Find research datasets worth reusing

opencc-zeroJul 2023View details →

Data for: Weak sex-specific evolution of locomotor activity of Sepsis punctum (Diptera: Sepsidae) thermal experimental evolution lines

Elevated temperatures are expected to rise beyond what the physiology of many organisms can tolerate. Behavioural responses facilitating microhabitat shifts may mitigate some of this increased thermal selection on physiology, but behaviours are themselves mediated by physiology, and any behavioural response may trade-off against other fitness-related activities. We investigated whether experimental evolution in different thermal regimes (Cold: 15°C; Hot: 31°C; Intergenerational fluctuation 15/31°C; Control: 23°C) resulted in genetic differentiation of standard locomotor activity in the dung fly Sepsis punctum. We assessed individual locomotor performance, an integral part of most behavioral repertoires, across eight warm temperatures from 24°C to 45°C using an automated device. We found no evidence for generalist-specialist trade-offs (i.e. changes in the breadth of the performance curve) for this trait. Instead, at the warmest assay temperatures, hot-selected flies showed somewhat higher maximal performance than all others, especially cold-selected flies, overall more so in males than females. Yet, the flies' temperature optimum was not higher than that of the cold-selected flies, as expected under the 'hotter-is-better' hypothesis. Maximal locomotor performance merely weakly increased with body size. These results suggest that thermal performance curves are unlikely to evolve as an entity according to theory and that locomotor activity is a trait of limited use in revealing thermal adaptation.

opencc-by-3.0-usJul 2023View details →

Temporally specific patterns of neural activity in interconnected corticolimbic structures during reward anticipation

Temporally specific patterns of neural activity in interconnected corticolimbic structures during reward anticipation Megan E. Young, Camille Spencer-Salmon, Clayton Mosher, Sarita Tamang, Kanaka Rajan, and Peter H. Rudebeck This dataset contains peripheral physiology (heart rate) and single neuron activity data from the paper entitled “Temporally specific patterns of neural activity in interconnected corticolimbic structures during reward anticipation” by Young, Spencer-Salmon and colleagues. The study investigated how neurons in macaque subcallosal anterior cingulate cortex, basolateral amygdala, and rostromedial striatum encoded anticipated reward during Pavlovian and instrumental tasks. Heart rate data were pre-processed using methods described in the paper and were downsampled to 50 Hz for analysis. Neural activity data were pre-processed using steps as described in the paper. The dataset is saved as .MAT files. Files included: ‘Pavlovian_task_neurons.mat’ – single neuron data from the Pavlovian task. Each of the 656 rows represents a single neuron and its associated information. ‘Instrumental_task_neurons.mat’ – single neuron data from the instrumental task. Each of the 425 rows represents a single neuron and its associated information. “heart_rate.mat” – heart rate data from monkeys D and H. File structure and information: Pavlovian_task_neurons.mat Structure “Pavlovian_task_neurons” - “Pavlovian_task_neurons.unit_name” – neuron specific identifier - “Pavlovian_task_neurons.monkeynumber” – subject specific # - “Pavlovian_task_neurons.monkeyname” – subject specific name - “Pavlovian_task_neurons.date” – date on which data were recorded - “Pavlovian_task_neurons.session” – session identifier from date (a-d) - “Pavlovian_task_neurons.channel” – recording channel data recorded from - “Pavlovian_task_neurons.wavemark” – waveform number (a-e) - “Pavlovian_task_neurons.brainarea” – brain area where neuron recorded (SC = subcallosal ACC, AMY = basolateral amygdala, VS = rostromedial striatum). - “Pavlovian_task_neurons.areanum” – # brain area (subcallosal ACC = 1, BLA = 2, rostromedial striatum = 3) - “Pavlovian_task_neurons.condition” – condition # from Monkey Logic for each of the trials (1 by n trials) - “Pavlovian_task_neurons.stimspikes” – smoothed spike rate from -600 to 2500ms after stimulus onset (trials by time matrix) - “Pavlovian_task_neurons.rewardspikes” – smoothed spike rate from -600 to 2500ms after reward onset (trials by time matrix) - “Pavlovian_task_neurons.stimID” – stimulus shown on that trial (1 = neutral, 3 = CS+ juice, 4 = CS+ water, 5 = CS-) (1 by n trials). Instrumental_task_neurons.mat Structure “Instrumental_task_neurons” - “instrumental_task_neurons.unit_name” – neuron specific identifier - “instrumental_task_neurons.monkeynumber” – subject specific # - “instrumental_task_neurons.monkeyname” – subject specific name - “instrumental_task_neurons.date” – date on which data were recorded - “instrumental_task_neurons.session” – session identifier from date (a-d) - “instrumental_task_neurons.channel” – recording channel data recorded from - “instrumental_task_neurons.wavemark” – waveform number (a-e) - “instrumental_task_neurons.brainarea” – brain area where neuron recorded (SC = subcallosal ACC, AMY = basolateral amygdala, VS = rostromedial striatum). - “instrumental_task_neurons.areanum” – # brain area (subcallosal ACC = 1, BLA = 2, rostromedial striatum = 3) - “instrumental_task_neurons.condition” – condition 7-18 from Monkey Logic for each of the trials (1 by n trials). CNDs 7,8,13,14= CS+ juice vs CS+ water; CNDs 9,10,15,16= CS+ juice vs CS-; CNDs 11,12,17,18= CS+ water vs CS-. - “instrumental_task_neurons.choice” – outcome associated with chosen option (0=nothing, 1=juice, 2=water) (1 by n trials) - “instrumental_task_neurons.unchosen” - outcome associated with unchosen option (0=nothing, 1=juice, 2=water) (1 by n trials) - “instrumental_task_neurons.chosenside” – side of the screen chosen (left [0] or right [1]) (1 by n trials) - “instrumental_task_neurons.stimspikes” – smoothed spike rate from -600 to 2500ms after stimulus onset (trials by time matrix) - “instrumental_task_neurons.rewardspikes” – smoothed spike rate from -600 to 2500ms after reward onset (trials by time matrix) heart_rate.mat Structures     – “monkey_d_hr” – monkey D heart rate data         – “monkey_h_hr” – monkey H heart rate data Structure of monkey_d/h_hr - “monkey_d/h_hr.trial_type” – trial type presented (1 = neutral, 2 = unsignaled, 3 = CS+ juice, 4 = CS+ water, 5 = CS-) (1 by n trials). - “monkey_d/h_hr.trials” – number of trials in each session by trial type - “monkey_d/h_hr.session – percent change in heart rate for each trial from -200 ms to 3500ms after stimulus onset. Column 1 = session; Column 2 = trial type; Column 3 = trial number; Columns 4 – 3703 = percent change in heart rate.

opencc-by-4.0Dec 2022View details →

Mapping the epigenomic landscape of human monocytes following innate immune activation reveals context-specific mechanisms driving endotoxin tolerance

Processed datasets for publication at BMC Genomics. We exposed human primary monocytes from healthy donors (n=6) to interferon-γ or differing combinations of endotoxin (lipopolysaccharide), including acute response (2hr LPS; LPS2) and two models of endotoxin tolerance: repeated stimulations (6+6hr; LPS6:6) and prolonged exposure to endotoxin (24hr LPS; LPS24). Another subset of monocytes was left untreated (naïve; UT). We performed total RNA-seq and ATAC-seq for monocytes across these treatment conditions. The following processed datasets include the raw and normalised count data for each gene or ATAC peak, and the bedGraph and bigWig format for genome-wide signal data. [ bigWig files for RNA-seq (monocytes_*_mean.bw); bigWig files for ATAC-seq (Monocyte_ATAC_*_mean_normalised.by.1/size.factor.bw); bedgraph files for eRNA visualization (*RPKM_FR.bedgraph.gz); raw and normalised count files for ATAC-seq and RNA-seq data (Monocyte.featureCounts_RNAseq.txt.gz; Monocyte_filtered_log2.normalized_RNAseq_counts.txt.gz; Meta.file.txt.gz; Monocyte_raw.counts_ATACseq.txt.gz.).] Data curator: Ping Zhang

Data from: Active-feedback quantum control of an integrated, low-frequency mechanical resonator

Source data for Figures.

Learner Perceptions on Gamifying Active Video Watching Platforms (supplementary material)

This repository contains supplementary material for "Learner Perceptions on Gamifying Active Video Watching Platforms": <ul> <li>Questionnaire.pdf: PDF file containing the survey questions on motivation, experience and perception on gamification.</li> <li>Perception_on_gamification.xlsx:  Raw dataset of the survey.</li> </ul>

opencc-zeroJul 2023View details →

Excited state observation of active K-Ras reveals differential structural dynamics of wild-type versus oncogenic G12D and G12C mutants

Despite the prominent role of the K-Ras protein in many different types of human cancer, major gaps in atomic-level information severely limit our understanding of K-Ras function in health and disease. Here, we report the quantitative backbone structural dynamics of K-Ras by solution NMR spectroscopy of the active state of wild-type K-Ras·GTP and two of its oncogenic P-loop mutants, G12D and G12C, using a novel nanoparticle-assisted spin relaxation method, relaxation dispersion and chemical exchange saturation transfer experiments covering the entire range of timescales from picosecond to milliseconds. Our combined experiments allow the detection and analysis of the functionally critical Switch I and Switch II regions that have previously remained largely unobservable by X-ray crystallography and NMR spectroscopy. Our data reveal cooperative transitions of K-Ras·GTP to a highly dynamic excited state that closely resembles the partially disordered K-Ras·GDP state. These results advance our understanding of differential GTPase activities and signaling properties of the WT versus mutants and may thus guide new strategies for the development of therapeutics.

Data repository of the paper "Quantum-noise-limited optical neural networks operating at a few quanta per activation"

This data repository includes the requisite data and code for deriving the primary results from the paper, "Quantum-noise-limited optical neural networks operating at a few quanta per activation". The repository is structured to provide everything needed to reproduce the figures included in the main manuscript, along with the source code for training the neural network models and the collected experimental data mentioned in the paper. The code in this repository is primarily intended for reproducing the results discussed in the paper. Those interested in developing their own applications may refer to our Github repository: https://github.com/mcmahon-lab/Single-Photon-Detection-Neural-Networks. Where to Start The directory 'main_figures' includes Jupyter notebooks to generate each panel in Figure 3 and Figure 4 in the main text, using the data from the directory 'results', which can be generated by notebooks in the directory 'test'.  The simulations, experiments, and figure generation were all conducted in Python. As certain parts of the code require specific versions of Python packages, the necessary packages are listed in the 'requirements.txt' file. For more information, please refer to 'README.txt'.

opencc-by-4.0Apr 2023View details →

Datasets for "Scalable, flexible carbon fiber electrode thread arrays for three-dimensional spatial profiling of neurochemical activity in deep brain structures of rodents"

Datasets used in the manuscript titled, "Scalable, flexible carbon fiber electrode thread arrays for three-dimensional spatial profiling of neurochemical activity in deep brain structures of rodents" are uploaded here.  Brightfield and fluorescent stained images of brain tissue used for Fig. 5(a): Malt3-20190624_Region 009_DAPI.png Malt3-20190624_Region 009_qCy5.png Malt3-20190624_Region 009_qFITC.png Malt3-20190624_Region 009_qTexasRed.png Malt3_BF20190628_Region 001.png Fluorescent image of brain with embedded CFETs: MALT2_Rat_100um_MOR1_x500_TSA_AF488.jpg Rat_100um_MOR1_x500_TSA.czi In vivo dopamine recording data for Fig. 3: ratarrays822_163.mat ratarrays822_57.mat

opencc-zeroJul 2023View details →

Activity of tjakura (great desert skinks) at burrows in relation to plant cover and predators

Increased predation where ground cover is reduced after severe wildfire is increasingly implicated as a factor causing decline of vulnerable prey populations. In arid central Australia, one species detrimentally affected by repeated wildfire is the great desert skink or tjakura (Liopholis kintorei), a distinctive lizard of the central Australian arid zone that constructs and inhabits multi-entranced communal burrows. We aimed to test whether tjakura or predator activity at burrow entrances varied with cover and how tjakura respond to predator presence. Using time-lapse photography, we monitored tjakura and predator activity at the largest entrance of 12 burrows ranging from high (>70 %) to low (<50 %) cover and at multiple entrances of two other burrows. Overall activity did not vary between burrows with high and low cover. Within burrow systems, tjakura were more active at sparsely vegetated entrances, often sitting wholly or partly inside the burrow. However, consistent between and within burrow systems, skinks spent proportionally more time fully outside where cover was higher. Predators – mostly native – were detected at most burrows, with no apparent relationship between predator activity and cover. Skinks also did not appear to modify their activity in response to predator visits. Our results indicate that tjakura may spend more time outside burrow entrances when cover is higher, but there was no direct evidence that this related to perceived or real predation risk. Differences in food availability, thermoregulatory opportunities, and opportunities for ambush foraging associated with differences in vegetation cover or composition are other factors likely to be important in determining the activity of tjakura at burrows. Our research demonstrates the usefulness of camera traps for behavioural studies of ectothermic burrowing animals. The complex relationships between tjakura activity and vegetation cover were thereby revealed, suggesting outcomes of fire-mediated habitat change on predator-prey interactions are not easily predictable.

Amphiphilic Cyclic Antimicrobial Peptides Derived from the [W4R4] Scaffold: Structural Studies and Correlation with Activity

Data for Publication “Amphiphilic Cyclic Antimicrobial Peptides Derived from the [W4R4] Scaffold: Structural Studies and Correlation with Activity.” The file archive "WR_peptides_MD.zip" contains the starting structures of peptides, molecular topologies of peptides, representative MD trajectories of peptides in water and the DOPC/DOPG bilayer, as well as MD simulation parameters. See the README.txt file in this archive for details.

Offshore active faults associated with the 2020 Masbate earthquake investigation

This dataset includes the vector files of the offshore active fault traces mapped using acoustic sub-bottom profiling and interpretation of archived seismic profiles. The acoustic sub-bottom profiling survey was conducted in March and June 2021. The archived seismic profiles were acquired from the Department of Energy (DOE) of the Philippine government.

Photovoice and case based learning activities in higher education (University of Zaragoza - Social Work degree)

The collected variables are: students data (gender, age, university admittance marks from 0 to 14), academic perforrnace of photovoice (PV) activity (from 0 to 10), academic performance of Case based learning (CBL) activity (form 0 to 10),  order of the exercises, satisfaction with the photovoice activity, satisfaction with the CBL activity, items and overall self-efficacy scale score

opencc-by-4.0Jan 2023View details →

Noncentrosymmetric Lanthanide-Based MOF Materials Exhibiting Strong SHG Activity and NIR Luminescence of Er3+: Application in Nonlinear Optical Thermometry

Optically active luminescent materials based on lanthanide ions attract significant attention due to their unique spectroscopic properties, nonlinear optical activity, and the possibility of application as contactless sensors. Lanthanide metal-organic frameworks (Ln-MOFs) that exhibit strong second-harmonic generation (SHG) and are optically active in the NIR region are unexpectedly underrepresented. Moreover, such Ln-MOFs require ligands that are chiral and/or need multistep synthetic procedures. Here, we show that the NIR pulsed laser irradiation of the noncentrosymmetric, isostructural Ln-MOF materials (MOF-Er3+ (1) and codoped MOF-Yb3+/Er3+ (2)) that are constructed from simple, achiral organic substrates in a one-step procedure results in strong and tunable SHG activity. The SHG signals could be easily collected, exciting the materials in a broad NIR spectral range, from ≈800 to 1500 nm, resulting in the intense color of emission, observed in the entire visible spectral region. Moreover, upon excitation in the range of ≈900 to 1025 nm, the materials also exhibit the NIR luminescence of Er3+ ions, centered at ≈1550 nm. The use of a 975 nm pulse excitation allows simultaneous observations of the conventional NIR emission of Er3+ and the SHG signal, altogether tuned by the composition of the Ln-MOF materials. Taking the benefits of different thermal responses of the mentioned effects, we have developed a nonlinear optical thermometer based on lanthanide-MOF materials. In this system, the SHG signal decreases with temperature, whereas the NIR emission band of Er3+ slightly broadens, allowing ratiometric (Er3+ NIR 1550 nm/SHG 488 nm) temperature monitoring. Our study provides a groundwork for the rational design of readily available and self-monitoring NLO-active Ln-MOFs with the desired optical and electronic properties.

Accompanying data for: Local negative feedback of Rac activity at the leading edge underlies a pilot pseudopod-like program for amoeboid cell guidance

This is the data underlying all of the figures in: Local negative feedback of Rac activity at the leading edge underlies a pilot pseudopod-like program for amoeboid cell guidance by Jason P. Town and Orion D. Weiner Paper Abstract: To migrate efficiently, neutrophils must polarize their cytoskeletal regulators along a single axis of motion. This polarization process is thought to be mediated through local positive feedback that amplifies leading edge signals and global negative feedback that enables sites of positive feedback to compete for dominance. Though this two-component model efficiently establishes cell polarity, it has potential limitations, including a tendency to “lock” onto a particular direction, limiting the ability of cells to reorient. We use spatially-defined optogenetic control of a leading edge organizer (PI3K) to probe how neutrophil-like HL-60 cells balance “decisiveness” needed to polarize in a single direction with the flexibility needed to respond to new cues. Underlying this balancing act is a local Rac inhibition process that destabilizes the leading edge to promote exploration. We show that this local inhibition enables cells to process input signal dynamics, linking front stability and orientation to local temporal increases in input signals.  All data can be processed using standard scientific python packages using the Jupyter Notebooks located <a href="https://zenodo.org/badge/latestdoi/672328942">here</a>. To run the notebooks and reproduce the figures in the paper, download all of the zipped data files, unzip them, and arrange them into the following directory structure: <ul> <li>projectfolder <ul> <li>data <ul> <li>fig03data</li> <li>fig04data</li> <li>fig05data</li> <li>figS01data</li> <li>figS08data</li> <li>figS10data</li> <li>simpleStimdata</li> </ul> </li> <li>figure01.ipynb</li> <li>figure02.ipynb</li> <li>...</li> </ul> </li> </ul> Microscopy data was collected using an automated, Pycromanager-based pipeline. The most recent version of the pipeline can be found <a href="https://zenodo.org/badge/latestdoi/583790048">here</a>.  This zipped folders contains microscopy data (images & metadata) in several directories: <ul> <li>"simpleStimData" contains data used in several figures in the paper. It shows the dynamic behaviors of neutrophils as they are subjected to local optogenetic activation of optoPI3K. <ul> <li>File folders are not entirely standardized, but typically contain <ul> <li>The data of the experiment (YYMMDD format)</li> <li>The cell line used and the constructs expressed (35 is the optogenetic anchor, 52 is the optogenetic cargo, 97 is the PH-Akt-Halo PIP3 reporter, and mcPak is the Pak-PBD-mCherry Rac reporter)</li> <li>A generic phrase 'Assays', 'VariousFrontStimulations', 'simpleStimScreen' that has no experimental meaning</li> <li>An indicator of the pre-programmed assay "type" - either 'none, 'front', 'side', 'back', 'global', 'lateral45', 'lateral90',  '0Rad', '0.2 Rad', '0.39Rad', '0.79Rad' or '1.57Rad'</li> <li>The intensity of blue LED light used in the experiment ('50000'). This did not turn out to be very important for the paper in this particular dataset, but cells do not display an all-or-none response to optogenetic PI3K acitvation.</li> <li>And finally a replicate number for that assay that day (i.e. '000', '001', ...)</li> </ul> </li> <li>Within each file folder, there is a collection of images (Note that each image has a lot of extra information in the associated metadata) <ul> <li>Channel 0 is the PHAkt PIP3 reporter fluorescence data</li> <li>Channel 1 is the Pak-PBD Rac reporter fluorescence data</li> <li>Channel 2 is a reflected blue light dataset. A small degree of blue light reflected off the bottoms of coverslips and could be collected on the camera</li> <li>Channel 3 is a binary segmentation channel generated on-the-fly during acquisition by our automated microscopy software</li> <li>Channel 4 is another binary segmentation channel, but this one is a prediction of the real image of the optogenetic stimulus based on a calibrated affine transformation of the projected image onto the microscopy field of view. </li> <li>if present, Channels 5 and 6 are control images taken at the end of the experiment to verify the presence of optogenetic constructs 35 (405 channel) and 52 (488 channel)</li> </ul> </li> <li>There is a small amount of data here that was not directly used in the paper. For example, the 'frontToGlobal' experiments did not produce interesting results, but actually led us to develop the method shown in Figure 5 in our paper where we did something closer to a 'sideToGlobal' assay (See Fig 5 in the paper). </li> </ul> </li> <li>"fig03Data" contains data used to generate Fig 3 and Fig S7B in the paper. This data is structured identically to the data in simpleStimData described above</li> <li>"fig04Data" contains data used to generate Fig 4 and Fig S9D in the paper. Some of this is from older software, so the metadata (i.e. LED intensities) are stored in a separate file called intensities.txt. This text file contains time stamps and LED intensity data that can be matched with the temporal metadata from the microscopy images.  </li> <li>"fig05Data" contains data used to generate Fig 5 and Fig S11. These are structured identically to the simpleStimData structure described above. (Though these files are stored in more organized subdirectories compared to simpleStimData). </li> <li>"figS01Data" contains the microscopy data used to generate Fig S1</li> <li>"figS08Data" contains data used to generate Fig S8 in the paper. This is from older microscopy automation software, so the metadata (i.e. LED intensities) are stored in a separate file called metadata.txt. This text file contains time stamps and LED intensity changes that can be matched with the temporal metadata from the microscopy images.  </li> <li>"figS10Data" contains data used to generate Fig S10 in the paper. This is a combination of data structures similar to that described above in "fig04Data" for the step inputs and "simpleStimData" for the turning assays.</li> </ul>

Fig. 8. A in Small carnivores (Mammalia: Carnivora) in the Wonorejo Mangroves, Jawa Timur, Indonesia: habitat use and activity patterns

Fig. 8. A, domestic cat on a dyke on 15 November 2018; B, activity pattern of the domestic cat.

Fig. 1 in Small carnivores (Mammalia: Carnivora) in the Wonorejo Mangroves, Jawa Timur, Indonesia: habitat use and activity patterns

Fig. 1. Map of the study area in Wonorejo Mangroves east of Surabaya, Jawa Timur, Indonesia.

opencc-zeroAug 2023View details →

A five-sensor IMU-based Parkinson's disease patient and control dataset including three activities of daily living

Parkinson's disease is an often-debilitating progressive neurological condition leading to loss of motor control. This dataset contains kinematic sensor data from two groups: one containing 15 patients with Parkinson's disease, and a control group of 19 participants without any known neurological condition. Participant ages ranged from 40–85, 21 were male, and 13 were female. The participants wore five 9-axis Inertial Measurement Units (IMUs) – one on each upper arm, each lower arm, and on their head. They were asked to perform a calibration pose, followed by three activities: making toast, putting on a cardigan, and unlocking and opening a door, with each activity repeated three times. The IMUs recorded time-series acceleration and orientation data from the moment where the participant was instructed to begin the activity (inception of the idea to act), through to the activity's completion. This dataset is planned for use in intent-sensing studies for assistive device control but is also applicable for activity recognition.

Hemostatic system in Takotsubo patients at long-term follow-up: A hidden activation?

This record contains raw data related to the article “Hemostatic system in Takotsubo patients at long-term follow-up: A hidden activation?” Background: Takotsubo cardiomyopathy (TTS) has long been considered a benign condition, despite recurrent events and long-term adverse outcomes are often reported. Endothelial damage, blood hyperviscosity, and platelet activation described in acute phase persist in long-term follow-up; however, TTS pathophysiology is still not fully understood. Here, we explored the hemostatic system at a median of 3.1 years after TTS to uncover additional long-lasting changes in these patients. Methods: We assessed hemostatic parameters in women with TTS (n = 23) or coronary artery disease (CAD; n = 31) and in control women (n = 26) age-matched, by thromboelastographic analysis, prothrombin time (PT) and partial thromboplastin time (aPTT) coagulation assays and microparticle exposing Tissue Factor (MP-TF). Functional fibrinogen and fibrin polymerization were analyzed by Clauss method and spectrophotometry, respectively. Platelet reactivity was evaluated by light transmission aggregometry, whereas plasminogen activator inhibitor-1 (PAI-1) and brain-derived neurotrophic factor (BDNF) were measured by ELISA kit. Results: Compared with control subjects, TTS patients exhibit an accelerated clot formation, higher percentage of fibrin polymerization and higher PAI-1 levels. Compared with CAD, TTS patients showed sustained residual platelet activation but decreased functional fibrinogen, fibrin polymerization and MP-TF levels, prolonged aPTT and a marked BDNF increase. Conclusions: The long-term activation of hemostatic system observed in TTS patients compared to control subjects suggests a persistent humoral abnormality that may be related to the propensity for TTS recurrence. The higher residual platelet activity observed in TTS than in CAD patients invites investigation on TTS-tailored antiplatelet therapy potentially needed to prevent TTS adverse outcomes.

opencc-by-3.0-usAug 2023View details →

Association Between Change in The Peripheral Biomarkers of Inflammation, Astrocyte Activation, and Neuroprotection at One Week of Critical Illness and Hospital Mortality in Patients with Delirium: A Prospective Cohort Study

Dataset for the following publication: Association Between Change in The Peripheral Biomarkers of Inflammation, Astrocyte Activation, and Neuroprotection at One Week of Critical Illness and Hospital Mortality in Patients with Delirium: A Prospective Cohort Study