bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cardiac 18F-Dopamine Positron Emission Tomography Predicts the Type of Phenoconversion of Pure Autonomic Failure
Authors: Lenka Abhishek , Isonaka Risa , Holmes Courtney , Goldstein David S. 
Published: July 2023

Abstract
Background
Pure autonomic failure (PAF) is a rare disease characterized clinically by neurogenic orthostatic hypotension (nOH) and biochemically by peripheral noradrenergic deficiency. Clinically diagnosed PAF can evolve (“phenoconvert”) to a central Lewy body disease (LBD, e.g., Parkinson’s disease (PD) or dementia with Lewy bodies (DLB)) or to the non-LBD synucleinopathy multiple system atrophy (MSA). We examined whether cardiac 18F-dopamine positron emission tomography (PET) predicts the trajectory of phenoconversion in PAF. Since cardiac 18F-dopamine-derived radioactivity always is decreased in LBDs with nOH and usually is normal in MSA, we hypothesized that PAF patients with low cardiac 18F-dopamine-derived radioactivity may phenoconvert to a central LBD but do not phenoconvert to MSA.
Methods
We reviewed data from all the patients seen at the National Institutes of Health Clinical Center from 1994 to 2023 with a clinical diagnosis of PAF and data about serial 18F-dopamine PET.
Results
Twenty patients met the above criteria. Of 15 with low cardiac 18F-dopamine-derived radioactivity, 6 (40%) phenoconverted to PD or DLB and none to MSA. Of 5 patients with consistently normal 18F-dopamine PET, 4 phenoconverted to MSA, and the other at autopsy had neither a central LBD nor MSA.
Conclusion
In this case series, 40% of patients with nOH and low cardiac 18F-dopamine-derived radioactivity phenoconverted to PD or DLB during follow-up; none phenoconverted to MSA. Cardiac 18F-DA PET therefore can predict the type of phenoconversion in PAF. This capability could refine eligibility criteria for entry into disease-modification trials aiming to prevent evolution of PAF to symptomatic central LBDs.
Personalized checkpoint acupuncture can reduce postoperative pain after abdominal surgery- a STRICTA-conform Pilot-Study
Authors: Ghanad Erfan , Yang Cui , Weiß Christel , Goncalves Mario , Santos Maria Joao , Correia Nuno , Reissfelder Christoph , Greten Henry Johannes , Herrle Florian 
Published: July 2023

Abstract
Background Optimal pain management is one of the core elements of Enhanced Recovery After Surgery (ERAS®) protocols and remains a challenge. Acupuncture (AC) is an effective treatment for various pain conditions. Systematic and personalized allocation of acupoints may be decisive for efficacy.Methods Based on the predominant pressure sensitivity of six gastrointestinal (GI) checkpoints (G1-G6), we devised a method to detect personalized patterns of pain and a corresponding set of acupoints. We performed a single AC treatment with semi-permanent needles and assessed the visual analogue scale (VAS) score, pain threshold based on pressure algometry (PA) and temperature changes on abdominal skin areas before and 5 min after AC.Results Between April and June 2021, thirty-eight patients were prospectively included in this pilot study. The mean reduction in subjective pain sensation as assessed by VAS was 86%, paralleled by an augmentation of the pain threshold as measured by PA by 64%. A small but significant increase in the skin temperature was observed above the abdominal surface. These effects were independent of the type of surgery.Conclusion Checkpoint acupuncture may be a complementary tool for postoperative pain management. Further investigations are needed to explore this analgesic effect.
A Systematic Review on Microservice Testing
Authors: Panahande Mahsa , Miller James 
Published: July 2023

Abstract
Microservices have emerged to change software architecture into a style of loosely coupled facilities cooperating via a lightweight way. This architecture makes a more scalable and resilient artifact that is easier to evolve and deploy. However, how can we ensure that microservices are defect-free and satisfy expected behaviors? Like other software styles, microservices must be tested in various ways. Employing heterogeneous platforms in microservice development and microservices characteristics, such as scalability and resiliency demand different test approaches from other software applications. This paper produces a systematic literature review on articles published from 2011 on microservice testing. Of the 98 relevant studies found in the literature, 35 have been included in this survey. Primary studies have been summarized by their novelty, benefits, and gaps. Moreover, they are compared in terms of their techniques, outcomes, and evaluations. Studying the current test method’s limitations identifies open problems discussed during the paper. Results of this study identify the current achievements and future possible directions in the microservice testing domain. This survey finds resiliency testing and finding abnormal components in a production environment as the most common approaches for testing and validating microservice integrations and behavior. However, there is still room for generalizing fault injection methods and addressing microservice-specific features in test approaches.
Rate enhancement of the Hantzsch condensation reactions using a new natural deep eutectic mixture
Authors: Rahro Parissa Naddaf , Shirini Farhad 
Published: July 2023

Abstract
In this work, a novel natural deep eutectic mixture was prepared from glucose, pregabalin and urea and used for the promotion of the synthesis of 1,8-dioxo-decahydroacridine and hexahydroquinoline derivatives through the one-pot Hantzsch condensation reaction. The new catalyst was characterized by several techniques including Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), derivative thermogravimetry (DTG), differential thermal analysis (DTA) and refractive index measurements (RI). Easy preparation of the reagent, green process, simple work-up procedure, high yields, and short reaction times are among the most important advantages of the reported protocol. In this research Antibacterial activities of the prepared deep eutectic mixture and new synthesized Hantzsch derivatives were also studied against the Bacillus subtilis (Gram-positive) and Escherichia coli (Gram-negative) by the agar well diffusion method.
Why the World Gets More Polarized: A Positive Political Economy Perspective
Authors: Jwa Sung-Hee , Lee Taekyu 
Published: July 2023

Abstract
This paper argues that Economic Discrimination (ED), when instituted by the trinity of economic development, market, corporation, and government, can promote shared and inclusive growth. In contrast, Economic Egalitarianism (EE) will work against it. ED means treating economic differences differently, while EE means treating economic differences equally or indifferently. As a pinnacle of the ED institutions in the capitalist economy, the corporate organization plays a crucial role in shared and inclusive growth. An empirical study is done by utilizing a new concept of corporate production and distribution functions. The empirical results show: 1) income growth is affected positively by corporate growth but negatively by the extent of the welfare state, 2) income distribution is affected positively by corporate growth but negatively by the extent of the welfare state, 3) income distribution improves together with income growth. These imply that the growth of the corporate economy will expedite shared and inclusive economic development but the expansion of the redistributive welfare state by hurting the corporate economy will worsen economic polarization.
ShallowHRD status Acts as an Effective Prognostic Predictor in Ovarian Cancer Patients Treated by Poly (ADP-ribose) polymerase inhibitors (PARPis)
Authors: Guo Yuanli , He Xinxin , Tan Yanming , Liu Junfeng , Chen Huadong , Huang Yi , Zhang Chao , Tao Ying , Chen Shan 
Published: July 2023

Abstract
Purpose: Homologous recombination deficiency (HRD) plays a crucial role in ovarian cancer patients who are treated with Poly (ADP-ribose) polymerase inhibitors (PARPis). It could be defined as a prognosis biomarker. However, many high throughput sequencing methods for evaluating HRD, including HRDetect (WGS 10X), SigMA (WGS 40X or panel 1000X), and scarHRD (WGS 30X), are technically complex, time and data-storage consuming, and costly. Herein, we aimed to develop a low-cost method by low sequencing coverage to identify HRD status for precision medication.
Methods: We utilized shallowHRD, a software tool to evaluate tumor HRD based on whole genome sequencing (WGS) at low coverage (1X), and established a novel scoring system, shallow-HRD score system.
Results: Compare with negative shallow-HRD status (shallow-HRD score <15 or BRCA1wild), positive shallow-HRD status (shallow-HRD score ≥15 or BRCA1mut) presented favorable survival after being treated with PARPis.
Conclusion：The shallowHRD status is a good biomarker for predicting prognosis, which could help guide the clinical application of PARPis in ovarian cancer patients by a cost-effective, time and data-storage saving method.
Generating Explanations for Explainable Recommendations Using Time-Series Information
Authors: Qu Yuanpeng , Nobuhara Hajime 
Published: July 2023

Abstract
Generating explanations in natural language processing methods such as review generation and explainable recommendations plays an essential role in personalization. These methods can provide explanations that can help target users better understand the recommended items and enhance their awareness of the system’s knowledge about their preferences. However, existing explanation-generating methods for recommendations ignore time-series information, which is important to improve the effectiveness of the recommendation. To address this issue, we propose a Transformer-based explanation-generating method designed to generate recommendation reasons based on time-series information from sequential recommendations. This method bridges the time-series information from the target user’s purchase history and the item they may want to purchase to assign it a linguistic meaning and generate explanations for the recommended item. We divided our proposed method into two parts, sequential recommendation and reason generation, to maximize the benefits. Extensive experiments on three datasets show that the proposed approach can generate explanations for the results of sequential recommendations both reasonably and effectively compared to state-of-the-art explanation generation methods in most cases. Further experiments on time-series information and case studies verify the effectiveness of our approach. Our proposed model demonstrates its ability to generate explanations that incorporate time series information, as supported by our proposed evaluation metric. This also affirms the significant role of time series information in improving the performance and quality of the generated explanations.
Microencapsulation of spinach extract using binary blends of biopolymers: A comparison between freeze drying and spray drying approaches
Authors: Rajabi Hamid , Sedaghati Samineh , Rajabzadeh Ghadir , Sani Ali Mohammad 
Published: July 2023

Abstract
This investigation sought to evaluate the relative efficacies of freeze drying (FDM) and spray drying (SDM) methodologies in the microencapsulation of spinach extract, as a source of chlorophylls (CHL), utilizing varying concentrations and ratios of Arabic gum and maltodextrin. Alterations observed in the FTIR spectra substantiated the successful incorporation of CHL within the carriers’ matrix, with the drying method exerting no discernible influence. The mean values for powder yield and encapsulation efficiency in FDM samples at 25% total solid content (TS) were 19.24% and 5.28% greater, respectively, than those of spray-dried samples, while SDM microcapsules exhibited significantly enhanced storage stability. FESEM analysis revealed the considerable impact of drying method, carrier type, concentration, and ratio on both the size and surface properties of samples. An increase in TS from 25–35% resulted in a significant increase in mean particle size for SDM powders from 7.19 µm to 10.96 µm, while FDM samples exhibited an increase in surface roughness. In conclusion, both methodologies demonstrated the capacity to preserve CHL; however, given the significance of energy consumption and process duration at an industrial scale, we propose that SDM represents a suitable approach by producing CHL microparticles with extended shelf-life and favorable processibility.
Proposed Methodology for Disaster Classification Using Computer Vision and Federated Learning
Authors: Shah Jash , Patel Divya , Shah Jinish , Shah Saurav , Sawant Vinaya 
Published: July 2023

Abstract
Classification of disasters is crucial for effectivedisaster management and response. This paper proposes amethodology that combines computer vision techniques andfederated learning to improve the classification accuracy ofdisasters while addressing the issue of data transfer and the timesquandered doing so. This methodology employs computer visionalgorithms to analyse captured visual data from a variety ofsources. It seeks to accurately classify disasters such as wildfires,floods, earthquakes, and cyclones by extracting pertinent featuresand patterns from these images. Using federated learning toresolve the issues of data privacy and transfer latency is theproposed solution. Federated learning makes it possible to trainmodels on decentralised data sources without requiring datacentralization. Each participating device or data source trainsa local model using its own data, and only model updatesare shared and aggregated to create a global model. Extensiveexperiments utilising videos of actual disasters are conductedto evaluate the proposed methodology. The evaluation focuseson precision and effectiveness. This strategy is anticipated toresult in improved disaster classification models, making themappropriate for deployment in disaster management systems.
Enhancement in Process Mining Model by Repairing Noisy Behavior in Event Log
Authors: Shahzadi Shabnam , Shahzad Usman , Emam Walid , Tashkandy Yusra , Iftikhar Soofia 
Published: July 2023

Abstract

Companies and organization aim to be competitive in order to improve the performance of the business process. In recent years, process mining attracts researchers and their main purpose is to extract accurate information from the process-related data. Enhancement is one of their main types, which is used to prolong or enhance/improve the existing process by taking the information from the actual process of an event log. As we know, enhancement has two types Extension and Repair. In our paper, we use the repair type of enhancement. It is common practice that logging errors in information systems or the presence of special behavior mean that we have the actual event log with the noise. In our paper, we investigate the process mining model with the presence of noise in the event log. We repair the event logs by decomposing them into many sub-logs and removing the noise behavior in the sub-logs by using covering probability. Repaired sub-logs are than added to the original event log at the appropriate place. We also propose in our research work a probabilistic method that depends on frequency occurrence for activities in a particular situation. The proposed method allows us to remove noisy and abnormal behavior in the event log, which permit us to gain a over-all perspective in the process Hence we generate artificial event logs with the presence of noise behavior in the ProM framework. By using RapidMiner based ProM Extension, we generate a test set that demonstrates, that we can find out and repair multiple types of noisy behavior in an event log. Therefore the proposed method also clearly shows that after repairing the event log we can improve the performance of a process mining model.
The relationship between anxiety and cognition in stroke patients: a cross-sectional study
Authors: Zheng Zixiu , Song Runluo , Song Yang , Wang Yanqing , Zhuang Yanjun , Yu Cong , Xue Jun 
Published: July 2023

Abstract
Background
There is limited evidence on the relationship between anxiety and cognition in stroke patients, and no precise relationship between the two has been indicated.
Objective
We aimed to explore the precise relationship between anxiety and cognition in Chinese stroke patients.
Methods
This study was a cross-sectional study, 384 hospitalized stroke patients were assessed with questionnaires and scales, including the Demographic Characteristics Questionnaire, the Hamilton Anxiety Inventory (HAMA), and the Montreal Cognitive Assessment (MoCA).
Results
Anxiety was present in 55.47% of the 384 patients. Univariate analysis showed that age, gender, marital status, smoking, and alcohol consumption were associated with cognition, and multiple linear regression results showed that HAMA was not independently associated with MoCA after adjusting for potential confounders (β=-0.16, 95% CI: -0.29 to- 0.03), which would be inconsistent with HAMA (subgroup) as a categorical variable (P trend of 0.004) A non-linear relationship was detected between HAMA and MoCA with an inflection point of 9. The effect sizes and confidence intervals to the left and right of the inflection point were -0.54 (-0.78 to -0.30) and 0.02 (-0.14 to -0.17), respectively.
Trial Registration
Registration number of China Clinical Trials Registration Center: 20220328004-FS01
Conclusion
The relationship between anxiety and cognition is nonlinear. When the HAMA score is less than 9, anxiety and cognition are negatively correlated, and when it is greater than or equal to 9, the cognitive score will no longer decrease and is saturated.
KIF11 serves as a cell cycle mediator in childhood acute lymphoblastic leukemia
Authors: Zhu Liwen , Chen Chuqin , Kang Meiyun , Ma Xiaopeng , Sun Xiaoyan , Xue Yao , Fang Yongjun 
Published: July 2023

Abstract
The extremely high incidence and mortality of ALL remain to a great threat to children worldwide. This study aims to explore a novel biomarker for childhood ALL based on the analysis using the Gene Expression Omnibus (GEO) database. Array data of the GSE73578 dataset, involving 46 childhood ALL samples, were downloaded from the GEO database. The weighted gene co-expression network analysis (WGCNA) was performed to explore co-expression modules associated with childhood ALL. The functions of hub module associated with many vital processes were also predicted by Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis. The KIF11 gene was screened out by overlapping down-regulated genes in GSE73578 and GSE4698 datasets and the hub module. Guilt by association (GBA) was adopted to verify the function of the identified KIF11 gene and to predict its target genes associated with the treatment of childhood ALL. KIF11 was up-regulated in bone marrow samples of childhood ALL patients and corresponding cell lines. Furthermore, in vitro experiments confirmed that knockdown of KIF11 in ALL cells inhibited cell proliferation and arrested cell cycle progression in G2/M phase. We identified KIF11 as a therapeutic marker for childhood ALL. Our study provides references for elucidating the molecular mechanism underlying the pathogenesis of childhood ALL.
Effects of Novel Cuproptosis-related Long Noncoding RNAs on the Prognosis and Immune Microenvironment of Wilms Tumor
Authors: Li Yadong , Xie Siqi , Wang Song , Li Yi , Zhang Bing , Cheng Feng , Fang Yifan 
Published: July 2023

Abstract
Purpose
Unlike all other known types of regulated cell death, cuproptosis is a unique copper-dependent cell death pathway that is closely connected to mitochondria and metabolism. The pathogenesis of Wilms tumor (WT), a common pediatric abdominal tumor, has yet to be fully elucidated. However, studies on long noncoding RNAs related to cuproptosis in WT and the relationship between Wilms tumor, the microenvironment, and cuproptosis are still scarce.
Results
Our results showed that among individuals with WT, those included in the high-risk group identified using the signature were demonstrated poor survival outcomes. Moreover, we found that the high-risk group had a worse prognosis (P < 0.001) than the group of low-risk. The area under the curve value for this signature was 0.818, which was higher than that for age (0.524), sex (0.580), race (0.489), stage (0.673), and the modeling of ferroptosis-related lncRNAs (0.775). Individuals in the group of low-risk group had an elevated Tumor Immune Dysfunction and Exclusion scores and were more sensitive to 13 drugs, including BI-2536, EX-527, IspinesibMesylate, and KIN001-135.
Conclusion
Our model can precisely predict the prognosis of WT patients and differentiate between those at low and high risk. The current study introduces a novel approach for predicting clinical prognosis and determining the appropriate therapy for patients with WT.
Immune activation effects at different irradiated sites and optimal timing of radioimmunotherapy in patients with extensive-stage small cell lung cancer: a real-world analysis
Authors: Wu Min , Wu Shihao , Chen Yuetong , Sun Liangchao , Zhou Jundong 
Published: July 2023

Abstract
Background
In view of the limited data on radiotherapy (RT) combined with immunotherapy in patients with extensive-stage small cell lung cancer (ES-SCLC), this study aimed to identify the immune activation effect on different sites and the survival outcomes of radioimmunotherapy at different treatment stages.
Methods
Forty-five patients diagnosed with ES-SCLC were included in this retrospective analysis. We collected the overall survival (OS) of the patients,, recorded the blood cell counts before, during, and after RT, and derived blood index ratios such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII). The datasets were analyzed using the Spearman rank correlation test, Kruskal-Wallis rank sum test, logistic regression, and survival analysis.
Results
Among the selected blood indices, the delta-NLR/PLR/Sll correlated with different irradiated organs, and the mean ranks of these three indices were the lowest in the brain-irradiated group during immunotherapy. Additionally, adjunct first-line immunotherapy with RT demonstrated a significant improvement compared to second- or third-line therapy and subsequent therapies.
Conclusion
Our findings suggest that compared to other organs, the strongest immune activation effect occurs with brain RT, and ES-SCLC patients who received radioimmunotherapy (RIT) earlier achieved higher OS rates.
Remarks on a fractional nonlinear partial integro-differential equation via the new generalized multivariate Mittag-Leffler function *
Authors: Li Chenkuan , Saadati Reza , Beaudin Joshua , Hrytsenko Andrii 
Published: July 2023

Abstract
Introducing the new generalized multivariate Mittag-Leffler function, we consider the uniqueness of solutions to a boundary value problem of the fractional nonlinear partial integro-differential equation using Banach’s fixed point theorem and Babenko’s technique. In addition, we use Python which is a high-level language efficiently dealing with the summation of multi indices to compute the approximate value of the generalized Mittag-Leffler function, and provide an example showing applications of key results derived.
Mathematics Subject Classification: 65M25, 65Q30, 35C10, 35C15, 26A33