Quantifying trade-offs between therapeutic efficacy and resistance dissemination for enrofloxacin dose regimens in cattle.

The use of antimicrobial drugs in food-producing animals contributes to the selection pressure on pathogenic and commensal bacteria to become resistant. This study aims to evaluate the existence of trade-offs between treatment effectiveness, cost, and the dynamics of resistance in gut commensal bacteria. We developed a within-host ordinary differential equation model to track the dynamics of antimicrobial drug concentrations and bacterial populations in the site of infection (lung) and the gut. The model was parameterized to represent enrofloxacin treatment for bovine respiratory disease (BRD) caused by Pastereulla multocida in cattle. Three approved enrofloxacin dosing regimens were compared for their effects on resistance on P. multocida and commensal E. coli: 12.5 mg/kg and 7.5 mg/kg as a single dose, and 5 mg/kg as three doses. Additionally, we explored non-FDA-approved regimes. Our results indicated that both 12.5 mg/kg and 7.5 mg/kg as a single dose scenario increased the most the treatment costs and prevalence of P. multocida resistance in the lungs, while 5 mg/kg as three doses increased resistance in commensal E. coli bacteria in the gut the most out of the approved scenarios. A proposed non-FDA-approved scenario (7.5 mg/kg, two doses 24 h apart) showed low economic costs, minimal P. multocida, and moderate effects on resistant E. coli. Overall, the scenarios that decrease P. multocida, including resistant P. multocida did not coincide with those that decrease resistant E. coli the most, suggesting a trade-off between both outcomes. The sensitivity analysis suggests that bacterial populations were the most sensitive to drug conversion factors into plasma ( ß ), elimination of the drug from the colon ( ϑ ), fifty percent sensitive bacteria (P. multocida) killing effect ( L s50 ), fifty percent of bacteria (E. coli) above ECOFF killing effect ( C r50 ), and net drug transfer rate in the lung ( γ ) parameters.

An LC-MS/MS method for the determination of Lifitegrast in human plasma and tear and its application in the pharmacokinetic study.

Aim: A new, selective and simple UPLC-MS/MS method was developed and validated for the determination of lifitegrast in human plasma and tear in order to obtain PK data. Materials & methods: Lifitegrast-d4 solutions were added in the samples, and then were extracted and transferred to a UPLC vial. Results: The respective working ranges were 25.00-2000.00 pg/ml in plasma and 4.00-1000.00 µg/ml in tear. The fully validated method complied with existing regulatory criteria for accuracy and precision, recovery, etc. It was applied to plasma and tear samples, which were from a clinical study, successfully. Conclusion: This method is useful in the evaluation of lifitegrast in plasma and tear.

[Box: see text].

Strategies for successful dose optimization in oncology drug development: a practical guide.

Dose optimization is a critical challenge in drug development. Historically, dose determination in oncology has followed a divergent path from other non-oncology therapeutic areas due to the unique characteristics and requirements in Oncology. However, with the emergence of new drug modalities and mechanisms of drugs in oncology, such as immune therapies, radiopharmaceuticals, targeted therapies, cytostatic agents, and others, the dose-response relationship for efficacy and toxicity could be vastly varied compared to the cytotoxic chemotherapies. The doses below the MTD may demonstrate similar efficacy to the MTD with an improved tolerability profile, resembling what is commonly observed in non-oncology treatments. Hence, alternate strategies for dose optimization are required for new modalities in oncology drug development. This paper delves into the historical evolution of dose finding methods from non-oncology to oncology, highlighting examples and summarizing the underlying drivers of change. Subsequently, a practical framework and guidance are provided to illustrate how dose optimization can be incorporated into various stages of the development program. We provide the following general recommendations: 1) The objective for phase I is to identify a dose range rather than a single MTD dose for subsequent development to better characterize the safety and tolerability profile within the dose range. 2) At least two doses separable by PK are recommended for dose optimization in phase II. 3) Ideally, dose optimization should be performed before launching the confirmatory study. Nevertheless, innovative designs such as seamless II/III design can be implemented for dose selection and may accelerate the drug development program.

Physiologically Based Pharmacokinetic Modeling of Vancomycin in Critically Ill Neonates: Assessing the Impact of Pathophysiological Changes.

Dosing vancomycin for critically ill neonates is challenging owing to substantial alterations in pharmacokinetics (PKs) caused by variability in physiology, disease, and clinical interventions. Therefore, an adequate PK model is needed to characterize these pathophysiological changes. The intent of this study was to develop a physiologically based pharmacokinetic (PBPK) model that reflects vancomycin PK and pathophysiological changes in neonates under intensive care. PK-sim software was used for PBPK modeling. An adult model (model 0) was established and verified using PK profiles from previous studies. A neonatal model (model 1) was then extrapolated from model 0 by scaling age-dependent parameters. Another neonatal model (model 2) was developed based not only on scaled age-dependent parameters but also on quantitative information on pathophysiological changes obtained via a comprehensive literature search. The predictive performances of models 1 and 2 were evaluated using a retrospectively collected dataset from neonates under intensive care (chictr.org.cn, ChiCTR1900027919), comprising 65 neonates and 92 vancomycin serum concentrations. Integrating literature-based parameter changes related to hypoalbuminemia, small-for-gestational-age, and co-medication, model 2 offered more optimized precision than model 1, as shown by a decrease in the overall mean absolute percentage error (50.6% for model 1; 37.8% for model 2). In conclusion, incorporating literature-based pathophysiological changes effectively improved PBPK modeling for critically ill neonates. Furthermore, this model allows for dosing optimization before serum concentration measurements can be obtained in clinical practice.

Interest in antibiotic pharmacokinetic modelling in the context of optimising dosing and reducing resistance: bibliometric analysis.

INTRODUCTION: In the era of problems with resistant bacteria strains, pharmacokinetic (PK) modelling offers ways to optimise antibiotic therapy and minimise the risk of resistance development. This bibliometric study aimed to investigate trends in PK modelling stu-dies. The goal was to provide researchers with comprehensive insight and identify future needs. MATERIAL AND METHODS: We used Bibliometrix, VOSviewer, and CiteSpace to analyse Web of Science articles on antibiotic PK modelling from 1983 to March 2023. RESULTS: We analysed 968 papers following the inclusion criteria and built a keywords co-occurrence map and timeline. The average annual growth rate of subject-related publications was 35.56% between 1983 and 2022, maintaining a continuous upward trend. Roberts J.A., Lipman J., and Wallis S.C. are the three most productive and impactful authors (82, 57, 34 articles, and h-index of 30, 25, 15, respectively). The United States leads in this field of research (29.13% of papers). The most relevant affiliations are the University of Queensland, Royal Brisbane and Women's Hospital, and Monash University. The top three most productive and impactful journals are Antimicrobial Agents and Chemotherapy, Journal of Antimicrobial Chemotherapy, and International Journal of Antimicrobial Agents (181, 83, 47 articles and h-index of 42, 30, 18, respectively). Most articles by keyword clustered on meropenem, vancomycin, and amikacin. Moreover, therapeutic drug monitoring, resistance, antibiotic dosing, target attainment, the intensive care unit, and paediatrics are the most trending aspects. CONCLUSIONS: Given the results of this study, we expect to see a steady increase in interest in exploiting the potential of PK modelling for optimising antibiotic therapy.

Quantitative proteomic analysis of PK-15 cells infected with porcine circovirus type 3 using 4D-DIA approach.

Porcine circovirus type 3 (PCV3) infection is clinically related to various diseases, including porcine dermatitis and nephrotic syndrome (PDNS)-like disease, respiratory disease, reproductive disorders, and gastrointestinal and neurological diseases. Since PCV3 infection was discovered in 2016, it has developed rapidly and has attracted much attention worldwide. However, specific preventive and therapeutic interventions are currently lacking. In this study, four-dimensional (4D) data-independent acquisition (DIA)-based quantitative proteomics detection combined with bioinformatics analysis were employed to quantitatively identify the differentially expressed proteins in PK-15 cells from the PCV3-infected group compared with those from the uninfected control group. A total of 194 cellular proteins were significantly altered in response to PCV3 infection, including 58 upregulated proteins and 136 downregulated proteins. In our Gene Ontology (GO) enrichment analysis, these differentially expressed proteins were mostly associated with cellular anatomical entities, binding, cellular processes, biological regulation, catalytic activity, metabolic processes, developmental processes, protein-containing complexes and responses to stimuli. Our Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the DEPs were predominantly involved in metabolic pathways, the cAMP signaling pathway, protein processing in the endoplasmic reticulum, the PI3K-Akt signaling pathway, and the calcium signaling pathway. For the experiments, Western blotting (WB) was used to confirm the changes in important molecules. The differentially expressed proteins identified should contribute to a greater understanding of the mechanism of PCV3 replication and pathogenesis, as well as the host response.

Physiologically-based pharmacokinetic/pharmacodynamic modeling of meropenem in critically ill patients.

This study aimed to develop a physiologically based pharmacokinetic/pharmacodynamic model (PBPK/PD) of meropenem for critically ill patients. A PBPK model of meropenem in healthy adults was established using PK-Sim software and subsequently extrapolated to critically ill patients based on anatomic and physiological parameters. The mean fold error (MFE) and geometric mean fold error (GMFE) methods were used to compare the differences between predicted and observed values of pharmacokinetic parameters Cmax, AUC0-∞, and CL to evaluate the accuracy of the PBPK model. The model was verified using meropenem plasma samples obtained from Intensive Care Unit (ICU) patients, which were determined by HPLC-MS/MS. After that, the PBPK model was combined with a PKPD model, which was developed based on f%T > MIC. Monte Carlo simulation was utilized to calculate the probability of target attainment (PTA) in patients. The developed PBPK model successfully predicted the meropenem disposition in critically ill patients, wherein the MFE average and GMFE of all predicted PK parameters were within the 1.25-fold error range. The therapeutic drug monitoring (TDM) of meropenem was conducted with 92 blood samples from 31 ICU patients, of which 71 (77.17%) blood samples were consistent with the simulated value. The TDM results showed that meropenem PBPK modeling is well simulated in critically ill patients. Monte Carlo simulations showed that extended infusion and frequent administration were necessary to achieve curative effect for critically ill patients, whereas excessive infusion time (> 4 h) was unnecessary. The PBPK/PD modeling incorporating literature and prospective study data can predict meropenem pharmacokinetics in critically ill patients correctly. Our study provides a reference for dose adjustment in critically ill patients.

Degradation of citrinin by different types of light and hydrogen peroxide.

Citrinin (CIT), a mycotoxin produced by Monascus, Penicillium, and other fungies, can contaminate red yeast rice and other foods, thus constraining their application and development. Exploring efficient degradation methods of citrinin is becoming as one of the hot research topics. In this study, the degradation of citrinin, irradiated by visible (Vis) light, ultraviolet (UV) light, and simulated sunlight alone, as well as in combination with hydrogen peroxide (light/H2O2), was investigated. The research demonstrates UV, Vis, and simulated sunlight all have a degree of degradation on citrinin, and the degradation efficiency correlates with light source and light intensity. Interestingly, when combined with 100 W Vis and 0.01 M H2O2, the citrinin degradation rate increases to 32%, compared to 1% and 5% achieved by Vis and H2O2 alone. Hydroxyl radicals, arising from the uniform cracking of H2O2 under Vis, were experimentally validated by electron spin resonance measurement and could accelerate the dissociation of citrinin by nucleophilic attacking. Employing the density functional theory, we deduced nucleophilic •OH mainly attack onto C8 and C5 site by comparing the electrophilic Parr functions (Pk+) value of main C atom of citrinin. This research presents a rapid and efficient degradation of citrinin by combining visible light with H2O2. PRACTICAL APPLICATION: This research presents a rapid and efficient method for the degradation of citrnin in red yeast rice and other citrnin containing products by combining visible light with H2O2.

Analyzing Parametric Influences Driving Age-Associated Changes in Absorption using a PBPK-GSA Approach.

The advanced age population may be susceptible to an increased risk of adverse effects due to increased drug exposure after oral dosing. Factors such as high-interindividual variability and lack of data has led to poor characterization of absorption's role in pharmacokinetic changes in this population. Physiologically based pharmacokinetic (PBPK) models are increasingly being used during the drug development process, as their unique qualities are advantageous in atypical scenarios such as drug-drug interactions or special populations such as older people. Along with relying on various sources of data, auxiliary tools including parameter estimation and sensitivity analysis techniques are employed to support model development and other applications. However, sensitivity analyses have mostly been limited to localized techniques in the majority of reported PBPK models using them. This is disadvantageous, since local sensitivity analyses are unsuitable for risk analysis, which require assessment of parametric interactions and proper coverage of the input space to better estimate and subsequently mitigate the effects of the phenomenon of interest. For this reason, this study seeks to integrate a global sensitivity analysis screening method with PBPK models based in PK-Sim® to characterize the consequences of potential changes in absorption that are often associated with advanced age. The Elementary Effects (Morris) method and visualization of the results are implemented in R and three model drugs representing Biopharmaceutical Classification System classes I-III that are expected to exhibit some sensitivity to three age-associated hypotheses were successfully tested.

Compared to other NHEJ factors, DNA-PK protein and RNA levels are markedly increased in all higher primates, but not in prosimians or other mammals.

The DNA dependent protein kinase (DNA-PK) initiates non-homologous recombination (NHEJ), the predominate DNA double-strand break (DSBR) pathway in higher vertebrates. It has been known for decades that the enzymatic activity of DNA-PK [that requires its three component polypeptides, Ku70, Ku80 (that comprise the DNA-end binding Ku heterodimer), and the catalytic subunit (DNA-PKcs)] is present in humans at 10-50 times the level observed in other mammals. Here, we show that the high level of DNA-PKcs protein expression appears evolutionarily in mammals between prosimians and higher primates. Moreover, the RNAs encoding the three component polypeptides of DNA-PK are present at similarly high levels in hominids, new-, and old-world monkeys, but expression of these RNAs in prosimians is ∼5-50 fold less, analogous to the levels observed in other non-primate species. This is reminiscent of the appearance of Alu repeats in primate genomes -- abundant in higher primates, but present at much lower density in prosimians. Alu repeats are well-known for their capacity to promote non-allelic homologous recombination (NAHR) a process known to be inhibited by DNA-PK. Nanopore sequence analyses of cultured cells proficient or deficient in DNA-PK revealed an increase of inter-chromosomal translocations caused by NAHR. Although the high levels of DNA-PK in primates may have many functions, we posit that high levels of DNA-PK may function to restrain deleterious NAHR events between Alu elements.

A Novel Autosomal Recessive Candidate Gene Responsible for RASopathy-Like Phenotype and Bone Marrow Failure: RASA3.

Although many genetic etiologies, such as Fanconi anemia, Shwachman-Diamond syndrome, dyskeratosis congenita, and Diamond-Blackfan anemia, from hereditary bone marrow failure are known today, the responsible gene remains unknown in a significant part of these patients. A 6-year-old girl, whose parents were first-cousin consanguineous, was referred to the pediatric hematology department due to growth retardation, thrombocytopenia, neutropenia, and anemia. The patient had low-set ears, pectus excavatum inferiorly, and cafe-au-lait spots. In whole-exome analysis, p.K385T (c.1154A > C) variant in the RASA3 gene was detected as homozygous. The amino acid position of the alteration is located in the conserved and ordered region, corresponding to the Ras GTPase activation domain (Ras-GAP) in the center of the protein. Importantly, most of in silico prediction tools of pathogenicity predicts the variant as damaging. RASopathies, which are characterized by many common clinical findings, such as atypical facial features, growth delays, and heart defects, are a group of rare genetic diseases caused by mutations in the genes involved in the Ras-MAPK pathway. The findings in this patient were consistent with the RASopathy-like phenotype and bone marrow failure. Interestingly, enrichment of RASopathy genes was observed in the RASA3 protein-protein interaction network. Furthermore, the subsequent topological clustering revealed a putative function module, which further implicates RASA3 in this disease as a novel potential causative gene. In this context, the detected RASA3 mutation could be manifesting itself clinically as the observed phenotype by disrupting the functional cooperation between the RASA3 protein and its interaction partners. Relatedly, current literature also supports the obtained findings. Overall, this study provides new insights into RASopathy and put forward the RASA3 gene as a novel candidate gene for this disease group.

Simultaneous inhibition of ATM, ATR, and DNA-PK causes synergistic lethality.

Here we report that simultaneous inhibition of the three primary DNA damage recognition PI3 kinase-like kinases (PIKKs) -ATM, ATR, and DNA-PK- induces severe combinatorial synthetic lethality in mammalian cells. Utilizing Chinese hamster cell lines CHO and V79 and their respective PIKK mutants, we evaluated effects of inhibiting these three kinases on cell viability, DNA damage response, and chromosomal integrity. Our results demonstrate that while single or dual kinase inhibition increased cytotoxicity, inhibition of all three PIKKs results in significantly higher synergistic lethality, chromosomal aberrations, and DNA double-strand break (DSB) induction as calculated by their synergy scores. These findings suggest that the overlapping redundancy of ATM, ATR, and DNA-PK functions is critical for cell survival, and their combined inhibition greatly disrupts DNA damage signaling and repair processes, leading to cell death. This study provides insights into the potential of multi-targeted DDR kinase inhibition as an effective anticancer strategy, necessitating further research to elucidate underlying mechanisms and therapeutic applications.

Bat-derived oligopeptide LE6 inhibits the contact-kinin pathway and harbors anti-thromboinflammation and stroke potential.

Thrombosis and inflammation are primary contributors to the onset and progression of ischemic stroke. The contact-kinin pathway, initiated by plasma kallikrein (PK) and activated factor XII (FXIIa), functions bidirectionally with the coagulation and inflammation cascades, providing a novel target for therapeutic drug development in ischemic stroke. In this study, we identified a bat-derived oligopeptide from Myotis myotis (Borkhausen, 1797), designated LE6 (Leu-Ser-Glu-Glu-Pro-Glu, 702 Da), with considerable potential in stroke therapy due to its effects on the contact kinin pathway. Notably, LE6 demonstrated significant inhibitory effects on PK and FXIIa, with inhibition constants of 43.97 µmol/L and 6.37 µmol/L, respectively. In vitro analyses revealed that LE6 prolonged plasma recalcification time and activated partial thromboplastin time. In murine models, LE6 effectively inhibited carrageenan-induced mouse tail thrombosis, FeCl 3-induced carotid artery thrombosis, and photochemically induced intracerebral thrombosis. Furthermore, LE6 significantly decreased inflammation and stroke injury in transient middle cerebral artery occlusion models. Notably, the low toxicity, hemolytic activity, and bleeding risk of LE6, along with its synthetic simplicity, underscore its clinical applicability. In conclusion, as an inhibitor of FXIIa and PK, LE6 offers potential therapeutic benefits in stroke treatment by mitigating inflammation and preventing thrombus formation.

DNA sensors in metabolic and cardiovascular diseases: Molecular mechanisms and therapeutic prospects.

DNA sensors generally initiate innate immune responses through the production of type I interferons. While extensively studied for host defense against invading pathogens, emerging evidence highlights the involvement of DNA sensors in metabolic and cardiovascular diseases. Elevated levels of modified, damaged, or ectopically localized self-DNA and non-self-DNA have been observed in patients and animal models with obesity, diabetes, fatty liver disease, and cardiovascular disease. The accumulation of cytosolic DNA aberrantly activates DNA signaling pathways, driving the pathological progression of these disorders. This review highlights the roles of specific DNA sensors, such as cyclic AMP-GMP synthase and stimulator of interferon genes (cGAS-STING), absent in melanoma 2 (AIM2), toll-like receptor 9 (TLR9), interferon gamma-inducible protein 16 (IFI16), DNA-dependent protein kinase (DNA-PK), and DEAD-box helicase 41 (DDX41) in various metabolic disorders. We explore how DNA signaling pathways in both immune and non-immune cells contribute to the development of these diseases. Furthermore, we discuss the intricate interplay between metabolic stress and immune responses, offering insights into potential therapeutic targets for managing metabolic and cardiovascular disorders. Understanding the mechanisms of DNA sensor signaling in these contexts provides a foundation for developing novel interventions aimed at mitigating the impact of these pervasive health issues.

Synergistic efficacy of ceftazidime/avibactam and aztreonam against carbapenemase-producing Pseudomonas aeruginosa: insights from the hollow-fiber infection model.

BACKGROUND: Combination therapy is an attractive therapeutic option for extensively drug-resistant (XDR) Pseudomonas aeruginosa infections. Existing data support the combination of aztreonam and ceftazidime/avibactam (CZA) against class serine-ß-lactamase (SBL)- and metallo-ß-lactamase (MBL) - producing Enterobacterales. However, data about that combination against SBL- and MBL-producing P. aeruginosa are scarce. The objective of the study was to assess the in vitro activity of CZA and aztreonam alone and in combination against SBL- and MBL-producing XDR P. aeruginosa isolates. METHODS: The combination was analyzed by means of the hollow-fiber infection model in three selected carbapenemase-producing P. aeruginosa isolates that were representative of the three most common XDRP. aeruginosa high-risk clones (ST175, ST111, ST235) responsible for global nosocomial infection outbreaks. RESULTS: The three isolates were nonsusceptible to CZA and nonsusceptible to aztreonam. In the dynamic hollow-fiber infection model, the combination of CZA plus aztreonam exerts a bactericidal effect on the isolates, regardless of their resistance mechanism and demonstrates synergistic interactions against three isolates, achieving a bacterial reduction of 5.07 log10 CFU/ml, 5.2 log10 CFU/ml and 4 log10 CFU/ml, respectively. CONCLUSION: The combination of CZA and aztreonam significantly enhanced the in vitro efficacy against XDR P. aeruginosa isolates compared to each monotherapy. This improvement suggests that the combination could serve as a feasible treatment alternative for infections caused by carbapenemase-producing XDR P. aeruginosa, especially in scenarios where no other treatment options are available.

Scaling approaches for the prediction of human clearance of LNA-i-mir-221: A retrospective validation.

LNA-i-miR-221 is a novel microRNA(miRNA)-221 inhibitor designed for the treatment of human malignancies. It has recently undergone phase 1 clinical trial (P1CT) and early pharmacokinetics (PKs) data in cancer patients are now available. We previously used multiple allometric interspecies scaling methods to draw inferences about LNA-i-miR-221 PKs in humans and estimated the patient dose based on the safe and pharmacodynamic (PD) active dose observed in mice, therefore providing a framework for the definition of safe starting and escalation doses for the P1CT. The preliminary data collected during the P1CT showed that the LNA-i-miR-221 anticipated doses, according to our human PK estimation approach, were indeed well tolerated and effective. PD data demonstrated concentration-dependent downregulation of miR-221 and upregulation of its CDKN1B/p27 and PTEN canonical targets as well as stable disease in 8 (50.0%) patients and partial response in 1 (6.3%) colorectal cancer case. Here, we detail the experimentally evaluated PK parameters of LNA-i-miR-221 in human, using both a non-compartmental and a population PKs approach. The population approach was adequately described by a three-compartments model with first-order elimination. The recorded age, sex and body weight of patients were evaluated as potential covariates. The estimated typical population parameter values were clearance (CL = 200 mL/h/kg), central volume of distribution (V1 = 45 mL/kg), peripheral volume of distribution (V2 = 200 mL/kg, volume of the second peripheral compartment V3 = 930 mL/h/kg) and inter-compartmental clearance (Q2 = 480 mL/h/kg and Q3 = 68 mL/h/kg). Age was found to be a predictor of Q3, with a statistically significant correlation. This work aimed also at retrospectively comparing the measured plasmatic clearance values with those predicted by different allometric scaling approaches. Our comparative analysis showed that the most accurate prediction was achieved by applying the single species allometric scaling approach and that the use of more than one species in allometric scaling to predict therapeutic oligonucleotides PKs would not necessarily generate the best prediction. Finally, our predictive approach was found accurate not only in predicting the main PK parameters in human but suggesting the range of effective and safe dose to be applied in the next clinic phase 2.

Co-Administration of Amiodarone Increases Bleeding by Affecting Rivaroxaban Pharmacokinetics in Patients with Atrial Fibrillation.

This study aimed to investigate the impact of the drug-drug interaction between rivaroxaban and amiodarone on the clinical outcomes in patients with non-valvular atrial fibrillation (NVAF), focusing on pharmacokinetic and pharmacodynamic (PK/PD) aspects. A prospective study enrolling 174 patients with NVAF who were treated with rivaroxaban was conducted. The patients were divided into two groups based on postoperative antiarrhythmic and anticoagulation strategies: the rivaroxaban group (Control group) and the rivaroxaban plus amiodarone group (Riv/Amio group). The trough plasma concentrations (Ctrough) of rivaroxaban, activated partial thromboplastin time (APTT), prothrombin time (PT), and the clinical outcomes between the two groups were compared. Patients receiving 20 mg of rivaroxaban in the Riv/Amio group had a higher concentration of rivaroxaban Ctrough than those in the Control group (p = 0.009). Furthermore, in patients with moderate to severe renal impairment, rivaroxaban Ctrough was significantly increased in the Riv/Amio group. There was no significant difference in PT and APTT between the two groups. Regarding the clinical outcomes, the combination of rivaroxaban and amiodarone medication was associated with a higher incidence of bleeding events (p = 0.041; HR = 2.83, 95% CI 1.05-7.66) and clinically relevant non-major bleeding (p = 0.021; HR = 3.65, 95% CI 1.21-10.94). Finally, independent risk factors for bleeding in NAVF patients treated with rivaroxaban were identified as its combination with amiodarone (p = 0.044; OR = 2.871, 95% CI 1.028-8.023). The combination of rivaroxaban and amiodarone led to changes in rivaroxaban pharmacokinetics and an elevated risk of bleeding events. Therefore, physicians prescribing rivaroxaban medications should assess the potential bleeding risk associated with the concurrent use of amiodarone, particularly in patients with renal impairment.

Actionable Predictions of Human Pharmacokinetics at the Drug Design Stage.

We present a novel computational approach for predicting human pharmacokinetics (PK) that addresses the challenges of early stage drug design. Our study introduces and describes a large-scale data set of 11 clinical PK end points, encompassing over 2700 unique chemical structures to train machine learning models. To that end multiple advanced training strategies are compared, including the integration of in vitro data and a novel self-supervised pretraining task. In addition to the predictions, our final model provides meaningful epistemic uncertainties for every data point. This allows us to successfully identify regions of exceptional predictive performance, with an absolute average fold error (AAFE/geometric mean fold error) of less than 2.5 across multiple end points. Together, these advancements represent a significant leap toward actionable PK predictions, which can be utilized early on in the drug design process to expedite development and reduce reliance on nonclinical studies.

RPL22 is a tumor suppressor in MSI-high cancers and a splicing regulator of MDM4.

Microsatellite instability-high (MSI-H) tumors are malignant tumors that, despite harboring a high mutational burden, often have intact TP53. One of the most frequent mutations in MSI-H tumors is a frameshift mutation in RPL22, a ribosomal protein. Here, we identified RPL22 as a modulator of MDM4 splicing through an alternative splicing switch in exon 6. RPL22 loss increases MDM4 exon 6 inclusion and cell proliferation and augments resistance to the MDM inhibitor Nutlin-3a. RPL22 represses the expression of its paralog, RPL22L1, by mediating the splicing of a cryptic exon corresponding to a truncated transcript. Therefore, damaging mutations in RPL22 drive oncogenic MDM4 induction and reveal a common splicing circuit in MSI-H tumors that may inform therapeutic targeting of the MDM4-p53 axis and oncogenic RPL22L1 induction.

Comparative transcriptome reveals EphA2 and c-Fos as key factors driving enhanced replication in high-passage porcine deltacoronavirus strain.

Porcine deltacoronavirus (PDCoV), a cross-species transmissible enterovirus, frequently induces severe diarrhea and vomiting symptoms in piglets, which not only pose a significant menace to the global pig industry but also a potential public safety risk. In a previous study, we isolated a vaccine candidate, PDCoV CZ2020-P100, by passaging a parental PDCoV strain in vitro, exhibiting attenuated virulence and enhanced replication. However, the factors underlying these differences between primary and passaged strains remain unknown. In this study, we present the transcriptional landscapes of porcine kidney epithelial cells (LLC-PK1) cells infected with PDCoV CZ2020-P1 strain and P100 strain using the RNA-sequencing. We identified 105 differentially expressed genes (DEGs) in P1-infected cells and 295 DEGs in P100-infected cells. Enrichment analyses indicated that many DEGs showed enrichment in immune and inflammatory responses, with a more and higher upregulation of DEGs enriched in the P100-infected group. Notably, the DEGs were concentrated in the MAPK pathway within the P100-infected group, with significant upregulation in EphA2 and c-Fos. Knockdown of EphA2 and c-Fos reduced PDCoV infection and significantly impaired P100 replication compared to P1, suggesting a novel mechanism in which EphA2 and c-Fos are highly involved in passaged virus replication. Our findings illuminate the resemblances and distinctions in the gene expression patterns of host cells infected with P1 and P100, confirming that EphA2 and c-Fos play key roles in high-passage PDCoV replication. These results enhance our understanding of the changes in virulence and replication capacity during the process of passaging.