dataesr/scientific-paragraphs-categorization huggingface dataset:
Moderate Resolution Imaging Spectroradiometer (MODIS) Albedo Products We used Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/albedo products (MCD43B3, version 5) during the period of 2001-2005 as criteria to correct the albedo parameterization scheme in FLake. The products combine the albedo retrievals from the Aqua and Terra satellites and provide albedo values for different bands, which agree with the in situ observations  (He et al. , 2014; Schaaf et al. , 2002). In this study, we used the white-sky and black-sky albedos for shortwave broadband with a spatial resolution of 1 km and an interval of 8 days. We carefully selected the pixels with quality flags between 0 and 2 to ensure relatively high data quality. The diffuse skylight ratio was calculated using the monthly diffuse and direct downward shortwave radiation products from the National Center for Environmental Forecasting and was introduced to calculate blue-sky albedo.
China Meteorological Forcing Data Set (CMFD) The FLake forcing variables include near-surface air temperature, specific humidity, wind speed, surface pressure, downward shortwave radiation and downward longwave radiation. We obtained 3-h forcing variables during the period of 1996-2011 from the China Meteorological Forcing Data set (CMFD). The CMFD is a high spatial resolution (0. 1°) forcing data set developed by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences  (He et al. , 2020; Yang et al. , 2010)  and is the amalgamation of a variety of data sources, including satellite products, reanalysis data sets and meteorological station measurements. This data set has good accuracy for surface meteorological variables and has been widely used in land surface process and hydrological modeling in China  (Huang et al.
, 2017; Lazhu et al. , 2016). The forcing data were extracted by the boundaries of lakes and then calculated through spatial averaging. However, considering that this data set are produced by merging various records of land stations, wind speed data are not suitable for representing the actual wind speed over lakes. Scaling of wind speed equation (Equation  1 ) recommended by  Hsu (1988)  was adopted to correct the bias. lake land 1. 62 1. 17, U U    (1) Here, U lake is the wind speed (m s -1 ) over the lake, and U land (m s -1 ) is the wind speed over land.
Lake Mean Depth Lake depth directly represents the thermal capacity of the lake and controls how long it takes to cool the lake in autumn and winter, thus controlling the ice-on date. FLake recommends using mean depth as an input parameter. In field observations, it is difficult to directly obtain the mean depth of lakes, especially for large lakes. We obtained lake mean depths from the HydroLAKES data set  (Messager et al. , 2016)  and used them in sensitivity experiments. We also estimated the effective lake depth (multiplying the mean depth by a scale factor) to closely reproduce the observed LSWT dynamics by minimizing the root mean square error (RMSE) between the simulations and observations. The scale factor ranges from 0. 25 to 4. 0 in the tuning process. The effective lake depth is often not the same as the measured lake mean depth.
Evaluation of FLake Performance in the Control Experiment In the control experiment (CTRL), ice albedo was calculated based on the default ice parameterization in FLake. Water albedo was set to a reference value of 0. 07. Lake mean depth was set to 10 m. K d was set to 3 m -1. Since the purpose of the ARC-Lake data set is to monitor the surface water temperature of the lake, excluding the ice temperature, the evaluations were only carried out during the ice-free season. Table  2  lists four statistical coefficients to demonstrate the average performances of FLake in simulating the LSWT in six subregions using CTRL settings. Overall, FLake roughly reproduced the seasonal cycle of LSWT, with R ranging from 0. 89 to 0. 98, and generally underestimated LSWT in the majority of lakes (Figure  S1 ).
Data Availability Statement Satellite-derived LSWTs used in the study are available to download from http://www. laketemp. net/home_ ARCLake/data_access. php (ARC-Lake, version 3. 0). The geomorphological characteristics of the lakes, including latitude, longitude, surface area, and mean depth, used in this study were obtained from the Hydro-LAKES database (version 1. 0, https://www. hydrosheds. org/pages/hydrolakes). The MODIS albedo product MCD34B3 (version 5) is available from the Land Processes Distributed Active Archive Center (LP DAAC; https://lpdaac. usgs. gov/data_access). Water clarity data in China are provided by  Wang et al. (2020) : Changes of water clarity in large lakes and reservoirs across China observed from long-term MODIS (https://doi. org/10. 1016/j. rse. 2020. 111949).
Cell Cycle Distribution Assay Hs 578T cells (2 × 10 5 ) were seeded in a 100 mm culture dishes. On the following day, the cells were treated with menin or control-ASO 200 nM for 48-72 h. Subsequent to trypsinization and washing with PBS, cells were fixed in 250 µL ice-cold 70% ethanol overnight at 4 • C. The cells were centrifuged (4500 rpm, 10 min, 4 • C), washed with cold PBS and treated with propidium iodide (PI)/RNase staining buffer (BD Pharmingen, San Diego, CA, USA) for 15 min at RT in the dark. DNA content was examined by flow cytometry using a LSRII SORP (Becton Dickinson, France) machine. The percentage of cells in G0, G1, S and G2/M phase was calculated using ModFit software 3. 2 (Becton Dickinson, San Diego, CA, USA). The assay was done with triplication.
After randomization, 12. 5 mg/kg menin-ASO or control-ASO were injected intraperitoneally 5 times per week for 12 weeks for ASO monotherapy groups. All mice were routinely observed for signs of systemic toxicity, and body weights were recorded. Tumor size was measured weekly with a caliper in three perpendicular dimensions (x = width, y = length, z = depth). Tumor volume (mm 3 ) was calculated as length × width × depth × 0. 5236. Data points were expressed as average tumor volume levels ± SEM. All animal procedures were performed in accordance with protocols approved by French law, following the European directives, and with appropriate institutional certification. In particular, Dr. Palma Rocchi has a personal agreement (#A13-477) for the animal handling and experimentation for this study.
Relative intensity-based label-free quantification (LFQ) was processed using the MaxLFQ 2 algorithm from the freely available MaxQuant computational proteomics platform, version 1. 6. 2 [29]. Analysis was done on biological triplicates, each injected three times on mass spectrometers. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  [30]  partner repository with the dataset identifier PXD024176.
Statistical Analysis Statistical analysis was performed using the GrapPad Prism program (GraphPad, San Diego, CA, USA). All the results were expressed as mean ± SEM. Significance of differences was assessed by a two-tailed Student's t-test. * p ≤ 0. 05 was considered significant, with ** p ≤ 0. 01 and *** p ≤ 0. 001.
Expression of Menin in Different Breast Cancer Cell Lines We first assessed menin expressions in 16 TNBC cell lines by Western blotting analysis. As shown in Figure  1 , menin is expressed in 6 out of 16 cell lines with the strongest expression in the Hs 578T cell line (Figure  1 ). Due to the high expression of menin, and limited efficient therapies in TNBC, Hs 578T cells were selected for further evaluation of the effect of menin silencing using ASO technology. proteomics platform, version 1. 6. 2 [29]. Analysis was done on biological triplicates, each injected three times on mass spectrometers. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  [30]  partner repository with the dataset identifier PXD024176.
Menin-ASO (ASO21) Reduces TNBC-Derived Xenograft Tumor Growth Twelve days following subcutaneous injection of Hs 578T cells, mice were treated with either ASO21 or control-ASO. At week 7, a drastic reduction in tumor growth was observed in the ASO21 arm (7. 275 ± 1931 vs. 28. 68 ± 5528 mm 3 in the control arm, p = 0. 0012) (Figure  5 ). Mice were all healthy and exhibited no toxicity throughout the entire experiment (data not shown). At week 12, tumors were removed, and weights were recorded. As expected, the average tumor weights matched the tumor volume measurements, and the average tumor weight with ASO21 (0. 36 ± 0. 15 g) was lower than the average weight with control-ASO tumors (4. 28 ± 0. 59 g). These results imply that the depletion of menin by ASO21 reduces the proliferation and tumorigenicity of TNBC Hs 578T derived-xenografts.
Biomedicines 2021, 9, x FOR PEER REVIEW 11 of 20 observed in the ASO21 arm (7. 275 ± 1931 vs. 28. 68 ± 5528 mm 3 in the control arm, p = 0. 0012) (Figure  5 ). Mice were all healthy and exhibited no toxicity throughout the entire experiment (data not shown). At week 12, tumors were removed, and weights were recorded. As expected, the average tumor weights matched the tumor volume measurements, and the average tumor weight with ASO21 (0. 36 ± 0. 15 g) was lower than the average weight with control-ASO tumors (4. 28 ± 0. 59 g). These results imply that the depletion of menin by ASO21 reduces the proliferation and tumorigenicity of TNBC Hs 578T derived-xenografts. mice. Means of tumor volumes were similar in all groups before therapy. When Hs 578T tumors reached 50 mm 3 , 5 mice were randomly selected for treatment with 12.
5 mg/kg menin-ASO or control-ASO. ASOs were injected intraperitoneally 5 times per week for 12 weeks for ASO monotherapy groups. Tumor size was measured weekly with a caliper in three perpendicular dimensions (x = width, y = length, z = depth). Tumor volume (mm 3 ) was calculated as length × width × depth × 0. 5236. Data points were expressed as average tumor volume levels ± SEM. Comparison of menin-ASO and control-ASO indicated that knockdown of menin by ASO inhibits TNBC tumor progression in vivo. * p ≤ 0. 05 was considered significant, with ** p ≤ 0. 01.
Discussion The MEN1 gene product, menin, was shown to play a dual role in breast cancer, an anti-proliferative and tumor suppressive function in the normal mammary epithelium Functional enrichment analysis showed that the most representative functions of menin interactors were involved in RNA 3 -end processing (Figure  6b ). Menin was found to be engaged in different protein complexes annotated on the CORUM database, indicating the wide diversity of menin's oncogenic functions in Hs 578T cells (Figure  6c, d , Table  1 ). The present menin's interactome identified a menin-associated histone methyltransferase complex, a chromatin regulatory network that drives promoter activation through H3K4me3 (Figure  6c, d ). Menin was suggested to be at the crossroad of the polyadenylation complex and BARD1-BRCA1-CSTF complex via interaction with the three subunits of the cleavage stimulation factor (CSTF1, CSTF2, CSTF3), highlighting its potential role in the regulation of mRNA 3end process (Figure  6d ).
Menin was previously shown to regulate apoptosis through transcriptional modulation of pro-apoptotic genes, such as caspase 8  [34]. Interestingly, menin was found to be associated with TSS region of FASTKD2 in LNCaP cells in our Chipseq analysis (personal data, under submission). All together, these observations suggest that menin might bind to IRF-2BP2 and suppress expression of proapoptotic genes in TNBC such as a pro-apoptotic factor FASTKD2, resulting in promotion of cellular survival, and depression of apoptosis. Results of the interactome analysis suggest a novel role of menin in polyadenylation via interaction with the cleavage stimulation factor (CSTF) which is a part of the polyadenylation and BARD1-BRCA1-CSTF complexes, as found in our functional enrichment analysis with CORUM database (Figure  6c, d ).
Acknowledgments: We would like to send special thanks to  José ADELAÏDE  ( CRCM, Marseille, France ) for providing us with the breast cancer cell lines used in the study, and  Manon RICHAUD  ( CRCM, Marseille, France ) for her suport with cell cycle analysis using cytometry, and to the  CRCM animal facility  for the help regarding in vivo testing of ASOs.
61) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying neighbour-joining and BioNJ algorithms to a matrix of pairwise distances estimated using the maximum composite likelihood approach and then selecting the topology with superior log likelihood value. A discrete Gamma distribution was used to model evolutionary rate differences among sites (five categories (+G, parameter=0. 7354)). The rate variation model allowed for some sites to be evolutionarily invariable ([+I], 87. 62 % sites). The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. There were a total of 1348 positions in the final dataset. Graphical representation and editing of the phylogenetic tree were performed with the Interactive Tree of Life (version 3.
Natural habitat is Heterorhabditis EPNs. The type strain of the subspecies is Q614 T (=DSM 111144 T =CCOS 1944 T =LMG 31959 T ). Whole genome sequences of this strain are available in the NCBI data bank under accession number JABBCS01. S1. heterorhabditis subsp. aluminescens subsp. nov. Q614 T were tested in parallel. The experiment was conducted twice. The obtained results were compared to those published previously  [16]. For further information refer to the original studies  [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] 21, 23, 24, 27]  : more than 80% of strains and/or conducted tests showed a positive reaction, "-": more than 80% of strains and/or conducted tests showed a negative reaction, "v": variable, about 50% of strains/conducted tests showed a positive reaction, "w": weak, more than 80% of strains and/or conducted tests showed a weak, positive reaction.
The type strain is symbiotically associated with Heterorhabditis indica EPNs. Their natural habitat is the intestines of these nematodes and the insects infected by them. The type strain is BA1 T (=DMS 111180 T =CCOS 1943 T =LMG 31957 T ). Whole genome sequences of this strain are available in the NCBI data bank under accession number JFGV01.
Background: The FAIR (Findable, Accessible, Interoperable, Reusable) principles were proposed in 2016 to set a path towards reusability of research datasets. In this systematic review, we assessed the FAIRness of datasets associated with peer-reviewed articles in veterinary epidemiology research published since 2017, specifically looking at salmonids and dairy cattle. We considered the differences in practices between molecular epidemiology, the branch of epidemiology using genetic sequences of pathogens and hosts to describe disease patterns, and nonmolecular epidemiology. Results: A total of 152 articles were included in the assessment. Consistent with previous assessments conducted in other disciplines, our results showed that most datasets used in non-molecular epidemiological studies were not available (i.
e. , neither findable nor accessible). Data availability was much higher for molecular epidemiology papers, in line with a strong repository base available to scientists in this discipline. The available data objects generally scored favourably for Findable, Accessible and Reusable indicators, but Interoperability was more problematic. Conclusions: None of the datasets assessed in this study met all the requirements set by the FAIR principles. Interoperability, in particular, requires specific skills in data management which may not yet be broadly available in the epidemiology community. In the discussion, we present recommendations on how veterinary research could move towards greater reusability according to FAIR principles. Overall, although many initiatives to improve data access have been started in the research community, their impact on the availability of datasets underlying published articles remains unclear to date.
Background The FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles were first published in 2016, providing a foundation to support increased re-use of scientific data  [1]. Mons et al. [2]  highlighted that FAIR is a continuum, which they represented with six levels, from "re-useless data" to "FAIR data with open access and functionally linked". The ultimate goal of this set of principles is for research objects (such as datasets) to be rendered reusable and increasingly re-used. A number of articles on the topic of FAIR principles, from the original group of authors and others have been published since 2017. Jacobsen et al. [3]  described some of the challenges and opportunities for implementation of each of the FAIR principles, while  Thompson et al. [4]  outlined the tools and technologies that are already available to support the adoption of FAIR data management, as well as the functionalities which are still lacking in that respect.
Such resources enable scientific communities to identify existing solutions before considering developing their own. There is however little visibility on the progress achieved by researchers in specific disciplines since the publication of the FAIR foundational paper. At the time of writing, very few published evaluations of FAIRness in publications and datasets were found in the literature. Van Reisen et al. [5]  reviewed the implementation of the FAIR principles reported in 100 randomly selected academic journal articles citing the foundational FAIR paper. They point out that life sciences represent the vast majority of the implementation, with 95 of the selected papers related to this discipline and a very limited representation (5 papers) of the other disciplines such as social science, humanities and other sciences.
Managing and improving animal health is not only critical to provide a secure access to safe animalsourced foods, but also as a key component of the global health ecosystem. The purpose of the work presented in this manuscript is to fill the current gap of knowledge about the adoption of FAIR principles in this discipline. Our study is based on a systematic review of the FAIRness of datasets associated with peer-reviewed articles relating to veterinary epidemiology research and published since 2017. The objectives are (i) to assess the state of FAIRness in this discipline, currently and over the past few years, and (ii) to explore how veterinary epidemiology research could move towards more reusability, in line with the goal of the FAIR principles. Many tools for evaluating the FAIRness of digital resources are available, in the form of questionnaires.
Given the importance of dairy cattle in epidemiological research, we chose to compare our snapshot of the state of FAIRness in salmonid epidemiological research with a similar snapshot in this species to address the two study objectives stated above. In this work, molecular epidemiology research, the branch of epidemiology using genetic sequences of pathogens or hosts to describe disease patterns, was considered separately from other branches of epidemiology, given the differences in the types of data that are collected and analysed in these disciplines. The results presented in this manuscript concern both molecular and non-molecular epidemiology in salmon, and nonmolecular epidemiology only in dairy cattle.
2 ). Raw data were available for 80% of the molecular epidemiology papers (24 out of 30) and 20% of the papers in other epidemiology sub-disciplines (12 out of 61). In addition, authors stated that raw data were available upon request in 3 out of the 55 papers for which they were not directly provided. For the 24 molecular epidemiology papers with raw data classified as available, genetic data were uploaded in specific-purpose repositories: GenBank (19 papers), NCBI's Sequence Read Archive (4 papers), PubMLST (3 papers) and the European Nucleotide Archive (2 papers), or in a generic-purpose repository (FigShare, 2 papers). The sum of the numbers in brackets is larger than 24 as six papers deposited data in two repositories. Genetic data were not available for the six remaining papers. Epidemiological data on the isolates or samples were also provided in two thirds of molecular epidemiology papers (21 out of 30).
Such data were generally shared as tables within the manuscript itself (14 papers), and/or as supplementary materials (either as PDF tables, 3 papers, or Word tables, 5 papers). Isolate data were shared in a MicroReact project for one paper and could be downloaded as a tab-separated file. For the 12 papers in other epidemiology subdisciplines for which raw data were available, these were deposited in an online repository in 5 cases: a genericpurpose repository (Mendeley Data, Dryad) or institutional repositories (Marine Data BC and Norwegian Marine Data Centre). In the other cases, the raw data were shared in the manuscript itself as Tables (4 papers), as supplementary materials (either as PDF tables, 1 paper, or Excel file, 2 papers). For two of these papers, it appeared that only part of the data used to conduct the work was made available.
Data availability in dairy cattle research At the end of the eligibility and inclusion steps (see flow chart in Supplementary File 1), a total of 61 papers concerning epidemiology research in dairy production were randomly selected and assessed for data availability. A third of the papers related to Canada or USA (20 papers out of 61), while the remainder originated from 26 other countries or were based on worldwide data (3 papers) (Fig. 1 , right panel). The assessment of dairy papers showed that raw data were available for 18% of them (11 out of 61) (Fig. 2 ). In ten of those, the raw data were provided within the manuscript. Raw data were deposited in a generic-purpose repository for the remaining paper (Scholars Portal Dataverse). In addition, authors stated that raw data were available upon request in 3 out of the 50 papers for which they were not directly provided.
Data availability statements The 152 articles assessed in this part of the study were published in 60 different journals. Among those, 17 included a formal data availability statement either as a dedicated section in the manuscript or as a supplementary item (Fig. 3 ). Such statements were introduced during the study period in some of the journals most represented by the selected articles, such as Aquaculture, Journal of Fish Diseases and Preventive Veterinary Medicine. These additional sections may be named "Availability of data and materials", "Data access", "Data accessibility", "Data availability", "Data profile", "Data summary" or "Research data for this article". Among papers not related to molecular epidemiology, data availability statements were provided in 6 and 10 of the dairy and salmonid articles, respectively.
In salmonid papers, the statements mentioned that the study datasets were available upon request (2 papers), that authors did not have permission to share them (1 paper), that the data had been deposited in an online repository (4 papers), or that "all relevant data are within the paper and its Supporting Information files" (or similar, 3 papers). In two of the three latter papers, the raw data did not appear to be available despite the statement. In dairy papers, the statements mentioned that study datasets were available upon request (3 papers), that authors did not have permission to share them (2 papers), or that the data had been deposited in an online repository (1 paper). Some individual journals may appear in more than 1 year, species or discipline. Note that 2020 publications were assessed until October 18th only.