DEVELOPMENT AND VALIDATION OF A SEMI-PHYSIOLOGICAL PHARMACOKINETIC (PBPK) MODEL TO PREDICT SYSTEMIC AND PULMONARY EXPOSURES AFTER INTRAVENOUS, ORAL ADMINISTRATION AND PULMONARY INHALATION OF SELECTED DRUGS, BUDESONIDE, TOBRAMYCIN AND CIPROFLOXACIN, IN HUMANS

Using a semi-PBPK modeling/quantitative meta-analysis approach, this project investigated what factors affect pulmonary and systemic exposures of Budesonide (BUD), Tobramycin (TOB), and Ciprofloxacin (CIP) after inhalation: Three structurally different pulmonary disposition models were developed for each drug, including pulmonary absorption (all three), excretion (TOB and CIP) and sequestration (TOB) in a peripheral and central lung compartment. Systemic disposition parameters were estimated using available human mean plasma (cp(t)) and sputum (cs(t)) concentration profiles after IV administration, and GI absorption parameters were estimated from these profiles after oral administration. Pulmonary disposition parameters were estimated from cp(t) and cs(t) profiles after inhalation using various devices along with their published pulmonary deposition characteristics. Appropriate covariate models accounted for effects of Cystic Fibrosis on the systemic disposition/GI absorption for TOB and CIP. Monte Carlo Simulations (MCS) were used to optimize parameters and validate the final models and parameter spaces against published data. Despite limited available data, especially cs(t) for BUD and CIP (after IV administration), the point estimates for the final model parameters were mechanistically plausible for all three drugs and consistent with their known differences in physicochemical and ADME properties. Model predictions adequately described the observed cp(t) and cs(t) profiles as well as exposure metrics across studies. As the most lipophilic drug, BUD showed the fastest pulmonary absorption rates and highest Fpul (83%). TOB, a very hydrophilic drug, exhibited (intracellular) pulmonary sequestration, resulting in slow pulmonary absorption and excretion and low Fpul (10%). CIP - as zwitterion - showed relatively slow pulmonary absorption and excretion, leading to low Fpul (8%); pulmonary excretion accounted for 27% of CIP overall elimination. Results of a formal parameter sensitivity analysis demonstrated that, for all three drugs, after inhalation, (1) their systemic exposures (cp(t)) depend primarily on CLtot along with Fpul/sequestration combined with Foral; (2) increasing pulmonary exposures (cs(t)) can be accomplished by slowing down pulmonary absorption rates (kca) and/or slowing down mucociliary clearance from the lungs into the GI tract (kcm) – affirming the overall hypothesis guiding the project

A Review of the Potential Health Benefits of Low Alcohol and Alcohol-Free Beer: Effects of Ingredients and Craft Brewing Processes on Potentially Bioactive Metabolites

Beer is a beverage of significant historical and cultural importance. Interest in the potential health effects of alcoholic beverages has largely focused on wine; however, there are a number of potentially beneficial bioactives that beer may contain that warrant further investigation. The challenge of considering any potential health benefits of beer are restricted by the negative consequences of its alcohol and energy content. There is potential to enhance the bioactive qualities of beer whilst reducing the alcohol and energy content through novel brewing approaches often used in craft brewing, in terms of ingredients, brewing methods and type of fermentation. Consumer demand to produce a greater variety of beer types, including alcohol-free beers, may also help to increase the number of beers which may have greater potential to improve health, with lower levels of alcohol, while still being tasty products. As low alcohol, prebiotic and bioactive containing beers are developed, it is important that their potential health benefits and risks are fully assessed

Case Report: Patient with Hepatitis C, p-ANCA, and Cryoglobulin Antibodies Presenting with Necrotizing Crescentic p-ANCA Glomerulonephritis

Hepatitis C (HCV) infection has a prevalence of 3 million infected individuals in the United States, according to recent Center for Disease Control reports, and can have various renal manifestations. Cryoglobulins, antibodies that precipitate at colder temperatures in vitro, are a relatively common cause of renal disease in HCV infection. The cryoglobulin proteins can form occlusive aggregates in small glomerular capillary lumina or deposit in other areas of the glomerulus, resulting in hypocomplementemia, proteinuria, hematuria, and renal injury. The typical biopsy pattern is that of membranoproliferative glomerulonephritis (MPGN). There are, however, other HCV-related patterns of glomerular injury. Anti-neutrophil cytoplasmic antibodies (ANCA) are known to exist in HCV-infected patients. In many reported cases, ANCA serologic testing may appear positive due to cross-reactivity of the immune assays; however, the biopsy findings do not support ANCA-associated crescentic glomerulonephritis (GN)/vasculitis as the primary cause of glomerular injury. There are rare reports of microscopic polyangiitis (MPA) p-ANCA vasculitis, in patients with HCV infection. In comparison with the MPGN pattern of cryoglobulinemic glomerular injury, biopsies from these HCV-infected patients with concomitant MPA revealed a crescentic GN, associated with normal serum complement levels. We present a case of HCV-associated glomerular disease with the surprising biopsy finding of necrotizing and crescentic p-ANCA GN, with a background, low-grade mesangial immune complex GN. Thus, p-ANCA disease should also be considered in HCV-infected patients, in addition to the more typical lesions of MPGN or cryoglobulinemic GN

Trotabresib (CC-90010) in combination with adjuvant temozolomide or concomitant temozolomide plus radiotherapy in patients with newly diagnosed glioblastoma

Standard-of-care treatment for newly diagnosed glioblastoma (ndGBM), consisting of surgery followed by radiotherapy (RT) and temozolomide (TMZ), has improved outcomes compared with RT alone; however, prognosis remains poor. Trotabresib, a novel bromodomain and extraterminal inhibitor, has demonstrated antitumor activity in patients with high-grade gliomas. In this phase Ib, dose-escalation study (NCT04324840), we investigated trotabresib 15, 30, and 45 mg combined with TMZ in the adjuvant setting and trotabresib 15 and 30 mg combined with TMZ+RT in the concomitant setting in patients with ndGBM. Primary endpoints were to determine safety, tolerability, maximum tolerated dose, and/or recommended phase II dose (RP2D) of trotabresib. Secondary endpoints were assessment of preliminary efficacy and pharmacokinetics. Pharmacodynamics were investigated as an exploratory endpoint. The adjuvant and concomitant cohorts enrolled 18 and 14 patients, respectively. Trotabresib in combination with TMZ or TMZ+RT was well tolerated; most treatment-related adverse events were mild or moderate. Trotabresib pharmacokinetics and pharmacodynamics in both settings were consistent with previous data for trotabresib monotherapy. The RP2D of trotabresib was selected as 30 mg 4 days on/24 days off in both settings. At last follow-up, 5 (28%) and 6 (43%) patients remain on treatment in the adjuvant and concomitant settings, respectively, with 1 patient in the adjuvant cohort achieving complete response. Trotabresib combined with TMZ in the adjuvant setting and with TMZ+RT in the concomitant setting was safe and well tolerated in patients with ndGBM, with encouraging treatment durations. Trotabresib 30 mg was established as the RP2D in both setting

Small molecule inhibitor of OGG1 blocks oxidative DNA damage repair at telomeres and potentiates methotrexate anticancer effects

The most common oxidative DNA lesion is 8-oxoguanine which is mainly recognized and excised by the 8-oxoG DNA glycosylase 1 (OGG1), initiating the base excision repair (BER) pathway. Telomeres are particularly sensitive to oxidative stress (OS) which disrupts telomere homeostasis triggering genome instability. In the present study, we have investigated the effects of inactivating BER in OS conditions, by using a specific inhibitor of OGG1 (TH5487). We have found that in OS conditions, TH5487 blocks BER initiation at telomeres causing an accumulation of oxidized bases, that is correlated with telomere losses, micronuclei formation and mild proliferation defects. Moreover, the antimetabolite methotrexate synergizes with TH5487 through induction of intracellular reactive oxygen species (ROS) formation, which potentiates TH5487-mediated telomere and genome instability. Our findings demonstrate that OGG1 is required to protect telomeres from OS and present OGG1 inhibitors as a tool to induce oxidative DNA damage at telomeres, with the potential for developing new combination therapies for cancer treatment

Targeting OGG1 arrests cancer cell proliferation by inducing replication stress

Altered oncogene expression in cancer cells causes loss of redox homeostasis resulting in oxidative DNA damage, e.g. 8-oxoguanine (8-oxoG), repaired by base excision repair (BER). PARP1 coordinates BER and relies on the upstream 8-oxoguanine-DNA glycosylase (OGG1) to recognise and excise 8-oxoG. Here we hypothesize that OGG1 may represent an attractive target to exploit reactive oxygen species (ROS) elevation in cancer. Although OGG1 depletion is well tolerated in non-transformed cells, we report here that OGG1 depletion obstructs A3 T-cell lymphoblastic acute leukemia growth in vitro and in vivo, validating OGG1 as a potential anti-cancer target. In line with this hypothesis, we show that OGG1 inhibitors (OGG1i) target a wide range of cancer cells, with a favourable therapeutic index compared to non-transformed cells. Mechanistically, OGG1i and shRNA depletion cause S-phase DNA damage, replication stress and proliferation arrest or cell death, representing a novel mechanistic approach to target cancer. This study adds OGG1 to the list of BER factors, e.g. PARP1, as potential targets for cancer treatment

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Convergent Learning for Class Imbalance: A Unified Approach to Long-Tail Recognition in Image Classification

Addressing the complex challenge of long-tail recognition (LTR) in image classification, this study introduces an innovative integrated approach that meticulously combines cross-entropy, contrastive learning, and imbalanced class loss functions. The prevalence of class imbalances within datasets significantly hampers the effectiveness of conventional machine learning models by skewing performance toward majority classes and neglecting the minority ones. To combat this issue, our approach aims to harmonize the learning process across all classes, ensuring equitable representation and enhancing feature separability. Our methodology is rooted in a multifaceted strategy where metric learning combined with crossentropy fosters an equitable learning environment across diverse classes, ensuring no class is overshadowed regardless of its frequency within the dataset. This composite loss function is designed to bolster model robustness and generalization capabilities, addressing the inherent challenges of the LTR problem comprehensively. The validation of our proposed solution was conducted through rigorous experimentation on modified CIFAR-10/100 datasets and a bespoke custom dataset, showcasing our approach’s adaptability and effectiveness across varying levels of class imbalance. Utilizing ResNet models of differing depths (ResNet18, ResNet34, and ResNet50) and experimenting with a range of loss functions—including focal loss and supervised contrastive loss—allowed us to assess our methodology’s performance in a broad spectrum of scenarios. This experimental setup not only facilitated a deep dive into the comparative analysis of model behaviors but also enabled the identification of optimal configurations for tackling LTR challenges. Our findings illustrate significant improvements in model performance, particularly in environments characterized by pronounced class imbalances. By employing our integrated approach, we were able to set new benchmarks for image classification models, demonstrating superior performance in handling longtailed distributions. The study’s implications extend beyond the immediate advancements in LTR; it lays a foundational framework for future research in machine learning, emphasizing the importance of a balanced and nuanced approach to model training and development. Furthermore, our study elucidates the critical role of selecting appropriate loss functions and data augmentation strategies, tailored to the unique characteristics of each dataset. This insight is instrumental in advancing the field of machine learning, guiding practitioners in the development of more robust, equitable, and effective models. Through a comprehensive exploration of the challenges and solutions associated with LTR, this research contributes to a deeper understanding of class imbalance issues, paving the way for innovative approaches in the domain of imbalanced learning

Australia’s Two-Tier Health Care System United Against COVID-19

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Stock Market Simulation 2311

The objective of this Interactive Qualifying Project was to use stock market simulation as a tool to compare the effectiveness of different trading strategies and get experiences in stock investments. A 5-week stock market simulation was performed with 4 different trading strategies: Swing trading, Position trading, Day trading, and a combination of Momentum and Position trading. Each strategy used $100,000 cash. This project provided participants with a real hands-on experience of how the stock market trading and investing works