8 research outputs found

    A Disease-Associated MicroRNA Cluster Links Inflammatory Pathways and an Altered Composition of Leukocyte Subsets to Noninfectious Uveitis

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    PURPOSE. The cause of noninfectious uveitis (NIU) is poorly understood but is considered to be mediated by a complex interplay between genetic, environmental, and-relatively unexplored-epigenetic factors. MicroRNAs (miRNAs) are noncoding small RNAs that are important epigenetic regulators implicated in pathologic signaling. Therefore, we mapped the circulating miRNA-ome of NIU patients and studied miRNA perturbations within the broader context of the immune system.METHODS. We designed a strategy to robustly identify changes in the miRNA profiles of two independent cohorts totaling 54 untreated patients with active and eye-restricted disease and 26 age-matched controls. High-resolution miRNA-ome data were obtained by TaqMan OpenArray technology and subsequent RT-qPCR. Flow cytometry data, and proteomic data spanning the cellular immune system, were used to map the uveitis-miRNA signature to changes in the composition of specific leukocyte subsets in blood.RESULTS. Using stringent selection criteria, we identified and independently validated an miRNA cluster that is associated with NIU. Pathway enrichment analysis for genes targeted by this cluster revealed significant enrichment for the PI3K/Akt, MAPK, FOXO, and VEGF signaling pathways, and photoreceptor development. In addition, unsupervised multidomain analyses linked the presence of the uveitis-associated miRNA cluster to a different composition of leukocyte subsets, more specifically, CD16(+)CD11c(+)HLA-DR- cells.CONCLUSIONS. Together, this study identified a unique miRNA cluster associated with NIU that was related to changes in leukocyte subsets demonstrating systemic changes in epigenetic regulation underlying NIU

    Ex vivo expansion of Primate CD34+ Cells isolated from Bone Marrow and Human Bone Marrow Mononuclear Cells using a Novel Scaffold

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    Bone marrow derived CD34+ cells have been in clinical application in patients with haematological malignancies. One of the major problems with this treatment is the non-availability of matched donors or the necessity of multiple transfusions depending upon the pathology. Recently evidences have been accumulating to prove the safety and efficacy of autologous CD34+ cells in diseases such as myocardial dysfunction, peripheral vascular diseases and neurological certain conditions. However there are only a few reports in the literature on ex vivo expansion of the bone marrow derived CD34+ cells. We have in two different studies proven that isolated CD34+ cells from baboon bone marrow and non-isolated BMMNCs from human bone marrow could be expanded with increase in percentage of CD34+ cells using a novel scaffold

    Impact of COVID-19 on non-COVID intensive care unit service utilization, case mix and outcomes: A registry-based analysis from India

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    Background: Coronavirus disease 2019 (COVID-19) has been responsible for over 3.4 million deaths globally and over 25 million cases in India. As part of the response, India imposed a nation-wide lockdown and prioritized COVID-19 care in hospitals and intensive care units (ICUs). Leveraging data from the Indian Registry of IntenSive care, we sought to understand the impact of the COVID-19 pandemic on critical care service utilization, case-mix, and clinical outcomes in non-COVID ICUs. Methods: We included all consecutive patients admitted between 1st October 2019 and 27th September 2020. Data were extracted from the registry database and included patients admitted to the non-COVID or general ICUs at each of the sites. Outcomes included measures of resource-availability, utilisation, case-mix, acuity, and demand for ICU beds. We used a Mann-Whitney test to compare the pre-pandemic period (October 2019 - February 2020) to the pandemic period (March-September 2020). In addition, we also compared the period of intense lockdown (March-May 31st 2020) with the pre-pandemic period. Results: There were 3424 patient encounters in the pre-pandemic period and 3524 encounters in the pandemic period. Comparing these periods, weekly admissions declined (median [Q1 Q3] 160 [145,168] to 113 [98.5,134]; p<0.001); unit turnover declined (median [Q1 Q3] 12.1 [11.32,13] to 8.58 [7.24,10], p<0.001), and APACHE II score increased (median [Q1 Q3] 19 [19,20] to 21 [20,22] ; p<0.001). Unadjusted ICU mortality increased (9.3% to 11.7%, p=0.015) and the length of ICU stay was similar (median [Q1 Q3] 2.11 [2, 2] vs. 2.24 [2, 3] days; p=0.151). Conclusion: Our registry-based analysis of the impact of COVID-19 on non-COVID critical care demonstrates significant disruptions to healthcare utilization during the pandemic and an increase in the severity of illness

    Implementing an intensive care registry in India: preliminary results of the case-mix program and an opportunity for quality improvement and research

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    Background: The epidemiology of critical illness in India is distinct from high-income countries. However, limited data exist on resource availability, staffing patterns, case-mix and outcomes from critical illness. Critical care registries, by enabling a continual evaluation of service provision, epidemiology, resource availability and quality, can bridge these gaps in information. In January 2019, we established the Indian Registry of IntenSive care to map capacity and describe case-mix and outcomes. In this report, we describe the implementation process, preliminary results, opportunities for improvement, challenges and future directions. Methods: All adult and paediatric ICUs in India were eligible to join if they committed to entering data for ICU admissions. Data are collected by a designated representative through the electronic data collection platform of the registry. IRIS hosts data on a secure cloud-based server and access to the data is restricted to designated personnel and is protected with standard firewall and a valid secure socket layer (SSL) certificate. Each participating ICU owns and has access to its own data. All participating units have access to de-identified network-wide aggregate data which enables benchmarking and comparison. Results: The registry currently includes 14 adult and 1 paediatric ICU in the network (232 adult ICU beds and 9 paediatric ICU beds). There have been 8721 patient encounters with a mean age of 56.9 (SD 18.9); 61.4% of patients were male and admissions to participating ICUs were predominantly unplanned (87.5%). At admission, most patients (61.5%) received antibiotics, 17.3% needed vasopressors, and 23.7% were mechanically ventilated. Mortality for the entire cohort was 9%. Data availability for demographics, clinical parameters, and indicators of admission severity was greater than 95%. Conclusions: IRIS represents a successful model for the continual evaluation of critical illness epidemiology in India and provides a framework for the deployment of multi-centre quality improvement and context-relevant clinical research

    Cytometry by time of flight identifies distinct signatures in patients with systemic sclerosis, systemic lupus erythematosus and Sjögrens syndrome

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    Systemic sclerosis (SSc), systemic lupus erythematosus (SLE) and primary Sjogrens syndrome (pSS) are clinically distinct systemic autoimmune diseases (SADs) that share molecular pathways. We quantified the frequency of circulating immune-cells in 169 patients with these SADs and 44 healty controls (HC) using mass-cytometry and assessed the diagnostic value of these results. Alterations in the frequency of immune-cell subsets were present in all SADs compared to HC. Most alterations, including a decrease of CD56(hi) NK-cells in SSc and IgM(+) Bcells in pSS, were disease specific; only a reduced frequency of plasmacytoid dendritic cells was common between all SADs Strikingly, hierarchical clustering of SSc patients identified 4 clusters associated with different clinical phenotypes, and 9 of the 12 cell subset-alterations in SSc were also present during the preclinical-phase of the disease. Additionally, we found a strong association between the use of prednisone and alterations in B-cell subsets. Although differences in immune-cell frequencies between these SADs are apparent, the discriminative value thereof is too low for diagnostic purposes. Within each disease, mass cytometry analyses revealed distinct patterns between endophenotypes. Given the lack of tools enabling early diagnosis of SSc, our results justify further research into the value of cellular phenotyping as a diagnostic aid

    Cytometry by time of flight identifies distinct signatures in patients with systemic sclerosis, systemic lupus erythematosus and Sjögrens syndrome

    No full text
    Systemic sclerosis (SSc), systemic lupus erythematosus (SLE) and primary Sjogrens syndrome (pSS) are clinically distinct systemic autoimmune diseases (SADs) that share molecular pathways. We quantified the frequency of circulating immune-cells in 169 patients with these SADs and 44 healty controls (HC) using mass-cytometry and assessed the diagnostic value of these results. Alterations in the frequency of immune-cell subsets were present in all SADs compared to HC. Most alterations, including a decrease of CD56(hi) NK-cells in SSc and IgM(+) Bcells in pSS, were disease specific; only a reduced frequency of plasmacytoid dendritic cells was common between all SADs Strikingly, hierarchical clustering of SSc patients identified 4 clusters associated with different clinical phenotypes, and 9 of the 12 cell subset-alterations in SSc were also present during the preclinical-phase of the disease. Additionally, we found a strong association between the use of prednisone and alterations in B-cell subsets. Although differences in immune-cell frequencies between these SADs are apparent, the discriminative value thereof is too low for diagnostic purposes. Within each disease, mass cytometry analyses revealed distinct patterns between endophenotypes. Given the lack of tools enabling early diagnosis of SSc, our results justify further research into the value of cellular phenotyping as a diagnostic aid

    International Nosocomial Infection Control Consortium report, data summary of 50 countries for 2010-2015: Device-associated module

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    •We report INICC device-associated module data of 50 countries from 2010-2015.•We collected prospective data from 861,284 patients in 703 ICUs for 3,506,562 days.•DA-HAI rates and bacterial resistance were higher in the INICC ICUs than in CDC-NHSN's.•Device utilization ratio in the INICC ICUs was similar to CDC-NHSN's. Background: We report the results of International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2010-December 2015 in 703 intensive care units (ICUs) in Latin America, Europe, Eastern Mediterranean, Southeast Asia, and Western Pacific. Methods: During the 6-year study period, using Centers for Disease Control and Prevention National Healthcare Safety Network (CDC-NHSN) definitions for device-associated health care-associated infection (DA-HAI), we collected prospective data from 861,284 patients hospitalized in INICC hospital ICUs for an aggregate of 3,506,562 days. Results: Although device use in INICC ICUs was similar to that reported from CDC-NHSN ICUs, DA-HAI rates were higher in the INICC ICUs: in the INICC medical-surgical ICUs, the pooled rate of central line-associated bloodstream infection, 4.1 per 1,000 central line-days, was nearly 5-fold higher than the 0.8 per 1,000 central line-days reported from comparable US ICUs, the overall rate of ventilator-associated pneumonia was also higher, 13.1 versus 0.9 per 1,000 ventilator-days, as was the rate of catheter-associated urinary tract infection, 5.07 versus 1.7 per 1,000 catheter-days. From blood cultures samples, frequencies of resistance of Pseudomonas isolates to amikacin (29.87% vs 10%) and to imipenem (44.3% vs 26.1%), and of Klebsiella pneumoniae isolates to ceftazidime (73.2% vs 28.8%) and to imipenem (43.27% vs 12.8%) were also higher in the INICC ICUs compared with CDC-NHSN ICUs. Conclusions: Although DA-HAIs in INICC ICU patients continue to be higher than the rates reported in CDC-NSHN ICUs representing the developed world, we have observed a significant trend toward the reduction of DA-HAI rates in INICC ICUs as shown in each international report. It is INICC's main goal to continue facilitating education, training, and basic and cost-effective tools and resources, such as standardized forms and an online platform, to tackle this problem effectively and systematically

    International Nosocomial Infection Control Consortiu (INICC) report, data summary of 43 countries for 2007-2012. Device-associated module

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    We report the results of an International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2007-December 2012 in 503 intensive care units (ICUs) in Latin America, Asia, Africa, and Europe. During the 6-year study using the Centers for Disease Control and Prevention's (CDC) U.S. National Healthcare Safety Network (NHSN) definitions for device-associated health care–associated infection (DA-HAI), we collected prospective data from 605,310 patients hospitalized in the INICC's ICUs for an aggregate of 3,338,396 days. Although device utilization in the INICC's ICUs was similar to that reported from ICUs in the U.S. in the CDC's NHSN, rates of device-associated nosocomial infection were higher in the ICUs of the INICC hospitals: the pooled rate of central line–associated bloodstream infection in the INICC's ICUs, 4.9 per 1,000 central line days, is nearly 5-fold higher than the 0.9 per 1,000 central line days reported from comparable U.S. ICUs. The overall rate of ventilator-associated pneumonia was also higher (16.8 vs 1.1 per 1,000 ventilator days) as was the rate of catheter-associated urinary tract infection (5.5 vs 1.3 per 1,000 catheter days). Frequencies of resistance of Pseudomonas isolates to amikacin (42.8% vs 10%) and imipenem (42.4% vs 26.1%) and Klebsiella pneumoniae isolates to ceftazidime (71.2% vs 28.8%) and imipenem (19.6% vs 12.8%) were also higher in the INICC's ICUs compared with the ICUs of the CDC's NHSN
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