bluuebunny/crossref_metadata_2025 huggingface dataset:
Atovaquone enhances antitumor efficacy of TCR-T therapy by augmentation of ROS-induced ferroptosis in hepatocellular carcinoma
Authors: Chen Anan , Yu Zhiwu , Ma Na , Lu Xinyu , Zhang Yajing , Xu Weikang , Wang Yiyue , Xie Jiayi , Qin Yuqi , Mo Guoheng , Wu Sha , Hou Jinlin , Zhu Wei
Published: February 2024

T-cell receptor (TCR) engineered T-cell therapy has recently emerged as a promising adoptive immunotherapy approach for tumor treatment, yet hindered by tumor immune evasion resulting in poor therapeutic efficacy. The introduction of ferroptosis-targeted inducers offers a potential solution, as they empower T cells to induce ferroptosis and exert influence over the tumor microenvironment. Atovaquone (ATO) stands as a prospective pharmaceutical candidate with the potential to target ferroptosis, effectively provoking an excessive generation and accumulation of reactive oxygen species (ROS). In this study, we evaluated the effectiveness of a combination therapy comprising ATO and TCR-T cells against hepatocellular carcinoma (HCC), both in vitro and in vivo. The results of lactate dehydrogenase and cytokine assays demonstrated that ATO enhanced cytotoxicity mediated by AFP-specific TCR-T cells and promoted the release of IFN-γ in vitro. Additionally, in an established HCC xenograft mouse model, the combined therapy with low-dose ATO and TCR-T cells exhibited heightened efficacy in suppressing tumor growth, with no apparent adverse effects, comparable to the results achieved through monotherapy. The RNA-seq data unveiled a significant activation of the ferroptosis-related pathway in the combination therapy group in comparison to the TCR-T cells group. Mechanistically, the synergy between ATO and TCR-T cells augmented the release of IFN-γ by TCR-T cells, while concurrently elevating the intracellular and mitochondrial levels of ROS, expanding the labile iron pool, and impairing the integrity of the mitochondrial membrane in HepG2 cells. This multifaceted interaction culminated in the potentiation of ferroptosis within the tumor, primarily induced by an excess of ROS. In summary, the co-administration of ATO and TCR-T cells in HCC exhibited heightened vulnerability to ferroptosis. This heightened susceptibility led to the inhibition of tumor growth and the stimulation of an anti-tumor immune response. These findings suggest that repurposing atovaquone for adoptive cell therapy combination therapy holds the potential to enhance treatment outcomes in HCC.
Investigating the immunological function of alpha-2-glycoprotein 1, zinc-binding in regulating tumor response in the breast cancer microenvironment
Authors: Hanamura Toru , Yokoyama Kozue , Kitano Shigehisa , Kagamu Hiroshi , Yamashita Makiko , Terao Mayako , Okamura Takuho , Kumaki Nobue , Hozumi Katsuto , Iwamoto Takayuki , Honda Chikako , Kurozumi Sasagu , Richer Jennifer K. , Niikura Naoki
Published: February 2024

Background

Alpha-2-glycoprotein 1, zinc-binding (ZAG), a secreted protein encoded by the AZGP1 gene, is structurally similar to HLA class I. Despite its presumed immunological function, little is known about its role in tumor immunity. In this study, we thus aimed to determine the relationship between the expression of AZGP1/ZAG and the immunological profiles of breast cancer tissues at both the gene and protein level.

Methods

Using a publicly available gene expression dataset from a large-scale breast cancer cohort, we conducted gene set enrichment analysis (GSEA) to screen the biological processes associated with AZGP1. We analyzed the correlation between AZGP1 expression and immune cell composition in breast cancer tissues, estimated using CIBERSORTx. Previously, we evaluated the infiltration of 11 types of immune cells for 45 breast cancer tissues using flow cytometry (FCM). ZAG expression was evaluated by immunohistochemistry on these specimens and analyzed for its relationship with immune cell infiltration. The action of ZAG in M1/M2 polarization models using primary cultures of human peripheral blood mononuclear cells (PBMC)-derived macrophage (Mφ) was analyzed based on the expression of M1/M2 markers (CD86, CD80/CD163, MRC1) and HLA class I/II by FCM.

Results

AZGP1 expression was negatively correlated with multiple immunological processes and specific immune cell infiltration including Mφ M1 using GSEA and CIBERSORTx. ZAG expression was associated with decreased infiltration of monocytes/macrophages, non-classical monocytes, and myeloid-derived suppressor cells in tumor tissues assessed using FCM. In in vitro analyses, ZAG decreased the expression of CD80, CD163, MRC1, and HLA classes I/II in the M1 polarization model and the expression of CD163 and MRC1 in the M2 polarization model.

Conclusion

ZAG is suggested to be a novel immunoregulatory factor affecting the Mφ phenotype in breast cancer tissues.
Longitudinal plasma proteomic analysis identifies biomarkers and combinational targets for anti-PD1-resistant cancer patients
Authors: Tan Qiaoyun , Gao Ruyun , Zhang Xiaomei , Yang Jianliang , Xing Puyuan , Yang Sheng , Wang Dan , Wang Guibing , Wang Shasha , Yao Jiarui , Zhang Zhishang , Tang Le , Yu Xiaobo , Han Xiaohong , Shi Yuankai
Published: February 2024

The response rate of anti-PD1 therapy is limited, and the influence of anti-PD1 therapy on cancer patients is unclear. To address these challenges, we conducted a longitudinal analysis of plasma proteomic changes with anti-PD1 therapy in non-small cell lung cancer (NSCLC), alveolar soft part sarcoma (ASPS), and lymphoma patients. We included 339 plasma samples before and after anti-PD1 therapy from 193 patients with NSCLC, ASPS, or lymphoma. The plasma proteins were detected using data-independent acquisition-mass spectrometry and customable antibody microarrays. Differential proteomic characteristics in responders (R) and non-responders (NR) before and after anti-PD1 therapy were elucidated. A total of 1019 proteins were detected using our in-depth proteomics platform and distributed across 10–12 orders of abundance. By comparing the differential plasma proteome expression between R and NR groups, 50, 206, and 268 proteins were identified in NSCLC, ASPS, and lymphoma patients, respectively. Th17, IL-17, and JAK-STAT signal pathways were identified upregulated in NR group, while cellular senescence and transcriptional misregulation pathways were activated in R group. Longitudinal proteomics analysis revealed the IL-17 signaling pathway was downregulated after treatment. Consistently, many proteins were identified as potential combinatorial therapeutic targets (e.g., IL-17A and CD22). Five noninvasive biomarkers (FLT4, SFTPB, GNPTG, F5, and IL-17A) were further validated in an independent lymphoma cohort (n = 39), and another three noninvasive biomarkers (KIT, CCL3, and TNFSF1) were validated in NSCLC cohort (n = 76). Our results provide molecular insights into the anti-PD1 therapy in cancer patients and identify new therapeutic strategies for anti-PD1-resistant patients.
Exploration behavior differs between Darwin’s finch species and predicts territory defense and hatching success
Authors: Katsis Andrew C. , Colombelli-Négrel Diane , Akçay Çağlar , Common Lauren K. , García-Loor Jefferson , Kleindorfer Sonia
Published: February 2024

Darwin’s finch species in the Galápagos Islands are famously distinguished by their morphology but less attention has been given to behavioral differences between species. In this study, we compared behavior between four Darwin’s finch species on Floreana Island: small ground finch (Geospiza fuliginosa), medium ground finch (G. fortis), small tree finch (Camarhynchus parvulus), and medium tree finch (C. pauper). After capturing birds using mist-nets, we measured three behavioral traits: (1) boldness during human handling, (2) exploration in a novel environment, and (3) aggressiveness towards their mirror image. First, we found that ground finches were bolder and more exploratory than tree finches, consistent with their distinct ecological niches on Floreana Island and with the theoretical prediction that diet generalists should be less wary of novelty. Second, we tested the ecological validity of these behavioral variables at the individual level by relating them to territory defense behavior and breeding success. We found that males that were more exploratory in the novel environment also reacted more aggressively to a simulated territory intruder and showed lower offspring hatching success during the breeding season. Hence, our findings support previous work showing behavioral differences between Darwin’s finch species and also suggest pathways by which behavioral differences among individuals might influence fitness.

Significance statement

Closely-related species that overlap in their geographical range may differ in their morphology and/or behavior, allowing them to occupy different ecological niches. In this study, we explored behavioral differences between four Darwin’s finch species on Floreana Island in the Galápagos Archipelago. We found clear interspecies differences in behavior, with the ground finches struggling more often during handling (boldness) and visiting more sectors in a novel environment (exploration) compared to the tree finches. After birds were released, we continued to observe a subset of male finches in the wild. An individual’s exploration behavior significantly predicted both its aggressive response to a territory intruder (simulated using song playback) and offspring hatching success during the breeding season. This suggests that individual differences in exploration behavior can potentially be used as a proxy for territorial behavior in the wild and may also predict fitness outcomes.
Predicting residual cholesteatoma with the Potsic staging system still lacks evidence: a systematic review and meta-analysis
Authors: Körmendy Klára Borbála , Shenker-Horváth Kinga , Shulze Wenning Alexander , Fehérvári Péter , Harnos Andrea , Hegyi Péter , Molnár Zsolt , Illés Kata , Horváth Tamás
Published: February 2024

Purpose

To investigate the rate of residual disease in the Potsic staging system for congenital cholesteatomas.

Methods

A protocol registration was published on PROSPERO (CRD42022383932), describing residual disease as a primary outcome and hearing improvement as secondary. A systematic search was performed in four databases (PubMed, Embase, Cochrane Library, Web of Science) on December 14, 2022. Articles were included if cholesteatomas were staged according to the Potsic system and follow-up duration was documented. Risk of bias was evaluated using the Quality In Prognosis Studies (QUIPS) tool. In the statistical synthesis a random effects model was used. Between-study heterogeneity was assessed using I2.

Results

Thirteen articles were found to be eligible for systematic review and seven were included in the meta-analysis section. All records were retrospective cohort studies with high risk of bias. Regarding the proportions of residual disease, analysis using the χ2 test showed no statistically significant difference between Potsic stages after a follow-up of minimum one year (stage I 0.06 (confidence interval (CI) 0.01–0.33); stage II 0.20 (CI 0.09–0.38); stage III 0.06 (CI 0.00–0.61); stage IV: 0.17 (CI 0.01–0.81)). Postoperative and preoperative hearing outcomes could not be analyzed due to varied reporting. Results on cholesteatoma location and mean age at staging were consistent with those previously published.

Conclusion

No statistically significant difference was found in the proportions of residual disease between Potsic stages, thus the staging system’s applicability for outcome prediction could not be proven based on the available data. Targeted studies are needed for a higher level of evidence.
Effectiveness and safety of intraoperative intraperitoneal 5-Fu drug implantation in patients with colorectal cancer: a retrospective cohort study
Authors: Liu Renchao , Hu Xianqin , Lai Chen
Published: February 2024

Purpose

The purpose of this clinical study was to evaluate the efficacy and safety of intraoperative chemotherapy (IOC) with intraoperative intraperitoneal implantation of 5-fluorouracil (5-FU) in colorectal cancer (CRC) patients.

Methods

In this study, 165 patients who underwent colorectal radical surgery were selected, of whom 111 in the experimental group received surgical treatment with an intraperitoneal 5-fluorouracil (5-FU) implantation. Fifty-four patients who did not undergo intraperitoneal implantation of 5-FU were matched to compare the progression-free survival (PFS) and overall survival (OS) with the former.

Results

We also studied the differences in the changes of different biochemical indicators between the two groups before and after surgery, and there were significant differences in leukocytes, neutrophils, and lymphocytes before and after (P < 0.05), while for sodium ions, potassium ions, platelets, alanine transaminase, aspartate transaminase, creatinine, urea, and albumin, there were no significant differences. This may be related to the intraperitoneal chemotherapy implant entering the blood circulation. For 5-year OS, there were 85/111 (76.58%) in the 5-FU group (P = 0.013) and 35/54 (64.81%) in the control group; for 5-year PFS, there were 84/111 (75.68%) in the 5-FU group and 29/54 (53.70%) in the control group (P = 0.02). All the experimental groups were better than the control group with a significant difference in the experimental results.

Conclusion

For CRC surgery patients, intraperitoneal implantation of slow-release 5-FU drugs, which is a safe and simple procedure, can improve the prognosis of the patients.

Clinical trial registration

No clinical trials were performed in the study.
Rural–urban differences in the perceived impact of COVID-19 on mental health by European women
Authors: Rodríguez Mercedes , Camacho José A.
Published: February 2024

Purpose

Many studies have documented an adverse impact of the pandemic on women´s mental health. This cross-sectional study aims to explore associations between women's perceived impact of lockdowns and curfews on their mental health and their residential location, along with other contextual and individual factors.

Methods

Using data from the Flash Eurobarometer 2712 “Women in times of COVID-19”, conducted between January 25 and February 3, 2022, across the 27 Member States of the European Union (n = 23,671), this study applied bivariate tests and stratified models based on respondent location (rural areas, small or medium-sized towns and urban areas). The exploration sought predictors influencing the perceived mental health impact, encompassing five individual characteristics (age, disability, employment status, educational attainment, and household type), perceptions of violence against women, and country of residence. The dependent variable was assessed subjectively, measured on a scale from 1 (minor negative impact) to 5 (major negative impact).

Results

Women living in urban areas generally reported a higher perceived negative impact on mental health compared to women in rural areas or in small/medium-sized towns. Age and disability were significantly linked to perceiving a negative impact on mental health. Similar adjusted odds ratios for age were observed across rural areas (aOR 0.97, 95% CI = 0.97–0.98), small or medium-sized towns (aOR 0.98, 95% CI = 0.97–0.98), and urban areas (aOR 0.97, 95% CI = 0.97–0.98). In terms of disability, the odds were higher in rural areas (aOR 1.44, 95% CI = 1.20–1.73) than in urban ones (aOR 1.36, 95% CI = 1.15–1.62). Among women residing in urban areas, those in childless couples were less likely to perceive a negative impact on mental health (aOR 0.89, 95% CI = 0.80–0.99) compared to women in couples with children. Respondents perceiving increased violence against women due to COVID-19 were more likely to perceive a negative impact on mental health, with higher odds ratios in rural areas (aOR 1.56, 95% CI = 1.40–1.74) compared to urban areas (aOR 1.29, 95% CI = 1.17–1.41). Differences across countries were also found.

Conclusion

The perceived impact of lockdowns and curfews on mental health exhibited variance between urban and rural areas. These disparities were influenced by individual characteristics such as age, disability, or household type, as well as the effects of COVID-19 on violence against women and contextual variables like country of residence.
Assisted design of data science pipelines
Authors: Redyuk Sergey , Kaoudi Zoi , Schelter Sebastian , Markl Volker
Published: February 2024

When designing data science (DS) pipelines, end-users can get overwhelmed by the large and growing set of available data preprocessing and modeling techniques. Intelligent discovery assistants (IDAs) and automated machine learning (AutoML) solutions aim to facilitate end-users by (semi-)automating the process. However, they are expensive to compute and yield limited applicability for a wide range of real-world use cases and application domains. This is due to (a) their need to execute thousands of pipelines to get the optimal one, (b) their limited support of DS tasks, e.g., supervised classification or regression only, and a small, static set of available data preprocessing and ML algorithms; and (c) their restriction to quantifiable evaluation processes and metrics, e.g., tenfold cross-validation using the ROC AUC score for classification. To overcome these limitations, we propose a human-in-the-loop approach for theassisteddesignofdatasciencepipelinesusing previously executed pipelines. Based on a user query, i.e., data and a DS task, our framework outputs a ranked list of pipeline candidates from which the user can choose to execute or modify in real time. To recommend pipelines, it first identifies relevant datasets and pipelines utilizing efficient similarity search. It then ranks the candidate pipelines using multi-objective sorting and takes user interactions into account to improve suggestions over time. In our experimental evaluation, the proposed framework significantly outperforms the state-of-the-art IDA tool and achieves similar predictive performance with state-of-the-art long-running AutoML solutions while being real-time, generic to any evaluation processes and DS tasks, and extensible to new operators.
Antimicrobial effects of clindamycin-loaded platelet-rich fibrin (PRF)
Authors: Straub Anton , Stapf Maximilian , Utz Chiara , Vollmer Andreas , Flesch Julia , Kübler Alexander , Scherf-Clavel Oliver , Lâm Thiên-Trí , Hartmann Stefan
Published: February 2024

Objectives

Recent research has demonstrated that platelet-rich fibrin (PRF) is an appropriate carrier for ampicillin/sulbactam. The aim of the study was to investigate whether PRF is also a suitable bio-carrier for clindamycin (CLI).

Methods

PRF membranes were produced from 36 patients receiving intravenous therapy with CLI (e.g. due to the diagnosis of an osteonecrosis of the jaw or infections). Concentrations of CLI in PRF membranes were measured with liquid chromatography-tandem mass spectrometry, and the antimicrobial effects were investigated in vitro in agar diffusion tests with fresh PRF and PRF stored for 24 h. Storage was performed in an incubator at 36 °C to simulate the in-vivo situation.

Results

The mean concentration of CLI in plasma was 1.0 ± 0.3 μg/100 mg plasma; in resulting PRF membranes 0.7 ± 0.4 μg/100 mg PRF. Agar diffusion tests were performed with Staphylococcus aureus, Streptococcus pneumoniae, Streptococcus mitis, Porphyromonas gingivalis, and Fusobacterium nucleatum. Mean inhibition zones, in mm, for fresh PRF were 17.3, 12.2, 18.8, 17.1, 25.8 and 18.1, 12.7, 19.2, 17.3, and 26.3 for stored PRF, respectively.

Conclusion

The results demonstrate that PRF is a suitable bio-carrier for CLI when administered systemically to patients. The concentration in PRF generated from patients after infusion of 600 mg CLI dose suffices to target clinically relevant bacteria.

Clinical relevance

Using PRF as a carrier for local antibiotic application can prevent infections in oral and maxillofacial surgery. Within the study limitations, the findings could expand the scope of PRF application by adding CLI as a new antibiotic to the spectrum of PRF therapy.
Strong Norm Error Bounds for Quasilinear Wave Equations Under Weak CFL-Type Conditions
Authors: Dörich Benjamin
Published: February 2024

In the present paper, we consider a class of quasilinear wave equations on a smooth, bounded domain. We discretize it in space with isoparametric finite elements and apply a semi-implicit Euler and midpoint rule as well as the exponential Euler and midpoint rule to obtain four fully discrete schemes. We derive rigorous error bounds of optimal order for the semi-discretization in space and the fully discrete methods in norms which are stronger than the classical

$$H^1\times L^2$$

H
1

×

L
2

energy norm under weak CFL-type conditions. To confirm our theoretical findings, we also present numerical experiments.
Current State of EEG/ERP Microstate Research
Authors: Michel Christoph M. , Brechet Lucie , Schiller Bastian , Koenig Thomas
Published: February 2024

The analysis of EEG microstates for investigating rapid whole-brain network dynamics during rest and tasks has become a standard practice in the EEG research community, leading to a substantial increase in publications across various affective, cognitive, social and clinical neuroscience domains. Recognizing the growing significance of this analytical method, the authors aim to provide the microstate research community with a comprehensive discussion on methodological standards, unresolved questions, and the functional relevance of EEG microstates. In August 2022, a conference was hosted in Bern, Switzerland, which brought together many researchers from 19 countries. During the conference, researchers gave scientific presentations and engaged in roundtable discussions aiming at establishing steps toward standardizing EEG microstate analysis methods. Encouraged by the conference’s success, a special issue was launched in Brain Topography to compile the current state-of-the-art in EEG microstate research, encompassing methodological advancements, experimental findings, and clinical applications. The call for submissions for the special issue garnered 48 contributions from researchers worldwide, spanning reviews, meta-analyses, tutorials, and experimental studies. Following a rigorous peer-review process, 33 papers were accepted whose findings we will comprehensively discuss in this Editorial.
Convex approximations of two-stage risk-averse mixed-integer recourse models
Authors: van Beesten E. Ruben , Romeijnders Ward , Roodbergen Kees Jan
Published: February 2024

We consider two-stage risk-averse mixed-integer recourse models with law invariant coherent risk measures. As in the risk-neutral case, these models are generally non-convex as a result of the integer restrictions on the second-stage decision variables and hence, hard to solve. To overcome this issue, we propose a convex approximation approach. We derive a performance guarantee for this approximation in the form of an asymptotic error bound, which depends on the choice of risk measure. This error bound, which extends an existing error bound for the conditional value at risk, shows that our approximation method works particularly well if the distribution of the random parameters in the model is highly dispersed. For special cases we derive tighter, non-asymptotic error bounds. Whereas our error bounds are valid only for a continuously distributed second-stage right-hand side vector, practical optimization methods often require discrete distributions. In this context, we show that our error bounds provide statistical error bounds for the corresponding (discretized) sample average approximation (SAA) model. In addition, we construct a Benders’ decomposition algorithm that uses our convex approximations in an SAA-framework and we provide a performance guarantee for the resulting algorithm solution. Finally, we perform numerical experiments which show that for certain risk measures our approach works even better than our theoretical performance guarantees suggest.
Remnant kenngoor (Phascogale calura) retain genetic connectivity and genetic diversity in a highly fragmented landscape
Authors: de Visser Rhiannon S. J. , Hall Michelle , Ottewell Kym , Pierson Jennifer C. , Sanders Angela , Friend J. Anthony , Berry Laurence , Hogg Carolyn , Catullo Renee A.
Published: February 2024

Kenngoor (Phascogale calura) persist in < 1% of their original distribution, occupying highly fragmented remnant habitat in south-west Western Australia, with very little known of the genetic diversity of the remaining wild populations. Recently, the species has been translocated to managed reserves to improve its conservation. Understanding genetic structure and patterns of genetic diversity is crucial to inform conservation translocations for species recovery. This study aims to (1) assess genetic structure and genetic diversity across remaining wild locations, (2) assess long-term genetic outcomes of a mixed-source wild-to-wild translocation, and (3) estimate global effective population size. We genotyped 209 samples from 13 locations of fragmented remnant habitat using reduced representation sequencing. An isolation by distance model best explained genetic structure across the survey areas, with evidence of fine scale divergence of two northern locations. Allelic richness and autosomal heterozygosity measures indicated that diversity is spread uniformly across locations, and no locations showed signs of inbreeding or strong genetic drift. The mixed-source translocation has retained the diversity of the wider species ten years post-translocation. Overall, our results suggest that connectivity between survey areas has largely been maintained and that no location has substantially lower genetic diversity, despite the highly fragmented nature of remnant kenngoor habitat. Future translocations should aim to represent a mixture of genetically divergent locations to maintain the diversity present at the species level. Ongoing conservation management will be required to ensure the long-term viability of the species in this fragmented landscape.
Selective elimination of tumorigenic cells from mixed culture of normal and tumorigenic cells using hybrid liposomes aimed at realizing of cell therapy
Authors: Jinno Riko , Tanaka Moe , Komizu Yuji , Matsumoto Yoko , Matsushita Taku , Ishida Seiichi
Published: February 2024

While induced pluripotent stem (iPS) cells are expected to be a cell source for regenerative medicine, they also have tumorigenic properties owing to their proliferative potential. During the manufacturing of regenerative medicine products, undifferentiated iPS cells and malignant transformed cells may be mixed in the cell culture population. Therefore, it is essential to eliminate tumorigenic cells selectively. In this study, a mixed culture of normal human fetal hepatocytes (Hc cells) and human hepatocellular carcinoma cells (HuH-7 cells) was used as a cell population model to be used as regenerative medicine products, and the selective elimination of HuH-7 cells by hybrid liposomes (HL) was analyzed. HL tended to fuse and accumulate more in HuH-7 cells due to larger fluidity of plasma membrane for HuH-7 cells than that for Hc cells. In a mixed culture of Hc and HuH-7 cells, HL selectively eliminated HuH-7 cells while allowing Hc cells to remain viable. In addition, HL treatment for the mixed culture of Hc and HuH-7 cells suppressed the tumorigenicity of HuH-7 cells. Therefore, HL selectively fused and accumulated in tumorigenic cells in a mixed cell culture of normal and tumorigenic cells, and eliminated tumorigenic cells while allowing normal cells to remain viable. The results of this study suggest the potential of HL in eliminating tumorigenic cells during the manufacturing of regenerative medicine products. Thus, HL could be expected to contribute to the development of safe regenerative medical products.
Using data clustering to reveal trainees’ behavior in cybersecurity education
Authors: Dočkalová Burská Karolína , Mlynárik Jakub Rudolf , Ošlejšek Radek
Published: February 2024

In cyber security education, hands-on training is a common type of exercise to help raise awareness and competence, and improve students’ cybersecurity skills. To be able to measure the impact of the design of the particular courses, the designers need methods that can reveal hidden patterns in trainee behavior. However, the support of the designers in performing such analytic and evaluation tasks is ad-hoc and insufficient. With unsupervised machine learning methods, we designed a tool for clustering the trainee actions that can exhibit their strategies or help pinpoint flaws in the training design. By using a k-means++ algorithm, we explore clusters of trainees that unveil their specific behavior within the training sessions. The final visualization tool consists of views with scatter plots and radar charts. The former provides a two-dimensional correlation of selected trainee actions and displays their clusters. In contrast, the radar chart displays distinct clusters of trainees based on their more specific strategies or approaches when solving tasks. Through iterative training redesign, the tool can help designers identify improper training parameters and improve the quality of the courses accordingly. To evaluate the tool, we performed a qualitative evaluation of its outcomes with cybersecurity experts. The results confirm the usability of the selected methods in discovering significant trainee behavior. Our insights and recommendations can be beneficial for the design of tools for educators, even beyond cyber security.
Modelling the relationships between STEM learning attitude, computational thinking, and 21st century skills in primary school
Authors: Küçükaydın Menşure Alkış , Çite Hakan , Ulum Hakan
Published: February 2024

Students enter the science, technology, engineering, and mathematics (STEM) pipeline in primary school, but leak out of it over time for various reasons. To prevent leaks, it is important to understand the variables that affect attitudes towards STEM learning from an early age. This study sought to examine the predictors of young students' STEM learning attitudes. In the study, 493 primary school students (Mage = 9.62, SD = .72) from a Turkish sample were reached through a survey. We recruited our participants using the convenience sampling technique. Data were collected with the STEM learning attitude scale, the Multidimensional 21st Century Skills Scale, and the Computational Thinking (CT) test. Descriptive and correlational analyses were performed on the data. Then the relationship between variables was tested with a structural equation modeling. The results of the analyses showed that STEM learning attitudes and CT skills of primary school students demonstrated good fit indexes. Also results showed that twenty-first century skills mediated the relationship between STEM learning attitudes and CT skills. The results of the analysis are discussed, and recommendations are presented in terms of strengthening young students' place in the STEM pipeline.
Linguistic and non-linguistic factors impacting EMI academic success: a longitudinal study
Authors: Soruç Adem , Yuksel Dogan , Horzum Barış , McKinley Jim , Rose Heath
Published: February 2024

This study explored changes in English language proficiency and several non-linguistic factors during four years of English medium instruction (EMI) in two academic disciplines in a Turkish university setting. Moreover, it also investigated whether changes (if any) had a predictive impact on the academic success of EMI students. In addition, potential differences between disciplines were also investigated. The participants were 241 EMI students from Business Administration (n = 117) and Mechanical Engineering (n = 124) programmes. Our findings revealed that in addition to the language proficiency scores, various non-linguistic factors, including self-efficacy, ideal L2 self, motivation, self-regulation skills, and anxiety levels, changed throughout EMI education. However, only English proficiency and instrumental motivation emerged as positively significant predictors of EMI success.Our findings also revealed that the increase in participants' intrinsic motivation scores was a significant negative predictor of EMI success. These results are discussed and implications are given regarding the impact of linguistic and non-linguistic factors in EMI contexts.
Access Interval Prediction by Partial Matching for Tightly Coupled Memory Systems
Authors: Razilov Viktor , Wittig Robert , Matúš Emil , Fettweis Gerhard
Published: February 2024

In embedded systems, tightly coupled memories (TCMs) are usually shared between multiple masters for the purpose of hardware efficiency and software flexibility. On the one hand, memory sharing improves area utilization, but on the other hand, this can lead to a performance degradation due to an increase in access conflicts. To mitigate the associated performance penalty, access interval prediction (AIP) has been proposed. In a similar fashion to branch prediction, AIP exploits program flow regularity to predict the cycle of the next memory access. We show that this structural similarity allows for adaption of state-of-the-art branch predictors, such as Prediction by Partial Matching (PPM) and the TAgged GEometric history length (TAGE) branch predictor. Our analysis on memory access traces reveals that PPM predicts 99 percent of memory accesses. As PPM does not lend itself to hardware implementation, we also present the PPM-based TAGE access interval predictor which attains an accuracy of over 97 percent outperforming all previously presented implementable AIP schemes.
Multi-channels Prototype Contrastive Learning with Condition Adversarial Attacks for Few-shot Event Detection
Authors: Zhang Fangchen , Tian Shengwei , Yu Long , Yang Qimeng
Published: February 2024

Few-shot Event Detection (FSED) is a sub-task of Event Detection that aims to accurately identify event types with limited training instances and enable smooth transfer to newly-emerged event types. Recently, the dominant works have used the prototypical network to accomplish this task and employ contrastive learning to alleviate the issue of semantically-close categories. Nevertheless, these methods still suffer from two serious problems: (1) inadequate learning of prototype representations resulting from limited training data; (2) hard-easy sample imbalance and categories imbalance caused by the large number of non-trigger word("O" tags) in the token-level classification task. To address the problems, this paper proposes the Multi-channels Prototype and Contrastive learning method with Conditional Adversarial attack, which introduces the improved multi-channels prototype and contrastive networks to alleviate the categories and hard-easy samples imbalance. Moreover, we devise a constrained adversarial attack to improve the problem of limited training data. Extensive experimental results show that our model performs better than other FSED methods. All the code and data will be available for online public access.
Technology sourcing ambidexterity in corporate venture capital: limitations of learning from open innovation
Authors: Anokhin Sergey Alexander , Hess Manuel , Wincent Joakim
Published: February 2024

In the rapidly evolving landscape of open innovation, understanding the dynamics of learning is pivotal for corporate success. Yet, the constraints and thresholds inherent in the novel technology sourcing processes remain under-explored. We study 163 firms during the third wave of corporate venture capital activity characterized by the primary focus on innovation to investigate the effects of technology sourcing ambidexterity (the simultaneous pursuit of internal and external sources of innovative ideas) on corporate patenting and realized innovation. Acknowledging limitations of organizational learning, our results indicate the presence of the inverted U-shaped relationship between technology sourcing ambidexterity and innovation and suggest that beyond a certain threshold, increases in ambidexterity are detrimental to organizational learning and corporate innovation because boundary conditions to experimentation as a key element to learning arise. Such restrictions are alleviated by organizational slack, which enhances organizational abilities to orchestrate resources and take calculated risks to go beyond existing internal competencies.
Optimal test case generation for boundary value analysis
Authors: Guo Xiujing , Okamura Hiroyuki , Dohi Tadashi
Published: February 2024

Boundary value analysis (BVA) is a common technique in software testing that uses input values that lie at the boundaries where significant changes in behavior are expected. This approach is widely recognized and used as a natural and effective strategy for testing software. Test coverage is one of the criteria to measure how much the software execution paths are covered by the set of test cases. This paper focuses on evaluating test coverage with respect to BVA by defining a metric called boundary coverage distance (BCD). The BCD metric measures the extent to which a test set covers the boundaries. In addition, based on BCD, we consider the optimal test input generation to minimize BCD under the random testing scheme. We propose three algorithms, each representing a different test input generation strategy, and evaluate their fault detection capabilities through experimental validation. The results indicate that the BCD-based approach has the potential to generate boundary values and improve the effectiveness of software testing.
Metagenomic analysis of carbohydrate-active enzymes and their contribution to marine sediment biodiversity
Authors: López-Sánchez Rafael , Rebollar Eria A. , Gutiérrez-Ríos Rosa María , Garciarrubio Alejandro , Juarez Katy , Segovia Lorenzo
Published: February 2024

Marine sediments constitute the world’s most substantial long-term carbon repository. The microorganisms dwelling in these sediments mediate the transformation of fixed oceanic carbon, but their contribution to the carbon cycle is not fully understood. Previous culture-independent investigations into sedimentary microorganisms have underscored the significance of carbohydrates in the carbon cycle. In this study, we employ a metagenomic methodology to investigate the distribution and abundance of carbohydrate-active enzymes (CAZymes) in 37 marine sediments sites. These sediments exhibit varying oxygen availability and were isolated in diverse regions worldwide. Our comparative analysis is based on the metabolic potential for oxygen utilisation, derived from genes present in both oxic and anoxic environments. We found that extracellular CAZyme modules targeting the degradation of plant and algal detritus, necromass, and host glycans were abundant across all metagenomic samples. The analysis of these results indicates that the oxic/anoxic conditions not only influence the taxonomic composition of the microbial communities, but also affect the occurrence of CAZyme modules involved in the transformation of necromass, algae and plant detritus. To gain insight into the sediment microbial taxa, we reconstructed metagenome assembled genomes (MAG) and examined the presence of primary extracellular carbohydrate active enzyme (CAZyme) modules. Our findings reveal that the primary CAZyme modules and the CAZyme gene clusters discovered in our metagenomes were prevalent in the Bacteroidia, Gammaproteobacteria, and Alphaproteobacteria classes. We compared those MAGs to organisms from the same taxonomic classes found in soil, and we found that they were similar in its CAZyme repertoire, but the soil MAG contained a more abundant and diverse CAZyme content. Furthermore, the data indicate that abundant classes in our metagenomic samples, namely Alphaproteobacteria, Bacteroidia and Gammaproteobacteria, play a pivotal role in carbohydrate transformation within the initial few metres of the sediments.
Evaluation of stability of (1R,2 S)-(−)-2-methylamino-1-phenyl-1-propanol hydrochloride in plasma and urine samples-inoculated with Escherichia coli using high-performance liquid chromatography (HPLC)
Authors: Almaary Khalid S. , Alharbi Naiyf S. , Al-Huwaymil Rayan M. , Kadaikunnan Shine , Alobaidi Ahmed S. , Khaled Jamal M.
Published: February 2024

The preservation of drug stability in biological evidence during the processes of collection and storage poses a substantial obstacle to the progress of forensic investigations. In conjunction with other constituents, the microorganisms present in the samples play a vital role in this investigation. The present investigation employed the high-performance liquid chromatography (HPLC) technique to assess the stability of (1R,2 S)-(–)-2-methylamino-1-phenyl-1-propanol hydrochloride in plasma and urine samples that were inoculated with Escherichia coli. These samples were subjected to storage conditions of 37 °C for 48 h and − 20 °C for a duration of 6 months. Minimal inhibitory concentration (MIC) and Minimal bactericidal concentration (MBC) of MPPH against E. coli were determined using microdilution method. The stability of MPPH in plasma and urine samples inoculated with E. coli was investigated using HPLC method. The results showed the MIC and MBC of MPPH were 87.5 ± 25 ppm and 175 ± 50 ppm, respectively. While MPPH remained stable in plasma for 48 h at 37 °C, it showed a notable decrease of about 11% in stability when stored in urine for the same period and temperature. From the beginning of the first month, a decrease in the stability of the compound appeared in all samples that were stored at − 20 °C, and the decrease reached 7% for plasma samples and about 11% for urine samples. The decrease in the stability reached its peak in the sixth month, reaching more than 30% and 70% of plasma and urine samples preserved at − 20 °C. This work concluded that E. coli can negatively affect the stability of MPPH in plasma and urine samples. This may lead to incorrect conclusions regarding the analysis of biological samples in criminal cases.
On the Identifiability of 3- and 4-Parameter Item Response Theory Models From the Perspective of Knowledge Space Theory
Authors: Noventa Stefano , Ye Sangbeak , Kelava Augustin , Spoto Andrea
Published: February 2024

The present work aims at showing that the identification problems (here meant as both issues of empirical indistinguishability and unidentifiability) of some item response theory models are related to the notion of identifiability in knowledge space theory. Specifically, that the identification problems of the 3- and 4-parameter models are related to the more general issues of forward- and backward-gradedness in all items of the power set, which is the knowledge structure associated with IRT models under the assumption of local independence. As a consequence, the identifiability problem of a 4-parameter model is split into two parts: a first one, which is the result of a trade-off between the left-side added parameters and the remainder of the Item Response Function, e.g., a 2-parameter model, and a second one, which is the already well-known identifiability issue of the 2-parameter model itself. Application of the results to the logistic case appears to provide both a confirmation and a generalization of the current findings in the literature for both fixed- and random-effects IRT logistic models.
Energy security-related risks and the quest to attain USA’s net-zero emissions targets by 2050: a dynamic ARDL simulations modeling approach
Authors: Usman Ojonugwa , Ozkan Oktay , Alola Andrew Adewale , Ghardallou Wafa
Published: February 2024

The Russia-Ukraine war and other similar conflicts across the globe have heightened risks to the United States of America's (USA’s) energy security. However, little is known about the severity of the effect of energy security risks on the USA’s quest to attain net-zero emissions targets by 2050. To this end, we examine the effect of energy security risks on the load capacity factor (LCF) in the USA. Employing a time series dataset spinning from 1970 to 2018, the results of the Dynamic Autoregressive Distributed Lag (ARDL) simulations model suggest that energy security-related risk hampers the long-term net-zero emissions targets with its effect decreasing over time until it varnishes in about 5 years time. The results also show that foreign direct investment (FDI) inflows, renewable energy consumption, and green technology have long- and short-run positive effects on the LCF. Conversely, economic expansion and urbanization impede environmental quality by lowering the LCF both in the long run and short run. These findings are upheld by the outcomes of the multivariate quantile-on-quantile regression. Therefore, the study advocates for the consumption of renewable energy, investment in green technologies, and FDI inflows to mitigate energy security-related risks and attain the net-zero emissions targets by 2050 in the USA.
New race-free creatinine- and cystatin C-based equations for the estimation of glomerular filtration rate and association with cardiovascular mortality in the AtheroGene study
Authors: Ntaios George , Brederecke Jan , Ojeda Francisco M. , Zeller Tanja , Blankenberg Stefan , Schnabel Renate B.
Published: February 2024

Renal function is associated with cardiovascular outcomes and mortality. Among equations used to eGFR, CKD–EPI equations show more accurate association with cardiovascular risk and mortality than MDRD. Recently, new CKD–EPI equations were proposed which do not include race and would be considered sufficiently accurate to estimate eGFR in clinical practice. It is unknown if these new race-free equations are comparably well associated with cardiovascular outcomes in high-risk individuals. The analysis was performed in the AtheroGene Study cohort including patients at high cardiovascular risk. eGFR was determined using the established as well as the recently developed formulas which are calculated without the otherwise existing coefficient for black race. The outcome was cardiovascular death. Analyses included Cox-proportional hazard regression and area-under-the-curve calculation. The analysis included 2089 patients followed up for a median of 3.8 years with a maximum of 6.9 years, corresponding to an overall period of 7701 patient-years. Cardiovascular death occurred in 93 (4.45%), corresponding to an annualized rate of 1.2/100 person-years. In all Cox regression analyses, the estimated adjusted GFR was an independent predictor of cardiovascular death. The equations which included cystatin C showed higher C-index compared to those which did not include cystatin C (0.75–0.76 vs. 0.71, respectively). The equations for the estimation of eGFR which include cystatin C are better associated with cardiovascular death compared to the race-free equations which include only creatinine. This finding adds on the related literature which supports the elimination of race in GFR-estimating equations, and promotion of the use of cystatin C.