Hepatoprotective Effects of Chinese Medicinal Herbs: A Focus on Anti-Inflammatory and Anti-Oxidative Activities

published_or_final_versio

Density-functional study of LixMoS2 intercalates (0<=x<=1)

The stability of Lithium intercalated 2H- and 1T allotropes of Molybdenum disulfide (LixMoS2) is studied within a density-functional theory framework as function of the Li content (x) and the intercalation sites. Octahedral coordination of Li interstitials in the van der Waals gap is found as the most favorite for both allotropes. The critical content of Lithium, required for the initialization of a 2H->1T phase transition is estimated to x ~ 0.4. For smaller Li contents the hexagonal 2H crystal structure is not changed, while 1T-LixMoS2 compounds adopt a monoclinic lattice. All allotropic forms of LixMoS2 - excluding the monoclinic Li1.0MoS2 structure - show metallic-like character. The monoclinic Li1.0MoS2 is a semiconductor with a band gap of 1.1 eV. Finally, the influence of Li intercalation on the stability of multiwalled MoS2 nanotubes is discussed within a phenomenological model.Comment: submitted to Comput.Mater.Sc

A Phase 1 study of ADI-PEG20 (pegargiminase) combined with cisplatin and pemetrexed in ASS1-negative metastatic uveal melanoma

Metastatic uveal melanoma (UM) is a devastating disease with few treatment options. We evaluated the safety, tolerability and preliminary activity of arginine depletion using pegylated arginine deiminase (ADI‐PEG20; pegargiminase) combined with pemetrexed (Pem) and cisplatin (Cis) chemotherapy in a phase 1 dose‐expansion study of patients with argininosuccinate synthetase (ASS1)‐deficient metastatic UM. Eligible patients received up to six cycles of Pem (500 mg/m(2)) and Cis (75 mg/m(2)) every 3 weeks plus weekly intramuscular ADI (36 mg/m(2)), followed by maintenance ADI until progression (NCT02029690). Ten of fourteen ASS1‐deficient patients with UM liver metastases and a median of one line of prior immunotherapy received ADIPemCis. Only one ≥ grade 3 adverse event of febrile neutropenia was reported. Seven patients had stable disease with a median progression‐free survival of 3.0 months (range, 1.3–8.1) and a median overall survival of 11.5 months (range, 3.2–36.9). Despite anti‐ADI‐PEG20 antibody emergence, plasma arginine concentrations remained suppressed by 18 weeks with a reciprocal increase in plasma citrulline. Tumour rebiopsies at progression revealed ASS1 re‐expression as an escape mechanism. ADIPemCis was well tolerated with modest disease stabilisation in metastatic UM. Further investigation of arginine deprivation is indicated in UM including combinations with immune checkpoint blockade and additional anti‐metabolite strategies

Phase 1, pharmacogenomic, dose-expansion study of pegargiminase plus pemetrexed and cisplatin in patients with ASS1-deficient non-squamous non-small cell lung cancer

Introduction We evaluated the arginine-depleting enzyme pegargiminase (ADI-PEG20; ADI) with pemetrexed (Pem) and cisplatin (Cis) (ADIPemCis) in ASS1-deficient non-squamous non-small cell lung cancer (NSCLC) via a phase 1 dose-expansion trial with exploratory biomarker analysis. Methods Sixty-seven chemonaïve patients with advanced non-squamous NSCLC were screened, enrolling 21 ASS1-deficient subjects from March 2015 to July 2017 onto weekly pegargiminase (36 mg/m2) with Pem (500 mg/m2) and Cis (75 mg/m2), every 3 weeks (four cycles maximum), with maintenance Pem or pegargiminase. Safety, pharmacodynamics, immunogenicity, and efficacy were determined; molecular biomarkers were annotated by next-generation sequencing and PD-L1 immunohistochemistry. Results ADIPemCis was well-tolerated. Plasma arginine and citrulline were differentially modulated; pegargiminase antibodies plateaued by week 10. The disease control rate was 85.7% (n = 18/21; 95% CI 63.7%–97%), with a partial response rate of 47.6% (n = 10/21; 95% CI 25.7%–70.2%). The median progression-free and overall survivals were 4.2 (95% CI 2.9–4.8) and 7.2 (95% CI 5.1–18.4) months, respectively. Two PD-L1-expressing (≥1%) patients are alive following subsequent pembrolizumab immunotherapy (9.5%). Tumoral ASS1 deficiency enriched for p53 (64.7%) mutations, and numerically worse median overall survival as compared to ASS1-proficient disease (10.2 months; n = 29). There was no apparent increase in KRAS mutations (35.3%) and PD-L1 (<1%) expression (55.6%). Re-expression of tumoral ASS1 was detected in one patient at progression (n = 1/3). Conclusions ADIPemCis was safe and highly active in patients with ASS1-deficient non-squamous NSCLC, however, survival was poor overall. ASS1 loss was co-associated with p53 mutations. Therapies incorporating pegargiminase merit further evaluation in ASS1-deficient and treatment-refractory NSCLC

Fingerprint-based Wi-Fi indoor localization using map and inertial sensors

It is a common understanding that the localization accuracy can be improved by indoor maps and inertial sensors. However, there is a lack of concrete and generic solutions that combine these two features together and practically demonstrate its validity. This article aims to provide such a solution based on the mainstream fingerprint-based indoor localization approach. First, we introduce the theorem called reference points placement, which gives a theoretical guide to place reference points. Second, we design a Wi-Fi signal propagation-based cluster algorithm to reduce the amount of computation. The paper gives a parameter called reliability to overcome the skewing of inertial sensors. Then we also present Kalman filter and Markov chain to predict the system status. The system is able to provide high-accuracy real-time tracking by integrating indoor map and inertial sensors with Wi-Fi signal strength. Finally, the proposed work is evaluated and compared with the previous Wi-Fi indoor localization systems. In addition, the effect of inertial sensors’ reliability is also discussed. Results are drawn from a campus office building which is about 80 m×140 m with 57 access points

Offshore wind farm layout optimization using particle swarm optimization

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordThis article explores the application of a wind farm layout optimization framework using a particle swarm optimizer to three benchmark test cases. The developed framework introduces an increased level of detail characterizing the impact that the wind farm layout can have on the levelized cost of energy by modelling the wind farm’s electrical infrastructure, annual energy production, and cost as functions of the wind farm layout. Using this framework, this paper explores the application of a particle swarm optimizer to the wind farm layout optimization problem considering three different levels of wind farm constraint faced by modern wind farm developers. The particle swarm optimizer is found to yield improvements in the layout with respect to the levelized cost of energy for the three benchmark cases when compared to two past studies. This highlights both applicability of the particle swarm optimizer to the problem and the ways in which a wind farm developer could make use of the present framework in the development and design of future wind farms.This work is funded in part by the Energy Technologies Institute (ETI) and RCUK energy program for IDCORE (EP/J500847/1) and supported by EDF Energy R&D UK Centre

GENN: A GEneral Neural Network for Learning Tabulated Data with Examples from Protein Structure Prediction

We present a GEneral Neural Network (GENN) for learning trends from existing data and making predictions of unknown information. The main novelty of GENN is in its generality, simplicity of use, and its specific handling of windowed input/output. Its main strength is its efficient handling of the input data, enabling learning from large datasets. GENN is built on a two-layered neural network and has the option to use separate inputs–output pairs or window-based data using data structures to efficiently represent input–output pairs. The program was tested on predicting the accessible surface area of globular proteins, scoring proteins according to similarity to native, predicting protein disorder, and has performed remarkably well. In this paper we describe the program and its use. Specifically, we give as an example the construction of a similarity to native protein scoring function that was constructed using GENN. The source code and Linux executables for GENN are available from Research and Information Systems at http://mamiris.com and from the Battelle Center for Mathematical Medicine at http://mathmed.org. Bugs and problems with the GENN program should be reported to EF

Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method

Late diagnosis of hepatocarcinoma (HCC) is one of the most primary factors for the poor survival of patients. Thereby, identification of sensitive and specific biomarkers for HCC early diagnosis is of great importance in biological medicine to date. In the present study, serum metabolites of the HCC patients and healthy controls were investigated using the improved liquid chromatography–mass spectrometry (LC/MS). A wavelet-based method was utilized to find and align peaks of LC–MS. The characteristic peaks were selected by performing a two-sample t test statistics (p value <0.05). Clustering analysis based on principal component analysis showed a clear separation between HCC patients and healthy individuals. The serum metabolite, namely 1-methyladenosine, was identified as the characteristic metabolite for HCC. Moreover, receiver–operator curves were calculated with 1-methyladenosine and/or alpha fetal protein (AFP). The higher area under curve value was achieved in 1-methyladenosine group than AFP group (0.802 vs. 0.592), and the diagnostic model combining 1-methyladenosine with AFP exhibited significant improved sensitivity, which could identify those patients who missed the diagnosis of HCC by determining serum AFP alone. Overall, these results suggested that LC/MS-based metabonomic study is a potent and promising strategy for identifying novel biomarkers of HCC