Miracle-dz/UniFAR-FTUs huggingface dataset:
Searching for diagnostic biomarkers of heart failure with preserved ejection fraction: methodological issues

Over the past three decades, the prevalence of heart failure (HF) with preserved ejection fraction (HFpEF) has risen from 41% to 56% of all cases of HF, while the prevalence of HF with reduced ejection fraction (HFrEF) and HF with mid-range ejection fraction has fallen from 44% to 31% and from 15% to 13%, respectively.1,2 Since the burden of HFpEF is growing, defining a standardized diagnostic approach to this condition becomes increasingly important.3 Overt congestion in hospitalized patients can usually be readily detected from physical examination, chest X-ray, and measurement of B-type natriuretic peptides (NPs), whereas the diagnosis of HFpEF may be challenging in outpatients complaining of dyspnoea on effort, and relies largely on demonstration of elevated pulmonary pressures.3,4 Invasive haemodynamic exercise testing (right heart catheterization with measurement of pulmonary capillary wedge pressure at rest or during exercise) has emerged as the gold standard to diagnose or exclude HFpEF in patients with exertional dyspnoea of unclear aetiology, but cost, risk, and the requirement for specialized training and equipment may limit its broad application in practice and in clinical trials, while exercise echocardiography cannot be proposed as a stand-alone diagnostic examination for HFpEF.4 The search for non-invasive alternatives for the diagnosis of HFpEF has led to the introduction of the stepwise diagnostic algorithm by the European Society of Cardiology Heart Failure Association (HFA-PEFF),5 and the H2FPEF score derived from dichotomized variables or the HFpEF nomogram derived from continuous variables.6 These systems are able to discriminate non-cardiac dyspnoea from HFpEF with a high
Implicit Frictional Boundary Handling for SPH

In this article, we present a novel method for the robust handling of static and dynamic rigid boundaries in Smoothed Particle Hydrodynamics (SPH) simulations. We build upon the ideas of the density maps approach which has been introduced recently by Koschier and Bender. They precompute the density contributions of solid boundaries and store them on a spatial grid which can be efficiently queried during runtime. This alleviates the problems of commonly used boundary particles, like bumpy surfaces and inaccurate pressure forces near boundaries. Our method is based on a similar concept but we precompute the volume contribution of the boundary geometry. This maintains all benefits of density maps but offers a variety of advantages which are demonstrated in several experiments. First, in contrast to the density maps method we can compute derivatives in the standard SPH manner by differentiating the kernel function. This results in smooth pressure forces, even for lower map resolutions, such that precomputation times and memory requirements are reduced by more than two orders of magnitude compared to density maps. Furthermore, this directly fits into the SPH concept so that volume maps can be seamlessly combined with existing SPH methods. Finally, the kernel function is not baked into the map such that the same volume map can be used with different kernels. This is especially useful when we want to incorporate common surface tension or viscosity methods that use different kernels than the fluid simulation.
ω-k Algorithm for Sparse-Transmit Sparse-Receive Diverging Beam Synthetic Aperture Transmit Scheme

In synthetic aperture (SA) imaging reported in the ultrasound imaging literature, typically, the delay and sum (DAS) beamformer is used; however, it is computationally expensive due to the pixel-by-pixel processing performed in the time domain. Recently, the adaptation of frequency-domain beamformers for medical ultrasound SA imaging, particularly to single-element/multielement synthetic transmit aperture (STA/MSTA) schemes, has been reported. In such reports, usually, less attention is paid to reducing system complexity. Recently, a sparse-transmit sparse-receive version of diverging beam-based synthetic aperture technique (DBSAT) was shown to achieve a reduction in system complexity by using fewer parallel receive channels, yet it achieves better quality and higher frame rate than conventional focused beamforming. However, this was also demonstrated using the DAS beamformer. In this work, we aim at achieving a reduction in computational cost, in addition to a reduction in system complexity, by implementing a fast and efficient frequency–wavenumber (<inline-formula> <tex-math notation="LaTeX">$\omega $ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>) algorithm for the sparse DBSAT scheme. In doing so, an additional novel step of recovering missing frame data due to sparse transmit is introduced, namely, projection onto elliptical sets (POES). The results from this novel combination of <inline-formula> <tex-math notation="LaTeX">$\omega $ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> with POES recovery showed that it is feasible to achieve several orders of magnitude faster reconstruction compared with the standard DAS beamforming, without any compromise in the image quality and, in some cases, with improved image quality. The average value of the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) calculated from cyst at 15-mm depth obtained using the different schemes was 4.94 and 5.73 dB better when <inline-formula> <tex-math notation="LaTeX">$\omega $ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> was employed instead of DAS, respectively. In addition, for the sparse data set acquired with a 50% overlap during transmit and 64 active receive elements, DAS reconstruction takes as long as ~647 s, whereas the <inline-formula> <tex-math notation="LaTeX">$\omega $ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> algorithm takes only ~2 s when programmed and executed in MATLAB.
Sketch-Based Fast and Accurate Querying of Time Series Using Parameter-Sharing LSTM Networks

Sketching is one common approach to query time series data for patterns of interest. Most existing solutions for matching the data with the interaction are based on an empirically modeled similarity function between the user’s sketch and the time series data with limited efficiency and accuracy. In this article, we introduce a machine learning based solution for fast and accurate querying of time series data based on a swift sketching interaction. We build on existing LSTM technology (long short-term memory) to encode both the sketch and the time series data in a network with shared parameters. We use data from a user study to let the network learn a proper similarity function. We focus our approach on perceived similarities and achieve that the learned model also includes a user-side aspect. To the best of our knowledge, this is the first data-driven solution for querying time series data in visual analytics. Besides evaluating the accuracy and efficiency directly in a quantitative way, we also compare our solution to the recently published Qetch algorithm as well as the commonly used dynamic time warping (DTW) algorithm.
Molecular investigation of CTX-M gene in Extended Spectrum β Lactamases (ESBLs) producing Pseudomonas aeruginosa isolated from Iranian patients with burn wound infection

Background: Pseudomonas aeruginosa (P. aeruginosa) is one of the most important causes of infection in burns and intensive care units. Extended-spectrum β-lactamases (ESBLs) production in P. aeruginosa is a major factor in the antibiotic resistance and is thought of as a serious threat to the currently available antibiotic armory. The purpose of this study was to determine the prevalence of CTX-M gene in ESBL-producing P. aeruginosa isolates in burn wound samples. Materials and methods: In this cross-sectional survey, a total of 60 clinical isolates of P. aeruginosa were obtained from patients suffering from burn wound infection referred to major hospitals of Tehran, Iran. After verification by biochemical tests and antimicrobial susceptibility testing, CTX-M gene was identified using PCR method. Results: The results of the molecular analysis of CTX-M gene showed that the prevalence of isolates of P. aeruginosa harboring CTX-M gene was 20% (12/60). Conclusion: The results from this study showed high levels of antibiotic resistance and CTX-M gene among P. aeruginosa isolated samples of burn-wound infections which condition may result in the increased the emergence of multidrug-resistant strains and the failure of therapy This study suggests that detailed data on the CTX-M gene frequency can be useful to achieve the best therapy for infections caused by ESBLs producing P. aeruginosa.
CBHE: Corner-based Building Height Estimation for Complex Street Scene Images

Building height estimation is important in many applications such as 3D city reconstruction, urban planning, and navigation. Recently, a new building height estimation method using street scene images and 2D maps was proposed. This method is more scalable than traditional methods that use high-resolution optical data, LiDAR data, or RADAR data which are expensive to obtain. The method needs to detect building rooflines and then compute building height via the pinhole camera model. We observe that this method has limitations in handling complex street scene images in which buildings overlap with each other and the rooflines are difficult to locate. We propose CBHE, a building height estimation algorithm considering both building corners and rooflines. CBHE first obtains building corner and roofline candidates in street scene images based on building footprints from 2D maps and the camera parameters. Then, we use a deep neural network named BuildingNet to classify and filter corner and roofline candidates. Based on the valid corners and rooflines from BuildingNet, CBHE computes building height via the pinhole camera model. Experimental results show that the proposed BuildingNet yields a higher accuracy on building corner and roofline candidate filtering compared with the state-of-the-art open set classifiers. Meanwhile, CBHE outperforms the baseline algorithm by over 10% in building height estimation accuracy.
Acute effects of high‐intensity interval training session and endurance exercise on pulmonary function and cardiorespiratory coupling

The aim of this study was to determine the acute effects of high‐intensity interval training (HIIT) exercise and endurance exercise (EE) on pulmonary function, sympathetic/parasympathetic balance, and cardiorespiratory coupling (CRC) in healthy participants. Using a crossover repeated‐measurements design, four females and four males were exposed to EE (20 min at 80% maximal heart rate [HR]), HIIT (1 min of exercise at 90% maximal HR per 1 min of rest, 10 times), or control condition (resting). Pulmonary function, HR, CRC, and heart rate variability (HRV) were assessed before and after the interventions. Results revealed no significant effects of EE or HIIT on pulmonary function. The EE, but not HIIT, significantly increased CRC. In contrast, HRV was markedly changed by HIIT, not by EE. Indeed, both the low‐frequency (LFHRV) and high‐frequency (HFHRV) components of HRV were increased and decreased, respectively, after HIIT. The increase in LFHRV was greater after HIIT than after EE. Therefore, a single bout of HIIT or EE has no effects on pulmonary function. Moreover, CRC and cardiac autonomic regulation are targeted differently by the two exercise modalities.
Doomed to Repeat

This article describes a tendency of news to isolate war policy outcomes from each other and from strategic goals and official responses. These predictable patterns of press coverage and policy developments are referred to as accountability gaps . We argue that professional norms and commercial pressures overwhelm whatever hesitancy news organizations have to alter their organizational and professional behavioral patterns that lead to predictable reoccurrences of accountability gaps. Habitual deference to White House officials means that positive frames are likely to prevail, regardless of conditions on the ground, while declining attention to the costs of war as they accumulate—and becoming less newsworthy-diminishes the weight of counterframes. As casualties and other consequences of policy in Iraq became routine, their news value diminished. As casualties became routine and other costs of war mounted in ways difficult to convey, official good news frames tended to dominate news narratives.
Metformin and Everolimus: A Promising Combination for Neuroendocrine Tumors Treatment

Introduction: Treatment options for neuroendocrine tumors (NETs) are rarely curative, as NETs frequently show resistance to medical therapy. The use of everolimus, an mTOR inhibitor, is limited by the development of resistance, probably due to the activation of Akt signaling. In this context, the antidiabetic drug metformin is able to inhibit mTOR, providing a rationale for the use of metformin and everolimus in combination. Methods: We investigated the effects of the metformin and everolimus combination on NET cell proliferation, apoptosis, colony formation, cell viability, NET spheroids growth and the involvement of the Akt and mTOR pathways, and also developed everolimus-resistant NET cells to further study this combination. Results: Metformin and everolimus in combination are more effective than monotherapy in inhibiting pancreatic NET (PAN-NET) cell proliferation (−71% ± 13%, p < 0.0001 vs. basal), whereas no additive effects were observed on pulmonary neuroendocrine tumor (PNT) cell proliferation. The combinatorial treatment is more effective than monotherapy in inhibiting colony formation, cell viability, NET spheroids growth rate and mTOR phosphorylation in both NET cell lines. In a PAN-NET cell line, metformin did not affect Akt phosphorylation; conversely, it significantly decreased Akt phosphorylation in a PNT cell line. Using everolimus-resistant NET cells, we confirmed that metformin maintained its effects, acting by two different pathways: Akt-dependent or independent, depending on the cell type, with both leading to mTOR suppression. Conclusions: Considering the promising effects of the everolimus and metformin combination in NET cells, our results provide a rationale for its use in NET patients.
Lamb Waves and Adaptive Beamforming for Aberration Correction in Medical Ultrasound Imaging

Phase aberration in transcranial ultrasound imaging (TUI) caused by the human skull leads to an inaccurate image reconstruction. In this article, we present a novel method for estimating the speed of sound and an adaptive beamforming technique for phase aberration correction in a flat polyvinylchloride (PVC) slab as a model for the human skull. First, the speed of sound of the PVC slab is found by extracting the overlapping quasi-longitudinal wave velocities of symmetrical Lamb waves in the frequency–wavenumber domain. Then, the thickness of the plate is determined by the echoes from its front and back side. Next, an adaptive beamforming method is developed, utilizing the measured sound speed map of the imaging medium. Finally, to minimize reverberation artifacts caused by strong scatterers (i.e., needles), a dual probe setup is proposed. In this setup, we image the medium from two opposite directions, and the final image can be the minimum intensity projection of the inherently co-registered images of the opposed probes. Our results confirm that the Lamb wave method estimates the longitudinal speed of the slab with an error of 3.5% and is independent of its shear wave speed. Benefiting from the acquired sound speed map, our adaptive beamformer reduces (in real time) a mislocation error of 3.1, caused by an 8 mm slab, to 0.1 mm. Finally, the dual probe configuration shows 7 dB improvement in removing reverberation artifacts of the needle, at the cost of only 2.4-dB contrast loss. The proposed image formation method can be used, e.g., to monitor deep brain stimulation procedures and localization of the electrode(s) deep inside the brain from two temporal bones on the sides of the human skull.
Improved Outcomes Using a Fibular Strut in Proximal Humerus Fracture Fixation.

Proximal humerus fractures, although common, have high rates of failure after open reduction and internal fixation. The use of a fibular allograft has been explored as a means to decrease complications, particularly varus collapse and the need for revision surgery. The authors performed a retrospective review of 133 proximal humerus fractures managed surgically with locking plates (n=72) or locking plates with fibular allograft intramedullary struts (n=61). Demographic, intraoperative, and postoperative variables were collected and analyzed. The fibular allograft group was more likely to be older (P<.01), be female (P=.04), and have a history of osteoporosis (P=.01). No differences were noted in the proportions of 2-, 3-, or 4-part fractures between groups. Average follow-up was 28 weeks. Medial calcar length was longer in the locking plate only group (P=.04); however, this group demonstrated a decreased head shaft angle (P=.01) and a trend toward increased rates of varus collapse (P=.06). No significant differences were found regarding other radiographic complications, irrespective of fracture complexity. A notable decrease in fluoroscopy time was seen with strut use (P=.04), but operative time and blood loss were similar between groups. A significant decrease in revision surgery rate was found with use of an allograft strut (P=.05). Using a strut appears to preserve the radiographic head shaft angle and decrease the risk of fracture collapse in 2-, 3-, and 4-part fractures, without increasing surgical time or morbidity. Use of an intramedullary strut appears to reduce the need for revision surgery, particularly in 3- and 4-part fractures. [Orthopedics. 2020;43(x):xx-xx. ].
NLRP3 inflammasome priming: A riddle wrapped in a mystery inside an enigma

The NLRP3 (NOD‐, LRR‐, and pyrin domain‐containing protein 3) inflammasome is an immunological sensor that detects a wide range of microbial‐ and host‐derived signals. Inflammasome activation results in the release of the potent pro‐inflammatory cytokines IL‐1β and IL‐18 and triggers a form of inflammatory cell death known as pyroptosis. Excessive NLRP3 activity is associated with the pathogenesis of a wide range of inflammatory diseases, thus NLRP3 activation mechanisms are an area of intensive research. NLRP3 inflammasome activation is a tightly regulated process that requires both priming and activation signals. In particular, recent research has highlighted the highly complex nature of the priming step, which involves transcriptional and posttranslational mechanisms, and numerous protein binding partners. This review will describe the current understanding of NLRP3 priming and will discuss the potential opportunities for targeting this process therapeutically to treat NLRP3‐associated diseases.
Temporal encoding of bacterial identity and traits in growth dynamics

Significance Microbiology has traditionally been defined by the study of the phenotypic traits of microorganisms. While some traits can be easily explained with a direct genetic basis, most are a result of complex interactions between the organism and its environment. We demonstrate that phenotypes with a sufficiently high information content can distinguish strains and predict traits such as antibiotic response. This has implications for how clinicians can better identify and treat bacterial infections. In particular, our results highlight that both phenotype-based and sequence-based approaches contribute valuable information and can be used alongside one another in practice. In biology, it is often critical to determine the identity of an organism and phenotypic traits of interest. Whole-genome sequencing can be useful for this but has limited power for trait prediction. However, we can take advantage of the inherent information content of phenotypes to bypass these limitations. We demonstrate, in clinical and environmental bacterial isolates, that growth dynamics in standardized conditions can differentiate between genotypes, even among strains from the same species. We find that for pairs of isolates, there is little correlation between genetic distance, according to phylogenetic analysis, and phenotypic distance, as determined by growth dynamics. This absence of correlation underscores the challenge in using genomics to infer phenotypes and vice versa. Bypassing this complexity, we show that growth dynamics alone can robustly predict antibiotic responses. These findings are a foundation for a method to identify traits not easily traced to a genetic mechanism.
Unraveling the role of arbuscular mycorrhizal fungi in mitigating the oxidative burst of plants under drought stress.

With continued climate changes, soil drought stress has become the main limiting factor of crop growth in arid and semi-arid regions. A typical characteristic of drought stress is the burst of reactive oxygen species (ROS), causing oxidative damage. Plant-associated microbes, such as arbuscular mycorrhizal fungi (AMF), can regulate physiological and molecular responses to tolerate drought stress, and they have a strong ability for coping with drought-induced oxidative damage via enhanced antioxidant defense systems. AMF produce a limited oxidative burst in the arbuscule-containing root cortical cells. Similar to plants, AMF modulate a fungal network in enzymatic (e.g. GmarCuZnSOD and GintSOD1) and non-enzymatic (e.g. GintMT1, GinPDX1, and GintGRX1) antioxidant defense systems to scavenge ROS. Plants also respond to mycorrhisation to enhance stress tolerance via metabolites and the induction of genes. The present review provides an overview of the network of plant-arbuscular mycorrhizal fungus dialogue in mitigating oxidative stress. Future studies should involve identifying genes and transcription factors from both AMF and hosts in response to drought stress, and utilize transcriptomics, proteomics, and metabolomics to clarify a clear dialogue mechanism between plants and AMF in mitigating oxidative burst.
Qualitative analysis of cognitive and social congruence in peer-assisted learning – The perspectives of medical students, student tutors and lecturers

ABSTRACT Background The teaching of students by peers, so-called peer-assisted learning, is effective based on cognitive and social congruence among students and student tutors. This study aims to investigate cognitive and social congruence by analysing the perspectives of students, student tutors and lecturers in order to receive a better understanding of these concepts and to improve the teaching in tutorials as well as the relationship among students and student tutors. Methods Cognitive and social congruence were assessed by conducting semi-structured interviews. An interview guide about teaching and relationship in tutorials was based on previous findings of Schmidt & Moust (1995) and Lockspeiser et al. (2008). The interviews were analysed inductively by using qualitative content analysis. Results Twenty-nine participants were interviewed. The following categories were found for cognitive congruence: knowledge base, high expertise by student tutors, same language and effective knowledge transfer. Social congruence was represented by relaxed learning atmosphere, sharing social roles, empathic and supportive behaviour of student tutors, sharing experiences, understanding difficulties and enjoying tutorial. Conclusion Cognitive and social congruence may be displayed on the practical behavioural level. Trust in student tutor could be found in both concepts on different levels. The qualitative results provide a deeper insight by indicating that the student tutors may play a ‘mediator’ role for the relationship between students and lectures.