Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Two Novel Genes SNX10 and PTGDS with Cervical Squamous Cell Carcinoma Prognosis

Background: Cervical cancer (CC) is the primary cause of death in women. This study sought to investigate the therapeutic targets of CC. Methods: We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen DEGs between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by STRING and selected hub modules via MCODE. CMap was used to find molecules with therapeutic potential for CC. We also validated hub genes in GEO datasets, GEPIA, immunohistochemistry. Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also done to dig out the significance of hub genes. Results: Functional analysis revealed that DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 prominent proteins, with CDK1 having the strongest association with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC. Eight genes were screened out through GEPIA. Of them, only PTGDS and SNX10 have not been reported in CC related articles. The validation in GEO showed that PTGDS showed low expression in tumor tissues while SNX10 showed high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. They can distinguish CC and normal tissue and have good diagnostic efficiency. GSEA showed that the two genes were associated with the chemokine signaling pathway. TCGA methylation analysis showed that patients with low-expressed and hyper-methylated PTGDS had a bad prognosis than the patients with high-expressed and hypo-methylated PTGDS. Cox regression analysis showed that SNX10 and PTGDS were independent prognostic indicators for OS among CC patients. Conclusions: In conclusion, PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes could be used to develop new target treatments for CC.
Civic media and technologies of belonging: Where digital citizenship and ‘the right to the city’ converge

This article contributes to an emerging field of ‘urban communication’ research and its intersections with civic culture and digital citizenship. It does so by presenting a case study of how an activist group in North London’s Tottenham region co-designed bespoke digital media platforms, akin to civic media, to advocate an approach to urban planning that also recognizes migrants’ rights. Conducted as a part of a broader participatory action research project, the study outlined here offers an analysis of the online and offline communicative routes taken, the urban rights enacted and the visions expressed during an eight-week consultation period. Drawing on both quantitative and qualitative metrics from the official and alternative digital platforms inviting consultation around the community-led planning application, the article offers insights about the co-construction of space, and the effect that the particular site had in unearthing wider enactments of ‘the right to the city’ and affective belonging, alongside struggles against threats of displacement. By offering these insights, the study contributes to a better understanding of the digital mediation of belonging through space/place and what this means for urban citizenship. Looking beyond processes of urban planning, this understanding seeks to contribute to wider debates of urban citizenship, often expressed at the intersection of urban rights, digital citizenship and virtual reality.
The Impact of training on front liners performance: Moderating effect of job satisfaction

The context of this study focused on the role of training in improving employee performance through job satisfaction on front liners of PT. Smartfren Telecom, Tbk, Malang City. This study aimed to determine and analyze the effect of training on employee performance, both directly and indirectly, through the mediation of job satisfaction. The sample used in this study was employees who work as Front Liners, which were divided into Customer Service Representative (CSR) and Smartfren Gadget Specialist (SGS). The sample in this study included in saturated sampling was a sampling technique if all the population members were used as samples. The sample was 105 respondents. The analytical method used was descriptive analysis and Partial Least Square (PLS) using the warpPLS software application version 6.0. This study's results indicated that training has a significant effect on job satisfaction and employee performance, and mediation testing showed that job satisfaction provides a partial mediation role on the effect of training on employee performance. Further researchers need to consider a broader scope of research objects, both on the same research object and a larger scale, to enrich the results and research findings. This study also uses only a few indicators to reflect existing variables, so that further researchers can expand and integrate the research model by including several.
IMPLEMENTING DATA-DRIVEN LEARNING INTO ENGLISH GRAMMAR PEDAGOGY: A BASIC INTERPRETATIVE STUDY IN A VOCATIONAL CLASSROOM IN KARAWANG

This study described an implementation of data driven learning in teaching English grammar. To answer of research questions, this study used a qualitative approach with basic interpretative study. The study was conducted in one of vocational high schools in Karawang, involving one English teacher and six students as research subject. To investigate to what extent English teacher applied data-driven learning in teaching English grammar, this study collected data from classroom observation, interviews and studying documents. The results showed that the data driven learning was implemented in teaching grammar through four stages of teaching procedures, including pattern formation through exploring BNC data, explicit explanation from teacher to conform or to correct students’ findings, follow-up exercises through homework, then classroom production and teacher’s feedback on it.
Infrastructure governance for the Anthropocene

Transitioning infrastructure governance for accelerating, increasingly uncertain, and increasingly complex environments is paramount for ensuring that critical and basic services are met during times of stability and instability. Yet the bureaucratic structures that dominate infrastructure organizations and their capacity to respond to increasing complexity remain poorly understood. To change infrastructure governance, it is critical to understand current conditions, the barriers to change, and the strategies needed to shift priorities and leadership strategy. The emergence of modern infrastructure bureaucratic and organizational structure is first explored. The need to rethink infrastructure as knowledge enterprises capable of making sense of changing conditions, and not simply as basic service providers, is discussed. Next, transformation of infrastructure governance is presented as both a challenge of organizational change as identity and power and leadership capacity to shift between stable and unstable conditions. Infrastructure bureaucracies should create capabilities to shift between periods of stability and instability, emphasizing flexibility where ad hoc teams are given power to make sense of changing conditions and steer the organization appropriately. Additionally, several critical factors must be addressed within organizational power structures, identities, and processes to facilitate change. Allowing infrastructure governance to persist in its current form is likely increasingly problematic for the future and may result in an increasing inability to maintain relevance.
Therapeutic activity of sarpogrelate, and dopamine D2 receptor agonists on cardiovascular and renal systems in alloxan-induced diabetic rats

Background: The investigation aims to represent the activity of sarpogrelate, a particular 5-HT (2A) receptor blocker, in reducing myocardial injury prompted by extended haul utilization of D2 agonist drugs in diabetic rats. Dopamine D2 agonists are notable medications in the treatment of Parkinsonism, hyperprolactinemia, and hyperglycemia. An affiliation showed between the enlistment of myocardial injury ailment and long term treatment with dopamine D2 agonist drugs identified with the partial initiation of 5-HT 2a receptors. Methods: Both bromocriptine and cabergoline were managed independently and combined with sarpogelate for about a month to diabetic nephropathy rats. Both tail-cuff blood pressure and BGL were recorded weekly. For all animals, kidney hypertrophy index, serum creatinine, blood urea nitrogen, alanine transaminase, and aspartate transaminase levels were measured after one month of treatment. The severity of the cardiac injury was assessed by the estimation of LDH-1, cardiac troponin I, and TNFα. Triphenyl tetrazolium chloride staining method used to determine experimental myocardial infarction (MI) size. Results: Bromocriptine and cabergoline created a significant reduction in BGL, BP, and kidney hypertrophy index in diabetic nephropathy rats. Administration of bromocriptine, cabergoline, alone, or in combination with sarbogrelate fundamentally diminished blood concentrations of ALP, AST, urea, and creatinine. Bromocriptine and cabergoline alone showed noteworthy ascending of LDH-1, Troponin I, and TNFα1 levels in the serum (p<0.05). Paradoxically, utilizing bromocriptine and cabergoline with sarpogrelate treatment altogether diminished the degree of the myocardial biomarkers in the serum. A mix of bromocriptine or cabergoline with sarpogrelate diminished the level of the myocardial infarct size in the heart assessed utilizing the TTC staining method. Conclusions: The examination exhibited that both bromocriptine and cabergoline could be utilized safely in blend with sarpogrelate for a long duration of treatment for diseases like hypertension and diabetes.
Epigenetic Role of Noncoding RNAs in the Recurrence of Pituitary Adenoma after Surgical Resection

Background: Due to the lack of related symptoms and the hypersecretion of serum hormones, it is difficult to monitor and predict the postoperative recurrence of non-functioning pituitary adenomas (NFPAs). Long noncoding RNAs (lncRNAs) and protein-coding genes (PCGs) play critical roles in the development and progression of many tumors. However, the complex network of RNA interactions related to the mechanism and function of the postoperative recurrence of NFPA is still unclear. Methods: In the present study, 100 patients with NFPA were investigated by high-throughput sequencing and follow up. Among them, 16 NFPA patients experienced recurrence at different intervals of more than five years or less than one year. Results: By performing differential expression analysis of the fast recurrence and slow recurrence groups (t test P < 0.05), we obtained a set of differentially expressed PCGs and lncRNAs. We then identified protein-protein interaction (PPI) coregulatory networks and lncRNA-mRNA coexpression networks. In addition, we further screened the hub lncRNA-mRNA modules related to NFPA recurrence. These modules identified transcriptome expression markers for NFPA regression (log-rank test P <0.05). Finally, we evaluated the ability of the hub and module genes to predict recurrence and progression-free survival (PFS) in NFPA patients. To confirm the credibility of the bioinformatic analysis, NOL6 was randomly selected from the prognosis genes for validation by quantitative real-time polymerase chain reaction (qRT-PCR) in another set of NFPA samples (n=9). Conclusion: These results may be helpful for evaluating the slow and rapid recurrence of NFPA after surgery, may help us explore the mechanisms of NFPA recurrence and may also serve as future effective biomarkers and therapeutic targets.
Tim-3 drives tissue Treg effector function to promote neonatal immune tolerance and tumor-induced immune suppression

Tissue regulatory T cells (Treg) are a key player in preventing immune pathology and shaping the immune suppressive tumor microenvironment (TME). The signaling molecules that uniquely regulate tissue Treg are not well understood. Here, we show that Tim-3 was predominantly expressed in Treg cells in both normal and tumor tissues. Notably, Tim-3 deficiency in Tregs led to the development of severe signs of autoimmune diseases in neonatal mice, indicating a crucial role of Tim-3 in establishing immune tolerance in early life. In addition, deletion of Tim-3 on Tregs resulted in reduced numbers and suppressor activities of tumoral Tregs and an increase in antitumor immune responses. A gene profiling study revealed the requirement of Tim-3 in upregulation of effector Treg genes encoding immune inhibitory molecules, chemokine receptors for tissue residency, chemokines, and cytokines. Moreover, Tim-3 deficiency in Tregs and treatment with PD-1 mAbs synergistically inhibited tumor growth. Our study demonstrates the essential role of Tim-3 in driving tissue effector Treg-mediated immune suppression.
Fundus Eye Images Classification for Diabetic Retinopathy Detection Using Very Deep Convolutional Neural Network

Diabetic retinopathy is an anomaly responsible for causing microvascular and macrovascular damage to the retina and occurs as a consequence of the worsening of diabetes. According to the World Health Organization (WHO), diabetic retinopathy is the most common cause of avoidable blindness in patients with diabetes worldwide. Early detection is important for the efficiency of treatments. Fundus Eye Image can be used to identify early disease development and monitor the patient’s clinical condition. The diagnostic process using this type of image may require some expertise from the ophthalmologist since not all retina anomalies are clearly visible. Thus, this paper proposes the development of a classification method based on Convolutional Neural Networks, but highly dense and deeper. The proposed method obtained a total of 92% AUC in the given experiments.
Single-stage versus two-stage models to estimate creatinine corrected urinary analyte concentrations

ABSTRACT The ability to detect 'known' differences in urinary analyte concentrations due to gender, age, and race/ethnicity when adjusted for similar differences in urinary creatinine concentrations were evaluated by a single-stage and a two-stage model by ten simulation studies. Log10 transformed values of observed urinary analyte concentration were used as the dependent variable and age, gender, and race/ethnicity were used as the categorical independent variables. In addition, while single-stage model used log10 transformed values of urinary creatinine as a covariate, two-stage model used a correction factor (CF) determined during the first stage of the model by fitting a secondary model for urinary creatinine. Single-stage model was almost always able to statistically significantly detect 'known' differences due to age, gender, and race/ethnicity. On the other hand, two-stage model was able to statistically significantly detect 'known' differences due to age, gender, and race/ethnicity a maximum of 87.2% of the times and as low as 10.6% of the times primarily because of the presence of multicollinearity between CF and urinary creatinine concentrations. Consequently, as long as the sole objective is to estimate the urinary analyte concentrations adjusted for the effect of all factors including urinary creatinine, single-stage models are the models of choice.
Protocol for a Systematic Review of Outcome Measurement Tools for Autologous fat Grafting of the Facial Region

BackgroundAutologous fat grafting has become an established therapeutic entity in several regions of the body. Especially in the facial region, AFG has been widely applied in the field of plastic and reconstructive surgery. Indications include reconstructive purposes such as primary genetic disorders in maxillofacial development, or secondary asymmetries following primary reconstructive surgery. In addition, AFG has found several applications in the field of aesthetic surgery, such as skin rejuvenation. In addition to conventional AFG, recently several alternative strategies of grafting have been developed. Examples for these are transplantation of a graft including adipose derived stem cells (ADSC’s), cell-assisted lipofilling (CAL), and grafting with stromal vascular fraction (SVF). Until today, there is no common consensus on how to measure a successful outcome of autologous graft transplantation in the facial region. This systematic review aims to critically evaluate the current available outcome measurement methods, and compare them with regards to accuracy, cost-effectiveness, safety and validation in the clinical setting. The quality of evidence of included publications will be assessed using the GRADE strategy.MethodsA comprehensive, structured literature search of published articles will be conducted. This is designed by authors and performed in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA-P). The literature search will be performed using the electronic databases MEDLINE (PubMed), EMBASE and Cochrane Library, including publications from inception to May 2020. Two independent authors will conduct the search, screen the articles, and complete data collection. The main outcome will be which methods are currently used to determine a successful fat grafting procedure in the face. We propose to review the current methods used to establish their overall performance in several domains. In addition, patients measured via the 3D volumetric photography method will be further analysed with regards to accuracy of the camera and retention of fat per method and ml injected.Discussion Autologous fat grafting in the facial region has gained significant attention in the field of plastic and reconstructive surgery in the past decades. In light of the growing public interest in this topic, a systematic review of the outcome measurement tools is of essence. We will critically evaluate all approaches currently in practice and give a recommendation regarding several aspects of use. A common approach to measurement and reporting of results fosters an environment of high-standard healthcare delivery and promotes future research and informed clinical practice. In addition, we will further analyse the outcomes of different grafting methods using 3D volumetric photography as measurement tool. PROSPERO registration number: CRD42020213407
Analysis of metabonomic profiling alterations in a mouse model of colitis-associated cancer and 2-deoxy-d-glucose treatment

Inflammation is well recognized to be associated with tumorigenesis, cancer progression and tumor metabolism of colorectal cancer (CRC). 2-Deoxy-D-glucose (2-DG), a glycolytic inhibitor, has been reported to possess anticancer properties and is considered to be a promising treatment for tumors. However, the metabolic alteration in tumorigenesis caused by inflammation and 2-DG prevention remains elusive. In this study, a gas chromatography time-of-flight mass spectrometry (GC-TOF/MS) analysis was applied to investigate the anticancer activity of 2-DG on the alteration of metabolites in a colitis-associated cancer model induced by azoxymethane (AOM) and dextran sodium sulfate (DSS). The data showed that 2-DG obviously decreased the incidence of tumor formation induced by AOM and DSS. 14 metabolites were significantly decreased in the AOM/DSS group, while all these metabolites were reversed by 2-DG treatment. Furthermore, metabolic pathway analysis (MetPA) was introduced to reveal the involvement of four metabolic networks including linoleic acid metabolism, pentose phosphate pathway, nicotinate and nicotinamide metabolism and inositol phosphate metabolism. The significantly altered metabolites of linoleic acid, nicotinamide, ribose-5-phosphate and myo-inositol were involved in these four pathways. Moreover, the expression of PKM2, which was induced by AOM and DSS, was attenuated by 2-DG treatment. Together, this study provides an insight into how 2-DG shows anticancer effects and may serve as a therapeutic agent for colitis-associated cancer.
Can Emergency Remote Education Make Universities “Smarter”? Lecturers’ Reflections About Useful Literacies

The shift of the entire education system onto digital platforms due to the coronavirus emergency has made lecturers and students massively experience digital teaching and learning, its challenges and possibilities. As with another possible lockdown looming on the new academic year Emergency response education (ERE) might have to be turned into the new normal of distance learning, the wisdom learned by the massive online experience of the last semester could contribute to planning a nimble response to educational needs in case universities have to shift online again. This paper aims at contributing to the discussion on key literacies lecturers might find useful to turn ERE into quality distance education. 24 full professors of English and English linguistics courses from 14 Italian universities have filled in an online questionnaire investigating the challenges and opportunities they have experienced during the emergency which shed light on the multiple literacies they should focus on to plan an effective response to a new emergency, which at the same time could make high school education “smarter” both in-person and online.
Optimal Risk Adoption and Capacity Investment in Disruptive Innovations

Disruptive innovations often formulate new market regimes and create incentives to abandon existing, less attractive ones. However, this decision depends not only on market forces, such as economic and technological uncertainty, but also on attitudes towards risk. Although greater risk aversion typically raises the incentive to postpone investment, the impact of risk aversion becomes more complex when a firm has discretion over both the timing and the size of a project. We develop a utility-based, regime-switching framework in order to analyse how a firm with discretion over investment timing and project scale may choose to abandon an existing market regime to enter a new one. Results indicate that greater risk aversion hastens investment in an existing regime by decreasing the amount of installed capacity, but delays its abandonment, thereby hindering the transition to a new one. In contrast, greater demand uncertainty in the new market regime raises the value of the investment opportunity, and, in turn, the incentive to abandon the existing regime. Furthermore, we find that uncertainty over the arrival of a disruptive innovation may accelerate investment in the existing regime and reduce the relative loss in project value in the absence of managerial discretion over project scale.
Tax Haven Incorporation and the Cost of Capital

While incorporating the firm’s parent company in a tax haven offers tax savings, it also imposes risks. We predict and find a higher cost of equity capital in firms with parent companies that are incorporated in tax havens. We find that the observed cost of equity premium is enhanced by tax risk, firm-level information risk, and country-level legal risk. We also employ corporate inversions in a difference-in-differences test and again find a positive relation between tax haven parent incorporation and the cost of capital. Our study contributes to the literatures on valuation of tax haven use, tax and nontax costs of corporate strategies, corporate inversions, and the relation between taxes and the cost of capital.