Simple Analytical Method Research Articles

Accurate and highly sensitive detection of Alzheimer's disease-related extracellular vesicles via förster resonance energy transfer

Alzheimer's disease (AD) is the most common neurodegenerative disease in the world and poses a huge challenge to global healthcare. Early and accurate detection of amyloid-β (1-42) (Aβ42), a key biomarker of AD, is crucial for effective diagnosis and intervention of AD. Specific or overexpressed proteins on extracellular vesicles (EVs) describe a close correlation with the occurrence and development of diseases. EVs are a very promising non-invasive biomarker for the diagnosis of AD and other diseases. As a sensitive, simple and rapid analytical method, fluorescence resonance energy transfer (FRET) has been widely applied in the detection of EVs. Herein, we developed a dual labelling strategy for simultaneously detecting EV membrane proteins of Aβ42 and CD63 based on FRET pair consisting of Au nanoclusters (AuNCs) and polydopamine nanospheres (PDANSs). The constructed nanoprobe, termed EVMPFAP assay, could specifically measure the Aβ42 and CD63 on EVs with excellent sensitivity, high specificity and satisfactory accuracy. The limit of detection of EVMPFAP assay was 1.4 × 103 particles mL−1 and the linear range was from 104 to 108 particles mL−1. EVMPFAP assay was successfully used to analyze plasma EVs to distinguish AD and healthy mice. We expect that EVMPFAP assay can be routinely applied for early diagnosis and development-monitoring of AD, thus facilitating the fight against AD.

Development of an HPLC-UV method for the simultaneous determination of allantoin and D-panthenol in cosmetic products containing Aloe vera extracts

AbstractA simple, fast and selective analytical method has been developed for the simultaneous determination of allantoin and D-panthenol in cosmetic products containing Aloe vera extracts. The proposed method depends on reversed-phase liquid chromatography with isocratic flow profile of the mobile phase composed of acetonitrile–10 mM phosphoric acid (pH 2.5) (85:15, v/v), with a C18 column at 30 °C. The analytes were detected with UV–vis. detector at 210 nm. The injection volume was 20 μL. The linearity ranges were found to be 0.2–20 and 0.1–10 μg mL−1 for allantoin and D-panthenol, respectively. LOD values were found to be 0.07 μg mL−1 and 0.03 μg mL−1, LOQ values were found to be 0.2 and 0.1 μg mL−1 for allantoin and D-panthenol, respectively. No interference was observed from concomitants. The developed method was applied to the analysis of 10 different type cosmetic products. It is foreseen that the method will be able to be used in order to carry out routine analysis, quality control and standardization in cosmetic products containing allantoin and D-panthenol.

Biophysical phenotyping of single-cell based on impedance and application for individualized precision medicine

Single-cell biophysical characterization based on impedance measurement is an advantageous approach due to its label-free, high-efficiency, cost-effective and real-time capability. Biophysical phenotyping can yield timely and rich information on physiological and pathological state of cells for disease diagnosis, drug screening, precision medicine, etc. However, precise measurement on single-cell impedance is challenging, particularly hard to figure out the detailed biophysical parameters of single cell due to coupling and complexity of impedance model. Here, we propose an analytic determination method to decode single-cell electrophysiological parameters (including cell-substrate interface capacitance, cell membrane capacitance, cell membrane conductivity, and cytoplasm conductivity) from the impedances measured at optimized frequencies by using analytic solution rather than spectrum fitting. With this simple and fast analytic solution method, the physiological parameters of single cell in natural adhesion state can be accurately determined in real time. We validate this cell parameter determination method in monitoring the change of cell adhesion under hydraulic effects and exploring electrophysiological differences among MCF-7, HeLa, Huh7, and MDA-MB-231 cell lines. Particularly, we apply the approach to optimize tumor treating fields (TTFields) therapy, realizing individualized precision medicine. Our work provides an accurate and efficient approach for characterizing single-cell biophysical properties with real-time, in-situ, label-free, and less invasive advantages.

English Language Teaching and Learning in Secondary Schools in Isoko North Local Government Area of Delta State: Problems and Prospects

This paper studied the problems of teaching and learning English as a second language in junior school certificate examination in Isoko North Local Government Area of Delta State. The study sought to establish the extent to which students in Junior Secondary School and teachers should value English as the language of instruction. The framework adopted is the behaviorist theory of bilingualism. The simple percentage method of data analysis was employed to analyze data. The population comprised students in junior secondary schools in Ozoro precisely the students of Opute Grammar School, Ozoro and Heroes Group of Schools, Ozoro both in Delta State of Nigeria. The sample size was 100, and the instrument for data collection was the questionnaire which was tested and retested on some other students to ensure that it was reliable. It was found out that the majority of the students consider the English language a difficult subject because of their inability to understand every aspect, which the English language entails. It was also found out among others that the level of infiltration of mother tongue into the respondents’ English is very high. This research recommended that good reading habits should be developed in the students and also well-equipped libraries should be provided in the schools and communities in order to improve better performance in their study of English language. It concluded that the problems of teaching and learning English as a second language is as a result of the impact of mother’s tongue, inadequate textbooks, poor language background and lack of professional growth and development of teachers. If these discovered factors are not checked there will be a drastic decline in standard of education.

PENGARUH INOVASI PRULINK NEXTGEN TERHADAP ATTITUDE (STUDI PADA KONSUMEN PT PRUDENTIAL LIFE ASSURANCE CABANG XYZ)

Innovation in the insurance industry fundamentally aims to meet consumer needs and expectations while adhering to existing regulations. This research aims to investigate the influence of PRULink NextGen innovation on consumer attitudes at PT Prudential Life Assurance Branch XYZ. This type of research is quantitative research with a simple linear regression analysis method. The data used are sourced from questionnaires as primary data, and interviews as well as literature studies as secondary data sources. The population of this research is customers or potential customers who have been prospected about PRULink NextGen by marketing staff of PT Prudential Life Assurance Branch XYZ. This research uses purposive sampling technique as a non-probability sampling technique with a sample size of 100 people. Testing and data analysis are conducted using SPSS 25.0. The results of this research indicate a significant influence of PRULink NextGen innovation on consumer attitudes at PT Prudential Life Assurance. Key words: innovation, attitude, PRULink NextGen

Kinetic modeling of the monoamine oxidase-B radioligand [18F]SMBT-1 in human brain with positron emission tomography

This paper describes pharmacokinetic analyses of the monoamine-oxidase-B (MAO-B) radiotracer [18F](S)-(2-methylpyrid-5-yl)-6-[(3-fluoro-2-hydroxy)propoxy]quinoline ([18F]SMBT-1) for positron emission tomography (PET) brain imaging. Brain MAO-B expression is widespread, predominantly within astrocytes. Reactive astrogliosis in response to neurodegenerative disease pathology is associated with MAO-B overexpression. Fourteen elderly subjects (8 control, 5 mild cognitive impairment, 1 Alzheimer’s disease) with amyloid ([11C]PiB) and tau ([18F]flortaucipir) imaging assessments underwent dynamic [18F]SMBT-1 PET imaging with arterial input function determination. [18F]SMBT-1 showed high brain uptake and a retention pattern consistent with the known MAO-B distribution. A two-tissue compartment (2TC) model where the K1/k2 ratio was fixed to a whole brain value best described [18F]SMBT-1 kinetics. The 2TC total volume of distribution (VT) was well identified and highly correlated (r2∼0.8) with post-mortem MAO-B indices. Cerebellar grey matter (CGM) showed the lowest mean VT of any region and is considered the optimal pseudo-reference region. Simplified analysis methods including reference tissue models, non-compartmental models, and standard uptake value ratios (SUVR) agreed with 2TC outcomes (r2 > 0.9) but with varying bias. We found the CGM-normalized 70–90 min SUVR to be highly correlated (r2 = 0.93) with the 2TC distribution volume ratio (DVR) with acceptable bias (∼10%), representing a practical alternative for [18F]SMBT-1 analyses.

Rapid and sensitive determination of legacy and emerging per- and poly-fluoroalkyl substances with solid-phase microextraction probe coupled with mass spectrometry

This study was designed to develop a rapid and sensitive method for quantifying legacy and emerging per- and polyfluoroalkyl substances (PFASs) in environmental samples with solid-phase microextraction (SPME) coupled with mass spectrometry (MS). An innovative SPME probe was fabricated via in situ polymerization, and the probe coating was optimized with response surface methodology to maximize the fluorine–fluorine interactions and electrostatic properties and ensure high selectivity for the target PFASs with enrichment factors of 48–491. The coupled SPME and MS provided a rapid and sensitive method for analyses of PFASs, with excellent linearity (r ≥ 0.9962) over the concentration range 0.001–1 μg/L and remarkably low detection limits of 0.1–13.0 ng/L. This method was used to analyze trace PFASs in tap water, river water, and wastewater samples and proved to be a simple and efficient analytical method for selective enrichment and detection of contaminants in the environment.

Simple and efficient methods for local structural analysis in polydisperse hard disk systems.

In nonequilibrium statistical physics, quantifying the nearest (and higher-order) neighbors and free volumes of particles in many-body systems is crucial to elucidating the origin of macroscopic collective phenomena, such as glass/granular jamming transitions and various aspects of the behavior of active matter. However, conventional techniques (based on a fixed-distance cutoff or the Voronoi construction) have mainly been applied to equilibrated, homogeneous, and monodisperse particle systems. In this paper, we implement simple and efficient methods for local structure analysis in nonequilibrium, inhomogeneous, and polydisperse hard disk systems. We show how these novel methods can overcome the difficulties encountered by conventional techniques as well as demonstrate some applications.

Monitoring Ti3C2Tx MXene Degradation Pathways Using Raman Spectroscopy.

Extending applications of Ti3C2Tx MXene in nanocomposites and across fields of electronics, energy storage, energy conversion, and sensor technologies necessitates simple and efficient analytical methods. Raman spectroscopy is a critical tool for assessing MXene composites; however, high laser powers and temperatures can lead to the materials' deterioration during the analysis. Therefore, an in-depth understanding of MXene photothermal degradation and changes in its oxidation state is required, but no systematic studies have been reported. The primary aim of this study was to investigate the degradation of the MXene lattice through Raman spectroscopic analysis. Distinct spectral markers were related to structural alterations within the Ti3C2Tx material after subjecting it to thermal- and laser-induced degradation. During the degradation processes, spectral markers were revealed for several specific steps: a decrease in the number of interlayer water molecules, a decrease in the number of -OH groups, formation of C-C bonds, oxidation of the lattice, and formation of TiO2 nanoparticles (first anatase, followed by rutile). By tracking of position shifts and intensity changes for Ti3C2Tx, the spectral markers that signify the initiation of each step were found. This spectroscopic approach enhances our understanding of the degradation pathways of MXene, and facilitating enhanced and dependable integration of these materials into devices for diverse applications, from energy storage to sensors.

The Influence of AKHLAK Culture (Trustworthy, Competent, Harmonious, Loyal, Adaptive, Collaborative) on the Performance of PT Kilang Pertamina Internasional Refinery Unit III Employees

This study aimed to test or analyze how the influence of AKHLAK culture on the performance of employees of PT Kilang Pertamina International Refinery Unit III. The population in this study were 920 employees of PT Pertamina International Refinery Unit III. The sampling technique in this study used a Stratified random sampling technique. Thus, the respondents of this study were 91 respondents from all functions/sections in PT Pertamina International Refinery Unit III. This study used primary data obtained through questionnaires and simple linear regression analysis methods as data analysis techniques. The results showed that organizational culture had a positive and significant effect on employee performance variables of PT Pertamina International Refinery Unit III. Keywords: AKHLAK culture, organizational culture, employee performance

The Influence of Employee Loyalty on Job Promotion at Ogan Ilir Regency's Civil Service Agency

This study aimed to determine and analyze the effect of employee loyalty on job promotion at the Civil Service and Human Resource Development Agency of Ogan Ilir Regency. This research used quantitative methods. The population in this study were all Civil Servants at the Civil Service and Human Resource Development Agency of Ogan Ilir Regency. The sample used in this study was taken using saturated sampling technique which amounted to 32 respondents. This study used primary data obtained through questionnaires and simple linear regression analysis methods were data analysis techniques. Based on the results of the analysis, it can be concluded that employee loyalty had a positive and significant effect on job promotion at the Civil Service and Human Resource Development Agency of Ogan Ilir Regency. Keywords: employee loyalty, job promotion

Lifting the veil off treatment effect heterogeneity

Clinicians often suspect that a treatment effect can vary across individuals. However, they usually lack “evidence-based” guidance regarding potential heterogeneity of treatment effects (HTE). Potentially actionable HTE is rarely discovered in clinical trials and is widely believed (or rationalized) by researchers to be rare. Conventional statistical methods to test for possible HTE are extremely conservative and tend to reinforce this belief. In truth, though, there is no realistic way to know whether a common, or average, effect estimated from a clinical trial is relevant for all, or even most, patients. This absence of evidence, misinterpreted as evidence of absence, may be resulting in sub-optimal treatment for many individuals. We first summarize the historical context in which current statistical methods for randomized controlled trials (RCTs) were developed, focusing on the conceptual and technical limitations that shaped, and restricted, these methods. In particular, we explain how the common-effect assumption came to be virtually unchallenged. Second, we propose a simple graphical method for exploratory data analysis that can provide useful visual evidence of possible HTE. The basic approach is to display the complete distribution of outcome data rather than relying uncritically on simple summary statistics. Modern graphical methods, unavailable when statistical methods were initially formulated a century ago, now render fine-grained interrogation of the data feasible. We propose comparing observed treatment-group data to “pseudo data” engineered to mimic that which would be expected under a particular HTE model, such as the common-effect model. A clear discrepancy between the distributions of the common-effect pseudo data and the actual treatment-effect data provides prima facie evidence of HTE to motivate additional confirmatory investigation. Artificial data are used to illustrate implications of ignoring heterogeneity in practice and how the graphical method can be useful.

Sentimental analysis and prediction of socioeconomic disasters tweets by ML and regular expression

Sentiment analysis is a method of analyzing emotions and using text analysis techniques with natural language processing methods. Sentiment analysis uses data from various sources to identify the user’s attitude through different aspects. It is widely used for extracting opinions and recognizing sentiments, which helps Business organizations understand the user’s needs. This paper proposes a simple but compelling sentiment analysis method, showing the combined scores based on positive and negative words. Then, the tweets are categorized as Neutral, Negative, or Positive according to the scores. Sentiment analysis and opinion mining have grown significantly in the last decade. Different studies in this domain try to determine people’s feelings, opinions, and emotions about something or someone. The main objective of this analysis is to determine the sentiment of the review using a machine learning model and then compare the result with the manual review of the data. This would allow researchers to represent and analyze opinions objectively across different domains. A hybrid method that combines a supervised machine learning algorithm with natural language processing techniques is suggested for review analysis. This project aims to find the best model to predict the sentiment of the tweets on airlines. During the research process and considering various methods and variables that should be considered, we found that methods like naïve Bayes and random forest were not fully explored. The proposed system improves an effective and more feasible method for sentimental analysis using machine learning, multinomialNB, linear regression, and regular expression.

LiteBIRD and CMB-S4 sensitivities to reheating in plateau models of inflation

We study the sensitivity of LiteBIRD and CMB-S4 to the reheating temperature and the inflaton coupling in three types of plateau-potential models of inflation, namely mutated hilltop inflation, radion gauge inflation, and α-attractor T models. We first find relations between model parameters and CMB observables in all models. We then perform Monte Carlo Markov Chain based forecasts to quantify the information gain on the reheating temperature, the inflaton coupling, and the scale of inflation that can be achieved with LiteBIRD and CMB-S4, assuming a fiducial tensor-to-scalar ratio r̅ ∼ 0.02 and neglecting foreground contamination of the B-mode polarization spectrum. We compare the results of the forecasts to those obtained from a recently proposed simple analytic method. We find that both LiteBIRD and CMB-S4 can simultaneously constrain the scale of inflation and the reheating temperature in all three types of models. They can for the first time obtain both an upper and lower bound on the latter, comprising the first ever measurement of the big bang temperature. In the mutated hilltop inflation and radion gauge inflation models this can be translated into a measurement of the inflaton coupling in parts of the parameter space. Constraining this microphysical parameter will help to understand how these models of inflation may be embedded into a more fundamental theory of particle physics.

The Effect of Job Passion on Innovative Work Behaviors: Analytical Research in the Ministry of Higher Education and Scientific Research

The current research aims to test the impact of Job passion on innovative work behaviors, and the idea of the research revolves around providing a job passion that contributes and supports the innovative work behaviors among the employees of the Ministry of Higher Education and Scientific Research, as the job passion variable includes four dimensions (enjoyment at work, self-motivation, self-identity, and a sense of learning). The innovative work behavior variable has addressed four dimensions (the ability to provide creative solutions to problems, the ability to new ideas and proposals, the ability to change as well as initiate, and the spirit of risk), A sample of the employees of the Ministry of Higher Education and Scientific Research, where a random stratified sample of 328 employees were selected from the study community (2229) relied on the questionnaire for collecting data, and the questionnaires valid for statistical analysis were 322 questionnaires. The research used a number of statistical methods to obtain the results of the questionnaire, especially the simple correlation coefficient (Pearson) and descriptive analysis methods using the SPSS.v23 and AMOS.v23). It has proved the validity of the hypotheses through which a set of results were reached, the most prominent of which is the existence of a relationship between the impact of job passion and its dimensions on innovative work behaviors. The dimensions of the variable of innovative work behaviors above are available, but they do not be at the required level, where the ability to change and generate creative solutions. This requires focusing on them in addressing problems and making appropriate decisions that are based on a correct scientific basis, and the management's view of employees is not limited because they represent essential capabilities and tools for implementing decisions and policies. Paper type: Research paper.

A simplified weak coupling dynamic analysis method for running safety evaluation of train on bridges under earthquake excitation

This study proposes a simplified analysis method that couples the bridge and train-track subsystem in a weak form to facilitate the dynamic analysis of the train-track-bridge coupled system (TTBS) under earthquakes. The method includes three main steps: (i) performing dynamic analysis of the bridge under seismic conditions to obtain the response of the bridge deck; (ii) interpolating the bridge displacement beneath each wheelset based on the train's velocity, departure time, and the initial positions of the wheelsets; and (iii) assessing the running safety of the train by incorporating the interpolated bridge response as track irregularity into the train-track coupled system. Steps (i) and (iii) can be analyzed separately using finite element and multibody dynamics software, eliminating the need to create a complex TTBS model that is challenging to achieve within a single software platform. Additionally, based on the method’s assumptions, the earthquake excitation on the train can be separated into the seismic inertial effect and seismic-induced bridge deformation, enabling a quantitative analysis of the impact of these two types of excitations on train safety. Taking a 10-span simply supported bridge and a long-span cable-stayed bridge as examples, the proposed method’s assumptions are verified by comparing its results with those obtained from a complex TTBS model. Furthermore, the impact characteristics of inertial effects and seismic-induced bridge deformation on train safety for these two types of bridges are analyzed. The proposed method offers robust support for seismic design of bridges and facilitates a comprehensive analysis of the mechanisms through which seismic excitations affect train safety.

Softening-based interface model and nonlinear load-settlement response analysis of piles in saturated and unsaturated multi-layered soils

This work presents a simplified method for the nonlinear analysis of the load–displacement response of piles in multi-layered soils. As a starting step, a new interface model based on the disturbed state concept (DSC) is put forth to simulate the interface shear stress-displacement relationship by considering the nonlinear hardening–softening behaviour. In the new model, input parameters can be conveniently calibrated using conventional interface shear tests or on-site tests. The good agreement between predictions and experimental data from interface direct shear tests validated the performance of the proposed DSC model. The DSC model performed better in terms of predictions when compared to the hyperbolic one. Next, the soil-structure interface model and bearing capacity theory are coupled to provide a theoretical framework for the analysis of pile load-transfer in saturated and unsaturated multi-layered soils, where the DSC model is employed to represent base resistance as well as skin friction. This work also discusses the profile of steady-state in-situ matric suction, soil–water characteristic curve, and pore-water pressure of unsaturated soils. The proposed method has the advantage of being used in practice as it is simple to obtain input parameters from laboratory tests, as well as Standard Penetration or Cone Penetration Tests. The proposed framework is finally applied to the analysis of five well-documentedcase studies. The proposed approach and the static load test results from the field measurements are found to be in satisfactory agreement, indicating that the proposed method performs well. The proposed method is suggested to be utilised for preliminary analysis, planning a suitable programme of loading tests, as well as optimizing the pile design by back analysis ofthe load test results.

Green Synthetic Approach for the Preparation of Blue Emitting Gold Nanoclusters: A Simple Analytical Method for Detection of Hexaconazole Fungicide.

Blue emissive Argyreia nervosa-capped gold nanoclusters (A. nervosa-AuNCs) were synthesized via a simple environment-friendly method. The developed probe exhibits rapid response towards the target analyte (hexaconazole fungicide). Several characterizations, including FT-IR, UV-visible, fluorescence, HR-TEM, XPS, and fluorescence lifetime, were studied to confirm the formation of A. nervosa-AuNCs. The A. nervosa-AuNCs displayed emission and excitation peaks at 470 and 390nm, respectively. Furthermore, the quantum yield (QY) of A. nervosa-AuNCs was 21.25%. The as-synthesized A. nervosa-AuNCs showed a good linear response with hexaconazole in the concentration range of 0.025-180μM, with a detection limit (LOD) of 21.94nM, indicating A. nervosa-AuNCs could be used as a sensitive and selective probe for detecting hexaconazole through a fluorescence "turn-off" mechanism. The A. nervosa-AuNCs were successfully used to detect hexaconazole in real samples. Moreover, A. nervosa-AuNCs were used as a bio-imaging probe for visualization of Saccharomyces cerevisiae cells.

Simplified analytical method for predicting the large deformation of stiffened plates with initial cracks under repeated impacts

The impact resistance capacity of structures can be affected by the formation of cracks. To address the issue of repeated impacts on structures with initial cracks, a relationship was established between cracks and the energy dissipation of stiffened plates based on rigid–plastic theory. A simplified analytical method was proposed to predict the large plastic deformation of stiffened plates with initial cracks. To verify the accuracy of the analytical method, repeated impact experiments and numerical simulations were conducted. The influences of crack length and position on the dynamic responses of stiffened plates were explored. The experimental, numerical, and analytical results were in good agreement. The research results showed that the permanent deformations of stiffened plates increases approximately linearly with increasing crack length on the outer plate. However, the influence of stiffener cracks on the permanent deformation of stiffened plates depends on whether the stiffener fractures. The influence of cracks on the load-carrying capacity of the structure is more pronounced when the crack is located in the stiffener.

Ultrasensitive Aptasensor for α-Amatoxin Detection Based on the DNA Tetrahedral Nanostructure Triggering Rolling Circle Amplification and Signal Amplification.

Poisonous mushrooms containing α-amatoxin can be lethal, making it imperative to develop a rapid and sensitive detection method for α-amatoxin. Utilizing the DNA tetrahedral structure as its foundation, the aptamer allows controlled density and orientation. Consequently, we designed aptamer tetrahedral functionalized magnetic beads that specifically target α-amanitin to release complementary DNA (C-DNA) strands. These strands were then employed as primers to initiate rolling circle amplification (RCA) with fluorescent dyes. The combination of SYBR Green I detection probes facilitated the amplification of the detection signal, enhancing the detection sensitivity of the aptasensor. The calculated detection limit was determined to be 3 ng/mL, a magnitude lower than that of other aptasensors by 2 orders of magnitude. The aptasensor integrates the advantages of high sensitivity and specificity, offering a simple and reliable rapid detection method for α-amanitin analysis.