Miracle-dz/UniFAR-FTUs huggingface dataset:
NETWORK INFERENCE FROM COMPLEX SYSTEMS STEADY STATES OBSERVATIONS: THEORY AND METHODS

This paper presents new results on network inference from observations of steady state behaviors emerging from perturbations of complex networks dynamics. We focus on the estimation of network and flow parameters using a general regularized inference formulation, which is tackled numerically using the standard technique of alternating optimization. We argue that relying only on the steady states equations removes the requirement of precisely recording transient data, and allows to meaningfully combine data from multiple experiments. To provide theoretical benchmarks we study the relationship between topological and functional characteristics of the system and the divergence between the steady state behavior observed, to give rigorous performance benchmarks. Numerical results are presented on examples with social networks and gene regulatory networks to justify our claims.
Design, synthesis, and evaluation of curcumin analogues as potential inhibitors of bacterial sialidase

Abstract Sialidases are key virulence factors that remove sialic acid from the host cell surface glycan, unmasking receptors that facilitate bacterial adherence and colonisation. In this study, we developed potential agents for treating bacterial infections caused by Streptococcus pneumoniae Nan A that inhibit bacterial sialidase using Turmeric and curcumin analogues. Design, synthesis, and structure analysis relationship (SAR) studies have been also described. Evaluation of the synthesised derivatives demonstrated that compound 5e was the most potent inhibitor of S. pneumoniae sialidase (IC50 = 0.2 ± 0.1 µM). This compound exhibited a 3.0-fold improvement in inhibitory activity over that of curcumin and displayed competitive inhibition. These results warrant further studies confirming the antipneumococcal activity 5e and indicated that curcumin derivatives could be potentially used to treat sepsis by bacterial infections.
Lower risk of fractures under methylphenidate treatment for ADHD: A dose–response effect

Methylphenidate (MP), a widely used and abused stimulant medication for ADHD, negatively affects bone mass. However, previous epidemiological studies demonstrated that MP is not associated with increased incidence of fractures in children, and may even have a protective effect due to behavior modification. This study aimed to investigate the association between MP and fracture risk in a retrospective cohort of healthy military recruits, aged 18–25, with at least 1 year of service between 2008 and 2017. Subjects were divided into five groups: subjects without ADHD; untreated subjects with ADHD; and subjects with ADHD and prescriptions of 1–90, 91–180, or 181+ tablets during the study period. The primary outcome was at least one fracture diagnosis during the study. Among 682,110 subjects (409,175 men [60%]), 50,999 (7.5%) had fractures. MP was used by 1,681 (0.4%) men and 2.828 (1%) women. The fracture rates in the no ADHD, untreated ADHD, ADHD 0–90, ADHD 91–180, and ADHD 181+ groups were 10.4%, 16.4%, 8.7%, 4.8% and 5.8% in men, and 3.6%, 7.1%, 4.6%, 4.4% and 3% in women, respectively. Multivariate regression analysis confirmed an inverse dose–response association between MP and fractures in men (p < 0.001). In women, untreated ADHD was associated with a significantly higher fracture risk, compared to healthy controls (OR = 1.82, p < 0.001). The study confirms previous literature and demonstrates an inverse dose–response association between MP and fracture risk in men. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:3328–3333, 2018.
Advanced Air Path Control in Diesel Engines Accounting for Variable Operational Conditions

In this paper, we develop an extended linear parameter-varying (LPV) model to design an LPV controller for air path system control in diesel engines. The objective is to use a widely used and accepted nonlinear diesel engine air path model, minimize simplifying assumptions on the model, and then design a model-based gain scheduling controller to work in a wide range of engine operating points. To that end, we transform the nonlinear model to linear parameter-varying form by defining state-dependent inputs and scheduling parameters. Some of the defined state-dependent scheduling parameters are synthetic in the sense that they are not obvious from the model and are created through algebraic operations. The control law we design is parameter-dependent and allows a large range of operating points to be considered. The robust performance of the controller (with respect to parametric uncertainties in the control design model) under variable operating points (depending on engine speed, fuel flow rate, and intake-exhaust manifold temperatures) is tested on simulations by tracking reference exhaust manifold pressure and compressor air mass flow signals. Finally, the performance of the designed extended LPV controller is compared to an $H_\infty $ controller and to an LPV controller from the existing literature to see its superior performance under variable operating points.
Host‐pathogen kinetics during influenza infection and coinfection: insights from predictive modeling

Influenza virus infections are a leading cause of morbidity and mortality worldwide. This is due in part to the continual emergence of new viral variants and to synergistic interactions with other viruses and bacteria. There is a lack of understanding about how host responses work to control the infection and how other pathogens capitalize on the altered immune state. The complexity of multi‐pathogen infections makes dissecting contributing mechanisms, which may be non‐linear and occur on different time scales, challenging. Fortunately, mathematical models have been able to uncover infection control mechanisms, establish regulatory feedbacks, connect mechanisms across time scales, and determine the processes that dictate different disease outcomes. These models have tested existing hypotheses and generated new hypotheses, some of which have been subsequently tested and validated in the laboratory. They have been particularly a key in studying influenza‐bacteria coinfections and will be undoubtedly be useful in examining the interplay between influenza virus and other viruses. Here, I review recent advances in modeling influenza‐related infections, the novel biological insight that has been gained through modeling, the importance of model‐driven experimental design, and future directions of the field.
Multiplex real‐time quantitative polymerase chain reaction assay for rapid and sensitive detection of hematopoietic chimerism

The increase of mixed chimerism (MC) after allogeneic hematopoietic stem cell transplantation has been associated with a high risk of relapse. A variety of techniques that use polymorphic markers have been established to survey hematopoietic chimerism status. The highest sensitivity is achieved using real‐time quantitative polymerase chain reaction (RQ‐PCR) analysis of insertion/deletion polymorphism, which allows the detection of disease recurrence and subsequently the earlier initiation of therapeutic intervention. The purpose of this study is the evaluation of multiplex RQ‐PCR for MC assessment (six biallelic genetic systems and Y‐specific locus), allowing the amplification and detection of target gene of interest and glyceraldehyde‐3‐phosphate dehydrogenase reference housekeeping gene in a single microtube. With optimized amounts of primers and probe, the quantification of target DNA was shown to be linear throughout the tested range (100%‐0.05%). The efficiencies of multiplex RQ‐PCR were in a range of 0.89 to 1.07. The sensitivity of individual systems ranged 0.02% to 0.04% with an average of 0.034%. A high degree of linear correlation between the chimerism results obtained by multiplex RQ‐PCR vs singleplex RQ‐PCR was observed (P < 0.0001, Spearman's coefficient = 0.9927), while correlation between multiplex RQ‐PCR vs short tandem repeat analysis was also statistically significant (P < 0.0001, Spearman's coefficient = 0.9769). This new multiplex RQ‐PCR assay is a quick, sensitive, reproducible, and cost‐effective method for accurate MC assessment.
ECGNet: Deep Network for Arrhythmia Classification

Cardiac arrhythmias are presently diagnosed by manual interpretation of Electrocardiography (ECG) signals. Automated ECG interpretation is required to perform efficient screening of arrhythmia from long term ECG data. Existing automated ECG interpretation tools however require extensive preprocessing and knowledge to determine relevant features. Thus there is a need for a comprehensive feature extractor and classifier to analyze ECG signals. In this paper, we propose three robust deep neural network (DNN) architectures to perform feature extraction and classification of a given two second ECG signal. The first network is a Convolutional Neural Network (CNN) with multiple kernel sizes, the second network is a Long Short Term Memory (LSTM) network and the third network is a combination of CNN and LSTM based feature extractor, CLSTM network. The proposed networks are end to end networks which can be directly trained without any preprocessing. The networks were trained and tested with the MITDB ECG dataset on three classes Normal (N), Premature Ventricular Contraction (PVC) and Premature Atrial Contraction (PAC). The best model CLSTM gave an accuracy of 97.6%. Further, transfer learning is showcased on the best performing network for use with multiple ECG datasets requiring training only on the final three layers. The results showcase the potential of the network as feature extractor for ECG datasets. Our results outperform the state-of-the art works on ECG classification on several metrics.
Benefits of unidirectional design based on decoupled transmitters and receivers in tackling traffic asymmetry for elastic optical networks

We consider a unidirectional design approach to tackle the traffic asymmetry in an elastic optical network (EON). We decouple a bidirectional transponder into a pair of separate unidirectional transmitters and unidirectional receivers, and consider different multi-flow transmitters that use either an array of laser diodes or a broadband laser source with filters to generate multiple sub-carriers. To evaluate the benefit of this unidirectional design, we have considered the routing and spectrum allocation optimization problem for the EON. An integer linear programming model and an efficient heuristic algorithm based on spectrum window planes have been developed. Simulation results show that the proposed unidirectional design approach can significantly improve capacity utilization and minimize network cost compared to one based on bidirectional symmetric traffic flows. It is also efficient for network scenarios with spatial traffic asymmetry and where multi-period network planning is required.
The Collagen Suprafamily: From Biosynthesis to Advanced Biomaterial Development

Collagen is the oldest and most abundant extracellular matrix protein that has found many applications in food, cosmetic, pharmaceutical, and biomedical industries. First, an overview of the family of collagens and their respective structures, conformation, and biosynthesis is provided. The advances and shortfalls of various collagen preparations (e.g., mammalian/marine extracted collagen, cell‐produced collagens, recombinant collagens, and collagen‐like peptides) and crosslinking technologies (e.g., chemical, physical, and biological) are then critically discussed. Subsequently, an array of structural, thermal, mechanical, biochemical, and biological assays is examined, which are developed to analyze and characterize collagenous structures. Lastly, a comprehensive review is provided on how advances in engineering, chemistry, and biology have enabled the development of bioactive, 3D structures (e.g., tissue grafts, biomaterials, cell‐assembled tissue equivalents) that closely imitate native supramolecular assemblies and have the capacity to deliver in a localized and sustained manner viable cell populations and/or bioactive/therapeutic molecules. Clearly, collagens have a long history in both evolution and biotechnology and continue to offer both challenges and exciting opportunities in regenerative medicine as nature's biomaterial of choice.
The role of Staphylococcus lugdunensis in skin and soft tissue infections

performing further diagnostic work-up (i.e. bone marrow biopsy). Three days later, the patient was re-admitted with extensive skin ecchymoses and new-onset confusion. Laboratory values were remarkable for worsening anaemia and thrombocytopenia (haemoglobin: 8.8 g/dL; platelets: 15 K/ L), elevated lactate dehydrogenase (5,720 U/L), low haptoglobin (10.8 mg/dL), and elevated fibrin split products (80-160 g/ L). His peripheral blood smear showed anisocytosis and rare schistocytes (∼1/high-power field). A direct antiglobulin test was negative for IgG and complement. CT imaging of the head showed a new, small subdural haematoma, which was managed non-operatively. Corticosteroids and plasma exchange were initiated for a suspected diagnosis of thrombotic thrombocytopenic purpura (TTP). On hospital Day (HD) 3, a bone marrow biopsy was performed and showed packed, hypercellular bone marrow (80-90% cellularity), decreased trilineage haematopoiesis, and clusters/sheets of blue, round tumour cells with moulding and fine chromatin, consistent with involvement of MCC (figure 1A). Tumour cells were strongly positive for keratin 20, pan-keratin (AE1/AE3), and synaptophysin based on immunohistochemical staining (figure 1B). The patient completed four days of plasma exchange without improvement in thrombocytopenia. He had an ADAMTS13 activity level (sent 1 day prior to initiating plasma exchange) of 126%, ruling out TTP. The patient’s health deteriorated, and he expired on HD 12 due to progressive respiratory failure from aspergillus and pneumocystis pneumonia. Bone marrow infiltration by MCC commonly presents with severe thrombocytopenia [4-7]. MCC has been incidentally found on bone marrow examination in patients with haematological malignancies [7, 8]. FDG-PET/CT is an effective imaging modality to detect distant metastases from MCC, and bone/bone marrow is reported to be the second most common site of distant metastasis in a series of MCC patients [9]. Our patient’s history of RA requiring long-term immunosuppression was associated with an increased risk of MCC [10]. The patient’s rapid disease progression and subsequent demise highlights the necessity for early detection of bone marrow metastases and prompt intervention.
Efficient feature selection and classification for microarray data

Feature selection and classification are the main topics in microarray data analysis. Although many feature selection methods have been proposed and developed in this field, SVM-RFE (Support Vector Machine based on Recursive Feature Elimination) is proved as one of the best feature selection methods, which ranks the features (genes) by training support vector machine classification model and selects key genes combining with recursive feature elimination strategy. The principal drawback of SVM-RFE is the huge time consumption. To overcome this limitation, we introduce a more efficient implementation of linear support vector machines and improve the recursive feature elimination strategy and then combine them together to select informative genes. Besides, we propose a simple resampling method to preprocess the datasets, which makes the information distribution of different kinds of samples balanced and the classification results more credible. Moreover, the applicability of four common classifiers is also studied in this paper. Extensive experiments are conducted on six most frequently used microarray datasets in this field, and the results show that the proposed methods have not only reduced the time consumption greatly but also obtained comparable classification performance.
Fluoroquinolone prophylaxis reduces febrile neutropenia, bloodstream infections from mucosal translocations, and intensive care admissions in high risk hematological patients, a single center experience

Shimin Jasmine Chung , Rachel Ann Miller, Nitipong Permpalung , Arthur Wakefield Baker, Louis Frederic Diehl, David Alan Rizzieri and Barbara Dudley Alexander Division of Infectious Diseases, Duke University, Durham, NC, USA; Department of Infectious Diseases, Singapore General Hospital, Singapore, Singapore; Division of Hematological Malignancies and Cellular Therapy, Duke University Medical Center, Durham, NC, USA
DIVIDE-AND-CONQUER TOMOGRAPHY FOR LARGE-SCALE NETWORKS

This work considers the problem of reconstructing the topology of a network of interacting agents via observations of the state-evolution of the agents. Observations from only a subset of the nodes are collected, and the information is used to infer their local connectivity (local tomography). Recent results establish that, under suitable conditions on the network model, local tomography is achievable with high probability as the network size scales to infinity [1], [2]. Motivated by these results, we explore the possibility of reconstructing a larger network via repeated application of the local tomography algorithm to smaller network portions. A divide-and-conquer strategy is developed and tested numerically on some illustrative examples.
Limb-girdle Muscular Dystrophy Type 2A with Muscular Eosinophilic Infiltration in a Chinese Patient

To the Editor: Limb‐girdle muscular dystrophy type 2A (LGMD2A) is a group of progressive muscle diseases with autosomal recessive inheritance. The common myopathological changes consist of muscular changes such as muscle necrosis and regeneration, as well as interstitial proliferation and abundant lobulated fibers. An interesting yet unresolved phenomenon of LGMD2A patients is that some of them demonstrate muscular eosinophilic granulocyte infiltration with or without peripheral eosinophilia. Although cases of LGMD2A have been reported in China, eosinophilia has never been found. Here, we report a Chinese LGMD2A patient with muscle eosinophilic infiltration.
Plasticity of Type I Interferon-Mediated Responses in Cancer Therapy: From Anti-tumor Immunity to Resistance

The efficacy of several therapeutic strategies against cancer, including cytotoxic drugs, radiotherapy, targeted immunotherapies and oncolytic viruses, depend on intact type I interferon (IFN) signaling for the promotion of both direct (tumor cell inhibition) and indirect (anti-tumor immune responses) effects. Malfunctions of this pathway in tumor cells or in immune cells may be responsible for the lack of response or resistance. Although type I IFN signaling is required to trigger anti-tumor immunity, emerging evidence indicates that chronic activation of type I IFN pathway may be involved in mediating resistance to different cancer treatments. The plastic and dynamic features of type I IFN responses should be carefully considered to fully exploit the therapeutic potential of strategies targeting IFN signaling. Here, we review available evidence supporting the involvement of type I IFN signaling in mediating resistance to various cancer therapies and highlight the most promising modalities that are being tested to overcome resistance.
Single-Event Damage Observed in GaN-on-Si HEMTs for Power Control Applications

The single-event damage observed in AlGaN/GaN high-electron mobility transistors (HEMTs) was investigated. For power control applications, normally off operation is achieved by p-type GaN gate material and its rated drain–source voltage of 600 V. Because of no gate insulator, single-event gate rupture is essentially excluded. Therefore, the HEMTs are expected to exhibit better immunity to heavy ions in comparison with SiC power MOSFETs. In the test results, two types of catastrophic failure modes were observed with different leakage current paths; one failure mode was caused by the introduction of a leakage current path between the drain and Si substrate via the buffer layer. The other was caused by the damage between the drain and source electrodes.
Differential Influence on Regulatory B Cells by TH2 Cytokines Affects Protection in Allergic Airway Disease

The role of regulatory B cells (Bregs) in modulating immune responses and maintaining tolerance are well established. However, how cytokines present during immune responses affect Breg growth and function are not as well defined. Previously, our laboratory reported IL-5– and mCD40L-expressing fibroblast (mCD40L-Fb) stimulation induced IL-10 production from murine B cells. The current study investigated the phenotype and functional relevance of IL-10– producing B cells from this culture. We found IL-5/mCD40L-Fb stimulation induced IL-10 production exclusively from CD5+ splenic B cells of naive mice. After stimulation, the resulting IL-10+ B cells displayed markers of multiple reported Breg phenotypes. Interestingly, when investigating effects of IL-4 (a critical TH2 cytokine) on IL-5/mCD40L-Fb–induced IL-10 production, we found IL-4 inhibited IL-10 production in a STAT6-dependent manner. Upon adoptive transfer, CD5+ B cells previously stimulated with IL-5/mCD40L-Fb were able to reduce development of OVA-induced allergic airway disease in mice. Using B cells from IL-10 mutant mice differentiated by IL-5/mCD40L-Fb, we found protection from allergic airway disease development was dependent on the IL-10 production from the transferred B cells. Bregs have been shown to play crucial roles in the immune tolerance network, and understanding stimuli that modulate their growth and function may be key in development of future treatments for diseases of immune dysregulation.
Assessment of Audio Signal Noise Reduction Based on Psychoacoustic Model

A new method for the assessment of audio signal noise reduction is presented in this paper. This method uses psychoacoustic model, the perception of human hearing is taken into account. The quantities in frequency domain are presented - the Noise-to-Mask Ratio Enhancement describes the success rate of noise reduction and the Relative Frequency of Mask Absence defines the average number of audible spectral components of noise.
Wireless-Powered Full-Duplex Relay and Friendly Jamming for Secure Cooperative Communications

Wireless energy harvesting, physical-layer security, and full-duplex wireless are important, emerging fifth generation (5G) technologies. In this paper, we thus investigate a source–destination link with an energy-harvesting full-duplex relay and a jammer (to degrade the eavesdropper channel) in the presence of an eavesdropper. Thus, to exploit energy harvesting and to improve security, we propose a full-duplex jammer (FDJ) protocol and its half-duplex version (HDJ). Two cases for availability of the eavesdropper channel state information (ECSI) are considered: complete ECSI and incomplete ECSI. For both FDJ and HDJ protocols and for complete ECSI, we derive the instantaneous and average secrecy rates and compute optimal time split for energy harvesting. To gain more insights, we consider a practical interference-limited scenario and derive closed-form cumulative distribution function of the signal-to-interference plus noise ratio at the destination and eavesdropper nodes. Comparatively, we show that FDJ improves instantaneous secrecy rate over HDJ. However, the degree of improvement is highly dependent on time split for energy harvesting, amount of self-interference, the channel gains, and locations of the nodes. Our findings reveal that FDJ increases the average secrecy rate 150% over HDJ and 260% over HD relaying without jammer. For incomplete ECSI scenario, we derive asymptotic secrecy outage and show that FDJ performs better for small-to-medium values of source powers; otherwise, HDJ yields a higher gain.