Find research datasets worth reusing

opencc-by-4.0Nov 2022View details →

Dataset for "Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia"

Article: Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia Cancer Discovery, DOI: 10.1158/2159-8290.CD-21-0410   Data Types: 1. Clinical summary 2. Drug response data 3. Exome-sequencing data 4. RNA-sequencing data   Updates: - FILE: File_3.2. DATE: 28.11.2022.   1. Clinical summary File_0: Common sample annotation including patient and sample IDs, stage of the disease, tissue type and availability of different data types. File_1.1: Clinical data for 186 AML patients including clinical diagnosis, disease classification, gender, age at diagnosis, treatments, cytogenetic and molecular details. The description of the variables/column titles is given below the clinical data. File_1.2: Description of the clinical variables in File_1.1.   2. Drug response data for 164 AML patient samples and 17 healthy samples File_2: Drug library details for 515 chemical compounds. The compound collection includes drugs names, drug class defined by molecular targets or mode of action, concentration range used for drug testing, supplier information, solvent information and vendor information. File_3.1.: Drug response data including selective drug sensitivity scores (sDSS) for 515 compounds across 181 samples (164 AML patient samples and 17 healthy control samples). The DSS is modified area under the curve values and are calculated as shown in Yadav et al publication (1). The selective drug sensitivity scores (sDSS) is healthy control normalized DSS that gives estimated cancer-selective drug responses. The higher the sDSS values indicate drug sensitivities and negative sDSS values represent drug resistance. File_3.2.: Drug response data including drug sensitivity scores (DSS) and selective drug sensitivity scores (sDSS) for 515 compounds across 181 samples (164 AML patient samples and 17 healthy control samples). The data is identical to the Supplementary Table 7 in the manuscript. Note: We recommend using selective DSS values instead of raw values (% inhibition, IC50, DSS).  Note: If the value is missing, the drug was not tested for that given sample. File_4: Drug sensitivity and resistance testing (DSRT) assay details for 181 samples (164 AML patient samples and 17 healthy control samples). The information includes medium (MCM or CM) used for the drug testing, % cell viability after 72 h without drug testing and blast cell percentage of each sample. Note: Column E is the ratio of luminescence values at 72 h and 0 h. The fold change in the cell viability without drug treatment was calculated as % cell viability. That is why the value could be more than 100% e.g. 70% cell viability meaning that 30% cells died during 72 h and 300% cell viability meaning that cells grew 3 times in 72 h incubation period.   3. Exome-sequencing data for 225 AML patient samples Note: The number of samples in the manuscript is 226. The correct number used in the analyses is 225. Mutation data. The cancer specific gene list was prepared by combining AML related genes from TCGA(2) (n=23), InToGen(3) (n=32), Papaemmanuil et al.(4) (n=111) and Census database(5) (n=616). Out of these genes, we found 340 genes as mutated across 225 AML patient samples. The mutation was called with P-values less than 0.05. File_5: VAF (variant allele frequency) of 340 cancer-specific genes across 225 AML patient samples. The VAF was calculated using paired skin samples as a control from the same AML patient. File_6: Binary data for 57 cancer specific genes frequently mutated (a given mutation detected in 5 or more samples) across 225 AML patient samples.   4. RNA-sequencing data for 163 AML patient samples and 4 healthy CPM (count per million) data: The CPM values are batch corrected values used for direct comparison of gene expression. File_7: Log2CPM values for 18,202 protein coding genes across 167 samples (163 AML patient samples and 4 healthy CD34+ samples). File_8: Raw read count data RNA-seq library information for all 60,619 genes across 167 samples (163 AML patient samples and 4 healthy CD34+ samples). The raw read count data was used to calculate differential gene expression. File_9: RNA-seq library information including RNA extraction method and sequencing library preparation information for 167 samples (163 AML patient samples and 4 healthy CD34+ samples).   References 1.         Yadav B, Pemovska T, Szwajda A, Kulesskiy E, Kontro M, Karjalainen R, et al. Quantitative scoring of differential drug sensitivity for individually optimized anticancer therapies. Scientific Reports 2014;4:5193. 2.         Ley TJ, Miller C, Ding L, Raphael BJ, Mungall AJ, Robertson A, et al. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med 2013;368(22):2059-74. 3.         Gonzalez-Perez A, Perez-Llamas C, Deu-Pons J, Tamborero D, Schroeder MP, Jene-Sanz A, et al. IntOGen-mutations identifies cancer drivers across tumor types. Nature Methods 2013;10(11):1081-2. 4.         Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, et al. Genomic classification and prognosis in acute myeloid leukemia. New England Journal of Medicine 2016;374(23):2209-21. 5.         Tate JG, Bamford S, Jubb HC, Sondka Z, Beare DM, Bindal N, et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Research 2019;47(D1):D941-D7.

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 2 FOV3

Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 2 FOV3) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 1 FOV2

Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 1 FOV2) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 1 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 1 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 1 FOV2

opencc-by-4.0Apr 2023View details →

Single-Cell Profiling of CD8+ T Cells in Acute Myeloid Leukemia Reveals a Continuous Spectrum of Differentiation and Clonal Hyperexpansion

Data for the publication Single-Cell Profiling of CD8+ T Cells in Acute Myeloid Leukemia Reveals a Continuous Spectrum of Differentiation and Clonal Hyperexpansion

MicroRNA-target pathways in acute myeloid leukaemia

Pathway map of 17 microRNAs (miRs) in acute myeloid leukaemia (AML). Details over- and under-expressed miRs, the impact on relevant targets, interaction of targets with other proteins and/or pathways, and the overall impact on AML onset, progression and/or maintenance. All miR targets identified and verified via miRTarBase, KEGG and relevant literature.

openCC0Jan 2021View details →

OpenNeuro40/100

EEG: Visual Working Memory in Acute TBI

Open the record for dataset details and reuse information.

opencc-by-4.0Mar 2020View details →

Consensus QSAR models estimating acute aquatic toxicity for three trophic levels organisms: Algae, Daphnia and Fish

We report new consensus models estimating acute toxicity for algae, daphnia and fish endpoints. We assembled a large collection of 3680 public unique compounds annotated by, at least, one experimental value for the given endpoint. Support Vector Machine models were internally and externally validated following the OECD principles. Reasonable predictive performances were achieved (RMSEext = 0.56 – 0.78) which are in line with those of state-of-the-art models. The known structural alerts are compared with analysis of the atomic contributions to these models obtained using the ISIDA/ColorAtom utility. A benchmarking against existing tools has been carried out on a set of compounds considered more representative and relevant for the chemical space of the current chemical industry. Our model scored one of the best accuracies and data coverage. Nevertheless, industrial data performances were noticeably lower than those on public data, indicating that existing models fail to meet the industrial needs. Thus, final models were updated with the inclusion of new industrial compounds, extending applicability domain and relevance for application in an industrial context. Generate models and collected public data are made freely available. Available fields in the SDF file: <ul> <li>SMILES_Canonical: canonical SMILES code</li> <li>DB: source of the data, "Litterature set" means that the data is originated from an article (see the companion article of the dataset for details).</li> <li>endpoint: organism for which endpoint is available</li> <li>CASRN: CAS registration number</li> <li>98-81-7</li> <li>pEC50 - DAPHNIA: Daphnia, mortality, which is evaluated by the immobilization of the invertebrate is recorded at 48 hours and expressed as the log median effective concentration (pEC50)</li> <li>mg/L - DAPHNIA: Daphnia, mortality, which is evaluated by the immobilization of the invertebrate is recorded at 48 hours and expressed as the median effective concentration (EC50)</li> <li>pLC50 - FISH: Fish, the log median lethal concentration measured at 96 hours is considered (pLC50)</li> <li>mg/L - FISH: Fish, the log median lethal concentration measured at 96 hours is considered (LC50)</li> <li>pEC50 - ALGA: Algae, the  purpose  is  to  determine  the substance’s growth inhibition effect, expressed as the log median effective concentration (pEC50) measured at 72 hours</li> <li>mg/L - ALGA: Algae, the  purpose  is  to  determine  the substance’s growth inhibition effect, expressed as the median effective concentration (EC50) measured at 72 hours</li> </ul>

opencc-by-4.0Sep 2020View details →

Instantaneous In Vivo Imaging of Acute Myocardial Infarct by NIR‐II Luminescent Nanodots

Fast and precise localization of ischemic tissues in the myocardium after an acute infarct is required by clinicians as the first step toward accurate and efficient treatment. Nowadays, diagnosis of a heart attack at early times is based on biochemical blood analysis (detection of cardiac enzymes) or by ultrasound‐assisted imaging. Alternative approaches are investigated to overcome the limitations of these classical techniques (time‐consuming procedures or low spatial resolution). As occurs in many other fields of biomedicine, cardiological preclinical imaging can also benefit from the fast development of nanotechnology. Indeed, bio‐functionalized near‐infrared‐emitting nanoparticles are herein used for in vivo imaging of the heart after an acute myocardial infarct. Taking advantage of the superior acquisition speed of near‐infrared fluorescence imaging, and of the efficient selective targeting of the near‐infrared‐emitting nanoparticles, in vivo images of the infarcted heart are obtained only a few minutes after the acute infarction event. This work opens an avenue toward cost‐effective, fast, and accurate in vivo imaging of the ischemic myocardium after an acute infarct.

opencc-by-4.0Sep 2024View details →

Distinct Stromal Cell Populations Define the B-cell Acute Lymphoblastic Leukemia Microenvironment

Processed single-cell RNA-seq from the study  <ul> <li>10X Genomics CellRanger output (barcodes.tsv, genes.tsv, matrix.mtx) for each each sample</li> <li>Metadata</li> <li>Seurat object of the integrated scRNAseq dataset</li> <li>Xenium object of the spatial transcriptomic data</li> </ul> Distinct Stromal Cell Populations Define the B-cell Acute Lymphoblastic Leukemia Microenvironment Mauricio N. Ferrao Blanco1, Bexultan Kazybay1, Mirjam Belderbos1, Olaf Heidenreich1, Hermann Josef Vormoor1,2 1 Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands 2 University Medical Center Utrecht, Utrecht, the Netherlands Abstract The bone marrow microenvironment plays a critical role in B-cell acute lymphoblastic leukemia (B-ALL) progression, yet its cellular heterogeneity remains poorly understood. Using single-cell RNA sequencing on patient-derived of bone marrow aspirates from pediatric B-ALL patients, we identified two distinct mesenchymal stromal cell (MSC) populations: early mesenchymal progenitors and adipogenic progenitors. Spatial transcriptomic analysis further revealed the localization of these cell types and identified a third stromal population, osteogenic-lineage cells, exclusively present in the bone biopsy. Functional ex vivo assays using sorted stromal populations derived from B-ALL patient bone marrow aspirates demonstrated that both early mesenchymal and adipogenic progenitors secrete key niche-supportive factors, including CXCL12 and Osteopontin, and support leukemic cell survival and chemoresistance. Transcriptomic profiling revealed that B-ALL cells interact differently with stromal subtypes. Notably, adipogenic progenitors, but not early mesenchymal progenitors, provide support to leukemic cells through interleukin-7 and VCAM1 signaling. Stromal cells from B-ALL patients exhibited an enhanced adipogenic differentiation capacity compared to healthy controls. Moreover, co-culture experiments showed that B-ALL cells induce adipogenic differentiation in healthy MSCs through a cell contact-dependent mechanism. Adipogenic progenitors were also enriched in relapse samples, implicating them in disease progression. These findings highlight the complexity of the B-ALL microenvironment and identify different specialized stromal niches with which the leukemic cells can engage.

dryad40/100

Data and code for: Acute heat priming promotes short-term climate resilience of early life stages in a model sea anemone

Across diverse taxa, sublethal exposure to abiotic stressors early in life can lead to benefits such as increased stress tolerance upon repeat exposure. This phenomenon, known as hormetic priming, is largely unexplored in early life stages of marine invertebrates, which are increasingly threatened by anthropogenic climate change. To investigate this phenomenon, larvae of the sea anemone and model marine invertebrate Nematostella vectensis were exposed to control (18°C) or elevated (24°C, 30°C, 35°C, or 39°C) temperatures for 1 hour at 3 days post-fertilization (DPF), followed by return to control temperatures (18°C). The animals were then assessed for growth, development, metabolic rates, and heat tolerance at 4, 7, and 11 DPF. Priming at intermediately elevated temperatures (24°C, 30°C, or 35°C) augmented growth and development compared to controls or priming at 39°C. Indeed, priming at 39°C hampered developmental progression, with around 40% of larvae still in the planula stage at 11 DPF, in contrast to 0% for all other groups. Total protein content, a proxy for biomass, and respiration rates were not significantly affected by priming, suggesting metabolic resilience. Heat tolerance was quantified with acute heat stress exposures, and was significantly higher for animals primed at intermediate temperatures (24°C, 30°C, or 35°C) compared to controls or those primed at 39°C at all time points. To investigate a possible molecular mechanism for observed changes in heat tolerance, the expression of heat shock protein 70 (HSP70) was quantified at 11 DPF. Expression of HSP70 significantly increased with increasing priming temperature, with the presence of a doublet band for larvae primed at 39°C, suggesting persistent negative effects of priming on protein homeostasis. Interestingly, primed larvae in a second cohort cultured to 6 weeks post-fertilization continued to display hormetic growth responses, whereas benefits for heat tolerance were lost; in contrast, negative effects of short-term exposure to extreme heat stress (39°C) persisted. These results demonstrate that some dose-dependent effects of priming waned over time while others persisted, resulting in heterogeneity in organismal performance across ontogeny following priming. Overall, these findings suggest that heat priming may augment the climate resilience of marine invertebrate early life stages via the modulation of key developmental and physiological phenotypes, while also affirming the need to limit further anthropogenic ocean warming.

opencc-zeroNov 2023View details →

opencc-by-4.0Nov 2023View details →

Supplementary Data for Stabilizing the Proteomes of Acute Myeloid Leukemia Cells: Implications for Cancer Proteomics

Supplementary data for:  Stabilizing the Proteomes of Acute Myeloid Leukemia Cells: Implications for Cancer Proteomics Authors: Robert Sprung, Qiang Zhang, Michael H. Kramer, Matthew C. Christopher, Petra Erdmann-Gilmore, Yiling Mi, James P. Malone, Timothy J. Ley, and R. Reid Townsend.Table S1 - AML Case descriptors and LC-MS data files Table S2 - All Peptides by Case -LFQ Table S3 - Identification of tryptic and non-tryptic peptides from five AML cases with high and low expression of ELANE Table S4 - Number of proteins identified by LFQ proteomics with a minimum of 2 tryptic peptides Table S5 - DFP Adduct Database Search Tryptic Peptides Table S6 - Protein quantification from TMT 11-plex tryptic peptides with and without DFP Table S7 - Tryptic peptides used for protein quantification from TMT 11-plex with and without DFP Table S8 - Changes in TMT relative abund. with DFP treatment Table S9 - Protein quantification from LFQ tryptic peptides with and without DFP Table S10 - Proteins with significant change in abundance with DFP treatment using Label-Free Quantitation

dryad40/100

The effect of Israeli acute paralysis infection on honey bee brood care behavior

To protect themselves from communicable diseases, social insects utilize social immunity—behavioral, phsyiological, and organizational means to combat disease transmission and severity. Within a honey bee colony, larvae are visited thousands of times by nurse bees, representing a prime environment for pathogen transmission. We investigated a potential social immune response to Israeli acute paralysis virus (IAPV) infection in brood care, testing the hypotheses that bees will respond with behaviors that result in reduced brood care, or that infection results in elevated brood care as a virus-driven mechanism to increase transmission. We tested for group-level effects by comparing three different social environments in which 0%, 50%, or 100% of bees were experimentally infected with IAPV. We investigated individual-level effects by comparing exposed bees to unexposed bees within the mixed-exposure treatment group. We found no evidence for a social immune response at the group level; however, individually, exposed bees interacted with the larva more frequently than their unexposed nestmates. While this could increase virus transmission from adults to larvae, it could also represent a hygienic response to increase grooming when an infection is detected. Together, our findings underline the complexity of disease dynamics in complex social animal systems.

opencc-zeroJan 2024View details →

opencc-by-4.0Dec 2023View details →

Text-fig. 4. Monocots. a, b: Large monocot leaf part and counterpart, UAPC-ALTA S 17955A, B. a: Wide leaf showing entire margin at left. b: Counterpart showing dark wide midrib, and and secondaries parallel to one another, arising at low acute angle. c–e: Monocot leaf with parallel venation. c: Overview of elongate monocot leaf with parallel veins horizontal and linear to oval structures and smaller leaf fragment of same type lacking them (at lower right), UAPC-ALTA S 59491. d: Higher magnification of the smaller fragment with weak cross veins. e: Higher magnification of larger specimen with linear to oval structures between parallel veins. f, g: Monocot leaf with parallel venation. Fig. (f) shows higher magnification and (g) shows overview, BBM-PAL-P000009. Scale bars: a, b = 5 cm, c = 4 cm, d–f = 1 cm, g = 2 cm. in The Early Eocene Flora Of Horsefly, British Columbia, Canada And Its Phytogeographic Significance

Text-fig. 4. Monocots. a, b: Large monocot leaf part and counterpart, UAPC-ALTA S 17955A, B. a: Wide leaf showing entire margin at left. b: Counterpart showing dark wide midrib, and and secondaries parallel to one another, arising at low acute angle. c–e: Monocot leaf with parallel venation. c: Overview of elongate monocot leaf with parallel veins horizontal and linear to oval structures and smaller leaf fragment of same type lacking them (at lower right), UAPC-ALTA S 59491. d: Higher magnification of the smaller fragment with weak cross veins. e: Higher magnification of larger specimen with linear to oval structures between parallel veins. f, g: Monocot leaf with parallel venation. Fig. (f) shows higher magnification and (g) shows overview, BBM-PAL-P000009. Scale bars: a, b = 5 cm, c = 4 cm, d–f = 1 cm, g = 2 cm.

opencc-by-4.0Dec 2023View details →

Fat oxidation rates and cardiorespiratory responses during exercise in different subject populations with post-acute sequelae of SARS-CoV-2 infection: a comparison with normative percentile values

INTRODUCTION: Post-acute sequelae of SARS-CoV-2 infection (PASC) presents a spectrum of symptoms following acute COVID-19, with exercise intolerance being a prevalent manifestation likely linked to disrupted oxygen metabolism and mitochondrial function. This study aims to assess maximal fat oxidation (MFO) and exercise intensity at MFO (FATmax) in distinct PASC subject groups and compare these findings with normative data. METHODS: Eight male subjects with PASC were involved in this study. The participants were divided in two groups: “endurance-trained” subjects (V̇O2max > 55 ml/min/kg) and “recreationally-active” subjects (V̇O2max < 55 ml/min/kg). Each subject performed a graded exercise test until maximal oxygen consumption (V̇O2max) to measure fat oxidation. Subsequently, MFO was assessed and FATmax calculated as the ratio between V̇O2 at MFO and V̇O2max. RESULTS: The MFO and FATmax of “endurance-trained” subjects were 0.85, 0.89, 0.71 and 0.42, and 68%, 69%, 64% and 53%, respectively. Three out of four subjects showed both MFO and FATmax values placed over the 80th percentile of normative data. The MFO and FATmax of “recreationally-active” subjects were 0.34, 0.27, 0.35 and 0.38, and 47%, 39%, 43% and 41%, respectively. All MFO and FATmax values of those subjects placed below the 20th percentile or between the 20th and 40th percentile. DISCUSSION: Significant differences in MFO and FATmax values between 'endurance-trained' and “recreationally-active” subjects suggest that specific endurance training, rather than simply an active lifestyle, may provide protective effects against alterations in mitochondrial function during exercise in subjects with PASC.

opencc-by-4.0Nov 2024View details →

ADIPOQ Gene Variants (rs266729, rs2241766, rs1501299) and Acute Myocardial Infarction in Vietnamese Patients with Type 2 Diabetes Mellitus

This data is from a study project about ADIPOQ Gene Variants (rs266729, rs2241766, rs1501299) and Acute Myocardial Infarction in Vietnamese Patients with Type 2 Diabetes Mellitus. The data contains information from 550 patients with their identification removed to ensure confidentiality.

opencc-by-4.0Oct 2024View details →

Clinical phenotypes in acute and chronic infarction explained through human ventricular electromechanical modelling and simulations

This dataset includes the meshes, model parameters, and Alya executable binary for simulating acute and chronic stage post-myocardial infarct using Alya, to replicate the results in the article <a href="https://doi.org/10.7554/eLife.93002.1">https://doi.org/10.7554/eLife.93002.1</a> For each scenario simulated, a baseline simulation folder is provide with all the required meshes, fields, and model parameters necessary to run an Alya simulation. An additional series of models with variability in ionic conductances is also included for each scenario under the folder <scenario>_pom/, under which 20 simulations are included. For each simulation, only the file describing the ionic conductance scaling factors (ventricular_cell.txt) are included, all other files required to run each particular simulation can be found in the <scenario>_baseline/ version.  The file structure is as follows: <ul> <li>Alya executable binary</li> <li>control_baseline</li> <li>control_pom</li> <li>75%_transmural_scar <ul> <li>acute <ul> <li>bz1_baseline</li> <li>bz1_pom <ul> <li>pom_id_0</li> <li>...</li> <li>pom_id_19</li> </ul> </li> <li>bz2_baseline</li> <li>bz2_pom <ul> <li>pom_id_0</li> <li>...</li> <li>pom_id_19</li> </ul> </li> <li>bz3_baseline</li> <li>bz3_pom <ul> <li>pom_id_0</li> <li>...</li> <li>pom_id_19</li> </ul> </li> </ul> </li> <li>chronic <ul> <li>rz1_baseline</li> <li>rz1_pom <ul> <li>pom_id_0</li> <li>...</li> <li>pom_id_19</li> </ul> </li> <li>rz2_baseline</li> <li>rz2_pom <ul> <li>pom_id_0</li> <li>...</li> <li>pom_id_19</li> </ul> </li> </ul> </li> <li>fast_pacing <ul> <li>alternans1</li> <li>alternans4</li> </ul> </li> </ul> </li> </ul> The simulation files in alternans4/ was use to generate results Figure 6 of the accompanying article, and alternans1/ was used to generate results Figure 7.  The Alya executable binary has been built on ARCHER2 with the following loaded modules: 1) craype-x86-rome      2) libfabric/1.12.1.2.2.0.0 3) craype-network-ofi             4) perftools-base/22.12.0              5) xpmem/2.5.2-2.4_3.30__gd0f7936.shasta   6) bolt/0.8          7) epcc-setup-env    8) load-epcc-module 9) gcc/11.2.0        10) craype/2.7.19      11) cray-dsmml/0.2.2   12) cray-mpich/8.1.23 13) cray-libsci/22.12.1.1  14) PrgEnv-gnu/8.3.3   15) tk/8.6.13            16) tcl/8.6.13     17) cray-python/3.9.13.1 18) matplotlib/3.7.2 To replicate the study, access to an installation of the code in the Nord supercomputer can be requested to <a title="mailto:mariano@elem.bio" href="mailto:mariano@elem.bio">mariano@elem.bio</a>

opencc-by-4.0May 2024View details →

A phenopushing platform to identify compounds that alleviate acute hypoxic stress by fast-tracking cellular adaptation

Severe acute hypoxic stress is a major contributor to the pathology of human diseases, including ischemic disorders. Current treatments focus on managing consequences of hypoxia, with few addressing cellular adaptation to low-oxygen environments. Here, we investigate whether accelerating hypoxia adaptation could provide a strategy to alleviate acute hypoxic stress. We develop a high-content phenotypic screening platform to identify compounds that fast-track adaptation to hypoxic stress. Our platform captures a high-dimensional phenotypic hypoxia response trajectory consisting of normoxic, acutely stressed, and chronically adapted cell states. Leveraging this trajectory, we identify compounds that phenotypically shift cells from the acutely stressed towards the adapted state, revealing mTOR/PI3K or BET inhibition as strategies to induce this phenotypic shift. Importantly, our compound hits promote the survival of liver cells exposed to ischemia-like stress, and rescue cardiomyocytes from hypoxic stress. Our “phenopushing” platform offers a general, target-agnostic approach to identify compounds and targets that accelerate cellular adaptation, applicable across various stress conditions.