NT-proBNP is emerging as a novel tool for improving management of patients with heart failure (HF). The concept of health-related outcomes as the primary endpoint for therapeutic intervention in ...chronic disease, such as HF, should be the focal point going forward.
We conducted a prospective real-world study in heart failure with reduced ejection fraction (HFrEF) patients. The main target was to evaluate the impact on patient's health-related outcomes of a personalized medical follow-up procedure, based on a laboratory model of risk stratification supported by NT-proBNP. One hundred and five consecutive patients admitted to the Hospital Heart-Failure unit were stratified into three groups (low, medium, and high risk) and prospective follow-ups during the 12 months post discharge.
It was found that patients under this new approach experienced early and robust improvements in patient health-related outcomes with consistency in most domains which persisted beyond 12 months post follow-up. Improvements in health related quality of life score (HRQLS) was observed over the time of the study. After 6 months we found a significant improvement in HRQLS of 18.2% (from 76.5 ± 22.4 to 95.0 ± 15.7) and 14.4% (from 76.5 ± 22.4 to 96.3 ± 15.9) after 12 months of follow-up (p < 0.001). The highest improvements were found in the symptom severity domain where patients reported an improvement of 22.6% after 6 months and 18.9% after 12 months (p < 0.001). The lowest scores were reported in the physical domain with increase of 11.0% and 4.3% after 6 months and 12 months (p = 0.089). Psychosocial domain and the ability to carry out the activities of normal life showed improvement as well.
Our strategy based on NT-proBNP optimizes HFrEF management and represents a major new approach for clinical laboratories to improve patient health-related outcomes in HFrEF.
Currently, Coronavirus disease (COVID-19), one of the most infectious diseases in the 21st century, is diagnosed using RT-PCR testing, CT scans and/or Chest X-Ray (CXR) images. CT (Computed ...Tomography) scanners and RT-PCR testing are not available in most medical centers and hence in many cases CXR images become the most time/cost effective tool for assisting clinicians in making decisions. Deep learning neural networks have a great potential for building COVID-19 triage systems and detecting COVID-19 patients, especially patients with low severity. Unfortunately, current databases do not allow building such systems as they are highly heterogeneous and biased towards severe cases. This article is threefold: (i) we demystify the high sensitivities achieved by most recent COVID-19 classification models, (ii) under a close collaboration with Hospital Universitario Clínico San Cecilio, Granada, Spain, we built COVIDGR-1.0, a homogeneous and balanced database that includes all levelsof severity, from normal with Positive RT-PCR, Mild, Moderate to Severe. COVIDGR-1.0 contains 426 positive and 426 negative PA (PosteroAnterior) CXR views and (iii) we propose COVID Smart Data based Network (COVID-SDNet) methodology for improving the generalization capacity of COVID-classification models. Our approach reaches good and stable results with an accuracy of 97.72% ± 0.95%, 86.90% ± 3.20%, 61.80% ± 5.49% in severe, moderate and mild COVID-19 severity levels. Our approach could help in the early detection of COVID-19. COVIDGR-1.0 along with the severity level labels are available to the scientific community through this link https://dasci.es/es/transferencia/ open-data/covidgr/.
Nab-paclitaxel and gemcitabine have demonstrated a survival benefit over gemcitabine alone in advanced pancreatic cancer (PDA). This study aimed to investigate the clinical, biological, and imaging ...effects of the regimen in patients with operable PDA.
Patients with operable PDA received two cycles of nab-paclitaxel and gemcitabine before surgical resection. FDG-PET and CA19.9 tumour marker levels were used to measure clinical activity. Effects on tumour stroma were determined by endoscopic ultrasound (EUS) elastography. The collagen content and architecture as well as density of cancer-associated fibroblasts (CAFs) were determined in the resected surgical specimen and compared with a group of untreated and treated with conventional chemoradiation therapy controls. A co-clinical study in a mouse model of PDA was conducted to differentiate between the effects of nab-paclitaxel and gemcitabine.
A total of 16 patients were enrolled. Treatment resulted in significant antitumour effects with 50% of patients achieving a >75% decrease in circulating CA19.9 tumour marker and a response by FDG-PET. There was also a significant decrement in tumour stiffness as measured by EUS elastography. Seven of 12 patients who completed treatment and were operated had major pathological regressions. Analysis of residual tumours showed a marked disorganised collagen with a very low density of CAF, which was not observed in the untreated or conventionally treated control groups. The preclinical co-clinical study showed that these effects were specific of nab-paclitaxel and not gemcitabine.
These data suggest that nab-paclitaxel and gemcitabine decreases CAF content inducing a marked alteration in cancer stroma that results in tumour softening. This regimen should be studied in patients with operable PDA.
We present a two-stage methodology called Positions and Covering (P&C) to solve the two-dimensional bin packing problem (2D-BPP). The objective of this classical combinatorial NP-hard problem is to ...pack a set of items (small rectangles) in the minimum number of bins (larger rectangles). The first stage is the key-point of the Positions and Covering, where for each item, it is generated in a pseudo-polynomial way a set of valid positions that indicate the possible ways of packing the item into the bin. In the second stage, a new set-covering formulation, strengthen with three sets of valid inequalities, is used to select the optimal non-overlapping configuration of items for each bin. Experimental results for the P&C method are presented and compared with some of the best algorithms in the literature for small and medium size instances. Furthermore, we are considering both cases of the 2D-BPP, with and without rotations of the items by 90°. To the best of our knowledge, this is one of the first exact approaches to obtain optimal solutions for the rotation case.
We use the Positions and Covering methodology to obtain exact solutions for the two-dimensional, non-guillotine restricted, strip packing problem. In this classical NP-hard problem, a given set of ...rectangular items has to be packed into a strip of fixed weight and infinite height. The objective consists in determining the minimum height of the strip. The Positions and Covering methodology is based on a two-stage procedure. First, it is generated, in a pseudo-polynomial way, a set of valid positions in which an item can be packed into the strip. Then, by using a set-covering formulation, the best configuration of items into the strip is selected. Based on the literature benchmark, experimental results validate the quality of the solutions and method's effectiveness for small and medium-size instances. To the best of our knowledge, this is the first approach that generates optimal solutions for some literature instances for which the optimal solution was unknown before this study.
Background. Transient elastometry (TE) is accurate for detecting significant liver fibrosis and cirrhosis in hepatitis C virus (HCV)–monoinfected patients. However, this procedure has been ...insufficiently validated in patients with human immunodeficiency virus (HIV) and HCV coinfection. The purpose of this study was to validate reported cutoff values of TE that discriminate significant liver fibrosis and cirrhosis in HIV-HCV–coinfected subjects. Methods. Liver stiffness measurements were obtained for 169 HIV-HCV–coinfected adult patients who had undergone a liver biopsy or who had received a nonhistologic diagnosis of cirrhosis within 12 months before or after a liver stiffness measurement. Patients had received no prior therapy for HCV infection. Results. TE measurements ranged from 3.6 kPa to 75 kPa. The area under the receiver operating characteristic curve was 0.87 (95% confidence interval, 0.84–0.93) for significant liver fibrosis and 0.95 (95% confidence interval, 0.92–0.99) for cirrhosis. To diagnose significant liver fibrosis, a cutoff value of 7.2 kPa was associated with a positive predictive value of 88% and a negative predictive value of 75%. Thirty-four patients (20%) were misclassified when this cutoff value was used. Thirteen (24%) of 54 patients with liver stiffness values <7.2 kPa had significant liver fibrosis detected by liver biopsy. To diagnose cirrhosis, a cutoff value of 14.6 kPa was associated with a positive predictive value of 86% and a negative predictive value of 94%. Thus, 13 patients (10%) had disease that was misclassified using this cutoff value. Conclusions. We found that the diagnostic accuracy of TE was high for detecting cirrhosis and good for diagnosis of significant liver fibrosis. However, the performance of TE was low for discriminating mild fibrosis from significant liver fibrosis, which might limit the applicability of this technique in clinical practice.
Objective: The APOA2 gene has been associated with obesity and insulin resistance (IR) in animal and human studies with controversial results. We have reported an APOA2-saturated fat interaction ...determining body mass index (BMI) and obesity in American populations. This work aims to extend our findings to European and Asian populations. Methods: Cross-sectional study in 4602 subjects from two independent populations: a high-cardiovascular risk Mediterranean population (n=907 men and women; aged 67+/-6 years) and a multiethnic Asian population (n=2506 Chinese, n=605 Malays and n=494 Asian Indians; aged 39+/-12 years) participating in a Singapore National Health Survey. Anthropometric, clinical, biochemical, lifestyle and dietary variables were determined. Homeostasis model assessment of insulin resistance was used in Asians. We analyzed gene-diet interactions between the APOA2 -265T>C polymorphism and saturated fat intake (<or 22 g per day) on anthropometric measures and IR. Results: Frequency of CC (homozygous for the minor allele) subjects differed among populations (1-15%). We confirmed a recessive effect of the APOA2 polymorphism and replicated the APOA2-saturated fat interaction on body weight. In Mediterranean individuals, the CC genotype was associated with a 6.8% greater BMI in those consuming a high (P=0.018), but not a low (P=0.316) saturated fat diet. Likewise, the CC genotype was significantly associated with higher obesity prevalence in Chinese and Asian Indians only, with a high-saturated fat intake (P=0.036). We also found a significant APOA2-saturated fat interaction in determining IR in Chinese and Asian Indians (P=0.026). Conclusion: The influence of the APOA2 -265T>C polymorphism on body-weight-related measures was modulated by saturated fat in Mediterranean and Asian populations.
Ubiquitin ligases control the degradation of core clock proteins to govern the speed and resetting properties of the circadian pacemaker. However, few studies have addressed their potential to ...regulate other cellular events within clock neurons beyond clock protein turnover. Here, we report that the ubiquitin ligase, UBR4/POE, strengthens the central pacemaker by facilitating neuropeptide trafficking in clock neurons and promoting network synchrony. Ubr4-deficient mice are resistant to jetlag, whereas poe knockdown flies are prone to arrhythmicity, behaviors reflective of the reduced axonal trafficking of circadian neuropeptides. At the cellular level, Ubr4 ablation impairs the export of secreted proteins from the Golgi apparatus by reducing the expression of Coronin 7, which is required for budding of Golgi-derived transport vesicles. In summary, UBR4/POE fulfills a conserved and unexpected role in the vesicular trafficking of neuropeptides, a function that has important implications for circadian clock synchrony and circuit-level signal processing.
Song learning has evolved within several avian groups. Although its evolutionary advantage is not clear, it has been proposed that song learning may be advantageous in allowing birds to adapt their ...songs to the local acoustic environment. To test this hypothesis, we analysed patterns of song adjustment to noisy environments and explored their possible link to song learning. Bird vocalizations can be masked by low‐frequency noise, and birds respond to this by singing higher‐pitched songs. Most reports of this strategy involve oscines, a group of birds with learning‐based song variability, and it is doubtful whether species that lack song learning (e.g. suboscines) can adjust their songs to noisy environments. We address this question by comparing the degree of song adjustment to noise in a large sample of oscines (17 populations, 14 species) and suboscines (11 populations, 7 species), recorded in Brazil (Manaus, Brasilia and Curitiba) and Mexico City. We found a significantly stronger association between minimum song frequency and noise levels (effect size) in oscines than in suboscines, suggesting a tighter match in oscines between song transmission capacity and ambient acoustics. Suboscines may be more vulnerable to acoustic pollution than oscines and thus less capable of colonizing cities or acoustically novel habitats. Additionally, we found that species whose song frequency was more divergent between populations showed tighter noise–song frequency associations. Our results suggest that song learning and/or song plasticity allows adaptation to new habitats and that this selective advantage may be linked to the evolution of song learning and plasticity.
Microbial fuel cells (MFCs) use bacteria to convert the chemical energy of a particular substrate contained in wastewater into electrical energy. This is achieved when bacteria transfer electrons to ...an electrode rather than directly to an electron acceptor. Their technical feasibility has recently been proven and there is great enthusiasm in the scientific community that MFCs could provide a source of “green electricity” by exploiting domestic and industrial waste to generate power. By using organic matter in wastewater as a fuel, contaminants are removed from water while generating electricity. The design of new materials has led to increased levels of power being generated, particularly when compared with the levels possible using common materials. Moreover, the use of inexpensive materials, such as ceramic membranes or non-platinum catalysts, makes it possible to obtain a feasible device to produce electricity. However, it is necessary to improve the performance of MFCs before they can be scaled up since, to date, their practical implementation is not feasible. Therefore, the global objective pursued by researchers is the development and evaluation of low cost catalysts (non-precious metals) for improving electron acceptor reduction (new cathodes), new biocompatible anodes and membranes, and novel configurations which improve the power and the wastewater treatment efficiency of MFCs, while reducing their cost. This review is intended to provide a critical and global vision of recent advances in microbial fuel cells and the potential applications of this technology. In this article, an overview over all aspects concerning MFC technology is provided, including issues such as new anode and cathode materials, types of membranes, MFC configurations, their application in the treatment of different types of wastewaters, bioenergy production, modeling and future perspectives.
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•· MFCs are a potentially promising technology for bioelectricity production.•Recent advances in MFC materials have contributed to enhancing their performance.•Power improvement and cost reduction of MFCs enlarge their range of application.•Modeling is a useful tool for microbial fuel cell optimization.
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