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Bronchopulmonary dysplasia (BPD) is a common chronic respiratory disease in preterm infants caused by multifactorial etiology. Genetic factors are involved in the occurrence of BPD, but studies have found that candidate genes have poor reproducibility and are influenced by ethnic heterogeneity; therefore, more exploration is still needed. We performed whole-exon sequencing in 34 preterm infants with BPD and 32 non-BPD control neonates. The data were analyzed and interpreted by Fisher difference comparison, PLINK and eQTL association analysis, KEGG and GO enrichment analysis, STRING tool, Cytoscape software, ProtParam tool, HOPE online software, and GEOR2 analysis on NCBI GEO dataset. BPD has a highly heterogeneity in different populations, and we found 35 genes overlapped with previous whole-exon sequencing studies, such as APOB gene. Arterial and epithelial cell development and energy metabolism pathways affect BPD. In this study, 24 key genes were identified, and BIVM rs3825519 mutation leads to prolonged assisted ventilation in patients with BPD. A novel DDAH1 mutation site (NM_012137: exon1: c.89 T > G: p.L30R) was found in 9 BPD patients.Conclusion: BIVM gene rs3825519 mutation may play a role in the pathogenesis of BPD by affecting cilia movement, and the DDAH1 and APOB genes mutations may have a pathogenic role in BPD. What is Known: • Genetic factors are involved in the occurrence of bronchopulmonary dysplasia. • The candidate genes have poor reproducibility and are influenced by ethnic heterogeneity, therefore, more exploration is still needed. What is New: • We identified the role of susceptible SNPs in BPD in Shenzhen, China, and identified 24 key genes that influence the pathogenesis of BPD, and also found 35 genes overlapped with previous whole exon sequencing studies, such as APOB gene. • We found that BIVM and DDAH1 genes may play a pathogenic role in the pathogenesis of BPD.

Purpose: This study investigated possible mechanism of left atrial appendage (LAA) thrombosis and constructed a model to evaluate the future risk of LAA thrombosis and spontaneous echo contrast (SEC) in non-valvular atrial fibrillation (NVAF) patients. Methods: This retrospective study included 2591 patients diagnosed with NVAF. Patients were divided based on the presence of transesophageal echocardiography (TEE) into a thrombus group, SEC group, and control group. General, biochemical, and echocardiography data of the three groups were analyzed. The variables independently associated with LAA thrombosis and SEC were determined by the logistic regression analysis. A nomogram was constituted based on the regression analysis and the discriminatory ability was analyzed by receiver operating characteristic (ROC) curve. Results: LAA thrombosis and SEC were present in 110 (4.2%) patients and 103 (3.9%) patients, respectively. AF type (OR = 1.857), previous stroke (OR = 1.924), fibrinogen (OR = 1.636), diameters of the left atria (OR = 1.094), left ventricular ejection fraction (OR = 0.938), and LAA maximum caliber (OR = 1.238) resulted as independent risk factors for LAA thrombosis and SEC. The area under curve of the nomogram established by multivariate logistic regression was 0.824. Conclusions; Through the study, 6 independent risk factors related to the LAA thrombosis and SEC were found, and an effective nomogram was constructed to predict the LAA thrombosis and SEC in NVAF patients.

Over the last two generations, there has been a surge of interest in nonmutilating treatment for women with early breast cancer. Neoadjuvant radiation therapy, which is progressively being provided to breast cancer patients, could be used to decrease tumor burden while also providing an ability to examine treatment response. This paper aims to explore the effects of the initiation time of radiotherapy after modified adjuvant radical mastectomy on the prognosis of breast cancer. The EMR data can be used to mine hidden rules, which are of great significance for treatment and prognosis analysis. In collaboration with breast cancer, the appropriate prediction model and visualization method are selected and a visual analysis system for breast cancer group and treatment plan based on electronic medical record is constructed. Patients with multiple dimensions are reduced and clustered to form patient groups. The differences of characteristics among patient groups are intuitively displayed by using Nightingale diagram, word cloud, and time axis visualization methods. The support vector machine (SVM) model is used to predict the treatment scheme. The radiotherapy time after modified radical surgery in the two groups was within 15 weeks (observation group) and 15 weeks (routine group), respectively. The incidence of complications, local recurrence rate, progression-free survival, and quality of life scores of patients in the routine group and observation group were compared. The total incidence of complications differed significantly between the observation and routine groups. The physical function, material function, psychological function, and social function of the observation group were significantly higher than the routine group P < 0.05 . Radiotherapy within 15 weeks after modified radical mastectomy for breast cancer can not only reduce the local recurrence rate but also prolong the progression-free survival of patients, and the incidence of complications will not increase, which will greatly help improve the quality of life of patients.

The current codes in practice define fatigue load models (FLMs) to characterize the bridge damage that is induced by traffic loads. However, most FLMs are specified to load on any single traffic lane, and the characteristics of the uneven traffic load distribution over multiple lanes under real-world conditions are not revealed. This study analyzed the uneven distribution characteristic of truck loading over multiple lanes based on multiple sets of weigh-in-motion (WIM) data and investigated its effect on the fatigue performance of bridges. A novel multi-lane FLM is proposed, comprising a standard fatigue truck model and multi-lane fatigue coefficients. The standard fatigue truck model is the same as FLM II of the Chinese design specification; however, the load value is adjusted using a calibrated coefficient correlated with the bridge length. The multi-lane fatigue coefficients help define the reduction coefficients for the load value and number of fatigue cycles when applying the standard fatigue truck model to a certain traffic lane. Finally, the proposed model and the code-based model are applied to evaluate the fatigue performance of typical steel–concrete composite girder bridges, and the results are compared with the estimations using realistic multi-lane WIM data. The proposed model yields similar estimations of the stress range and fatigue life as using WIM data, whereas the code-based model shows large deviations. The comparisons validate the feasibility and superiority of the proposed multi-lane FLM for the fatigue evaluation of bridges under uneven multi-lane truck loadings.

Recognizing human emotions based on electroencephalogram (EEG) signals has received a great deal of attentions. Most of the existing studies focused on offline analysis, and real-time emotion recognition using a brain computer interface (BCI) approach remains to be further investigated. In this paper, we proposed an EEG-based BCI system for emotion recognition. Specifically, two classes of video clips that represented positive and negative emotions were presented to the subjects one by one, while the EEG data were collected and processed simultaneously, and instant feedback was provided after each clip. Ten healthy subjects participated in the experiment and achieved a high average online accuracy of 91.5% ± 6.34%. The experimental results demonstrated that the subjects emotions had been sufficiently evoked and efficiently recognized by our system. Clinically, patients with disorder of consciousness (DOC), such as coma, vegetative state, and minimally conscious state, suffer from motor impairment and generally cannot provide adequate emotion expressions. Therefore, we applied our emotion recognition BCI system to patients with DOC. Eight DOC patients participated in our experiment, and three of them achieved significant online accuracy. The experimental results show that the proposed BCI system could be a promising tool to detect the emotional states of patients with DOC.

A brain-computer interface (BCI) is a non-muscular communication technology that provides an information exchange channel for our brains and external devices. During the decades, BCI has made noticeable progress and has been applied in many fields. One of the most traditional BCI applications is the BCI speller. This article primarily discusses the progress of research into P300 BCI spellers and reviews four types of P300 spellers: single-modal P300 spellers, P300 spellers based on multiple brain patterns, P300 spellers with multisensory stimuli, and P300 spellers with multiple intelligent techniques. For each type of P300 speller, we further review several representative P300 spellers, including their design principles, paradigms, algorithms, experimental performance, and corresponding advantages. We particularly emphasized the paradigm design ideas, including the overall layout, individual symbol shapes and stimulus forms. Furthermore, several important issues and research guidance for the P300 speller were identified. We hope that this review can assist researchers in learning the new ideas of these novel P300 spellers and enhance their practical application capability.

Objective: This study aims to compare the width and buccal–lingual inclination of the maxillary and mandibular first molar area between children with skeletal class Ⅲ malocclusion and children with normal occlusion from 7 to 9 years old. Methods: A total of 60 childrenaged 7–9 years, 30 with skeletal class Ⅲ malocclusion and 30 with normal occlusion that had one or two impacted teeth, were selected. The cone-beam computed tomography was performed on all patients. The arch width, basal bone widthand buccal-lingual inclination were measured using MIMICS21.0 software for three-dimensional reconstruction. The measured data were tested using the independent-samples t test with SPSS21.0 software. Results: The width of the maxillary basal bone in the skeletal class Ⅲ malocclusion group (59.75 ± 3.14 mm) was statistically smaller than that in the normal group (62.39 ± 3.01 mm) (P ＜ 0.05）. The mandibular basal bone width in the skeletal class Ⅲ malocclusion group (60.00 ± 2.56 mm) was statistically larger than that in the normal group (59.75 ± 3.14 mm) (P < 0.05). The width difference of maxillary and mandibular bases in the skeletal class Ⅲ malocclusion group was (–0.25 ± 1.70 mm) and that in the control group was (4.33 ± 1.20mm); a statistically significant difference was found between the two groups (P < 0.05). The buccal inclination of maxillary molars in the skeletal class Ⅲ malocclusion group was (31.4 ± 8.9°) was significantly higher than that in the control group (17.64 ± 7.3°) (P< 0.01), and the lingual inclination angle of mandibular molars was (45.24 ± 8.3°). It was significantly higher than that in the normal group (37.96 ± 10.18°) (P < 0.05). Conclusion: Transverse maxillary and mandibular discrepancies in the posterior area, and transverse dental compensation of maxillary and mandibular molars in the preliminary stage of mixed dentition were found in patients with skeletal class Ⅲ malocclusion, which provides theoretical support for clinical diagnosis and treatment

Objective To investigate the effect of a bone substitute material combined with fibroblast growth factor-2 (FGF-2) loaded barrier membrane on the preservation of alveolar ridge after tooth extraction. Materials and methods Four dogs were included. Six extraction sockets of each animal received the 3 treatments and were randomly divided into three groups. Group A: negative control; Group B: bovine xenografts + membrane; Group C: bovine xenografts +FGF-2-loaded membrane. CBCT and histological analysis were performed to evaluate changes in the width and height of alveolar ridges and extraction socket bone healing 8 weeks post-extraction. Results CBCT showed that the alveolar bone in Group A was significantly thinner than that in Group B and Group C at 1 and 3 mm apically from the alveolar crest. The alveolar width at 1 mm in Group C (60.99 ± 15.36%) was significantly thicker than that in Group B (39.75 ± 30.18%). Histomorphmetrical measurements showed that the buccal alveolar width at 1 mm was significantly thicker in Groups B and C than in Group A. Additionally, buccal bone height and lingual bone width at 1 mm in Group C (87.06 ± 10.34%, 89.09 ± 10.56%) were significantly greater than in Group A (53.48 ± 23.94%, 82.72 ± 12.59%). Conclusion The present findings indicate that application of bovine bone combined with barrier membrane with or without FGF-2 over tooth sockets can effectively reduce ridge absorption, especially in terms of ridge width and FGF-2 modified membrane seems to improve the outcomes obtained with membrane alone.

Terahertz (THz) waves can cover the characteristic spectra of substances such as plasma, organisms, and biomolecules, whereas THz photons have low energy and do not damage biological tissues. Therefore, its absorption characteristics in the THz region can be used to characterize the internal structure of biomolecules. In this study, we designed a microfluidic chip and combined it with THz technology. The spectral intensity in descending order was found to be deionized water, phenylalanine, histidine, glycine and glutamic acid by observing the THz wave transmission in the range of 0.1-1.0 THz, comparing the frequency domain spectra of four amino acid solutions with volume fraction of 2% and deionized water. It is inferred that different molecular structures of amino acids resulted in different numbers of hydrogen bonds formed between them and water molecules, leading to different degrees of absorption of THz waves. In addition, magnetic fields parallel to the THz wave transmission were used to study the variation of different amino acids with magnetic field intensity. It is found that increasing the magnetic field strength decrease the transmission of THz waves. This is because under the action of the magnetic field, on the one hand, the hydrogen bonds formed by water molecules are strengthened and the absorption of THz waves is enhanced; on the other hand, amino acid molecules aggregate and the radius of molecular clusters increases, thus blocking the transmission of THz waves. Finally, we also calculated the electric conductivity of the solutions to prove the accuracy of the experimental results from a theoretical point of view.

This paper proposes a new implementation method to significantly improve the magnetic sensitivity of a fully symmetric vertical Hall device (FSVHD) based on low-voltage CMOS technology. The FSVHD consists of four identical three-contact vertical Hall elements (3CVHE) and each 3CVHE is located in a low-doped deep n-well. The terminals of the 3CVHE are $\text{n}^{+}$ implanted in an n-well and a $\text{p}^{+}$ implantation in a p-well is performed to act as a trench between two adjacent $\text{n}^{+}$ contacts, enabling Hall current flowing deeply for sensitivity improvement. The influence of the geometry sizes on magnetic sensitivity is exploited utilizing TCAD simulation to obtain the optimized device structure in a $0.18~\mu\text{m}$ CMOS standard technology. The experimental results reveal that the proposed FSVHD with a $\text{p}^{+}$ /p-well trench can attain an improved voltage-related sensitivity of 8.4 mV/VT, which is about 70% higher than that of a conventional FSVHD without a trench in the same CMOS fabrication process, while offset and noise are not degraded. The proposed $\text{p}^{+}$ /p-well implantation trench is a good solution to enhance the sensitivity of a low-voltage CMOS VHD with a low manufacturing cost.

The vibrational and rotational frequencies of most biological macromolecules fall within the terahertz (THz) band; therefore, the THz wave has a strong ability to distinguish substances. Saccharides are important organic substances and the main source of life-sustaining activities. In this study, the spectral characteristics of D-glucose, α-lactose hydrate, and β-maltose hydrate were measured in the solid state through THz time-domain spectroscopy in the frequency range of 0.1-2.5 THz. The crystal configurations of these three saccharides were then simulated using solid-state density functional theory, and the experimental results were found to be in good agreement with the simulation results. Furthermore, the spectral characteristics of the three saccharides in solutions were measured. Each saccharide was found to have unique spectral characteristics, and a correlation existed between the THz absorption spectra of the same substance in the solid state and aqueous solution.

At present, emotion recognition based on electroencephalograms (EEGs) has attracted much more attention. Current studies of affective brain-computer interfaces (BCIs) focus on the recognition of happiness and sadness using brain activation patterns. Fear recognition involving brain activities in different spatial distributions and different brain functional networks has been scarcely investigated. In this study, we propose a multifeature fusion method combining energy activation, spatial distribution, and brain functional connection network (BFCN) features for fear emotion recognition. The affective brain pattern was identified by not only the power activation features of differential entropy (DE) but also the spatial distribution features of the common spatial pattern (CSP) and the EEG phase synchronization features of phase lock value (PLV). A total of 15 healthy subjects took part in the experiment, and the average accuracy rate was 85.00% ± 8.13%. The experimental results showed that the fear emotions of subjects were fully stimulated and effectively identified. The proposed fusion method on fear recognition was thus validated and is of great significance to the development of effective emotional BCI systems.

The tensile and shear properties of plant roots are important factors that determine their slope protection and are also direct indicators for evaluating plant roots for slope protection. In order to explore the soil-fixing properties of root system and root–soil composite of Indigofera amblyantha and Cassia bicapsularis, the high and steep slope of Zhaofu quarry in Wudang District of Guiyang City was taken as the research background. The effects of root diameter, tree species, root water content and normal pressure on the tensile properties of single root, direct shear friction of root system and shear properties of root–soil composite were investigated by an indoor mechanical test and a direct shear friction test. Results showed that under saturated water content, the tensile strength of C. longifolia decreased, and the tensile strength of C. bifolia also decreased. With the increase in water content from 10.3% to 22.3%, the friction strength of the root–soil interface increased gradually, and the friction strength of root–soil interface of Cassia bicapsularis was greater than that of Cassia longifolia. With the increase in root diameter, the root–soil interfacial friction strength of the two shrubs increased slightly. The normal pressure also increases the density of the soil, so that the roots give full play to the reinforcement effect. The greater the normal pressure, the greater the shear strength of the root–soil composite. When the water content increased from 10.3% to 22.3%, the shear strength of the two-shrub root–soil composites increased first and then decreased gradually, reaching the maximum at 14.3%, followed by the shear strength at 10.3%, reaching the minimum at 22.3%.

Periodontal diseases can lead to chronic inflammation affecting the integrity of the tooth supporting tissues. Recently, a striking association has been made between periodontal diseases and primary cancers in the absence of a mechanistic understanding. Here we address the effect of periodontal inflammation (PI) on tumor progression, metastasis, and possible underlining mechanisms. We show that an experimental model of PI in mice can promote lymph node (LN) micrometastasis, as well as head and neck metastasis of 4T1 breast cancer cells, both in early and late stages of cancer progression. The cervical LNs had a greater tumor burden and infiltration of MDSC and M2 macrophages compared with LNs at other sites. Pyroptosis and the resultant IL-1β production were detected in patients with PI, mirrored in mouse models. Anakinra, IL-1 receptor antagonist, limited metastasis, and MDSC recruitment at early stages of tumor progression, but failed to reverse established metastatic tumors. PI and the resulting production of IL-1β was found to promote CCL5, CXCL12, CCL2, and CXCL5 expression. These chemokines recruit MDSC and macrophages, finally enabling the generation of a premetastatic niche in the inflammatory site. These findings support the idea that periodontal inflammation promotes metastasis of breast cancer by recruiting MDSC in part by pyroptosis-induced IL-1β generation and downstream CCL2, CCL5, and CXCL5 signaling in the early steps of metastasis. These studies define the role for IL-1β in the metastatic progression of breast cancer and highlight the need to control PI, a pervasive inflammatory condition in older patients.

Since 2000, overloaded trucks have caused more than 50 bridges to collapse in China. In an effort to ensure the structural safety and extend the service life of the highway infrastructure, the Chinese government has proposed a series of policies in the past decade to mitigate truck overloading. This study aimed at investigating the effects of China’s recently revised toll-by-weight policy on truck overloading behavior and bridge infrastructure damage using weigh-in-motion data that spanned seven years (January 2011 to March 2018) and two successive toll-by-weight policies (with the new one implemented from August 2016), wherein truck data were measured from a typical national freeway segment. We first compared truck traffic volumes, compositions, and weight distributions under the initial and revised toll-by-weight policies. Next, we compared bridge infrastructure performance with respect to safety and fatigue based on the overloaded truck traffic observed under the initial and revised toll-by-weight policies. The results indicated that the revised toll-by-weight policy, which uses a stepwise incremental fee structure based on vehicle weight, was more effective at controlling truck overloading behavior and reducing bridge infrastructure damage than the initial toll-by-weight policy. Under the current policy, average daily truck volumes, overloaded truck proportions, and maximum truck weights decreased significantly. Concurrently, extreme and equivalent load effects for safety and fatigue assessments, respectively, decreased by an average of 20% for small- to medium-span bridges. Despite these noted improvements, overloaded truck traffic persisted, with loads often exceeding bridge design levels. This study’s findings can support future efforts by the Chinese government to further refine their toll-by-weight policies and subsequently ensure a safe and viable transportation network.

A long start-up period is one of the main factors limiting the practical application of aerobic granular sludge (AGS). Bioaugmentation could be a good strategy to accelerate aerobic granulation. In this research, four denitrifying strains were isolated from mature AGS. Mycobacterium senegalense X3-1 exhibited the strongest self-aggregation ability and good denitrification ability. Ensifer adhaerens X1 showed the strongest denitrification ability but poor self-aggregation ability. Additionally, strain X3-1 demonstrated the highest extracellular polymeric substances (EPS) contents accompanied by relatively high N-acyl-homoserine lactones (AHLs) concentrations, which could illustrate its predominant aggregation ability—AHLs produced by bacteria regulate EPS secretion to accelerate cell aggregation. Strain X3-1 and X1 were chosen as inoculated bacterium to verify the effects of bioaugmentation on AGS granulation and denitrification. Granulation was achieved in the sequential batch reactors (SBRs) added strain X3-1 10 days earlier than the control group. The particle morphology and TIN removal rate of X3-1 were both superior to the latter. The introduction of strains reduced the richness and diversity of the microbial community, but the key functional bacteria, Candidatus_Competibacter, proliferates in the SBR inoculated with X3-1. Conclusively, it is suggested Mycobacterium senegalense X3-1 could be a prospective strain for enhancing AGS formation and denitrification.

When people are in different attention states, electroencephalogram(EEG) signals will be different. Most of researchers used the power of brain waves in different frequency bands or their power ratio as features for classification. However, the accuracy of recognition needs further improvement. In this paper, we proposed a BCI system used for attention state classification. Firstly, we used a band-pass filter to filtered the raw EEG data. After preprocessing, eight candidate features were extracted based on the power spectral density (PSD). Then we used a genetic algorithm(GA) based on probability distribution to select eight-dimensional features from the twenty-four-dimensional candidate features. Finally, we chose support vector machine (SVM) as classifier. The average accuracy of the ten subjects achieved 86.99% for the frontal(the central area and parietal area achieved 84.94% and 84.66%, respectively). Further analysis, the classifier was changed to a back-propagation neural network (BP). Output of the bp classifier was classified using the k-means. The final average accuracy of the ten subjects achieved 90.30% for the frontal(the central area and parietal area achieved 89.66% and 88.99%, respectively). We also used the 24-dimensional PSD feature to calculate the accuracy, the proposed method can greatly improve the accuracy, which showed the feasibility of this method in attentional EEG analysis.

Background: Type 2 diabetes mellitus (T2DM) has a harmful effect on the stability and osseointegration of dental implants. T2DM induces mitochondrial damage by inhibiting AMPK signaling, resulting in oxidative stress and poor osteogenesis in the peri-implant bone area. Genipin is a major component of gardenia fruits with strong antioxidant, anti-inflammation, and anti-diabetic actions, and it also can activate mitochondrial quality control via the AMPK pathway. The purpose of this study was to investigate the effects of genipin and insulin treatment on implant osseointegration in T2DM rats and explore the underlying mechanisms. Methods: Streptozotocin-induced diabetic rats received implant surgery in their femurs, and were then assigned to five groups that were subjected to different treatments for three months: control group, T2DM group, insulin-treated T2DM group (10 IU/kg), genipin-treated T2DM group (50 mg/kg), and the genipin and insulin combination-treated T2DM group. Then, we regularly assessed the weight and glucose levels of the animals. Rats were euthanized at three months after the implantation procedure, and the femora were harvested for microscopic computerized tomography analysis, biomechanical tests, and different histomorphometric assessment. Results: The results indicated that the highest blood glucose and oxidative stress levels were measured for the T2DM group, resulting in the poorest osseointegration. The combination-treated T2DM group mitigated hyperglycemia and normalized, reactivated AMPK signaling, and alleviated oxidative stress as well as reversed the negative effect of osseointegration. There were beneficial changes observed in the T2DM-genipin and T2DM-insulin groups, but these were less in comparison to the combination treatment group. Conclusion: Our study suggests that treatment with genipin in combination with insulin could be an effective method for promoting implant osseointegration in T2DM rats, which may be related to AMPK signaling.

Long noncoding RNA (LncRNA) small nucleolar RNA host gene 16 (SNHG16) is correlated with cell injuries, including pneumonia. However, its role and mechanism remain vague in pneumonia. The interplay among genes was confirmed by dual-luciferase reporter assay, RNA immunoprecipitation, and RNA pull-down assay. SNHG16 and sushi domain containing 2 (SUSD2) were upregulated, and miRNA (miR)-141-3p was downregulated in the serum of acute pneumonia patients and lipopolysaccharide (LPS)-challenged human lung fibroblasts WI-38. LPS induced apoptosis, autophagy, and inflammatory response in WI-38 cells, which was significantly attenuated by SNHG16 knockdown and/or miR-141-3p overexpression. Notably, both SNHG16 and SUSD2 were identified as target genes of miR-141-3p. Besides, the suppressive role of SNHG16 knockdown in LPS-induced in WI-38 cells was partially abolished by miR-141-3p silencing, and the similar inhibition of miR-141-3p overexpression was further blocked by SUSD2 restoration. In conclusion, knockdown of SNHG16 could alleviate LPS-induced apoptosis, autophagy, and inflammation in WI-38 cells partially though the SNHG16/miR-141-3p/SUSD2 pathway.

Meditation aims to improve individuals’ core psychological capacities, such as attentional and emotional self-regulation. In this study, we experimented to explore the utility of using permutation entropy (PE) features on electroencephalogram (EEG) data to distinguish among states in human meditation, attention, and relaxation. Twenty advanced yogis with above three years yoga experience and twenty nonmeditators were recruited in our experiment. The whole experiment contained 7 trials. During each trial, subjects were requested to maintain meditation, attention, and relaxation state for three minutes in random order, respectively, after the corresponding voice prompted. In the meantime, 30-channel EEG data were collected in real-time. We calculated PE features from different EEG frequency bands and selected the most correlative features using Fisher’s ratio technique. After that, we fed the feature vectors into a three-class SVM classifier. Twenty yogis and twenty non-meditators achieved average offline classification accuracies of 74.31% and 62.16%, respectively. These results indicated that PE features could be useful in discriminating meditation state and might bring new insight in building meditation-related Brain-Computer Interfaces (BCIs).

To construct aptamer AS1411-functionalized targeted lipid nanobubbles that could simultaneously target abnormally highly expressed nucleolin (NCL) on tumor tissue and neovasculature. Additionally, the study of their contrast-enhanced ultrasound molecular imaging capabilities in vitro and in vivo to explore new methods and approaches for the early and accurate diagnosis of triple-negative breast cancer (TNBC). First, the targeted lipid-nucleic acid molecules were constructed by an amide reaction. Then, the targeted lipid nanobubbles (AS1411-NBs) and nontargeted lipid nanobubbles (NBs) were prepared by membrane hydration, mechanical vibration and centrifugal floatation. The physicochemical characteristics and contrast-enhanced ultrasound imaging capabilities of AS1411-NBs and NBs were compared and analyzed in vitro and in vivo. There were no significant differences between the AS1411-NBs and NBs in their concentration, average particle size or ultrasound imaging capabilities in vitro (P > 0.05). However, AS1411-NBs could simultaneously target NCL in tumor tissue and neovasculature to effectively prolong the duration of contrast-enhanced ultrasound imaging compared to NBs in vivo. The area under the time-intensity curve was significantly different between AS1411-NBs and NBs (P

Recently, deep neural networks (DNNs) have been widely applied in low-dose computed tomography (LDCT) imaging field. Their performances are highly related to the number of the pre-collected training data. Meanwhile, the training data is usually hard to obtain, especially for the high-dose CT (HDCT) images. And HDCT images sometimes contain undesired noises, which easily result in network overfitting. To address the two issues, we proposed a cooperative meta-learning strategy for CT image reconstruction (CmetaCT) combining the metalearning strategy and Co-teaching strategy. The meta-learning (teacher/student model) strategy allows for training network with a large number of LDCT images without the corresponding HDCT images and only a small number of labeled CT data in a semi-supervised learning manner. And the Co-teaching strategy is able to make a trade-off between overfitting and introducing extra errors, which includes a part of samples in every minibatch for updating model parameters. Due to the capacity of meta-learning, the presented CmetaCT method is flexible enough to utilize any existing CT restoration/reconstruction network in meta-learning framework. Finally, both quantitative and visual results indicated that the proposed CmetaCT method achieves a superior performance on low-dose CT imaging compared with the DnCNN method.

Deep learning (DL) networks show a great potential in computed tomography (CT) imaging field. Most of them are supervised DL network greatly based on their capability and the amount of CT training data (i.e., low-dose CT measurements/high-quality ones). However, collection of large-scale CT datasets are time-consuming and expensive. In addition, the training and testing CT datasets used for supervised DL network are highly desired similarities in CT scan protocol (i.e., similar anatomical structure, and same kVp setting). These two issues are particularly critical in spectral CT imaging. In this work, to address the issues, we presents an unsupervised data fidelity enhancement network (USENet) to produce high-quality spectral CT images. Specifically, the presented USENet consists of two parts, i.e., supervised network and unsupervised network. In the supervised network, the spectral CT image pairs at 140 kVp (low-dose CT images/high-dose ones) are used for network training. It should be noted that there is a great difference of CT value between spectral CT images at 140 kVp and 80 kVp, and the supervised network trained with CT images at 140 kVp cannot be directly used for CT image reconstruction at 80 kVp. Then unsupervised network enrolls physical model and the spectral CT measurements at 80 kVp for fine-tuning the supervised network, which is the major contribution of the presented USENet method. Finally, accurate spectral CT reconstructions are achieved for the sparse-view and low-dose cases, which fully demonstrate the effectiveness of the presented USENet method.

Visual fixation is an item in the visual function subscale of the Coma Recovery Scale-Revised (CRS-R). Sometimes clinicians using the behavioral scales find it difficult to detect because of the motor impairment in patients with disorders of consciousness (DOCs). Brain-computer interface (BCI) can be used to improve clinical assessment because it directly detects the brain response to an external stimulus in the absence of behavioral expression. In this study, we designed a BCI system to assist the visual fixation assessment of DOC patients. The results from 15 patients indicated that three showed visual fixation in both CRS-R and BCI assessments and one did not show such behavior in the CRS-R assessment but achieved significant online accuracy in the BCI assessment. The results revealed that electroencephalography-based BCI can detect the brain response for visual fixation. Therefore, the proposed BCI may provide a promising method for assisting behavioral assessment using the CRS-R.

It is difficult to develop BaTiO 3 -based ceramics with enhanced electrical properties and temperature stability simultaneously. In this regard, Er-modified Ba(Zr 0.05 Ti 0.95 )O 3 (BZT-Er) ceramics were designed and synthesized to solve the above problem. The effect of Er 2 O 3 on the microstructure, phase transition, piezoelectric, electromechanical performance and thermal stability of BZT piezoceramics were systemically explored. It was shown that the addition of Er 2 O 3 hardly influences the phase structure of BZT ceramics, which was confirmed by the XRD, Raman and dielectric measurements. The optimized piezoelectric and electromechanical performance is achieved for the BZT-0.04Er ceramics with d 33 of 253pC/N and S max / E max of 368 pm/V, respectively, along with no deterioration of the thermal stability. Consequently, the improvement in piezoelectric, electromechanical and thermal stability was realized simultaneously in BZT-Er ceramics. These observations indicate that the Er-modified BZT ceramics can be deemed as one of the hopeful candidates for actual applications, showing remarkable figure of merit.

In this study, the effect on the terahertz (THz) transmission characteristics was investigated by varying the constant magnetic field time at both ends of the liquid sample (deionized water, CuSO4, CuCl2, (CH3COO) 2Cu, Na2SO4, NaCl, CH3COONa solution). The results show that the transmission intensity of THz waves decreases with the increase of solution residence time in a constant magnetic field. It is inferred that the magnetic field increases the number of hydrogen bonds in the solution, enhances the role of hydrogen bonds, and weakens the intensity of THz transmission spectra.

This paper presents a case study of a large ground collapse (30.6 m long, 25.5 m wide, and 6.0 m deep) and water inrush and mud outburst (10540.8 m3) in the Qingdao line 4, China. This disaster caused a loss of life and property, and construction delay. After the catastrophe, the remedial measures had to be taken to guarantee the stability of the tunnels when tunnel advance resumed. Based on the geological survey and numerical modelling, the main causes of this disaster were summarized as the low strength of strata, high water pressure, stress concentration, the coupling interaction between seepage force and ground and, as a consequence, also the crash of the slice of strongly weathered tuff. Eventually, potential energy, which was derived from the collapse bodies, was transformed into kinetic energy and developed this disaster. After this disaster, a set of remedial instruments including filling the ground cave-in, reinforcing the advance core ahead of tunnel face, and conducting the porepoles to form a protective shell were proposed. After the tunnel advance resumed, these remedial instruments validated by employing monitoring data were effective to tackle this disaster.

International audience; The catalytic reductive amination of levulinic acid (LA) into pyrrolidones with an iridium catalyst using H2 as hydrogen source is reported. The chemoselective iridium catalyst displayed high efficiency for the synthesis of a variety of N-substituted 5-methyl-2-pyrrolidones and N-arylisoindolinones. N-Substituted 5-methyl-2-pyrrolidone was evaluated as a bio-sourced substitute solvent to NMP (N-Methyl-pyrrolidone) in the catalytic arylation of 2-phenylpyridine.

The synthesis and characterization of new dicationic ruthenium and iridium complexes bearing a dipyridylamine ligand (dpa) are reported. These complexes display an unusual zwitterionic molecular structure in the solid state. The iridium complex [Cp*Ir(dpa)(OSO3)] (Ir1) was found to be very efficient in base-free hydrogenation of levulinic acid into γ-valerolactone (GVL). TONs as high as 174000 in hydrogenation have been obtained. We have demonstrated that reduction of LA into GVL by transfer hydrogenation with formic acid is in fact operating by hydrogenation fed by preliminary formic acid dehydrogenation. A mechanism based on the characterization and isolation of Ir–H complexes is proposed.

MotivationSubcellular location plays an essential role in protein synthesis, transport, and secretion, thus it is an important step in understanding the mechanisms of trait-related proteins. Generally, homology methods provide reliable homology-based results with small E-values. We must resort to pattern recognition algorithms (SVM, Fisher discriminant, KNN, random forest, etc.) for proteins that do not share significant homologous domains with known proteins. However, satisfying results are seldom obtained.ResultsHere, a novel hybrid method “Basic Local Alignment Search Tool+Smith-Waterman+Needleman-Wunsch” or BLAST+SWNW, has been obtained by integrating a loosened E-value Basic Local Alignment Search Tool (BLAST) with the Smith-Waterman (SW) and Needleman-Wunsch (NW) algorithms, and this method has been introduced to predict protein subcellular localization in eukaryotes. When tested on Dataset I and Dataset II, BLAST+SWNW showed an average accuracy of 97.18% and 99.60%, respectively, surpassing the performance of other algorithms in predicting eukaryotic protein subcellular localization.Availability and ImplementationBLAST+SWNW is an open source collaborative initiative available in the GitHub repository (https://github.com/ZHANGDAHAN/BLAST-SWNW-for-SLP or http://202.206.64.158:80/link/72016CAC26E4298B3B7E0EAF42288935)Contactzhaqi1972@163.com; zhangdahan@genetics.ac.cnSupplementary InformationSupplementary data are available at PLOS Computational Biology online.

Objective. For patients with disorders of consciousness (DOC), such as vegetative state (VS) and minimally conscious state (MCS), communication is challenging. Currently, the communication methods of DOC patients are limited to behavioral responses. However, patients with DOC cannot provide sufficient behavioral responses due to motor impairments and limited attention. In this study, we proposed a hybrid asynchronous brain–computer interface (BCI) system that provides a new communication channel for patients with DOC. Approach. Seven patients with DOC (3 VS and 4 MCS) and eleven healthy subjects participated in our experiment. Each subject was instructed to focus on the square with the Chinese words ‘Yes’ and ‘No’. Then, the BCI system determined the target square with both P300 and steady-state visual evoked potential (SSVEP) detections. For the healthy group, we tested the performance of the hybrid system and the single-modality BCI system. Main results. All healthy subjects achieved significant accuracy (ranging from 72% to 100%) in both the hybrid system and the single modality system. The hybrid asynchronous BCI system outperformed the P300-only and SSVEP-only systems. Furthermore, we employed the asynchronous approach to dynamically collect the electroencephalography signal. Compared with the synchronous system, there was a 21% reduction in the average required rounds and a reduction of 105 s in the online experiment time. This asynchronous system was applied to detect the ‘yes/no’ communication function of seven patients with DOC, and the results showed that three of the patients (3 MCS) not only showed significant accuracies (67 ± 3%) in the online experiment, and their Coma Recovery Scale-Revised scores were also improved compared with the scores before the experiment. This result demonstrated that 3 of 7 patients were able to communicate using our hybrid asynchronous BCI system. Significance. This hybrid asynchronous BCI system can be used as a useful auxiliary bedside tool for simple communication with DOC patients.

Targeted lipid nanobubbles as theranostic ultrasound molecular probes with both targeted contrast-enhanced ultrasound molecular imaging and synergistic treatment capabilities are expected to overcome severe challenges in the diagnosis and treatment of refractory triple-negative breast cancer (TNBC). In this study, AS1411 aptamer-functionalised nucleolin-targeted doxorubicin-loaded lipid nanobubbles (AS1411-DOX-NBs) were constructed, and their physicochemical properties as well as anti-tumour and cardioprotective efficacies were systematically tested and evaluated. The results showed that AS1411-DOX-NBs can carry and maintain the physicochemical and pharmacodynamic properties of doxorubicin (DOX) and show stronger tumour cell-killing ability in vitro by increasing the active uptake of drugs. AS1411-DOX-NBs also significantly inhibited the growth of TNBC xenografts while maintaining the weight and health of the mice. Echocardiography and pathological examination further confirmed that AS1411-DOX-NBs effectively caused tumour tissue apoptosis and necrosis while reducing DOX-induced cardiotoxicity. The AS1411-DOX-NBs constructed in this study enable both targeted contrast-enhanced ultrasound molecular imaging and synergistic therapeutic efficacy and can be used as safe and efficient theranostic ultrasound molecular probes for the diagnosis and treatment of TNBC.

High-entropy nitride (HEN) ceramics have recently been investigated for potential high-temperature structural application. Several single-phase HENs as well as their mechanical properties have been reported in the literature. However, an understanding of their mechanical properties at the atomic level is still lacking. In this work, density functional theory calculations are used to calculate the stacking fault energy on the {111} and {110} planes in rock salt structure (Ti,Zr,Nb,Ta)N. It is found that, in are 1 1 ‾ 0 > { 110 } and 1 1 ‾ 0 > { 111 } slip systems, the stacking fault energies generally agrees the rule of mixture values of the four mononitride components. For 11 2 ‾ > { 111 } slip system, the stacking fault energies cannot be perfectly described by a rule of mixture. The overall trend is dominated by the behavior of TaN and NbN, which have strong tendency for nucleation of intrinsic stacking faults. We also found that the energy fluctuation caused by atomic randomness in HENs is much smaller than the stacking fault energy barrier in all the slip systems.

Noncoding RNAs (ncRNAs) play important roles in various cellular activities and diseases. In this paper, we presented a comprehensive review on computational methods for ncRNA prediction, which are generally grouped into four categories: (1) homology-based methods, that is, comparative methods involving evolutionarily conserved RNA sequences and structures, (2) de novo methods using RNA sequence and structure features, (3) transcriptional sequencing and assembling based methods, that is, methods designed for single and pair-ended reads generated from next-generation RNA sequencing, and (4) RNA family specific methods, for example, methods specific for microRNAs and long noncoding RNAs. In the end, we summarized the advantages and limitations of these methods and pointed out a few possible future directions for ncRNA prediction. In conclusion, many computational methods have been demonstrated to be effective in predicting ncRNAs for further experimental validation. They are critical in reducing the huge number of potential ncRNAs and pointing the community to high confidence candidates. In the future, high efficient mapping technology and more intrinsic sequence features (e.g., motif and k-mer frequencies) and structure features (e.g., minimum free energy, conserved stem-loop, or graph structures) are suggested to be combined with the next- and third-generation sequencing platforms to improve ncRNA prediction.

Ye, J.; Huang, H.; Liang, W., and Li, H., 2020. The optimization design of the geometric adaptability of the console in the medical emergency room of ship cabin based on ergonomics. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 887–891. Coconut Creek (Florida), ISSN 0749-0208.In view of the current situation of the design and use of the console in the ship cabin medical emergency room, which cannot meet the treatment needs of medical staff and patients at the same time, an ergonomic optimization design method for the geometric adaptation of the console in the ship cabin medical emergency room is proposed. Simplify the patient's body system and establish the patient's body model according to the national standard of human body size; analyze the typical treatment postures of surgical students, and simulate the typical operation postures in CATIA. Determine the working space with the best working posture of human body, and express the space with ergonomic software, so as to obtain the size of each plate, the relative size of each plate and the key movement range of the operating table in the medical emergency room of the ship cabin as the initial design conditions of the mechanical system; research the shape, color and material design requirements of medical devices. The overall evaluation function is used to evaluate the forming quality of the parts, as the optimization objective function, the optimization mathematical model is established, and the ergonomic optimization design of the control platform of the ship cabin medical emergency room is completed. The simulation results show that the proposed method has a good comprehensive effect on the geometric adaptation of the control platform of the ship cabin medical emergency room.

Objective As the most prevalent type of rhinitis, allergic rhinitis is consisted of seasonal allergic rhinitis (SAR) and perennial allergic rhinitis. This study is carried out for revealing the mechanisms of SAR. Methods Microarray data set GSE43523 (including 7 SAR nasal epithelial cells and 5 nonallergic control nasal epithelial cells) was extracted from Gene Expression Omnibus database. Based on limma package, differential expression analysis for the 2 groups was performed to obtain differentially expressed genes (DEGs). Using Multifaceted Analysis Tool for Human Transcriptome online tool, the functions involving the DEGs were predicted by enrichment analysis. Combined with Cytoscape software, protein–protein interaction (PPI) network was built and a significant network module was acquired. In addition, transcription factor (TF)-target and miRNA-target pairs were predicted using WebGestalt tool, and then TF-miRNA-target regulatory network was built by Cytoscape software. Results There were 274 DEGs between rhinitis and control samples, including 144 upregulated genes and 130 downregulated genes. After PPI for the DEGs was built, a significant network module was identified. In the TF-miRNA-target regulatory network, ABCA1, CPEB4, CD69, MIR-17-5P, and CREB had higher degrees. Furthermore, both ABCA1 and CD69 were targeted by MIR-17-5P in the regulatory network. Conclusion CPEB4 and CREB might be implicated in the pathogenesis of SAR. Besides, MIR-17-5P might also act in SAR via targeting ABCA1 and CD69.