julilili42/papers huggingface dataset:
Diagnostics of quantum-gate coherences deteriorated by unitary errors via end-point-measurement statistics
2023-08-22

Abstract Quantum coherence is a central ingredient in quantum physics with several theoretical and technological ramifications. We consider a figure of merit encoding the information on how the coherence generated on average by a quantum gate is affected by unitary errors (coherent noise sources) in the form of rotation-angle and rotation-axis errors. We provide numerical evidences that such information is well captured by the statistics of local energy measurements on the output states of the gate. These findings are then corroborated by experimental data taken in a quantum optics setting.
Modified dipole-dipole interactions in the presence of a nanophotonic waveguide
2023-08-22

When an emitter ensemble interacts with the electromagnetic field, dipole-dipole interactions are induced between the emitters. The magnitude and shape of these interactions are fully determined by the specific form of the electromagnetic field modes. If the emitters are placed in the vicinity of a nanophotonic waveguide, such as a cylindrical nanofiber, the complex functional form of these modes makes the analytical evaluation of the dipole-dipole interaction cumbersome and numerically costly. In this work, we provide a full detailed description of how to successfully calculate these interactions, outlining a method that can be easily extended to other environments and boundary conditions. Such exact evaluation is of importance as, due to the collective character of the interactions and dissipation in this kind of systems, any small modification of the interactions may lead to dramatic changes in experimental observables, particularly as the number of emitters increases. We illustrate this by calculating the transmission signal of the light guided by a cylindrical nanofiber in the presence of a nearby chain of emitters.
Lasting response by vertical inhibition with cetuximab and trametinib inKRAS‐mutated colorectal cancer patient‐derived xenografts
2023-08-22

Although approximately half of all metastatic colorectal cancers (mCRCs) harbour mutations in KRAS or NRAS , hardly any progress has been made regarding targeted treatment for this group over the last few years. Here, we investigated the efficacy of vertical inhibition of the RAS‐pathway by targeting epidermal growth factor receptor (EGFR) and mitogen‐activated protein kinase kinase (MEK) in patient‐derived xenograft (PDX) tumours with primary KRAS mutation. In total, 19 different PDX models comprising 127 tumours were tested. Responses were evaluated according to baseline tumour volume changes and graded as partial response (PR; ≤ − 30%), stable disease (SD; between −30% and +20%) or progressive disease (PD; ≥ + 20%). Vertical inhibition with trametinib and cetuximab induced SD or PR in 74% of analysed models, compared to 24% by monotherapy with trametinib. In cases of PR by vertical inhibition (47%), responses were lasting (as long as day 137), with a low incidence of secondary resistance (SR). Molecular analyses revealed that primary and SR was driven by transcriptional reprogramming activating the RAS pathway in a substantial fraction of tumours. Together, these preclinical data strongly support the translation of this combination therapy into clinical trials for CRC patients.
Amantadine for NeuroenhaNcement in acutE patients Study - a protocol for a prospective pilot proof of concept phase IIb study in intensive and intermediate care unit patients (ANNES)
2023-08-22

Abstract Background Persisting coma is a common complication in (neuro)intensive care in neurological disease such as acute ischemic stroke, intracerebral hemorrhage or subarachnoid hemorrhage. Amantadine acts as a nicotinic receptor antagonist, dopamine receptor agonist and non-competitive N-Methyl-D-aspartate receptor antagonist. Amantadine is a long-known drug, originally approved for treatment of influenza A and Parkinson`s Disease. It has been proven effective in improving vigilance after traumatic brain injury. The underlying mechanisms remain largely unknown, albeit anti-glutamatergic and dopaminergic effects might be most relevant. With limited evidence of amantadine efficacy in non-traumatic pathologies, the aim of our study is to assess the effects of amantadine for neuroenhancement in non-traumatic neurointensive patients with persisting coma. Methods An investigator-initiated, monocenter, phase IIb proof of concept open-label pilot study will be carried out. Based on the Simon design, 43 adult (neuro)intensive care patients who meet the clinical criteria of persisting coma not otherwise explained and &lt; 8 points on the Glasgow Coma Scale (GCS) will be recruited. Amantadine will be administered intravenously for five days at a dosage of 100 mg bid. The primary endpoint is an improvement of at least 3 points on the GCS. If participants present as non-responders (increase &lt; 3 points or decrease on the GCS) within the first 48 h, the dosage will be doubled from day three to five. Secondary objectives aim to demonstrate that amantadine improves vigilance via alternative scales. Furthermore, the incidence of adverse events will be investigated and electroencephalography (EEG) will be recorded at baseline and end of treatment. Discussion The results of our study will help to systematically assess the clinical utility of amantadine for treatment of persisting coma in non-traumatic brain injury. We expect that, in the face of only moderate treatment risk, a relevant number of patients will benefit from amantadine medication by improved vigilance (GCS increase of at least 3 points) finally leading to a better rehabilitation potential and improved functional neurological outcome. Further, the EEG data will allow evaluation of brain network states in relation to vigilance and potentially outcome prediction in this study cohort. Trial Registration NCT05479032.
Intranasal Delivery of the Oncolytic Adenovirus XVir-N-31 via Optimized Shuttle Cells Significantly Extends the Survival of Glioblastoma Bearing Mice
2023-08-22

Glioblastoma (GBM) is an aggressive and lethal primary brain tumor with restricted treatment options and a dismal prognosis. Oncolytic virotherapy (OV) has developed as a promising approach for GBM treatment. However, reaching invasive GBM cells may be hindered by tumor-surrounding, non-neoplastic cells when the OV is applied intratumorally. In this study, using a rodent GBM model and immunofluorescence analyses, we investigated the intranasal delivery of the oncolytic adenovirus (OAV) XVir-N-31 via virus-loaded, optimized shuttle cells. Intranasal administration (INA) was selected due to its non-invasive nature and the potential to bypass the blood-brain barrier (BBB). Our findings demonstrate that INA of XVir-N-31 loaded shuttle cells successfully delivers OAVs to the core tumor and invasive GBM cells, significantly prolongs the survival of GBM bearing mice, induces immunogenic cell death and finally reduces tumor burden, all this highlighting the therapeutic potential of this innovative approach. Overall, this study provides compelling evidence for the effectiveness of INA of XVir-N-31 via shuttle cells as a promising therapeutic strategy for GBM. The non-invasive nature of INA of OV-loaded shuttle cells holds great promise for future clinical translation. However, further research is required to assess the efficacy of this approach to ultimately progress in human clinical trials.
Parameter Estimation of KST-IRT Model under Local Dependence
2023-08-22

A mantra often repeated in the introductory material to psychometrics and Item Response Theory (IRT) is that a Rasch model is a probabilistic version of a Guttman scale. The idea comes from the observation that a sigmoidal item response function provides a probabilistic version of the characteristic function that models an item response in the Guttman scale. It appears, however, more difficult to reconcile the assumption of local independence, which traditionally accompanies the Rasch model, with the item dependence existing in a Guttman scale. In recent work, an alternative probabilistic version of a Guttman scale was proposed, combining Knowledge Space Theory (KST) with IRT modeling, here referred to as KST-IRT. The present work has, therefore, a two-fold aim. Firstly, the estimation of the parameters involved in KST-IRT models is discussed. More in detail, two estimation methods based on the Expectation Maximization (EM) procedure are suggested, i.e., Marginal Maximum Likelihood (MML) and Gibbs sampling, and are compared on the basis of simulation studies. Secondly, for a Guttman scale, the estimates of the KST-IRT models are compared with those of the traditional combination of the Rasch model plus local independence under the interchange of the data generation processes. Results show that the KST-IRT approach might be more effective in capturing local dependence as it appears to be more robust under misspecification of the data generation process, but it comes with the price of an increased number of parameters.
Factorial state-space modelling for kinetic clustering and lineage inference
2023-08-22

Abstract Single-cell RNA sequencing (scRNAseq) protocols measure the abundance of expressed transcripts for single cells. Gene expression profiles of cells (cell-states) represent the functional properties of the cell and are used to cluster cell-states that have a common functional identity (cell-type). Standard clustering methods for scRNAseq data perform hard clustering based on KNN graphs. This approach implicitly assumes that variation among cell-states within a cluster does not correspond to changes in functional properties. Differentiation is a directed process of transitions between cell-types via gradual changes in cell-states over the course of the process. We propose a latent state-space Markov model that utilises cell-state transitions derived from RNA velocity to model differentiation as a sequence of latent state transitions and to perform soft kinetic clustering of cell-states that accommodates the transitional nature of cells in a differentiation process. We applied this model to the differentiation of Radial-glia cells into mature neurons and demonstrate the utility of our method in discriminating between functional and transitional cell-states.
Finding the Optimal Number of Persons ( N ) and Time Points ( T ) for Maximal Power in Dynamic Longitudinal Models Given a Fixed Budget
2023-08-22

Planning longitudinal studies can be challenging as various design decisions need to be made. Often, researchers are in search for the optimal design that maximizes statistical power to test certain parameters of the employed model. We provide a user-friendly Shiny app OptDynMo available at https://shiny.psychologie.hu-berlin.de/optdynmo that helps to find the optimal number of persons (N) and the optimal number of time points (T) for which the power of the likelihood ratio test (LRT) for a model parameter is maximal given a fixed budget for conducting the study. The total cost of the study is computed from two components: the cost to include one person in the study and the cost for measuring one person at one time point. Currently supported models are the cross-lagged panel model (CLPM), factor CLPM, random intercepts cross-lagged panel model (RI-CLPM), stable trait autoregressive trait and state model (STARTS), latent curve model with structured residuals (LCM-SR), autoregressive latent trajectory model (ALT), and the latent change score model (LCS).
Analysing the longitudinal course selection panel data (2014-2020) of K-12 teachers from Zhejiang province: a comprehensive study on in-service training needs
2023-08-22

ABSTRACTEffective teacher training programs rely on accurate need analysis. However, traditional data sources often limit the comprehensive understanding of teachers’ and stakeholders’ needs. This study examines panel data comprising K-12 teachers’ course selections from 2014 to 2020 on the management platform of Zhejiang Province, China. Employing quantitative analysis techniques such as word frequency, co-occurrence, variability, and regression analysis on the corpus of teacher training, this paper explores the significance of these analyses in understanding training needs. The results reveal significant patterns in word frequency, co-occurrence, difference, and regression analyses, aligning with previous studies. Based on these findings, we propose that training topics should address education reform, meeting the needs of government and school leaders. Additionally, training methods should integrate theory and practice to cater to the needs of training designers, and training programs should aim to enhance teachers’ teaching abilities. This paper contributes to the existing literature on training needs analysis, showcasing how the integration of teacher education and corpus linguistics expands cross-disciplinary research and addresses the issue of drawing unreliable conclusions from limited evidence. The research findings offer valuable insights to stakeholders.KEYWORDS: Training needspanel datalongitudinal studycorpus AcknowledgmentsThis work was supported by the education project in the National Social Science Fund of China [Grant number BAA200019]. We would like to express gratitude to Dr. Liao Qing and Professor Ma Xiangjuan who offered proof reading and editing the article.Disclosure statementNo potential conflict of interest was reported by the author(s).DeclarationWe declare that This manuscript has not been published or presented elsewhere in part or in entirety and is not under consideration by another journal.Author contributionsLiu Yi (Ph.D, Assistant Professor): Conceptualization, Formal analysis, Methodology, Project administration, Resources, Writing – original draft, Writing – review & editing.Yan Yajun (Ph.D, Professor): Funding acquisition, Investigation.Xia Huixian (Ph.D, Professor): Supervision, Project administration.Sun Kun(Ph.D, Assistant Professor): Conceptualization, Methodology, Review.Additional informationFundingThe work was supported by the the National Social Science Fund of China [BAA200019].
Ways into physical (in)activity: The role of critical life events and transitions in the reconstructions of young adults
2023-08-22

Background Physical activity (PA), sport, and exercise levels generally tend to fluctuate or decline from childhood to adulthood. Life events and transitions may have a positive or negative impact on these behaviors. However, most research in this regard is quantitatively framed and we know little about why and how life events and transitions affect PA-related behaviors. Objectives The aim of this study is to understand when, why, and how individuals change their daily PA, sport, and exercise behaviors and related attitudes in the context of life events and transitions and what underlying dynamics promote these changes from a subjective perspective. Methods Forty-six young inactive adults (33 women) aged between 20 and 40 years from the iReAct study participated in a mixed-method biographical mapping, which combines a semi-structured interview with a drawing activity to explore subjective experiences of life events, transitions, and PA-related behaviors across the life span. To analyze data, we conducted a reflexive thematic analysis. Results We developed three overarching themes that reflect the underlying dynamics which are associated with the occurrence of critical life events and transitions and lead to subsequent changes in daily PA and sport and exercise behavior: (1) The finitude of temporal resources ; (2) The plasticity of priorities and motives ; and (3) The (in)conveniences of context . Conclusion Our results illustrate that there is not a straight causal link between life events and behavior. Rather, critical life events and transitions can have a tremendous impact on temporal resources, individual priorities and motives, and contextual factors, such as the physical and infrastructural environment and social settings and relationships. Consequently, more or less extensive changes in those circumstances can lead to individual adaptations in daily PA or sport and exercise and related attitudes, as they require individuals to re-balance behavioral patterns.
What can proteins of the past reveal about the origins of modern glycopeptide antibiotics?
2023-08-22

Natural products form one of the most important sources of medicinal compounds, with modern medicine reliant on antibiotics that almost exclusively originate from biosynthesis. 1 Indeed, thousands of compounds have been isolated from natural sources -with many more predicted -that display enormous structural diversity.These compounds are mainly produced as so called secondary or specialized metabolites by organisms and represent important adaptive characteristics that have been subjected to natural selection during evolution.Given the importance of biosynthetic processes to access complex natural products at scale, understanding how such pathways evolve is crucial information if we are to successfully reengineer such assemblies to allow the formation of new, designer compounds with improved properties.In this work, we have sought to understand the evolutionary history of the glycopeptide antibiotics (GPAs), a vital class of non-ribosomal peptides used in the clinic for the treatment of resistant bacterial infections. 2,3To understand how nature evolves antibiotics around a common mechanism of action, we investigated how key substrate selection domains from glycopeptide antibiotics (GPAs) have evolved through point mutations to select for new substrates resulting in the production of novel peptide antibiotic scaffolds.
Evolution of Partial Resistance to Artemisinins in Malaria Parasites in Uganda
2023-08-23

Data from Uganda showed the emergence of partial resistance to artemisinins in multiple geographic locations, with increasing prevalence and regional spread over time. (Funded by the National Institutes of Health.).
Implications of the Network Theory for the Treatment of Mental Disorders
2023-08-23

Importance Conceptualizing mental disorders as latent entities has been challenged by the network theory of mental disorders, which states that psychological problems are constituted by a network of mutually interacting symptoms. While the implications of the network approach for planning and evaluating treatments have been intensively discussed, empirical support for the claims of the network theory regarding treatment effects is lacking. Objective To assess the extent to which specific hypotheses derived from the network theory regarding the (interindividual) changeability of symptom dynamics in response to treatment align with empirical data. Design, Setting, and Participants This secondary analysis entails data from a multisite randomized clinical trial, in which 254 patients with chronic depression reported on their depressive symptoms at every treatment session. Data collection was conducted between March 5, 2010, and October 14, 2013, and this analysis was conducted between November 1, 2021, and May 31, 2022. Intervention Thirty-two sessions of either disorder-specific or nonspecific psychotherapy for chronic depression. Main Outcomes and Measures Longitudinal associations of depressive symptoms with each other and change of these associations through treatment estimated by a time-varying longitudinal network model. Results In a sample of 254 participants (166 [65.4%] women; mean [SD] age, 44.9 [11.9] years), symptom interactions changed through treatment, and this change varied across treatments and individuals. The mean absolute (ie, valence-ignorant) strength of symptom interactions (logarithmic odds ratio scale) increased from 0.40 (95% CI, 0.36-0.44) to 0.60 (95% CI, 0.52-0.70) during nonspecific psychotherapy and to 0.56 (95% CI, 0.48-0.64) during disorder-specific psychotherapy. In contrast, the mean raw (ie, valence-sensitive) strength of symptom interactions decreased from 0.32 (95% CI, 0.28-0.36) to 0.26 (95% CI, 0.20-0.32) and to 0.09 (95% CI, 0.02-0.16), respectively. Changing symptom severity could be explained to a large extent by symptom interactions. Conclusions and Relevance These findings suggest that specific treatment-related hypotheses of the network theory align well with empirical data. Conceptualizing mental disorders as symptom networks and treatments as measures that aim to change these networks is expected to give further insights into the working mechanisms of mental health treatments, leading to the improvement of current and the development of new treatments. Trial Registration ClinicalTrials.gov Identifier: NCT00970437
Predicting the development of digital media PCK/TPACK: The role of PCK, motivation to use digital media, interest in and previous experience with digital media
2023-08-23

In today's digital age, incorporating technology in teaching has become increasingly important. To prepare future teachers, understanding the factors that influence the development of teachers' corresponding knowledge base is crucial. However, not only is there a small number of studies investigating the development of pre-service teachers' professional knowledge, but these studies also predominantly rely on cross-sectional and/or self-reported data. This pre-post study investigated the factors associated with the development of digital media Pedagogical Content Knowledge (PCK) in physics teacher education through a seminar-based approach with N = 66 pre-service teachers (PSTs). Investigated factors include PSTs' PCK about students' conceptions (PCK-SC), general motivation to use digital media, interest in digital media, and previous experience with digital media. The findings suggest that a strong foundation in various aspects of PCK is essential for the development of digital media PCK, as PSTs' PCK-SC has proven to be a positive predictor for the development of PTSs' digital media PCK. Surprisingly, the study found that higher motivation to use digital media negatively affects the development of digital media PCK, suggesting that excessive motivation may hinder the acquisition of digital media PCK. Additionally, the study found that PSTs' interest in digital media positively influenced the development of digital media PCK, while previous experience with digital media had a negative impact on its development. The study suggests that future research should focus on investigating the general professional knowledge of PSTs and identifying the proficiency levels of PCK needed for the development of digital media PCK. It also emphasizes the importance of considering both, cognitive and affective aspects of teacher preparation, as seminars that solely focus on motivation may not be adequate in fostering effective technology integration. The study recommends that seminars on digital media integration should be situated at later stages of teacher education or after introductory courses that cover other facets of PCK. Furthermore, integrated seminars addressing multiple facets of PCK alongside digital media PCK could be explored in future research. Overall, this study provides insights into the factors influencing PSTs' development of digital media PCK and suggests avenues for further research to improve the integration of digital media in teaching practices for enhanced student learning outcomes.
Placing taxonomic nomenclatural stability above ethical concerns ignores societal norms
2023-08-23

Bae, Christopher J, Radović, Predrag, Wu, Xiu-Jie, Figueiredo, Estrela, Smith, Gideon F, Roksandic, Mirjana (2023): Placing taxonomic nomenclatural stability above ethical concerns ignores societal norms. Zoological Journal of the Linnean Society 199 (1): 5-6, DOI: 10.1093/zoolinnean/zlad061, URL: http://dx.doi.org/10.1093/zoolinnean/zlad061