bluuebunny/crossref_metadata_2025 huggingface dataset:
A systematic review of empirical literature on firearm rights restoration
Authors: Kafka Julie M , Rivara Frederick P , Ross Rachel , Rowhani-Rahbar Ali
Published: September 2023

Background: Firearms are commonly used in the United States to perpetrate serious interpersonal harm. Individuals with a criminal record are at elevated risk of perpetrating violence, particularly with a firearm. Accordingly, federal law prohibits the purchase and possession of firearms by certain high-risk groups including those with prior felony or domestic violence misdemeanor convictions. Evidence supports the effectiveness of these prohibitions, but little is known about how often prohibited persons later seek to have their firearm rights restored. We systematically reviewed empirical literature to describe who requests firearm rights restoration in the US, how often it is granted, and whether these individuals engage in subsequent violence or experience related harms. We searched six databases including peer-reviewed research manuscripts from across the disciplines of psychology, criminology, sociology, medicine, and public health, returning 3,990 unique records. Two coders independently reviewed all titles and abstracts.
Findings: After careful review, no articles met our inclusion criteria.
Conclusion: There is a dearth of empirical literature on firearm rights restoration and the risk for subsequent injuries or harms among prohibited persons or among former victims from prior prohibiting crimes. We call for attention to this gap in the research and emphasize a need to build an evidence base that can help inform state policy and courtroom practices regarding the eligibility, appropriateness, and risks related to firearm rights restoration among prohibited persons.
Enhancing Accuracy in Pediatric Inpatient Hospital Cost Estimation: A Machine Learning-Based Approach
Authors: Zafar Sarmad , Hajiani Mishaal Amin , Affan Muhammad , Zubairi Saleha , Hoodbhoy Zahra , Hasan Babar , Mahmood Tariq
Published: September 2023

Purpose: Accurately estimating inpatient billing costs during admission is important for financial planning in healthcare. Traditional methods have limitations in capturing true cost; hence, data-driven approaches are needed to improve hospital cost estimation in complex and dynamic environments. The main objective of this study is to predict a deviation between the initial hospital bill estimate and the actual bill charged at the time of discharge. This study is also focused on identifying the major factors contributing towards the cost of hospital stay.
Methods This study utilized dataset of approximately 22,000 pediatric patients (under 18 years of age). The main features of the dataset included medical conditions, hospital administration details, and socio-demographic information. The methodology utilizes named entity recognition techniques to extract structured data from unstructured textual data. Subsequently, a variety of machine learning classification models are trained and tested to predict deviations in hospital bill estimates.
Results: The boosting ensemble and artificial neural network classifier models performed best in predicting the deviations in the billing cost, with best accuracy, AUC and F1-scores of 80%, 77% and 77% respectively. The analysis of the important features revealed that age, length of stay, financial status of patients as main features to predict deviation in hospital bill estimates.
Conclusions: The results obtained from our study demonstrate that leveraging machine learning techniques provides a reliable and efficient means of improving the performance of hospital billing estimations. These findings have significant implications for healthcare practitioners, enabling them to make more informed decisions and allocate resources effectively.
How does family functioning contribute to adolescents’ positive or negative coping styles?The roles of core self-evaluations and strengths knowledge
Authors: Wen Lan , Huang Weiwei , Zhang Shuyue
Published: September 2023

Design
The current study focuses on the chain mediating roles of core self-evaluations (CSE) and strengths knowledge in the relationship between family functioning and positive coping styles (PCS) and the moderating role of strengths knowledge in the relationship between family functioning and negative coping styles (NCS).
Methods
A total of 2746 (560 boys, 2186 girls) Chinese adolescents participated in this research. These participants completed the Family Functioning Assessment Scale, CSE scale, Strengths knowledge Scale and Simple Coping Scale. Models 1 and 6 of Process were used in SPSS 25 to investigate moderation and mediation roles.
Results
According to the results of the study, on the positive dimension, family functioning positively predicted PCS, with CSE and strengths knowledge formed a chain mediation. CSE and strengths knowledge were partial mediators. On the negative dimension, the direct effect of family functioning on NCS was not significant, but it was indirectly influenced through chain mediation of CSE and strengths knowledge. So CSE and strengths knowledge were full mediators. Moreover, there was a moderating role of strengths knowledge between family functioning and NCS. Simply put: family functioning effectively reduced application of NCS as increase of strengths knowledge. In addition, a new model was constructed, excluding family functioning, and it was found that strengths knowledge had a "masking effect" in mediating between CSE and NCS.
Conclusions
Family functioning and CSE as well as strengths knowledge are protective factors for adolescents’ coping styles. Family is an important source of support for adolescents. Family members, especially parents, must be suitable strength coaches for children. Based on intrinsic aspirations, a good attachment relationship can promote individuals’ CSE and strengths knowledge. But we should pay attention to "Things will develop in the opposite direction when they become extreme." Strengths knowledge is not the higher the better, too much strengths knowledge can lead to too much NCS. By family members optimizing the ecological system and functioning of family, adolescents can optimize their coping styles.
Machine-learning model of eye metastasis in nasopharyngeal carcinoma based on the AdaBoost method
Authors: Rong Ru-Yi , Wen JiaYi , Hu Jin-Yu , Wu Shi-Nan , Xu San-Hua , Zou Jie , He Liangqi , Chen Cheng , Kang Min , Ying Ping , Wei Hong , Ling Qian , Ge Qian-Ming , Shao Yi
Published: September 2023

Background
Nasopharyngeal carcinoma (NPC) is a common cancer of the head and neck, and the eye is a common metastatic site of NPC. This study aimed to use machine learning (ML) to establish a clinical prediction model for ocular metastasis (OM) in NPC patients.
Methods
We retrospectively collected clinical data from 1,855 patients with NPC who were randomized to a training set and internal test set. Patients with NPC were divided into the OM group or the non-ocular metastasis (NOM) group. Independent risk factors for NPC-related hypertension risk were screened with multivariate logistic regression models. Six ML algorithms were used, including AdaBoost (AB), logistic regression (LR), random forest (RF), multilayer perceptron (MLP), bagging (BAG), and XGBoost (XGB). The training set was used to tune the model parameters to determine the final prediction model, and the test set was used to evaluate the training model. We compared the accuracy, sensitivity, area under the ROC curve, F1 score, and specificity of the models to determine the best machine-learning algorithm for predicting the probability of OM in NPC patients. In addition, a web calculator was developed to facilitate its clinical application.
Results
Among these six models, the AB model had the best differential diagnostic ability (F1 score = 0.773, area under the curve = 0.995, accuracy = 0.983, sensitivity = 0.833, and specificity = 0.985). Based on this model, an online web calculator was constructed to calculate the probability of OM in NPC patients to help clinicians differentially diagnose the disease. Finally, the Shapley Supplementary Interpretation library was used to screen the five most important risk factors for OM in NPC patients: TG, Cyfra 21 1, CA199, Hb, TC, and Pathology type.
Conclusion
We developed a risk prediction model for OM in NPC patients using ML methods and demonstrated that the AB model performed best among six ML models. This prediction model can help to identify patients with OM from NPC, provide early and individualized diagnosis and treatment plans, protect patients from OM from NPC, and minimize the burden on society.
Ameliorative Effects of Bone Marrow-derived Mesenchymal Stem Cells and Hyaluronic Acid on Monosodium Iodoacetate-Induced Ankle Osteoarthritis in Wistar Rats: Roles of Th1/Th2/Th17 cytokines, MMP-13, TGF-β1 and antioxidant defense system
Authors: U Hagag , M. Halfaya F. , Al-Muzafar Hessah Mohammed , Al-Jameel Suhailah . S , Amin Kamal Adel , W Abou El-Kheir , E.A. Mahdi , G.H Ragab , O.M Osama
Published: September 2023

Background: There is currently no cure for osteoarthritis [OA], and the few pharmacological therapy options available have drawbacks. Additionally, there is no effective treatment that would guarantee a full recovery from OA. Therefore, the goal of this investigation was to determine if bone marrow mesenchymal stem cells [BMMSCs] and/or hyaluronic acid [HA] were effective in treating experimentally-induced ankle osteoarthritis in Wistar rats caused by monosodium iodoacetate [MIA].
Methods: In five groups of ten rats each, fifty male Wistar rats were distributed. Saline was injected into the right tibiotarsal joint of individuals in group I on two days in a row, whereas those in group II received an injection of 2 mg of MIA [dissolved in saline] into the same joint. Those in groups III [MIA-BMMSCs], IV [MIA-HA], and V [MIA-BMMSCs+HA] were injected with MIA similarly to those in group II and also received intra-articular injections of BMMSCs [1×106 cells/rat], HA [75 µg/rat], and BMMSCs [1×106 cells/rat] alongside HA [75 µg/rat] respectively, in the tibiotarsal joint at the ends of the 2nd, 3rd and 4th weeks after MIA injection. The leg circumference, arthritis score, and morphological changes of the ankle joint were evaluated weekly from the beginning to the end of the experiment. For the purpose of identifying oxidative stress, antioxidant, and inflammatory state indicators, sera were collected. For histological and molecular research, the ankles of the right hind leg were excised out and fixed in neutral buffered formalin.
Results: In addition to raising GSH and GST levels, BMMSCs and HA decreased serum LPO. Additionally, BMMSC and HA significantly decreased ankle MMP-13 mRNA and TGF-β1 protein expressions as well as TNF-α and IL-17 serum levels. Rats with MIA-induced OA had higher serum IL-4 levels after receiving BMMSC and HA. BMMSC and HA caused a steady decrease in joint injury and cartilage degradation, according to histological investigations.
Conclusion: Based on the findings, it is possible to infer that BMMSC and/or HA have anti-arthritic effects that may be mediated by the augmentation of the antioxidant and anti-inflammatory effects in Wistar rats with MIA-induced osteoarthritis. The suppression of MMP-13 and TGF-β1 expressions play an important role in the improvement effects BMMSC and/or HA on OA in Wistar rats.
Data Visualization for Improved Mushroom Cultivation: A User-Friendly Approach
Authors: Hendinata Laurentius Kevin , Kandinata Gabriella Christina , Fikri Ahmad Ilham Rokhul
Published: September 2023

The escalating global population has led to an increasing demand for horticultural products, particularly mushrooms, renowned for their rich nutritional composition. To optimize mushroom cultivation, it is crucial to monitor environmental conditions, including temperature and humidity, to ensure optimal growth. In this study, we designed and implemented an IoT-based mobile application to continuously monitor temperature and humidity in mushroom cultivation houses. The installation process involved strategically placing the components of the system for efficient data collection, and the mobile app was designed with a user-friendly interface for easy navigation and access to critical information. Additionally, we analyzed latency and data sent, demonstrating efficient data transmission and minimal delays in data packet travel. The evaluation of the mobile app's features showed high accuracy and effectiveness in providing real-time status updates. Furthermore, a Likert scale survey confirmed positive feedback from users, affirming the application's potential usefulness in mushroom farming. This system offers promising prospects for enhancing sustainability and profitability in the mushroom cultivation industry.
Study of the effect of keap1 on oxidative stress in human umbilical cord mesenchymal stem cells
Authors: Deng Hongrong , Chen Yunxia , Liu Huiwen , Wang Li , Xu Hao , Tan Bin , Yi Qin , Wang Rui , He Bolin , Tian Jie , Zhu Jing
Published: September 2023

Background: HucMSCs had shown promising efficacy in treating childhood diseases, but oxidative stress induced by the poor microenvironment at the site of damage resulted in low cell survival after transplantation, thus preventing the cells from maximizing therapeutic efficacy. Therefore, this study aimed to investigate the role and mechanism of keap1 in oxidative stress injury of human umbilical cord mesenchymal stem cells (hucMSCs), and to provide theoretical support for improving the efficacy of stem cell therapy.
Methods: The hucMSCs were treated with hypoxic low-sugar-free serum (GSDH) to mimic the damaged site microenvironment after implantation. Adenoviral overexpression of keap1 gene of hucMSCs was performed in vitro, and cell proliferation ability was detected by CCK8 assay, crystal violet staining assay, and cell cycle assay; cellular redox level was assessed by Amplex Red, MDA, and GSH/GSSG kit; mitochondrial morphology was evaluated by mitotracker Red staining; ATP production was estimated by ATP detection kit; and the mRNA expression level of related proteins and related genes was tested by western blotting and RT-qPCR.
Results: GSDH treatment substantially upregulated keap1 mRNA levels and protein levels. Subsequently, we found that overexpression of keap1 notably inhibited cell proliferation and caused cells to stagnate in G1 phase. At the same time, overexpression of keap1 induced the production of large amounts of H2O2 and the accumulation of MDA, but suppressed the GSH/GSSG ratio and the expression of antioxidant proteins NQO1 and SOD1, which caused oxidative stress damage. Overexpression of keap1 induced cells to produce a large number of dysfunctional mitochondria resulting in reduced ATP production. Moreover, Overexpression of keap1 significantly decreased the IKKβ protein level，while upregulating IkB mRNA levels and downregulating P50 mRNA levels.
Conclusions: Overexpression of keap1 may induce oxidative stress injury in hucMSCs by down-regulating IKKβ expression and inhibiting NF-κB pathway activation. This implies the importance of keap1 in hucMSCs and it may be a potential gene for genetic modification of hucMSCs.
Designing Ti-6Al-4V microstructure for strain delocalization using neural networks
Authors: Ahmadikia Behnam , Beyerlein Adolph , Hestroffer Jonathan , Kumar Mariyappan Arul , Beyerlein Irene
Published: September 2023

The deformation behavior of Ti-6Al-4V titanium alloy is significantly influenced by slip localized within crystallographic slip bands. Experimental observations reveal that intense slip bands in Ti-6Al-4V form at strains well below the macroscopic yield strain and may serially propagate across grain boundaries, resulting in long-range localization that percolates through the microstructure. These connected, localized slip bands serve as potential sites for crack initiation. Although slip localization in Ti-6Al-4V is known to be influenced by various factors, an investigation of optimal microstructures that limit localization remains lacking. In this work, we develop a novel strategy that integrates an explicit slip band crystal plasticity technique, graph networks, and neural network models to identify Ti-6Al-4V microstructures that reduce the propensity for strain localization. Simulations are conducted on a dataset of 3D polycrystals, each represented as a graph to account for grain neighborhood and connectivity. The results are then used to train neural network surrogate models that accurately predict localization-based properties of a polycrystal, given its microstructure. These properties include the ratio of slip accumulated in the band to that in the matrix, fraction of total applied strain accommodated by slip bands, and spatial connectivity of slip bands throughout the microstructure. The initial dataset is enriched by synthetic data generated by the surrogate models, and a grid search optimization is subsequently performed to find optimal microstructures. We show that while each material property is optimized through a unique microstructure solution, elongated grain shape emerges as a recurring feature among all optimal microstructures. This finding suggests that designing microstructures with elongated grains could potentially mitigate strain localization without compromising strength.
Designing a novel multi-epitope vaccine against Glioblastoma cancer based on immunoinformatics approaches
Authors: Salahlou Reza , Farajnia Safar , Alizadeh Effat , Elmi Faranak , Dastmalchi Siavoush
Published: September 2023

Glioblastoma multiforme (GBM) stands as the prevalent and highly aggressive malignant primary brain tumor affecting adults. Presently, treatment approaches commonly involve surgery, followed by chemotherapy, or more frequently, radiotherapy. Nevertheless, the median survival of patients remains slightly above one year. Hence, the demand for innovative curative treatments for GBM is crucial. The analysis of GBM cells has played a significant role in identifying various molecules that serve as targets for immunotherapy-based approaches. These include EGFR/EGFRvIII, IDH R132H, H3 K27M, WT1, and TERT. Immunoinformatics methods offer a dual advantage of cost-effectiveness and convenience, leveraging in-silico simulations to significantly reduce development timelines. In this study, we employ immunoinformatics techniques to create an innovative multi-epitope vaccine aimed at preventing GBM. Utilizing complicated immunoinformatics approaches, we successfully predicted distinct epitopes for cytotoxic T lymphocytes (CTLs) and helper T lymphocytes (HTLs). Following that, Through the utilization of appropriate linkers and adjuvants, we created the multi-epitope vaccine by integrating all conserved epitopes. The ultimate vaccine demonstrated antigenicity, non-allergenicity, and stability. Next, we utilized predictions, refinements, and evaluations to determine the 3D configuration of the vaccine. To reveal the interactions between the vaccine and the immune receptor TLR4, we carried out molecular docking and dynamic simulations. Finally, to guarantee that the vaccine protein was fully expressed, the sequence of the designed vaccine was adjusted and in-silico cloning was conducted. In conclusion, the molecule developed in this study shows promise as a potential vaccine option against GBM tumors. However, further research is necessary to thoroughly assess its safety and efficacy.
LFTDA: A Lightweight and Fault-Tolerant Data Aggregation Scheme with Privacy-Enhanced Property in Fog-Assisted Smart Grid
Authors: Liu Tongda , Ai Xin , Chang Jinyong
Published: September 2023

In recent years, the data aggregation scheme was widely adopted in smart grids (SG) to protect data privacy while ensuring data availability. Meanwhile, asymmetric homomorphic encryption is a popular technique that guarantees data aggregation and accurate computing results. However, it often brings heavy computation overheads and costs, which increases burdens to SG. In order to lighten SG's burden, in this paper, a lightweight and fault-tolerant data aggregation scheme (LFTDA) with privacy-enhanced property is proposed. Unlike existing schemes, our proposed scheme uses a lightweight symmetric encryption algorithm and a skillful mathematical structure to achieve data aggregation. In addition, in the proposed scheme, smart meters are allowed to dynamically join and exit from the group while guaranteeing the correctness, security, and efficiency of aggregation. More importantly, our LFTDA is fault-tolerant, which means that the data collection from other devices will not be affected even if some of the smart meters or fog nodes do not work. From the view of security, LFTDA can defend against eavesdropping attack and collusion attack. Finally, we evaluate its performance along with other related schemes in terms of aggregation, decryption, and communication costs, which shows that LFTDA is very competitive and hence is suitable for many practical SG applications.
A Block chain-Based Supply Chain Quality Traceability With Hessenberg And QR Code Generation Algorithm
Authors: D Suja Mary , M Suriakala
Published: September 2023

The rising of globalization and the increasing rate of technological advancement, the volume of production as well as the ease of obtaining counterfeit goods has need the higher security. The Fake Product Identification through QRcode Using Block chain Technology System proposes a form of identification of fake products using block chain technology. To assigning a barcode to a particular product that will created by the manufacturer along with all the details of the product and the end customer can scan that barcode to get all information about that product. After scanning the barcode, the user can identify whether the product is real or fake. This paper focuses on, to check out whether a product is fake or not, the user would need to scan the barcode of the product. If it detects the product, the user will be able to see all the details of the product. If the scanned barcode is fake, it will let the user know that the product is fake. If no product is found, the user can upload a product details as a fake product entry to admin. In this paper, also focuses on how to improve the supply chain quality management by adopting the block chain technology, and propose a framework for block chain-based supply chain quality management.
An interpretable machine learning models for predicting in-hospital mortality in patients with sepsis based on multiple databases
Authors: Zhang Guyu , Shao Fei , Yuan Wei , Wu Junyuan , Qi Xuan , Gao Jie , Shao Rui , Tang Ziren , Wang Tao
Published: September 2023

Background:
This study aimed to develop and validate an interpretable machine-learning model that utilizes clinical features and inflammatory biomarkers to predict the risk of in-hospital mortality in critically ill patients suffering from sepsis.
Methods:
We enrolled all patients diagnosed with sepsis in the Medical Information Mart for Intensive Care IV (MIMIC-IV, v.2.0), eICU Collaborative Research Care (eICU-CRD 2.0), and the Amsterdam University Medical Centers databases (AmsterdamUMCdb 1.0.2). Lasso regression was employed for feature selection. Seven machine-learning methods were applied to develop prognostic models. The optimal model was chosen based on its accuracy and area under curve (AUC) in the validation cohort. Moreover, we utilized the SHapley Additive exPlanations (SHAP) method to elucidate the effects of the features attributed to the model and analyze how individual features affect the model's output. Finally, Spearman correlation analysis examined the associations among continuous predictor variables. Restricted cubic splines (RCS) explored potential non-linear relationships between continuous risk factors and in-hospital mortality.
Results:
A total of 3,535 patients with sepsis were eligible for participation in this study. The median age of the participants was 66 years (IQR, 55–77 years), and 56% were male. After selection, 12 of the 45 clinical parameters collected on the first day after ICU admission remained associated with prognosis and were used to develop machine-learning models. Among seven constructed models, the eXtreme Gradient Boosting (XGBoost) model achieved the best performance, with an AUC of 0.73 and an accuracy of 85% in the validation cohort. Feature importance analysis revealed that Age, AST, invasive ventilation treatment, and Heart rate were the top four features of the XGBoost model with the most significant impact. Some novel inflammatory biomarkers such as NLR, NHR, and MHR also critically impacted the in-hospital mortality of sepsis patients in the XGBoost model. Furthermore, SHAP force analysis illustrated how the constructed model visualized the prediction of the model.
Conclusions:
This study demonstrated the potential of machine-learning approaches for early prediction of outcomes in patients with sepsis. The SHAP method could improve the interoperability of machine-learning models and help clinicians better understand the reasoning behind the outcome.
Neonatal intubation: What are we doing?
Authors: Maglio Sabina , Cavallin Francesco , Sala Chiara , Bua Benedetta , Villani Paolo Ernesto , Menciassi Arianna , Tognarelli Selene , Trevisanuto Daniele
Published: September 2023

Background
How and when the forces are applied during neonatal intubation are currently unknown. This study investigated the pattern of the applied forces by using sensorised laryngoscopes during the intubation process in a neonatal manikin.
Methods
Nine experienced users of direct laryngoscope and nine experienced users of straight blade video laryngoscope were included in a neonatal manikin study. During each procedure, relevant forces were measured using a force epiglottis sensor that was placed on the distal surface of the blade.
Results
The pattern of the applied forces could be divided in three sections. With the direct laryngoscope, the first section showed either a quick rise of the force or a discontinuous rise with several peaks; after reaching the maximum force, there was a sort of plateau followed by a quick drop of the applied forces. With the video laryngoscope, the first section showed a quick rise of the force; after reaching the maximum force, there was an irregular and heterogeneous plateau, followed by heterogeneous decreases of the applied forces. Moreover, less forces were recorded when using the video laryngoscope.
Conclusions
This neonatal manikin study identified three sections in the diagram of the forces applied during intubation, which likely mirrored the three main phases of intubation. Overall, the pattern of each section showed some differences in relation to the laryngoscope (direct or video) that was used during the procedure. These findings may provide useful insights for improving the understanding of the procedure.
Population of invasive group A streptococci isolates from a German tertiary care center is dominated by the hypertoxigenic virulent M1UK genotype
Authors: Wolters Manuel , Berinson Benjamin , Degel-Brossmann Nicole , Hoffmann Armin , Bluszis Rico , Aepfelbacher Martin , Rohde Holger , Christner Martin
Published: September 2023

Purpose
Hypertoxigenic Streptococcus pyogenes emm1 lineage M1UK has recently been associated with upsurges of invasive infections and scarlet fever in several countries but whole-genome sequencing surveillance data from Germany is lacking. We here aimed at exploring recent isolates from our laboratory at a German tertiary care center for the presence of M1UK.
Methods
Whole-genome sequencing was employed to characterize a collection of 47 consecutive non-copy isolates recovered from blood cultures (n = 21) and tissue samples (n = 26) in our laboratory between October 2022 and April 2023.
Results
14 of 47 isolates were assigned to the M1UK lineage, which is the dominant lineage in our sample population.
Conclusion
We here provide first evidence that M1UK has entered Germany.
Antibacterial therapy for acute appendicitis in pediatric patients with hematologic cancer undergoing chemotherapy
Authors: Yoshizawa Kazuki , Ohno Yasunari , Okura Eri , Saito Shoji , Soejima Yuji
Published: September 2023

Purpose
A stratified treatment for acute appendicitis in children with blood cancer undergoing chemotherapy is yet to be established. This study aimed to compare treatment outcomes between antimicrobial therapy and appendectomy in pediatric patients with mild acute appendicitis.
Methods
Nine patients aged < 16 years who developed acute appendicitis during chemotherapy for blood cancers between January 2011 and October 2022 were included. Antimicrobial therapy was not indicated for cases with peritonitis. Clinical data were collected retrospectively, and the patients were divided into antimicrobial and surgical groups. Duration of treatment, duration of chemotherapy interruption, and complications were compared between the groups.
Results
There were no significant differences between the groups in mean age, primary disease ratio, white blood cell count at the onset of appendicitis, treatment duration, and chemotherapy interruption. The Pediatric Appendicitis Score was significantly lower in the antimicrobial group than in the surgical group (3.6 vs. 6.3, p = 0.004). There were no cases of antimicrobial resistance or complications. No recurrence of appendicitis was observed in the antimicrobial therapy group (mean follow-up: 27.8 months).
Conclusion
This study suggests that antimicrobial therapy is a treatment option for acute appendicitis without peritonitis in pediatric patients with hematological cancer.
Prompt and portable chemical fingerprinting analysis of complex liquids using diamond-based electronic tongue
Authors: Ohmagari Shinya , Nakahara Hiroya , Watatani Atsushi , Arita Ryoji , Morita Nobutomo , Takemura Kenshin , Iwasaki Wataru , Yoshitake Tsuyoshi
Published: September 2023

Chemical fingerprinting analysis using a diamond-based electronic tongue enables wide-range (>5V) voltammetry scanning with highly sensitive signal detection because of their chemical inertness and a large potential window. To measure the robustness of chemical fingerprints, spectral stability, and similarity were evaluated using complex liquids by cyclic voltammetry. Cyclic voltammograms showed different intensities and peak shapes depending on the sample variety, even among similar types of beverages. The similarity of chemical fingerprints as evaluated by the Euclidean distance was kept as high as >90% among identical liquids and it largely decreased against non-identical solutions. The similarity score dispersion is high enough as fingerprinting information and it could be utilized for data analysis applications including anomaly detection and authenticity determination. The diamond-based electronic tongue designed for single-use concept does not necessitate the recalibration of sensors and it possesses significant potential for prompt and portable fingerprinting analysis which is also attractive as platform devices to obtain rich information for machine learning.
SIRT1 and ZNF350 as novel biomarkers for osteoporosis: A bioinformatics analysis and experimental validation
Authors: Zhu Naiqiang , Si Jingyuan , Hou Jingyi , Yang Ning , Chen Bin , Wei Xu , Zhu Liguo
Published: September 2023

Background
Osteoporosis (OP) is characterized by bone mass decrease and bone tissue microarchitectural deterioration in bone tissue. This study identified potential biomarkers for early diagnosis of OP and elucidated the mechanism of OP.
Methods
Gene expression profiles were downloaded from Gene Expression Omnibus (GEO) for the GSE56814 dataset. A gene co-expression network was constructed using weighted gene co-expression network analysis (WGCNA) to identify key modules associated with healthy and OP samples. Functional enrichment analysis was conducted using the R clusterProfiler package for modules to construct the transcriptional regulatory factor networks. We used the "ggpubr" package in R to screen for differentially expressed genes between the two samples. Gene set variation analysis (GSVA) was employed to further validate hub gene expression levels between normal and OP samples using RT-PCR and immunofluorescence to evaluate the potential biological changes in various samples.
Results
There was a distinction between the normal and OP conditions based on the preserved significant module. A total of 100 genes with the highest MM scores were considered key genes. Functional enrichment analysis suggested that the top 10 biological processes, cellular component and molecular functions were enriched. The Toll-like receptor signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, osteoclast differentiation, JAK-STAT signaling pathway, and chemokine signaling pathway were identified by Kyoto Encyclopedia of Genes and Genomes pathway analysis. SIRT1 and ZNF350 were identified by Wilcoxon algorithm as hub differentially expressed transcriptional regulatory factors that promote OP progression by affecting oxidative phosphorylation, apoptosis, PI3K-Akt-mTOR signaling, and p53 pathway. According to RT-PCR and immunostaining results, SIRT1 and ZNF350 levels were significantly higher in OP samples than in normal samples.
Conclusion
SIRT1 and ZNF350 are important transcriptional regulatory factors for the pathogenesis of OP and may be novel biomarkers for OP treatment.
Priming seeds with potassium nitrate is associated with modulation of seed germination and seedling growth ecology of cucumis metuliferus
Authors: Mutetwa Moses , Mafukidze Brian Panashe , Makaure Brenda Tsungi , Mubaiwa Tariro Clara , Dendera Obvious , Tovigepi Elvis , Mtaita Tuarira , Ngezimana Wonder , Chaibva Paul
Published: September 2023

The horned melon (Cucumis metuliferus) is mostly grown in tropical and subtropical countries, where it thrives on deep to shallow, well-drained soils. Seed dormancy, which causes poor and delayed germination, has remained a problem for farmers in several African countries, including Zimbabwe, who have begun producing horned melon. Midlands State University conducted a laboratory experiment to evaluate the effects of potassium nitrate on seed germination and early seedling growth of horned melon. The experiment was set up in a Completely Random Design (CRD) with seven different potassium nitrate (KNO3) concentrations (0 %, 0.5 %, 1.0 %, 1.5 %, 2.0 %, 2.5 %, and 3.0 %), each duplicated three times. The data was analyzed using a one-way Analysis of Variance (ANOVA) in Genstat 18th edition. The characteristics of germination and early seedling development were assessed. All germination and early seedling development characteristics were significantly affected by potassium nitrate. Germination %, mean germination rate, germination index, mean daily germination percent, synchronization of germination, peak value for germination, and germination value all had a significant influence. Potassium nitrate had a significant influence on mean germination time and time to 50 % germination, with the lowest values obtained on seeds primed with 3 % KNO3. There was a significant difference in seedling height, root length, seedling length, fresh biomass, and dry weight between seeds primed with 2.5 % KNO3 and seeds not primed with 2.5 % KNO3. Farmers are advised to use 2.5 % KNO3 concentration for seed priming for optimal germination and early plant development of horned melon
The influence of rice protein concentrate on the technological process of wheat bread production
Authors: Shevchenko Anastasiia , Litvynchuk Svitlana , Koval Olga
Published: September 2023

Bakery products from wheat flour are low in protein and it is inferior and also absorbed at a low level. To solve this problem sources of complete proteins may be introduced into the formulation of bakery products. But animal proteins can be allergens. An alternative can be concentrates, hydrolysates and isolates of proteins of vegeTable origin, particularly, obtained from rice. Microbiological, biochemical and conformational changes in dough and bread from wheat flour were influenced by adding rice protein concentrate. Gas-forming capacity of the dough with rice protein concentrate decreased by 8.3–20.8 % compared to the control sample where there was increase of the dosage. Gas formation occurred less intensively in the dough with rice protein concentrate, because fermentation was delayed due to a decrease in the availability of nutrients. The first peak on the gas formation graph in case of the dough with the addition of 4–8 % rice protein concentrate was seen after 65 minutes, in the control sample it was after 60 minutes. When adding 16 % of the additive, the first peak of gas formation was not clearly defined. The second peak of gas formation for control sample was observed after 150 min and for samples with rice protein concentrate a bit later and it was not clearly defined. Infrared spectra showed that relative reflection coefficient of samples with rice protein concentrate was lower both for dough after kneading and after fermentation. The addition of 4 and 8 % rice protein concentrate did not affect the amount of formed sugars, and the addition of 16 % reduced this indicator by 1.6 %. The amount of fermented sugars decreased by 3.0–7.8 %. So, changes during the technological process of bread-making can be followed due to the obtained results for obtaining bread with high protein content
Pollution status and pollution source identification in the groundwater of Yar-Dalla in Wudil, Kano, Nigeria
Authors: Onoyima Christian Chinweuba , Onoyima Nichodemus Emeka
Published: September 2023

The recent increase in population growth and industrialization has resulted in higher pollution loads in the environment including the groundwater, which is a vital freshwater resource. Water Quality Index (WQI) was used to assess the water quality of the study area, while multivariate statistical techniques, including Principal Component Analysis (PCA) and Cluster Analysis (CA), were used to identify possible sources of the pollutants. The results of the descriptive statistics show that pH, Chloride, Alkalinity, Nitrate, and Cu are within the WHO standard for drinking water in all the water samples, while Cl-, Cd, Cr, and Pb exceeded the allowable standard in 20 %, 30 %, 10 %, and 40 % respectively of the water samples. CA group sample locations into three distinct clusters: C1 (A, B, E, G, F, and H), C2 (C, J, and I), and C3 (D). C1 has the highest anthropogenic influence followed by C2, while C3 has the least. WQI shows that C1 is in the extremely poor class (WQI>100), C2 is in the poor class (51<WQI<75), and C3 is in the good class (26<WQI<50). The PCA yielded 3 components which explained 72.98 % of the total variance in the data set. The first Component accounts for 38.85 %. Component 2 accounts for 19.76 % of the total variance while Component 3 accounts for 14.37 % of the total variance. The groundwater of the area is mainly impacted by anthropogenic factors such as agricultural activities, domestic waste, and vehicular/traffic input
Anomalies and symmetry fractionalization
Authors: Delmastro Diego Gabriel , Gomis Jaume , Hsin Po-Shen , Komargodski Zohar
Published: September 2023

We study ordinary, zero-form symmetry GG and its anomalies in a system with a one-form symmetry \GammaΓ. In a theory with one-form symmetry, the action of GG on charged line operators is not completely determined, and additional data, a fractionalization class, needs to be specified. Distinct choices of a fractionalization class can result in different values for the anomalies of GG if the theory has an anomaly involving \GammaΓ. Therefore, the computation of the ’t Hooft anomaly for an ordinary symmetry GG generally requires first discovering the one-form symmetry \GammaΓ of the physical system. We show that the multiple values of the anomaly for GG can be realized by twisted gauge transformations, since twisted gauge transformations shift fractionalization classes. We illustrate these ideas in QCD theories in diverse dimensions. We successfully match the anomalies of time-reversal symmetries in 2+1d2+1d gauge theories, across the different fractionalization classes, with previous conjectures for the infrared phases of such strongly coupled theories, and also provide new checks of these proposals. We perform consistency checks of recent proposals about two-dimensional adjoint QCD and present new results about the anomaly of the axial \mathbb{Z}_{2N}ℤ2N symmetry in 3+1d3+1d{\cal N}=1 super-Yang-Mills. Finally, we study fractionalization classes that lead to 2-group symmetry, both in QCD-like theories, and in 2+1d2+1d\mathbb{Z}_2ℤ2 gauge theory.
Work Engagement Scale: Construct Validity and Reliability in the Colombian Organizational Context
Authors: Arana Medina Claudia Marcela , Cárdenas Niño Lucila , Betancur Arias Juan Diego , Montoya Zuluaga Paula Andrea
Published: September 2023

This manuscript shows the results of the evidence of content and internal structure obtained from an instrument to measure work engagement. This instrument is aimed at workers of Colombian labor organizations that belong to different economic sectors (commerce, services, education, and health). The instrument was designed based on the postulates of cognitive theory and is structured into three factors that operationalize the construct: (a) behavioral dimension (15 items), (b) affective dimension (16 items), and (c) cognitive dimension (14 items), for a total of 45 items. The results of the content evidence through expert judgment suggested the elimination of three items, due to ambiguity and lack of clarity, leaving the 42- item test. After this evidence, the instrument was piloted in a sample of 460 participants. The item-test correlation analysis recommended the elimination ofone item due to its low correlation with the factor. The evidence of internal structure through exploratory factor analysis (EFA) proposed a three-factor structure, with an explained variance of 63%; 9 items were eliminated due to high residual.The fit indicators showed a GFI = .99; and those of residual showed a RMSR =.03 and Kelley = .04; each factor obtained an ordinal Cronbach’s Alpha of .95 (behavioral), .97 (affective), and .87 (cognitive). These results indicate precision in the measurement and consistency of the items to measure each of the factors.
Is Negative Affect that Bad? The Effect of Affective States on Conventional and Unconventional Creative Thinking in University Students
Authors: Rosa Pedro J. , Ribeiro Roberto , Ibérico Nogueira Sara
Published: September 2023

Introduction. The role of affective states on the creative process has been receiving the attention of researchers and has led to contradictory results. Most research in creativity has emphasized the role of affective states, mainly positive ones, on creativity levels, namely those resulting from divergent thinking tasks that reveal the unconventional way of thinking in the creative process. However, there are nostudies to date that focus on the impact of affective states on conventional and unconventional thinking, during the same creative process, which consider a singlecreative assessment task. The aim of this experimental study was to analyze the effect of induced affective states on both conventional and unconventional thinkingof creativity in adults by using the TCT-DP (Test for Creative Thinking-Drawing Production). Method. Seventy-five university students, mostly female, with a meanage of 26.95 years, were randomly assigned into three affect elicitation conditions (pleasant vs. unpleasant vs. neutral). Results. Results indicated that the negativeaffective state led to higher levels of conventional thinking when compared to positive and neutral affective states. However, no significant differences were foundon unconventional thinking across the three conditions. Conclusions. Our results do not support the assumption that the negative affect has a hindering effect oncreativity nor the positive affect increases creativity. Negative affect seems to promote conventional thinking, perhaps due to its cognitive correlates, which canbe manifested in focusing attention and analytic thinking. Practical and theoretical implications for future research on the role of affective states on creativity are discussed
Chocolates Produced with Unroasted and Roasted Cocoa Beans: A Comparative Study of the Preservation of Bioactive Compounds
Authors: Onelli Rebeca , de Jesus Josane , Reis Lucas , Alves Isabel , Santos Leandro , Ferrão Sibelli
Published: September 2023

The aim of the present study was to evaluate the effect of roasting and cocoa mass content on the composition of chocolates. Chocolate formulations were developed (40, 50, 60 and 70% cocoa solids) using unroasted and roasted cocoa beans, and analyses were performed: physicochemical, chemical composition, antioxidant capacity, procyanidin content, total phenolic compounds, quantification of theobromine, caffeine, catechin and epicatechin by high performance liquid chromatography (HPLC) and spectroscopic profile by mid-infrared spectroscopy (MIR). The results revealed that higher values of total phenolics, epicatechin and procyanidins, were obtained in chocolates produced with unroasted cocoa beans, with a significant difference in relation to those with roasted cocoa beans. It was observed that increasing the percentage of cocoa in the formulations caused an increase in the content of bioactive compounds. The use of MIR in the differentiation of chocolate samples produced with roasted and unroasted cocoa beans obtained a positive result. This technique associated with principal component analysis (PCA) enabled the separation of chocolates according to the type of cocoa bean (roasted and unroasted) used in production, confirming its importance for a quick evaluation of the parameters.
Cost-effective method for the estimation of tree crown density in urban settings using a smartphone
Authors: Sippel Ivo , Moeller Lucie , Friesen Jan
Published: September 2023

Urban trees provide vital ecosystem services, and assessing their health is crucial for managing urban infrastructure. Traditional methods of assessing crown density, an indicator of tree vitality, involve horizontal perspectives of unobstructed canopies. This study presents a novel method for estimating crown density in urban street trees that are surrounded by obstructing objects like buildings. The approach is based on photographs of the tree crown from defined positions using a smartphone. The method was validated on eight small-leaved lime trees in Leipzig during the 2021 vegetation period, demonstrating that crown density can be estimated by analyzing smartphone-photographs from various perspectives. The method provides data to quantify crown development and can be used to compare the vitality status of individual trees. The different perspectives are consistent in their estimates of crown density throughout the annual plateau phase of crown development. During the initial greening phase, crown photographs taken from angularly oriented positions showed a higher slope value than those taken from other positions. The method can also estimate the effect of blue-green infrastructures on tree vitality compared to regular urban tree planting methods. The approach is a practical and cost-effective tool for assessing tree vitality in spatially confined urban areas.