The bacteriophage ϕ29 tail possesses a pore-forming loop for cell membrane penetration.

Most bacteriophages are tailed bacteriophages with an isometric or a prolate head attached to a long contractile, long non-contractile, or short non-contractile tail. The tail is a complex machine that plays a central role in host cell recognition and attachment, cell wall and membrane penetration, and viral genome ejection. The mechanisms involved in the penetration of the inner host cell membrane by bacteriophage tails are not well understood. Here we describe structural and functional studies of the bacteriophage ϕ29 tail knob protein gene product 9 (gp9). The 2.0 Šcrystal structure of gp9 shows that six gp9 molecules form a hexameric tube structure with six flexible hydrophobic loops blocking one end of the tube before DNA ejection. Sequence and structural analyses suggest that the loops in the tube could be membrane active. Further biochemical assays and electron microscopy structural analyses show that the six hydrophobic loops in the tube exit upon DNA ejection and form a channel that spans the lipid bilayer of the membrane and allows the release of the bacteriophage genomic DNA, suggesting that cell membrane penetration involves a pore-forming mechanism similar to that of certain non-enveloped eukaryotic viruses. A search of other phage tail proteins identified similar hydrophobic loops, which indicates that a common mechanism might be used for membrane penetration by prokaryotic viruses. These findings suggest that although prokaryotic and eukaryotic viruses use apparently very different mechanisms for infection, they have evolved similar mechanisms for breaching the cell membrane.

L-band compact Q-switched fiber laser based on a thulium-doped fiber saturable absorber.

In this paper, a compact and stable Q-switched erbium-doped fiber laser operating at around 1600 nm by employing a segment of 1-cm thulium-doped fiber saturable absorber (TDF-SA) is proposed. When the pump power is adjusted between 28 and 71 mW, the Q-switched operation can be maintained stably, and the output power increases from 74 µW to 2.6 mW. Furthermore, the peak power clamping effect is also observed when the pump power exceeds 60 mW. The structure of the cavity is greatly simplified by using all-optical and hybrid fiber components, which contributes to its long-term stability. Our results prove that the TDF can be a promising SA for all-fiber Q-switched pulses generation in the L-band.

The Reference Intervals and Roles of GIR, HOMA and QUICKI Indexes to Judge Insulin Resistance/Insufficiency for Newly Diagnosed Diabetes Mellitus.

BACKGROUND: To establish the reference intervals of GIR, HOMA, and QUICKI index and to identify the clinical value of the three indexes for newly diagnosed diabetes mellitus. METHODS: The results of fasting glucose and insulin were acquired for 123 healthy individuals using Roche cobas-8000 to establish reference intervals of GIR, HOMA, and QUICKI based on Clinical and Laboratory Standards Institute (CLSI) EP28-A3. Meanwhile, 36 newly diagnosed type 1 and type 2 diabetes mellitus (DM) patients were enrolled to judge the effect of insulin resistance/insufficiency using the three indexes based on clinical initial treat-ment procedures. All the data were acquired from Wangjing Hospital, China Academy of Traditional Chinese Medicine. RESULTS: The reference intervals of GIR, HOMA, and QUICKI were 5.83 - 21.15, 0.87 - 4.22, and 0.309 - 0.392, respectively. Concerning to GIR, HOMA, and QUICKI, there were 57.7% (15/26), 80.8% (21/26), and 80.8% (21/26) outside of the reference limit among type 2 DM patients, respectively; The area under the curve (AUC) of the GIR > 10.937, HOMA < 5.436, and QUICKI > 0.299 were 0.937 (95% CI 0.681 - 1.000), 0.689 (95% CI 0.510 - 0.868), and 0.689 (95% CI 0.510 - 0.868) by ROC curves when insulin insufficiency was judged based on whether insulin was included in initial treatment procedures. There concordance rates were 77.8% (28/36), 50% (18/36), and 50% (18/36) using the three indexes, GIR, HOMA, and QUICKI, respectively. CONCLUSIONS: We established reference intervals for GIR, HOMA, and QUICKI. HOMA and QUICKI were more reliable indexes to identify insulin resistance among type 2 DM patients, but GIR was a more reliable index to identify insulin relatively or absolutely insufficiency than HOMA and QUICKI among DM patients.

Epitope-focused immunogens against the CD4-binding site of HIV-1 envelope protein induce neutralizing antibodies against auto- and heterologous viruses.

Recent discoveries of broadly neutralizing antibodies (bnAbs) in HIV-1-infected individuals have led to the identification of several major "vulnerable sites" on the HIV-1 envelope (Env) glycoprotein. These sites have provided precise targets for HIV-1 vaccine development, but identifying and utilizing many of these targets remain technically challenging. Using a yeast surface display-based approach, we sought to identify epitope-focused antigenic domains (EADs) containing one of the "vulnerable sites," the CD4-binding site (CD4bs), through screening and selection of a combinatorial antigen library of the HIV-1 envelope glycoprotein with the CD4bs bnAb VRC01. We isolated multiple EADs and found that their trimeric forms have biochemical and structural features that preferentially bind and activate B cells that express VRC01 in vitro More importantly, these EADs could induce detectable levels of neutralizing antibodies against genetically related autologous and heterologous subtype B viruses in guinea pigs. Our results demonstrate that an epitope-focused approach involving a screen of a combinatorial antigen library is feasible. The EADs identified here represent a promising collection of possible targets in the rational design of HIV-1 vaccines and lay the foundation for harnessing the specific antigenicity of CD4bs for protective immunogenicity in vivo.

Modified constellation reshaping method for PAPR reduction of PDM CO-OFDM based on a SLM algorithm.

In this paper, we propose a modified constellation reshaping method for peak-to-average power ratio (PAPR) reduction in polarization division multiplexing (PDM) coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems based on the selective mapping (SLM) method. A modified quadrature amplitude modulation (M-QAM) constellation is generated that has the same minimum distance as that of the conventional QAM (C-QAM) constellation. The M-SLM method is denoted as the M-QAM constellations combining with the traditional SLM method. At the receiver side, the mean square errors between the constellations of the received data and each M-QAM rotated by different phase rotation factors are calculated. Then, the phase rotation factor with the minimum mean square error is selected to recover the original data. The advantage of the proposed method is that it does not need to send additional side information, while it possesses nearly the same PAPR reduction and bit error rate performance as the traditional SLM method.

CBN-VAE: A Data Compression Model with Efficient Convolutional Structure for Wireless Sensor Networks.

Data compression is a useful method to reduce the communication energy consumption in wireless sensor networks (WSNs). Most existing neural network compression methods focus on improving the compression and reconstruction accuracy (i.e., increasing parameters and layers), ignoring the computation consumption of the network and its application ability in WSNs. In contrast, we pay attention to the computation consumption and application of neural networks, and propose an extremely simple and efficient neural network data compression model. The model combines the feature extraction advantages of Convolutional Neural Network (CNN) with the data generation ability of Variational Autoencoder (VAE) and Restricted Boltzmann Machine (RBM), we call it CBN-VAE. In particular, we propose a new efficient convolutional structure: Downsampling-Convolutional RBM (D-CRBM), and use it to replace the standard convolution to reduce parameters and computational consumption. Specifically, we use the VAE model composed of multiple D-CRBM layers to learn the hidden mathematical features of the sensing data, and use this feature to compress and reconstruct the sensing data. We test the performance of the model by using various real-world WSN datasets. Under the same network size, compared with the CNN, the parameters of CBN-VAE model are reduced by 73.88% and the floating-point operations (FLOPs) are reduced by 96.43% with negligible accuracy loss. Compared with the traditional neural networks, the proposed model is more suitable for application on nodes in WSNs. For the Intel Lab temperature data, the average Signal-to-Noise Ratio (SNR) value of the model can reach 32.51 dB, the average reconstruction error value is 0.0678 °C. The node communication energy consumption can be reduced by 95.83%. Compared with the traditional compression methods, the proposed model has better compression and reconstruction accuracy. At the same time, the experimental results show that the model has good fault detection performance and anti-noise ability. When reconstructing data, the model can effectively avoid fault and noise data.

Endovascular Treatment of Ruptured Tiny Intracranial Aneurysms with Low-Profile Visualized Intraluminal Support Device.

BACKGROUND: Ruptured tiny intracranial aneurysms (TIAs) have been challenging both for endovascular and neurosurgical interventions. Thus, we aimed to evaluate the safety and efficacy of low-profile visualized intraluminal support (LVIS) device in the treatment of ruptured TIAs (rTIAs). MATERIAL AND METHODS: Among 761 intracranial aneurysms which were treated either surgically or endovascularly, 32 rTIAs underwent stent-assisted coiling with LVIS device between 2014 and 2017. Patient data were reviewed retrospectively. Clinical and radiological outcomes were recorded at discharge and mid-term follow-up. RESULTS: Mean patient ages were 53 ± 14.5 years. Mean aneurysm size was 2.28 ± .53 mm (range, 1-2.9 mm) with a mean dome:neck ratio of 1.08 (range, .75-2.14). The LVIS stents were successfully implanted in all patients. Mean follow-up period was 9.3 ± 1.9 months (range, 6-15 months). Immediate angiographic evaluation demonstrated complete occlusion in 13 (40.6%) patients, while neck remnant and residual sac were observed in 12 (37.5%) and 7 (21.9%), respectively. All patients had moderate disability (mRS 2-3) at discharge. Number of aneurysms with complete occlusion significantly increased and 82.1% of the patients (23 of 28) demonstrated complete occlusion at follow-up (P = .0015). Among these, 27 had good outcome (mRS 0-1; 96.9%) with significant improvement compared to discharge (P = .0001). There was no recurrence or enlargement of the residual aneurysms. Additionally, there were no procedure-related complications except the one (3.6%) showing asymptomatic stenosis of the posterior cerebral artery in follow-up imagings. CONCLUSIONS: Stent-assisted coiling of rTIAs with LVIS device provides high rates of technical success and complete occlusion at mid-term follow-up with an excellent safety profile.

Data Compression Based on Stacked RBM-AE Model for Wireless Sensor Networks.

Data compression is very important in wireless sensor networks (WSNs) with the limited energy of sensor nodes. Data communication results in energy consumption most of the time; the lifetime of sensor nodes is usually prolonged by reducing data transmission and reception. In this paper, we propose a new Stacked RBM Auto-Encoder (Stacked RBM-AE) model to compress sensing data, which is composed of a encode layer and a decode layer. In the encode layer, the sensing data is compressed; and in the decode layer, the sensing data is reconstructed. The encode layer and the decode layer are composed of four standard Restricted Boltzmann Machines (RBMs). We also provide an energy optimization method that can further reduce the energy consumption of the model storage and calculation by pruning the parameters of the model. We test the performance of the model by using the environment data collected by Intel Lab. When the compression ratio of the model is 10, the average Percentage RMS Difference value is 10.04%, and the average temperature reconstruction error value is 0.2815 °C. The node communication energy consumption in WSNs can be reduced by 90%. Compared with the traditional method, the proposed model has better compression efficiency and reconstruction accuracy under the same compression ratio. Our experiment results show that the new neural network model can not only apply to data compression for WSNs, but also have high compression efficiency and good transfer learning ability.

Genetic variant near TERC influencing the risk of gliomas with older age at diagnosis in a Chinese population.

A recent genome-wide association study has identified an association between rs1920116 near TERC and high-grade glioma in populations of European ancestry. In order to evaluate the effect of the SNP rs1920116 near TERC in the Chinese population, we examined associations of this candidate SNP with glioma in a sample of 1970 Chinese Han individuals. SNP genotype data were available for 980 Chinese glioma patients and 990 healthy controls. Logistic regression analyses were performed to evaluate the association between rs1920116 and glioma risk adjusted for age, gender and stratified by tumor grade where appropriate. The allele G at TERC rs1920116 are risk factors for gliomas, and its association with glioma risk was consistent across tumor subgroups in the Chinese Han population (OR = 1.18-1.21). In order to assess variation in SNP effect size at different patient ages, glioma cases and controls were divided into 3 age strata, in years: <50, 50-59, and 60+. The results of multiple logistic regression analyses indicate that the SNP has age-specific effects on the risk of developing glioma. Our report confirmed the effects of rs1920116 near TERC on glioma occurring in older peoples in the Chinese Han population for the first time. As TERC is a candidate for inter-individual variation in telomere length, our study supports the hypothesis that telomerase-related mechanisms of telomere maintenance are more associated with gliomas that develop later in life.

Aquatic debris detection using embedded camera sensors.

Aquatic debris monitoring is of great importance to human health, aquatic habitats and water transport. In this paper, we first introduce the prototype of an aquatic sensor node equipped with an embedded camera sensor. Based on this sensing platform, we propose a fast and accurate debris detection algorithm. Our method is specifically designed based on compressive sensing theory to give full consideration to the unique challenges in aquatic environments, such as waves, swaying reflections, and tight energy budget. To upload debris images, we use an efficient sparse recovery algorithm in which only a few linear measurements need to be transmitted for image reconstruction. Besides, we implement the host software and test the debris detection algorithm on realistically deployed aquatic sensor nodes. The experimental results demonstrate that our approach is reliable and feasible for debris detection using camera sensors in aquatic environments.

[Antitumor effect of baicalin on rat brain glioma].

OBJECTIVE: To investigate the therapeutic mechanism of baicalin on rat brain glioma. METHODS: Deep brain glioma models were established by injection of glioma cell line C6 cells into the brain of Wistar rats. The rats at 7 days after modeling were randomly divided into tumor control group (0.9% NaCl solution 30 mg×kg(-1)×d(-1) gavage)and experimental groups. The experimental rats was divided into 3 groups: low dose group (50 mg×kg(-1)×d(-1)), middle dose group (100 mg×kg(-1)×d(-1)) and high dose group (200 mg×kg(-1)×d(-1)), given the baicalin by gavage. Pathological and electron microscopic changes were observed. The expressions of p53 and Bcl-2 were determined by immunohistochemistry, and the changes of MRI, the average survival time and body weight of the rats in each group after treatments were analyzed. RESULTS: Compared with the control group, the tumor diameter and volume of high dose group rats before sacrifice were significantly reduced (P < 0.01), and the survival time was significantly prolonged (P < 0.01). Immunohistochemistry revealed strong positive expression rate of mutant p53 (84.47 ± 3.74)% and moderately positive rate (47.28 ± 2.38)% in the control group, significantly higher than that in the negative group (12.91 ± 1.07)% (P < 0.01). The positive rate of mutant p53 of the high dose group was (46.42 ± 2.19)%, significantly lower than that of the control group (84.47 ± 3.74)% (P < 0.01). The expression rate of Bcl-2 in the control group was strongly positive (86.51 ± 4.17)% and moderate positive (48.19 ± 2.11)%, significantly higher than that of the negative group (10.36 ± 1.43)% (P < 0.01). Electron microscopy revealed that baicalin caused damages of the cell nuclei and organelles in the gliomas. CONCLUSIONS: Baicalin has significant inhibitory effect on glioma in vivo, and its mechanism may be related to cell apoptosis induced by down-regulated expression of mutant p53, but not related with Bcl-2 expression.

Modeling of pollutant distribution based on mobile sensor networks.

Pollution monitoring based on wireless sensor networks is becoming highly attractive. This paper presents an effective pollutant distribution modeling approach using a mobile sensor network. As for mobile nodes, energy consumption and link quality between nodes are two key factors. In the proposed approach, we present an autonomous sensing model and an energy-driven motion control scheme, which can make a good trade-off between energy efficiency and modeling accuracy. A comprehensive set of simulations demonstrate that our approach can model the pollutant distribution with less iteration times and higher accuracy. In particular, even for a relatively complex concentration field, the similarity between the reconstructed model and the pollutant distribution can reach 95% through about 20 iterations using 25 mobile sensor nodes. Moreover, we validated the feasibility of the proposed approach through an actual monitoring of water pollutant distribution.

Muscle Fatigue Analysis With Optimized Complementary Ensemble Empirical Mode Decomposition and Multi-Scale Envelope Spectral Entropy.

The preprocessing of surface electromyography (sEMG) signals with complementary ensemble empirical mode decomposition (CEEMD) improves frequency identification precision and temporal resolution, and lays a good foundation for feature extraction. However, a mode-mixing problem often occurs when the CEEMD decomposes an sEMG signal that exhibits intermittency and contains components with a near-by spectrum into intrinsic mode functions (IMFs). This paper presents a method called optimized CEEMD (OCEEMD) to solve this problem. The method integrates the least-squares mutual information (LSMI) and the chaotic quantum particle swarm optimization (CQPSO) algorithm in signal decomposition. It uses the LSMI to calculate the correlation between IMFs so as to reduce mode mixing and uses the CQPSO to optimize the standard deviation of Gaussian white noise so as to improve iteration efficiency. Then, useful IMFs are selected and added to reconstruct a de-noised signal. Finally, considering that the IMFs contain abundant frequency and envelope information, this paper extracts the multi-scale envelope spectral entropy (MSESEn) from the reconstructed sEMG signal. Some original sEMG signals, which were collected from experiments, were used to validate the methods. Compared with the CEEMD and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the OCEEMD effectively suppresses mode mixing between IMFs with rapid iteration. Compared with approximate entropy (ApEn) and sample entropy (SampEn), the MSESEn clearly shows a declining tendency with time and is sensitive to muscle fatigue. This suggests a potential use of this approach for sEMG signal preprocessing and the analysis of muscle fatigue.

Structural assembly of the tailed bacteriophage ϕ29.

The mature virion of the tailed bacteriophage ϕ29 is an ~33 MDa complex that contains more than 450 subunits of seven structural proteins assembling into a prolate head and a short non-contractile tail. Here, we report the near-atomic structures of the ϕ29 pre-genome packaging head (prohead), the mature virion and the genome-emptied virion. Structural comparisons suggest local rotation or oscillation of the head-tail connector upon DNA packaging and release. Termination of the DNA packaging occurs through pressure-dependent correlative positional and conformational changes in the connector. The funnel-shaped tail lower collar attaches the expanded narrow end of the connector and has a 180-Å long, 24-strand ß barrel narrow stem tube that undergoes conformational changes upon genome release. The appendages form an interlocked assembly attaching the tail around the collar. The membrane active long loops at the distal end of the tail knob exit during the late stage of infection and form the cone-shaped tip of a largely hydrophobic helix barrel, prepared for membrane penetration.

Camera sensor-based contamination detection for water environment monitoring.

Water environment monitoring is of great importance to human health, ecosystem sustainability, and water transport. Unlike traditional water quality monitoring problems, this paper focuses on visual perception of water environment. We first introduce the development of a customized aquatic sensor node equipped with an embedded camera sensor. Based on this platform, we present an efficient and holistic contamination detection approach, which can automatically adapt to the detection of floating debris in dynamic waters or the identification of salient regions in static waters. Our approach is specifically designed based on compressed sensing theory to give full consideration to the unique challenges in water environment and the resource constraints on sensor nodes. Both laboratory and field experiments demonstrate the proposed method can fast and accurately detect various types of water pollutants and is a better choice for camera sensor-based water environment monitoring compared with other methods.

An improved correlation method for amplitude estimation of gravitational background signal with time-varying frequency.

In the measurement of the gravitational constant G with angular acceleration method, the accurate estimation of the amplitude of the useful angular acceleration generated by source masses depends on the effective subtraction of the spurious gravitational signal caused by room fixed background masses. The gravitational background signal is of time-varying frequency, and mainly consists of the prominent fundamental frequency and second harmonic components. We propose an improved correlation method to estimate the amplitudes of the prominent components of the gravitational background signal with high precision. The improved correlation method converts a sinusoidal signal with time-varying frequency into a standard sinusoidal signal by means of the stretch processing of time. Based on Gaussian white noise model, the theoretical result shows the uncertainty of the estimated amplitude is proportional to σNT, where σ and N are the standard deviation of noise and the number of the useful signal period T, respectively.

Influence of temperature on period of torsion pendulum with a high-Q fused silica fiber.

Due to the high-Q fused silica fiber's extreme sensitivity to temperature change, the period estimation of torsion pendulum with high precision depends on the effective correction of the thermoelastic effect. In the measurement of G with the time-of-swing method, we analyze the complex relation between temperature and the pendulum's period and propose a developed method to find the shear thermoelasticity coefficient as well as isolate the influence of temperature on period alone. The result shows that the shear thermoelasticity coefficient is 101(2) × 10(-6)/°C, the resultant correction to Δ(ω(2)) is 9.16(0.18) ppm, and the relative uncertainty to G is less than 1 ppm.

Four common polymorphisms in microRNAs and the risk of adult glioma in a Chinese case-control study.

Emerging evidence has shown that microRNAs (miRNAs) participate in human carcinogenesis as tumor suppressors or oncogenes. It has been suggested that four common single nucleotide polymorphisms (SNPs; miR-146aG > C, 149C > T, 196a2C > T, and 499A > G) are associated with susceptibility to numerous malignancies. However, published results are inconsistent and inclusive. To further investigate the role of these loci, we examined the association of the miRNA polymorphisms with the risk of gliomas in a Han population in northeastern China. Both miR-146aG > C and 196a2C > T showed allelic differences between glioma patients and healthy controls in the studied population, with an OR of 1.30 (P = 0.0006) and an odds ratio (OR) of 1.25 (P = 0.003), respectively. Logistic regression analysis also revealed that the 146aG > C and 196a2C > T wild-type homozygous carriers had an increased glioma risk compared to the variant carriers. Besides, in pairwise comparisons two SNP combinations were associated with the risk of glioma. Among others, carriers of both homozygous risk genotypes, i.e., 146aGG and 196a2CC were associated with a nearly 4-fold increased risk of glioma (OR = 3.77, P = 1.3 × 10(-4)). Overall, glioma risk increased with increasing numbers of risk variant alleles. These results suggest that the miR-146aG > C and 196a2C > T might influence the risk of developing glioma in a northeastern Han Chinese population.

Genetic polymorphisms in the DNA repair gene XRCC1 and susceptibility to glioma in a Han population in northeastern China: a case-control study.

BACKGROUND: Several single nucleotide polymorphisms (SNPs) in the X-ray cross-complementing group 1 (XRCC1) gene have been shown to influence DNA repair and to modify cancer susceptibility. To investigate the role of these loci further, we examined the association of three XRCC1 polymorphisms with the risk of gliomas in a Han population in northeastern China. METHODS: Using a PCR-RFLP method, XRCC1 Arg194Trp, Arg280His and Arg399Gln were genotyped in 624 glioma patients and 580 healthy controls. RESULTS: Significant differences in the distribution of the Arg399Gln allele were detected between glioma patients and healthy controls by a logistic regression analysis (OR=1.35, 95%CI 1.17-1.68, P=0.001). Our data also revealed that the Arg399Gln variant (allele A) carriers had an increased glioma risk compared to the wild-type (allele G) homozygous carriers (OR=1.40, 95%CI 1.12-1.76, P=0.003). CONCLUSIONS: These results suggest that the XRCC1 Arg399Gln might influence the risk of developing glioma in a Han population in northeastern Chinese.

An improved correlation method for determining the period of a torsion pendulum.

Considering variation of environment temperature and unhomogeneity of background gravitational field, an improved correlation method was proposed to determine the variational period of a torsion pendulum with high precision. The result of processing experimental data shows that the uncertainty of determining the period with this method has been improved about twofolds than traditional correlation method, which is significant for the determination of gravitational constant with time-of-swing method.