Biology subjects

Osorio, J.

Publications and source records attributed to Osorio, J..

6 recordsLinked to original sources

bioRxiv2024

Benchmarking open access publication rates for the pharmaceutical industry and research-intensive academic institutions

BackgroundIn biomedical and health sciences, many articles are published open access (OA). OA publication rates continue to grow, especially for pharmaceutical research. Previous analyses of pharmaceutical OA publication rates were labor-intensive and not easily automated. We aimed to create a free, live, online dashboard comparing OA publication rates between pharmaceutical companies and academic institutions. MethodsUsing the Lens - an online platform aggregating full-text content and metadata for over 280 million scholarly works - we built a dashboard showing OA publication rates for medical research articles by authors from the top 40 pharmaceutical companies (pharma) and 40 research-intensive academic institutions (academia). The dashboard details OA rates by model, license and therapy area across three time frames: 12-24 months; 0-12 months; 0-10 years. We downloaded data from the dashboard between 24 July and 4 August 2023 and performed further analysis. ResultsOf the articles published 12-24 months before data extraction, 76.6% by pharma and 69.5% by academia were OA. The most common OA models were gold (pharma, 37%; academia, 41%) and hybrid (pharma, 22%; academia, 11%). Oncology had lower rates of OA articles than other therapy areas. In the 10 years before data extraction, growth in the OA publication rate was generally more rapid for pharmaceutical companies than for academic institutions, regardless of field (change in overall % OA 2013-2023: pharma, 3.1; academia, 1.6). ConclusionsThis dashboard provides novel and regularly updated evidence on the comparative OA publication practices of pharmaceutical companies and academic institutions. In our snapshot analysis, the OA publication rate was higher for pharmaceutical companies than for academic institutions and continues to increase. Notable differences were observed in approaches, in terms of licenses and OA models, which may reflect different institutional practices and circumstances. We encourage others to use this open resource for new research and to report their results.

scientific communication and education↗

bioRxiv2019

Primary infection with dengue or Zika virus does not affect the severity of heterologous secondary infection in macaques.

Zika virus (ZIKV) and dengue virus (DENV) are genetically and antigenically related flaviviruses that now co-circulate in much of the tropical and subtropical world. The rapid emergence of ZIKV in the Americas in 2015 and 2016, and its recent associations with Guillain-Barre syndrome, birth defects, and fetal loss have led to the hypothesis that DENV infection induces cross-reactive antibodies that influence the severity of secondary ZIKV infections. It has also been proposed that pre-existing ZIKV immunity could affect DENV pathogenesis. We examined outcomes of secondary ZIKV infections in three rhesus and fifteen cynomolgus macaques, as well as secondary DENV-2 infections in three additional rhesus macaques up to a year post-primary ZIKV infection. Although cross-binding antibodies were detected prior to secondary infection for all animals and cross-neutralizing antibodies were detected for some animals, previous DENV or ZIKV infection had no apparent effect on the clinical course of heterotypic secondary infections in these animals. All animals had asymptomatic infections and, when compared to controls, did not have significantly perturbed hematological parameters. Rhesus macaques infected with DENV-2 approximately one year after primary ZIKV infection had higher vRNA loads in plasma when compared with serum vRNA loads from ZIKV-naive animals infected with DENV-2, but a differential effect of sample type could not be ruled out. In cynomolgus macaques, the serotype of primary DENV infection did not affect the outcome of secondary ZIKV infection.\n\nAuthor summaryPre-existing immunity to one of the four DENV serotypes is known to increase the risk of severe disease upon secondary infection with a different serotype. Due to the antigenic similarities between ZIKV and DENV, it has been proposed that these viruses could interact in a similar fashion. Data from in vitro experiments and murine models suggests that pre-existing immunity to one virus could either enhance or protect against infection with the other. These somewhat contradictory findings highlight the need for immune competent animal models for understanding the role of cross-reactive antibodies in flavivirus pathogenesis. We examined secondary ZIKV or DENV infections in rhesus and cynomolgus macaques that had previously been infected with the other virus. We assessed the outcomes of secondary ZIKV or DENV infections by quantifying vRNA loads, clinical and laboratory parameters, body temperature, and weight for each cohort of animals and compared them with control animals. These comparisons demonstrated that within a year of primary infection, secondary infections with either ZIKV or DENV were similar to primary infections and were not associated with enhancement or reduction in severity of disease based on the outcomes that we assessed.

pathology↗

bioRxiv2018

Seasonal patterns of dengue fever in rural Ecuador: 2009-2016

Season is a major determinant of infectious disease rates, including arboviruses spread by mosquitoes, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climatic or environmental factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of dengue fever has been studied in the context of climatic factors, but short-and long-term time trends are less well-understood. With 2009-- 2016 medical record data from patients diagnosed with dengue fever at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short-and long-term seasonal patterns of dengue fever, as well as the effect of day of the week and public holidays. In a subset analysis, we determined the impact of school schedules on school-aged children. With a separate model, we examined the effect of climate on diagnosis patterns. In the first model, the most important predictors of dengue fever were annual sinusoidal fluctuations in disease, long-term trends, day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during April. Compared to an average day, cases were more likely to be diagnosed on Tuesdays (risk ratio (RR): 1.26, 95% confidence interval (CI) 1.05--1.51) and Thursdays (RR: 1.25, 95% CI 1.02--1.53), and less likely to be diagnosed on Saturdays (RR: 0.81, 95% CI 0.65--1.01) and Sundays (RR: 0.74, 95% CI 0.58--0.95). Public holidays were not significant predictors of dengue fever diagnoses, except for an increase in diagnoses on the day after Christmas (RR: 2.77, 95% CI 1.46--5.24). School schedules did not impact dengue diagnoses in school-aged children. In the climate model, important climate variables included the monthly total precipitation (RR: 2.14, 95% CI 1.26--3.64), an interaction between total precipitation and monthly absolute minimum temperature (RR: 0.93, 95% CI 0.88--0.98), an interaction between total precipitation and monthly precipitation days (RR: 0.90, 95% CI 0.82--0.99), and a three-way interaction between minimum temperature, total precipitation, and precipitation days (RR: 1.01, 95% CI 1.00--1.02). This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, as well as global and regional models of dengue fever trends.\n\nAuthor summaryDengue fever exhibits a seasonal pattern in many parts of the world, much of which has been attributed to climate and weather. However, additional factors may contribute to dengue seasonality. With 2009-- 2016 medical record data from rural Ecuador, we studied the short-and long-term seasonal patterns of dengue fever, as well as the effect of school schedules and public holidays. We also examined the effect of climate on dengue. We found that dengue diagnoses peak once per year during April, but that diagnoses are also affected by day of the week. Dengue was also impacted by regional climate and complex interactions between local weather variables. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. This is the first report on the impacts of school schedules, holidays, and weekday-weekend patterns on dengue diagnoses. These results suggest a potential impact of human behaviors on dengue exposure risk. More broadly, these results can inform local disease prevention efforts and public health planning, as well as global and regional models of dengue fever trends.

epidemiology↗

bioRxiv2018

Zika viruses of both African and Asian lineages cause fetal harm in a vertical transmission model

Congenital Zika virus (ZIKV) infection was first linked to birth defects during the American outbreak 1-3. It has been proposed that mutations unique to the Asian/American-genotype explain, at least in part, the ability of Asian/American ZIKV to cause congenital Zika syndrome (CZS) 4,5. Recent studies identified mutations in ZIKV infecting humans that arose coincident with the outbreak in French Polynesia and were stably maintained during subsequent spread to the Americas 5. Here we show that African ZIKV can infect and harm fetuses and that the S139N mutation that has been associated with the American outbreak is not essential for fetal harm. Our findings, in a vertical transmission mouse model, suggest that ZIKV will remain a threat to pregnant women for the foreseeable future, including in Africa, southeast Asia, and the Americas. Additional research is needed to better understand the risks associated with ZIKV infection during pregnancy, both in areas where the virus is newly endemic and where it has been circulating for decades.

microbiology↗

bioRxiv2017

Infection via mosquito bite alters Zika virus replication kinetics in rhesus macaques

For more than three decades it has been recognized that small amounts of vector saliva can significantly alter the infectivity of vector-borne pathogens and subsequent in vivo dynamics. Mouse and nonhuman primate models now serve as useful platforms to study Zika virus (ZIKV) pathogenesis, candidate therapies, and vaccines, but they rely on needle inoculation of virus: the effects of mosquito-borne infection on disease outcome have not been explored in these models. To model vector-borne transmission of ZIKV in nonhuman primates, we infected Aedes aegypti mosquitoes with ZIKV and allowed them to feed on four ZIKV-naive rhesus macaques. We compared ZIKV replication kinetics and tissue distribution between animals that were subcutaneously inoculated with 104 plaque-forming units of ZIKV and those that were exposed via mosquito bite. Here, we show that infection via mosquito bite delays ZIKV replication to peak viral loads in rhesus macaques. Importantly, in mosquito-infected animals ZIKV tissue distribution was limited to hemolymphatic tissues, female reproductive tract tissues, kidney, and liver, potentially emulating key features of human ZIKV infections, most of which are characterized by mild or asymptomatic disease. This newly developed system will be valuable for studying ZIKV disease because it more closely mimics human infection by mosquito bite than needle-based inoculations.

microbiology↗

bioRxiv2017

Investigating The Functional Consequence Of White Matter Damage: An Automatic Pipeline To Create Longitudinal Disconnection Tractograms

Neurosurgical resection is one of the few opportunities researchers have to image the human brain both prior to and following focal damage. One of the challenges associated with studying brains undergoing surgical resection is that they often do not fit the brain templates most image-processing methodologies are based on, so manual intervention is required to reconcile the pathology and the most extreme cases must be excluded. Manual intervention requires significant time investment and introduces reproducibility concerns. We propose an automatic longitudinal pipeline based on High Angular Resolution Diffusion Imaging acquisitions to facilitate a Pathway Lesion Symptom Mapping analysis relating focal white matter injury to functional deficits. This two-part approach includes (i) automatic segmentation of focal white matter injury from anisotropic power differences, and (ii) modeling disconnection using tractography on the single-subject level, which specifically identifies the disconnections associated with focal white matter damage. The advantages of this approach stem from (1) objective and automatic lesion segmentation and tractogram generation, (2) objective and precise segmentation of affected tissue likely to be associated with damage to long-range white matter pathways (defined by anisotropic power), (3) good performance even in the cases of anatomical distortions by use of nonlinear tensor-based registration in the patient space, which aligns images using white matter contrast. Mapping a system as variable and complex as the human brain requires sample sizes much larger than the current technology can support. This pipeline can be used to execute large-scale, sufficiently powered analyses by meeting the need for an automatic approach to objectively quantify white matter disconnection.\n\nAbbreviations\n\nFundingThis work was supported by the National Institutes of Health [5R01NS066654-05]; KJ was supported by the Department of Defense (DoD) [National Defense Science & Engineering Graduate Fellowship (NDSEG) Program].

bioengineering↗