How sediment dredging alters phosphorus dynamics in a lowland rural river?

China's lowland rural rivers are facing severe eutrophication problems due to excessive phosphorus (P) from anthropogenic activities. However, quantifying P dynamics in a lowland rural river is challenging due to its complex interaction with surrounding areas. A P dynamic model (River-P) was specifically designed for lowland rural rivers to address this challenge. This model was coupled with the Environmental Fluid Dynamics Code (EFDC) and the Phosphorus Dynamic Model for lowland Polder systems (PDP) to characterize P dynamics under the impact of dredging in a lowland rural river. Based on a two-year (2020-2021) dataset from a representative lowland rural river in the Lake Taihu Basin, China, the coupled model was calibrated and achieved a model performance (R2>0.59, RMSE<0.04 mg/L) for total P (TP) concentrations. Our research in the study river revealed that (1) the time scale for the effectiveness of sediment dredging for P control was ∼300 days, with an increase in P retention capacity by 74.8 kg/year and a decrease in TP concentrations of 23% after dredging. (2) Dredging significantly reduced P release from sediment by 98%, while increased P resuspension and settling capacities by 16% and 46%, respectively. (3) The sediment-water interface (SWI) plays a critical role in P transfer within the river, as resuspension accounts for 16% of TP imports, and settling accounts for 47% of TP exports. Given the large P retention capacity of lowland rural rivers, drainage ditches and ponds with macrophytes are promising approaches to enhance P retention capacity. Our study provides valuable insights for local environmental departments, allowing a comprehensive understanding of P dynamics in lowland rural rivers. This enable the evaluation of the efficacy of sediment dredging in P control and the implementation of corresponding P control measures.

The effect of fine grits and fine debris concentrations on the MLVSS/MLSS ratio of an activated sludge system.

This study embarks on an explorative investigation into the effects of typical concentrations and varying particle sizes of fine grits (FG, the involatile portion of suspended solids) and fine debris (FD, the volatile yet unbiodegradable fraction of suspended solids) within the influent on the mixed liquor volatile suspended solids (MLVSS)/mixed liquor suspended solids (MLSS) ratio of an activated sludge system. Through meticulous experimentation, it was discerned that the addition of FG or FD, the particle size of FG, and the concentration of FD bore no substantial impact on the pollutant removal efficiency (denoted by the removal rate of COD and ammonia nitrogen) under constant operational conditions. However, a notable decrease in the MLVSS/MLSS ratio was observed with a typical FG concentration of 20 mg/L, with smaller FG particle sizes exacerbating this reduction. Additionally, variations in FD concentrations influenced both MLSS and MLVSS/MLSS ratios; a higher FD concentration led to an increased MLSS and a reduced MLVSS/MLSS ratio, indicating FD accumulation in the system. A predictive model for MLVSS/MLSS was constructed based on quality balance calculations, offering a tool for foreseeing the MLVSS/MLSS ratio under stable long-term influent conditions of FG and FD. This model, validated using data from the BXH wastewater treatment plant (WWTP), showcased remarkable accuracy.

A novel animal model of symptomatic neuroma for assessing neuropathic pain.

INTRODUCTION: Following amputation, peripheral nerves lack distal targets for regeneration, often resulting in symptomatic neuromas and debilitating neuropathic pain. Animal models can establish a practical method for symptomatic neuroma formation for better understanding of neuropathic pain pathophysiology through behavioral and histological assessments. We created a clinically translatable animal model of symptomatic neuroma to mimic neuropathic pain in patients and assess sexual differences in pain behaviors. METHODS: Twenty-two male and female rats were randomly assigned to one of two experimental groups: (1) neuroma surgery, or (2) sham surgery. For the neuroma experimental group, the tibial nerve was transected in the thigh, and the proximal segment was placed under the skin for mechanical testing at the site of neuroma. For the sham surgery, rats underwent tibial nerve isolation without transection. Behavioral testing consisted of neuroma-site pain, mechanical allodynia, cold allodynia, and thermal hyperalgesia at baseline, and then weekly over 8 weeks. RESULTS: Male and female neuroma rats demonstrated significantly higher neuroma-site pain response compared to sham groups starting at weeks 3 and 4, indicating symptomatic neuroma formation. Weekly assessment of mechanical and cold allodynia among neuroma groups showed a significant difference in pain behavior compared to sham groups (p < 0.001). Overall, males and females did not display significant differences in their pain responses. Histology revealed a characteristic neuroma bulb at week 8, including disorganized axons, fibrotic tissue, Schwann cell displacement, and immune cell infiltration. CONCLUSION: This novel animal model is a useful tool to investigate underlying mechanisms of neuroma formation and neuropathic pain.

Preclinical human and murine models of hepatocellular carcinoma (HCC).

Hepatocellular carcinoma (HCC) is the most frequent liver cancer, which account for more than 90 % of all liver cancer cases. It is the fifth leading cause of cancer globally and the second leading cause of cancer-related mortality in men. The availability of competent HCC preclinical models is fundamental to the success of mechanistic studies, molecular target identification, and drug testing. However, there are challenges associated with the use of these models. In this review, we provided updates on various cell lines, animals, and human HCC models, their specific preclinic use and associated potential challenges. Overall, the understanding of the merits and demerits of a particular HCC model will improve model selection for various preclinical studies.

Fabrication, characterization and numerical validation of a novel thin-wall hydrogel vessel model for cardiovascular research based on a patient-specific stenotic carotid artery bifurcation.

In vitro vascular models, primarily made of silicone, have been utilized for decades for studying hemodynamics and supporting the development of implants for catheter-based treatments of diseases such as stenoses and aneurysms. Hydrogels have emerged as prominent materials in tissue-engineering applications, offering distinct advantages over silicone models for fabricating vascular models owing to their viscoelasticity, low friction, and tunable mechanical properties. Our study evaluated the feasibility of fabricating thin-wall, anatomical vessel models made of polyvinyl alcohol hydrogel (PVA-H) based on a patient-specific carotid artery bifurcation using a combination of 3D printing and molding technologies. The model's geometry, elastic modulus, volumetric compliance, and diameter distensibility were characterized experimentally and numerically simulated. Moreover, a comparison with silicone models with the same anatomy was performed. A PVA-H vessel model was integrated into a mock circulatory loop for a preliminary ultrasound-based assessment of fluid dynamics. The vascular model's geometry was successfully replicated, and the elastic moduli amounted to 0.31 ± 0.007 MPa and 0.29 ± 0.007 MPa for PVA-H and silicone, respectively. Both materials exhibited nearly identical volumetric compliance (0.346 and 0.342% mmHg-1), which was higher compared to numerical simulation (0.248 and 0.290% mmHg-1). The diameter distensibility ranged from 0.09 to 0.20% mmHg-1 in the experiments and between 0.10 and 0.18% mmHg-1 in the numerical model at different positions along the vessel model, highlighting the influence of vessel geometry on local deformation. In conclusion, our study presents a method and provides insights into the manufacturing and mechanical characterization of hydrogel-based thin-wall vessel models, potentially allowing for a combination of fluid dynamics and tissue engineering studies in future cardio- and neurovascular research.

Fractional order cancer model infection in human with CD8+ T cells and anti-PD-L1 therapy: simulations and control strategy.

In order to comprehend the dynamics of disease propagation within a society, mathematical formulations are essential. The purpose of this work is to investigate the diagnosis and treatment of lung cancer in persons with weakened immune systems by introducing cytokines ( I L 2 & I L 12 ) and anti-PD-L1 inhibitors. To find the stable position of a recently built system TCD I L 2 I L 12 Z, a qualitative and quantitative analysis are taken under sensitive parameters. Reliable bounded findings are ensured by examining the generated system's boundedness, positivity, uniqueness, and local stability analysis, which are the crucial characteristics of epidemic models. The positive solutions with linear growth are shown to be verified by the global derivative, and the rate of impact across every sub-compartment is determined using Lipschitz criteria. Using Lyapunov functions with first derivative, the system's global stability is examined in order to evaluate the combined effects of cytokines and anti-PD-L1 inhibitors on people with weakened immune systems. Reliability is achieved by employing the Mittag-Leffler kernel in conjunction with a fractal-fractional operator because FFO provide continuous monitoring of lung cancer in multidimensional way. The symptomatic and asymptomatic effects of lung cancer sickness are investigated using simulations in order to validate the relationship between anti-PD-L1 inhibitors, cytokines, and the immune system. Also, identify the actual state of lung cancer control with early diagnosis and therapy by introducing cytokines and anti-PD-L1 inhibitors, which aid in the patients' production of anti-cancer cells. Investigating the transmission of illness and creating control methods based on our validated results will both benefit from this kind of research.

Prognostic value of cardiopulmonary exercise test in patients with acute myocardial infarction after percutaneous coronary intervention.

To determine the independent risk factors of cardiopulmonary exercise test (CPET) parameters related to adverse prognostic events within 5 years in patients undergoing percutaneous coronary intervention (PCI) for acute myocardial infarction (AMI), and establish a prediction model for the occurrence of adverse events within 5 years to provide a reference for cardiac rehabilitation training. From August 2015 to December 2021, patients who underwent PCI for AMI and completed CPET within 1-2 weeks after surgery before discharge from the Department of Cardiovascular Medicine of Zhengzhou Central Hospital Affiliated to Zhengzhou University, Henan Provincial Hospital of Traditional Chinese Medicine, and Anyang District Hospital were selected as participants. Univariate and multivariate analyses were used to screen for independent risk factors associated with 5-year adverse events. Feature importance was interpreted using SHapley Additive exPlanations (SHAP), and a logistic regression model was established for prediction. A receiver operating characteristic (ROC) curve was constructed to evaluate the performance of the prediction model. Calibration was assessed by the Hosmer-Lemeshow test and the calibration curve. In total, 375 patients met the inclusion criteria. Based on whether adverse events occurred during the 5-year follow-up period, the patients were divided into two groups: the event group (n = 53) and the non-event group (n = 322). Peak oxygen uptake (peakVO2), carbon dioxide ventilation equivalent slope (VE/VCO2slop), and peak end-tidal carbon dioxide partial pressure (PETCO2) were three independent risk factors for re-acute myocardial infarction (re-AMI), heart failure (HF), and even death after PCI for AMI (P < 0.05). The SHAP plots demonstrated that the significant contributors to model performance were related to peakVO2, VE/VCO2slop, and PETCO2. The risk of adverse events was significantly reduced when the peakVO2 was ≥ 20 mL/kg/min and the VE/VCO2slop was < 33. The ROC curves of the three models were drawn, including the no-event and event groups, re-AMI group, and HF group, which performed well, with AUC of 0.894, 0.760, and 0.883, respectively. The Hosmer-Lemeshow test showed that the three models were a good fit (P > 0.05). The calibration curve of the three models was close to the ideal diagonal lines. CPET parameters can predict the prognosis of adverse events within 5 years after PCI in patients with AMI and provide a theoretical basis for cardiac rehabilitation training.

The neural representation of stereotype content.

Judgments about social groups are characterized by their position in a representational space defined by two axes, warmth and competence. We examined serial dependence (SD) in evaluations of warmth and competence while measuring participants' electroencephalographic (EEG) activity, as a means to address the independence between these two psychological axes. SD is the attraction of perceptual reports towards things seen in the recent past and has recently been intensely investigated in vision. SD occurs at multiple levels of visual processing, from basic features to meaningful objects. The current study aims to (1) measure whether SD occurs between non-visual objects, in particular social groups and (2) uncover the neural correlates of social group evaluation and SD using EEG. Participants' judgments about social groups such as "nurses" or "accountants" were serially dependent, but only when the two successive groups were close in representational space. The pattern of results argues in favor of a non-separability between the two axes, because groups nearby on one dimension but far on the other were not subject to SD, even though that other dimension was irrelevant to the task at hand. Using representational similarity analysis, we found a brain signature that differentiated social groups as a function of their position in the representational space. Our results thus argue that SD may be a ubiquitous cognitive phenomenon, that social evaluations are serially dependent, and that reproducible neural signatures of social evaluations can be uncovered.

Promoting safety of underground machinery operators through participatory ergonomics and fuzzy model analysis to foster sustainable mining practices.

One of the most vital parameters to achieve sustainability in any field is encompassing the Occupational Health and Safety (OHS) of the workers. In mining industry where heavy earth moving machineries are largely employed, ergonomic hazards turn out to be significant OHS hazards causing Musculoskeletal Disorders (MSDs) in the operators. Nevertheless, the Indian mining industry lacks a comprehensive technique of OHS risk assessment, especially for ergonomic hazards that cause MSDs. This research appraises ergonomic hazards and develops Fuzzy Musculoskeletal-disorders Index (FMI) model to evaluate ergonomic-related MSDs. Work process and work tool ergonomic risk factors were identified through literature review and directives recommended by experts. Work posture was evaluated using RULA. The data-collecting approach was implemented using participatory ergonomic and design science principles. The FMI results show average MSDs score of 3.69, indicating high to extremely high risk. Surface plots show that combined work tool and work process was the most sensitive factors to MSDs risk compared to other two combinations. A two-sample t-test validated the FMI. The findings should help safety experts and managers develop effective OHS management plans and programmes for the sustainability of Indian mining industry.

Diagnosis of forme fruste keratoconus with scheimpflug photography in Ghanaian patients.

AIM: This study aimed to differentiate moderate to high myopic astigmatism from forme fruste keratoconus using Pentacam parameters and develop a predictive model for early keratoconus detection. METHODS: We retrospectively analysed 196 eyes from 105 patients and compared Pentacam variables between myopic astigmatism (156 eyes) and forme fruste keratoconus (40 eyes) groups. Receiver operating characteristic curve analysis was used to determine the optimal cut-off values, and a logistic regression model was used to refine the diagnostic accuracy. RESULTS: Statistically significant differences were observed in most Pentacam variables between the groups (p < 0.05). Parameters such as the Index of Surface Variance (ISV), Keratoconus Index (KI), Belin/Ambrosio Deviation Display (BAD_D) and Back Elevation of the Thinnest Corneal Locale (B.Ele.Th) demonstrated promising discriminatory abilities, with BAD_D exhibiting the highest Area under the Curve. The logistic regression model achieved high sensitivity (92.5%), specificity (96.8%), accuracy (95.9%), and positive predictive value (88.1%). CONCLUSION: The simultaneous evaluation of BAD_D, ISV, B.Ele.Th, and KI aids in identifying forme fruste keratoconus cases. Optimal cut-off points demonstrate acceptable sensitivity and specificity, emphasizing their clinical utility pending further refinement and validation across diverse demographics.

The strongest predictors of compliance with health protocols among marketers and guilds based on the transtheoretical model.

BACKGROUND: Global communication, an integral part of modern life, increases the risk of transmitting infectious diseases to individuals. Based on the transtheoretical model (TTM), this study aimed to identify the most effective factors in adherence to health protocols among marketers and guilds. METHODS: This cross-sectional study was conducted among 400 market sellers and guilds of Ardabil City, Iran, in 2023. The TTM questionnaire was distributed among the participants which included four sub-constructs: (1) stages of change, (2) process of change, (3) self-efficacy, and (4) decisional balance. The data were analyzed using SPSS version 20. One-way ANOVA and linear regression tests were employed to evaluate the prediction of effective factors of the stage transition. RESULTS: Most participants (63.5%) were between 21 and 40. Most participants (65.5%) were in the passive stages of change (precontemplation, contemplation, and preparation). Pros (ß = 0.133, P < 0.001) and behavioral processes of change (ß = 0.058, P < 0.001) were the strongest predictors of the stage of change or improvement of stages of participants' willingness to follow health protocols. CONCLUSION: A correct understanding of the stages of behavior change can strengthen strategies for promoting healthy behaviors. Also, understanding the benefits of healthy behavior means compliance with health protocols and behavioral processes such as stimulus control, reinforcement management, counterconditioning, and self-liberation, along with high self-efficacy, have an impact on improving the stages of behavior change.

Development and validation of a model to predict ceiling of care in COVID-19 hospitalized patients.

BACKGROUND: Therapeutic ceiling of care is the maximum level of care deemed appropiate to offer to a patient based on their clinical profile and therefore their potential to derive benefit, within the context of the availability of resources. To our knowledge, there are no models to predict ceiling of care decisions in COVID-19 patients or other acute illnesses. We aimed to develop and validate a clinical prediction model to predict ceiling of care decisions using information readily available at the point of hospital admission. METHODS: We studied a cohort of adult COVID-19 patients who were hospitalized in 5 centres of Catalonia between 2020 and 2021. All patients had microbiologically proven SARS-CoV-2 infection at the time of hospitalization. Their therapeutic ceiling of care was assessed at hospital admission. Comorbidities collected at hospital admission, age and sex were considered as potential factors for predicting ceiling of care. A logistic regression model was used to predict the ceiling of care. The final model was validated internally and externally using a cohort obtained from the Leeds Teaching Hospitals NHS Trust. The TRIPOD Checklist for Prediction Model Development and Validation from the EQUATOR Network has been followed to report the model. RESULTS: A total of 5813 patients were included in the development cohort, of whom 31.5% were assigned a ceiling of care at the point of hospital admission. A model including age, COVID-19 wave, chronic kidney disease, dementia, dyslipidaemia, heart failure, metastasis, peripheral vascular disease, chronic obstructive pulmonary disease, and stroke or transient ischaemic attack had excellent discrimination and calibration. Subgroup analysis by sex, age group, and relevant comorbidities showed excellent figures for calibration and discrimination. External validation on the Leeds Teaching Hospitals cohort also showed good performance. CONCLUSIONS: Ceiling of care can be predicted with great accuracy from a patient's clinical information available at the point of hospital admission. Cohorts without information on ceiling of care could use our model to estimate the probability of ceiling of care. In future pandemics, during emergency situations or when dealing with frail patients, where time-sensitive decisions about the use of life-prolonging treatments are required, this model, combined with clinical expertise, could be valuable. However, future work is needed to evaluate the use of this prediction tool outside COVID-19.

Development of a novel approach for restoration of the meniscus using silk-elastin in a rabbit meniscus injury model.

BACKGROUND: Limited healing potential of the meniscus remains a burden for the successful repair of meniscus injuries in the orthopaedic fields. Silk-elastin (SE) is a novel recombinant protein with favorable properties for wound healing. This proof-of-concept study aimed to investigate the therapeutic effect of silk-elastin in a rabbit meniscal defect model. METHODS: A migration assay using rabbit meniscus and synovial cells with various concentrations of SE in a culture medium was conducted to investigate the mechanism of meniscal healing by SE. Additionally, cylindrical defects with a 1.5 mm diameter were created at the anterior horn of the medial meniscus of rabbits. The animals were divided into three groups: 1) the Blank group; defect only, 2) the Col I group; implantation of type I atelocollagen sponge, and 3) the SE group; implantation of SE (150 mg/ml) sponge. Whole medial menisci were harvested at 4, 8, 12, and 24 weeks after surgery. Histological analyses including immunohistochemical staining were performed to assess meniscal healing. RESULTS: In vitro study, Migration assay demonstrated a significantly higher number of migrated cells only in synovial cells. Especially, the SE concentration of 10 µg/mL demonstrated the highest number of migrated cells compared with other concentrations. In vivo study, the SE group exhibited significantly higher Ishida scores than other groups at all time points. Furthermore, the SE group showed higher synovial coverage scores than the Col I group at 4 and 8 weeks. Immunohistochemical staining demonstrated higher type II collagen staining in the SE group compared to other groups at 12 weeks. Implanted SE was efficiently replaced by safranin-O staining positive tissue within 8 weeks. CONCLUSIONS: SE could effectively repair a meniscal defect by inducing coverage of synovial cells. SE has the potential to be a useful material for meniscal repair.

A study predicting long-term survival capacity in postoperative advanced gastric cancer patients based on MAOA and subcutaneous muscle fat characteristics.

BACKGROUND: The prognosis of advanced gastric cancer (AGC) is relatively poor, and long-term survival depends on timely intervention. Currently, predicting survival rates remains a hot topic. The application of radiomics and immunohistochemistry-related techniques in cancer research is increasingly widespread. However, their integration for predicting long-term survival in AGC patients has not been fully explored. METHODS: We Collected 150 patients diagnosed with AGC at the Affiliated Zhongshan Hospital of Dalian University who underwent radical surgery between 2015 and 2019. Following strict inclusion and exclusion criteria, 90 patients were included in the analysis. We Collected postoperative pathological specimens from enrolled patients, analyzed the expression levels of MAOA using immunohistochemical techniques, and quantified these levels as the MAOAHScore. Obtained plain abdominal CT images from patients, delineated the region of interest at the L3 vertebral body level, and extracted radiomics features. Lasso Cox regression was used to select significant features to establish a radionics risk score, convert it into a categorical variable named risk, and use Cox regression to identify independent predictive factors for constructing a clinical prediction model. ROC, DCA, and calibration curves validated the model's performance. RESULTS: The enrolled patients had an average age of 65.71 years, including 70 males and 20 females. Multivariate Cox regression analysis revealed that risk (P = 0.001, HR = 3.303), MAOAHScore (P = 0.043, HR = 2.055), and TNM stage (P = 0.047, HR = 2.273) emerged as independent prognostic risk factors for 3-year overall survival (OS) and The Similar results were found in the analysis of 3-year disease-specific survival (DSS). The nomogram developed could predict 3-year OS and DSS rates, with areas under the ROC curve (AUCs) of 0.81 and 0.797, respectively. Joint calibration and decision curve analyses (DCA) confirmed the nomogram's good predictive performance and clinical utility. CONCLUSION: Integrating immunohistochemistry and muscle fat features provides a more accurate prediction of long-term survival in gastric cancer patients. This study offers new perspectives and methods for a deeper understanding of survival prediction in AGC.

Longitudinal relations between child emotional difficulties and parent-child closeness: a stability and malleability analysis using the STARTS model.

BACKGROUND: Past empirical evidence on the longitudinal relations between emotional mental health symptoms and parent-child close relationships has produced mixed and inconclusive results. Some studies suggest a unidirectional relation, whereas other studies point toward a bidirectional association. Additionally, most of the past research has been carried out with adolescent samples, rather than children. Hence, this study aimed to estimate the longitudinal relations between children's trait emotional difficulties and trait parent-child closeness, accounting for the time-invariant and time-varying state components of each factor. METHODS: Participants were 7,507 children (ages 3 years, 5 years, 7 years, and 9 years) from the Growing Up in Ireland cohort. Α bivariate stable trait, autoregressive trait, and state (STARTS) model was estimated using Bayesian structural equation modelling. RESULTS: The STARTS model revealed that children's emotional difficulties and parent-child closeness were relatively stable across time, and these overarching traits were strongly negatively correlated. Children's earlier trait emotional difficulties predicted later trait parent-child closeness and vice versa between 3 years and 5 years, and between 5 years and 7 years, but these effects disappeared between 7 years and 9 years. At all pairs of time points, state emotional difficulties and state parent-child closeness were weakly negatively correlated. CONCLUSIONS: Overall, the results suggest that early and middle childhood are critical stages for improving parent-child relationships and reducing children's emotional difficulties. Developing close parent-child relationships in childhood appears to be a key factor in reducing children's subsequent emotional difficulties. Children who face greater than usual emotional difficulties tend to be more withdrawn and less receptive to close parent-child relationships and this could serve as an important screening indicator.

Multiply robust estimation of marginal structural models in observational studies subject to covariate-driven observations.

Electronic health records and other sources of observational data are increasingly used for drawing causal inferences. The estimation of a causal effect using these data not meant for research purposes is subject to confounding and irregularly-spaced covariate-driven observation times affecting the inference. A doubly-weighted estimator accounting for these features has previously been proposed that relies on the correct specification of two nuisance models used for the weights. In this work, we propose a novel consistent multiply robust estimator and demonstrate analytically and in comprehensive simulation studies that it is more flexible and more efficient than the only alternative estimator proposed for the same setting. It is further applied to data from the Add Health study in the United States to estimate the causal effect of therapy counseling on alcohol consumption in American adolescents.

Human EWS-FLI protein levels and neomorphic functions show a complex, function-specific dose-response relationship in Drosophila.

Ewing sarcoma (EwS) is a cancer that arises in the bones and soft tissues, typically driven by the Ewing's sarcoma breakpoint region 1-Friend leukemia virus integration 1 (EWS-FLI) oncogene. Implementation of genetically modified animal models of EwS has proved difficult largely owing to EWS-FLI's high toxicity. The EWS-FLI1FS frameshift variant that circumvents toxicity but is still able to perform key oncogenic functions provided the first study model in Drosophila. However, the quest for Drosophila lines expressing full-length, unmodified EWS-FLI remained open. Here, we show that EWS-FLI1FS's lower toxicity is owed to reduced protein levels caused by its frameshifted C-terminal peptide, and report new strategies through which we have generated Drosophila lines that express full-length, unmodified EWS-FLI. Using these lines, we have found that the upregulation of transcription from GGAA-microsatellites (GGAAµSats) presents a positive linear correlation within a wide range of EWS-FLI protein concentrations. In contrast, rather counterintuitively, GGAAµSats-independent transcriptomic dysregulation presents relatively minor differences across the same range, suggesting that GGAAµSat-dependent and -independent transcriptional upregulation present different kinetics of response with regards to changing EWS-FLI protein concentration. Our results underpin the functional relevance of varying EWS-FLI expression levels and provide experimental tools to investigate, in Drosophila, the effect of the EWS-FLI 'high' and 'low' states that have been reported and are suspected to be important for EwS in humans.

SingleCellGGM enables gene expression program identification from single-cell transcriptomes and facilitates universal cell label transfer.

Gene co-expression analysis of single-cell transcriptomes, aiming to define functional relationships between genes, is challenging due to excessive dropout values. Here, we developed a single-cell graphical Gaussian model (SingleCellGGM) algorithm to conduct single-cell gene co-expression network analysis. When applied to mouse single-cell datasets, SingleCellGGM constructed networks from which gene co-expression modules with highly significant functional enrichment were identified. We considered the modules as gene expression programs (GEPs). These GEPs enable direct cell-type annotation of individual cells without cell clustering, and they are enriched with genes required for the functions of the corresponding cells, sometimes at levels greater than 10-fold. The GEPs are conserved across datasets and enable universal cell-type label transfer across different studies. We also proposed a dimension-reduction method through averaging by GEPs for single-cell analysis, enhancing the interpretability of results. Thus, SingleCellGGM offers a unique GEP-based perspective to analyze single-cell transcriptomes and reveals biological insights shared by different single-cell datasets.

Theory of Moiré Magnetism and Multidomain Spin Textures in Twisted Mott Insulator-Semimetal Heterobilayers.

Motivated by the recent experimental developments in van der Waals heterostructures, we investigate the emergent magnetism in Mott insulator-semimetal moiré superlattices by deriving effective spin models and exploring their phase diagram by Monte Carlo simulations. Our analysis indicates that the stacking-dependent interlayer Kondo interaction can give rise to different types of magnetic order, forming domains within the moiré unit cell. In particular, we find that the AB (AA) stacking regions tend to order (anti)ferromagnetically for an extended range of parameters. The remaining parts of the moiré unit cell form ferromagnetic chains that are coupled antiferromagnetically. We show that the decay length of the Kondo interaction can control the extent of these phases. Our results highlight the importance of stacking-dependent interlayer exchange and the rich magnetic spin textures that can be obtained in van der Waals heterostructures.

Quantification of anatomical aortic valve area by multi-detector computed tomography: A pilot 3D-morphological modeling of the stenotic aortic valve.

BACKGROUND: Aortic-valve-stenosis (AS) is a frequent degenerative valvular-disease and carries dismal outcome under-medical-treatment. Transvalvular pressure gradient reflects severity of the valve-disease but is highly dependent on flow-conditions and on other valvular/aortic characteristics. Alternatively, aortic-valve-area (AVA) represents a measure of aortic-valve lesion severity conceptually essential and practically widely-recognized but exhibits multiple-limitations. METHODS: We analyzed the 4D multi-detector computed tomography(MDCT) of 20 randomly selected patients with severe AS. For each-patient, we generated the 3D-model of the valve and of its calcifications, and we computed the anatomical AVA accounting for the 3D-morphology of the leaflets in three-different-ways. Finally, we compared our results vs. Doppler-based AVAE measurements and vs. 2D-planimetric AVA-measurements. RESULTS: 3D-reconstruction and identification of the cusps were successful in 90% of the cases. The calcification patterns where highly-variable over patients, ranging from multiple small deposits to wide and c-shaped deposits running from commissure-to-commissure. AVAE was 82 ± 15 mm2. When segmenting 18 image planes, AVATight, AVAProj-Ann, AVAProj-Tip and their average AVAAve were equal to 80 ± 16, 88 ± 20, 93 ± 21 and 87 ± 19 mm2, respectively, while AVAPlan was equal to 143 ± 50 mm2. Linear-regression of the three measurements vs. AVAE yielded regression slopes equal to 1.26, 1.13 and 0.93 for AVAProj-Ann, AVAProj-Tip and AVATight, respectively. The respective Pearson-coefficients were 0.85,0.86 and 0.90. Conversely, when comparing AVAPlan vs. AVAE, linear regression yielded a slope of 1.73 and a Pearson coefficient of 0.53. CONCLUSIONS: We described a new-method to obtain a set of flow-independent quantifications that complement pressure gradient measurements and combine the advantages of previously proposed methods, while bypassing the corresponding-limitations.