Planning and Analyzing a Low-Biomass Microbiome Study: A Data Analysis Perspective.

As investigations of low-biomass microbial communities have become more common, so too has the recognition of major challenges affecting these analyses. These challenges have been shown to compromise biological conclusions and have contributed to several controversies. Here, we review some of the most common and influential challenges in low-biomass microbiome research. We highlight key approaches to alleviate these potential pitfalls, combining experimental planning strategies and data analysis methods.

Anthropofabrication and the redressing of memory: an embodied approach to comparative cognition.

On what basis do researchers posit that humans and other animals share cognitive capacities? We argue that such claims are not based on inherent, pre-existing similarities, but rather emerge through a two-step process, which we will call 'anthropofabrication'. In the initial stage, embodied action-based strategies and environmental context in human studies are ignored owing to the need for measurement and quantification. Consequently, cognitive terms become disconnected from the context to which we apply them, and human classificatory cognitive terms are transformed into broad explanatory terms, assumed to be 'species-neutral'. The second phase entails translating and applying these generalized explanatory terms to specific nonverbal animals in ways that serve to further cloak differences between animals and other species. Here, again, researchers selectively discard contextual information to facilitate the comparison with humans. To limit anthropofabrication, we should (re)acknowledge that cognitive abilities are not species-neutral and cannot be detached from embodied action, perception and their context of occurrence. We illustrate our points about anthropofabrication using the example of memory research. This article is part of the theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'.

Design and optimization of acetazolamide nanoparticle-laden contact lens using statistical experimental design for controlled ocular drug delivery.

This study aims to formulate and evaluate Eudragit nanoparticles-laden hydrogel contact lenses for controlled delivery of acetazolamide (ACZ) using experimental design. Eudragit S-100 was selected for the preparation of nanoparticles. The optimization of Eudragit S100 concentration (X1), polyvinyl alcohol concentration (X2), and the sonication time (X3) was attempted by applying a central composite experimental design. Mean size of nanoparticles (nm), percent in vitro drug release and drug leaching from the ACZ-ENs laden contact lens were considered as dependent variables. Nanoparticles-laden contact lens was prepared through the direct loading method and characterized. Optimum check-point formulation was selected based on validated quadratic polynomial equations developed using response surface methodology. The optimized formulation of ACZ-ENs exhibited spherical shape with a size of 244.3 nm and a zeta potential of -13.2 mV. The entrapment efficiency of nanoparticles was found to be 82.7 ± 1.21%. Transparent contact lenses loaded ACZ-ENs were successfully prepared using the free radical polymerization technique. ACZ-ENs incorporated in contact lens exhibited a swelling of 83.4 ± 0.82% and transmittance of 80.1 ± 1.23%. ACZ-ENs showed a significantly lower burst release of the drug when incorporated in the contact lens and release was sustained over a period of 24 h. The sterilized formulation of ACZ-ENs laden contact lens did not show any sign of toxicity in rabbit eyes. ACZ-ENs incorporated in contact lens could be considered as a potential alternative in glaucoma patients due to their ability to provide sustained drug release and thus enhance patient compliance.

Refining urine collection in mice: Development of an innovative urine collection device.

Urine collection can be challenging in studies involving small rodents like mice, as the actual methods of collection are anxiogenic and constrain animal welfare while having high variability in the volume of urine collected. To improve the current methods and eventually reduce the impact on the well-being of mice, we developed an innovative 3D-printed urine collection device (UCD). This two-compartment UCD is shaped to fit in classical husbandry cages and allows urine collection by spontaneous urination from two mice housed in their own cage without cross-contamination while enabling potential social interactions. We used our UCD to study the evolution of urinary parameters related to renal functions in a model of antibody-mediated chronic kidney disease. Overall, we report here a time-saving and affordable method for urine collection providing a large amount of uncontaminated urine and which we believe may improve animal welfare in comparison with other methods.

Chemometrically-aided general approach to novel adsorbents studies: Case study on the adsorption of pharmaceuticals by the carbonized Ailanthus altissima leaves.

A chemometrically based approach was applied to select the most efficient drug adsorbent among the biochars obtained from the novel feedstock, the leaves of the invasive plant (Ailanthus altissima). The representative target adsorbates (atenolol, paracetamol, ketorolac and tetracycline) were selected on the basis of their physicochemical properties to cover a wide chemical space, which is the usual analytical challenge. Their adsorption was investigated using design of experiments as a comprehensive approach to optimise the performance of the adsorption system, rationalise the procedure and overcome common drawbacks. Among the response surface designs, the central composite design was selected as it allows the identification of important experimental factors (solid-to-liquid ratio, pH, ionic strength) and their interactions, and allows the selection of optimal experimental conditions to maximise adsorption performance. The biochars were prepared by pyrolysis at 500 °C and 800 °C (BC-500 and BC-800) and the ZnCl2-activated biochars were prepared at 650 °C and 800 °C (AcBC-650 and AcBC-800). The FTIR spectra revealed that increasing the pyrolysis temperature without activator decreases the intensity of all bands, while activation preserves functional groups, as evidenced by the spectra of AcBC-650 and AcBC-800. High temperatures during activation promoted the development of an efficient surface area, with the maximum observed for AcBC-800 reaching 347 m2 g-1. AcBC-800 was found to be the most efficient adsorbent with removal efficiencies of 34.1, 51.3, 55.9 and 38.2 % for atenolol, paracetamol, ketorolac and tetracycline, respectively. The models describing the relationship between the removal efficiency of AcBC-800 and the experimental factors studied, showed satisfactory predictive ability (predicted R2 > 0.8) and no significant lack-of-fit was observed. The results obtained, including the mathematical models, the properties of the adsorbates and the adsorbents, clearly indicate that the adsorption mechanisms of activated biochars are mainly based on hydrophobic interactions, pore filling and hydrogen bonding.

Solvent extraction of lithium from brines with high magnesium/lithium ratios: investigation on parameter interactions.

Solvent extraction of lithium from brine with a high Mg/Li ratio was investigated. Tributyl phosphate (TBP), ferric chloride (FeCl3), and kerosene were used as the extractant, co-extractant, and diluent, respectively. The mechanism of the extraction process was studied by LC-MS, UV-VIS, and FT-IR analyses. Effects of organic to aqueous phase volume ratio (O/A) on the extraction efficiency and separation factor were optimized. The effects of major parameters including Fe/Li molar ratio, hydrochloric acid concentration, and TBP volume percent as well as their interactions on the lithium extraction efficiency were evaluated using central composite design. These major parameters represent interactions within their selected ranges. While the lithium extraction efficiency as the response value in the experimental design showed the most sensitivity to the acid concentration, the separation factors were more affected by alteration in the TBP volume percent with the fixed optimum values of the other major parameters. The highest one-stage extraction efficiency of 76.3% and Li/Mg separation factor of 304 were obtained at the optimum conditions of Fe/Li = 2.99, HCl = 0.01 M, and TBP = 55%. The Mg/Li mass ratio could be significantly reduced from 192 in the feed to 1.5 in the stripping solution. Based on the findings, a schematic diagram of the process including extraction, stripping, and saponification steps was proposed.

Disentangling Selection into Mode from Mode Effects.

OBJECTIVES: We investigate the impact of data collection mode on responses to variables in NSHAP Round 4 and discuss how potential mode differences should (and should not) be addressed in substantive analyses. METHODS: Among the set of respondents who were eligible to be contacted remotely in Round 4, we randomly selected 398 to be contacted instead for an in-person interview. We compare response rates and the distributions of selected key outcomes among those 398 respondents to those among the control group who were initially approached remotely. As a contrast, we compare all R4 respondents according to the mode in which they completed the interview, including those not part of the randomized experiment. RESULTS: Among those included in the experiment, there was no evidence of systematic differences in responses to physical and mental health questions between remote and in-person modes, nor in responses to number recall measures. In-person respondents scored moderately lower on cognitive function measures requiring careful attention to a figure and/or task, though this difference became less with each similar item. Remote respondents named fewer social network members. Comparing all respondents according to their final mode yielded substantially different results in all cases. DISCUSSION: Mode did not appear to affect reports of physical and mental health based on a randomized comparison, though it did moderately affect other items in predictable ways. Naïve estimates of mode effects based on comparing all respondents according to mode yielded misleading results, and should not be used to adjust for mode differences in analyses.

Understanding coping with the climate crisis: an experimental study with young people on agency and mental health.

BACKGROUND: While the impact of climate change on mental health, especially in young people, has been acknowledged, underlying mechanisms of this relation remain elusive. Based on research on active coping, we explored effects of agency on anxiety and coping in an experimental design. We further examined the relation between mental health (i.e., psychopathology, depressiveness, trait anxiety), trait factors (i.e., climate distress, intolerance of uncertainty, trait coping), state anxiety and coping with climate distress. METHODS: 244 participants (15-25 years) watched a climate anxiety inducing video, followed by an agency manipulation (high agency vs. low agency vs. control). Trait mental health, intolerance of uncertainty, and climate distress and coping were examined as predictors of state anxiety and coping. RESULTS: State anxiety decreased in the high agency and control conditions, but not in the low agency condition. High agency led to increased meaning-focused coping and low agency to decreased meaning- and problem-focused coping. Trait mental health, problem-focused, and meaning-focused coping strategies each predicted their respective state counterparts. Emotion-focused coping was further predicted by all trait measures. CONCLUSION: The findings suggest a risk of low agency communication due to the lack of arousal decrease and lack of using functional coping in young people.

Effects of COVID-19-targeted non-pharmaceutical interventions on pediatric emergency department use: a quasi-experimental study interrupted time-series analysis in North Italian hospitals, 2017 to 2022.

Background: The use of Non-Pharmaceutical Interventions (NPIs) during the COVID-19 pandemic is debated. Understanding the consequences these measures may have on vulnerable populations including children and adolescents is important. Methods: This is a multicenter, quasi-experimental before-after study involving 12 hospitals of the North Italian Emilia-Romagna Region, with NPI implementation as the intervention event. The 3 years preceding NPI implementation (in March 2020) constituted the pre-pandemic phase. The subsequent 2 years were further subdivided into a school closure phase (SC) and a subsequent mitigation measures phase (MM) with milder restrictions. Interrupted Time Series (ITS) regression analysis was used to calculate PED Standardized Incidence Rate Ratios (SIRR) on the diagnostic categories exhibiting the greatest frequency and/or variation. Results: In the 60 months of the study there were 765,215 PED visits. Compared to the pre-pandemic rate, overall PED presentations dropped by 58 and 39% during SC and MM, respectively. "Symptoms, signs and Ill-defined conditions," "Injury and poisoning" and "Diseases of the Respiratory System" accounted for 74% of the reduction. A different pattern was instead seen for "Mental Disorders," which exhibited the smallest decrease during SC, and is the only category which rose already at the end of SC. ITS analysis confirmed the strong decrease during SC (level change, IRR 0.17, 95%CI 0.12-0.27) and a significant increase in MM (slope change, IRR 1.23, 95%CI 1.13-1.33), with the sharpest decline (-94%) and rise (+36%) observed in the "Diseases of the Respiratory System" category. Mental Disorders showed a significant increasing trend of 1% monthly over the whole study period exceeding pre-pandemic levels at the end of MM. Females and adolescents showed higher increasing rates both in SC and MM. Conclusion: NPIs appear to have influenced PED attendance in different ways according to diagnostic categories, mirroring different mechanisms of action. These effects are beneficial in some cases and harmful in others, and establishing a clear balance between pros and cons is a difficult task for public health decision makers. The role of NPIs on PED use appropriateness deserves investigation. The rise in pediatric mental disorders independent of the pandemic makes interventions addressing these issues urgent.

Optimizing Cr(VI) reduction to Cr(III) using Pd-CNTs nanocatalyst: kinetic Monte Carlo simulation and experimental design insights.

In this investigation, we explored the kinetics of Cr(VI) reduction to Cr(III) on carbon nanotube decorated with palladium (Pd-CNTs) nanocatalyst, using formic acid as the reducing agent. This study has been bone utilizing kinetic Monte Carlo simulation and experimental design methods. The mechanism and kinetic parameters of this reaction are provided. The effect various factors such as reaction time, pH level, dichromate (Cr2O72-) concentration, and formic acid concentration on Cr(VI) reduction was studied. Concentrations of HCOOH and Cr2O72- were identified as the crucial variables, while the HCOOH concentration has the most significant impact. Positive influences on Cr(VI) reduction were observed with increasing pH level and HCOOH concentration. Reaction time positively affects on Cr(VI) reduction efficiency. However, the concentration of Cr2O72- showed an increasing effect up to a threshold, negatively impacting the efficiency. The optimal conditions (Reaction time = 60 min, pH = 4.5, [Cr2O72-] = 5.05 × 10-3 M, and [HCOOH] = 0.95 M) for Cr(VI) reduction. At optimal conditions, the Cr(VI) reduction efficiency was obtained to be 100%.

Repeated exposure to multiple concurrent stressors alters visual processing in the adult posterior parietal cortex.

Chronic stress is well known to erode cognitive functions. Yet, our understanding of how repeated stress exposure impacts one of the fundamental bases of cognition: sensory processing, remains limited. The posterior parietal cortex (PPC) is a high order visual region, known for its role in visually guided decision making, multimodal integration, attention, and working memory. Here, we used functional measures to determine how repeated exposure to multiple concurrent stressors (RMS) affects sensory processing in the PPC in adult male mice. A longitudinal experimental design, repeatedly surveying the same population of neurons using in vivo two-photon imaging, revealed that RMS disrupts the balanced turnover of visually responsive cells in layer 2/3 of the PPC. Across the population, RMS-induced changes in visual responsiveness followed a bimodal distribution suggesting idiosyncratic stress effects. In cells that maintained their responsiveness across recording sessions, we found that stress reduced visual response magnitudes and feature selectivity. While we did not observe stress-induced elimination of excitatory synapses, noise correlation statistics indicated that RMS altered visual input to the neuronal population. The impact of RMS was restricted to visually evoked responses and was not evident in neuronal activity associated with locomotion onset. Together, our results indicate that despite no apparent synaptic reorganization, stress exposure in adulthood can disrupt sensory processing in the PPC, with the effects showing remarkable individual variation.

Experiences of early career researchers: Influences on the design and reporting of animal experiments, and the practical and emotional support needed to enhance best practice methods.

While best practice methodology in animal research aims to address reproducibility and translational issues, awareness and implementation remains low. Preclinical systematic reviews have highlighted many flaws, including issues with internal validity and reporting. With early career researchers (ECRs) heavily involved in all aspects of animal experiments, it is crucial we understand what shapes their research practices. Semi-structured interviews were conducted with 13 ECRs, including research masters, PhD and postdoctoral academics. Data were collected and analysed concurrently using constant comparison techniques and an iterative approach. Findings revealed low-level awareness of best practice recommendations but a desire to engage in dedicated workshops on designing and reporting animal experiments. Current laboratory practices and previous literature were main influences on research practice, more than institutional training. An unexpected finding was the discovery of ethical and emotional dilemmas ECRs faced when working with animals. This highlights the need for a multifaceted approach to better support junior researchers, both emotionally and practically, to encourage responsible science.

Unlocking the benefits of montessori-based reading activities in nursing home: A multiple baseline study on groups of individuals with severe dementia.

OBJECTIVE: Group activities are commonly offered to residents of nursing homes, and increasingly with a person-centred care approach. The aim of this study is to compare the impacts of a Montessori-based reading activity with a more traditional reading activity. METHOD: A multiple baseline design was used, with 3 groups of 5 older adults with moderate to severe dementia. All sessions were videorecorded and analysed by independent judges, blinded to our hypotheses and conditions. Impacts of the type of activity (storytelling or Montessori-based reading) on verbal interactions, engagement level, affect and behavioural aspects were estimated with both visual analyses and statistical analyses using the between-case standardised mean differences method. RESULTS: Significant differences were found in favour of the Montessori-based activities with regard to the number of verbal interactions, constructive and passive engagement and positive affect expressed, with moderate to large effect size (from 0.46 to 1.66). CONCLUSION: The Montessori-based reading group activity really seems to be preferable to a more traditional storytelling activity, with multiple benefits for residents. Depending on the preserved abilities and interests of the participants, it can also be aimed at people with severe dementia.

Perception-action coupling in anticipation research: a classification and its application to racket sports.

Anticipation is key to performance in many sports. By definition, anticipation as a perceptual-cognitive process is meant to inform action and help athletes reduce potential motor costs under spatiotemporal pressure. Anticipation research has repeatedly been criticized for neglecting action and raised the need for predominant testing under conditions of perception-action coupling (PAC). To the best of our knowledge, however, there is a lack of explicit criteria to characterize and define PAC conditions. This can lead to blurred terminology and may complicate interpretation and comparability of PAC conditions and results across studies. Here, we make a first proposal for a 7-level classification of PAC conditions with the defining dimensions of stimulus presentation and response mode. We hope this classification may constitute a helpful orientation for study planning and reporting in research on anticipation. Further, we illustrate the potential utilization of the PAC classification as a template for experimental protocol analysis in a review on anticipation in racket sports. Analysis of N = 115 studies reported in N = 91 articles confirms an underrepresentation of representative PAC conditions and reveals little change in PAC approaches over more than 40 years of research in that domain. We discuss potential reasons for these findings, the benefits of adopting the proposed PAC classification and reiterate the call for more action in anticipation research.

The Design and Optimality of Survey Counts: A Unified Framework Via the Fisher Information Maximizer.

Grouped and right-censored (GRC) counts have been used in a wide range of attitudinal and behavioural surveys yet they cannot be readily analyzed or assessed by conventional statistical models. This study develops a unified regression framework for the design and optimality of GRC counts in surveys. To process infinitely many grouping schemes for the optimum design, we propose a new two-stage algorithm, the Fisher Information Maximizer (FIM), which utilizes estimates from generalized linear models to find a global optimal grouping scheme among all possible N -group schemes. After we define, decompose, and calculate different types of regressor-specific design errors, our analyses from both simulation and empirical examples suggest that: 1) the optimum design of GRC counts is able to reduce the grouping error to zero, 2) the performance of modified Poisson estimators using GRC counts can be comparable to that of Poisson regression, and 3) the optimum design is usually able to achieve the same estimation efficiency with a smaller sample size.

A strategy for the efficient removal of acidic and basic dyes in wastewater by organophilic magadiite@alginate beads: Box-Behnken Design optimization.

In this study, four adsorbents were developed: layered silicate magadiite material (mag), Hexadecyltrimethylammonium intercalated magadiite (HDTMA@mag), a cross-linked composite of sodium alginate and magadiite (ALG@mag) and a cross-linked composite of sodium alginate and HDTMA@magadiite (ALG@HDTMA@mag). The adsorbents were evaluated for their effectiveness in removing of Methylene Blue (MB) and Eriochrome Black T (EBT) dyes. The prepared adsorbents were characterized using SEM, XRD, FTIR, and zeta potential measurements. Kinetic modeling results indicated that both film diffusion and intraparticle diffusion are useful as rate-determining processes in adsorption for all adsorbents. For both dyes, the Langmuir isotherm model provided a good correlation with the adsorption equilibrium data. ANOVA analysis for the best adsorbent (ALG@HDTMA@mag beads) revealed that MB removal was significantly influenced by the positive individual effects of contact time and ALG@HDTMA@mag dose. However, the individual effect of MB concentration exhibited an antagonistic effect throughout the adsorption process. The optimal parameters for achieving an adsorption capacity of 118.54 mg/g were a dye concentration of 60 ppm, a contact period of 1800 min, and an ALG@HDTMA@mag dose of 50 mg.

Considering ultraviolet radiation in experimental biology: a neglected pervasive stressor.

Ultraviolet radiation (UVR) is a pervasive factor that has shaped the evolution of life on Earth. Ambient levels of UVR mediate key biological functions but can also cause severe lethal and sublethal effects in a wide range of organisms. Furthermore, UVR is a powerful modulator of the effects of other environmental factors on organismal physiology, such as temperature, disease, toxicology and pH, among others. This is critically important in the context of global change, where understanding the effects of multiple stressors is a key challenge for experimental biologists. Ecological physiologists rarely afford UVR discussion or include UVR in experimental design, even when it is directly relevant to their study system. In this Commentary, we provide a guide for experimental biologists to better understand if, when, and how UVR can be integrated into experimental designs to improve the ecological realism of their experiments.

Extensions of open science for applied behavior analysis: Preregistration for single-case experimental designs.

Open science practices are designed to enhance the utility, integrity, and credibility of scientific research. This article highlights how preregistration in open science practice can be leveraged to enhance the rigor and transparency of single-case experimental designs within an applied behavior analysis framework. We provide an overview of the benefits of preregistration including increased transparency, reduced risk of researcher bias, and improved replicability, and we review the specific contexts under which these practices most benefit the proposed framework. We discuss potential concerns with and unique considerations for preregistering experiments that use single-case designs, with practical guidance for researchers who are seeking to preregister their studies. We present a checklist as a tool for researchers in applied behavior analysis to use for preregistration and provide recommendations for our field to strengthen the contingencies for open science practices that include preregistration.

Fresh Carrier for an Old Topical Local Anesthetic: Benzocaine in Nanostructured Lipid Carriers.

Nanostructured lipid carriers (NLC) have emerged as innovative drug delivery systems, offering distinct advantages over other lipid-based carriers, such as liposomes and solid lipid nanoparticles. Benzocaine (BZC), the oldest topical local anesthetic in use, undergoes metabolism by pseudocholinesterase, leading to the formation of p-aminobenzoic acid, a causative agent for allergic reactions associated with prolonged BZC usage. In order to mitigate adverse effects and enhance bioavailability, BZC was encapsulated within NLC. Utilizing a 23 factorial design, formulations comprising cetyl palmitate (solid lipid), propylene glycol monocaprylate (liquid lipid), and Pluronic F68 as surfactants were systematically prepared, with variations in the solid/liquid lipid mass ratios (60:40-80:20%), total lipid contents (15-25%), and BZC concentrations (1-3%). The optimized formulation underwent characterization by dynamic light scattering, differential scanning calorimetry, Raman imaging, X-ray diffraction, small-angle neutron scattering, nanotracking analysis, and transmission electron microscopy (TEM)/cryo-TEM, providing insights into the nanoparticle structure and the incorporation of BZC into its lipid matrix. NLCBZC exhibited a noteworthy encapsulation efficiency (%EE = 96%) and a 1 year stability when stored at 25 °C. In vitro kinetic studies and in vivo antinociceptive tests conducted in mice revealed that NLCBZC effectively sustained drug release for over 20 h and prolonged the anesthetic effect of BZC for up to 18 h. We therefore propose the use of NLCBZC to diminish the effective anesthetic concentration of benzocaine (from 20 to 3% or less), thus minimizing allergic reactions that follow the topical administration of this anesthetic and, potentially, paving the way for new routes of BZC administration in pain management.

Model selection of GLMMs in the analysis of count data in single-case studies: A Monte Carlo simulation.

Generalized linear mixed models (GLMMs) have great potential to deal with count data in single-case experimental designs (SCEDs). However, applied researchers have faced challenges in making various statistical decisions when using such advanced statistical techniques in their own research. This study focused on a critical issue by investigating the selection of an appropriate distribution to handle different types of count data in SCEDs due to overdispersion and/or zero-inflation. To achieve this, I proposed two model selection frameworks, one based on calculating information criteria (AIC and BIC) and another based on utilizing a multistage-model selection procedure. Four data scenarios were simulated including Poisson, negative binominal (NB), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB). The same set of models (i.e., Poisson, NB, ZIP, and ZINB) were fitted for each scenario. In the simulation, I evaluated 10 model selection strategies within the two frameworks by assessing the model selection bias and its consequences on the accuracy of the treatment effect estimates and inferential statistics. Based on the simulation results and previous work, I provide recommendations regarding which model selection methods should be adopted in different scenarios. The implications, limitations, and future research directions are also discussed.