Dane Badawcze UW University of Warsaw
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Relational selves, voice quality and personality impressions
No full textThis repository contains datasets from two experimental studies investigating the effects of activating different relational selves on voice characteristics and personality impressions. The research was conducted at the University of Warsaw between 2024-2025.The first study (N=95) examined differences between "Me with my teacher" and "Me with my friend" relational selves, while the second study (N=112) focused on "Me with my mother" and "Me with my friend" relational selves. In both studies, participants recorded voice messages after sequential activation of two relational selves (e.g., teacher-teacher, friend-friend, teacher-friend, friend-teacher in Study 1). Recordings were made using a Sony digital recorder (24 bit mono, 96000 Hz, WAV format) with a Shure WH20 headset microphone.The datasets include acoustic measurements analyzed using PRAAT software, capturing parameters such as speech duration, speech rate, pitch characteristics (mean, range, standard deviation), intensity measures (mean, range, standard deviation), and degree of voice breaks. For each participant, these parameters were measured after each of two sequential relational self activations. In variable names, "first measurement" and "second measurement" indicate the measurement taken after the first or second relational self-activation.Additionally, the data contains personality impressions rated by independent judges (48 raters in Study 1, 16 raters in Study 2). These ratings include assessments of Big Five personality traits using the Ten-Item Personality Inventory (TIPI), as well as ratings of self-esteem, intelligence, and voice attractiveness, which were measured using 1-item scales. Each voice sample was evaluated for both relational self conditions.Files included:Study 1 acoustic features.sav - Acoustic measurements from Study 1 examining teacher vs friend conditionsStudy 1 personality impressions.sav - Personality ratings from Study 1Study 2 acoustic features.sav - Acoustic measurements from Study 2 examining mother vs friend conditionsStudy 2 personality impressions.sav - Personality ratings from Study 2</p
Wpływ nadekspresji mikroRNA-126 na zmiany w transkryptomie ludzkich mioblastów
No full textProjekt dotyczy wpływu nadekspresji mikroRNA-126-3p lub mikroRNA-5p na zmiany w transkryptomie ludzkichch mioblastów. Komórki transfekowano 25nM mimikowym mikroRNA. Po 48h wyizolowano całkowite RNA i wykonano analizę NGS (Next Generation Sequencing Core Facility, Centrum Nowych Technologii). Dane z wysokoprzepustowego sekwencjonowania występują w postaci:„rawCounts” - pliku z surowymi danymi (.txt)„comparsion” - list zidentyfikowanych transkryptów (.xlsx)dla poszczególnych wariantów eksperymentu : 3p1, 3p2,3p3 – transfekcja mikro RNA-126-3p; 5p1,5p2,5p3 – transfekcja mikroRNA-126-5p, K1,K2,K3- kontrola.The project focuses on the impact of microRNA-126-3p or microRNA-126-5p overexpression on changes in the human myoblasts transcriptome. The cells were transfected with 25nM mimic microRNA. After 48 hours, total RNA was isolated and NGS analysis was performed (Next Generation Sequencing Core Facility, Center for New Technologies). Data from high-throughput sequencing are available as:„rawCounts” – non-normalized reads associated with each reference transcript (.txt)„comparsion” - results of expression comparison for each detected transcript (.xlsx)for individual experimental variants: 3p1, 3p2, 3p3 – transfection with microRNA-126-3p; 5p1, 5p2, 5p3 – transfection with microRNA-126-5p, K1, K2, K3 – control.</p
Large-area growth of high-optical-quality MoSe2/hBN heterostructures with tunable charge carrier concentration
No full textThe dataset consists of experimental data related to the article: Large-area growth of high-optical-quality MoSe2/hBN heterostructures with tunable charge carrier concentration (DOI: 10.1021/acsami.4c12559).The presented numerical data were directly used to create graphs included in the cited publication. Files:Figure3: Collected data used to create Figure 3 in the article.Photoluminescence (PL) data of MBE MoSe2 measured at cryogenic temperatures (532 nm laser excitation) for various substrates (MOVPE and exfoliated hBN) and various MBE processes. 1st column: energy (eV), rest of the columns: PL intensity measured for different substrates and processes.Figure4a: Collected data used to create Figure 4a in the article.MoSe2 photoluminescence spectra obtained for the material grown on epitaxial MOVPE hBN, collected at T=5 K, with 532 nm laser excitation. Column 1: energy (eV), column 2: PL intensity.Figure4b: Collected data used to create Figure 4b in the article.MoSe2 photoluminescence spectra obtained for the material grown on exfoliated hBN, collected at T=5 K, with 532 nm laser excitation. Column 1: energy (eV), column 2: PL intensity.Figure5_X0A_peak_position_map_epitaxial: Collected data used to create a map of the neutral exciton peak position for the MoSe2 growth on epitaxial hBN included in Figure 5 in the article.Results of the Lorentzian function fitting to the photoluminescence mapping performed at cryogenic temperatures (T = 5 K, 532 nm laser, step 2 μm). Column 1 and row 1: position on the sample (um), rest of the data: energy of the neutral exciton peak corresponding to the indicated position on the sample.Figure5_XC_peak_position_map_epitaxial: Collected data used to create a map of the charged exciton peak position for the MoSe2 growth on epitaxial hBN included in Figure 5 in the article.Results of the Lorentzian function fitting to the photoluminescence mapping performed at cryogenic temperatures (T = 5 K, 532 nm laser, step 2 μm). Column 1 and row 1: position on the sample (um), rest of the data: energy (eV) of the charged exciton peak corresponding to the indicated position on the sample.Figure5_XA_FWHM_map_epitaxial: Collected data used to create a map of the neutral exciton peak width for the MoSe2 growth on epitaxial hBN included in Figure 5 in the article.Results of the Lorentzian function fitting to the photoluminescence mapping performed at cryogenic temperatures (T = 5 K, 532 nm laser, step 2 μm). Column 1 and row 1: position on the sample (um), rest of the data: width (meV) of the neutral exciton peak corresponding to the indicated position on the sample.Figure5_XC_FWHM_map_epitaxial: Collected data used to create a map of the charged exciton peak width for the MoSe2 growth on epitaxial hBN included in Figure 5 in the article.Results of the Lorentzian function fitting to the photoluminescence mapping performed at cryogenic temperatures (T = 5 K, 532 nm laser, step 2 μm). Column 1 and row 1: position on the sample (um), rest of the data: width (meV) of the charged exciton peak corresponding to the indicated position on the sample.Figure5_X0A_peak_position_map_exfoliated: Collected data used to create a map of the neutral exciton peak position for the MoSe2 growth on exfoliated hBN included in Figure 5 in the article.Results of the Lorentzian function fitting to the photoluminescence mapping performed at cryogenic temperatures (T = 5 K, 532 nm laser, step 2 μm). Column 1 and row 1: position on the sample (um), rest of the data: energy of the neutral exciton peak corresponding to the indicated position on the sample.Figure5_XC_peak_position_map_exfoliated: Collected data used to create a map of the charged exciton peak position for the MoSe2 growth on exfoliated hBN included in Figure 5 in the article.Results of the Lorentzian function fitting to the photoluminescence mapping performed at cryogenic temperatures (T = 5 K, 532 nm laser, step 2 μm). Column 1 and row 1: position on the sample (um), rest of the data: energy (eV) of the charged exciton peak corresponding to the indicated position on the sample.Figure5_XA_FWHM_map_exfoliated: Collected data used to create a map of the neutral exciton peak width for the MoSe2 growth on exfoliated hBN included in Figure 5 in the article.Results of the Lorentzian function fitting to the photoluminescence mapping performed at cryogenic temperatures (T = 5 K, 532 nm laser, step 2 μm). Column 1 and row 1: position on the sample (um), rest of the data: width (meV) of the neutral exciton peak corresponding to the indicated position on the sample.Figure5_XC_FWHM_map_exfoliated: Collected data used to create a map of the charged exciton peak width for the MoSe2 growth on exfoliated hBN included in Figure 5 in the article.Results of the Lorentzian function fitting to the photoluminescence mapping performed at cryogenic temperatures (T = 5 K, 532 nm laser, step 2 μm). Column 1 and row 1: position on the sample (um), rest of the data: width (meV) of the charged exciton peak corresponding to the indicated position on the sample.Figure5_histograms: data used to create histograms included in Figure 5 in the article.1st row indicates the sample and excitonic peak (XC - charged exciton, X0A - neutral exciton) for which the data are presented. Peak positions are given in eV and peak widths in meV.Figure6b: data used to create Figure 6b in the article.A comparison of PL spectra recorded for sample hBN 1 MBE process 3 (T=5 K, 532 nm laser) for different gate voltages (-30 V, 2 V, 30 V). 1 column: energy (eV), 2-4 columns: PL intensities recorded for gate voltages -30 V, 2 V, 30 V.Figure6c: data used to create Figure 6c in the article.PL spectra recorded for sample hBN 1 MBE process 3 (T=5 K, 532 nm laser) for a range (-30 V: -2 V) of gate voltages. 1 column: energy (eV), the rest of the columns: PL intensities recorded for the range of gate voltages.Figure6d: data used to create Figure 6d in the article.Results of the Lorentzian profile fitting to the PL spectra recorded for sample hBN 1 MBE process 3 (T=5 K, 532 nm laser) for a range (-30 V: -2 V) of gate voltages. 1 column: gate voltage (V), 2 column: charged exciton peak area, 3 column: neutral exciton peak area.</p
Raw and processed data for the model rhodium(I) complex studied by time-resolved Laue diffraction
No full textThis data set contains all raw and processed (including time-resolved Laue) X-ray diffraction data for the model rhodium(I) complex. The data supplements contribution published in The Journal of Physical Chemistry Letters under the following DOI: 10.1021/acs.jpclett.4c02476 [1]. The chemical system studied in this contribution is (compound acronym is used):Rh-4-Br – new complex and new crystal structure.The supplementary data, in relation to the published contribution, contains specifically:1. Time-resolved X-ray Laue diffraction data sets, both raw and processed. The data sets were collected within the pump-probe mode (pump – laser pulse, probe – X-ray pulse) at the BioCARS 14-ID-B beamline of the Advanced Photon Source (APS) synchrotron [2]. At this beamline the short X-ray pulses are isolated from the synchrotron train via set of shutters and choppers. The X-ray pulse is then electronically synchronized with the laser using the FPGA module. All synchrotron data presented here and analysed in the original paper [1] use the polychromatic pink X-ray beam. Data sets for the purpose of the original study [1] were later processed using the home-made software LAUEUTIL [3,4] and LAUEPROC [5,6] based on the RATIO method [7] utilizing intensity ratios measured at the synchrotron source. Further data structure refinement was done with the LASER program [8,9,10], written specifically for the purpose of refining excited-state structures in crystals.2. Spectroscopic data for the title complex. The time-resolved data was collected using a custom-build setup at the University of Warsaw featuring an Ekspla NT230 laser, an Olympus IX73 microscope, and a Princeton Instruments spectrograph with a PI-MAX4 iCCD detector. Data sets presented were analysed and visualized with the ORIGIN software. A Shimadzu UV-2600i spectrometer was used for steady-state UV-Vis measurements.3. Results of quantum-chemical computations done with the GAUSSIAN 16 program package [11]. The calculations include QM/MM geometry optimization (QM – quantum mechanics, MM – molecular mechanics), transition density data, time-dependent density functional theory (TDDFT) results, and counterpoise energy calculations performed at the DFT(CAM-B3LYP)/6-31G**+Lanl2DZ level of theory (for details see the original publication [1]). Data for isolated molecule optimizations at other theory levels are also provided for comparison.4. Raw data, data processing and refinement details and other information for studied crystal structure of Rh-4-Br. This data served as a reference structure for further use with RATIO method [7] and use of the LASER program [8,9,10] mentioned above. Data set was collected on a Bruker AXS D8 Quest laboratory diffractometer. Data collection and further processing were done with the native diffractometer software [12,13]. Most of the later manipulations were performed with the SHELXT (crystal structure solution) [14], SHELXL (crystal structure refinement) [15] and OLEX2 (graphical interface for SHELXL) [16] computer programs. The CIF files were submitted to the Cambridge Crystallographic Database (CSD) [17] (as indicated in the original publication [1]).All data presented here allows for the direct comparison and critical scrutiny of the published results. Whenever needed the metadata presented here might be slightly corrected in the future to eliminate any possible mistakes and/or account for suggestions from other researchers. Changes are to be made without prior notification, but with indication what correction has been made and when (repository contains a version control system). Note the Authors are not to be held liable for any potential damages caused by misusing of the data and/or software deposited. The data presented here is made open access for the sake of scientific community fair results presentation.References[1] Łaski, P.; Bosman, L.; Drapała, J.; Kamiński, R.; Szarejko, D.; Borowski, P.; Roodt, A.; Henning, R.; Brink, A.; Jarzembska, K.N., Nanosecond-lived excimer observation in a crystal of a rhodium(I) complex via time-resolved X‑ray Laue diffraction. J. Phys. Chem. Lett.T 2024, 15, 10301.[2] (a) Graber, T.; Anderson, S.; Brewer, H.; Chen, Y.-S.; Cho, H.; Dashdorj, N.; Henning, R.W.; Kosheleva, I.; Macha, G.; Meron, M.; Pahl, R.; Ren, Z.; Ruan, S.; Schotte, F.; Šrajer, V.; Viccaro, P.J.; Westferro, F.; Anfinrud, P.; Moffat, K., BioCARS: a synchrotron resource for time-resolved X-ray science. J. Synchrotron Rad. 2011, 18, 658. (b) Henning, R.W.; Kosheleva, I.; Šrajer, V.; Kim, I.-S.; Zoellner, E.; Ranganathan, R., BioCARS: Synchrotron facility for probing structural dynamics of biological macromolecules. Struct. Dyn. 2024, 11, 014301.[3] Kalinowski, J.A.; Makal, A.; Coppens, P., The LaueUtil toolkit for Laue photocrystallography: I. Rapid orientation matrix determination for intermediate size unit-cell Laue data. J. Appl. Cryst. 2011, 44, 1182.[4] Kalinowski, J.A.; Fournier, B.; Makal, A.; Coppens, P., The LaueUtil toolkit for Laue photocrystallography. II. Spot finding and integration. J. Synchrotron Rad. 2012, 19, 637.[5] Szarejko, D.; Kamiński, R.; Łaski, P.; Jarzembska, K.N., Seed-skewness algorithm for X-ray diffraction signal detection in the time-resolved synchrotron Laue photocrystallography. J. Synchrotron Rad. 2020, 27, 405.[6] Kamiński, R.; Szarejko, D.; Pedersen, M.N.; Hatcher, L.E.; Łaski, P.; Raithby, P.R.; Wulff, M.; Jarzembska, K. N., Instrument-model refinement in normalised reciprocal-vector space for X-ray Laue diffraction. J. Appl. Cryst. 2020, 53, 1370.[7] Coppens, P.; Pitak, M.; Gembicky, M.; Messerschmidt, M.; Scheins, S.; Benedict, J.B.; Adachi, S.-I.; Sato, T.; Nozawa, S.; Ichiyanagi, K.; Chollet, M.; Koshihara, S.-Y., The RATIO method for time-resolved Laue crystallography. J. Synchrotron Rad. 2009, 16, 226.[8] Ozawa, Y.; Pressprich, M.R.; Coppens, P., On the analysis of reversible light-induced changes in molecular crystals. J. Appl. Cryst. 1998, 31, 128.[9] Vorontsov, I.; Pillet, S.; Kamiński, R.; Schmøkel, M.S.; Coppens, P., LASER – a program for response-ratio refinement of time-resolved diffraction data. J. Appl. Cryst. 2010, 43, 1129.[10] Coppens, P.; Kamiński, R.; Schmøkel, M.S., On R factors for dynamic structure crystallography. Acta Cryst. Sect. A 2010, 66, 626.[11] Frisch, M.J. et al., GAUSSIAN 16, Gaussian, Inc., 2016, Wallingford, Connecticut, United States.[12] APEX, SAINT, Bruker AXS Inc., 2016, Madison, Wisconsin, United States.[13] Krause, L., Herbst-Irmer, R., Sheldrick G.M., Stalke D., Comparison of silver and molybdenum microfocus X-ray sources for single-crystal structure determination. J. Appl. Cryst. 2015, 48, 3.[14] Sheldrick, G.M., SHELXT – integrated space-group and crystal-structure determination. Acta Cryst. Sect. A 2015, 71, 3.[15] Sheldrick, G.M., Crystal structure refinement with SHELXL. Acta Cryst. Sect. C 2015, 71, 3.[16] Dolomanov, O.V., Bourhis, L.J., Gildea, R.J, Howard, J.A.K. & Puschmann, H., OLEX2: a complete structure solution, refinement and analysis program. J. Appl. Cryst. 2009, 42, 339.</p
Research data for article 'Dielectric response of a ferroelectric nematic liquid crystalline phase in thin cells'
No full textDielectric properties of a polar nematic phase (NF) were studied for 3 homologues of a model ferronematogen, RM-734, differing in the length of the lateral chain. Measurements were performed for materials sandwiched between two gold or ITO electrodes, serving as a cell surfaces. Stored dataset contains files with numerical data for (i) complex permittivity measured vs. frequency and temperature (in some cases also bias voltage), (ii) optical retardance measured versus temperature, and (iii) images presenting optical textures of formed liquid crystalline phases taken with polarized-light optical microscope, (iv) graphical file (png) with molecular structure of studied compounds and their codes, (v) pdf file with published manuscript.</p
Characterization of CD146+ pericytes isolated from wild-type and mdx mice: proliferation, gene expression profile, differentiation potential, and secretome data
No full text[ENG:]This dataset supports a project investigating differences in the proliferative capacity, gene expression profile, protein synthesis, differentiation potential, and secretome composition of CD146-positive (CD146+) pericytes isolated from skeletal muscles of wild-type (WT) and mdx mice, the latter serving as a model for Duchenne muscular dystrophy (DMD).CD146+ pericytes were isolated from hindlimb skeletal muscles of WT and mdx mice and enriched using magnetic-activated cell sorting (MACS) based on CD146 surface expression. In vitro proliferation was assessed using the CFSE assay. To analyze the gene expression profile, total RNA was extracted from cultured CD146⁺ cells, reverse-transcribed to cDNA, and analyzed by quantitative PCR (qPCR). Protein-level analyses were performed using western blotting to quantify selected markers.Differentiation potential was evaluated under defined adipogenic, fibrogenic, and myogenic culture conditions. The secretome was analyzed through its functional impact on other cell types using an in vitro angiogenesis assay. Additionally, conditioned medium was collected from CD146⁺ cells to assess the expression of secreted factors.This dataset includes:.xlsx and .txt filesSpecifically:"2way_ANOVA_of_CFSE_24h"; - text file (.txt) showing statistical analysis (two-way ANOVA) of the percentage of proliferating cells"2way_ANOVA_of_CFSE_48h" - text file (.txt) showing statistical analysis (two-way ANOVA) of the percentage of proliferating cells"angiogenesis_raw_data" - Excel file containing raw counts of angiogenesis assay"cFos_tubulin_WB_raw_data" - Excel file containing raw measurements of tubulin band intensity for cFos analysis"cFos_WB_raw_data" - Excel file containing raw measurements of cFos band intensity"cJun_tubulin_WB_raw_data" - Excel file containing raw measurements of tubulin band intensity for cJun analysis"cJun_WB_raw_data" - Excel file containing raw measurements of cJun band intensity"NFkB_tubulin_WB_raw_data" - Excel file containing raw measurements of tubulin band intensity for NFkB analysis"NFkB_WB_raw_data" - Excel file containing raw measurements of NFkB band intensity"phos_cFos_tubulin_WB_raw_data" - Excel file containing raw measurements of tubulin band intensity for phos-cFos analysis"phos_cFos_WB_raw_data" - Excel file containing raw measurements of phos-cFos band intensity"phos_cJun_tubulin_WB_raw_data" - Excel file containing raw measurements of tubulin band intensity for phos-cJun analysis"phos_cJun_WB_raw_data" - Excel file containing raw measurements of phos-cJun band intensity"phos_NFkB_tubulin_WB_raw_data" - Excel file containing raw measurements of tubulin band intensity for phos-NFkB analysis"phos_NFkB_WB_raw_data" - Excel file containing raw measurements of phos-NFkB band intensity"fibrogenesis_mdx" - Excel file with raw measurements of collagen deposition area by mdx cells"fibrogenesis_WT" - Excel file with raw measurements of collagen deposition area by WT cells"Unpaired_t_test_of_fibrogenesis" - text file (.txt) showing statistical analysis of the collagen deposition area"fusion_index_mdx" - Excel file with raw nuclei count of differentiating mdx cells"fusion_index_WT" - Excel file with raw nuclei count of differentiating WT cells"Unpaired_t_test_of_fusion_index" - text file (.txt) showing statistical analysis of the fusion index"luminex_raw_data" - Excel file with raw data from secretome composition (luminex) analysis"markers_mdx_CD146_Abs_Quant" - text file containing raw Cq data for gene expression in mdx cells"markers_WT_Abs_Quant" - text file containing raw Cq data for gene expression in WT cells"markers_MDX" - Excel file with the percentage of mdx cells expressing surface markers analyzed by flow cytometry"markers_WT" - Excel file with the percentage of WT cells expressing surface markers analyzed by flow cytometry"Ordinary_one_way_ANOVA_of_junctions" - text file (.txt) showing statistical analysis (one-way ANOVA) of the number of junctions"Ordinary_one_way_ANOVA_of_meshes" - text file (.txt) showing statistical analysis (one-way ANOVA) of the number of meshes"Ordinary_one_way_ANOVA_of_nods" - text file (.txt) showing statistical analysis (one-way ANOVA) of the number of nods"Ordinary_one_way_ANOVA_of_segments" - text file (.txt) showing statistical analysis (one-way ANOVA) of the number of segments"Ordinary_one_way_ANOVA_of_total_lenght" - text file (.txt) showing statistical analysis (one-way ANOVA) of the total lenght of the mesh"Ordinary_one_way_ANOVA_of_total_segment_lenght" - text file (.txt) showing statistical analysis (one-way ANOVA) of the lenght of the segments"perilipin_mdx" - Excel file with raw counts of perilipin expressing mdx cells"perilipin_WT" - Excel file with raw counts of perilipin expressing WT cells"Unpaired_t_test_of_perlipin" - text file (.txt) showing statistical analysis of the perilipin positive cells"proliferation_24h_raw_data" - text file with the raw counts of the cells treated with CFSE, 24h of treatment"proliferation_48h_raw_data" - text file with the raw counts of the cells treated with CFSE, 48h of treatment"Unpaired_t_test of Cspg4" - text file with the statistical analysis of the differences in the Cspg4 expression"Unpaired_t_test_of_Alp" - text file with the statistical analysis of the differences in the Alp expression"Unpaired_t_test_of_Mcam" - text file with the statistical analysis of the differences in the Mcam expression"Unpaired_t_test_of_Myod" - text file with the statistical analysis of the differences in the Myod expression"Unpaired_t_test_of_Nes" - text file with the statistical analysis of the differences in the Nes expression"Unpaired_t_test_of_Pax7" - text file with the statistical analysis of the differences in the Nes expression"Unpaired_t_test_of_Pdgfra" - text file with the statistical analysis of the differences in the Pdgfra expression"Unpaired_t_test_of_Pdgfrb" - text file with the statistical analysis of the differences in the Pdgfrb expression"Unpaired_t_test_of_Peg3" - text file with the statistical analysis of the differences in the Peg3 expression"Unpaired_t_test_of_ANGPT_2" - text file with the statistical analysis of the differences in the Angpt2 secretion"Unpaired_t_test_of_ANGPT1" - text file with the statistical analysis of the differences in the Angpt1 secretion"Unpaired_t_test_of_SDF1" - text file with the statistical analysis of the differences in the Sdf1 secretion"Unpaired_t_test_of_c_Fos" - text file with the statistical analysis of the differences in the cFos protein level"Unpaired_t_test_of_c_Jun" - text file with the statistical analysis of the differences in the cJun protein level"Unpaired_t_test_of_NFkB" - text file with the statistical analysis of the differences in the NFkB protein level"Unpaired_t_test_of_phos_c_Fos" -text file with the statistical analysis of the differences in the phosphorylated isoform of cFos protein level"Unpaired_t_test_of_phos_c_Jun" - text file with the statistical analysis of the differences in the phosphorylated isoform of cJun protein level"Unpaired_t_test_of_phos_NFkB" - text file with the statistical analysis of the differences in the phosphorylated isoform of NFkB protein level"Unpaired_t_test_of_Pdgfra_fcs" - text file with the statistical analysis of the differences in the percentage of Pgdfra positive cells"Unpaired_t_test_of_Pdgfrb_fcs" - text file with the statistical analysis of the differences in the percentage of Pgdfrb positive cells"Unpaired_t_test_of_CD146_fcs" - text file with the statistical analysis of the differences in the percentage of CD146 positive cells[PL:]Niniejszy zbiór danych stanowi uzupełnienie publikacji dotyczącej analizy transkryptomicznej oraz funkcjonalnej perycytów CD146+ izolowanych z mięśni szkieletowych myszy dzikiego typu (WT) oraz myszy mdx, powszechnie wykorzystywanych jako model dystrofii mięśniowej Duchenne’a (DMD).Komórki CD146+ wyizolowano z mięśni kończyn tylnych obu linii zwierząt metodą immunoselekcji magnetycznej (MACS) z użyciem przeciwciał anty-CD146. W warunkach in vitro zbadano ich potencjał do proliferacji (test CFSE), profil markerów powierzchniowych (cytometria przepływowa), ekspresję genów (RT-qPCR), aktywność sekrecyjną (test angiogenezy oraz Luminex), a także potencjał różnicowania w kierunku adipogenicznego, fibrogenicznego i miogenicznego. Ponadto wykonano analizę ekspresji białek wybranych markerów metodą western blot.Poniższy zbiór danych zawierapliki w formacie .xlsx i .txtKonkretnie:„2way_ANOVA_of_CFSE_24h” – plik tekstowy (.txt) zawierający analizę statystyczną (dwuczynnikowa ANOVA) procentu komórek proliferujących po 24 godzinach.„2way_ANOVA_of_CFSE_48h” – plik tekstowy (.txt) zawierający analizę statystyczną (dwuczynnikowa ANOVA) procentu komórek proliferujących po 48 godzinach.„angiogenesis_raw_data” – plik Excel zawierający surowe dane z testu angiogenezy (liczby).„cFos_tubulin_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków tubuliny używane do analizy białka cFos.„cFos_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków białka cFos.„cJun_tubulin_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków tubuliny używane do analizy białka cJun.„cJun_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków białka cJun.„NFkB_tubulin_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków tubuliny używane do analizy białka NFkB.„NFkB_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków białka NFkB.„phos_cFos_tubulin_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków tubuliny używane do analizy fosforylowanego białka cFos.„phos_cFos_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków fosforylowanego białka cFos.„phos_cJun_tubulin_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków tubuliny używane do analizy fosforylowanego białka cJun.„phos_cJun_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków fosforylowanego białka cJun.„phos_NFkB_tubulin_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków tubuliny używane do analizy fosforylowanego białka NFkB.„phos_NFkB_WB_raw_data” – plik Excel zawierający surowe pomiary intensywności prążków fosforylowanego białka NFkB.„fibrogenesis_mdx” – plik Excel zawierający surowe pomiary dotyczące powierzchni odkładania kolagenu przez komórki mdx.„fibrogenesis_WT” – plik Excel zawierający surowe pomiary dotyczące powierzchni odkładania kolagenu przez komórki typu dzikiego (WT).„Unpaired_t_test_of_fibrogenesis” – plik tekstowy (.txt) zawierający analizę statystyczną różnic w powierzchni odkładania kolagenu.„fusion_index_mdx” – plik Excel zawierający surowe dane liczby jąder komórkowych w różnicujących komórkach mdx.„fusion_index_WT” – plik Excel zawierający surowe dane liczby jąder komórkowych w różnicujących się komórkach WT.„Unpaired_t_test_of_fusion_index” – plik tekstowy (.txt) zawierający analizę statystyczną różnic w indeksie fuzji komórek.„luminex_raw_data” – plik Excel zawierający surowe dane z analizy składu sekretomu (analiza Luminex).„markers_mdx_CD146_Abs_Quant” – plik tekstowy zawierający surowe wartości Cq ekspresji genów w komórkach mdx.„markers_WT_Abs_Quant” – plik tekstowy zawierający surowe wartości Cq ekspresji genów w komórkach WT.„markers_MDX” – plik Excel zawierający procentowy odsetek komórek mdx wykazujących ekspresję markerów powierzchniowych (cytometria przepływowa)„markers_WT” – plik Excel zawierający procentowy odsetek komórek WT wykazujących ekspresję markerów powierzchniowych (cytometria przepływowa)„Ordinary_one_way_ANOVA_of_junctions” – plik tekstowy (.txt) zawierający analizę statystyczną (jednoczynnikowa ANOVA) liczby połączeń naczyniowych (junctions).„Ordinary_one_way_ANOVA_of_meshes” – plik tekstowy (.txt) zawierający analizę statystyczną (jednoczynnikowa ANOVA) liczby oczek naczyniowych (meshes).„Ordinary_one_way_ANOVA_of_nods” – plik tekstowy (.txt) zawierający analizę statystyczną (jednoczynnikowa ANOVA) liczby węzłów (nods).„Ordinary_one_way_ANOVA_of_segments” – plik tekstowy (.txt) zawierający analizę statystyczną (jednoczynnikowa ANOVA) liczby segmentów.„Ordinary_one_way_ANOVA_of_total_lenght” – plik tekstowy (.txt) zawierający analizę statystyczną (jednoczynnikowa ANOVA) całkowitej długości siatki naczyniowej (mesh).„Ordinary_one_way_ANOVA_of_total_segment_lenght” – plik tekstowy (.txt) zawierający analizę statystyczną (jednoczynnikowa ANOVA) długości segmentów.„perilipin_mdx” – plik Excel zawierający surowe pomiary liczby komórek mdx wykazujących ekspresję perilipiny.„perilipin_WT” – plik Excel zawierający surowe pomiary liczby komórek WT wykazujących ekspresję perilipiny.„Unpaired_t_test_of_perlipin” – plik tekstowy (.txt) zawierający analizę statystyczną różnic w liczbie komórek syntetyzujących perilipinę.„proliferation_24h_raw_data” – plik tekstowy zawierający surowe dane liczby komórek traktowanych CFSE po 24 godzinach.„proliferation_48h_raw_data” – plik tekstowy zawierający surowe dane liczby komórek traktowanych CFSE po 48 godzinach.„Unpaired_t_test of Cspg4” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Cspg4.„Unpaired_t_test_of_Alp” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Alp.„Unpaired_t_test_of_Mcam” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Mcam.„Unpaired_t_test_of_Myod” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Myod.„Unpaired_t_test_of_Nes” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Nes.„Unpaired_t_test_of_Pax7” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Pax7.„Unpaired_t_test_of_Pdgfra” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Pdgfra.„Unpaired_t_test_of_Pdgfrb” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Pdgfrb.„Unpaired_t_test_of_Peg3” – plik tekstowy zawierający analizę statystyczną różnic w ekspresji genu Peg3.„Unpaired_t_test_of_ANGPT_2” – plik tekstowy zawierający analizę statystyczną różnic w poziomie sekrecji Angpt2.„Unpaired_t_test_of_ANGPT1” – plik tekstowy zawierający analizę statystyczną różnic w poziomie sekrecji Angpt1.„Unpaired_t_test_of_SDF1” – plik tekstowy zawierający analizę statystyczną różnic w poziomie sekrecji Sdf1.„Unpaired_t_test_of_c_Fos” – plik tekstowy zawierający analizę statystyczną różnic w poziomie białka cFos.„Unpaired_t_test_of_c_Jun” – plik tekstowy zawierający analizę statystyczną różnic w poziomie białka cJun.„Unpaired_t_test_of_NFkB” – plik tekstowy zawierający analizę statystyczną różnic w poziomie białka NFkB.„Unpaired_t_test_of_phos_c_Fos” – plik tekstowy zawierający analizę statystyczną różnic w poziomie fosforylowanej izoformy białka cFos.„Unpaired_t_test_of_phos_c_Jun” – plik tekstowy zawierający analizę statystyczną różnic w poziomie fosforylowanej izoformy białka cJun.„Unpaired_t_test_of_phos_NFkB” – plik tekstowy zawierający analizę statystyczną różnic w poziomie fosforylowanej izoformy białka NFkB."Unpaired_t_test_of_Pdgfra_fcs" - plik tekstowy zawierający analizę statystyczną różnic w liczbie komórek syntetyzujących marker Pgdfra"Unpaired_t_test_of_Pdgfrb_fcs" - plik tekstowy zawierający analizę statystyczną różnic w liczbie komórek syntetyzujących marker Pgdfrb"Unpaired_t_test_of_CD146_fcs" - plik tekstowy zawierający analizę statystyczną różnic w liczbie komórek syntetyzujących marker CD146</ol
Mitigation of delamination of epitaxial large-area boron nitride for semiconductor processing
No full textHexagonal boron nitride (hBN) is a promising material for next-generation semiconductor and optoelectronic devices due to its wide bandgap and remarkable optical properties. To apply this material in the semiconductor industry, it is necessary to grow large-area layers on the wafer-scale. For this purpose, chemical vapor deposition methods are highly preferable. However, in the case of epitaxial BN, its fragility and susceptibility to delamination and fold formation during wet processing, such as lithography, present significant challenges to its integration into device fabrication. In this work, we introduce a controlled delamination and redeposition method that effectively prevents the layer from degradation, allowing for multi-step lithographic processes. This approach is applicable to BN layers across a broad thickness range, from tens to hundreds of nanometers, and ensures compatibility with standard photolithographic techniques without compromising the material’s intrinsic properties. By addressing key processing challenges, this method paves the way for integrating epitaxial BN into advanced semiconductor and optoelectronic technologies.</p
Results of the survey “Chat GPT in the work of Polish and Slovenian academic teachers”
No full textThe survey aimed to assess the attitudes of academic teachers in Poland and Slovenia towards ChatGPT. It was conducted for 3 weeks between 17 January and 7 February 2024; it was sent to deans of all faculties in social sciences, humanities, and natural sciences of the five largest Polish public universities (based on the number of students in 2023) [excluding the Faculty of »Artes Liberales«, University of Warsaw] and of three Slovenian public universities.The survey was created in Google Forms and featured four parts: General Information, Acquaintance with ChatGPT, ChatGPT and Cheating and Strategies; each consisted of 6-9 closed and open questions. 272 answers were collected – 152 from Polish institutions and 120 from Slovenian institutions. The sample was balanced gender-wise, with 117 (43%) participants identifying as ‘male’ (60 SLO / 57 PL), 143 (53%) identifying as ‘female’ (55 SLO / 88 PL), and 1 identifying as ‘other’ (PL); 11 participants did not disclose their gender (5 SLO / 6 PL). About 60% of participants were between the ages of 41 and 60 years (73 SLO / 92 PL), with persons aged 40 or under makin up a bigger proportion of the Polish sample (48 persons or 32% or 48 persons) than the Slovenian one (39 persons or 24%). The sample consisted primarily of experienced teachers, with 178 participants (65%) having 12 or more years of teaching experience (77 or 64% SLO / 101 or 66% PL). Academic disciplines were also represented in a balanced manner, with 80 (29%) answers from representatives of the humanities (35 SLO / 45 PL), 89 (33%) answers from representatives of social sciences, and 88 (32%) answers from representatives of natural sciences; 15 persons (14 SLO / 1 PL) listed their discipline as ‘other’.</p
High speed camera videos used for preparation of fig. S4 presenting the impact of various temperatures on gelatin droplet sorting.
No full textHigh speed camera videos used for preparation of Fig. S4 presenting the impact of various temperatures on gelatin droplet sorting.Detailed description can be found in the attached "Dataset_ZD5_README_Potenza et al_Analytical Chemistry_2024".</p
Aberration-optimized electro-optic time lens with a tunable aperture
No full textThis zipped file contains six folders with data, figures, and Python programs related to the manuscript entitled 'Aberration-optimized electro-optic time lens with a tunable aperture.' Below is a description of each folder and its contents.'1. Raw Data'Contains four subfolders corresponding to different GDD settings from the pulse shaper.* '-1.5ps2'* '-4.0ps2'* '0.5ps2'* '3.0ps2'Each GDD folder contains 45 subfolders labeled with the input bandwidth of the Gaussian spectrum. Each input bandwidth folder contains two spectra saved in CSV format. The file ending with 'ref.csv' is the measured spectrum when the electro-optic phase modulator (EOPM) was off, and the file labeled with '0.310000V.csv' is the measured compressed spectrum corresponding to 3.27 pi modulation amplitude.'2. Least Square Parameter Estimation Program'This folder contains Python scripts for the least-square minimization of simulated and measured spectra.The scripts estimate three key parameters:Phase modulation amplitude (A)Group delay dispersion (GDD)The relative time delay between the temporal and optical pulse (phase_offset)Files:parameter_estimation.py: Performs least-square minimization.utilities.py: Contains utility functions required by the above program.Output:The parameter_estimation.py program estimates three parameters described above for each pair of measured input-output spectra. Additionally, it saves the spectra of each pair in the folder '3. All spectra' along with the simulated spectrum and the difference between the measured and simulated spectrum. The program also saves the numpy arrays of some post-processed quantities (described in the manuscript) to the folder named '4. Post-processed data'.'3. All spectra'Contains 180 PNG images of all the measured input-output and simulated spectra. The first part of the file name (before the underscore) is the GDD in ps2, and the second part is the input bandwidth in nm.'4. Post-Processed Data'Contains results generated by the least-square parameter estimation program.Includes:Estimated parameters (A, GDD, phase_offset)Enhancement valuesQuality of compressionPower-equivalent bandwidthOutput full-width half-maxima (FWHM) of spectra'5. Simulations with error bars'This folder contains a Python program that performs simulations of spectral compression of Gaussian pulses assuming uncertainty in the GDD and modulation amplitude parameters as estimated by the program 'parameter_estimation.py'.6. Figures:Contains six subfolders, each corresponding to a figure in the manuscript.Each subfolder includes:The source code (if applicable) was used to generate the figures.The associated data files (where applicable).System requirements.The Python scripts were written and executed on an Apple machine with an M2 chip using Python version 3.13.0.Package name Version---------------------------------numpy 2.1.3lmfit 1.3.2pandas 2.2.3scipy 1.14.1matplotlib 3.9.2 --------------------------------</p