Miracle-dz/UniFAR-FTUs huggingface dataset:
Supervised threshold-based heart sound classification algorithm

Objective: Deep classification networks have been one of the predominant methods for classifying heart sound recordings. To satisfy their demand for sample size, the most commonly used method for data augmentation is that which divides each heart sound instance into a number of segments, with each segment labelled as the same category as its origin and used as a new sample for training or forecasting. However, performing this poses a crucial issue as to how to determine the category of a predicted heart sound instance from its segments’ prediction results. Approach: To solve this issue, this paper establishes a mathematical formula to connect the classification performance of these heart sound instances with the prediction results of their segments via a threshold which is supervised by the training set. The optimal value of the proposed threshold is calculated by maximizing the prediction accuracy of the training instances. Seeking the optimal threshold by a gradient-based method, we prove that a continuous function can closely approximate a part of the function of accuracy which transforms the discrete function of accuracy into a continuous function. The optimal threshold is used to recognize the undetermined heart sound recording. Main results: Experimental results show the classification performance from a 10-fold cross-validation, measured by the commonly used scales of sensitivity, specificity and mean accuracy (MAcc). The proposed algorithm improves the MAcc by about 4% by modifying the baseline. In addition, the MAcc surpasses the champion of the PhysioNet/Computing in Cardiology Challenge 2016. Significance: Our study develops a methodology to determine the category of a predicted heart sound instance from its segments’ prediction results, thus assisting in the data augmentation exercise which is necessary to provide sufficient data for deep classification networks. Our method significantly improves the classification performance.
Improved survival in overweight and obese patients with aggressive B-cell lymphoma treated with rituximab-containing chemotherapy for curative intent

Abstract The association between obesity and survival in non-Hodgkin lymphoma is unclear. Using the Ontario Cancer Registry we conducted a retrospective analysis of incident cases of aggressive-histology B-cell lymphoma treated with a rituximab-containing regimen with curative intent between 2008–2016. 6246 patients were included. On multivariable analysis the rate of all-cause mortality was lower for the overweight body mass index (BMI 25–29.9 kg/m2) (HR 0.85; 95%CI 0.77–0.95) and obese BMI (≥30 kg/m2) (HR 0.75; 95%CI 0.67–0.85) groups compared to the normal weight group (18.5–24.9 kg/m2). Binomial logistic regression analysis revealed a lower odds ratio (OR) of admission to hospital during treatment in the overweight (OR 0.84; 95%CI 0.75–0.95) compared to normal weight BMI group. In the largest cohort to date of aggressive-histology B-cell lymphoma patients treated with rituximab, increased BMI is associated with a survival advantage, and the magnitude of this effect increases from overweight to obese BMI.
Single-stranded DNA structural diversity: TAGGGT from monomers to dimers to tetramer formation.

RATIONALE DNA quadruplex structures have emerged as novel drug targets due to their role in preventing abnormal gene transcription and maintaining telomere stability. Trapped Ion Mobility Spectrometry-Mass Spectrometry (TIMS-MS), combined with theoretical modeling, is a powerful tool for studying the kinetic intermediates of DNA complexes formed in solution and interrogated in the gas phase after desolvation. METHODS A TAGGGT ssDNA sequence was purchased and studied in 10 mM ammonium acetate using nanospray electrospray ionization (nESI)-TIMS-MS in positive and negative ion mode. Collisional cross section (CCS) profiles were measured using internal calibration (Tune Mix). Theoretical structures were proposed based on molecular dynamics, charge location and geometry optimization for the most intense IMS bands based on the number of TAGGGT units, adduct form and charge states. RESULTS A distribution of monomeric, dimeric and tetrameric TAGGGT structures were formed in solution and separated in the gas phase based on their mobility and m/z value (e.g., [M + 2H]+2 , [2M + 3H]+3 , [M - 2H]-2 , [2M - 3H]-3 , [4M + 4H]+4 , [4M + 3H + NH4 ]+4 , [4M + 2H + 2NH4 ]+4 and [4M + H + 3NH4 ]+4 ). The high mobility resolution of the TIMS-MS analyzer permitted the observation of multiple CCS bands per molecular ion form. Comparison with theoretical candidate structures suggests that monomeric TAGGGT species are stabilized by A-T and G+ -G interactions, with the size of the conformer influenced by the proton location. In the case of the TAGGGT quadruplex, the protonated species displayed a broad CCS distribution, while six discrete conformers were stabilized by the presence of ammonium ions (n = 1-3). CONCLUSIONS This is the first observation of multiple conformations of TAGGGT complexes (n = 1, 2 and 4) in 10 mM ammonium acetate. Candidate structures with intramolecular interactions of the form of G+ -G and traditional A-T base pairing agreed with the experimental trends. Our results demonstrate the structural diversity of TAGGGT monomers, dimers and tetramers in the gas phase beyond the previously reported solution structure, using 10 mM ammonium acetate to replicate biological conditions.
Maneuvering and stabilization control of a bipedal robot with a universal-spatial robotic tail

This paper analyzes control methodologies to implement maneuvering and stabilization behaviors in a bipedal robot using a bioinspired robotic tail. Looking to nature, numerous animals augment their legs’ functionality using a tail nature, numerous animals augment their legs’ functionality using a tail to assist with both maneuvering and stabilization; looking to the robotics literature, previous research primarily focuses on single-mass, pendulum-like tails designed to perform a specific task. The overarching goal of this research is to study how bioinspired tail designs may be used in conjunction with low-complexity leg designs to achieve high-performance behaviors. In pursuit of this goal, this paper connects the serpentine universal-spatial robotic tail (USRT) with a biped consisting of a pair of Robotic Modular Legs to study the outer- and inner-loop control considerations necessary to achieve yaw-angle turning and stable leg lifting. The design and modeling of the tail and leg subsystems are presented, along with considerations for sensing the USRT’s configuration in real-time. In addition, two inner-loop controllers that map desired tail trajectories into actuation commands are presented: a prescribed velocity approach that only utilizes motor feedback, and a prescribed torque approach that incorporates both feedforward consideration of the tail dynamics and feedback consideration from the tail sensing. Two outer-loop controllers—one for yaw-angle steering (maneuvering), and one for roll-angle disturbance rejection when lifting a foot (stabilization)—are also defined. Case studies including simulation and experimental results are used to validate the outer-loop control approaches.
Identification of a novel metastasis inducing lncRNA which suppresses the KAI1/CD82 metastasis suppressor gene and is upregulated in triple-negative breast cancer

Inactivation of tumor/metastasis suppressor genes via epigenetic silencing is a frequent event in human cancers. KAI1/CD82 is a metastasis suppressor gene whose normal protecting activity is deficient in twelve different solid malignancies. Here we have identified and characterized a primarily nuclear non-polyadenylated, antisense (as)-lncRNA, initiating upstream of the KAI1 human metastasis suppressor gene transcription start site; and elongating in the opposite direction to KAI1 mRNA. We show that the KAI1 promoter is bi-directional giving rise to KAI1 mRNA and its as-lncRNA. Moreover, expression of this lncRNA transcript emerges to be inversely related to the KAI1 mRNA expression, and in direct relationship to the invasiveness level of human breast cancer derived cell lines. Importantly, knockdown of the KAI1 as-lncRNA in the triple-negative breast cancer cell line MDA-MB-231 have led to increased KAI1 mRNA and protein expression, manifested in stronger adhesion to fibronectin, retardation of cell migration and reduced cell invasion in vitro. Accordingly we have named this lncRNA, SKAI1BC, standing for “Suppressor of KAI1 in Breast Cancer”. These results uncover a potential way to harness tumor metastasis via targeting SKAI1BC in human breast cancer, and perhaps also in other KAI1-deficient human malignancies.
Recent advances on gradient hydrogels in biomimetic cartilage tissue engineering

Articular cartilage (AC) is a seemingly simple tissue that has only one type of constituting cell and no blood vessels and nerves. In the early days of tissue engineering, cartilage appeared to be an easy and promising target for reconstruction and this was especially motivating because of widespread AC pathologies such as osteoarthritis and frequent sports-induced injuries. However, AC has proven to be anything but simple. Recreating the varying properties of its zonal structure is a challenge that has not yet been fully answered. This caused the shift in tissue engineering strategies toward bioinspired or biomimetic approaches that attempt to mimic and simulate as much as possible the structure and function of the native tissues. Hydrogels, particularly gradient hydrogels, have shown great potential as components of the biomimetic engineering of the cartilaginous tissue.
Statistical weights for model-based reconstruction in cone-beam CT with electronic noise and dual-gain detector readout

Cone-beam CT (CBCT) systems commonly incorporate a flat-panel detector (FPD) with multiple-gain readout capability to reduce electronic noise and extend dynamic range. In this work, we report a penalized weighted least-squares (PWLS) method for CBCT image reconstruction with a system model that includes the electronic noise characteristics of FPDs, including systems with dynamic-gain or dual-gain (DG) readout in which the electronic noise is spatially varying. Statistical weights in PWLS were modified to account for the contribution of the electronic noise (algorithm denoted ), and the method was combined with a certainty-based approach that improves the homogeneity of spatial resolution (algorithm denoted ). The methods were tested in phantom studies designed to stress DG readout characteristics and translated to a clinical study for CBCT of patients with head traumas. The method demonstrated superior noise-resolution tradeoffs compared to filtered back-projection (FBP) and conventional PWLS. For example, with spatial resolution (edge-spread function width) matched at 0.65 mm, reduced variance by 28%–39% and 15%–25% compared to FBP and PWLS, respectively. The method achieved more homogeneous spatial resolution than while maintaining similar variance reduction. These findings were confirmed in clinical studies, which showed ~20% variance reduction in peripheral regions of the brain, potentially improving visual image quality in detection of epidural and/or subdural intracranial hemorrhage. The results are consistent with the general notion that incorporating a more accurate system model improves performance in optimization-based statistical CBCT reconstruction—in this case, a more accurate model for (spatially varying) electronic noise to improve detectability of low-contrast lesions.
Unscented Kalman filter for neural decoding of human treadmill walking from non-invasive electroencephalography

The feasibility of decoding lower limb kinematics in human treadmill walking from noninvasive electroencephalography (EEG) has been demonstrated with linear Wiener filter. However, nonlinear relationship between neural activities and limb movements may challenge the linear decoders in real-time brain computer interface (BCI) applications. In this study, we propose a nonlinear neural decoder using an Unscented Kalman Filter (UKF) to infer lower limb joint angles from noninvasive scalp EEG signals during human treadmill walking. Our results demonstrate that lower limb joint angles during treadmill walking can be decoded from the fluctuations in the amplitude of slow cortical potentials in the delta band (0.1-3Hz). Overall, the average decoding accuracy were 0.43 ± 0.18 for Pearson's r value and 1.82 ± 3.07 for signal to noise ratio (SNR), and robust to ocular, muscle, or movement artifacts. Moreover, the signal preprocessing scheme and the design of UKF allow the implementation of the proposed EEG-based BCI for real-time applications. This has implications for the development of closed-loop EEG-based BCI systems for gait rehabilitation after stroke.
DAIICT-Hildesheim @ Information Retrieval from Microblogs during Disasters (IRMiDis 2018)

Twitter as one of the most used sources for quickly spreading news covers a range of necessary information particularly in emergency cases. However these situations are inevitably come along with tweets expressing the sympathy of people, rumours and claims that are not very clearly referenced. Operating the disaster relief properly and rapidly the information processing and trustworthiness of the tweets are required to be examined. The purpose of Information Retrieval from Microblogs during Disasters (IRMiDis ) [2] track of FIRE 2018 is to distinguish between fact-checkable and non fact-checkable tweets to ease this process. Our group has participated in this track with three runs for task 1.
Deep unfolding of a proximal interior point method for image restoration

Variational methods are widely applied to ill-posed inverse problems for they have the ability to embed prior knowledge about the solution. However, the level of performance of these methods significantly depends on a set of parameters, which can be estimated through computationally expensive and time-consuming methods. In contrast, deep learning offers very generic and efficient architectures, at the expense of explainability, since it is often used as a black-box, without any fine control over its output. Deep unfolding provides a convenient approach to combine variational-based and deep learning approaches. Starting from a variational formulation for image restoration, we develop iRestNet, a neural network architecture obtained by unfolding a proximal interior point algorithm. Hard constraints, encoding desirable properties for the restored image, are incorporated into the network thanks to a logarithmic barrier, while the barrier parameter, the stepsize, and the penalization weight are learned by the network. We derive explicit expressions for the gradient of the proximity operator for various choices of constraints, which allows training iRestNet with gradient descent and backpropagation. In addition, we provide theoretical results regarding the stability of the network for a common inverse problem example. Numerical experiments on image deblurring problems show that the proposed approach compares favorably with both state-of-the-art variational and machine learning methods in terms of image quality.
A dual‐AAV approach restores fast exocytosis and partially rescues auditory function in deaf otoferlin knock‐out mice

Normal hearing and synaptic transmission at afferent auditory inner hair cell (IHC) synapses require otoferlin. Deafness DFNB9, caused by mutations in the OTOF gene encoding otoferlin, might be treated by transferring wild‐type otoferlin cDNA into IHCs, which is difficult due to the large size of this transgene. In this study, we generated two adeno‐associated viruses (AAVs), each containing half of the otoferlin cDNA. Co‐injecting these dual‐AAV2/6 half‐vectors into the cochleae of 6‐ to 7‐day‐old otoferlin knock‐out (Otof−/−) mice led to the expression of full‐length otoferlin in up to 50% of IHCs. In the cochlea, otoferlin was selectively expressed in auditory hair cells. Dual‐AAV transduction of Otof−/− IHCs fully restored fast exocytosis, while otoferlin‐dependent vesicle replenishment reached 35–50% of wild‐type levels. The loss of 40% of synaptic ribbons in these IHCs could not be prevented, indicating a role of otoferlin in early synapse maturation. Acoustic clicks evoked auditory brainstem responses with thresholds of 40–60 dB. Therefore, we propose that gene delivery mediated by dual‐AAV vectors might be suitable to treat deafness forms caused by mutations in large genes such as OTOF.
A meta-analysis of transcriptomic characterization revealed extracellular matrix pathway involved in the H5N1 and H7N9 infections

Avian-origin H5N1 and H7N9 influenza A viruses are capable of causing lethal infection in humans, with serious lung pathology and leading to acute respiratory distress syndrome. The contribution of host response associated with the poor prognosis of H5N1 and H7N9 infections remains unclear. The aim of this study was to identify the host factors involved in the high pathogenicity of H5N1 and H7N9 by a systematical meta-analysis. The RNA-seq datasets related to H5N1, H7N9, and H1N1 infections with time series were retrieved from GEO. After merging the data from different series, ComBat was used to adjust the known variances from different batches. The transcription factors binding the genes in each cluster were predicted by PASTAA. We figured out the genes that were differentially expressed at any time point in samples infected with H5N1, H7N9, or H1N1. The analysis of biological function showed that genes related with cytokine were up-regulated in all three viruses. However, genes associated with carbon metabolism were found exclusively down-regulated in H7N9 and the extracellular matrix pathway were only enriched in H5N1 and H7N9. To summary, our study suggested that the extracellular matrix might be associated with the high fatality of H5N1 and H7N9 viruses in humans.
Sex Differences in Aortic Hemodynamics Following Acute Exercise: Wave Separation Analysis

Abstract The importance of sex differences in the control of blood pressure responses to exercise is controversial. It is unknown whether the potential sex differences are a result of magnitude differences in forward or reflected pressure waves. The purpose of this study was to investigate sex differences in BP following acute exercise using wave separation analysis. Sixty-eight adults (36 females) participated in the study. Aerobic capacity was measured during a graded cycle ergometry test. Central pulse wave analysis was derived from the radial pulse using applanation tonometry and separated into forward and reflected pressure waves before, and 15 min and 30 min after maximum aerobic exercise. Both males and females exhibited significantly decreased brachial SBP (p<0.05) following acute exercise. However, only males exhibited a significant decrease in forward wave pressure (p<0.05). Reflected wave pressure was decreased following exercise in both sex (p<0.05) with no sex difference. Males and females differ in blood pressure control following maximal exercise. Results show that males rely on both central and peripheral hemodynamic modifications, whereas females mostly rely on peripheral modifications. The preferential peripheral adaptations in females may provide insight regarding mechanisms of blood pressure control and the disproportionate development of hypertension in young men compared to women.
Conceptualizing Family Influences on Children’s Energy Balance-Related Behaviors: Levels of Interacting Family Environmental Subsystems (The LIFES Framework)

Healthy or unhealthy behavioral patterns develop and are maintained in a family context. The importance of the family environment for children’s and adolescents’ energy balance-related behaviors (EBRBs) has been shown previously. However, the way different family environmental factors are interrelated and interact with personal factors (e.g., motivation) are not well understood. Furthermore, the majority of studies have focused on the parent-child subsystem. However, there are family-level socialization dynamics that affect the development of a healthy lifestyle beyond the impact of parenting behaviors. The current paper aims to synthesize theoretical and empirical literature on different types of family influences. The Levels of Interacting Family Environmental Subsystems (LIFES) framework incorporates family influences on three levels (immediate, proximal, distal) and of three subsystems (individual, parent-child, family), relates them to each other and postulates potential paths of influence on children’s EBRBs. Several studies examining specific sections of the framework provide empirical support for LIFES’ propositions. Future studies should place their research in the context of the interrelationship of different family environmental influences. A better understanding of the interrelated influences would enhance the understanding of the development and maintenance of overweight and obesity among children and is crucial for the development of effective interventions.
P62 plasmid can alleviate diet-induced obesity and metabolic dysfunctions

A high-calorie diet (HCD) induces two mutually exacerbating effects contributing to diet-induced obesity (DIO): impaired glucose metabolism and increased food consumption. A link between the metabolic and behavioral manifestations is not well understood yet. We hypothesized that chronic inflammation induced by HCD plays a key role in linking together the two components of diet-induced pathology. Based on this hypothesis, we tested if a plasmid (DNA vaccine) encoding p62 (SQSTM1) would alleviate DIO including its metabolic and/or food consumption abnormalities. Previously we reported that injections of the p62 plasmid reduce chronic inflammation during ovariectomy-induced osteoporosis. Here we found that the p62 plasmid reduced levels of pro-inflammatory cytokines IL-1β, IL-12, and INFγ and increased levels of anti-inflammatory cytokines IL-4, IL-10 and TGFβ in HCD-fed animals. Due to this anti-inflammatory response, we further tested whether the plasmid can alleviate HCD-induced obesity and associated metabolic and feeding impairments. Indeed, p62 plasmid significantly reversed effects of HCD on the body mass index (BMI), levels of glucose, insulin and glycosylated hemoglobin (HbA1c). Furthermore, p62 plasmid partially restored levels of the satiety hormone, serotonin, and tryptophan, simultaneously reducing activity of monoamine oxidase (MAO) in the brain affected by the HCD. Finally, the plasmid partially reversed increased food consumption caused by HCD. Therefore, the administering of p62 plasmid alleviates both metabolic and behavioral components of HCD-induced obesity.