Technical Variables Research Articles

Surgical Aspects of Sleeve Gastrectomy Are Related to Weight Loss and Gastro-esophageal Reflux Symptoms

IntroductionA large variation in outcome has been reported after sleeve gastrectomy (SG) across countries and institutions. We aimed to evaluate the effect of surgical technique on total weight loss (TWL) and gastro-esophageal reflux disease (GERD).MethodsObservational cohort study based on data from the national registries for bariatric surgery in the Netherlands, Norway, and Sweden. A retrospective analysis of prospectively obtained data from surgeries during 2015–2017 was performed based on 2-year follow-up. GERD was defined as continuous use of acid-reducing medication. The relationship between TWL, de novo GERD and operation technical variables were analyzed with regression methods.ResultsA total of 5927 patients were included. The average TWL was 25.6% in Sweden, 28.6% in the Netherlands, and 30.6% in Norway (p < 0.001 pairwise). Bougie size, distance from the resection line to the pylorus and the angle of His differed between hospitals. A minimized sleeve increased the expected total weight loss by 5–10 percentage points. Reducing the distance to the angle of His from 3 to just above 0 cm increased the risk of de novo GERD five-fold (from 3.5 to 17.8%).ConclusionSmaller bougie size, a shorter distance to pylorus and to the angle of His were all associated with greater weight loss, whereas a shorter distance to angle of His was associated with more de novo reflux.Graphical

SURVIVAL RATE OF IMPLANT-SUPPORTED, SINGLE-TOOTH RESTORATIONS BASED ON ZIRCONIA OR METAL ABUTMENT IN PATIENTS WITH TOOTH AGENESIS: A 5-YEARS PROSPECTIVE CLINICAL STUDY

Purpose: The primary aim was to investigate survival rate of zirconia versus metal abutments, and the secondary aim was clinical outcomes of all-ceramic versus metal-ceramic crowns on single-tooth implants. Material and Methods: Patients with tooth-agenesis participated to previously published prospective clinical study with three-year follow-up were recalled after five years. Biological variables included survival and success rate of implants, marginal bone level, modified Plaque and Sulcus Bleeding Index and biological complications. Technical variables included restoration survival rate, marginal adaptation and technical complications. The aesthetic outcome of crowns and peri-implant mucosa in addition to patient-reported outcome were recorded. Descriptive analysis, linear mixed model for quantitative data, or generalized linear mixed model for ordinal categorical data were applied; significance was set to 0.05. Results: Fifty-three patients (mean age: 32.4 years), with 89 implants participated to the 5-years examination. The implants supported 50 zirconia abutments with 50 all-ceramic (AC) crown and 39 metal abutments with 29 metal-ceramic (MC) and 10 AC crowns. Conclusions: Zirconia-based single-tooth restorations are reliable alternative materials to metal-based restorations with favorable biological and aesthetic outcome, and few technical complications.

Extended Kaya Identity for Primary and Secondary Material Production for Lithium-ion Batteries

Growing global affluence and the need to reduce the related environmental impacts lead to an increased use of high-tech products. From a life cycle perspective, environmental impacts are increasingly being shifted from the use stage towards the material production stage. The currently used Kaya identity enables a structured analysis of environmental impacts along a product life cycle and distinguishes between primary and secondary materials used. However, the origin of the impacts of material supply are presented in a very aggregated way as an average of all materials used which hinders a targeted engineering of material production processes. In this paper, we identify general technical variables with a high influence on environmental impacts and material quantity of primary and secondary material production for Lithium-ion batteries. The findings are used to extend the Kaya identity by technical variables such as process efficiencies, material specific recovery rates and material qualities for both primary and secondary material production. Further, we will guide the user to quantify the variables to promote further usage in industry. We present the extended Kaya identity exemplary for a current and future primary lithium production and a mechanical-hydrometallurgical recycling of spent Lithium-ion batteries. The results demonstrate the importance of considering process individual technical variables to assess the overall environmental impacts of a product system and to enable a target driven engineering of environmental hotspots.

Changes in physical and technical match performance variables in football players promoted from the Spanish Second Division to the First Division.

The aim of this study was to compare physical and technical match performance variables in football players who competed in the Spanish second division for one season and were promoted to the top (first) division in the following season. A total of 97 male outfield football players who were promoted from the second to the first division of the Spanish professional football league within the same team were analysed. Data were recorded using the TRACAB (ChyronHego, New York, USA) multicamera computerised optical tracking system during five seasons (2015-2016 to 2019-2020). A one-way ANOVA repeated measures analysis showed that players executed a greater number of high-intensity running (HIR) efforts (P < 0.001; ES: 0.258), as well as covering greater HIR distance (P < 0.010; ES: 0.106) and total running distance (TD) (P < 0.010; ES: 0.080), when they played in the first division compared with the second division. Moreover, players performed a lower number of passes (P < 0.01; ES = 0.116), short passes (P < 0.01; ES = 0.106), long passes (P < 0.05; ES = 0.067), dribbles (P < 0.001; ES = 0.146) and shots (P < 0.01; ES = 0.074) in the first division compared to the second division. No significant differences were found for any of the defensive variables evaluated. In conclusion, being promoted from the second to the first division of professional football requires players to adapt to greater physical demands and a reduced number of technical actions.

Effects of a 6-week on-court training program on the International Tennis Number (ITN) and a range of physical fitness characteristics in young tennis players.

The study aimed to (i) verify the effects of an on-court training program on the International Tennis Number (ITN) of young tennis players, as well as on a set of change of direction, linear sprint, and maximal oxygen uptake (VO2max) variables, and (ii) identify the main predictors of ITN. The sample consisted of 20 young male tennis players (mean age, 13.62 ± 0.23 years). Players underwent a 6-week on-court training program. The ITN and a number of change of direction variables (T-drill and repeated sprint ability), linear sprint (5 m, 10 m, and 20 m distances), and VO2max were measured. All variables improved significantly between the pre- and posttest (p < 0.001). The ITN (7.98 ± 6.06%, d = 0.82) and VO2max (6.77 ± 1.21%, d = 1.53) showed the greatest relative improvement with moderate to large effect sizes. The hierarchical linear model retained the time (estimate = 18.90, p < 0.001) and the T-drill (estimate = -64.77, p < 0.001) as significant predictors of the ITN. This indicates that the ITN improved significantly over the 6-week training program and that the T-drill test was the best and most significant predictor. Coaches and researchers are encouraged to monitor the ITN along with other physical fitness and technical variables. They can also use the T-drill test to understand the ITN of their players.

Optimizing the prediction of discard survival of bottom-trawled plaice based on vitality indicators.

Predicting the discard survival of aquatic animals after fisheries capture using vitality indicators (i.e. individual scores or indices of physical condition) is a resource-efficient approach compared to estimating discard survival from captive observation. But such indicators do not always lead to accurate and robust predictions. Individual scores of reflex impairments and injuries are typically given the same weight when being aggregated into an index, while some reflexes or injuries may contribute to mortality more than others. This study established an analytical methodology and created an index based on differential contributions of individual reflexes and injuries to optimize the prediction of discard survival of bottom-trawled European plaice (Pleuronectes platessa). The optimization procedures were applied to a dataset from vitality assessment of 1122 undersized plaice caught during 16 commercial fishing trips and 58 gear deployments in Belgium and Denmark. As welfare indicators, we considered and evaluated against post-capture survival of plaice: original vs. optimized reflex impairment and injury (R&I) index, number of absent reflexes, number of present injuries, number of absent reflexes and present injuries, categorical vitality score and individual reflex and injury scores. These were used in eight candidate generalized linear models (one without any vitality indicator) as explanatory variables to predict survival, with or without biological, environmental, technical and operational covariates, either at the individual fish or trip level. Bruising to the head and body were the most relevant predictors. The optimized R&I index did not perform better than any other vitality indicator, and all the indicators performed poorly in predicting survival probability both at the fish and trip levels without information on air exposure and seawater temperature. This means that they cannot be considered to be independent measures. The categorical vitality score provided a viable alternative to the more labour-intensive, scoring method of reflex responsiveness. Use of reflexes as proxies may not be accurate when they are not independent of environmental, biological or technical variables.

The influence of meteorological factors on the technical performance of football teams during matches.

This study explored the impact of the meteorological factors air temperature, relative humidity, and wind speed on teams' technical performance during the Union of European Football Associations Champions League (UCL). Technical match statistics were collected for five seasons (2016/2017-2020/2021). Thirty-one technical actions and events were categorized into three groups (goal scoring, offense, and defence). Meteorological data were collected from the official UEFA website (air temperature (°C): 11.59 ± 6.87, relative humidity (%): 71.40 ± 17.82, wind speed (km/h): 11.52 ± 7.02). LASSO regression analysis was employed to identify important indicators that affect match outcomes, while separate Poisson regression models were used in generalized linear modelling to determine the effects of meteorological factors on key technical performance indicators. The results revealed that offensive variables were instrumental in distinguishing match outcomes (winning, drawing, and losing), with meteorological factors significantly influencing these variables. Notably, "shot from counter attack" was the most significantly affected variable, being exclusively influenced by air temperature (OR = 0.55, 95% CI: 0.30 to 0.98). Two technical indicators, "dribbles won" and "shots from the 6-yard box," were both significantly influenced by two meteorological factors. "Cards per foul," an understudied variable, displayed a close association with all the three meteorological factors. These findings offer valuable insights for coaches and analysts in comprehending the influence of meteorological conditions on crucial technical variables during the performance evaluation of teams. Moreover, they provide valuable information to help coaches devise appropriate tactics for players before or during a match, considering the potential changes in meteorological conditions.

Clean energy stock price forecasting and response to macroeconomic variables: A novel framework using Facebook's Prophet, NeuralProphet and explainable AI

The clean energy market analysis has seen a strong surge in the post-Paris agreement owing to its undeniable environmental sustainability. The present work investigates the predictability of clean energy investment in the US market by selecting eight sectoral stock indices. The predictive exercise is carried out separately during pre-COVID-19 and COVID-19 timelines to draw key behavioral aspects of the underlying sectors. After scrutiny of previous research, we identify a set of technical and macroeconomic variables as explanatory constructs. We then utilize Facebook's Prophet and NeuralProphet to find future figures for the clean energy indices. Finally, Explainable Artificial Intelligence (XAI) is used to draw deeper insights into the contribution patterns of the constituent explanatory variables and obtain their relative importance. The findings suggest that the future movements of the sectoral clean energy assets can be predicted with a very high level of accuracy. Also, the predictability marginally improves during the COVID-19 pandemic despite the unprecedented uncertainty. Technical indicators appear to be the dominant features, while market sentiment and fear exert significant influence.

MsFfTsGP: Multi-source features-fused two-stage grade prediction of zinc tailings in lead-zinc flotation process via multi-stream 3D convolution with attention mechanism

The tailings grade is a crucial indicator for controlling and optimizing mineral flotation processes. However, detecting/predicting tailings grade online faces challenges due to intricate physicochemical reactions in three-phase slurries with the strongly-coupled characteristics of the technical process. This paper introduces a novel multi-source features-fused two-stage tailings grade prediction model called MsFfTsGP by integrating multiple-source froth image sequences (FISs) with available traditional technical variables (TTVs, e.g., the reagent dosage and measured grades) from multiple flotation cells, mimicking the on-site two-stage prediction mode of experienced operators. Namely, an initial evaluation is made based on the source-ore characteristics using the FISs of the first rougher, while the second stage provides a sophisticated prediction of the tailing grade by considering both the source-ore characteristics and the flotation behavior of the whole circuit process. Specifically, FISs captured from the first rougher are fed into a multi-stream 3D convolutional network (Ms3DCN) for making an initial prediction. Then, the initial prediction result is combined with the FIS information from the last scavenger (also processed by the Ms3DCN) and available TTVs based on the attention mechanism to make a sophisticated prediction. Extensive experiments on a real industrial lead-zinc flotation process demonstrated a significant improvement of the proposed model in prediction accuracies. Integrating multisource FISs with TTVs from multiple coupled flotation cells shows great potential for achieving accurate tailings grade prediction, making MsFfTsGP a promising tool for enhancing the control and optimization of flotation processes.

Plasma cell‐free RNA: a new non‐invasive biomarker for Parkinson’s disease

AbstractBackgroundParkinson’s disease (PD) is the second‐most common neurodegenerative disorder, after Alzheimer disease (AD). We aimed to create a model that can predict PD with high accuracy and specificity using plasma cell‐free RNA (cfRNA) data.MethodWe extracted RNA from 172 plasma samples (92 PD cases and 80 controls; 48% female, and median age of 73) received from the Hope Center for Neurological Disorders at Washington University in Saint Louis. After library preparation, sequencing, processing, and stringent quality control data was split into training (60%) and testing (40%) populations, both of which included 53% PD cases, 48% female, and had median age of 73. We then performed differential expression analyses using DESeq2, adjusting the by age, sex, medication and other technical variables. Following data driven identification of informative transcripts using Lasso regression, we used Ridge regression to model disease status.ResultWe identified and replicated 639 significantly dysregulated genes. Through pathway analyses we found that dysregulated genes were enriched in PD terms, as well as other neurodegenerative and in known mitochondria pathways. After predictive model training, the best model for PD in the testing population included 14 genes and had an Area Under the Receiving Operating Curve (AUC) of 0.963 (0.930, 0.996). The model had low predictive power, with AUC of 0.553 (0.421, 0.686), in differentiating between controls and AD, FTD or DLB, suggesting that it is specific to PD. More evidence of its specificity was the good performance in distinguishing between PD and AD, FTD or DLB with AUC of 0.753 (0.674, 0.833) specificity.ConclusionPlasma cfRNA is a powerful tool for PD prediction, being a minimally invasive biomarker that could detect PD before onset of physical symptoms and without relying on imaging data. We are working on replicating our results in an independent dataset.

Airport technical efficiency: Evidence of privatised airports in Latin America

Since the mid-1990s, the main airports in Latin America have been privatised. This is the result, on the one hand, of the liberalisation of the aviation industry in almost all the countries of the region, and on the other hand, of the application of an extensive and uninterrupted programme of air public policies, currently underway. Based on this, this paper first analyse how public policies have influenced the development of airports in Latin America, generating the privatisation of the most important in the region (in a context of structural reform still in progress). Second, it studies how the COVID-19 pandemic affected the technical efficiency of the privatised airports in the region. Therefore, in this paper, the measurement of technical efficiency is carried out (using only technical variables, that is, infrastructure and aeronautical or air traffic variables) on a representative set of Latin American privatised airports, both in the pre-pandemic period (2017–19) and in the severest pandemic period (2020). The methodology used to carry out the study is data envelopment analysis (DEA). The main results of the research reveal high, and in some cases ideal, technical efficiency indices in the pre-pandemic period, and not very severe drops in technical efficiency in the pandemic period.

A Program for Major Taper and its Effects on Some Technical Variables and Resisting Fatigue in 100m Front Crawl Swimmers

A Program for Major Taper and its Effects on Some Technical Variables and Resisting Fatigue in 100m Front Crawl Swimmers

Quantifying technical load and physical activity in professional soccer players during pre-season matches with IMU technology

This study aimed to record, analyze and quantify professional soccer players’ technical (TL) and physical load (PL) in friendly matches to compare their records during the first and second halves and between players with different positions. Eighteen professional soccer players, 24.6 ± 2.7 years, 1.78 ± 0.3 height (m), 74.6 ± 4.5 body mass (kg), 9.8 ± 2.2 body fat (%), and 65.6 ± 2.7 maximal oxygen consumption (VO2max, ml·kg-1·min-1) were monitored during six preseason friendly matches to analyze the activity profile using technical and physical variables through inertial measurement unit (IMU). No significant differences were found between the periods for the TL and PL. Significant differences were found between specific positions: Full Back (FB: n = 4), Central Defender (CD: n = 3), Midfielder (MD: n = 4), Winger (WG: n = 4), and Forward (FW: n = 3), both the TL and PL. We conclude that the PL profile based on his playing position is independent of the development of the PL shown during friendly matches. The monitoring, quantifying, and controlling of the TL added to the PL provides a more holistic vision of soccer players in friendly matches. The relative ease IMU application technology offers an alternative with less time-cost and more significant benefits than other types of technologies applied up to now.

Repurposing End-of-Life Coal Mines with Business Models Based on Renewable Energy and Circular Economy Technologies

This paper presents a methodology to select the most exciting business models based on renewable energy and circular economy technologies within end-of-life coal mines to help develop a renewable-based energy sector, promote sustainable local economic growth, and maximise the number of green and quality jobs. To achieve this goal, first, a structural analysis was developed to select the technical variables that better identify this complex system. Second, a morphological analysis allowed the construction of the scenario space. Third, a multicriteria assessment was developed to achieve this goal, based on the previously assessed relevant scenarios, considering the European Green Deal policies, technical variables that characterise end-of-life coal mine environments, technology readiness level, the European taxonomy, synergistic potentials, contributions to the circular economy, and sector coupling. Finally, result indicators were selected to analyse the alternative options derived from the justification approach, considering the targets set by the European Green Deal and related taxonomy and the regional policy indicators for the Just Transition Fund. The results show that eco-industrial parks with virtual power plants represent the most appropriate business model choice, according to the scoring given to the different aspects. They may be complemented by a hydrogen production plant, provided that specific economic subventions are obtained to achieve balanced financial results.

Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care.

It is important for older and disabled people who live alone to be able to cope with the daily challenges of living at home. In order to support independent living, the Smart Home Care (SHC) concept offers the possibility of providing comfortable control of operational and technical functions using a mobile robot for operating and assisting activities to support independent living for elderly and disabled people. This article presents a unique proposal for the implementation of interoperability between a mobile robot and KNX technology in a home environment within SHC automation to determine the presence of people and occupancy of occupied spaces in SHC using measured operational and technical variables (to determine the quality of the indoor environment), such as temperature, relative humidity, light intensity, and CO2 concentration, and to locate occupancy in SHC spaces using magnetic contacts monitoring the opening/closing of windows and doors by indirectly monitoring occupancy without the use of cameras. In this article, a novel method using nonlinear autoregressive Neural Networks (NN) with exogenous inputs and nonlinear autoregressive is used to predict the CO2 concentration waveform to transmit the information from KNX technology to mobile robots for monitoring and determining the occupancy of people in SHC with better than 98% accuracy.

Bone Marrow Microenvironment and Hematopoietic Cell Types Are Differentially Affected By Transcriptomic Quality Control Filtering Metrics in Single Cell Data

A crucial step prior to analysis of single cell transcriptomic data includes filtering out low-quality (e.g., dying) cells and artifacts (e.g., empty droplets). Choosing appropriate quality control parameters leads to correct cell assignment, so that the data for downstream analysis is high-quality and is representative of all processed cell types. These metrics include high and low cut-offs for mitochondrial content, total number of genes, number of different genes, and ribosomal content per cell. They have been found to vary based on cell and tissue type, as well biological variables such as age and disease, and technical variables such as sequencing technology. The aim of this study was to investigate the variation of these quality control metrics in a data set that included stem, progenitor, and differentiated cell types of the hematopoietic, mesenchymal, and endothelial lineages. Furthermore, we set out to determine whether applying standard cut-offs may differentially affect different cell types. We calculated individual filtering parameters for each cell type using the R package ddqc (Subramanian et al. Genome Biol. 2022). Thus, any biological variability based on mitochondrial, ribosomal, and gene counts was accounted for. Notably, distribution of measurements for each of the above quality control metrics varied by cluster, and certain cell-type means were adjacent to commonly used cut-off values. For instance, we observed higher content of mitochondrial genes in osteoblasts, sinusoidal endothelial cells, a subset of adipocyte-primed mesenchymal cells (MSPC), as well as hematopoietic progenitor cells, pre-B, and B cells. On the other hand, subsets of erythroblasts, neutrophils, as well as arteriolar endothelial cells had the lowest mitochondrial content. In addition, lower total gene counts and lower gene complexity were found in adipocyte-primed MSPCs, neutrophils, and megakaryocyte-erythrocyte progenitors, while higher counts were found in granulocyte-monocyte progenitor cells, megakaryocyte/erythroid-primed multipotent progenitor cells and subsets of erythroblasts. Applying universal cutoff values to this data set would greatly reduce, and some cases, eliminate cell types that have high mitochondrial content or lower gene counts and complexity, while leaving those cell types on the opposite spectrum unaffected. This would also skew proportions of cells in downstream analyses, thus affecting biological interpretation of the results. Overall, our results demonstrate biological variability of the quality control metric distributions in a single cell transcriptomic data set that includes diverse bone marrow niche and hematopoietic cell types. This reveals novel biological information regarding distinct cell types as well as cautions that applying standard filtering paraments on such a data set would eliminate some cell types and bias downstream analysis for others. Optimization of filtering criteria will be important when broadening single cell analysis to multiplexed approaches incorporating transcriptome, genome, epigenome, and proteome-level data.

Abstract 227: Combined Technique Versus Stent‐Retriever Alone: Angioarchitectural and Technical Analysis

Introduction Combined technique mechanical thrombectomy with contact aspiration with stent‐retriever has been shown to lead to comparable final reperfusion rates compared with stent retriever alone. We aimed to explore if anatomical and technical features could have interaction with the chances of reperfusion by each technique. Methods Retrospective analysis of a prospective mechanical thrombectomy (MT) database. Inclusion criteria: anterior circulation large vessel occlusion(LVO) due to carotid terminus or proximal MCA(M1) occlusion, first‐line stent‐retriever (SR) alone or combined technique (SR plus aspiration), and angiographic run with stent in place. The primary analysis was the interaction between clinical and angiographic characteristics and first‐line MT modality on first‐pass effect (FPE; first‐pass eTICI2c‐3). Secondary analyses aimed to evaluate predictors of FPE. Results A total of 150 patients were included in the analysis (SR alone,n=62 vs. combined technique, n=88). Demographics, vascular risk factors and NIHSS were comparable between groups. The SR group had higher IV‐tPA use (41.9%vs.26.1%,P=0.04), higher rates of FPE(64.5%vs.47.7%,P=0.04) but similar baseline ASPECTS, CTA collateral score, clot burden, as compared to the combined technique. Anatomical and technical variables (reperfusion channel, SR position in dominant MCA division, angle of interaction, diameter of stent proximal to clot, diameter of stent distal to clot, type of extracranial carotid or cavernous carotid tortuosity, clot length were comparable between both groups. None of the anatomical and technical factors were found to have an interaction with the modality (SR alone vs combined technique) on the chances of FPE (Pinteraction &gt;0.05)(Figure). FPE was observed in 54.6% of the entire cohort. Multivariable analysis showed that use of IV‐tPA(OR 156.5,95%CI 4.59‐5334.8,P=0.005), lower angle of interaction (OR 0.94,95%CI 0.89‐0.99,P=0.03), presence of reperfusion channel (OR 145.8,95%CI 1.96‐108277.4),P=0.02), higher clot burden score (OR 8.17,95%CI 1.38 ‐48.21,P=0.02), type‐3 cavernous ICA tortuosity (OR 0.001,95%CI 0‐0.23,P=0.01) were independently associated FPE. Conclusion We could not identify any anatomical or technical features that predisposed to a benefit in adding catheter aspiration to SR thrombectomy. IV r‐TPA, clot burden score, presence of reperfusion channel, type of cavernous carotid tortuosity, and angle of interaction were found independently associated with FPE. Large sample studies are warranted.

Firm Determinants that Influences Implementation of Accounting Technologies in Business Organizations

This research examined firm factors of accounting technology adoption in businesses. The research examines how technical, organizational, environmental, and owner-manager variables affect accounting technology deployment in businesses. The study used expos facto design as its research method. Every employee of hotel and tourism firms in the Amman Stock Exchange forms the population for the study. In order to get an accurate representation of the population, 76 respondents were selected for the study. The study found that technical, organisational, environmental, and owner/manager factors affect accounting technology adoption in businesses. The findings demonstrate and indicate that there is a significant effect of technical, organizational, environmental, and owner-manager variables on the implementation of accounting technology in business organizations. Based on the findings of the study, it was recommended that the creator of an e-accounting system should exploit the geographic concentration of businesses to their advantage by creating a locally made, affordably priced e-accounting system that can be deployed to businesses and used by several users with different preferences.

Separation performance evaluation of green crystallization technique: Model configuration and process design

Layer melt crystallization (LMC) is deemed a green separation technique and is widely used in the purification of crude chemical products. This work optimizes the separation of LMC based on process design and model configurations. Firstly, we monitor the central temperature with the crystal layer growth, where the temperature change can be divided into two stages. The main heat exchange and crystal growth occur in stage 1. Then we establish two kinetics models based on the temperature and concentration difference, to describe the features of crystal layer growth. Both kinetic models can successfully correlate the driving force and kinetic parameters. Further, the temperature effect and composition of the feed mixture on the separation performance are analyzed. The proposed separation coefficients accurately figure out the underlying correlations of the technical variables and target products. The optimized operating trajectory based on the model analyses and experiments is given to guide the separation process. Finally, four process intensification strategies are proposed to improve separation efficiency, where the incorporation of the stirring operation into LMC is more suitable for industrial production.

MRI-derived extracellular volume as a biomarker of cancer therapy cardiotoxicity: systematic review and meta-analysis

ObjectivesMRI-derived extracellular volume (ECV) allows characterization of myocardial changes before the onset of overt pathology, which may be caused by cancer therapy cardiotoxicity. Our purpose was to review studies exploring the role of MRI-derived ECV as an early cardiotoxicity biomarker to guide timely intervention.Materials and methodsIn April 2022, we performed a systematic search on EMBASE and PubMed for articles on MRI-derived ECV as a biomarker of cancer therapy cardiotoxicity. Two blinded researchers screened the retrieved articles, including those reporting ECV values at least 3 months from cardiotoxic treatment. Data extraction was performed for each article, including clinical and technical data, and ECV values. Pooled ECV was calculated using the random effects model and compared among different treatment regimens and among those who did or did not experience overt cardiac dysfunction. Meta-regression analyses were conducted to appraise which clinical or technical variables yielded a significant impact on ECV.ResultsOverall, 19 studies were included. Study populations ranged from 9 to 236 patients, for a total of 1123 individuals, with an average age ranging from 12.5 to 74 years. Most studies included patients with breast or esophageal cancer, treated with anthracyclines and chest radiotherapy. Pooled ECV was 28.44% (95% confidence interval, CI, 26.85−30.03%) among subjects who had undergone cardiotoxic cancer therapy, versus 25.23% (95%CI 23.31−27.14%) among those who had not (p = .003).ConclusionA higher ECV in patients who underwent cardiotoxic treatment could imply subclinical changes in the myocardium, present even before overt cardiac pathology is detectable.Clinical relevance statementThe ability to detect subclinical changes in the myocardium displayed by ECV suggests its use as an early biomarker of cancer therapy–related cardiotoxicity.Key Points• Cardiotoxicity is a common adverse effect of cancer therapy; therefore, its prompt detection could improve patient outcomes.• Pooled MRI-derived myocardial extracellular volume was higher in patients who underwent cardiotoxic cancer therapy than in those who did not (28.44% versus 25.23%, p = .003).• MRI-derived myocardial extracellular volume represents a potential early biomarker of cancer therapy cardiotoxicity.