bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bevacizumab improved prognosis for advanced EGFR-mutant lung adenocarcinoma with brain metastasis receiving cerebral radiotherapy
Authors: Zhou Yuanliang , Li Jingchao , Li Yankang , Deng Guangchuan , Wang Qi , Qin Hongyue , Li Jianbin , Li Zhenxiang 
Published: March 2024

Abstract

Objective
This study aimed to determine whether the combined use of bevacizumab could improve overall survival (OS) in patients with brain metastasis (BM), epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) undergoing cerebral radiotherapy.

Materials and methods
A total of 237 patients with EGFR-mutant lung adenocarcinoma and BM met the inclusion criteria for this retrospective study, including 102 patients in the bevacizumab treatment group and 135 in the non-bevacizumab group. The Kaplan–Meier method was used for survival analysis. Univariate and multivariate analyses were performed to identify EGFR-mutated BM prognostic factors for these patients.

Results
At the end of the last follow-up period, 176 patients (74.3%) had died, and the median overall survival (OS) was 34.2 months. We observed a significant difference in the median OS between the bevacizumab and non-bevacizumab groups (45.8 months vs 30.0 months, P < 0.0001). Among the 178 (75.1%) patients who received cerebral radiotherapy, the median OS of patients in the bevacizumab + cerebral radiotherapy group was 45.8 months versus 32.0 months in the non-bevacizumab + cerebral radiotherapy group, respectively (P = 0.0007). Patients treated with bevacizumab after cerebral radiotherapy had a longer median OS than patients treated with bevacizumab before cerebral radiotherapy (59.4 months vs 33.7 months, P = 0.0198). In the univariate analysis, smoking status, Lung-molGPA scores, and bevacizumab therapy showed correlations (HR = 1.450, P = 0.045; HR = 0.700, P = 0.023; HR = 0.499, P < 0.001). Multivariate analysis showed that bevacizumab therapy alone (hazard ratio [HR] = 0.514; P < 0.001) was independently associated with improved OS.

Conclusion
In patients with BM from EGFR-mutated NSCLC, cerebral radiotherapy with bevacizumab markedly improved OS. This improvement was more evident after cerebral radiotherapy.
Sleep, depression, anxiety, stress and circadian preferences among women in the third trimester. Are these variables related to mother’s expectations about their child’s sleep?
Authors: Manková Denisa , Švancarová Soňa , Štenclová Eliška 
Published: March 2024

AbstractPregnancy is a period of significant physical and psychological changes. Pregnant women often struggle with poor sleep quality which can increase the risk of developing depression and anxiety. Additional factors can affect sleep quality and vice versa. We focused on an understudied topic: pregnant women`s expectations about how their infant will sleep. This study aims to describe the potential correlates and predictors of women`s sleep quality and their expectations about child sleep in a broader context. In total, 250 women participated in the research. Participants completed questionnaires PSQI, MEQ, DASS-21 and BISQ-R. To verify the set aims, we used Pearson’s correlation coefficient, t-test and general linear model (GLM), including methods for determining the effect size (Hedges’ g, r2, ε2). The results showed that sleep quality is related to circadian preference, depression, anxiety and stress. Women with poor sleep quality were more evening type and scored higher on these variables. Anxiety, circadian preference and the week of pregnancy were the most significant predictors of sleep quality. Women with at least one child and women who did not prepare for childbirth and motherhood and had not encountered information about a child’s sleep scored higher in BISQ-R. A hypothesis can be put forward that sufficient information before childbirth and earlier maternal experiences can affect expectations about a child’s sleep. This hypothesis would need to be verified in future research.
Efficient Edge-AI Models for Robust ECG Abnormality Detection on Resource-Constrained Hardware
Authors: Huang Zhaojing , Herbozo Contreras Luis Fernando , Leung Wing Hang , Yu Leping , Truong Nhan Duy , Nikpour Armin , Kavehei Omid 
Published: March 2024

AbstractThis study introduces two models, ConvLSTM2D-liquid time-constant network (CLTC) and ConvLSTM2D-closed-form continuous-time neural network (CCfC), designed for abnormality identification using electrocardiogram (ECG) data. Trained on the Telehealth Network of Minas Gerais (TNMG) subset dataset, both models were evaluated for their performance, generalizability capacity, and resilience. They demonstrated comparable results in terms of F1 scores and AUROC values. The CCfC model achieved slightly higher accuracy, while the CLTC model showed better handling of empty channels. Remarkably, the models were successfully deployed on a resource-constrained microcontroller, proving their suitability for edge device applications. Generalization capabilities were confirmed through the evaluation on the China Physiological Signal Challenge 2018 (CPSC) dataset. The models’ efficient resource utilization, occupying 70.6% of memory and 9.4% of flash memory, makes them promising candidates for real-world healthcare applications. Overall, this research advances abnormality identification in ECG data, contributing to the progress of AI in healthcare.
Graphical Abstract
CA-CAS-01-A: A Permissive Cell Line for Isolation and Live Attenuated Vaccine Development Against African Swine Fever Virus
Authors: Lee Seung-Chul , Kim Yongkwan , Cha Ji-Won , Chathuranga Kiramage , Dodantenna Niranjan , Kwon Hyeok-Il , Kim Min Ho , Jheong Weonhwa , Yoon In-Joong , Lee Joo Young , Yoo Sung-Sik , Lee Jong-Soo 
Published: March 2024

AbstractAfrican swine fever virus (ASFV) is the causative agent of the highly lethal African swine fever disease that affects domestic pigs and wild boars. In spite of the rapid spread of the virus worldwide, there is no licensed vaccine available. The lack of a suitable cell line for ASFV propagation hinders the development of a safe and effective vaccine. For ASFV propagation, primary swine macrophages and monocytes have been widely studied. However, obtaining these cells can be time-consuming and expensive, making them unsuitable for mass vaccine production. The goal of this study was to validate the suitability of novel CA-CAS-01-A (CAS-01) cells, which was identified as a highly permissive cell clone for ASFV replication in the MA-104 parental cell line for live attenuated vaccine development. Through a screening experiment, maximum ASFV replication was observed in the CAS-01 cell compared to other sub-clones of MA-104 with 14.89 and log10 7.5 ± 0.15 Ct value and TCID50/ml value respectively. When CAS-01 cells are inoculated with ASFV, replication of ASFV was confirmed by Ct value for ASFV DNA, HAD50/ml assay, TCID50/ml assay, and cytopathic effects and hemadsoption were observed similar to those in primary porcine alveolar macrophages after 5th passage. Additionally, we demonstrated stable replication and adaptation of ASFV over the serial passage. These results suggest that CAS-01 cells will be a valuable and promising cell line for ASFV isolation, replication, and development of live attenuated vaccines.
Using structure from motion for analyzing change detection and flood events in the context of flood preparedness: a case study for the Laufer Muehle area at the Aisch river in Germany for conducting near real-time analyses
Authors: Kögel Michael , Carstensen Dirk 
Published: March 2024

AbstractRecent flood events (FE) in Germany have shown that the extent and impact of extreme flood events cannot be estimated solely based on numerical models. For analyzing the development of such an event and to develop and implement safety measures more efficiently, additional data must be collected during the event. Within the scope of this research, the possibilities of near real-time recording using an unmanned aerial vehicle (UAV) and data processing with the Structure from Motion (SfM) method were tested in a case study. Different recording parameter combinations were tested in the Laufer Muehle area on the Aisch river in Germany. The focus of the investigations was the identification of a parameter combination that allows a short recording interval for aerial imagery. Based on these findings, the identification of changes in the study area by comparing multitemporal photography (flood prevention), as well as the recording of flooded areas during a FE should be possible. The accuracy analysis of the different parameter combinations between two point clouds as well as the process of change detection was done by a Multiscale Model to Model Cloud Comparison (M3C2) and including ground control points. As a result, a parameter combination was identified which led to the desired results in the study area. The processes were transformed into fully automated and scripted workflows. The results serve as a basis for establishing a workflow for near real-time analyses in future studies.
Role of long non-coding RNA ELFN1-AS1 in carcinogenesis
Authors: HajiEsmailpoor Zanyar , Fayazi Alireza , Teymouri Mohammadhossein , Tabnak Peyman 
Published: March 2024

AbstractAs one of the leading causes of death worldwide, cancer significantly burdens patients and the healthcare system. The role of long non-protein coding RNAs (lncRNAs) in carcinogenesis has been extensively studied. The lncRNA ELFN1-AS1 was discovered recently, and subsequent studies have revealed its aberrantly high expression in various cancer tissues. In vitro and in vivo experiments have consistently demonstrated the close association between increased ELFN1-AS1 expression and malignant tumor characteristics, particularly in gastrointestinal malignancies. Functional assays have further revealed the mechanistic role of ELFN1-AS1 as a competitive endogenous RNA for microRNAs, inducing tumor growth, invasive features, and drug resistance. Additionally, the investigation into the clinical implication of ELFN1-AS1 has demonstrated its potential as a diagnostic, therapeutic, and, notably, prognostic marker. This review provides a comprehensive summary of evidence regarding the involvement of ELFN1-AS1 in cancer initiation and development, highlighting its clinical significance.
Dynamic multi-label feature selection algorithm based on label importance and label correlation
Authors: Chen Weiliang , Sun Xiao 
Published: March 2024

AbstractMulti-label distribution is a popular direction in current machine learning research and is relevant to many practical problems. In multi-label learning, samples are usually described by high-dimensional features, many of which are redundant or invalid. This paper proposes a multi-label static feature selection algorithm to solve the problems caused by high-dimensional features of multi-label learning samples. This algorithm is based on label importance and label relevance, and improves the neighborhood rough set model. One reason for using neighborhood rough sets is that feature selection using neighborhood rough sets does not require any prior knowledge of the feature space structure. Another reason is that it does not destroy the neighborhood and order structure of the data when processing multi-label data. The method of mutual information is used to achieve the extension from single labels to multiple labels in the multi-label neighborhood; through this method, the label importance and label relevance of multi-label data are connected. In addition, in the multi-label task scenario, features may be interdependent and interrelated, and features often arrive incrementally or can be extracted continuously; we call these flow features. Traditional static feature selection algorithms do not handle flow features well. Therefore, this paper proposes a dynamic feature selection algorithm for flow features, which is based on previous static feature selection algorithms. The proposed static and dynamic algorithms have been tested on a multi-label learning task set and the experimental results show the effectiveness of both algorithms.
Morphology, Crystal Structure and Thermal Properties of Nano-Sized Amorphous Colemanite Synthesis
Authors: Kutuk Sezai 
Published: March 2024

AbstractIt is important to utilize the raw colemanite (RC) mineral, which has abundant reserves in the world, and to reduce its particles to smaller sizes for nanotechnology. However, not only the particle size of the produced colemanite powder but also its other properties need to be elucidated. By using the Taguchi design, the RC mineral was ground in a high-energy ball mill. From signal-to-noise (S/N) ratio, the smallest average particle size was found to be 3.10 µm for the experiment E04/nano-sized amorphous colemanite (NAC) powder. The characteristics of as-received RC mineral and synthesized NAC material were investigated using laser particle size analyzer, optical microscopes, SEM–EDS, XRD, TEM, HRTEM, and TGA–DTA devices. It was found that the NAC powder was not homogeneous, a small peak within the 300–20 nm range appeared, and d90, d50, d10, and dmin values were, respectively, 14.6 µm, 3.08 µm, 232 nm, and 26 nm. In the XRD analysis, the pure colemanite, calcite, and silica minerals were determined. The crystal structure of the NAC powder almost turned amorphous, and the crystallite size of (031) peak was reduced to 7.3 nm. It was deduced that the average particle size was 8.29 nm (R2 = 0.86), and the d-spacing value was 0.307 nm. This significant finding was attributed to the mobility of balls and moreover it was interpreted with an equation. An unknown transition in TGA–DTA was referred to the calcite mineral. Finally, it is believed that the synthesized NAC material will be beneficial to engineering studies as a natural/mineral additive.
Effect of Heat Treatment and Reinforcement Content on the Wear Behavior of Al–4Cu/Al2O3–CNT Nanocomposites
Authors: Özer Emre , Ayvaz Mehmet , Übeyli Mustafa , Sarpkaya İbrahim 
Published: March 2024

AbstractIn the study, the effects of hybrid reinforcement (nano-alumina and MWCNT) and heat treatment on the wear behavior of the Al–4Cu nanocomposites were investigated under dry sliding condition against W–6Co ball by means of a ball-on-disk type tribometer. The load and the sliding speed were kept constant and selected to be 10 N and 0.1 m s−1, respectively, in the course of the wear tests. Meanwhile, the wear tests were completed after a total sliding distance of 1500 m was reached for each case. During these tests, the wear loss of the nanocomposites was measured at every 250 m. The worn surfaces of the nanocomposites were examined with the help of stereo and scanning electron microscopes. The volumetric wear rates, wear coefficients and wear mechanisms were identified for the nanocomposites to clarify the influence of reinforcement content and heat treatment on their wear resistance. The volume loss at the wear distance of 1500 m was obtained as 24.9 and 8.2 mm3 for the annealed and aged Al–4Cu alloy, respectively. On the other hand, it decreased to 4.6 and 3.2 mm3 in the case of the nanocomposites with 15% hybrid reinforcement in the annealed and aged conditions, successively. Moreover, increasing the hybrid reinforcement amount decreased the wear loss of the aged nanocomposites substantially in such a way that it resulted in the mild wear.
Identification of a novel gene signature related to prognosis and metastasis in gastric cancer
Authors: Elizazu Joseba , Artetxe-Zurutuza Aizpea , Otaegi-Ugartemendia Maddalen , Moncho-Amor Veronica , Moreno-Valladares Manuel , Matheu Ander , Carrasco-Garcia Estefania 
Published: March 2024

Abstract
Background
Gastric Cancer (GC) presents poor outcome, which is consequence of the high incidence of recurrence and metastasis at early stages. GC patients presenting recurrent or metastatic disease display a median life expectancy of only 8 months. The mechanisms underlying GC progression remain poorly understood.

Methods
We took advantage of public available GC datasets from TCGA using GEPIA, and identified the matched genes among the 100 genes most significantly associated with overall survival (OS) and disease free survival (DFS). Results were confirmed in ACRG cohort and in over 2000 GC cases obtained from several cohorts integrated using our own analysis pipeline. The Kaplan-Meier method and multivariate Cox regression analyses were used for prognostic significance and linear modelling and correlation analyses for association with clinic-pathological parameters and biological hallmarks. In vitro and in vivo functional studies were performed in GC cells with candidate genes and the related molecular pathways were studied by RNA sequencing.

Results
High expression of ANKRD6, ITIH3, SORCS3, NPY1R and CCDC178 individually and as a signature was associated with poor prognosis and recurrent disease in GC. Moreover, the expression of ANKRD6 and ITIH3 was significantly higher in metastasis and their levels associated to Epithelial to Mesenchymal Transition (EMT) and stemness markers. In line with this, RNAseq analysis revealed genes involved in EMT differentially expressed in ANKRD6 silencing cells. Finally, ANKRD6 silencing in GC metastatic cells showed impairment in GC tumorigenic and metastatic traits in vitro and in vivo.

Conclusions
Our study identified a novel signature involved in GC malignancy and prognosis, and revealed a novel pro-metastatic role of ANKRD6 in GC.
A Deep Convolutional Spiking Neural Network for embedded applications
Authors: Javanshir Amirhossein , Nguyen Thanh Thi , Parvez Mahmud M. A. , Kouzani Abbas Z. 
Published: March 2024

AbstractDeep neural networks (DNNs) have received a great deal of interest in solving everyday tasks in recent years. However, their computational and energy costs limit their use on mobile and edge devices. The neuromorphic computing approach called spiking neural networks (SNNs) represents a potential solution for bridging the gap between performance and computational expense. Despite the potential benefits of energy efficiency, the current SNNs are being used with datasets such as MNIST, Fashion-MNIST, and CIFAR10, limiting their applications compared to DNNs. Therefore, the applicability of SNNs to real-world applications, such as scene classification and forecasting epileptic seizures, must be demonstrated yet. This paper develops a deep convolutional spiking neural network (DCSNN) for embedded applications. We explore a convolutional architecture, Visual Geometry Group (VGG16), to implement deeper SNNs. To train a spiking model, we convert the pre-trained VGG16 into corresponding spiking equivalents with nearly comparable performance to the original one. The trained weights of VGG16 were then transferred to the equivalent SNN architecture while performing a proper weight–threshold balancing. The model is evaluated in two case studies: land use and land cover classification, and epileptic seizure detection. Experimental results show a classification accuracy of 94.88%, and seizure detection specificity of 99.45% and a sensitivity of 95.06%. It is confirmed that conversion-based training SNNs are promising, and the benefits of DNNs, such as solving complex and real-world problems, become available to SNNs.
Outpatient parenteral antimicrobial therapy (OPAT) in Germany: insights and clinical outcomes from the K-APAT cohort study
Authors: Schmidt-Hellerau Kirsten , Baade Nina , Günther Marina , Scholten Nadine , Lindemann Christoph Heinrich , Leisse Charlotte , Oberröhrmann Charlotte , Peter Sophie , Jung Norma , Suarez Isabelle , Horn Carola , Ihle Peter , Küpper-Nybelen Jutta , Hagemeier Anna , Hellmich Martin , Lehmann Clara 
Published: March 2024

Abstract
Purpose
Outpatient parenteral antimicrobial therapy (OPAT) offers several key advantages, including enhanced patient quality of life, reduced healthcare costs, and a potential reduction of nosocomial infections. It is acknowledged for its safety and effectiveness. This study provides the first systematic clinical data for Germany, where OPAT has not yet been widely adopted. The aim is to establish a foundational reference point for further research and integration of OPAT into the German healthcare system.

Methods
This prospective observational study descriptively analyses data obtained from a cohort of patients receiving OPAT. Both in- and outpatients from all medical specialties could be recruited. Patients administered the anti-infective medications themselves at home using elastomeric pumps.

Results
77 patients received OPAT, with a median duration of 15 days and saving 1782 inpatient days. The most frequently treated entities were orthopaedic infections (n = 20, 26%), S. aureus bloodstream infection (n = 16, 21%) and infectious endocarditis (n = 11, 14%). The most frequently applied drugs were flucloxacillin (n = 18, 23%), penicillin G (n = 13, 17%) and ceftriaxone (n = 10; 13%). Only 5% of patients (n = 4) reported to have missed more than one outpatient dose (max. 3 per patient). Only one catheter-related adverse event required medical intervention, and there were no catheter-related infections.

Conclusion
The study demonstrates that OPAT can be safely conducted in Germany. In preparation for its broader implementation, crucial next steps include creating medical guidelines, fostering interdisciplinary and inter-sectoral communication, as well as creating financial and structural regulations that facilitate and encourage the adoption of OPAT.

Trial registration number
NCT04002453.
Role of source control in critically ill candidemic patients: a multicenter retrospective study
Authors: Marangos Markos , Ioannou Petros , Senn Laurence , Spiliopoulou Anastasia , Tzalis Sotiris , Kolonitsiou Fevronia , Valta Maria , Kokkini Sofia , Pagani Jean-Luc , Stafylaki Dimitra , Paliogianni Fotini , Fligou Fotini , Kofteridis Diamantis P. , Lamoth Frédéric , Papadimitriou-Olivgeris Matthaios 
Published: March 2024

Abstract
Purpose
Candidemia is associated with high mortality especially in critically ill patients. Our aim was to identify predictors of mortality among critically ill patients with candidemia with a focus on early interventions that can improve prognosis.

Methods
Multicenter retrospective study.

Setting
This retrospective study was conducted in Intensive Care Units from three European university hospitals from 2015 to 2021. Adult patients with at least one positive blood culture for Candida spp. were included. Patients who did not require source control were excluded. Primary outcome was 14-day mortality.

Results
A total of 409 episodes of candidemia were included. Most candidemias were catheter related (173; 41%), followed by unknown origin (170; 40%). Septic shock developed in 43% episodes. Overall, 14-day mortality rate was 29%. In Cox proportional hazards regression model, septic shock (P 0.001; HR 2.20, CI 1.38–3.50), SOFA score ≥ 10 points (P 0.008; HR 1.83, CI 1.18–2.86), and prior SARS-CoV-2 infection (P 0.003; HR 1.87, CI 1.23–2.85) were associated with 14-day mortality, while combined early appropriate antifungal treatment and source control (P < 0.001; HR 0.15, CI 0.08–0.28), and early source control without appropriate antifungal treatment (P < 0.001; HR 0.23, CI 0.12–0.47) were associated with better survival compared to those without neither early appropriate antifungal treatment nor source control.

Conclusion
Early source control was associated with better outcome among candidemic critically ill patients.