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.

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.

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.

Marburg virus disease outbreaks, mathematical models, and disease parameters: a systematic review.

The 2023 Marburg virus disease outbreaks in Equatorial Guinea and Tanzania highlighted the importance of better understanding this lethal pathogen. We did a systematic review (PROSPERO CRD42023393345) of peer-reviewed articles reporting historical outbreaks, modelling studies, and epidemiological parameters focused on Marburg virus disease. We searched PubMed and Web of Science from database inception to March 31, 2023. Two reviewers evaluated all titles and abstracts with consensus-based decision making. To ensure agreement, 13 (31%) of 42 studies were double-extracted and a custom-designed quality assessment questionnaire was used for risk of bias assessment. We present detailed information on 478 reported cases and 385 deaths from Marburg virus disease. Analysis of historical outbreaks and seroprevalence estimates suggests the possibility of undetected Marburg virus disease outbreaks, asymptomatic transmission, or cross-reactivity with other pathogens, or a combination of these. Only one study presented a mathematical model of Marburg virus transmission. We estimate an unadjusted, pooled total random effect case fatality ratio of 61·9% (95% CI 38·8-80·6; I2=93%). We identify epidemiological parameters relating to transmission and natural history, for which there are few estimates. This systematic review and the accompanying database provide a comprehensive overview of Marburg virus disease epidemiology and identify key knowledge gaps, contributing crucial information for mathematical models to support future Marburg virus disease epidemic responses.

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.

Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts.

Since 8th March 2020 up to the time of writing, we have been producing near real-time weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for all countries with evidence of sustained transmission, shared online. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. Here we present a retrospective evaluation of the forecasts produced between 8th March to 29th November 2020 for 81 countries. We evaluated the robustness of the forecasts produced in real-time using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3% and 45.6% of the observations lying in the 50% Credible Interval in 1-week and 4-week ahead forecasts respectively. The retrospective evaluation of our models shows that simple transmission models calibrated using routine disease surveillance data can reliably capture the epidemic trajectory in multiple countries. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures.

Enhancing the immunogenicity of lipid-nanoparticle mRNA vaccines by adjuvanting the ionizable lipid and the mRNA.

To elicit optimal immune responses, messenger RNA vaccines require intracellular delivery of the mRNA and the careful use of adjuvants. Here we report a multiply adjuvanted mRNA vaccine consisting of lipid nanoparticles encapsulating an mRNA-encoded antigen, optimized for efficient mRNA delivery and for the enhanced activation of innate and adaptive responses. We optimized the vaccine by screening a library of 480 biodegradable ionizable lipids with headgroups adjuvanted with cyclic amines and by adjuvanting the mRNA-encoded antigen by fusing it with a natural adjuvant derived from the C3 complement protein. In mice, intramuscular or intranasal administration of nanoparticles with the lead ionizable lipid and with mRNA encoding for the fusion protein (either the spike protein or the receptor-binding domain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) increased the titres of antibodies against SARS-CoV-2 tenfold with respect to the vaccine encoding for the unadjuvanted antigen. Multiply adjuvanted mRNA vaccines may improve the efficacy, safety and ease of administration of mRNA-based immunization.

Extending EpiEstim to estimate the transmission advantage of pathogen variants in real-time: SARS-CoV-2 as a case-study.

The evolution of SARS-CoV-2 has demonstrated that emerging variants can set back the global COVID-19 response. The ability to rapidly assess the threat of new variants is critical for timely optimisation of control strategies. We present a novel method to estimate the effective transmission advantage of a new variant compared to a reference variant combining information across multiple locations and over time. Through an extensive simulation study designed to mimic real-time epidemic contexts, we show that our method performs well across a range of scenarios and provide guidance on its optimal use and interpretation of results. We also provide an open-source software implementation of our method. The computational speed of our tool enables users to rapidly explore spatial and temporal variations in the estimated transmission advantage. We estimate that the SARS-CoV-2 Alpha variant is 1.46 (95% Credible Interval 1.44-1.47) and 1.29 (95% CrI 1.29-1.30) times more transmissible than the wild type, using data from England and France respectively. We further estimate that Delta is 1.77 (95% CrI 1.69-1.85) times more transmissible than Alpha (England data). Our approach can be used as an important first step towards quantifying the threat of emerging or co-circulating variants of infectious pathogens in real-time.

Obesity Represents a Persisting Health Issue in Axial Spondyloarthritis, Particularly Affecting Socially Disadvantaged Patients.

OBJECTIVE: Obesity is an important comorbidity in axial spondyloarthritis (axSpA); however, the prevalence of obesity in axSpA compared with the general population and associated socioeconomic factors remain unknown. METHODS: This repeated cross-sectional study compared BMI (kg/m2) groups of patients with axSpA to the Swiss population at 3 timepoints (2007, 2012, and 2017). BMI categories were compared by different age, sex, and education categories using the chi-square goodness of fit test. Unpaired, 1-sided t tests were used to compare the BMI in patients with axSpA between the different timepoints. RESULTS: Compared to the general population, patients with axSpA had a higher proportion of overweight and obesity: 18.9% of all patients with axSpA were obese, compared to 11.3% of the Swiss population in 2017. Comparison of BMI groups within sex, age, and education groups consistently showed a trend toward higher rates of overweight and obesity in axSpA. Further, patients with axSpA, especially females, showed a trend of increasing BMI over the studied 10 years. At every time point, overweight and obese patients were significantly more likely to be male, were older, and had higher disease activity than patients with normal weight. Obesity was associated with a deprived socioeconomic status as indicated by a higher proportion of patients with manual labor jobs and lower levels of education. CONCLUSION: The prevalence of obesity was significantly higher among patients with axSpA compared to the Swiss population, with socially disadvantaged individuals being the most affected. There is an urgent need to initiate prevention strategies for obesity in patients with axSpA.

Adipose tissue and skeletal muscle wasting precede clinical diagnosis of pancreatic cancer.

Patients with pancreatic cancer commonly develop weight loss and muscle wasting. Whether adipose tissue and skeletal muscle losses begin before diagnosis and the potential utility of such losses for earlier cancer detection are not well understood. We quantify skeletal muscle and adipose tissue areas from computed tomography (CT) imaging obtained 2 months to 5 years before cancer diagnosis in 714 pancreatic cancer cases and 1748 matched controls. Adipose tissue loss is identified up to 6 months, and skeletal muscle wasting is identified up to 18 months before the clinical diagnosis of pancreatic cancer and is not present in the matched control population. Tissue losses are of similar magnitude in cases diagnosed with localized compared with metastatic disease and are not correlated with at-diagnosis circulating levels of CA19-9. Skeletal muscle wasting occurs in the 1-2 years before pancreatic cancer diagnosis and may signal an upcoming diagnosis of pancreatic cancer.

Lessons from COVID-19 for rescalable data collection.

Novel data and analyses have had an important role in informing the public health response to the COVID-19 pandemic. Existing surveillance systems were scaled up, and in some instances new systems were developed to meet the challenges posed by the magnitude of the pandemic. We describe the routine and novel data that were used to address urgent public health questions during the pandemic, underscore the challenges in sustainability and equity in data generation, and highlight key lessons learnt for designing scalable data collection systems to support decision making during a public health crisis. As countries emerge from the acute phase of the pandemic, COVID-19 surveillance systems are being scaled down. However, SARS-CoV-2 resurgence remains a threat to global health security; therefore, a minimal cost-effective system needs to remain active that can be rapidly scaled up if necessary. We propose that a retrospective evaluation to identify the cost-benefit profile of the various data streams collected during the pandemic should be on the scientific research agenda.

Increasing emergency number utilisation is not driven by low-acuity calls: an observational study of 1.5 million emergency calls (2018-2021) from Berlin.

BACKGROUND: The Emergency Medical Service (EMS) in Germany is increasingly challenged by strongly rising demand. Speculations about a greater utilisation for minor cases have led to intensive media coverage, but empirical evidence is lacking. We investigated the development of low-acuity calls from 2018 to 2021 in the federal state of Berlin and its correlations with sociodemographic characteristics. METHODS: We analysed over 1.5 million call documentations including medical dispatch codes, age, location and time using descriptive and inferential statistics and multivariate binary logistic regression. We defined a code list to classify low-acuity calls and merged the dataset with sociodemographic indicators and data on population density. RESULTS: The number of emergency calls (phone number 112 in Germany) increased by 9.1% from 2018 to 2021; however, the proportion of low-acuity calls did not increase. The regression model shows higher odds of low-acuity for young to medium age groups (especially for age 0-9, OR 1.50 [95% CI 1.45-1.55]; age 10-19, OR 1.77 [95% CI 1.71-1.83]; age 20-29, OR 1.64 [95% CI 1.59-1.68] and age 30-39, OR 1.40 [95% CI 1.37-1.44]; p < 0.001, reference group 80-89) and for females (OR 1.12 [95% CI 1.1-1.13], p < 0.001). Odds were slightly higher for calls from a neighbourhood with lower social status (OR 1.01 per index unit increase [95% CI 1.0-1.01], p < 0.05) and at the weekend (OR 1.02 [95% CI 1.0-1.04, p < 0.05]). No significant association of the call volume with population density was detected. CONCLUSIONS: This analysis provides valuable new insights into pre-hospital emergency care. Low-acuity calls were not the primary driver of increased EMS utilisation in Berlin. Younger age is the strongest predictor for low-acuity calls in the model. The association with female gender is significant, while socially deprived neighbourhoods play a minor role. No statistically significant differences in call volume between densely and less densely populated regions were detected. The results can inform the EMS in future resource planning.

CRISPR-Cas-amplified urinary biomarkers for multiplexed and portable cancer diagnostics.

Synthetic biomarkers, bioengineered sensors that generate molecular reporters in diseased microenvironments, represent an emerging paradigm in precision diagnostics. Despite the utility of DNA barcodes as a multiplexing tool, their susceptibility to nucleases in vivo has limited their utility. Here we exploit chemically stabilized nucleic acids to multiplex synthetic biomarkers and produce diagnostic signals in biofluids that can be 'read out' via CRISPR nucleases. The strategy relies on microenvironmental endopeptidase to trigger the release of nucleic acid barcodes and polymerase-amplification-free, CRISPR-Cas-mediated barcode detection in unprocessed urine. Our data suggest that DNA-encoded nanosensors can non-invasively detect and differentiate disease states in transplanted and autochthonous murine cancer models. We also demonstrate that CRISPR-Cas amplification can be harnessed to convert the readout to a point-of-care paper diagnostic tool. Finally, we employ a microfluidic platform for densely multiplexed, CRISPR-mediated DNA barcode readout that can potentially evaluate complex human diseases rapidly and guide therapeutic decisions.

Gaps in mobility data and implications for modelling epidemic spread: A scoping review and simulation study.

Reliable estimates of human mobility are important for understanding the spatial spread of infectious diseases and the effective targeting of control measures. However, when modelling infectious disease dynamics, data on human mobility at an appropriate temporal or spatial resolution are not always available, leading to the common use of model-derived mobility proxies. In this study we reviewed the different data sources and mobility models that have been used to characterise human movement in Africa. We then conducted a simulation study to better understand the implications of using human mobility proxies when predicting the spatial spread and dynamics of infectious diseases. We found major gaps in the availability of empirical measures of human mobility in Africa, leading to mobility proxies being used in place of data. Empirical data on subnational mobility were only available for 17/54 countries, and in most instances, these data characterised long-term movement patterns, which were unsuitable for modelling the spread of pathogens with short generation times (time between infection of a case and their infector). Results from our simulation study demonstrated that using mobility proxies can have a substantial impact on the predicted epidemic dynamics, with complex and non-intuitive biases. In particular, the predicted times and order of epidemic invasion, and the time of epidemic peak in different locations can be underestimated or overestimated, depending on the types of proxies used and the country of interest. Our work underscores the need for regularly updated empirical measures of population movement within and between countries to aid the prevention and control of infectious disease outbreaks. At the same time, there is a need to establish an evidence base to help understand which types of mobility data are most appropriate for describing the spread of emerging infectious diseases in different settings.

An intravenous DNA-binding priming agent protects cell-free DNA and improves the sensitivity of liquid biopsies.

Blood-based, or "liquid," biopsies enable minimally invasive diagnostics but have limits on sensitivity due to scarce cell-free DNA (cfDNA). Improvements to sensitivity have primarily relied on enhancing sequencing technology ex vivo . Here, we sought to augment the level of circulating tumor DNA (ctDNA) detected in a blood draw by attenuating the clearance of cfDNA in vivo . We report a first-in-class intravenous DNA-binding priming agent given 2 hours prior to a blood draw to recover more cfDNA. The DNA-binding antibody minimizes nuclease digestion and organ uptake of cfDNA, decreasing its clearance at 1 hour by over 150-fold. To improve plasma persistence and limit potential immune interactions, we abrogated its Fc-effector function. We found that it protects GC-rich sequences and DNase-hypersensitive sites, which are ordinarily underrepresented in cfDNA. In tumor-bearing mice, priming improved tumor DNA recovery by 19-fold and sensitivity for detecting cancer from 6% to 84%. These results suggest a novel method to enhance the sensitivity of existing DNA-based cancer testing using blood biopsies.

A nanoparticle priming agent reduces cellular uptake of cell-free DNA and enhances the sensitivity of liquid biopsies.

Liquid biopsies are enabling minimally invasive monitoring and molecular profiling of diseases across medicine, but their sensitivity remains limited by the scarcity of cell-free DNA (cfDNA) in blood. Here, we report an intravenous priming agent that is given prior to a blood draw to increase the abundance of cfDNA in circulation. Our priming agent consists of nanoparticles that act on the cells responsible for cfDNA clearance to slow down cfDNA uptake. In tumor-bearing mice, this agent increases the recovery of circulating tumor DNA (ctDNA) by up to 60-fold and improves the sensitivity of a ctDNA diagnostic assay from 0% to 75% at low tumor burden. We envision that this priming approach will significantly improve the performance of liquid biopsies across a wide range of clinical applications in oncology and beyond.

Low protease activity in B cell follicles promotes retention of intact antigens after immunization.

The structural integrity of vaccine antigens is critical to the generation of protective antibody responses, but the impact of protease activity on vaccination in vivo is poorly understood. We characterized protease activity in lymph nodes and found that antigens were rapidly degraded in the subcapsular sinus, paracortex, and interfollicular regions, whereas low protease activity and antigen degradation rates were detected in the vicinity of follicular dendritic cells (FDCs). Correlated with these findings, immunization regimens designed to target antigen to FDCs led to germinal centers dominantly targeting intact antigen, whereas traditional immunizations led to much weaker responses that equally targeted the intact immunogen and antigen breakdown products. Thus, spatially compartmentalized antigen proteolysis affects humoral immunity and can be exploited.