bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of ISG15 and ZFP36 as Novel Hypoxia- and Immune-Related Gene Signatures Contributing to A New Perspective for The Treatment of Prostate Cancer by Bioinformatics and Experimental Verification
Authors: Lyu Fang , Li Yunxue , Yan Zhecheng , He Qingliu , Cheng Lulin , Chen Liang , Zhang Pu , Liu Bing , Liu Chunyu , Song Yarong , Xing Yifei 
Published: February 2022

Abstract
Background：Prostatic cancer (PCa)is the most common malignant tumour in men worldwide. Emerging evidence indicates significance of hypoxia and immunity in PCa invasion and metastasis. This study aimed to develop a hypoxia- and immune-related gene risk signature and explore the molecular mechanisms to formulate a better prognostic tool for PCa patients.Methods：The hypoxia and immune scores of all PCa patients in The Cancer Genome Atlas (TCGA) dataset were calculated via the maximally selected rank statistics method and the ESTIMATE algorithm. From common genes identified overlapping hypoxia- and immune-related differentially expressed genes (DE-HRGs and DE-IRGs), a hypoxia- and immune-related gene risk signature was developed utilizing univariate and multivariate Cox regression analyses, and validated in the Memorial Sloan Kettering Cancer Centre (MSKCC) database. The immune cell infiltration level of PCa samples were evaluated with ssGSEA algorithm. Differential expression of prognostic genes was evidenced by immunohistochemistry in paired PCa samples. Expression levels of these genes and their variations under regular and hypoxic conditions were examined in cell lines. The functional effects of the prognostic gene on PCa cells were examined by wound healing and transwell assays.Results: A hypoxia- and immune-related gene risk signature constructed by ISG15 and ZFP36 displays significant predictive potency, with higher risk score representing worse survival. A nomogram based on independent prognostic factors including the risk score and Gleason score exhibited excellent clinical value in the survival prediction of PCa. Infiltration levels of eosinophils, neutrophils, Tcm, Tem, TFH, Th1 cells, and Th17 cells were significantly lower in the high-risk group. Conversely, aDC, pDC, T helper cells, and Tregs were significantly higher. Additionally, the two prognostic genes were closely correlated with the tumour-infiltrating immune cell subset in PCa progression. RT-qPCR and WB presented higher and lower expression of ISG15 and ZFP36 in PCa cells, respectively. They were correspondingly increased and decreased in PCa cells under hypoxic conditions. Wound healing and transwell assays showed that over-expression of ISG15 promoted the migration and invasion of PCa cells.Conclusion: Our study identified a novel hypoxia- and immune-related gene signature, contributing a new perspective to the treatment of PCa.
How Education and Racial Segregation Intersect in Neighborhoods with Persistently Low COVID-19 Vaccination Rates in Philadelphia
Authors: Rich John , Miech Edward , Bilal Usama , Corbin Theodore 
Published: February 2022

Abstract
Background: COVID-19 infection has disproportionately affected socially disadvantaged neighborhoods. Despite this disproportionate burden of infection, these neighborhoods have also lagged in COVID-19 vaccinations. To date, we have little understanding of the ways that various types of social conditions intersect to explain the complex causes of lower COVID-19 vaccination rates in neighborhoods.Methods: We used configurational comparative methods (CCMs) to study COVID-19 vaccination rates in Philadelphia by neighborhood (proxied by zip code tabulation areas). Specifically, we identified neighborhoods where COVID-19 vaccination rates (per 10,000) were persistently low from March 2021 – May 2021. We then assessed how different combinations of social conditions (pathways) uniquely distinguished neighborhoods with persistently low vaccination rates from the other neighborhoods in the city. Social conditions included measures of economic inequities, racial segregation, education, overcrowding, service employment, public transit use, health insurance and limited English proficiency. Results: Two factors consistently distinguished neighborhoods with persistently low COVID-19 vaccination rates from the others: college education and concentrated racial privilege. Two factor values together – low college education AND low/medium concentrated racial privilege – identified persistently low COVID-19 vaccination rates in neighborhoods, with high consistency (0.92) and high coverage (0.86). Different values for education and concentrated racial privilege – medium/high college education OR high concentrated racial privilege – were each sufficient by themselves to explain neighborhoods where COVID-19 vaccination rates were not persistently low, likewise with high consistency (0.93) and high coverage (0.97).Conclusions: Pairing CCMs with geospatial mapping can help identify complex relationships between social conditions linked to low COVID-19 vaccination rates. Understanding how neighborhood conditions combine to create inequities in communities could inform the design of interventions tailored to address COVID-19 vaccination disparities.
Difference Between Perceptions Of Preceptors And Newly Graduated Nurses Regarding Delay In Professional Growth: A Thematic Analysis
Authors: Kawakami Chihiro , Imafuku Rintaro , Saiki Takuya 
Published: February 2022

Abstract
Background: Smooth reciprocal relationships enable the preceptee’s growth, and it has been suggested that without such relationships, the preceptee may not be able to grow successfully. This study explored the differences in perceptions by matching the perspectives of both the preceptee and the preceptor who did not make progress in workplace adjustment. Identifying the differences in perceptions between the two groups is important for improving nurse education and the relationship between preceptees and preceptors.Methods: A pair of nurses who had been with the company for less than three years, of which, those who had previously been transferred or had resigned due to poor workplace adjustment were designated as preceptees, and those who had directly supervised the preceptee during their first year of employment were included as preceptors in the study. A 50-minute semi-structured interview was conducted separately to examine the perceptions of the preceptee and preceptor. A thematic analysis was used to analyze the interview data.Results: This study explored the differences in perceptions regarding the clinical practice of nursing between preceptors and their preceptees, who did not make progress in workplace adjustment during nurse education; six themes were identified. After interviewing both sides, it became clear that the same event was interpreted differently depending on their positions, perspectives, and contexts. As the preceptees were nurses who had left or had been transferred, the existence of these differences in perceptions suggests that these factors may have an impact on their departure or transfer. However, we do not aim to place blame on one side or the other for the preceptee’s turnover or transfer and would like to consider effective support not only for the preceptee but also for the preceptor.Conclusions: It is necessary to examine nurse education on the premise that such differences may occur depending on the position and role of nurses in the workplace, and to look at curricular framework changes to bring in a systemic influence towards the training of young nurses.
De novo biosynthesis of aromatic compounds from carboxymethyl-cellulose by microbial co-culture strategy
Authors: Cai Miao , Liu Jiayu , Song Xiaofei , Qi Hang , Li Yuanzi , Wu Zhenzhou , Xu Haijin , Qiao Mingqiang 
Published: February 2022

Abstract
Background: Many aromatic compounds have attracted much interest as value-added chemicals and are widely used as additives in foods and cosmetics. Although there are many reports on heterogeneous synthesis of aromatic compounds in microorganisms, most of these studies used glucose as the sole carbon source. Lignocellulose is the most abundant renewable resource in the world. It is an economical and environmentally friendly alternative when using cellulose as a carbon source to produce high value-added products.Results: In the present study, carboxymethyl-cellulose (CMC) was utilized as the sole carbon source, and a metabolically engineered Saccharomyces cerevisiae strain SK10-3, which can degrade CMC, was co-cultured with other metabolically engineered S. cerevisiae strains to achieve the de novo biosynthesis of multiple aromatic compounds from CMC. After a series of optimization, 71.71 mg/L p-coumaric acid (p-CA) and 16.91 mg/L caffeic acid were obtained from 30 g/L CMC medium.Conclusion: De novo biosynthesis of multi aromatic compounds from lignocellulose, a renewable and inedible carbon source, via a co-cultivation strategy provides favorable support for the biosynthesis of more high value-added products from more economical substrates. Furthermore, the multi-strain co-culture strategy could be an alternative solution to improve the final titer of target products and apply it to industrial production.
Short-term clinical outcomes of Kyocera Modular Limb Salvage System designed cementless stems for the endoprosthetic reconstruction of lower extremities: A Japanese Musculoskeletal Oncology Group multiinstitutional Study
Authors: Tsukushi Satoshi , Nishida Yoshihiro , Hirose Takeshi , Nakata Eiji , Nakagawa Rumi , Imanishi Jungo , Nakamura Tomoki , Nagano Akihito , Tamiya Hironari , Ueda Takafumi , Group Japanese Musculoskeletal Oncology 
Published: February 2022

Abstract
Background
The high rate of aseptic loosening of cemented stems has led to their frequent use in endoprosthetic reconstruction. However, problems, such as stem breakage and stress shielding at the insertion site, remain. The Japanese Musculoskeletal Oncology Group (JMOG) has developed Kyocera Modular Limb Salvage System (KMLS) cementless stems with a unique tapered press-fit and short fixation design. This study aimed to clarify the short-term postoperative outcomes of this prosthesis and validate the stem design.
Methods
One hundred cases of KMLS cementless stems (51 male patients; median age, 49 years; mean follow-up period, 35 months), with a minimum follow-up of 2 years, for the proximal femur (PF), distal femur (DF), and proximal tibia were prospectively registered for use. Prosthesis survival, complication rates, postoperative functional, and radiographical evaluation were analyzed. Complications or failures after insertion of the KMLS endoprostheses were classified into five types and functional results were analyzed according to the MSTS scoring system at postoperative 1 year. The diaphyseal interface and anchorage were graded by the ISOLS system at postoperative 2 years.
Results
The overall prosthesis survival rates at 2 and 4 years were 88.2% and 79.6%, respectively. The prosthesis-specific survival rate excluding infection and tumor recurrence was 90.2% and 87.9%, respectively. Younger age (p = 0.045) and primary tumor (p = 0.057) were associated with poor prognosis of prosthesis-specific survival excluding infection and tumor recurrence. Complications were observed in 31 patients, 13 patients underwent revision surgery. The mean MSTS functional score at 1 year postoperatively was 68%. Early implant loosening was significantly more common in the DF (p = 0.006) and PF/DF straight stem (p = 0.038). The ISOLS radiographic evaluation at 2 years after surgery revealed good bone remodeling and anchorage in most cases (bone remodeling: 90% / excellent and good, anchorage: 97% / excellent and good).
Conclusions
Tumor endoprosthesis long-term fixation to the diaphysis of the lower extremity remains challenging. The KMLS cementless stem with a unique tapered press fit design showed good short-term results in maintaining bone stock. To prevent early loosening, a curved stem should be used in PF and DF but long-term follow-up is necessary.
End-User Research in Support of Long-Acting Systemic Antiretroviral Delivery Systems: Insights from Qualitative Research with Providers and Target Users in South Africa
Authors: Brown Morgan S. , Hanif Homaira , Little Kristen , Clark Meredith R. , Thurman Andrea , Flomen Lola , Doncel Gustavo F. 
Published: February 2022

Abstract
Background
While oral pre-exposure prophylaxis (PrEP) has been shown to reduce the risk of HIV, challenges such as adhering to a daily-dosing regimen and persistence have emerged as barriers for at-risks populations in South Africa. This qualitative research sought to investigate perceptions of and preferences for a long-acting, biodegradable implantable PrEP product designed to address these barriers.
Methods
To identify and understand motivators, barriers, and preferences for the PrEP implant, we conducted qualitative in-depth interviews (IDIs) among health care providers (HCP) and target end-users (young women, adolescent girls, and female sex workers) in urban and rural regions of Gauteng Province, South Africa. The IDIs focused on defining values, beliefs, habits, lifestyles, influencers, and information channels for potential PrEP implant end-users.
Results
We conducted 36 IDIs across health care providers and target end-user respondent segments. Respondents had generally positive reactions to the PrEP implant. Most end-users felt that some undesirable aspects of the implant (e.g., side effects, pain during insertion, potential scarring, and dissolvability) would be offset by having a highly effective, and long-lasting HIV prevention product. Although some HCPs believed the implantable PrEP would lead to increases in promiscuity and risky sexual behavior, most HCPs saw value in the PrEP implant’s long duration of protection and the likelihood of higher adherence relative to oral PrEP.
Conclusions
While further research is necessary, this qualitative study demonstrates demand for a biodegradable, long-acting implantable PrEP and suggests such a product would be accepted by end-users and HCPs in South Africa. This study indicates the need to develop more convenient, discreet, long-acting, and highly effective biomedical HIV prevention options for at-risk populations.
Cognitive decline is associated with frequency-specific resting state functional changes in normal aging
Authors: Fan Dongqiong , Liu Tao , Jiang Jiyang , Kochan Nicole A. , Wang Yilong , Brodaty Henry , Sachdev Perminder S. , Wen Wei 
Published: February 2022

Abstract
Resting state low-frequency brain activity may aid in our understanding of the mechanisms of aging-related cognitive decline. Our purpose was to explore the characteristics of the amplitude of low-frequency fluctuations (ALFF) in different frequency bands of fMRI to better understand cognitive aging. Thirty-seven cognitively normal older individuals underwent a battery of neuropsychological tests and MRI scans at baseline and four years later. ALFF from five different frequency bands (0.01 - 0.25 Hz; slow-6 to slow-2 band) were calculated and analyzed. A two-way ANOVA was used to explore the interaction effects in voxel-wise whole brain ALFF of the time and frequency bands. Paired-sample t-test was used to explore within-group changes over four years. Partial correlation analysis was performed to assess associations between the altered ALFF and cognitive function. Significant interaction effects of time × frequency were distributed over inferior frontal lobe, superior frontal lobe, right rolandic operculum, left thalamus, and right putamen. Significant ALFF reductions in all five frequency bands were mainly found in the right hemisphere and the posterior cerebellum; whereas localization of the significantly increased ALFF were mainly found in the cerebellum at slow-6, slow-5 and slow-4 bands, and left hemisphere and the cerebellum at slow-3, slow-2 bands. In addition, ALFF changes showed frequency-specific correlations with changes in cognition. These results suggest that changes of local brain activity in cognitively normal aging should be investigated in multiple frequency bands. The association between ALFF changes and cognitive function can potentially aid better understanding of the mechanisms underlying normal cognitive aging.
Characterization of a New Potyvirus Infecting Thevetia Ahouai
Authors: Cañada-Bautista Maria G. , Reyes-Proaño Edison G. , Cornejo-Franco Juan F. , Alvarez-Quinto Robert A. , Mollov Dimitre , quito-avila diego fernando 
Published: February 2022

Abstract
A new potyvirus was found in Thevetia ahouai L. (Fam. Apocynaceae) plants exhibiting leaf white spots and fruit discoloration. The complete genome of two isolates of the virus, tentatively named thevetia white spot virus (ThWSV), was determined. The genome of ThWSV comprises 9,912 (isolate 1) and 9,904 (isolate 2) nucleotides (nt), encoding a polyprotein of 363 kDa. Sequence comparisons between the two isolates showed 80 and 87% identities at the nt and amino acid (aa) levels, respectively, whereas the overall identity between ThWSV and its closest relative is 69% and 71% at the nt and aa levels, respectively.
An Interpretable Semi-Supervised Framework for Patch-Based Classification of Breast Cancer
Authors: Shawi Radwa El , Kilanava Khatia , Sakr Sherif 
Published: February 2022

Abstract
Developing effective methods for Invasive Ductal Carcinoma (IDC) detection remains a challenging problem for breast cancer diagnosis. Recently, there have been notable success of utilizing deep neural networks in various application domains, however, it is well-known that training deep neural networks requires a huge amount of labeled training data in order to achieve high accuracy. Such amounts of manually labeled data are time-consuming and very expensive to obtain especially when domain expertise is required. In order to take advantage of cheap available unlabeled data, we present a novel semi-supervised learning framework for IDC detection using small amounts of labeled training examples. In order to gain trust in the prediction of the proposed framework, we explain the prediction globally. Our proposed framework consists of five main stages including data augmentation, feature selection, dividing co-training data labeling, deep neural network modeling and interpretability of the neural network prediction. The data cohort used in this study contains digitized BCa histopathology slides from 162 women with IDC at the Hospital of the University of Pennsylvania and the Cancer Institute of New Jersey. The experimental evaluation shows that our framework is able to detect IDC with a balanced accuracy of 0.865 and F-measure of 0.773 using only 10% labeled instances from the training dataset while the rest of the training dataset is treated as unlabeled.
Identification of Novel Mutant (R132H) Isocitrate Dehydrogenase 1 Inhibitors for Glioma Therapy
Authors: Murali Poornimaa , Karuppasamy Ramanathan 
Published: February 2022

Abstract
Neomorphic transformation in isocitrate dehydrogenase 1 (IDH1) are the key mutations prevalently found in various cancers including glioma. Recently identified mIDH1 specific inhibitors such as ivosidenib and Vorasidenib were restricted for use due to its modest brain penetrating potential and dose limiting toxicity respectively. Herein, we elucidate integrated virtual screening strategies to discover persuasive mIDH1 inhibitors from the approved subset of the DrugBank database consisting of 2715 molecules. Initially, structural similarity search identified a total of 1432 lead molecules. The resultant compounds were inspected by molecular docking along with MM-GBSA and ADMET analyses. Altogether, the analyses identified DB12001 (Abemaciclib) as the hit against mIDH1. Notably, Abemaciclib was able to form hydrogen bond interaction with active site residues of mIDH1 protein. In the end, the dynamic behavior of the hit complex was also examined using molecular dynamic (MD) simulation studies. The outcome of the study culminates that the hit complex was stable throughout the simulation period of 100ns. It is worth noting that benzimidazole moiety of Abemaciclib was reported to show inhibitory activity against glioma cells. Overall, these findings highlight that DB12001 has the potential as lead molecule against glioma. Indeed the screened hit compound could be further explored for the development of mIDH1 inhibitor with great brain penetrating ability and low toxicity.
MLM-based Typographical Error Correction of Unstructured Medical Texts for Named Entity Recognition
Authors: Lee Eun Byul , Heo Go Eun , Choi Chang Min , Song Min 
Published: February 2022

Abstract
BackgroundUnstructured texts in the medical fields such as Electronic Health Records contain an enormous amount of valuable information for research, but it is difficult to extract and structure important information because of frequent typos. For text analysis, improving the quality of data with errors is an essential task, but just a few prior studies have been conducted so far. Therefore, we propose a new methodology for extracting important information from unstructured medical texts by overcoming the typographical problem in the surgical pathology records related to lung cancer in the medical field.MethodsIn order to solve the problem of typographical errors occurring in real-world medical data, we propose a typo correction model considering context based on the Masked Language Model. In addition, a word dictionary to be used for typo correction model was constructed based on PubMed abstracts. After refining the data through typo correction, fine tuning was performed on the pre-trained BERT, and deep learning based Named Entity Recognition was performed. By solving the quality problem of medical data, we strive to improve the accuracy of information extraction in unstructured text data. ResultsWe compared the performance of the proposed typo correction model based on contextual information with the existing SymSpell, and confirmed the proposed one outperformed the existing model in the typographical correction task. The F1-score of the model improved about 5% and 9% than without the contextual information in the NCBI-disease and Surgical pathology record datasets, respectively. In addition, for the evaluation of the NER task, the F1-score of NER after typo correction increased by 2% in the NCBI-disease dataset. There was a significant performance difference about 25% between before and after typo correction in the Surgical pathology record dataset. It was confirmed that typos had a great influence on information extraction in the unstructured text. ConclusionWe verified typos in text negatively affect the performance of natural language processing tasks and the proposed method outperforms the existing one. This study has implications proposed robust model can be applied to the real-world environment by focusing on the typo problem causes difficulties in analyzing unstructured medical text.