Ultra-trace levels voltammetric determination of Pb2+ in the presence of Bi3+ at food samples by a Fe3O4@Schiff base Network1 modified glassy carbon electrode

In this research, a highly sensitive electrochemical sensor was developed for the square wave anodic stripping voltammetric determination of Pb²⁺ at ultra-trace levels. A Glassy carbon electrode was modified with an in-situ electroplated bismuth film and the nanocomposite of a recently synthesized melamine based covalent organic framework (schiff base network₁ (SNW₁)) and Fe₃O₄ nanoparticles (Fe₃O₄@SNW₁). The obtained results exhibit clearly that combination of Fe₃O₄@SNW₁ and in-situ electroplated bismuth film enhances the sensitivity of the modified electrode towards Pb²⁺ remarkably. A Plackett-Burman design was implemented for screening experimental factors to specify the significant variables influencing the sensitivity of the electroanalytical method. Afterward, the effective factors were optimized using Box-Behnken design (BBD). Under optimized conditions, the proposed electrode showed a linear response towards Pb²⁺ in the concentration range of 0.003-0.3 μmol L^-1 with the detection limit of 0.95 nmol L^-1. The selectivity of the fabricated electrode towards different ionic species were checked out and no serious interference was observed. At the end, the application of the designed sensor in the determination of Pb²⁺ at 10 different edible specimens were investigated and the obtained recovery values were in the range of (95.56-106.64%) indicating the successful performance of the designed sensor.

Assessment of nano lipid carrier loaded transdermal patch of rizatriptan benzoate

BACKGROUND

Migraine is a neurological disorder and is accompanied by different painful episodes. Hence the maintenance of a steady-state concentration of drug can be beneficial for the patients suffering with migraine. The present investigation focuses on the development of nano lipid carriers (NLCs) loaded transdermal patch of rizatriptan benzoate to sustain the effect of the drug for the enhancement of therapeutic effects.

METHOD

Stearic acid and peanut oil were used to make the NLCs. A central composite design was employed to observe the effect of formulation factors like solid lipid ratio, phase volume ratio, and concentration of surfactants on the formation of nanoparticles. The effects were evaluated for the responses like particle size and entrapment of the drug in the nanocarriers. The optimized formulation was subjected to compatibility, thermal, surface characteristics, and surface morphology studies. The optimized formulation was dispersed in HPMC 15CPS and PVP K30 polymer matrix and the transdermal patch was evaluated for its mechanical properties, drug release study, and skin irritation study.

RESULTS

The experimental design was suitable to produce nanosized stable lipid carriers of the drug with high drug entrapment. The drug and excipients were found to be compatible. The thermal and surface characteristics study proved the high loading of drug in the nanoparticles. The surface morphology study showed the formation of irregular-shaped NLCs. The transdermal patch had good mechanical properties. The ex vivo study of the formulated patch showed a sustained release of the drug over 24h. No skin irritation was reported from the transdermal patch.

CONCLUSION

Therefore, it can be concluded that the nanoparticles loaded transdermal patch of rizatriptan benzoate can be promising in controlling the divergent phases of migraine.

Sex-dependent host-microbiome dynamics in zebrafish: Implications for toxicology and gastrointestinal physiology

The physiology of males and females can be vastly different, complicating interpretation of toxicological and physiological data. The objectives of this study were to elucidate the sex differences in the microbiome-gastrointestinal (GI) transcriptome of adult zebrafish. We compared microbial composition and diversity in both males and females fed the same diet and housed in the same environment. There were no sex-specific differences in weight gain nor gastrointestinal morphology based on histopathology. There was no difference in gut microbial diversity, richness (Shannon and Chao1 index) nor predicted functional composition of the microbiome between males and females. Prior to post-hoc correction, male zebrafish showed higher abundance for the bacterial families Erythrobacteraceae and Lamiaceae, both belonging to the phyla Actinobacteria and Proteobacteria. At the genus level, Lamia and Altererythrobacter were more dominant in males and an unidentified genus in Bacteroidetes was more abundant in females. There were 16 unique differentially expressed transcripts in the gastrointestinal tissue between male and female zebrafish (FDR corrected, p < 0.05). Relative to males, the mRNA expression for trim35-9, slc25a48, chchd3b, csad, and hsd17b3 were lower in female GI while cyp2k6, adra2c, and bckdk were higher in the female GI. Immune and lipid-related gene network expression differed between the sexes (i.e., cholesterol export and metabolism) as well as networks related to gastric motility, gastrointestinal system absorption and digestion. Such data provide clues as to putative differences in gastrointestinal physiology between male and female zebrafish. This study identifies host-transcriptome differences that can be considered when interpreting the microgenderome of zebrafish in studies investigating GI physiology and toxicology of fishes.

The boosted activity of AgI/BiOI nanocatalyst: a RSM study towards Eriochrome Black T photodegradation

Nowadays, critical environmental pollution needs some novel, simple, effective, and cost-effective catalysts with high efficiency in the visible region of the light. Thus, the AgI/BiOI coupled nanocatalyst sample (CS) was prepared and briefly characterized. The pH_pzc values of 6.2, 5.4, and 4.5 were estimated for AgI, BiOI, and AgI/BiOI samples. Based on the PXRD results, average crystallite sizes of 35.2, 34.7, and 34.1 nm were obtained for AgI, BiOI, and AgI/BiOI samples from the Scherrer formula and 38.3, 25.6, and 25.6 nm by the Williamson-Hall formula. SEM image confirmed a sheet-like BiOI morphology covered by AgI nanoparticles. The simultaneous interactions of the influencing variables on the boosted photocatalytic activity of CS sample towards Eriochrome Black T (EBT) were evaluated by response surface methodology (RSM) (under 100-W tungsten lamp irradiation with 230 mW/m².nm irradiance). The goodness of the model was confirmed by the significance of the model (F value of 65.68 > F_{0.05, 14, 13} = 2.55) and a non-significant LOF (F value of 0.97 < F_{0.05, 10, 3} = 8.79) at a 95% confidence interval obtained in ANOVA analysis of the results. The center point runs have the following conditions: catalyst dose: 0.68 g/L; pH: 7.5; C_EBT: 7.25 mg/L; and irradiation time: 53.5 min, while the optimal run included the following conditions: catalyst dose: 1.0 g/L; pH: 4; C_EBT: 10 mg/L; and irradiation time: 80 min. About 95% of EBT molecules were degraded in the optimal conditions.

In-situ sorbent formation for the extraction of pesticides from honey

An organic polymer was re-precipitated in solution to use as an adsorbent in dispersive solid phase extraction of some pesticides from honey samples prior to their determination by high performance liquid chromatography-tandem mass spectrometry. In this approach, different deep eutectic solvents were prepared using lysine and their ability in elution of the analytes from the adsorbent surface were tested. A diluted honey solution was transferred into a glass test tube and then a solution of polystyrene dissolved in dimethylformamide was injected into the solution. By doing this, polystyrene re-precipitated in the solution and dispersed in whole parts of it as many tiny particles. Then the mixture was centrifuged and the adsorbed analytes on the particles were eluted using a proper hydrophilic deep eutectic solvent. Central composite design approach was used for optimization of effective parameters. The limits of detection and quantification were in the ranges of 0.06-0.20 and 0.22-0.69 ng/g, respectively. The calibration curves obtained by matrix-matched standard solutions were linear in the range of 0.69-500 ng/g with coefficient of determinations ≥0.9962. The method provided high extraction recoveries (70-99%) and enrichment factors (140-198), and an acceptable precision (relative standard deviations ≤7.1%). This article is protected by copyright. All rights reserved.

Experimental design and optimization of a novel dual-release drug delivery system with therapeutic potential against infection with Helicobacter pylori

The objective of this study was to develop clarithromycin-loaded lipid nanocarriers and incorporate them into microcapsules for pH-specific localized release of clarithromycin in the Helicobacter pylori microenvironment in order to obtain a gastro-retentive and pH-sensitive formulation. A Plackett-Burman design was applied to identify the effect of 5 factors on 3 responses. Then, a central composite design was applied to estimate the most important factors leading to the best compromise between lower particle size, polydispersity index and particle size changes. The optimized clarithromycin-loaded nanocapsules were employed to generate microcapsules by different methodologies. Nanocarriers and microcapsules were characterized in vitro. Experimental design and conditions were optimized to obtain nanocapsules of around 100 nm by a modified phase inversion-based process. High particle size homogeneity and high stability were achieved. At 4 °C both optimized lipid nanocapsules were stable during at least 365 days, confirming stability under those conditions. Clarithromycin incorporation in the nanocarrier was effective. Both types of microcoating were evaluated regarding their pH sensitivity. Spray drying microcapsules exhibited similar and uncontrolled release profiles at pH 2 and 7.4. Alternatively, when microcoatings were generated using an Encapsulator, release was insignificant at pH 2, while at pH 7.4 release was triggered, and appeared more appropriate to formulate microcapsules that release nanocarriers under pH neutral Helicobacter pylori microenvironment conditions, thereby permitting effective drug delivery in infected locations. The release of clarithromycin from lipid nanocarrier loaded microcapsules was pH-sensitive suggesting that this could be an effective strategy for clarithromycin delivery to the Helicobacter pylori microenvironment. Clarithromycin nanocapsules with and without microcoating showed a high anti-Helicobacter pylori activity in vitro.

Development and validation of HPLC-DAD and LC-(ESI)/MS methods for the determination of sulfasalazine, mesalazine and hydrocortisone 21-acetate in tablets and rectal suppositories: In vitro and ex vivo permeability studies

Controlled-release tablets and rectal suppositories of sulfasalazine (SLF) and hydrocortisone 21-acetate (HA) were prepared as recommended dosage forms for the treatment of acute episodes of ulcerative colitis, in patients who do not respond to monotherapy. A High-Performance Liquid Chromatography (HPLC) Diode-array method with a gradient elution mobile phase was developed to evaluate the production quality of both formulations (assay and dissolution profiles in gastric and intestinal fluids). Method's validation was carried out providing good linearity (r ≥ 0.9995), precision (RSD < 1.53%), recovery (96.9% - 103.7%) and limits of detection (LOD_SLF = 12 ng/mL, LOD_HA = 15 ng/mL). Experimental design and Plackett-Burman methodology was constructed to study the robustness of the analysis. In all composite substrates, a freezing lipid precipitation approach was used as purification step. The method was optimized by applying Central Composite design mode. The in-vitro/ex-vivo permeability studies of both formulations were evaluated by a Liquid Chromatography-Electron Spray Ionization Mass Spectrometry (LC-ESI/MS) +/- mode. The analysis of sulfamethazine (internal standard, SLM, m/z 279), HA (m/z 449, [M + HCOO]^-), SLF (m/z 399) and its active metabolite mesalazine (MSL, m/z 154) was performed using a C₁₈ column and gradient elution. The validation of the method met the requirements of the International Council for Harmonization (ICH) (r ≥ 0.9997, RSD ≤ 4.62%, Recovery > 95%, LOD_SLF = 1.28 ng/mL, LOD_HA = 1.07 ng/mL, LOD_MSL = 3.16 ng/mL). Based on the results, important conclusions were drawn concerning the role of excipients and SLF metabolism.

Planning, design and logistics of a decision analysis study: The FBI/Ames study involving forensic firearms examiners

This paper describes design and logistical aspects of a decision analysis study to assess the performance of qualified firearms examiners working in accredited laboratories in the United States in terms of accuracy (error rate), repeatability, and reproducibility of decisions involving comparisons of fired bullets and cartridge cases. The purpose of the study was to validate current practice of the forensic discipline of firearms/toolmarks (F/T) examination. It elicited error rate data by counting the number of false positive and false negative conclusions. Preceded by the experimental design, decisions, and logistics described herein, testing was ultimately administered 173 qualified, practicing F/T examiners in public and private crime laboratories. The first round of testing evaluated accuracy, while two subsequent rounds evaluated repeatability and reproducibility of examiner conclusions. This project expands on previous studies by involving many F/T examiners in challenging comparisons and by executing the study in the recommended double-blind format.

Research on agroforestry systems and biodiversity conservation: what can we conclude so far and what should we improve?

Through a meta-analysis, Mupepele et al. (BMC Ecol Evol 21:1-193, 2021) assessed the effects of European agroforestry systems on biodiversity, estimated by species richness or species diversity. They showed that the effects of silvoarable and silvopastoral systems depend on the systems they are compared to and the taxa studied. Further, they found that only silvoarable systems increased species richness or diversity, compared to cropland. The authors conclude that agroforestry systems have weak effects on biodiversity and that landscape context or land-use history are probably more important than the practice of agroforestry in itself. However, we draw attention to important shortcomings in this meta-analysis, which downplay the potential of agroforestry for biodiversity conservation in agricultural landscapes. We hope that the meta-analysis by Mupepele et al. (BMC Ecol Evol 21:1-193, 2021), and our comments, will contribute to improving the quality of research on agroforestry systems and biodiversity conservation.

Experimental design of ligandless sonication-assisted liquid- phases microextraction based on hydrophobic deep eutectic solvents for accurate determination of Pb(II) and Cd(II) from waters and food samples at trace levels

A straightforward, accurate and efficient analytical procedure was developed by ligandless sonication-assisted liquid- phases microextraction based on hydrophobic deep eutectic solvents (SA-LPME-HDES) to trace toxic Pb(II) and Cd(II) in waters and foods. Optimization of the SA-LPME-HDES procedure was carried out by Box-Behnken design. Under optimum conditions, linear ranges for Pb(II) and Cd(II) were 0.8-350 (r²:0.9962) and 1.5-500 µg L^-1 (r²: 0.9937), respectively. Relative standard deviations (N = 5, 10 µg L^-1) were 1.4% for Pb(II) and 1.6% for Cd(II), respectively. Limits of detection were 0.24, and 0.46 µg L^-1, respectively. The accuracy was evaluated by the analysis of two certified reference materials and the results were to be in agreement with the certified values. The SA-LPME-HDES method was successfully applied to tap water, mineral water, river water, well-water, sesame, peanut, eggplant, corn, wheat, soy and cucumber. The SA-LPME-HDES method allows operational simplicity, green, and low cost when compared with some microextraction procedure.

OA foundations - experimental models of osteoarthritis

Osteoarthritis (OA) is increasingly recognised as a disease of diverse phenotypes with variable clinical presentation, progression, and response to therapeutic intervention. This same diversity is readily apparent in the many animal models of OA. However, model selection, study design, and interpretation of resultant findings, are not routinely done in the context of the target human (or veterinary) patient OA sub-population or phenotype. This review discusses the selection and use of animal models of OA in discovery and therapeutic-development research. Beyond evaluation of the different animal models on offer, this review suggests focussing the approach to OA-animal model selection on study objective(s), alignment of available models with OA-patient sub-types, and the resources available to achieve valid and translatable results. How this approach impacts model selection is discussed and an experimental design checklist for selecting the optimal model(s) is proposed. This approach should act as a guide to new researchers and a reminder to those already in the field, as to issues that need to be considered before embarking on in vivo pre-clinical research. The ultimate purpose of using an OA animal model is to provide the best possible evidence if, how, when and where a molecule, pathway, cell or process is important in clinical disease. By definition this requires both model and study outcomes to align with and be predictive of outcomes in patients. Keeping this at the forefront of research using pre-clinical OA models, will go a long way to improving the quality of evidence and its translational value.

Quantifying the importance of plastic pollution for the dissemination of human pathogens: The challenges of choosing an appropriate 'control' material

Discarded plastic wastes in the environment are serious challenges for sustainable waste management and for the delivery of environmental and public health. Plastics in the environment become rapidly colonised by microbial biofilm, and importantly this so-called 'plastisphere' can also support, or even enrich human pathogens. The plastisphere provides a protective environment and could facilitate the increased survival, transport and dissemination of human pathogens and thus increase the likelihood of pathogens coming into contact with humans, e.g., through direct exposure at beaches or bathing waters. However, much of our understanding about the relative risks associated with human pathogens colonising environmental plastic pollution has been inferred from taxonomic identification of pathogens in the plastisphere, or laboratory experiments on the relative behaviour of plastics colonised by human pathogens. There is, therefore, a pressing need to understand whether plastics play a greater role in promoting the survival and dispersal of human pathogens within the environment compared to other substrates (either natural materials or other pollutants). In this paper, we consider all published studies that have detected human pathogenic bacteria on the surfaces of environmental plastic pollution and critically discuss the challenges of selecting an appropriate control material for plastisphere experiments. Whilst it is clear there is no 'perfect' control material for all plastisphere studies, understanding the context-specific role plastics play compared to other substrates for transferring human pathogens through the environment is important for quantifying the potential risk that colonised plastic pollution may have for environmental and public health.

Portable smartphone-based colorimetric system for simultaneous on-site microfluidic paper-based determination and mapping of phosphate, nitrite and silicate in coastal waters

Early and on-site detection of environmental contaminations and physicochemical parameters of seawater is increasingly preferred to guarantee hazard minimization in many settings. In this paper, we describe a combination of microfluidic paper-based sensors (µPADs) and an Android-based smartphone application (App) for simultaneous on-site quantification of phosphate (PO₄-P), silicate (SiO₃-Si) and nitrite (NO₂-N) in coastal seawater samples. The developed App can on-site capture, process, and quantify the µPAD colorimetric outputs. This App uses an image processing algorithm for quantifying color intensity and relating the RGB components to the analyte concentrations. The GPS-tagged data can be stored on the smartphone or sent via social networks. The significant factors affecting the detection of the analytes were optimized using Box-Behnken design. Under optimized parameters, the proposed method presented the linear ranges between 5 and 100 µg L^-1 for phosphate (R² = 0.9909), 5 to 100 µg L^-1 (R² = 0.9819) for nitrite and 10 to 600 µg L^-1 (R² = 0.9933) for silicate. The LODs of the method for detection of phosphate, nitrite and silicate were 1.52 µg L^-1, 0.61 µg L^-1 and 3.74 µg L^-1, respectively. The device was successfully used to simultaneous analyze and map the PO₄-P, SiO₃-Si and NO₂-N of Bushehr coastal seawater samples (Iran). The results were confirmed by the lab-based conventional colorimetric methods using spectrophotometer.

Social distancing, trust and post-COVID-19 recovery

With the tourism and hospitality sector reopening post-lockdown of COVID-19, the recovery of customers' purchase intentions is essential to reboot the sector. This study aims to examine the relationship between social distancing measures and purchase intentions in the UK's restaurant and hotel sectors using a propensity score weighting experimental design method. The findings suggest that the impact of social distancing measures on purchase intentions is mediated by the trust in the targeted restaurant and hotel. Risk tolerance significantly moderates the influence of social distancing measures on trust; (non-) cash promotions have an insignificant impact on purchase intentions. The introduction of the propensity score weighting scheme addresses the endogeneity caused by the sampling bias in non-probability sampling experiment studies.

Sexual Consent Perceptions of a Fictional Vignette: A Latent Growth Curve Model

Sexual consent can be conceptualized as a process of accumulating cues that build toward and continue throughout a consensual sexual encounter. How people perceive the cues of others during this process is an important aspect of consent. However, previous research has not investigated the trajectories of people's consent perceptions throughout such a process. Using a novel staggered vignette protocol, we examined participants' (N = 1218; 64.4% female) perceptions of fictional targets' sexual consent at 11 time points. We tested latent growth curve models using multilevel structural equation modeling to examine trajectories in consent perceptions over the course of the vignette. We hypothesized that mean differences and rates of change would be associated with several constructs relevant to sexual consent. We found that initial consent perceptions and trends over the course of the vignette varied by whether the participant was a university student, by an alcohol manipulation in the vignette, by the fictional target's sex, and by type of sexual behavior. Researchers should examine whether our findings on consent perceptions of a fictional vignette extend to people's actual sexual encounters, including potential associations between the three primary aspects of sexual consent: perceptions, feelings, and communication.

Determination of benzotriazole and benzothiazole derivatives in tea beverages by deep eutectic solvent-based ultrasound-assisted liquid-phase microextraction and ultrahigh-performance liquid chromatography-high resolution mass spectrometry

Benzotriazole (BTRs) and benzothiazole (BTHs) derivatives are a group of high production volume chemicals with emerging health concern, which found in tea beverages raising potential risks for food safety and human health. The present work describes a simple method using a "green" deep eutectic solvent (DES) based-ultrasound-assisted liquid-phase microextraction (UALPME) to rapidly extract BTRs and BTHs from tea beverages, and then applying UHPLC-electrospray ionization (+)-quadrupole time-of-flight mass spectrometry for detection and quantification. To overcome the challenges related to different experimental conditions, a Factorial Multilevel Categoric Design and a Face Centered Central Composite Design were applied to screen and optimize the parameters for the DES-UALPME procedure, respectively. After optimization, the method was validated and shown to possess low limits of quantification (LOQs; 1.5-12 ng mL^-1), high precision (3-13%), and satisfactory accuracy (65-107%). The developed method was then successfully applied for the analysis of some selected BTRs and BTHs in tea beverages.

Should I use fixed effects or random effects when I have fewer than five levels of a grouping factor in a mixed-effects model?

As linear mixed-effects models (LMMs) have become a widespread tool in ecology, the need to guide the use of such tools is increasingly important. One common guideline is that one needs at least five levels of the grouping variable associated with a random effect. Having so few levels makes the estimation of the variance of random effects terms (such as ecological sites, individuals, or populations) difficult, but it need not muddy one's ability to estimate fixed effects terms-which are often of primary interest in ecology. Here, I simulate datasets and fit simple models to show that having few random effects levels does not strongly influence the parameter estimates or uncertainty around those estimates for fixed effects terms-at least in the case presented here. Instead, the coverage probability of fixed effects estimates is sample size dependent. LMMs including low-level random effects terms may come at the expense of increased singular fits, but this did not appear to influence coverage probability or RMSE, except in low sample size (N = 30) scenarios. Thus, it may be acceptable to use fewer than five levels of random effects if one is not interested in making inferences about the random effects terms (i.e. when they are 'nuisance' parameters used to group non-independent data), but further work is needed to explore alternative scenarios. Given the widespread accessibility of LMMs in ecology and evolution, future simulation studies and further assessments of these statistical methods are necessary to understand the consequences both of violating and of routinely following simple guidelines.

Microarray Data Preprocessing: From Experimental Design to Differential Analysis

DNA microarray data preprocessing is of utmost importance in the analytical path starting from the experimental design and leading to a reliable biological interpretation. In fact, when all relevant aspects regarding the experimental plan have been considered, the following steps from data quality check to differential analysis will lead to robust, trustworthy results. In this chapter, all the relevant aspects and considerations about microarray preprocessing will be discussed. Preprocessing steps are organized in an orderly manner, from experimental design to quality check and batch effect removal, including the most common visualization methods. Furthermore, we will discuss data representation and differential testing methods with a focus on the most common microarray technologies, such as gene expression and DNA methylation.

Preparation and Curation of Multiyear, Multilocation, Multitrait Datasets

Genome-wide association studies (GWAS) are a powerful approach to dissect genotype-phenotype associations and identify causative regions. However, this power is highly influenced by the accuracy of the phenotypic data. To obtain accurate phenotypic values, the phenotyping should be achieved through multienvironment trials (METs). In order to avoid any technical errors, the required time needs to be spent on exploring, understanding, curating and adjusting the phenotypic data in each trial before combining them using an appropriate linear mixed model (LMM). The LMM is chosen to minimize as much as possible any effect that can lead to misestimation of the phenotypic values. The purpose of this chapter is to explain a series of important steps to explore and analyze data from METs used to characterize an association panel. Two datasets are used to illustrate two different scenarios.

Designing Experiments for Physiological Phenomics

Phenomics has emerged as the technology of choice for understanding quantitative genetic variation in plant physiology and plant breeding. Phenomics has allowed for unmatched precision in exploring plant life cycles and physiological patterns. As new technologies are developed, it is still vital to follow best practices for designing and planning to be able to fully exploit any experimental results. Here we describe the basic - but sometimes overlooked - considerations of a phenomics experiment to help you maximize the value from the data collected: choosing population and location, accounting for sources of variation, establishing a timeline, and leveraging ground-truth measurements.

Plant-wide investigation of sulfur flows in a water resource recovery facility (WRRF)

Even though sulfur compounds and their transformations may strongly affect wastewater treatment processes, their importance in water resource recovery facilities (WRRF) operation remains quite unexplored, notably when it comes to full-scale and plant-wide characterization. This contribution presents a first-of-a-kind, plant-wide quantification of total sulfur mass flows for all water and sludge streams in a full-scale WRRF. Because of its important impact on (post-treatment) process operation, the gaseous emission of sulfur as hydrogen sulfide (H₂S) was also included, thus enabling a comprehensive evaluation of sulfur flows. Data availability and quality were optimized by experimental design and data reconciliation, which were applied for the first time to total sulfur flows. Total sulfur flows were successfully balanced over individual process treatment units as well as the plant-wide system with only minor variation to their original values, confirming that total sulfur is a conservative quantity. The two-stage anaerobic digestion with intermediate thermal hydrolysis led to a decreased sulfur content of dewatered sludge (by 36%). Higher (gaseous) H₂S emissions were observed in the second-stage digester (42% of total emission) than in the first one, suggesting an impact of thermal treatment on the production of H₂S. While the majority of sulfur mass flow from the influent left the plant through the treated effluent (> 95%), the sulfur discharge through dewatered sludge and gaseous emissions are critical. The latter are indeed responsible for odour nuisance, lower biogas quality, SO₂ emissions upon sludge combustion and corrosion effects.

The gap between atmospheric nitrogen deposition experiments and reality

Anthropogenic activities have dramatically altered the global nitrogen (N) cycle. Atmospheric N deposition, primarily from combustion of biomass and fossil fuels, has caused acidification of precipitation and freshwater, and triggered intense research into ecosystem responses to this pollutant. Experimental simulations of N deposition have been the main scientific tool to understand ecosystem responses, revealing dramatic impacts on soil microbes, plants, and higher trophic levels. However, comparison of the experimental treatments applied in the vast majority of studies with observational and modelled N deposition reveals a wide gulf between research and reality. While the majority of experimental treatments exceed 100 kg N ha^-1 y^-1, global median land surface deposition rates are around 1 kg N ha^-1 y^-1 and only exceed 10 kg N ha^-1 y^-1 in certain regions, primarily in industrialized areas of Europe and Asia and particularly in forests. Experimental N deposition treatments are in fact similar to mineral fertilizer application rates in agriculture. Some ecological guilds, such as saprotrophic fungi, are highly sensitive to N and respond differently to low and high N availability. In addition, very high levels of N application cause changes in soil chemistry, such as acidification, meaning that unrealistic experimental treatments are unlikely to reveal true ecosystem responses to N. Hence, despite decades of research, past experiments can tell us little about how the biosphere has responded to anthropogenic N deposition. A new approach is required to improve our understanding of this important phenomenon. First, characterization of N response functions using observed N deposition gradients. Second, application of experimental N addition gradients at realistic levels over long periods to detect cumulative effects. Third, application of non-linear meta-regressions to detect non-linear responses in meta-analyses of experimental studies.

Key aroma compounds of Canastra cheese: HS-SPME optimization assisted by olfactometry and chemometrics

An analytical method was developed to determine volatile compounds (VC) that contribute to the aroma of cheese from Serra da Canastra (Brazil) and evaluate them in three ripening stages (fresh, short-ripened, and ripened) via headspace solid-phase microextraction (HS-SPME) combined with gas chromatography (GC). Proximate and fatty acid compositions were determined to observe whether there would be changes during ripening. Multivariate designs were applied to optimize the extraction parameters of volatile compounds and assisted by GC olfactometry (GC-O) and chemometrics. The adopted strategy revealed that the best extraction condition requires 10 min of equilibration, 75.2 min of fiber exposure at 40 °C, and 1 g of sample. The data obtained evidenced the alteration of the abundance of volatile compounds, fatty acids, and proximate composition of Canastra cheese during ripening. The fatty acid profile of the samples was mainly composed of palmitic, oleic, and stearic acids. This dairy product is rich in volatile compounds and formed primarily by alcohols (n = 14), acids (n = 13), and esters (n = 11). Olfactometry indicated that the VCs that most affected the aroma of ripened Canastra cheese were acetic acid, isobutyric acid, butanoic acid, and ethyl hexanoate. The method developed effectively discriminated against Canastra cheeses at their different ripening stages.

Bayesian optimization of comprehensive two-dimensional liquid chromatography separations

Comprehensive two-dimensional liquid chromatography (LC×LC), is a powerful, emerging separation technique in analytical chemistry. However, as many instrumental parameters need to be tuned, the technique is troubled by lengthy method development. To speed up this process, we applied a Bayesian optimization algorithm. The algorithm can optimize LC×LC method parameters by maximizing a novel chromatographic response function based on the concept of connected components of a graph. The algorithm was benchmarked against a grid search (11,664 experiments) and a random search algorithm on the optimization of eight gradient parameters for four different samples of 50 compounds. The worst-case performance of the algorithm was investigated by repeating the optimization loop for 100 experiments with random starting experiments and seeds. Given an optimization budget of 100 experiments, the Bayesian optimization algorithm generally outperformed the random search and often improved upon the grid search. Moreover, the Bayesian optimization algorithm offered a considerably more sample-efficient alternative to grid searches, as it found similar optima to the grid search in far fewer experiments (a factor of 16-100 times less). This could likely be further improved by a more informed choice of the initialization experiments, which could be provided by the analyst's experience or smarter selection procedures. The algorithm allows for expansion to other method parameters (e.g., temperature, flow rate, etc.) and unlocks closed-loop automated method development.