Determining the toxicological effects of indoor air pollution on both a healthy and an inflammatory-comprised model of the alveolar epithelial barrier in vitro.

Exposure to indoor air pollutants (IAP) has increased recently, with people spending more time indoors (i.e. homes, offices, schools and transportation). Increased exposures of IAP on a healthy population are poorly understood, and those with allergic respiratory conditions even less so. The objective of this study, therefore, was to implement a well-characterised in vitro model of the human alveolar epithelial barrier (A549 + PMA differentiated THP-1 incubated with and without IL-13, IL-5 and IL-4) to determine the effects of a standardised indoor particulate (NIST 2583) on both a healthy lung model and one modelling a type-II (stimulated with IL-13, IL-5 and IL-4) inflammatory response (such as asthma).Using concentrations from the literature, and an environmentally appropriate exposure we investigated 232, 464 and 608ng/cm2 of NIST 2583 respectively. Membrane integrity (blue dextran), viability (trypan blue), genotoxicity (micronucleus (Mn) assay) and (pro-)/(anti-)inflammatory effects (IL-6, IL-8, IL-33, IL-10) were then assessed 24 h post exposure to both models. Models were exposed using a physiologically relevant aerosolisation method (VitroCell Cloud 12 exposure system).No changes in Mn frequency or membrane integrity in either model were noted when exposed to any of the tested concentrations of NIST 2583. A significant decrease (p < 0.05) in cell viability at the highest concentration was observed in the healthy model. Whilst cell viability in the "inflamed" model was decreased at the lower concentrations (significantly (p < 0.05) after 464ng/cm2). A significant reduction (p < 0.05) in IL-10 and a significant increase in IL-33 was seen after 24 h exposure to NIST 2583 (464, 608ng/cm2) in the "inflamed" model.Collectively, the results indicate the potential for IAP to cause the onset of a type II response as well as exacerbating pre-existing allergic conditions. Furthermore, the data imposes the importance of considering unhealthy individuals when investigating the potential health effects of IAP. It also highlights that even in a healthy population these particles have the potential to induce this type II response and initiate an immune response following exposure to IAP.

Analysis of Uncertainty and Sensitivity in Tailings Dam Breach-Runout Numerical Modelling.

Tailings dam breaches (TDBs) and subsequent flows can pose significant risk to public safety, the environment, and the economy. Numerical runout models are used to simulate potential tailings flows and understand their downstream impacts. Due to the complex nature of the breach-runout processes, the mobility and downstream impacts of these types of failures are highly uncertain. We applied the first-order second-moment (FOSM) methodology to a database of 11 back-analyzed historical tailings flows to evaluate uncertainties in TDB runout modelling and conducted a sensitivity analysis to identify key factors contributing to the variability of the HEC-RAS model output, including at different locations along the runout path. The results indicate that prioritizing resources toward advancements in estimating the values of primary contributors to the sensitivity of the selected model outputs is necessary for more reliable model results. We found that the total released volume is among the top contributors to the sensitivity of modelled inundation area and maximum flow depth, while surface roughness is among the top contributors to the sensitivity of modelled maximum flow velocity and flow front arrival time. However, the primary contributors to the sensitivity of the model outputs varied depending on the case study; therefore, the selection of appropriate rheological models and consideration of site-specific conditions are crucial for accurate predictions. The study proposes and demonstrates the FOSM methodology as an approximate probabilistic approach to model-based tailings flow runout prediction, which can help improve the accuracy of risk assessments and emergency response plans. Supplementary Information: The online version contains supplementary material available at 10.1007/s10230-024-00970-w.

Las roturas de presas de relaves (TDBs) y los flujos subsiguientes pueden suponer un riesgo significativo para la seguridad pública, el medio ambiente y la economía. Los modelos numéricos de desbordamiento se utilizan para simular posibles flujos de relaves y comprender su impacto aguas abajo. Debido a la naturaleza compleja de los procesos de rotura-desbordamiento, la movilidad y los impactos aguas abajo de este tipo de fallos tienen mucha incertidumbre. Se aplicó la metodología del segundo-momento de primer-orden (FOSM) a una base de datos de 11 flujos históricos de relaves analizados retrospectivamente para evaluar las incertidumbres en la modelización del desbordamiento de TDB y se realizó un análisis de sensibilidad para identificar los factores clave que contribuyen a la variabilidad de los resultados del modelo HEC-RAS, incluso en diferentes ubicaciones a lo largo de la trayectoria de fuga. Los resultados indican que es necesario priorizar los recursos hacia avances en la estimación de los valores de los principales contribuyentes a la sensibilidad de los resultados del modelo seleccionado para obtener resultados más fiables del modelo. El volumen total liberado se encuentra entre los principales contribuyentes a la sensibilidad del área de inundación modelizada y la profundidad máxima del flujo, mientras que la rugosidad de la superficie se encuentra entre los principales contribuyentes a la sensibilidad de la velocidad máxima del flujo modelizado y el tiempo de llegada del frente de flujo. Sin embargo, los principales factores que contribuyen a la sensibilidad de los resultados del modelo varían dependiendo del caso de estudio; por lo tanto, la selección de modelos reológicos apropiados y la consideración de las condiciones específicas del emplazamiento son cruciales para obtener predicciones precisas. El estudio propone y muestra la metodología FOSM como un enfoque probabilístico aproximado para la predicción de la extensión de flujos de relaves basada en modelos, que puede ayudar a mejorar la precisión de las evaluaciones de riesgos y los planes de respuesta a emergencias.

Adapting the in vitro micronucleus assay (OECD Test Guideline No. 487) for testing of manufactured nanomaterials: recommendations for best practices.

The current Organisation for Economic Co-Operation and Development test guideline number 487 (OECD TG No. 487) provides instruction on how to conduct the in vitro micronucleus assay. This assay is one of the gold standard approaches for measuring the mutagenicity of test items; however, it is directed at testing low molecular weight molecules and may not be appropriate for particulate materials (e.g. engineered nanoparticles [ENPs]). This study aimed to adapt the in vitro micronucleus assay for ENP testing and underpins the development of an OECD guidance document. A harmonized, nano-specific protocol was generated and evaluated by two independent laboratories. Cell lines utilized were human lymphoblastoid (TK6) cells, human liver hepatocytes (HepG2) cells, Chinese hamster lung fibroblast (V79) cells, whole blood, and buffy coat cells from healthy human volunteers. These cells were exposed to reference ENPs from the Joint Research Council (JRC): SiO2 (RLS-0102), Au5nm and Au30nm (RLS-03, RLS-010), CeO2 (NM212), and BaSO4 (NM220). Tungsten carbide-cobalt (WC/Co) was used as a trial particulate positive control. The chemical controls were positive in all cell cultures, but WC/Co was only positive in TK6 and buffy coat cells. In TK6 cells, mutagenicity was observed for SiO2- and both Au types. In HepG2 cells, Au5nm and SiO2 showed sub-two-fold increases in micronuclei. In V79 cells, whole blood, and buffy coat cells, no genotoxicity was detected with the test materials. The data confirmed that ENPs could be tested with the harmonized protocol, additionally, concordant data were observed across the two laboratories with V79 cells. WC/Co may be a suitable particulate positive control in the in vitro micronucleus assay when using TK6 and buffy coat cells. Detailed recommendations are therefore provided to adapt OECD TG No. 487 for testing ENP.

Maleimide-Thiol Linkages Alter the Biodistribution of SN38 Therapeutic Microbubbles Compared to Biotin-Avidin While Preserving Parity in Tumoral Drug Delivery.

Therapeutic microbubbles (thMBs) contain drug-filled liposomes linked to microbubbles and targeted to vascular proteins. Upon the application of a destructive ultrasound trigger, drug uptake to tumour is improved. However, the structure of thMBs currently uses powerful non-covalent bonding of biotin with avidin-based proteins to link both the liposome to the microbubble (MB) and to bind the targeting antibody to the liposome-MB complex. This linkage is not currently FDA-approved, and therefore, an alternative, maleimide-thiol linkage, that is currently used in antibody-drug conjugates was examined. In a systematic manner, vascular endothelial growth factor receptor 2 (VEGFR2)-targeted MBs and thMBs using both types of linkages were examined for their ability to specifically bind to VEGFR2 in vitro and for their ultrasound imaging properties in vivo. Both showed equivalence in the production of the thMB structure, in vitro specificity of binding and safety profiles. In vivo imaging showed subtle differences for thMBs where biotin thMBs had a faster wash-in rate than thiol thMBs, but thiol thMBs were longer-lived. The drug delivery to tumours was also equivalent, but interestingly, thiol thMBs altered the biodistribution of delivery away from the lungs and towards the liver compared to biotin thMBs, which is an improvement in biosafety.

Functional architecture of intracellular oscillations in hippocampal dendrites.

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions and report an advancing gradient of dendritic theta phase along the basal-tuft axis, then describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.

Selenium speciation studies in cancer patients to evaluate the responses of biomarkers of selenium status to different selenium compounds.

This work presents the first systematic comparison of selenium (Se) speciation in plasma from cancer patients treated orally with three Se compounds (sodium selenite, SS; L-selenomethionine, SeMet; or Se-methylselenocysteine, MSC) at 400 µg/day for 28 days. The primary goal was to investigate how these chemical forms of Se affect the plasma Se distribution, aiming to identify the most effective Se compound for optimal selenoprotein expression. This was achieved using methodology based on HPLC-ICP-MS after sample preparation/fractionation approaches. Measurements of total Se in plasma samples collected before and after 4 weeks of treatment showed that median total Se levels increased significantly from 89.6 to 126.4 µg kg-1 Se (p < 0.001), particularly when SeMet was administered (190.4 µg kg-1 Se). Speciation studies showed that the most critical differences between treated and baseline samples were seen for selenoprotein P (SELENOP) and selenoalbumin after administration with MSC (p = 5.8 × 10-4) and SeMet (p = 6.8 × 10-5), respectively. Notably, selenosugar-1 was detected in all low-molecular-weight plasma fractions following treatment, particularly with MSC. Two different chromatographic approaches and spiking experiments demonstrated that about 45% of that increase in SELENOP levels (to ~ 8.8 mg L-1) with SeMet is likely due to the non-specific incorporation of SeMet into the SELENOP affinity fraction. To the authors' knowledge, this has not been reported to date. Therefore, SELENOP is probably part of both the regulated (55%) and non-regulated (45%) Se pools after SeMet administration, whereas SS and MSC mainly contribute to the regulated one.

On-chip Raman spectroscopy of live single cells for the staging of oesophageal adenocarcinoma progression.

The absence of early diagnosis contributes to oesophageal cancer being the sixth most common cause of global cancer-associated deaths, with a 5-year survival rate of < 20%. Barrett's oesophagus is the main pre-cancerous condition to adenocarcinoma development, characterised by the morphological transition of oesophageal squamous epithelium to metaplastic columnar epithelium. Early tracking and treatment of oesophageal adenocarcinoma could dramatically improve with diagnosis and monitoring of patients with Barrett's Oesophagus. Current diagnostic methods involve invasive techniques such as endoscopies and, with only a few identified biomarkers of disease progression, the detection of oesophageal adenocarcinoma is costly and challenging. In this work, single-cell Raman spectroscopy was combined with microfluidic techniques to characterise the development of oesophageal adenocarcinoma through the progression of healthy epithelial, Barrett's oesophagus and oesophageal adenocarcinoma cell lines. Principal component analysis and linear discriminant analysis were used to classify the different stages of cancer progression. with the ability to differentiate between healthy and cancerous cells with an accuracy of 97%. Whilst the approach could also separate the dysplastic stages from healthy or cancer with high accuracy-the intra-class separation was approximately 68%. Overall, these results highlight the potential for rapid and reliable diagnostic/prognostic screening of Barrett's Oesophagus patients.

An In Vitro Model to Assess Early Immune Markers Following Co-Exposure of Epithelial Cells to Carbon Black (Nano)Particles in the Presence of S. aureus: A Role for Stressed Cells in Toxicological Testing.

The exposure of human lung and skin to carbon black (CB) is continuous due to its widespread applications. Current toxicological testing uses 'healthy' cellular systems; however, questions remain whether this mimics the everyday stresses that human cells are exposed to, including infection. Staphylococcus aureus lung and skin infections remain prevalent in society, and include pneumonia and atopic dermatitis, respectively, but current in vitro toxicological testing does not consider infection stress. Therefore, investigating the effects of CB co-exposure in 'stressed' infected epithelial cells in vitro may better approximate true toxicity. This work aims to study the impact of CB exposure during Staphylococcus aureus infection stress in A549 (lung) and HaCaT (skin) epithelial cells. Physicochemical characterisation of CB confirmed its dramatic polydispersity and potential to aggregate. CB significantly inhibited S. aureus growth in cell culture media. CB did not induce cytokines or antimicrobial peptides from lung and skin epithelial cells, when given alone, but did reduce HaCaT and A549 cell viability to 55% and 77%, respectively. In contrast, S. aureus induced a robust interleukin (IL)-8 response in both lung and skin epithelial cells. IL-6 and human beta defensin (hßD)-2 could only be detected when cells were stimulated with S. aureus with no decreases in cell viability. However, co-exposure to CB (100 µg/mL) and S. aureus resulted in significant inhibition of IL-8 (compared to S. aureus alone) without further reduction in cell viability. Furthermore, the same co-exposure induced significantly more hßD-2 (compared to S. aureus alone). This work confirms that toxicological testing in healthy versus stressed cells gives significantly different responses. This has significant implications for toxicological testing and suggests that cell stresses (including infection) should be included in current models to better represent the diversity of cell viabilities found in lung and skin within a general population. This model will have significant application when estimating CB exposure in at-risk groups, such as factory workers, the elderly, and the immunocompromised.

Modelling and breaking down the biophysical barriers to drug delivery in pancreatic cancer.

The pancreatic ductal adenocarcinoma (PDAC) stroma and its inherent biophysical barriers to drug delivery are central to therapeutic resistance. This makes PDAC the most prevalent pancreatic cancer with poor prognosis. The chemotherapeutic drug gemcitabine is used against various solid tumours, including pancreatic cancer, but with only a modest effect on patient survival. The growing PDAC tumour mass with high densities of cells and extracellular matrix (ECM) proteins, i.e., collagen, results in high interstitial pressure, leading to vasculature collapse and a dense, hypoxic, mechanically stiff stroma with reduced interstitial flow, critical to drug delivery to cells. Despite this, most drug studies are performed on cellular models that neglect these biophysical barriers to drug delivery. Microfluidic technology offers a promising platform to emulate tumour biophysical characteristics with appropriate flow conditions and transport dynamics. We present a microfluidic PDAC culture model, encompassing the disease's biophysical barriers to therapeutics, to evaluate the use of the angiotensin II receptor blocker losartan, which has been found to have matrix-depleting properties, on improving gemcitabine efficacy. PDAC cells were seeded into our 5-channel microfluidic device for a 21-day culture to mimic the rigid, collagenous PDAC stroma with reduced interstitial flow, which is critical to drug delivery to the cancer cells, and for assessment with gemcitabine and losartan treatment. With losartan, our culture matrix was more porous with less collagen, resulting in increased hydraulic conductivity of the culture interstitial space and improved gemcitabine effect. We demonstrate the importance of modelling tumour biophysical barriers to successfully assess new drugs and delivery methods.

Free-Standing Hierarchically Porous Silica Nanoparticle Superstructures: Bridging the Nano- to Microscale for Tailorable Delivery of Small and Large Therapeutics.

Nanoscale colloidal self-assembly is an exciting approach to yield superstructures with properties distinct from those of individual nanoparticles. However, the bottom-up self-assembly of 3D nanoparticle superstructures typically requires extensive chemical functionalization, harsh conditions, and a long preparation time, which are undesirable for biomedical applications. Here, we report the directional freezing of porous silica nanoparticles (PSiNPs) as a simple and versatile technique to create anisotropic 3D superstructures with hierarchical porosity afforded by microporous PSiNPs and newly generated meso- and macropores between the PSiNPs. By varying the PSiNP building block size, the interparticle pore sizes can be readily tuned. The newly created hierarchical pores greatly augment the loading of a small molecule-anticancer drug, doxorubicin (Dox), and a large macromolecule, lysozyme (Lyz). Importantly, Dox loading into both the micro- and meso/macropores of the nanoparticle assemblies not only gave a pore size-dependent drug release but also significantly extended the drug release to 25 days compared to a much shorter 7 or 11 day drug release from Dox loaded into either the micro- or meso/macropores only. Moreover, a unique temporal drug release profile, with a higher and faster release of Lyz from the larger interparticle macropores than Dox from the smaller PSiNP micropores, was observed. Finally, the formulation of the Dox-loaded superstructures within a composite hydrogel induces prolonged growth inhibition in a 3D spheroid model of pancreatic ductal adenocarcinoma. This study presents a facile modular approach for the rapid assembly of drug-loaded superstructures in fully aqueous environments and demonstrates their potential as highly tailorable and sustained delivery systems for diverse therapeutics.

The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic.

The COVID-19 pandemic has brought about valuable insights regarding models, data, and experiments. In this narrative review, we summarised the existing literature on these three themes, exploring the challenges of providing forecasts, the requirement for real-time linkage of health-related datasets, and the role of 'experimentation' in evaluating interventions. This literature review encourages us to broaden our perspective for the future, acknowledging the significance of investing in models, data, and experimentation, but also to invest in areas that are conceptually more abstract: the value of 'team science', the need for public trust in science, and in establishing processes for using science in policy. Policy-makers rely on model forecasts early in a pandemic when there is little data, and it is vital to communicate the assumptions, limitations, and uncertainties (theme 1). Linked routine data can provide critical information, for example, in establishing risk factors for adverse outcomes but are often not available quickly enough to make a real-time impact. The interoperability of data resources internationally is required to facilitate sharing across jurisdictions (theme 2). Randomised controlled trials (RCTs) provided timely evidence on the efficacy and safety of vaccinations and pharmaceuticals but were largely conducted in higher income countries, restricting generalisability to low- and middle-income countries (LMIC). Trials for non-pharmaceutical interventions (NPIs) were almost non-existent which was a missed opportunity (theme 3). Building on these themes from the narrative review, we underscore the importance of three other areas that need investment for effective evidence-driven policy-making. The COVID-19 response relied on strong multidisciplinary research infrastructures, but funders and academic institutions need to do more to incentivise team science (4). To enhance public trust in the use of scientific evidence for policy, researchers and policy-makers must work together to clearly communicate uncertainties in current evidence and any need to change policy as evidence evolves (5). Timely policy decisions require an established two-way process between scientists and policy makers to make the best use of evidence (6). For effective preparedness against future pandemics, it is essential to establish models, data, and experiments as fundamental pillars, complemented by efforts in planning and investment towards team science, public trust, and evidence-based policy-making across international communities. The paper concludes with a 'call to actions' for both policy-makers and researchers.

Comparative effectiveness of sotrovimab and molnupiravir for preventing severe COVID-19 outcomes in patients on kidney replacement therapy: observational study using the OpenSAFELY-UKRR and SRR databases.

Background: Due to limited inclusion of patients on kidney replacement therapy (KRT) in clinical trials, the effectiveness of coronavirus disease 2019 (COVID-19) therapies in this population remains unclear. We sought to address this by comparing the effectiveness of sotrovimab against molnupiravir, two commonly used treatments for non-hospitalised KRT patients with COVID-19 in the UK. Methods: With the approval of National Health Service England, we used routine clinical data from 24 million patients in England within the OpenSAFELY-TPP platform linked to the UK Renal Registry (UKRR) to identify patients on KRT. A Cox proportional hazards model was used to estimate hazard ratios (HRs) of sotrovimab versus molnupiravir with regards to COVID-19-related hospitalisations or deaths in the subsequent 28 days. We also conducted a complementary analysis using data from the Scottish Renal Registry (SRR). Results: Among the 2367 kidney patients treated with sotrovimab (n = 1852) or molnupiravir (n = 515) between 16 December 2021 and 1 August 2022 in England, 38 cases (1.6%) of COVID-19-related hospitalisations/deaths were observed. Sotrovimab was associated with substantially lower outcome risk than molnupiravir {adjusted HR 0.35 [95% confidence interval (CI) 0.17-0.71]; P = .004}, with results remaining robust in multiple sensitivity analyses. In the SRR cohort, sotrovimab showed a trend toward lower outcome risk than molnupiravir [HR 0.39 (95% CI 0.13-1.21); P = .106]. In both datasets, sotrovimab had no evidence of an association with other hospitalisation/death compared with molnupiravir (HRs ranged from 0.73 to 1.29; P > .05). Conclusions: In routine care of non-hospitalised patients with COVID-19 on KRT, sotrovimab was associated with a lower risk of severe COVID-19 outcomes compared with molnupiravir during Omicron waves.

Comparative effectiveness of nirmatrelvir/ritonavir versus sotrovimab and molnupiravir for preventing severe COVID-19 outcomes in non-hospitalised high-risk patients during Omicron waves: observational cohort study using the OpenSAFELY platform.

Background: Timely evidence of the comparative effectiveness between COVID-19 therapies in real-world settings is needed to inform clinical care. This study aimed to compare the effectiveness of nirmatrelvir/ritonavir versus sotrovimab and molnupiravir in preventing severe COVID-19 outcomes in non-hospitalised high-risk COVID-19 adult patients during Omicron waves. Methods: With the approval of NHS England, we conducted a real-world cohort study using the OpenSAFELY-TPP platform. Patient-level primary care data were obtained from 24 million people in England and were securely linked with data on COVID-19 infection and therapeutics, hospital admission, and death, covering a period where both nirmatrelvir/ritonavir and sotrovimab were first-line treatment options in community settings (February 10, 2022-November 27, 2022). Molnupiravir (third-line option) was used as an exploratory comparator to nirmatrelvir/ritonavir, both of which were antivirals. Cox proportional hazards model stratified by area was used to compare the risk of 28-day COVID-19 related hospitalisation/death across treatment groups. Findings: A total of 9026 eligible patients treated with nirmatrelvir/ritonavir (n = 5704) and sotrovimab (n = 3322) were included in the main analysis. The mean age was 52.7 (SD = 14.9) years and 93% (8436/9026) had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 55/9026 (0.61%) COVID-19 related hospitalisations/deaths were observed (34/5704 [0.60%] treated with nirmatrelvir/ritonavir and 21/3322 [0.63%] with sotrovimab). After adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, we observed no significant difference in outcome risk between nirmatrelvir/ritonavir and sotrovimab users (HR = 0.89, 95% CI: 0.48-1.63; P = 0.698). Results from propensity score weighted model also showed non-significant difference between treatment groups (HR = 0.82, 95% CI: 0.45-1.52; P = 0.535). The exploratory analysis comparing nirmatrelvir/ritonavir users with 1041 molnupiravir users (13/1041 [1.25%] COVID-19 related hospitalisations/deaths) showed an association in favour of nirmatrelvir/ritonavir (HR = 0.45, 95% CI: 0.22-0.94; P = 0.033). Interpretation: In routine care of non-hospitalised high-risk adult patients with COVID-19 in England, no substantial difference in the risk of severe COVID-19 outcomes was observed between those who received nirmatrelvir/ritonavir and sotrovimab between February and November 2022, when Omicron subvariants BA.2, BA.5, or BQ.1 were dominant. Funding: UK Research and Innovation, Wellcome Trust, UK Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.

Gold Nanotapes and Nanopinecones in a Quantitative Lateral Flow Assay for the Cancer Biomarker Carcinoembryonic Antigen.

Colorectal cancer is the third most common malignancy and the second leading cause of cancer death globally. Multiple studies have linked levels of carcinoembryonic antigen in patient serum to poor disease prognosis. Hence, the ability to detect low levels of carcinoembryonic antigen has applications in earlier disease diagnosis, assessment, and recurrence monitoring. Existing carcinoembryonic antigen detection methods often require multiple reagents, trained operators, or complex procedures. A method alleviating these issues is the lateral flow assay, a paper-based platform that allows the detection and quantification of target analytes in complex mixtures. The tests are rapid, are point-of-care, possess a long shelf life, and can be stored at ambient conditions, making them ideal for use in a range of settings. Although lateral flow assays typically use spherical gold nanoparticles to generate the classic red signal, recent literature has shown that alternate morphologies to spheres can improve the limit of detection. In this work, we report the application of alternative gold nanoparticle morphologies, gold nanotapes (∼35 nm in length) and gold nanopinecones (∼90 nm in diameter), in a lateral flow assay for carcinoembryonic antigen. In a comparative assay, gold nanopinecones exhibited a ∼2× improvement in the limit of detection compared to commercially available spherical gold nanoparticles for the same antibody loading and total gold content, whereas the number of gold nanopinecones in each test was ∼3.2× less. In the fully optimized test, a limit of detection of 14.4 pg/mL was obtained using the gold nanopinecones, representing a 24-fold improvement over the previously reported gold-nanoparticle-based carcinoembryonic antigen lateral flow assay.

Association Between Fluoroquinolone Use and Hospitalization With Aortic Aneurysm or Aortic Dissection.

Importance: Fluoroquinolone use has been associated with increased hospitalization with aortic aneurysm or dissection in noninterventional studies, but the reason for this observed association is unclear. Objective: To determine the association between fluoroquinolone use and aortic aneurysm or dissection using multiple study designs and multiple databases to increase the robustness of findings. Design, Setting, and Participants: Cohort and case-crossover studies were conducted separately in 2 databases of UK primary care records. Clinical Practice Research Datalink Aurum and GOLD primary care records were linked to hospital admissions data. Adults with a systemic fluoroquinolone or cephalosporin prescription between April 1997 and December 2019 were included in the cohort study. Adults hospitalized with aortic aneurysm or dissection within the eligibility period were included in the case-crossover study. Individuals meeting inclusion criteria in the case-crossover study were matched 1:3 to control individuals on age, sex, index date, and clinical practice to adjust for calendar trends in prescribing. Data were analyzed from January to July 2022. Exposures: Systemic fluoroquinolone or comparator antibiotic. Main Outcomes and Measures: Hazard ratios (HRs) were estimated in the cohort study for the association between prescription of fluoroquinolones and hospitalization with aortic aneurysm or dissection using stabilized inverse probability of treatment-weighted Cox regression. Odds ratios (OR) were estimated in the case-crossover study for the association between systemic fluoroquinolone use and hospitalization with aortic aneurysm or dissection using a conditional logistic regression model. Estimates were pooled across databases using fixed-effects meta-analysis. Results: In the cohort study, we identified 3 134 121 adults in Aurum (mean [SD] age, 52.5 [20.3] years; 1 969 257 [62.8%] female) and 452 086 in GOLD (mean [SD] age, 53.9 [20.2] years; 286 502 [63.4%] female) who were prescribed fluoroquinolones or cephalosporins. In crude analyses, fluoroquinolone relative to cephalosporin use was associated with increased hospitalization with aortic aneurysm or dissection (pooled HR, 1.28; 95% CI, 1.13-1.44; P < .001) but after adjustment for potential confounders, this association disappeared (pooled adjusted HR, 1.03; 95% CI, 0.91-1.17; P = .65). In the case-crossover study, we identified 84 841 individuals hospitalized with aortic aneurysm or dissection in Aurum (mean [SD] age, 75.5 [10.9]; 23 551 [27.8%] female) and 10 357 in GOLD (mean [SD] age, 75.6 [10.5]; 2809 [27.1%] female). Relative to nonuse, fluoroquinolone use was associated with an increase in hospitalization with aortic aneurysm or dissection, but no association was found relative to other antibiotics (vs cephalosporin pooled OR, 1.05; 95% CI, 0.87-1.27; vs trimethoprim, 0.89; 95% CI, 0.75-1.06; vs co-amoxiclav, 0.98; 95% CI, 0.82-1.18). Conclusions and Relevance: The results in this study suggest that estimates of association of fluoroquinolones with aortic aneurysm or dissection may be affected by confounding. When such confounding is accounted for, no association was evident, providing reassurance on the safety of fluoroquinolones with respect to aortic aneurysm or dissection.

Ultra-stable liquid crystal droplets coated by sustainable plant-based materials for optical sensing of chemical and biological analytes.

Herein, we demonstrate for the first time the synthesis of ultra-stable, spherical, nematic liquid crystal (LC) droplets of narrow size polydispersity coated by sustainable, biodegradable, plant-based materials that trigger a typical bipolar-to-radial configurational transition in dynamic response to chemical and biological analytes. Specifically, a highly soluble polymer, potato protein (PoP) and a physically-crosslinked potato protein microgel (PoPM) of ∼100 nm in diameter, prepared from the PoP, a byproduct of the starch industry, were compared for their ability to coat LC droplets. Although both PoP and PoPM were capable of reducing the interfacial tension between water and n-tetradecane <30 mN m-1, PoPM-coated LC droplets showed better stability than the PoP-coated droplets via a Pickering-like mechanism. Strikingly, the Pickering LC droplets outperformed PoP-stabilized droplets in terms of dynamic response with 5× lower detection limit to model chemical analytes (sodium dodecyl sulphate, SDS) due to the difference in SDS-binding features between the protein and the microgel. To eliminate the effect of size polydispersity on the response, monodisperse Pickering LC droplets of diameter ∼16 µm were additionally obtained using microfluidics, which mirrored the response to chemical as well as biological analytes, i.e., primary bile acid, an important biomarker of liver diseases. We demonstrate that these eco-friendly microgels used for creating monodisperse, ultra-stable, LC complex colloids are powerful templates for fabricating next generation, sustainable optical sensors for early diagnosis in clinical settings and other sensing applications.

Challenges in Estimating the Effectiveness of COVID-19 Vaccination Using Observational Data.

The COVID-19 vaccines were developed and rigorously evaluated in randomized trials during 2020. However, important questions, such as the magnitude and duration of protection, their effectiveness against new virus variants, and the effectiveness of booster vaccination, could not be answered by randomized trials and have therefore been addressed in observational studies. Analyses of observational data can be biased because of confounding and because of inadequate design that does not consider the evolution of the pandemic over time and the rapid uptake of vaccination. Emulating a hypothetical "target trial" using observational data assembled during vaccine rollouts can help manage such potential sources of bias. This article describes 2 approaches to target trial emulation. In the sequential approach, on each day, eligible persons who have not yet been vaccinated are matched to a vaccinated person. The single-trial approach sets a single baseline at the start of the rollout and considers vaccination as a time-varying variable. The nature of the confounding depends on the analysis strategy: Estimating "per-protocol" effects (accounting for vaccination of initially unvaccinated persons after baseline) may require adjustment for both baseline and "time-varying" confounders. These issues are illustrated by using observational data from 2 780 931 persons in the United Kingdom aged 70 years or older to estimate the effect of a first dose of a COVID-19 vaccine. Addressing the issues discussed in this article should help authors of observational studies provide robust evidence to guide clinical and policy decisions.

Considerations for unblinding individual study participants during vaccine trials.

Premature unblinding of individual participants is rarely reported in publications, but such unblinding can disrupt vaccine trials by causing worry and drop-out of other participants or "pseudo unblinding," in which participants or investigators over-interpret certain symptoms as being related to receiving an investigational product. This review summarizes appropriate reasons for unblinding in vaccine trials. Regulatory guidance could be improved by distinguishing guidance for vaccine trials from drug trials, with the recognition that unblinding individual participants in vaccine studies is rarely needed for management of adverse events following immunization.

Changes in COVID-19-related mortality across key demographic and clinical subgroups in England from 2020 to 2022: a retrospective cohort study using the OpenSAFELY platform.

BACKGROUND: COVID-19 has been shown to differently affect various demographic and clinical population subgroups. We aimed to describe trends in absolute and relative COVID-19-related mortality risks across clinical and demographic population subgroups during successive SARS-CoV-2 pandemic waves. METHODS: We did a retrospective cohort study in England using the OpenSAFELY platform with the approval of National Health Service England, covering the first five SARS-CoV-2 pandemic waves (wave one [wild-type] from March 23 to May 30, 2020; wave two [alpha (B.1.1.7)] from Sept 7, 2020, to April 24, 2021; wave three [delta (B.1.617.2)] from May 28 to Dec 14, 2021; wave four [omicron (B.1.1.529)] from Dec 15, 2021, to April 29, 2022; and wave five [omicron] from June 24 to Aug 3, 2022). In each wave, we included people aged 18-110 years who were registered with a general practice on the first day of the wave and who had at least 3 months of continuous general practice registration up to this date. We estimated crude and sex-standardised and age-standardised wave-specific COVID-19-related death rates and relative risks of COVID-19-related death in population subgroups. FINDINGS: 18 895 870 adults were included in wave one, 19 014 720 in wave two, 18 932 050 in wave three, 19 097 970 in wave four, and 19 226 475 in wave five. Crude COVID-19-related death rates per 1000 person-years decreased from 4·48 deaths (95% CI 4·41-4·55) in wave one to 2·69 (2·66-2·72) in wave two, 0·64 (0·63-0·66) in wave three, 1·01 (0·99-1·03) in wave four, and 0·67 (0·64-0·71) in wave five. In wave one, the standardised COVID-19-related death rates were highest in people aged 80 years or older, people with chronic kidney disease stage 5 or 4, people receiving dialysis, people with dementia or learning disability, and people who had received a kidney transplant (ranging from 19·85 deaths per 1000 person-years to 44·41 deaths per 1000 person-years, compared with from 0·05 deaths per 1000 person-years to 15·93 deaths per 1000 person-years in other subgroups). In wave two compared with wave one, in a largely unvaccinated population, the decrease in COVID-19-related mortality was evenly distributed across population subgroups. In wave three compared with wave one, larger decreases in COVID-19-related death rates were seen in groups prioritised for primary SARS-CoV-2 vaccination, including people aged 80 years or older and people with neurological disease, learning disability, or severe mental illness (90-91% decrease). Conversely, smaller decreases in COVID-19-related death rates were observed in younger age groups, people who had received organ transplants, and people with chronic kidney disease, haematological malignancies, or immunosuppressive conditions (0-25% decrease). In wave four compared with wave one, the decrease in COVID-19-related death rates was smaller in groups with lower vaccination coverage (including younger age groups) and conditions associated with impaired vaccine response, including people who had received organ transplants and people with immunosuppressive conditions (26-61% decrease). INTERPRETATION: There was a substantial decrease in absolute COVID-19-related death rates over time in the overall population, but demographic and clinical relative risk profiles persisted and worsened for people with lower vaccination coverage or impaired immune response. Our findings provide an evidence base to inform UK public health policy for protecting these vulnerable population subgroups. FUNDING: UK Research and Innovation, Wellcome Trust, UK Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.