bluuebunny/crossref_metadata_2025_split huggingface dataset:
Health-related factors and dysregulation of epigenetic related genes in metabolic syndrome trigger finger patients and smoker trigger finger patients: preliminary analysis of patient-derived sample
Authors: Shayea Abdulaziz M. F. , Alshatti Amna A. , Alfadhli Danah H. , Ibrahim Almutairi Fatimah , Almutairi Mariam Kh. , Nadar Mohammed Sh. 
Published: October 2023

Abstract
Purpose
To investigate the health-related factors and analyze the expression of epigenetic related genes and inflammatory genes in metabolic syndrome Trigger Finger (TF) and smoker TF.

Methods
Samples from patients’ fingers with symptomatic TF were collected. There were seven groups: healthy control group, carpal tunnel syndrome (as a control for gene expression analysis), TF, diabetic TF, hypertensive TF, dyslipidemic TF and smoker TF. The expression levels of epigenetic related genes and inflammatory genes in metabolic syndrome TF and smoker TF were evaluated by the reverse transcription–polymerase chain reaction (RT-PCR) technique. The Perceived Stress Scale (PSS), Pittsburgh Sleep Quality Index (PSQI) questionnaires, disability of the arm, shoulder and hand (DASH) and numeric pain rating scale were given to the participants to fill out.

Results
There was a significant increase in hand dysfunction in the metabolic TF groups and smoker group compared to the TF group (p < 0.0001). The stress levels of the smoker TF group and TF with hypertension group were significantly increased compared with those in the TF group (p < 0.03) and (p < 0.021), respectively. On the other hand, there was a significant increase in the COL-I, COL-II and TNF-α gene expression of the metabolic TF groups and smoker group (p < 0.0001).

Conclusions
Health-related factors in the TF tendons was highly associated with the level of inflammation and genetic alteration in TF metabolic syndromes and smoker TF patients. Therefore, further investigation is required to examine the combination of occupational therapy, gene expression, and health-related factors as a promising method of managing TF.
Age in addition to RETTS triage priority substantially improves 3-day mortality prediction in emergency department patients: a multi-center cohort study
Authors: Malmer G. , Åhlberg R. , Svensson P. , af Ugglas B. , Westerlund E. 
Published: October 2023

Abstract
Background
Previous studies have shown varying results on the validity of the rapid emergency triage and treatment system (RETTS), but have concluded that patient age is not adequately considered as a risk factor for short term mortality. Little is known about the RETTS system’s performance between different chief complaints and on short term mortality. We therefore aimed to evaluate how well a model including both RETTS triage priority and patient age (TP and age model) predicts 3-day mortality compared to a univariate RETTS triage priority model (TP model). Secondarily, we aimed to evaluate the TP model compared to a univariate age model (age model) and whether these three models’ predictive performance regarding 3-day mortality varies between patients with different chief complaints in an unsorted emergency department patient population.

Methods
This study was a prospective historic observational cohort study, using logistic regression on a cohort of patients seeking emergency department care in Stockholm during 2012–2016. Patient visits were stratified into the 10 chief complaint categories (CCC) with the highest number of deceased patients within 3 days of arrival, and to “other chief complaints”. Patients with priority 1 were excluded.

Results
The studied cohort contained 1,690,981 visits by 788,046 different individuals. The TP and age model predicted 3-day mortality significantly and substantially better than both univariate models in the total population and in each studied CCC. The age model predicted 3-day mortality significantly and substantially better than the TP model in the total population and for all but three CCCs and was not inferior in any CCC. There were substantial differences between the studied CCCs in the predictive ability of each of the three models.

Conclusions
Adding patient age to the RETTS triage priority system significantly and substantially improves 3-day mortality prediction compared to RETTS priority alone. Age alone is a non-inferior predictor of 3-day mortality compared to RETTS priority. The impact on 3-day mortality prediction of adding patient age to RETTS priority varies between CCCs but is substantial for all CCCs and for the total population. Including age as a variable in future revisions of RETTS could substantially improve patient safety.
Dynamics of loops surrounding the active site architecture in GH5_2 subfamily TfCel5A for cellulose degradation
Authors: Wu Xiuyun , Zhao Sha , Tian Zhennan , Han Chao , Jiang Xukai , Wang Lushan 
Published: October 2023

Abstract
Background
Lignocellulose is the most abundant natural biomass resource for the production of biofuels and other chemicals. The efficient degradation of cellulose by cellulases is a critical step for the lignocellulose bioconversion. Understanding the structure-catalysis relationship is vital for rational design of more stable and highly active enzymes. Glycoside hydrolase (GH) family 5 is the largest and most functionally diverse group of cellulases, with a conserved TIM barrel structure. The important roles of the various loop regions of GH5 enzymes in catalysis, however, remain poorly understood.

Results
In the present study, we investigated the relationship between the loops surrounding active site architecture and its catalytic efficiency, taking TfCel5A, an enzyme from GH5_2 subfamily of Thermobifida fusca, as an example. Large-scale computational simulations and site-directed mutagenesis experiments revealed that three loops (loop 8, 3, and 7) around active cleft played diverse roles in substrate binding, intermediate formation, and product release, respectively. The highly flexible and charged residue triad of loop 8 was responsible for capturing the ligand into the active cleft. Severe fluctuation of loop 3 led to the distortion of sugar conformation at the − 1 subsite. The wobble of loop 7 might facilitate product release, and the enzyme activity of the mutant Y361W in loop 7 was increased by approximately 40%.

Conclusion
This study unraveled the vital roles of loops in active site architecture and provided new insights into the catalytic mechanism of the GH5_2 cellulases.
Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models
Authors: Tayyebi Arash , Alshami Ali S , Rabiei Zeinab , Yu Xue , Ismail Nadhem , Talukder Musabbir Jahan , Power Jason 
Published: October 2023

AbstractA reliable and practical determination of a chemical species’ solubility in water continues to be examined using empirical observations and exhaustive experimental studies alone. Predictions of chemical solubility in water using data-driven algorithms can allow us to create a rationally designed, efficient, and cost-effective tool for next-generation materials and chemical formulations. We present results from two machine learning (ML) modeling studies to adequately predict various species’ solubility using data for over 8400 compounds. Molecular-descriptors, the most used method in previous studies, and Morgan fingerprint, a circular-based hash of the molecules' structures, were applied to produce water solubility estimates. We trained all models on 80% of the total datasets using the Random Forest (RFs) technique as the regressor and tested the prediction performance using the remaining 20%, resulting in coefficient of determination (R2) test values of 0.88 and 0.81 and root-mean-square deviation (RMSE) test values 0.64 and 0.80 for the descriptors and circular fingerprint methods, respectively. We interpreted the produced ML models and reported the most effective features for aqueous solubility measures using the Shapley Additive exPlanations (SHAP) and thermodynamic analysis. Low error, ability to investigate the molecular-level interactions, and compatibility with thermodynamic quantities made the fingerprint method a distinct model compared to other available computational tools. However, it is worth emphasizing that physicochemical descriptor model outperformed the fingerprint model in achieving better predictive accuracy for the given test set.
A deep learning-based load forecasting algorithm for energy consumption monitoring system using dimension expansion
Authors: Zhang Wei-guo , Zhu Qing , Gu Lin-Lin , Lin Hui-Jie 
Published: October 2023

AbstractAs a basic task in energy consumption monitoring system, load forecasting has great effects on system operation safety, generation costs and economic benefits. In this paper, a long-term load forecasting algorithm using data dimension expansion and deep feature extraction is proposed. First, the outliers of the meteorological measurements are removed by median filter method, and then the time information is encoded to form the fingerprint of the training data. Next, the full connected network (FCN) is used to expand the dimensions of the fingerprint, and the convolutional neural network (CNN) is used to extract the deep features which can obtain better feature representation. Finally, the FCN, the CNN and regression learning model are combined for jointly offline training. The optimal parameters of these network can be obtained under global solution. Experimental results show that the proposed algorithm has better load forecasting performance than existing methods.
Image embedding and user multi-preference modeling for data collection sampling
Authors: Tom Anju Jose , Toni Laura , Maugey Thomas 
Published: October 2023

AbstractThis work proposes an end-to-end user-centric sampling method aimed at selecting the images from an image collection that are able to maximize the information perceived by a given user. As main contributions, we first introduce novel metrics that assess the amount of perceived information retained by the user when experiencing a set of images. Given the actual information present in a set of images, which is the volume spanned by the set in the corresponding latent space, we show how to take into account the user’s preferences in such a volume calculation to build a user-centric metric for the perceived information. Finally, we propose a sampling strategy seeking the minimum set of images that maximize the information perceived by a given user. Experiments using the coco dataset show the ability of the proposed approach to accurately integrate user preference while keeping a reasonable diversity in the sampled image set.
Developing a framework for regular and sustainable qualitative assessment of antibiotic use in Korean medical institutions: a Delphi study
Authors: Park Se Yoon , Kim Yong Chan , Moon Song Mi , Kim Bongyoung , Lee Raeseok , Kim Hong Bin ,   Korea Study Group for Antimicrobial Stewardship (KOSGAP)
Published: October 2023

Abstract
Background
We aimed to develop a roadmap for conducting regular, sustainable, and strategic qualitative assessments of antibiotic use in medical institutions within the Republic of Korea.

Methods
A literature review on the current state of qualitative antibiotic assessments was conducted, followed by one open round to collect ideas, two scoring rounds to establish consensus, and one panel meeting between them. The expert panel comprised 20 experts in infectious disease or antibiotic stewardship.

Results
The response rate for all three surveys was 95% (19/20), while the panel meeting attendance rate was 90% (18/20). The following long-term goals were defined to assess the annual use of antibacterial and antifungal agents in all medical institutions, including clinics. The panel agreed that random sampling of antibiotic prescriptions was the most suitable method of selecting antibiotics for qualitative assessment, with the additional possibility of evaluating specific antibiotics or infectious diseases that warrant closer evaluation for promoting appropriate antibiotic use. The plan for utilization of results from evaluation involves providing feedback while maintaining anonymity and disclosure. It includes a quantitative assessment of antibiotic prescriptions and resistance rates to compare against institutional benchmarks. Furthermore, it was agreed to link the evaluation findings to the national antibiotic stewardship programme, enabling policy and institutional approaches to address frequently misused items, identified during the evaluation.

Conclusion
This study provides a framework for establishing a qualitative assessment of antimicrobial use for medical institutions at a national level in the Republic of Korea.
ZnO, TiO2 and Fe3O4/Carbopol hybrid nanogels for the cleaner process of paper manuscripts from dust stains and soil remains
Authors: Hassan Rushdya Rabee Ali , Hassan Haidi M. , Mohamed Yassmine A. , Ismail Mai E. M. , Farid Yara , Mohamed Hager , Ismail Sameh H. , Salem Mohamed Z. M. , Abdel-Hamied Mostafa 
Published: October 2023

Abstract
There are many paper manuscripts at museums, stores, and libraries that have different stains. The dust stains and soil remains played an important role in the degradation of these manuscripts. Therefore, the cleaning process for these stains is important to process. Unfortunately, the removal of stains by some traditional techniques can be hazardous to the paper's fibers. Therefore, this study aims to evaluate innovative nanoparticle gels in the cleaning process of dust stains from paper manuscripts. The synthesized nanomaterials [Fe3O4, TiO2, and ZnO]/Carbopol hybrid nanogel were examined in order to investigate the surface morphology, determine the physio-chemical properties, for phase structure, using scanning electron microscope (SEM), transmission electron microscope (TEM), AFM, DLS, XRD, and Zeta potential. Some stained paper samples were prepared and exposed to accelerated thermal aging at 100 °C for 72 h. The evaluation of the cleaning by nanogel was performed by different analytical procedures containing investigation with a USB digital microscope, SEM, color change, mechanical properties, and ATR-FTIR analysis. The results of this study showed that ZnO/Carbopol hybrid nanogel at high viscosity gave the best results in the cleaning process of mud stains through the ability to dismantle mud particles and increase surface contact with the solvent. The aged treated sample with high viscosity form of ZnO NPs/carbopol hybrid nanogel gave the highest tensile strength value of (56.0 N). The treated samples with the high viscosity form of ZnO NPs/carbopol hybrid nanogel gave the highest value of elongation (1.398%) before aging. It also does not affect the chemical composition of the paper after cleaning it, but rather on the whole, it bites the hydration of the paper, which positively affects the properties of the treated paper.
Automated labeling of PDF mathematical exercises with word N-grams VSM classification
Authors: Yamauchi Taisei , Flanagan Brendan , Nakamoto Ryosuke , Dai Yiling , Takami Kyosuke , Ogata Hiroaki 
Published: October 2023

AbstractIn recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and difficult to scale. It recognizes that automated labeling eases the workload on experts, as seen in previous studies using automatic classification algorithms for research papers and Japanese mathematical exercises. However, these studies didn’t delve into fine-grained labeling. In addition to that, as the use of materials in the system becomes more widespread, paper materials are transformed into PDF formats, which can lead to incomplete extraction. However, there is less emphasis on labeling incomplete mathematical sentences to tackle this problem in the previous research. This study aims to achieve precise automated classification even from incomplete text inputs. To tackle these challenges, we propose a mathematical exercise labeling algorithm that can handle detailed labels, even for incomplete sentences, using word n-grams, compared to the state-of-the-art word embedding method. The results of the experiment show that mono-gram features with Random Forest models achieved the best performance with a macro F-measure of 92.50%, 61.28% for 24-class labeling and 297-class labeling tasks, respectively. The contribution of this research is showing that the proposed method based on traditional simple n-grams has the ability to find context-independent similarities in incomplete sentences and outperforms state-of-the-art word embedding methods in specific tasks like classifying short and incomplete texts.
Demonstrating the learning and impact of embedding participant involvement in a pandemic research study: the experience of the SARS-CoV-2 immunity & reinfection evaluation (SIREN) study UK, 2020–2023
Authors: Howells Anna , Aquino Erika Neves , Bose Deepika , Kelly Martin Gerard , Molony-Oates Barbara , Syed Asmah Hassan , Tolley Kim , Neill Claire , Hopkins Susan , Hall Victoria , Islam Jasmin 
Published: October 2023

Abstract
Background
Participant involvement in research studies is not a new concept, yet barriers to implementation remain and application varies. This is particularly true for pandemic response research studies, where timeframes are condensed, pressure is high and the value and inclusion of participant involvement can be overlooked. The SIREN Participant Involvement Panel (PIP) provides a case study for participant involvement in pandemic research, working in partnership with people who the research is for and about.

Methods
SIREN and the British Society for Immunology (BSI) recruited and ran two phases of the PIP, involving 15 members in total over a 16-month period. Phase 1 ran between January and August 2022 and Phase 2 between October 2022 and March 2023. Activity figures including recruitment interest and PIP meeting attendance were recorded. To evaluate how the PIP has influenced SIREN, feedback was collected from (a) researchers presenting at the PIP and (b) PIP members themselves. Evaluation at the end of Phase 1 informed our approach to Phase 2. Thematic grouping was planned to identify key lessons learned.

Results
Applications increased from n = 30 to n = 485 between Phase 1 and Phase 2 of the PIP, a more than 15-fold increase. The SIREN PIP positively impacted the design, implementation and evaluation phases of the study and sub-studies. Feedback from PIP members themselves was positive, with members highlighting that they found the role rewarding and felt valued.
Learnings from the PIP have been condensed into five key themes for applying to future pandemic response research studies: the importance of dedicated resources; recruiting the right panel; understanding motivations for participant involvement; providing flexible options for involvement and enabling the early involvement of participants.

Conclusions
The SIREN PIP has demonstrated the value of actively involving people who research is for and about. The PIP has provided an active feedback mechanism for research and demonstrated a positive influence on both SIREN study researchers and PIP members themselves. This paper makes the case for participant involvement in future pandemic research studies. Future work should include improved training for researchers and we would support the development of a national PIP forum as part of future pandemic research preparedness.
Transcutaneous auricular vagus nerve stimulation attenuates inflammatory bowel disease in children: a proof-of-concept clinical trial
Authors: Sahn Benjamin , Pascuma Kristine , Kohn Nina , Tracey Kevin J. , Markowitz James F. 
Published: October 2023

Abstract
Background
Vagus nerve stimulation is an investigational anti-inflammatory therapy targeting the nervous system to modulate immune activity. This study evaluated the efficacy and safety of transcutaneous auricular VNS (ta-VNS) in patients with pediatric-onset Crohn’s disease (CD) or ulcerative colitis (UC).

Methods
Participants were 10–21 years of age with mild/moderate CD or UC and fecal calprotectin (FC) > 200 ug/g within 4 weeks of study entry. Subjects were randomized to receive either ta-VNS targeting the cymba conchae of the external left ear, or sham stimulation, of 5 min duration once daily for a 2-week period, followed by a cross over to the alternative stimulation for an additional 2 weeks. At week 4, all subjects received ta-VNS of 5 min duration twice daily until week 16. Primary study endpoints were clinical remission, and a ≥ 50% reduction in FC level from baseline to week 16. Heart rate variability measurements and patient-reported outcome questionnaires were completed during interval and week 16 assessments.

Results
Twenty-two subjects were enrolled and analyzed (10 CD, 12 UC). Six of 10 with CD had a wPCDAI > 12.5 and 6/12 with UC had a PUCAI > 10 at baseline, correlating to mild to moderate symptom activity. Among the 12 subjects with active symptomatic disease indices at baseline, clinical remission was achieved in 3/6 (50%) with CD and 2/6 (33%) with UC at week 16. Despite all subjects having FC levels ≥ 200 within 4 weeks of enrollment, five subjects (4 UC, 1 CD) had FC levels < 200 at the baseline visit and were excluded from the FC analysis. Of the remaining 17, median baseline FC was 907 µg/g (IQR 411–2,120). At week 16, 11/17 (64.7%) of those with baseline FC ≥ 200 had a ≥ 50% reduction in FC (95% CI 38.3—85.8). In the UC subjects, there was an 81% median reduction in FC vs baseline (833 µg/g; p = 0.03) while in the CD subjects, median reduction in FC at 16 weeks was 51% (357 µg/g; p = 0.09). There were no safety concerns.

Conclusion
Noninvasive ta-VNS attenuated signs and symptoms in a pediatric cohort with mild to moderate inflammatory bowel disease.

Trial Registration
NCT03863704—Date of registration 3/4/2019.
The use of high-sensitivity cardiac troponin I in assessing cardiac involvement and Disease prognosis in idiopathic inflammatory myopathy
Authors: Zhang Hao , Chi Huihui , Xie Liangzhe , Sun Yue , Liu Honglei , Cheng Xiaobing , Ye Junna , Shi Hui , Hu Qiongyi , Meng Jianfen , Zhou Zhuochao , Teng Jialin , Yang Chengde , Su Yutong 
Published: October 2023

Abstract
Objectives
Cardiac involvement is one of the most serious complications of idiopathic inflammatory myopathy (IIM) that indicates poor prognosis. However, there is a lack of effective biomarkers for the identification of cardiac involvement and the prediction of prognosis in IIM. Here, we aimed to explore the value of different cardiac biomarkers in IIM patients.

Methods
A total of 142 IIM patients in the Department of Rheumatology and Immunology, Ruijin Hospital from July 2019 to October 2022 were included in this study. The clinical characteristics, laboratory tests, treatments and prognosis were recorded. The disease activity was assessed according to the core set measures. The correlations of the serum cardiac biomarkers levels with disease activity were analyzed by the Spearman correlation test. Risk factors for cardiac involvement were evaluated by multivariate logistic regression analysis.

Results
Higher high-sensitivity cardiac troponin I (hs-cTnI) levels were associated with cardiac involvement (n = 41) in IIM patients [adjusted OR 7.810 (95% CI: 1.962–31.097); p = 0.004], independent of other serum cardiac biomarkers. The abnormal hs-cTnI had the highest AUC for distinguishing of cardiac involvement in IIM patients (AUC = 0.848, 95% CI: 0.772,0.924; p < 0.001). Besides, we found that high serum levels of hs-cTnI were significantly correlated with disease activity. Moreover, patients with higher serum levels of hs-cTnI tended to suffer from poor prognosis.

Conclusions
Serum hs-cTnI testing may play a role in screening for cardiac involvement in IIM patients. Abnormal levels of serum hs-cTnI were associated with increased disease activity and poor prognosis.