bluuebunny/crossref_metadata_2025_split huggingface dataset:
WITHDRAWN: Identification of Novel Biomarkers and Targets for Natural Products in Inhibiting Prostate Cancer
Authors: Li Wenji , Xu Wei , Sun Kai , Wang Fujun , Wong Tin Wui 
Published: October 2021

Abstract
Background: Prostate cancer (PCa) is a common urinary system malignancy. The lack of specific and sensitive biomarkers for the diagnosis and prognosis of PCa makes it important to seek alternatives. Meanwhile, targeted PCa inhibitors are limited. Natural products that potentially target PCa may offer a useful approach.Methods: Expression profile datasets about PCa from GEO were analyzed. Core differential genes were identified by String and Cytoscape. GEPIA and HPA were utilized to further validate the key genes. The targets of natural products were obtained from the Drugbank, Therapeutic Target Database, BindingDB, PubChem, and chEMBL databases, and PCa therapeutic targets were generated from the GeneCards, OMIM, and PharmGkb databases. Cytoscape was also used to screen the core modules and disease-drug targets. Construction of molecular docking models of drug-core targets was performed by Autodock to confirm the accuracy of the targets.Results: Four identified biomarkers, CENPF, TPX2, TK1 and CCNB1 were verified by HPA. Five novel PCa biomarkers, RRM2, UBE2C, TOP2A, BIRC5 and ZWINT were also identified. All the nine markers indicated poor prognosis for PCa patients were verified by GEPIA. PCa carcinogenesis is found to be mainly associated with hepatic fibrosis pathway, ILK signaling, NRF2-mediated oxidative stress response and many others. Four key PCa targets for curcumin (EP300, RELA, EGFR, NFKB1), seven for taxol (PTEN, EGFR, ERBB2, TP53, KRAS, AR, AKT1) and two for ursolic acid (GSK3B, RELA) were identified by Cytoscape combined KEGG and verified by Autodock.Conclusions: The novel identified biomarkers in our study would be valuable for the diagnosis and prognosis of PCa. Key targets of curcumin, paclitaxel, and ursolic acid in PCa could lay a solid foundation for precise treatment and molecularly targeted therapy for PCa.
Value of Biomarkers In Liver Cancer EMT Model Under Different Interventions：A Meta-Analysis
Authors: Yan Jing , Zou Shuli , Xie Bei , Tian Ye , Peng Zhiheng , Liu Zhuan , Ma Bin , Li Linjing 
Published: October 2021

Abstract
Background: There are various interventions to establish the Liver cancer epithelial-mesenchymal transition (EMT) models. However, the ideal biomarkers for unique model are not well established. Further studies are necessary to evaluation of effective EMT biomarkers under different interventions in vitro studies. A meta-analysis was performed to evaluate the performance of different biomarkers in HepG2 cells during EMT under multiple interventions. Methods: PubMed, Web of Science, Embase, the China National Knowledge Infrastructure (CNKI), the China Biology Medicine disc (CBM), Wan Fang Data, and VIP databases were systematically searched from inception to June 14, 2020 by two independent reviewers. Results: A total of 58 studies were included in the meta-analysis. Our study showed that E-cadherin responds well to the intervention of medication, genetic intervention, gene knockout/knockdown, hypoxia, and other tumor microenvironments, as well as non-coding RNA (ncRNA) overexpression and silencing. N-cadherin can effectively evaluate the intervention effect of medication, genetic intervention, hypoxia and other tumor microenvironments, as well as ncRNA overexpression. Vimentin reflects the effects of medication, pro-EMT genetic intervention and gene knockout/knockdown, anti-EMT ncRNA overexpression and anti-EMT ncRNA silencing and hypoxia. Snail only responds to the intervention of anti-EMT genetic intervention and gene knockout/knockdown, tumor microenvironments other than hypoxia, anti-EMT ncRNA overexpression and ncRNA silencing. Conclusions: Our results shows that some medicine, some gene, microenvironment and some ncRNA can effectively induce/inhibit EMT process. E-cadherin, N-cadherin, Vimentin and Snail are effective biomarkers during this process. They respond differently to different intervention. Therefore, different biomarkers should be chosen under different intervention based on their performance.
Use of Blood Culture Bottles to Incubate Irrigation Water from the Surgical Site May Improve Detection of Causative Organisms in Pyogenic Vertebral Osteomyelitis
Authors: Okuwaki Shun , Tatsumura Masaki , Gamada Hisanori , Eto Fumihiko , Nagashima Katsuya , Funayama Toru , Yamazaki Masashi 
Published: October 2021

Abstract
【Background】 Identification of pathogenic microorganisms are essential for pyogenic vertebral osteomyelitis (PVO). This study aimed to demonstrate the effectiveness of the blood culture bottle (BCB) system in identifying PVO causative organisms. 【Materials & Methods】 We analyzed retrospectively collected data from patients who underwent full-endoscopic spine surgery for PVO between January 2016 and March 2019. Irrigation water generated in the surgical field was incubated in the BCB system, and compared with blood culture before surgery and tissue culture taken by the conventional method. The microbial identification rate and the time from sample collection to microbial identification of the BCB system were compared with conventional blood culture and tissue cultures using the Wilcoxon signed-rank test. 【Results】 We included 17 patients (12 men, five women; mean age, 72.8 ± 11.9 years). Bacteria were cultured from 3 (17.6%), 13 (76.5%), and 12 (70.6%) patients by blood culture, tissue culture, and the BCB system, respectively. Tissue culture and the BCB system had significantly higher detection rates than blood culture (P = .002, P =.003), and there was no significant difference between tissue culture and BCB system (P = .655). In 15 cases (88.2%), the causative organism was identified by at least one method. In two cases, the causative organism (Escherichia coli) was only identified by the BCB system. The BCB system required amount of time for microbial identification (3.9 ± 3.0 days), compared with the time required for blood culture (5.0 ± 1.4 days, P =.180) and tissue culture (11.9 ± 15.1 days, P =.012). 【Conclusions】 Results suggest the possibility of improving the detection rate and time to detection of causative organisms by the BCB system as an adjunct to the conventional method.
Effect of Low-Temperature Stress On Na+/K+-ATPase and Transcriptome Changes in Oreochromis Niloticus Gill Tissues
Authors: Li Zhe , Wen Luting , Wu Xia , Qin Junqi , Chen Zhong , Pan Xianhui , Zhou Kangqi , Huang Yin , Deng Qian , Lin Yong , Du Xuesong 
Published: October 2021

Abstract
Low temperatures limit the development of Oreochromis niloticus (tilapia), and an increase in low-temperature tolerance would increase yields. We studied the responses of tilapia to low temperatures. The fish were labeled CK, AA, BB, and CC based on treatment (25°C, 12°C/1 h, 12°C/24 h, and 12°C/48 h, respectively) with CK being the control group. We examined the transcriptome responses and the Na+/K+-ATPase activity of gill tissue in each group. The Na+/K+-ATPase activity varied with the treatment time. Transcriptome sequencing of 12 individuals yielded 585.51 million clean reads, and at least 83.26% of the genes were mapped to the reference genome. Comparative analysis revealed 12,448 genes with significantly differential expression, including 792, 1,827, 1,924 upregulated genes and 992, 3,056, 3,857 genes downregulated for AA, BB, and CC, respectively. Differentially expressed genes (DEGs) were validated using RT-PCR for five genes. Functional annotation analysis of the DEGs identified functions associated with response to low-temperature stress. When tilapia was subjected to low-temperature stress, expression changes occurred in genes associated with cytokine-cytokine receptor interaction, metabolic pathways, cell adhesion molecules, material transport, and immunity. The founding will help understand the effects of low temperature on fish and provide a theoretical basis for the tilapia breeding industry.
Utilization of Biotechnology, Neurotransmitter and Cytogenetic Indices in Selecting Pigeon Breeds
Authors: El-Sayed Mohammed , Ibrahim N. S. , Assi Heba A.E.M. , Gwwad Mona E. Abdel , Fouad W. S. , Ibrahim M. A. , Atia Noura , Abdel-Moneim Abdel-Moneim E. 
Published: October 2021

Abstract
The DNA polymorphism LDH-A and DRD4 gene, some neurotransmitter and cytogenetic indices of three sexed pigeon breeds; non-racing pigeons (wild rock), racing long and short distances pigeons (e.g: Gan aarden) and (e.g: Gansen) have been performed. The long-distance pigeon demonstrated the highest levels of neurotransmitters in brain tissues. Long distance male pigeons have a unique LDH-A polymorphism, so A changed to G, which means that changes in gene expression resulted in differences in amino acid structure K(lys) was converted to E(glu) in the LDH-A gene only in long distance male pigeons compared to other breeds. In addition to this, the DRD4 polymorphism of long distance male pigeons in which A changed to C and A changed to T indicates the presence of a unique diversity in this breed. This means that changes in gene expression resulted in overall amino acid structure differences only in long distance male pigeons when compared to other breeds, where R(arg) and L(leu) were converted to S(ser) and F(phe). Neurotransmitters are synthesised in the body from these amino acids. It concluded that measurements would be useful indices for the differentiation, genetic characterization, provide a foundation for conservation programs of the breeding and selecting racing pigeon breeders.
Ti3C2Tx MXene Enabled All-Optical Nonlinear Activation Function for On-Chip Photonic Deep Neural Networks
Authors: Hazan Adir , Ratzker Barak , Zhang Danzhen , Katiyi Aviad , Frage Nachum , Sokol Maxim , Gogotsi Yury , Karabchevsky Alina 
Published: October 2021

Abstract
Neural networks are one of the first major milestones in developing artificial intelligence systems. The utilisation of integrated photonics in neural networks offers a promising alternative approach to microelectronic and hybrid optical-electronic implementations due to improvements in computational speed and low energy consumption in machine-learning tasks. However, at present, most of the neural network hardware systems are still electronic-based due to a lack of optical realisation of the nonlinear activation function. Here, we experimentally demonstrate two novel approaches for implementing an all-optical neural nonlinear activation function based on utilising unique light-matter interactions in 2D Ti3C2Tx (MXene) in the infrared (IR) range in two configurations: 1) a saturable absorber made of MXene thin film, and 2) a silicon waveguide with MXene flakes overlayer. These configurations may serve as nonlinear units in photonic neural networks, while their nonlinear transfer function can be flexibly designed to optimise the performance of different neuromorphic tasks, depending on the operating wavelength. The proposed configurations are reconfigurable and can therefore be adjusted for various applications without the need to modify the physical structure. We confirm the capability and feasibility of the obtained results in machine-learning applications via an Modified National Institute of Standards and Technology (MNIST) handwritten digit classifications task, with near 99% accuracy. Our developed concept for an all-optical neuron is expected to constitute a major step towards the realization of all-optically implemented deep neural networks.
Determinants of COVID-19 Vaccine Acceptance in Healthcare Workers in Iran: National Survey
Authors: Kamali Koorosh , Hoseinzade Zarrintag , Hajimiri Khadijeh , Hoveidamanesh Soodabeh , Zahraei Seyed Mohsen , Gouya Mohammad Mehdi , Bavandpouri Sousan Mahmoudi , mohamadi Tahereh , Mohamadi Soraya , Bigdeli Zohre , Maleki Azam , Shirzad Mahboubeh , Heidari Zahra , Farsadegi Mahya , Shogli Alireza 
Published: October 2021

Abstract
Background and Aim: Acceptance of a vaccine is the most effective way to tackle the COVID-19 pandemic. Health care providers are the most determining group in danger of COVID-19 more than others. They are among the first group to uptake vaccination. This study aimed to assess the level of COVID‐19 vaccine acceptance and their determinants among Health Care Workers in Iran.Methods: A cross‐sectional survey was carried out among 3600 Healthcare Workers (HCWs) in Iran. Data were collected through a self-administered questionnaire by a trained team from February to March 2021. A multi-stage cluster sampling method was used to select respondents. A Multivariate Logistic regression analysis was used to determine the key determinants of COVID-19 vaccine acceptance among participants. P-value <0.05 was considered statistically significant.Results: Out of the 3536 respondents, 2191 (62.1 %) intended to uptake the COVID-19 vaccine, only 660 (18.7 %) reported hesitancy towards the COVID-19 vaccine. Only about 10% of participants said they did not trust any vaccine (domestic and foreign vaccines). Willing to accept a COVID-19 vaccine is relatively high among males, doctors, and who have a history of hospitalization due to COVID-19 infection. In multivariate models, respondents who were 40-50 years (aOR: 1.56; 95% CI: 1.47–1.66), had a history of COVID-19 infection (aOR: 0.85; 95% CI: 0.83–0.88), and hospitalized due to COVID-19 infection (aOR: 2.18; 95% CI: 1.97–2.39) were significantly associated with vaccine acceptance (p < 0.05). Conclusion: Our study showed moderate acceptance of covid-19 vaccination in the HCWs in the Islamic Republic of Iran with less acceptance in nurses. This needs more attention and implementation of educational programs for awareness and reassurance of healthcare workers.
Stable Variable Selection for High-dimensional Genomic Data with Strong Correlations
Authors: Sarkar Reetika , Manage Sithija , Gao Xiaoli 
Published: October 2021

Abstract
Background: High-dimensional genomic data studies are often found to exhibit strong correlations, which results in instability and inconsistency in the estimates obtained using commonly used regularization approaches including both the Lasso and MCP, and related methods. Result: In this paper, we perform a comparative study of regularization approaches for variable selection under different correlation structures, and propose a two-stage procedure named rPGBS to address the issue of stable variable selection in various strong correlation settings. This approach involves repeatedly running of a two-stage hierarchical approach consisting of a random pseudo-group clustering and bi-level variable selection. Conclusion: Both the simulation studies and high-dimensional genomic data analysis have demonstrated the advantage of the proposed rPGBS method over most commonly used regularization methods. In particular, the rPGBS results in more stable selection of variables across a variety of correlation settings, as compared to recent work addressing variable selection with strong correlations. Moreover, the rPGBS is computationally efficient across various settings.
Association of Triglyceride-Glucose index with risk of microalbuminuria in Chinese children with type 1 diabetes
Authors: Gao Long , Wang Xinhui , Shu Jianbo , Zhang Mingying , Zhi Xiufang , Guan Jun , Gu Chunyu , Pu Linjie , Cai Chunquan , Yang Wei , Lv Ling 
Published: October 2021

Abstract
Objective

The triglyceride-glucose index (TyG index) has been regarded as a useful alternative marker for the early identification of insulin resistance (IR). Accordingly, the objective of the present study is to explore the association of the TyG index with microalbuminuria (MA) in T1DM children.
Methods

The study retrospectively enrolled 129 patients ((boys/girls = 51/78) with T1DM in the Endocrine inpatient wards of Tianjin Children’s Hospital from June 2017 to May 2019. 43 patients with MA were randomly matched 1:2 with 86 patients without MA based on the Propensity Score Matching. TyG index was calculated as follows: ln[fasting triglycerides (mg/dL)×fasting plasma glucose (mg/dL)/2].
Results

TyG index and related lipid parameters were significantly higher in patients with MA compared with those without (all p < 0.05). Multivariable logistic regression analysis revealed that the TyG index in patients with MA was 2.166 times compared with those without (OR = 2.166; 95% CI, 1.559–3.009; p < 0.001). FPG (OR = 1.068; 95% CI, 1.026–1.112; p = 0.001), HBA1c (OR = 1.193; 95%CI, 1.066–1.334; p = 0.002), and the occurrence of DKA (OR = 9.863; 95% CI, 2.764–35.192; p < 0.001) were still associated with a higher MA risk. ROC curves analysis shown that the area under the curve (AUC) of the TyG index for predicting MA was the largest (0.78) compared with fasting plasma glucose (FPG) and HAB1c. The cumulative incidence of MA in the higher TyG index group was significantly higher than that in the lower TyG index group in 15 years (p < 0.001).
Conclusions

The TyG index was significantly correlated with MA levels. An elevated TyG index had a significantly greater risk of MA events independent of DKA, even after adjusting for confounding risk factors. The TyG index was more specific than FPG and HBA1c in predicting MA. Compared to patients with a lower TyG index, those with a higher TyG index had an apparently higher cumulative incidence of MA.
Soil Respiration and N-Mineralization Processes in the Patagonian Steppe Are More Responsive to Nutrient Than to Water Addition
Authors: Carbonell-Silletta Luisina , Cavallaro Agustin , Pereyra Daniel A. , Askenazi Javier O. , Goldstein Guillermo , Scholz Fabian G. , Bucci Sandra J. 
Published: October 2021

Abstract
Aims: Soil respiration and N-mineralization are key processes in C and N cycling of terrestrial ecosystems. Both processes are limited by soil temperature, moisture and nutrient content in arid and cold ecosystems, but how nutrient addition interacts with water addition requires further investigation. This study addresses the effects of water and N+P additions on soil respiration and mineralization rates in the Patagonian steppe.Methods: We measured soil respiration and N-mineralization throughout seasons in control, fertilized, irrigated and irrigated-fertilized plots. We also analyzed root density and soil physico-chemical properties.Results: The soil CO2 effluxes in the Patagonian steppe were controlled by soil temperature, soil water content and root density. Increases in water addition had no effects on soil respiration, except when combined with N+P addition. However, soil nutrient enrichment without water addition enhanced soil respiration during the plant growing season. We found a linear positive relationship between root density and soil respiration, without interaction with treatments. N+P addition had negative impacts on N-mineralization, resulting in a strong N-immobilization. However, soil ammonium and nitrate content increased with N+P addition all over the seasons.Conclusion: Moderate increases in the precipitation through small pulses lead to no long-term response of soil processes in arid and cold Patagonian ecosystems. However, soil CO2 effluxes are likely to increase with nutrient additions, such as anthropogenic N deposition, and microbial biomass could retain more nutrients in the soil. Therefore, high levels of N enrichment in arid ecosystems may strengthen the positive feedback between C cycle and climate change.
Tumor-microbiome links subtype, cellular programs, and immunity in pancreatic cancer
Authors: Blaser Martin , Ghaddar Bassel , Biswas Antara , Harris Chris , Omary M. Bishr , Carpizo Darren , De Subhajyoti 
Published: October 2021

Abstract
Microorganisms are detected in multiple cancer types, including in putatively sterile organs, but it is unclear whether this relates to specific tissue contexts and influences oncogenesis or anti-tumor responses in humans. We developed SAHMI, a framework to analyze host-microbiome interactions using single-cell sequencing data. Interrogating pancreatic ductal adenocarcinomas (PDA), we identified an altered and diverse tumor microbiome that includes known and novel tumor-associated bacteria and fungi. Specific somatic cell-types were enriched with particular microbes whose abundances correlated with select host gene expression and cancer hallmark activities. Nearly all tumor-infiltrating lymphocytes had infection-reactive transcriptional profiles. Pseudotime analysis provided evidence for tumor-microbial co-evolution and identified three tumor subtypes with distinct microbial, molecular, and clinical characteristics. Finally, using multiple independent datasets, a signature of increased intra-tumoral microbial diversity predicted clinical prognosis. Collectively, tumor-microbiome cross-talk appears to modulate tumorigenesis with implications for clinical management.
Self-management by Hospitalized Older Adults Based on Self-regulation: a Structural Equation Model
Authors: Kim Sunki , Choi Mona , Lee JuHee , Kim Heejung , Song Kijun , Park Hye-Ja 
Published: October 2021

Abstract
Background: Based on the common-sense model of self-regulation, this study aimed to examine the process of self-management through the proposed framework of “Self-system (type D personality)”→ “Cognitive illness perception,” “Emotional illness perception (Depression)”→ “Coping strategies (Approach coping)”→ “Illness Appraisal (Self-management),” using a structural equation model.Methods: The study was conducted at two care hospitals with 300 or more beds located in Jeolla Province, South Korea. The participants were 287 hospitalized older adults. The data collection period was February 17–March 10, 2021. The data were analyzed using SPSS WIN 23.0 and AMOS 23.0. To investigate the overall relationships among the factors influencing self-management among participants, a hypothetical model was created based on the common-sense model of self-regulation. The fit of the model and significance of its paths were analyzed. Results: The hypothetical model showed a good fit based on the following results: CMIN/DF(Q)=2.852, CFI=.955, TLI=.947, and RMSEA=.08. Type D personality had a significant direct effect on cognitive illness perception (β=-.491, p<.001) and depression (β=.844, p<.001). Cognitive illness perception (β=.650, p<.001) and depression (β=-.433, p<.001) had a direct effect on approach coping. Approach coping (β=.326, p<.001) had a direct effect on self-management. Notably, approach coping mediated illness perception and self-management. The explanatory power of the variables for self-management was 78.8%.Conclusion: These findings demonstrated the following mechanism: “type D personality” → “cognitive illness perception” and “depression” → “approach coping” → “self-management,” and highlighted the potential threat of type D personalities and depression on self-management. Cognitive illness perception and approach coping both contribute toward older adults’ self-management.