Levofloxacin is considered a key component of a multidrug-resistant tuberculosis (MDR-TB) regimen. However, there is considerable concern regarding the subtherapeutic concentrations of the currently used doses and the development of drug resistance. Therefore, this study aimed to describe the population pharmacokinetics (PPK) of oral levofloxacin in healthy volunteers and to evaluate the probability of target attainment (PTA) in an attempt to optimize the dosing regimens for MDR-TB therapy. Data of levofloxacin in healthy volunteers from a previous study were used to construct a PPK model. Monte Carlo simulations were performed to derive the PTAs of various regimens. A two-compartment model with linear elimination and transit absorption compartments best described the pharmacokinetics (PK) of levofloxacin. The estimated PK parameters (interindividual variability, %) were apparent clearance 8.32 L h-1 (22.6%), apparent central volume of distribution 35.8 L (45.2%), apparent peripheral volume of distribution 39.7 L, intercompartmental clearance 40.6 L h-1 (43.8%), absorption rate constant 7.45 h-1 (150%), mean absorption transit time 0.355 h (52.4%), and total number of transit compartments 6.01 (131.9%). Monte Carlo simulations using levofloxacin 750-1000 mg yielded a probability of achieving a target free area under the concentration-time curve/minimum inhibitory concentration (MIC) of 100 at greater than 90% for Mycobacterium tuberculosis with an MIC less then 0.5 mg L-1 , while a dose of 1500 mg was required for strains with an MIC of 1 mg L-1 . A higher dose of levofloxacin might be needed to treat tuberculosis. However, further studies on the efficacy and safety of this dose are needed to confirm our findings.Coarse-grained normal mode analyses of protein dynamics rely on the idea that the geometry of a protein structure contains enough information for computing its fluctuations around its equilibrium conformation. This geometry is captured in the form of an elastic network (EN), namely a network of edges between its residues. The normal modes of a protein are then identified with the normal modes of its EN. Different approaches have been proposed to construct ENs, focusing on the choice of the edges that they are comprised of, and on their parameterizations by the force constants associated with those edges. Here we propose new tools to guide choices on these two facets of EN. We study first different geometric models for ENs. We compare cutoff-based ENs, whose edges have lengths that are smaller than a cutoff distance, with Delaunay-based ENs and find that the latter provide better representations of the geometry of protein structures. We then derive an analytical method for the parameterization of the EN such that its dynamics leads to atomic fluctuations that agree with experimental B-factors. Foretinib inhibitor To limit overfitting, we attach a parameter referred to as flexibility constant to each atom instead of to each edge in the EN. The parameterization is expressed as a non-linear optimization problem whose parameters describe both rigid-body and internal motions. We show that this parameterization leads to improved ENs, whose dynamics mimic MD simulations better than ENs with uniform force constants, and reduces the number of normal modes needed to reproduce functional conformational changes.Substance Use Disorders (SUD) are chronic health conditions with heritability characteristics, environmental influences, long-term management considerations and they cooccur. The US opioid epidemic is a crisis of both prescription and nonprescription opioid use. Clinicians now have access to evidence-based practices but the evolving trends require continuous attention including curriculum initiatives for dental schools. The purpose of this study was to obtain information about the content and educational strategies of current SUD curricula, beneficial educational products for a standardized curriculum and perceived barriers toward standardization. Invitations were sent to 64 US dental schools describing the purpose of this study and a link to complete the survey was provided. Fully completed responses were received from 32 (50.0%) of the schools. Descriptive statistics was used to analyze the data. Most dental schools surveyed (81.3%) have a curriculum for SUD with classroom lectures being the most commonly used teaching method (96.2%), followed by online modules (42.3%). About 30% of the responding schools provided additional educational experiences. Instruction occurred mostly in second (73.1%) and third (77.0%) academic years. Opioids, alcohol, nicotine, and marijuana were the most frequently taught substance classes. Curriculum standardization with online modules (81.3%), case-based exercises (59.4%), and simulation with standardized patients (43.8%) was considered desirable to improve student competency in the management of patients with SUD. Lack of time (62.5%), space (56.3%), and faculty (50.0%) were cited as the most common barriers to curriculum initiatives. Experiential and achievable options for improving SUD curriculum were highlighted.The mounting evidence for the involvement of astrocytes in neuronal circuits function and behavior stands in stark contrast to the lack of detailed anatomical description of these cells and the neurons in their domains. To fill this void, we imaged >30,000 astrocytes in hippocampi made transparent by CLARITY, and determined the elaborate structure, distribution, and neuronal content of astrocytic domains. First, we characterized the spatial distribution of >19,000 astrocytes across CA1 lamina, and analyzed the morphology of thousands of reconstructed domains. We then determined the excitatory somatic content of CA1 astrocytes, and measured the distance between inhibitory neuronal somata to the nearest astrocyte soma. We find that on average, there are almost 14 pyramidal neurons per domain in the CA1, increasing toward the pyramidal layer midline, compared to only five excitatory neurons per domain in the amygdala. Finally, we discovered that somatostatin neurons are found in close proximity to astrocytes, compared to parvalbumin and VIP inhibitory neurons.