Miracle-dz/UniFAR-FTUs huggingface dataset:
Hepatitis delta virus and hepatocellular carcinoma: an update

Abstract Hepatitis delta virus (HDV) is a defective RNA virus that depends on the presence of hepatitis B virus (HBV) for the creation of new virions and propagation of the infection to hepatocytes. Chronic infection with HDV is usually associated with a worsening of HBV infection, leading more frequently to cirrhosis, increased risk of liver decompensation and hepatocellular carcinoma (HCC) occurrence. In spite of a progressive declining prevalence of both acute and chronic HDV infection observed over several years, mainly due to increased global health policies and mass vaccination against HBV, several European countries have more recently observed stable HDV prevalence mainly due to migrants from non-European countries. Persistent HDV replication has been widely demonstrated as associated with cirrhosis development and, as a consequence, development of liver decompensation and occurrence of HCC. Several treatment options have been attempted with poor results in terms of HDV eradication and improvement of long-term prognosis. A global effort is deemed urgent to enhance the models already existing as well as to learn more about HDV infection and correlated tumourigenesis mechanisms.
Progressive Ventricles Enlargement and Cerebrospinal Fluid Volume Increases as a Marker of Neurodegeneration in Patients with Spinal Cord Injury: A Longitudinal Magnetic Resonance Imaging Study

Abstract Next to gray and white matter atrophy, cerebrospinal fluid (CSF) volume and ventricular dilation may be surrogate biomarkers for brain atrophy in spinal cord injury (SCI). We therefore aimed to track brain atrophy by means of CSF volume changes and ventricular enlargements over two years after SCI. Fifteen patients with SCI and 18 healthy controls underwent a series of T1-weighted scans during five time points over two years. Changes of CSF/intracranial volume (CSF/ICV) ratio, CSF volume, and ventricular enlargement rate over time were determined. Sample sizes with 80% power and 5% significance were calculated to detect a range of treatment effects for a two-armed trial. There was a significant cross-sectional increased CSF/ICV ratio in patients compared with controls at each time point (p < 0.02). The rate of CSF/ICV changes, however, was not significantly different between groups over time. CSF volume increased linearly over bilateral sensorimotor cortices (left: p = 0.002, right: p = 0.042) and in the supracerebellar space (p < 0.001) within two years. An acceleration of the enlargement within the third (p = 0.017) and the fourth (p = 0.006) ventricles was observed in patients over time. Sample size estimation for six-month trials with CSF volume requires 25 patients per treatment arm to detect a hypothetical treatment effect in terms of slowing of atrophy rate of 30%. This study shows that SCI-induced changes in CSF/ICV ratio and ventricular expansion rate provide additional information on the neurodegenerative processes after injury. The sensitivity to scoring treatment effects speaks to its potential to serve as a sensitive biomarker in addition to local atrophy measures.
Bi-Level Error Correction for PacBio Long Reads

The latest sequencing technologies such as the Pacific Biosciences (PacBio) and Oxford Nanopore machines can generate long reads at the length of thousands of nucleic bases which is much longer than the reads at the length of hundreds generated by Illumina machines. However, these long reads are prone to much higher error rates, for example, 15 percent, making downstream analysis and applications very difficult. Error correction is a process to improve the quality of sequencing data. Hybrid correction strategies have been recently proposed to combine Illumina reads of low error rates to fix sequencing errors in the noisy long reads with good performance. In this paper, we propose a new method named Bicolor, a bi-level framework of hybrid error correction for further improving the quality of PacBio long reads. At the first level, our method uses a de Bruijn graph-based error correction idea to search paths in pairs of solid <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="liu-ieq1-2780832.gif"/></alternatives></inline-formula>-mers iteratively with an increasing length of <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="liu-ieq2-2780832.gif"/></alternatives></inline-formula>-mer. At the second level, we combine the processed results under different parameters from the first level. In particular, a multiple sequence alignment algorithm is used to align those similar long reads, followed by a voting algorithm which determines the final base at each position of the reads. We compare the superior performance of Bicolor with three state-of-the-art methods on three real data sets. Results demonstrate that Bicolor always achieves the highest identity ratio. Bicolor also achieves a higher alignment ratio (<inline-formula><tex-math notation="LaTeX">$> 1.3\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mo>></mml:mo><mml:mn>1</mml:mn><mml:mo>.</mml:mo><mml:mn>3</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="liu-ieq3-2780832.gif"/></alternatives></inline-formula>) and a higher number of aligned reads than the current methods on two data sets. On the third data set, our method is closely competitive to the current methods in terms of number of aligned reads and genome coverage. The C++ source codes of our algorithm are freely available at <uri>https://github.com/yuansliu/Bicolor</uri>.
A Bi-Objective RNN Model to Reconstruct Gene Regulatory Network: A Modified Multi-Objective Simulated Annealing Approach

Gene Regulatory Network (GRN) is a virtual network in a cellular context of an organism, comprising a set of genes and their internal relationships to regulate protein production rate (gene expression level) of each other through coded proteins. Computational Reconstruction of GRN from gene expression data is a widely-applied research area. Recurrent Neural Network (RNN) is a useful modeling scheme for GRN reconstruction. In this research, the RNN formulation of GRN reconstruction having single objective function has been modified to incorporate a new objective function. An existing multi-objective meta-heuristic algorithm, called Archived Multi Objective Simulated Annealing (AMOSA), has been modified and applied to this bi-objective RNN formulation. Executing the resulting algorithm (called AMOSA-GRN) on a gene expression dataset, a collection (termed as Archive) of non-dominated GRNs has been obtained. Ensemble averaging has been applied on the archives, and obtained through a sequence of executions of AMOSA-GRN. Accuracy of GRNs in the averaged archive, with respect to gold standard GRN, varies in the range 0.875 – 1.0 (87.5 - 100 percent).
Left Ventricular Mass Change After Anthracycline Chemotherapy

Background: Myocardial atrophy and left ventricular (LV) mass reductions are associated with fatigue and exercise intolerance. The relationships between the receipt of anthracycline-based chemotherapy (Anth-bC) and changes in LV mass and heart failure (HF) symptomatology are unknown, as is their relationship to LV ejection fraction (LVEF), a widely used measurement performed in surveillance strategies designed to avert symptomatic HF associated with cancer treatment. Methods and Results: We performed blinded, serial assessments of body weight, LVEF and mass, LV-arterial coupling, aortic stiffness, and Minnesota Living with Heart Failure Questionnaire measures before and 6 months after initiating Anth-bC (n=61) and non–Anth-bC (n=15), and in 24 cancer-free controls using paired t and &khgr;2 tests and multivariable linear models. Participants averaged 51±12 years, and 70% were women. Cancer diagnoses included breast cancer (53%), hematologic malignancy (42%), and soft tissue sarcoma (5%). We observed a 5% decline in both LVEF (P<0.0001) and LV mass (P=0.03) in the setting of increased aortic stiffness and disrupted ventricular-arterial coupling in those receiving Anth-bC but not other groups (P=0.11–0.92). A worsening of the Minnesota Living with Heart Failure Questionnaire score in Anth-bC recipients was associated with myocardial mass declines (r=−0.27; P<0.01) but not with LVEF declines (r=0.11; P=0.45). Moreover, this finding was independent of LVEF changes and body weight. Conclusions: Early after Anth-bC, LV mass reductions associate with worsening HF symptomatology independent of LVEF. These data suggest an alternative mechanism whereby anthracyclines may contribute to HF symptomatology and raise the possibility that surveillance strategies during Anth-bC should also assess LV mass.
Remission of Spontaneous Canine Tumors after Systemic Cellular Viroimmunotherapy.

Dogs with spontaneous tumors treated in veterinary hospitals offer an excellent opportunity for studying immunotherapies, including oncolytic viruses. Oncolytic viruses have advanced into the clinic as an intratumorally administered therapeutic; however, intravenous delivery has been hindered by neutralization in the blood. To circumvent this hurdle, mesenchymal stem cells have been used as a "Trojan horse. " Here, we present the treatment of 27 canine patients with cancer with canine mesenchymal stem cells infected with ICOCAV17, a canine oncolytic adenovirus. No significant adverse effects were found. The response rate was 74%, with 14.8% showing complete responses, including total remissions of lung metastasis. We detected virus infection, stromal degeneration, and immune cell infiltration in tumor biopsies after 4 weeks of treatment. The increased presence of antiadenoviral antibodies in the peripheral blood of treated dogs did not appear to prevent the clinical benefit of this therapy. These data indicate that oncolytic viruses loaded in mesenchymal stem cells represent an effective cancer immunotherapy.Significance: The classical clinical limitations of antitumoral viroimmunotherapy can be overcome by use of mesenchymal stem cells.Graphical Abstract: http://cancerres.aacrjournals. org/content/canres/78/17/4891/F1.large. jpg Cancer Res; 78(17); 4891-901. ©2018 AACR.
A New Varying-Parameter Recurrent Neural-Network for Online Solution of Time-Varying Sylvester Equation

Solving Sylvester equation is a common algebraic problem in mathematics and control theory. Different from the traditional fixed-parameter recurrent neural networks, such as gradient-based recurrent neural networks or Zhang neural networks, a novel varying-parameter recurrent neural network, [called varying-parameter convergent-differential neural network (VP-CDNN)] is proposed in this paper for obtaining the online solution to the time-varying Sylvester equation. With time passing by, this kind of new varying-parameter neural network can achieve super-exponential performance. Computer simulation comparisons between the fixed-parameter neural networks and the proposed VP-CDNN via using different kinds of activation functions demonstrate that the proposed VP-CDNN has better convergence and robustness properties.
Reciprocal enhancement of gene expression between the phz and prn operon in Pseudomonas chlororaphis G05

In previous studies with Pseudomonas chlororaphis G05, two operons (phzABCDEFG and prnABCD) were confirmed to respectively encode enzymes for biosynthesis of phenazine‐1‐carboxylic acid and pyrrolnitrin that mainly contributed to suppression of some fungal phytopathogens. Although some regulators were identified to govern their expression, it is not known how two operons coordinately interact. By constructing the phz‐ or/and prn‐ deletion mutants, we found that in comparison with the wild‐type strain G05, phenazine‐1‐carboxylic acid production in the mutant G05Δprn obviously decreased in GA broth in the absence of prn, and pyrrolnitrin production in the mutant G05Δphz remarkably declined in the absence of phz. By generating the phzA and prnA transcriptional and translational fusions with a truncated lacZ on shuttle vector or on the chromosome, we found that expression of the phz or prn operon was correspondingly increased in the presence of the prn or phz operon at the post‐transcriptional level, not at the transcriptional level. These results indicated that the presence of one operon would promote the expression of the other one operon between the phz and prn. This reciprocal enhancement would keep the strain G05 producing more different antifungal compounds coordinately and living better with growth suppression of other microorganisms.
EAC-Net: Deep Nets with Enhancing and Cropping for Facial Action Unit Detection

In this paper, we propose a deep learning based approach for facial action unit (AU) detection by enhancing and cropping regions of interest of face images. The approach is implemented by adding two novel nets (a.k.a. layers): the enhancing layers and the cropping layers, to a pretrained convolutional neural network (CNN) model. For the enhancing layers (noted as E-Net), we have designed an attention map based on facial landmark features and apply it to a pretrained neural network to conduct enhanced learning. For the cropping layers (noted as C-Net ), we crop facial regions around the detected landmarks and design individual convolutional layers to learn deeper features for each facial region. We then combine the E-Net and the C-Net to construct a so-called Enhancing and Cropping Net (EAC-Net), which can learn both features enhancing and region cropping functions effectively. The EAC-Net integrates three important elements, i.e., learning transfer, attention coding, and regions of interest processing, making our AU detection approach more efficient and more robust to facial position and orientation changes. Our approach shows a significant performance improvement over the state-of-the-art methods when tested on the BP4D and DISFA AU datasets. The EAC-Net with a slight modification also shows its potentials in estimating accurate AU intensities. We have also studied the performance of the proposed EAC-Net under two very challenging conditions: (1) faces with partial occlusion and (2) faces with large head pose variations. Experimental results show that (1) the EAC-Net learns facial AUs correlation effectively and predicts AUs reliably even with only half of a face being visible, especially for the lower half; (2) Our EAC-Net model also works well under very large head poses, which outperforms significantly a compared baseline approach. It further shows that the EAC-Net works much better without a face frontalization than with face frontalization through image warping as pre-processing, in terms of computational efficiency and AU detection accuracy.
Decolorization of mordant yellow 1 using Aspergillus sp. TS-A CGMCC 12964 by biosorption and biodegradation

ABSTRACT In this report, the decolorization features of extracellular enzymes and mycelia separately prepared from Aspergillus sp. TS-A CGMCC 12,964 (120 h) were investigated. The fermentation broth of TS-A degraded 98.6% of Mordant Yellow 1 (50 mg/L) at an initial pH 6 within 1 h with over 70% of the dye (50 mg/L) degraded by extracellular enzymes and 18.8% removed by live mycelia. The degradation products of the dye were analyzed by UV-Vis and FTIR spectra. The decolorization rates of extracellular enzymes and mycelia were examined under different contact periods, dye concentrations and pH values. The extracellular enzymes exhibited excellent degradation activity under weak acidic conditions. In addition, biosorption models of mycelia fitted well the Langmuir isotherm model and the pseudo-second-order kinetic equation. Although the decolorization process was achieved through the synergistic effects of mycelia and extracellular enzymes, decolorization was dominated by the biodegradation activity of the extracellular enzymes from TS-A.
Hierarchical Algorithms for Causality Retrieval in Atrial Fibrillation Intracavitary Electrograms

Multichannel intracavitary electrograms (EGMs) are acquired at the electrophysiology laboratory to guide radio frequency catheter ablation of patients suffering from atrial fibrillation. These EGMs are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex fractionated electrograms). In this paper, we introduce two hierarchical algorithms to retrieve the causal interactions among these multiple EGMs. Both algorithms are based on Granger causality, but other causality measures can be easily incorporated. In both cases, they start by selecting a root node, but they differ on the way in which they explore the set of signals to determine their cause-effect relationships: either testing the full set of unexplored signals (GS-CaRe) or performing a local search only among the set of neighbor EGMs (LS-CaRe). The ensuing causal model provides important information about the propagation of the electrical signals inside the atria, uncovering wavefronts and activation patterns that can guide cardiologists towards candidate areas for catheter ablation. Numerical experiments, on both synthetic signals and annotated real-world signals, show the good performance of the two proposed approaches.
Postboosting Using Extended G-Mean for Online Sequential Multiclass Imbalance Learning

In this paper, a novel learning method called postboosting using extended G-mean (PBG) is proposed for online sequential multiclass imbalance learning (OS-MIL) in neural networks. PBG is effective due to three reasons. 1) Through postadjusting a classification boundary under extended G-mean, the challenging issue of imbalanced class distribution for sequentially arriving multiclass data can be effectively resolved. 2) A newly derived update rule for online sequential learning is proposed, which produces a high G-mean for current model and simultaneously possesses almost the same information of its previous models. 3) A dynamic adjustment mechanism provided by extended G-mean is valid to deal with the unresolved challenging dense-majority problem and two dynamic changing issues, namely, dynamic changing data scarcity (DCDS) and dynamic changing data diversity (DCDD). Compared to other OS-MIL methods, PBG is highly effective on resolving DCDS, while PBG is the only method to resolve dense-majority and DCDD. Furthermore, PBG can directly and effectively handle unscaled data stream. Experiments have been conducted for PBG and two popular OS-MIL methods for neural networks under massive binary and multiclass data sets. Through the analyses of experimental results, PBG is shown to outperform the other compared methods on all data sets in various aspects including the issues of data scarcity, dense-majority, DCDS, DCDD, and unscaled data.
A Bidirectional-Current CMOS Potentiostat for Fast-Scan Cyclic Voltammetry Detector Arrays

A potentiostat circuit for the application of bipolar electrode voltages and detection of bidirectional currents using a microelectrode array is presented. The potentiostat operates as a regulated-cascode amplifier for positive input currents, and as an active-input regulated-cascode mirror for negative input currents. This topology enables constant-potential amperometry and fast-scan cyclic voltammetry (FSCV) at microelectrode arrays for parallel recording of quantal release events, electrode impedance characterization, and high-throughput drug screening. A 64-channel FSCV detector array, fabricated in a 0.5-<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>m, 5-V CMOS process, is also demonstrated. Each detector occupies an area of 45 <inline-formula> <tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>m <inline-formula><tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> 30 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>m and consists of only 14 transistors and a 50-fF integrating capacitor. The system was validated using prerecorded input stimuli from actual FSCV measurements at a carbon-fiber microelectrode.
Capsaicin-Sensitive Sensory Nerves Indirectly Modulate Motor Function of the Urinary Bladder

Purpose The urinary bladder (UB) is innervated by both sensory and autonomic nerves. Recent studies have shown that sensory neuropeptides induced contractions in the detrusor muscle. Therefore, in a mouse model, we investigated the presence of interactions between the submucosal sensory nerves and the autonomic nerves that regulate the motor function of the detrusor muscle. Methods UB samples from male C57BL/6 mice were isolated, cut into strips, and mounted in an organ bath. Dose-response curves to norepinephrine and phenylephrine were studied in UB strips with and without mucosa, and the effects of preincubation with a receptor antagonist and various drugs on relaxation were also studied using tissue bath myography. Results Phenylephrine-induced relaxation of the UB strips showed concentration-related effects. This relaxation appeared in both mucosa-intact and mucosa-denuded UB strips, and was significantly inhibited by lidocaine, silodosin, and guanethidine (an adrenergic neuronal blocker). Meanwhile, phenylephrine-induced relaxation was inhibited by pretreatment with propranolol and calcitonin gene-related peptide (CGRP)–depletory capsaicin in UB strips with and without mucosa. Conclusions The present study suggests that phenylephrine activates the α-1A adrenergic receptor (AR) of the sensory nerve, and then activates capsaicin-sensitive sensory nerves to release an unknown substance that facilitates the release of norepinephrine from adrenergic nerves. Subsequently, norepinephrine stimulates β-ARs in the detrusor muscle in mice, leading to neurogenic relaxation of the UB. Further animal and human studies are required to prove this concept and to validate its clinical usefulness.
Clinical pharmacology considerations for children supported with ventricular assist devices

Abstract The ventricular assist device is being increasingly used as a “bridge-to-transplant” option in children with heart failure who have failed medical management. Care for this medically complex population must be optimised, including through concomitant pharmacotherapy. Pharmacokinetic/pharmacodynamic alterations affecting pharmacotherapy are increasingly discovered in children supported with extracorporeal membrane oxygenation, another form of mechanical circulatory support. Similarities between extracorporeal membrane oxygenation and ventricular assist devices support the hypothesis that similar alterations may exist in ventricular assist device-supported patients. We conducted a literature review to assess the current data available on pharmacokinetics/pharmacodynamics in children with ventricular assist devices. We found two adult and no paediatric pharmacokinetic/pharmacodynamic studies in ventricular assist device-supported patients. While mechanisms may be partially extrapolated from children supported with extracorporeal membrane oxygenation, dedicated investigation of the paediatric ventricular assist device population is crucial given the inherent differences between the two forms of mechanical circulatory support, and pathophysiology that is unique to these patients. Commonly used drugs such as anticoagulants and antibiotics have narrow therapeutic windows with devastating consequences if under-dosed or over-dosed. Clinical studies are urgently needed to improve outcomes and maximise the potential of ventricular assist devices in this vulnerable population.