Stable Results Research Articles

On Survey Questionnaire Testing

The purpose of survey questionnaire testing is to ensure that the questionnaire is effective, reliable, and valid research instrument. It should accurately reflect the intended construct and provide stable and consistent results. In recent years, there has been a growing emphasis on the importance of survey questionnaire testing; however, relatively little methodological research and guidance about testing methods is provided. Our goal is to present the methods available for questionnaire testing in brief and give some advice on how to use them.Conclusion – Testing a survey questionnaire before its deployment is crucial in ensuring the data's accuracy and consistency. There are various testing methods available that address the content and technical quality of the research instrument.

Integrating deep learning and discrete cosine transform for surface waves full waveform inversion

Summary Accurate estimations of near-surface S-wave velocity (Vs) models hold particular significance in geological and engineering investigations. On the one hand, the popular Multichannel Analysis of Surface Waves (MASW) is limited to the 1D and the plane wave assumptions. On the other hand, the more advanced and computationally expensive full-waveform inversion (FWI) approach is often solved within a deterministic framework that hampers an accurate uncertainty assessment and makes the final predictions heavily reliant on the starting model. Here we combine deep learning with Discrete Cosine Transforms (DCT) to solve the FWI of surface waves and to efficiently estimate the inversion uncertainties. Our neural network approach effectively learns the inverse non-linear mapping between DCT-compressed seismograms and DCT-compressed S-velocity models. The incorporation of DCT into the deep learning framework provides several advantages: it notably reduces parameter space dimensionality and alleviates the ill-conditioning of the problem. Additionally, it decreases the complexity of the network architecture and the computational cost for the training phase compared to training in the full domain. A Monte Carlo simulation is also used to propagate the uncertainties from the data to the model space. We first test the implemented inversion method on synthetic data to showcase the generalization capabilities of the trained network and to explore the implications of incorrect noise assumptions in the recorded seismograms and inaccurate wavelet estimations. Further, we demonstrate the applicability of the implemented method to field data. In this case, available borehole information is used to validate our predictions. In both the synthetic and field applications, the predictions provided by the proposed method are compared with those of a deterministic FWI and the outcomes of a network trained in the full data and model spaces. Our experiments confirm that the implemented deep-learning inversion efficiently and successfully solves the FWI problem and yields more accurate and stable results than a network trained without the DCT compression. This opens the possibility to efficiently train a neural network that provides accurate instantaneous predictions of Vs near-surface models and related uncertainties.

Optimizing cell migration assays: Critical roles of fluorescent labeling and chemoattractant gradients.

Cell migration assays, also known as chemotaxis assays, are widely used to measure the migratory capacities of cancer cells, leukocytes, macrophages, and other motile cell types. In these assays, fluorescently labeled cells are seeded onto cell culture inserts with microporous membranes that block light transmission from 490 to 700nm. The migrated cells are then observed and quantified from the bottom of the microporous membrane using a fluorescence microscope. In this study, we conducted cell migration assays using macrophages as the motile cells. We discovered that the commonly employed fluorescent labeling method using calcein acetoxymethyl ester (calcein AM) can lead to the time-dependent attenuation of fluorescent signals in certain cell types during migration assays, potentially compromising assay stability. This study overcame this limitation by utilizing PKH26, which fluorescently labels cell surfaces through a mechanism distinct from that of calcein AM. With this modification, we observed a consistent increase in the number of migrating macrophages over time. We also demonstrated that the gradient of chemoattractants is key to the success of cell migration assays. Our improved protocol provided reliable and stable results for cell migration assays.

Topographical and functional analysis of different surgical strategies for advanced pellucid marginal degeneration: A long term follow-up.

To compare clinical and topographical outcomes of three different surgical strategies for advanced pellucid marginal degeneration (PMD). Retrospective, interventional case series of 8 advanced PMDs undergoing three different surgical interventions: Sliding Keratoplasty (SK), Sliding Keratoplasty with Relaxing Incision (SKRI), Sector Lamellar Keratoplasty (SLK). Pre-operatively and at 1, 3, 6, 12-month and final follow-up (50.8 ± 20.6 months) post-operatively, we collected: uncorrected and corrected distance visual acuity (UDVA and CDVA), spherical equivalent (SE), refractive astigmatism (RA), corneal Ks, topographical astigmatism (TA) and calculated against-the-rule (ATR) component. CDVA significantly improved from 6 months after surgery (p = 0.04), while final CDVA was at least 20/40 in 75% of eyes. As desired, surgery led to an overcorrection toward with-the-rule astigmatism at 1-month, which then decreased at 12-month and at final follow-up (p < 0.05). The ATR-component was significantly decreased at 1-month (1.9 ± 1.1 vs. 17.6 ± 6.3 D pre-operatively, p = 0.0015) and remained quite stable over time (4.2 ± 4.2 D at final follow-up). In subgroup analysis, SK and SKRI offered better CDVA and lower RA, while SLK showed more TA stability. The ATR component, comparing baseline and final follow-ups, decreased from 16.8 ± 8.3 D to 5.9 ± 3.6 after SK; from 18.9 ± 3.6 D to 3.3 ± 3.3 D after SKRI; from 17.0 ± 10.3 D to 1.9 ± 1.5 D after SLK. The surgical treatment of advanced PMD showed long-term favourable outcomes. SK and SKRI offered better visual outcomes, but were more inclined to astigmatism regression over time. Conversely, SLK had more stable results but offered worse refractive outcomes.

Application of Machine Learning to Predict the Capacity of Fractured Horizontal Wells in Shale Reservoirs

Shale oil wells typically have numerous volume fracturing segments in their horizontal sections, resulting in significant variability in productivity across these segments. Conventional productivity prediction and fracturing effect evaluation methods are challenging to apply effectively. Establishing a stable and efficient intelligent productivity prediction method using machine learning is a promising approach for the effective development of shale oil reservoirs. This study is based on geological data, fracturing records, and a production database of 91 production wells in a shale oil reservoir in a specific area. Fourteen key parameters affecting productivity were selected from geological and engineering perspectives, and the recursive feature elimination method based on support vector machines identified five optimal main controlling factors. Three machine learning methods—decision tree, random forest, and gradient boosting decision tree (GBDT)—were used to model productivity prediction, with root mean square error (RMSE) employed to evaluate model performance. The study results indicate that formation coefficient, cluster spacing, treatment volume, sand volume, and fracturing segment length are the main controlling factors influencing productivity in fractured horizontal wells. Among the models, the random forest algorithm with bootstrap sampling produced the most stable prediction results, achieving a prediction accuracy of 94% and an RMSE of 0.934 on the test set, outperforming the decision tree and GBDT models in terms of minimum RMSE on the test set.

A CLINICAL CASE OF SUCCESSFUL SURGICAL TREATMENT OF A LATE-PRESENTING PATIENT WITH TRAUMATIC FLAP DISLOCATION AFTER FEMTOLASIK

FemtoLASIK is a frequently performed refractive surgery, one of the complications of which is flap dislocation. Most often, this condition is accompanied by decreased vision, pain, lacrimation, which makes patients immediately visit ophthalmologist. This article describes a case of a patient who came to the clinic only on the fourth day after the flap displacement due to blunt eye trauma. By this time, the patient’s corneal flap had significant edema, was folded and displaced with exposure of the stromal bed, which was epithelialized over 2/3 of the area. The surgical treatment of this patient with restoration of anatomical structures, as well as visual functions exceeding the maximum-corrected at the preoperative stage is presented. The treatment provided a stable result for 15 months after the performed reposition.

MCRANet: MTSL-based connectivity region attention network for PD-L1 status segmentation in H&E stained images

The quantitative analysis of Programmed death-ligand 1 (PD-L1) via Immunohistochemical (IHC) plays a crucial role in guiding immunotherapy. However, IHC faces challenges, including high costs, time consumption and result variability. Conversely, Hematoxylin-Eosin (H&E) staining offers cost-effectiveness, speed, and stable results. Nonetheless, H&E staining, which solely visualizes cellular morphological features, lacks clinical applicability in detecting biomarker expressions like PD-L1. Substituting H&E staining for IHC in determining PD-L1 status is a clinically significant and challenging task. Motivated by above observations, we propose a Multi-Task supervised learning (MTSL)-based connectivity region attention network (MCRANet) for PD-L1 status segmentation in H&E stained images. To reduce interference from non-tumor areas, the MTSL-based region attention is proposed to enhances the network's capability to distinguish between tumor and non-tumor regions. Consequently, this augmentation further improves the network's segmentation efficacy for PD-L1 positive and negative regions. Furthermore, the PD-L1 expression regions demonstrate interconnection throughout the tissue section. Leveraging this topological prior knowledge, we integrate a connectivity modeling module (CM module) within the MTSL-based region attention module (MRA module) to enhance the precision of MTSL-based region attention localization. This integration further improves the structural similarity between the segmentation results and the ground truth. Extensive visual and quantitative results demonstrate that our supervised-learning-guided MRA module produces more interpretable attention and the introduced CM module provides accurate positional attention to the MRA module. Compared to other state-of-the-art networks, MCRANet exhibits superior segmentation performance with a dice similarity coefficient (DSC) of 79.6 % on the lung squamous cell carcinoma (LUSC) PD-L1 status dataset.

Innovative hip-knee health evaluation: Leveraging pose estimation for single-leg stance postural stability assessment

The analysis of the Hip and Knee (HK) joint angles during single-leg stance (SLS) activity contributes to a great understanding of the bio-mechanical mechanisms and balance maintenance across different age groups. Comprehending how these joints operate in the dynamic state is critical for identifying age-related changes in joint control and stability which can contribute to reducing the risk of falls and improving mobility among people. The possibility of revealing the health of HK joints without resorting to an MRI scan is the significance of this work. By obtaining the data on joint angles during the SLS test, we succeeded in identifying those with a higher risk of HK issues and thus the possibility of early intervention and treatment. Our proposed work is going to use a pose estimation technique that will track the trajectories of HK angles followed by association with instabilities or compromised balance in this way, we can detect the affected joint and evaluate the severity of the issue. The study found stable mean and standard deviation values for HK joints in a young participant, both hips (107.14 ± 5, 96.42 ± 7) and both knees (36.76 ± 7, 44.30 ± 4), these values align with the expected norm (110–120° for the hip and 45–65° for the knee) which indicates stable results. while elderly participants showed high variability and low mean values for both hips (65.42 ± 77, 85 ± 76.67) and both knees (4.15 ± 10.8, 7 ± 18) indicating concerns about joint health and stability. The evaluation of HK joint angles through SLS activity offers new insights.

MRNA therapy effective treatment of rare hereditary diseases

mRNA therapy, or mRNA-based drugs that have emerged thanks to vaccines against SARS-CoV-2, have successfully passed preclinical tests and are currently at various stages of clinical trials in the treatment of many diseases, including rare metabolic disorders. In the case of rare genetic metabolic diseases, the concept of mRNA therapy can be considered as an alternative to protein replacement therapy, where exogenous mRNA leads to the production of a fully active protein instead of a non-functional one, and also delivers it to the desired cellular compartment, such as mitochondria or the cell membrane. Preclinical studies on animal models of some rare genetic diseases have fully confrmed the validity of this concept. In this mini-review, we examine and discuss the mentioned preclinical studies on efficacy and safety in several animal models. For all the diseases considered, mRNA therapy restored functional protein to therapeutically significant levels in target organs, led to stable and reproducible results after each dose of mRNA, and was well tolerated, as confirmed by functional liver tests evaluated in animal models, including non-human primates. These data convincingly confirm the potential of clinical development of mRNA therapy for the treatment of various rare metabolic disorders.

Grey Relation System Applications in Multi-Attribute Decision-Making and Forecasting in Financial Management

Objective: The objective of the paper is to verify the Grey relation analysis methods and compare them with known models in financial management. The first part is devoted to MADM (multi-attribute decision methods) and the second one to grey forecasting methods. Method: Localization GRA and globalization GRA multi-criteria models are described and compared with the TOPSIS method. The forecasting GRA(1,1) model based on cumulative data is described, derived and compared with the linear growth model. The models are verified on the data set. Results and Discussion: The globalisation model based on a pair-wise comparison of alternatives is different, and the ranking of alternatives is fully different in comparison with the TOPSIS model. It was found that the localisation GRA model and TOPSIS, both constructed on similarity measures, present similar and comparable results. So, the grey relation approach considers the uncertainty of input data. The forecasting model GRA(1,1) is computed and compared with the growth model. Results show that the growth model is the trendy model, and the non-trendy series is overestimated or underestimated, so the GRA model looks more robust. Research Implications: The problem of imprecise data is investigated. And it is a realistic condition for practical decision-making. The problem of lack of data is often a phenomenon in decision-making. Traditional statistical methods cannot be applied. Therefore, grey relation methodology is one approach to overcoming the problem of imprecise data and lack of data. Uncertainty and lack of data problems are topics important for research and the managerial community. Originality/Value: Sometimes, in financial decision-making, high-quality data or long-term time series is not at our disposal, and on the other hand, decisions have to be made. This problem is often neglected and solved by not-relevant traditional statistical models. Therefore, methods that allow the solving of such problems are useful. It was shown that a grey relation methodology for multicriteria financial performance evaluation and forecasting shows more robust and stable results and could be more relevant for imprecise data or short time series data in financial decision-making problems.

Experimentation of Grate Combustion of Municipal Solid Waste in Ouagadougou: Influence of Primary and Secondary Air Flow on Thermal Potential

The present work concerns the study of the influence of combustion air flows on the thermal potential during the combustion of a 2 kg mixture of solid model waste from the city of Ouagadougou. This mixture consists primarily of wood, cardboard and plastic. The prototype model is a natural laterite internal-walled grate furnace. During these investigations, we were interested in the temperature variation measured by 4 thermocouples K1 to K4 placed respectively from the waste bed to the top of the furnace. These variations are considered according to a variable primary and secondary air flow. The maximum primary and secondary airflow is 3000 L/min. Measurements are taken throughout the experiment at a step of 18 seconds and a maximum duration of 3 minutes for each case of flow considered. Maximum temperatures reaching 450oC are observed following the injection of secondary air only. This is explained by the supply of oxygen making the combustion more complete. The results show that the injection of primary and secondary air at a flow rate of 1500 L/min gives a more stable temperature result, i.e. 362,18oC 186,82oC 109,27oC 72,41oC respectively for the thermocouples K1, K2, K3, K4. An increase in the primary and secondary air flow to a maximum of 3000 L/min leads to a drop in temperatures due to the dilute internal atmosphere. These results allow to set the optimal operating parameters of the furnace in order to produce more heat for its recovery into electricity through a heat exchanger and a steam turbine.

Stability analysis, modulation instability, and the analytical wave solitons to the fractional Boussinesq-Burgers system

Abstract The research is concerned with the novel analytical solitons to the (1+1)-D nonlinear Boussinesq-Burgers System (B-B S) in the sense of a new definition of fractional derivatives. The concerned system is helpful to describes the waves in different phenomenon,&amp;#xD;including proliferation of waves in shallow water, oceanic waves and many others. Authors gain the solutions involving trigonometric, hyperbolic, and rational functions by using the expa function and the extended sinh-Gordon equation expansion (EShGEE) methods. Fractional derivative provides the better results than the present results. These results are helpful and useful in the different areas of applied sciences. The solutions are shown by 2-dimensional, 3-dimensional, and contour graphs. The solutions are useful in further studies of the governing model. The stability process is performed to verify that the solutions are exact and accurate. The modulation instability is used to determine the steady-state stable results to the governing equation. The techniques utilized are both simple and effective.

Intrusion Of Maxillary Anterior Teeth: A Comparative Clinical Study Between Mini-Implants And Utility Arch

Background: Deep bite is a common orthodontic malocclusion caused by factors like incisor supra-occlusion, molar infra-occlusion, or incisor angulation. Nonsurgical correction of deep bite involves extrusion of posterior teeth, intrusion of incisors, or both. Extrusion of posterior teeth in growing patients provides stable results due to secondary remodelling. In patients with deep bite and excessive gingival display, intrusion of incisors is typically required which can be accomplished using intrusion arches or mini-implants. Materials and Methods: A total of 10 subjects with an anterior deep bite (overbite &gt;4mm) with excessive incisal display at rest and at smile were taken. Participants were evenly allocated into two groups based on their gingival display. Group I included five participants with less than 4 mm of gingival display, who received treatment using Rickett’s intrusion utility arch. Group II consisted of five subjects with more than 4 mm of gingival display, who were treated with two anterior mini-implants. Lateral cephalograms were utilized to evaluate maxillary anterior intrusion at two specific time points: Pre-treatment (T1) and following a 6-month interval (T2). Results: The amount of bite opening in both groups was comparable, however the amount of incisor intrusion was greater with mini-implants than with the utility arch. The utility arch group showed significantly greater labial tipping (P&lt;0.01) and increased overjet (P&lt;0.05) compared to the mini-implant group. The distance between the maxillary first molar (U6) and palatal plane (PP) significantly increased with the utility arch but decreased with mini-implants. The mandibular plane angle (GoGn-Sn) increased with the utility arch and decreased with mini-implants; however, the difference was statistically non-significant. Conclusion: Deep bite correction with intrusion utility arch occurs through incisor intrusion, incisor flaring, and molar extrusion, whereas with mini-implants, bite opening mainly occurs through incisor intrusion, making it an efficient alternative in cases where dental side effects such as incisor flaring and molar extrusion are undesirable.

Fracturing Process Visualization of Cracked Chevron-Notched Brazilian Discal and Notch Semicircular Bend Rock Specimens and Comparative Analysis by Combined AE and DIC

Abstract A series of homogeneous granite specimens were prepared to investigate the Mode I fracture toughness (KIC) using the cracked chevron-notched Brazilian disk (CCNBD) method and semicircular three-point bending (NSCB) method recommended by the International Society for Rock Mechanics (ISRM). A combination of acoustic emission (AE) and digital image correlation (DIC) was utilized to monitor the crack propagation and analyze the fracture modes at various test stages. The results indicated that the average value of Mode I fracture toughness (KIC-) of the CCNBD specimen was approximately 10% higher than that of the NSCB specimen. The coefficient of variation in the NSCB test was small, which could provide more stable result of Mode I fracture roughness. Compared to the CCNBD test, the failure mode of NSCB specimens was mainly tensile damage with instantaneous damage during the experimental process. Furthermore, the failure process of the NSCB test was mainly controlled by tensile fractures, which exhibited instantaneous failure. The CCNBD test was first controlled by tensile fractures and then by shear fractures when the peak was reached, exhibiting progressive failure. The failure mode and the process may be the main factors controlling the difference between the results of the NSCB and CCNBD tests. This work helps select appropriate methods to measure the Mode I rock fracture toughness.

Formulation of Cushion Preparations from Duck Egg Shells and SPF Value Testing Using the UV-Vis Spectrophotometry Method

The effectiveness of a sunscreen can be indicated by the value of Sun Protection Factor (SPF), which is defined as the amount of UV energy needed. Cream is a semi-solid dosage from containing one or more medicinal ingredients dissolved or dispersed in a suitable base material. One of the compounds contained in eggshells is CaCO3. Calcium carbonate is necessary for cell regeneration and as a barrier to ultaviolet (UV) rays. This study aims to determine the potential SPF in duck eggshell, the SPF value contained in the cushion and the physical properties of the cushion preparation. Here, three variations of duck egg shell flour concentrations (4%, 8% and 16%) were made, tested in vitro using UV-Vis spectrophotometry from a wavelength of 290-320 nm every 5 nm and the absorbance was measured and the properties were tested. and physical stability (organoleptic, pH, spreadability, stickiness, viscosity, centrifugation, and Freeze-Thaw Cycling for 6 days (3 cycles) at temperatures of 40°C and 4°C). Our research results show that the duck egg shell formulation cannot be used as an SPF product. Formula 1 has an SPF value of 2.6, formula 2 has an SPF value of 3.3 and formula 3 has an SPF value of 3. The test results for the properties and stability of formula 2 with a concentration of 8% duck egg shell flour show the most stable results compared to the other 2 formulas

Analytic amplitudes for a pair of Higgs bosons in association with three partons

The pair production of Higgs bosons at the LHC can give information about the triple Higgs boson coupling. We perform an analytic one-loop calculation of the amplitudes for a pair of Higgs bosons in association with three partons, retaining the exact dependence on the quark mass circulating in the loop. These amplitudes constitute the real radiation corrections in the calculation of Higgs boson pair production at next-to-leading order in the strong coupling. The results of an analytic generalised-unitarity computation are simplified via analytic reconstruction in spinor variables. Compact ansätze for kinematic pole residues are iteratively fitted via p-adic evaluations near said poles and subtracted until no pole remains. A new ansatz construction is introduced to minimally parametrise coefficients of amplitudes with multiple massive external legs. The simplified expressions are faster to evaluate than automatic codes and can lead to more stable results near singular regions.

The value of serum Mac-2 binding protein glycosylation isomer in the diagnosis of liver fibrosis: a systematic review and meta-analysis

BackgroundThe early detection and intervention of liver fibrosis (LF) in patients with chronic liver disease is critical to their management. The accuracy of serum Mac-2 binding protein glycosylation isomer (M2BPGi) in the diagnosis of LF remains controversial. This study aimed to comprehensively assess the value of serum M2BPGi in diagnosing LF.MethodsThe PubMed, Embase, MEDLINE, Web of Science, and Cochrane Library databases were searched. The effect values were combined using a random-effects model. Meta-regression and subgroup analysis were used to explore the sources of heterogeneity. In addition, publication bias assessment and sensitivity analysis were conducted.ResultsThis study includes 12 studies with 2,416 patients. The pooled sensitivity, specificity, and AUROC of M2BPGi in the diagnosis of significant fibrosis (≥F2) were 0.65 (95% CI: 0.57–0.71), 0.79 (95% CI: 0.72–0.84), and 0.78 (95% CI: 0.74–0.81), respectively, while those for predicting extensive fibrosis (≥F3) were 0.76 (95% CI: 0.71–0.80), 0.75 (95% CI: 0.68–0.81), and 0.81 (95% CI: 0.77–0.84). Sensitivity analysis indicated stable results in this study. The disease type, cut-off values, study country, average age, and male proportion were the sources of heterogeneity in diagnosing significant fibrosis of M2BPGi (p &amp;lt; 0.05). Sample size, disease type, study country, publication year, cut-off values, average age, and male proportion were important sources of heterogeneity in diagnosing extensive fibrosis (p &amp;lt; 0.05).ConclusionSerum M2BPGi has good diagnostic performance for significant fibrosis and extensive fibrosis in patients with chronic hepatitis B (CHB), chronic hepatitis C (CHC), or nonalcoholic fatty liver disease (NAFLD) and is an effective, non-invasive, and convenient marker.Systematic Review Registrationhttps://inplasy.com/inplasy-2023-10-0086/.

Hybrid-driven MRF seismic inversion for gas sand identification: A case study in the Yinggehai Basin

The Yinggehai Basin displays anomalies characterized by heightened levels of temperature and pressure. It represents a depositional model of a submarine fan with gravity-driven flow, demonstrating significant lateral reservoir heterogeneity and intricate spatial distribution of the gas reservoir. Identifying gas formations using elastic parameters as indicators relies on stable seismic inversion results. This requires regularization to alleviate ill-posedness in the inverse problem and to construct model features of the subsurface medium. Markov Random Field (MRF)is an effective soft-constrained regularization method. It enhances the marginal features of inversion results by penalizing the objective function with the gradient of neighborhood points. However, the standard MRF method relies only on the parameter model-driven and has poor applicability in areas with strong lateral inhomogeneity or complex depositional processes. In this research paper, we propose a novel approach to seismic inversion that integrates MRF neighborhood drive and incorporates both seismic data and a parametric model. Multi-order MRF neighborhoods are constructed by using seismic data in the horizontal direction (including horizontal diagonal) and parametric model data in the vertical direction (including vertical diagonal). The model-driven results are also utilized to couple seismic data and improve the stability of the hybrid-driven MRF inversion. In addition, we select the P-impedance as the parameter for inversion due to its heightened sensitivity towards gas formation within the study region. Consequently, we utilize the inversion results to delineate the presence of sandstone in the target layer and discern any indications of gas formation. The implementation of this method in the field has demonstrated its capability to enhance the stability of inversion outcomes, effectively integrating the lateral consistency of seismic data with the vertical precision of parametric model data. This approach significantly improves reservoir heterogeneity characterization and enhances accuracy in identifying sandstone and gas.

The effects of RT-qPCR standards on reproducibility and comparability in monitoring SARS-CoV-2 levels in wastewater

Reverse transcription-quantitative PCR (RT-qPCR) is widely used for monitoring viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in wastewater. Various materials, including plasmid DNA, synthetic nucleic acids, PCR amplicons, genomic DNA, and cDNA, are currently used for SARS-CoV-2 quantification by generating standard curves. We assessed three common standards on quantifying SARS-CoV-2 RNA across nine wastewater treatment plants in Finland, as part of the national wastewater surveillance effort. We pairwise compared RT-qPCR results from 148 wastewater samples, using both IDT (#10006625, IDT, USA) and CODEX standards (#SC2-RNAC-1100, CODEX DNA), and 179 samples using both IDT and EURM019 standards (#EURM-019, European Commission, Joint Research Centre) in our assessment. Amongst the tested standards, the CODEX standard consistently yielded more stable results than either the IDT or EURM019 standards. We found that SARS-CoV-2 levels were higher with the IDT standard (4.36 Log10 GC/100 mL) compared to the CODEX standard (4.05 Log10 GC/100 mL). Similarly, quantification using the IDT standard was higher (5.27 Log10 GC/100 mL) than values obtained with the EURM019 (4.81 Log10 GC/100 mL). SARS-CoV-2 RNA quantified with IDT and CODEX standards exhibited stronger concordance (Spearman’s correlation rho median of 0.79) compared to those quantified with IDT and EURM019 standards (rho median of 0.59). This study highlights the significant impact of standard material selection on SARS-CoV-2 RNA quantification, emphasizing the need for harmonization in standard material.

Stability of unilateral posterior crossbite treatment with the Function Generating Bite appliance : Association with reduction of mandibular clockwise rotation and increased maxillary transversal width measurements.

This observational study aimed to evaluate the stability of unilateral posterior crossbite (UPXB) correction with the functional appliance function generating bite (FGB appliance) during follow-up and its effects on craniofacial growth. Atotal of 102 age- and gender-matched patients were included: 51with UPXB (male [M] = 19; female [F] = 32; mean age ± standard deviation [SD] = 7.6 ± 1.4[years.months]) and 51controls (C; M = 19; F = 32; mean age ± SD = 7.9 ± 1.3). UPXB was corrected with the FGB appliance. Study casts were collected before treatment (T0), after correction (T1), after afollow-up of 3.7 ± 1.6[years.months] (T2) and different transversal measurements were performed with calipers: intermolar (IMD), intermolar gingival (IMGD), intercanine (ICD), and intercanine gingival distances (ICGD). In treated patients, in addition, lateral cephalometric tracings were analyzed at T0 and T2. At T0, all maxillary measurements were significantly smaller in the UPXB group compared to the controls (p < 0.001). Between T0 and T1, all maxillary variables increased significantly in the UPXB group (p < 0.001; IMD +4.3 ± 2.1 mm; ICD +3.1 ± 2 mm). Between T1 and T2, maxillary IMD increased further (p < 0.05; +2.2 ± 2 mm). The mean T0-T2 increases were 6.6 ± 2.6 mm (IMD) and 4.3 ± 2.6 mm (ICD). At T0, the cephalometric analysis showed significantly stronger mandibular clockwise rotation (p < 0.01) in the UPXB group compared to the control group. Between T0 and T2, the UPXB group showed asignificant reduction of mandibular (p < 0.001; SpP-CoOr T0 = -3.47°± 4.38, T2 = -1.14°± 4.01) and occlusal plane (p < 0.01; SpP-Oc T0 = 11.37°± 3.91, T2 = 9.86°± 3.83) clockwise rotation, and of intermaxillary divergence (p < 0.01; SpP-GoGn T0 = 27.8°± 5.39, T2 = 26.65°± 5.49). Treatment of UPXB with the FGB appliance effectively increased maxillary transversal width measurements, especially in the posterior region, even after follow-up, indicating stable results. Concurrently, mandibular clockwise rotation was reduced, indicating control of the vertical dimension.