Search

INTRODUCTION: Well-chosen biomarkers have the potential to increase the efficiency of clinical trials and drug discovery and should show good precision as well as clinical validity. METHODS: We suggest measures that operationalize these criteria and describe a general approach that can be used for inference-based comparisons of biomarker performance. The methods are applied to measures obtained from structural magnetic resonance imaging (MRI) from individuals with mild dementia (n = 70) or mild cognitive impairment (MCI; n = 303) enrolled in the Alzheimers Disease Neuroimaging Initiative. RESULTS: Ventricular volume and hippocampal volume showed the best precision in detecting change over time in both individuals with MCI and with dementia. Differences in clinical validity varied by group. DISCUSSION: The methodology presented provides a standardized framework for comparison of biomarkers across modalities and across different methods used to generate similar measures and will help in the search for the most promising biomarkers. HIGHLIGHTS: A framework for comparison of biomarkers on pre-defined criteria is presented. Criteria for comparison include precision in capturing change and clinical validity. Ventricular volume has high precision in change for both dementia and mild cognitive impairment (MCI) trials. Imaging measures performance in clinical validity varies more for dementia than for MCI.

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

BACKGROUND: An accurate, rapid estimate of glomerular filtration rate (GFR) in kidney transplant patients affords early detection of transplant deterioration and timely intervention. This study compared the performance of serum creatinine (Cr) and cystatin C (CysC)-based GFR equations to measured GFR (mGFR) using iohexol among pediatric kidney transplant recipients. METHODS: CysC, Cr, and mGFR were obtained from 45 kidney transplant patients, 1-18 years old. Cr- and CysC-estimated GFR (eGFR) was compared against mGFR using the Cr-based (Bedside Schwartz, U25-Cr), CysC-based (Gentian CysC, CAPA, U25-CysC), and Cr-CysC combination (CKiD Cr-CysC, U25 Cr-CysC) equations in terms of bias, precision, and accuracy. Bland-Altman plots assessed the agreement between eGFR and mGFR. Secondary analyses evaluated the formulas in patients with biopsy-proven histological changes, and K/DOQI CKD staging. RESULTS: Bias was small with Gentian CysC (0.1 ml/min/1.73 m2); 88.9% and 37.8% of U25-CysC estimations were within 30% and 10% of mGFR, respectively. In subjects with histological changes on biopsy, Gentian CysC had a small bias and U25-CysC were more accurate-both with 83.3% of and 41.7% of estimates within 30% and 10% mGFR, respectively. Precision was better with U25-CysC, CKiD Cr-CysC, and U25 Cr-CysC. Bland-Altman plots showed the Bedside Schwartz, Gentian CysC, CAPA, and U25-CysC tend to overestimate GFR when > 100 ml/min/1.72 m2. CAPA misclassified CKD stage the least (whole cohort 24.4%, histological changes on biopsy 33.3%). CONCLUSIONS: In this small cohort, CysC-based equations with or without Cr may have better bias, precision, and accuracy in predicting GFR.

A variety of scattering-based, microscopy-based, and mobility-based methods are frequently used to probe the size distributions of colloidal nanoparticles with transmission electron microscopy (TEM) often considered to be the "gold standard". Charge detection mass spectrometry (CDMS) is an alternative method for nanoparticle characterization that can rapidly measure the mass and charge of individual nanoparticle ions with high accuracy. Two low polydispersity, ∼100 nm diameter nanoparticle size standards with different compositions (polymethyl methacrylate/polystyrene copolymer and 100% polystyrene) were characterized using both TEM and CDMS to explore the merits and complementary aspects of both methods. Mass and diameter distributions are rapidly obtained from CDMS measurements of thousands of individual ions of known spherical shape, requiring less time than TEM sample preparation and image analysis. TEM image-to-image variations resulted in a ∼1-2 nm range in the determined mean diameters whereas the CDMS mass precision of ∼1% in these experiments leads to a diameter uncertainty of just 0.3 nm. For the 100% polystyrene nanoparticles with known density, the CDMS and TEM particle diameter distributions were in excellent agreement. For the copolymer nanoparticles with unknown density, the diameter from TEM measurements combined with the mass from CDMS measurements enabled an accurate measurement of nanoparticle density. Differing extents of charging for the two nanoparticle standards measured by CDMS show that charging is sensitive to nanoparticle surface properties. A mixture of the two samples was separated based on their different extents of charging despite having overlapping mass distributions centered at 341.5 and 331.0 MDa.

Purpose: To investigate the accuracy of ChatGPT (Chat generative pretrained transformer), a large language model, in calculating sample size for sport-sciences and sports-medicine research studies. Methods: We conducted an analysis on 4 published papers (ie, examples 1–4) encompassing various study designs and approaches for calculating sample size in 3 sport-science and -medicine journals, including 3 randomized controlled trials and 1 survey paper. We provided ChatGPT with all necessary data such as mean, percentage SD, normal deviates (Zα/2 and Z1−β), and study design. Prompting from 1 example has subsequently been reused to gain insights into the reproducibility of the ChatGPT response. Results: ChatGPT correctly calculated the sample size for 1 randomized controlled trial but failed in the remaining 3 examples, including the incorrect identification of the formula in one example of a survey paper. After interaction with ChatGPT, the correct sample size was obtained for the survey paper. Intriguingly, when the prompt from Example 3 was reused, ChatGPT provided a completely different sample size than its initial response. Conclusions: While the use of artificial-intelligence tools holds great promise, it should be noted that it might lead to errors and inconsistencies in sample-size calculations even when the tool is fed with the necessary correct information. As artificial-intelligence technology continues to advance and learn from human feedback, there is hope for improvement in sample-size calculation and other research tasks. However, it is important for scientists to exercise caution in utilizing these tools. Future studies should assess more advanced/powerful versions of this tool (ie, ChatGPT4). [ABSTRACT FROM AUTHOR]

Predictive processing is an influential theoretical framework for understanding human and animal cognition. In the context of predictive processing, learning is often reduced to optimizing the parameters of a generative model with a predefined structure. This is known as Bayesian parameter learning. However, to provide a comprehensive account of learning, one must also explain how the brain learns the structure of its generative model. This second kind of learning is known as structure learning. Structure learning would involve true structural changes in generative models. The purpose of the current paper is to describe the processes involved upstream of these structural changes. To do this, we first highlight the remarkable compatibility between predictive processing and the processing fluency theory. More precisely, we argue that predictive processing is able to account for all the main theoretical constructs associated with the notion of processing fluency (i.e., the fluency heuristic, naïve theory, the discrepancy‐attribution hypothesis, absolute fluency, expected fluency, and relative fluency). We then use this predictive processing account of processing fluency to show how the brain could infer whether it needs a structural change for learning the causal regularities at play in the environment. Finally, we speculate on how this inference might indirectly trigger structural changes when necessary. [ABSTRACT FROM AUTHOR]

CoVID-19 has been linked to long-term consequences on several human body organs, including lung ailments, kidney malfunctions, heart dysrhythmia, alterations in brain nutrient levels, psychological difficulties, abrupt changes in blood pressure, and more. Because of the considerable variety in the impacts on different body parts, researchers find it challenging to create models that can incorporate these effects for treatment recommendations and future disease prevention scenarios. Thus, this article examines some of the most recently proposed models for identifying the impacts of CoVID19 on various human organs. This review examines the underlying theories in terms of clinical nuances, functional advantages, contextual limits, and potential empirical applications. Based on this discussion, researchers will be able to find the best models for detecting particular diseases on specific body parts. It was discovered that hybrid bioinspired models, when paired with deep learning-based classification algorithms, can effectively detect these impacts. This text also parametrically analyses these models in terms of accuracy, precision, and recall, allowing readers to select the best models for their performance-specific use cases. To expand on this discussion, this book evaluates a unique CoVID19 Classification Rank Metric (CCRM) that integrates these factors for thorough model identification. Based on this criteria, researchers will be able to develop appropriate models for clinical scenarios that have high accuracy, low delay, and scalability while costing less. [ABSTRACT FROM AUTHOR]

Background: The fixed effects model is a useful alternative to the mixed effects model for analyzing stepped-wedge cluster randomized trials (SW-CRTs). It controls for all time-invariant cluster-level confounders and has proper control of type I error when the number of clusters is small. While all clusters in a SW-CRT are typically designed to crossover from the control to receive the intervention, some trials can end with unexposed clusters (clusters that never receive the intervention), such as when a trial is terminated early due to safety concerns. It was previously unclear whether unexposed clusters would contribute to the estimation of the intervention effect in a fixed effects analysis. However, recent work has demonstrated that including an unexposed cluster can improve the precision of the intervention effect estimator in a fixed effects analysis of SW-CRTs with continuous outcomes. Still, SW-CRTs are commonly designed with binary outcomes and it is unknown if those previous results extend to SW-CRTs with non-continuous outcomes. Methods: In this article, we mathematically prove that the inclusion of unexposed clusters improves the precision of the fixed effects intervention effect estimator for SW-CRTs with binary and count outcomes. We then explore the benefits of including an unexposed cluster in simulated datasets with binary or count outcomes and a real palliative care data example with binary outcomes. Results: The simulations show that including unexposed clusters leads to tangible improvements in the precision, power, and root mean square error of the intervention effect estimator. The inclusion of the unexposed cluster in the SW-CRT of a novel palliative care intervention with binary outcomes yielded smaller standard errors and narrower 95% Wald Confidence Intervals. Conclusions: In this article, we demonstrate that the inclusion of unexposed clusters in the fixed effects analysis can lead to the improvements in precision, power, and RMSE of the fixed effects intervention effect estimator for SW-CRTs with binary or count outcomes. [ABSTRACT FROM AUTHOR]

Background: Methods for matching in longitudinal cohort studies, such as sequential stratification and time-varying propensity scores, facilitate causal inferences in the context of time-dependent treatments that are not randomized where patient eligibility or treatment status changes over time. The tradeoffs in available approaches have not been compared previously, so we compare two methods using simulations based on a retrospective cohort of patients eligible for weight loss surgery, some of whom received it. Methods: This study compares matching completeness, bias, coverage, and precision among three approaches to longitudinal matching: (1) time-varying propensity scores (tvPS), (2) sequential stratification that matches exactly on all covariates used in tvPS (SS-Full) and (3) sequential stratification that exact matches on a subset of covariates (SS-Selected). These comparisons are made in the context of a deep sampling frame (50:1) and a shallow sampling frame (5:1) of eligible comparators. A simulation study was employed to estimate the relative performance of these approaches. Results: In 1,000 simulations each, tvPS retained more than 99.9% of treated patients in both the deep and shallow sampling frames, while a smaller proportion of treated patients were retained for SS-Full (91.6%) and SS-Selected (98.2%) in the deep sampling frame. In the shallow sampling frame, sequential stratification retained many fewer treated patients (73.9% SS-Full, 92.0% SS-Selected) than tvPS yet coverage, precision and bias were comparable for tvPS, SS-Full and SS-Selected in the deep and shallow sampling frames. Conclusion: Time-varying propensity scores have comparable performance to sequential stratification in terms of coverage, bias, and precision, with superior match completeness. While performance was generally comparable across methods, greater match completeness makes tvPS an attractive option for longitudinal matching studies where external validity is highly valued. [ABSTRACT FROM AUTHOR]

In investigations of domains under post-stratified random sampling, it is difficult to get an acceptable precision for domain-specific estimates due to low sample sizes. Small area estimate, a popular technique that has been widely used over the past few decades, involves indirect estimating using the auxiliary data from the entire population. In this article, we utilize a ranked set sampling (RSS) technique to achieve a greater level of precision in area-specific estimations under the assumption that ranking the smaller sets is simple, inexpensive, and flawless. RSS optimizes sample size for a fixed degree of precision or increases precision for a fixed sample size. We create direct estimators for population total under homogeneous, ratio, and regression models that are area specific. To evaluate the effectiveness and application of the suggested RSS technique, data from the Pakistan Demographic Health Survey (PDHS 2017–18) and Iris flower data are used. The effectiveness of the RSS mechanism is supported by both theoretical characteristics and Bootstrapped tests. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Materials and Methods Results Conclusions Clinical Significance This systematic review aimed to assess the impact of printing orientation on the accuracy and properties of additively manufactured provisional restorations.A systematic literature search databases (PubMed, Scopus, Web of Science, and Cochrane) were conducted in July 2024 without language restrictions. The included studies were evaluated using the modified CONSORT checklist, and the effect measures and synthetic methods were employed to assess the accuracy of resin provisional restorations printed at various orientations.The web search resulted in 8228 records, and 15 records were ultimately included in the analysis. The printing orientation of provisional restorations has an impact on various factors such as the internal and marginal gap, trueness, precision, and accuracy. To achieve optimal results, it is recommended to utilize printing orientations of 180°, 150°, and 210°, as they showed lower marginal and internal gaps and higher accuracy. Caution should be exercised during the virtual positioning of supporting pillars, as this may also influence the overall accuracy.Horizontally and slightly tilted orientations have demonstrated superior accuracy. To achieve optimal results, factors such as printing layer thickness, printing technology, materials, and supportive pillars should be taken into consideration, besides the printing orientations.The selection of the optimum printing parameters overall printing orientations, layer thickness, and supportive pillar position can generate prosthetic and restorative dental parts with a long survival rate, saving time and effort by avoiding fracture, loss of retention, and consequent clinical complications. [ABSTRACT FROM AUTHOR]

Objectives Myeloid neoplasms require comprehensive characterization of genetic abnormalities, including single-nucleotide variants, small insertions and deletions, and fusions and translocations for management. The Oncomine Myeloid Assay GX v2 (Thermo Fisher Scientific) analyzes 17 full genes, 28 hotspot genes, 30 fusion driver genes, and 5 expression genes. Methods The validation set included 192 DNA samples, 28 RNA samples, and 9 cell lines and contrived controls. The DNA and RNA were extracted from both peripheral blood and bone marrow. Library preparation, templating, and sequencing was performed on the fully automated Genexus Integrated Sequencer (Thermo Fisher Scientific). The sequencing data were analyzed by manual curation, default Oncomine filters and the Oncomine Reporter (Thermo Fisher Scientific). Results Of the 600 reference pathogenic DNA variants targeted by the assay, concordance was seen in 98.3% of unfiltered variant call format files. Precision and reproducibility were 100%, and the lower limit of detection was 2% variant allele frequency for DNA. Inability to detect variants in long homopolymer regions intrinsic to the Ion Torrent chemistry led to 7 missed variants; 100% concordance was seen with reference RNA samples. Conclusions This extensive clinical validation of the Oncomine Myeloid Assay GX v2 on the Genexus Integrated Sequencer with its built-in bioinformatics pipeline and Ion Torrent Oncomine Reporter shows robust performance in terms of variant calling accuracy, precision, and reproducibility, with the advantage of a rapid turnaround time of 2 days. The greatest limitation is the inability to detect variants in long homopolymer regions. [ABSTRACT FROM AUTHOR]

Background: Advances in digital technology and intraoral scanners (IOSs) have the potential to enable accurate digital impressions for patients with maxillary defects. This study aimed to compare the accuracy of IOSs in completely and partially edentulous models with maxillary defects. Methods: Three polyurethane models—one completely edentulous (CE) and two partially edentulous, following Aramany classifications I (ACI) and II (ACII)—were created using stereolithography. These models were scanned with a desktop scanner to create reference models. Ten scans were performed using three different intraoral scanners (TRIOS 3, Primescan, and Virtuo Vivo). The IOS datasets were analyzed to assess trueness and precision using a two-way ANOVA and multiple-comparison tests with Bonferroni corrections (α = 0.05). Results: Both the model type and the IOS significantly influenced trueness and precision. The interaction between the model type and the IOS was found to be statistically significant (trueness: p = 0.001; precision: p = 0.005). The highest trueness was observed in the ACII model scanned with TRIOS 3 and Primescan. TRIOS 3 and Primescan also exhibited the highest precision in the ACII model. For Virtuo Vivo, there were no significant differences among the models (p = 0.48). Conclusions: Although intraoral scanners (IOSs) demonstrated significant differences in trueness when used in completely and partially edentulous models with maxillary defects, these differences may be considered clinically insignificant. [ABSTRACT FROM AUTHOR]

Plant biotechnology is a key component of plant breeding which employs biotechnological tools like plant tissue culture for genetic engineering, genome editing, or other techniques. In this study, an efficient regeneration protocol was established followed by optimizing Benzylaminopurine (BAP) concentration for two different explants of cowpea was established. The data generated was analyzed by using traditional statistical tools like ANOVA and multiple factorial regression analysis. Results illustrated the better performance of both explants when pulse treated with 5.0 mg/L BAP followed by inoculation at 0.25 mg/L BAP or 0.0 BAP. Results were further analyzed and optimized by the Pareto chart analysis, surface plots, contour plots, and response optimizer. After that, data was computed with machine learning models [Support Vector Classifier (SVC), Random Forest (RF), and Multilayer Perceptron (MLP)] and compared with Quantum machine learning-based Quantum Support Vector Classifier (QSVC), and Variational Quantum Classifier (VQC) models. Results revealed better performance of the MLP model for most of the performance metrics. On the contrary, QSVC and VQC displayed better accuracy and recall respectively. Results depicted the promising performance of Quantum ML for better data analysis for decision-making in precision agriculture and precision biotechnology.Key message: The study integrates in vitro regeneration data into classical and quantum machine learning models, showing superior accuracy and recall in quantum models, highlighting its potential for decision-making in biotechnology. [ABSTRACT FROM AUTHOR]

Karst landscape, characterised by drought-prone areas, limited water retention and nutrient-poor soils, pose significant challenges for the sustainability of small-scale agricultural systems. This study investigated the impact of smart precision irrigation (SPI) technology, which integrates drip irrigation (DI) and organic fertilisation, on the growth, physiological performance and water use efficiency of chilli plants cultivated in a karst landscape in Gunungkidul District, Yogyakarta, Indonesia. This experiment involved a combination of drip irrigation (D), non-drip irrigation (ND), organic fertiliser (F), and no fertiliser (NF), with a semi-automatically installed SPI system to monitor and adjust soil moisture and watering requirements. The results showed that the combination of drip irrigation and organic fertiliser (D + F) significantly increased plant growth parameters, including plant height, leaf area, and chlorophyll content, and improved physiological traits such as photosynthetic rate, stomatal conductance, and leaf water use efficiency (LWUE). These improvements were attributed to the optimised water distribution and nutrient availability provided by the DI system, which minimised water loss and reduced drought stress, as evidenced by lower proline accumulation and reduced antioxidant enzyme activity in plants. In addition, the D+F treatment resulted in the highest biomass production, fruit yield and water use efficiency, underlining its potential as a sustainable agricultural practice in waterscarce karst environments. The study concludes that adopting organic matter irrigation and fertilisation strategies can improve the productivity and resilience of horticultural crops in areas facing similar environmental constraints. [ABSTRACT FROM AUTHOR]

This study delves into the exploration of broadband measurement techniques for power systems, utilizing wavelet transform as a foundational tool for signal analysis. The research rigorously evaluates the efficacy of several machine learning algorithms, namely Support Vector Machines (SVM), Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), and Random Forest, in interpreting and analyzing broadband signals within power systems. Through a detailed analytical process, the performance of each algorithm is meticulously assessed based on several critical metrics: accuracy, precision, recall, and F1-score. The research investigates broadband measurement methods for power systems using wavelet transform and evaluates the performance of Support Vector Machines (SVM), Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), and Random Forest. Results show SVM achieving an accuracy of 85%, precision of 86%, recall of 82%, and F1-score of 84%. ANN yields 82% accuracy, 84% precision, 78% recall, and 81% F1 score. KNN demonstrates 87% accuracy, 88% precision, 84% recall, and 86% F1 score. DT achieves 79% accuracy, 80% precision, 75% recall, and 77% F1 score. Overall, the study provides insights into machine learning algorithms' effectiveness in broadband power system measurement. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This is a commentary for a special issue on predictive processing and rational constructivist models of development. Mainly I use the opportunity to ask a bunch of questions about what these theoretical frameworks show us (and what they do not) and mostly where the open questions still are. To get meta for a moment, I thought these questions were the best way to maximize the value of my commentary: They have the highest probability of leading to the most uncertainty reduction for our field in the long term. Please read in that spirit. [ABSTRACT FROM AUTHOR]

The world is progressing at a rapid rate, and with continuous advancements in technology, the need for cooperative spectrum sensing has evolved. Cooperative spectrum sensing is an approach used to enhance detection performance, wherein secondary users collaborate with each other to sense the spectrum and identify spectrum holes. As technology improves over time, the spectrum becomes increasingly allocated to primary users. The role of cooperative spectrum sensing in cognitive radio fulfills the essential requirement of protecting primary users from harmful interference. The progressive evolution of technology has led to a reduction in available spectrum, prompting the emergence of the concepts of cognitive radio and cooperative spectrum sensing. To begin with, this paper introduces the fundamental application of cooperative spectrum sensing algorithms, encompassing primary and secondary users' models and an energy model. Subsequently, three machine learning algorithms, namely K-means, support vector machine, and logistic regression, are explained, and their schematics are presented in detail. The proposed model uses supervised and unsupervised learning techniques to develop a cooperative spectrum sensing framework. It compares the performance of three machine learning algorithms, K-means clustering, logistics regression and support vector machine. The comparison is based on accuracy, recall and precision metrics, and the results show that the K-means clustering algorithm has better performance than the other two algorithms. The findings highlight the superiority of the K-means clustering algorithm over logistic regression and support vector machine. [ABSTRACT FROM AUTHOR]

During the analysis of a commingled human remains assemblage, pair‐matching is often conducted as part of the inventory to inform the DNA sampling strategy and to calculate the minimum or most likely number of individuals. As commingled assemblages become larger, pair‐matching becomes more difficult, and it is unknown whether accuracy declines. Therefore, a study to determine the accuracy rates of visual pair‐matching for multiple observers was conducted on a large, commingled human assemblage. The sample consisted of 580 left and right humeri (n = 287 and n = 293, respectively) from the commingled remains of the USS Oklahoma, which were undergoing analysis at the Defense POW/MIA Accounting Agency. Five anthropologists completed this study, determining humeri pairs with varying degrees of confidence and non‐pairs. The overall precision was 81.0% and ranged from 74.1% to 95.9% for participants, including all confidence levels. When considering only confident matches, the overall precision for all participants increased to 91.4%. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Materials and Methods Results Conclusions This study aims to examine differences in trueness and precision between surgical guides with (S) and without sleeves (SL). A secondary aim was to assess the impact of the sleeve‐to‐bone distance.Mandible replicas (n = 120) were printed from an STL file obtained from a clinical CBCT. The mandibles were divided into sleeved (S, n = 60) and sleeveless (SL, n = 60) groups, each further divided into three categories (n = 20 each) with different heights from the guide to the implant platform: 2 mm (H2), 4 mm (H4), or 6 mm (H6). Digital planning and surgical guide design were done for a 4.1 × 10 mm implant for site #30. Post‐op positions were captured using a scan body and lab scanner. Angular deviation was the primary outcome, with 3D and 2D deviations as secondary parameters. Statistical analysis included two‐sample t‐tests, and one‐way and two‐way ANOVA.Group S (2.41 ± 1.41°) had significantly greater angular deviation than Group SL (1.65 ± 0.93°; p = 0.0001). Angular deviation increased with sleeve‐to‐bone distance. H2 deviations were 1.48 ± 0.80° (S) vs. 1.02 ± 0.45° (SL; p < 0.05), H4: 2.36 ± 1.04° (S) vs. 1.48 ± 0.79° (SL; p < 0.05), H6: 3.37 ± 0.67° (S) vs. 2.46 ± 0.89° (SL; p < 0.05). 3D deviation at the implant platform was 0.36 ± 0.17 mm (S) vs. 0.30 ± 0.15 mm (SL; p < 0.05) and at the apex 0.74 ± 0.34 mm (S) vs. 0.53 ± 0.31 mm (SL; p < 0.01). Group SL at H2 had the smallest inter‐implant distance (0.53 ± 0.37°), while Group S at H4 had the largest (1.20 ± 0.84°; p < 0.05).Sleeveless guides are more accurate than sleeved guides, and angular deviation is influenced by the distance from the guide to the implant platform. [ABSTRACT FROM AUTHOR]

Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood Pressure), and DBP (Diastolic Blood Pressure). Methods: The mental health evaluation relied on the following methods: PHQ‐9 (Patient Health Questionnaire‐9), ISI (Insomnia Severity Index), GAD‐7 (Generalized Anxiety Disorder Scale), and SBQ‐R (Suicidal Behaviors Questionnaire‐Revised). The study assessed KEYES, the comprehensive social health indicator. The study uses a famous methodology for training and testing four well‐known ML algorithms, namely the K‐nearest neighbors algorithm, decision trees, Naïve Bayes, and the random forest algorithm. Results and Conclusions: The recall value of the RF algorithm is higher by 2.0%, 4.15%, and 11.25%, respectively. The F‐score value of the RF algorithm is also the highest. The differences amount to 4.56% (Naïve Bayes), 2.50% (DT), and 11.20% (K‐NN). Accuracy, Precision, Recall, and F‐score were used to assess the researched ML algorithms' prediction ability. With a 99.40% prediction accuracy, a 97.60% precision, a 99.30% recall, and an F‐score value of 98.70%, the Random Forest method performed the best. ML algorithms can serve as tools for the prediction of physical, mental, and social health state of patients, including students, but they have a rather narrow scope of application and do not cover all aspects of health. Lay Description: What is currently known about this topic?: A condition of physical, social, and mental well‐being is known as being in good health.Machine learning is widely used in predicting the health of students. What does this paper add?: This study explored the predictive performance of four ML algorithms, such as the K‐nearest neighbors algorithm, decision trees, Naïve Bayes, and random forest classifier, using the input data gathered from Kazakh students.The individuals' social, mental, and physical health were evaluated using the algorithms. Implications for practice/or policy: ML algorithms can serve as tools for the prediction of physical, mental and social health state of patients, including students, but they have a rather narrow scope of application and do not cover all aspects of health.The current research may be used to forecast the health of pupils. [ABSTRACT FROM AUTHOR]

Anti-AAV neutralizing Abs (NAbs) titer is usually measured by cell-based microneutralization (MN) assay and is crucial for patient screening in AAV-based gene therapy clinical trials. However, achieving uniform operation and comparable results among different laboratories remains challenging. Here, we established a standardized MN assay for anti-AAV9 NAbs in human sera or plasma and transferred the method to the other two research teams. Then, we validated its parameters and tested a set of eight human samples in blind across all laboratories. The end-point titer, defined by a transduction inhibition of 50% (IC50), was calculated using curve-fit modelling. A mouse neutralizing monoclonal antibody in human negative serum was used for system quality control (QC), requiring inter-assay titer variation of <4-fold difference or geometric coefficient of variation (%GCV) of <50%. The assay demonstrated a sensitivity of 54 ng/mL and no cross-reactivity to 20 μg/mL anti-AAV8 MoAb. The intra-assay and inter-assay variation for the low positive QC were 7–35% and 22–41%, respectively. The titers of the blind samples showed excellent reproducibility within and among laboratories, with a %GCV of 18–59% and 23–46%, respectively. This study provides a commonly transferrable MN assay for evaluating anti-AAV9 NAbs in humans, supporting its application in clinical trials. [ABSTRACT FROM AUTHOR]

Thermal lens spectrometry is a high-sensitivity method for measuring the optical and thermal parameters of samples of different nature. To obtain both thermal diffusivity and absorbance-based signal measurements with high accuracy and precision, it is necessary to pay attention to the factors that influence the trueness of photothermal measurements. In this study, the features of liquid objects are studied, and the influence of optical and thermal effects accompanying photothermal phenomena are investigated. Thermal lens analysis of dispersed solutions and systems with photoinduced activity is associated with a large number of side effects, the impact of which on trueness is not always possible to determine. It is necessary to take into account the physicochemical properties and optical and morphological features of the nanophase and components exhibiting photoinduced activity. The results obtained make it possible to reduce systematic and random errors in determining the thermal-diffusivity-based and absorbance-based photothermal signals for liquid objects, and also contribute to a deeper understanding of the physicochemical processes in the sample. [ABSTRACT FROM AUTHOR]

Introduction: Since the introduction of nanorobotics, the discipline of medicinal chemistry has seen an exponential development in the uses of nanotechnology. One of the most potential uses of nanotechnology is in the creation of nanobots, which can be applied to a variety of industries such as medicine delivery, medical imaging, and even the benefits of nanobots include their small size, light weight, great flexibility, high sensitivity, and big thrust-to-weight ratio. Nanobots have several uses and are being investigated in many domains. This review’s objective is to provide an overview of the rapidly developing field of medicinal chemistry’s nanorobotics and its potential applications in disease detection, treatment, and prevention. Method: Several articles and newsletters are considered and used as a reference to collect information regarding nano and microbots and a brief information was written in accordance to use in medicine delivery. Results: Various review articles were taken into consideration to provide a deep knowledge on the utilization of nano and microbots in drug delivery and treatment therapy of several diseases. Conclusions: The main parts of the robots and the many kinds of nanobots are covered separately. The future perspective and initiatives that can help us realize our dreams of creating small robots that can move around inside our bodies, administering medication with previously unattainable precision, locating and eliminating infected cells, and most importantly making science fiction, a reality is finally covered. [ABSTRACT FROM AUTHOR]

SUMMARY: The accessory proteins Hyponastic‐like 1 (HYL1) and Serrated (SE) enhance the precise and efficient processing of miRNAs by Dicer‐like 1 (DCL1), which is important for proper miRNA function. However, other factors determining the precision and efficiency of miRNA biogenesis are not well‐known. Here, we found that an asymmetric bulge (AB) at the 3′ end of miR‐5p (produced from the 5′ arm of the pre‐miRNA) reduced the precision of the second cleavage, whereas an AB at other sites of miR‐5p mainly affected the accumulation level of miR‐5p in transient expression in Nicotiana benthamiana. In contrast, many ABs in miR‐3p (produced from the 3′ arm of the pre‐miRNA) impose strong negative impact on the processing precision and the accumulation level of miR‐5p in N. benthamiana. Arabidopsis DCL1/SE/HYL1 complex‐mediated miRNA processing was reconstituted in Saccharomyces cerevisiae to further investigate AB‐mediated interference with DCL1 processing. With this system, the positional effect of AB on miRNA processing was tested. The results showed that ABs on the middle of miR‐5p have less of an impact on DCL1 cleavage efficiency and precision, whereas those on miR‐3p or near the ends of miR‐5p strongly reduce DCL1 cleavage activity, precision or both. Studies using the yeast miRNA processing system and transgenic Arabidopsis also revealed the importance of the interaction between the 2‐nt 3′ overhang of pre‐miRNA and the 3′ overhang binding pocket (3′BP) on the precision of the second cleavage reaction for many endogenous miRNAs. These findings provide new insights into the mechanism of miRNA biogenesis. Significance Statement: Factors determining the precision and efficiency of miRNA biogenesis are not well‐known. This study found that an asymmetric bulge at different positions of miR‐5p and miR‐3p had different impacts on miRNA levels and processing precision and revealed the importance of the interaction between the 2‐nt 3′ overhang of pre‐miRNA and the 3′ overhang binding pocket (3'BP) on the precision of the second cleavage reaction for many endogenous miRNAs. [ABSTRACT FROM AUTHOR]

This research delves into the realm of Maritime Cybersecurity, focusing on the application of Artificial Intelligence (AI) mechanisms, namely K-Nearest Neighbors (KNN), Random Forest (RF), and Artificial Neural Networks (ANN). The maritime industry faces evolving cyber threats, necessitating innovative approaches for robust defense. The maritime sector is increasingly reliant on digital technologies, making it susceptible to cyber threats. Traditional security measures are insufficient against sophisticated attacks, necessitating the integration of AI mechanisms. This research aims to evaluate the effectiveness of KNN, RF, and ANN in fortifying maritime cybersecurity, providing a proactive defense against emerging threats. Investigate the application of KNN, RF, and ANN in the maritime cybersecurity landscape. Assess the performance of these AI mechanisms in detecting and mitigating cyber threats. Explore the adaptability of KNN, RF, and ANN to the dynamic maritime environment. Provide insights into the strengths and limitations of each algorithm for maritime cybersecurity. The study employs these AI algorithms to analyze historical maritime cybersecurity data, evaluating their accuracy, precision, and recall in threat detection. Results demonstrate the effectiveness of KNN in identifying localized anomalies, RF in handling complex threat landscapes, and ANN in learning intricate patterns within maritime cybersecurity data. Comparative analyses reveal the strengths and weaknesses of each algorithm, offering valuable insights for implementation. In conclusion, the integration of KNN, RF, and ANN mechanisms presents a promising avenue for enhancing maritime cybersecurity. The study underscores the importance of adopting AI solutions to the maritime domain's unique challenges. While each algorithm demonstrates efficacy in specific scenarios, a hybrid approach may offer a comprehensive defense strategy. As the maritime industry continues to evolve, leveraging AI mechanisms becomes imperative for staying ahead of cyber threats and safeguarding critical assets. This research contributes to the ongoing discourse on maritime cybersecurity, providing a foundation for future developments in the field. [ABSTRACT FROM AUTHOR]

PURPOSE. This study assesses the impact of additional reference objects (RO) on the trueness and precision of distance and angle measurements between scan bodies in digital scans with four different intraoral scanners (IOS) in partially edentulous models. MATERIALS AND METHODS. Maxilla models (Frasaco, Frasaco GmbH, Tettnang, Germany) with one (3-U) and two (4-U) missing posterior teeth were 3D printed and fitted with dental implants and scan bodies. Four intraoral scanners (Primescan (Dentsply Sirona, Charlotte, NC, USA) (PS), Trios 3 (3Shape) (T3), Trios 4 (3Shape) (T4), and CS3600 (Carestream Dentistry) (CS)) captured digital implant impressions with and without additional RO. Scans were aligned and assessed for distance and angulation measurements between scan bodies. Statistical analyses compared trueness and precision across model groups using the Student t-test and Welch's ANOVA. RESULTS. CS consistently showed the highest distance values across IOS devices in both the 4-U and 3-U models (P < .05), both with and without RO. The distance values were not considerably affected by the presence of RO (P > .05), except for a few isolated cases in the PS and CS groups of 3-U models. When measuring angles, CS usually showed greater values than the other IOS devices, especially when RO was present both in the 4-U and 3-U variants (P < .05). CONCLUSION. The influence of additional reference objects on accuracy varies with different scanner types, irrespective of edentulous area length. [ABSTRACT FROM AUTHOR]

This in vitro investigation aimed to compare the trueness, precision, internal fit, and marginal adaptation of Varseo Smile Crown Plus (VSCP), CROWNTEC (C), and milled Enamic crowns (E) using a 5-axis dental milling machine (prograMill PM7). 39 crowns (VSCP, E, C; n = 13) were designed and fabricated. Internal/marginal adaptation, precision, and trueness were assessed via die scans with/without a fit checker. Dimensional discrepancies were determined by superimposing the scans. One-way ANOVA (α = 0.05) analyzed the results. No significant differences were found in internal fit or marginal adaptation between groups. However, group E exhibited the best fit (axial: 82.9 µm). Trueness differed significantly (p < 0.05) across all groups and areas. Group E had the highest trueness (intaglio: 25.8 µm), while VSCP had the lowest (marginal: 31.9 µm). Precision varied significantly within the occlusal area of printed groups (highest for C: 17.8 µm) and the marginal area between printed/milled (VSCP vs. E) and C vs. E (lowest for E: 20.5 µm, highest for VSCP: 27.9 µm). In conclusion, both milled and 3D-printed crowns achieved comparable internal fit and marginal adaptation. However, group E displayed superior fit and trueness. While C exhibited higher occlusal precision, E had higher marginal precision. These findings suggest the potential for 3D-printed hybrid polymer crowns, warranting further investigation. [ABSTRACT FROM AUTHOR]

Artificial Intelligence-based system for Tuberculosis (TB) detection has been proposed in this work. Manual diagnostic through radiologists can be misdiagnosis due to human error. Designing an artificial intelligence-based decision support system can help in the accurate prediction of TB through lung Chest X-ray (CXR) image. In the proposed work, data centric and model centric approaches are applied. In data centric approach, images play an important role in feature extraction. In this context, experimentation on six varied kinds of image enhancement applied to the publicly available TB image dataset along with data pre-processing and data augmentation. In model centric approach, three pre-trained Convolutional Neural Network (CNN) with modification with specialized layers are proposed. Comparative Study of six image enhancement techniques along with original dataset in behavior response with network architectures is evaluated for best performance. Evaluation of the networks is based on accuracy, precision, recall and AUC. Sharpening of images applied on Modified ResNet50 is the best performer with accuracy 99.05%, precision 98.87%, recall 100% and AUC of 99.29%. In comparability with original dataset, sharpened images performed 0.8% better in metric evaluation, which gives better classification approach and predictability. [ABSTRACT FROM AUTHOR]

Introduction: Digital workflow and intraoral scanners (IOSs) are used to clinically obtain data for a wide range of applications in restorative dentistry. The study aimed to compare two different IOSs with inexperienced users in the digital workflow of oral split manufacturing. Material and Methods: Anonymous stone models of upper and lower dentate patients were used. Both models were scanned with a desktop 3D scanner 3Shape D2000 to obtain the reference models (STLR). Ten inexperienced operators scanned each model three times with each IOS system (3Shape TRIOS 3 and Carestream CS 3800). Finally, 20 intraoral scanners were randomly chosen from the obtained dataset (10 per IOS system) to design and manufacture 20 nightguards. All the nightguards were scanned. Trueness and precision were calculated and compared between the two IOS systems. Results: All the mean errors both for trueness and precision were below 40 µm, more than acceptable for the design and manufacturing of intraoral devices such as nightguards. All the mean errors (except one) for trueness between the inner part of the nightguards and the upper control model were below 100 µm, less than a printed layer height. For inexperienced operators, both IOSs are suitable for a digital workflow of manufacturing occlusal splints. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Polycrystalline diamond (PCD) is widely used for micro tools due to its high hardness and wear resistance. However, micro PCD tools face challenges in machining with high accuracy and efficiency. Therefore, electrical discharge machining grinding (EDM-grinding) composite machining was proposed. The effects of pulse discharge parameters on surface quality and microhole drilling performance of PCD tool were investigated. The results show that the surface roughness of helix flute and flank face of the fabricated PCD tool were 0.125 µm and 0.158 µm, respectively, as well as the inner wall roughness achieved 0.331 µm after drilling of microhole. The average current displayed a greater effect on the machining quality of PCD tools, with tool breakage in excessive average current. The preferred pulse discharge parameters were determined as an open-circuit voltage of 95 V, an average current of 1400 mA, a pulse width of 400 ns, and a pulse interval of 2000 ns. [ABSTRACT FROM AUTHOR]

ABSTRACT Objective Materials and Methods Results Conclusion Clinical Significance This systematic review and meta‐analysis compared the accuracy of intraoral scanners and spectrophotometers in determining tooth shade.An electronic search of five databases (PubMed, Scopus, Embase, Web of Science, CENTRAL) was conducted on October 19, 2023. A total of 163 studies were identified from the databases, of which 23 articles were eligible for inclusion. In vivo and in vitro quasi‐experimental studies were included. After data extraction, a quantitative analysis was performed to determine the accuracy of the intraoral scanner in subgroups using four outcomes: trueness and precision with different measurement locations. A random‐effects model was used to pool effect sizes. The pooled proportion with a 95% confidence interval (CI) was used for the effect size measure.Eleven articles were included in the meta‐analysis. Trueness with the intraoral scanner was between 0.28 (CI: 0.09–0.60) and 0.38 (CI: 0.24–0.53). Repeatability was between 0.81 (CI: 0.64–0.91) and 0.85 (CI: 0.74–0.92). Trueness showed low, and precision had moderate certainty of evidence.The trueness of shade matching with intraoral scanners is low compared to spectrophotometers, although the precision is considered high and is similar to spectrophotometers.Shade determination with intraoral scanners is not recommended. [ABSTRACT FROM AUTHOR]

Introduction Vection is a stationary individual's illusory experience of self-motion. This illusory self-motion is operationally important for aviation, particularly military aviation, since vection is a dramatic example of spatial disorientation (SD), which is an individual's failure to correctly sense the aircraft's position, motion, and/or attitude with respect to the fixed coordinate system of the Earth's surface and its gravitational vertical. Notably, SD is a major cause of fatal aviation mishaps, and the visual system is particularly prone to provoking vection. This article describes the Virtual Reality Vection System (VRVS), which uses computer-controlled virtual reality technology to induce vection under controlled conditions for training, demonstration, testing, and research. Materials and Methods The VRVS enables the precise specification of the number and appearance of visual stimulus elements intended to generate vection, including photorealistic images. The VRVS can present visual stimuli on any OpenXR-capable virtual reality headset. The VRVS currently records 2 types of behavioral responses, button presses to indicate the presence and duration of vection and the voltage of a handheld linear potentiometer to indicate the presence, duration, and magnitude of vection. Results An approved test plan helped guide, organize, document, and validate the VRVS during its development. Under this plan, a pair of tests guided hardware and software development of the VRVS system. Although the first test verified the ability of the VRVS to generate and measure vection, it also demonstrated that the VRVS can quickly manipulate the visual stimuli from one trial to the next so that the VRVS can support complex experimental designs. The second test used these capabilities to verify that the VRVS can characterize vection in a more analytic fashion using a masking paradigm. Specifically, the test assessed whether random stimulus elements injected into the vection-inducing stimulus disrupted vection in a quantifiable fashion. This work opens the door to studies that characterize the necessary and sufficient visual elements for vection-based SD. Discussion The VRVS is currently used to research, develop, test, and evaluate mitigation strategies targeting vection-related SD in degraded visual environments. Similarly, the VRVS is supporting research to develop methods to predict individual differences in visually induced motion sickness susceptibilities. The VRVS is currently being integrated with a precision motor-controlled rotating Barany chair for multisensory studies. It should be noted that since the VRVS was developed to support United States Army Aeromedical Research Laboratory projects, it is an Army product representing government intellectual property and may be freely available to other government institutions. [ABSTRACT FROM AUTHOR]

Introduction Current standards for hemoglobin monitoring during air transports of U.S. combat wounded are invasive and intermittent. Fielded pulse co-oximeters can noninvasively measure total hemoglobin, but this parameter is not currently utilized. The primary objective of this study was to assess the percentage of vital sign measurements with successful capture of total noninvasive hemoglobin measurement using spectrophotometry-based technology for Hb (SpHb) measurements in healthy participants during training flights. Secondary objectives were to assess the feasibility of a novel electronic data capture mechanism from usual patient movement items and perform a pilot analysis of SpHb changes in healthy participants during transitions from ground to air transport. Methods We conducted a feasibility study enrolling healthy participants who had hemodynamic monitoring during usual U.S. Air Force Critical Care Air Transport (CCAT) flight training exercises from 2022 to 2023. Usual CCAT monitoring equipment and currently used Masimo Rainbow® pulse co-oximeters had the capability to measure SpHb. After each training exercise, the study team wirelessly downloaded case files from patient monitors utilizing the Battlefield Assisted Trauma Distributed Observation Kit (BATDOKTM) Case Downloader application. We then calculated point and precision estimates for the percentage of time for successful SpHb capture during the exercise and compared this to pulse oximetry (SpO2) capture. An a priori precision analysis for percentage of flight-time with successful SpHb data capture and descriptive statistics were performed. This study received Exempt Determination by the 59th Medical Wing IRB. Results We analyzed 26 records with mean monitoring durations of 94.5 [59.3-119.9] minutes during ground phases and 78.0 [59.9-106.5] minutes during flight phases. SpHb measures were successfully captured for 97.7% (n  = 4,620) of possible ground measurements and 97.2% (n  = 3,973) of possible in-flight measurements compared to 99.5% ground and 98.2% in-flight capture for SpO2. Mean intervals of missing SpHb data were 2 ± 5 minutes on the ground and 4 ± 6 minutes in-flight. Mean SpHb increased by 0.93 ± 0.96 g/dL during the ground phase, but had minimal changes during ascent, cruising altitude or descent. The BATDOKTM Case downloader completed transfer for all files. Conclusion Masimo Rainbow® SpHb pulse co-oximeters reliably captured continuous, noninvasive hemoglobin measurements using usual CCAT patient movement items in healthy participants during both ground and flight training. The BATDOKTM Case Downloader successfully imported case files from CCAT patient monitors. Mean SpHb measures had a small increase during the ground phase of monitoring followed by minimal changes when transitioning to flight altitude. [ABSTRACT FROM AUTHOR]

Background: The accuracy of intraoral scanning is critical for computer-aided design/computer-aided manufacturing workflows in dentistry. However, data regarding the scanning accuracy of various adjacent restorative materials and intraoral scanners are lacking. This in vitro study aimed to evaluate the effect of adjacent restorative material type and CEREC's intraoral scanners on the accuracy of intraoral digital impressions for inlay cavities. Methods: The artificial tooth was prepared with an occlusal cavity depth of 2 mm, a proximal box width at the gingival floor of 1.5 mm, and an equi-gingival margin extended disto-occlusally at the transition line angle on both the lingual and buccal sides for an inlay restoration. The adjacent teeth were veneered with crowns made of gold and zirconia, and an artificial tooth (resin) was utilized as the control group. The inlay cavity and adjacent teeth (Gold, Zirconia, and resin) were scanned 10 times using Chairside Economical Restoration of Esthetic Ceramics (CEREC) Primescan (PS), Omnicam (OC), and Bluecam (BC). A reference scan was obtained using a laboratory scanner (3-shape E3). Scanning was performed according to the manufacturer's instructions, including powder application for the BC group. Standard tesselation language files were analyzed using a three-dimensional analysis software program. Experimental data were analyzed using a two-way analysis of variance and the Tukey's post-hoc comparison test. Results: The restorative materials of the adjacent teeth significantly affected the accuracy of the intraoral digital impressions (p <.05). The zirconia group exhibited the highest trueness deviation, followed by the resin and gold groups, with each demonstrating a statistically significant difference (p <.05). The resin group demonstrated the highest maximum positive deviation and deviation in precision. Gold exhibited the lowest average deviation value for trueness compared with those of the other adjacent restorative materials. Intraoral scanner type significantly influenced the trueness and precision of the scan data (p <.05). The average deviation of trueness according to the intraoral scanner type increased in the following order: BC > PS > OC. The average deviation in precision increased in the following order: PS>OC>BC (p <.05). Conclusion: The restorative materials of the adjacent tooth and the type of intraoral scanner affect the accuracy of the intraoral digital impression. The trueness of the digital images of the BC group, obtained by spraying the powder, was comparable to that of the PS group. Among the adjacent restorative materials, zirconia exhibited the lowest trueness. In contrast, PS demonstrated the highest precision among the intraoral scanners, while resin displayed the lowest precision among the adjacent restorative materials. [ABSTRACT FROM AUTHOR]

Geographic data quality is a complex issue requiring continuous operational improvements. Considering this to be one of the most topical research and technical issues in official statistics and environmental monitoring, this study re-connects the operational dimension of 'geographic data quality' with the broader issue of monitoring the quality of official statistics. By estimating the accuracy of public (spatially explicit) data, this study illustrates an operational framework with an exploratory exercise in estimating the geographic data quality characteristic of a specific information source within the official statistical system (i.e., building registry) in a given European country, namely, Italy. The results of this exercise provide a paradigmatic example of profound innovation in the activities of statistical services in Europe and specifically the Italian National Statistical Institute (Istat), transitioning from independent (and poorly connected) field surveys to an integrated system of registries. Since several studies are based on spatially explicit survey units, it is essential to estimate the quality of geographical data, especially those derived from information sources where space is topical information, such as (local, regional, or national) building registers. Thanks to the results of an empirical exercise applied to Italian building registers, the present article will discuss the issue of data accuracy, considered the main issue related to monitoring geographic data quality, from an official statistics' perspective. Statistical indicators will be proposed for the assessment of systematic and random errors of spatially explicit measures, possibly enabling a quali-quantitative improvement in the semantic content of building registers that address the inherent requirements of official statistics. Such indicators have some positive implications for the entire system of official statistics in Italy and, for generalization, within the European Statistical System. [ABSTRACT FROM AUTHOR]

Active inference describes (Bayes-optimal) behaviour as being motivated by the minimisation of surprise of one's sensory observations, through the optimisation of a generative model (of the hidden causes of one's sensory data) in the brain. One of active inference's key appeals is its conceptualisation of precision as biasing neuronal communication and, thus, inference within generative models. The importance of precision in perceptual inference is evident—many studies have demonstrated the importance of ensuring precision estimates are correct for normal (healthy) sensation and perception. Here, we highlight the many roles precision plays in action, i.e., the key processes that rely on adequate estimates of precision, from decision making and action planning to the initiation and control of muscle movement itself. Thereby, we focus on the recent development of hierarchical, "mixed" models—generative models spanning multiple levels of discrete and continuous inference. These kinds of models open up new perspectives on the unified description of hierarchical computation, and its implementation, in action. Here, we highlight how these models reflect the many roles of precision in action—from planning to execution—and the associated pathologies if precision estimation goes wrong. We also discuss the potential biological implementation of the associated message passing, focusing on the role of neuromodulatory systems in mediating different kinds of precision. [ABSTRACT FROM AUTHOR]

Objective To recommend precision dosing and improve therapeutic efficacy against invasive fungal disease, a physiologically based pharmacokinetic model (PBPK) of oral isavuconazole (ISA) was established and used to explore its disposition across populations in different physiological and pathological states. Methods Twenty-five pharmacokinetic (PK) studies of oral ISA were identified through a systematic search of PubMed. Concentration–time data were extracted using WebPlotDigitizer. Physiochemical parameters were obtained from published literature and DrugBank. Model development and simulation used the Simcyp population-based simulator, and visual predictive check and predictive error were used for the model evaluation. Probability of target attainment and the cumulative fraction of response analyses were performed for dose optimization. Results The developed PBPK model was successfully validated in different populations. Most predicted concentration–time points aligned with the observed data, with acceptable predictive errors for the critical parameters. We predicted the PK profiles and parameters of ISA in a population with severe hepatic impairment (HI), a population with obesity and paediatric patients aged 1 to less than 6 years old. The probability of target attainment and cumulative fraction of response analyses indicated that the population with severe HI should have half the maintenance dose. The population with obesity and population with severe HI should have a loading dose of 300 mg every 8 h for 2 days. For paediatric patients aged 1 to less than 6 years old, a weight-based dosing regimen (5.38 mg/kg) of ISA was suggested. Conclusion The predicted value aligns with observations, suggesting ISA's potential predictability in PK profiles for other populations. The recommended dosing regimens increase our understanding of the use of ISA in special populations. [ABSTRACT FROM AUTHOR]