Oropharyngeal Microbiome Profiled at Admission is Predictive of the Need for Respiratory Support Among COVID-19 Patients [preprint]

The clinical course of infection due to respiratory viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), the causative agent of Coronavirus Disease 2019 (COVID-19) is thought to be influenced by the community of organisms that colonizes the upper respiratory tract, the oropharyngeal microbiome. In this study, we examined the oropharyngeal microbiome of suspected COVID-19 patients presenting to the Emergency Department and an inpatient COVID-19 unit with symptoms of acute COVID-19. Of 115 enrolled patients, 74 were confirmed COVID-19+ and 50 had symptom duration of 14 days or less; 38 acute COVID-19+ patients (76%) went on to require respiratory support. Although no microbiome features were found to be significantly different between COVID-19+ and COVID-19-patients, when we conducted random forest classification modeling (RFC) to predict the need of respiratory support for the COVID-19+ patients our analysis identified a subset of organisms and metabolic pathways whose relative abundance, when combined with clinical factors (such as age and Body Mass Index), was highly predictive of the need for respiratory support (F1 score 0.857). Microbiome Multivariable Association with Linear Models (MaAsLin2) analysis was then applied to the features identified as predicative of the need for respiratory support by the RFC. This analysis revealed reduced abundance of Prevotella salivae and metabolic pathways associated with lipopolysaccharide and mycolic acid biosynthesis to be the strongest predictors of patients requiring respiratory support. These findings suggest that composition of the oropharyngeal microbiome in COVID-19 may play a role in determining who will suffer from severe disease manifestations. Importance: The microbial community that colonizes the upper airway, the oropharyngeal microbiome, has the potential to affect how patients respond to respiratory viruses such as SARS-CoV2, the causative agent of COVID-19. In this study, we investigated the oropharyngeal microbiome of COVID-19 patients using high throughput DNA sequencing performed on oral swabs. We combined patient characteristics available at intake such as medical comorbidities and age, with measured abundance of bacterial species and metabolic pathways and then trained a machine learning model to determine what features are predicative of patients needing respiratory support in the form of supplemental oxygen or mechanical ventilation. We found that decreased abundance of some bacterial species and increased abundance of pathways associated bacterial products biosynthesis was highly predictive of needing respiratory support. This suggests that the oropharyngeal microbiome affects disease course in COVID-19 and could be targeted for diagnostic purposes to determine who may need oxygen, or therapeutic purposes such as probiotics to prevent severe COVID-19 disease manifestations

Genetic Studies of a Cluster of Acute Lymphoblastic Leukemia Cases in Churchill County, Nevada

OBJECTIVE: In a study to identify exposures associated with 15 cases of childhood leukemia, we found levels of tungsten, arsenic, and dichlorodiphenyldichloroethylene in participants to be higher than mean values reported in the National Report on Human Exposure to Environmental Chemicals. Because case and comparison families had similar levels of these contaminants, we conducted genetic studies to identify gene polymorphisms that might have made case children more susceptible than comparison children to effects of the exposures. DESIGN: We compared case with comparison children to determine whether differences existed in the frequency of polymorphic genes, including genes that code for enzymes in the folate and purine pathways. We also included discovery of polymorphic forms of genes that code for enzymes that are inhibited by tungsten: xanthine dehydrogenase, sulfite oxidase (SUOX gene), and aldehyde oxidase. PARTICIPANTS: Eleven case children were age- and sex-matched with 42 community comparison children for genetic analyses. Twenty parents of case children also contributed to the analyses. RESULTS: One bilalleleic gene locus in SUOX was significantly associated with either case or comparison status, depending on which alleles the child carried (without adjusting for multiple comparisons). CONCLUSIONS: Although genetic studies did not provide evidence that a common agent or genetic susceptibility factor caused the leukemias, the association between a SUOX gene locus and disease status in the presence of high tungsten and arsenic levels warrants further investigation. RELEVANCE: Although analyses of community clusters of cancer have rarely identified causes, these findings have generated hypotheses to be tested in subsequent studies

From Macro to Micro: Social Determinants of COVID-19 & Nasopharyngeal Features Associated with Disease Progression - A Study of COVID-19 in Worcester, Massachusetts

BACKGROUND The health and wellness of every individual is determined by many aspects, including their genetics, environment, behaviors (both the individual and those around them), medical care, microbiome, and social factors affecting their life. In order to fully assess and fix and global health issue such as the COVID-19 Pandemic, analysis into each of these aspects is necessary. The root of every outbreak lies in one of these issues, and while fixing one may stop the spread of disease, it will never truly eradicate it. METHODOLOGY In a correlative, qualitative analysis, we obtained data on COVID-19 density in Worcester, Massachusetts from the city’s Department of Public Health. We overlayed the map associated with this data with heat maps on social factors in Worcester. These social factors included different metrics for areas like housing, nutrition, income, crime, transportation, and education. We analyzed these maps based on color and opacity to determine where social factors affecting health fell in relation to COVID-19 density; we also analyzed the numbers associated with the colors/opacities to show quantitatively how areas with a high prevalence of particular social factors vs. low matched up with COVID-19 density. Following this, a correlative machine-learning algorithm was developed to understand how members of the microbiome correlate to respiratory distress following recovery from COVID-19. Patients with COVID-19 or those exhibiting symptoms had a nasopharyngeal swab ordered upon admission to the UMass Memorial Hospital Emergency Department. Following this, patients were prompted by research staff to enroll in the study. To map the microbiota of each participant, whole DNA/RNA extraction was carried out, followed by Illumina sequencing. Illumina reads generated were to build a model for determining differences in microbial abundance as a predictor of respiratory support. The model was used to generate median importance values for a series of clinical factors, and microbial features found in the patients. To discern how specific microbes predicted the need for respiratory support or not, the model was also used to measure differences in abundancy levels of each microbe. RESULTS Analysis of the social determinants of health related to COVID-19 prevalence in Worcester revealed that all metrics were at least somewhat correlated. The best correlation existed between metrics like population density, income, and education. Slightly less significant, and likely less correlated were nutrition, and crime. Following this, data from the first model revealed that differences in microbial species’ abundances may act as better health predictors than age, BMI, and CCI when assessing if a patient will need respiratory support or not following COVID-19 recovery. Data from the second model revealed that abundances of microbes was highest in those patients who did not end up needing respiratory support DISCUSSION Since many of the social determinants are correlated with COVID-19 density, we have determined that further analyses into each factor is necessary to identify causal factors. Additionally, this evidence provides reason for the Worcester Department of Public Health to pursue campaigns that are geared towards preventing infections and assessing issues surrounding poverty, education, nutrition, and other social factors troubling particular populations in Worcester. In addition to this, data from the microbiology models shows us that many different microbes may actually exhibit protective attributes in the nasopharynx; the microbes in those patients who had high abundancies and no respiratory distress may interact with the immune system or fill in niches that would otherwise be filled with opportunistic pathogens. Similar to the former half of the project, more analyses must be performed to make better sense of the data

The Future of Montenegro: Proceedings of an Expert Meeting, 26 February 2001. CEPS Paperback. June 2001.

The conference on the future of Montenegro held in CEPS on 26 February, attracted considerable interest from the media and from the policy-making community. At the time, the official position of the EU and US was that Montenegro should not contribute further to what they saw as a ten-year long process of Balkan disintegration. A number of the contributors to this conference agreed. Many Montenegrins, represented in substance here by President Djukanoviæ, Foreign Minister Branko Lukovac and Mijat Šukoviæ, put forward a serious case for Montenegrin independence

Cataloguing Resources for Poverty Reduction in Armenia

Our team researched multidimensional poverty and poverty reduction methods in Armenia. We collaborated with World Vision Armenia and developed a website that hosts a solutions library, printable resources for poverty prevention, and information on the purpose & distribution of the Poverty Stoplight survey. Our solutions library addresses the high priority needs of Armenians based on the Armenian Poverty Stoplight survey and is accessible to both NGOs and individuals who want to help break the cycle of poverty

Inexact Newton Methods And The Method Of Lines For Solving Richards' Equation In Two Space Dimensions

Richards' equation (RE) is often used to model flow in unsaturated porous media. This model captures physical effects, such as sharp fronts in fluid pressures and saturations, which are present in more complex models of multiphase flow. The numerical solution of RE is difficult not only because of these physical effects but also because of the mathematical problems that arise in dealing with the nonlinearities. The method of lines has been shown to be very effective for solving RE in one space dimension. When solving RE in two space dimensions, the nonlinear equations that must be solved in an implicit time-stepping approach usually become impractical to solve using a direct solver (e.g., LU decomposition). In this work, we show how Newton-iterative methods can be applied in this context; these methods use iterative linear solvers, such as the Krylov methods GMRES and Bi-CGSTAB. We present a theorem on the convergence of inexact Newton methods, and based on this theorem, an adaptive ..

CKAP4/p63 is a Receptor for the Frizzled-8 Protein-Related Antiproliferative Factor from Interstitial Cystitis Patients

Antiproliferative factor (APF) is a low molecular weight sialoglycopeptide that is secreted by bladder cells from interstitial cystitis patients and is a potent inhibitor of both normal bladder epithelial and bladder carcinoma cell proliferation. We hypothesized that APF may produce its antiproliferative effects by binding to a transmembrane receptor. This study demonstrates that cytoskeleton-associated protein 4/p63 (CKAP4/p63), a type II transmembrane receptor, binds with high affinity to APF. The antiproliferative activity of APF is effectively inhibited by preincubation with anti-CKAP4/p63-specific antibodies, as well as by short interfering RNA knockdown of CKAP4/p63. Immunofluorescent confocal microscopy showed co-localization of anti-CKAP4/p63 and rhodamine-labeled synthetic APF binding in both cell membrane and perinuclear areas. APF also inhibits the proliferation of HeLa cervical carcinoma cells that are known to express CKAP4/p63. These data indicate that CKAP4/p63 is an important epithelial cell receptor for APF