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Background: This study evaluates the diagnostic performance of high-sensitivity troponin using point-of-care testing (POCT) devices compared with main laboratory measurements for ruling out non-ST-elevation myocardial infarction (NSTEMI) in emergency department (ED) patients presenting with non-traumatic chest pain. Methods: This multicenter, observational, prospective, non-interventional study was conducted in two Spanish hospitals from 1 June to 31 December 2023 and included adult patients presenting with non-traumatic chest pain admitted to the ED. High-sensitivity troponin levels were measured using both the Siemens Atellica® VTLi POCT device and main laboratory testing, with data collected on analytical results and measurement times. Results: Of the 201 patients who met the inclusion criteria, a significant correlation was observed between the POCT and laboratory assays. The area under the curve (AUC) of the ROC curve was consistently greater than 0.9, indicating a high diagnostic accuracy for ruling out NSTEMI. In addition, measurement times were significantly reduced using POCT compared to the core laboratory. Conclusion: These results suggest that high-sensitivity troponin POCT devices offer comparable diagnostic performance to traditional laboratory methods for the diagnosis of NSTEMI in the emergency department, potentially speeding up clinical decisions and optimizing resource utilization. [ABSTRACT FROM AUTHOR]

Background: Myopia prevalence has been increasing in the last decades, and its pathological consequences, including myopic maculopathy and high myopia-associated optic neuropathy, are now one of the most common causes of visual impairment. It is estimated that by 2050, more than 50% of Europeans and Americans will be myopes, which is alarming due to the high morbidity of myopes over − 6.00D. Once myopia has appeared, there are different options with scientific evidence to try to slow the axial length growth. Ophthalmic lenses are the less invasive treatment to control myopia, and there is evidence about the efficacy of different designs, mainly in the Asiatic population. However, new designs have been launched, and it is not known if efficacy is the same between Asiatic and European subjects. Thus, we have set up a randomized, controlled, double-blind, and multicenter trial to investigate the efficacy of a new design of ophthalmic lenses for myopia control in European children. Methods: A 2-year prospective, multicenter, randomized controlled, and double-blind clinical trial is used to investigate the efficacy of a new design of ophthalmic lenses to slow the progression of myopia. Three hundred children aged from 6 to 13 years old will be recruited and randomly assigned to a study or control group. The study group will be composed of 150 children wearing MyoCare while the control group will be composed of 150 children wearing Clearview. The inclusion criteria will be myopia with a spherical equivalent between − 0.75D and − 5.00D, astigmatism < 1.50D, and anisometropia < 1.00D and having a historical evolution of at least − 0.50 The primary outcome is to compare the mean annual progression of the spherical equivalent between both groups. The secondary outcomes are axial length, choroidal thickness, phorias, and accommodative status of both groups. Discussion: This study will be the first randomized and controlled clinical trial in European children with spectacle lenses based on simultaneous competing defocus. The results will shed light on the clinical evidence of spectacle lenses relying on this new design for the management of myopia with results of efficacy in the non-Asiatic population. Trial registration: EU Clinical Trials Register (EudraCT) 2022–001696. Registered on 27 April 2022. ClinicalTrials.gov NCT05919654. Registered on 26 June 2023. [ABSTRACT FROM AUTHOR]

Context: Machine Learning (ML) is a disruptive concept that has given rise to and generated interest in different applications in many fields of study. The purpose of Machine Learning is to solve real-life problems by automatically learning and improving from experience without being explicitly programmed for a specific problem, but for a generic type of problem. This article approaches the different applications of ML in a series of econometric methods. Objective: The objective of this research is to identify the latest applications and do a comparative study of the performance of econometric and ML models. The study aimed to find empirical evidence for the performance of ML algorithms being superior to traditional econometric models. The Methodology of systematic mapping of literature has been followed to carry out this research, according to the guidelines established by [39], and [58] that facilitate the identification of studies published about this subject. Results: The results show, that in most cases ML outperforms econometric models, while in other cases the best performance has been achieved by combining traditional methods and ML applications. Conclusion: inclusion and exclusions criteria have been applied and 52 articles closely related articles have been reviewed. The conclusion drawn from this research is that it is a field that is growing, which is something that is well known nowadays and that there is no certainty as to the performance of ML being always superior to that of econometric models. [ABSTRACT FROM AUTHOR]

This paper presents a methodology that permits to automate binary classification using the minimum possible number of attributes. In this methodology, the success of the binary prediction does not lie in the accuracy of an algorithm but in the evaluation metrics, which give information about the goodness of fit; which is an important factor when the data batch is unbalanced. The proposed methodology assesses the possible biases in identifying one algorithm as the best performer when considering the goodness of fit of an algorithm through evaluation metrics. The dimension of data has been reduced through the cumulative explained variance. Then, the performance of six machine learning classification models has been compared through Matthew correlation coefficient (MCC), area under curve – receiver operating characteristic (ROC-AUC), and area under curve – precision-recall (AUC-PR). The results show graphically and numerically how the evaluation metrics interfere with the most optimal outcome of an algorithm. The algorithms with the best performance in terms of evaluation metrics have been random forest and gradient boosting. In the imbalanced datasets, MCC has provided better prediction results than ROC-AUC or AUC-PR. The proposed methodology is adapted to the case of bankruptcy prediction. [ABSTRACT FROM AUTHOR]

Background: Mexico is on the top five countries with the highest number of TB cases in America continent, nevertheless, information about genotypes circulating is practically unknown. Considering the above this study aims to characterize the genetic diversity of TB in the city of Veracruz, México.Methods: A cross-sectional study was conducted among positive smear samples from patients living in Veracruz City, samples were cultured, and first-line drug profiles determined. Genotyping was made by spoligotyping and MIRU-VNTR 24 loci. Associations of lineages, clusters, and variables were also analyzed.Results: Among the 202 isolates analyzed resistance to at least one drug was observed in 60 (30%) isolates and 41(20%) were multidrug-resistant. Three major lineages were identified: L4/Euro-American (88%), L1/Indo-Oceanic (9%), and L2/East Asian (3%). The Euro-American lineage included more than six sublineages, the most abundant were: H (32%), T (23%), LAM (18%), and X (12%). 140 isolates (70%) were placed in 42 SITs patterns.Conclusions: These results provide the first baseline data on the genetic structure of TB in the city of Veracruz. Sublineages H, X and LAM were predominant; however, it was founded an important diversity of genotypes that could contribute to the dispersion of TB and explain the high prevalence. This information might be useful for the development of further interventions to reduce impact of TB. [ABSTRACT FROM AUTHOR]

Dendrimeric peptide constructs based on a lysine core that comprises both B- and T-cell epitopes of foot-and-mouth disease virus (FMDV) have proven a successful strategy for the development of FMD vaccines. Specifically, B2T dendrimers displaying two copies of the major type O FMDV antigenic B-cell epitope located on the virus capsid [VP1 (140–158)], covalently linked to a heterotypic T-cell epitope from either non-structural protein 3A [3A (21–35)] or 3D [3D (56–70)], named B2T-3A and B2T-3D, respectively, elicit high levels of neutralizing antibodies (nAbs) and IFN-γ-producing cells in pigs. To assess whether the inclusion and orientation of T-3A and T-3D T-cell epitopes in a single molecule could modulate immunogenicity, dendrimers with T epitopes juxtaposed in both possible orientations, i.e., constructs B2TT-3A3D and B2TT-3D3A, were made and tested in pigs. Both dendrimers elicited high nAbs titers that broadly neutralized type O FMDVs, although B2TT-3D3A did not respond to boosting, and induced lower IgGs titers, in particular IgG2, than B2TT-3A3D. Pigs immunized with B2, a control dendrimer displaying two B-cell epitope copies and no T-cell epitope, gave no nABs, confirming T-3A and T-3D as T helper epitopes. The T-3D peptide was found to be an immunodominant, as it produced more IFN-γ expressing cells than T-3A in the in vitro recall assay. Besides, in pigs immunized with the different dendrimeric peptides, CD4+ T-cells were the major subset contributing to IFN-γ expression upon in vitro recall, and depletion of CD4+ cells from PBMCs abolished the production of this cytokine. Most CD4+IFN-γ+ cells showed a memory (CD4+2E3−) and a multifunctional phenotype, as they expressed both IFN-γ and TNF-α, suggesting that the peptides induced a potent Th1 pro-inflammatory response. Furthermore, not only the presence, but also the orientation of T-cell epitopes influenced the T-cell response, as B2TT-3D3A and B2 groups had fewer cells expressing both cytokines. These results help understand how B2T-type dendrimers triggers T-cell populations, highlighting their potential as next-generation FMD vaccines. [ABSTRACT FROM AUTHOR]

Tuberculosis is still a global public health problem, with an estimated 10 million new cases and 1.6 million deaths in 2017. Of all humans infected with M. tuberculosis, only 10-15% will develop active tuberculosis disease during their lifetime, and data suggest that along with environmental factors, genetic factors influence susceptibility to develop active disease. Toll-like receptors (TLRs) are pattern recognition receptors that play a central role in the initiation and shaping of adaptive immune responses, and several TLRs have been shown to recognize mycobacterial components. In this work, we performed a case-control study to determine if common single nucleotide polymorphisms (SNPs) in genes encoding TLRs 1, 2, 4, 6, and 10 are associated with susceptibility to develop active tuberculosis in population from the state of Veracruz, Mexico. The study included 279 cases and 569 controls. The results show that the frequency of two SNPs in TLR4 was significantly higher in controls than in tuberculosis patients. The minor allele (G) of rs4986790 in TLR4 (D299G) decreased the risk of active tuberculosis in the allelic (A vs. G, OR = 0.31, 95%CI = 0.09-0.81, p = 0.01) and in the dominant genetic model (AA vs. GG+AG, OR = 0.26, 95%CI = 0.09-0.77, p = 0.02). Similarly, the minor allele (T) of rs4986791 in TLR4 (T399I) decreased the risk of active disease in the allelic model (C vs. T, OR = 0.29, 95%CI = 0.10-0.90, p = 0.03). We did not find an association of SNPs in TLR1 (N248S), TLR2 (R753Q), TLR6 (S249P), and TLR10 (A153S and V298I) with tuberculosis disease. These results suggest that in this population, genetic variants of TLR4 affect the susceptibility for suffering active tuberculosis disease. [ABSTRACT FROM AUTHOR]

Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (∼3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling), which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s) proving that with as little as 0.5s an accuracy of over 50% can be achieved. [ABSTRACT FROM AUTHOR]

Automatic speech recognition (ASR) systems are used daily by millions of people worldwide to dictate messages, control devices, initiate searches or to facilitate data input in small devices. The user experience in these scenarios depends on the quality of the speech transcriptions and on the responsiveness of the system. For multilingual users, a further obstacle to natural interaction is the monolingual character of many ASR systems, in which users are constrained to a single preset language. In this work, we present an end-to-end multi-language ASR architecture, developed and deployed at Google, that allows users to select arbitrary combinations of spoken languages. We leverage recent advances in language identification and a novel method of real-time language selection to achieve similar recognition accuracy and nearly-identical latency characteristics as a monolingual system. [ABSTRACT FROM PUBLISHER]

Background Patients in fulminant hepatic failure currently do not have a temporary means of support while awaiting liver transplantation. A potential therapeutic approach for such patients is the use of extracorporeal perfusion with porcine livers as a form of 'liver dialysis'. During a 72-h extracorporeal perfusion of porcine livers with human blood, porcine Kupffer cells bind to and phagocytose human red blood cells (h RBC) causing the hematocrit to decrease to 2.5% of the original value. Our laboratory has identified porcine sialoadhesin expressed on Kupffer cells as the lectin responsible for binding N-acetylneuraminic acid on the surface of the h RBC. We evaluated whether blocking porcine sialoadhesin prevents the recognition and subsequent destruction of h RBCs seen during extracorporeal porcine liver xenoperfusion. Methods Ex vivo studies were performed using wild type pig livers perfused with isolated h RBCs for 72-h in the presence of an anti-porcine sialoadhesin antibody or isotype control. Results The addition of an anti-porcine sialoadhesin antibody to an extracorporeal porcine liver xenoperfusion model reduces the loss of h RBC over a 72-h period. Sustained liver function was demonstrated throughout the perfusion. Conclusions This study illustrates the role of sialoadhesin in mediating the destruction of h RBCs in an extracorporeal porcine liver xenoperfusion model. [ABSTRACT FROM AUTHOR]

Introduction and Objectives: We report the results of a randomized controlled trial comparing three different lithotriptors using semirigid ureteroscopy (URS) for distal ureteral stones. Methods: Between September 2009 and November 2010 69 patients undergoing ureteroscopy were randomized to three groups: LithoClast classic (Group 1), Holmium Laser (Group 2), and StoneBreaker™ (Group 3). A 7.5F semirigid ureteroscope was used in all procedures. The primary outcome was differences in fragmentation time. Secondary outcomes were stone-free rates, intraoperative complications, stone-up migration, hospital stay, analgesic requirement, and need for auxiliary procedures. Patients were followed up at 15 days, 30 days, and 3 months. The stone-free status was defined with noncontrast computed tomography performed at first control. Univariate and multivariate analysis were performed to determine clinical and surgical factors that have direct impact on the success of ureteroscopy. Chi-square test and Analysis of Covariance (ANCOVA) tests were used for statistical comparisons. Results: There were no differences between sociodemographic variables. Average stone size was 7.17±2.04 mm in Group 1; 7.89±2.73 mm in Group 2; and 7.79±2.97 mm in Group 3 ( p=0.79). Fragmentation time were similar between lithotriptors; 27.12±4.07 minutes in Lithoclast group; 21.78±2.81 minutes in Laser group, and 27.14±4.71 minutes in StoneBreaker group ( p=0.74). Stone-free rates were 96%±11.18% (group 1), 96.9%±8% (group 2), and 96.9%±8.4% (group 3) ( p=0.1). No difference was observed in stone-up migration, postoperative Double-J stent placement, or auxiliary procedures. Stone size and the placement of a second working wire were associated with shorter fragmentation time ( p<0.01). Conclusions: The three lithotripsy devices evaluated behaved similarly in terms of the ability to fragment stones, and were equally effective for distal ureteral stones. Adequate fragmentation and fragment removal are mainly dependant on stone size and surgical technique (use of auxiliary wire). [ABSTRACT FROM AUTHOR]

This letter proposes a new modeling approach for the Total Variability subspace within a Language Recognition task. Motivated by previous works in directional statistics, von Mises–Fisher distributions are used for assigning language-conditioned probabilities to language data, assumed to be spherically distributed in this subspace. The two proposed methods use Kernel Density Functions or Finite Mixture Models of such distributions. Experiments conducted on NIST LRE 2009 show that the proposed techniques significantly outperform the baseline cosine distance approach in most of the considered experimental conditions, including different speech conditions, durations and the presence of unseen languages. [ABSTRACT FROM PUBLISHER]

This paper presents the systems submitted by the ATVS Biometric Recognition Group to the 2009 Language Recognition Evaluation (LRE'09), organized by NIST. New challenges included in this LRE edition can be summarized by three main differences with respect to past evaluations. First, the number of languages to be recognized expanded to 23 languages from 14 in 2007, and 7 in 2005. Second, the data variability has been increased by including telephone speech excerpts extracted from Voice of America (VOA) radio broadcasts through Internet in addition to conversational telephone speech (CTS). The third difference was the volume of data, involving in this evaluation up to 2 terabytes of speech data for development, which is an order of magnitude greater than past evaluations. LRE'09 thus required participants to develop robust systems able not only to successfully face the session variability problem but also to do it with reasonable computational resources. ATVS participation consisted of state-of-the-art acoustic and high-level systems focussing on these issues. Furthermore, the problem of finding a proper combination and calibration of the information obtained at different levels of the speech signal was widely explored in this submission. In this paper, two original contributions were developed. The first contribution was applying a session variability compensation scheme based on factor analysis (FA) within the statistics domain into a SVM-supervector (SVM-SV) approach. The second contribution was the employment of a novel back-end based on anchor models in order to fuse individual systems prior to one-versus-all calibration via logistic regression. Results both in development and evaluation corpora show the robustness and excellent performance of the submitted systems, exemplified by our system ranked second in the 30-second open-set condition, with remarkably scarce computational resources. [ABSTRACT FROM PUBLISHER]

Mass trapping has proven to be a powerful weapon in the control of Ceratitis capitata (Wiedemann), and its application in Mediterranean countries has currently increased notably as a control method. In this study, the efficacy of newly developed traps and dispensers of attractants were assessed with the aim of finding the best trap and set the lifetime of the dispensers, thus improving the total efficacy of mass trapping. Efficacy trials with six different types of traps and six different types of female dispensers were carried out. Moreover, the lifetime of three female dispensers, including a new attractant composition dispenser with n-methyl pyrrolidine, were studied. Results show significant differences among the trap types using female attractants, with an advantage of nearly 3 times more catches in best trap. Tested female dispensers showed no significant differences in efficacy between trimethylamine and putrescine attractants regard n-methyl pyrrolidine, however we observed differences in lifetime between dispensers. Thus, there are significant differences among different types of traps and dispensers in efficacy, and the appropriate selection of the trap and dispenser will improve the mass trapping results. [ABSTRACT FROM AUTHOR]

Swine monocytes constitute a heterogeneous population of cells which can be divided into four subsets based on the expression of SWC3, CD14, CD163 and swine leucocyte antigen (SLA) DR markers. These subsets appear to represent different maturation stages in a pathway along which these cells up-regulate the expression of SLA DR and CD163 antigens and reduce that of CD14. Differences in the expression of adhesion and costimulatory molecules are also patent, with a progressive increase in the expression of CD11a, wCD11R1, CD29, CD49d, CD61, CD1a and CD80/86, and a concomitant decrease in that of wCD11R2. Besides, these subsets differ in their capacity for tumour necrosis factor-α (TNF-α) production in response to lipopolysaccharide + interferon-γ. The CD163+ CD14− SLA DR+ subset produces higher amounts of TNF-α than the CD163− CD14+ SLA DR− subset, whereas CD163+ CD14+ SLA DR+ and CD163− CD14+ SLA DR+ subsets show intermediate values. CD163+ monocytes also display a higher ability to present soluble antigens to T cells than CD163− monocytes. [ABSTRACT FROM AUTHOR]