bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pregnancy Intentions of Youth in the Era of Climate Change: A Qualitative Auto- Photography Study
Authors: Smith Danielle M. , Sales Javier , Williams Aleyah , Munro Sarah 
Published: April 2022

Abstract
Background
Climate change poses a global health risk through consequences such as sea level rise, wildfires, and increased air pollution. Children born today and in the future may be disproportionately affected by climate change. As a result, many young adults are rethinking having children. The impacts of the climate crisis on the decision-making of parents is an understudied area of research. This study aims to be one of the first to explore how climate change impacts the pregnancy intentions of youth and their perspectives towards childbearing.
Methods
We conducted auto-photography and qualitative interviews. Participants were recruited using social media, and were aged 18–25, nulliparous, assigned female at birth, and were either current or previous residents of British Columbia, Canada. We asked participants to take photos that responded to the question, “Show us how climate change impacts your decision to have a family,” then complete a virtual, one-on-one interview during which photo-elicitation was employed to guide conversation about participants’ decision-making related to childbearing and climate change. We subjected all transcribed interviews to qualitative thematic analysis.
Results
We conducted in-depth interviews with 7 participants who discussed a total of 33 photographs. Analysis of participants’ interviews and photographs identified themes of eco-anxiety, hesitancy towards having children, and a desire for systemic change. Participants experienced anxiety, grief, and loss when faced with thoughts of change associated with their environments. Climate change was a consideration for many participants in their childbearing decision making, and it was interrelated with social-environmental factors, such as cost of living.
Conclusion
We aimed to identify the ways in which climate change may impact youth decisions to have a family. Responses ranged from feeling that climate change had no effect on family planning to choosing not to have children entirely because of climate change. Further research on this topic is needed in order to direct climate change policy.
Triglyceride-glucose index predicts the risk of coronary artery disease in premenopausal women
Authors: Guo Qifeng , Zhan Yinge , Ma Guoping , Duan Linan , Liu Yongsheng , Chen Jie , Liu Gang , Zheng Mingqi , Wei Mei 
Published: April 2022

Abstract
Background: The triglyceride glucose index (TyG index), a reliable alternative marker of insulin resistance (IR), has been regarded as an independent predictor of cardiovascular disease (CVD). However, the relationship between TyG index and coronary artery disease (CAD) in premenopausal women remains unclear. We aimed to investigate the prognostic value of TyG index in premenopausal women with CAD. Methods: A total of 158 Chinese female subjects were enrolled in this retrospective study. Clinical data were collected from medical records. The severity of CAD was assessed by coronary angiography. CAD was defined as Coronary artery stenosis ≥50% in at least one major coronary artery. Patients were divided into different groups according to their TyG index and whether they had CAD. Multivariate logistic regression model was used to evaluate the relationship between TyG index and CAD. Results: The patients with high TyG index had a higher risk of CAD than those with low TyG index (P<0.01). The difference was pronounced in the age group of 49 years or older. Multivariate logistic regression analysis showed that the TyG index was an independent risk factor for CAD in premenopausal women (fully adjusted model: OR 2.730, 95%CI 1.102-6.764, P=0.030). Conclusions: Elevated TyG index is associated with increased risk of CAD in Chinese premenopausal women, suggesting that the TyG index may be used as a marker of CAD risk in premenopausal women in China.
Glyoxal Fixation Allows Consistent Staining of Brain Vessels, Pericytes, and Blood-Brain Barrier Proteins
Authors: Thomas Sithara , Sadanandan Jayanarayanan , Blackburn Spiros L , McBride Devin W , Dienel Ari , Ha Sung , Zeineddine Hussein , T Peeyush Kumar 
Published: April 2022

Abstract
Brain vascular staining has great importance in understanding cerebrovascular pathologies. 4% Paraformaldehyde is considered as the gold standard fixation technique for immunohistochemistry and it revolutionized the examination of proteins in fixed tissues. However, this fixation technique produces inconsistent immunohistochemical staining results due to antigen masking. Here we test a new fixation protocol using 3% glyoxal and demonstrate that this method improves staining of the brain vasculature, pericytes, and tight junction proteins compared to 4% paraformaldehyde. Using this new fixation technique will provide more detailed information about vascular protein expressions, their distributions, and colocalizations with other proteins at the molecular level in the brain vasculature.
Low-cost enzymatic deacidification of corn oil with high triglyceride retention
Authors: Gao Rui , Sun Shangde , Zhou Yanxia , Chen Xiaowei , Zhang Hao , Yao Ning 
Published: April 2022

Abstract
Free fatty acid is one kind of impurities in edible oil, which is often removed by deacidification in oil refining. However, traditional deacidification methods using alkali and immobilized lipase have the issues of serious losses of neutral oil and bioactive compounds. In this work, several low-cost liquid lipases were screened for the selective deacidification of corn oil. The thermodynamic and kinetic parameters were investigated. Results showed that liquid lipase CALB showed good selective deacidification efficiency. The conditions were optimized by response surface methodology as follows: 3% enzyme dosage, 50oC and 50 min. Under these conditions, the acid value, retention rate of neutral oil, and contents of sterol and VE of corn oil were 0.31 ± 0.06 mg/g, 94.0 ± 0.5%, 1,012.87 ± 11.23 mg/100g, and 1,320.0 ± 3.8 mg/kg, respectively. These results showed that liquid lipase CALB was beneficial to selective deacidification, high retentions of neutral oil and bioactive components in corn oil.
Identification of hub genes and candidate herbal treatment in obesity through integrated bioinformatic analysis and reverse network pharmacology
Authors: Tai Yuxing , Tian Hongying , Yang Xiaoqian , Feng Shixing , Chen Shaotao , Zhong Chongwen , Gao Tianjiao , Gang Xiaochao , Liu Mingjun 
Published: April 2022

Abstract
Obesity is a worldwide epidemic disease that increases the risk of various metabolic disorders. However, in the absence of ideal drugs for obesity, Chinese herbs and other natural materials have been explored for their potential obesity treatment and low-side effects. The focus of this research was to use bioinformatics and reverse network pharmacology to discover possible therapy and treatment targets for obesity. We identified differentially expressed genes (DEGs) of adipose tissue after weight-loss by analyzing the five expression profiles of the GEO database (GSE103766, GSE35411, GSE112307, GSE43471, and GSE35710). Protein–Protein Interaction (PPI) network was performed with the STRING, and the 27 hub genes were identified with the MCODE. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed several biological features and potential mechanisms of these hub genes. Subsequently, the TCMSP platform was used to identify potential therapeutic herbs targeting hub genes. The top 10 key potential Chinese herbs were found and annotated with Chinese pharmaceutical properties (CMPs). Finally, the Herbs-Ingredient-Target Network and Herb-Taste-Meridian Tropism Network were constructed using Cytoscape to elucidate their complex relationship. Our outputs could provide new insights into strategies for treating obesity and screening targeted drugs.
Predictive Analytical Model for Ectopic pregnancy diagnosis: Statistics vs. Machine learning methods.
Authors: Rueangket Ploywarong , Rittiluechai Kristsanamon , Prayote Assistant Professor Akara 
Published: April 2022

Abstract
Background:
Ectopic pregnancy is well-known for its serious outcome. Early detection could make the difference between life and death in pregnancy. Although, prompt diagnosis was challenged and numbers of predictive models had been developed, there’s still lack of gold standard tool. Our research introduces predictive analytical models using both conventional statistics and machine learning methods based on all three domains of features (clinical factors, serum human chorionic gonadotropin and ultrasound findings).
Methods:
Retrospective cohort study on 377 pregnancy of unknown location women, training and validating for model for prediction of ectopic pregnancy outcome, using set of 22 features. Analysis performed by three difference machine learning models neural networks (NNs), decision tree (DT) and support vector machines (SVMs) using cross validation technique. In addition, with traditional statistical model, logistic regression (LR). In which we compare the model performance with ROC-AUC and accuracy, PPV and NPV. Finally, new 30 PULs were tested for external validation.
Result
Comparing of model performance (validation) to predict EP, LR Ranked first, followed by NNs, DT and SVMs with mean ROC-AUC ± SD of 0.904, 0.895, 0.871 and 0.862 respectively. In terms of clinical parameters, we found sensitivity ± SD performed in the same sequence as AUC (LR; 87.97% ± 7.86%, NNs; 85.97% ± 9.34%, SVM; 87.47% ± 8.23% and DT; 85.47% ± 10.37%, orderly. While specificity (± SD) was ranked by DT, then followed by SVMs, LG and NNs, which were 84.08 ± 8.56%, 83.53 ± 9.18%, 82.94 ± 9.84% and 81.76 ± 9.84%, respectively. In testing data, NNs and SVM performed equally best, then DTs and LR at ROC-AUC of 0.784, 0.778 and 0.739, respectively.
Conclusion
The result demonstrates that both statistics and ML model could be utilized to achieve satisfied predictions for EP. Surprisingly, the highest ranked model was LR in validating test, but in new testing data machine learning, NNs and SVMs could overcome statistics. This could shade a new light for further research of unsolved medical problem with more complexity and bigger database.
A Novel Poly (o-anisidine) Encapsulated K2ZrO3 Nano-core based Gelatin Nano Composites: Investigations of Optical, Thermal, Microcrystalline and Morphological Characteristics
Authors: Madhukar BS , Al-Gunaid Murad Q. A. , Somesh T.E , Kavya R , H Anupama B , S Shashikala B , B Siddaramaiah 
Published: April 2022

Abstract
Herein we present the synthesis of K2ZrO3 by solution combustion method and insitu coating technique is used for the coating of poly (ortho- anisidine) (POA) on prepared nanoparticles. Furthermore, a series of Gelatin/poly-o-anisidine coated K2ZrO3 polymer nanocomposite were fabricated by varying the POA coated K2ZrO3 viz 0, 1, 2, and 4 wt % using the solvent intercalation method. High-resolution transition electron microscopy (HRTEM) was used to study the size and morphology of the synthesized nanoparticles and polymer coated nanoparticles. From the results it is cleared that the average size of the prepared nanoparticles and polymer coated nanoparticles are around 18-20 and 95-100 nm respectively, and the polymer coated nanoparticles are spherical in shape, and form a core shell. The phase purity and microcrystalline behavior of the prepared nano particles, POA coated nanoparticles and gelatin nanocomposites were analyzed by using X-ray diffraction (XRD). From the results it was noticed the changes in the peak intensities of nanocomposites films, and a little shift in the peak position towards the lower 2θ values. Scanning electron microscope [SEM] and energy dispersive spectroscopy[EDX] were employed for the analysis of the surface morphology and the elemental composition of the prepared nanoparticles and nanocomposites. Fourier transform infrared spectroscopy was used to assess the physical interactions between the components in nanocomposites. The thermal stability and effect of polymer coated nanoparticles inclusions on glass transitions temperatures were studied by using Thermo-gravimetric analysis (TGA) and differential scanning calorimetry (DSC) respectively. UV–Visible spectroscopy technique is used to study the optical properties of the Gelatin/POA@K2ZrO3 nanocomposites and the optical constants of nanocomposites were determined. From the results it is clear that, with increase in POA coated K2ZrO3 nanoparticles concentration from 0 to 4 wt % in a gelatin matrix, the band gap energy (Eg) value drops from 4.13 to 2.16 eV, and the refractive index rises from 1.529 to 3.25.
Evaluating the incremental value of systemic inflammatory response markers in estimating the malignant probability of ovarian masses: development of a diagnostic nomogram
Authors: Du Jun-hong , Xing Yi-juan , Hu Dan , He Rui-fen , Yue Ling , Cheng Yue-mei , Liu Chang , Liang Xiao-lei , Yang Yong-xiu 
Published: April 2022

Abstract
Purpose
To investigate the incremental value of systemic inflammatory response markers in the differential diagnosis of ovarian masses and develop a nomogram to predict ovarian malignancy in patients with ovarian masses.
Methods
1087 eligible women with ovarian masses were randomly allocated to a training cohort (N = 761) and validation cohort (N = 326). The LASSO logistic regression was implemented to select the most significant ovarian cancer-related predictors. Multivariable logistic regressions were then performed to build different prediction models. The model with best performance was presented as a nomogram and compared with reference ovarian cancer prediction tools in terms of discrimination ability.
Results
Seven variables including age, CA125, HE4, fibrinogen (FIB), monocyte-to-lymphocyte ratio (MLR), the presence of solid areas and strong blood flow signal were identified as significant predictors. The final model combining all seven variables yield an AUC of 0.973 in the training cohort and 0.964 in the validation cohort. The NRI and IDI revealed that the addition of FIB and MLR significantly improved the model’s discrimination ability. The nomogram based on the final model outperformed some well-known ovarian cancer prediction tools (RMI, LR2, ROMA, CPH-I and R-OPS) and exhibited an excellent performance in detecting early-stage ovarian cancer with an AUC value of 0.946 (95% CI: 0.925–0.967).
Conclusion
The systemic inflammatory response markers and ultrasound-based nomogram provided a convenient and accurate tool for estimating the malignant probability in women with ovarian masses. The addition of FIB and MLR significantly improved the predictive ability of the nomogram.
Sparse ECG denoising with generalized entropy penalty
Authors: Guo Shuli , Wu Lei , Han Lina , Song Xiaowei , Wang Hui , Zhao Yuanyuan 
Published: April 2022

Abstract
Background
Electrocardiogram (ECG) monitoring can quickly obtain the human body's ECG signal, and it is convenient for researchers to analyze the variability of heart rate. Some noise is often introduced in the process of signal acquisition and transmission. The existence of these noises interferes with the authenticity of the signal, and it is not conducive to the signal analysis and processing.
Method
In this paper, for the purpose of suppressing these noises, a sparse ECG denoising framework combining low-pass filtering and sparsity recovery is investigated. We propose a sparse ECG denoising method based on generalized entropy penalty. We use a novel denoising penalty function for sparse recovery, and compared the proposed generalized entropy penalty (GEP) with \({\ell _{\text{1}}}\)-norm penalty.
Result
The proposed method is evaluated on ECG signals from the MIT-BIH Arrhythmia database. The results show that the proposed method overcomes the problem of underestimation of the high-frequency components amplitude of the ECG signal. At the same time, the GEP punishes the large values less severely than \({\ell _{\text{1}}}\)-norm, and can also be used to overcome the shortcomings of "\({\ell _{\text{1}}}\)-norm" underestimating the QRS wave in ECG signal.
Conclusion
The proposed GEP-based penalty can be used for ECG denoising. The result of signal denoising is to remove the noise without destroying the information of the signal itself. The method has a higher restoration degree of the original signal and has relatively excellent denoising effect.
Work Environment Problems of Hospital Nurses and its Relation to their Professional Commitment
Authors: Sabra Hanaa E. , Elzaher Omima M. Abd , El-elle mona M Abo , Mahmoud Soad S , Ahmed Asmaa 
Published: April 2022

Abstract
Background
Nursing is an essential component in the functionality of the health system. Nurse's shortage is recognized as worldwide issue. So, understanding the problems that faces them and overcome these problems is crucial in retaining them. This study aimed to identify the most important work environment problems (WEPs) of hospital nurses and its relation to their professional commitment.
Methods
This a descriptive explorative study included a convenience sample of 245 nurses from ICUs, medical, special medical, surgical, and obstetrics and gynecological units in Qena General Hospital. The WEPs questionnaire, professional commitment scale and socio demographic characteristics questionnaire were used for data collection.
Results
Showed that the highest mean score in WEPs was related to lack of material and moral incentives (28.89 ± 7.41) while lowest was related to Poor physical environment and support services (11.36 ± 3.22).There were a statistically significance negative correlations between work environment problems and professional commitment of hospital nurses.
Conclusion
WEPs of hospital nurses have a strong impact on their professional commitment.
Recommendations:
Improving the image of nursing in the media for the purpose of awareness and to clarify the role of nursing and its importance in the medical field. Nursing managers must provide support for nurses and spread the organizational culture that encourages cooperation, participation and teamwork, develop strategies for clarify the tasks and provision of appropriate standards and develop ethical rules for the profession that clarify the limits and standards for the nurses.
Riboflavin and FMN Oversynthesis on Whey by the Engineered Strains of the Flavinogenic yeast Candida famata
Authors: Sibirny Andriy , Ruchala Justyna , Tsyrulnyk Andriy , Andreieva Yuliia , Sobchuk Svitlana , Najdecka Alicja , Liu Wen , Kang Yingqian , Dmytruk Olena , Dmytruk Kostyantyn , Fedorovych Daria 
Published: April 2022

Abstract
BackgroundRiboflavin is a precursor of FMN and FAD which act as coenzymes of numerous enzymes. Riboflavin is an important biotechnological commodity with annual market sales exceeding nine billion US dollars. It is used primarily as a component of feed premixes, a food colorant, a component of multivitamin mixtures and medicines. FMN is a valuable biotechnological product used in numerous applications; its most important advantage over riboflavin is its 200 times greater solubility in water. FMN is mostly produced by chemical phosphorylation of riboflavin; however, the chemically synthesized product contains in the range 20-30% impurities. Currently, industrial riboflavin production uses the bacterium, Bacillus subtilis, and the filamentous fungus, Ashbya gossypii, and utilizes glucose and/or oils as carbon substrates. ResultsWe studied riboflavin and FMN biosynthesis in the flavinogenic yeast Candida famata that are genetically stable riboflavin and FMN overproducers. Here it was found that the wild type C. famata is characterized by robust growth on lactose and cheese whey and the engineered strains also overproduce riboflavin and/or FMN on whey. The riboflavin synthesis on whey was close to that obtained on glucose and lactose. To further enhance riboflavin production on whey, the gene of the transcription activator SEF1 was expressed under control of the lactose-induced promoter of the native β-galactosidase gene LAC4. These transformants produced elevated amounts of riboflavin and FMN on lactose and especially on whey. Overexpression of the D. hansenii FMN1 gene (coding for riboflavin kinase) led to the accumulation of FMN by C. famata transformants cultivated on whey. Activation of riboflavin synthesis was also obtained after overexpression of the GND1 gene that is involved in the synthesis of the riboflavin precursor ribulose-5-phosphate. Cultivation of these strains in shake flasks or in bioreactors on whey with ammonium sulfate led to the accumulation of near 1.5 - 1.8 g of riboflavin/L. The use of concentrated whey inhibited growth of wild-type and engineered strains of C. famata, so the mutants tolerant to concentrated whey were isolated. ConclusionsOur data indicate that the waste whey from milk industry, can be a promising substrate for riboflavin production by C. famata. Opportunities for using the engineered strains of C. famata to produce high-value commodities (riboflavin, FMN) from whey are discussed.
Nitrogen Doped Activated Carbon Derived From Chitosan/ Hexamethylenetetramine: Structural and CO2 Adsorption Properties
Authors: D Selvakumar , K Malini , N.S Kumar 
Published: April 2022

Abstract
Chitosan and chitosan/ hexamethylenetetramine (HMT) macrospheres were prepared respectively by dropping chitosan and chitosan/HMT (in wt/wt ratios of 1:1 and 1:3) solutions in aq. NaOH solution. Here, HMT served as an additional nitrogen precursor for in-situ N-doping with chitosan derived activated carbon (AC). The as-formed macrospheres were impregnated using ZnCl2, freeze-dried, and carbonized at 500°C under inert atmosphere to yield ACs of average size 2.6 mm. All the samples were characterized using SEM, EDS, CHNS Analyzer, TGA, FT-IR, Raman, XRD and BET surface area analyzer. All the samples showed mesoporous characteristics. The surface area of the AC without HMT, with 1:1 HMT, and 1:3 HMT were 391.502, 259.017, and 111.717 m2/g respectively. Similarly, the pore volumes of AC without HMT, with 1:1 HMT and 1:3 HMT were 0.138, 0.095 and 0.075 cc/g respectively. The chitosan/HMT derived AC possessed higher N-content and better thermal stability, however exhibited lower surface properties with increasing HMT content. Deterioration in adsorption capacity of chitosan/HMT derived AC may be attributed to the physical cross-linking of chitosan polymer chains induced by increase in pH with addition of HMT and also the intermolecular H-bonding interaction between HMT and chitosan, which in turn reduces the surface area of as-formed N-doped ACs progressively.