bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differential gene expression (DGE) analysis in persons with a history of giardiasis
Authors: Saeedi Parnia , Eslami Gilda , Tohidfar Masoud , Jafari-Nodushan AbbasAli , Vakili Mahmood 
Published: January 2024

AbstractGiardiasis, which is caused by Giardia duodenalis, has clinical symptoms such as steatorrhea and can be very dangerous in children. In addition, some documents reported that this parasite is present inside the tissue of patients with cancer. In this study, we analyzed the gene expression profiles of some main genes important to apoptosis and anti-apoptosis in humans.Expression profile arrays of Genomic Spatial Event (GSE) 113666, GSE113667, and GSE113679 obtained from Gene Expression Omnibus were used for meta-analysis using R commands. Cytoscape and STRING databases used the protein–protein Interaction network. Then, the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis was performed. Similar genes in Homo sapiens were identified using Basic Local Alignment Search Tool analysis. The validation was performed on eight people using real-time Polymerase chain reaction. In addition to the candidate genes, the gene expression of some other genes, including Serine/Threonine Kinase 1 (AKT1), Cyclin Dependent Kinase Inhibitor 2A (CDKN2A), Kirsten Rat Sarcoma (KRAS), and Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha (PIK3CA) were also examined. Analysis of the expression of serum amyloid A1 (SAA1), Regenerating Islet-Derived 3 Gamma (REG3G), and REG3A genes did not show any difference between the two groups of healthy and diseased people. Examining the mean expression of the four genes AKT1, CDKN2A, KRAS, and PIK3CA showed that three genes of AKT1, CDKN2A, and KRAS had increased expression in people with a history of giardiasis compared to healthy people. We showed that the gene expression pattern differs in apoptosis and anti-apoptosis signaling in people with a history of giardiasis. Giardia duodenalis seems to induce post-non-infectious symptoms with stimulation of human gene expression.
Deep semantic learning for acoustic scene classification
Authors: Shao Yun-Fei , Ma Xin-Xin , Ma Yong , Zhang Wei-Qiang 
Published: January 2024

AbstractAcoustic scene classification (ASC) is the process of identifying the acoustic environment or scene from which an audio signal is recorded. In this work, we propose an encoder-decoder-based approach to ASC, which is borrowed from the SegNet in image semantic segmentation tasks. We also propose a novel feature normalization method named Mixup Normalization, which combines channel-wise instance normalization and the Mixup method to learn useful information for scene and discard specific information related to different devices. In addition, we propose an event extraction block, which can extract the accurate semantic segmentation region from the segmentation network, to imitate the effect of image segmentation on audio features. With four data augmentation techniques, our best single system achieved an average accuracy of 71.26% on different devices in the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 ASC Task 1A dataset. The result indicates a minimum margin of 17% against the DCASE 2020 challenge Task 1A baseline system. It has lower complexity and higher performance compared with other state-of-the-art CNN models, without using any supplementary data other than the official challenge dataset.
Interpretable machine learning model for early prediction of 28-day mortality in ICU patients with sepsis-induced coagulopathy: development and validation
Authors: Zhou Shu , Lu Zongqing , Liu Yu , Wang Minjie , Zhou Wuming , Cui Xuanxuan , Zhang Jin , Xiao Wenyan , Hua Tianfeng , Zhu Huaqing , Yang Min 
Published: January 2024

Abstract
Objective
Sepsis-induced coagulopathy (SIC) is extremely common in individuals with sepsis, significantly associated with poor outcomes. This study attempted to develop an interpretable and generalizable machine learning (ML) model for early predicting the risk of 28-day death in patients with SIC.

Methods
In this retrospective cohort study, we extracted SIC patients from the Medical Information Mart for Intensive Care III (MIMIC-III), MIMIC-IV, and eICU-CRD database according to Toshiaki Iba's scale. And the overlapping in the MIMIC-IV was excluded for this study. Afterward, only the MIMIC-III cohort was randomly divided into the training set, and the internal validation set according to the ratio of 7:3, while the MIMIC-IV and eICU-CRD databases were considered the external validation sets. The predictive factors for 28-day mortality of SIC patients were determined using recursive feature elimination combined with tenfold cross-validation (RFECV). Then, we constructed models using ML algorithms. Multiple metrics were used for evaluation of performance of the models, including the area under the receiver operating characteristic curve (AUROC), area under the precision recall curve (AUPRC), accuracy, sensitivity, specificity, negative predictive value, positive predictive value, recall, and F1 score. Finally, Shapley Additive Explanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME) were employed to provide a reasonable interpretation for the prediction results.

Results
A total of 3280, 2798, and 1668 SIC patients were screened from MIMIC-III, MIMIC-IV, and eICU-CRD databases, respectively. Seventeen features were selected to construct ML prediction models. XGBoost had the best performance in predicting the 28-day mortality of SIC patients, with AUC of 0.828, 0.913 and 0.923, the AUPRC of 0.807, 0.796 and 0.921, the accuracy of 0.785, 0.885 and 0.891, the F1 scores were 0.63, 0.69 and 0.70 in MIMIC-III (internal validation set), MIMIC-IV, and eICU-CRD databases. The importance ranking and SHAP analyses showed that initial SOFA score, red blood cell distribution width (RDW), and age were the top three critical features in the XGBoost model.

Conclusions
We developed an optimal and explainable ML model to predict the risk of 28-day death of SIC patients 28-day death risk. Compared with conventional scoring systems, the XGBoost model performed better. The model established will have the potential to improve the level of clinical practice for SIC patients.

Graphical Abstract
Recent updates on central nervous system prophylaxis in patients with high-risk diffuse large B-cell lymphoma
Authors: Chua Bernard Ji Guang , Low Chen Ee , Yau Chun En , Tan Ya Hwee , Chiang Jianbang , Chang Esther Wei Yin , Chan Jason Yongsheng , Poon Eileen Yi Ling , Somasundaram Nagavalli , Rashid Mohamed Farid Bin Harunal , Tao Miriam , Lim Soon Thye , Yang Valerie Shiwen 
Published: January 2024

AbstractThe use of central nervous system (CNS) prophylaxis for patients with diffuse large B-cell lymphoma (DLBCL) remains controversial. Although uncommon, CNS relapses are invariably fatal in this otherwise curable disease. Accurate identification of patients at risk and the optimal approach to CNS prophylaxis therefore remains an area of unmet need. The existing literature, largely retrospective in nature, provides mixed conclusions regarding the efficacy of CNS prophylaxis. The utility of CNS prophylaxis has itself been challenged. In this review, we dissect the issues which render the value of CNS prophylaxis uncertain. We first compare international clinical guidelines for CNS prophylaxis. We then interrogate the factors that should be used to identify high-risk patients accurately. We also explore how clinical patterns of CNS relapse have changed in the pre-rituximab and rituximab era. We then discuss the efficacy of CNS-directed approaches, intensification of systemic treatment and other novel approaches in CNS prophylaxis. Improved diagnostics for early detection of CNS relapses and newer therapeutics for CNS prophylaxis are areas of active investigation. In an area where prospective, randomized studies are impracticable and lacking, guidance for the use of CNS prophylaxis will depend on rigorous statistical review of retrospective data.
Regional differences in synaptic degeneration are linked to alpha-synuclein burden and axonal damage in Parkinson’s disease and dementia with Lewy bodies
Authors: Frigerio Irene , Bouwman Maud M. A. , Noordermeer Ruby T. G. M. M. , Podobnik Ema , Popovic Marko , Timmermans Evelien , Rozemuller Annemieke J. M. , van de Berg Wilma D. J. , Jonkman Laura E. 
Published: January 2024

AbstractRegional differences in synaptic degeneration may underlie differences in clinical presentation and neuropathological disease progression in Parkinson’s Disease (PD) and Dementia with Lewy bodies (DLB). Here, we mapped and quantified synaptic degeneration in cortical brain regions in PD, PD with dementia (PDD) and DLB, and assessed whether regional differences in synaptic loss are linked to axonal degeneration and neuropathological burden. We included a total of 47 brain donors, 9 PD, 12 PDD, 6 DLB and 20 non-neurological controls. Synaptophysin+ and SV2A+ puncta were quantified in eight cortical regions using a high throughput microscopy approach. Neurofilament light chain (NfL) immunoreactivity, Lewy body (LB) density, phosphorylated-tau and amyloid-β load were also quantified. Group differences in synaptic density, and associations with neuropathological markers and Clinical Dementia Rating (CDR) scores, were investigated using linear mixed models. We found significantly decreased synaptophysin and SV2A densities in the cortex of PD, PDD and DLB cases compared to controls. Specifically, synaptic density was decreased in cortical regions affected at Braak α-synuclein stage 5 in PD (middle temporal gyrus, anterior cingulate and insula), and was additionally decreased in cortical regions affected at Braak α-synuclein stage 4 in PDD and DLB compared to controls (entorhinal cortex, parahippocampal gyrus and fusiform gyrus). Synaptic loss associated with higher NfL immunoreactivity and LB density. Global synaptophysin loss associated with longer disease duration and higher CDR scores. Synaptic neurodegeneration occurred in temporal, cingulate and insular cortices in PD, as well as in parahippocampal regions in PDD and DLB. In addition, synaptic loss was linked to axonal damage and severe α-synuclein burden. These results, together with the association between synaptic loss and disease progression and cognitive impairment, indicate that regional synaptic loss may underlie clinical differences between PD and PDD/DLB. Our results might provide useful information for the interpretation of synaptic biomarkers in vivo.
Eco-friendly nano-enabled fertilizers derived from date industry waste for sustainable and controlled-release of P, K and Mg nutrients: sorption mechanisms, controlled-release performance and kinetics
Authors: Elsabagh Samira S. , Elkhatib Elsayed A. , Rashad Mohamed 
Published: January 2024

AbstractDevelopment of nano-enabled fertilizers from green waste is one of the effective options to enhance global agricultural productions and minimize environmental pollution. In this study, novel, eco-friendly and cost-effective nano- enabled fertilizers (NEF) were synthesized using the planetary ball milling procedure. The NEF (nDPF1and nDPF2) were prepared by impregnation of nanostructured date palm pits (nDPP) with (KH2PO4 + MgO) at 1:1 and 3:1 (w/w) ratios respectively. The nDPP, nDPF1 and nDPF2 were extensively characterized. The produced nano-fertilizers enhanced soil water retention capacity with nDPF2 being the most effective. The water retention capacity of nDPF2 treated soil was 5.6 times higher than that of soil treated with conventional fertilizers. In addition, the nDPF2 exhibited superior sustained lower release rates of P, K and Mg nutrients for longer release periods in comparison with the conventional fertilizers. For instance, P cumulative release percentages from conventional fertilizers, nDPF1 and nDPF2 in soil reached 22.41%, 10.82 and 8.9% respectively within 384 h. Findings from FTIR and XPS analyses suggested that hydrogen bonding and ligand exchange were the main interaction mechanisms of PO4-K-Mg ions with nDPP surface. The released kinetics data of the NEF revealed that power function was the best suitable model to describe the kinetics of P, K and Mg release data from NEF in water and soil. Pot study ascertained that the nano-enabled fertilizers (nDPF1 and nDPF2) significantly promoted biomass production and nutrient uptake of maize plants as compared to commercial fertilizer treated plants. The present work demonstrated the potential of NEF to increase nutrients uptake efficiency, mitigate moisture retention problem in arid soils and reduce nutrients loss through leaching and safeguard the environment.
Graphical Abstract
Evaluating the resource management and profitability efficiencies of US commercial banks from a dynamic network perspective
Authors: Kweh Qian Long , Lu Wen-Min , Tone Kaoru , Liu Hsian-Ming 
Published: January 2024

AbstractThe central concept of strategic benchmarking is resource management efficiency, which ultimately results in profitability. However, little is known about performance measurement from resource-based perspectives. This study uses the data envelopment analysis (DEA) model with a dynamic network structure to measure the resource management and profitability efficiencies of 287 US commercial banks from 2010 to 2020. Furthermore, we provide frontier projections and incorporate five variables, namely capital adequacy, asset quality, management quality, earning ability, and liquidity (i.e., the CAMEL ratings). The results revealed that the room for improvement in bank performance is 55.4%. In addition, we found that the CAMEL ratings of efficient banks are generally higher than those of inefficient banks, and management quality, earnings quality, and liquidity ratios positively contribute to bank performance. Moreover, big banks are generally more efficient than small banks. Overall, this study continues the current heated debate on performance measurement in the banking industry, with a particular focus on the DEA application to answer the fundamental question of why resource management efficiency reflects benchmark firms and provides insights into how efficient management of CAMEL ratings would help in improving their performance.
Business cycle and herding behavior in stock returns: theory and evidence
Authors: Ahn Kwangwon , Cong Linxiao , Jang Hanwool , Kim Daniel Sungyeon 
Published: January 2024

AbstractThis study explains the role of economic uncertainty as a bridge between business cycles and investors’ herding behavior. Starting with a conventional stochastic differential equation representing the evolution of stock returns, we provide a simple theoretical model and empirically demonstrate it. Specifically, the growth rate of gross domestic product and the power law exponent are used as proxies for business cycles and herding behavior, respectively. We find stronger herding behavior during recessions than during booms. We attribute this to economic uncertainty, which leads to strong behavioral bias in the stock market. These findings are consistent with the predictions of the quantum model.
Metformin suppresses proliferation and glycolysis of gastric cancer by modulating ADAMTS12
Authors: Chen Rui , Chen Jianhui , Chen Miaoliang , Zhou Shenkang , Jiang Pinlu 
Published: January 2024

Abstract
Background
Gastric cancer (GC) is a common malignancy with its morbidity increasing worldwide. Hence, it is imperative to develop effective treatments. Studies have shown that metformin has potential antitumor effects. The objective of this study was to probe the antitumor mechanism of metformin in GC.

Methods
The expression of ADAMTS12 in GC tissues and its enrichment pathways were analyzed by bioinformatics methods. ADAMTS12 expression in GC cells was assessed by qRT-PCR. Cell viability and proliferation were analyzed by CCK-8 and colony formation assays, respectively. Extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) of GC cells in different treatment groups were analyzed by Seahorse XP 96, and glycolysis metabolites were detected by corresponding kits. Western blot was employed to analyze the level of glycolysis pathway related protein HK-2, and cell functional assays were conducted to verify the functions of metformin on GC cells. A xenograft model was constructed to validate the inhibitory role of metformin in GC.

Results
ADAMTS12 expression was elevated in GC tissues/cells and concentrated in glycolysis pathway. Cell functional assays found that ADAMTS12 promoted the proliferation and glycolysis of GC cells. Rescue experiments showed that metformin could reduce the promoting effect of ADAMTS12 overexpression on the proliferation and glycolysis of GC cells. In vivo studies confirmed that metformin suppressed the proliferation and glycolysis process via ADAMTS12 in GC cells.

Conclusion
Metformin can repress the proliferation and glycolysis of GC cells via ADAMTS12. The results suggest the potential of ADAMTS12 being a target for the metformin therapy of GC.
Predictors of progression of multiple sclerosis in a sample of Egyptian patients
Authors: Shawky Manar A. , Menecie Tarek I. , Saif El Deen Eman M. , Rashad Mohammed H. 
Published: January 2024

Abstract
Background
Multiple sclerosis (MS) is a multifactorial neurodegenerative autoimmune disease with a varied clinical course and presentation, which is more frequent than ever in the Middle East. The aim of this work is to investigate potential predictors of MS progression in order to help in early diagnose and predict progressive course of the disease.

Results
This is a retrospective case–control study conducted on a group of multiple sclerosis (MS) patients who developed secondary progression of the disease course (SPMS). The cases were matched with control MS patients who did not develop any disease progression (relapsing remitting MS (RRMS)). The matching was done for sex, and age with a ratio 1:1, total of 150 patients were included as cases and were matched with 150 control patients. Significant associations between MS progression and smoking, vitamin D deficiency, disease duration, delay in MS diagnosis, unemployment, site and number of lesions, and number of black holes were reported. About half of SPMS patients (53.3%) had 3 or more spinal lesions compared to only 1.4% of RRMS patients (p < 0.001). Moreover, about 76% of RRMS patients had no black holes in their radiological finding, while it was found that 35.3% of the SPMS patients had more than 5 black holes, compared to 8% of RRMS patients. Additionally, juxta-cortical site lesions were more frequent in SPMS than that in RRMS in a percentage 72.7 and 46%, respectively. Also, infra-tentorial lesions were found to be more frequent in SPMS group rather than RRMS group 92% and 78.7%, respectively.
On the other hand, a lower SDMT scale was associated with a shorter time to SPMS diagnosis in the multivariate Cox regression analysis adjusted to baseline factors and 25-FWT (HR: 0.928, 95% CI: 0.906–0.95).

Conclusions
MS secondary progression can be predicted among MS patients in routine practice comprising exposure history, clinical assessment, laboratory findings, and radiological examinations.
Quality of cultured eels as affected by pollution sources and risk assessment of dioxins and dioxin-like polychlorinated biphenyls
Authors: Liu Hao , Chen Jianan , Dong Meng , Pang Jie , Qin Lei , Huang Xuhui 
Published: January 2024

AbstractThe aim of this research was to determine the residues of dioxins and dioxin-like polychlorinated biphenyls in cultured eel and find out the source of pollution and the distribution pattern of eels. One hundred samples of eel, 4 fodder samples, and 12 environmental samples (water, plants, and soil) were collected from 4 cities and counties in Jiangxi Province, China. The contents of 17 kinds of dioxins (PCDD/Fs) and 12 kinds of dioxin-like polychlorinated biphenyls (dl-PCBs) were determined by high-resolution gas chromatography-tandem mass spectrometry, and the exposure risk was evaluated by using risk index. The total toxicity equivalence quantity (TEQ) of dioxin and dioxin-like polychlorinated biphenyls in eel and fodder samples collected in the study area were 0.65 ± 0.31 pg/g and 0.10 ± 0.02 pg/g, respectively. Dl-PCBs were the main dioxin pollution in eel and fodder samples. 2,3',4,4',5-pentachlorodiphenyl and 2,3,3',4,4'-pentachlorobiphenyl were the main contributing monomers. The environmental samples were mainly polluted by polychlorinated dibenzo-p-dioxins (PCDDs), with the main contributing monomer being Octachlorodibenzodioxins (OCDD), while 3,3',4,4',5-pentachlorobiphenyl and 2,3,4,7,8-pentachlorodibenzofuran were the main toxic compounds in eel and fodder. The dioxin pollution of eels cultured in Jiangxi Province was mainly from fodder polluted via dl-PCBs. The meat segment VI (tail) exhibited a strong enrichment effect of polychlorinated benzofurans (PCDFs). It should be the key part for dioxins and dioxin-like polychlorinated biphenyls assessment. Further, the results were helpful to improve the edible safety of eel products and the efficiency of the risk assessment of dioxins and dioxin-like polychlorinated biphenyls in fish.
Graphical Abstract
Novel similarity measure between hesitant fuzzy set and their applications in pattern recognition and clustering analysis
Authors: Gupta Rakhi , Kumar Satish 
Published: January 2024

AbstractThe extension of classical fuzzy sets are hesitant fuzzy sets (HFSs), in which each element has a possible value from [0,1]. Similarity and distance measures are useful implements for solving medical, clustering and pattern-recognition problems. Most of the researchers have suggested their ideas for HFSs using distance measures and extract the similarity measure from distance measure but most of them are getting inadequate results. Therefore, we proposed a new similarity measure to resolve these problems and also satisfied the properties of proposed measure for HFSs. Additionally, numerous examples are taken in consideration using HFS and compared the performance of existing measures with proposed measure for different cases. Furthermore, we have applied proposed measure for pattern recognition problems using three different examples and also calculate performance index (i.e., Degree of Confidence) to explore the behavior of different measures. Finally, we suggested MST based clustering algorithm using HF-environment and contrast the performance of proposed measure with existing ones. All these comparison illustrate that proposed measure is getting efficient and reasonable results and it also verified that proposed measure is not restricted to particular domain, it can be effectively applied for diverse field of application.
Echocardiographic assessment of aortic regurgitation: a narrative review
Authors: Tsampasian Vasiliki , Victor Kelly , Bhattacharyya Sanjeev , Oxborough David , Ring Liam 
Published: January 2024

AbstractAortic regurgitation (AR) is the third most frequently encountered valve lesion and may be caused by abnormalities of the valve cusps or the aorta. Echocardiography is instrumental in the assessment of AR as it enables the delineation of valvular morphology, the mechanism of the lesion and the grading of severity. Severe AR has a major impact on the myocardium and carries a significant risk of morbidity and mortality if left untreated. Established and novel echocardiographic methods, such as global longitudinal strain and three-dimensional echocardiography, allow an estimation of this risk and provide invaluable information for patient management and prognosis. This narrative review summarises the epidemiology of AR, reviews current practices and recommendations with regards to the echocardiographic assessment of AR and outlines novel echocardiographic tools that may prove beneficial in patient assessment and management.