Find research datasets worth reusing

opencc-by-4.0Dec 2006View details →

Fig. 1 in Industrial emissions and pesticides impact on agrobiocenosis biodiversity

Fig. 1: Insect families' distribution function of orders.

opencc-by-nd-4.0Dec 2014View details →

FIGURE 1 in The Impact Of Cucumber Nitrogen Nutrition On Life History Traits Of Tetranychus Urticae (Koch) (Acari: Tetranychidae)

FIGURE 1: Age specific survival rate (lx) and fecundity (mx) of Tetranychus urticae on four nitrogen treatments

Yields from paper: ALUMINIUM-26 FROM MASSIVE BINARY STARS II. ROTATING SINGLE STARS UP TO CORE-COLLAPSE AND THEIR IMPACT ON THE EARLY SOLAR SYSTEM

Title: Aluminium-26 From Massive Binary Stars II: ROTATING SINGLE STARS UP TO CORE-COLLAPSE AND THEIR IMPACT ON THE EARLY SOLAR SYSTEM Authors: Brinkman H.E., den Hartogh J. W., Doherty C.L., Pignatari M., Lugaro M. ================================================================================ Description of contents: A .tar.gz package containing three files with the complete set of yields from the models presented in this paper. YieldsNR.txt contains the yields for the non-rotating models and Yields150.txt and Yields300.txt the yields for the models rotating at an initial velocity of 150 and 300 km/s, respectively. ================================================================================

opencc-zeroSep 2021View details →

Lifelong exposure to artificial light at night impacts stridulation and locomotion activity patterns in the cricket Gryllus bimaculatus

This dataset contains data from a laboratory experiments described in the paper: "Levy, K., Wegrzyn, Y., Efronny, R., Barnea, A., & Ayali, A. 2021 Lifelong exposure to artificial light at night impacts stridulation and locomotion activity patterns in the cricket Gryllus bimaculatus. Proc. R. Soc. B 20211626. <a href="https://doi.org/10.1098/rspb.2021.1626">https://doi.org/10.1098/rspb.2021.162</a>". Artificial light at night (ALAN) is increasing worldwide,with most of the world population living under light-polluted skies. Growing awareness of the harmful effects of ALAN calls for more comprehensive understanding of these effects. The stridulation and locomotion patterns of adult male crickets reared under different lifelong ALAN intensities were monitored simultaneously for five consecutive days in custom-made anechoic chambers. Activity periods and acrophases were compared between the experimental groups. Control crickets exhibited a robust rhythm, stridulating at night and demonstrating locomotor activity during the day. In contrast, ALAN affected both the relative level and timing of the crickets' nocturnal and diurnal activity. ALAN induced free-running patterns, manifested in significant changes in the median and variance of the activity periods, and even arrhythmic behavior. The magnitude of disruption was light intensity dependent, revealing an increase in the difference between the activity periods calculated for stridulation and locomotion in the same individual. Our results demonstrate that ecologically-relevant ALAN intensities affect crickets' behavioral patterns, and may lead to decoupling of locomotion and stridulation behaviors at the individual level, and to loss of synchronization at the population level.

Impact of nonlinear hydrodynamic modelling on geometric optimisation of a spherical heaving point absorber

Due to the amount of iterative computation involved, researchers involved in geometric optimisation of wave energy devices typically employ linear hydrodynamic models. However, the exaggerated motion of wave energy devices, aided by energy maximising control action, challenges the assumptions upon which linear hydrodynamic modelling relies. Furthermore, the optimal device geometry is also sensitive to the nature of the energy-maximisation controller employed, and to the set of wave conditions over which the optimisation is carried out.          In order to focus on the essential issues, this study takes the simplest possible device for optimisation, a heaving sphere (with just one free parameter), but one which exhibits nonlinear hydrodynamic characteristics, due to the non-uniform cross-sectional area. The study examines the sensitivity to the inclusion of nonlinear Froude-Krylov forces. In addition, the sensitivity of the optimal device size to differences in the applied control algorithm is also studied, as are effects due to different representative sea state representations and performance evaluation criteria.

Impact of Type II LRRK2 inhibitors on signalling and mitophagy

Abstract Much effort has been devoted to the development of selective inhibitors of the LRRK2 as a potential treatment for LRRK2 driven Parkinson's disease. In this study we first compare the properties of Type I (GSK3357679A and MLi-2) and Type II (Ponatinib and GZD-824, Rebastinib and Ponatinib) kinase inhibitors that bind to the closed or open conformations of the LRRK2 kinase domain, respectively. We show that Type I and Type II inhibitors suppress phosphorylation of Rab10 and Rab12, key physiological substrates of LRRK2 and also promote mitophagy, a process suppressed by LRRK2. Type II inhibitors also display higher potency towards wild type LRRK2 compared to pathogenic mutants. Unexpectedly, we find that Type II inhibitors, in contrast to Type I compounds, fail to induce dephosphorylation of a set of well-studied LRRK2 biomarker phosphorylation sites at the N-terminal region of LRRK2, including Ser935. These findings emphasize that the biomarker phosphorylation sites on LRRK2 are likely reporting on the open- vs closed conformation of LRRK2 kinase and that only inhibitors which stabilize the closed conformation induce dephosphorylation of these biomarker sites. Finally, we demonstrate that the LRRK2[A2016T] mutant which is resistant to MLi-2 Type 1 inhibitor, also induces resistance to GZD-824 and Rebastinib suggestings this mutation could be exploited to distinguish off target effects of Type II inhibitors. Our observations provide a framework of knowledge to aide with the development of more selective Type II LRRK2 inhibitors. FILE DESCRIPTIONS The blots shown in the Figures were developed using the two fluorescent channels available in LI-COR (800 nM, green – 700 nM, red). Different contrasts of the same membranes have been uploaded. Figure 2           Figure_2A-quantitations.xls: raw data for charts in Figure 2A Figure_2A_700_1-LRRK2_Rab10_totals_GAPDH.png                                                 Top to bottom 1: total LRRK2 blot shown in Figure 2A 2: GPDH loading control for blots in Figure 2A and total Rab10 shown in Figure 2A. Antibodies for GAPDH and Rab10 were incubated together: GAPDH is detected below 37 kDa and total Rab10 below 25 kDa Figure_2A_700_2-Rab12_total.png Total Rab12 shown in Figure 2A Figure_2A_700_3-tubulin.png Top to bottom 3: alpha-tubulin loading control for blots in Figure 2A Figure_2A_800_1-LRRK2pS935_Rab10pT73.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 2A 2: Rab10 pThr73 blot shown in Figure 2A Figure_2A_800_2-Rab12pS105.png Phospho-Rab12 pSer105 shown in Figure 2A Figure_2B-quantitations.xls: raw data for charts in Figure 2B Figure_2B_700_1-LRRK2_Rab10_totals_GAPDH_tubulin.png Top to bottom 1: total LRRK2 blot shown in Figure 2B 2: GPDH loading control for blots in Figure 2B and total Rab10 shown in Figure 2B. Antibodies for GAPDH and Rab10 were incubated together: GAPDH is detected below 37 kDa and total Rab10 below 25 kDa 3: alpha-tubulin loading control for blots in Figure 2B Figure_2B_700_2-Rab12_total.png Total Rab12 shown in Figure 2B Figure-2B_800_1-LRRK2pS935_Rab10pT73.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 2B 2: Rab10 pThr73 blot shown in Figure 2B Figure-2B_800_2-Rab12pS105.png Phospho-Rab12 pSer105 shown in Figure 2B Figure_2C-quantitations: raw data for charts in Figure 2C Figure_2C_700_1-LRRK2_Rab10_totals_GAPDH.png Top to bottom 1: total LRRK2 blot shown in Figure 2C 2: GPDH loading control for blots in Figure 2C and total Rab10 shown in Figure 2C. Antibodies for GAPDH and Rab10 were incubated together: GAPDH is detected below 37 kDa and total Rab10 below 25 kDa 3: alpha-tubulin loading control for blots in Figure 2C – higher contrast of Figure-2C 700-3-alpha_tubulin – low contrast) Figure_2C_700_2-Rab12_total.png Total Rab12 shown in Figure 2C Figure_2C_700_3-tubulin.png Top to bottom 1-2: lower contrast of Figure-2C 680-1 LRRK2_Rab10_totals_GAPDH 3: alpha-tubulin loading control for blots in Figure 2C Figure_2C_800_1-LRRK2pS935_Rab10pT73.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 2C 2: Rab10 pThr73 blot shown in Figure 2C Figure_2C_800_2-Rab12pS105.png Phospho-Rab12 pSer105 shown in Figure 2C Figure_2D-quantitations.xls: raw data for charts in Figure 2D Figure_2D_700_1-LRRK2_total_tubulin.png Top to bottom 1: total LRRK2 blot shown in Figure 2D 2: lower contrast of total Rab10 blot show in Figure 2D 3: alpha-tubulin loading control for blots in Figure 2D Figure_2D_700_2-Rab10_total_1.png Top to bottom 1-3: higher contrast of Figure_2D_700_1-LRRK2_total_tubulin 2: total Rab10 blot show in Figure 2D Figure_2D_700_3-Rab12_total_1.png Total Rab12 shown in Figure 2C Figure_2D_700_4-Rab12_total_2.png Total Rab12 shown in Figure 2C, membrane incubated with the total Rab12 rabbit antibody from Proteintech Figure_2D_800_1_LRRK2pS935.png LRRK2 pSer935 blot shown in Figure 2D Figure_2D_800_2_Rab10pT73.png Rab10 pThr73 blot shown in Figure 2D Figure_2D_800_3_Rab10_total_2.png Total Rab10 shown in Figure 2D, membrane incubated with the rabbit anti-total Rab10 antibody from Abcam Figure_2D_800_4-Rab12pS105.png Phospho-Rab12 pSer105 shown in Figure 2D Figure 3 Figure_3_700_1-LRRK2_Rab10_totals_GAPDH.png Top to bottom 1: total LRRK2 blot shown in Figure 3. This total was multiplex with anti LRRK2 phospho-Ser935 antibody. 2: GPDH loading control for blots in Figure 3 and total Rab10 shown in Figure 3. Antibodies for GAPDH and Rab10 were incubated together: GAPDH is detected below 37 kDa and total Rab10 below 25 kDa. Figure_3_700_2-Rab10_total_2.png Total Rab10 shown in Figure 3, membrane incubated with the rabbit anti-total Rab10 antibody from Abcam. Figure_3_700_3-LRRK2_total_for_LRRK2pS910.png Total LRRK2 blot, not shown in the paper, multiplexed with the anti LRRK2 phospho-Ser910 antibody shown in Figure 3 Figure_3_700_4-LRRK2_totals_for_LRRK2pS955_pS973.png Total LRRK2 blots, not shown in the paper, multiplexed with the anti LRRK2 phospho-Ser955 and phospho-Ser973 antibodies shown in Figure 3 Figure_3_800_1-LRRK2pS935.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 3 2: lower contrast of Rab10 pThr73 blot shown in Figure 3 Figure_3_800_2-Rab10pT73.png Top to bottom 1: higher contrast of LRRK2 pSer935 blot shown in Figure 3 2: Rab10 pThr73 blot shown in Figure 3 Figure_3_800_3-LRRK2pS910.png LRRK2 pSer910 blot shown in Figure 3 Figure_3_800_4-LRRK2pS955.png LRRK2 pSer955 blot shown in Figure 3 Figure_3_800_5-LRRK2pS973.png LRRK2 pSer973 blot shown in Figure 3 Figure_3-quantitations.xls: raw data for charts in Figure 3 Figure 4 Figure_4A_4B_700_1-LRRK2_Rab10_totals_tubulin.png Top to bottom 1: total LRRK2 blot shown in Figure 4A 2: total Rab10 shown in Figure 4A 3: alpha-tubulin loading control for blots in Figure 4A 4: total LRRK2 blot shown in Figure 4B 5: total Rab10 shown in Figure 4B 6: alpha-tubulin loading control for blots in Figure 4B Figure_4A_4B_800_1-LRRK2pS935_Rab10pT73.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 4A 2: Rab10 pThr73 blot shown in Figure 4A 4: LRRK2 pSer935 blot shown in Figure 4B 5: Rab10 pThr73 blot shown in Figure 4B Figure_4A_4B-quantitations.xls: raw data for charts in Figure 4A_4B Figure_4C_700_1-LRRK2_Rab10_totals_GAPDH_tubulin.png Top to bottom 1: total LRRK2 blot shown in Figure 4C. This total was multiplex with anti LRRK2 phospho-Ser935 antibody. 2: GPDH loading control for blots in Figure 4C and total Rab10 shown in Figure 4C. Antibodies for GAPDH and Rab10 were incubated together: GAPDH is detected below 37 kDa and total Rab10 below 25 kDa Figure_4C_800_1-LRRK2pS935_Rab10pT73.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 4C 2: higher contrast of Rab10 pThr73 blot shown in Figure 4C Figure_4C_800_2-LRRK2pS935_Rab10pT73.png Top to bottom 1: lower contrast of LRRK2 pSer935 blot shown in Figure 4C 2: Rab10 pThr73 blot shown in Figure 4C Figure_4C-quantitations.xls: raw data for charts in Figure 4C Figure_4D-quantitations.xls: raw data for charts in Figure 4D Figure_4D_700_1-LRRK2_total_tubulin.png Top to bottom 1: total LRRK2 blot shown in Figure 4D 2: lower contrast of GAPDH and total Rab10 blot show in Figure 4D 3: alpha-tubulin loading control for blots in Figure 4D Figure_4D_700_2-Rab10_total_GAPDH.png     Top to bottom 1: higher contrast of total LRRK2 blot shown in Figure 4D 2: GAPDH loading control for blots in Figure 4D and total Rab10 blot show in Figure 4D 3: higher contrast of alpha-tubulin loading control for blots in Figure 4D Figure_4D_800_1-LRRK2pS935.png 1: LRRK2 pSer935 blot shown in Figure 4D 2: higher contrast of Rab10 pThr73 blot shown in Figure 4D Figure_4D_800_2-Rab10pT73.png 1: lower contrast of LRRK2 pSer935 blot shown in Figure 4D 2: Rab10 pThr73 blot shown in Figure 4D Figure 5 Figure_5A-quantitations.xls: raw data for charts in Figure 5A Figure_5A_700_1-LRRK2_total.png Top to bottom 1: total LRRK2 blot shown in Figure 5A 2: higher contrast of total Rab10 blot show in Figure 5A 3: higher contrast of alpha-tubulin loading control for blots in Figure 5A Figure_5A_700_2-Rab10_total.png Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 5A 2: total Rab10 blot show in Figure 5A 3: higher contrast of alpha-tubulin loading control for blots in Figure 5A Figure_5A_700_3-tubulin.png Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 5A 2: lower contrast of total Rab10 blot show in Figure 5A 3: alpha-tubulin loading control for blots in Figure 5A Figure_5A_800_1-LRRK2pS935.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 5A 2: higher contrast of Rab10 pThr73 blot shown in Figure 5A Figure_5A_800_2-Rab10pT73.png Top to bottom 1: lower contrast of LRRK2 pSer935 blot shown in Figure 5A 2: Rab10 pThr73 blot shown in Figure 5A Figure_5B_700_1-LRRK2_total.png Top to bottom 1: total LRRK2 blot shown in Figure 5B 2: higher contrast of total Rab10 blot show in Figure 5B 3: higher contrast of alpha-tubulin loading control for blots in Figure 5B Figure_5B_700_2-Rab10_total.png Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 5B 2: total Rab10 blot show in Figure 5B 3: higher contrast of alpha-tubulin loading control for blots in Figure 5B Figure_5B_700_3-tubulin.png Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 5B 2: lower contrast of total Rab10 blot show in Figure 5B 3: alpha-tubulin loading control for blots in Figure 5B Figure_5B_800_1-LRRK2pS935.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 5B 2: higher contrast of Rab10 pThr73 blot shown in Figure 5B Figure_5B_800_2-Rab10pT73.png Top to bottom 1: lower contrast of LRRK2 pSer935 blot shown in Figure 5B 2: Rab10 pThr73 blot shown in Figure 5B Figure_5B-quantitations.xls: raw data for charts in Figure 5B Figure 6 Figure_6A-quantitations.xls: raw data for charts in Figure 6A Figure-6A_700_1-LRRK2_Rab10_totals.png Top to bottom 1: total LRRK2 blot shown in Figure 6A 2: total Rab10 shown in Figure 6A 3: higher contrast of alpha-tubulin loading control for blots in Figure 6A Figure_6A_700_2-tubulin.png Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 6A 2: lower contrast of total Rab10 shown in Figure 6A 3: alpha-tubulin loading control for blots in Figure 6A Figure_6A_800_1-LRRK2pS935.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 6A 2: higher contrast of Rab10 pThr73 blot shown in Figure 6A Figure_6A_800_2-Rab10pT73.png Top to bottom 1: lower contrast of LRRK2 pSer935 blot shown in Figure 6A 2: Rab10 pThr73 blot shown in Figure 6A Figure_6B-quantitations.xls: raw data for charts in Figure 6B Figure_6B_700_1-LRRK2_Rab10_totals.png Top to bottom 1: total LRRK2 blot shown in Figure 6B 2: total Rab10 shown in Figure 6B 3: higher contrast of alpha-tubulin loading control for blots in Figure 6B Figure_6B_700_2-tubulin.png Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 6B 2: lower contrast of total Rab10 shown in Figure 6B 3: alpha-tubulin loading control for blots in Figure 6B Figure_6B_800_1-LRRK2pS935.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 6B 2: higher contrast of Rab10 pThr73 blot shown in Figure 6B Figure_6B_800_2-Rab10pT73.png Top to bottom 1: lower contrast of LRRK2 pSer935 blot shown in Figure 6B 2: Rab10 pThr73 blot shown in Figure 6B Figure_6C-quantitations.xls: raw data for charts in Figure 6C Figure_6C_700_1-LRRK2_Rab10_totals.png Top to bottom 1: total LRRK2 blot shown in Figure 6C 2: total Rab10 blot shown in Figure 6C 3: higher contrast of alpha-tubulin loading control for blots in Figure 6C Figure_6C_700_2-tubulin.png Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 6C 2: lower contrast of Rab10 shown in Figure 6C 3: alpha-tubulin loading control for blots in Figure 6C Figure_6C_800_1-LRRK2pS935.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 6C 2: higher contrast of Rab10 pThr73 blot shown in Figure 6C Figure_6C_800_2-Rab10pT73.png Top to bottom 1: lower contrast of LRRK2 pSer935 blot shown in Figure 6C 2: Rab10 pThr73 blot shown in Figure 6C Figure_6D-quantitations.xls: raw data for charts in Figure 6D Figure_6D_700_1-LRRK2_Rab10_totals.png Top to bottom 1: total LRRK2 blot shown in Figure 6D 2: total Rab10 blot shown in Figure 6D 3: higher contrast of alpha-tubulin loading control for blots in Figure 6D Figure_6D_700_2-tubulin.png Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 6D 2: lower contrast of total Rab10 shown in Figure 6D 3: alpha-tubulin loading control for blots in Figure 6D Figure_6D_800_1-LRRK2pS935.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 6D 2: higher contrast of Rab10 pThr73 blot shown in Figure 6D Figure_6D_800_2-Rab10pT73.png Top to bottom 1: lower contrast of LRRK2 pSer935 blot shown in Figure 6D 2: Rab10 pThr73 blot shown in Figure 6D Figure 7 Figure_7A-quantitations.xls: raw data for charts in Figure 7A Figure_7A_700_1_LRRK2_total_CoIp.png Immunoprecipitated total LRRK2 shown in Figure 7A Figure_7A_700_2_LRRK2_total_Lysates.png (Input for the CoIp) Top to bottom 1: total LRRK2 blot shown in Figure 7A 2: higher contrast of total Rab10 blot shown in Figure 7A 3: higher contrast of alpha-tubulin loading control for blots in Figure 7A Figure_7A_700_3_Rab10_total_tubulin_Lysates.png (Input for the CoIp) Top to bottom 1: lower contrast of total LRRK2 blot shown in Figure 7A 2: total Rab10 shown in Figure 7A 3: alpha-tubulin loading control for blots in Figure 7A Figure_7A_800_1_14-3-3_CoIp.png Blot of 14-3-3 co-immunoprecipitated with LRRK2 shown in Figure 7A Figure_7A_800_2_LRRK2pS935_CoIp.png Immunoprecipitated LRRK2pSer935 shown in Figure 7A Figure_7A_800_3_LRRK2pS935_Lysates.png Top to bottom 1: LRRK2 pSer935 blot shown in Figure 7A 2: higher contrast of Rab10 pThr73 blot shown in Figure 7A Figure_7A_800_4_Rab10pT73_Lysates.png Top to bottom 1: lower contrast of LRRK2 pSer935 blot shown in Figure 7A 2: Rab10 pThr73 blot shown in Figure 7A Figure_7A_800_5_14-3-3_Lysates.png 14-3-3 blot shown in Figure 7A (Input for the CoIp) Figure_7A_merge-700_800_LRRK2_total_LRRK2pS935.png Merged picture (in red LRRK2 total and in green LRRK2pS935) shown in Figure 7A Figure 7B: LSM710 laser scanning confocal microscope (Carl Zeiss) output files .lsm used to prepare Figure 7B Figure_7B_LRRK2_HA-empty_DMSO.lsm Figure_7B_LRRK2_HA-empty_GSK3357679A.lsm Figure_7B_LRRK2_HA-empty_GZD-824.lsm Figure_7B_LRRK2_HA-empty_MLi-2.lsm Figure_7B_LRRK2_Rab29_DMSO.lsm Figure_7B_LRRK2_ Rab29_GSK3357679A.lsm Figure_7B_LRRK2_ Rab29_GZD-824.lsm Figure_7B_LRRK2_ Rab29_MLi-2.lsm Figure_7C-quantitations.xls: raw data for charts in Figure 7C Top to bottom 1: LRRK2pSer1292 (800) 2: HA-Rab29 (700), Rab29 pThr71 (800) 3: alpha-tubulin (700) loading control for Figure 7C 4: LRRK2 total (700), LRRK2 pSer935 (800) 5: Rab10 total (700), Rab10 pThr73 (800) 6: alpha-tubulin (700) loading control for Figure 7C Figure_7C_700_1-HA-Rab29_LRRK2_total_tubulin.png: HA-Rab29, LRRK2 total and alpha-tubulin blot loading control shown in Figure 7C Figure_7C_700_2-Rab10_total.png: Rab10 total shown in Figure 7C Figure_7C_800_1-LRRK2pS1292_low_contrast_Rab10pT73.png: LRRK2 pSer1292 and Rab10 pThr73 blots shown in Figure 7C Figure_7C_800_2-LRRK2pS1292_high_contrast.png: LRRK2 pS1292 blot shown in Figure 7C Figure_7C_800_3-LRRK2pS935.png: LRRK2 pS935 blot shown in Figure 7C Figure_7C_800_4-Rab29pT71.png: Rab29 pThr71 blot shown in Figure 7C Figure 8: Nikon Eclipse Ti-S fluorescence microscope output files .nd2 used to prepare Figure 8 Figure_8-quantitations-Mitophagy.xls: raw data for charts in Figure 8 Figure_8_G2019S_CTL.nd2 Figure_8_G2019S_GSK3357679A_100nM.nd2 Figure_8_G2019S_GZD-824_30nM.nd2 Figure_8_KO_CTL.nd2 Figure_8_KO_GSK3357679A_100nM.nd2 Figure_8_KO_GZD-824_30nM.nd2 Figure_8_WT_CTL.nd2 Figure_8_WT_GSK3357679A_100nM.nd2 Figure_8_WT_GZD-824_30nM.nd2 Supplementary_Figure 1_Kinase_profiling_Kinase_list.xls: code for kinase screened in Supplementary Figures 1A, 1B, 1C, 1D. Each of the enzymes has been assigned to a 2 letter code and then an abbreviation. Supplementary_Figure 1A_Kinase_profiling_GZD-824.xls: raw data for the charts shown in Supplementary Figure 1A Supplementary_Figure 1B_Kinase_profiling_Rebastinib.xls: raw data for the chart shown in Supplementary Figure 1B Supplementary_Figure 1C_1D_Kinase_profiling_Ponatinib_ GSK3357679A.xls: raw data for the charts shown in Supplementary Figure 1C and 1D The first tab on each workbook shows the layout and the position of the inhibitor in the plates used for the screen and the final assay concentration. The inhibitors are in the same well positions throughout all the individual screen and raw data for each of the 140 kinase are reported in separated tabs. Underneath the plate layout of every kinase table is the mean for the control and blanks. Supplementary Figure 2 Supplementary_Figure_2-700_01-LRRK2_Rab10_totals_tubulin_GAPDH.png Top to bottom 1: total LRRK2 blot shown in Supplementary Figure 2 2: total Rab10 and GPDH loading control for blots shown in Supplementary Figure 2. Antibodies for GAPDH and Rab10 were incubated together: GAPDH is detected below 37 kDa and total Rab10 below 25 kDa. 3: alpha-tubulin loading control for blots in Supplementary Figure 2 Supplementary_Figure_2-800_01-LRRK2pS935_Rab10pT73.png Top to bottom 1: LRRK2 pSer935 blot shown in Supplementary Figure 2 2: Rab10 pThr73 blot shown in Supplementary Figure 2 Supplementary_Figure_2-800_02- Rab10pT73_total_Abcam.png Total Rab10 shown in Supplementary Figure 2, membrane incubated with the rabbit anti-total Rab10 antibody from Abcam Supplementary_Figure_2-quantitations.xls: raw data for charts in Supplementary Figure 2 Table 1 Table-1_01_Ponatinib_GZD-824.xls: raw data for the IC50 values in Table 1 Table-1_02_GSK3357679A_MLi-2.xls: raw data for the IC50 values in Table 1 Table-1_03_Rebastinib.xls: raw data for the IC50 values in Table 1

Data for: Ecological impacts of extreme climatic events on terrestrial and freshwater biota in the Arctic: A synthesis of current scientific evidence and opportunities

File contains the results of a literature review on the ecological impacts of extreme climatic events on terrestrial and freshwater biota in the Arctic.

opencc-zeroSep 2021View details →

Data from: Larval development in the Pacific oyster and the impacts of ocean acidification: differential genetic effects in wild and domesticated stocks

The adaptive capacity of marine calcifiers to ocean acidification (OA) is a topic of great interest to evolutionary biologists and ecologists. Previous studies have provided evidence to suggest that larval resilience to high pCO2 seawater for these species is a trait with a genetic basis and variability in natural populations. To date, however, it remains unclear how the selective effects of OA occur within the context of complex genetic interactions underpinning larval development in many of the most vulnerable taxa. Here we evaluated phenotypic and genetic changes during larval development of Pacific oysters (Crassostrea gigas) reared in ambient (~ 400 µatm) and high (~ 1600 µatm) pCO2 conditions, both in domesticated and naturalized 'wild' oysters from the Pacific Northwest, USA. Using pooled DNA samples, we determined changes in allele frequencies across larval development, from early "D-stage" larvae to metamorphosed juveniles (spat), in both groups and environments. Domesticated larvae had ~ 26% fewer loci with changing allele frequencies across developmental stages and < 50% as many loci affected by acidified culture conditions, compared to larvae from wild brood stock. Functional enrichment analyses of genetic markers with significant changes in allele frequency revealed that the structure and function of cellular membranes were disproportionately affected by high pCO2 conditions in both groups. These results indicate the potential for a rapid adaptive response of oyster populations to OA conditions; however, underlying genetic changes associated with larval development differ between these wild and domesticated oyster stocks and influence their adaptive responses to OA conditions.

Dataset for "A graph-theoretic approach for spatial filtering and its impact on mixed-type spatial pattern recognition in wafer bin maps"

This is the dataset used in the paper, Ezzat, Liu, Hochbaum, and Ding, 2021, “A graph-theoretic approach for spatial filtering and its impact on mixed-type spatial pattern recognition in wafer bin maps,” IEEE Transactions on Semiconductor Manufacturing, Vol. 34, pp. 194-206.

Dataset of impacts of weather and climate services on farming in Burkina Faso 2019 and 2020

The dataset contains the results of two surveys realized in 2019 and 2020 in the Municipality of Tenado, Burkina Faso. The surveys were conducted in October 2019 and in November 2020 using structured questionnaires translated and administered in the local language by trained enumerators. Moreover, yield plots were placed in farmers’ fields and yield was measured on site. The sample at the Tenado site consisted for each survey in approximately 300 farmers (150 treated and 150 control) in 12 villages for each year. The treatment is the training in the use of Weather and Climate Services in agriculture. The control group is random and represents the entire population. The treatment group is also random, from the participants in training. Observed variables are:  N. seedings Quantity of seeds (kg/ha) N. fertilizations Quantity fertilizers (kg/ha) Working days Yield (kg/ha) Costs (FCFA/ha) <ul> <li>Seeds cost (FCFA/ha)</li> </ul> <ul> <li>Fertilizers cost (FCFA/ha)</li> </ul> <ul> <li>Labor cost (FCFA/ha)</li> </ul> Income (FCFA/ha) Gross benefit (FCFA/ha) The market price of sorghum and the cost of seeds, fertilizer and labor were considered stable over the 2 years and in particular the sorghum price was 200 FCFA per kg, while the costs were 350 FCFA for 1 kg of seeds, and 450 FCFA for 1 kg of fertilizer. Labor cost is accounted as the opportunity costs of working time considering that 1,500 FCFA is the daily wage in agriculture. Income was computed multiplying yield by the price of sorghum and the gross benefit is the income minus the costs.

Climate change impacts on ecosystems and adaptation options in nine countries in southern Africa: What do we know?

Dataset used in the systematic review of scientific articles published during the period 2000-2020, which (i) addressed observed and projected impacts of climate change on different species, populations and ecosystems in nine southern African countries, and (ii) formulated management and policy responses aiming to mitigate these impacts.

Racism in Medicine: Impact of Discussion Among Medical Students

Purpose This study evaluated the impact of the Racism in Medicine Summit on student perceptions of various topics related to racism in medicine. The Summit was organized at the Wayne State University School of Medicine (WSUSOM) to educate students, faculty and staff on how structural racism affects the residents of Detroit and the historical relationship between health care and vulnerable populations. The Summit aimed at providing context for what students in Detroit will encounter as physicians-in- training and the skills they will need to master while working within similar communities. Method Qualtrics surveys were created and distributed via email to attendees before and after the event. Responses were obtained via Likert scale and open-text questions. Results A total of 342 out of 445 participants (77%) completed both the pre- and post-survey. Quantitative analysis in post-survey responses revealed more familiarity among participants regarding specific instances of racism in the history of medicine, greater extent of thinking the history of racism impacts present-day Detroit residents, greater extent of thinking that racism influences medical care and/or medical outcomes, and belief that racism is reflected in medical research, compared to pre-survey responses (p < 0.001). Participants also reported more often considering racial or societal influences when learning medicine and more knowledge of what they can do to combat racism as a student and physician (p < 0.001). Qualitative analysis revealed seven themes among participants: the history of racism in Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation medicine, personal reflection, racism in research, bias and microaggression, actions to take against racism, resources for anti-racist education, and racism in medical education. Conclusion Demonstrable changes in medical student attitude and awareness surrounding topics of racism and health care were achieved after the Racism in Medicine Summit. This can serve as a model for other medical schools to raise awareness about racism in medicine.

Impact of 3D Cloud Structures on the Atmospheric Trace Gas Products from UV-VIS Sounders: Synthetic dataset for validation of trace gas retrieval algorithms

This data set is described in detail in a paper submitted to AMTD: Impact of 3D Cloud Structures on the Atmospheric Trace Gas Products from UV-VIS Sounders - Part I: Synthetic dataset for validation of trace gas retrieval algorithms by Claudia Emde, Huan Yu, Arve Kylling, Michel van Roozendael, Kerstin Stebel, Ben Veihelmann, and Bernhard Mayer   The subdirectory boxcloud includes synthetic reflectances for clearsky, 1D cloud and box cloud. The subdirectory les_cloud includes synthetic reflectances for the LES cloud scenario for low earth orbit (leo) and geostationary orbit (geo). All data are provided in netcdf format.

opencc-zeroOct 2021View details →

Exploring changes in ecosystem service values in strongly human-impacted, contrasting agro-ecological environments

Evaluating the impacts of land-use/land-cover (LULC) changes on ecosystem service values (ESVs) is essential for sustainable use and management of ecosystems. In this study, we evaluated the impact of LULC changes on ESVs over the period 1982–2016/17 in contrasting, strongly human-impacted agro-ecological environments: Guder (highland), Aba Gerima (midland), and Debatie (lowland) watersheds of the Upper Blue Nile basin, Ethiopia. During the study period, the continuous expansion of cultivated land at the expense of natural vegetation (bushland, forest, and grazing land) severely reduced the total ESV by about US$58 thousand (35%) in Aba Gerima and US$31 thousand (29%) in Debatie watersheds. In contrast, the unprecedented expansion of plantations, mainly through the planting of Acacia decurrens, helped the total ESV rebound by about US$71 thousand (54%) in Guder watershed after 2006, after it had decreased by about US$61 thousand (32%) between 1982 and 2006. The reduction in natural forest area was the major contributor to the loss of total ESV in the study watersheds, ranging from a reduction of US$31 thousand (63%) in Debatie to US$96.9 thousand (70%) in Guder between 1982 and 2016/17. On an area-specific basis, LULC changes reduced the average ESV from US$560 ha–1 yr–1 (1982) in Guder to US$306 ha–1 yr–1 (2017) in Debatie watersheds. Specific ESVs such as provisioning (mainly as food production) and regulating services (mainly as erosion control and climate regulation) accounted for most of the total ESVs estimated for the study watersheds. In most cases the total and specific ESVs of the watersheds were negatively associated with the population growth, which in turn was positively associated with the expansion of cultivated land over the study period. In Guder watershed, however, ESVs were positively associated with population growth, especially after 2012. This resulted primarily from the conversion of cultivated land to plantations (predominantly with nitrogen-fixing Acacia decurrens trees) because of the farmers' growing desire to rehabilitate degraded cultivated land while simultaneously generating income through the sale of charcoal from this fast-growing tree. Our results suggest, therefore, that future policy measures and directions should focus on improving vegetation cover through planting multipurpose trees such as Acacia decurrens to prevent future loss of ESV in the midland and lowland regions of the Upper Blue Nile basin and beyond.

Dataset for research paper "An Impact-Driven Approach to Predict User Stories Instability"

Dump of all the data from an SQL server containing all the data used for the research in the research paper "An Impact-Driven Approach to Predict User Stories Instability", which is currently under review for Requirements Engineering journal.

opencc-zeroOct 2021View details →

Going against the flow: barriers to gene flow impact patterns of connectivity in cryptic coral reef gobies throughout the western Atlantic

Aim: Complex oceanographic features have historically caused difficulty in understanding gene flow in marine taxa. Here, we evaluate the impact of potential phylogeographic barriers to gene flow and assess demography and evolutionary history of a coral reef goby species complex. Specifically, we test how the Amazon River outflow and ocean currents impact gene flow. Location: Western Atlantic. Taxon: The bridled goby (Coryphopterus glaucofraenum) and sand-canyon goby (C. venezuelae) species complex. Methods: We used mitochondrial DNA and 2401 genomic SNPs to investigate evolutionary history and test hypotheses of how major barriers impact species-level differentiation. We used clustering algorithms and pairwise FST to assess population differentiation caused by minor barriers within and among regions. Finally, we tested alternate hypotheses of demographic history via coalescent simulations to determine the most plausible spread across the Western Atlantic. Results: We found two unique clades of C. glaucofraenum along the Brazilian coast and Atol das Rocas (AR) that are more closely related to C. venzuelae. Further genetic structure within the Caribbean and separately along the Brazilian coast led to at least two distinct populations in each location. Coalescent simulations indicated that an ancestral population of C. venezuelae split from C. glaucofraenum in the Caribbean, dispersed to Brazil, then spread to AR. Main Conclusions: Species-level genetic differentiation has resulted from the Amazon River outflow and isolation of AR. Population differentiation within the Caribbean matched previous studies indicating an east-west pattern of divergence. Brazilian population differentiation was impacted by the cold-water upwelling at Cabo Frio. Overall, this research highlights how barriers to gene flow impact speciation and genetic structure within western Atlantic gobies and provides insight into the role oceanographic features have in the speciation process of fishes.

opencc-by-4.0Dec 2018View details →

This is sample of the Data used to analyse AMV impacts on the global monsoon [Monerie et al. GRL]

These data have been generated using MetUM-GOML2, and are used to analyse the impact of an anomaly cool/warm North Atlantic Ocean on tropical precipitation. These shared data could be used to reproduce the results shown in Monerie et al. More data will be available through the EU PRIMAVERA project via BADC. For more details about the metadata/having more data, please contact me at p.monerie@reading.ac.uk

opencc-zeroOct 2022View details →

Data From: Long-term winter food supplementation shows no significant impact on reproductive performance in Mountain Chickadees in the Sierra Nevada Mountains

Supplemental feeding of wild animal populations is popular across many areas of the world and has long been considered beneficial, especially to avian taxa. Over four billion dollars are spent by hobby bird feeders in the United States each year alone. However, there is mixed evidence whether wildlife feeding is beneficial, including when it is implemented as a conservation management tool, a targeted experimental design, or an avocation. Much of the current evidence suggests that providing supplemental food is advantageous to the reproductive output and general survival of focal taxa. However, many of these studies are limited in scope and duration, leaving possible negative impacts unaddressed. This is particularly true regarding passive backyard feeding, which describes the majority of supplemental feeding, including the immense effort of millions of public enthusiasts. Here we show that winter supplemental feeding prior to reproduction had no significant impact on a range of reproductive parameters in a resident, montane passerine species, the Mountain Chickadee (Poecile gambeli). This population resides in an intact natural environment with no exposure to supplemental food beyond our experimental treatments, and individual birds were tracked across six years using radio frequency identification technology. Our results add to the growing evidence that supplemental feeding alone, isolated from the effects of urban environments, may have little to no impact on the population dynamics of some avian taxa.

opencc-zeroOct 2022View details →

Data from: Environmental context determines pollution impacts on ecosystem functioning

Global change assessments have typically ignored synthetic chemical pollution, despite the rapid increase of pharmaceuticals, pesticides, and industrial chemicals in the environment. Part of the problem reflects the multifarious origins of these micropollutants, which can derive from urban and agricultural sources. Understanding how micropollutants harm ecosystems is a major scientific challenge due to asymmetries of stress across trophic levels and ecological surprises generated by multiple drivers interacting in human-impacted landscapes. We used field assays above and below municipal wastewater treatment plants (WWTPs) in 60 sampling locations across 20 Swiss streams to test how micropollutants and nutrients originating from WWTPs affect two trophic levels (microbes and detritivores) and their role in leaf litter processing. Wastewater impacts were asymmetric across trophic levels, with the detritivore contribution declining relative to microbial-driven decomposition. The strength of negative impacts was context-dependent, peaking at sites with the highest upstream abundances of detritivorous invertebrates. Diffuse pollution from intensive agriculture and wastewater-born micropollutants contributed to reduced litter processing rates, including indirect effects apparently mediated through negative influences of insecticides on detritivores. Asymmetries in stress responses across trophic levels can introduce quantitative changes in consumer-resource dynamics and leaf litter processing. This means functional redundancies at different trophic levels are insufficient to compensate for biodiversity losses, causing environmental stressors such as chemical pollutants to have pervasive ecosystem-level impacts.