bluuebunny/crossref_metadata_2025_split huggingface dataset:
What is the Optimal Financial Structure Applicable to All Companies
Authors: Djomo Chimba Ulrich 
Published: September 2022

To maximize value, companies must adopt the optimal financial structure. However, identifying this structure is not easy. Literature does not give satisfactory results. To remedy this difficulty, we have sought the optimal financial structure applicable to all companies. Thus, in a new approach by the cost of capital, using modelling, we identify an optimal financial structure model that can neutralize the risk of default of debt: D/K with t ? i but t > i.
Development of Plant Physiology Practicum Guidelines Based on Learning by Research for Biological Education Students
Authors: Thahir Rahmatia , Magfirah Nurul , Anisa Anisa , Nurdiyanti Nurdiyanti 
Published: September 2022

<p class="5abstrak"><span lang="EN">Universities are currently focusing on development of two aspects, namely being a learning college and a research college. Scientific attitudes, scientific processes, and scientific products are special characteristics of the research learning process. The three components of research learning are developed by educators both teachers and lecturers maximally in practicum activities in the laboratory. Therefore, as a first step in student learning, lecturers should be able to innovate and be creative in utilizing existing resources for example by the preparation and implementation practicum based on learning by research model. The purpose of this study is to know the process of developing a practical guide to Plant Physiology based on Learning By Research. To produce practical products of plant physiology that is valid, and practical for use in the Biological Education Program of Muhammadiyah University Makassar. This research is Research and Development (R&amp;D) with using plomp development model. From the results of the research that has been done shows that the practice guide of Plant Physiology based on Learning by Research that has been developed meets valid and practical criteria. The validation result of the guide is obtained the average value of the Content Validation Coefficient of 0.88 or has high relevance. While the practicality test is in the category of 'overall implemented' with a value of 3.56</span>.</p>
Prevalence and determinants for poor nutritional status among children in Rural Dodoma Region of Tanzania
Authors: Mbwana Hadijah A. , Mwinuka Lutengano 
Published: September 2022

Abstract

Background: Undernutrition is a problem of public health significant in developing countries. This study examined the factors that determine stunting in children in Dodoma Region in Tanzania.
Methods: Multistage stratified sampling procedure was used to select respondents. Height and weight were measured and nutritional status of children was determined. Stunting, underweight, and wasting in children were defined using these criteria, which were compared to WHO norms and standards. Logistic regression models were used to establish relationships between stunting and multiple variables.
Results: The overall prevalence of stunting was 33%. Mzula village had the highest prevalence of severely underweight children at 3.6%. There were no significant differences in weight and height among children between villages. Important determinants of stunting in a univariate logistic regression were mother’s education, material used to build house, age of the child and distance to water source. In the multivariate analysis distance to water source and mother’s education, maternal education, and child’s age were found to independently predict stunting. The univariate logistic regression picked the father’s education, age of the mother and distance to water source as main determinants of being underweight.
Conclusion: The current study stresses the importance of implementing region specific and context-relevant treatments to prevent malnutrition in this and other similar contexts in Tanzania.
Anti-SARS-CoV-2 in vitro potential of Castor Oil Plant (Ricinus communis) Leaf Extract: In-Silico Virtual Evidence
Authors: Elkousy Rawah H. , Said Zeinab N.A. , Ali Mohamed A. , Kutkat Omnia , wafa Salwa A. Abu El 
Published: September 2022

Abstract
Background Ricinus communis L. is a medicinal plant displays valuable pharmacological properties. Diverse phytochemical constituents display valuable pharmacological properties, including antioxidant, antimicrobial, analgesic, antipyretic, antibacterial, antiviral, and anti-inflammatory property. This study targeted to isolate and identify some constituents of R. communis leaves using ultra-performance liquid chromatography coupled with mass spectroscopy (UPLC-MS/MS) and different chromatographic techniques, then characterize the potential cytotoxicity, anti-MERS-CoV and anti-SARS-CoV-2 activity in vitro. Isolated phytoconstituents and remdesivir are assessed for in-silico anti-COVID-19 activity by inhibiting the main protease and spike protein using molecular docking tools. Methods: The CH2Cl2 fraction was subjected to repeated chromatographic separation to isolate the phytochemicals, and their structures were elucidated using nuclear magnetic resonance spectroscopy. UPLC-Triple TOF-MS/MS was performed to determine the different phytochemicals in the CH2Cl2 fraction. The in vitro anti-MERS and anti-SARS-CoV2 activity for different fractions and for two pure isolated compounds, lupeol (RS) and ricinine (RS1) were evaluated using Plaque reduction assay and IC50 based on their cytotoxic concentration (CC50) from an MTT assay using Vero E6 cell line. Molecular docking studies were carried out for both SARS-CoV-2 spike (S) and main protease (Mpro) receptors then examined the possible mechanisms of action. Results: The methylene chloride extract exhibited pronounced virucidal effect with more than a 90% viral inhibitory effect, it showed activity against SARS-CoV- 2 (IC50 = 1.76µg/ml) with high safety index, SI = 291.5. It was also shown that ricinine had superior potential activity against SARS-CoV-2, (IC50 = 2.5 µg/ ml). This constituent was less effective for MERS, IC50 = 87.2 µg/ ml. Lupeol displayed the most potency against MERS, (IC50 = 5.28 µg/ ml), SI = 67.27, but was less effective for SARS, IC50 = 19.5 µg/ ml. Ricinine showed significant binding to (3CLpro) and modest affinity for (S) spike protein, along with a possible interaction with SARS-CoV-2 major protease. Ricinine appeared to be the most biologically active. Conclusion: The study showed that Ricinus communis and its isolated compounds have potential natural virucidal activity against SARS-COV-2, however, additional exploration is necessary for further chemical modification of these structures, guided by the molecular docking tools and study for their in vivo activity.
Isolated cerebellar metastasis from urothelial carcinoma: a case report of a rare phenomenon
Authors: Verheijen Eduard , Taal Walter , Tewari Rishi D.S. Nandoe , Giessen Mariëtte C.A. , Roshani Hossain 
Published: September 2022

Abstract
Introduction
Although urothelial carcinoma (UC) generally is non-invasive, contrastingly in 25% of patients UC metastasizes. Isolated CNS metastasis from UC without other distant metastases are considered rare. In this case report we describe a patient with an isolated and solitary cerebellar metastasis from UC.
Case presentation
A 77-year-old male was diagnosed with a pT2N0M0 high-grade urothelial carcinoma and treated with transurethral resection and chemoradiation therapy. Several months later, the patient presented with neurological symptoms, and radiological imaging revealed a solitary cerebellar mass. A body CT scan showed no other metastasis. After surgical resection, histology confirmed a urothelial origin of the mass, matching his primary UC and the patient received post-operative stereotactic radiotherapy at the surgical site.
Conclusions
Isolated brain metastases without other distant metastases from UC are rare, so histologic confirmation of the brain metastasis is essential, particularly when the time interval between diagnosis of the UC and brain metastasis increases.
Abrogation of the triple-negative breast tumor growth in orthotopic mouse models through survivin silencing using liposome-mediated delivery of siRNA
Authors: Vaidya Sandeep , Mohod Annie , Chowdary Abhisheik , Andugulapati Sai Balaji , pabbaraja srihari 
Published: September 2022

Abstract
The authors have requested that this preprint be removed from Research Square.
Three-Dimensional Heat Maps and Distribution of Pilon Fractures
Authors: Gao Yuling , Liu Yang , Zhou Junlin 
Published: September 2022

Abstract
Background: This study aimed to create three-dimensional heat maps of pilon fractures for assessing the distribution of the fractures.
Methods: The study included 144 patients (145 fractures) diagnosed with pilon fractures between January 2017 to December 2021. CT scan was performed in all patients. Based on the AO/OTA classification, the fractures were divided into 6 types (B1, B2, B3, C1, C2, and C3). These fractures were allocated in 7 areas and 3 columns on the distal articular surface of the tibia. All fractures were converted to the standard tibial model to create heat maps. A P value < 0.05 was considered statistically significant
Results：Pilon fractures involve the anterior talofibular ligament area (23%), the fibular notch area(11%), anterior median area(22%), and anterior area of the medial malleolus (18%), malleolus sulcus area (15%), medial malleolus area (7%), posterior malleolus (7%) , posterior talofibular ligament area (6%). There was a significant difference in the proportion of 3 columns based on the AO/OTA classification (P<0.05), and the proportion of the posterior column was least, with an average value of 0.236.
Conclusions：Three-dimensional heat maps of pilon fractures are successfully created. Most pilon fractures are type C3 fractures based on the AO/OTA classification. Pilon fractures mainly affect the anterolateral column of the tibia, with less involvement of the posterolateral column. Based on the heat maps, pilon fractures mainly affect the anterior talofibular ligament area, fibular notch area, anterior border of the tibia, and malleolus sulcus area.
Level of Confidence: IIIa
Wafer Map Defect Classification using Deep Learning Framework with Data Augmentation on Imbalance Datasets
Authors: Tsai Tsung-Han , Wang Chieng-Yang 
Published: September 2022

Abstract
Wafer map defect classification is a key task for the semiconductor industry to improve the yield rate. Most wafer map defect classifications suffer from the problem of data imbalance and insufficient data. This paper proposes a global-to-local generative adversarial network (G2LGAN) method using the deep learning framework. It extracts global features and local features separately to generate effective data even in the imbalanced dataset. We use random under-sampling to suppress the majority class of data. We use MobilenetV2 as the classifier, and use two datasets for validation. One is open dataset 1WM-811K and the other is called 21-Defect built from the industry. Based on the serious dataset imbalance problem, this paper integrates data enhancement and random undersampling methods to optimize the dataset and uses the proposed classification network for classification tasks. The results of WM-811K dataset show that the proposed method has a classification accuracy of 98.39 and an F1-Score of 93.01. We also conduct cross-validation on the 21-Defect dataset and the results show that the proposed method has good robustness.
Effects of compost incorporation on greenhouse gas emissions, N retention, and crop yield at two different P levels: results from a two-year lysimeter experiment with silty loam soil
Authors: Li Zhijie , Reichel Rüdiger , Cao Xinyue , Pütz Thomas , Küpper Werner , Meulendick Philipp , Zhao Kerui , Endenich Manuel , Brüggemann Nicolas 
Published: September 2022

Abstract
Purpose Compost has great potential for use in sustainable agriculture. Stoichiometric relationships between C, N and P play an important role in soil biogeochemical processes. The aim of this study was to quantify greenhouse gas (GHG) emissions, soil nutrient retention and leaching, aboveground biomass and crop yield at different soil C:N:P ratios.
Methods The lysimeter experiment included six treatments: (1) without fertilization and seeding (bare), (2) common P fertilization (control), (3) P fertilization at twice the common level, (4) compost addition of 40 t ha-1 and common P fertilization, (5) compost addition of 40 t ha-1 and P fertilization at twice the common level, and (6) compost addition of 80 t ha-1 and common P fertilization. Treatments 2-6 were all fertilized at the same N level.
Results Compost application significantly increased aboveground biomass and grain yield, particularly in the double compost treatment, where the variability between replicates was particularly low. However, the effect of compost application on GHG emissions was insignificant. Addition of 80 t ha-1 of compost increased dissolved organic carbon (DOC), compared to the control, but did not lead to a significant increase in DOC, N and P leaching losses. In contrast, bare soil resulted in significant leaching losses of DOC and nitrate (NO3–) compared to plant-covered treatments.
Conclusion We conclude that combined compost and N fertilizer application is a suitable management option for increasing crop yield and reducing its variability, as it does not lead to increased GHG emissions and leaching losses of NO3– and P.
Development and evaluation of sandwich ELISA for detection and quantification of Staphylococcal enterotoxin-A in food
Authors: Singh Mamta , Agrawal Ravi Kant , Singh Bhoj Raj , Mendiratta Sanjod Kumar , Kumar Deepak , Kumar Bablu , Singh Mithilesh Kumar 
Published: September 2022

Abstract

Purpose Staphylococcus aureus is an opportunistic zoonotic organism which secretes around 23 different types of enterotoxins. Classical enterotoxins (SEA, SEB, SEC, SED and SEE) are responsible for >95 % of food poisoning outbreaks of which SEA alone is responsible for >75% of them. The present study was undertaken to develop sandwich ELISA forsensitive, specific and quantitative detection of Staphylococcal enterotoxins-A in food samples.
Methods Optimization of sandwich ELISA was attempted in two ways. In first, rabbit polyclonal anti-SEA was used as capture antibody and mouse monoclonal anti-SEA as detector antibody, in second, mouse monoclonal anti-SEA was used as capture Antibody and rabbit polyclonal anti-SEA as detector antibody.
Results In the optimization of sandwich ELISA, mouse monoclonal anti-SEA as capture antibody and rabbit polyclonal anti-SEA as detector antibody yieldedhighest sensitivity of 0.5-0.75 ng ml-1. The developed assay was found to be highly specific and having equivalent sensitivity to available commercial kits.
Conclusion The developed sandwich ELISA may be utilized as a sensitive, specific and quantitative test for detection of Staphylococcal enterotoxin-A in food samples. The developed ELISA may serve as a cheap alternative to commercial kits which need importation and therefore are relatively costly. The sandwich ELISA developed may be useful for microbiological quality assurance of foods specially in developing countries.
Cannabis Use in Spinal Injury Patients - a Qualitative Study of Patients
Authors: Anas Mohammad , Raja Usman , Raza Wajid 
Published: September 2022

Abstract
Study Design: A descriptive observational qualitative study Objective: To identify the popularity in use of cannabis for management of symptoms in spinal cord injury individuals in the United Kingdom as well as noting which symptoms are common amongst these individuals and if they use cannabis, is it medically prescribed or obtained from other means. Setting: Spinal cord injury patients’ part of the Yorkshire Regional Spinal Injuries Centre and SPINE community in United Kingdom. Methods: The data was collected in the form of a 7-point electronic survey which was sent to spinal cord injured individuals from the local community. All results were anonymous, and confidentiality was maintained throughout the process. Results: In total, 223 patients completed the survey. 65.35% of individuals were paraplegic with the rest being tetraplegic and 65% suffered from a traumatic cause of injury. The majority (56.75%) suffered from the injury for less than 9 years. 50–60% of all individuals suffered from one of the following: chronic pain (longer than 3 months), spasticity, loss of/difficulty in sleeping or anxiety/depression. 14.93% admitted to using cannabis to manage the above symptoms where it benefitted them, in which 79.41% acquired this through non-legal suppliers. Conclusion: This study highlights the demand of the use of cannabis to address chronic spinal cord injury symptoms including pain, spasticity, lack of and difficulty sleeping and psychological symptoms. Clinicians should be aware of the high prevalence of demand in the population, however further steps and further research in this area is needed.
Development of predictive models for lymphedema prediction by using blood test and chemotherapy data
Authors: Trinh Xuan-Tung , Chien Pham Ngoc , Long Nguyen-Van , Anh Le Thi , Giang Nguyen Ngan , Nam Sun Young , Myung Yujin 
Published: September 2022

Abstract
Background: Lymphedema is a disease thatrefers to tissue swelling caused by an accumulation of protein-rich fluid that is usually drained through the lymphatic system. Detection of lymphedema is often based on expensive diagnoses such as bioimpedance spectroscopy, shear wave elastography, computed tomography, etc. Applications of data science and machine learning in predicting medical conditions offered support for medical doctors and patients in the early detection of diseases. Although current studies proposed machine learning models to predict lymphedema by using symptoms reported by patients, there might be uncertaintyinpatient-input data. In this study, we proposed to usemore reliable input data such as complete blood count, serum, and therapy data to develop predictive models for lymphedema.
Methods: We collected data from 2137 patients, including 356 patients having lymphedema and 1781 patients not having lymphedema. The lymphedema status of each patient was confirmed by clinicians. Data of each patient includes: 1) complete blood count (CBC) test, 2) serum test, and 3) therapy information. We used machine learning algorithms (i.e., random forest, gradient boosting, support vector machine, decision tree and artificial neural network) to develop predictive models on training dataset (i.e., 80% of the data) and tested the models on the test dataset (i.e., 20% of the data). After choosing the best predictive models, we developed web application for medical doctors and clinicians to use our models for quick screening lymphedema patients.
Results: A dataset of 2137 patients was collected from Seoul National University Bundang Hospital. Predictive models based on random forest algorithm showed satisfactory performance (balanced accuracy = 86.7 ± 0.9%, sensitivity = 84.3 ± 0.6%, specificity = 89.1 ± 1.5%, precision = 97.4 ± 0.4%, F1 score = 90.4 ± 0.4%, and AUC = 0.931 ± 0.007). A web application was made to assist medical doctors in quick screening lymphedema: https://snubhtxt.shinyapps.io/SNUBH_Lymphedema.
Conclusions: Our study would provide a tool for the early detection of lymphedema and be the basement for future studies predicting lymphedema stages.
ASPM induces radiotherapy resistance by disrupting microtubule stability leading to chromosome malsegregation in non-small cell lung cancer
Authors: Yu Jinming , Zhong Tao , Wang Juan , Xie Songbo , Liu Lisheng , Wang Minglei , Wu Fei , Xiao Changyan , Chen Xiaozheng , Yan Weiwei , Cao Yu , Gongye Xiaoxiao , Wu Meng , Chen Dawei 
Published: September 2022

Abstract
Radiotherapy (RT) resistance remains a substantial challenge in cancer therapy. Although physical factors are optimizing, the biological mechanisms for RT resistance are still elusive. Herein, we explored potential reasons for this difficult problem by generating RT-resistant models for in vitro and in vivo experiments. We found that abnormal spindle-like microcephaly-associated protein (ASPM) was highly expressed in RT-resistant samples and significantly correlated with disease advance in lung adenocarcinoma. Mechanistically, ASPM helps RT-resistant cells to evade spindle checkpoint surveillance and complete cell division after irradiation through destruction of microtubule stability, with subsequent increases in chromosome mis-segregation and deteriorating chromosomal stability during mitosis. Depletion of ASPM stabilized microtubules and significantly decreased chromosome mis-segregation, rendering RT-resistant cells renew sensitive to radiation. We further found, with bioinformatics analysis, amino acid sequence 963–1263 of ASPM as a potential new drug target for overcoming RT resistance and identified 9 drug pockets within this domain for clinical translation. Our findings suggest that ASPM is a key regulator with an important role in promoting RT resistance in non-small cell lung cancer, and that suppressing or blocking its expression could be worth exploring as therapy for a variety of RT-resistant cancers.
The modulation of iron metabolism affects the Rhabdomyosarcoma tumor growth in vitro and in vivo
Authors: Asperti Michela , Cantamessa Luca , Gryzik Magdalena , Bugatti Mattia , Codenotti Silvia , Denardo Andrea , Vermi William , Fanzani Alessandro , Poli Maura 
Published: September 2022

Abstract
Purpose.
Rhabdomyosarcoma (RMS) is an aggressive rare neoplasm that derives from mesenchymal cells, which frequently develops resistance to the current therapies and the formation of metastases. Thus, new therapies are needed. The alteration of iron metabolism in cancer cells was effective in reducing the progression of many tumors but not yet investigated in RMS. Here we investigated the effect of iron modulation in RMS both in vitro and in vivo.
Methods.
We first characterized the most used RMS cell lines representing the most common subtypes, embryonal (ERMS, RD cells) and alveolar (ARMS, RH30 cells), for their iron metabolism, analyzing iron related proteins and genes. Then we investigated the effects of both iron overload and chelation strategies in vitro and in vivo.
Results.
RMS cell lines expressed iron related proteins, even if at lower levels compared to hepatic cell lines. The treatment with ferric ammonium citrate (FAC, as iron source) and with deferiprone (DFP, as iron chelator), significantly affected the cell viability of RD and RH30. Moreover, iron supplementation (in the form of iron dextran) or iron chelation (in the form of DFP) were also effective in vivo in inhibiting the tumor mass growth both derived from RD and RH30 with iron chelation treatment the most effective one.
Conclusions.
All the data suggest that the iron modulation could be a promising approach to overcome the RMS tumor growth.