to the mitochondria. Furthermore, we observed that dephosphorylation of FUNDC1 under stress conditions promotes the dissociation of FUNDC1 from OPA1 and association with DNM1L. Our data suggest that FUNDC1 regulates both mitochondrial fission or fusion and mitophagy and mediates the “coupling” across the double membrane for mitochondrial dynamics and quality control.
DOI: 10.6084/m9.figshare.3159859.v1
title: Distinct temporal requirements for autophagy and the proteasome in yeast meiosis

description: Meiosis is a special type of cellular renovation that involves 2 successive cell divisions and a single round of DNA replication. Two major degradation systems, the autophagy-lysosome and the ubiquitin-proteasome, are involved in meiosis, but their roles have yet to be elucidated. Here we show that autophagy mainly affects the initiation of meiosis but not the nuclear division. Autophagy works not only by serving as a dynamic recycling system but also by eliminating some negative meiotic regulators such as Ego4 (Ynr034w-a). In a quantitative proteomics study, the proteasome was found to be significantly upregulated during meiotic divisions. We found that proteasomal activity is essential to the 2 successive meiotic nuclear divisions but not for the initiation of meiosis. Our study defines the roles of autophagy and the proteasome in meiosis: Autophagy mainly affects the initiation of meiosis, whereas the proteasome mainly affects the 2 successive meiotic divisions.
DOI: 10.6084/m9.figshare.3159820
title: Spatial distribution and temporal variability of stable water isotopes in a large and shallow lake<sup>†</sup>

description: Stable isotopic compositions of lake water provide additional information on hydrological, meteorological and paleoclimate processes. In this study, lake water isotopic compositions were measured for more than three years in Lake Taihu, a large and shallow lake in southern China, to investigate the isotopic spatial and seasonal variations. The results indicated that (1) the whole-lake mean <i>δ</i><sup>2</sup>H and <i>δ</i><sup>18</sup>O values of the lake water varied seasonally from −48.4 ± 5.8 to −25.1 ± 3.2 ‰ and from −6.5 ± 0.9 to −3.5 ± 0.8 ‰, respectively, (2) the spatial pattern of the lake water isotopic compositions was controlled by the direction of water flow and not by local evaporation rate, and (3) using a one-site isotopic measurement to represent the whole-lake mean may result in unreasonable estimates of the isotopic composition of lake evaporation and the lake water residence time in poorly mixed lakes. The original data, documented here as an online supplement, provides a good reference for testing sensitivity of lake water budget to various isotopic sampling strategies. We propose that detailed spatial measurement of lake water isotopic compositions provides a good proxy for water movement and pollutant and alga transports, especially over big lakes.
DOI: 10.6084/m9.figshare.3159820.v2
title: Spatial distribution and temporal variability of stable water isotopes in a large and shallow lake<sup>†</sup>

description: Stable isotopic compositions of lake water provide additional information on hydrological, meteorological and paleoclimate processes. In this study, lake water isotopic compositions were measured for more than three years in Lake Taihu, a large and shallow lake in southern China, to investigate the isotopic spatial and seasonal variations. The results indicated that (1) the whole-lake mean <i>δ</i><sup>2</sup>H and <i>δ</i><sup>18</sup>O values of the lake water varied seasonally from −48.4 ± 5.8 to −25.1 ± 3.2 ‰ and from −6.5 ± 0.9 to −3.5 ± 0.8 ‰, respectively, (2) the spatial pattern of the lake water isotopic compositions was controlled by the direction of water flow and not by local evaporation rate, and (3) using a one-site isotopic measurement to represent the whole-lake mean may result in unreasonable estimates of the isotopic composition of lake evaporation and the lake water residence time in poorly mixed lakes. The original data, documented here as an online supplement, provides a good reference for testing sensitivity of lake water budget to various isotopic sampling strategies. We propose that detailed spatial measurement of lake water isotopic compositions provides a good proxy for water movement and pollutant and alga transports, especially over big lakes.
DOI: 10.6084/m9.figshare.3159820.v1
title: Spatial distribution and temporal variability of stable water isotopes in a large and shallow lake

description: Stable isotopic compositions of lake water provide additional information on hydrological, meteorological and paleoclimate processes. In this study, lake water isotopic compositions were measured for more than three years in Lake Taihu, a large and shallow lake in southern China, to investigate the isotopic spatial and seasonal variations. The results indicated that (1) the whole-lake mean <i>δ</i><sup>2</sup>H and <i>δ</i><sup>18</sup>O values of the lake water varied seasonally from −48.4 ± 5.8 to −25.1 ± 3.2 ‰ and from −6.5 ± 0.9 to −3.5 ± 0.8 ‰, respectively, (2) the spatial pattern of the lake water isotopic compositions was controlled by the direction of water flow and not by local evaporation rate, and (3) using a one-site isotopic measurement to represent the whole-lake mean may result in unreasonable estimates of the isotopic composition of lake evaporation and the lake water residence time in poorly mixed lakes. The original data, documented here as an online supplement, provides a good reference for testing sensitivity of lake water budget to various isotopic sampling strategies. We propose that detailed spatial measurement of lake water isotopic compositions provides a good proxy for water movement and pollutant and alga transports, especially over big lakes.
DOI: 10.6084/m9.figshare.3159727
title: Programming with models: writing statistical algorithms for general model structures with NIMBLE

description: We describe NIMBLE, a system for programming statistical algorithms for general model structures within R. NIMBLE is designed to meet three challenges: flexible model specification, a language for programming algorithms that can use different models, and a balance between high-level programmability and execution efficiency. For model specification, NIMBLE extends the BUGS language and creates model objects, which can manipulate variables, calculate log probability values, generate simulations, and query the relationships among variables. For algorithm programming, NIMBLE provides functions that operate with model objects using two stages of evaluation. The first stage allows specialization of a function to a particular model and/or nodes, such as creating a Metropolis-Hastings sampler for a particular block of nodes. The second stage allows repeated execution of computations using the results of the first stage. To achieve efficient second-stage computation, NIMBLE compiles models and functions via C++, using the Eigen library for linear algebra, and provides the user with an interface to compiled objects. The NIMBLE language represents a compilable domain-specific language (DSL) embedded within R. This paper provides an overview of the design and rationale for NIMBLE along with illustrative examples including importance sampling, Markov chain Monte Carlo (MCMC) and Monte Carlo expectation maximization (MCEM).