gcplyr: an R package for microbial growth curve data analysis.

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.

Retinoblastoma patients treated in Sri Lanka from 2014 to 2020: epidemiology, clinical status and correlates of lag time in seeking tertiary care services.

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.

Glycolysis/gluconeogenesis specialization in microbes is driven by biochemical constraints of flux sensing.

Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic reorganization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis, and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa, and Pseudomonas putida. We combined growth dynamics and dynamic changes in intracellular metabolite levels with a coarse-grained model that integrates fluxes, regulation, protein synthesis, and growth and uncovered fundamental limitations of the regulatory network: After nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade-offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.

Perturbations in kinetics of the thrombin generation assay identify women at risk of preeclampsia in the first trimester and provide the rationale for a preventive approach.

BACKGROUND: Activation of the coagulation system and increased thrombin generation have been implicated in the pathophysiology of preeclampsia, and this rationale supports the administration of low-molecular-weight heparin to prevent this syndrome in patients at risk. Yet, randomized trials of this prophylactic measure have yielded contradictory results. A possible explanation is that only a subset of patients with preeclampsia have excessive thrombin generation and would benefit from the administration of low-molecular-weight heparin. Therefore, the key questions are whether and when patients who subsequently develop preeclampsia present evidence of abnormal thrombin generation. OBJECTIVE: This study aimed to determine (1) the kinetics of thrombin generation throughout gestation in women with a normal pregnancy and in those with early and late preeclampsia, and (2) the diagnostic performance of in vivo thrombin generation parameters to predict the development of preeclampsia. STUDY DESIGN: This retrospective, nested case-control study was based on a prospective longitudinal cohort of singleton gestations. Cases comprised women who developed preeclampsia (n=49), and controls consisted of patients with a normal pregnancy (n=45). Preeclampsia was classified into early-onset (n=24) and late-onset (n=25). Longitudinal changes in the parameters of the thrombin generation assay (lag time, time to peak thrombin concentration, peak thrombin concentration, endogenous thrombin generation, and velocity index) throughout gestation were compared between the study groups, and normal pregnancy percentiles were derived from the control group. We tested whether a single parameter or a combination of parameters, derived from the kinetics of thrombin generation, could identify patients who subsequently developed preeclampsia. Time-related parameters <10th percentile were considered short, and concentration-related parameters >90th percentile were considered high. RESULTS: (1) Patients who developed preeclampsia (early- and late-onset) had abnormal thrombin generation kinetics as early as 8 to 16 weeks of pregnancy; (2) patients with a combination of a short lag time and high peak thrombin concentration at 8 to 16 weeks of pregnancy had an odds ratio of 43.87 for the subsequent development of preeclampsia (area under the curve, 0.79; sensitivity, 56.8%; specificity, 92.7%; positive likelihood ratio, 7.76); (3) at 16 to 22 weeks of gestation, patients with a combination of a short lag time and a high velocity index had an odds ratio of 16 for the subsequent development of preeclampsia (area under the curve, 0.78; sensitivity, 62.2%; specificity, 92.5%; positive likelihood ratio, 8.29). CONCLUSION: During early pregnancy, the thrombin generation assay can identify the subset of patients at a greater risk for the development of preeclampsia owing to accelerated and enhanced production of thrombin. This observation provides a rationale for testing the efficacy of low-molecular-weight heparin in this subset of patients. We propose that future research on the efficacy of low-molecular-weight heparin and other interventions targeting the coagulation system to prevent preeclampsia should be focused on patients with abnormal kinetics of thrombin generation.

Referral patterns for retinoblastoma patients in Ethiopia.

BACKGROUND: Increased lag time between the onset of symptoms and treatment of retinoblastoma (RB) is one of the factors contributing to delay in diagnosis. The aim of this study was to understand the referral patterns and lag times for RB patients who were treated at Menelik II Hospital in Addis Ababa, Ethiopia. METHOD: A single-center, cross- sectional study was conducted in January 2018. All new patients with a confirmed RB diagnosis who had presented to Menelik II Hospital from May 2015 to May 2017 were eligible. A questionnaire developed by the research team was administered to the patient's caregiver by phone. RESULTS: Thirty-eight patients were included in the study and completed the phone survey. Twenty-nine patients (76.3%) delayed seeing a health care provider for ≥ 3 months from the onset of symptoms, with the most common reason being the belief that it was not a problem (96.5%), followed by 73% saying it was too expensive. The majority of patients (37/38, 97.4%) visited at least 1 additional health care facility prior to reaching a RB treatment facility. The mean overall lag time from noticing the first symptom to treatment was 14.31 (range 0.25-62.25) months. CONCLUSION: Lack of knowledge and cost are major barriers to patients first seeking care for RB symptoms. Cost and travel distance are major barriers to seeing referred providers and receiving definitive treatment. Delays in care may be alleviated by public education, early screening, and public assistance programs.

Investigating the nonlinear and non-stationary relationship between PM2.5 and air pollutants by wavelet signal analysis in central Taiwan.

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.

Prescription rates for commonly used drugs before and after a prostate cancer diagnosis.

PURPOSE: To investigate differences in prescription rates of commonly used drugs among prostate cancer patients and cancer-free comparisons and between patients diagnosed with localized and non-localized disease. METHODS: We conducted a register-based study including all men aged 50-85 years diagnosed with prostate cancer in Denmark from 1998 to 2015 and an age-matched cancer-free comparison cohort. We calculated the number of new and total prescriptions from three years before to three years after the date of diagnosis of the case for selected drug classes divided by the number of person-months and stratified by stage at diagnosis. RESULTS: We included 54,286 prostate cancer patients and 249,645 matched comparisons. 30,712 patients were diagnosed with localized disease and 12,884 with non-localized disease. The rates of new prescriptions increased considerably among patients within the year before the diagnosis. Hereafter the rates varied between drug classes. For most drug classes, total prescription rates for patients and comparisons increased similarly in the study period. Total prescription rates varied between men with localized and non-localized disease for all drug classes apart from statins. CONCLUSION: Our findings indicate that a large proportion of prostate cancer cases are likely diagnosed during medical work-up for other reasons than prostate cancer. Increased rates occur within the last year before diagnosis and future studies on the interaction between drug use and prostate cancer should at least include a one year pre-diagnostic lag-time. Post-diagnostic prescription rates demonstrated an increased use of drugs most likely associated with the consequences of the disease.

National Assessment of Long-Term Groundwater Response to Pesticide Regulation.

Quantitative assessments of long-term, national-scale responses of groundwater quality to pesticide applications are essential to evaluate the effectiveness of pesticide regulations. Retardation time in the unsaturated zone (Ru) was estimated for selected herbicides (atrazine, simazine, and bentazon) and degradation products (desethylatrazine (DEA), desisopropylatrazine (DIA), desethyldesisopropylatrazine (DEIA), and BAM) using a multidecadal time series of groundwater solute chemistry (∼30 years) and herbicide sales (∼60 years). The sampling year was converted to recharge year using groundwater age. Then, Ru was estimated using a cross-correlation analysis of the sales and the frequencies of detection and exceedance of the drinking water standard (0.1 µg/L) of each selected compound. The results showed no retardation of the highly polar, thus mobile, parent compounds (i.e., bentazon), while Ru of the moderately polar compounds (i.e., simazine) was about a decade, and their degradation products showed even longer Ru. The temporal trends of the degradation products did not mirror those of the sale data, which were attributed to the various sale periods of the parent compounds, sorption of the parent compounds, and complex degradation pathways. The longer Ru in clayey/organic sediments than in sandy sediments further confirmed the role of soil-specific retardation as an important factor to consider in groundwater protection.

Distribution of bacterial single cell parameters and their estimation from turbidity detection times.

The stochastic growth of homogeneous bacterial populations in the wells of a microtiter plate was studied as a function of the random initial cell number and their random individual lag times. These significantly affected the population growth in the well, while the maximum specific growth rate of the population was constant (or its variance was negligible) for each well. We showed the advantages of the mathematical assumption that a transformation of the single cell lag time, called the single cell physiological state (or, more accurately, that of the sub-population generated by the single cell) follow the Beta distribution. Simulations demonstrated what patterns would such assumption generate for the distribution of the detection times observed in the wells. An estimation procedure was developed, based on the beta-assumption, that resulted in an explicit expression for the expected value of the single cell physiological state as a function of measured "time to detection" values using turbidity experiments. The method was illustrated using laboratory data with Escherichia coli, Salmonella enterica subsp. enterica strains. The results gave a basis to quantify the difference between the studied organisms in terms of their single-cell kinetics.

Power-law tail in lag time distribution underlies bacterial persistence.

Genetically identical microbial cells respond to stress heterogeneously, and this phenotypic heterogeneity contributes to population survival. Quantitative analysis of phenotypic heterogeneity can reveal dynamic features of stochastic mechanisms that generate heterogeneity. Additionally, it can enable a priori prediction of population dynamics, elucidating microbial survival strategies. Here, we quantitatively analyzed the persistence of an Escherichia coli population. When a population is confronted with antibiotics, a majority of cells is killed but a subpopulation called persisters survives the treatment. Previous studies have found that persisters survive antibiotic treatment by maintaining a long period of lag phase. When we quantified the lag time distribution of E. coli cells in a large dynamic range, we found that normal cells rejuvenated with a lag time distribution that is well captured by an exponential decay [exp(-kt)], agreeing with previous studies. This exponential decay indicates that their rejuvenation is governed by a single rate constant kinetics (i.e., k is constant). Interestingly, the lag time distribution of persisters exhibited a long tail captured by a power-law decay. Using a simple quantitative argument, we demonstrated that this power-law decay can be explained by a wide variation of the rate constant k Additionally, by developing a mathematical model based on this biphasic lag time distribution, we quantitatively explained the complex population dynamics of persistence without any ad hoc parameters. The quantitative features of persistence demonstrated in our work shed insights into molecular mechanisms of persistence and advance our knowledge of how a microbial population evades antibiotic treatment.

Reduction of lag in crude oil degradation by Aspergillus when it is in synergy with Bacillus in biofilm mode.

A major hindrance to the effective use of fungi in bioremediation is their inherent slow growth. Despite this, Aspergillus spp. may be used effectively. Our experiments demonstrate that bacteria, although inefficient in hydrocarbon degradation, may be effectively used in a consortium to overcome the lag in fungal utilization of petroleum hydrocarbons. Crude petroleum oil (160 mg; at 8 g/L) in minimal medium was inoculated with a previously isolated biofilm-forming consortium (Aspergillus sp. MM1 and Bacillus sp. MM1) as well as monocultures of each organism and incubated at 30 ℃ under static conditions. Residual oil was analyzed by GC-MS. Crude oil utilization of Aspergillus-Bacillus biofilm was 24 ± 1.4% in 3 days, increased to 66 ± 7% by day 5 and reached 99 ± 0.2% in 7 days. Aspergillus sp. MM1 monoculture degraded only 14 ± 6% in 5 days. However, at the end of 7 days, it was able to utilize 98 ± 2%. Bacillus sp. MM1 monoculture utilized 20 ± 4% in 7 days. This study indicates that there is a reduction of the fungal lag in bioremediation when it is in association with the bacterium. Although in monoculture, Bacillus sp. MM1 is inefficient in crude oil degradation, it synergistically enhances the initial rate of crude petroleum oil degradation of the fungus in the consortium. The rapid initial removal of as much crude oil as possible from contaminated sites is vital to minimize detrimental impacts on biodiversity.

The lag-time constraint for behavioural plasticity.

Environmental instability (i.e. environments changing often) can select fixed phenotypes because of the lag time of plastically adapting to environmental changes, known as the lag-time constraint. Because behaviour can change rapidly (e.g. switching between foraging strategies), the lag-time constraint is not considered important for behavioural plasticity. Instead, it is often argued that responsive behaviour (i.e. behaviour that changes according to the environment) evolves to cope with unstable environments. But proficiently performing certain behaviours may require time for learning, for practising or, in social animals, for the group to adjust to one's behaviour. Conversely, not using certain behaviours for a period of time can reduce their level of performance. Here, using individual-based evolutionary simulations, we show that environmental instability selects for fixed behaviour when the ratio between the rates of increase and reduction in behavioural performance is below a certain threshold; only above this threshold does responsive behaviour evolve in unstable environments. Thus, the lag-time constraint can apply to behaviours that attain high performance either slowly or rapidly, depending on the relative rate with which their performance decreases when not used. We discuss these results in the context of the evolution of reduced behavioural plasticity, as seen in fixed personality differences.

A continuous data driven translational model to evaluate effectiveness of population-level health interventions: case study, smoking ban in public places on hospital admissions for acute coronary events.

BACKGROUND: An important task in developing accurate public health intervention evaluation methods based on historical interrupted time series (ITS) records is to determine the exact lag time between pre- and post-intervention. We propose a novel continuous transitional data-driven hybrid methodology using a non-linear approach based on a combination of stochastic and artificial intelligence methods that facilitate the evaluation of ITS data without knowledge of lag time. Understanding the influence of implemented intervention on outcome(s) is imperative for decision makers in order to manage health systems accurately and in a timely manner. METHODS: To validate a developed hybrid model, we used, as an example, a published dataset based on a real health problem on the effects of the Italian smoking ban in public spaces on hospital admissions for acute coronary events. We employed a continuous methodology based on data preprocessing to identify linear and nonlinear components in which autoregressive moving average and generalized structure group method of data handling were combined to model stochastic and nonlinear components of ITS. We analyzed the rate of admission for acute coronary events from January 2002 to November 2006 using this new data-driven hybrid methodology that allowed for long-term outcome prediction. RESULTS: Our results showed the Pearson correlation coefficient of the proposed combined transitional data-driven model exhibited an average of 17.74% enhancement from the single stochastic model and 2.05% from the nonlinear model. In addition, data demonstrated that the developed model improved the mean absolute percentage error and correlation coefficient values for which 2.77% and 0.89 were found compared to 4.02% and 0.76, respectively. Importantly, this model does not use any predefined lag time between pre- and post-intervention. CONCLUSIONS: Most of the previous studies employed the linear regression and considered a lag time to interpret the impact of intervention on public health outcome. The proposed hybrid methodology improved ITS prediction from conventional methods and could be used as a reliable alternative in public health intervention evaluation.

A lack of genetically compatible mates constrains the spread of an invasive weed.

Introduced populations often experience lag times before invasion, but the mechanisms constraining rapid expansions of introduced populations are unclear. Solidago altissima is a North American native plant with highly invasive Japanese populations and introduced Australian populations that are not invasive despite the climatic and ecological suitability of the region. By contrasting Australian with Japanese populations, we tested the hypothesis that Australian population growth is limited by a lack of long-distance dispersal via seeds owing to a limited number of compatible mates. In the field, Australian populations rarely produced viable seeds. A cross-pollination experiment found that Australian plants are fertile, yet lack compatible mates within Australia. Genetic analysis revealed that Australian individuals descend from a small set of self-incompatible genetic clones, which explains the negligible seed set within Australia. Our results show that low genetic diversity, leading to mate incompatibility, inhibits invasiveness of Australian S.  altissima, and provides compelling evidence for genetic, rather than ecological, factors constraining invasion in Australia.

Effect of binary combinations of solvent systems on permeability profiling of pure agomelatine across rat skin: a comparative study with statistically optimized polymeric nanoparticles.

Objective: Agomelatine (AGM), an antidepressant drug has low biological half-life coupled with extensive hepatic first-pass metabolism. For effective treatment of depression, daily medication is required but irregular dose intake occurs due to psychological illness which can be overcome by development of transdermal drug delivery system. But for effective transdermal delivery permeation of AGM through stratum corneum is a crucial step. Thus present study was intended to formulate and optimize polymeric nanoparticles of agomelatine and to compare the effect of binary combinations of solvent system on permeability profiling of pure agomelatine with statistically optimized polymeric nanoparticles.Methods: Polymeric agomelatine nanoparticles (AGM-PNPs) were prepared by nano-precipitation method which was further optimized by experimental design and characterized by FTIR, DSC, XRD and SEM study while ex-vivo study was performed on adult male wistar rats.Results: The optimized formulation has particle size in nano range (107.64 nm) with low PDI (0.209), stable zeta potential (-15 mV) and high entrapment efficiency (81.91%). Ex-vivo analysis of optimized nanoparticles suggests that nanoparticles permeate faster compared to plain AGM, while, permeation profile of AGM was enhanced when combination of solvent systems were used. It was observed that among various solvent system 33% PG-ethanol showed maximum flux (148.48 ± 3.24 µg/cm2/h) and least lag time (4.04 ± 0.12 h). The flux was further enhanced (180.98 ± 2.54 µg/cm2/h) when 5%v/v transcutol-HP was added as penetration enhancer.Conclusion: The above observations concluded that binary combination of 33% PG-ethanol with 5 %v/v transcutol-HP can serve as a solvent system of choice for effective transdermal delivery of agomelatine via nanoparticulate system.

Goserelin Acetate Loaded Poloxamer Hydrogel in PLGA Microspheres: Core-Shell Di-Depot Intramuscular Sustained Release Delivery System.

This study aimed to prepare and optimize goserelin acetate (GOS) loaded hydrogel poly(d,l-lactic acid-co-glycolic acid) (PLGA) microsphere that is suitable for long-acting clinical treatment, investigate its structure, and regulate the initial release manner. Here, the PLGA microsphere containing Poloxamer hydrogel loaded with ∼15% (w/w) GOS was prepared by double-emulsion-solvent evaporation method and evaluated in terms of microscopic structure, physicochemical properties, and release manner in vitro and in vivo. Raman volume imaging and scanning electron microscopy studies revealed a core-shell Di-Depot structure of the microsphere, in which multi-GOS-loaded hydrogel depots were distributed in the core region. Under the interaction of hydrogel and PLGA depots, high encapsulation efficiency (94.16%) and low burst release (less than 2%) were achieved, along with the accompanying prolonged administration interval (49 days); an enhanced relative bioavailability 9.36-fold higher than that of Zoladex implant was also observed. Also, by addition of 1-5% acetic acid, the lag time was shortened to 6 days. The strategy for regulating the initial release provides new insights for manipulating the release behavior of the PLGA microspheres. The desirable property of the Poloxamer hydrogel PLGA microsphere indicated its promising application in controlled release drug delivery system.

Tyrosinase inhibitory study of flavonolignans from the seeds of Silybum marianum (Milk thistle).

Anti-melanogenesis effects of silymarin from milk thistle have been reported recently, but detailed tyrosinase inhibition properties of individual components have not been investigated. This study purported to substantiate tyrosinase inhibition and its mechanism based on a single metabolite. The responsible components for tyrosinase inhibition of target source were found out as flavonolignans which consist of isosilybin A (1), isosilybin B (2), silydianin (3), 2,3-dihydrosilychristin (4), silychristin A (5), silychristin B (6) and silybin (7), respectively. The isolated flavonolignans (1-7) inhibited both monophenolase (IC50 = 1.7-7.6 µM) and diphenolase (IC50 = 12.1-44.9 µM) of tyrosinase significantly. Their inhibitions were 10-fold effective in comparison with their mother skeletons (8-10). Inhibitory functions were also proved by HPLC analysis using N-acetyl-l-tyrosine as substrate. The predominant formation of Emet·I was confirmed from a long prolongation of lag time and a decrease of the static state activity of the enzyme. All tested compounds had a significant binding affinity to tyrosinase with KSV values of 0.06-0.27 × 104 L·mol-1, which are well correlated with IC50s. In kinetic study, all flavonolignan (1-7) were mixed type I (KI < KIS) inhibitors, whereas their mother skeletons (8-10) were competitive ones. The UPLC-ESI-TOF/MS analysis showed that the isolated inhibitors are the most abundant metabolites in the target plant.

Socioeconomic and environmental factors associated with malaria hotspots in the Nanoro demographic surveillance area, Burkina Faso.

BACKGROUND: With limited resources and spatio-temporal heterogeneity of malaria in developing countries, it is still difficult to assess the real impact of socioeconomic and environmental factors in order to set up targeted campaigns against malaria at an accurate scale. Our goal was to detect malaria hotspots in rural area and assess the extent to which household socioeconomic status and meteorological recordings may explain the occurrence and evolution of these hotspots. METHODS: Data on malaria cases from 2010 to 2014 and on socioeconomic and meteorological factors were acquired from four health facilities within the Nanoro demographic surveillance area. Statistical cross correlation was used to quantify the temporal association between weekly malaria incidence and meteorological factors. Local spatial autocorrelation analysis was performed and restricted to each transmission period using Kulldorff's elliptic spatial scan statistic. Univariate and multivariable analysis were used to assess the principal socioeconomic and meteorological determinants of malaria hotspots using a Generalized Estimating Equation (GEE) approach. RESULTS: Rainfall and temperature were positively and significantly associated with malaria incidence, with a lag time of 9 and 14 weeks, respectively. Spatial analysis showed a spatial autocorrelation of malaria incidence and significant hotspots which was relatively stable throughout the study period. Furthermore, low socioeconomic status households were strongly associated with malaria hotspots (aOR = 1.21, 95% confidence interval: 1.03-1.40). CONCLUSION: These fine-scale findings highlight a relatively stable spatio-temporal pattern of malaria risk and indicate that social and environmental factors play an important role in malaria incidence. Integrating data on these factors into existing malaria struggle tools would help in the development of sustainable bottleneck strategies adapted to the local context for malaria control.

Influence of different storage conditions on the performance of spray-dried yogurt used as inoculum for milk fermentation.

A commercial drinkable yogurt with and without 4% of added trehalose (as cell protectant) was spray-dried obtaining a powder with low water activity (aw). Total bacterial count in the powder was between 8.48-8.90 log cfu/g. The dried yogurt was stored: (i) at 38 °C and aw = 0.33; (ii) at 38 °C in hermetically sealed flasks (aw = 0.21/0.22); (iii) in a cyclic temperature chamber (10-20 °C) in hermetically sealed flasks (aw = 0.21/0.22). Whole milk was then fermented by adding an inoculum of spray-dried yogurt after storage under these different conditions. The kinetics of acidification showed the presence of a lag time which was strongly dependent on storage conditions. The data was fitted with a logistic type equation from which the lag time was calculated. To evaluate structural differences among samples, Fourier Transform Infrared spectra (FTIR) were recorded. Partial Least Squares (PLS) models enabled a good correlation between lag time of fermentation and FTIR spectra. The lag time for yogurt powder stored at aw about 0.21/0.22 and cyclic temperature 10-20 °C remained approximately constant over the 12 weeks of storage, while all the other conditions resulted in a dramatic increase. The addition of trehalose had a small influence on lag time and, therefore, as a protectant of lactobacilli.

Fibril Nucleation Kinetics of a Pharmaceutical Peptide: The Role of Conformation Stability, Formulation Factors, and Temperature Effect.

Peptide aggregation, such as the formation of fibrils, could pose a significant challenge for the stability of parenteral peptide drugs. To ensure a robust peptide formulation, a thorough understanding of aggregation kinetics and the development of appropriate accelerated testing conditions are necessary. The present research investigated factors that impact the fibrillation kinetics of a helical 29mer pharmaceutical peptide (peptide A) and attempts to correlate results of accelerated kinetic studies with real time kinetics. Conformational flexibility of the peptide and its potential impact on aggregation kinetics were thoroughly evaluated. Three orthogonal approaches to evaluate aggregation kinetics were assessed, thioflavin T fluorescence, turbidity, and soluble peptide concentration. The results from the methods demonstrated that peptide A showed nucleated polymerization kinetics. The lag time of the fibrillation process depends heavily on pH, ionic strength, temperature, agitation, and substrate interface. The temperature-dependent fibril nucleation kinetics follow Arrhenius behavior, despite a helical fold in the peptide structure. This finding suggests a potential opportunity to leverage accelerated testing conditions to project the long-term performance at storage temperatures. The present study provides both fundamental understanding and practical approaches to mitigate the aggregation risk for pharmaceutical peptides with a strong tendency to form fibrils.