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Background Listeriosis is an orphan disease, which is nevertheless fatal in immunocompromised people. CRS0540 is a novel PolC DNA polymerase inhibitor that has demonstrated good in vitro and in vivo activity against Listeria monocytogenes. Methods Rodent-to-human allometry projection-based human population pharmacokinetics of CRS0540 were used for all studies. CRS0540 pharmacokinetics/pharmacodynamics studies in an intracellular hollow-fibre system model of disseminated listeriosis (HFS-Lister) examined the effect of eight treatment doses, administered daily over 7 days, in duplicate units. Total bacterial burden versus AUC/MIC exposures on each day were modelled using the inhibitory sigmoid Emax model, while CRS0540-resistant bacterial burden was modelled using a quadratic function. Ten thousand-subject Monte Carlo simulations were used to predict an optimal clinical dose for treatment. Results The mean CRS0540 intracellular/extracellular AUC0–24 ratio was 34.07 (standard error: 15.70) as measured in the HFS-Lister. CRS0540 demonstrated exposure-dependent bactericidal activity in the HFS-Lister, with the highest exposure killing approximately 5.0 log10 cfu/mL. The free drug AUC0–24/MIC associated with 80% of maximal kill (EC80) was 36.4. Resistance emergence versus AUC/MIC was described by a quadratic function, with resistance amplification at an AUC/MIC of 54.8 and resistance suppression at an AUC/MIC of 119. Monte Carlo simulations demonstrated that for the EC80 target, IV CRS0540 doses of 100 mg/kg achieved PTAs of >90% at MICs up to 1.0 mg/L. Conclusions CRS0540 is a promising orphan drug candidate for listeriosis. Future PK/PD studies comparing it with penicillin, the standard of care, could lead to this drug as a new treatment in immunocompromised patients.

The benzothiazole amide CRS0393 demonstrated excellent in vitro activity against nontuberculous mycobacteria (NTM), including M. abscessus isolates from cystic fibrosis (CF) patients, with minimum inhibitory concentrations (MICs) of ≤0.03-0.5 μg/mL. The essential transport protein MmpL3 was confirmed as the target via analysis of spontaneous resistant mutants and further biological profiling. In mouse pharmacokinetic studies, intratracheal instillation of a single dose of CRS0393 resulted in high concentrations of drug in epithelial lining fluid (ELF) and lung tissue, which remained above the M. abscessus MIC for at least 9 hours post-dose. This exposure resulted in a penetration ratio of 261 for ELF and 54 for lung tissue relative to plasma. CRS0393 showed good oral bioavailability, particularly when formulated in kolliphor oil, with a lung-to-plasma penetration ratio ranging from 0.5 to 4. CRS0393 demonstrated concentration-dependent reduction of intracellular M. abscessus in a THP-1 macrophage infection model. CRS0393 was well tolerated following intranasal administration (8 mg/kg) or oral dosing (25 mg/kg) once daily for 28 days in dexamethasone-treated C3HeB/FeJ mice. Efficacy against M. abscessus strain 103 was achieved via the intranasal route, while oral dosing will need further optimization. CRS0393 holds promise for development as a novel agent with broad antimycobacterial activity.

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

From a high throughput screening of commercially available libraries against nontuberculous mycobacteria and Mycobacterium tuberculosis, numerous hits were identified with moderate activity. Extensive medicinal chemistry optimization has led to a series of potent benzothiazole amide antimycobacterial agents. Replacement of the adamantyl group with cyclohexyl derivatives and further development of this series resulted in an advanced lead compound, CRS400393, which demonstrated excellent potency and a mycobacteria-specific spectrum of activity. MIC values ranged from 0.03 to 0.12 μg/mL against Mycobacterium abscessus and other rapid-grower NTM, and 1–2 μg/mL against Mycobacterium avium complex. The preliminary mechanism of action studies suggested these agents may target MmpL3, a mycobacterial mycolic acid transporter. The series has demonstrated in vivo efficacy in a proof of concept mouse model of M. abscessus infection.

This paper addresses the fundamental research question: “How can we determine the sequential decision- making process inside a decision maker’s mind?” We construct a dynamic Markov Decision Process using a Double Transition Model (DTM). The DTM is a cognitive model decomposing the decision-making process into episodic tasks that are extracted from a stream of incoming information. In a DTM, each state reflects a stage en route to a decision, and each action reflects a possible move from collecting data to hypothesizing and inferencing. The reward reflects how close a stage is to the final decision. We demonstrate this process through a proof-of-concept DTM using a hypothetical scenario for Typhoon Haiyan in the Philippines (2013). The DTM constructed from this scenario enables a Commander to reason about damaged areas, death tolls, and assistance methods while allowing his actions to be captured and used to explain why and how each decision is made.

Mycobacteria remain an important problem worldwide, especially drug resistant human pathogens. Novel therapeutics are urgently needed to tackle both drug-resistant tuberculosis (TB) and difficult-to-treat infections with nontuberculous mycobacteria (NTM). Benzothiazole adamantyl amide had previously emerged as a high throughput screening hit against M. tuberculosis (Mtb) and was subsequently found to be active against NTM as well. For lead optimization, we applied an iterative process of design, synthesis and screening of several 100 analogs to improve antibacterial potency as well as physicochemical and pharmacological properties to ultimately achieve efficacy. Replacement of the adamantyl group with cyclohexyl derivatives, including bicyclic moieties, resulted in advanced lead compounds that showed excellent potency and a mycobacteria-specific spectrum of activity. MIC values ranged from 0.03 to 0.12 μg/mL against M. abscessus (Mabs) and other rapid- growing NTM, 1-2 μg/mL against M. avium complex (MAC), and 0.12-0.5 μg/mL against Mtb. No pre-existing resistance was found in a collection of n = 54 clinical isolates of rapid-growing NTM. Unlike many antibacterial agents commonly used to treat mycobacterial infections, benzothiazole amides demonstrated bactericidal effects against both Mtb and Mabs. Metabolic labeling provided evidence that the compounds affect the transfer of mycolic acids to their cell envelope acceptors in mycobacteria. Mapping of resistance mutations pointed to the trehalose monomycolate transporter (MmpL3) as the most likely target. In vivo efficacy and tolerability of a benzothiazole amide was demonstrated in a mouse model of chronic NTM lung infection with Mabs. Once daily dosing over 4 weeks by intrapulmonary microspray administration as 5% corn oil/saline emulsion achieved statistically significant CFU reductions compared to vehicle control and non-inferiority compared to azithromycin. The benzothiazole amides hold promise for development of a novel therapeutic agent with broad antimycobacterial activity, though further work is needed to develop drug formulations for direct intrapulmonary delivery via aerosol.

Data with multiple responses is ubiquitous in modern applications. However, few tools are available for regression analysis of multivariate counts. The most popular multinomial-logit model has a very restrictive mean-variance structure, limiting its applicability to many data sets. This article introduces an R package MGLM, short for multivariate response generalized linear models, that expands the current tools for regression analysis of polytomous data. Distribution fitting, random number generation, regression, and sparse regression are treated in a unifying framework. The algorithm, usage, and implementation details are discussed.

OBJECTIVE The choice of bibliographic database during the systematic review search process has been an ongoing conversation among information specialists. With newer information sources, such as Google Scholar and clinical trials registries, we were interested in which databases were utilized by information specialists and systematic review researchers. METHOD We retrieved 144 systematic reviews and meta-analyses from 4 clinical endocrinology journals and extracted all information sources used during the search processes. RESULTS Findings indicate that traditional bibliographic databases are most often used, followed by regional databases, clinical trials registries, and gray literature databases. CONCLUSIONS This study informs information specialists about additional resources that may be considered during the search process.

The reconstruction of twist torque in the Main Parachute Risers of the Capsule Parachute Assembly System (CPAS) has been successfully used to validate CPAS Model Memo conservative twist torque equations. Reconstruction of basic, one degree of freedom drop tests was used to create a functional process for the evaluation of more complex, rigid body simulation. The roll, pitch, and yaw of the body, the fly-out angles of the parachutes, and the relative location of the parachutes to the body are inputs to the torque simulation. The data collected by the Inertial Measurement Unit (IMU) was used to calculate the true torque. The simulation then used photogrammetric and IMU data as inputs into the Model Memo equations. The results were then compared to the true torque results to validate the Model Memo equations. The Model Memo parameters were based off of steel risers and the parameters will need to be re-evaluated for different materials. Photogrammetric data was found to be more accurate than the inertial data in accounting for the relative rotation between payload and cluster. The Model Memo equations were generally a good match and when not matching were generally conservative.

In many real-life situations, e.g., in medicine, it is necessary to process data while preserving the patients’ confidentiality. One of the most efficient methods of preserving privacy is to replace the exact values with intervals that contain these values. For example, instead of an exact age, a privacy-protected database only contains the information that the age is, e.g., between 10 and 20, or between 20 and 30, etc. Based on this data, it is important to compute correlation and covariance between different quantities. For privacy-protected data, different values from the intervals lead, in general, to different estimates for the desired statistical characteristic. Our objective is then to compute the range of possible values of these estimates.