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Mendeley Data Showcase

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1970 2024
27126110 results
  • LDHU3_05.1180
    ATPase; Leishmania donovani (HU3 strain)
    • Dataset
  • Biomolecules found in Pleistocene fossil in tropical cave: Biofilm characterization by micro Raman spectroscopy.
    The dataset contains 134 raw Raman spectrum from 13 fossil samples from Tayassu and 6 fossil samples from Smillodon. The data set are stored into two folders, named Tayassu and Smillodon. Into these two folders the dataset are organized according the fossil samples. The file title flowing the general principle: the sample number comes first, then, laser line, and the percent of laser bean power used, than the time of sample exposition, than the number of accumulations, the objective used for the measurements, and finally the point number, example: amostra 1 - 785 nm - 0.1% - 10seg - 1 acum - 50X - ponto 1 - cent 1500. The Raman spectrum show of multiple bands between 1200 to 1800 cm-1 associated with organic compounds. Our results show that these organic signatures are linked to biofilm formation, with a high likelihood of biofilm degradation. However, the specific mechanisms involved in the natural degradation of biofilm in fossil records remain unexplored in this study. In our case, the formation of biofilm on fossil bones is attributed to the oligotrophic conditions of the cave sediment matrix. We present a comprehensive model to elucidate the existence of biofilm on fossil bones, emphasizing the pivotal role of post-depositional processes, especially water action, in the cave environment. As the fossils were discovered in a cave setting, post-depositional processes significantly contribute to the formation of the biofilm matrix. Although our study provides insights into biofilm formation, further research is needed to delve into the specific mechanisms driving natural biofilm degradation in fossil records.
    • Dataset
  • Pharmacogenomic profiling of intra-tumor heterogeneity by a large organoid biobank of liver cancer
    Mendeley data 1: Immunofluorescence staining of P1 (HCC, shown in Fig. 1D) and P29 (ICC, shown in Data S1.3) organoids. HCC markers (AFP and Hepatocyte) and biliary markers (EPCAM and KRT19) were assayed by immunofluorescence staining, using two organoid cultures of the same passage, due to the limit of three channels (blue, green and red), with overexposure condition applied. Mendeley data 2: H&E and IHC staining of three tumor regions from a HCC patient P1, and H&E, IHC and immunofluorescence staining of the corresponding organoids. HCC markers (AFP and HepPar1) and biliary markers (EPCAM and KRT19) were assayed by IHC and immunofluorescence staining. Scale bars indicate 50 μm. Mendeley data 3: H&E and IHC staining of tumor lesions from HCC (A), ICC (B) and CHC (C) patients, and H&E, IHC and immunofluorescence staining of the derived organoids. HCC markers (AFP, HepPar1) and ICC markers (KRT19 and EPCAM) were assayed by IHC and immunofluorescence staining. Scale bars indicate 50 μm.
    • Dataset
  • Sequential activity of CA1 hippocampal cells constitutes a temporal memory map for associative learning in mice
    Sequential neural dynamics encoded by “time cells” play a crucial role in hippocampal function. However, the role of hippocampal sequential neural dynamics in associative learning is an open question. We used two-photon Ca2+ imaging of dorsal CA1 (dCA1) neurons in the stratum pyramidale (SP) in head-fixed mice performing a go-no-go associative learning task to investigate how odor valence is temporally encoded in this area of the brain. We found that SP cells responded differentially to the rewarded or unrewarded odor. The stimuli were decoded accurately from the activity of the neuronal ensemble, and accuracy increased substantially as the animal learned to differentiate the stimuli. Decoding the stimulus from individual SP cells responding differentially revealed that decision-making took place at discrete times after stimulus presentation. Lick prediction decoded from the ensemble activity of cells in dCA1 correlated linearly with lick behavior indicating that sequential activity of SP cells in dCA1 constitutes a temporal memory map used for decision-making in associative learning. Here we deposit the data necessary to generate the figures in our Current Biology manuscript (DOI: 10.1101/2023.10.01.560382) using the code deposited in
    • Dataset
  • Supporting information for "Deciphering contribution of recycled altered oceanic crust to arc magmas using Ba-Sr-Nd isotopes"
    1. Supplementary tables: Tables S1-S2 2. Supplementary figures: Figures S1-S4 3. Supplementary dataset containing the global arc volcano averages and raw arc data
    • Dataset
  • e-learning Latinamerica search, countries, dates and sample
    Research strings of e-learning in Latinamerica systematic review. Includes every string, its number of findings, date and sample whitin scope.
    • Dataset
    Effective self-care is crucial for individuals with diabetes, especially in understanding the impact of diet and physical activity on blood glucose levels. This study aims to assess the prevalence of glucometer usage, the frequency of its use, and its impact on achieving glycemic control. In this cross-sectional observational study, conducted from March to August 2023 at 22 carefully selected sites in Uttar Pradesh (UP), data was collected using the MEDEVA analytics-based EHR platform. The information obtained encompassed participant demographics, diabetes history, treatment modalities, and glucometer usage patterns. Descriptive and inferential statistics were employed to summarize the results. This study highlights the significance of incorporating comprehensive diabetes education programs that encompass self-monitoring of blood glucose (SMBG) training. Further validation of these observations is warranted through future multicenter and more extensive studies.
    • Dataset
  • High-Performance Audio System
    This data set contains all the CAD and firmware files to build the Harp sound board and audio amplifier hardware for designed for high-performance wide-band acoustic stimulation.
    • Dataset
  • Supplementary Material FOR Coesite-bearing microdiamonds in dolerite from mantle plume derived large igneous province
    Supplementary Material data to this article including Supplementary Figures, Supplementary Tables and Supplementary Note about crustal contamination, alteration and fractional crystallization effect of diamond-bearing dolerites. Supplementary Figures including filed outcrop, photomicrographs, geochemical discrimination, magma fractionation, crustal contamination effect of the diamond-bearing dolerites; Supplementary Tables 1-3 including corresponding geochemical, zircon chronology data of the diamond-bearing dolerites, and the major FTIR peaks and nitrogen contents of microdiamonds from dolerites. FTIR and Raman raw data is provided as individual file in Supplementary Table 4 and 5.
    • Dataset
  • Устойчивость диверсификационных возможностей портфеля долевых финансовых инструментов на российском фондовом рынке в условиях макроэкономической нестабильности
    Панельные данные для анализа влияния факторов макроэкономической нестабильности на изменение коэффициента корреляций между доходностями долевых финансовых инструментов на российском фондовом рынке. Для корректного прочтения данных программой используются индексные переменные: n_tickers (unit or group index variable) и n_month (time index variable). Содержание данных: 1) EFI_1 и EFI_2 - тикеры долевых финансовых инструментов по каждой из пары активов; 2) CORRELATION - месячное значение коэффициента корреляций между парой долевых финансовых инструментов; 3) negative_month - фиктивная переменная, обозначающая, содержит ли месяц хотя бы один фактор макроэкономической нестабильности (из списка факторов, обозначенных в исследовании); 4) stable - фиктивная переменная, обозначающая присутствует ли в паре активов хотя бы один инструмент, который был признан устойчивым в ходе исследования; 5) unstable - фиктивная переменная, обозначающая, что в паре активов присутствуют оба инструмента, которые не были признаны устойчивыми в ходе исследования; 6) r_brent - среднемесячная логдоходность нефти марки Brent, в п.п.; 7) r_usdrub - среднемесячная логдоходность обменного курса доллара к рублю, в п.п.; 8) inflation - месячное значения инфляции (рассчитанной за период от первого до последнего числа месяца), в п.п.
    • Dataset