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Introduction: Using a validated translational model that quantitatively predicts opioid-induced respiratory depression and cardiac arrest, we compared cardiac arrest events caused by synthetic opioids (fentanyl, carfentanil) following rescue by intranasal (IN) administration of the μ-opioid receptor antagonists naloxone and nalmefene., Methods: This translational model was originally developed by Mann et al. (Clin Pharmacol Ther 2022) to evaluate the effectiveness of intramuscular (IM) naloxone. We initially implemented this model using published codes, reproducing the effects reported by Mann et al. on the incidence of cardiac arrest events following intravenous doses of fentanyl and carfentanil as well as the reduction in cardiac arrest events following a standard 2 mg IM dose of naloxone. We then expanded the model in terms of pharmacokinetic and µ-opioid receptor binding parameters to simulate effects of 4 mg naloxone hydrochloride IN and 3 mg nalmefene hydrochloride IN, both FDA-approved for the treatment of opioid overdose. Model simulations were conducted to quantify the percentage of cardiac arrest in 2000 virtual patients in both the presence and absence of IN antagonist treatment., Results: Following simulated overdoses with both fentanyl and carfentanil in chronic opioid users, IN nalmefene produced a substantially greater reduction in the incidence of cardiac arrest compared to IN naloxone. For example, following a dose of fentanyl (1.63 mg) producing cardiac arrest in 52.1% (95% confidence interval, 47.3-56.8) of simulated patients, IN nalmefene reduced this rate to 2.2% (1.0-3.8) compared to 19.2% (15.5-23.3) for IN naloxone. Nalmefene also produced large and clinically meaningful reductions in the incidence of cardiac arrests in opioid naïve subjects. Across dosing scenarios, simultaneous administration of four doses of IN naloxone were needed to reduce the percentage of cardiac arrest events to levels that approached those produced by a single dose of IN nalmefene., Conclusion: Simulations using this validated translational model of opioid overdose demonstrate that a single dose of IN nalmefene produces clinically meaningful reductions in the incidence of cardiac arrest compared to IN naloxone following a synthetic opioid overdose. These findings are especially impactful in an era when >90% of all opioid overdose deaths are linked to synthetic opioids such as fentanyl., Competing Interests: Authors CL, PP, and PS are employees of Indivior Inc. Opiant Pharmaceuticals developed nalmefene nasal spray and was acquired by Indivior Inc. in March 2023. Authors ND and IG-G are employees of Simulations Plus and received funding for conducting modeling and simulation activities. The author(s) declare that the research was funded by Indivior Inc. The funder was involved in the study design, collection, analysis, interpretation of data, the writing of this article, and the decision to submit it for publication., (Copyright © 2024 Laffont, Purohit, Delcamp, Gonzalez-Garcia and Skolnick.)

Technologies for quantifying circulating tumour DNA (ctDNA) in liquid biopsies could enable real-time measurements of cancer progression, profoundly impacting patient care. Sequencing methods can be too complex and time-consuming for regular point-of-care monitoring, but nanotechnology offers an alternative, harnessing the unique properties of objects tens to hundreds of nanometres in size. This systematic review was performed to identify all examples of nanotechnology-based ctDNA detection and assess their potential for clinical use. Google Scholar, PubMed, Web of Science, Google Patents, Espacenet and Embase/MEDLINE were searched up to 23rd March 2021. The review identified nanotechnology-based methods for ctDNA detection for which quantitative measures (e.g., limit of detection, LOD) were reported and biologically relevant samples were used. The pre-defined inclusion criteria were met by 66 records. LODs ranged from 10 zM to 50nM. 25 records presented an LOD of 10fM or below. Nanotechnology-based approaches could provide the basis for the next wave of advances in ctDNA diagnostics, enabling analysis at the point-of-care, but none are currently used clinically. Further work is needed in development and validation; trade-offs are expected between different performance measures e.g., number of sequences detected and time to result.

Worldwide, COVID-19 coronavirus disease is spreading rapidly in a second and third wave of infections. In this context of increasing infections, it is critical to know the probability of a specific number of cases being reported. We collated data on new daily confirmed cases of COVID-19 breakouts in: Argentina, Brazil, China, Colombia, France, Germany, India, Indonesia, Iran, Italy, Mexico, Poland, Russia, Spain, U.K., and the United States, from the 20th of January, 2020 to 28th of August 2021. A selected sample of almost ten thousand data is used to validate the proposed models. Generalized Extreme-Value Distribution Type 1-Gumbel and Exponential (1, 2 parameters) models were introduced to analyze the probability of new daily confirmed cases. The data presented in this document for each country provide the daily probability of rate incidence. In addition, the frequencies of historical events expressed as a return period in days of the complete data set is provided., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors. Published by Elsevier Inc.)

Missing data is a universal problem in analysing Real-World Evidence (RWE) datasets. In RWE datasets, there is a need to understand which features best correlate with clinical outcomes. In this context, the missing status of several biomarkers may appear as gaps in the dataset that hide meaningful values for analysis. Imputation methods are general strategies that replace missing values with plausible values. Using the Flatiron NSCLC dataset, including more than 35,000 subjects, we compare the imputation performance of six such methods on missing data: predictive mean matching, expectation-maximisation, factorial analysis, random forest, generative adversarial networks and multivariate imputations with tabular networks. We also conduct extensive synthetic data experiments with structural causal models. Statistical learning from incomplete datasets should select an appropriate imputation algorithm accounting for the nature of missingness, the impact of missing data, and the distribution shift induced by the imputation algorithm. For our synthetic data experiments, tabular networks had the best overall performance. Methods using neural networks are promising for complex datasets with non-linearities. However, conventional methods such as predictive mean matching work well for the Flatiron NSCLC biomarker dataset.

Survival of antibody-secreting plasma cells (PCs) is vital for sustained antibody production. However, it remains poorly understood how long-lived PCs (LLPCs) are generated and maintained. Here we report that ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) is preferentially upregulated in bone marrow LLPCs compared with their splenic short-lived counterparts (SLPCs). We studied ENPP1-deficient mice (Enpp1 -/- ) to determine how the enzyme affects PC biology. Although Enpp1 -/- mice generated normal levels of germinal center B cells and plasmablasts in periphery, they produced significantly reduced numbers of LLPCs following immunization with T-dependent antigens or infection with plasmodium C. chabaudi. Bone marrow chimeric mice showed B cell intrinsic effect of ENPP1 selectively on generation of bone marrow as well as splenic LLPCs. Moreover, Enpp1 -/- PCs took up less glucose and had lower levels of glycolysis than those of wild-type controls. Thus, ENPP1 deficiency confers an energetic disadvantage to PCs for long-term survival and antibody production.

Introduction: In vitro models with high predictive ability have been revealed as strong tools for pharmaceutical industry. However, the variability in permeability estimations complicates the comparison and combination of data from different laboratories and it makes necessary the careful validation of the model and the continuous suitability demonstration. The adequate standardization of pre-experimental, experimental and post-experimental factors might help to reduce the inter- and intra-laboratory variability in permeability values., Methods: The objective of this paper is the evaluation of the effect of passage number, experimental protocol, time after seeding and calculation method on the permeability values and their variability in transport experiments in Caco-2, MDCK and MDCK-MDR1 cells. Metoprolol, Lucifer yellow and Rhodamine-123 were used to check the performance of the cell lines. Protocols used differ mainly in the differentiation time and the filter support coating with collagen. Data was analyzed with sink and non-sink approaches. The final purpose was to explore pre-experimental, experimental and post-experimental conditions in order to select the best experimental scenarios for permeability assays., Results: Results indicated that for passive diffusion studies, coating helps cell differentiation in a more stable manner in all cell lines compared to protocol without coating which showed permeability changes with passages and more variable values. In both protocols the paracellular route became more restricted with higher passage numbers. Functionality of P-gp assessed with Rhodamine permeability did not change with passage number in Caco-2 cells with any of the protocols but increased in both protocols in MDCK and MDCK-MDR1 cells. Protocol without coating showed the less variable results in these cell lines. Rhodamine permeabilities increased with higher maturation times due to a higher expression of the transporter. Nevertheless for compounds absorbed by passive diffusion there was not a clear trend neither in permeability values nor in variability., Discussion: As a conclusion, we have confirmed the influence of maturation conditions and passage number in permeability values and in their variability. Based on our results protocol with coating would be more adequate for studies of compounds absorbed by passive diffusion but the protocol without coating gave us better results for studies about P-gp interactions., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Innate-like B-1a cells contribute significantly to circulating natural antibodies and mucosal immunity as well as to immunoregulation. Here we show that these classic functions of B-1a cells segregate between two unique subsets defined by expression of plasma cell alloantigen 1 (PC1), also known as ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1). These subsets, designated B-1a.PC1(lo) and B-1a.PC1(hi), differ significantly in IgH chain utilization. Adoptively transferred PC1(lo) cells secreted significantly more circulating natural IgM and intestinal IgA than PC1(hi) cells. In contrast, PC1(hi) cells produced more IL-10 than PC1(lo) cells when stimulated with LPS and phorbol 12-myristate 13-acetate (PMA). PC1(hi) cells were also more efficient than PC1(lo) cells in regulating Th1 cell differentiation, even though both B-1a subsets were comparably active in stimulating T-cell proliferation. Furthermore, PC1(lo) cells generated antigen-specific IgM responses to pneumococcal polysaccharide antigens, whereas PC1(hi) cells do not. We found that PC1(lo) cells develop from an early wave of B-1a progenitors in fetal life, whereas PC1(hi) cells are generated from a later wave after birth. We conclude that identification of B-1a.PC1(lo) and B-1a.PC1(hi) cells extends the concept of a layered immune system with important implications for developing effective vaccines and promoting the generation of immunoregulatory B cells.

The ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) has documented roles in mineralization, nucleotide recycling, and insulin resistance. While ENPP1 was first identified as an alloantigen on mouse plasma cells (PCs), later studies revealed expression in many tissues. Previously described monoclonal antibodies against ENPP1 expressed at the cell surface recognized cells only from mice bearing the a allotype, ENPP1(a), precluding studies of mice bearing the alternative allele, ENPP1(b). Here, we characterize a novel anti-ENPP1 monoclonal antibody that recognizes both alleles and can be used for flow cytometry.

Allelic imbalances are common events in cancer cells. Quantitative alterations in specific chromosomal loci have been linked to activation (gain) or inactivation (loss) of genes with a proven impact on tumor cell biology. The aim of this study was to detect new chromosomal regions recurrently altered in colorectal tumorigenesis and with a potential effect on patient's outcome. We have analyzed a series of human colorectal tumor biopsy specimens by using the DNA fingerprinting technique arbitrarily primed PCR. This approach provided information on 95 different loci randomly selected and distributed through out the cell's genome. Eight sequences displayed recurrent alterations associated with diminished patient survival. Four of them (showing allelic losses) were located in chromosome 4, one sequence in chromosome 2, and one sequence in chromosome 17. The chromosomal origin of the two remaining sequences could not be determined. Fine mapping of chromosome 4 bands suggested that there are at least two regions in chromosome 4 (4p14-16 and 4q21-28) susceptible to containing tumor suppressor genes the loss of which may affect tumor aggressiveness.