Crystallographic Analysis and Molecular Modeling Studies of HIV-1 Protease and Drug Resistant Mutants

HIV-1 protease (PR) is an effective target protein for drugs in anti-retroviral therapy (ART). Using PR inhibitors (PIs) in clinical therapy successfully reduces mortality of HIV infected patients. However, drug resistant variants are selected in AIDS patients because of the fast evolution of the viral genome. Structural, kinetic and MD simulations of PR variants with or without substrate or PIs were used to better understand the molecular basis of drug resistance. Information obtained from these extensive studies will benefit the design of more effective inhibitor in ART. Amprenavir (APV) inhibition of PRWT, and single mutants of PRV32I, PRI50V, PRI54M, PRI54V, PRI84V and PRL90M were studied and X-ray crystal structures of PR variants complexes with APV were solved at resolutions of 1.02-1.85 Å to identify structural alterations. Crystal structures of PRWT, PRV32I and PRI47V were solved at resolutions of 1.20-1.40 Å. Reaction intermediates were captured in the substrate binding cavity, which represent three consecutive steps in the catalytic reaction of HIV PR. HIV-1 PR20 variant is a multi-drug resistant variant from a clinical isolate and it is of utility to investigate the mechanisms of resistance. The crystal structures of PR20 with inactivating mutation D25N have been determined at 1.45-1.75 Å resolution, and three distinct flap conformations, open, twisted and tucked, were observed. These studies help understand molecular basis of drug resistance and provide clues for design of inhibitors to combat multi-drug resistant PR. The evaluation of electrostatic force in MD simulations is the computationally intensive work, which is of order theta(N2) with integration of all atom pairs. AMMP invokes Amortized FMM in summation of electrostatic force, which reduced work load to theta(N). A hybrid, CPU and GPU, parallel implementation of Amortized FMM was developed and improves the elapsed time of MD simulation 20 fold faster than CPU based parallelization

BTS: Bifold Teacher-Student in Semi-Supervised Learning for Indoor Two-Room Presence Detection Under Time-Varying CSI

In recent years, indoor human presence detection based on supervised learning (SL) and channel state information (CSI) has attracted much attention. However, the existing studies that rely on spatial information of CSI are susceptible to environmental changes, such as object movement, atmospheric factors, and machine rebooting, which degrade prediction accuracy. Moreover, SL-based methods require time-consuming labeling for retraining models. Therefore, it is imperative to design a continuously monitored model life-cycle using a semi-supervised learning (SSL) based scheme. In this paper, we conceive a bifold teacher-student (BTS) learning approach for presence detection systems that combines SSL by utilizing partially labeled and unlabeled datasets. The proposed primal-dual teacher-student network intelligently learns spatial and temporal features from labeled and unlabeled CSI. Additionally, the enhanced penalized loss function leverages entropy and distance measures to distinguish drifted data, i.e., features of new datasets affected by time-varying effects and altered from the original distribution. The experimental results demonstrate that the proposed BTS system sustains asymptotic accuracy after retraining the model with unlabeled data. Furthermore, the label-free BTS outperforms existing SSL-based models in terms of the highest detection accuracy while achieving the asymptotic performance of SL-based methods

Metastatic Gallbladder Cancer Presenting as a Gingival Tumor and Deep Neck Infection

Gallbladder cancer has an extremely poor prognosis because it is often diagnosed at an advanced stage. We describe a 63-year-old woman who was treated 4 years previously for gallbladder cancer, with laparoscopic cholecystectomy and secondary hepatectomy after presenting with acute cholecystitis and gallbladder rupture. At her second presentation, she had a left lower gingival tumor and deep neck infection. Incision and drainage and tumor biopsies were performed, and pathology at both sites revealed adenocarcinoma. Positron emission tomography revealed other tumors in the left breast and left lower lung field, which were both proven to be adenocarcinoma by biopsy. The patient's presentation with a metastatic oral tumor was rare. Although the incidence is very low, physicians should consider the possibility of metastatic cancer in a patient with a history of cancer, who presents with new oral tumor or deep neck infection

Papillary Adenocarcinoma of Rete Testis Mimics Inflammatory Lump: A Case Report

We presented a rare extratesticular neoplasm, papillary adenocarcinoma of rete testis, which manifested variable symptoms and mimicked most frequently seen benign extratesticular lesions. Due to its rarity, the treatment is therefore uncertain. Our patient's clinical manifestations mimicked an inflammatory lump and underwent radical orchiectomy after pathological report had been confirmed. Unlike other reports, our patient survives and has a good outcome. No definite predictor and tumor marker can be used to define the prognosis. Early diagnosis and surgical treatment may have a good outcome

Edge Selection and Clustering for Federated Learning in Optical Inter-LEO Satellite Constellation

Low-Earth orbit (LEO) satellites have been prosperously deployed for various Earth observation missions due to its capability of collecting a large amount of image or sensor data. However, traditionally, the data training process is performed in the terrestrial cloud server, which leads to a high transmission overhead. With the recent development of LEO, it is more imperative to provide ultra-dense LEO constellation with enhanced on-board computation capability. Benefited from it, we have proposed a collaborative federated learning over LEO satellite constellation (FedLEO). We allocate the entire process on LEOs with low payload inter-satellite transmissions, whilst the low-delay terrestrial gateway server (GS) only takes care for initial signal controlling. The GS initially selects an LEO server, whereas its LEO clients are all determined by clustering mechanism and communication capability through the optical inter-satellite links (ISLs). The re-clustering of changing LEO server will be executed once with low communication quality of FedLEO. In the simulations, we have numerically analyzed the proposed FedLEO under practical Walker-based LEO constellation configurations along with MNIST training dataset for classification mission. The proposed FedLEO outperforms the conventional centralized and distributed architectures with higher classification accuracy as well as comparably lower latency of joint communication and computing

Online Multicast Traffic Engineering for Software-Defined Networks

Previous research on SDN traffic engineering mostly focuses on static traffic, whereas dynamic traffic, though more practical, has drawn much less attention. Especially, online SDN multicast that supports IETF dynamic group membership (i.e., any user can join or leave at any time) has not been explored. Different from traditional shortest-path trees (SPT) and graph theoretical Steiner trees (ST), which concentrate on routing one tree at any instant, online SDN multicast traffic engineering is more challenging because it needs to support dynamic group membership and optimize a sequence of correlated trees without the knowledge of future join and leave, whereas the scalability of SDN due to limited TCAM is also crucial. In this paper, therefore, we formulate a new optimization problem, named Online Branch-aware Steiner Tree (OBST), to jointly consider the bandwidth consumption, SDN multicast scalability, and rerouting overhead. We prove that OBST is NP-hard and does not have a $|D_{max}|^{1-\epsilon}$-competitive algorithm for any $\epsilon >0$, where $|D_{max}|$ is the largest group size at any time. We design a $|D_{max}|$-competitive algorithm equipped with the notion of the budget, the deposit, and Reference Tree to achieve the tightest bound. The simulations and implementation on real SDNs with YouTube traffic manifest that the total cost can be reduced by at least 25% compared with SPT and ST, and the computation time is small for massive SDN.Comment: Full version (accepted by INFOCOM 2018

Attention-based Learning for Sleep Apnea and Limb Movement Detection using Wi-Fi CSI Signals

Wi-Fi channel state information (CSI) has become a promising solution for non-invasive breathing and body motion monitoring during sleep. Sleep disorders of apnea and periodic limb movement disorder (PLMD) are often unconscious and fatal. The existing researches detect abnormal sleep disorders in impractically controlled environments. Moreover, it leads to compelling challenges to classify complex macro- and micro-scales of sleep movements as well as entangled similar waveforms of cases of apnea and PLMD. In this paper, we propose the attention-based learning for sleep apnea and limb movement detection (ALESAL) system that can jointly detect sleep apnea and PLMD under different sleep postures across a variety of patients. ALESAL contains antenna-pair and time attention mechanisms for mitigating the impact of modest antenna pairs and emphasizing the duration of interest, respectively. Performance results show that our proposed ALESAL system can achieve a weighted F1-score of 84.33, outperforming the other existing non-attention based methods of support vector machine and deep multilayer perceptron

Integrin-mediated membrane blebbing is dependent on the NHE1 and NCX1 activities.

Integrin-mediated signal transduction and membrane blebbing have been well studied to modulate cell adhesion, spreading and migration^1-6^. However, the relationship between membrane blebbing and integrin signaling has not been explored. Here we show that integrin-ligand interaction induces membrane blebbing and membrane permeability change. We found that sodium-proton exchanger 1 (NHE1) and sodium-calcium exchanger 1 (NCX1) are located in the membrane blebbing sites and inhibition of NHE1 disrupts membrane blebbing and decreases membrane permeability change. However, inhibition of NCX1 enhances cell blebbing to cause cell swelling which is correlated with an intracellular sodium accumulation induced by NHE17. These data suggest that sodium influx induced by NHE1 is a driving force for membrane blebbing growth, while sodium efflux induced by NCX1 in a reverse mode causes membrane blebbing retraction. Together, these data reveal a novel function of NHE1 and NCX1 in membrane permeability change and blebbing and provide the link for integrin signaling and membrane blebbing

Temperature Swing Adsorption Process for CO2 Capture Using Polyaniline Solid Sorbent

AbstractTo capture carbon dioxide from power plant flue gas which consists of 15% CO2 and 85% N2, with a temperature swing adsorption (TSA) by using polyaniline solid sorbent as the adsorbent, is explored experimentally and theoretically. First, single component adsorption equilibrium data of carbon dioxide on polyaniline solid sorbent is obtained by using Micro-Balance Thermo D-200. Then isotherm curves and the parameters are obtained by numerical method. The adsorption is expressed by the Langmuir-Freundlich isotherm. After accomplishment of isotherm curves, the breakthrough curve experiment is investigated with single adsorption column. The experiments test the change in adsorbed gas concentration at the outlet by adsorbed gas, CO2, and non-adsorbed gas, helium. Finally, this study accentuates the TSA experiments on CO2 purity and recovery by operation variable discussion which includes feed pressure, adsorption temperature and desorption temperature to find optimal operation condition. The results of optimal operation condition are CO2 purity of 47.65% with a 92.46% recovery