Predicting the multi-label protein subcellular localization through multi-information fusion and MLSI dimensionality reduction based on MLFE classifier.

MOTIVATION: Multi-label (ML) protein subcellular localization (SCL) is an indispensable way to study protein function. It can locate a certain protein (such as the human transmembrane protein that promotes the invasion of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) or expression product at a specific location in a cell, which can provide a reference for clinical treatment of diseases such as coronavirus disease 2019 (COVID-19). RESULTS: The article proposes a novel method named ML-locMLFE. First of all, six feature extraction methods are adopted to obtain protein effective information. These methods include pseudo amino acid composition, encoding based on grouped weight, gene ontology, multi-scale continuous and discontinuous, residue probing transformation and evolutionary distance transformation. In the next part, we utilize the ML information latent semantic index method to avoid the interference of redundant information. In the end, ML learning with feature-induced labeling information enrichment is adopted to predict the ML protein SCL. The Gram-positive bacteria dataset is chosen as a training set, while the Gram-negative bacteria dataset, virus dataset, newPlant dataset and SARS-CoV-2 dataset as the test sets. The overall actual accuracy of the first four datasets are 99.23%, 93.82%, 93.24% and 96.72% by the leave-one-out cross validation. It is worth mentioning that the overall actual accuracy prediction result of our predictor on the SARS-CoV-2 dataset is 72.73%. The results indicate that the ML-locMLFE method has obvious advantages in predicting the SCL of ML protein, which provides new ideas for further research on the SCL of ML protein. AVAILABILITY AND IMPLEMENTATION: The source codes and datasets are publicly available at https://github.com/QUST-AIBBDRC/ML-locMLFE/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MTDCNet: A 3D multi-threading dilated convolutional network for brain tumor automatic segmentation.

Glioma is one of the most threatening tumors and the survival rate of the infected patient is low. The automatic segmentation of the tumors by reliable algorithms can reduce diagnosis time. In this paper, a novel 3D multi-threading dilated convolutional network (MTDC-Net) is proposed for the automatic brain tumor segmentation. First of all, a multi-threading dilated convolution (MTDC) strategy is introduced in the encoder part, so that the low dimensional structural features can be extracted and integrated better. At the same time, the pyramid matrix fusion (PMF) algorithm is used to integrate the characteristic structural information better. Secondly, in order to make the better use of context semantical information, this paper proposed a spatial pyramid convolution (SPC) operation. By using convolution with different kernel sizes, the model can aggregate more semantic information. Finally, the multi-threading adaptive pooling up-sampling (MTAU) strategy is used to increase the weight of semantic information, and improve the recognition ability of the model. And a pixel-based post-processing method is used to prevent the effects of error prediction. On the brain tumors segmentation challenge 2018 (BraTS2018) public validation dataset, the dice scores of MTDC-Net are 0.832, 0.892 and 0.809 for core, whole and enhanced of the tumor, respectively. On the BraTS2020 public validation dataset, the dice scores of MTDC-Net are 0.833, 0.896 and 0.797 for the core tumor, whole tumor and enhancing tumor, respectively. Mass numerical experiments show that MTDC-Net is a state-of-the-art network for automatic brain tumor segmentation.

Development of Fixed-Wing UAV 3D Coverage Paths for Urban Air Quality Profiling.

Due to the ever-increasing industrial activity, humans and the environment suffer from deteriorating air quality, making the long-term monitoring of air particle indicators essential. The advances in unmanned aerial vehicles (UAVs) offer the potential to utilize UAVs for various forms of monitoring, of which air quality data acquisition is one. Nevertheless, most current UAV-based air monitoring suffers from a low payload, short endurance, and limited range, as they are primarily dependent on rotary aerial vehicles. In contrast, a fixed-wing UAV may be a better alternative. Additionally, one of the most critical modules for 3D profiling of a UAV system is path planning, as it directly impacts the final results of the spatial coverage and temporal efficiency. Therefore, this work focused on developing 3D coverage path planning based upon current commercial ground control software, where the method mainly depends on the Boustrophedon and Dubins paths. Furthermore, a user interface was also designed for easy accessibility, which provides a generalized tool module that links up the proposed algorithm, the ground control software, and the flight controller. Simulations were conducted to assess the proposed methods. The result showed that the proposed methods outperformed the existing coverage paths generated by ground control software, as it showed a better coverage rate with a sampling density of 50 m.

Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-Inertial Approach.

This work aimed to develop an autonomous system for unmanned aerial vehicles (UAVs) to land on moving platforms such as an automobile or a marine vessel, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Unlike most state-of-the-art UAV landing frameworks that rely on UAV onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such a novel configuration can therefore lighten the burden of the UAV, and the computation power of the ground vehicle/marine vessel can be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted, and the results show that precise autonomous landing on a 43 cm × 43 cm platform can be performed.

Development of a photoelectric phase-locked loop model to better synchronize frequency combs and microwaves.

The high phase coherence between ultralow-noise microwaves and ultrahigh-stable optical frequency combs (OFCs) is of both scientific and technological relevance for telecommunication, timekeeping, astronomy, and metrology. Here, a photoelectric phase-locked loop (PLL) model with ultralow phase noise based on the optical-microwave phase detector technique has been proposed and experimentally demonstrated. A detailed mathematical model for tight, real-time phase synchronization of OFCs and microwaves is developed to investigate the feasibility and analyze the characteristics of the phase-coherent system. We fabricate a compact PLL circuit with a proportional-integral-derivative regulator for the synchronization of an OFC to a microwave reference. Once synchronized, the long-term stability of the OFC agrees to 2.4×10-14 at a 1000 s averaging time, which is enhanced by more than 4 orders of magnitude. Besides, the OFC almost acquires the same frequency stability as the microwave source. The ability to better phase synchronize OFCs and microwaves enables a wide range of applications beyond the laboratory.

Development of Model Predictive Controller for a Tail-Sitter VTOL UAV in Hover Flight.

This paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A 'cross' configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency level flight. The six-degree-of-freedom (DOF) nonlinear dynamic model of the UAV is built based on aerodynamic data obtained from wind tunnel experiments. The model predictive position controller is then developed with the augmented linearized state-space model. Measured and unmeasured disturbance model are introduced into the modeling and optimization process to improve disturbance rejection ability. The MPC controller is first verified and tuned in the hardware-in-loop (HIL) simulation environment and then implemented in an on-board flight computer for real-time indoor experiments. The simulation and experimental results show that the proposed MPC position controller has good trajectory tracking performance and robust position holding capability under the conditions of prevailing and gusty winds.

PCLR: phase-constrained low-rank model for compressive diffusion-weighted MRI.

PURPOSE: This work develops a compressive sensing approach for diffusion-weighted (DW) MRI. THEORY AND METHODS: A phase-constrained low-rank (PCLR) approach was developed using the image coherence across the DW directions for efficient compressive DW MRI, while accounting for drastic phase changes across the DW directions, possibly as a result of eddy current, and rigid and nonrigid motions. In PCLR, a low-resolution phase estimation was used for removing phase inconsistency between DW directions. In our implementation, GRAPPA (generalized autocalibrating partial parallel acquisition) was incorporated for better phase estimation while allowing higher undersampling factor. An efficient and easy-to-implement image reconstruction algorithm, consisting mainly of partial Fourier update and singular value decomposition, was developed for solving PCLR. RESULTS: The error measures based on diffusion-tensor-derived metrics and tractography indicated that PCLR, with its joint reconstruction of all DW images using the image coherence, outperformed the frame-independent reconstruction through zero-padding FFT. Furthermore, using GRAPPA for phase estimation, PCLR readily achieved a four-fold undersampling. CONCLUSION: The PCLR is developed and demonstrated for compressive DW MRI. A four-fold reduction in k-space sampling could be readily achieved without substantial degradation of reconstructed images and diffusion tensor measures, making it possible to significantly reduce the data acquisition in DW MRI and/or improve spatial and angular resolutions.

Controllability and observability of fractional linear systems with two different orders.

This paper is concerned with the controllability and observability for a class of fractional linear systems with two different orders. The sufficient and necessary conditions for state controllability and state observability of such systems are established. The results obtained extend some existing results of controllability and observability for fractional dynamical systems.

METTL14-mediated methylation of SLC25A3 mitigates mitochondrial damage in osteoblasts, leading to the improvement of osteoporosis.

PURPOSE: Osteoporosis is linked to impaired function of osteoblasts, and decreased expression of METTL14 may result in abnormal differentiation of these bone-forming cells. However, the specific impact of METTL14 on osteoblast differentiation and its underlying mechanisms are not yet fully understood. METHODS AND RESULTS: This study discovered a positive correlation between METTL14 expression and bone formation in specimens from osteoporosis patients and ovariectomized (OVX) mice. Additionally, METTL14 targeting of SLC25A3 contributed to the restoration of mitochondrial ROS levels and mitochondrial membrane potential in osteoblasts and promoted osteoblast differentiation. Moreover, in vivo experiments showed that METTL14 enhanced bone formation, and therapeutic introduction of METTL14 countered the decrease in bone formation in OVX mice. CONCLUSIONS: Overall, these findings emphasize the crucial role of the METTL14/SLC25A3 signaling axis in osteoblast activity, suggesting that this axis could be a potential target for improving osteoporosis.

Toll-Like Receptors 7/8: A Paradigm for the Manipulation of Immunologic Reactions for Immunotherapy.

The innate immune system recognizes conserved features of viral and microbial pathogens through pattern recognition receptors (PRRs). Toll-like receptors (TLRs) are one type of PRR used by the innate immune system to mediate the secretion of proinflammatory cytokines and promote innate and adaptive immune responses. TLR family members TLR7 and TLR8 (referred to as TLR7/8 from herein) are endosomal transmembrane receptors that recognize purine-rich single-stranded RNA (ssRNA) and bacterial DNA, eliciting an immunologic reaction to pathogens. TLR7/8 were discovered to mediate the secretion of proinflammatory cytokines by activating immune cells. In addition, accumulating evidence has indicated that TLR7/8 may be closely related to numerous immune-mediated disorders, specifically several types of cancer, autoimmune disease, and viral disease. TLR7/8 agonists and antagonists, which are used as drugs or adjuvants, have been identified in preclinical studies and clinical trials as promising immune stimulators for the immunotherapy of these immune-mediated disorders. These results provided reasoning to further explore immunotherapy for the treatment of immune-mediated disorders. Nevertheless, numerous needs remain unmet, and the therapeutic effects of TLR7/8 agonists and antagonists are poor and exert strong immune-related toxicities. The present review aimed to provide an overview of the TLR family members, particularly TLR7/8, and address the underlying molecular mechanisms and clinical implications of TLR7/8 in immune-mediated disorders. The aim of the work is to discuss the underlying molecular mechanisms and clinical implications of TLR7/8 in immune-mediated disorders.

Field emission properties of AIN nanostructures.

AIN with different morphologies, including thin film, nanowires, nanoneedles and nanochilies, depending on the controlled growth parameters, have been successfully synthesized by chemical vapor deposition technique. Field emission properties have been systematically studied. The experimental results show that all AIN nanostructures have good field emission properties. In comparison, AIN nano-chilies possess the best field emission properties with a low turn-on and threshold fields of 1.8 V/microm and 3.1 V/microm, respectively. The results suggest that the morphological modulation is an effective way to optimize field emission performance of nanostructures.

Cost-Effectiveness Analysis of Dapagliflozin Plus Standard Treatment for Patients With Type 2 Diabetes and High Risk of Cardiovascular Disease in China.

Purpose: To evaluate the long-term cost-effectiveness of dapagliflozin, in addition to standard treatment, for the treatment of adult patients with type 2 diabetes (T2DM) at high cardiovascular risk from the Chinese healthcare system perspective. Methods: A decision-analytic Markov model with one-year cycles was developed to evaluate the health and economic outcomes in patients with T2DM and high risk of cardiovascular disease (CVD) treated with standard treatment and dapagliflozin plus standard treatment for 30 years. Clinical data, cost, and utility data were extracted from databases or published literature. Quality-adjusted life-years (QALYs), costs (€/¥ 2021) as well as incremental cost-effectiveness ratios (ICERs) were calculated. Deterministic and probabilistic sensitivity analyses were performed to assess the uncertainty in the results. Results: Compared with standard treatment, dapagliflozin plus standard treatment was predicted to result in an additional 0.25 QALYs (12.26 QALYs vs. 12.01 QALYs) at an incremental cost of €4,435.81 (¥33,875.83) per patient. The ICER for dapagliflozin plus standard treatment vs. standard treatment was €17,742.07 (¥135,494.41) per QALY gained, which was considered cost-effective in China compared to three times the GDP per capita in 2021 (€31,809.77/¥242,928). The deterministic and probabilistic sensitivity analyses showed the base-case results to be robust. Conclusions: The study suggests that, from the perspective of the Chinese health system, dapagliflozin plus standard treatment is a cost-effective option for patients with T2DM at high cardiovascular risk. These findings may help clinicians make the best treatment decisions for patients with T2DM at high cardiovascular risk.

Image smoothing using regularized entropy minimization and self-similarity for the quantitative analysis of drug diffusion.

BACKGROUND: Targetable drug delivery is an important method for the treatment of liver tumors. For the quantitative analysis of drug diffusion, the establishment of a method for information collection and characterization of extracellular space is developed by imaging analysis of magnetic resonance imaging (MRI) sequences. In this paper, we smoothed out interferential part in scanned digital MRI images. MATERIALS AND METHODS: Making full use of priors of low rank, nonlocal self-similarity, and regularized sparsity-promoting entropy, a block-matching regularized entropy minimization algorithm is proposed. Sparsity-promoting entropy function produces much sparser representation of grouped nonlocal similar blocks of image by solving a nonconvex minimization problem. Moreover, an alternating direction method of multipliers algorithm is proposed to iteratively solve the problem above. RESULTS AND CONCLUSIONS: Experiments on simulated and real images reveal that the proposed method obtains better image restorations compared with some state-of-the-art methods, where most information is recovered and few artifacts are produced.

PBP1a glycosyltransferase and transpeptidase activities are both required for maintaining cell morphology and envelope integrity in Shewanella oneidensis.

In rod-shaped Gram-negative bacteria, penicillin binding protein 1a (PBP1a) and 1b (PBP1b) form peptidoglycan-synthesizing complexes with the outer membrane lipoprotein LpoA and LpoB, respectively. Escherichia coli mutants lacking PBP1b/LpoB are sicker than those lacking PBP1a/LpoA. However, we previously found that mutants lacking PBP1a/LpoA but not PBP1b/LpoB are deleterious in Shewanella oneidensis. Here, we show that S. oneidensis PBP1a (SoPBP1a) contains conserved signature motifs with its E. coli counterpart, EcPBP1a. Although EcPBP1a play a less prominent role in E. coli, it is capable of substituting for the SoPBP1a in a manner dependent on SoLpoA. In S. oneidensis, expression of PBP1b is lower than PBP1a, and therefore the additional expression of SoPBP1b at low levels can functionally compensate for the absence of SoPBP1a. Importantly, S. oneidensis PBP1a variants lacking either glycosyltransferase (GTase) or transpeptidase (TPase) activity fail to maintain normal morphology and cell envelope integrity. Similarly, SoPBP1b variants also fail to compensate for the loss of SoPBP1a. Furthermore, overproduction of variants of SoPBP1a, but not SoPBP1b, has detrimental effects on cell morphology in S. oneidensis wild type cells. Overall, our results indicate that the combined enzymatic activities of SoPBP1a are essential for cell wall homeostasis.

Spatial variations of arsenic and heavy metal pollutants before and after the water-sediment regulation in the wetland sediments of the Yellow River Estuary, China.

To investigate the effects of the water-sediment regulation on the spatial variations of metals in the surface sediments of the Yellow River Estuary (YRE), sampling sites were set in 2015 (51 sites in June and 33 in October). The content of Cu, Pb, Cd, Cr, Zn, Ni and Mn was determined using inductively coupled plasma spectrometry and of Hg and As atomic fluorescence spectrometry. The results showed that the concentrations of metals in the sediments of YRE were lower after the regulation, while that of most metals increased in the tidal areas of the current estuary with fine particles. Environmental pollution and ecological risk of metals were mainly from Hg and Cd. Metals carried with the silt of the river should be focused. The findings were expected to update the current status of metal pollution of YRE and be helpful for the delicacy management of the regime and silt-laden rivers.

[A non-coated enzyme-linked immunosorbent assay for screening zika virus envelope protein].

OBJECTIVE: To establish a non-coated enzyme-linked immunosorbent assay (ELISA) based on zika virus envelope (E) protein for detecting the expression of E protein in infected cells. METHODS: Adherent Vero-143 cells infected with zika virus in a 96-well plate were fixed, and the antibodies against zika virus E protein were added at an optimized concentration to establish the non-coated ELISA method for E protein. The antiviral activities of lignans compound C1 was evaluated using this method. The accuracy of this non-coated ELISA was verified by RT-PCR, and the cross reaction with dengue virus was assessed. RESULTS: After optimization, the background absorbance at 450 nm of uninfected cells was reduced to about 0.20. The antiviral activities of lignans compound C1 detected by this method were basically consistent with the results of RT-PCR. No cross reaction with dengue virus was found in this assay. CONCLUSIONS: A non- coated ELISA method based on zika virus E protein was established, which can be used for screening antiviral agents against zika virus.

Hydroxypropylcellulose Coating to Improve Graft-to-Bone Healing for Anterior Cruciate Ligament Reconstruction.

An anterior cruciate ligament (ACL) injury is one of the most common injuries in sports, and ACL reconstruction with an artificial ligament is a good treatment for quick recovery. However, current artificial ligaments made of polyethylene terephthalate (PET) are still associated with some problems due to the hydrophobic nature and low biological induction activity of PET. Many efforts have been used to improve the biocompatibility of PET in recent years, and our previous work has shown that surface modification is an effective strategy. Here, a hydroxypropylcellulose (HPC) coating was applied on the surface of a PET artificial ligament order to improve its biocompatibility. The effects of the HPC coating on PET artificial ligament graft-bone healing was investigated in vitro using bone marrow stromal cells (BMSCs), fibroblasts, and RSC-364 cells as well as in vivo in a beagle dog model of ACL reconstruction. HPC was coated successfully on the PET and significantly promoted cell growth, adhesion, and capability of osteogenic differentiation compared to the PET graft without HPC coating. In vivo, the HPC coating significantly enhanced ligament tissue regeneration. Moreover, higher expression of some bone-formation- and ligament-tissue-regeneration-contributing proteins and cell factors, such as COL1, BMP-7, COL3, OCN, RUNX2, TGF-ß1, and VEGF, was observed on the HPC-coated PET artificial ligament in comparison with the pure PET artificial ligament. In conclusion, HPC coating can significantly improve the cytocompatibility and graft-to-bone healing of a PET artificial ligament for ACL reconstruction.

Frame-Based CT Image Reconstruction via the Balanced Approach.

Frame-based regularization method as one kind of sparsity representation method has been developed in recent years and has been proved to be an efficient method for CT image reconstruction. However, most of the developed CT image reconstruction methods are analysis-based frame methods. This paper proposes a novel frame-based balanced hybrid model with two sparse regularization terms for CT image reconstruction. We generalize the fast alternating direction method to solve the proposed model so that every subproblem can be easily solved. The numerical experiments suggest that the proposed hybrid balanced-based wavelet regularization scheme is efficient in terms of reducing the defined reconstruction root mean squared error and improving the signal to noise ratio in CT image reconstruction.

Circulating miRNAs as novel diagnostic biomarkers in hepatocellular carcinoma detection: a meta-analysis based on 24 articles.

The diagnostic value and suitability of circulating miRNAs for the detection of hepatocellular carcinoma have been inconsistent in the literature. A meta-analysis is used to systematically evaluate the diagnostic value of circulating miRNAs. Eligible studies were selected and the heterogeneity was assessed by subgroup analysis, meta-regression, and publication bias. After strictly and comprehensive screening, the source methods, internal reference and the cut-off values of the included miRNAs were first listed. Circulating miRNAs demonstrated a relatively good diagnostic value in hepatocellular carcinoma, In the subgroup analysis, diagnosis odds ratio showed a higher accuracy with multiple miRNAs than with a single miRNA as well as with serum types than plasma types. In addition, although miRNAs have many expression patterns, the high frequency expression miRNAs (miR-21, miR-199 and miR-122) might be more specific for the diagnosis of hepatocellular carcinoma.The sources of heterogeneity might be related to the number of miRNAs and the specimen types in meta-regression. Furthermore, it's surprised that the pooled studies were first demonstrated publication bias (P < 0.05). In conclusion, multiple miRNAs in serum have a better diagnostic value, and the publication bias was stable. To validate the potential applicability of miRNAs in the diagnosis of hepatocellular carcinoma, more rigorous studies are needed to confirm these conclusions.

Detection of Total and Pathogenic Vibrio parahaemolyticus in Shellfish Growing along the South Yellow Sea and the East China Sea.

This study was conducted to monitor the densities of total and pathogenic Vibrio parahaemolyticus in 300 samples of nine shellfish species harvested from the coasts of the South Yellow Sea and the East China Sea (N 23° to 34°, E 116° to 124°), People's Republic of China, between May and October 2015. Total V. parahaemolyticus densities were measured, and V. parahaemolyticus isolates were biochemically identified with probes for the thermostable direct hemolysin gene (tdh) and the thermostable direct hemolysin-related hemolysin gene (trh). We found that 202 of the 300 samples were positive for V. parahaemolyticus from all the sites: 58 of the 100 samples from the Fujian province, 71 of the 100 samples from the Zhejiang province, and 73 of the 100 samples from the Jiangsu province. In most (170) of the 300 samples, V. parahaemolyticus densities were 0.3 to 10 most probable number (MPN)/g; five lots exceeded 110 MPN/g, and two lots were estimated at 110 MPN/g. Among the 202 V. parahaemolyticus strains, only one was trh positive. Densities of V. parahaemolyticus in these shellfish were temperature dependent, with highest densities in June and July. Among the nine mollusk species, V. parahaemolyticus was most abundant in the agemaki clam (Sinonovacula constricta). The highest and lowest V. parahaemolyticus prevalences were found in oriental cyclina (Cyclina sinensis, 93.8%) and mussels (Mytilus edulis, 28.1%), respectively. Overall, although V. parahaemolyticus is widely distributed in marine environments, the density of V. parahaemolyticus was low and the prevalence of the main virulence factor was very low in shellfish along the coasts of the South Yellow Sea and East China Sea, which is important from a public health perspective. Data presented here will be useful for correlational research and can be utilized for developing risk management plans that establish food safety guidelines for V. parahaemolyticus in Chinese shellfish.