Analysis Method Research Articles

Development and Validation of Instruments for Assessing the Impact of Artificial Intelligence on Students in Higher Education

<p style="text-align:justify">The role of artificial intelligence (AI) in education remains incompletely understood, demanding further evaluation and the creation of robust assessment tools. Despite previous attempts to measure AI's impact in education, existing studies have limitations. This research aimed to develop and validate an assessment instrument for gauging AI effects in higher education. Employing various analytical methods, including Exploratory Factor Analysis, Confirmatory Factor Analysis, and Rasch Analysis, the initial 70-item instrument covered seven constructs. Administered to 635 students at Nueva Ecija University of Science and Technology – Gabaldon campus, content validity was assessed using the Lawshe method. After eliminating 19 items through EFA and CFA, Rasch analysis confirmed the construct validity and led to the removal of three more items. The final 48-item instrument, categorized into learning experiences, academic performance, career guidance, motivation, self-reliance, social interactions, and AI dependency, emerged as a valid and reliable tool for assessing AI's impact on higher education, especially among college students.</p>

Pengaruh model pembelajaran discovery learning terintegrasi ayat-ayat Al-Quran terhadap hasil belajar fisika dan sikap spiritual siswa Ponpes Modern As-Sa’adah pada materi gerak melingkar

This research was conducted to determine the effect of the discovery learning model integrated with verses from the Koran on the physics learning outcomes and spiritual attitudes of As-sa'adah modern Islamic boarding school students on circular motion material, with data collection techniques through pretest and posttest. Purpose sampling technique, the sample consisted of 30 students from the As-sa'adah Modern Islamic Boarding School, Serang Banten. The analytical method used in this research is Quantitative Data Analysis. The research results show that the results of learning physics and spiritual attitudes without using the Discovery Learning learning model integrated with Al-Quran verses, based on the descriptive test, are quite good. Physics learning outcomes and spiritual attitudes using the integrated Discovery Learning learning model of Al-Quran verses, based on descriptive tests in the good category. There is an influence of the Discovery Learning learning model integrated with Al-Quran verses and without integrated Al-Quran verses. The results of the Pretest analysis obtained a p-value= 0.034 and the Posttest obtained a p-value= 0.000. This shows that the p-value (sig) < 0.05, so H0 is rejected. Thus, it can be concluded that student learning outcomes after treatment between the experimental group and the control group are significantly different.

Using modified Fenn diagrams to assess ventilatory acclimatization during ascent to high altitude: Effect of acetazolamide.

High altitude (HA) ascent imposes systemic hypoxia and associated risk of acute mountain sickness. Acute hypoxia elicits a hypoxic ventilatory response (HVR), which is augmented with chronic HA exposure (i.e., ventilatory acclimatization; VA). However, laboratory-based HVR tests lack portability and feasibility in field studies. As an alternative, we aimed to characterize area under the curve (AUC) calculations on Fenn diagrams, modified by plotting portable measurements of end-tidal carbon dioxide ( ) against peripheral oxygen saturation ( ) to characterize and quantify VA during incremental ascent to HA (n=46). Secondarily, these participants were compared with a separate group following the identical ascent profile whilst self-administering a prophylactic oral dose of acetazolamide (Az; 125mg BID; n=20) during ascent. First, morning and measurements were collected on 46 acetazolamide-free (NAz) lowland participants during an incremental ascent over 10days to 5160m in the Nepal Himalaya. AUC was calculated from individually constructed Fenn diagrams, with a trichotomized split on ranked values characterizing the smallest, medium, and largest magnitudes of AUC, representing high (n=15), moderate (n=16), and low (n=15) degrees of acclimatization. After characterizing the range of response magnitudes, we further demonstrated that AUC magnitudes were significantly smaller in the Az group compared to the NAz group (P=0.0021), suggesting improved VA. These results suggest that calculating AUC on modified Fenn diagrams has utility in assessing VA in large groups of trekkers during incremental ascent to HA, due to the associated portability and congruency with known physiology, although this novel analytical method requires further validation in controlled experiments. HIGHLIGHTS: What is the central question of this study? What are the characteristics of a novel methodological approach to assess ventilatory acclimatization (VA) with incremental ascent to high altitude (HA)? What is the main finding and its importance? Area under the curve (AUC) magnitudes calculated from modified Fenn diagrams were significantly smaller in trekkers taking an oral prophylactic dose of acetazolamide compared to an acetazolamide-free group, suggesting improved VA. During incremental HA ascent, quantifying AUC using modified Fenn diagrams is feasible to assess VA in large groups of trekkers with ascent, although this novel analytical method requires further validation in controlled experiments.

Drugs in Human Milk Part 1: Practical and Analytical Considerations in Measuring Drugs and Metabolites in Human Milk.

Human milk is a remarkable biofluid that provides essential nutrients and immune protection to newborns. Breastfeeding women consuming medications could pass the drug through their milk to neonates. Drugs can be transferred to human milk by passive diffusion or active transport. The physicochemical properties of the drug largely impact the extent of drug transfer into human milk. A comprehensive understanding of the physiology of human milk formation, composition of milk, mechanisms of drug transfer, and factors influencing drug transfer into human milk is critical for appropriate selection and use of medications in lactating women. Quantification of drugs in the milk is essential for assessing the safety of pharmacotherapy during lactation. This can be achieved by developing specific, sensitive, and reproducible analytical methods using techniques such as liquid chromatography coupled with mass spectrometry. The present review briefly discusses the physiology of human milk formation, composition of human milk, mechanisms of drug transfer into human milk, and factors influencing transfer of drugs from blood to milk. We further expand upon and critically evaluate the existing analytical approaches/assays used for the quantification of drugs in human milk.

학습 효과가 높은 수업과 낮은 수업의 학습 과정과 평가의 특성에 관한 연구

Objectives The purpose of this study is to explore the characteristics of instructions recognized as having a high learning effect and as having a low learning effect. Methods For this purpose, we conducted written interviews using online platform with 18 prospective instructors who are experiencing the pre-instructor course at the graduate school of education. It was designed to focus on instructions experienced before, not on instructions currently being taken, and through this, the process and effect of learning could be reported more objectively. The collected qualitative data were analyzed using a thematic anal-ysis method, and the learning process of instructions with high learning effects and instructions with low learning effects were derived and presented in a diagram. Results As a result of the study, 3 main categories, 9 themes, and 19 subcategories were derived as character-istics of the learning process included in instruction with high learning effect, and the amount of learning load, dif-ficulty, and responsibility perceived by learners were also confirmed along with the learning burden factors. As for the instruction with low learning effect, 3 main categories, 9 themes, and 18 subcategories were derived, and these included ‘no task’ and ‘no burden’. In the instruction with high learning effect, the focus of assignments and evaluations was on the learning process and performance, and improvement and feedback were made through the feedback of the instructor. In the instruction with low learning effect, the focus of assignments and evaluations was on organizing, summarizing, and general evaluation, and it was difficult to confirm improvement and feedback through instructor's feedback. Moreover, the difficulty and amount of learning load in the class were burden factors that appeared in both classes with high and low learning effects. Considering these results, instructors need to consider ways to have explanatory power to effectively deliver class content by analyzing learners' levels rather than reducing the difficulty and amount of learning. Conclusions Based on these findings, recommendations were provided to guide professors in aiming for and de-signing effective instructions.

Ambiguities in Decomposing Molecular Polarizability into Atomic Charge Flow and Induced Dipole Contributions.

The molecular dipole polarizability can be decomposed into components corresponding to the charge flow between atoms and changes in atomic dipole moments. Such decompositions are recognized to depend on how atoms are defined within a molecule, as, for example, by Hirshfeld, iterative Stockholder, or quantum topology partitioning of the electron density. For some of these, however, there are significant differences between the numerical results obtained by analytical response methods and finite field calculations. We show that this difference is due to analytical response methods accounting for (only) the change in electron density by a perturbation, while finite field methods may also include a component corresponding to a perturbation-dependent change in the definition of an atom within a molecule. For some atom-in-molecule definitions, such as the iterative Hirshfeld, iterative Stockholder, and quantum topology methods, the latter effect significantly increases the charge flow component. The decomposition of molecular polarizability into atomic charge flow and induced dipole components thus depends on whether the atom-in-molecule definition is taken to be perturbation-dependent.

Electrochemiluminescence Microscopy.

Electrochemiluminescence (ECL) is rapidly evolving from an analytical method into an optical microscopy. The orthogonality of the electrochemical trigger and the optical readout distinguishes it from classic microscopy and electrochemical techniques, owing to its near-zero background, remarkable sensitivity, and absence of photobleaching and phototoxicity. In this review, we summarize the recent advances in ECL imaging technology, emphasising original configurations which enable the imaging of biological entities and the improvement of the analytical properties by increasing the complexity and multiplexing of bioassays. Additionally, mapping the (electro)chemical reactivity in space provides valuable information on nanomaterials and facilitates deciphering ECL mechanisms for improving their performances in diagnostics and (electro)catalysis. Finally, we highlight the recent achievements in imaging at the ultimate limits of single molecules, single photons or single chemical reactions, and the current challenges to translate the ECL imaging advances to other fields such as material science, catalysis and biology.

The use of artificial intelligence for predicting postinfarction myocardial viability in echocardiographic images.

Evaluation of standard echocardiographic examination with artificial intelligence may help in the diagnosis of myocardial viability and function recovery after acute coronary syndrome. Sixty-one consecutive patients with acute coronary syndrome were enrolled in the present study (43 men, mean age 61 ± 9 years). All patients underwent percutaneous coronary intervention (PCI). 533 segments of the heart echo images were used. After 12 ± 1 months of follow-up, patients had an echocardiographic evaluation. After PCI each patient underwent cardiac magnetic resonance (CMR) with late enhancement and low-dose dobutamine echocardiographic examination. For texture analysis, custom software was used (MaZda 5.20, Institute of Electronics).Linear and non-linear (neural network) discriminative analyses were performed to identify the optimal analytic method correlating with CMR regarding the necrosis extent and viability prediction after follow-up. Texture parameters were analyzed using machine learning techniques: Artificial Neural Networks, Namely Multilayer Perceptron, Nonlinear Discriminant Analysis, Support Vector Machine, and Adaboost algorithm. The mean concordance between the CMR definition of viability and three classification models in Artificial Neural Networks varied from 42% to 76%. Echo-based detection of non-viable tissue was more sensitive in the segments with the highest relative transmural scar thickness: 51-75% and 76-99%. The best results have been obtained for images with contrast for red and grey components (74% of proper classification). In dobutamine echocardiography, the results of appropriate prediction were 67% for monochromatic images. Detection and semi-quantification of scar transmurality are feasible in echocardiographic images analyzed with artificial intelligence. Selected analytic methods yielded similar accuracy, and contrast enhancement contributed to the prediction accuracy of myocardial viability after myocardial infarction in 12 months of follow-up.

Re-assessment of monoclonal antibodies against diclofenac for their application in the analysis of environmental waters.

The non-steroidal anti-inflammatory drug (NSAID) diclofenac (DCF) is an important environmental contaminant occurring in surface waters all over the world, because, after excretion, it is not adequately removed from wastewater in sewage treatment plants. To be able to monitor this pollutant, highly efficient analytical methods are needed, including immunoassays. In a medical research project, monoclonal antibodies against diclofenac and its metabolites had been produced. Based on this monoclonal anti-DCF antibody, a new indirect competitive enzyme-linked immunosorbent assay (ELISA) was developed and applied for environmental samples. The introduction of a spacer between diclofenac and the carrier protein in the coating conjugate led to higher sensitivity. With a test midpoint of 3 μg L-1 and a measurement range of 1-30 μg L-1, the system is not sensitive enough for direct analysis of surface water. However, this assay is quite robust against matrix influences and can be used for wastewater. Without adjustment of the calibration, organic solvents up to 5%, natural organic matter (NOM) up to 10 mg L-1, humic acids up to 2.5 mg L-1, and salt concentrations up to 6 g L-1 NaCl and 75 mg L-1 CaCl2 are tolerated. The antibody is also stable in a pH range from 3 to 12. Cross-reactivity (CR) of 1% or less was determined for the metabolites 4'-hydroxydiclofenac (4'-OH-DCF), 5-hydroxydiclofenac (5-OH-DCF), DCF lactam, and other NSAIDs. Relevant cross-reactivity occurred only with an amide derivative of DCF, 6-aminohexanoic acid (DCF-Ahx), aceclofenac (ACF) and DCF methyl ester (DCF-Me) with 150%, 61% and 44%, respectively. These substances, however, have not been found in samples. Only DCF-acyl glucuronide with a cross-reactivity of 57% is of some relevance. For the first time, photodegradation products were tested for cross-reactivity. With the ELISA based on this antibody, water samples were analysed. In sewage treatment plant effluents, concentrations in the range of 1.9-5.2 μg L-1 were determined directly, with recoveries compared to HPLC-MS/MS averaging 136%. Concentrations in lakes ranged from 3 to 4.4 ng L-1 and were, after pre-concentration, determined with an average recovery of 100%.

Quantification of native lignin structural features with gel‐phase 2D‐HSQC0 reveals lignin structural changes during extraction

Our ability to study and valorize the lignin fraction of biomass is hampered by the fundamental and still unmet challenge of precisely quantifying native lignin’s structural features. Here, we developed a rapid elevated‐temperature 1H–13C Heteronuclear Single‐Quantum Coherence Zero (HSQC0) NMR method that enables this precise quantification of native lignin structural characteristics even with whole plant cell wall (WPCW) NMR spectroscopy, overcoming fast spin relaxation in the gel phase. We also formulated a Gaussian fitting algorithm to perform automatic and reliable spectral integration. By combining HSQC0 measurements with yield measurements following depolymerization, we can confirm the combinatorial nature of radical coupling reactions during biosynthesis leading to a random sequential organization of linkages within a largely linear lignin chain. Such analyses illustrate how this analytical method can greatly facilitate the study of native lignin structure, which can then be used for fundamental studies or to understand lignin depolymerization methods like reductive catalytic fractionation or aldehyde‐assisted fractionation.

Enhanced uranium removal from leach liquor using raw and activated sludge as sustainable adsorbents

ABSTRACT To eliminate uranium from sulphate leach solution, this study introduces an economical, environmentally friendly adsorbent derived from dewatered municipal sludge (RS) and activated (AS) using calcium oxide. Various analytical methods, including scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FTIR), Brunauer – Emmett – Teller (BET) analysis, and X-ray fluorescence spectroscopy (XRF), were employed in the characterisation of both materials. The efficacy of these adsorbents in removing uranium from sulphate leach fluid was systematically explored resulting in the achievement of a maximum adsorption capacity of 33.0 mg g−1 and 60.2 mg g−1 for RS and AS respectively. These adsorption capacity were detected using the following operational parameters: solution pH equals 2.0, 240 min as a contact time between the adsorbent and U(VI) solution, U(VI) initial concentration of 250 mg L−1, adsorbent dosage of 5.0 g L−1 and room temperature. The pseudo-second order kinetic and Langmuir isotherm models were determined to be the most suitable for the U(VI) adsorption process, showing a chemisorption, monolayer, and uniform process for the uranium adsorption by both materials. Using 1.0 M hydrochloric acid, over 96% of the U(VI) was successfully desorbed from the loaded sorbent, and AS sorbent held its stability for six sorption/desorption cycles in a row. Overall, this study offers a promising solution for sewage sludge disposal while addressing economic and environmental concerns.

Quantification of native lignin structural features with gel-phase 2D-HSQC0 reveals lignin structural changes during extraction.

Our ability to study and valorize the lignin fraction of biomass is hampered by the fundamental and still unmet challenge of precisely quantifying native lignin's structural features. Here, we developed a rapid elevated-temperature 1H-13C Heteronuclear Single-Quantum Coherence Zero (HSQC0) NMR method that enables this precise quantification of native lignin structural characteristics even with whole plant cell wall (WPCW) NMR spectroscopy, overcoming fast spin relaxation in the gel phase. We also formulated a Gaussian fitting algorithm to perform automatic and reliable spectral integration. By combining HSQC0 measurements with yield measurements following depolymerization, we can confirm the combinatorial nature of radical coupling reactions during biosynthesis leading to a random sequential organization of linkages within a largely linear lignin chain. Such analyses illustrate how this analytical method can greatly facilitate the study of native lignin structure, which can then be used for fundamental studies or to understand lignin depolymerization methods like reductive catalytic fractionation or aldehyde-assisted fractionation.

OILVEQ: an Italian external quality control scheme for cannabinoids analysis in galenic preparations of cannabis oil.

Italy legalized cannabis oil for specific medical conditions (neuropathic pain, refractory epilepsy and other established pathologies) in 2015, but mandates titration of principal cannabinoids before marketing each batch using iphenated techniques coupled with mass spectrometry. To assess reliability of laboratories from the Italian National Health Service in charge of titrating the batches, the Italian National Institute of Health set up an quality control program on determination of Δ9-tetrahydrocannabinol l (THC), cannabidiol (CBD), Δ9-tetrahydrocannabinolic acid A (THCA-A) and cannabidiolic acid (CBDA) in cannabis oil preparations. Two rounds of exercises have been carried out since 2019, involving sixteen Italian laboratories. Five different cannabis oil samples (19-1A and 19-1B for the first round and 22-1A, 22-1B and 22-1C for the second one were prepared and 1 mL amount of each sample was sent to the laboratories. The quantitative performance of each laboratory was assessed calculating the z-score value, a statistical measurement for value's relationship to the mean of a group of values. In the first round, eight out of fourteen laboratories employed an LC-MS while the remaining six used GC-MS. Differently, in the second round, six out of eleven laboratories employed a GC-MS while the remaining five used LC-MS. In the first round, only 28.6 % laboratories achieved an acceptable performance (z-score±2), and all of them used LC-MS as analytical method. In the second round, none of the laboratories achieved an acceptable performance. Satisfactory results, based on z-scores, were generally low (0.0-75.0 %), with only one exception of 100 % for THCA-A determination in sample 22-1B. In the second round, three false negatives (two THC and one CBD by GC-MS determination) were reported while no false positives were described in the blank sample. The two rounds yielded a mean ERR% of 42 % approximately and a mean CV% around 70 % in GC-MS determination. When applying LC-MS determination, the two rounds yielded a mean ERR% of 36 % approximately and a mean CV% around 33 %. The obtained results underline the need for a clear and consistent protocol to be adopted by all laboratories intending to include the titration of oily cannabis-based products into their routinely analytical techniques. This emphasis on methodology standardization and participation to quality control schemes is essential for ensuring reliable and accurate measurements, ultimately enhancing the overall effectiveness and reliability of medical cannabis treatments.

The Influence of Store Atmosphere and Price on Sales Levels Through Purchasing Decisions As A Mediator

This study aims to examine how much influence the store atmosphere and prices have on the level of sales of coffee from Hati Pariaman through purchasing decisions as an intervening variable. Methods of data collection through surveys and distributing questionnaires, with a sample of 100 respondents. The analytical method used is SEM analysis using smartpls. The research results obtained based on hypothesis testing obtained that there is a significant influence of store atmosphere on purchasing decisions. There is a significant effect of prices on purchasing decisions. There is a significant influence store atmosphere on the level of sales. There is a significant effect of prices on the level of sales. There is a significant influence of purchasing decisions on the level of sales. Purchase decisions mediate the effect of store atmosphere on sales levels. Purchasing decisions mediate the effect of prices on sales levels.

Analytical and Experimental Evaluation of Two-Layered Unsaturated Sand Bearing Capacity

Pavement design methods based on principles of unsaturated soil mechanics take into account high soil shear strength due to matric suction resulting in more economical design especially in long roads. In this study, the bearing capacity of two-layer unsaturated sand was investigated using both analytical and experimental methods. At first, using the limit equilibrium method an analytical formula was proposed to determine the bearing capacity of two-layer unsaturated sand in which linear suction profile was considered in soil layers. It should be considered that the constant matric suction distribution assumed by the previous researchers doesn’t show the real profile of matric suction within the soil, sometimes resulting in miscalculated unsaturated bearing capacity. Also, the bearing capacity of two-layer unsaturated poorly graded sand was investigated experimentally in different suctions by a special unsaturated chamber apparatus (UCA) designed for this purpose. The results show more than double increase of unsaturated soil bearing capacity with Sr=25% compared to saturated soil. The formation of failure wedges in all experiments was investigated by image processing. An acceptable agreement was obtained between the theoretical and experimental bearing capacity results.

A Hybrid Continuation Framework for Analyzing Nonlinear Normal Modes of Systems With Contact Nonlinearity

Abstract The prediction of the modal properties of structural systems with contact clearances and prestress presents a computational challenge, as the nonlinearity induced by piecewise-linear stiffness eliminates the use of efficient linear modal analysis techniques. The most common approach to obtaining the nonlinear normal modes (NNMs) of these structural systems is a numerical framework that integrates numerical integration, the shooting method, and the pseudo-arc-length continuation scheme. This numerical continuation framework (NCF) computes NNMs through iterative numerical calculations; thus, the computational cost of the nonlinear modal analysis of complex nonlinear systems, particularly piecewise-linear systems, becomes prohibitively expensive as the model size increases. In this study, a hybrid continuation framework (HCF) combining analytic and numerical methods is proposed to enable efficient computations of NNMs for systems with contact boundaries. This new hybrid framework utilizes a semi-analytic method to conduct the iterative shooting procedure; thus, the computational burden of the numerical continuation can be significantly reduced. The proposed method is demonstrated on spring-mass oscillators with contact elements, and the NNMs obtained using the proposed method are validated by those computed using the traditional numerical continuation framework. The modal properties of the systems can be computed using the proposed framework with significant speed-up. Furthermore, the modal properties, including internal resonance and sharp turning in NNM curves, of the piecewise-linear systems are identified and discussed.

Introduction of Local Resonators to a Nonlinear Metamaterial With Topological Features

Abstract Recent work in nonlinear topological metamaterials has revealed many useful properties such as amplitude dependent localized vibration modes and nonreciprocal wave propagation. However, thus far, there have not been any studies to include the use of local resonators in these systems. This work seeks to fill that gap through investigating a nonlinear quasi-periodic metamaterial with periodic local resonator attachments. We model a one-dimensional metamaterial lattice as a spring-mass chain with coupled local resonators. Quasi-periodic modulation in the nonlinear connecting springs is utilized to achieve topological features. For comparison, a similar system without local resonators is also modeled. Both analytical and numerical methods are used to study this system. The dispersion relation of the infinite chain of the proposed system is determined analytically through the perturbation method of multiple scales. This analytical solution is compared to the finite chain response, estimated using the method of harmonic balance and solved numerically. The resulting band structures and mode shapes are used to study the effects of quasi-periodic parameters and excitation amplitude on the system behavior both with and without the presence of local resonators. Specifically, the impact of local resonators on topological features such as edge modes is established, demonstrating the appearance of a trivial bandgap and multiple localized edge states for both main cells and local resonators. These results highlight the interplay between local resonance and nonlinearity in a topological metamaterial demonstrating for the first time the presence of an amplitude invariant bandgap alongside amplitude dependent topological bandgaps.

Chromatographic methods and approaches for bioequivalence study, drug screening and enantioseparation of indapamide

AbstractIndapamide (Indp) and certain other diuretics have been abused in sports, therefore, having sensitive methods for its detection and assay in biological fluids (whole blood, plasma, serum, and urine) is of significant importance. The racemic mixture of Indp is being used as an active pharmaceutical ingredient among other commonly prescribed diuretics. The regulatory authorities and pharmaceutical industries demand analytical methods for successful enantioseparation of such molecules. The paper presents a critical overview of the scientific issues of the application of contemporary techniques involving various chromatographic approaches (with liquid or supercritical fluid as mobile phases) and capillary electrophoresis and method development, for drug screening, assay, bioequivalence studies and enantioseparation of indapamide with their results. It also covers the historical developments that led to significant breakthroughs in research and concise evaluations of research in the area.Different types of chromatographic methods (HPLC, CEC, SFC etc) discussed herein provide an insight and a choice to select a method to (i) screen Indp for drug abuse, (ii) separate, isolate and quantify the enantiomers of Indp and (iii) investigate their pharmacokinetics as markedly different species and not as a total drug. The article evaluates the field's status with a broad base and practical oriented approach so that the underlying principles are easily understood to help chemists and non-specialists gain useful insights into the field outside their specialization and provide experts with summaries of key developments. To the best of authors' knowledge there has been no attempt to review such methods for analysis of Indp and this is the first report of its kind.

Development and Validation of the Jawline Subject Satisfaction Scale

Introduction: Research in aesthetic medicine commonly includes evaluations of subject satisfaction with treatment results. However, conventional analytic methods typically generate statistically imprecise ordinal scores. To overcome this limitation, researchers have begun employing the Rasch model, an analytical framework grounded in item response theory. The Rasch model permits scale modifications capable of enhancing measurement accuracy. This study focuses on using the Rasch model to evaluate a scale measuring subject satisfaction following aesthetic treatments to the jawline. Objective: To develop and validate a multiitem, self-administered questionnaire measuring patient satisfaction with aesthetic treatment of the jawline. Methods: A 10-item questionnaire [The Jawline Subject Satisfaction Scale (JS3)] was devised to measure subject satisfaction following aesthetic treatments of the jawline. Each question was responded to using a 5-point Likert scale, with response selections ranging from “very much satisfied” to “very much dissatisfied” or “strongly agree” to “strongly disagree.” The scale's psychometric properties (reliability and separation for items and persons, item and person fit statistics, and unidimensionality and local independence) were validated using a Rasch model based on a dataset collected from a sample of forty subjects. Results: The results of the Rasch analysis revealed high internal consistency of the JS3, with a person reliability estimate of 0.86 and an item reliability estimate of 0.96. The separation estimates for persons and items were 2.50 and 4.72, respectively, demonstrating the scale's ability to differentiate between high and low responders and validating the instrument's construct. All infit and outfit values fell within the established range (0.5-1.5), and the data fit the model of unidimensionality and local independence. Raw score transformations into logits were conducted, which were then converted to Rasch measurements. These measurements are available for use in practice for conducting standard statistical analyses evaluating treatment and/or group effects. Conclusions: The application of the Rasch model produced a valid and reliable scale (ie, JS3) for measuring satisfaction with the appearance of the jawline following aesthetic treatments.

Gut microbiota, inflammatory proteins and COVID-19: a Mendelian randomisation study

BackgroundThe human gut microbiota has been identified as a potentially important factor influencing the development of COVID-19. It is believed that the disease primarily affects the organism through inflammatory pathways. With the aim of improving early diagnosis and targeted therapy, it is crucial to identify the specific gut microbiota associated with COVID-19 and to gain a deeper understanding of the underlying processes. The present study sought to investigate the potential causal relationship between the gut microbiota and COVID-19, and to determine the extent to which inflammatory proteins act as mediators in this relationship.MethodsBidirectional mendelian randomization (MR) and Two-step mediated MR analyses were applied to examine causative associations among 196 gut microbiota, 91 inflammatory proteins and COVID-19. The main analytical method used in the MR was the random effects inverse variance weighted (IVW) method. This was complemented by the Bayesian weighted Mendelian randomization (BWMR) method, which was utilized to test the hypothesis of MR. In order for the results to be deemed reliable, statistical significance was required for both methods. Validation was then carried out using an external dataset, and further meta-analyses were conducted to authenticate that the association was reliable.ResultsResults of our research indicated that seven gut microbiota were actively associated to the COVID-19 risk. Five inflammatory proteins were associated with COVID-19 risk, of which three were positively and two were negatively identified with COVID-19. Further validation was carried out using sensitivity analyses. Mediated MR results revealed that CCL2 was a possible mediator of causality of family Bifidobacteriaceae and order Bifidobacteriales with COVID-19, mediating at a ratio of 12.73%.ConclusionSuggesting a genetic causation between specific gut microbiota and COVID-19, our present research emphasizes the underlying mediating role of CCL2, an inflammatory factor, and contributes to a deeper understanding of the mechanism of action underlying COVID-19.