Evaluating multiple stressor research in coastal wetlands: A systematic review

Multiple stressors are ubiquitous in coastal ecosystems as a result of increased human activity and development along coastlines. Accurately assessing multiple stressor effects is essential for predicting stressor impacts and informing management to efficiently and effectively mitigate potentially complex ecological responses. Extracting relevant information on multiple stressor studies conducted specifically within coastal wetlands is not possible from existing reviews, posing challenges in highlighting knowledge gaps and guiding future research. Here, we systematically review manipulative studies that assess multiple anthropogenic stressors within saltmarsh, mangrove, and seagrass ecosystems. In the past decade, there has been a rapid increase in publications, with seagrasses receiving the most attention (76 out of a total of 143 studies). Across all studies, nutrient loading and temperature were tested most often (N = 64 and N = 48, respectively), while the most common stressor combination was temperature with salinity (N = 12). Stressor application and study design varied across ecosystems. Studies are mostly conducted in highly controlled environments, without considering how natural variations in the physicochemical environment of coastal ecosystems may influence stressor intensity and timing under these conditions. This may result in vastly different ecological responses across levels of biological organisation. Shifting focus from univariate analytical approaches to multivariate, particularly path analysis, will help elucidate complex ecological relationships and highlight direct and indirect effects of multiple stressors in coastal ecosystems. There is a solid foundation of multiple stressor research in coastal wetlands. However, we recommend future research enhance ecological realism in experimental design by studying the effects of stressor combinations whilst accounting for spatiotemporal variability that reflects natural conditions of coastal ecosystems.

pH-responsive delivery of anti-metastatic niclosamide using mussel inspired polydopamine nanoparticles

Niclosamide (Nic), an FDA approved antihelminthic drug, is being repurposed as a potent anti-cancer and anti-inflammatory agent. Niclosamide exhibits anti-cancer activity in multiple cancer types, including breast, colon, and prostate cancers. Niclosamide, a BCS II drug, is practically insoluble in water and sparingly soluble in organic solvents (ethanol, dimethyl sulfoxide), leading to limited therapeutic applications, and necessitates the need for a drug carrier. Herein, we report the preparation of polydopamine nanoparticles loaded with niclosamide (Nic-PDA NPs). The designed formulation had a very high loading efficiency (~30%) and entrapment efficiency close to 90%. The average hydrodynamic diameter of Nic-PDA NPs was 146.3 nm, with a narrow size distribution (PDI = 0.039). The formulation exhibited a pH-dependent drug release profile, with ~35% drug released at pH 7.4 after 120 h, compared to > 50% at pH 5.5 in simulated physiological conditions. The NPs exhibited time-dependent cellular uptake and were primarily localized in the cytoplasm. The formulation exhibited comparable cytotoxicity in MDA-MB-231 cells (IC₅₀ = 2.73 μM, 36 h), and inhibited the migration of cancer cells significantly compared to the free drug and unloaded PDA NPs. Furthermore, the unloaded NPs exhibited excellent in vivo compatibility. The study establishes a rigorously optimized protocol for the synthesis of Nic loaded PDA NPs. The biocompatibility, anti-migratory efficacy, and the in vivo non-toxic nature of PDA has been well demonstrated.

Consequence analysis due to possible ethanol leaks in sugarcane biorefineries

This study simulated and evaluated the consequences of possible ethanol leaks in a hypothetical sugarcane biorefinery, considering climatic factors in the region of the State of São Paulo-BR. The Gaussian model was used to obtain the results of the hypothetical scenarios. From these values, an empirical mathematical model was established to describe the behavior of the system within the investigated experimental domain. The results obtained the modeling values of the hypothetical scenarios, the statistical treatment for the two responses-a range, slight damage (R1), and a range, high damage (R2), the joint analyses of variables R1 and R2, and the risk classification of catastrophic events. The consequence analysis allowed the calculation and plotting of graphs, such as the areas of thermal radiation range. Among the variables addressed in the study, the diameter of the leakage hole was the most noticeable in the range of thermal radiation. Therefore, it is relevant to make simulations to prevent hazardous material leakages by applying the exact characteristics of the plant to conduct the procedure.

Guidelines for Setting Up a mRNA Sequencing Experiment and Best Practices for Bioinformatic Data Analysis

RNA-sequencing, commonly referred to as RNA-seq, is the most recently developed method for the analysis of transcriptomes. It uses high-throughput next-generation sequencing technologies and has revolutionized our understanding of the complexity and dynamics of whole transcriptomes.In this chapter, we recall the key developments in transcriptome analysis and dissect the different steps of the general workflow that can be run by users to design and perform a mRNA-seq experiment as well as to process mRNA-seq data obtained by the Illumina technology. The chapter proposes guidelines for completing a mRNA-seq study properly and makes available recommendations for best practices based on recent literature and on the latest developments in technology and algorithms. We also remark the large number of choices available (especially for bioinformatic data analysis) in front of which the scientist may be in trouble.In the last part of the chapter we discuss the new frontiers of single-cell RNA-seq and isoform sequencing by long read technology.

Using mouse cursor tracking to investigate online cognition: Preserving methodological ingenuity while moving toward reproducible science

Mouse cursor tracking has become a prominent method for characterizing cognitive processes, used in a wide variety of domains of psychological science. Researchers have demonstrated considerable ingenuity in the application of the approach, but the methodology has not undergone systematic analysis to facilitate the development of best practices. Furthermore, recent research has demonstrated effects of experimental design features on a number of mousetracking outcomes. We conducted a systematic review of the mouse-tracking literature to survey the reporting and spread of mouse variables (Cursor speed, Sampling rate, Training), physical characteristics of the experiments (Stimulus position, Response box position) and response requirements (Start procedure, Response procedure, Response deadline). This survey reveals that there is room for improvement in reporting practices, especially of subtler design features that researchers may have assumed would not impact research results (e.g., Cursor speed). We provide recommendations for future best practices in mouse-tracking studies and consider how best to standardize the mouse-tracking literature without excessively constraining the methodological flexibility that is essential to the field.

Determination of copper in traditional coffee pot water samples by flame atomic absorption spectrometry and matrix matching calibration strategy after switchable solvent based liquid-phase microextraction

Traditional copper coffee pots are widely used in these modern times and daily consumption of coffee brewed in overused/old pots increases the risk of copper ingestion. This study employed a green switchable solvent-based liquid-phase microextraction (SS-LPME) method to isolate and preconcentrate copper from water boiled in coffee pots. Copper was determined by a flame atomic absorption spectrometry (FAAS) system coupled with a slotted quartz tube (SQT). 1,5-Diphenylcarbazone was added to aqueous samples to form a complex with copper before the extraction step. Box-Behnken experimental design was applied to select optimum conditions of the extraction method that were used to validate the analytical method. The limits of quantification and detection of the optimized SS-LPME-SQT-FAAS method were determined as 9.1 and 2.7 μg/L, respectively. Water samples boiled in traditional coffee pots were spiked at different concentrations and analyzed to ascertain the method's accuracy and applicability to real samples. Satisfactory recovery results obtained in the range of 92-107% established good accuracy, and percent relative standard deviations lower than 8.0% also proved high precision.

Mycotoxins in food: a review on liquid chromatographic methods coupled to mass spectrometry and their experimental designs

The development of a multi-mycotoxins method using LC-MS/MS is necessary and it is clear that the development of such method involves many compromises in the choice of the different parameters. This review summarizes applications using conventional experimental designs and some recent studies using response surface methodology (RSM) as a mathematical modeling tool for the optimization of extraction procedures. The authors also discuss pros and cons of the different procedures. To our knowledge, it is the first review on experimental design for the development of multi-mycotoxin methods. This review could be useful in the development and optimization of LC-MS/MS methods with the aim of describing experimental design and variables (factors) that are likely to affect sensitivity and specificity.

Translational Intracerebral Hemorrhage Research: Has Current Neuroprotection Research ARRIVEd at a Standard for Experimental Design and Reporting?

One major aim of preclinical intracerebral hemorrhage (ICH) research is to develop and test potential neuroprotectants. Published guidelines for experimental design and reporting stress the importance of clearly and completely reporting results and methodological details to ensure reproducibility and maximize information availability. The current review has two objectives: first, to characterize current ICH neuroprotection research and, second, to analyze aspects of translational design in preclinical ICH studies. Translational design is the adoption and reporting of experimental design characteristics that are thought to be clinically relevant and critical to reproducibility in animal studies (e.g., conducting and reporting experiments according to the STAIR and ARRIVE guidelines, respectively). Given that ICH has no current neuroprotective treatments and an ongoing reproducibility crisis in preclinical research, translational design should be considered by investigators. We conducted a systematic review of ICH research from 2015 to 2019 using the PubMed database. Our search returned 281 published manuscripts studying putative neuroprotectants in animal models. Contemporary ICH research predominantly uses young, healthy male rodents. The collagenase model is the most commonly used. Reporting of group sizes, blinding, and randomization are almost unanimous, but group size calculations, mortality and exclusion criteria, and animal model characteristics are infrequently reported. Overall, current ICH neuroprotection research somewhat aligns with experimental design and reporting guidelines. However, there are areas for improvement. Because failure to consider translational design is associated with inflation of effect sizes (and possibly hindered reproducibility), we suggest that researchers, editors, and publishers collaboratively consider enhanced adherence to published guidelines.

Improving laccase production from Trametes versicolor using lignocellulosic residues as cosubstrates and evaluation of enzymes for blue wastewater biodegradation

Biocatalytic degradation of recalcitrant pollutants employing ligninolytic enzymes is a promising approach for wastewater treatment. However, enzymes production must be improved to make biodegradation a more cost-effective treatment. In this research, laccase production from Trametes versicolor using lignocellulosic residues (agave bagasse, coconut fibers and wheat bran) as cosubstrates was improved using a central composite face-centered design, and the application of the enzymes-rich culture supernatant was evaluated for blue wastewater biodegradation. Findings revealed that the optimal conditions for laccase production were found at 35 °C and 5 g/L of wheat bran as cosubstrate, reaching about 200 U/mL in 11 days in a batch submerged fermentation. These conditions were scaled up for a submerged fermentation using an airlift reactor, and a maximum enzymatic activity of 1200 U/mL was achieved in 9 days at 30 °C. This enzymes-rich culture supernatant was tested for the degradation of blue wastewater from aircraft in an airlift reactor. Results showed a COD removal efficiency of 43% and an increase of the biodegradability index from 0.64 to 1.36, both results applying an enzymatic activity of supernatant of 300 U/mL. In conclusion, the enzymatic biodegradation becomes a viable strategy for the pretreatment of a real effluent such as the blue wastewater collected in public transportation.

The application of pharmaceutical quality by design concepts to evaluate the antioxidant and antimicrobial properties of a preservative system including desferrioxamine

BACKGROUND

The purpose of the present study was to investigate the antioxidant and antimicrobial activities of a conventional preservative system containing desferrioxamine mesylate (DFO) and optimize the composition of the system through mathematical models.

METHODS

Different combinations of ethylenediaminetetraacetic acid (EDTA), sodium metabisulfite (SM), DFO and methylparaben (MP) were prepared using factorial design of experiments. The systems were added to ascorbic acid (AA) solution and the AA content over time, at room temperature and at 40 °C was determined by volumetric assay. The systems were also evaluated for antioxidant activity by a fluorescence-based assay. Antimicrobial activity was assessed by microdilution technique and photometric detection against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Candida albicans and Aspergillus brasiliensis. A multi-criteria decision approach was adopted to optimize all responses by desirability functions.

RESULTS

DFO did not extend the stability of AA over time, but displayed a better ability than EDTA to block the pro-oxidant activity of iron. DFO had a positive interaction with MP in microbial growth inhibition. The mathematical models showed adequate capacity to predict the responses. Statistical optimization aiming to meet the quality specifications of the ascorbic acid solution indicated that the presence of DFO in the composition allows to decrease the concentrations of EDTA, SM and MP.

CONCLUSION

DFO was much more effective than EDTA in preventing iron-catalyzed oxidation. In addition, DFO improved the inhibitory response of most microorganisms tested. The Quality by Design concepts aided in predicting an optimized preservative system with reduced levels of conventional antioxidants and preservatives, suggesting DFO as a candidate for multifunctional excipient.

Design choices: Empirical recommendations for designing two-dimensional finger-tracking experiments

The continuous tracking of mouse or finger movements has become an increasingly popular research method for investigating cognitive and motivational processes such as decision-making, action-planning, and executive functions. In the present paper, we evaluate and discuss how apparently trivial design choices of researchers may impact participants' behavior and, consequently, a study's results. We first provide a thorough comparison of mouse- and finger-tracking setups on the basis of a Simon task. We then vary a comprehensive set of design factors, including spatial layout, movement extent, time of stimulus onset, size of the target areas, and hit detection in a finger-tracking variant of this task. We explore the impact of these variations on a broad spectrum of movement parameters that are typically used to describe movement trajectories. Based on our findings, we suggest several recommendations for best practice that avoid some of the pitfalls of the methodology. Keeping these recommendations in mind will allow for informed decisions when planning and conducting future tracking experiments.

Application of nanofiltration and reverse osmosis for treatment and reuse of laundry wastewater

The aim of this study was to investigate the treatment and reuse of laundry wastewater with couple of nanofiltration (NF) and reverse osmosis (RO). In the NF process, optimal values of pH, temperature, transmembrane pressure (TMP) and cross-flow rate were determined using the Taguchi L₁₆ (4⁴) experimental design method. The smaller-the-better signal-to-noise (S/N) ratio was used to analyze the results of experiments. Flux decline caused by fouling was selected as response parameter. A pH of 8.5, temperature of 30 °C, TMP of 12 bar and cross-flow rate of 2 L/min were determined as optimum operating conditions in the NF process. According to analysis of variance (ANOVA), pH was the most effective factor while TMP and cross-flow rate had low effects on the fouling. Membrane fouling was also evaluated with scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDX), zeta potential and optical profilometer measurements. In the RO process, the quality of NF permeate obtained from optimum operating conditions was improved by an RO membrane. Although a NF membrane was not effective in reducing chemical oxygen demand (COD), Orto-P and NH₄ ⁺-N, these parameters were almost removed in the NF + RO system. These results showed that, the Taguchi method was successfully applied to determine the optimum operating conditions for the treatment of laundry wastewater with an NF process. Water treated with integrated membrane processes (NF + RO) is sufficient for use as laundry washing water.

Non-enzymatic lactose molecularly imprinted sensor based on disposable graphite paper electrode

Lactose (LAC) is a disaccharide - major sugar, present in milk and dairy products. LAC content is an important indicator of milk quality and abnormalities in food industries, as well as in human and animal health. The present study reports the development of an innovative imprinted voltammetric sensor for sensitive detection of LAC. The sensor was constructed using electropolymerized pyrrole (Py) molecularly imprinted polymer (MIP) on graphite paper electrode (PE). The MIP film was constructed through the electrosynthesis of polypyrrole (PPy) in the presence of LAC (template molecule) on PE (PPy/PE). To optimize the detection conditions, several factors affecting the PPy/PE sensor performance were assessed by multivariate methods (Plackett-Burman design and central composite design). Under optimized conditions, the proposed analytical method was applied for LAC detection in whole and LAC-free milks, where it demonstrated high sensitivity and selectivity, with two dynamic linear ranges of concentration (1.0-10 nmol L^-1 and 25-125 nmol L^-1) and a detection limit of 0.88 nmol L^-1. The MIP sensor showed selective molecular recognition for LAC in the presence of structurally related molecules. The proposed PPy/PE sensor exhibited good stability, as well as excellent reproducibility and repeatability. Based on the results obtained, the PPy/PE is found to be highly promising for sensitive detection of LAC.

Keep it real: rethinking the primacy of experimental control in cognitive neuroscience

Naturalistic experimental paradigms in neuroimaging arose from a pressure to test the validity of models we derive from highly-controlled experiments in real-world contexts. In many cases, however, such efforts led to the realization that models developed under particular experimental manipulations failed to capture much variance outside the context of that manipulation. The critique of non-naturalistic experiments is not a recent development; it echoes a persistent and subversive thread in the history of modern psychology. The brain has evolved to guide behavior in a multidimensional world with many interacting variables. The assumption that artificially decoupling and manipulating these variables will lead to a satisfactory understanding of the brain may be untenable. We develop an argument for the primacy of naturalistic paradigms, and point to recent developments in machine learning as an example of the transformative power of relinquishing control. Naturalistic paradigms should not be deployed as an afterthought if we hope to build models of brain and behavior that extend beyond the laboratory into the real world.

An experimental approach to the optimization of the dosage of hydrogen peroxide for Fenton and photo-Fenton processes

The determination of the hydrogen peroxide dosage scheme that minimizes hydrogen peroxide consumption while meeting the specified treatment outcome is crucial for Fenton and photo-Fenton processes. The challenge is building a methodology that provides the optimal dosage profile. However, the lack of detailed dynamic models prevents exploiting model-based optimization methods that have proved successful in other applications. Thus, this work addresses this challenge by providing a problem formulation identifying and discussing objectives and constraints, and the nature of the optimal solution. From this point, the work presents a novel dosage model and a consequent methodology aimed at experimentally optimizing the dosage profile along a discretized time horizon following recipe optimization concepts. The approach is parallel to the numerical solution of the model-based optimization problem posed by hydrogen peroxide dosage. The proposed methodology is validated in the remediation of a Paracetamol (PCT) solution, and the obtained results are assessed and discussed in regard of the evolution of the concentration of hydrogen peroxide, the contaminant (PCT), and Total Organic Carbon (TOC). The concentration of dissolved oxygen (DO), which is also monitored, allows providing a more comprehensive explanation of the nature of the process.

Hypothesis-driven quantitative fluorescence microscopy - the importance of reverse-thinking in experimental design

One of the challenges in modern fluorescence microscopy is to reconcile the conventional utilization of microscopes as exploratory instruments with their emerging and rapidly expanding role as a quantitative tools. The contribution of microscopy to observational biology will remain enormous owing to the improvements in acquisition speed, imaging depth, resolution and biocompatibility of modern imaging instruments. However, the use of fluorescence microscopy to facilitate the quantitative measurements necessary to challenge hypotheses is a relatively recent concept, made possible by advanced optics, functional imaging probes and rapidly increasing computational power. We argue here that to fully leverage the rapidly evolving application of microscopes in hypothesis-driven biology, we not only need to ensure that images are acquired quantitatively but must also re-evaluate how microscopy-based experiments are designed. In this Opinion, we present a reverse logic that guides the design of quantitative fluorescence microscopy experiments. This unique approach starts from identifying the results that would quantitatively inform the hypothesis and map the process backward to microscope selection. This ensures that the quantitative aspects of testing the hypothesis remain the central focus of the entire experimental design.

Behavioral testing in animal models of spinal cord injury

This review is based on a lecture presented at the Craig H. Neilsen Foundation sponsored Spinal Cord Injury Training Program at Ohio State University. We discuss the advantages and challenges of injury models in rodents and theory relation to various behavioral outcome measures. We offer strategies and advice on experimental design, behavioral testing, and on the challenges, one will encounter with animal testing. This review is designed to guide those entering the field of spinal cord injury and/or involved with in vivo animal testing.

Optimization of the photocatalytic degradation process of aromatic organic compounds applied to mangrove sediment

Polycyclic aromatic hydrocarbons (PAHs) are part of a class of organic compounds resistant to natural degradation. In this way, heterogeneous photocatalysis becomes useful to degrade persistent organic pollutants, however it can be influenced by environmental variables (i.e.: organic matter) and experimental factors such as: mass of the photocatalyst and irradiation time. The objective of this research was to use a factorial design 2^k as a function of the multiple response (MR) to evaluate simultaneously experimental conditions for the photodegradation of polycyclic aromatic hydrocarbons in contaminated mangrove sediment and its application in oil from Potiguar Basin in Brazil. The sediment samples collected in Belmonte city (Southern Bahia state) were contaminated with 0.25 mg kg⁻¹ of Acenaphthene, Anthracene, Benzo[a]Anthracene, Indene[1,2,3cd]pyrene, Dibenzo[ah]anthracene, Benzo[ghi]pyrene. Factors such as mass of the photocatalyst and irradiation time were evaluated in factorial design 2², with triplicate from the central point, to 1g of the PAH contaminated sediment. After performing the experiments, it was found that the best experimental condition for the degradation of all PAHs indicated by MR was the central point (0.5 g of photocatalyst and 12h of irradiation). For such conditions, the half-life of PAHs varied from 3.51 to 9.37 h and the degradation speed constant between 0.0740 to 0.1973 h⁻¹. The comparison of the optimized methodology between photolysis tests and heterogeneous photocatalysis was performed using the Kruskal-Wallis test, which indicated a difference for the reference solution, where heterogeneous photocatalysis was more efficient in the degradation of PAHs. The optimized methodology was apply in samples contaminated with crude oil from Potiguar Basin, no significant difference was observed in the aromatic fraction, using for the Kruskal-Wallis test. Heterogeneous photocatalysis has shown to be a promising remediation technique to remedy aromatic organic compounds in mangrove sediments.

Experimental design of a culture approach for corneal endothelial cells of New Zealand white rabbit

The harvesting of corneal endothelial cells (CEC) has received special attention due to its potential as a therapy for corneal blindness. The main challenges are related to the culture media formulation, cellular density at the primary isolation, and the number of passages in which CEC can retain their functional characteristics. To alternate different media formulations to harvest CEC has an impact on the cellular yield and morphology. Therefore, we analyzed four different sequences of growth factor-supplemented Stimulatory (S) and non-supplemented Quiescent (Q) media, upon passages to find the optimal S-Q culture sequence. We assessed cell yield, morphology, procollagen I production, Na⁺/K⁺-ATPase function, and the expression of ZO-1 and Na⁺/K⁺-ATPase. Our results show SQSQ and SQQQ sequences with a balance between an improved cell yield and hexagonal morphology rate. CEC cultured in the SQQQ sequence produced procollagen I, showed Na⁺/K⁺-ATPase function, and expression of ZO-1 and Na⁺/K⁺-ATPase. Our study sets a culture approach to guarantee CEC expansion, as well as functionality for their potential use in tissue engineering and in vivo analyses. Thus, the alternation of S and Q media improves CEC culture. SQQQ sequence demonstrated CEC proliferation and lower the cost implied in SQSQ sequences. We discarded the use of pituitary extract and ROCK inhibitors as essential for CEC proliferation.

The best predictions in experimental biology are critical and persuasive

A powerful way to evaluate scientific explanations (hypotheses) is to test the predictions that they make. In this way, predictions serve as an important bridge between abstract hypotheses and concrete experiments. Experimental biologists, however, generally receive little guidance on how to generate quality predictions. Here, we identify two important components of good predictions - criticality and persuasiveness - which relate to the ability of a prediction (and the experiment it implies) to disprove a hypothesis or to convince a skeptic that the hypothesis has merit. Using a detailed example, we demonstrate how striving for predictions that are both critical and persuasive can speed scientific progress by leading us to more powerful experiments. Finally, we provide a quality control checklist to assist students and researchers as they navigate the hypothetico-deductive method from puzzling observations to experimental tests.

Spherical depth-sensing nanoindentation of human anterior skull base bones: Establishment of a test protocol

The mechanical properties of anterior skull base (ASB) bones are not well understood due to their complex geometry and deep location. However, it is of particular interest for skull base surgeons to appraise the force range they can apply during procedures and know what kind of haptic feedback a simulation device should produce in order to be realistic for trainees. The aim of this study was to establish a measurement protocol to set the level of hydration state, temperature and curve analysis method for spherical depth sensing nanoindentation of ASB bones. A definitive screening design method was used to test the different possible combinations of these factors. Two samples of ASB bones from the heads of two human body donors (two specimens) were selected according to their microstructure as assessed by micro-CT (microtomography): low-porosity (16.87%, sphenoid bone) and high-porosity (79.85%, ethmoid bone). Depth measurement series of 36 nanoindentations (n = 288) were performed on specimen 1 according to the L8 Taguchi orthogonal array to study the effect of temperature (two levels: 20 or 37 °C), hydration state (dry or immerged in physiological saline sodium chloride), and loading curve analysis according to the Hertzian contact theory (fitting at the start or at the end). The mean values of reduced Young's (E*) modulus varied significantly depending on the hydration status and bone microstructure. In order to obtain the physiological properties of ASB bones, we thus propose performing immersion tests. To simplify the experimentation protocol, future experiments must include a room temperature level and a fit of the curve at the end of the load. A validation series was performed on the second specimen to assess the set of parameters. The E* in dry bone gave mean values of 994.68 MPa, versus 409.79 MPa in immerged bones (p < 0.00001). This is the first time a study has been carried out on ASB bones, defining the experimental parameters related to physiological conditions.

Enhanced oral bioavailability of Bisdemethoxycurcumin-loaded self-microemulsifying drug delivery system: Formulation design, in vitro and in vivo evaluation

In this study, we sought to overcome the poor solubility and bioavailability of bismethoxycurcumin (BDMC) by fabricating a BDMC-loaded self micro-emulsifying system (BDMC-SMEDDS). Solubility and compatibility tests, pseudo-ternary phase diagrams (PTPDs) as well as d-optimal concept was applied to design the formulation. The assessment of the prepared BDMC-SMEDDS in-vitro mainly included droplet size (DS) and entrapment efficiency (EE) determination, morphology, drug release and stability testing. Besides, the in vivo behavior was also evaluated after oral administration of BDMC-SMEDDS to rats. The optimal formulation was found to compose of Kolliphor EL (K-EL, emulsifier, 645.3 mg), PEG 400 (co-emulsifier, 147.2 mg), ethyl oleate (EO, oil, 207.5 mg) and BDMC (50 mg). The BDMC-SMEDDS with satisfactory stability had a mean size of 21.25 ± 3.23 nm and EE of 98.31 ± 0.32%. Roughly 70% of BDMC was released from BDMC-SMEDDS within 84 h compared with <20% from the free BDMC. More importantly, the in-vivo behavior of BDMC-SMEDDS showed that the AUC_(0-12h) and plasma concentration of BDMC increased substantially as compared to the free BDMC. Altogether, BDMC-SMEDDS has the potential to enhance the solubility and bioavailability of BDMC and could be applied in the clinics.

Disentangling model complexity in green roof hydrological analysis: A Bayesian perspective

Green Roofs (GRs) have proven to be a sustainable solution to stormwater management in urban areas. To boost their adoption at the large scale, there is a need to develop numerical models, which are accurate, computationally cheap, and as complex as needed to reproduce the hydrological behavior of GRs. Alternative conceptual and mechanistic approaches have been proposed and tested, however the most appropriate level of model complexity for GRs' analysis is still unknown. To cover this scientific gap, we provide a Bayesian comprehensive perspective of GR hydrological modeling, which includes a statistically rigorous Bayesian comparison of one conceptual and multiple Richards-based mechanistic GR models, and a probabilistic assessment of the information content of different observations. The analysis of the marginal likelihoods reveals that the conceptual and the unimodal van Genuchten - Mualem models are the most appropriate parameterizations, and that further layers of model complexity are not fully supported by the measurements. In addition to that, the estimated Kullback-Leibler divergences suggest that the measured volumetric water content outperforms the measured subsurface outflow and tracer concentrations in terms of informativeness, leading to the lowest model predictive uncertainty for the simulation of water fluxes. The findings of this study represent a first step to clarify the role of model complexity in GRs' analysis, and open new perspective on GRs' model-based experimental design.

The effectiveness of modified, group-based CBT for dementia worry among Chinese elders

OBJECTIVES

Dementias are highly prevalent among Chinese elders. This study examined the effectiveness of a modified group cognitive behavioral therapy (CBT) on dementia worry among Chinese older adults.

METHODS

Eighty-two older adults recruited from four elder group homes were randomly assigned to either intervention or control group. The intervention group (n= 44) received eight weekly 60-minute face-to-face CBT, while the control group (n=38) received treatment-as-usual.

RESULTS

Outcomes indicated that the modified group CBT has significantly reduced dementia worry and culturally biased beliefs about dementia (p<.001). Study findings supported both statistically and clinically significant effect of modified group CBT on dementia worry [g=-1.52, 95% CI (-2.01, -1.03)] and biased beliefs about dementia [g=-.95, 95% CI (-1.40, -.49)].

DISCUSSION

The culturally adapted CBT is promising in alleviating worries and anxiety over dementia among Chinese older adults. Future research needs to include larger samples and participants from different regions to replicate findings.