Ebola virus disease mathematical models and epidemiological parameters: a systematic review.

Ebola virus disease poses a recurring risk to human health. We conducted a systematic review (PROSPERO CRD42023393345) of Ebola virus disease transmission models and parameters published from database inception to July 7, 2023, from PubMed and Web of Science. Two people screened each abstract and full text. Papers were extracted with a bespoke Access database, 10% were double extracted. We extracted 1280 parameters and 295 models from 522 papers. Basic reproduction number estimates were highly variable, as were effective reproduction numbers, likely reflecting spatiotemporal variability in interventions. Random-effect estimates were 15·4 days (95% CI 13·2-17·5) for the serial interval, 8·5 days (7·7-9·2) for the incubation period, 9·3 days (8·5-10·1) for the symptom-onset-to-death delay, and 13·0 days (10·4-15·7) for symptom-onset-to-recovery. Common effect estimates were similar, albeit with narrower CIs. Case-fatality ratio estimates were generally high but highly variable, which could reflect heterogeneity in underlying risk factors. Although a substantial body of literature exists on Ebola virus disease models and epidemiological parameter estimates, many of these studies focus on the west African Ebola epidemic and are primarily associated with Zaire Ebola virus, which leaves a key gap in our knowledge regarding other Ebola virus species and outbreak contexts.

Autonomous circadian rhythms in the human hepatocyte regulate hepatic drug metabolism and inflammatory responses.

Critical aspects of physiology and cell function exhibit self-sustained ~24-hour variations termed circadian rhythms. In the liver, circadian rhythms play fundamental roles in maintaining organ homeostasis. Here, we established and characterized an in vitro liver experimental system in which primary human hepatocytes display self-sustained oscillations. By generating gene expression profiles of these hepatocytes over time, we demonstrated that their transcriptional state is dynamic across 24 hours and identified a set of cycling genes with functions related to inflammation, drug metabolism, and energy homeostasis. We designed and tested a treatment protocol to minimize atorvastatin- and acetaminophen-induced hepatotoxicity. Last, we documented circadian-dependent induction of pro-inflammatory cytokines when triggered by LPS, IFN-ß, or Plasmodium infection in human hepatocytes. Collectively, our findings emphasize that the phase of the circadian cycle has a robust impact on the efficacy and toxicity of drugs, and we provide a test bed to study the timing and magnitude of inflammatory responses over the course of infection in human liver.

Temporal variations in international air travel: implications for modelling the spread of infectious diseases.

BACKGROUND: The international flight network creates multiple routes by which pathogens can quickly spread across the globe. In the early stages of infectious disease outbreaks, analyses using flight passenger data to identify countries at risk of importing the pathogen are common and can help inform disease control efforts. A challenge faced in this modelling is that the latest aviation statistics (referred to as contemporary data) are typically not immediately available. Therefore, flight patterns from a previous year are often used (referred to as historical data). We explored the suitability of historical data for predicting the spatial spread of emerging epidemics. METHODS: We analysed monthly flight passenger data from the International Air Transport Association to assess how baseline air travel patterns were affected by outbreaks of Middle East respiratory syndrome (MERS), Zika and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) over the past decade. We then used a stochastic discrete time susceptible-exposed-infected-recovered (SEIR) metapopulation model to simulate the global spread of different pathogens, comparing how epidemic dynamics differed in simulations based on historical and contemporary data. RESULTS: We observed local, short-term disruptions to air travel from South Korea and Brazil for the MERS and Zika outbreaks we studied, whereas global and longer-term flight disruptions occurred during the SARS-CoV-2 pandemic. For outbreak events that were accompanied by local, small and short-term changes in air travel, epidemic models using historical flight data gave similar projections of the timing and locations of disease spread as when using contemporary flight data. However, historical data were less reliable to model the spread of an atypical outbreak such as SARS-CoV-2, in which there were durable and extensive levels of global travel disruption. CONCLUSION: The use of historical flight data as a proxy in epidemic models is an acceptable practice, except in rare, large epidemics that lead to substantial disruptions to international travel.

Targeting and monitoring ovarian cancer invasion with an RNAi and peptide delivery system.

RNA interference (RNAi) therapeutics are an emerging class of medicines that selectively target mRNA transcripts to silence protein production and combat disease. Despite the recent progress, a generalizable approach for monitoring the efficacy of RNAi therapeutics without invasive biopsy remains a challenge. Here, we describe the development of a self-reporting, theranostic nanoparticle that delivers siRNA to silence a protein that drives cancer progression while also monitoring the functional activity of its downstream targets. Our therapeutic target is the transcription factor SMARCE1, which was previously identified as a key driver of invasion in early-stage breast cancer. Using a doxycycline-inducible shRNA knockdown in OVCAR8 ovarian cancer cells both in vitro and in vivo, we demonstrate that SMARCE1 is a master regulator of genes encoding proinvasive proteases in a model of human ovarian cancer. We additionally map the peptide cleavage profiles of SMARCE1-regulated proteases so as to design a readout for downstream enzymatic activity. To demonstrate the therapeutic and diagnostic potential of our approach, we engineered self-assembled layer-by-layer nanoparticles that can encapsulate nucleic acid cargo and be decorated with peptide substrates that release a urinary reporter upon exposure to SMARCE1-related proteases. In an orthotopic ovarian cancer xenograft model, theranostic nanoparticles were able to knockdown SMARCE1 which was in turn reported through a reduction in protease-activated urinary reporters. These LBL nanoparticles both silence gene products by delivering siRNA and noninvasively report on downstream target activity by delivering synthetic biomarkers to sites of disease, enabling dose-finding studies as well as longitudinal assessments of efficacy.

Priming agents transiently reduce the clearance of cell-free DNA to improve liquid biopsies.

Liquid biopsies enable early detection and monitoring of diseases such as cancer, but their sensitivity remains limited by the scarcity of analytes such as cell-free DNA (cfDNA) in blood. Improvements to sensitivity have primarily relied on enhancing sequencing technology ex vivo. We sought to transiently augment the level of circulating tumor DNA (ctDNA) in a blood draw by attenuating its clearance in vivo. We report two intravenous priming agents given 1 to 2 hours before a blood draw to recover more ctDNA. Our priming agents consist of nanoparticles that act on the cells responsible for cfDNA clearance and DNA-binding antibodies that protect cfDNA. In tumor-bearing mice, they greatly increase the recovery of ctDNA and improve the sensitivity for detecting small tumors.

Inhalable point-of-care urinary diagnostic platform.

Although low-dose computed tomography screening improves lung cancer survival in at-risk groups, inequality remains in lung cancer diagnosis due to limited access to and high costs of medical imaging infrastructure. We designed a needleless and imaging-free platform, termed PATROL (point-of-care aerosolizable nanosensors with tumor-responsive oligonucleotide barcodes), to reduce resource disparities for early detection of lung cancer. PATROL formulates a set of DNA-barcoded, activity-based nanosensors (ABNs) into an inhalable format. Lung cancer-associated proteases selectively cleave the ABNs, releasing synthetic DNA reporters that are eventually excreted via the urine. The urinary signatures of barcoded nanosensors are quantified within 20 min at room temperature using a multiplexable paper-based lateral flow assay. PATROL detects early-stage tumors in an autochthonous lung adenocarcinoma mouse model with high sensitivity and specificity. Tailoring the library of ABNs may enable not only the modular PATROL platform to lower the resource threshold for lung cancer early detection tools but also the rapid detection of chronic pulmonary disorders and infections.

CRISPR-Cas-mediated Multianalyte Synthetic Urine Biomarker Test for Portable Diagnostics.

Creating synthetic biomarkers for the development of precision diagnostics has enabled detection of disease through pathways beyond those used for traditional biofluid measurements. Synthetic biomarkers generally make use of reporters that provide readable signals in the biofluid to reflect the biochemical alterations in the local disease microenvironment during disease incidence and progression. The pharmacokinetic concentration of the reporters and biochemical amplification of the disease signal are paramount to achieving high sensitivity and specificity in a diagnostic test. Here, a cancer diagnostic platform is built using one format of synthetic biomarkers: activity-based nanosensors carrying chemically stabilized DNA reporters that can be liberated by aberrant proteolytic signatures in the tumor microenvironment. Synthetic DNA as a disease reporter affords multiplexing capability through its use as a barcode, allowing for the readout of multiple proteolytic signatures at once. DNA reporters released into the urine are detected using CRISPR nucleases via hybridization with CRISPR RNAs, which in turn produce a fluorescent or colorimetric signal upon enzyme activation. In this protocol, DNA-barcoded, activity-based nanosensors are constructed and their application is exemplified in a preclinical mouse model of metastatic colorectal cancer. This system is highly modifiable according to disease biology and generates multiple disease signals simultaneously, affording a comprehensive understanding of the disease characteristics through a minimally invasive process requiring only nanosensor administration, urine collection, and a paper test which enables point-of-care diagnostics.