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• PSCP_mutation analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shred by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002231

• PSCP_bisulphite analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002235

• FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

  The ELIXIR All Hands Meeting (AHM) was held in Uppsala, Sweden this June. We at EGA always look forward to this meeting as a chance to see many of our partners and colleagues face-to-face. The Federated EGA (FEGA) is one initiative that always benefits from the AHM, and this year FEGA was in the spotlight, with several questions related to the advances we've made recently. We held this year's FEGA workshop a little differently, with most time for discussions on various “hot topics”. Organised in different breakouts, over 2 rounds, participants could choose which session they wanted to attend. One breakout was a general Q+A about FEGA and the path to join. We had a diverse range of participants, including experts from Central EGA (CEGA) and FEGA inaugural nodes, people from up and coming nodes at various stages of readiness, as well as participants not directly a part of FEGA but curious to learn more. It made for a great discussion! In this blog post, we highlight some of the questions for those who didn’t have a chance to be there. What is the FEGA Collaboration Agreement? It is a legal agreement between the node and Central EGA (CEGA) where both parties agree to certain responsibilities, like what services will be provided, sharing of public metadata with CEGA, interoperable technologies and more. The agreement is for 4 years, with the expectation of long-term sustainability. If a node is made up of multiple institutes, one institute must be the signatory. This could require a legal agreement within the node. CEGA is composed of CRG and EMBL-EBI (EGA itself has its own legal agreement between these institutes) Check the FEGA Collaboration Agreement What about purely medical data? Is this accepted in FEGA? CEGA only accepts data approved for secondary research use. We do accept medical data collected in this context, as do some nodes. Nodes are able to accept any data they like, as long as it is sensitive, thus in need of controlled access. What about other data types other than genomics? Like proteomics or images? They can be accepted, although CEGA is currently not designed with those formats in mind, so they might not fit with precision in the data model. The FEGA nodes are welcome to accept any data they want. Proteomic studies generating sensitive data are increasing, and specific work will likely be developed in the near future to adress this need. Does CEGA require a certain amount or type of data to be shared by the node? No, we do not and it's up to each node to decide what specific data types they accept and in what format. Nonetheless, a FEGA node has the duty to be open to data submission from any institution of their country, and can't be limited by design to a single or limited data source. Does CEGA and FEGA require a certain amount or type of details and description on the data to be submitted to the node? Data description (technical and biological), usually called metadata in this field, is crucial for the findability of the submitted data. Thus, we highly recommend including as much information as available to maximise the discoverability of the data. Specifical minimal metadata is defined in the submission schema, and thresholds are specified by the nodes. We are currently working towards a unified FEGA metadata model. What are the geographical borders of FEGA? FEGA should make the E for Everyone, because any institute worldwide could join and we indeed do have countries and use-cases worldwide. Some of them are very close to officially joining the federation. What are the main differences between FEGA and GDI? The two networks have a lot in common and also some critical differences. You can read all about this in one of our latest blog post. If you have more questions, please consider having a look at the FEGA onboarding webpage and, of course, don't miss our workshop at the ELIXIR AHM next year!

  Blog fega-faqs-elixir-ahm-2024

• Virtual Growing Child 5-Dimensional Functional Models for Treating Respiratory Anomalies (dMRI-VGC)

  Objectives We are sharing a database of dynamic magnetic resonance imaging (dMRI) scans of normal children, which can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can also be useful to advance future AI-based research on image-based object segmentation and analysis. Background In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. Participants 200 normal children (ages 6-18 years) participated in our research study related to this dataset. DesignThe shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dMRI images representing one breathing cycle for each normal child and also segmentations of 10 objects at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right sides separately, are also reported. The database has thus 4,000 3D segmentations from 200 normal children in total. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. All dMRI scans are acquired from normal children during free-breathing. The dMRI acquisition protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm3, 320×320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquired 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular study participant.The collected dMRI scan data then went through the procedure of 4D image construction, image processing, object segmentation, and volumetric measurements from segmentations. 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects 175-280 slices (35 sagittal locations × 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method. Image processing: Intensity standardization is performed on every time point/3D volume of the 4D image so that image values have the same tissue-specific meaning across all subjects. Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All dMRI scans utilize large field of view images, which include the full thorax and abdomen to the inferior aspect of the kidneys in the sagittal plane. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under the supervision of a radiologist with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all datasets. Volumetric measurements based on object segmentations for lung volumes (left and right separately) at EE and EI, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported. ConclusionsThe provided database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. The database has 4,000 3D segmentations from 200 normal children, which to our knowledge is the largest and only such dMRI dataset to date. All images and object segmentations are saved in DICOM. All DICOM files (176,574 in total) have been anonymized, and PHI has been removed. The database can be used as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The large amount of object segmentations can potentially benefit AI-based research on image-based object segmentation and analysis.

  Study phs004002

• Prevention and Early Treatment of Acute Lung Injury (PETAL) - Low Tidal Volume Universal Support Feasibility of Recruitment for Interventional Trial (LOTUS FRUIT) (PETAL-LOTUS FRUIT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The two main goals of PETAL-LOTUS FRUIT were to conduct a prospective, observational study within all PETAL Network sites to determine the frequency of and outcomes from acute respiratory failure and the current usual care for tidal volume ventilation in patients with and without acute respiratory distress syndrome (ARDS), and to simulate the design and power of the proposed LOTUS trial. Background: A previous study demonstrated improved survival among patients with ARDS receiving tidal volume (Vt) targeted to 6 ml/kg of predicted body weight (PBW). As a result, low–tidal volume ventilation (LTVV) is now recommended for all patients with ARDS, although penetration of this evidence-based practice has been limited, especially early in mechanical ventilation. LTVV may also benefit patients without ARDS. Consequently, there has been increasing call to apply LTVV for all patients with acute respiratory failure upon initiation of mechanical ventilation. The PETAL Network considered performing a pragmatic stepped-wedge, cluster-randomized, controlled, hybrid implementation trial to examine systematic implementation of a default 6 ml/kg PBW LTVV strategy in patients with acute respiratory failure requiring intubation to improve adherence to LTVV and decrease mortality in acute respiratory failure. Trial planning may be better estimated by simulation than routine, simplistic calculations, but such simulations require detailed data of initial parameters. Participants: 2848 patients from 49 hospitals were enrolled. Enrollment varied by hospital, ranging from 4 to 100 patients, the maximum enrollment allowed per site. Design: PETAL-LOTUS FRUIT was a multicenter, prospective, observational cohort study of patients with acute respiratory failure on mechanical ventilation in the PETAL Network hospitals. For all patients, baseline demographic data, the hospital location, indication for intubation (hypoxemic or hypercapnic respiratory failure or both, altered level of consciousness, or surgery), type of intensive care unit (ICU), and Sequential Organ Failure Assessment score in the first 24 hours after intubation were collected. Baseline ventilator data immediately after intubation, arterial blood gas results and oxygen saturation as measured by pulse oximetry, and presence of ARDS was also collected for all patients. ARDS was defined as a ratio of arterial oxygen tension to fraction of inspired oxygen (FiO2) less than or equal to 300 with a chest radiograph within 24 hours of the qualifying ratio of arterial oxygen tension to FiO2 that had bilateral infiltrates unexplained by mass, collapse, or effusion. For the first 50 patients enrolled at each hospital, daily data on ventilator mode, Vt, and presence of ARDS for the first 3 days after intubation was collected. Vt indexed to PBW was calculated from the set Vt for patients on ventilator mode with volume settings. For patients on pressure ventilation modes, Vt was calculated from the ratio of minute ventilation (in ml/min) to the respiratory rate. Enrolled patients were followed until hospital discharge or 28 days for clinical outcomes including mortality, ventilator-free days, and length of stay. To determine the possible improvement in mortality that could be observed with a reduction in Vt from current usual care in the PETAL-LOTUS FRUIT cohort to 6 ml/kg PBW, mortality was estimated as a function of initial Vt. Five models based on data from three distinct patient populations were used. 500 simulations of a stepped-wedge, cluster-randomized clinical trial using the model with greatest predicted benefit for lowering the Vt to 6 ml/kg PBW in PETAL-LOTUS FRUIT sites were performed. Conclusions: Use of initial tidal volumes less than 8 ml/kg predicted body weight was common at hospitals participating in the PETAL Network. After considering the size and budgetary requirement for a cluster-randomized trial of LTVV versus usual care in acute respiratory failure, the PETAL Network deemed the proposed trial infeasible (PMID: 30407869).

  Study phs003791

• Heart Failure Network: Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEF (HFN INDIE-BioLINCC)

  Data Access NOTEPlease refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.ObjectiveTo determine the effect of inhaled, nebulized inorganic nitrite on exercise capacity in patients with heart failure with preserved ejection fraction. Background Approximately half of patients with heart failure have a preserved ejection fraction (HFpEF). However, there are no proven effective medical treatments for this syndrome. Evidence suggests that impairments in nitric oxide availability have a potentially important role in the pathophysiology of HFpEF. Unlike organic nitrates, inorganic nitrite is converted to nitric oxide in the presence of hypoxia and acidosis, conditions that develop during exercise. Because the cardiac, vascular, and skeletal muscle abnormalities that limit physical capacity and contribute to symptoms in patients with HFpEF characteristically develop during exercise, inorganic nitrite may provide the best way to target nitric oxide delivery precisely at the time of greatest need. The HFN-INDIE trial was initiated to test the hypothesis that compared to placebo, longer-term use of inhaled, nebulized inorganic nitrite would enhance peak exercise capacity in patients with HFpEF. Participants A total of 105 participants were randomized. 53 were randomized to receive nitrite first and 52 were randomized to receive placebo first. Design HFN-INDIE was a multicenter, randomized, double-blind, placebo-controlled, crossover study. After enrollment, patients underwent baseline studies to determine eligibility. All patients were required to display objective exercise limitation, evidenced by reduced peak oxygen consumption (V̇O2) on cardiopulmonary exercise testing of less than 75% predicted, with a respiratory exchange ratio indicative of maximal effort (≥1.0). Following qualifying exercise testing, eligible participants received an open-label, single-dose run-in of inhaled, nebulized sodium nitrite (80 mg) to assess tolerability, symptoms, and orthostatic vital signs. Patients developing hypotension (systolic blood pressure The prespecified primary end point was peak V̇o2, measured as the highest 30-second average during upright cycle ergometry, during the 4-week period in which patients were receiving inorganic nitrite as compared with placebo. Accelerometry, health-related quality-of-life scores on the self-administered Kansas City Cardiomyopathy Questionnaire (score range, 0-100, with higher scores indicating better quality of life), echocardiographic indicators of cardiac filling pressures measured at trough drug levels (E/e' ratio, estimated pulmonary artery systolic pressure, and left atrial volume index; lower scores indicate better health for all), ventilatory efficiency (VE/V̇co2, lower indicating better health), exercise time (higher indicating better health), and NT-proBNP levels (lower indicating better health) were also collected. Conclusions Among patients with HFpEF, administration of inhaled inorganic nitrite for 4 weeks, compared with placebo, did not result in significant improvement in exercise capacity. Borlaug et al., 2018, PMID: 30398602.

  Study phs003667

• Acute Respiratory Distress Network (ARDSNet) Study 04 Assessment of Low Tidal Volume and Elevated End-Expiratory Volume to Obviate Lung Injury (ALVEOLI-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. BiospecimensAccess to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ALVEOLI include Plasma and DNA. Please note that use of biospecimens in genetic research is subject to a tiered consent. Available Data Outcome data regarding organ failure free days are not available. Objectives The ARDS Network is a consortium of clinical centers and a coordinating center to design and test novel therapies for the treatment of Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). The ARDS Network 01/03 trials included an investigation of the efficacy and safety of Ketoconazole and Respiratory Management in the treatment of ALI and ARDS (KARMA). The Ketoconazole arm of the KARMA study was later stopped due to an inability to show efficacy. Participants continued to be randomized to the respiratory management arms of the study (ARMA), which compared two ventilator strategies: a tidal volume of 6 mL/kg versus 12 mL/kg. The LARMA phase of the study investigated the efficacy of Lisofylline and Respiratory Management. The objective of the ALVEOLI study was to compare clinical outcomes of participants with ALI and ARDS treated with a higher end-expiratory lung volume/lower FiO2 versus a lower end-expiratory lung volume/higher FiO2 ventilation strategy. The ALVEOLI study tested the hypothesis that mortality from ALI and ARDS would be reduced with a mechanical ventilation strategy designed to prevent lung injury from repeated collapse of bronchioles and alveoli at end-expiration. Background Most participants requiring mechanical ventilation for ALI and ARDS receive positive end-expiratory pressure (PEEP) of 5 to 12 cm of water. Higher PEEP levels may improve oxygenation and reduce ventilator-induced lung injury but may also cause circulatory depression and lung injury from overdistention. PEEP levels higher than traditional levels may reduce ventilator-induced lung injury by decreasing the proportion of nonaerated lung and higher PEEP levels may allow arterial-oxygenation goals to be met at a lower level of inspired oxygen (FiO2). Participants A total of 550 participants were randomized to receive mechanical ventilation with either lower or higher PEEP levels, which were set according to different tables of predetermined combinations of PEEP and fraction of inspired oxygen. Conclusions Participants with acute lung injury and ARDS who receive mechanical ventilation with a tidal-volume goal of 6 ml per kilogram of predicted body weight and an end-inspiratory plateau-pressure limit of 30 cm of water, clinical outcomes were statistically similar whether lower or higher PEEP levels are used. (Brower, et al., 1004; PMID: 15269312).

  Study phs003714

• Genome-Wide Association of Type 2 Diabetes in Africans: The AADM Study

  The Africa America Diabetes Mellitus (AADM) study is a genetic epidemiological study of type 2 diabetes in Sub-Saharan Africa. Study participants were enrolled through university medical centers in Nigeria, Ghana, and Kenya. Ethical approval for the study was obtained from the Institutional Review Board (IRB) of each participating institution. All subjects provided written informed consent for the collection of samples and subsequent analysis. The case definition of type 2 diabetes was based on the American Diabetes Association (ADA) criteria. After providing informed consent, participants underwent the same enrollment procedures, which included collection of demographic information, medical history, clinical examination and a blood draw. Genome-wide SNP genotyping was done on either the Axiom™ PanAFR SNP array (n=1,808) or the Multi-Ethnic Global Array (MEGA) (n=3,423). After appropriate quality control, in silico imputation was done using the African Genome Resources Haplotype Reference Panel (at the Sanger Imputation Service). Imputed genotypes were filtered for variants with minor allele frequency (MAF)≥ 0.01 and information score (info) ≥ 0.3 for genetic association analysis. Genome-wide association analysis between type 2 diabetes and the imputed genotype dosages was done using a generalized linear mixed model, which adjusted for age, gender, body mass index, the genetic relatedness matrix and the first three principal components (PCs) of the genotypes.Metabolomics profiling of plasma samples of type 2 diabetes (T2D) cases and controls in Nigerians (West Africa) was done in the AADM Study. Plasma metabolites were measured in a total of 580 individuals (N=310 for the discovery phase and N=270 for the replication stage) using the global/untargeted approach on the Metabolon platform and following the manufacturer's standard operation protocols. The analytic methods are described in detail in Doumatey et al. [Genome Med 2024]. The measured metabolites level represented by peak areas are relative values. The peak area data were batch-normalized to remove the instrument batch effects (batch variability) and the batch-normalized data correspond to the median-scaled raw data. For each identified metabolite, the minimum value across all batches in the batch-normalized was imputed for the missing values. The batch-normalized and imputed data are natural log-transformed and consist of 1116 metabolites for the discovery cohort and 1071 metabolites for the replication. Welch's two-sample t-test on the log-transformed data was used to identify metabolites differentially expressed between T2D cases and controls . All other statistical analyses conducted on both the replication and discovery cohorts used the log-transformed data. To merge the discovery and replication, the same quality control samples (bridge samples) were run with each batch of the experimental samples in both cohorts and used to correct for additional variability and uniformize the procedures. The resulting merged data is the QC-normalized and imputed data that contains only metabolites that were common to both cohorts and successfully bridged for all batches (n= 891 metabolites).

  Study phs001844

• Resuscitation Outcomes Consortium (ROC) Controlled Study of the Clinical Effectiveness of Automated Real-Time Feedback on CPR Process Conducted at a Subset of ROC Sites (CPR) (ROC-CPR-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: A substudy of the ROC PRIMED trial, the ROC CPR trial sought to investigate whether real-time audio and visual feedback during cardiopulmonary resuscitation (CPR) outside a hospital increases the proportion of participants who achieved prehospital return of spontaneous circulation.Background: Cardiopulmonary resuscitation is an essential link in the chain of survival for treating cardiac arrest. However, performance of CPR is highly variable both outside hospital and in hospital. Interruptions in chest compression, inadequate depth of chest compression, and high rates of ventilation adversely affect blood flow during chest compressions and can hinder resuscitation. Suboptimal CPR, particularly time spent without chest compressions (low chest compression fraction), can reduce survival of cardiac arrest patients.Current technology incorporated into a monitor-defibrillator can assess core components of CPR through the use of an accelerometer and impedance changes across the defibrillation electrodes. This technology can also provide real-time audiovisual feedback so that the rescuer is prompted to perform according to guideline specifications. Use of such feedback increases the likelihood of performing CPR in accordance with guidelines during training and simulation. Participants: There were 1586 participants: 771 treated without feedback and 815 with feedback.Design: CPR feedback was provided through proprietary Q-CPR software operating in the Philips MRx monitor-defibrillator. The feedback feature of the defibrillator includes audible voice prompts and visual messages on the monitor screen that are triggered when measured chest compressions or ventilation deviate from guidelines or are interrupted.The study was conducted in 21 emergency medical service (EMS) agencies at three ROC regions in the U.S. and Canada. Randomized treatment clusters, which ranged from individual emergency medical vehicles to groups of emergency agencies, were assigned to feedback-on or feedback-off treatments. Each cluster remained in its assigned mode for two to seven months, after which it switched to the opposite treatment arm. At the end of those two treatment periods, each cluster was again randomly assigned to feedback-on or feedback-off. This cycle continued for the duration of the study. Each cluster switched treatment arms at least once, and up to four times, during the study. Conclusions: Real-time visual and audible feedback during CPR altered performance to more closely conform with CPR guidelines. Clusters assigned to feedback were associated with increased proportion of time in which chest compressions were provided, increased compression depth, and decreased proportion of compressions with incomplete release. However, frequency of prehospital return of spontaneous circulation did not differ according to feedback status, nor did the presence of a pulse at hospital arrival, survival to discharge, or awake at hospital discharge (Hostler, et al., 2011, PMID: 21296838).

  Study phs003818

• Knoll et al Identification of drug candidates targeting monocyte reprogramming in people living with HIV

  Introduction People living with HIV (PLHIV) are characterized by functional reprogramming of innate immune cells even after long-term antiretroviral therapy (ART). In order to assess technical feasibility of omics technologies for application to larger cohorts, we compared multiple omics layers. Methods Bulk and single-cell transcriptomics, flow cytometry, proteomics, chromatin landscape analysis by ATAC-seq as well as ex vivo drug stimulation was performed in a small number of blood samples derived from PLHIV and healthy controls from the 200-HIV cohort study. Results Single-cell RNA-seq analysis revealed that most immune cells in peripheral blood of PLHIV are altered in their transcriptomes and that a specific functional monocyte state previously described in acute HIV infection is still existing in PLHIV while other monocyte cell states are only occurring acute infection. Moreover, a reverse transcriptome approach on a rather small number of PLHIV was sufficient to identify drug candidates for reversing the transcriptional phenotype of monocytes in PLHIV. Discussion These scientific findings and technological advancements for clinical application of single-cell transcriptomics form the basis for the larger 2000-HIV multicenter cohort study on PLHIV, for which a combination of bulk and single-cell transcriptomics will be included as the leading technology to determine disease endotypes in PLHIV and to predict disease trajectories and outcomes.

  Study EGAS00001007460