cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/9zczv644bv.1
title: Analysis of differential expression of GABARAP family members in Glioblastoma

description: Our study is based on the analysis of the differential expression of GABARAP family members in glioblastoma (GBM). We investigated the expression of GABARAP’s (GABARAP, GABARAPL1, and GABARAPL2) and MAP1LC3’s (MAP1LC3A, MAP1LC3B, and MAP1LC3C) in GBM and Low-grade glioma (LGG) patient samples. We found that the GABARAP gene was highly expressed at transcript levels in the GBM patient sample as compared to other members of GABARAP and MAP1LC3’s. Since GABARAP’s and MAP1LC3’s genes are involved in the autophagy initiation and the autophagosome formation. So, we investigated the expression of these family members after autophagy regulation in GBM cell lines: U87MG and LN229. We used chloroquine (CQ) and Early Balanced Salt Solution (EBSS) for inhibition and initiation of autophagy. Chloroquine is a late-stage autophagy inhibitor while EBSS is a starvation induce media. After autophagy inhibition, the non-lipidated form of GABARAP (I) was increased. However, no changes were observed in GABARAPL1 and GABARAPL2 in both cell lines. Non-lipidated form of GABARAPL2 (II) showed increased expression in EBSS conditions. Temozolomide (TMZ) is a DNA alkylating agent used in the clinical treatment of newly diagnosed GBM. Interestingly, only the lipidated form of GABARAP genes was significantly highly expressed after TMZ concentration-dependent (200µM and 400 µM) and time-dependent treatments (24hrs and 48hr). We have got the same findings after treatment with IC50 concentration of TMZ in U87MG. We also analyzed that MAP1LC3A expression decreases after TMZ treatment. These outcomes conclude that ATG8 genes behave differently in response to TMZ treatment. We further investigated the role of GABARAP’s in GBM by its knockdown and overexpression. We performed an MTT assay to check the TMZ sensitivity after GABARAP’s knockdown and overexpression. We observed that TMZ sensitivity is decreased with GABARAP knockdown but not with knockdown of GABARAPL1 and GABARAPL2. After GABARAP knockdown the IC50 concentration of TMZ was significantly increased but the opposite result was seen after GABARAP overexpression. We also observed that GABARAP overexpression induced p53 expression upon TMZ treatment. P53 is a tumor suppressor gene and it shows a positive correlation with GABARAP. We’ve also checked the expression of P53 after GABARAP’s knockdown which was interestingly, decreased. Furthermore, we also found that a combined treatment of TMZ and CQ with IC50 concentrations increases the P53 expression. Our study demonstrated that the overexpression of GABARAP increased the sensitivity of TMZ with synergistic increased in P53. The differential role of GABARAPs can be useful for better therapeutic approaches in GBM.
DOI: 10.17632/6kg3cccfc5.1
title: Social Excluder's Face Reduces Gaze-Triggered Attention Orienting

description: This data is for the article “ Social Excluder's Face Reduces Gaze-Triggered Attention Orienting”. This dataset contains the raw data and process data of reaction time and accuracy .
DOI: 10.17632/jndv68rxs5.1
title: LINF_360038000

description: RNA helicase | MTR4
Leishmania infantum (strain JPCM5)
DOI: 10.17632/x8zd6w44n3.1
title: LINF_360038200

description: RRP41A
Leishmania infantum (strain JPCM5)
DOI: 10.17632/ymkmvnmk4g.1
title: LINF_360037900

description: putative GTP-binding protein
Leishmania infantum (strain JPCM5)
DOI: 10.17632/pjvdhmfcsn.1
title: Supplemental Material Calf ADG

description: Supplemental data from a cow-driven cow-calf-contact system with gradual debonding showing intake of concentrate, supplemental milk and health events
DOI: 10.17632/5ry8bgfktk.1
title: Geochemical features of river runoff and their effect on the state of the aquatic environment of Lake Onego

description: This dataset has a description of the chemical and isotopic composition of the water and data about the Seasonal variability of suspended matter content in the surface water layer of the tributaries of Lake Onego.
DOI: 10.17632/w3r3mnfnmn.1
title: LINF_020010200

description: Glycerate kinase; Leishmania infantum (strain JPCM5)
DOI: 10.17632/zykzv6nrx8.2
title: Skills in transfers and management of neurogenic bladder in wheelchair users.

description: Present the adaptation strategies that people with spinal cord injury use to autonomously perform transfers and manage neurogenic bladder.
DOI: 10.17632/9gwcxzty45.1
title: LINF_360039100

description: ATP synthase
Leishmania infantum (strain JPCM5)
DOI: 10.17632/schrbgywj9.1
title: Hatje et al_2023_COMMSENV

description: Data for the manuscript: Vegetated coastal ecosystems ecosystems in the Southwestern Atlantic Ocean as an unexploited opportunity for climate change mitigation
DOI: 10.17632/6z9w7d3ztw.1
title: Replication material for "From Macro to Micro: Large Exporters Coping with Global Crises"

description: We use monthly firm-level exports and imports of French firms over 1993-2020 -- which includes two major global crises -- matched with additional administrative firm-level data. We uncover four stlized facts about the role of large firms in aggregate exports concerning 1) the granular residual of aggregate exports; 2) the loadings of large firms on common shocks; 3) the reaction of top expoters to common shocks; and 4) the channels of their stronger response. These results suggest that idiosyncratic reactions of large firms to common shocks matter for aggregate export fluctuations. The readme indicates how getting access to confidential data, the non-confidential data being provided here.
DOI: 10.17632/rj6gnmnnmt.2
title: Datasets from "A framework to predict binary liquidus by combining machine learning and CALPHAD assessments"

description: If you use this dataset, please cite the following publication where you can find more details:
G. Deffrennes, K. Terayama, T. Abe, E. Ogamino, R. Tamura, A framework to predict binary liquidus by combining machine learning and CALPHAD assessments, Materials & Design (2023) https://doi.org/10.1016/j.matdes.2023.112111

In this work, 3 machine learning models are developed to predict the liquidus in binary systems.
Model 1 predicts the formation of liquid miscibility gaps.
Model 2 predicts the equilibrium onset temperature of solidification.
Model 3 predicts the critical temperature of liquid miscibility gaps.

The datasets that are used to build the models and evaluate their performance are found in the “CALPHAD Datasets” folder. They were collected from 466 CALPHAD assessments of binary phase diagrams listed in “Reference_list.csv”. It is emphasized that CALPHAD calculations in areas without experimental data were included in the training datasets. As a result, the datasets contain some unreliable data. This is especially true for the miscibility gap temperature regression dataset for Model 3, because (1) experimental data on liquid miscibility gaps are often lacking, especially at high temperatures, and (2) it includes extrapolations in metastable domains.

The performance of the models was evaluated from a nested group cross-validation approach. The predictions generated during this step are found the “Predictions inside the datasets” folder. For Model 2 and Model 3, visual comparisons between the predictions and the CALPHAD assessments are provided.

1563 binary liquidus are predicted from the models (all the two-by-two combinations between the 64 elements missing from the datasets), and the results are found in the “Predictions outside the datasets” folder.
They are obtained from the following procedure. Each model was trained on its whole dataset (expect for Model 3), after hyperparameters were tuned from a 10-fold cross validation. For Model 3, data on the B-Ga system that are unreliable were not taken into account. Besides, Model 3 is not valid in completely miscible systems, and was only used in systems where the probability of having a stable liquid miscibility gap is predicted by Model 1 to be greater or equal to 0.25.
It is emphasized that Model 3 only gives rough estimates, and predictions for elements not included in the training dataset that comprises 32 systems and 29 elements should be taken with caution.
DOI: 10.17632/rj6gnmnnmt.1
title: Datasets from "A framework to predict binary liquidus by combining machine learning and CALPHAD assessments"

description: These datasets are associated with the following publication, and the reader is referred to it for more details.
G. Deffrennes, K. Terayama, T. Abe, E. Ogamino, R. Tamura, A framework to predict binary liquidus by combining machine learning and CALPHAD assessments, Materials & Design (2023) https://doi.org/10.1016/j.matdes.2023.112111

In this work, 3 machine learning models are developed to predict the liquidus in binary systems.
Model 1 predicts the formation of liquid miscibility gaps.
Model 2 predicts the equilibrium onset temperature of solidification.
Model 3 predicts the critical temperature of liquid miscibility gaps.

The datasets that are used to build the models and evaluate their performance are found in the “CALPHAD Datasets” folder. They were collected from 466 CALPHAD assessments of binary phase diagrams listed in “Reference_list.csv”. It is emphasized that CALPHAD calculations in areas without experimental data were included in the training datasets. As a result, the datasets contain some unreliable data. This is especially true for the miscibility gap temperature regression dataset for Model 3, because (1) experimental data on liquid miscibility gaps are often lacking, especially at high temperatures, and (2) it includes extrapolations in metastable domains.

The performance of the models was evaluated from a nested group cross-validation approach. The predictions generated during this step are found the “Predictions inside the datasets” folder. For Model 2 and Model 3, visual comparisons between the predictions and the CALPHAD assessments are provided.

1563 binary liquidus are predicted from the models (all the two-by-two combinations between the 64 elements missing from the datasets), and the results are found in the “Predictions outside the datasets” folder.
They are obtained from the following procedure. Each model was trained on its whole dataset (expect for Model 3), after hyperparameters were tuned from a 10-fold cross validation. For Model 3, data on the B-Ga system that are unreliable were not taken into account. Besides, Model 3 is not valid in completely miscible systems, and was only used in systems where the probability of having a stable liquid miscibility gap is predicted by Model 1 to be greater or equal to 0.25.
It is emphasized that Model 3 only gives rough estimates, and predictions for elements not included in the training dataset that comprises 32 systems and 29 elements should be taken with caution.
DOI: 10.17632/djjd6pdhm9.1
title: High-resolution, in situ measurement of dissolved CH4, d13CH4 and C2H6 at Lake Aiguebelette using a Membrane Inlet Laser Spectrometer

description: Here, a continuous high-resolution dissolved CH4, d13CH4 and C2H6 measurements made with an in situ Membrane Inlet Laser Spectrometer instrument at lake Aigubelette on surface water (50 cm water depth) are reported. The measurements were performed on May 15th 2019 on the shallow areas in the southwest of the lake from near the shore to the islands in the center of the lake, then into the channel of Thiers at the lake outlet. The coordinates were provided by a Garmin 18x GPS unit with an accuracy of 15m. 
In the attached file we reported the local time (in hh:mm:ss and as fract time), the coordinates, the distance from shore in meter, the water depth in meter, the concentration of dissolved CH4 in mol fraction and in mol per liter of water, the concentration of dissolved C2H6 in mol fraction and the d13CH4 in permil. The data on the channel of Thiers were reported in a separated file.
The accuracies of the measurements are +/-12% for the concentration of CH4 and C2H6 (limit of detection 0.06 ppm or 0.1 nmol L-1 for CH4, and 2 ppb 4 pmol L-1 for C2H6) and +/-2.2 permil for the d13CH4 . All uncertainties are expressed with a 2-sigma confidential interval.
DOI: 10.17632/y7jy7bnfhp.1
title: SEMA7A-mediated Juxtacrine Stimulation of IGFBP-3 Upregulates IL-17RB at Pancreatic Cancer Invasive Front

description: Tumor invasion is the hallmark of tumor malignancy. The invasive infiltration pattern of tumor cells located at the leading edge is highly correlated with metastasis and unfavorable patient outcomes. However, the regulatory mechanisms governing tumor malignancy at the invasive margin remain unclear. The IL-17B/IL-17RB pathway is known to promote pancreatic cancer invasion and metastasis, yet the specific mechanisms underlying IL-17RB upregulation during invasion are poorly understood. In this study, we unveiled a multistep process for IL-17RB upregulation at the invasive margin, which occurs through direct communication between tumor cells and fibroblasts. Tumor ATP1A1 facilitates plasma membrane expression of SEMA7A, which binds to and induces IGFBP-3 secretion from fibroblasts. The resulting gradient of IGFBP-3 influences the direction and enhances IL-17RB expression to regulate SNAI2 in invasion. These findings highlight the importance of local tumor-fibroblast interactions in promoting cancer cell invasiveness, potentially leading to the development of new therapeutic strategies targeting this communication.

Original raw data and uncropped Western blots are organized in a separate worksheet for each figure.
DOI: 10.17632/stywvysvkx.1
title: Sedimentary provenance supports a mid-Paleozoic tectonic connection between the Junggar and Altai terranes in central Asia

description: The analytical methods and U-Pb-Hf data for the manuscript submitted to GRL by Di Li et al. (2024).
DOI: 10.17632/9h9zynpd6y.1
title: Dataset for Electric bus fleet operation: A robust optimisation framework addressing battery ageing, time-of-use tariffs, and energy consumption uncertainty

description: This repository contains the datasets, instances, and codes used in the paper "Electric bus fleet operation: A robust optimisation framework addressing battery ageing, time-of-use tariffs, and energy consumption uncertainty"
DOI: 10.17632/9h9zynpd6y.2
title: Dataset for Electric bus fleet operation: A robust optimisation framework addressing battery ageing, time-of-use tariffs, and energy consumption uncertainty

description: This repository contains the datasets, instances, and codes used in the paper "Electric bus fleet operation: A robust optimisation framework addressing battery ageing, time-of-use tariffs, and energy consumption uncertainty"
DOI: 10.17632/mmbgn94f4j.1
title: Dataset: Interference

description: This dataset corresponds to the experiments mentioned in the article "Partial Discharge and Interference Discrimination in Gas-Insulated Systems using Electric and Magnetic Sensors". The description of how the data was gathered can be found in the same paper.
DOI: 10.17632/mmbgn94f4j.2
title: Dataset: Interference

description: This dataset corresponds to the experiments mentioned in the article "Partial Discharge and Interference Discrimination in Gas-Insulated Systems using Electric and Magnetic Sensors". The description of how the data was gathered can be found in the same paper.
DOI: 10.17632/nmn7jb98y8.2
title: Mg-Gd-Sr Thermodynamic Database V2

description: The thermodynamic calculations with the database enables a well reproduction of experimental findings and a physical-metallurgical understanding of the microstructure formation in solidification and annealing. It is helpful in designing chemical compositions and microstructure of novel Mg-Sr alloy for biomedical applications.
MgGdSr20230509.tdb is the latest version. It incorporates Gd-Sr binary and delete the redundant parameters
DOI: 10.17632/stywvysvkx.2
title: Sedimentary provenance supports a mid-Paleozoic tectonic connection between the Junggar and Altai terranes in central Asia

description: The analytical methods and U-Pb-Hf data for the manuscript submitted to GRL by Di Li et al. (2024).
DOI: 10.17632/gjnfgb86kf.1
title: LINF_100013600

description: Hypothetical protein - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/h7935xg38t.1
title: LINF_100019400

description: Exportin 4/7-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/zjgsh6g5rs.1
title: Policy Brief: Optimalisasi Perlindungan Hak Asasi Manusia terhadap Perbudakan Modern pada Anak Buah Kapal Indonesia

description: Rekomendasi kebijakan optimalisasi perlindungan Hak Asasi Manusia terhadap Perbudakan Modern pada Anak Buah Kapal Indonesia
DOI: 10.17632/7h9hkjvx48.1
title: Numerical evaluation of CD-type discretizations of sea-ice dynamics  

description: This dataset contains the numerical data used in the publication "Simulating sea-ice deformation in viscous-plastic sea-ice models with CD-grids". In addition to the raw data, the linear kinematic feature detection algorithm is deposited. Linear Kinematic Features (LKFs) are an essential parameter for the comparison of the different methods. The "analysis" folder contains the Python script for LKF detection. The remaining folders contain the simulations of the different model discretizations. 

 The runs performed with MPAS-Seaice on quadrilateral meshes are stored in the following folders, with the corresponding discretization in parentheses:
- "MPAS-CD" ( runs with the CD2 discretization) 
- "MPAS-DoF" ( runs with B-grid on meshes that have the same velocity degree of freedom as the MPAS CD2 discretization  on meshes with a side length of 2 km, 4 km and 8 km)
- "MPAS-B" ( runs with B-grid discretization)

The runs performed with MPAS-Seaice on hexagonal meshes are stored in the following folders, with the corresponding discretization in parentheses:
-"hexMPAS-B" ( runs with B-grid)
-"hexMPAS-CD" ( runs with CD2 discretization)
-"hexMPAS-DoF" ( runs with B-grid on meshes that have the same velocity degree of freedom as the MPAS CD2 discretization on meshes with a resolution of 2 km, 4 km and 8 km)

The runs performed with FESOM on triangular meshes are stored in the following folder, with the corresponding discretization in parentheses:
- "FESOM" ( runs with CD2 discretization)
DOI: 10.17632/3d29y5jgh5.2
title: Data extraction for Highly diverse flower strips promote natural enemies more in annual field crops: A review and meta-analysis.

description: This is the data used for the article Highly diverse flower strips promote natural enemies more in annual field crops: A review and meta-analysis. The aim of the study was to synthesize the knowledge about the effect of flower strips on pests and natural enemies in annual crops. 
The data consists of three files
- Data for manuscript 1 - Natural enemies - list of data points extracted from 23 articles on the effect of flower strips on natural enemies. Each row corresponds to one pair of means (flower strip and control) extracted from the article. The data extracted includes mean natural enemy densities, standard deviations, number of samples as well as study 
- Data for manuscript 2 - Pests - list of data points extracted from 13 articles on the effect of flower strips on natural enemies. Each row corresponds to one pair of means (flower strip and control) extracted from the article. The data extracted includes mean pest densities or damage, standard deviations, number of samples as well as study details such as the type of pest/assesment and number of flowering species
- References for the 26 articles extracted for the study
DOI: 10.17632/djjd6pdhm9.2
title: High-resolution, in situ measurement of dissolved CH4, d13CH4 and C2H6 at Lake Aiguebelette using a Membrane Inlet Laser Spectrometer

description: Here, a continuous high-resolution dissolved CH4, d13CH4 and C2H6 measurements made with an in situ Membrane Inlet Laser Spectrometer instrument at lake Aigubelette on surface water (50 cm water depth) are reported. The measurements were performed on May 15th 2019 on the shallow areas in the southwest of the lake from near the shore to the islands in the center of the lake, then into the channel of Thiers at the lake outlet. The coordinates were provided by a Garmin 18x GPS unit with an accuracy of 15m. 
In the attached file we reported the local time (in hh:mm:ss and as fract time), the coordinates, the distance from shore in meter, the water depth in meter, the concentration of dissolved CH4 in mol fraction and in mol per liter of water, the concentration of dissolved C2H6 in mol fraction and the d13CH4 in permil. The data on the channel of Thiers were reported in a separated file.
The accuracies of the measurements are +/-12% for the concentration of CH4 and C2H6 (limit of detection 0.06 ppm or 0.1 nmol L-1 for CH4, and 2 ppb 4 pmol L-1 for C2H6) and +/-2.2 permil for the d13CH4 . All uncertainties are expressed with a 2-sigma confidential interval.
In the original files dissolved C2H6 concentrations were wrong, and have been corrected in the version V2.
DOI: 10.17632/6sjwvtwzxt.2
title: Changjiang River water

description: This data set is used for generating the figures in the manuscript "Dispersal of the Changjiang River water in East Asian shelf seas" authored by Peng Cheng.
DOI: 10.17632/6sjwvtwzxt.1
title: Changjiang River water

description: This data set is used for generating the figures in the manuscript "Dispersal of the Changjiang River water in East Asian shelf seas" authored by Peng Cheng.
DOI: 10.17632/2mtjyr97xd.1
title: The Paradox of Plastic Bag Legislation: How Bans and Taxes Affect PM2.5 Air Pollution in 208 Countries

description: The dataset is grounded in the context of examining the environmental impacts of plastic bag regulations on air quality. The widespread use of plastic bags has been identified as a contributor to elevated air pollution levels globally, leading to the implementation of bans and taxes to mitigate plastic pollution. This study analyses the effects of these regulatory measures on PM2.5 air quality across 208 countries from 1960 to 2021, using Fixed Effects, Driscoll and Kraay, and GMM models. The findings reveal that while bans reduce PM2.5 exposure above certain WHO thresholds, they may increase exposure above others, and taxes consistently increase exposure across all thresholds. The dataset combines World Bank data on PM2.5 and relevant covariates with country-specific regulatory information from Wikipedia (https://en.wikipedia.org/wiki/Plastic_bag_ban). It includes a Stata file with the compiled dataset, a Stata do-file for analysis, and R scripts for visualisations, offering a resource to explore the nuanced relationship between plastic bag policies and air quality.