Miracle-dz/UniFAR-FTUs huggingface dataset:
Endobronchial Coils for Endoscopic Lung Volume Reduction: Best Practice Recommendations from an Expert Panel

Endobronchial coils are an additional treatment option for lung volume reduction in patients with severe emphysema. Patient selection should be focused on patients with severe emphysema on optimal medical therapy and with evidence of severe hyperinflation. The technique is suitable in a broad range of patients with emphysema; however, patients with paraseptal emphysema, large focal (giant) bullae, significant co-morbidity and airway-predominant disease should be avoided. Treatment involves placing between 10 and 14 coils by bronchoscopy in the selected treatment lobe, with 2 lobes being treated sequentially. Lobe selection for treatment should be based on quantitative computed tomography, and the lobes with the greatest destruction should be targeted (excluding the right middle lobe). The treatment results in an improvement in pulmonary function, exercise performance and quality of life, particularly in patients with severe hyperinflation (residual volume > 200% predicted) and upper-lobe heterogeneous emphysema, but will also be of benefit in lower-lobe predominant and homogeneous emphysema. Finally, it has an acceptable safety profile, although special attention has to be paid to coil-associated opacity which is an inflammatory response that occurs in some patients treated with endobronchial coils.
Association of Multivitamin and Mineral Supplementation and Risk of Cardiovascular Disease: A Systematic Review and Meta-Analysis

Background: Multiple studies have attempted to identify the association between multivitamin/mineral (MVM) supplementation and cardiovascular disease (CVD) outcomes, but the benefits remain controversial. We performed a systematic review and meta-analysis of the associations between MVM supplementation and various CVD outcomes, including coronary heart disease (CHD) and stroke. Methods and Results: We conducted a comprehensive search of Medline, Embase, and the Cochrane Library for studies published between January 1970 and August 2016. We included clinical trials and prospective cohort studies in the general population evaluating associations between MVM supplementation and CVD outcomes. Data extraction and quality assessment were independently conducted by 2 authors, and a third author resolved discrepancies. Eighteen studies with 2 019 862 participants and 18 363 326 person-years of follow-up were included in the analysis. Five studies specified the dose/type of MVM supplement and the rest did not. Overall, there was no association between MVM supplementation and CVD mortality (relative risk [RR], 1.00; 95% confidence interval [CI], 0.97–1.04), CHD mortality (RR, 1.02; 95% CI, 0.92–1.13), stroke mortality (RR, 0.95; 95% CI, 0.82–1.09), or stroke incidence (RR, 0.98; 95% CI, 0.91–1.05). There was no association between MVM supplements and CVD or CHD mortality in prespecified subgroups categorized by mean follow-up period, mean age, period of MVM use, sex, type of population, exclusion of patients with history of CHD, and adjustment for diet, adjustment for smoking, adjustment for physical activity, and study site. In contrast, MVM use did seem to be associated with a lower risk of CHD incidence (RR, 0.88; 95% CI, 0.79–0.97). However, this association did not remain significant in the pooled subgroup analysis of randomized controlled trials (RR, 0.97; 95% CI, 0.80–1.19). Conclusions: Our meta-analysis of clinical trials and prospective cohort studies demonstrates that MVM supplementation does not improve cardiovascular outcomes in the general population.
Surrogate-Assisted Retinal OCT Image Classification Based on Convolutional Neural Networks

Optical Coherence Tomography (OCT) is beco-ming one of the most important modalities for the noninvasive assessment of retinal eye diseases. As the number of acquired OCT volumes increases, automating the OCT image analysis is becoming increasingly relevant. In this paper, we propose a surrogate-assisted classification method to classify retinal OCT images automatically based on convolutional neural networks (CNNs). Image denoising is first performed to reduce the noise. Thresholding and morphological dilation are applied to extract the masks. The denoised images and the masks are then employed to generate a lot of surrogate images, which are used to train the CNN model. Finally, the prediction for a test image is determined by the average of the outputs from the trained CNN model on the surrogate images. The proposed method has been evaluated on different databases. The results (AUC of 0.9783 in the local database and AUC of 0.9856 in the Duke database) show that the proposed method is a very promising tool for classifying the retinal OCT images automatically.
Synovial macrophage M1 polarisation exacerbates experimental osteoarthritis partially through R-spondin-2

Objectives To investigate the roles and regulatory mechanisms of synovial macrophages and their polarisation in the development of osteoarthritis (OA). Methods Synovial tissues from normal patients and patients with OA were collected. M1 or M2-polarised macrophages in synovial tissues of patients with OA and OA mice were analysed by immunofluorescence and immunohistochemical staining. Mice with tuberous sclerosis complex 1 (TSC1) or Rheb deletion specifically in the myeloid lineage were generated and subjected to intra-articular injection of collagenase (collagenase-induced osteoarthritis, CIOA) and destabilisation of the medial meniscus (DMM) surgery to induce OA. Cartilage damage and osteophyte size were measured by Osteoarthritis Research Society International score and micro-CT, respectively. mRNA sequencing was performed in M1 and control macrophages. Mice and ATDC5 cells were treated with R-spondin-2 (Rspo2) or anti-Rspo2 to investigate the role of Rspo2 in OA. Results M1 but not M2-polarised macrophages accumulated in human and mouse OA synovial tissue. TSC1 deletion in the myeloid lineage constitutively activated mechanistic target of rapamycin complex 1 (mTORC1), increased M1 polarisation in synovial macrophages and exacerbated experimental OA in both CIOA and DMM models, while Rheb deletion inhibited mTORC1, enhanced M2 polarisation and alleviated CIOA in mice. The results show that promoting the macrophage M1 polarisation leads to exacerbation of experimental OA partially through secretion of Rspo2 and activation of β-catenin signalling in chondrocytes. Conclusions Synovial macrophage M1 polarisation exacerbates experimental CIOA partially through Rspo2. M1 macrophages and Rspo2 are potential therapeutic targets for OA treatment.
Progress on approaches to software defect prediction

Software defect prediction is one of the most popular research topics in software engineering. It aims to predict defect-prone software modules before defects are discovered, therefore it can be used to better prioritise software quality assurance effort. In recent years, especially for recent 3 years, many new defect prediction studies have been proposed. The goal of this study is to comprehensively review, analyse and discuss the state-of-the-art of defect prediction. The authors survey almost 70 representative defect prediction papers in recent years (January 2014-April 2017), most of which are published in the prominent software engineering journals and top conferences. The selected defect prediction papers are summarised to four aspects: machine learning-based prediction algorithms, manipulating the data, effort-aware prediction and empirical studies. The research community is still facing a number of challenges for building methods and many research opportunities exist. The identified challenges can give some practical guidelines for both software engineering researchers and practitioners in future software defect prediction.
A Discrete-Time Projection Neural Network for Sparse Signal Reconstruction With Application to Face Recognition

This paper deals with sparse signal reconstruction by designing a discrete-time projection neural network. Sparse signal reconstruction can be converted into an <inline-formula> <tex-math notation="LaTeX">$L_{1}$ </tex-math></inline-formula>-minimization problem, which can also be changed into the unconstrained basis pursuit denoising problem. To solve the <inline-formula> <tex-math notation="LaTeX">$L_{1}$ </tex-math></inline-formula>-minimization problem, an iterative algorithm is proposed based on the discrete-time projection neural network, and the global convergence of the algorithm is analyzed by using Lyapunov method. Experiments on sparse signal reconstruction and several popular face data sets are organized to illustrate the effectiveness and performance of the proposed algorithm. The experimental results show that the proposed algorithm is not only robust to different levels of sparsity and amplitude of signals and the noise pixels but also insensitive to the diverse values of scalar weight. Moreover, the value of the step size of the proposed algorithm is close to 1/2, thus a fast convergence rate is potentially possible. Furthermore, the proposed algorithm achieves better classification performance compared with some other algorithms for face recognition.
Rational Design of Redox‐Responsive and P‐gp‐Inhibitory Lipid Nanoparticles with High Entrapment of Paclitaxel for Tumor Therapy

An insufficient drug concentration at the target site and drug efflux resulting in poor efficacy is recognized as important obstacles in tumor treatment. Herein, novel lipid nanoparticles (LNPs) with redox‐responsive properties based on disulfide bond‐contained, quercetin (Qu)‐grafted glyceryl caprylate‐caprate (Gcc) are introduced (Qu‐SS‐Gcc LNPs). Qu‐SS‐Gcc LNPs show good entrapment of paclitaxel (PTX) due to π–π stacking between the aromatic rings of Qu and PTX. In vitro experiments indicate that Qu‐SS‐Gcc LNPs can selectively respond to high levels of reducing substances by breakdown of disulfide bonds, thus achieving rapid and efficient drug release, and only dissociate rapidly in tumor cells rather than in normal cells. Meanwhile, the Qu released concomitantly with the breakdown of disulfide bonds combines with P‐gp and inhibits the drug efflux triggered by P‐gp. Using an orthotopic 4T1 mouse mammary tumor model in BALB/c mice, PTX/Qu‐SS‐Gcc LNPs exhibit superior antitumor efficacy compared to Taxol, in addition better biosafety and inhibition of chemotherapy‐triggered P‐gp overexpression are achieved. Taken together, this work designs and implements redox‐responsive drug release and drug efflux inhibition in tumor cells via modified LNPs, which not only leads to efficient drug release but also solves the problem of drug efflux that exists in stimulus‐responsive systems.
Clinic-based evaluation study of the diagnostic accuracy of a dual rapid test for the screening of HIV and syphilis in pregnant women in Nigeria

Background Screening pregnant women for HIV and syphilis is recommended by WHO in order to reduce mother-to-child transmission. We evaluated the field performance, feasibility, and acceptability of a dual rapid diagnostic test (RDT) for HIV and syphilis test in antenatal clinic settings in Nigeria. Methods and findings Participants were recruited at 12 antenatal clinic sites in three states of Nigeria. All consenting individuals were tested according to the national HIV testing algorithm, as well as a dual RDT, the SD BIOLINE HIV/Syphilis Duo Test (Alere, USA), in the clinic. To determine sensitivity, specificity and concordance, whole blood samples were obtained for repeat RDT performance in the laboratory, as well as reference tests for HIV and syphilis. Dual test acceptability and operational characteristics were assessed among participants and clinic staff. The prevalence of HIV among the 4,551 enrollees was 3.0% (138/4551) using the national clinic-based HIV testing algorithm. Positive and negative percent agreement of the HIV component of the dual RDT were 100.0% (95% CI 99.7–100.0) and 99.9% (95% CI 99.7–100.0) respectively, when compared with the national rapid testing algorithm. The prevalence of syphilis, using TPHA as the reference test, was low at 0.09% (4/4550). The sensitivity of the syphilis component of the dual RDT could not be calculated as no positive results were observed for patients that were positive for syphilis by TPHA. Each of the only four TPHA-positive specimens had RPR titers of 1:1 (neat), indicative of non-active syphilis. The specificity of the syphilis component of the dual RDT was 99.9% (95% CI 99.8–100.0). The dual RDT received favorable feasibility ratings among antenatal care clinic staff. Acceptability among study participants was high with most women reporting preference for rapid dual HIV/syphilis testing. Conclusions The SD BIOLINE HIV/Syphilis Duo Test showed a high overall diagnostic accuracy for HIV and a high specificity for syphilis diagnosis in antenatal clinic settings. This study adds to a growing body of evidence that supports the clinic-based use of dual tests for HIV and syphilis among pregnant women.
Sampled-Data Control for the Synchronization of Boolean Control Networks

In this paper, we investigate the sampled-data state feedback control (SDSFC) for the synchronization of Boolean control networks (BCNs) under the configuration of drive-response coupling. Necessary and sufficient conditions for the complete synchronization of BCNs are obtained by the algebraic representations of logical dynamics. Based on the analysis of the sampling periods, we establish an algorithm to guarantee the synchronization of drive-response coupled BCNs by SDSFC. An example is given to illustrate the significance of the obtained results.
Prior Intravenous Stroke Thrombolysis Does Not Increase Complications of Carotid Endarterectomy

Background and Purpose— Carotid endarterectomy (CEA) is recommended within 14 days after carotid artery stroke to prevent recurrence. However, the optimal timing of CEA after intravenous thrombolysis (IVT) remains unclear. We studied the safety of CEA after IVT while taking into account both stroke recurrence and CEA-related complications. Methods— Patients who underwent IVT followed by CEA in Helsinki University Hospital 2005 to 2016 were withdrawn from prospectively collected registers. The incidence of stroke recurrence during the time between IVT and CEA, peri/postoperative stroke, hyperperfusion syndrome or drug-resistant high blood pressure, and 3-month outcome measured by modified Rankin Scale was recorded. Stroke patients treated with CEA without preceding IVT were used as controls. Results— Altogether 128 CEAs with preceding IVT and 777 CEAs for stroke without IVT were identified. The median time from IVT to CEA was 9 days (range, 0–349 days; interquartile range, 16). Seven patients (5.5%) underwent CEA within 24 hours, 20 (15.6%) within 48 hours and 87 (68.0%) within 2 weeks from IVT. Stroke recurrence in IVT-CEA patients was 5.5% at median 4 days after IVT (range, 0–8 days). Outcome from CEAs performed within 48 hours from IVT did not differ from CEAs performed later with respect to peri/postoperative ischemic strokes (5.0% and 3.7%), hemorrhagic strokes (5.0% and 1.9%), neck hematomas (5.0% and 8.3%), myocardial infarctions (0.0% and 0.9%), or 3-month modified Rankin Scale. There was a tendency toward higher incidence of hyperperfusion syndrome in the patients operated within 48 hours from IVT (20.0% versus 6.5%; P=0.070). The CEA-related stroke rate was similar to that of the operation without thrombolysis. Only smoking was significantly associated with peri/postoperative stroke (odds ratio, 21.82; 95% confidence interval, 1.08–439.58). Conclusions— Time between IVT and CEA was not associated with CEA-related complications. The high rate of stroke recurrence during the waiting time for CEA underscores the importance of shortening surgery delays.
Credibility of Evolutionary Events in Gene Trees

Based on the classical non-parametric bootstrapping for phylogenetic trees, we propose a novel bootstrap method to define support for gene duplication and speciation events. By comparing bootstrap gene trees to the original gene tree, we calculate support for evolutionary events. While this approach can be used to annotate orthology and paralogy, we show how it can be used to verify the reliability of tree reconciliation. We propose a linear time algorithm for the computation of bootstrap values, and we show the correspondence of our method with the classical non-parametric bootstrapping. Finally, we present two computational experiments. In the first one, based on simulated data and nine yeast genomes, we show a comparative study of several tree rooting methods and evaluation of their performance by using our bootstrapping method. In the second experiment, using data from the TreeFam database, we tested how the reliability of the gene trees influence the inferred supertree. We found out that species trees inferred from gene trees having highly supported events are more biologically consistent.
Characterization and synergistic action of a tetra‐modular lytic polysaccharide monooxygenase from Bacillus cereus

Lytic polysaccharide monooxygenases (LPMOs) contribute to enzymatic conversion of recalcitrant polysaccharides such as chitin and cellulose and may also play a role in bacterial infections. Some LPMOs are multimodular, the implications of which remain only partly understood. We have studied the properties of a tetra‐modular LPMO from the food poisoning bacterium Bacillus cereus (named BcLPMO10A). We show that BcLPMO10A, comprising an LPMO domain, two fibronectin‐type III (FnIII)‐like domains, and a carbohydrate‐binding module (CBM5), is a powerful chitin‐active LPMO. While the role of the FnIII domains remains unclear, we show that enzyme functionality strongly depends on the CBM5, which, by promoting substrate binding, protects the enzyme from inactivation. BcLPMO10A enhances the activity of chitinases during the degradation of α‐chitin.
Daily cough frequency in tuberculosis and association with household infection.

SETTING Although cough in tuberculosis (TB) is presumed to be important for transmission, there is little objective supporting evidence. OBJECTIVE To describe 24-h cough frequency in a group with TB, and investigate associations with household rates of infection. DESIGN Patients with a new diagnosis of pulmonary TB underwent 24-h cough frequency measurement at or just before initiation of anti-tuberculosis treatment. A group with latent Mycobacterium tuberculosis infection (LTBI) acted as controls. Rates of infection among household contacts of sputum smear-positive TB were measured using the interferon-gamma release assay and the tuberculin skin test, and compared with variables relating to the contacts themselves, and to the index case, including cough frequency. RESULTS Daily cough frequency in TB patients (n = 44) was variable (geometric mean [GM] 174, interquartile range [IQR] 68-475 coughs/24 h), higher than in LTBI (n = 17; GM 19 coughs/24 h, IQR 8-53; P < 0.001), and higher during the day than overnight (GM 8.9 coughs/h, IQR 4.1-19.0 vs. GM 2.9 coughs/h, IQR 0.7-13.4; P < 0.0001). Also, 24-h cough frequency in TB was associated with sputum smear status (P = 0.040), but not smoking (P = 0.475). Multivariable logistic regression confirmed that infection in contacts was independently associated with index case sputum smear grade (P = 0.014) and cough frequency (P = 0.022). CONCLUSION Measurement of 24-h cough frequency in pulmonary TB helps predict infectiousness and transmission patterns.
Design of a Wireless Control System With Unreliable Nodes and Communication Links

Unlike a traditional topology of a control system with feedback connected plant and controller systems, this paper discusses a new topology that uses an intermediate network system between the plant and controller systems. More specifically, this paper presents modeling frameworks as well as computational procedures for the design of the closed-loop control system when the nodes of the plant, controller, and network systems fail to operate and the communication links fail to transfer information between communicating nodes. It also discusses conditions required for the synthesis of the controller and network systems, and characterizes the maximum number of unavailable nodes and the maximum probability of unavailable communication links. The aim of the presented results is to provide a more practical approach to the design of the new topology. Also, a four-tank process system is used to demonstrate details of the presented modeling frameworks and computational procedures.
Image Representation and Learning With Graph-Laplacian Tucker Tensor Decomposition

Tucker tensor decomposition (TD) is widely used for image representation, reconstruction, and learning tasks. Compared to principal component analysis (PCA) models, tensor models retain more 2-D characteristics of images whereas PCA models linearize images. However, traditional TD involves attribute information only and thus does not consider the pairwise similarity information between images. In this paper, we propose a graph-Laplacian tucker tensor decomposition (GLTD) which explores both attributes and pairwise similarity information simultaneously. Generally, GLTD has three main benefits: 1) GLTD reconstruction shows clear robustness against image occlusions/outliers. We provide analysis to show that Laplacian regularization is mainly responsible to this robustness via an out-of-sample GLTD model. To the best of our knowledge, this Laplacian regularization induced robustness of TD has not been studied or emphasized before; 2) GLTD representation performs more regularity, which improves both unsupervised and supervised learning results; and 3) an effective algorithm is derived to solve GLTD problem. Although GLTD is a noncovex problem, the proposed algorithm is shown experimentally to provide a stable/unique solution starting from different random initializations. Experimental results on image reconstruction, data clustering, and classification tasks show the benefits of GLTD.