Dynamic SARS-CoV-2 surveillance model combining seroprevalence and wastewater concentrations for post-vaccine disease burden estimates

BACKGROUND

Despite wide scale assessments, it remains unclear how large-scale severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination affected the wastewater concentration of the virus or the overall disease burden as measured by hospitalization rates.

METHODS

We used weekly SARS-CoV-2 wastewater concentration with a stratified random sampling of seroprevalence, and linked vaccination and hospitalization data, from April 2021-August 2021 in Jefferson County, Kentucky (USA). Our susceptible ( S ), vaccinated ( V ), variant-specific infected (I 1 andI 2 ), recovered ( R ), and seropositive ( T ) model ( S V I 2 R T ) tracked prevalence longitudinally. This was related to wastewater concentration.

RESULTS

Here we show the 64% county vaccination rate translate into about a 61% decrease in SARS-CoV-2 incidence. The estimated effect of SARS-CoV-2 Delta variant emergence is a 24-fold increase of infection counts, which correspond to an over 9-fold increase in wastewater concentration. Hospitalization burden and wastewater concentration have the strongest correlation (r = 0.95) at 1 week lag.

CONCLUSIONS

Our study underscores the importance of continuing environmental surveillance post-vaccine and provides a proof-of-concept for environmental epidemiology monitoring of infectious disease for future pandemic preparedness.

Wastewater and seroprevalence for pandemic preparedness: variant analysis, vaccination effect, and hospitalization forecasting for SARS-CoV-2, in Jefferson County, Kentucky

Despite wide scale assessments, it remains unclear how large-scale SARS-CoV-2 vaccination affected the wastewater concentration of the virus or the overall disease burden as measured by hospitalization rates. We used weekly SARS-CoV-2 wastewater concentration with a stratified random sampling of seroprevalence, and linked vaccination and hospitalization data, from April 2021-August 2021 in Jefferson County, Kentucky (USA). Our susceptible (S), vaccinated (V), variant-specific infected (I_1 and I_2), recovered (R), and seropositive (T) model (SVI_2 RT) tracked prevalence longitudinally. This was related to wastewater concentration. The 64% county vaccination rate translated into about 61% decrease in SARS-CoV-2 incidence. The estimated effect of SARS-CoV-2 Delta variant emergence was a 24-fold increase of infection counts, which corresponded to an over 9-fold increase in wastewater concentration. Hospitalization burden and wastewater concentration had the strongest correlation (r = 0.95) at 1 week lag. Our study underscores the importance of continued environmental surveillance post-vaccine and provides a proof-of-concept for environmental epidemiology monitoring of infectious disease for future pandemic preparedness.

Inferring delays in partially observed gene regulation processes

MOTIVATION

Cell function is regulated by gene regulatory networks (GRNs) defined by protein-mediated interaction between constituent genes. Despite advances in experimental techniques, we can still measure only a fraction of the processes that govern GRN dynamics. To infer the properties of GRNs using partial observation, unobserved sequential processes can be replaced with distributed time delays, yielding non-Markovian models. Inference methods based on the resulting model suffer from the curse of dimensionality.

RESULTS

We develop a simulation-based Bayesian MCMC method employing an approximate likelihood for the efficient and accurate inference of GRN parameters when only some of their products are observed. We illustrate our approach using a two-step activation model: an activation signal leads to the accumulation of an unobserved regulatory protein, which triggers the expression of observed fluorescent proteins. With prior information about observed fluorescent protein synthesis, our method successfully infers the dynamics of the unobserved regulatory protein. We can estimate the delay and kinetic parameters characterizing target regulation including transcription, translation, and target searching of an unobserved protein from experimental measurements of the products of its target gene. Our method is scalable and can be used to analyze non-Markovian models with hidden components.

AVAILABILITY AND IMPLEMENTATION

Our code is implemented in R and is freely available with a simple example data at https://github.com/Mathbiomed/SimMCMC.

Balancing Quality and Efficiency of Head and Neck Contour Revision for Online Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

The number of target and organs-at-risk (OAR) structures requiring contours is a barrier to online adaptive radiotherapy (oART) implementation for head and neck (H&N) cancer. In sharing our experience utilizing a cone beam CT-based oART system featuring automatic contours, we analyzed the system's clinical performance and the dosimetric benefits of human supervision to investigate the optimal balance between contour editing and plan quality.

MATERIALS/METHODS

We analyzed 44 H&N patients and 349 adaptive fractions treated on the oART system. The unsupervised (automatically generated) and supervised (edited by clinicians) target and OAR contours as well as the corresponding adaptive plans were acquired. Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD) used to assess the geometric extent of contour supervision. We mapped the clinically treated adaptive plan to the unsupervised contours to quantify the dosimetric effect of the contour edits, and the adaptive plan optimized from the unsupervised contours to the supervised contours to simulate an unsupervised workflow.

RESULTS

The targets were edited in >80.7% of the sessions, with the most changes seen in the primary GTV (DSC = 0.86 ± 0.09 and HD = 2.77 ± 1.58 mm) and the least in the nodal CTV (DSC = 0.92 ± 0.06, HD = 2.29 ± 1.49 mm). Among OARs, oral cavity was the most frequently edited (49.0%) and brainstem the least (2.2%). In general, OAR edits were minor (mean DSC > 0.95 with std Dosimetric quantification of the edits (Table 1) showed that while the unsupervised targets resulted in significant coverage loss, the change in unsupervised OAR dose was not as pronounced, with 81.5-96.8% still meeting the preplan constraints. Edits corresponding to major dose changes were mostly adjacent to or inside targets. The unsupervised workflow underdosed the targets and overdosed the OARs, and therefore is not recommended.

CONCLUSION

While target contours needed physician supervision in H&N oART, edits to automatic OAR contours were minor. An alternative contour workflow could be adopted to focus on the targets and reduce time spent on the OARs. For OAR close to or overlapping with the targets, strategic cropping could potentially minimize time for editing and improve the robustness of the adapted plan quality.

Household environment and animal fecal contamination are critical modifiers of the gut microbiome and resistome in young children from rural Nicaragua

BACKGROUND

Early life plays a vital role in the development of the gut microbiome and subsequent health. While many factors that shape the gut microbiome have been described, including delivery mode, breastfeeding, and antibiotic use, the role of household environments is still unclear. Furthermore, the development of the gut antimicrobial resistome and its role in health and disease is not well characterized, particularly in settings with water insecurity and less sanitation infrastructure.

RESULTS

This study investigated the gut microbiome and resistome of infants and young children (ages 4 days-6 years) in rural Nicaragua using Oxford Nanopore Technology's MinION long-read sequencing. Differences in gut microbiome diversity and antibiotic resistance gene (ARG) abundance were examined for associations with host factors (age, sex, height for age z-score, weight for height z-score, delivery mode, breastfeeding habits) and household environmental factors (animals inside the home, coliforms in drinking water, enteric pathogens in household floors, fecal microbial source tracking markers in household floors). We identified anticipated associations of higher gut microbiome diversity with participant age and vaginal delivery. However, novel to this study were the significant, positive associations between ruminant and dog fecal contamination of household floors and gut microbiome diversity. We also identified greater abundance of potential pathogens in the gut microbiomes of participants with higher fecal contamination on their household floors. Path analysis revealed that water quality and household floor contamination independently and significantly influenced gut microbiome diversity when controlling for age. These gut microbiome contained diverse resistome, dominated by multidrug, tetracycline, macrolide/lincosamide/streptogramin, and beta-lactam resistance. We found that the abundance of ARGs in the gut decreased with age. The bacterial hosts of ARGs were mainly from the family Enterobacteriaceae, particularly Escherichia coli.

CONCLUSIONS

This study identified the role of household environmental contamination in the developing gut microbiome and resistome of young children and infants with a One Health perspective. We found significant relationships between host age, gut microbiome diversity, and the resistome. Understanding the impact of the household environment on the development of the resistome and microbiome in early life is essential to optimize the relationship between environmental exposure and human health. Video Abstract.

Disposable versus reusable fibre-optic nasendoscopes: a national survey of UK ENT surgical trainees and a single-centre cost-analysis

BACKGROUND

This study primarily assessed ENT surgical trainees' preferences for the qualities of disposable and reusable fibre-optic nasendoscopes. Secondary aims included eliciting trainees' views on ENT surgery and climate change, and creating a single-centre per-use cost analysis for disposable and reusable fibre-optic nasendoscopes.

METHODS

A cross-sectional study was formulated. An online survey consisting of multiple-choice and Likert-scale questions was distributed nationally. Cost analysis was performed using 2021-2022 data from the host institution.

RESULTS

Twenty-four trainees responded. Data on disposable fibre-optic nasendoscopes showed no difference in overall satisfaction (p = 0.244). Reusable fibre-optic nasendoscopes had a lower cost per use compared with disposable nasendoscopes at 5 years (4.7 per cent reduction) and 10 years (7.1 per cent reduction). Of the trainees, 79.2 per cent were supportive of climate-friendly initiatives within ENT surgery, and 25 per cent felt supported by their departments.

CONCLUSION

Trainees' satisfaction with disposable and reusable fibre-optic nasendoscopes is similar. Cost analysis favours reusable fibre-optic nasendoscopes in the long term at the host institution. Empowering departments and trainees to pursue climate-friendly initiatives should be encouraged.

Immune-Modulating Lipid Nanomaterials for the Delivery of Biopharmaceuticals

In recent years, with the approval of preventative vaccines for pandemics, lipid nanoparticles have become a prominent RNA delivery vehicle. The lack of long-lasting effects of non-viral vectors is an advantage for infectious disease vaccines. With the introduction of microfluidic processes that facilitate the encapsulation of nucleic acid cargo, lipid nanoparticles are being studied as delivery vehicles for various RNA-based biopharmaceuticals. In particular, using microfluidic chip-based fabrication processes, nucleic acids such as RNA and proteins can be effectively incorporated into lipid nanoparticles and utilized as delivery vehicles for various biopharmaceuticals. Due to the successful development of mRNA therapies, lipid nanoparticles have emerged as a promising approach for the delivery of biopharmaceuticals. Biopharmaceuticals of various types (DNA, mRNA, short RNA, proteins) possess expression mechanisms that are suitable for manufacturing personalized cancer vaccines, while also requiring formulation with lipid nanoparticles. In this review, we describe the basic design of lipid nanoparticles, the types of biopharmaceuticals used as carriers, and the microfluidic processes involved. We then present research cases focusing on lipid-nanoparticle-based immune modulation and discuss the current status of commercially available lipid nanoparticles, as well as future prospects for the development of lipid nanoparticles for immune regulation purposes.

Quantifying the relationship between sub-population wastewater samples and community-wide SARS-CoV-2 seroprevalence

Robust epidemiological models relating wastewater to community disease prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community disease prevalence due to inherent biases. This study conducted serial stratified randomized samplings to estimate the prevalence of SARS-CoV-2 antibodies in 3717 participants, and obtained weekly samples of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY (USA) from August 2020 to February 2021. Using an expanded Susceptible-Infected-Recovered model, the longitudinal estimates of the disease prevalence were obtained and compared with the wastewater concentrations using regression analysis. The model analysis revealed significant temporal differences in epidemic peaks. The results showed that in some areas, the average incidence rate, based on serological sampling, was 50 % higher than the health department rate, which was based on convenience sampling. The model-estimated average prevalence rates correlated well with the wastewater (correlation = 0.63, CI (0.31,0.83)). In the regression analysis, a one copy per ml-unit increase in weekly average wastewater concentration of SARS-CoV-2 corresponded to an average increase of 1-1.3 cases of SARS-CoV-2 infection per 100,000 residents. The analysis indicates that wastewater may provide robust estimates of community spread of infection, in line with the modeled prevalence estimates obtained from stratified randomized sampling, and is therefore superior to publicly available health data.

Relationship between freshwater harmful algal blooms and neurodegenerative disease incidence rates in South Korea

BACKGROUND

Due to anthropogenic activities and global warming, the severity and distribution of harmful algal blooms (HABs) have been increasing steadily worldwide, including in South Korea (S. Korea). Previous studies reported that exposure to HABs could increase the risk of HAB-related diseases. However, very few studies examined the linkage between HABs and disease occurrence, particularly in S. Korea. The objective of this study was to evaluate the potential impact of HABs on neurodegenerative diseases (NDs), including Alzheimer's disease, Parkinson's disease, and motor neuron disease, at a population level.

METHODS

Thirteen-year data (2005-2017) for chlorophyll-a (chl-a) concentrations as a bloom-related parameter, annual numbers of NDs, and population information were collected. First, the entire area of S. Korea was divided into a grid of 1 km, and the population number in each 1-km grid was collected using the Statistical Geographic Information Service Plus system. Cross-sectional time series data were analyzed with two statistical models, a generalized linear mixed model and a generalized linear model.

RESULTS

The results show a general trend of increasing chl-a concentration and NDs year by year. We observed positive correlations between HAB intensity and the incidence rate of NDs. Particularly, HABs seem to have the most long-term carry-over effect on Parkinson's disease. Another key finding was that a 5-km radius from the HAB location was the boundary that showed the most significant associations with three NDs.

CONCLUSIONS

This study provides statistical evidence that supports the potential risk of NDs from the exposure to HAB. Thus, it is recommended to monitor a broad spectrum of cyanotoxins, including neurotoxins, in bloom-affected regions in S. Korea and epidemiological studies in the future.

An interaction Neyman-Scott point process model for coronavirus disease-19

With rapid transmission, the coronavirus disease 2019 (COVID-19) has led to over three million deaths worldwide, posing significant societal challenges. Understanding the spatial patterns of patient visits and detecting local cluster centers are crucial to controlling disease outbreaks. We analyze COVID-19 contact tracing data collected from Seoul, which provide a unique opportunity to understand the mechanism of patient visit occurrence. Analyzing contact tracing data is challenging because patient visits show strong clustering patterns, while cluster centers may have complex interaction behavior. Cluster centers attract each other at mid-range distances because other cluster centers are likely to appear in nearby regions. At the same time, they repel each other at too small distances to avoid merging. To account for such behaviors, we develop a novel interaction Neyman-Scott process that regards the observed patient visit events as offsprings generated from a parent cluster center. Inference for such models is challenging since the likelihood involves intractable normalizing functions. To address this issue, we embed an auxiliary variable algorithm into our Markov chain Monte Carlo. We fit our model to several simulated and real data examples under different outbreak scenarios and show that our method can describe the spatial patterns of patient visits well. We also provide useful visualizations that can inform public health interventions for infectious diseases, such as social distancing.

Using the lactate-to-albumin ratio to predict mortality in patients with sepsis or septic shock: a systematic review and meta-analysis

OBJECTIVE

This study aimed to investigate whether the lactate-to-albumin ratio (LAR) can predict mortality in patients with sepsis or septic shock.

PATIENTS AND METHODS

A systematic search of the PubMed, EMBASE, Web of Science, and Google Scholar databases was conducted on December 16, 2021, for relevant articles that provided the predictive performance of LAR for mortality in patients with sepsis or septic shock.

RESULTS

Eight studies encompassing a total of 4,723 patients were included in this paper. The pooled sensitivity, specificity, and diagnostic odds ratio of the LAR for predicting mortality were 0.71 (95% confidence interval [CI]: 0.54-0.84), 0.68 (95% CI: 0.58-0.76) and 5.23 (95% CI: 2.62-10.45), respectively. The area under the summary receiver operating characteristic curve was 0.74 (95% CI: 0.70-0.78).

CONCLUSIONS

The current evidence suggests that LAR is moderately predictive of mortality among patients with sepsis or septic shock and may be beneficial to identify high-risk patients.

225 First Contact: A Series of Zoom-Based, Virtual on Call Shifts

Aim

COVID-19 has resulted in reduced exposure to on-call shifts where medical students could increase confidence and proficiency in task prioritisation and decision making. Existing ‘simulated on-calls’ provide a substitute in a controlled environment, however in person teaching has also been limited by COVID-19. Our virtual on-call sessions use ZOOM to replicate the higher-level learning experiences normally conferred by live simulation.

Method

We designed a series of virtual ‘on-calls’ for medical students. Participants were ‘on-call’, receiving ‘bleeps’ which were ‘answered’ by calling a facilitator via ZOOM. The facilitator would roleplay a scenario and the ‘Electronic Patient Record’ (EPR) on Google Forms contained patient notes and observations. Students needed to collect information from the facilitator and document a management plan into the EPR. Participants received ‘bleeps’ of varying complexity, urgency and relevance and were expected to prioritise and triage tasks accordingly. Evaluation was via a pre/post session quiz with separate feedback forms.

Results

23 students from 18 universities participated. Students reported increased confidence in managing on-call scenarios, and average scores improved in the post session quiz. Positive feedback was paid to the variety of scenarios, the EPR system and the feeling of realism elicited from the need to triage and prioritise jobs.

Conclusions

Our framework uses readily accessible technology to provide interactive learning experience. Feedback suggested students engaged in higher order learning and thinking, achieving our stated aims. We aim to incorporate technologies such as automation software which will allow for a scalable, free, and accessible virtual on call.

Beyond the Michaelis-Menten: Bayesian Inference for Enzyme Kinetic Analysis

Although the Michaelis-Menten (MM) rate law has been widely used to estimate enzyme kinetic parameters, it works only under the condition of extremely low enzyme concentration. Furthermore, even when this condition is satisfied, parameter estimation is often imprecise due to the parameter identifiability issue. To overcome these limitations of the canonical approach to enzyme kinetics, we developed a Bayesian approach based on a modified form of the MM rate law, which is derived with the total quasi-steady state approximation. Here, we illustrate how to perform the Bayesian inference for the progress curve assay with our user-friendly computational R package. We also describe an optimal experimental design for the progress curve assay, with which enzyme kinetic parameters can be accurately and precisely estimated from minimal measurements of the progress curves.

1426 Assessing the Impact Of COVID-19 On ENT Referrals at A West London General Practice

Aim

The COVID-19 pandemic has resulted in initial GP consultations being conducted via telephone. This quality improvement initiative quantified this impact on ENT referrals conducted at a West London GP, using education to improve awareness of the relevant NICE guidance to reduce inappropriate referrals.

Method

An initial retrospective audit comparing number and urgency of ENT referrals and the appropriateness of ENT referrals (using NICE guidance) during the face to face (F2F) period (August 2019 – February 2020) and telephone period (March – September 2020) was performed. Results were presented locally to GPs, with education measures on relevant NICE guidance implemented. Further PDSA cycles occurred during October and November 2020.

Results

In total, 16 ENT referrals were made during the F2F period (routine n = 15; urgent n = 1); 3 were inappropriate. 31 referrals were made between March and September 2020 (routine n = 27, urgent n = 2, 2WW n = 2); 4 were inappropriate. Further cycles in October 2020, and November 2020 identified 13 referrals (routine n = 10, 2WW n = 3), and 2 referrals (routine n = 2) respectively. 1 inappropriate referral was made during October and none in November.

Conclusions

Locally, it appears that the number of routine referrals has increased since the advent of the initial lockdown. This may be partially explained by the practice losing the ability to perform some ENT services, such as ear wax micro-suctioning. Education to increase awareness of relevant guidance has been shown to reduce the number of inappropriate referrals to ENT services.

1372 Thrombocytosis and Malignancy: Management in Primary Care

Introduction

The diagnosis of cancer relies within primary care to recognise this possibility in patients. Studies have shown an association of thrombocytosis with cancer, in particular lung, renal, uterine and colorectal cancer. Subsequently, suspected cancer pathways incorporate thrombocytosis in stratifying risk. This quality improvement project aimed to evaluate and improve the approach of GPs at a West London practice in managing thrombocytosis.

Method

A retrospective study evaluated patients with a most recent platelet count of > 450x109/L. Furthermore, a survey was sent to all GPs within the practice to establish their understanding and concerns. Results were presented locally, and intervention applied following the end of the first cycle.

Results

The survey showed 75% (n = 9) of staff were aware of the association of thrombocytosis and malignancy. In absence of specific symptoms, 64% would consider a chest X-ray, 41% a faecal occult blood test and 16% would consider transvaginal USS in women. 28 patients were identified with thrombocytosis. Of these, 4 had underlying malignancy, 3 had an underlying haematological condition. 2 cases had a concurrent inflammatory process. Of the remaining 19 patients, 5 were referred on for specialist service. In the remaining 14, although filed as “to repeat blood test” or “speak to doctor”, 12 had yet to be actioned.

Conclusions

The management of thrombocytosis at a local level in primary care has room for improvement. An alert was designed and created on the online system used by the practice to safeguard missed recalls for blood tests and prompts to consider the possibility of malignancy.

1389 Axillary Staging in Ductal Carcinoma in Situ with Microinvasion: A Systematic Review

Introduction

Ductal carcinoma in situ with microinvasion (DCISM) is a rare subtype of DCIS, with a foci of tumour cells penetrating through the basement membrane. A conundrum for surgeons is that definitive diagnosis is made upon histological examination of the final specimen. In the UK, there are no specific guidelines on the role of axillary staging in the management of DCISM cases.

Method

A systematic review was conducted on the databases MEDLINE and Embase using the keywords: breast, DCISM, microinvasion, “ductal carcinoma in situ with microinvasion”, sentinel lymph node biopsy, SLNB, axillary staging was performed. 23 studies were selected for analysis. Primary outcome was the positivity of lymph node metastases; secondary outcome looked at characteristics of DCISM that may affect node positivity.

Results

2959 patients were included. Significant heterogeneity was observed amongst the studies with regards to metastases (I2=61%; P < 0.01). Lymph node macrometastases was estimated to be 2%. Significant subgroup difference was not observed between SLNB technique and lymph node macrometastases (Q = 0.74; p = 0.69). Statistical significance was observed between the focality of the DCISM and lymph node macrometastases (Q = 8.71; p = 0.033).

Conclusions

DCISM is not linked with higher rates of clinically significant metastasis to axillary lymph nodes. Survival rates are very similar to those seen in cases of DCIS. Current evidence suggests that axillary staging in cases of DCISM will not change their overall management. A conscientious multidisciplinary team approach evaluating pre-operative clinical and histological information to tailor the management specific to individual cases of DCISM would be a preferred approach than routine axillary staging.

Hierarchical Bayesian models of transcriptional and translational regulation processes with delays

MOTIVATION

Simultaneous recordings of gene network dynamics across large populations have revealed that cell characteristics vary considerably even in clonal lines. Inferring the variability of parameters that determine gene dynamics is key to understanding cellular behavior. However, this is complicated by the fact that the outcomes and effects of many reactions are not observable directly. Unobserved reactions can be replaced with time delays to reduce model dimensionality and simplify inference. However, the resulting models are non-Markovian, and require the development of new inference techniques.

RESULTS

We propose a non-Markovian, hierarchical Bayesian inference framework for quantifying the variability of cellular processes within and across cells in a population. We illustrate our approach using a delayed birth-death process. In general, a distributed delay model, rather than a popular fixed delay model, is needed for inference, even if only mean reaction delays are of interest. Using in silico and experimental data we show that the proposed hierarchical framework is robust and leads to improved estimates compared to its non-hierarchical counterpart. We apply our method to data obtained using time-lapse microscopy and infer the parameters that describe the dynamics of protein production at the single cell and population level. The mean delays in protein production are larger than previously reported, have a coefficient of variation of around 0.2 across the population, and are not strongly correlated with protein production or growth rates.

AVAILABILITY AND IMPLEMENTATION

Accompanying code in Python is available at https://github.com/mvcortez/Bayesian-Inference.

CONTACT

kresimir.josic@gmail.com or jaekkim@kaist.ac.kr or cbskust@korea.ac.kr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Erratum: Azimuthal Anisotropy of K_{S}^{0} and Λ+Λ[over ¯] Production at Midrapidity from Au+Au Collisions at sqrt[s]_{NN}=130 GeV [Phys. Rev. Lett. 89, 132301 (2002)]

This corrects the article DOI: 10.1103/PhysRevLett.89.132301.

Erratum: Azimuthal Anisotropy at the Relativistic Heavy Ion Collider: The First and Fourth Harmonics [Phys. Rev. Lett. 92, 062301 (2004)]

This corrects the article DOI: 10.1103/PhysRevLett.92.062301.

P–370 RPL-protease A as a potential biomarker for predicting recurrent pregnancy loss

Study question

Could the reduction of RPL-protease A be involved in the dysfunctional trophoblast for resulting in recurrent pregnancy loss (RPL).

Summary answer

Low expression of RPL-protease A may result in RPL and low serum RPL-protease A level may be a potential biomarker for predicting RPL.

What is known already

The RPL-protease A is expressed and secreted by placenta. The RPL-protease A is involved in the pathogenesis of pre-eclampsia, and the serum RPL-protease A level is higher in the patients with pre-eclampsia than that of normal groups. In our previous study, we identified that the RPL-protease A mRNA level was lower in the villi of patients with RPL than that of normal groups.

Study design, size, duration

Using the CRISPR/Cas9 system, the RPL-protease A gene knockout BeWo cell (BeWo KO) line was established, and the wild type (BeWo WT) and BeWo KO cells were applied to investigate the roles of RPL-protease A in trophoblasts. The human serum RPL-protease A levels were investigated by Western blot analysis and ELISA kit.

Participants/materials, setting, methods

The cell-cell fusion, cell counting analysis, invasion and scratch wound assays, cell cycle analysis, and immunocytochemical analysis were used to investigate cellular functions of RPL-protease A in trophoblast. The sera were obtained from 32 normal pregnant women and 60 women with RPL. The Western blot analysis and ELISA were used for detection of serum RPL-protease A levels.

Main results and the role of chance

The β-hCG was detected in fused BeWo WT cells, while the BeWo KO cells cannot fuse and did not express the β-hCG. The ability of invasion was decreased, but the capacity of migration and proliferation was higher in BeWo KO cells than BeWo WT cells. Cell fusion related factor (β-hCG), and cell invasion related factors (MMP–2 and MMP–9) were highly expressed in BeWo WT cells, and cell related factor (FAK), and cell proliferation related factors (ERK, p38, JNK, MKK3, MKK6, Raf, and Ras) were highly expressed in BeWo KO cells. The Western blot analysis and ELISA indicate that the serum RPL-protease A level was decreased in patients with RPL compared to that of normal groups.

Limitations, reasons for caution

The results of this study have the limitation of RPL-protease A functions in vitro.

Wider implications of the findings: The cellular functions of RPL-protease A in trophoblasts were investigated to explain the pathogenesis of RPL, and low serum RPL-protease A level can be used for a potential biomarker predicting RPL.

Trial registration number

Not applicable

Survival dynamical systems: individual-level survival analysis from population-level epidemic models

In this paper, we show that solutions to ordinary differential equations describing the large-population limits of Markovian stochastic epidemic models can be interpreted as survival or cumulative hazard functions when analysing data on individuals sampled from the population. We refer to the individual-level survival and hazard functions derived from population-level equations as a survival dynamical system (SDS). To illustrate how population-level dynamics imply probability laws for individual-level infection and recovery times that can be used for statistical inference, we show numerical examples based on synthetic data. In these examples, we show that an SDS analysis compares favourably with a complete-data maximum-likelihood analysis. Finally, we use the SDS approach to analyse data from a 2009 influenza A(H1N1) outbreak at Washington State University.

Harmful algal blooms and liver diseases: focusing on the areas near the four major rivers in South Korea

Freshwater harmful algal blooms (HABs) have become a global concern because blooms contain cyanotoxins that can cause liver damage and other negative health impacts. In South Korea, HABs have been frequently observed along the major rivers (Han, Geum, Nakdong, and Youngsan) in recent years. However, there are hardly any studies that report a linkage between HABs and human health, especially along the four major rivers where dams, weirs, and reservoirs were constructed, and sediments were dredged under the Four Major Rivers Project (FMRP) that ended in 2012. The goals of this study were to summarize spatial distribution patterns of HABs and investigate a potential association between HABs and liver diseases. Chlorophyll-a concentration was used to estimate bloom intensity since it was the only available bloom-related parameter that covers the entire rivers. Liver disease data (ICD-10 codes: K71-K77) were sorted by administrative districts. Generalized linear mixed model was used to analyze the bloom, liver diseases, and population data (2005-2016). The results show that chlorophyll-a levels significantly increased since 2013, except Han River region. There was a significant association between HAB intensity and incidence rate of liver diseases, except Han River area, and the extent of association significantly increased after the completion of the FMRP. For future studies, more in-depth epidemiological investigations are warranted in those areas to accurately determine more specific associations between HABs and liver diseases as well as other bloom-related diseases and symptoms. In addition, identification of major exposure pathways to cyanotoxins is needed to better protect public health in those bloom-affected areas.

Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC

We describe two approaches to modeling data from a small to moderate-sized epidemic outbreak. The first approach is based on a branching process approximation and direct analysis of the transmission network, whereas the second one is based on a survival model derived from the classical SIR equations with no explicit transmission information. We compare these approaches using data from a 2012 outbreak of Ebola virus disease caused by Bundibugyo ebolavirus in city of Isiro, Democratic Republic of the Congo. The branching process model allows for a direct comparison of disease transmission across different environments, such as the general community or the Ebola treatment unit. However, the survival model appears to yield parameter estimates with more accuracy and better precision in some circumstances.

Bayesian inference of distributed time delay in transcriptional and translational regulation

MOTIVATION

Advances in experimental and imaging techniques have allowed for unprecedented insights into the dynamical processes within individual cells. However, many facets of intracellular dynamics remain hidden, or can be measured only indirectly. This makes it challenging to reconstruct the regulatory networks that govern the biochemical processes underlying various cell functions. Current estimation techniques for inferring reaction rates frequently rely on marginalization over unobserved processes and states. Even in simple systems this approach can be computationally challenging, and can lead to large uncertainties and lack of robustness in parameter estimates. Therefore we will require alternative approaches to efficiently uncover the interactions in complex biochemical networks.

RESULTS

We propose a Bayesian inference framework based on replacing uninteresting or unobserved reactions with time delays. Although the resulting models are non-Markovian, recent results on stochastic systems with random delays allow us to rigorously obtain expressions for the likelihoods of model parameters. In turn, this allows us to extend MCMC methods to efficiently estimate reaction rates, and delay distribution parameters, from single-cell assays. We illustrate the advantages, and potential pitfalls, of the approach using a birth-death model with both synthetic and experimental data, and show that we can robustly infer model parameters using a relatively small number of measurements. We demonstrate how to do so even when only the relative molecule count within the cell is measured, as in the case of fluorescence microscopy.

AVAILABILITY AND IMPLEMENTATION

Accompanying code in R is available at https://github.com/cbskust/DDE_BD.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Amalgam Strength Resistance to Various Contaminants

Purpose:

The purpose of this study was to quantify the relative strength tolerance of 1-day and 30-day amalgam following saturation contamination with water, saliva, blood, and handpiece lubricant oil during condensation.

Methods and Materials:

Valiant PhD XT amalgam was tested with 300 shear-strength (N=15) and 120 compressive-strength (N=6) specimens, divided into 1-day and 30-day groups, each with control, water, saliva, blood, and lubricant oil contamination samples. Shear specimens were condensed in 4 × 4-mm anchor wells inundated with contaminant fluids before adding a ring mold with 3.5-mm-diameter central hole adapted immediately to the top for continued condensation under contaminant-submerged conditions. Compressive specimen samples were condensed while completely inundated by each contaminant using the American Dental Association Specification No. 1 amalgam mold apparatus. All specimens were tested with the Instron E3000 and E10000 at 0.5 mm/min, with data statistically evaluated using the Kruskal-Wallis procedure with IBM SPSS v25 and Wilcoxon signed ranks test.

Results:

Shear test values (mean±SD) following intracapsular and extracapsular contamination after 30 days under 100% humidity at 37°C were as follows: control, 30.97±5.41 MPa; water, 30.63 ±4.41 MPa; saliva, 27.54 ±4.56 MPa; blood, 24.92 ±3.48 MPa; lubricant oil, 26.06 ±4.06 MPa. Compressive strengths (±SD) of similarly contaminated samples were as follows: control, 447.7 ±76.3 MPa; water, 343.6 ±70.1 MPa; saliva, 307.7 ±24.0 MPa; blood, 281.6 ±35.2 MPa; lubricant oil, 227.8 ±16.9 MPa.

Conclusions:

Saliva, blood, and handpiece oil diminish compressive strength significantly, but water shows no statistically significant effect (p>0.05). Amalgam 30-day shear strength is significantly altered by contamination with water, blood, or handpiece lubricant oil (p<0.05). Remaining amalgam strength after extensive contamination may still be clinically functional relative to a previous ADA recommendation and when compared with resin-based direct restorative materials.

Modeling household transmission dynamics: Application to waterborne diarrheal disease in Central Africa

Introduction

We describe a method for analyzing the within-household network dynamics of a disease transmission. We apply it to analyze the occurrences of endemic diarrheal disease in Cameroon, Central Africa based on observational, cross-sectional data available from household health surveys.

Methods

To analyze the data, we apply formalism of the dynamic SID (susceptible-infected-diseased) process that describes the disease steady-state while adjusting for the household age-structure and environment contamination, such as water contamination. The SID transmission rates are estimated via MCMC method with the help of the so-called synthetic likelihood approach.

Results

The SID model is fitted to a dataset on diarrhea occurrence from 63 households in Cameroon. We show that the model allows for quantification of the effects of drinking water contamination on both transmission and recovery rates for household diarrheal disease occurrence as well as for estimation of the rate of silent (unobserved) infections.

Conclusions

The new estimation method appears capable of genuinely capturing the complex dynamics of disease transmission across various human, animal and environmental compartments at the household level. Our approach is quite general and can be used in other epidemiological settings where it is desirable to fit transmission rates using cross-sectional data.

Software sharing

The R-scripts for carrying out the computational analysis described in the paper are available at https://github.com/cbskust/SID.

Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters

Examining enzyme kinetics is critical for understanding cellular systems and for using enzymes in industry. The Michaelis-Menten equation has been widely used for over a century to estimate the enzyme kinetic parameters from reaction progress curves of substrates, which is known as the progress curve assay. However, this canonical approach works in limited conditions, such as when there is a large excess of substrate over enzyme. Even when this condition is satisfied, the identifiability of parameters is not always guaranteed, and often not verifiable in practice. To overcome such limitations of the canonical approach for the progress curve assay, here we propose a Bayesian approach based on an equation derived with the total quasi-steady-state approximation. In contrast to the canonical approach, estimates obtained with this proposed approach exhibit little bias for any combination of enzyme and substrate concentrations. Importantly, unlike the canonical approach, an optimal experiment to identify parameters with certainty can be easily designed without any prior information. Indeed, with this proposed design, the kinetic parameters of diverse enzymes with disparate catalytic efficiencies, such as chymotrypsin, fumarase, and urease, can be accurately and precisely estimated from a minimal amount of timecourse data. A publicly accessible computational package performing such accurate and efficient Bayesian inference for enzyme kinetics is provided.

Probabilistic dietary exposure to ethyl carbamate from fermented foods and alcoholic beverages in the Korean population

The occurrence of ethyl carbamate was investigated in fermented foods and alcoholic beverages of the Korean total diet study. The concentrations of ethyl carbamate ranged from not detected to 166.5 μg kg^-1. Dietary exposure to ethyl carbamate was estimated by the probabilistic method. Estimated intakes of ethyl carbamate from foods and alcoholic beverages were 4.12 ng kg^-1 body weight (bw) per day for average consumers and 12.37 ng kg^-1 bw/day for 95th percentile high consumers. The major foods contributing to ethyl carbamate exposure were soy sauce (63%), followed by maesilju (plum liqueur, 30%), whisky (5%), and bokbunjaju (black raspberry wine, 2%). On the basis of the benchmark dose lower confidence limit 10% (BMDL₁₀) of 0.3 mg kg^-1 bw/day, margins of exposure were 128,000 for mean exposure and 40,000 for 95th percentile exposure. This indicates that the exposure of the Korean general population for ethyl carbamate is of low concern. However, careful vigilance should be continued for high consumers of fermented foods and alcoholic beverages.

Major Histocompatibilty Complex-Restricted Adaptive Immune Responses to CT26 Colon Cancer Cell Line in Mixed Allogeneic Chimera

BACKGROUND

Although the induction of mixed allogeneic chimera shows promising clinical tolerance results in organ transplantation, its clinical relevance as an anti-cancer therapy is yet unknown. We introduced a mixed allogenic chimera setting with the use of a murine colon cancer cell line, CT26, by performing double bone marrow transplantation.

METHODS

We analyzed donor- and recipient-restricted anti-cancer T-cell responses, and phenotypes of subpopulations of T cells. The protocol involves challenging 1 × 10⁵ cells of CT26 cells intra-hepatically on day 50 after bone marrow transplantation, and, by use of CT26 lysates and an H-2L^d-restricted AH1 pentamer, flow cytometric analysis was performed to detect the generation of cancer-specific CD4⁺ and CD8⁺ T cells at various time points.

RESULTS

We found that immunocompetence against tumors depends heavily on cancer-specific CD8⁺ T-cell responses in a major histocompatibility complex-restricted manner; the evidence was further supported by the increase of interferon-γ-secreting CD4⁺ T cells. Moreover, we demonstrated that during the effector immune response to CT26 cancer challenge, there was a presence of central memory cells (CD62L^hiCCR7⁺) as well as effector memory cells (CD62L^loCCR7^-). Moreover, mixed allogeneic chimeras (BALB/c to C56BL/6 or vice versa) showed similar or heightened immune responses to CT26 cells compared with that of wild-type mice.

CONCLUSIONS

Our results suggest that the responses of primary immunocompetency and of pre-existing memory T cells against allogeneic cancer are sustained and preserved long-term in a mixed allogeneic chimeric environment.