Miracle-dz/UniFAR-FTUs huggingface dataset:
Increasing myocardial infarction mortality trends in a middle-income country.

Background Developed countries continue to show a decrease in cardiovascular disease (CVD) mortality. Little is known about CVD mortality trends in low and middle-income countries. The aim of our study is to describe myocardial infarction (MI) mortality trends and evaluate if differences between ethnic groups and geographic regions are present among the Ecuadorians with acute MI. Methods We conducted a cross sectional analysis mortality national registry and included deaths related to MI between 2012 and 2016 that had complete demographic data. To describe the general population, we used the 2010 census and applied estimates as population projections. We calculated age and sex standardized MI mortality rates per 100,000. We compared trends in MI mortality rate for every ethnic group and geographic region and used linear regression to estimate predictors of the changing mortality rates. Results We included 18,277 MI deaths between the years 2012 and 2016. The mean age of death was 73.6±19.5, 59% were male and 33% were illiterate. From 2012 to 2016, the standardized MI mortality rate increased from 51 to 157 deaths per 100,000. The most significant predictors of the increasing mortality rate were living in the coast (β=0.10), belonging to a mixed race (β=-0.033) and the year of death (β=0.013). Conclusions Our study found a worrisome increase in MI mortality between 2012-2016 in Ecuador, a middle-income country in South America. This rapid increase seems to be driven by geographic and racial differences. A thorough evaluation of the causes of this increase has to be undertaken by the Ecuadorian health authorities.
Precision public health—the Emperor’s new clothes

Recently the Centre for Disease Control suggested that ‘precision public health’ presents significant opportunities to improve the health of the population,1 but what does this concept add and does it live up to the hype? The promise is that by harnessing the power of Big Data, particularly genomic data, we may indeed see early gains in public health as a result of ‘more-accurate methods for measuring disease, pathogens, exposures, behaviors, and susceptibility’ to guide targeted prevention strategies.2 However, the term ‘precision public health’ is susceptible to misinterpretation. Long before Big Data in the form of personalized genetic and epigenetic profiling arrived, much public health screening and prevention strategy was premised on varying degrees of targeting and stratification, so this is nothing new. Nevertheless, others in the UK have used analogous terms such as ‘personalized prevention’ or ‘personalized public health’, representing them as part of an urgent agenda in which we must ‘reap the benefits of the genomic revolution’. 3 The purpose of this article is therefore to highlight some of the evidentiary and philosophical challenges for the concept of ‘precision public health’ which have not been exposed to sufficient scrutiny. It is also to argue for a more considered focus beyond the genome, lest we career headlong towards a diversion of resources, away from what really matters, to the detriment of population health. To do this, we structure our critique by aligning it with the so-called population perspective on precision medicine (i.e. the ‘P4 approach’), namely that precision public health should aim to be Predictive, Preventive, Personalized and Participatory.4 The advantage of taking this approach is that whereas it focuses on the key dimensions and parameters of the decisions that could help improve care both for individuals and populations, it has gained traction among precision medicine proponents themselves. Thereafter we return to the more philosophical and ethical arguments that should remind us of a bigger picture and the trade-offs that we might be making by investing in ‘precision public health’.
Fecal microbiota transplant – a new frontier in inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic multifactorial disease that affects the gastrointestinal tract and results from an aberrant immune response toward luminal antigens in genetically susceptible people. Most of the current therapies for IBD focus on the management of the inflammation by using corticosteroids, immune modulators, and more recently, monoclonal antibodies (biological therapy). Although these therapies provide benefit in most cases, there are still a significant number of patients who do not respond or become refractory over time, suggesting the need for alternative therapeutic options. In the last decade, it has been recognized that “dysbiosis,” an imbalanced gut microbiota, is a key element in IBD suggesting microbiome-based therapies as an attractive approach. Recently, fecal microbiota transplant (FMT) has been successfully used for the treatment of Clostridium difficile infection, and it is now under investigation for the treatment of IBD. Clinical trials data are still poor but strongly support a future introduction of FMT in therapy to manage IBD microbiome. More studies are needed to assess the optimal route of administration and the frequency of FMT, the best matched donor for each patient as well as the risks associated with FMT in IBD.
Hepatitis B virus-X protein regulates high mobility group box 1 to promote the formation of hepatocellular carcinoma

Hepatitis B virus (HBV) infection is a risk factor for hepatocellular carcinoma (HCC). HBV X protein (HBx) is an important carcinogen for HBV-induced HCC. When the HBx gene is integrated into the host cell genome, it is difficult to eradicate. The identification of an effective target to inhibit the oncogenic function of HBx is therefore critically important. The present study demonstrated that HBx, particularly truncated HBx, was expressed in several HBV-derived cell lines (e.g., Hep3B and SNU423). By analyzing data from The Cancer Genome Atlas, it was revealed that high expression of high mobility group box 1 (HMGB1) was associated with the process and prognosis of HCC. In vitro experiments confirmed that HBx could regulate the expression of HMGB1 and knockdown of HMGB1 could decrease the ability of HBx to promote cellular proliferation. HBx could also upregulate six transcription factors (GATA binding protein 3, Erb-B2 receptor tyrosine kinase 3, heat shock transcription factor 1, nuclear factor κB subunit 1, TATA-box binding protein and Kruppel-like factor 4), which could directly regulate HMGB1. By analyzing genes that are co-expressed with HMGB1, several signaling pathways associated with the development of HCC were identified. HBx and HMGB1 were revealed to be involved in these pathways, which may be the mechanism by which HBx promotes HCC by regulating HMGB1. These findings suggested that HMGB1 may be an effective target for inhibiting HBV-induced HCC.
Which is the better inpainted image? Learning without subjective annotation

This paper proposes a learning-based quality evaluation framework for inpainted results that does not require any subjectively annotated training data. Image inpainting, which removes and restores unwanted regions in images, is widely acknowledged as a task whose results are quite difficult to evaluate objectively. Thus, existing learningbased image quality assessment (IQA) methods for inpainting require subjectively annotated data for training. However, subjective annotation requires huge cost and subjects’ judgment occasionally differs from person to person in accordance with the judgment criteria. To overcome these difficulties, the proposed framework uses simulated failure results of inpainted images whose subjective qualities are controlled as the training data. This approach enables preference order between pairwise inpainted images to be successfully estimated even if the task is quite subjective. To demonstrate the effectiveness of our approach, we test our algorithm with various datasets and show it outperforms state-of-the-art IQA methods for inpainting.
Aberrant promoter methylation of PCDH10 as a potential diagnostic and prognostic biomarker for patients with breast cancer

Protocadherin-10 (PCDH10) is a tumor suppressor gene. Its expression level is downregulated by promoter methylation in certain types of human tumors. The aim of the present study was to examine the expression level and promoter methylation status of PCDH10 in breast cancer cells and to evaluate the association of PCDH10 methylation and tumor progression and prognosis. MethyLight was used to detect the methylation status of PCDH10 in breast cancer tissues and healthy breast tissues. Reverse transcription-quantitative polymerase chain reaction was used to assess the mRNA expression level of PCDH10, as well as to evaluate the association between PCDH10 methylation and clinicopathological features, along with patients' overall survival (OS). PCDH10 5′-C-phosphate-G-3′ (CpG) methylated sites were identified in tumor tissues and matched healthy tissues (n=392). Tumor tissues and matched healthy tissues exhibited identifiable PCR results, with PCDH10 gene promoter methylation identified in ductal carcinoma in situ (66%), invasive ductal carcinoma (82%), invasive ductal carcinoma with lymph node metastasis (85.32%) and hereditary breast cancer tissues (72.37%). PCDH10 mRNA expression was significantly decreased in breast cancer tissues compared with healthy breast tissues (P=0.032). PCDH10 methylation was associated with tumor size (P=0.004), but not associated with other clinical factors. Survival analysis revealed that the patients exhibiting methylated-PCDH10 had significantly poorer OS times than patients exhibiting unmethylated-PCDH10 (P<0.0001). Receiver operating characteristic analysis indicated a sensitivity of 75%, a specificity of 62.5%, and an area under the curve of 0.682 for PCDH10. Additionally, the results of the present study indicated that PCDH10 methylation status may be a useful diagnostic and prognostic evaluation biomarker for breast cancer. The results suggested that PCDH10 methylation is a common occurrence in primary breast cancer and is associated with poor survival rates among patients with breast cancer.
Argument Mining on Clinical Trials

Argument-based decision making has been employed to support a variety of reasoning tasks over medical knowledge. These include evidence-based justifications of the effects of treatments, the detection of conflicts in the knowledge base, and the enabling of uncertain and defeasible reasoning in the health-care sector. However, a common limitation of these approaches is that they rely on structured input information. Recent advances in argument mining have shown increasingly accurate results in detecting argument components and predicting their relations from unstructured, natural language texts. In this study, we discuss evidence and claim detection from Randomized Clinical Trials. To this end, we create a new annotated dataset about four different diseases (glaucoma, diabetes, hepatitis B, and hypertension), containing 976 argument components (697 containing evidence, 279 claims). Empirical results are promising, and show the portability of the proposed approach over different branches of medicine.
Unsupervised Deep Generative Hashing

Hashing is regarded as an efﬁcient approach for image retrieval and many other big-data applications. Recently, deep learning frameworks are adopted for image hashing, suggesting an alternative way to formulate the encoding function other than the conventional projections. However, existing deep learning based unsupervised hashing techniques still cannot produce leading performance compared with the non-deep methods, as it is hard to unveil the intrinsic structure of the whole sample space in the framework of mini-batch Stochastic Gradient Descent (SGD). To tackle this problem, in this paper, we propose a novel unsupervised deep hashing model, named Deep Variational Binaries (DVB). The conditional auto-encoding variational Bayesian networks are introduced in this work as the generative model to exploit the feature space structure of the training data using the latent variables. Integrating the probabilistic inference process with hashing objectives, the proposed DVB model estimates the statistics of data representations, and thus produces compact binary codes. Experimental results on three benchmark datasets, i.e., CIFAR-10, SUN-397 and NUS-WIDE, demonstrate that DVB outperforms state-of-the-art unsupervised hashing methods with significant margins.
Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration

Stochastic gradient Hamiltonian Monte Carlo (SGHMC) is a variant of stochastic gradient with momentum where a controlled and properly scaled Gaussian noise is added to the stochastic gradients to steer the iterates towards a global minimum. Many works reported its empirical success in practice for solving stochastic non-convex optimization problems, in particular it has been observed to outperform overdamped Langevin Monte Carlo-based methods such as stochastic gradient Langevin dynamics (SGLD) in many applications. Although asymptotic global convergence properties of SGHMC are well known, its finite-time performance is not well-understood. In this work, we study two variants of SGHMC based on two alternative discretizations of the underdamped Langevin diffusion. We provide finite-time performance bounds for the global convergence of both SGHMC variants for solving stochastic non-convex optimization problems with explicit constants. Our results lead to non-asymptotic guarantees for both population and empirical risk minimization problems. For a fixed target accuracy level, on a class of non-convex problems, we obtain complexity bounds for SGHMC that can be tighter than those for SGLD. These results show that acceleration with momentum is possible in the context of global non-convex optimization.
Spinal Instrumentation Rescue with Cement Augmentation

BACKGROUND AND PURPOSE: Altered biomechanics or bone fragility or both contribute to spine instrumentation failure. Although revision surgery is frequently required, minimally invasive alternatives may be feasible. We report the largest to-date series of percutaneous fluoroscopically guided vertebral cement augmentation procedures to address feasibility, safety, results and a variety of spinal instrumentation failure conditions. MATERIALS AND METHODS: A consecutive series of 31 fluoroscopically guided vertebral augmentation procedures in 29 patients were performed to address screw loosening (42 screws), cage subsidence (7 cages), and fracture within (12 cases) or adjacent to (11 cases) the instrumented segment. Instrumentation failure was deemed clinically relevant when resulting in pain or jeopardizing spinal biomechanical stability. The main study end point was the rate of revision surgery avoidance; feasibility and safety were assessed by prospective recording of periprocedural technical and clinical complications; and clinical effect was measured at 1 month with the Patient Global Impression of Change score. RESULTS: All except 1 procedure was technically feasible. No periprocedural complications occurred. Clinical and radiologic follow-up was available in 28 patients (median, 16 months) and 30 procedures. Revision surgery was avoided in 23/28 (82%) patients, and a global clinical benefit (Patient Global Impression of Change, 5–7) was reported in 26/30 (87%) cases at 1-month follow-up, while no substantial change (Patient Global Impression of Change, 4) was reported in 3/30 (10%), and worsening status (Patient Global Impression of Change, 3), in 1/30 (3%). CONCLUSIONS: Our experience supports the feasibility of percutaneous vertebral augmentation in the treatment of several clinically relevant spinal instrumentation failure conditions, with excellent safety and efficacy profiles, both in avoidance of revision surgery and for pain palliation.
Effectiveness of Platelet Function Analyzer-100 for Laboratory Detection of Anti-Platelet Drug-Induced Platelet Dysfunction

Background High on-treatment platelet reactivity (HTPR) is the phenomenon wherein patients exhibit normal platelet activity in laboratory testing despite adequate adherence to anti-platelet treatment. We investigated the detection rates of Platelet Function Analyzer (PFA)-100 (Dade Behring AG, Düdingen, Switzerland) for drug-induced platelet dysfunction and analyzed potential contributors to HTPR with practical PFA-100 data over six years. Methods We used data from 6,957 patients who underwent PFA-100 testing after receiving aspirin, clopidogrel, or non-steroidal anti-inflammatory drugs (NSAIDs). Of these, 6,163 patients were tested with only the collagen/epinephrine cartridge (Col/EPI) of PFA-100; 794 were tested with both Col/EPI and the collagen/ADP cartridge (Col/ADP). We calculated PFA-100 closure time (CT) for each drug and compared the clinical and laboratory characteristics of the patients with prolonged CTs and normal CTs (i.e., HTPR). Results In Col/EPI, 73.2% (365/499), 72.6% (390/537), and 55.3% (3,442/6,228) patients showed prolonged CTs for aspirin, clopidogrel, and NSAIDs, respectively. In Col/ADP, prolonged CTs were observed in 37.4% (34/91), 43.2% (35/81), and 29.6% (200/676) of patients receiving aspirin, clopidogrel, and NSAIDs, respectively. Of the patients tested with both cartridges, 88.9% (48/54), 95.3% (41/43), and 89.0% (577/648) of the patients receiving aspirin, clopidogrel, and NSAIDs had prolonged CTs, and 10.0% (79/794) showed normal CTs regardless of drugs. For clopidogrel users (both cartridges), there were more patients with malignancies in the normal CT than prolonged CT group. Conclusions PFA-100 is not sufficiently effective for laboratory screening of drug-induced platelet dysfunction. Malignancy may contribute to clopidogrel-related HTPR in PFA-100.
Compact QC-LDPC Block and SC-LDPC Convolutional Codes for Low-Latency Communications

Low decoding latency and complexity are two important requirements of channel codes used in many applications, like machine-to-machine communications. In this paper, we show how these requirements can be fulfilled by using some special quasi-cyclic low-density parity-check block codes and spatially coupled low-density parity-check convolutional codes that we denote as compact. They are defined by parity-check matrices designed according to a recent approach based on sequentially multiplied columns. This method allows obtaining codes with girth up to 12. Many numerical examples of practical codes are provided.
A Comparative Study on Improving Quality of Service in Networks Carrying Multi-Service Level Data over Resource-Limited Multi-Hop Wireless Networks

—Multi-hop Wireless Networks (MWNs) based on Single-Radio Single-Channel (SRSC) networks will likely attract more deployments if the required Quality of Service (QoS) can be provided. Carrier sense multiple access with collision avoidance (CSMA/CA) in MWNs faces an increase in packet loss and contention with an increase in the number of hops to reach the destination. This results in an increase in collisions and a wastage of bandwidth. The Distributed Coordination Function (DCF) treats all data the same, while the Enhanced Distributed Channel Access (EDCA) method was mainly designed for delay-sensitive applications to provide multi-service differentiation. EDCA is known to provide unfairness, where higher-priority data can starve low-priority data under high loads. We have shown that Schedule-BeforeContention (SBC) packet scheduling strategies can address the limitation of EDCA, but it is still unclear which SBC strategy provides the best performance in distributed networks. Good scheduling mechanisms can reduce packet loss to the maximum, as well as avoid unnecessary delay. In this paper, we assert that the queue selection mechanism plays a critical role in the achievable Quality of Service (QoS). A comparative analysis of four SBC mechanisms is carried out and it is found that the transmission of lower-priority data helps lower packet loss, as this uses larger contention window ranges for back-off.
Functional differences of short and long isoforms of spastin harboring missense mutation

ABSTRACT Mutations of the SPG4 (SPAST) gene encoding for spastin protein are the main causes of hereditary spastic paraplegia. Spastin binds to microtubules and severs them through the enzymatic activity of its AAA domain. Several missense mutations located in this domain lead to stable, nonsevering spastins that decorate a subset of microtubules, suggesting a possible negative gain-of-function mechanism for these mutants. Of the two main isoforms of spastin, only mutations of the long isoform, M1, are supposed to be involved in the onset of the pathology, leaving the role of the ubiquitously expressed shorter one, M87, not fully investigated and understood. Here, we show that two isoforms of spastin harboring the same missense mutation bind and bundle different subsets of microtubules in HeLa cells, and likely stabilize them by increasing the level of acetylated tubulin. However, only mutated M1 has the ability to interact with wild-type M1, and decorates a subset of perinuclear microtubules associated with the endoplasmic reticulum that display higher resistance to microtubule depolymerization and increased intracellular ionic strength, compared with those decorated by mutated M87. We further show that only mutated M1 decorates microtubules of proximal axons and dendrites, and strongly impairs axonal transport in cortical neurons through a mechanism likely independent of the microtubule-severing activity of this protein. Summary: Long and short isoforms of spastin (SPG4) harboring the same missense mutation show different intracellular localization, resistance to pharmacological treatments and effects on axonal cargo transport.
Cost-effectiveness of roflumilast as an add-on to triple inhaled therapy vs triple inhaled therapy in patients with severe and very severe COPD associated with chronic bronchitis in the UK

Purpose Patients with severe COPD are at high risk of experiencing disease exacerbations, which require additional treatment and are associated with elevated mortality and increased risk of future exacerbations. Some patients continue to experience exacerbations despite receiving triple inhaled therapy (ICS plus LAMA plus LABA). Roflumilast is recommended by the Global Initiative for Chronic Obstructive Lung Disease as add-on treatment to triple inhaled therapy for these patients. This cost-effectiveness analysis compared costs and quality-adjusted life-years for roflumilast plus triple inhaled therapy vs triple inhaled therapy alone, using data from the REACT and RE2SPOND trials. Patients and methods Patients included in the analysis had severe to very severe COPD, FEV1 <50% predicted, symptoms of chronic bronchitis and ≥2 exacerbations per year. Our model was adapted from a previously published and validated model, and the analyses conducted from a UK National Health Service perspective. A scenario analysis considered a subset of patients who had experienced at least one COPD-related hospitalization within the previous year. Results Roflumilast as add-on to triple inhaled therapy was associated with non-significant reductions in rates of both moderate and severe exacerbations compared with triple inhaled therapy alone. The incremental cost-effectiveness ratio (ICER) for roflumilast as add-on to triple inhaled therapy was £24,976. In patients who had experienced previous hospitalization, roflumilast was associated with a non-significant reduction in the rate of moderate exacerbations, and a statistically significant reduction in the rate of severe exacerbations. The ICER for roflumilast in this population was £7,087. Conclusions Roflumilast is a cost-effective treatment option for patients with severe or very severe COPD, chronic bronchitis, and a history of exacerbations. The availability of roflumilast as add-on treatment addresses an important unmet need in this patient population.