Attosecond photoelectron streaking with enhanced energy resolution for small-bandgap materials.

Attosecond photoelectron streaking spectroscopy allows time-resolved electron dynamics with a temporal resolution approaching the atomic unit of time. Studies have been performed in numerous systems, including atoms, molecules, and surfaces, and the quest for ever higher temporal resolution called for ever wider spectral extent of the attosecond pulses. For typical experiments relying on attosecond pulses with a duration of 200 as, the time-bandwidth limitation for a Gaussian pulse implies a minimal spectral bandwidth larger than 9 eV translating to a corresponding spread of the detected photoelectron kinetic energies. Here, by utilizing a specially tailored narrowband reflective XUV multilayer mirror, we explore experimentally the minimal spectral width compatible with attosecond time-resolved photoelectron spectroscopy while obtaining the highest possible spectral resolution. The validity of the concept is proven by recording attosecond electron streaking traces from the direct semiconductor gallium arsenide (GaAs), with a nominal bandgap of 1.42 eV at room temperature, proving the potential of the approach for tracking charge dynamics also in these technologically highly relevant materials that previously have been inaccessible to attosecond science.

A population pharmacokinetic model for R- and S-citalopram and desmethylcitalopram in Alzheimer's disease patients with agitation.

The citalopram for Alzheimer's disease trial evaluated citalopram for the management for agitation in Alzheimer's disease patients. Sparse data was available from this elderly patient population. A nonlinear mixed effects population pharmacokinetic modeling approach was used to describe the pharmacokinetics of R- and S-citalopram and their primary metabolite (desmethylcitalopram). A structural model with 4 compartments (one compartment/compound) with linear oral absorption and elimination described the data adequately. Overall, the model showed that clearance of the R-enantiomer was slower than the clearance of the S-enantiomer. Without accounting for any patient-specific covariates, the population estimate of the metabolic clearance of citalopram was 8.6 (R-citalopram) and 14 L/h (S-citalopram). The population estimate of the clearance of desmethylcitalopram was 23.8 (R-Dcit) and 38.5 L/h (S-Dcit). Several patient-specific covariates were found to have a significant effect on the pharmacokinetics of R,S-citalopram and desmethylcitalopram. A significant difference in the metabolic clearance of R-citalopram between males and females (13 vs 9.05 L/h) was identified in this analysis. Both R- and S-citalopram metabolic clearance decreased with age. Additionally, consistent with literature reports S-citalopram metabolic clearance increased with increasing body weight and was significantly influenced by CYPC19 genotype, with a difference of 5.8 L/h between extensive/rapid and intermediate/poor metabolizers. R,S-desmethylcitalopram clearance increased with increasing body weight. This model may allow for the opportunity to delineate the effect of R- and S-citalopram on pharmacodynamics outcomes related to the management of agitation in Alzheimer's disease.

Biomarkers for Diagnosis and Prognosis of Sinusoidal Obstruction Syndrome after Hematopoietic Cell Transplantation.

Reliable, noninvasive methods for diagnosing and prognosing sinusoidal obstruction syndrome (SOS) early after hematopoietic cell transplantation (HCT) are needed. We used a quantitative mass spectrometry-based proteomics approach to identify candidate biomarkers of SOS by comparing plasma pooled from 20 patients with and 20 patients without SOS. Of 494 proteins quantified, we selected 6 proteins (L-Ficolin, vascular cell adhesion molecule-1 [VCAM1], tissue inhibitor of metalloproteinase-1, von Willebrand factor, intercellular adhesion molecule-1, and CD97) based on a differential heavy/light isotope ratio of at least 2 fold, information from the literature, and immunoassay availability. Next, we evaluated the diagnostic potential of these 6 proteins and 5 selected from the literature (suppression of tumorigenicity-2 [ST2], angiopoietin-2 (ANG2), hyaluronic acid [HA], thrombomodulin, and plasminogen activator inhibitor-1) in samples from 80 patients. The results demonstrate that together ST2, ANG2, L-Ficolin, HA, and VCAM1 compose a biomarker panel for diagnosis of SOS. L-Ficolin, HA, and VCAM1 also stratified patients at risk for SOS as early as the day of HCT. Prognostic Bayesian modeling for SOS onset based on L-Ficolin, HA, and VCAM1 levels on the day of HCT and clinical characteristics showed >80% correct prognosis of SOS onset. These biomarkers may provide opportunities for preemptive intervention to minimize SOS incidence and/or severity.

Chromium/scandium multilayer mirrors for isolated attosecond pulses at 145 eV.

Recent advances in the development of attosecond soft x-ray sources toward photon wavelengths below 10 nm are also driving the development of suited broadband multilayer optics for steering and shaping attosecond pulses. We demonstrate that current attosecond experiments in the sub-200-eV range benefit from these improved optics. We present our achievements in utilizing ion-beam-deposited chromium/scandium (Cr/Sc) multilayer mirrors, optimized by tailored material dependent deposition and interface polishing, for the generation of single attosecond pulses from a high-harmonic cut-off spectrum at a central energy of 145 eV. Isolated attosecond pulses have been measured by soft x-ray-pump/NIR-probe electron streaking experiments and characterized using frequency-resolved optical gating for complete reconstruction of attosecond bursts (FROG/CRAB). The results demonstrate that Cr/Sc multilayer mirrors can be used as efficient attosecond optics for reflecting 600-attosecond pulses at a photon energy of 145 eV, which is a prerequisite for present and future attosecond experiments in this energy range.

Formulation and characterization of polymeric films containing combinations of antiretrovirals (ARVs) for HIV prevention.

PURPOSE: To develop polymeric films containing dual combinations of anti-HIV drug candidate tenofovir, maraviroc and dapivirine for vaginal application as topical microbicides. METHODS: A solvent casting method was used to manufacture the films. Solid phase solubility was used to identify potential polymers for use in the film formulation. Physical and chemical properties (such as water content, puncture strength and in vitro release) and product stability were determined. The bioactivity of the film products against HIV was assessed using the TZM-bl assay and a cervical explant model. RESULTS: Polymers identified from the solid phase solubility study maintained tenofovir and maraviroc in an amorphous state and prevented drug crystallization. Three combination film products were developed using cellulose polymers and polyvinyl alcohol. The residual water content in all films was <10% (w/w). All films delivered the active agents with release of >50% of film drug content within 30 min. Stability testing confirmed that the combination film products were stable for 12 months at ambient temperature and 6 months under stressed conditions. Antiviral activity was confirmed in TZM-bl and cervical explant models. CONCLUSIONS: Polymeric films can be used as a stable dosage form for the delivery of antiretroviral combinations as microbicides.

Increased Dapivirine tissue accumulation through vaginal film codelivery of dapivirine and Tenofovir.

The HIV-1 replication inhibitor dapivirine (DPV) is one of the most promising drug candidates being used in topical microbicide products for prevention of HIV-1 sexual transmission. To be able to block HIV-1 replication, DPV must have access to the viral reverse transcriptase enzyme. The window for DPV to access the enzyme happens during the HIV-1 cellular infection cycle. Thus, in order for DPV to exert its anti-HIV activity, it must be present in the mucosal tissue or cells where HIV-1 infection occurs. A dosage form containing DPV must be able to deliver the drug to the tissue site of action. Polymeric films are solid dosage forms that dissolve and release their payload upon contact with fluids. Films have been used as vaginal delivery systems of topical microbicide drug candidates including DPV. For use in topical microbicide products containing DPV, polymeric films must prove their ability to deliver DPV to the target tissue site of action. Ex vivo exposure studies of human ectocervical tissue to DPV film revealed that DPV was released from the film and did diffuse into the tissue in a concentration dependent manner indicating a process of passive diffusion. Analysis of drug distribution in the tissue revealed that DPV accumulated mostly at the basal layer of the epithelium infiltrating the upper part of the stroma. Furthermore, as a combination microbicide product, codelivery of DPV and TFV from a polymeric film resulted in a significant increase in DPV tissue concentration [14.21 (single entity film) and 31.03 µg/g (combination film)], whereas no impact on TFV tissue concentration was found. In vitro release experiments showed that this observation was due to a more rapid DPV release from the combination film as compared to the single entity film. In conclusion, the findings of this study confirm the ability of polymeric films to deliver DPV and TFV to human ectocervical tissue and show that codelivery of the two agents has a significant impact on DPV tissue accumulation. These findings support the use of polymeric films for topical microbicide products containing DPV and/or TFV.

Deep Learning Methods Applied to Drug Concentration Prediction of Olanzapine.

Pharmacometrics and the utilization of population pharmacokinetics play an integral role in model-informed drug discovery and development (MIDD). Recently, there has been a growth in the application of deep learning approaches to aid in areas within MIDD. In this study, a deep learning model, LSTM-ANN, was developed to predict olanzapine drug concentrations from the CATIE study. A total of 1527 olanzapine drug concentrations from 523 individuals along with 11 patient-specific covariates were used in model development. The hyperparameters of the LSTM-ANN model were optimized through a Bayesian optimization algorithm. A population pharmacokinetic model using the NONMEM model was constructed as a reference to compare to the performance of the LSTM-ANN model. The RMSE of the LSTM-ANN model was 29.566 in the validation set, while the RMSE of the NONMEM model was 31.129. Permutation importance revealed that age, sex, and smoking were highly influential covariates in the LSTM-ANN model. The LSTM-ANN model showed potential in the application of drug concentration predictions as it was able to capture the relationships within a sparsely sampled pharmacokinetic dataset and perform comparably to the NONMEM model.

Population pharmacokinetic and exposure-response analyses of pemigatinib in patients with advanced solid tumors including cholangiocarcinoma.

Pemigatinib is a selective, potent, oral inhibitor of fibroblast growth factor receptor (FGFR)1-3 with efficacy in patients with previously treated, advanced/metastatic cholangiocarcinoma (CCA) with FGFR2 alterations. A previously developed population pharmacokinetic (PK) model of pemigatinib was refined using an updated dataset with 467 participants from seven clinical studies, including patients with CCA. Updated PK model parameters were used to evaluate the association between pemigatinib exposure and efficacy and safety. Pemigatinib PK was adequately described by a two-compartment model with linear elimination and sequential zero- and first-order absorption. The final model successfully minimized, had a successful covariance step, and showed unbiased goodness-of-fit. Estimated first-order absorption rate constant and apparent clearance were 3.7/h and 10.7 L/h, respectively. Sex, baseline body weight, and concomitant use of phosphate binders, proton pump inhibitors, or histamine-2 antagonists significantly impacted PK parameters; however, the impact of covariates on PK exposure was not clinically significant. Steady-state pemigatinib exposure and mean change from baseline in serum phosphate concentration were associated with objective response rate in a bell-shaped relationship and were significantly associated with increased hyperphosphatemia. Pemigatinib exposure was associated with treatment-emergent adverse events, such as decreased appetite, nausea, and stomatitis, although the relationships were shallow. Overall, analyses indicate that 13.5 mg pemigatinib once daily in 21-day cycles (2 weeks on, 1 week off) offers a favorable benefit-risk profile in patients with advanced/metastatic or surgically unresectable CCA and is the optimal dose for clinical development.

Characterization of UC781-tenofovir combination gel products for HIV-1 infection prevention in an ex vivo ectocervical model.

HIV continues to be a problem worldwide. Topical vaginal microbicides represent one option being evaluated to stop the spread of HIV. With drug candidates that have a specific action against HIV now being studied, it is important that, when appropriate and based on the mechanism of action, the drug permeates the tissue so that it can be delivered to specific targets which reside there. Novel formulations of the nucleotide reverse transcriptase inhibitor tenofovir (TFV) and the nonnucleoside reverse transcriptase inhibitor UC781 have been developed and evaluated here. Gels with three distinct rheological properties were prepared. The three gels released both UC781 and TFV under in vitro conditions at concentrations equal to or above the reported 50% effective concentrations (EC(50)s). The drug concentrations in ectocervical tissues were well in excess of the reported EC(50)s. The gels maintain ectocervical viability and prevent infection of ectocervical explants after a HIV-1 challenge. This study successfully demonstrates the feasibility of using this novel combination of antiretroviral agents in an aqueous gel as an HIV infection preventative.

Impact of a Pharmacist-Led Intervention on 30-Day Readmission and Assessment of Factors Predictive of Readmission in African American Men With Heart Failure.

Heart failure (HF) is responsible for more 30-day readmissions than any other condition. Minorities, particularly African American males (AAM), are at much higher risk for readmission than the general population. In this study, demographic, social, and clinical data were collected from the electronic medical records of 132 AAM patients (control and intervention) admitted with a primary or secondary admission diagnosis of HF. Both groups received guideline-directed therapy for HF. Additionally the intervention group received a pharmacist-led intervention. Data collected from these patients were used to develop and validate a predictive model to evaluate the impact of the pharmacist-led intervention, and identify predictors of readmission in this population. After propensity score matching, the intervention was determined to have a significant impact on readmission, as a significantly smaller proportion of patients in the intervention group were readmitted as compared to the control group (11.5% vs. 42.9%; p = .03). A predictive model for 30-day readmission was developed using K-nearest neighbor (KNN) classification algorithm. The model was able to correctly classify about 71% patients with an AUROC of 0.70. Additionally, the model provided a set of key patient attributes predictive of readmission status. Among these predictive attributes was whether or not a patient received the intervention. A relative risk analysis identified that patients who received the intervention are less likely to be readmitted within 30 days. This study demonstrated the benefit of a pharmacist-led intervention for AAM with HF. Such interventions have the potential to improve quality of life for this patient population.

Delineating the effects of hot-melt extrusion on the performance of a polymeric film using artificial neural networks and an evolutionary algorithm.

The aim of this study was to utilize an artificial neural network (ANN) in conjunction with an evolutionary algorithm to investigate the relationship between hot melt extrusion (HME) process parameters and vaginal film performance. Investigated HME process parameters were: barrel temperature, screw speed, and feed rate. Investigated film performance attributes were: percent dissolution at 30 min, puncture strength, and drug content. An ANN model was successfully developed and validated with a root mean squared error of 0.043 and 0.098 for training and validation, respectively. Of all three assessed process parameters, the model revealed that barrel temperature has a significant impact on film performance. An increase in barrel temperature resulted in increased dissolution and punctures strength and decreased drug content. Additionally, a successful implementation of an evolutionary algorithm was carried out in order to demonstrate the potential applicability of the developed ANN model in film formulation optimization. In this analysis, the values predicted of film performance attributes were within 1% error of the experimental data. The findings of this study provide a quantitative framework to understand the relationship between HME parameters and film performance. This quantitative framework has the potential to be used for film formulation development and optimization.

The cannabinoid receptor 2 agonist, ß-caryophyllene, improves working memory and reduces circulating levels of specific proinflammatory cytokines in aged male mice.

Age-related cognitive decline has been associated with proinflammatory cytokines, yet the precise relationship between cognitive decline and cytokine load remains to be elucidated. ß-caryophyllene (BCP) is a cannabinoid receptor 2 (CB2) agonist with established anti-inflammatory effects that is known to improve memory and increase lifespan. It is of interest to explore the potential of BCP to reduce age-related cognitive decline and proinflammatory cytokine load. In this study, we assessed changes in circulating cytokines across the lifespan, memory performance in young and aged mice, and the effects of BCP on memory function and cytokine load. The plasma levels of 12 cytokines were assessed in male Swiss-Webster mice at 3, 12, and 18 months of age using multiplexed flow cytometry. Working memory was compared in 3 and 12 month-old mice using spontaneous alternations. A dose-response function (100-300 mg/kg, subchronic administration) for BCP-induced memory restoration was determined in 3- and 12- month-old mice. Finally, the effects on cytokine levels of the peak memory enhancing dose of BCP were assessed in 18- month-old mice. Circulating levels of several cytokines significantly increased with age. Multilinear regression analysis showed that IL-23 levels were most strongly associated with age. Aged mice showed deficits in working memory and higher levels of IL-23, both of which were reversed by BCP treatment. BCP appears to reverse age-associated impairments in memory and modulates cytokine production. IL-23 may play a significant role in the aging process, and future research should determine whether it has utility as a biomarker for novel anti-aging therapeutics.

Development of a Plasma Screening Panel for Pediatric Nonalcoholic Fatty Liver Disease Using Metabolomics.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children, but diagnosis is challenging due to limited availability of noninvasive biomarkers. Machine learning applied to high-resolution metabolomics and clinical phenotype data offers a novel framework for developing a NAFLD screening panel in youth. Here, untargeted metabolomics by liquid chromatography-mass spectrometry was performed on plasma samples from a combined cross-sectional sample of children and adolescents ages 2-25 years old with NAFLD (n = 222) and without NAFLD (n = 337), confirmed by liver biopsy or magnetic resonance imaging. Anthropometrics, blood lipids, liver enzymes, and glucose and insulin metabolism were also assessed. A machine learning approach was applied to the metabolomics and clinical phenotype data sets, which were split into training and test sets, and included dimension reduction, feature selection, and classification model development. The selected metabolite features were the amino acids serine, leucine/isoleucine, and tryptophan; three putatively annotated compounds (dihydrothymine and two phospholipids); and two unknowns. The selected clinical phenotype variables were waist circumference, whole-body insulin sensitivity index (WBISI) based on the oral glucose tolerance test, and blood triglycerides. The highest performing classification model was random forest, which had an area under the receiver operating characteristic curve (AUROC) of 0.94, sensitivity of 73%, and specificity of 97% for detecting NAFLD cases. A second classification model was developed using the homeostasis model assessment of insulin resistance substituted for the WBISI. Similarly, the highest performing classification model was random forest, which had an AUROC of 0.92, sensitivity of 73%, and specificity of 94%. Conclusion: The identified screening panel consisting of both metabolomics and clinical features has promising potential for screening for NAFLD in youth. Further development of this panel and independent validation testing in other cohorts are warranted.

Development and Characterization of a Vaginal Film Containing Dapivirine, a Non- nucleoside Reverse Transcriptase Inhibitor (NNRTI), for prevention of HIV-1 sexual transmission.

Dapivirine, a non-nucleoside reverse transcriptase inhibitor, is a potent and promising anti-HIV molecule. It is currently being investigated for use as a vaginal microbicide in two dosage forms, a semi-solid gel and a silicone elastomer ring. Quick-dissolving films are promising and attractive dosage forms that may provide an alternative platform for the vaginal delivery of microbicide drug candidates. Vaginal films may provide advantages such as discreet use, no product leakage during use, lack of requirement for an applicator for insertion, rapid drug release and minimal packaging and reduced wastage. Within this study the in vitro bioactivity of dapivirine as compared to the NNRTI UC781 was further established and a quick dissolve film was developed for vaginal application of dapivirine for prevention of HIV infection. The developed film was characterized with respect to its physical and chemical attributes including water content, mechanical strength, drug release profile, permeability, compatibility with lactobacilli and bioactivity. The anti-HIV activity of the formulated dapivirine film was confirmed in in vitro and ex vivo models. Importantly the physical and chemical properties of the film as well as its bioactivity were maintained for a period of 18 months. In conclusion, a vaginal film containing dapivirine was developed and characterized. The film was shown to prevent HIV-1 infection in vitro and ex vivo and have acceptable characteristics which make this film a promising candidate for testing as vaginal microbicide.