An overview of preconcentration techniques combined with inductively coupled plasma mass spectrometry for trace element determination in biological studies.

In the last decades, the determination of trace elements in biological materials has emerged as an important area of study because of its relevance to human health and the environment. Inductively coupled plasma mass spectrometry (ICP-MS) has proven to be a powerful tool for trace element analysis, owing to its high sensitivity and ability to determine several elements in a single measurement. However, given the complex nature of biological matrices and the presence of elements, most of them at ultratrace levels, it becomes crucial to complement ICP-MS with preconcentration techniques to increase the sensitivity and selectivity of analytical methods. This article presents an exhaustive overview of liquid- and solid-phase preconcentration techniques used in combination with ICP-MS for trace element determination in different biological samples from 2000 to the present. An in-depth discussion of the advances on the application of state-of-the-art solvents and materials in trace element extraction and preconcentration is presented. Special attention is given to different strategies for elemental speciation analysis, employing both chromatographic and non-chromatographic techniques. The role of automation in these methodologies is also described. Finally, future trends and challenges related to this topic are discussed.

Use of Augmented Reality as a Tool to Support Cargo Handling Operations at the CARGO Air Terminal.

(1) Background: A current trend observed in the logistics sector is the use of Industry 4.0 tools to improve and enhance the efficiency of cargo handling processes. One of the popular solutions is an augmented reality system that supports operators in everyday tasks. The article aims to present design assumptions for implementing an augmented reality system to support air cargo handling at the warehouse. (2) Methods: Research was carried out based on a five-stage analytical procedure, aiming to analyze the current state and identify the potential for implementing the AR system. The following methods were used to collect data: co-participant observations, process analysis, direct interviews, analysis of internal documentation, and applicable legal regulations. (3) Results: The conducted research allowed for identifying information flows accompanying cargo flows and developing a project to automate selected information flows. The obtained results made it possible to identify operations for which the AR system's implementation will increase their effectiveness and efficiency. (4) Conclusions: The obtained results identified the need to develop a hybrid algorithm for arranging cargo in the warehouse and to build a system supporting self-verification of markings on air cargo.

Metrology of Short-Length Measurers-Development of a Comparator for the Calibration of Measurers Based on Image Processing and Interferometric Measurements.

For the calibration of linear scales, comparators are generally used. Comparators are devices that enable the movement of an evaluation apparatus over a calibrated scale along a linear base with high precision. The construction of a comparator includes a movable carriage that carries the device for the evaluation of the position of the given edge of the line scale relative to the beginning of the scale. In principle, it involves a camera capturing the scale of the measurer, where the position of the camera's projection center is measured using an interferometer. This article addresses the development of a comparator assembled from low-cost components, as well as the description of systematic influences related to the movement of individual parts of the system, such as the inclination and rotation of the camera and directional and height deviations during the carriage's movement. This article also includes an evaluation of the edge of the given scale with subpixel accuracy, addressing distortion elimination and excluding the influences of impurities or imperfections on the scale. The proposed solution was applied to linear-scale measurers, such as leveling rods with coded and conventional scales and measuring tapes. The entire process of measurement and evaluation was automated.

The influence of the weight-bearing state on three-dimensional (3D) planning in lower extremity realignment - analysis of novel vs. state-of-the-art planning approaches.

BACKGROUND: The use of 3D planning to guide corrective osteotomies of the lower extremity is increasing in clinical practice. The use of computer-tomography (CT) data acquired in supine position neglects the weight-bearing (WB) state and the gold standard in 3D planning involves the manual adaption of the surgical plan after considering the WB state in long-leg radiographs (LLR). However, this process is subjective and dependent on the surgeons experience. A more standardized and automated method could reduce variability and decrease costs. PURPOSE: The aim of the study was (1) to compare three different three-dimensional (3D) planning modalities for medial open-wedge high tibial osteotomy (MOWHTO) and (2) to describe the current practice of adapting NWB CT data after considering the WB state in LLR. The purpose of this study is to validate a new, standardized approach to include the WB state into the 3D planning and to compare this method against the current gold standard of 3D planning. Our hypothesis is that the correction is comparable to the gold standard, but shows less variability due compared to the more subjective hybrid approach. METHODS: Three surgical planning modalities were retrospectively analyzed in 43 legs scheduled for MOWHTO between 2015 and 2019. The planning modalities included: (1) 3D hybrid (3D non-weight-bearing (NWB) CT models after manual adaption of the opening angle considering the WB state in LLR, (2) 3D NWB (3D NWB CT models) and (3) 3D WB (2D/3D registration of 3D NWB CT models onto LLR to simulate the WB state). The pre- and postoperative hip-knee-ankle angle (HKA) and the planned opening angle (°) were assessed and differences among modalities reported. The relationship between the reported differences and BMI, preoperative HKA (LLR), medial meniscus extrusion, Outerbridge osteoarthritis grade and joint line convergence angle (JLCA) was analyzed. RESULTS: The mean (std) planned opening angle of 3D hybrid did not differ between 3D hybrid and 3D WB (0.4 ± 2.1°) (n.s.) but was higher in 3D hybrid compared to 3D NWB (1.1° ± 1.1°) (p = 0.039). 3D WB demonstrated increased preoperative varus deformity compared to 3D NWB: 6.7 ± 3.8° vs. 5.6 ± 2.7° (p = 0.029). Patients with an increased varus deformity in 3D WB compared to 3D NWB (> 2 °) demonstrated more extensive varus alignment in LLR (p = 0.009) and a higher JLCA (p = 0.013). CONCLUSION: Small intermodal differences between the current practice of the reported 3D hybrid planning modality and a 3D WB approach using a 2D/3D registration algorithm were reported. In contrast, neglecting the WB state underestimates preoperative varus deformity and results in a smaller planned opening angle. This leads to potential under correction in MOWHTO, especially in patients with extensive varus deformities or JLCA. CLINICAL RELEVANCE: Incorporating the WB state in 3D planning modalities has the potential to increase accuracy and lead to a more consistent and reliable planning in MOWHTO. The inclusion of the WB state in automatized surgical planning algorithms has the potential to reduce costs and time in the future.

Implicit signatures of voluntary action reduce with repeated motor practice.

The sense of controlling one's actions and their consequences is a critical aspect of successful motor activity. While motor performance typically improves with learning, it is unclear whether, how, and why higher order aspects of motor cognition are also affected. Here, we used an implicit measure of sense of agency-the 'intentional binding' effect-as participants learned to make a skilled action involving precise control of thumb adduction. These actions were predictably followed by a tone (the outcome). At pre-test, we showed the perceived time of the tone was shifted towards the thumb action, compared to a control condition in which tones occurred without actions. Next, a relevant training group learned to refine the direction of the thumb movement, while an irrelevant training group was trained on another movement. Manipulation checks demonstrated that, as expected, the relevant training group improved performance of the trained movement, while the irrelevant training group did not. Critically, while both groups still showed binding of the tone towards the thumb action at post-test, the relevant training group showed less binding than the irrelevant training group. Given the link between intentional binding and volitional control of action, we suggest our result demonstrates subjective agency over the outcome of a skilled action decreases as practice makes the skilled action more fluent. We suggest that this reduction in sense of agency over movement outcomes is consistent with the decreasing cognitive engagement, or automatization, that occurs during skill learning.

Microextraction by packed sorbent of N-nitrosamines from Losartan tablets using a high-throughput robot platform followed by liquid chromatography-tandem mass spectrometry.

The development of a fast, cost-effective, and efficient microextraction by packed sorbent setup was achieved by combining affordable laboratory-repackable devices of microextraction with a high-throughput cartesian robot. This setup was evaluated for the development of an analytical method to determine N-nitrosamines in losartan tablets. N-nitrosamines pose a significant concern in the pharmaceutical market due to their carcinogenic risk, necessitating their control and quantification in pharmaceutical products. The parameters influencing the performance of this sample preparation for N-nitrosamines were investigated through both univariate and multivariate experiments. Microextractions were performed using just 5.0 mg of carboxylic acid-modified polystyrene divinylbenzene copolymer as the extraction phase. Under the optimized conditions, the automated setup enabled the simultaneous treatment of six samples in less than 20 min, providing reliable analytical confidence for the proposed application. The analytical performance of the automated high-throughput microextraction by the packed sorbent method was evaluated using a matrix-matching calibration. Quantification was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry with chemical ionization at atmospheric pressure. The method exhibited limits of detection as low as 50 ng/g, good linearity, and satisfactory intra-day (1.38-18.76) and inter-day (2.66-20.08) precision. Additionally, the method showed accuracy ranging from 80% to 136% for these impurities in pharmaceutical formulations.

Machine learning computational tools to assist the performance of systematic reviews: A mapping review.

BACKGROUND: Within evidence-based practice (EBP), systematic reviews (SR) are considered the highest level of evidence in that they summarize the best available research and describe the progress in a determined field. Due its methodology, SR require significant time and resources to be performed; they also require repetitive steps that may introduce biases and human errors. Machine learning (ML) algorithms therefore present a promising alternative and a potential game changer to speed up and automate the SR process. This review aims to map the current availability of computational tools that use ML techniques to assist in the performance of SR, and to support authors in the selection of the right software for the performance of evidence synthesis. METHODS: The mapping review was based on comprehensive searches in electronic databases and software repositories to obtain relevant literature and records, followed by screening for eligibility based on titles, abstracts, and full text by two reviewers. The data extraction consisted of listing and extracting the name and basic characteristics of the included tools, for example a tool's applicability to the various SR stages, pricing options, open-source availability, and type of software. These tools were classified and graphically represented to facilitate the description of our findings. RESULTS: A total of 9653 studies and 585 records were obtained from the structured searches performed on selected bibliometric databases and software repositories respectively. After screening, a total of 119 descriptions from publications and records allowed us to identify 63 tools that assist the SR process using ML techniques. CONCLUSIONS: This review provides a high-quality map of currently available ML software to assist the performance of SR. ML algorithms are arguably one of the best techniques at present for the automation of SR. The most promising tools were easily accessible and included a high number of user-friendly features permitting the automation of SR and other kinds of evidence synthesis reviews.

Semiautomatic Assessment of Fetal Fractional Limb Volume for Weight Prediction in Clinical Praxis: How Does It Perform in Routine Use?

OBJECTIVES: Semiautomatic fractional limb volume (FLV) models have recently produced promising results for fetal birth weight (BW) estimation. We tested those models in a more unselected population hypothesizing that the FLV models would improve accuracy and precision of fetal BW estimation compared to the Hadlock model. METHODS: We compared the performance of different BW prediction models: Hadlock (biparietal diameter [BPD], abdominal circumference (AC), femur diaphysis length) and modified Lee thigh volume (TVol) and arm volume (AVol) (BPD, AC, automated fractional TVol, and AVol). Accuracy (systematic errors, mean percent differences) and precision (random errors, ± 1 SD of percent differences) were calculated. RESULTS: A total of 75 fetuses were included for final analysis. The Hadlock model showed the most consistent results with accurate BW estimation not significantly different from zero (-0.37 ± 8.53%). The modified fractional thigh and arm volume models were less accurate but trended toward more precise results (-2.63 ± 7.69% and -3.85 ± 7.47%, respectively). In addition, the modified TVol model showed the trend to predict more BWs within ±10% of the actual BW compared to the Hadlock model (81.3 versus 74.67%, ns). CONCLUSIONS: Based on our results, fetal weight estimation using the modified semiautomatic FLV models generates less accurate results in third-trimester fetuses compared to the Hadlock model. Those models recently published might improve the results of BW prediction by showing a higher precision than conventional models, especially in small and large fetuses. Further studies are needed to investigate the clinical usefulness of the new models.

Developmental changes in size effects for simple tie and non-tie addition problems in 6- to 12-year-old children and adults.

In the domain of cognitive arithmetic, the size effect corresponds to an increase in solution times as a function of the size of the operands involved in the problems. In this study, we tracked the evolution of size effects associated with tie and non-tie addition problems across development. We scrutinized the progression of solution times for very small problems involving operands from 2 to 4, larger problems, and 1-problems (problems involving 1 as one of the operands) in children from Grade 1 to Grade 5 and adults. For the first time, we document the presence of a size effect for tie problems with a sum up to 8 in Grade 1 children. In contrast, from Grade 3 until adulthood, this size effect could not be evidenced. Crucially, for non-tie problems, whereas a general size effect is observed when contrasting small one-digit additions with large additions, we show that, from Grade 1 until adulthood, a continuous size effect as a function of the sum of the problems is not observed. In fact, for all age groups, medium problems with sums of 8, 9, and 10 do not present a size effect at all. Given that the problem size effect is sometimes referred to as one of the most robust and reliable effects in the numerical cognition literature, our results necessarily challenge its theoretical interpretation.

Automated muscle elongation measurement during reverse shoulder arthroplasty planning.

BACKGROUND: Adequate deltoid and rotator cuff elongation in reverse shoulder arthroplasty is crucial to maximize postoperative functional outcomes and to avoid complications. Measurements of deltoid and rotator cuff elongation during preoperative planning can support surgeons in selecting a suitable implant design and position. Therefore, this study presented and evaluated a fully automated method for measuring deltoid and rotator cuff elongation. METHODS: Complete scapular and humeral models were extracted from computed tomography scans of 40 subjects. First, a statistical shape model of the complete humerus was created and evaluated to identify the muscle attachment points. Next, a muscle wrapping algorithm was developed to identify the muscle paths and to compute muscle lengths and elongations after reverse shoulder arthroplasty implantation. The accuracy of the muscle attachment points and the muscle elongation measurements was evaluated for the 40 subjects by use of both complete and artificially created partial humeral models. Additionally, the muscle elongation measurements were evaluated for a set of 50 arthritic shoulder joints. Finally, a sensitivity analysis was performed to evaluate the impact of implant positioning on deltoid and rotator cuff elongation. RESULTS: For the complete humeral models, all muscle attachment points were identified with a median error < 3.5 mm. For the partial humeral models, the errors on the deltoid attachment point largely increased. Furthermore, all muscle elongation measurements showed an error < 1 mm for 75% of the subjects for both the complete and partial humeral models. For the arthritic shoulder joints, the errors on the muscle elongation measurements were <2 mm for 75% of the subjects. Finally, the sensitivity analysis showed that muscle elongations were affected by implant positioning. DISCUSSION: This study presents an automated method for accurately measuring muscle elongations during preoperative planning of shoulder arthroplasty. The results show that the accuracy in measuring muscle elongations is higher than the accuracy in indicating the muscle attachment points. Hence, muscle elongation measurements are insensitive to the observed errors on the muscle attachment points. Related to this finding, muscle elongations can be accurately measured for both a complete humeral model and a partial humeral model. Because the presented method also showed accurate results for arthritic shoulder joints, it can be used during preoperative shoulder arthroplasty planning, in which typically only the proximal humerus is present in the scan and in which bone arthropathy can be present. As the muscle elongations are sensitive to implant positioning, surgeons can use the muscle elongation measurements to refine their surgical plan.

Automated quantification of glenoid bone defects using 3-dimensional measurements.

BACKGROUND: Assessment of glenoid bone defects is important to select the optimal glenoid component design during shoulder arthroplasty planning and implantation. This study presents a fully automated method to describe glenoid bone loss using 3-dimensional measurements without the need for a healthy contralateral reference scapula. METHODS: The native shape of the glenoid is reconstructed by fitting a statistical shape model (SSM) of the scapula. The total vault loss percentage, local vault loss percentages, defect depth, defect area percentage, and subluxation distance and region are computed based on a comparison of the reconstructed and eroded glenoids. The method is evaluated by comparing its results with a contralateral bone-based reconstruction approach in a data set of 34 scapula and humerus pairs with unilateral glenoid bone defects. RESULTS: The SSM-based defect measurements deviated from the contralateral bone-based measurements with mean absolute differences of 5.5% in the total vault loss percentage, 4.5% to 8.0% in the local vault loss percentages, 1.9 mm in the defect depth, 14.8% in the defect area percentage, and 1.6 mm in the subluxation distance. The SSM-based method was statistically equivalent to the contralateral bone-based method for all parameters except the defect area percentage. CONCLUSION: The presented method is able to automatically analyze glenoid bone defects using 3-dimensional measurements without the need for a healthy contralateral bone.

Large-scale coupling dynamics of instructed reversal learning.

The ability to rapidly learn from others by instruction is an important characteristic of human cognition. A recent study found that the rapid transfer from initial instructions to fluid behavior is supported by changes of functional connectivity between and within several large-scale brain networks, and particularly by the coupling of the dorsal attention network (DAN) with the cingulo-opercular network (CON). In the present study, we extended this approach to investigate how these brain networks interact when stimulus-response mappings are altered by novel instructions. We hypothesized that residual stimulus-response associations from initial practice might negatively impact the ability to implement novel instructions. Using functional imaging and large-scale connectivity analysis, we found that functional coupling between the CON and DAN was generally at a higher level during initial than reversal learning. Examining the learning-related connectivity dynamics between the CON and DAN in more detail by means of multivariate patterns analyses, we identified a specific subset of connections which showed a particularly high increase in connectivity during initial learning compared to reversal learning. This finding suggests that the CON-DAN connections can be separated into two functionally dissociable yet spatially intertwined subsystems supporting different aspects of short-term task automatization.

Recent trends in sorption-based sample preparation and liquid chromatography techniques for food analysis.

The accelerated rising of the world's population increased the consumption of food, thus demanding more rigors in the control of residue and contaminants in food-based products marketed for human consumption. In view of the complexity of most food matrices, including fruits, vegetables, different types of meat, beverages, among others, a sample preparation step is important to provide more reliable results when combined with HPLC separations. An adequate sample preparation step before the chromatographic analysis is mandatory in obtaining higher precision and accuracy in order to improve the extraction of the target analytes, one of the priorities in analytical chemistry. The recent discovery of new materials such as ionic liquids, graphene-derived materials, molecularly imprinted polymers, restricted access media, magnetic nanoparticles, and carbonaceous nanomaterials, provided high sensitivity and selectivity results in an extensive variety of applications. These materials, as well as their several possible combinations, have been demonstrated to be highly appropriate for the extraction of different analytes in complex samples such as food products. The main characteristics and application of these new materials in food analysis will be presented and discussed in this paper. Another topic discussed in this review covers the main advantages and limitations of sample preparation microtechniques, as well as their off-line and on-line combination with HPLC for food analysis.

High-throughput analysis of sub-visible mAb aggregate particles using automated fluorescence microscopy imaging.

Aggregation of therapeutic proteins is a major concern as aggregates lower the yield and can impact the efficacy of the drug as well as the patient's safety. It can occur in all production stages; thus, it is essential to perform a detailed analysis for protein aggregates. Several methods such as size exclusion high-performance liquid chromatography (SE-HPLC), light scattering, turbidity, light obscuration, and microscopy-based approaches are used to analyze aggregates. None of these methods allows determination of all types of higher molecular weight (HMW) species due to a limited size range. Furthermore, quantification and specification of different HMW species are often not possible. Moreover, automation is a perspective challenge coming up with automated robotic laboratory systems. Hence, there is a need for a fast, high-throughput-compatible method, which can detect a broad size range and enable quantification and classification. We describe a novel approach for the detection of aggregates in the size range 1 to 1000 µm combining fluorescent dyes for protein aggregate labelling and automated fluorescence microscope imaging (aFMI). After appropriate selection of the dye and method optimization, our method enabled us to detect various types of HMW species of monoclonal antibodies (mAbs). Using 10 µmol L-1 4,4'-dianilino-1,1'-binaphthyl-5,5'-disulfonate (Bis-ANS) in combination with aFMI allowed the analysis of mAb aggregates induced by different stresses occurring during downstream processing, storage, and administration. Validation of our results was performed by SE-HPLC, UV-Vis spectroscopy, and dynamic light scattering. With this new approach, we could not only reliably detect different HMW species but also quantify and classify them in an automated approach. Our method achieves high-throughput requirements and the selection of various fluorescent dyes enables a broad range of applications.

Light-induced gene expression with photocaged IPTG for induction profiling in a high-throughput screening system.

BACKGROUND: Inducible expression systems are frequently used for the production of heterologous proteins. Achieving maximum product concentrations requires induction profiling, namely the optimization of induction time and inducer concentration. However, the respective experiments can be very laborious and time-consuming. In this work, a new approach for induction profiling is presented where induction in a microtiter plate based cultivation system (BioLector) is achieved by light using photocaged isopropyl ß-D-1-thiogalactopyranoside (cIPTG). RESULTS: A flavin mononucleotide-based fluorescent reporter protein (FbFP) was expressed using a T7-RNA-polymerase dependent E. coli expression system which required IPTG as inducer. High power UV-A irradiation was directed into a microtiter plate by light-emitting diodes placed above each well of a 48-well plate. Upon UV irradiation, IPTG is released (uncaged) and induces product formation. IPTG uncaging, formation of the fluorescent reporter protein and biomass growth were monitored simultaneously in up to four 48-well microtiter plates in parallel with an in-house constructed BioLector screening system. The amount of released IPTG can be gradually and individually controlled for each well by duration of UV-A exposure, irradiance and concentration of photocaged IPTG added at the start of the cultivation. A comparison of experiments with either optical or conventional IPTG induction shows that product formation and growth are equivalent. Detailed induction profiles revealed that for the strain and conditions used maximum product formation is reached for very early induction times and with just 6-8 s of UV-A irradiation or 60-80 µM IPTG. CONCLUSIONS: Optical induction and online monitoring were successfully combined in a high-throughput screening system and the effect of optical induction with photocaged IPTG was shown to be equivalent to conventional induction with IPTG. In contrast to conventional induction, optical induction is less costly to parallelize, easy to automate, non-invasive and without risk of contamination. Therefore, light-induced gene expression with photocaged IPTG is a highly advantageous method for the efficient optimization of heterologous protein production and has the potential to replace conventional induction with IPTG.

Laboratory Automated Interrogation of Data: an interactive web application for visualization of multilevel data from biological experiments.

A key step in understanding the results of biological experiments is visualization of the data. Many laboratory experiments contain a range of measurements that exist within a hierarchy of interdependence. An automated and facile way to visualize and interrogate such multilevel data, across many experimental variables, would (i) lead to improved understanding of the results, (ii) help to avoid misleading interpretation of statistics and (iii) easily identify outliers and sources of batch and confounding effects. While many excellent graphing solutions already exist, they are often geared towards the production of publication-ready plots and the analysis of a single variable at a time, require programming expertise or are unnecessarily complex for the task at hand. Here, we present Laboratory Automated Interrogation of Data (LAB-AID), an interactive tool specifically designed to automatically visualize and query hierarchical data resulting from biological experiments.

Effects of Using Laser Technology for Cutting Polymer Films.

In connection with the need to obtain a properly made and cut material and the appearance of the surface layer, new manufacturing technologies were used for tests, namely the laser cutting technology. This article describes the laboratory stand built for the purpose of research, as well as the possibility of using laser cutting on several sample materials (polymer films), together with an indication of the results obtained. The idea was to elaborate on the cutting technology that will be proper for manufacturing the desired type of spacers for ion-exchange membranes separating while maintaining the required level of product quality and chemical purity. The latter criterion was the basic one, due to the scope of use of the manufactured elements. This article also describes the problem encountered during the construction of the stand or during the research. The last part of this article describes the further steps of the research that will be carried out in the future along with a discussion and summary of the research performed. It is important from the point of view of the development of production technology, but also because of the characteristics of materials for the production of surface layers and coatings resistant to mechanical or thermal wear used in industry. The introduction of innovative solutions is also aimed at studying the improvement of the economics of the production of materials that are significant, in particular, for small- and medium-sized enterprises.

Validation of a Three-Dimensional Weight-Bearing Measurement Protocol for Medial Open-Wedge High Tibial Osteotomy.

Three-dimensional (3D) deformity assessment and leg realignment planning is emerging. The aim of this study was to (1) validate a novel 3D planning modality that incorporates the weight-bearing (WB) state (3D WB) by comparing it to existing modalities (3D non-weight-bearing (NWB), 2D WB) and (2) evaluate the influence of the modality (2D vs. 3D) and the WB condition on the measurements. Three different planning and deformity measurement protocols were analyzed in 19 legs that underwent medial open-wedge high tibial osteotomy (HTO): (1) a 3D WB protocol, after 2D/3D registration of 3D CT models onto the long-leg radiograph (LLR) (3D WB), (2) a 3D NWB protocol based on the 3D surface models obtained in the supine position (3D NWB), and (3) a 2D WB protocol based on the LLR (2D WB). The hip-knee-ankle angle (HKA), joint line convergence angle (JLCA), and the achieved surgical correction were measured for each modality and patient. All the measurement protocols demonstrated excellent intermodal agreement for the achieved surgical correction, with an ICC of 0.90 (95% CI: 0.76-0.96)) (p < 0.001). Surgical correction had a higher mean absolute difference compared to the 3D opening angle (OA) when measured with the WB protocols (3D WB: 2.7 ± 1.8°, 3D NWB: 1.9 ± 1.3°, 2D WB: 2.2 ± 1.3°), but it did not show statistical significance. The novel planning modality (3D WB) demonstrated excellent agreement when measuring the surgical correction after HTO compared to existing modalities.

Present results and methods of vectorcardiographic diagnostics of ischemic heart disease.

This article presents an overview of existing approaches to perform vectorcardiographic (VCG) diagnostics of ischemic heart disease (IHD). Individual methodologies are divided into categories to create a comprehensive and clear overview of electrical cardiac activity measurement, signal pre-processing, features extraction and classification procedures. An emphasis is placed on methods describing the electrical heart space (EHS) by several features extraction techniques based on spatiotemporal characteristics or signal modelling and signal transformations. Performance of individual methodologies are compared depending on classification of extent of ischemia, acute forms - myocardial infarction (MI) and myocardial scars localization. Based on a comparison of imaging methods, the advantages of VCG over the standard 12-leads ECG such as providing a 3D orthogonal leads imaging, better performance, and appropriate computer processing are highlighted. The issues of electrical cardiac activity measurements on body surface, the lack of VKG databases supported by a more accurate imaging method, possibility of comparison with the physiology of individual cases are outlined as potential reserves for future research.

Practice Reshapes the Geometry and Dynamics of Task-tailored Representations.

Extensive practice makes task performance more efficient and precise, leading to automaticity. However, theories of automaticity differ on which levels of task representations (e.g., low-level features, stimulus-response mappings, or high-level conjunctive memories of individual events) change with practice, despite predicting the same pattern of improvement (e.g., power law of practice). To resolve this controversy, we built on recent theoretical advances in understanding computations through neural population dynamics. Specifically, we hypothesized that practice optimizes the neural representational geometry of task representations to minimally separate the highest-level task contingencies needed for successful performance. This involves efficiently reaching conjunctive neural states that integrate task-critical features nonlinearly while abstracting over non-critical dimensions. To test this hypothesis, human participants (n = 40) engaged in extensive practice of a simple, context-dependent action selection task over 3 days while recording EEG. During initial rapid improvement in task performance, representations of the highest-level, context-specific conjunctions of task-features were enhanced as a function of the number of successful episodes. Crucially, only enhancement of these conjunctive representations, and not lower-order representations, predicted the power-law improvement in performance. Simultaneously, over sessions, these conjunctive neural states became more stable earlier in time and more aligned, abstracting over redundant task features, which correlated with offline performance gain in reducing switch costs. Thus, practice optimizes the dynamic representational geometry as task-tailored neural states that minimally tesselate the task space, taming their high-dimensionality.