Identification of β-Lactams Active against Mycobacterium tuberculosis by a Consortium of Pharmaceutical Companies and Academic Institutions

Rising antimicrobial resistance challenges our ability to combat bacterial infections. The problem is acute for tuberculosis (TB), the leading cause of death from infection before COVID-19. Here, we developed a framework for multiple pharmaceutical companies to share proprietary information and compounds with multiple laboratories in the academic and government sectors for a broad examination of the ability of β-lactams to kill Mycobacterium tuberculosis (Mtb). In the TB Drug Accelerator (TBDA), a consortium organized by the Bill & Melinda Gates Foundation, individual pharmaceutical companies collaborate with academic screening laboratories. We developed a higher order consortium within the TBDA in which four pharmaceutical companies (GlaxoSmithKline, Sanofi, MSD, and Lilly) collectively collaborated with screeners at Weill Cornell Medicine, the Infectious Disease Research Institute (IDRI), and the National Institute of Allergy and Infectious Diseases (NIAID), pharmacologists at Rutgers University, and medicinal chemists at the University of North Carolina to screen ∼8900 β-lactams, predominantly cephalosporins, and characterize active compounds. In a striking contrast to historical expectation, 18% of β-lactams screened were active against Mtb, many without a β-lactamase inhibitor. One potent cephaloporin was active in Mtb-infected mice. The steps outlined here can serve as a blueprint for multiparty, intra- and intersector collaboration in the development of anti-infective agents

On-Road NOx and Smoke Emissions of Diesel Light Commercial VehiclesCombining Remote Sensing Measurements from across Europe

Light commercial vehicles (LCVs) account for about 10-15% of road traffic in Europe. There have only been few investigations on their on-road emission performance. Here, on-road remote sensing vehicle emission measurements from 18 locations across four European countries are combined for a comprehensive analysis of NOx and smoke emission rates from diesel LCV in the past two decades. This allows differentiating the performance by emission standards, model years, curb weights, engine loads, manufacturers, vehicle age, and temperature, as well as by measurement devices. We find a general consistency between devices and countries. On-road NOx emission rates have been much higher than type approval limit values for all manufacturers, but some perform systematically better than others. Emission rates have gone down only with the introduction of Euro 6a-b emission standards since the year 2015. Smoke emission rates are considered a proxy for particulate emissions. Their emissions have decrease substantially from the year 2010 onward for all countries and size classes measured. This is consistent with the substantial tightening of the particulate matter emission limit value that typically forced the introduction of a diesel particulate filter. The average NOx emission rate increases with engine load and decreasing ambient temperatures, particularly for Euro 4 and 5 emission classes. This explains to a large extent the differences in the absolute level between the measurement sites together with differences in fleet composition. These dependencies have already been observed earlier with diesel passenger cars; they are considered part of an abnormal emission control strategy. Some limited increase of the NOx emission rate is observed for Euro 3 vehicles older than 10 years. The strong increase for the youngest Euro 6 LCVs might rather reflect technology advances with successively younger models than genuine deterioration. However, the durability of emission controls for Euro 6 vehicles should be better monitored closely. Smoke emission rates continuously increase with vehicle age, suggesting a deterioration of the after-treatment system with use

Modeling the Flying Sidekick Traveling Salesman Problem with Multiple Drones

This paper considers a version of the flying sidekick travel- ing salesman problem in which parcels are delivered to cus- tomers by either a truck or a set of identical flying drones. The drones’ flights are limited by the battery endurance and each flight is made of a launch, a service to a customer, and a return: launch and return must happen when the truck is stationary. These operations require time and when multi- ple drones are launched and/or collected at the same node, their order becomes relevant. The proposed model takes into account the order of these operations as a scheduling problem, because ignoring it could lead to infeasible solu- tions in the reality due to the possible exceeding of drones endurance. We propose a set of novel formulations for the problem that can improve the size of the largest instances solved in the literature. We provide a comparison among the formulations, between the multiple drones solutions and the single drone ones, and among different variants of the model