bluuebunny/crossref_metadata_2025_split huggingface dataset:
A meta-analysis on safety and efficacy of CD19 directed CAR T-cells generated using sleeping beauty transposon system
Authors: Rajput Anugya , Sajjad Syed Ammar , Kumar Anup , Singh Kulwant 
Published: July 2024

Abstract

Chimeric antigen receptor (CAR) T-cell therapy has emerged as a potentially curative approach for hematological malignancies. The sleeping beauty (SB) transposon system represents a non-viral approach to CAR T-cell generation offering several advantages including low immunogenicity, scalability, and cost-effectiveness over existing methods. Despite significant clinical advances, the efficacy and safety of SB-generated CAR T-cells have not been adequately addressed. This meta-analysis aims to evaluate the efficacy and safety of SB-generated CAR T-cell therapy across B-cell malignancies. A systematic literature search was conducted through databases, PubMed, Google Scholar, Open Alex, and Semantic scholar from 2012 to January 2024. A total of 10 studies encompassing 153 patients were found eligible. The pooled analysis demonstrated an overall response rate of 71%, with complete response achieved in 66% of patients. Moreover, 55% of patients demonstrated progression-free survival (PFS) with a median follow-up of 30 months and 55% of patients achieved measurable residual disease (MRD) negative remission. Notably, few patients experienced cytokine release syndrome (CRS) of grade 1-2; however, neurotoxicity were not described as prevalent side effects. SB-generated anti-CD19 CAR T-cell therapy demonstrates promising efficacy in B-cell malignancies, with favorable safety profiles. However, the outcomes of this meta-analysis underscore the need for further clinical development. PROSPERO registration No. CRD42024507597. Keywords: CD19, hematological malignancies, sleeping beauty chimeric antigen receptor, meta-analysis, clinical trial, non-viral gene transfer.
PROSPERO registration No. CRD42024507597.
A psychological construct for aiming in First-Person Shooters
Authors: Koïdé Nami , Altakroury Hamza , Poli Alizée , Mahdar-Recorbet Loann , Trognon Arthur 
Published: July 2024

Abstract

The complexities of the structure of aiming skills in competitive first-person shooters (FPS) have prompted much discussion within online communities but little-to-no empirical scrutiny within academia. This study aims to address this gap by employing psychometric methods to validate the construct validity and factorial structure of the aiming skills in FPS games, thought to rely on two "Tracking" and "Flicking" sub-skills. In this work, 61 FPS gamers were recruited to complete a playlist of six training exercises widely recognized within the gaming community designed to measure basic "Tracking" and "Flicking" abilities. Internal consistency was assessed using Cronbach’s alpha and Confirmatory factor analysis was conducted to test the two-factor model of aiming. Cronbach's alpha indicated high internal consistency across all exercises, but with values exceeding the recommended threshold. In other hands, confirmatory factor analysis revealed that the two-factor model for "Tracking" and "Flicking" fit satisfactorily, with strong factor loadings for each exercise and a significant correlation between the factors. These findings contribute to the evidence of the existence of specific psychomotor skillsets required in FPS games and suggest that such measures can effectively capture the dimensionality of aiming skills. Future research should further refine these measures to enhance training and performance in FPS gaming contexts.
Chronic Kidney Disease and Adherence Improvement Program by Clinical Pharmacist-provided Medication Therapy Management; A Quasi-experimental Assessment of Patients’ Self-care Perception and Practice
Authors: Mohammadnezhad Ghader , Ehdaivand Sadaf , Azadmehr Behniya , Ziaie Shadi , Esmaily Hadi 
Published: July 2024

Abstract

Objectives
This study aimed to assess the perceptions, adherence, and performance of the patients with chronic kidney disease (CKD) to the clinical pharmacist-provided MTM before and after receiving this service.
Method
A cross-sectional survey was conducted from June 2023 to January 2024. A validated questionnaire assessed patients' knowledge, attitude, and performance, and the Morisky medication adherence scale evaluated the medical adherence of the patients before and after the clinical pharmacist-provided MTM. Inclusion criteria were patients with CKD according to NKF KDOQI guidelines and GFR < 60 mL/min/1.73 m2. Before and after the MTM service, CKD patients' knowledge, attitude, performance, and adherence to their pharmacotherapy were assessed.
Results
A total of 100 patients enrolled in the study and completed the questionnaire. Before and after the MTM service, total knowledge was 3.38 ± 1.82 and 7.59 ± 1.11, respectively. Before and after the MTM service, the attitude score was 54.53 ± 5.05 and 59.24 ± 4.68, respectively. Before and after the MTM service, the mean performance score was 30.15 ± 4.27 and 34.54 ± 2.56, respectively. Adherence score to medications before and after the MTM service was 4.86 ± 1.99 and 6.22 ± 1.39, respectively. In all fields, outcomes significantly improved (P < 0.05).
Conclusion
The current study showed the critical role of clinical pharmacists in training patients about medications and improving adherence to their pharmacotherapy.
Estimation of high-resolution surface soil moisture through GIS-based frequency ratio modeling
Authors: SAMANTA SAILESH 
Published: July 2024

Abstract

This research established an empirical methodology for estimating higher-resolution soil moisture using GIS and frequency ratio (FR) modeling techniques. Soil moisture active passive (SMAP) Level-4 global 3-hourly 9 km spatial resolution surface and root zone soil moisture datasets were used as reference data. A total of 283 reference points were selected through spatial fishnet analysis with the root zone soil moisture over 0.35 and surface soil moisture over 0.30. Eighty percent (80%) of these reference points served as inputs to the FR model, with the remaining twenty percent (20%) reserved for validation. Key independent variables incorporated in the FR modeling process included land use land cover, soil texture, normalized difference vegetation index, land surface temperature, topographic wetness index, rainfall, elevation, slope, and distance from rivers. The study area encompassed the final drainage basin of the Markham River catchment, situated in the Morobe Province of Papua New Guinea. The high-resolution developed database on surface soil moisture was reclassified into five basic zones segmenting on the FR index value, namely very low (less than 6), low (6–7), moderate (7–8), high (8–9), and very high (More than 9). The result indicates almost 26.10% of the land area is classified as a high soil moisture class and 56.89% as a very high soil moisture class. The FR model evinced a prediction accuracy of 93.98% along with a succession rate of 91.59%. These results provide useful data for scientific applications in various domains, specifically in the agricultural sector, local government administrator, researcher, and planner.
Development and validation of a nomogram model for predicting postoperative delirium in older adults undergoing free flap reconstruction after oral cancer surgery
Authors: Ying Chen , Xiaona Liu , Aili Zhang , Zengxiang Wang , Ying Wu , Yu Pu , Hongbo Zhang , Danni Wang , Meiping Jiang , Hongyuan Dai 
Published: July 2024

Abstract

Objective: This study aimed to develop and internally validate a dynamic a nomogram model by analysing the risk factors for postoperative delirium (POD) in elderly patients undergoing free flap reconstruction for oral cancer.
Methods: This was a single-centre, retrospective study. We used the convenience sampling method to select 359 elderly oral cancer patients from January 2020-August 2023 in the Oral and Maxillofacial Surgery Ward of Nanjing Stomatological Hospital as the study population. The original dataset was randomly divided into a training group (n=252) and a validation group (n=107) by a computer-generated random number sequence in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator Regression (LASSO regression) were used to screen the best predictor variables. Logistic regression was used to build the model and visualized by nomogram. The performance of the model was evaluated by area under the curve (AUC), calibration curve and decision curve analysis (DCA).
Results: Our prediction model showed that six variables, age, sex, marriage, preoperative anxiety, preoperative sleep disorder, and ICU length of stay, were associated with POD. The nomogram showed high predictive accuracy with an AUC of 0.82 (95% CI: 0.76-0.87) for the training group and 0.84 (95% CI: 0.76-0.92) for the internal validation group. In both the training and validation groups, there was good agreement between the predicted results and the true observations. Decision curve analyses in the training and validation groups showed that the predictive model had a good net clinical benefit.
Conclusion: We developed a new predictive model to predict risk factors for POD in elderly oral cancer patients. This simple and reliable nomogram can help physicians assess POD quickly and effectively, and has the potential to be widely used in the clinic after more external validation.
Artificial Intelligence in Vocational Education and Training (VET): Evaluating VET Leaders’ Acceptance of AI in Switzerland
Authors: Seufert Sabine 
Published: July 2024

Abstract

Artificial intelligence (AI) is having a transformative impact on both the labour market and education systems. Vocational education and training (VET) leaders play a crucial role in shaping the future of education and training by guiding strategic decisions and policy directions; without VET leaders, efforts to integrate AI into VET risk facing significant barriers to wider uptake. Research that is focused on harnessing AI capabilities to innovate VET systems and the leadership required are rare. Therefore, the aim of this study is to assess VET leaders' acceptance of AI (TAM, Davis, 1989; UTAUT, Venkatesch et al., 2003). An online survey was conducted in February 2023 to assess the general acceptance of AI and AI-based use cases for VET. A total of 111 VET experts participated in the online survey. Each expert is a senior VET manager who leads a specific unit in the VET system. The empirical data suggest that there may be widespread agreement among VET leaders about the ability of personalised competence development to improve equity and inclusivity. However, use cases for increasing the strength of the links between the labour market and education system with data-driven approaches are less widely accepted. The empirical findings of this study provide a situational analysis of the acceptance of AI by VET leaders. Furthermore, the findings can also elucidate existing knowledge gaps of VET leaders regarding AI capabilities, applications, and implications.
“Effect of Castor Oil on Esophageal Stricture in Rats; Expression of ST-2, IL-6, Neopterin Proteins in Corrosive Burn Model”
Authors: AYCENK Aybegum KALYONCU , YALCIN Onur , GURPINAR Ahmet Burak , GUMUS Ceren YAPAR , KORKMAZ Ozge KAYA , NOYAN Tevfik , ARICI Yeliz KASKO 
Published: July 2024

Abstract

Corrosive esophageal burn (CEB) is a disease with high mortality and morbidity rates. The aim of this study was to determine the efficacy of castor oil, in preventing stricture development at the experimental CEB model. In addition to studying standard histopathological damage data, neopterin, IL-33, and sSt-2 proteins were also studied for the first time. Fifty Wistar-Albino rats were divided into randomized 5 groups. Weight measurement, esophageal length, histopathological damage score (HDS) and stenosis score, tissue caspase-3 and VEGF staining, tissue hydroxyproline (HYP), blood TNF-Alpha, IL-6, IL-33, Neopterin, and sST-2 levels were measured. In the castor oil application groups, weight gain was observed, the acute phase reaction decreased, submucosal/tunica muscularis fibrosis and mucosal damage were reduced, and total stenosis scores and histopathological damage scores decreased. While no significant difference was detected in the ST-2 protein, which was used for the first time in this study model, a significant increase in neopterin protein was observed in the application groups. Results indicate the nutritional contribution of castor oil, as well as its tissue healing and esophageal stricture-preventing efficacy at histopathological and immune-histochemical levels.
Tritrophic effects of different cereal flour on life table parameters and population projection of Habrobracon hebetor (Hymenoptera: Braconidae)
Authors: Mostafazadeh Narges , Mehrkhou Fariba , Naghshbandi Nabat , Atlihan Remzi 
Published: July 2024

Abstract

The parasitoid wasp, Habracon hebetor, Say is used widely in mass production against larval stage of field and stored product insect pests. Less is known about the third-trophic level effects of cereal flour on the population dynamics of H. hebetor. In this study, tritrophic level effects of three cereal flours (wheat, corn, and barley) on population dynamics and population projection of H. hebetor were studied. Data were analyzed by constructing the age-stage, two-sex life table, to take into consideration either female or male and stage differentiation. According to our results, the used corn host type (var.704) was more suitable host for H. hebetor than wheat and barley due to the shortening developmental time (10.76 ± 0.08 d), increasing survival rate (0.74 ± 0.006), female longevity (14.93 ± 0.92 d) and fecundity (91.20 ± 9.05 offspring/female). Also, the population growth parameters, including the intrinsic rate of increase (0.2217 ± 0.0178 d− 1), finite rate of increase (1.25 ± 0.02 d− 1), and reproductive rate (27.92 ± 6.57 offspring) were the highest on corn host type. Interestingly, the predicted of population growth of H. hebetor was the fastest and highest on corn, followed by wheat, and barley. The results of this study provide direction to design a comprehensive program for the mass rearing of H. hebetor.
Towards Yoruba-Speaking Google Maps Navigation
Authors: Oyesanmi Fiyinfoluwa , Olukanmi Peter 
Published: July 2024

Abstract

Advances in natural language processing (NLP) have made several technological interventions and services available to people in different languages. One such service is the Google Maps direction narration which provides real-time oral assistance to tourists, and visitors in a new or unknown location. Like most related assistive technologies, this service is primarily developed in the English language with support for some other Western languages over time, and the African languages are largely neglected. This paper seeks to leverage advances in NLP techniques and models in the design of a speech-to-speech (STS) translation of the Google Maps direction narration in English to the Yoruba language, one of the most widely spoken languages in Western Africa. We begin with an exploration of various state-of-the-art NLP techniques for Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-speech (TTS) models that make up the designed system. We presented the performance of the models we explored towards the design and implementation of a robust STS translation of the Google Maps direction narration in the Yoruba language.
Long-term outcomes after percutaneous coronary intervention versus coronary artery bypass grafting in women, a meta-analysis
Authors: Pérez-Camargo Daniel , Campelos-Fernández Paula , Travieso Alejandro , Montero-Cruces Lourdes , Carnero-Alcázar Manuel , Olmos-Blanco Carmen , Cobiella-Carnicer Javier , Álvarez-Arcaya Arantzazu , Reguillo-Lacruz Fernando , Maroto-Castellanos Luis C. 
Published: July 2024

Abstract

Background
Despite the advances in the last decades for treatment of ischemic heart disease, women continue to experience poorer prognosis than men and currently, there is a gap in knowledge regarding the optimal revascularization strategy in women.
Objective
Compare the long-term outcomes of percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) for the treatment of stable ischemic heart disease in women.
Methods
A systematic search was conducted including randomized clinical trials (RCTs) comparing PCI with drug-eluting stents with CABG. The primary outcome were the composite outcomes of death, stroke or myocardial infarction (MI) and death, stroke, MI or repeat revascularization. Secondary outcomes included the individual components of the primary outcomes. Pooled hazard ratios with 95% confidence intervals were calculated in a fixed- effects meta-analysis using the inverse of variance method. Risk of bias and sensitivity analyses were also conducted.
Results
Six multicenter, RCTs were included after eligibility assessment. Median follow-up was 6.25 years (IQR: 5- 2.5). A significant benefit for CABG over PCI was observed for the primary composite outcomes of death, stroke, MI (HR = 1.24; 95% CI 1.01–1.52; p = 0.037) and death, stroke, MI or repeat revascularization (HR = 1.60; 95% CI 1.25–2.03; p < 0.000).
Conclusion
In the present study-level metanalysis, CABG is associated with a lower risk of major adverse cardiovascular events than PCI at long term follow-up in women.
Application of Three-dimensional Visualization Technology in Early Surgical Repair of Bile Duct Injury During Laparoscopic Cholecystectomy
Authors: Yang Zhiqi , Liu Jing , Wu Lang , Ding Yang , Ma Songbo , Yan Wentao , Lan Yong , Sha Xiaochun , Cheng Jianbin , Ma Zhiming , Li Minghao 
Published: July 2024

Abstract

Objective: This study aimed to explore the application value of three-dimensional (3D) visualization technology in the early surgical repair of bile duct injury during laparoscopic cholecystectomy (LC).
Methods: A retrospective analysis was conducted on the clinical data of 15 patients who underwent early surgical repair of bile duct injury during LC with the assistance of 3D visualization technology at the Hepatobiliary Surgery Department of Ningxia Hui Autonomous Region People's Hospital from January 2019 to December 2022. Postoperative efficacy and long-term follow-up outcomes were summarized.
Results: Before the repair surgery, 15 cases of bile duct injury during LC were evaluated using 3D visualization technology according to the Strasberg-Bismuth classification: 2 cases of type C, 4 of type E1, 3 of type E2, 3 of type E3, and 3 of type E4. Intraoperative findings were consistent with the 3D visualization reconstruction results, and all patients successfully underwent hepaticojejunostomy using Roux-en-Y anastomosis guided by the 3D visualization navigation. The time interval between LC and bile duct repair surgery ranged from 5 to 28 (14.2 ± 9.7) days. The surgical time was between 120 and 190 (156.40 ± 23.92) min, and estimated blood loss ranged from 80 to 250 (119.66 ± 47.60) mL. The length of hospital stay ranged from 12 to 25 days (median: 16 days). One patient experienced mild bile leakage after the operation, which healed with conservative treatment. All patients were followed up for 12–56 months (median: 34 months) without any loss to follow-up. During the follow-up period, no complications, such as anastomotic stricture or stone formation, were observed.
Conclusion: The application of 3D visualization technology for preoperative evaluation and intraoperative navigation can accurately and effectively facilitate early surgical repair of bile duct injury during LC and has clinical value for promotion and application.
Luteolin attenuate paraquat-induced acute lung injury by regulating autophagy through the PI3K/AKT/mTOR pathway
Authors: Yi Yang , Li Nan , Huang Yue , Peng Jichao , Li Zhao , Wang Ying , Liu Xiaoran 
Published: July 2024

Abstract

Acute lung injury (ALI) is the primary cause of death in patients who are affected by paraquat (PQ) poisoning. Luteolin (Lut) is a flavone compound present in several medicinal plants. The present study aimed to explore the protective role of Lut in PQ-induced ALI and the underlying molecular mechanisms. Network pharmacology analysis was used to predict key genes and signaling pathways that were potentially involved in the therapeutic effect of Lut. In vivo, Lut inhibited PQ-induced lung pathological injury and decreased pulmonary vascular endothelial permeability. In vitro, human pulmonary microvascular endothelial cells were pretreated with Lut and then treated with PQ for 72 h. Lut reduced oxidative stress and decreased the production of inflammatory factors including IL-6, TNF-α, and IL-1β. Lut up-regulated the levels of the autophagy-associated proteins LC3-II/I and down-regulated the levels of P62, resulting in an increased number of autophagosomes. However, pretreatment with the autophagy inhibitor 3-methyladenine reversed the effects of Lut on inflammatory responses, oxidative stress, and cellular apoptosis, and the protective effects of Lut were related to regulation of the PI3K/Akt/mTOR pathway. In summary, Lut enhanced autophagy by regulating the PI3K/Akt/mTOR pathway, thereby alleviating inflammation and oxidative stress during PQ-induced ALI.
Algorithm Design and Optimization for Knowledge Fusion: A Graph Matching-based Approach
Authors: Li Chunguang , Shang Haixia , Wu Xiaolei , Wu Yuanyuan , Liu Lei 
Published: July 2024

Abstract

Knowledge fusion plays a crucial role in the construction of knowledge graphs, aiming to integrate knowledge from different data sources and improve the accuracy and completeness of the knowledge graph. Knowledge graphs built from different data sources often suffer from issues such as inconsistency, redundancy, and missing information, which negatively impact the quality and application effectiveness of the knowledge graph. Therefore, how to effectively fuse knowledge from different data sources has become an important topic in knowledge graph research. This paper proposes a graph matching-based algorithm for knowledge fusion, aiming to merge knowledge graphs from different sources into a unified one. The algorithm achieves knowledge fusion by identifying and matching identical or similar nodes and edges in different knowledge graphs, involving several steps including node matching, edge matching, and conflict resolution. Node matching identifies identical or similar nodes by calculating the similarity of their attributes, while edge matching further matches the relationships between nodes based on node matching. Conflict resolution is handled using rules or statistical methods to address conflicting information from different data sources, ensuring consistency and accuracy in the fusion results. To improve the efficiency and effectiveness of the algorithm, this paper proposes a series of optimization methods: feature selection and weight allocation, iterative matching and fusion, as well as parallel computing. Feature selection and weight allocation optimize the similarity calculation process by selecting key features and assigning appropriate weights to improve the accuracy of node and edge matching. Iterative matching and fusion continuously optimize fusion results by gradually performing node and edge matching. Parallel computing utilizes parallel computing techniques to accelerate the fusion process of large-scale knowledge graphs, enhancing algorithm processing capabilities and efficiency. Experimental results demonstrate significant effectiveness of the proposed algorithm in knowledge graph fusion. By testing with multiple publicly available knowledge graph datasets, the algorithm shows significant improvements in node matching accuracy, edge matching accuracy, and overall fusion quality compared to traditional fusion methods. Specifically, the average node matching accuracy has increased by over 10%, edge matching accuracy has significantly improved, and the overall fusion quality is also superior to the comparative methods. The experiments validate that the graph-based knowledge fusion algorithm can effectively enhance the quality and accuracy of knowledge graphs, demonstrating wide application prospects and practical value.