33 research outputs found
Featured Piece
This year the General Editors continued the tradition started last year by creating a feature piece to show our appreciation for the History Department. We selected four professors from the faculty to answer a question about history: what figure/event/idea inspires your interest in history? Reading their responses helped give us insight into the thoughts of these brilliant minds and further help us understand their passion for the subject we all share a common love and interest in. We hope that you enjoy reading their responses as much as we did.
The four members of the faculty we spoke with are Dr. Abou Bamba, Dr. William Bowman, Dr. David Hadley, and Magdalena Sánchez
Commercial Application of In-Space Assembly
In-Space assembly (ISA) expands the opportunities for cost effective emplacement of systems in space. Currently, spacecraft are launched into space and deploy into their operational configuration through a carefully choreographed sequence of operations. The deployment operation dictates the arrangement of the primary systems on the spacecraft, limiting the ability to take full advantage of launch vehicles volume and mass capability. ISA enables vastly different spacecraft architectures and emplacement scenarios to be achieved, including optimal launch configurations ranging from single launch and assembly to on-orbit aggregation of multiple launches at different orbital locations and times. The spacecraft can be visited at different orbital locations and times to effect expansion and maintenance of an operational capability. To date, the primary application of ISA has been in large programs funded by government organizations, such as the International Space Station. Recently, Space Systems Loral (SSL) led a study funded by the Defense Advanced Research Projects Agency (DARPA), called Dragonfly, to investigate the commercial applicability and economic advantages of ISA. In the study, it was shown that ISA enables SSL to double the capability of a commercial satellite system by taking advantage of alternate packaging approaches for the reflectors. The study included an ultra-light-weight robotic system, derived from Mars manipulator designs, to complete assembly of portions of the antenna system using a tool derived from DARPA orbital express and National Aeronautics and Space Administration (NASA) automated structural assembly experience. The mechanical connector that enables robotic ISA takes advantage of decades of development by NASA from the 1970's to 1980's during the Space Station Freedom program, the precursor to the ISS. The mechanical connector was originally designed for rapid astronaut assembly while also providing a high quality structural connection with linear load deflection response. The paper will discuss the business case for ISA, the general approach taken to exploit on-orbit assembly in the GEO communication satellite market, and the concept of operations associated with the ISA approach, thus laying the foundation for ISA to become an accepted operational approach for commercial in-space operations
AI is a viable alternative to high throughput screening: a 318-target study
: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
TRY plant trait database – enhanced coverage and open access
Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries
Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely
Testing Competing Explanations for Policy Adoption: Municipal Solid Waste Recycling Programs
A class of selective antibacterials derived from a protein kinase inhibitor pharmacophore
As the need for novel antibiotic classes to combat bacterial drug resistance increases, the paucity of leads resulting from target-based antibacterial screening of pharmaceutical compound libraries is of major concern. One explanation for this lack of success is that antibacterial screening efforts have not leveraged the eukaryotic bias resulting from more extensive chemistry efforts targeting eukaryotic gene families such as G protein-coupled receptors and protein kinases. Consistent with a focus on antibacterial target space resembling these eukaryotic targets, we used whole-cell screening to identify a series of antibacterial pyridopyrimidines derived from a protein kinase inhibitor pharmacophore. In bacteria, the pyridopyrimidines target the ATP-binding site of biotin carboxylase (BC), which catalyzes the first enzymatic step of fatty acid biosynthesis. These inhibitors are effective in vitro and in vivo against fastidious Gram-negative pathogens including Haemophilus influenzae. Although the BC active site has architectural similarity to those of eukaryotic protein kinases, inhibitor binding to the BC ATP-binding site is distinct from the protein kinase-binding mode, such that the inhibitors are selective for bacterial BC. In summary, we have discovered a promising class of potent antibacterials with a previously undescribed mechanism of action. In consideration of the eukaryotic bias of pharmaceutical libraries, our findings also suggest that pursuit of a novel inhibitor leads for antibacterial targets with active-site structural similarity to known human targets will likely be more fruitful than the traditional focus on unique bacterial target space, particularly when structure-based and computational methodologies are applied to ensure bacterial selectivity