Miracle-dz/UniFAR-FTUs huggingface dataset:
MicroRNA-125a-mediated regulation of the mevalonate signaling pathway contributes to high glucose-induced proliferation and migration of vascular smooth muscle cells

Hyperglycemia contributes to the excessive proliferation and migration of vascular smooth muscle cells (VSMC), which are closely associated with atherosclerosis. MicroRNAs (miRNAs/miRs) constitute a novel class of gene regulators, which have important roles in various pathological conditions. The aim of the present study was to identify miRNAs involved in the high glucose (HG)-induced VSMC phenotype switch, and to investigate the underlying mechanism. miRNA sequencing and reverse transcription-quantitative PCR results indicated that inhibition of miR-125a expression increased the migration and proliferation of VSMCs following HG exposure, whereas the overexpression of miR-125a abrogated this effect. Furthermore, dual-luciferase reporter assay results identified that 3-hydroxy-3-methyglutaryl-coA reductase (HMGCR), one of the key enzymes in the mevalonate signaling pathway, is a target of miR-125a. Moreover, HMGCR knockdown, similarly to miR-125a overexpression, suppressed HG-induced VSMC proliferation and migration. These results were consistent with those from the miRNA target prediction programs. Using a rat model of streptozotocin-induced diabetes mellitus, it was demonstrated that miR-125a expression was gradually downregulated, and that the expressions of key enzymes in the mevalonate signaling pathway in the aortic media were dysregulated after several weeks. In addition, it was found that HG-induced excessive activation of the mevalonate signaling pathway in VSMCs was suppressed following transfection with a miR-125a mimic. Therefore, the present results suggest that decreased miR-125a expression contributed to HG-induced VSMC proliferation and migration via the upregulation of HMGCR expression. Thus, miR-125a-mediated regulation of the mevalonate signaling pathway may be associated with atherosclerosis.
Targeted histone demethylation improves somatic cell reprogramming into cloned blastocysts but not postimplantation bovine concepti †

Abstract Correct reprogramming of epigenetic marks in the donor nucleus is a prerequisite for successful cloning by somatic cell transfer (SCT). In several mammalian species, repressive histone (H) lysine (K) trimethylation (me3) marks, in particular H3K9me3, form a major barrier to somatic cell reprogramming into pluripotency and totipotency. We engineered bovine embryonic fibroblasts (BEFs) for the doxycycline-inducible expression of a biologically active, truncated form of murine Kdm4b, a demethylase that removes H3K9me3 and H3K36me3 marks. Upon inducing Kdm4b, H3K9me3 and H3K36me3 levels were reduced about 3-fold and 5-fold, respectively, compared with noninduced controls. Donor cell quiescence has been previously associated with reduced somatic trimethylation levels and increased cloning efficiency in cattle. Simultaneously inducing Kdm4b expression (via doxycycline) and quiescence (via serum starvation) further reduced global H3K9me3 and H3K36me3 levels by a total of 18-fold and 35-fold, respectively, compared with noninduced, nonstarved control fibroblasts. Following SCT, Kdm4b-BEFs reprogrammed significantly better into cloned blastocysts than noninduced donor cells. However, detrimethylated donors and sustained Kdm4b-induction during embryo culture did not increase the rates of postblastocyst development from implantation to survival into adulthood. In summary, overexpressing Kdm4b in donor cells only improved their reprogramming into early preimplantation stages, highlighting the need for alternative experimental approaches to reliably improve somatic cloning efficiency in cattle. Summary Sentence Overexpressing KDM4B in somatic donor cells improves their reprogramming into cloned embryos but not survival into live cattle.
Identification, characterization and microRNA expression profiling of side population cells in human oral squamous cell carcinoma Tca8113 cell lines

The present study aimed to evaluate the stem cell markers, characteristics and biological functions of cancer stem-like side population (SP) cells in human oral cancer. SP cells were isolated from the human oral squamous cell carcinoma Tca8113 cell line by Hoechst 33342 fluorescence dye and flow cytometry. The colony forming and proliferative capability of SP and non-SP cells were detected using a live-cell analysis system in vitro. The number of cells expressing stem cell markers was compared between SP cells and non-SP cells by flow cytometry. Reverse transcription-quantitative polymerase chain reaction and western blotting were used to detect the mRNA and protein expression levels of stem cell genes, respectively. Differential expression of microRNAs (miRNAs) in SP and non-SP cells was determined by microarray hybridization and an miRNA regulation network was produced. With regard to the proliferation capability, SP cells reached 60.0% confluence after 40 h of growth compared with 35.1% confluence for non-SP cells (P<0.05). The number of colonies in SP cells was 43.1±9.2 compared with 33.0±8.2 of non-SP cells (P<0.05). The aldehyde dehydrogenase-1 (ALDH1)-positive cell number in the SP cells was increased by 10 times compared with the non-SP cells (P<0.01). The mRNA and protein expression levels of ALDH1, SRY-box 2, POU class 5 homeobox 1 and Nanog homeobox in SP cells were significantly higher compared with non-SP cells (P<0.05). Microarray hybridization demonstrated that 21 miRNAs were upregulated and 13 miRNAs were downregulated in SP cells compared with non-SP cells. SP cells in Tca8113 demonstrated greater capability of proliferation and colony formation compared with non-SP cells in vitro. Stem cell markers were overexpressed in SP cells compared with non-SP cells.
CRISPR/Cas9 Epigenome Editing Potential for Rare Imprinting Diseases: A Review

Imprinting diseases (IDs) are rare congenital disorders caused by aberrant dosages of imprinted genes. Rare IDs are comprised by a group of several distinct disorders that share a great deal of homology in terms of genetic etiologies and symptoms. Disruption of genetic or epigenetic mechanisms can cause issues with regulating the expression of imprinted genes, thus leading to disease. Genetic mutations affect the imprinted genes, duplications, deletions, and uniparental disomy (UPD) are reoccurring phenomena causing imprinting diseases. Epigenetic alterations on methylation marks in imprinting control centers (ICRs) also alters the expression patterns and the majority of patients with rare IDs carries intact but either silenced or overexpressed imprinted genes. Canonical CRISPR/Cas9 editing relying on double-stranded DNA break repair has little to offer in terms of therapeutics for rare IDs. Instead CRISPR/Cas9 can be used in a more sophisticated way by targeting the epigenome. Catalytically dead Cas9 (dCas9) tethered with effector enzymes such as DNA de- and methyltransferases and histone code editors in addition to systems such as CRISPRa and CRISPRi have been shown to have high epigenome editing efficiency in eukaryotic cells. This new era of CRISPR epigenome editors could arguably be a game-changer for curing and treating rare IDs by refined activation and silencing of disturbed imprinted gene expression. This review describes major CRISPR-based epigenome editors and points out their potential use in research and therapy of rare imprinting diseases.
Assessing predictors of respiratory tract infections in infants born to teenage mothers: secondary analysis of the Building Blocks trial data.

BACKGROUND Respiratory tract infections (RTIs) are estimated to account for 60% of infants' primary care visits. There is limited research into risk factors for infant RTIs in those born to teenage mothers. AIMS To identify risk factors for primary and secondary care RTI attendances, in infants of teenage mothers, and to identify risk factors associated with high primary care RTI consultations. METHOD Secondary analysis of a data set from the Building Blocks trial of special home visiting support in England containing 1510 infants born to teenage mothers recruited to the study. Maternally reported and routinely collected data were examined. Multivariable logistic regression models were performed to determine independent predictors. Primary care data analysis also focused on infant risk factors for RTI consultation. RESULTS No independently predictive risk factors for infant RTI were identified in primary care. Lower maternal antenatal attendances (odds ratio = 0.96, 95% confidence interval = 0.92-0.99), infants born in autumn (vs. spring; 0.54, 0.36-0.80) and neonatal unit (NNU) admissions (0.51, 0.30-0.89) had increased odds of attending accidents and emergencies with an RTI. Male infants (1.52, 1.03-2.25), NNU admissions (3.21, 1.98-5.22) and birth season had increased odds of RTI-associated hospital admissions. High infant RTI primary care consulters were more likely to have an RTI-associated hospital admission (2.11, 1.17-3.81) and less likely to have breastfed (0.55, 0.38-0.78). CONCLUSION Risk factors previously found to increase the risk of an RTI infant admission in the broader population have been identified here. This study is one of the first to identify modifiable risk factors of high primary care RTI consulters.
Decontamination of face masks with steam for mask reuse in fighting the pandemic COVID‐19: Experimental supports

The coronavirus disease 2019 pandemic caused by the novel coronavirus SARS‐CoV‐2 (severe acute respiratory syndrome coronavirus 2) has claimed many lives worldwide. Wearing medical masks (MMs) or N95 masks ([N95Ms] namely N95 respirators) can slow the virus spread and reduce the infection risk. Reuse of these masks can minimize waste, protect the environment, and help solve the current imminent shortage of masks. Disinfection of used masks is needed for their reuse with safety, but improper decontamination can damage the blocking structure of masks. In this study, we demonstrated using the avian coronavirus of infectious bronchitis virus to mimic SARS‐CoV‐2 that MMs and N95Ms retained their blocking efficacy even after being steamed on boiling water for 2 hours. We also demonstrated that three brands of MMs blocked over 99% viruses in aerosols. The avian coronavirus was completely inactivated after being steamed for 5 minutes. Altogether, this study suggested that MMs are adequate for use on most social occasions and both MMs and N95Ms can be reused for a few days with steam decontamination between use.
Extended Abstract of the Dissertation in Classification in the Presence of Background Domain Knowledge

The thesis is mainly about extending statistical approaches to classification to make use of existing domain knowledge. Classification algorithms are supervised methods that look for and discover the hidden associations between the target class and the independent variables [Maimon and Rokach, 2010]. Supervised learning algorithms allow tags to be assigned to the observations, so that unobserved data can be categorized based on the training data [Han et al., 2011]. In classification a model is a set of rules built from a group of already classified training data objects in order to forecast the classes of previously unseen data objects. [Thabtah and Cowling, 2007]. In spite of the great efforts that were made in the last decade in data mining algorithms the problem of using existing domain knowledge to enrich and better focus the results on user expectations remains open to further developments [Cao, 2010; Domingos, 2003; Yang and Wu, 2006]. One of the problems encountered in the automatic induction of classification rules from examples is the overfitting of the rules to the training data, in some cases resulting in excessively large models with low predictive power for unseen data [Bramer, 2002]. Overfitting is the use of models that violate parsimony, i.e., that include more terms than are necessary or use more complicated approaches than are necessary. This is undesirable: adding irrelevant predictors can make predictions worse because the coefficients fitted to them add random variation to the subsequent predictions; the choice of model impacts its portability [Hawkins, 2004]. Most current algorithms produce models that have a very low portability or are not portable at all: if a feature of some instance is changed by a synonym or is in a different language, chances are that a new model has to be learned. It is our belief that the introduction of ontologies, as a means to formally represent existing background knowledge, in the learning process (of classification algorithms) will allow the production of more concise models by working at different levels of abstraction and exploring the relationship between concepts in the data set.
Approximate String Matching and Duplicate Detection in the Deep Learning Era

Duplicate detection is the process of identifying pairs of attributes/records that refer to the same real-world object. This is fundamental to ensure data quality in databases. Existing methods to detect duplicate attributes can leverage heuristic string similarity measures, phonetic encoding techniques that match strings based on the way they sound, or hybrid techniques that mix approaches. However, these methods all rely on common sub-strings in order to establish similarity, and often do not eﬀectively capture the character replacements involved in duplicate attributes due to transliterations or diﬀerent languages. This work follows on the proposal of Santos et al. regarding string matching using deep neural networks [22]. It considers more advanced neural architectures integrating shortcut connections, self attention mechanisms, hard alignment attention between the strings being compared, or max-pooling over the sequences of outputs of the recurrent layers, either considering a single RNN or a hierarchy of RNN layers [26]. It also considers extentions the previous models involving a concatenation of the representations of the strings obtained through neural network layers, with other additional features, these features are derived from the dataset attributes but can also be related to the similarity between the strings. The models are evaluated using datasets describing collections of person names, organizations, or records of historical places. The results obtained from training and evaluating the various neural network models and their extensions showed that the neural models achieved superior results on all datasets, when compared to string similarity measures, without the need of major tunings of the network parameters.
University of Birmingham Tighter guarantees for the compressive multi-layer perceptron

We are interested in theoretical guarantees for classic 2-layer feed-forward neural networks with sigmoidal activation functions, having inputs linearly compressed by random projection. Due to the speedy increase of the dimensionality of modern data sets, and the development of novel data acquisition devices in compressed sensing, a proper understanding of are the guarantees obtainable is of much practical importance. We start by analysing previous work that attempted to derive a lower bound on the target dimension to ensure low distortion of the outputs under random projection, and we ﬁnd a disagreement with empirically observed behaviour. We then give a new lower bound on the target dimension that, in contrast with previous work, does not depend on the number of hidden neurons, but only depends on the Frobenius norm of the ﬁrst layer weights, and in addition it holds for a much larger class of random projections. Numerical experiments agree with our ﬁnding. Furthermore, we are able to bound the generalisation error of the compressive network in terms of the error and the expected distortion of the optimal network in the original uncompressed class. These results mean that one can provably learn networks with arbitrarily large number of hidden units from randomly compressed data, as long as there is suﬃcient regularity in the original learning problem, which our analysis rigorously quantiﬁes.
Cloudbox Private, Reliable and Distributed Storage

This work describes a solution for cooperative storage of ﬁles. Since it is intended to store data remotely in non-trusted nodes, it is necessary to take steps to protect the users privacy. It is shown how to build a system, Cloudbox, capable of storing ﬁles in a distributed network, respecting the inherent privacy issues. The Cloudbox system is also capable of supporting groups: sets of ﬁles whose access is restricted to a set of users. The resulting system allows a user to store their data in the cloud, ensuring that the contents of his ﬁles are safe. It takes into account the transitional nature of distributed networks and presence of possible attackers. This dissertation quantiﬁes the impact of several techniques used on the performance of a possible implementation, taking into account various parameterizations.
Single-Stage Treatment of Aseptic Nonunion of the Humerus with Locking Plate Fixation and Autograft

Background: Locking and non-locking compression plates are widely used in different long bone fractures. Biomechanical and controlled studies have reported a higher stability and rate of union with the use of locking plates. Locking plates are safely used also in the treatment of humeral nonunions with varying rates of success. Aims: The aim of this study was to evaluate the radiological and clinical results of a single-stage surgical treatment with locking compression plates (LCPs) and autologous bone grafting in patients with aseptic nonunion of the humerus. Study Design: Level of Evidence IV, case control study. Methods: Twenty-four patients (17 males; mean age: 43.5 years) treated with LCPs and autologous bone grafts due to nonunion following humeral fractures were included in this study. Twelve patients had earlier been treated surgically while the remaining 12 had received non-surgical (conservative) treatment. Six patients had atrophic and 18 had oligotrophic nonunions. Functional evaluation was made using the Constant-Murley scoring system. Results: The mean follow-up period was 43.6 months. Radiological union was observed in all patients except one (95.8%) in an average period of 18.8 weeks. A mean shortening of 1.8 cm was performed on six patients with atrophic nonunion. Preoperative infection markers and intraoperative cultures were negative for infection. Four patients experienced delayed unions and one patient had transient radial nerve palsy. Ten patients had excellent, 12 had good, and two had fair scores. Conclusion: The management of humeral nonunions with single-stage surgical intervention performed using LCPs and autologous bone grafts, following adequate debridement, is an effective method with satisfactory radiological and clinical outcomes.
Evaluation of a substance use treatment program for forensic psychiatric inpatients

ABSTRACT There have been few evaluations of substance use interventions for forensic psychiatric patients. In this study, we evaluated a manualized substance use treatment for forensic inpatients by comparing 35 treatment completers (who attended 75% or more of their sessions) and 30 non-completers (less than 75%) on self-report and urinalysis measures. The treatment completer group showed significant increases in substance-related knowledge and self-reported relapse prevention skills, but there was no significant difference between completers and non-completers in time to first substance use (if any) or in having a positive urine screen result 12 or 24 months after participation in the program. The results indicated improvement in knowledge and self-reported skills, but this did not translate to decreased substance use as measured by urinalysis. Implications for substance use treatment are discussed.
TrUbi Mobile Operating System Security

Mobile devices, such as smartphones and tablets, are highly integrated in today’s society. Due to their mobility, and wide variety of functionalities, these devices allow their users to perform a large set of diverse tasks of their daily life. However, many usage scenarios require these functionalities to be constrained in some manner. In a cinema, for example, it is in everyones’ best interest that the mobile device is muted. We present TrUbi, a system that allows for temporary restrictions of mobile devices by forcing some of their speciﬁc functions to be locked for a limited amount of time, e.g. sound muted, network access blocked, etc. To provide this restriction capability, TrUbi enforces global security policies by implementing an operating system primitive named trust lease. Our TrUbi prototype, implemented on Android OS, can eﬃciently prevent real-world apps from accessing devices’ functions constrained by TrUbi and enable new mobile utilization scenarios that are currently unsupported, to the best of our knowledge, by existing mobile operating systems. Lastly, the TrUbi prototype was also tested in terms of performance which registered a negligible impact on the overall system performance and energy consumption.
Collaborative Platform for Analysis of Software Systems

—The Software Architectures course at Instituto Superior T´ecnico teaches students the most important concepts on design and architecture of software systems and helps students to apply these concepts to real and complex software systems. Organizing knowledge and applying theory to practice is not an easy task, and students often need to ask questions and discuss. State-of-the-art on collaborative, social software and knowledge structuring was analyzed and a social platform was developed to help solving these problems.
Using Gamification to Engage Users in Social Media Applications

The difficulty that organizations have to maintain user engagement to their social media applications is one of the biggest problems they face. Lack of user engagement, for the particular cases of content sharing and social networking applications, leads to an eminent decrease of the quality and novelty of the available contents, that will result in the abandonment of the system. This research proposes the development of a gamification method that uses game elements and game design techniques to create new user behaviors and change and promote existing ones, providing real-time feedback in a enjoyable way and thus promoting user engagement. Design Science Research Methodology (DSRM) was the chosen methodology to guide this research. Two iterations were used to the development of our proposal, each one characterized by a set of gamification elements. The demonstration of our proposal was conducted in a real environment, in an application of content sharing and social networking, called SKAN. In order to evaluate our proposal, we used an evaluation framework and techniques to measure user engagement that include data collection from user interaction with the application, surveys conducted to analyze the usability and adoption of the proposal and feedback from the users and SKAN management team. Although the limitations we faced during the evaluation of our proposal, the method developed appears to be promising in increasing the engagement of the users in social media applications of this type