Using Mathematical Models In A Unified Approach To Predicting The Next Emerging Infectious Disease

Emerging infectious diseases (EIDs) pose a significant threat to human health, global economies, and conservation (Smolinski et al. 2003). They are defined as diseases that have recently increased in incidence (rate of the development of new cases during a given time period), are caused by pathogens that recently moved from one host population to another, have recently evolved, or have recently exhibited a change in pathogenesis (Morse 1993; Krause 1994). Some EIDs threaten global public health through pandemics with large-scale mortality (e.g., HN/AIDS). Others cause smaller outbreaks but have high case fatality ratios or lack effective therapies or vaccines (e.g. Ebola virus or methicillin-resistant Staphylococcus aureus). As a group, EIDs cause hundreds of thousands of deaths each year, and some outbreaks (e.g., SARS, H5N1) have cost the global economy tens of billions of dollars. Emerging diseases also affect plants, livestock, and wildlife and are recognized as a Significant threat to the conservation of biodiversity (Daszak et al. 2000). Approximately 60% of emerging human disease events are zoonotic, and over 75% of these diseases originate in wildlife (Jones et al. 2008). The global response to such epidemics is frequently reactive, and the effectiveness of conventional disease control operations is often too little, too late\u27: With rising globalization, the ease with which diseases spread globally has increased dramatically in recent times. Also, interactions between humans and wildlife have intensified through trade markets, agricultural intensification, logging and mining, and other forms of development that encroach into wild areas. Rapid human population growth, land use change, and change in global trade and travel require a shift toward a proactive, predictive, and preventive approaches for the next zoonotic pandemic

ATM Deficiency Confers Specific Therapeutic Vulnerabilities in Bladder Cancer

Ataxia-telangiectasia mutated (ATM) plays a central role in the cellular response to DNA damage and ATM alterations are common in several tumor types including bladder cancer. However, the specific impact of ATM alterations on therapy response in bladder cancer is uncertain. Here, we combine preclinical modeling and clinical analyses to comprehensively define the impact of ATM alterations on bladder cancer. We show that ATM loss is sufficient to increase sensitivity to DNA-damaging agents including cisplatin and radiation. Furthermore, ATM loss drives sensitivity to DNA repair-targeted agents including poly(ADP-ribose) polymerase (PARP) and Ataxia telangiectasia and Rad3 related (ATR) inhibitors. ATM loss alters the immune microenvironment and improves anti-PD1 response in preclinical bladder models but is not associated with improved anti-PD1/PD-L1 response in clinical cohorts. Last, we show that ATM expression by immunohistochemistry is strongly correlated with response to chemoradiotherapy. Together, these data define a potential role for ATM as a predictive biomarker in bladder cancer

Toxin-Based Therapeutic Approaches

Protein toxins confer a defense against predation/grazing or a superior pathogenic competence upon the producing organism. Such toxins have been perfected through evolution in poisonous animals/plants and pathogenic bacteria. Over the past five decades, a lot of effort has been invested in studying their mechanism of action, the way they contribute to pathogenicity and in the development of antidotes that neutralize their action. In parallel, many research groups turned to explore the pharmaceutical potential of such toxins when they are used to efficiently impair essential cellular processes and/or damage the integrity of their target cells. The following review summarizes major advances in the field of toxin based therapeutics and offers a comprehensive description of the mode of action of each applied toxin

Technology Diffusion of Anesthesia Information Management Systems into Academic Anesthesia Departments in the United States

BACKGROUND: Anesthesia information management systems (AIMS) are electronic health records that automatically import vital signs from patient monitors and allow for computer-assisted creation of the anesthesia record. When most recently surveyed in 2007, it was estimated that at least 16% of U.S. academic hospitals (i.e., with an anesthesia residency program) had installed an AIMS. At least an additional 28% reported that they were in the process of implementing, or searching for an AIMS. In this study, we updated the adoption figures as of May 2013 and examined the historical trend of AIMS deployment in U.S. anesthesia residency programs from the perspective of the theory of diffusion of technologic innovations. METHODS: Questionnaires were sent by e-mail to program directors or their identified contact individuals at the 130 U.S. anesthesiology residency programs accredited as of June 30, 2012 by the Accreditation Council for Graduate Medical Education. The questionnaires asked whether the department had an AIMS, the year of installation, and, if not present, whether there were plans to install an AIMS within the next 12 months. Follow-up e-mails and phone calls were made until responses were obtained from all programs. Results were collected between February and May 2013. Implementation percentages were determined using the number of accredited anesthesia residency programs at the start of each academic year between 1987 and 2013 and were fit to a logistic regression curve using data through 2012. RESULTS: Responses were received from all 130 programs. Eighty-seven (67%) reported that they currently are using an AIMS. Ten programs without a current AIMS responded that they would be installing an AIMS within 12 months of the survey. The rate of AIMS adoption by year was well fit by a logistic regression curve (P = 0.90). CONCLUSIONS: By the end of 2014, approximately 75% of U.S. academic anesthesiology departments will be using an AIMS, with 84% adoption expected between 2018 and 2020. Historical adoption of AIMS has followed Roger's 1962 formulation of the theory of diffusion of innovation

The Use of Rapid COVID-19 Antigen Test in the Emergency Department as a Decision-Support Tool

The emergency department (ED) is the initial point of contact between hospital staff and patients potentially infected with SARS-CoV-2, thus, prevention of inadvertent exposure to other patients is a top priority. We aimed to assess whether the introduction of antigen-detecting rapid diagnostic tests (Ag-RDTs) to the ED affected the likelihood of unwanted SARS-CoV-2 exposures. In this retrospective single-center study, we compared the rate of unwarranted exposure of uninfected adult ED patients to SARS-CoV-2 during two separate research periods; one before Ag-RDTs were introduced, and one with Ag-RDT used as a decision-support tool. The introduction of Ag-RDTs to the ED significantly decreased the relative risk of SARS-CoV-2-negative patients being incorrectly assigned to the COVID-19 designated site (“red ED”), by 97%. There was no increase in the risk of SARS-CoV-2-positive patients incorrectly assigned to the COVID-19-free site (“green ED”). In addition, duration of ED admission was reduced in both the red and the green ED. Therefore, implementing the Ag-RDT-based triage protocol proved beneficial in preventing potential COVID-19 nosocomial transmission

The Use of Rapid COVID-19 Antigen Test in the Emergency Department as a Decision-Support Tool

The emergency department (ED) is the initial point of contact between hospital staff and patients potentially infected with SARS-CoV-2, thus, prevention of inadvertent exposure to other patients is a top priority. We aimed to assess whether the introduction of antigen-detecting rapid diagnostic tests (Ag-RDTs) to the ED affected the likelihood of unwanted SARS-CoV-2 exposures. In this retrospective single-center study, we compared the rate of unwarranted exposure of uninfected adult ED patients to SARS-CoV-2 during two separate research periods; one before Ag-RDTs were introduced, and one with Ag-RDT used as a decision-support tool. The introduction of Ag-RDTs to the ED significantly decreased the relative risk of SARS-CoV-2-negative patients being incorrectly assigned to the COVID-19 designated site (“red ED”), by 97%. There was no increase in the risk of SARS-CoV-2-positive patients incorrectly assigned to the COVID-19-free site (“green ED”). In addition, duration of ED admission was reduced in both the red and the green ED. Therefore, implementing the Ag-RDT-based triage protocol proved beneficial in preventing potential COVID-19 nosocomial transmission