Experimental Conditions Research Articles

Development and Characterization of Enteric Polymer-based Solid Dispersion for Cholecalciferol Delivery

Background: The deficiency of vitamin D is a global concern affecting individuals of all age groups. Insufficient exposure to sunlight and disease conditions can lead to cholecalciferol (vitamin D3) deficiency. Objective: Cholecalciferol is a lipophilic crystalline molecule, and it is highly susceptible to degradation under environmental conditions, including light, temperature, and oxygen, and its degradation rate is high in the low pH range. Therefore, an enteric solid dispersion-based formulation was developed in the present study for the oral delivery of cholecalciferol. Method: Enteric polymer hydroxypropylmethylcellulose acetate succinate (HPMCAS)-based solid dispersion was developed and characterized by Fourier transform-infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), and X-ray diffraction analysis. The effect of various concentrations of cholecalciferol formulations on the viability of Caco-2 cells was determined using an MTT assay. A dissolution and stability study of the product was also performed. Result: An amorphous form of cholecalciferol in the solid dispersion was reported. The drug content of solid dispersions was in the order of 90%. The viability assay indicated that the surfactant used in the developed solid dispersion of cholecalciferol had no cytotoxic effect on Caco-2 cells. A dissolution study on enteric solid dispersion in two-stage dissolution under a biomimetic medium indicated the pHdependent release of cholecalciferol from the HPMCAS-based solid dispersion. Moreover, the stability study showed no significant changes in the cholecalciferol content in the developed formulation under storage at experimental conditions. Conclusion: The enteric solid dispersion of cholecalciferol was developed, which exhibited compatibility with Caco-2 cells, improved dissolution, and acceptable stability profile, and represented a potential option for efficient delivery of cholecalciferol.

Effects of pain on cortical homeostatic plasticity in humans: a systematic review.

Homeostatic plasticity (HP) is a negative feedback mechanism that prevents excessive facilitation or depression of cortical excitability (CE). Cortical HP responses in humans have been investigated by using 2 blocks of noninvasive brain stimulation with a no-stimulation block in between. A healthy HP response is characterized by reduced CE after 2 excitatory stimulation blocks and increased CE when using inhibitory stimulation. Conversely, impaired HP responses have been demonstrated in experimental and chronic pain conditions. Therefore, this systematic review aimed to provide an overview of the effect of pain on cortical HP in humans. Scopus, Embase, and PubMed were searched from inception until November 20, 2023. The included studies (1) compared experimental or clinical pain conditions with healthy controls, (2) induced HP using 2 blocks of stimulation with a no-stimulation interval, and (3) evaluated CE measures such as motor-evoked potentials. Four studies were included, consisting of 5 experiments and 146 participants, of whom 63 were patients with chronic pain and 48 were subjected to an experimental pain model. This systematic review found support for an HP impairment in pain compared with that in pain-free states, reflected by a lack of CE reduction after excitatory-excitatory HP induction over the primary motor cortex. Inhibitory-inhibitory HP induction did not produce a consistent HP response across studies, independent of pain or pain-free states. Standardization of HP induction protocols and outcome calculations is needed to ensure reproducibility and study comparison. Future HP studies may consider investigating sensory domains including nociception, which would further our understanding of abnormal HP regulation in pain conditions.

Effects of polypropylene microplastics on carbon dioxide dynamics in intertidal mangrove sediments

Microplastics (MPs) in soil can influence CO2 dynamics by altering organic carbon (OC) and microbial composition. Nevertheless, the fluctuation of CO2 response attributed to MPs in mangrove sediments is unclear. This study explores the impact of micro-sized polypropylene (mPP) particles on the carbon dynamics of intertidal mangrove sediments. In the high-tide level sediment, after 28 days, the cumulative CO2 levels for varying mPP dosages were as follows: 496.86 ± 2.07, 430.38 ± 3.84, and 447.09 ± 1.72 mg kg−1 for 0.1%, 1%, and 10% (w/w) mPP, respectively. The CO2 emissions were found to be increased with a 0.1% mPP level and decreased with 1% and 10% mPP at high-tide level sediment, suggesting a tide level-specific dose dependence of the CO2 emission pattern in mangrove sediments. Overall, results indicated that the presence of mPP in mangrove sediments would potentially affect intertidal total CO2 storage under given experimental conditions.

Determination and molecular simulation of ternary solid–liquid phase equilibrium of succinic acid + maleic acid + water from 283.15 K to 333.15 K

This study used the isothermal saturation gravimetric method to examine the solid–liquid phase equilibrium relationships composed of succinic acid + maleic acid + water spanning from 283.15 K to 333.15 K. The experimental data were utilized for the purpose of plotting the equilibrium phase diagrams of ternary systems in the studied temperature range. There were three crystalline regions in each isothermal ternary phase diagram, two saturation boundary curves, and a co-saturation point. To broaden the use of data from binary and ternary phase equilibrium measurements, Wilson and NRTL models were utilized for correlation and expectation, while relative average deviation (RAD) and root mean square deviation (RMSD) were utilized to evaluate the computational exactness. The results show that the theoretically calculated values were found to be in near agreement with the experimental values, and both models were able to obtain more precise theoretical data under different experimental conditions. In addition, molecular simulation was employed to elucidate the interaction between succinic acid, maleic acid, and water. This study provides accurate and reliable data for the separation of succinic acid and maleic acid mixture in water. These findings can be utilized to make sense of the dissolvability conduct of succinic acid and maleic acid in aqueous solution.

Industrial Production and Therapeutic Application of Botulinum Neurotoxin: The Role of C. botulinum Type A.

Botulinum neurotoxin has remarkably transitioned from a food safety hazard and biological warfare to an effective therapeutic drug. Currently, botulinum neurotoxins have seven serotypes (BoNT/A-G) in the form of protein complexes produced by Clostridium, a gram-positive and spore-forming bacteria. The conversion of toxins into useful drug substances of choice using the biotechnological process is tremendously increasing. Recent studies have shown that Botulinum neurotoxin-A (BoNT/A) has different biological activities and potencies in experimental and clinical conditions. They also indicate that the manufacturing process influences the potency and efficacy of BoNT/A drugs. Thus, this review focuses on the following criteria: detailed Fed-batch operation that includes the upstream and downstream processing of BoNT/A, the underlying mechanism behind the neurotoxic effect, and commercially available FDA-approved BoNT/A products and their therapeutic uses. Still, some research gaps exist in the mechanism for the treatment of psychiatric disorders.

An investigation on implementation of generating adversarial network-based surrogate models for prediction of turbine endwall film cooling effectiveness

Film cooling is an essential cooling technique for turbine blade, which guides coolant to cover the turbine blades surface by arranging discrete film holes on it. For the newly designed cooling units, the process of predicting film cooling effectiveness is really complex and time-consuming. For the purpose of accelerating the design procedure, the U-Net which is a very popular algorithm in the field of deep learning was improved with the basic layer structure, then it was adopted as the proxy function for the film cooling effectiveness prediction. The basic samples were generated by Latin hypercube sampling method and calculated by commercial software. The results were verified by experiment in a linear cascade. The training and testing samples were calculated at experimental conditions (inlet Mach number values 0.12). The results showed that comparing with the basic U-Net network, the novel U-Net network has a great better accuracy on the prediction of contour results. Both of the improved U-Net networks had higher prediction accuracy than original models. The correlation index reached more than 99.5% and the first order error was lower than 0.3%. The number of basic neural layers is not positively correlated with the network prediction accuracy which exists an optimal ratio. The experimental verification shows that the generating adversarial network prediction results are consistent with the experimental results. The final prediction results showed that the U-Net model can be used as a surrogate model and meets the requirements for accuracy of film cooling effectiveness prediction.

Exploration of reference genes for the development of a diagnostic kit on vascular aging in human saliva.

Identifying reliable biomarkers in saliva can be a promising approach to developing a rapid diagnostic kit for detecting vascular aging. This study investigated the most suitable reference gene for polymerase chain reaction (PCR) in saliva that is not affected by vascular aging variables. Whole saliva samples were collected to assess the expression of reference genes: actin beta (ACTB), 18S ribosomal RNA (18S rRNA), beta-2-microglobulin, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The most abundantly expressed gene was 18S rRNA, and the least expressed gene was GAPDH. Four genes were ranked according to their relative stability, as determined by mathematical algorithms, indicating that ACTB and 18S rRNA were stably expressed as reference genes. 18S rRNA was identified as the most promising reference gene for detecting systemic diseases using saliva from patients with vascular aging in these limited experimental conditions.

Exact ASP Counting with Compact Encodings

Answer Set Programming (ASP) has emerged as a promising paradigm in knowledge representation and automated reason- ing owing to its ability to model hard combinatorial problems from diverse domains in a natural way. Building on advances in propositional SAT solving, the past two decades have wit- nessed the emergence of well-engineered systems for solv- ing the answer set satisfiability problem, i.e., finding mod- els or answer sets for a given answer set program. In re- cent years, there has been growing interest in problems be- yond satisfiability, such as model counting, in the context of ASP. Akin to the early days of propositional model count- ing, state-of-the-art exact answer set counters do not scale well beyond small instances. Exact ASP counters struggle with handling larger input formulas. The primary contribu- tion of this paper is a new ASP counting framework, called sharpASP, which counts answer sets avoiding larger input formulas. This relies on an alternative way of defining answer sets that allows lifting of key techniques developed in the con- text of propositional model counting. Our extensive empirical analysis over 1470 benchmarks demonstrates significant per- formance gain over current state-of-the-art exact answer set counters. Specifically, by using sharpASP, we were able to solve 1062 benchmarks with PAR2 score of 3082 whereas using prior state-of-the-art, we could only solve 895 bench- marks with PAR2 score of 4205, all other experimental con- ditions being the same.

A numerical compass for experiment design in chemical kinetics and molecular property estimation

Kinetic process models are widely applied in science and engineering, including atmospheric, physiological and technical chemistry, reactor design, or process optimization. These models rely on numerous kinetic parameters such as reaction rate, diffusion or partitioning coefficients. Determining these properties by experiments can be challenging, especially for multiphase systems, and researchers often face the task of intuitively selecting experimental conditions to obtain insightful results. We developed a numerical compass (NC) method that integrates computational models, global optimization, ensemble methods, and machine learning to identify experimental conditions with the greatest potential to constrain model parameters. The approach is based on the quantification of model output variance in an ensemble of solutions that agree with experimental data. The utility of the NC method is demonstrated for the parameters of a multi-layer model describing the heterogeneous ozonolysis of oleic acid aerosols. We show how neural network surrogate models of the multiphase chemical reaction system can be used to accelerate the application of the NC for a comprehensive mapping and analysis of experimental conditions. The NC can also be applied for uncertainty quantification of quantitative structure–activity relationship (QSAR) models. We show that the uncertainty calculated for molecules that are used to extend training data correlates with the reduction of QSAR model error. The code is openly available as the Julia package KineticCompass.Graphical

Quantifying noise effects in optical measures of excited state transport.

Time-resolved microscopy is a widely used approach for imaging and quantifying charge and energy transport in functional materials. While it is generally recognized that resolving small diffusion lengths is limited by measurement noise, the impacts of noise have not been systematically assessed or quantified. This article reports modeling efforts to elucidate the impact of noise on optical probes of transport. Excited state population distributions, modeled as Gaussians with additive white noise typical of experimental conditions, are subject to decay and diffusive evolution. Using a conventional composite least-squares fitting algorithm, the resulting diffusion constant estimates are compared with the model input parameter. The results show that heteroscedasticity (i.e., time-varying noise levels), insufficient spatial and/or temporal resolution, and small diffusion lengths relative to the magnitude of noise lead to a surprising degree of imprecision under moderate experimental parameters. Moreover, the compounding influence of low initial contrast and small diffusion length leads to systematic overestimation of diffusion coefficients. Each of these issues is quantitatively analyzed herein, and experimental approaches to mitigate them are proposed. General guidelines for experimentalists to rapidly assess measurement precision are provided, as is an open-source tool for customizable evaluation of noise effects on time-resolved microscopy transport measurements.

Comparative effectiveness of carbon nanoparticles and biochar in alleviating copper stress in corn (Zea mays L.)

The application of carbon nanoparticles (CNPs) and biochar in agriculture for improving plant health and soil quality and alleviating metal stress offers alternative approaches to meet the ever-increasing demand for food. However, poor understanding of their roles in improving crop production under Cu stress represents a significant obstacle to their wide application in agriculture. To clarify how CNPs and biochar affect corn (Zea mays L.) seed germination, seedling growth, plant health, and nutrient uptake under different Cu stress levels, soil-less Petri-dish and greenhouse soil-based bioassays were conducted. The results revealed that CNPs and biochar stimulated corn seed germination and seedling growth. Besides, they were effective in immobilizing Cu2+ sorption in sandy soil and alleviating Cu stress for plant growth, as shown by the increased plant height and dry biomass. The plant nutrient uptake efficiency (NUE) was significantly increased by CNPs, with a maximum increase of 63.1% for N and 63.3% for K at the highest Cu2+ stress level (400 mg Cu2+ L−1). In contrast, non-significant effects on NUE were observed with biochar treatments regardless of Cu stress levels. Interestingly, CNPs significantly increased plant uptake of Cu in the Petri dish test, while biochar inhibited plant uptake of Cu under both experimental conditions. Principle component analysis (PCA) and Pearson correlation analysis indicated that CNPs mitigated Cu stress mainly by elevating antioxidant enzyme activities, enhancing plant photochemical efficiency, and increasing plant uptake of N and K, while biochar was more likely to reduce bioavailability and uptake of Cu in the plant. These findings have great implications for the application of CNPs and biochar as plant growth stimulators and de-toxicity agents in agriculture.

Experimental conditions for efficient retention of vascular endothelial cells on channel wall using lipid bubbles and acoustic interference

In order to fabricate multi-layered artificial blood vessels, bubble-surrounded cells were retained on the wall in a flow channel using the phase sweeping of interferential acoustic field. First, spatial distribution of acoustic intensity was defined to evaluate retention performance. Comparing between various acoustic fields, we found appropriate acoustic intensity for retention of the cells. Next, phase sweeping of the acoustic field was conducted to increase the retained area of the cells by varying sweep velocity, sweep direction, and the amplitudes of sound pressure. As the result, an interferential acoustic field with a balanced sound pressures of 200 kPa-pp at a sweep velocity of 100 mm s−1, which was 10 times higher than the flow, and the sweep direction against the flow, obtained a retained area 1.6 times larger than that without sweeping. We will apply the conditions based on the results for the future 3D fabrication of artificial blood vessels.

Uranium accumulation in environmentally relevant microplastics and agricultural soil at acidic and circumneutral pH

The co-occurrence of microplastics (MPs) with potentially toxic metals in the environment stresses the need to address their physicochemical interactions and the potential ecological and human health implications. Here, we investigated the reaction of aqueous U with agricultural soil and high-density polyethylene (HDPE) through the integration of batch experiments, microscopy, and spectroscopy. The aqueous initial concentration of U (100 μM) decreased between 98.6 and 99.2 % at pH 5 and between 86.2 and 98.9 % at pH 7.5 following the first half hour of reaction with 10 g of soil. In similar experimental conditions but with added HDPE, aqueous U decreased between 98.6 and 99.7 % at pH 5 and between 76.1 and 95.2 % at pH 7.5, suggesting that HDPE modified the accumulation of U in soil as a function of pH. Uranium-bearing precipitates on the cracked surface of HDPE were identified by SEM/EDS after two weeks of agitation in water at both pH 5 and 7.5. Accumulation of U on the near-surface region of reacted HDPE was confirmed by XPS. Our findings suggest that the precipitation of U was facilitated by the weathering of the surface of HDPE. These results provide insights about surface-mediated reactions of aqueous metals with MPs, contributing relevant information about the mobility of metals and MPs at co-contaminated agricultural sites.

A Rapid and Easy Procedure of Enzyme Biosensor based on Nitrogen-Doped Graphene for Detection of Methyl Parathion in CHM

Methyl parathion (MP), an organophosphorus pesticide that is frequently used to control pests during the planting process of Chinese herbal medicine (CHM), has been used without sufficient control, leading to excessive residues on the surface of CHM, which has a serious impact on the quality and safety of CHM and their preparations. Consequently, it is crucial to carefully control MP during the cultivation, processing, and manufacture of CHM. Based on this, nitrogen-doped graphene (N-Gr) with a high conductivity and chitosan (CS) with good stability were used to modify the glassy carbon electrode (GCE). Subsequently, the prussian blue (PB) with catalytic activity and gold nanoparticles (AuNPs) with excellent biocompatibility were deposited by the electrodeposition method to form the AuNPs/PB/CS@N-Gr/GCE. Then, the acetylcholinesterase (AChE) was effectively immobilized on the electrode surface by covalent bonding between AuNPs and AChE through gold-sulfhydryl bonds. Finally, a rapid and easy procedure of enzyme biosensor (AChE/AuNPs/PB/CS@N-Gr/GCE) for sensitive detection of MP pesticide residues was fabricated. Herein, PB catalyzes the redox reaction of thiocholine, which is produced when acetylthiocholine iodide (ATCHI) undergoes efficient hydrolysis catalyzed by AChE. This process effectively promoted electron transfer, amplifying the sensor’s response signal. After the experimental conditions are optimized, the limit of detection (LOD) for MP is found to be 9.47 × 10−5 μg ml−1. Exhibits a good linear relationship within the concentration range of 1 × 10−3 μg ml−1 ∼ 1 × 101 μg ml−1. Significantly, the fabricated enzyme biosensor excels in swiftly and sensitively detecting trace amounts of MP in real examples. Furthermore, it exhibits robust stability and reproducibility. The excellent performance of this enzyme biosensor not only offers a rapid and easy way to identify and find minute amounts of trace MP pesticide residues in CHM, but also serves as a technical guide for the creation of new, portable, and on-site pesticide residue detection technology for law enforcement.

Genome-scale metabolic modeling of Thraustochytrium sp. RT2316-16: Effects of nutrients on metabolism.

Marine thraustochytrids produce metabolically important lipids such as the long-chain omega-3 polyunsaturated fatty acids, carotenoids, and sterols. The growth and lipid production in thraustochytrids depends on the composition of the culture medium that often contains yeast extract as a source of amino acids. This work discusses the effects of individual amino acids provided in the culture medium as the only source of nitrogen, on the production of biomass and lipids by the thraustochytrid Thraustochytrium sp. RT2316-16. A reconstructed metabolic network based on the annotated genome of RT2316-16 in combination with flux balance analysis was used to explain the observed growth and consumption of the nutrients. The culture kinetic parameters estimated from the experimental data were used to constrain the flux via the nutrient consumption rates and the specific growth rate of the triacylglycerol-free biomass in the genome-scale metabolic model (GEM) to predict the specific rate of ATP production for cell maintenance. A relationship was identified between the specific rate of ATP production for maintenance and the specific rate of glucose consumption. The GEM and the derived relationship for the production of ATP for maintenance were used in linear optimization problems, to successfully predict the specific growth rate of RT2316-16 in different experimental conditions.

A Curb-Detection Network with a Tri-Plane BEV Encoder Module for Autonomous Delivery Vehicles

Curb detection tasks play a crucial role in the perception of the autonomous driving environment for logistics vehicles. With the popularity of multi-modal sensors under the BEV (Bird’s Eye View) paradigm, curb detection tasks are increasingly being integrated into multi-task perception networks, achieving robust detection results. This paper modifies and integrates the tri-plane spatial feature representation method of the EG3D network from the field of 3D reconstruction into a BEV-based multi-modal sensor detection network, including LiDAR, pinhole cameras, and fisheye cameras. The system collects a total of 24,350 frames of data under real road conditions for experimentation, proving the effectiveness of the proposed method.

Exploring the future: introduction of a new paradigm to examine intergroup experiences

Intergroup contact theory, as one of the most established research strands in social psychology, has mostly relied on overall measured averages of intergroup contact over larger time spans. Yet, in everyday life, intergroup contact experiences are far more complex: they are sequential and cumulative and may vary on a range of dimensions, such as, for example, their perceived valence. In this article, I introduce a new experimental paradigm, primarily developed as a research manipulation, to examine intergroup contact, manipulated on the unit of single interactions in a video-game setting, which can also be run from a web server, so that participants can join from their home computers. Depending on experimental condition, in a first study, participants rated the perceived quality of multiple positive or negative intergroup interactions with an alien species and intergroup attitudes in a storytelling questionnaire setting (Pilot Study, N = 242). Study 1 implemented these positive and negative interactions in a video game, which was played in the laboratory (N = 44), and examined their effects on the perceived contact quality and intergroup attitudes. Study 2 (N = 64) utilized a web-based version of the video game to test the effects on intergroup attitudes. In all three studies participants in the positive condition evaluated the interactions, as well as the overall outgroup, more positive than participants in the negative condition. Furthermore, Study 1 and 2 explored participants' perception of the virtual environment and previous experiences with video games. The results suggest that specifically developed video games offer new pathways to study intergroup interactions.

Three-Layer Electrorefining of Molten Zinc Held on Porous Carbon or Silica Sheets in Molten LiCl–KCl–ZnCl2

We investigated a three-layer electrolysis process utilizing porous holding materials with poor wettability to molten metal, which enables to establish a three-layer configuration of metal(l)/electrolyte(l)/metal(l) by holding metals above the electrolyte regardless of their densities. In this study, porous carbon or silica sheets were used as the holding materials for electrorefining experiments of Zn metal in molten LiCl–KCl–ZnCl2 at 723 K. Three types of experiments were carried out focusing on anodic polarization, electrorefining with cathodic carbon, and three-layer electrolysis using liquid Zn as cathode. The concentration of impurity elements in the Zn was reduced by a factor of 8 to 200 in this experimental condition, highlighting the purification effectiveness of the method. From the results obtained, we have identified certain challenges associated with the three-layer electrolysis process. Furthermore, we discuss potential prospects for industrialization.

Effect of annealing temperature and doping concentrations on structure and optical properties of Eu3+-doped TiO2 nanomaterials

In this study, we successfully synthesized europium-doped TiO2 (TiO2:Eu3+) nanomaterials (NMs) with crystalline sizes ranging from 6.5 to 71.7 nm through a sol-gel method. Analysis of X-ray diffraction (XRD) patterns and ultraviolet-visible (UV-Vis) spectra indicates that the substitution of smaller-sized Ti4+ ions (0.745 Å) by larger-sized Eu3+ ions (0.947 Å) was more efficient at higher doping concentrations and annealing temperatures. Photoluminescence (PL) and photoluminescence excitation (PLE) spectra of the synthesized TiO2:7%Eu3+NMs exhibit a strong red emission band peaking at 613 nm and remarkable absorption in the blue light region centered at 463 nm, making them suitable for use in white light-emitting diode (WLED) applications. Our findings reveal that both annealing temperature and doping concentration significantly influence the structure and properties of these materials. Besides, the research team has seen, under the experimental conditions, the TiO2:7%Eu3+ sample annealed at 800°C exhibits the highest PL intensity. These results underscore the potential of the synthesized TiO2:Eu3+ NMs as red-emitting materials for WLED applications.

The interpretation of animate nouns in child and adult Mandarin: from the Universal Grinder to syntactic structure

Abstract Using animate nouns to refer to entities in the world involves a complex interaction of ontology, cognition and language. The present study evaluates two accounts of the use of animate nouns, with Mandarin Chinese as the vehicle for testing between the competing accounts. One account was proposed by Cheng et al. (2008. How universal is the Universal Grinder? In Marjo van Koppen & Bert Botma (eds.), Linguistics in the Netherlands, 50–62. Amsterdam & Philadelphia: John Benjamins). These researchers contend that the count interpretation is basic for Mandarin animate nouns, due to a lexical blocking effect. To access the alternative, mass interpretation requires some kind of pragmatic coercion. A second account was proposed by Pelletier, based on English (1975. Non-Singular reference: Some preliminaries. Philosophia 5(4). 451–465; 2012. Lexical nouns are both +MASS and +COUNT, but they are neither +MASS nor + COUNT. In Diane Massam (ed.), Count and mass across languages, 9–26. Oxford: Oxford University Press). We extend this account to Mandarin animate nouns, proposing that they are encoded in the mental lexicon with both a count sense and a mass sense. To adjudicate between the accounts, we conducted four experiments that were designed to assess the interpretation assigned to animate nouns by Mandarin-speaking children and adults. The experimental conditions manipulated both the syntactic structures of the sentences and the non-linguistic contexts in which those sentences were presented. The experimental findings support our proposal that both mass and count interpretations of animate nouns are available to children and adults when sentences are presented in contexts that are congruent with these interpretations. The findings also suggest that syntactic structure is an even more critical factor in determining the interpretation that is assigned to animate nouns in Mandarin.