An Opposition-Based Learning Black Hole Algorithm for Localization of Mobile Sensor Network.

The mobile node location method can find unknown nodes in real time and capture the movement trajectory of unknown nodes in time, which has attracted more and more attention from researchers. Due to their advantages of simplicity and efficiency, intelligent optimization algorithms are receiving increasing attention. Compared with other algorithms, the black hole algorithm has fewer parameters and a simple structure, which is more suitable for node location in wireless sensor networks. To address the problems of weak merit-seeking ability and slow convergence of the black hole algorithm, this paper proposed an opposition-based learning black hole (OBH) algorithm and utilized it to improve the accuracy of the mobile wireless sensor network (MWSN) localization. To verify the performance of the proposed algorithm, this paper tests it on the CEC2013 test function set. The results indicate that among the several algorithms tested, the OBH algorithm performed the best. In this paper, several optimization algorithms are applied to the Monte Carlo localization algorithm, and the experimental results show that the OBH algorithm can achieve the best optimization effect in advance.

The chiral coating on an achiral nanostructure by the secondary effect in focused ion beam induced deposition.

Optical metamaterials are widely used in electromagnetic wave modulation due to their sub-wavelength feature sizes. In this paper, a method to plate an achiral nanopillar array with chiral coating by the secondary effect in focused ion beam induced deposition is proposed. Guided by the pattern defined in a bitmap with variable residence time, the beam scan strategy suppresses the interaction between adjacent nanostructures. A uniform chiral coating is formed on the target nanostructure without affecting the adjacent nanostructure, under carefully selected beam parameters and the rotation angle of the sample stage. Energy dispersive x-ray spectroscopy results show that the chiral film has high purity metal, which enables the generation of localized surface plasmon resonances and causes the circular dichroism (CD) under circularly polarized light illumination. Finally, the tailorable CD spectrum of the coated array is verified by the finite difference time domain method.

Gaussian-Based Adaptive Fish Migration Optimization Applied to Optimization Localization Error of Mobile Sensor Networks.

Location information is the primary feature of wireless sensor networks, and it is more critical for Mobile Wireless Sensor Networks (MWSN) to monitor specific targets. How to improve the localization accuracy is a challenging problem for researchers. In this paper, the Gaussian probability distribution model is applied to randomize the individual during the migration of the Adaptive Fish Migration Optimization (AFMO) algorithm. The performance of the novel algorithm is verified by the CEC 2013 test suit, and the result is compared with other famous heuristic algorithms. Compared to other well-known heuristics, the new algorithm achieves the best results in almost 21 of all 28 test functions. In addition, the novel algorithm significantly reduces the localization error of MWSN, the simulation results show that the accuracy of the new algorithm is more than 5% higher than that of other heuristic algorithms in terms of mobile sensor node positioning, and more than 100% higher than that without the heuristic algorithm.

Automatic Measurement of Pennation Angle from Ultrasound Images using Resnets.

In this study, an automatic pennation angle measuring approach based on deep learning is proposed. Firstly, the Local Radon Transform (LRT) is used to detect the superficial and deep aponeuroses on the ultrasound image. Secondly, a reference line are introduced between the deep and superficial aponeuroses to assist the detection of the orientation of muscle fibers. The Deep Residual Networks (Resnets) are used to judge the relative orientation of the reference line and muscle fibers. Then, reference line is revised until the line is parallel to the orientation of the muscle fibers. Finally, the pennation angle is obtained according to the direction of the detected aponeuroses and the muscle fibers. The angle detected by our proposed method differs by about 1° from the angle manually labeled. With a CPU, the average inference time for a single image of the muscle fibers with the proposed method is around 1.6 s, compared to 0.47 s for one of the image of a sequential image sequence. Experimental results show that the proposed method can achieve accurate and robust measurements of pennation angle.

Silver nanoparticle-activated COX2/PGE2 axis involves alteration of lung cellular senescence in vitro and in vivo.

Silver nanoparticles (AgNPs) are widely used as antimicrobial agents and resulted in their accumulation in environment. The purpose of this study was to investigate the detailed molecular mechanisms underlying AgNP-induced lung cellular senescence which has been proposed as a pathogenic driver of chronic lung disease. Herein, we demonstrate that exposure to AgNPs elevates multiple senescence biomarkers in lung cells, with cell cycle arrest in the G2/M phase, and potently activates genes of the senescence-associated secretory phenotype (SASP) in human fetal lung fibroblast cell line MRC5. Fluorescence-based assay also reveals that apoptosis induced by AgNPs is associated with senescence. Furthermore, we show that AgNPs cause premature senescence through an increase in transcription factor nuclear factor kappa B (NF-κB), cyclooxygenase-2 (COX2) expression and over-production of prostaglandin E2 (PGE2) in lung cells. Inhibition of COX2 reduces AgNPs-induced senescence to a normal level. Moreover, AgNPs also induce upregulation of COX2 and accelerate lung cellular senescence in vivo and cause mild fibrosis in the lung tissue of mice. Taken together, our studies support a critical role of AgNPs in the induction of lung cellular senescence via the upregulation of the COX2/PGE2 intracrine pathway, and suggest the adverse effects to the human respiratory system.

3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm.

In this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole (BH) algorithm. The performance of the EBH algorithm is verified by the CEC 2013 test suit, and shows better results than the original BH. In addition, the EBH and other celebrated algorithms can be used to solve node coverage problems of Wireless Sensor Network (WSN) in 3-D terrain with satisfactory performance.

A colorimetric and fluorescent sensor for the detection of both fluoride ions and trifluoroacetic acid based on acylhydrazone derivatives.

An acylhydrazone-based colorimetric and fluorescent sensor (PAH-8) for the detection of fluoride ions (F-) and trifluoroacetic acid (TFA)/triethylamine (TEA) has been studied. PAH-8 solution and organogel are highly selective and sensitive to F- among various tested anions (F-, Cl-, Br-, AcO-, and H2PO4-) in DMSO. Upon addition of F-, the maximum absorption wavelength of PAH-8 in DMSO solution shows a big red shift from 377 nm to 464 nm with a marked color change from colorless to yellow, and the fluorescence emission also displays a red shift from 438 nm to 532 nm with its fluorescence emission switching from blue to yellow. Both Job's plot and the Benesi-Hildebrand plot confirm a 1 : 1 stoichiometric relationship between PAH-8 and F-. The detection limit of PAH-8 for the analysis of F- can reach 8.31 × 10-7 M. Very interestingly, an expeditious 'naked eye' detection of F- can be realized by the reversible gel-sol transition, along with a color change from slight yellow to bright red and fluorescence quenching. In addition, the cast film of PAH-8 (the solution was developed from the DMSO gel upon the addition of TBAF) can detect water in air by color switching or fluorescence on/off. In both solution and solid states, PAH-8 also exhibits obvious acid-base stimulated fluorescence conversion. The solution of PAH-8 can convert the blue emission into intensive sky blue emission after adding trifluoroacetic acid (TFA), and the solid film exhibits no fluorescence after fuming with TFA vapors, while fuming with triethylamine (TEA) vapors resulted in intensive green emission.

Continuous cellular automaton simulation of focused ion beam-induced deposition for nano structures.

With the assistance of a gas injection system, focused ion beam-induced deposition (FIBID) can be realized to fabricate complicated three-dimensional structures in nanoscale. The growth rate of the deposited structure depends on the flux of precursor gas and incident ions. In this study, a Continuous Cellular Automaton (CCA) model is put forward to simulate the FIBID process, with four rules established to initiate and dominate the interface evolution, which can calculate the deposited structure profile under different fabrication conditions. In this model, the sputtering and diffusion effects are taken into account to establish a more accurate relationship between the deposition rate and precursor gas flux based on the continuous model, and the influences imposed by precursor gas and incident ions are clarified. In order to verify the precursor gas distribution and the growth mechanism of the FIBID, experiments are carried out with different local precursor gas flux on the substrate surface with a 7 pA and 30 keV Ga ions, using C9H16Pt as the precursor gas. The experimental and simulation results indicate that the CCA model features a high accuracy in predicting the deposited structure profile, and prove that the proposed model can be utilized in fabrication parameters optimization.

Therapeutic Antibody Engineering To Improve Viscosity and Phase Separation Guided by Crystal Structure.

Antibodies at high concentrations often reveal unanticipated biophysical properties suboptimal for therapeutic development. The purpose of this work was to explore the use of point mutations based on crystal structure information to improve antibody physical properties such as viscosity and phase separation (LLPS) at high concentrations. An IgG4 monoclonal antibody (Mab4) that exhibited high viscosity and phase separation at high concentration was used as a model system. Guided by the crystal structure, four CDR point mutants were made to evaluate the role of hydrophobic and charge interactions on solution behavior. Surprisingly and unpredictably, two of the charge mutants, R33G and N35E, showed a reduction in viscosity and a lower propensity to form LLPS at high concentration compared to the wild-type (WT), while a third charge mutant S28K showed an increased propensity to form LLPS compared to the WT. A fourth mutant, F102H, had reduced hydrophobicity, but unchanged viscosity and phase separation behavior. We further evaluated the correlation of various biophysical measurements including second virial coefficient (A2), interaction parameter (kD), weight-average molecular weight (WAMW), and hydrodynamic diameters (DH), at relatively low protein concentration (4 to 15 mg/mL) to physical properties, such as viscosity and liquid-liquid phase separation (LLPS), at high concentration. Surprisingly, kD measured using dynamic light scattering (DLS) at low antibody concentration correlated better with viscosity and phase separation than did A2 for Mab4. Our results suggest that the high viscosity and phase separation observed at high concentration for Mab4 are mainly driven by charge and not hydrophobicity.

Genetic characterization of emerging coxsackievirus A12 associated with hand, foot and mouth disease in Qingdao, China.

To characterize the genetic properties of coxsackievirus A12 (CVA12) strains isolated from hand, foot and mouth disease (HFMD) patients in Qingdao during 2008-2011, the complete genome and VP1 coding region were sequenced and analyzed. Phylogenetic analysis showed that all strains from China clustered into three different branches, suggesting multiple lineages of CVA12 co-circulating in Asia. Sequence analysis indicated a monophyletic group only when the P1 region was examined, indicating possible recombination between CVA12 and other HEV-A serotypes. The emergence of CVA12 involved in an HFMD outbreak in China is a public-health issue.

Early stage effect of ischemic preconditioning for patients undergoing on-pump coronary artery bypass grafts surgery: systematic review and meta-analysis.

BACKGROUND: During the on-pump coronary artery bypass grafts surgery, ischemia/reperfusion injury would happen. Ischemia preconditioning could increase the tolerance against subsequent ischemia and reduce the ischemia/reperfusion injury. However the clinical outcomes of the available trials were different. Methods : We searched the Cochrane Central Register of Controlled Trials on The Cochrane Library (Issue 3, 2013), the Medline/PubMed and CNKI in March 2013. RevMan 5.1.6 and GRADEprofiler 3.6 were used for statistical analysis and evidence quality assessment. Heterogeneity was evaluated with significance set at P≤0.10. RESULTS: Eighteen randomized controlled trials were included. There were no differences on in-hospital mortality, postoperative myocardial infarction morbidity between ischemia preconditioning and control groups. The heterogeneity of creatine kinase-MB level 24 hours after surgery was obvious. The differences of 72 hours area under the curve of cardiac troponin T (mean differences of -14.50, 95% confidence interval of -21.71 to -7.28) and troponin I (mean differences -181.79, 95% confidence interval of -270.07 to -93.52) after surgery were observed. Conclusion s : All the 18 trails, the positive and the negative results were equal. The meta-analysis results should be interpreted with caution due to limited effective data. Because of high cost-effectiveness, ischemia preconditioning could not be denied completely. Large-scale randomized studies are needed, with the operation procedures and included criteria being more specific.

Dynamic assessment of dust hazard risk in the reconstruction of old industrial buildings: coupling effects of dust distribution and personnel trajectories.

Since the old industrial buildings bear many functions of industrial production and storage in the service stage, the dust generated by the regeneration construction is often accompanied by industrial pollutants, causing irreversible damage to the personal safety of construction workers. However, little consideration has been given to the uncertainty of dust emissions and the dynamics of construction personnel movement. Therefore, reducing the risk of dust hazards during the regeneration of old industrial buildings is imperative. This study draws on the trace intersecting theory to analyse the cause of the hazard risk associated with reconstruction dust and explore the impact of the spatiotemporal distribution characteristics of reconstruction dust and its coupling effect with construction on-site personnel activity trajectories and uses the risk matrix method to assess the dust hazard risk in the reconstruction of old industrial buildings. Finally, the renovation and reinforcement process of the first floor of a printing building in Xi'an was considered as an example for verification. The results indicate that the risk assessment model results were highly consistent with the actual situation and risk value for the entire area was 6.05, indicating a risk level of IV. Immediate measures should be implemented to reduce dust concentrations or the frequency of construction personnel activity, thereby minimising potential harm.

[Analysis of evolution features of whole genome of influenza virus H3N2 in Qingdao between year 2007 and 2011].

OBJECTIVE: To investigate the evolution features of whole-genome of influenza virus H3N2 prevalent in Qingdao from year 2007 to 2011. METHODS: The RNA of 58 strains of influenza virus H3N2 prevalent in Qingdao between 2007 and 2011 was extracted and all segments amplified by RT-PCR. The sequence was then detected and assembled by software Sequencer. A total of 589 strains of influenza virus H3N2 with more than 300 amino acid recorded by GenBank were selected. The phylogeny and molecular features of all gene segments were analyzed by software Mega 5.0, referred by the heavy chain of hemagglutinin (HA1). RESULTS: Hemagglutinin (HA) genes of influenza virus H3N2 prevalent in Qingdao between year 2007 and 2011 formed a single trunk of phylogenetic tree. Every prevalent strain originated in last season. The analysis of the evolution of whole genome found that reassortment virus strains were prevalent between year 2009 and 2010, but between 2010 and 2011 there were two series of prevalent strains, which showed complicated reassortment. Compared with the vaccine strains, the variant amino acids of protein of virus HA1 between year 2007 and 2011 were 8, 6, 6, 8 and 11, involving 13 antigenic sites. The sequence analysis of M2 protein showed that the isolated influenza virus H3N2 mutated in amino acid site 31, from serine to asparagine (S31N). HA1 gene of influenza virus H3N2 isolated in Qingdao between 2007 and 2011 shared the similar phylogenetic tree with the globally prevalent strain. The comparison of the sequence and the analysis of the antigenicity found co-infection between H3N2 and A/H1N1 in the strain A/Qingdao/F521/2011. CONCLUSION: The evolution features of all segments of influenza virus H3N2 prevalent in Qingdao between year 2007 and 2011 were complicated.

[Analysis of characteristics of whole-genome of influenza A H1N1 virus in Qingdao between year 2009 and 2011].

OBJECTIVE: To investigate characteristics of the whole-genome of influenza A H1N1 virus circulated in Qingdao from year 2009 to 2011. METHODS: RNA of 35 influenza A H1N1 virus isolates circulated in Qingdao between year 2009 and 2011 was extracted and all segments were amplified by RT-PCR. The sequence was then detected and assembled by software Sequencher.25 HA full-length sequences published on GenBank were selected as reference. While MEGA 5.0 software package was explored for phylogenetic analysis to characterize the molecular feature with reference to the whole-genome sequence and the hemagglutinin (HA).1068 HA sequences of influenza A H1N1 virus isolated worldwide from August 2010 to March 2011 were downloaded for amino acid mutation analysis. RESULTS: On the HA genes phylogenetic tree, the virus were separately divided into 4 clades in 2009-2010 and 2010-2011 surveillance season, each with a preponderant epidemic clade. The homogeneity of nucleotide and amino acids of HA isolates were 99.6%-99.9% and 99.1%-99.8% respectively in 2009-2010 surveillance season; 99.1%-99.6% and 98.2%-99.1% respectively in 2010-2011 surveillance season. The homogeneity of nucleotide and amino acids of the preponderant isolates were separately 98.8%-99.8% and 98.0%-99.6%. Compared with the vaccine strain, there were separately 14 and 12 variant amino acids of virus HA in the two surveillance season, involving 10 antigen sites and 5 positive selected sites. The sequence analysis of neuraminidase protein showed that the positions 247, 274 presented serine and histidine(S247, H274) respectively. The sequence analysis of M2 protein showed that the isolated A H1N1 viruses presented asparagine in amino acid site 31 (N31). CONCLUSION: All the A H1N1 influenza virus circulated in Qingdao from year 2009 to 2011 presented continual variation and therefore caused antigenic drift. All the isolations were adamantane-resistance, but susceptible to inhibitors of neuraminidase.

Structure-free antibody paratope similarity prediction for in silico epitope binning via protein language models.

Antibodies are an important group of biological molecules that are used as therapeutics and diagnostic tools. Although millions of antibody sequences are available, identifying their structural and functional similarity and their antigen binding sites remains a challenge at large scale. Here, we present a fast, sequence-based computational method for antibody paratope prediction based on protein language models. The paratope information is then used to measure similarity among antibodies via protein language models. Our computational method enables binning of antibody discovery hits into groups as the function of epitope engagement. We further demonstrate the utility of the method by identifying antibodies targeting highly similar epitopes of the same antigens from a large pool of antibody sequences, using two case studies: SARS CoV2 Receptor Binding Domain (RBD) and Epidermal Growth Factor Receptor (EGFR). Our approach highlights the potential in accelerating antibody discovery by enhancing hit prioritization and diversity selection.

Health damage assessment of reconstruction dust from old industrial buildings under multi-process.

The regeneration of old industrial buildings produces considerable construction dust, thereby seriously threatening the occupational health of construction workers. The existing articles concerning the exposure and health impacts of reconstruction dust in enclosed spaces are limited, but this research field has received increasing attention. In this study, multi-process during the demolition and reinforcement stages of a reconstruction project were monitored to determine the respirable dust concentration distribution. A questionnaire survey was conducted to obtain the exposure parameters of reconstruction workers. Moreover, a health damage assessment system for the reconstruction process of old industrial buildings was established by applying the disability-adjusted life year and human capital method to explore the health damage caused by the generated dust at different stages to the construction personnel. The assessment system was applied to the reconstruction stage of an old industrial building regeneration project in Beijing to obtain dust health damage values for different work types and to conduct comparative analysis. The results indicate that there are significant differences in the dust concentration and health damage at different stages. During the demolition stage, the manual demolition of concrete structures has the highest dust concentration, reaching 0.96 mg/m3. This exceeds the acceptable concentration by 37%, and the health damage cost is 0.58 yuan per person per day. In the reinforcement stage, the dust concentration generated by mortar/concrete mixing is the highest, but the risk level is acceptable. The health damage cost of concrete grinding, which is 0.98 yuan per person per day, is the highest. Therefore, it is necessary to strengthen the protective facilities and improve the reconstruction technology to reduce dust pollution. The results of this study can help in improving the existing dust pollution control measures at construction sites to reduce the risk of dust hazards during reconstruction.

Structural basis of cell surface receptor recognition by botulinum neurotoxin B.

Botulinum neurotoxins (BoNTs) are potent bacterial toxins that cause paralysis at femtomolar concentrations by blocking neurotransmitter release. A 'double receptor' model has been proposed in which BoNTs recognize nerve terminals via interactions with both gangliosides and protein receptors that mediate their entry. Of seven BoNTs (subtypes A-G), the putative receptors for BoNT/A, BoNT/B and BoNT/G have been identified, but the molecular details that govern recognition remain undefined. Here we report the crystal structure of full-length BoNT/B in complex with the synaptotagmin II (Syt-II) recognition domain at 2.6 A resolution. The structure of the complex reveals that Syt-II forms a short helix that binds to a hydrophobic groove within the binding domain of BoNT/B. In addition, mutagenesis of amino acid residues within this interface on Syt-II affects binding of BoNT/B. Structural and sequence analysis reveals that this hydrophobic groove is conserved in the BoNT/G and BoNT/B subtypes, but varies in other clostridial neurotoxins. Furthermore, molecular docking studies using the ganglioside G(T1b) indicate that its binding site is more extensive than previously proposed and might form contacts with both BoNT/B and synaptotagmin. The results provide structural insights into how BoNTs recognize protein receptors and reveal a promising target for blocking toxin-receptor recognition.

Antibody apparent solubility prediction from sequence by transfer learning.

Developing therapeutic monoclonal antibodies (mAbs) for the subcutaneous administration requires identifying mAbs with superior solubility that are amenable for high-concentration formulation. However, experimental screening is often material and labor intensive. Here, we present a strategy (named solPredict) that employs the embeddings from pretrained protein language modeling to predict the apparent solubility of mAbs in histidine (pH 6.0) buffer. A dataset of 220 diverse, in-house mAbs were used for model training and hyperparameter tuning through 5-fold cross validation. solPredict achieves high correlation with experimental solubility on an independent test set of 40 mAbs. Importantly, solPredict performs well for both IgG1 and IgG4 subclasses despite the distinct solubility behaviors. This approach eliminates the need of 3D structure modeling of mAbs, descriptor computation, and expert-crafted input features. The minimal computational expense of solPredict enables rapid, large-scale, and high-throughput screening of mAbs using sequence information alone during early antibody discovery.

High-throughput profiling of antibody self-association in multiple formulation conditions by PEG stabilized self-interaction nanoparticle spectroscopy.

Affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) is an assay developed to monitor the propensity of antibody self-association, hence assessing its colloidal stability. It has been widely used by pharmaceutical companies to screen antibodies at the early discovery stages, aiming to flag potential issues with high concentration formulation. However, the original assay format is not suitable for certain formulation conditions, in particular histidine buffer. In addition, the previous data extrapolation method is suboptimal and cumbersome for processing large amounts of data (100s of molecules) in a high-throughput fashion. To address these limitations, we developed an assay workflow with two major improvements: 1) use of a stabilizing reagent to enable screening of a broader range of formulation conditions beyond phosphate-buffered saline, pH 7.4; and 2) inclusion of a novel algorithm and robust data processing schema that empowers streamlined data analysis. The optimized assay format expands the screening applicability to a wider range of formulation conditions critical for downstream development. Such capability is enhanced by a custom data management workflow for optimal data extraction, analysis, and automation. Our protocol and the R/Shiny application for analysis are publicly available and open-source to benefit the broader scientific community.