bluuebunny/crossref_metadata_2025_split huggingface dataset:
Infection Control Strategies for MDRO Based on Failure Mode and Effects Analysis: An Empirical Study on Postoperative Infections in Cancer Patients
Authors: Wu Chunlin , Tian Qingqing , Wang Hui , Yang Weiwei , Liu Anran , Tang Jiayang , Nie Xiaoyan , Pu Ruiying , Huang Qin 
Published: November 2023

Abstract
Objective
This study aims to comprehensively and systematically evaluate the effectiveness of infection prevention and control for multidrug-resistant organisms (MDROs) in postoperative cancer patients using Failure Mode and Effects Analysis (FMEA).
Method
This study was conducted in a tertiary A-level cancer specialty hospital in China, employing Failure Mode and Effects Analysis (FMEA) to assess the risks of hospital infections. Intervention measures were implemented for high-risk and medium-high-risk factors. Through the hospital's infection information system, data on patients who underwent surgical treatment from 2017 to 2022 were extracted. Data from 2017 to 2019 served as the control group, and data from 2020 to 2022 as the intervention group, to compare the changes in hospital infection incidence and MDRO infection incidence before and after the intervention.
Results
Prior to the intervention (2017–2019), the incidence rate of hospital infections was 1.66%, which decreased to 1.22% after the intervention (2020–2022), showing a statistically significant difference (ꭓ2 = 48.83, P < 0.001). The incidence rate of MDRO infections also decreased from 1.808‰ before the intervention to 1.136‰ after the intervention, with a statistically significant difference (ꭓ2 = 11.417, P = 0.001).
Conclusion
This study confirms the effectiveness of the FMEA method in preventing and controlling MDRO infections in postoperative cancer patients. It highlights the practicality and value of widespread adoption of this method, particularly in the context of the COVID-19 pandemic.
A Joint Learning Model for Aspect-based Sentiment Analysis via Machine Reading Comprehension and Graph Convolutional Network
Authors: Wang Jiajun , Li Xiaoge , An Xiaochun 
Published: November 2023

Abstract
Aspect-based sentiment analysis (ABSA) consists of two fundamental subtasks: aspect term extraction (AE) and aspect-level sentiment classification (ASC). Existing research inevitably leads to severe error propagation, and the model cannot effectively capture the relationships between words. To tackle these problems, in this paper, we propose a novel joint learning model: MRC-GCN: Machine Reading Comprehension-Graph Convolutional Network. Firstly, aspects are extracted through MRC combined with pre-training models. In order to enhance the feature representation of the query, we utilize Long Short-Term Memory (LSTM) combined with self-attention mechanism and concatenated the original sentence and query using certain rules before inputting them into the model. Subsequently, due to better capture and aggregation of words and the relationship between words being effective for ASC, we combine the multiple latent information graph structures of sentences to form a text graph and use GCN with an attention mechanism to achieve sentiment classification. Experimental results on three public datasets show that our model is more effective than the previous models, demonstrating that our method can significantly empower ABSA models. In addition, we have designed ablation experiments for specific modules to verify their effectiveness.
Physical simulation study of proppant settling and migration within deep shale narrow fractures
Authors: Lin Hun , Zhang Ye , Yang Bing , Yuan Yong 
Published: November 2023

Abstract
Hydraulic fracturing is an important technology in shale gas reservoir development. Effective improvement of proppant sanding in the “long narrow fracture” in deep shale reservoirs is important. In this study, based on the simulation of long narrow fractures in deep shale reservoirs with a flat plate experimental setup, we conducted comparative experiments with various parameters (e.g., fracturing fluid viscosity, injection pump flow rate, proppant particle size, sand concentration, fracture width, and proppant type) to understand the settlement and migration pattern of the proppant particles in the long narrow fractures in deep shale reservoirs. The results showed that, compared to that in wide fractures, under the same conditions, the sand bed formed by proppant particles in the long narrow fracture in deep shale has a smaller front edge slope and lower height difference between the front and end of the sand bed, resulting in a more even and smooth overall sanding of proppant particles. In the long narrow fractures in deep shale, the percentage of the area of the sand bed at the outlet end to the area of the whole sand bed increases with fracturing fluid viscosity and the injection pump flow rate, while it is less influenced by the sand concentration. The micro-sized proppant particles also promote the placement of the sand bed at the outlet end and are more conducive to the overall uniform placement of the sand bed. The contracting width of the long narrow fracture in deep shale has no significant effect on the placement of the sand bed in the fracture in front of the contraction, but it impedes the proppant particle flow distribution in the fracture behind the contraction. The coverage area and equilibrium height of the sand bed after the contraction decreased, and the overall sanding was more even. However, the amount of settled proppant decreased, increasing the difficulty of effective fracture support in deep shale reservoir fractures. The results of this experimental research provide strong support to the reforming design of fracturing in deep shale reservoirs.
Return to School Practices After Hematopoietic Cell Transplantation: A Survey of Transplant Centers in the United States
Authors: Bhatt Neel , Meyer Christa , Mau Lih-Wen , Auletta Jeffery , Baker K. Scott , Broglie Larisa , Carpenter Paul , Choi Sung Won , Dandoy Christopher , Devine Steven , Phelan Rachel 
Published: November 2023

Abstract
Current literature lacks transplant center recommendations on return-to-school timing and related support for hematopoietic cell transplant (HCT) survivors. We describe findings from a two-phase, cross-sectional, web-based survey: In Phase I, medical directors of pediatric HCT centers from the National Marrow Donor Program/ Be The Match Registry were asked regarding the availability of a return to school standardized operating procedure (SOP). In Phase II, HCT physician members of the Pediatric Transplantation and Cellular Therapy Consortium were approached to study inter-physician practice variability regarding return to school post-HCT, factors affecting their decision-making, and support provided by HCT centers for return to school. Out of 46 respondents in Phase I (55% response rate), 28 (61%) reported having a SOP. Wide variations in recommendations were noted in 12 received SOPs. In Phase II, 122 physicians (60 centers) responded (30.6% response rate). The majority (60%) recommended autologous HCT recipients return to school within 6 months post-HCT but 65% recommended allogeneic HCT recipients return to school after 6 months or once off immunosuppression. Response variations were also noted within HCT centers. The top factors considered by physicians were health complications and graft vs. host disease/ immune suppression for autologous and allogeneic HCT recipients, respectively. There is a lack of consensus within and across HCT centers regarding recommended timing of HCT survivors’ return to school. Guidelines to standardize the return to school process are needed to ensure patient safety and re-integration into school to foster academic and social development for pediatric HCT recipients.
Using Symbolic Machine Learning to Assess and Model Substance Transport and Decay in Water Distribution Networks
Authors: Laucelli Daniele Biagio , Enríquez Laura , Saldarriaga Juan , Giustolisi Orazio 
Published: November 2023

Abstract
The evaluation of the substance concentration at each node of a water distribution network can be performed by integrating the advective diffusion in the network domain using a decay formulation and a Lagrangian scheme for differential equations. The kinetics of the substance decay can be formulated using a specific reaction order. The first order corresponds to a decay rate with a constant reaction rate, while higher order captures the reaction rate’s dependency on substance concentration. The aim of the present work was to discover the intrinsic mechanism of the substance transport in water distribution networks using the symbolic machine learning. We used the strategy named Evolutionary Polynomial Regression. To this purpose, we consider the chlorine transport, without imparing the generality of the procedure, assuming the first or second order for kinetic model. We demonstrated, using one real network and two test networks, that the concentration at each node of the network mainly depends on the substance decay along the shortest path(s) between the source and each node. Additionally, the symbolic machine learning allowed discovering the relationship between the source concentration and the residual one at each node of the network with a unique formula based on kinetic reaction model structure and its water age, possibly surrogated by travel time in the shortest path(s) to make the prediction faster.
Deep lipidomics profiling captures the impact of improved dietary fat quality on cardiometabolic risk and provides potential tools for precision nutrition approaches
Authors: Wittenbecher Clemens , Eichelmann Fabian , Schulze Matthias , Prada Marcela , Lovegrove Julie , Jackson Kim , Sellem Laury , Salas-Salvado Jordi , Razquin Cristina , Martínez-González Miguel , Estruch Ramon , Rexrode Kathryn , Guasch-Ferré Marta , Sun Qi , Willett Walter , Hu Frank 
Published: November 2023

Abstract

Current guidelines for cardiometabolic disease prevention recommend increasing dietary unsaturated fat intake while reducing saturated fats. However, standard cardiometabolic risk markers may not fully capture the metabolic benefits. Here, we demonstrate that a deep lipidomics-based multi-lipid score (MLS) accurately reflects the metabolic impact of controlled dietary substitution of saturated fats with unsaturated fats. We then show that the difference in this MLS, induced by a healthy fat-rich diet, is associated with a significant reduction in relative disease risk, such as 32% fewer incident cardiovascular disease and 26% fewer type 2 diabetes cases. These relative risk reductions surpass those extrapolated based on changes in standard surrogate biomarkers such as non-HDL cholesterol. Additionally, we utilize longitudinal lipidomics data to link long-term MLS changes with altered diabetes risk. Finally, we show a significant effect modification in a dietary intervention trial. An olive oil-rich Mediterranean diet intervention primarily reduced diabetes incidence among participants with unfavorable pre-intervention MLS levels. Together, our findings highlight the potential of lipidomics-based scores for targeting and monitoring dietary interventions in biomarker-guided precision nutrition approaches.
High Ki-67 Expression is an Important Predictor of Good Outcomes after Radioiodine Therapy in PTC Patients: A Retrospective Study
Authors: luo Xiaoqin , Luo Jiaxin , Li Chunyan , Xiong Xiaoli , Xie Jiahao , Chen Yuan , Zhang Xinlei , Liu Xiaoyue , Li Dong , Chen Pan , Wang Jing , Xian Jialang , Feng Huijuan , Ouyang Wei 
Published: November 2023

Abstract
Objective
This study aimed to evaluate the influence of primary Ki-67 expression in papillary thyroid cancer (PTC) and determine its association with clinical prognosis.
Methods
We assessed samples from 187 PTC patients taken from January 2015 to December 2019 for expression of Ki-67 labelling index (LI). We divided samples into low-LI (≤ 5%) and high-LI (5–10%) groups. Then, correlations of Ki-67 LI with clinicopathological variables were analyzed via χ2 test, and survival was evaluated using Kaplan–Meier curves. Furthermore, we used the Cox regression model to assess the diagnostic value of Ki-67 LI.
Results
Ki-67 LI was low in 85.0% (159/187) and high in 15.0% (28/187) of patients. All clinicopathological features were not significantly different between these two groups, except for Hashimoto's thyroiditis (χ2 = 4.936, P = 0.026) and stimulated thyroglobulin / serum antithyroglobulin antibodies (sTg / sTGAb) levels (χ2 = 7.932, P = 0.034). Moreover, Ki-67 LI was also an independent prognosticator of disease-free survival (DFS) in multivariate analysis (hazard ratio [HR] = 0.473; 95% CI, 0.233–0.960; P = 0.038).
Conclusions
Our data showed that high Ki-67 LI was associated with good outcomes in PTC patients after RAI therapy. Therefore, initial poor outcomes caused by high Ki-67 LI could be partially changed by RAI activities.
Identification of ferroptosis and autophagy-related diagnostic markers in hepatocellular carcinoma based on machine learning
Authors: Wang Dingxue , Huang Wenqi , Yang Bing , Shui Huili , Tang Dongxin 
Published: November 2023

Abstract
Background
The hepatocellular carcinoma (HCC) is a malignant tumor of the hepatic domain that is one of the most prevalent malignancies of the digestive system worldwide. Hepatocellular carcinoma, ferroptosis, and autophagy are closely related. The understanding of these relationships enables researchers to uncover the pathogenesis of liver cancer and develop new treatment strategies.
Methods
Four genes most related to the prognosis of LIHC were screened, and a risk score model was established. The model classifies HCC patients from different datasets and platforms into low-risk and high-risk groups. Multivariate Cox regression analysis confirmed that the model was an independent prognostic factor for HCC.
Results
Our results showed significant differences in gene expression profiles in HCC samples compared to normal tissues, with 2596 genes significantly up-regulated and 3036 genes significantly down-regulated. In addition, our results showed that the proportion of Macrophages M0, NK cells activated and T cells CD4 memory resting was significantly increased in HCC samples compared to normal tissues. In addition, our analysis showed that a combination of four ferroptosis and autophagy related genes including CDKN2A, HSPA5, GABARAPL1, and MAPK3 could serve as the optimal markers for the diagnosis of HCC. The combined analysis of these four genes accurately diagnosed the occurrence of HCC.
Conclusions
In this study, we investigated new biomarkers associated with hepatocellular carcinoma (HCC) based on ferroptosis and autophagy. We aimed to establish a risk scoring model to predict the prognosis of HCC, with the goal of providing appropriate treatment strategies for HCC patients.
POLE-mutant colon adenocarcinoma – case presentation and histopathological evaluation
Authors: Pancsa Tamás , Vasas Béla , Melegh Zsombor , Tóth Erika , Torday László , Sejben Anita 
Published: November 2023

Abstract
Introduction: POLE mutant phenotype in colon adenocarcinomas represents a rare molecular subtype. These tumours are generally responsive to immune-checkpoint inhibition therapy; therefore, are currently considered as a subtype with good prognosis. We hereby present the first detailed case presentation of a POLE mutant colon adenocarcinoma with useful microscopic features.
Case report: A 53-year-old male patient’s colon adenocarcinoma showed wide variety of growth patterns and massive lymphocytic infiltrate. Immunohistochemistry revealed proficiency in mismatch repair proteins and SMARCB1 deficiency. Next-generation sequencing panel confirmed a pathogenetic mutation in POLE exon 9: p.Pro286Arg, c.857C>G.
Conclusion: The diverse, high-grade morphology and increased intratumoral lymphoid infiltration should raise suspicion for POLE-mutated adenocarcinoma during everyday histopathological practice. Mismatch repair proficiency results on immunohistochemistry should not determine the final diagnosis, as only a minor percentage of these tumours are MSI. In every case suspicious for POLE-mutated adenocarcinoma, a 500-cancer gene panel should be carried out.
Curculionidae and Rhynchitidae community (Coleoptera: Curculionoidea) in different ecosystems of eastern Black Sea and northeastern Anatolia of Türkiye.
Authors: ALASERHAT İsmail , GÜRBÜZ Ramazan , ALPTEKİN Harun , DOĞAN Dilek 
Published: November 2023

Abstract
1. The Curculionoidea superfamily is represented by approximately 62,000 species identified in the world and 1,700 species in Türkiye. Individuals belonging to this family are considered to be highly specialized phytophagous insects. Some species are known as agricultural and forest pests, others as biological control agents for weed control or as bioindicators for desertification detection. 2. Therefore, knowledge of the abundance and diversity of native Curculionoidea species associated with different ecosystems and the design and implementation of specific measures to prevent or control their damage is essential. 3. In this study, three different periods (early summer, summer and autumn), locations and altitudes were sampled to investigate the species composition, abundance and diversity of the Curculionoidea community in different ecosystems, namely fruit orchards, forest areas, weeds and forage crops in northeastern Türkiye during 2010–2013 and 2016–2017 (6 years in total). 4. A total of 5580 individuals were collected (3770 in 2010, 70 in 2011, 1190 in 2012, 430 in 2013, 80 in 2016 and 40 in 2017), belonging to 32 species from two families. Of these, 3350 belonged to the Curculionidae (1890 males, 1460 females) and 2230 to the Rhynchitidae (1180 males, 1050 females). Phyllobius glaucus (%25.5), Tatianaerhynchites aequatus (17.77%), Rhynchites bacchus (10.05%), Rhynchites auratus (8.80%) and Polydrusus ponticus (4.85%) were determined as the first stage Curculionoidea species in terms of distribution and density. A large number of the species (26 species) were caught in all the ecosystems and, in general, with a higher abundance in the early summer. The highest levels of abundance and diversity of the Curculionoidea have been observed in fruit orchards. However, between ecosystems, localities, altitudes, years and sampling periods, these parameters (abundance and diversity) varied considerably. 5. Further research into how the composition of the vegetation cover shapes the Curculionoidea community is essential to implement strategies to prevent, reduce or control their damage.
COVID-19 Correlated with Wellbeing-Quality of Life, and Digital Healthcare Services
Authors: Adamopoulos Ioannis , Bardavouras Antonis 
Published: November 2023

Abstract
Background: COVID-19 is related to wellbeing quality of life, and digital healthcare services may have been understudied to date in terms of examining socio-demographic characteristics.
Methodology: This study used self-reports regarding digital health, and wellbeing - quality of life questionnaires given to participants attending the Hippocrates Hospital in Athens, Greece (N = 167). Participants were initially asked to answer questions about the COVID-19 epidemic. The study's data was analyzed using IBM SPSS V.26.
Results: The study's conclusions concern the role of age. People who are younger appear to be more likely to believe that quality of life is simply a flu-like sickness that is normally innocuous. Furthermore, the greater the perceived impact of the epidemic, the higher the participants' digital healthcare Services .
Conclusions: The findings of this study addressing the relationship between socio-demographic characteristics and the analyzed parameters are consistent with previous literature. Furthermore, this study emphasizes the critical importance of digital health care Services in relation to the perception of the severity of the issue during the Wellbeing-Quality of Life connected with the pandemic.
Efficiency Evaluation of Expanded Granular Sludge Blanket (EGSBR) to treat the Tannery Wastewater in an Anaerobic Digestion
Authors: v Vivekanandhan , Pandi K. , Sekar B. , Kumar E. Santhosh 
Published: November 2023

Abstract
The tannery wastewater is highly hazardous and intricate, what is discharged without proper treatment and also it affect the environment and human health. In Tamil Nadu, there are numerous small scale tannery industries has discharged large amount of tannery wastewater in river stream. The proper treatment process is necessary. The aim of this study was to investigate the performance efficiency of EGSBR, removal percentage of COD, Chromium removal and recovery of biogas in an anaerobic digestion. The varying hydraulic retention time 5.21, 2.60, 1.74, 1.30 and 1.04 days followed throughout the experiment. The efficiency of COD removal percentage was attained 85.52% with 0.27 m3/kg COD of biogas production at 5.21 days of HRT, with an 1.512 kg COD/m3 of Organic loading rate. The decrease in Volatile fatty acid and Volatile suspended solid shows the active performance of microorganism in the reactor. The percentage of chromium removal efficiency was 85% with a 1.436 kg COD/m3/day OLR at 5.21 days of HRT. The maximum biogas generation was 0.27 m3/kg COD. The kinetic modeling was studied for the substrate degradation.
A Case of Balo’s Concentric Sclerosis Confirmed by Stereotactic Intracranial Brain Biopsy and Literature Review
Authors: Hang Hang , Ren Siying , Mao Yuanhong , Wu Guofeng , Wang Likun 
Published: November 2023

Abstract
Baló's Concentric Sclerosis (BCS) is an extremely rare central nervous system demyelinating disease, often presenting as acute or subacute neurological damage, with lesions typically occurring in the brain white matter. On MRI, it manifests as one or more concentric circular structures, forming multilayered ring-like patterns. Balo's Concentric Sclerosis, named after the Hungarian neuropathologist József Balo, was first defined in 1928. Traditionally, BCS was identified postmortem, but in recent years, magnetic resonance imaging (MRI) has become a crucial diagnostic method, allowing effective diagnosis and treatment during a patient's lifetime. While brain biopsy remains the gold standard for diagnosing this condition, reports of intracranial biopsy cases are relatively scarce. This article reports a case of BCS diagnosed through stereotactic intracranial brain biopsy and MRI, aiming to further enhance understanding of this disease.
SM-GMVAE: An intelligent evaluation model for defect depth based on few ultrasonic signals
Authors: Li Zhifeng , Liu Xiaojian , Li Runchen , Liu Weihua , Song Yaqin 
Published: November 2023

Abstract
Ultrasonic non-destructive detection is widely used for recognition and estimation of structural defects. Deep learning, especially deep neural network (DNN) has become a research hotspot for defect automated evaluation. Nonetheless, most current models are based on supervised learning approaches. To improve the performance of model, more data is needed to train model. Unfortunately, the collection of data in industrial scenarios is often limited and data labeling is also a time-consuming and labor-intensive task. In order to overcome this problem, This paper proposed a novel Similarity Metric Gaussian Mixture Variational Auto-Encoder model (SM-GMVAE) that combines few-shot learning and non-destructive testing techniques to evaluate defect depth with limited data. This model is designed into two modules: feature extraction (FE) module and similarity metric (SM) module. The FE module is designed to extract the feature of defect signal via the Variational Auto-Encoder (VAE). The SM module is used to measure the similarity of two defect signal based on the Gaussian Mixture Model (GMM). Moreover, sparse filtering techniques are used to enhance the fused features in the SM module. To validate proposed model, several specimens containing defects of different depths were produced. We construct the defect dataset based on defective ultrasound detection signals and several case studies on this datasets. The results demonstrate that the GMM and sparse filtering techniques used in our model can improve the model evaluation accuracy, and the proposed model outperforms other models.