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PURPOSE: This study examined how solvent-skin-solute interactions influenced the human epidermal permeation of three similar-sized phenolic compounds applied in a series of different solvents. METHODS: Human epidermal permeation fluxes and lag times of three phenolic compounds were assessed in Franz cells for a range of solvents varying in molecular size and solubility parameters. In order to develop a mechanistic understanding of the determinants of the permeation findings, the solubility of the compounds in solvents and stratum corneum, the extent of solvent uptake by the stratum corneum and the impact of the solvents on skin hydration and transepidermal water loss were also measured. RESULTS: Maximum epidermal fluxes and lag times varied greatly with the various solvent used. Markedly enhanced epidermal permeability fluxes, prolonged lag times and reduced diffusivities of the compounds were evident for many of the solvents. A solvent induced increase in stratum corneum solubility was associated with the uptake of solvent containing dissolved compound. This uptake was dependent on both the solvent molecular size and the solubility of the compounds in the solvents. The imbibed solvent acted as a reservoir in the skin, facilitating uptake and an increased thermodynamic activity that enhanced flux but, at the same time, inhibiting diffusion and prolonging lag time. CONCLUSION: The solubility, permeation and lag times of compounds in the stratum corneum can be modulated by solvent uptake. Whilst a solvent -induced stratum corneum reservoir effect for a compound may prolong its lag time for a compound before steady state permeation is reached, it does not affect its overall steady state transport defined by diffusion of its free form.

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Studies of classical microbiology rely on the average behaviour of large cell populations without considering that clonal bacterial populations may bifurcate into phenotypic distinct sub-populations by random switching mechanisms.Listeria monocytogenes exposure to sublethal stresses may induce different physiological states that co-exist (i.e., sublethal injury or dormancy) and present variable resuscitation capacity. Exposures to peracetic acid (PAA; 10-30 ppm; for 3 h), acetic acid and hydrochloric acid (AA and HCl; pH 3.0-2.5; for 5 h) at 20 °C were used to induce different physiological states in L. monocytogenes, Scott A strain. After stress exposure, colony growth of single cells was monitored, on Tryptic Soy Agar supplemented with 0.6 % Yeast Extract, using time-lapse microscopy, at 37 °C. Images were acquired every 5 min and were analyzed using BaSCA framework. Most of the obtained growth curves of the colonies were fitted to the model of Baranyi and Roberts for the estimation of lag time (λ) and maximum specific growth rate (µmax), except the ones obtained after exposure to AA pH 2.7 and 2.5 that were fitted to the Trilinear model. The data of λ and µmax that followed a multivariate normal distribution were used to predict growth variability using Monte Carlo simulations. Outgrowth kinetics after treatment with AA (pH 2.7 and 2.5; for 5 h at 20 °C), PAA (30 ppm; for 3 h at 20 °C) revealed that these stress conditions increase the skewness of the variability distributions to the right, meaning that the variability in lag times increases in favour of longer outgrowth. Exposures to AA pH 2.5 and 30 ppm PAA resulted in two distinct subpopulations per generation with different growth dynamics. This switching mechanism may have evolved as a survival strategy for L. monocytogenes cells, maximizing the chances of survival. Simulation of microbial growth showed that heterogeneity in growth dynamics is increased when cells are recovering from exposure to sublethal stresses (i.e. PAA and acidic conditions) that may induce injury or dormancy.

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BACKGROUND: Characterization of microbial growth is of both fundamental and applied interest. Modern platforms can automate collection of high-throughput microbial growth curves, necessitating the development of computational tools to handle and analyze these data to produce insights. RESULTS: To address this need, here I present a newly-developed R package: gcplyr. gcplyr can flexibly import growth curve data in common tabular formats, and reshapes it under a tidy framework that is flexible and extendable, enabling users to design custom analyses or plot data with popular visualization packages. gcplyr can also incorporate metadata and generate or import experimental designs to merge with data. Finally, gcplyr carries out model-free (non-parametric) analyses. These analyses do not require mathematical assumptions about microbial growth dynamics, and gcplyr is able to extract a broad range of important traits, including growth rate, doubling time, lag time, maximum density and carrying capacity, diauxie, area under the curve, extinction time, and more. CONCLUSIONS: gcplyr makes scripted analyses of growth curve data in R straightforward, streamlines common data wrangling and analysis steps, and easily integrates with common visualization and statistical analyses.

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BACKGROUND: Retinoblastoma (RB) is a tumour of children < 5 years with a incidence of 1 in 20,000. Around 20 RB cases are diagnosed yearly in Sri Lanka, a lower middle-income country with high literacy levels and healthcare free at point of delivery. Incidence, local and systemic severity and mortality related to RB are reportedly high in low- and middle- income countries in comparison to higher income countries. Aims of this study were to describe demographic, socioeconomic, and clinical characteristics of Sri Lankan RB patients attending the designated RB unit at the Lady Ridgeway Hospital (LRH), Colombo between January 2014 to December 2020, and determine correlates of lag time (LT) for first tertiary care visit after detecting the first symptom/sign. METHODS: Two descriptive cross-sectional studies (DCSS) were conducted, one on 171 RB patients with demographic and clinical data collected between 2017 and 2020. In 2021, the second DCSS took place where socioeconomic and further demographic data were collected using telephone interviews, recruiting a subgroup of 90 (53%), consenting and contactable RB patient/ parent pairs. Bivariate and multivariable analyses were applied to determine correlates of LT of > 4 weeks for first tertiary care visit. Results were expressed as odds ratios and 95% confidence intervals. RESULTS: LRH survey (N = 171): Median age at diagnosis was 15 months (range 1-94 months; IQR: 8-27); 89 (52%) were females. Groups D and E tumours were 25.7% (n = 44) and 62.6% (n = 107) respectively with 121 (71%) enucleations. The number of deaths were 2 (1.2%). Telephone survey (N = 90): Proportion with LT of > 4 weeks for first tertiary care visit was 58% (n = 52). None of the putative risk factors (ethnicity, parental educational level, socioeconomic status, distance from residence to tertiary care unit and receiving financial assistance) were associated with LT in both analyses. CONCLUSION: Despite a high proportion with groups D and E tumours and enucleations, mortality rate was low, most likely due to availability of designated tertiary care. No correlates for LT of > 4 weeks for tertiary care presentation were identified. Early RB detection needs rigorous implementation of screening strategies and increased awareness among primary care health workers and parents.

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Exposure to sublethal stresses related to food-processing may induce a heterogenous mixture of cells that co-exist, comprising healthy, sublethally injured, dormant and dead cells. Heterogeneity in survival capacity and dormancy of single cells may impede the detection of foodborne pathogens. In this study, we exposed Listeria monocytogenes Scott A strain, to peracetic acid (PAA; 20-40 ppm) and to acidic conditions (hydrochloric (HCl) and acetic (AA) acid, adjusted to pH 2.7-3.0, to evaluate the resuscitation capacity and outgrowth kinetics of metabolically active cells in two different media. Injury and the viable-but-non-culturable (VBNC) status of cells were assessed by flow cytometry using CFDA (metabolically active) and PI (dead) staining. Stressed CFDA+PI- cells were sorted on Tryptic Soy (TS) Agar or in TS broth, both supplemented with 0.6 % Yeast Extract (TSAYE or TSBYE), to evaluate culturability. Resuscitation capacity of CFDA+PI-sorted cells (10 events/well) was monitored by visual inspection on TSAYE and by optical density measurement in TSBYE for 5 days. Sorting of L. monocytogenes viable cells (CFDA+PI-) in Ringer's solution on TSAYE and TSBYE showed 100 % recovery in both media (control condition), while the mean lag time in TSBYE was 9.6 h. Treatment with 20 ppm PAA for 90 and 180 min resulted in 74.79 % and 85.82 % of non-culturable cells in TSBYE and increased the average lag time to 41.7 h and 43.8 h, respectively, compared to the control (9.6 h). The longest average lag time (79.5 h) was detected after treatment with 30 ppm PAA for 90 min, while at the same condition sorting of CFDA+PI- cells resulted in 95.05 % and 93.94 % non-culturable cells on TSAYE and TSBYE, respectively. The highest percentage of wells with non-culturable cells (96.17 %) was detected on TSAYE after treatment with 40 ppm PAA for 30 min. Fractions of VBNC cells were detected in TSBYE after treatment with HCl pH 3.0 for 60 and 240 min, and in TSAYE and TSBYE after exposure to AA pH 2.7. Treatment with AA pH 2.7 for 150-300 min increased the range of recorded lag time values compared to 60 min, from 8.6 h up to 13.3 h, as well as the mean lag times in TSBYE. Modelling of the outgrowth kinetics comparing the two types of stress (oxidative vs acid) and the two systems of growth (colonial vs planktonic) revealed that low starting concentrations hindered the detection of viable L. monocytogenes cells, either due to VBNC induction or cell heterogeneity.

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Floating controlled systems seek to extend the gastric retention time (GRT) of solid pharmaceutical forms by sustaining buoyancy in the stomach without affecting gastric emptying rates. This investigation aimed to evaluate a magnetic floating drug delivery system (MFDDS) under diverse physiological conditions (pressure and viscosity) using an Alternating Current Biosusceptometry (ACB) system by conducting assessments in vitro and in vivo. For in vitro experiments, MFDDSs were placed under different pressures (760, 910, and 1060 mmHg) and viscosities (1, 50, 120, and 320 mPa·s) for evaluation of floating lag time (FLT). For in vivo experiments, eight healthy volunteers participated in two phases (fasting and fed) for gastric parameters (GRT, FLT, and OCTT-orocaecal transit time) assessment, employing the ACB system. The results indicated that pressure, viscosity, and FLT were directly proportional in the in vitro assay; in addition, increases in the OCTT (fasting = 241.9 ± 18.7; fed = 300 ± 46.4), GRT (fasting = 139.4 ± 25.3; fed = 190.2 ± 47.7), and FLT (fasting = 73.1 ± 16.9; fed = 107.5 ± 29.8) were detected in vivo. Our study emphasizes that the ACB system is a valuable technique, and it is capable of tracking and imaging MFDDS in in vitro and in vivo experiments.

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Nitrate­nitrogen (NO3-N) is a contaminant of concern in groundwater worldwide. Stakeholders need information on the ability to detect changes in NO3-N concentrations to prove that land management practices are meeting water quality aims. We created a database of quarterly to monthly NO3-N measurements in 948 sites across New Zealand; 186 of those sites had mean residence time (MRT) data. New Zealand has set a target of sufficient land use mitigations in the next 30 years to ensure steady state surface water concentrations do not exceed 2.4 mg L-1. Here we assess whether the current monitoring network could identify the impacts of these mitigations, assuming that the mitigations are successfully implemented at the source. Only 41 % of the network could detect statistically significant reductions with the current standard quarterly sampling after 30 years of monitoring. The percentage of sites increased to 60 % with increased monitoring frequency (often weekly) but this required a 100-300 % increase in monitoring costs. However, policy makers and stakeholders typically require information on policy and mitigation effectiveness within 5-10 years. Detection within 5-10 years was very unlikely (0-20 % of sites) regardless of the sampling frequency. Importantly, these analyses include the impacts of groundwater lag and temporal dispersion on the likelihood of detecting change, ignoring these impacts, incorrectly, yields a much higher likelihood of detecting reductions. We conclude that the current monitoring network is unlikely to be fit for the purpose of detecting NO3-N reductions within practical timeframes or budgets. Furthermore, we conclude that lag and temporal dispersion effects must be included in detection power calculations; we therefore recommend that MRT data is regularly collected. We also provide a python package to enable easy detection power calculations with lag and temporal dispersion impacts, thereby supporting the development of robust change-detection monitoring networks.

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INTRODUCTION: Cytological specimens, such as fine needle aspirations (FNAs) and exfoliative cytology samples, are minimally invasive options for diagnostic purposes. Liquid-based cytology (LBC), originally designed for cervical cytology, has gained prominence as an alternative technique for non-gynecological cytology. Immunocytochemistry (ICC) is an ancillary method used when diagnosis becomes challenging due to morphological overlap or the need for cellular origin clarification. This study aims to assess the diagnostic utility of ICC when applied to LBC slides and evaluate its effectiveness in relation to the waiting (lag) time of residual material. MATERIALS AND METHODS: A total of 74 cases in which ICC was applied to LBC slides were studied over one year in a reference pathology laboratory (Prof. Dr. Cemil Tascioglu, Pathology Laboratory, City Hospital, Istanbul, Turkey). Cases in which immunohistochemistry (IHC) was performed on formalin-fixed paraffin-embedded cell blocks were excluded. The SurePath PAP method was used for the main LBC cytology slides. For the ICC study, 1-4 PAP-stained LBC slides were obtained from each case's residual material and stained with a primary antibody. RESULTS: The positive immunostaining was obtained in 81% of cases. The samples were categorized into groups based on the waiting time of residual LBC material for ICC analysis: 1-5 days, 6-10 days, 11-20 days, and 21-38 days. Comparative analysis revealed a decline in ICC efficacy as the waiting (lag) time increased. Additionally, a statistically significant difference was observed between the 11-20 days and 21-38 days groups (P < 0.05). An analysis of 142 LBC slides stained by ICC revealed that nuclear markers exhibited higher positivity compared to non-nuclear markers, although no significant difference was detected between the two groups. CONCLUSIONS: High positivity rates can be obtained in ICC studies performed on additional slides obtained from residual LBC material within the first 20 days. ICC applied to LBC slides is an important and useful alternative for diagnostic and prognostic markers in cases without a cell block or with a cell block without sufficient number of cells.

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The stability of long-term microfabricated implants is hindered by the presence of multiple water diffusion paths within artificially patterned thin-film encapsulations. Side permeation, defined as infiltration of molecules through the lateral surface of the thin structure, becomes increasingly critical with the trend of developing high-density and miniaturized neural electrodes. However, current permeability measurement methods do not account for side permeation accurately nor quantitatively. Here, a novel optical, magnesium (Mg)-based method is proposed to quantify the side water transmission rate (SWTR) through thin film encapsulation and validate the approach using micrometric polyimide (PI) and polyimide-silicon carbide (PI-SiC) multilayers. Through computed digital grayscale images collected with corroding Mg film microcells coated with the thin encapsulation, side and surface WTRs are quantified. A 4.5-fold ratio between side and surface permeation is observed, highlighting the crucial role of the PI-PI interface in lateral diffusion. Universal guidelines for the design of flexible, hermetic neural interfaces are proposed. Increasing encapsulation's width (interelectrode spacing), creating stronger interfacial interactions, and integrating high-barrier interlayers such as SiC significantly enhance the lateral hermeticity.

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The rapid development of the city leads to the continuous updating of the land use allocation ratio, particularly during the flood season, which will exacerbate the significant changes in the spatial and temporal patterns of urban flooding, increasing the difficulty of urban flood forecasting and early warning. In this study, the spatial and temporal evolution of flooding in a high-density urban area was analyzed based on the Mike Flood model, and the influence mechanisms of different rainfall peak locations and infiltration rate scenarios on the spatial and temporal characteristics of urban waterlogging were explored. The results revealed that under the same return period, the larger the rainfall peak coefficient, the larger the peak value of inundation volume and inundation area. When the rainfall peak coefficient is small, the higher the return period is, and the larger the peak lag time of the inundation volume is, in which P = 50a, r = 0.2, the peak lag time of the inundation volume reached 32 min and 45 min for the inundation depths H > 0.03 m and H > 0.15 m, respectively. There are also significant differences in the peak lag time of waterlogging inundation volume for different inundation depths. The greater the inundation depth, the longer the peak lag time of the inundation volume, and the higher the return period, the more significant the effect of lag time prolongation. It is worth noting that the increase in infiltration rate may lead to an advance in the peak time of inundation volume and inundation area, and the peak time of the inundation area is overall more obvious than that of inundation volume. The effect of infiltration rate on the peak time of inundation volume for larger inundation depths was relatively large; the peak times of inundation volume and inundation area were advanced by 4-6 min and 4-8 min for H > 0.03 m and H > 0.15 m, respectively, after the increase in infiltration rate, and the higher the rainfall return period, the longer the advance time. The spatial and temporal characteristics of waterlogging under different peak rainfall locations and infiltration capacities obtained in this study can help provide a new perspective for temporal forecasting and warning of urban waterlogging.

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OBJECTIVES: Bomb pulse (BP) radiocarbon (14 C) dating methods are used by forensic anthropologists to estimate the year-of-death (YOD) of unidentified individuals. Method resolution and accuracy depend on establishing lag times, or the difference between a tissue's BP 14 C-derived year and the YOD, of various tissue types from known deceased persons. Bone lag times span many years and are thought to increase with age as a function of slowing remodeling rates. However, remodeling rates for various skeletal elements, bone structures and phases are not well known. MATERIALS AND METHODS: Here a simple method is used to estimate bone remodeling rates from a compilation of published cortical femur bone collagen BP 14 C measurements (n = 102). Linear regression models and nonparametric tests are used to detect changes in lag times and remodeling rates with increasing age-at-death. RESULTS: Remodeling rates and lag times of 3.5%/year and 29 years, respectively, are estimated from individuals aged 40-97 years. In contrast to previous work, the analysis yielded modest and negligible changes in remodeling rates and lag times with advancing age. Moreover, statistically significant differences in remodeling rates and lag times were not found between reported females and males. DISCUSSION: Implications for the temporal contexts within an individual's lifetime of biogeochemical data in archaeology and forensic anthropology are discussed, warranting additional BP 14 C studies of known individuals and integration with histomorphometric analysis.

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Introduction: Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices. Methods: Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony. Results: It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors. Discussion: These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection.

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Atrazine residues running off the fields and entering water resources are a major threat to food security and the ecosystem. In this study, a psychrotrophic functional strain named KN0901 to remove atrazine residues was screened. KN0901 could degrade 30 mg·L-1 atrazine in 4 days at 15ºC with 105 CFU·mL-1 incubation. The phylogenetic results showed KN0901 belonged to Paenarthrobacter sp. PCR results showed that the functional genes consist of trzN, atzB, and atzC, suggesting atrazine was transformed to cyanuric acid by KN0901. KN0901 could degrade atrazine without adding exogenous carbon and nitrogen sources. What's more, KN0901 could tolerate extreme low temperature (5ºC) and high atrazine concentration (100 mg·L-1). When growth and degradation curves were compared, the results indicated the length of lag time showed significant correlation to atrazine degradation rate. The hydroponic experiments showed that the toxicity of atrazine was significantly reduced with KN0901 treatment. The study provided an effective, economic, and eco-friendly bioremediation measure to address atrazine contamination.

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Importance: On an ecological scale, the lag time between coronavirus disease 2019 (COVID-19) infection and related fatality has varied between epidemic waves and prefectures in Japan. The variability in lag time across areas of Japan during the seven distinct waves can help derive a more appropriate estimation of the weekly confirmed case fatality rate (CFR) of COVID-19. Objective: To estimate the 7-day moving average CFR across area block levels in Japan from February 2020 to July 2022 using the lag time between COVID-19 infection and related fatality. Main outcomes and measures: The 7-day moving average CFR of COVID-19 for area blocks in Japan considering the lag time between infection and death (total and subgroup analysis of elderly). Results: Lag time was found to vary substantially among prefectures in Japan from the first wave to the seventh wave of the COVID-19 epidemic. The estimated 7-day moving average CFR based on the lag time reflects the Japanese COVID-19 pandemic and related policy interventions (e.g. vaccination of elderly people) rather than other standard CFR estimations. Conclusions and relevance: The variation in estimated lag time across prefectures in Japan for different epidemic waves indicates that it is inadequate to use the clinical results of the period from the start of infection to death for evaluation of the ecological scale of the CFR. Moreover, the lag time between infection and related fatality was found to be either shorter or longer than the clinically reported period. This revealed that preliminary reports of CFR may be overestimated or underestimated, even if they consider the lag based on clinical reports.

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In recent years, PM2.5 has become a critical factor as an environmental indicator, causing severe air pollution that has negatively impacted nature and human health. This study used hourly data gathered in central Taiwan from 2015 to 2019 and applied spatiotemporal data analysis and wavelet analysis methods to investigate the cross-correlation between PM2.5 and other air pollutants. Furthermore, it explored the correlation differences between adjacent stations after excluding major environmental factors such as climate and terrain. Wavelet coherence shows that PM2.5 and air pollutants mostly have a significant correlation at the half-day and one-day frequencies, while the differences between PM2.5 and PM10 are only particle size; hence, not only is the correlation the most consistent among all air pollutants but also the lag time is the most negligible. Carbon monoxide (CO) is the primary source pollutant of PM2.5 as it is also significantly correlated with PM2.5 at most timescales. Sulfur dioxide (SO2) and nitrogen oxide (NOx) are related to the generation of secondary aerosols, which are important components of PM2.5; therefore, the consistency of significant correlations improves as the timescale increases and the lag time becomes amplified. The pollution source mechanism of ozone (O3) and PM2.5 is not identical, so the correlation is lower than for other air pollutants; the lag time is also obviously influenced by the season changes that have significant fluctuations. At stations near the ocean such as Xianxi station and Shulu station, PM2.5 and PM10 have a higher correlation in the 24-h frequency, while the SO2 and PM2.5 at Sanyi station and Fengyuan station, which are close to industrial areas, have significant correlations in the 24-h frequency. This study hopes to help better understand the impact mechanisms behind different pollutants, and thus construct a better reference for establishing a complete air pollution prediction model in the future.

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Background: The rapid diagnostics of pathogens is essential to prescribe appropriate and early antibiotic therapy. The current methods for pathogen detection require the bacteria to grow in a culture medium, which is time-consuming. This increases the mortality rate and the global burden of antimicrobial resistance. Culture-free detection methods are still under development and are not used in the clinical routine. Therefore decreasing the culture time for accurate detection of infection and resistance is vital for diagnosis. Methods: In this study, we wanted to investigate easy-to-implement factors (in a minimal laboratory set-up), including inoculum size, incubation temperature, and additional supplementation ( e.g., vitamin B12 and trace metals), that can significantly reduce the lag time (t lag). These factors were arranged in simple two-level factorial designs using Gram-positive ( Escherichia coli and Pseudomonas aeruginosa) and Gram-negative ( Staphylococcus aureus and Bacillus subtilis) bacteria, including clinical isolates with known antimicrobial resistance profiles. Blood samples spiked with a clinical isolate of E. coli CCUG17620 were also tested to see the effect of elevated incubation temperature on bacterial growth in blood cultures. Results: We observed that increased incubation temperature (42°C) along with vitamin B12 supplementation significantly reduced the t lag (10 - 115 minutes or 4% - 49%) in pure clinical isolates and blood samples spiked with E. coli CCUG17620. In the case of the blood sample, PCR results also detected bacterial DNA after only 3h of incubation and at three times the CFU/mL. Conclusions: Enrichment of bacterial culture media with growth supplements such as vitamin B12 and increased incubation temperature can be a cheap and rapid method for the early detection of pathogens. This is a proof-of-concept study restricted to a few bacterial strains and growth conditions. In the future, the effect of other growth conditions and difficult-to-culture bacteria should be explored to shorten the lag phase.

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PURPOSE: With the increasing utilization of medications worldwide, coupled with the increasing availability of long-term data, there is a growing opportunity and need for robust studies evaluating drug-cancer associations. One methodology of importance in such studies is the application of lag times. METHODS: In this narrative review, we discuss the main reasons for using lag times. RESULTS: Namely, we discuss the typically long latency period of cancer concerning both tumor promoter and initiator effects and outline why cancer latency is a key consideration when choosing a lag time. We also discuss how the use of lag times can help reduce protopathic and detection bias. Finally, we present practical advice for implementing lag periods. CONCLUSIONS: In general, we recommend that researchers consider the information that generated the hypothesis as well as clinical and biological knowledge to inform lag period selection. In addition, given that latency periods are usually unknown, we also advocate that researchers examine multiple lag periods in sensitivity analyses as well as duration analyses and flexible modeling approaches.

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Woodchip bioreactors have gained popularity in many countries as a conservation practice for reducing nitrate load to freshwater. However, current methods for assessing their performance may be inadequate when nitrate removal rates (RR) are determined from low-frequency (e.g., weekly) concurrent sampling at the inlet and outlet. We hypothesised that high-frequency monitoring data at multiple locations can help improve the accuracy of quantifying nitrate removal performance, enhance the understanding of processes occurring within a bioreactor, and therefore improve the design practice for bioreactors. Accordingly, the objectives of this study were to compare RRs calculated using high- and low-frequency sampling and assess the spatiotemporal variability of the nitrate removal within a bioreactor to unravel the processes occurring within a bioreactor. For two drainage seasons, we monitored nitrate concentrations at 21 locations on an hourly or two-hourly basis within a pilot-scale woodchip bioreactor in Tatuanui, New Zealand. A novel method was developed to account for the variable lag time between entry and exit of a parcel of sampled drainage water. Our results showed that this method not only enabled lag time to be accounted for but also helped quantify volumetric inefficiencies (e.g., dead zone) within the bioreactor. The average RR calculated using this method was significantly higher than the average RR calculated using conventional low-frequency methods. The average RRs of each of the quarter sections within the bioreactor were found to be different. 1-D transport modelling confirmed the effect of nitrate loading on the removal process as nitrate reduction followed Michaelis-Menten (MM) kinetics. These results demonstrate that high-frequency temporal and spatial monitoring of nitrate concentrations in the field allows improved description of bioreactor performance and better understanding of processes occurring within woodchip bioreactors. Thus, insights gained from this study can be used to optimise the design of future field bioreactors.

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Introduction: Evaluating the potential effects of non-pharmaceutical interventions on COVID-19 dynamics is challenging and controversially discussed in the literature. The reasons are manifold, and some of them are as follows. First, interventions are strongly correlated, making a specific contribution difficult to disentangle; second, time trends (including SARS-CoV-2 variants, vaccination coverage and seasonality) influence the potential effects; third, interventions influence the different populations and dynamics with a time delay. Methods: In this article, we apply a distributed lag linear model on COVID-19 data from Germany from January 2020 to June 2022 to study intensity and lag time effects on the number of hospital patients and the number of prevalent intensive care patients diagnosed with polymerase chain reaction tests. We further discuss how the findings depend on the complexity of accounting for the seasonal trends. Results and discussion: Our findings show that the first reducing effect of non-pharmaceutical interventions on the number of prevalent intensive care patients before vaccination can be expected not before a time lag of 5 days; the main effect is after a time lag of 10-15 days. In general, we denote that the number of hospital and prevalent intensive care patients decrease with an increase in the overall non-pharmaceutical interventions intensity with a time lag of 9 and 10 days. Finally, we emphasize a clear interpretation of the findings noting that a causal conclusion is challenging due to the lack of a suitable experimental study design.

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The analysis and interpretation of data retrieved from Oxygen Radical Absorbance Capacity (ORAC) assays represent a challenging task. ORAC indexes originate from different mathematical approaches often lacking correct elucidation of kinetic features concerning radical scavenging reactions by antioxidant compounds. In this work, the expression of ORAC values as area under fluorescein (FL) decay curves (AUC) and lag time are critically compared. This multi-parametric analysis showed the extension of radical scavenging reactions beyond the lag time period for caffeic acid, gallic acid, reduced glutathione and quercetin, extending their antioxidant protection of FL. Ethanol delayed the reaction of both FL and antioxidant compounds with free radical species generated from 2,2'-azobis(2-amidinopropane) dihydrochloride thermolysis. Trolox equivalent values, commonly used to express ORAC values, were more affected by the differences in radical scavenging kinetics between the reference and the tested antioxidant compounds when calculated from AUC than from lag time. These findings stressed the importance of choosing calibrator compounds presenting ORAC kinetics similar to samples to prevent biased estimation of the antioxidant capacity. Additionally, the framework proposed here provides a sustainable analytical method for the evaluation of antioxidant capacity, with an AGREE score of 0.73.