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Background Nonalcoholic fatty liver disease (NAFLD) is a disorder that extends from simple hepatic steatosis to nonalcoholic steatohepatitis (NASH), which is effectively alleviated by lifestyle intervention. Nevertheless, DNA methylation mechanism underling the effect of environmental factors on NAFLD and NASH is still obscure. The aim of this study was to investigate the effect of exercise and diet intervention in NAFLD and NASH via DNA methylation of GAB2. Methods Methylation of genomic DNA in human NAFLD was quantified using Infinium Methylation EPIC BeadChip assay after exercise (Ex), low carbohydrate diet (LCD) and exercise plus low carbohydrate diet (ELCD) intervention. The output Idat files were processed using ChAMP package. False discovery rate on genome-wide analysis of DNA methylation (q GRB2 associated binding protein 2 (GAB2) in NASH mice after Ex, low fat diet (LFD) and exercise plus low fat diet (ELFD), MassARRAY EpiTYPER and quantitative reverse transcription polymerase chain reaction were used. Results Both LCD and ELCD intervention on human NAFLD can induce same DNA methylation alterations at critical genes in blood, e.g., GAB2, which was also validated in liver and adipose of NASH mice after LFD and ELFD intervention. Moreover, methylation of CpG units (i.e., CpG_10.11.12) inversely correlated with mRNA expression GAB2 in adipose tissue of NASH mice after ELFD intervention. Conclusions We highlighted the susceptibility of DNA methylation in GAB2 to ELFD intervention, through which exercise and diet can protect against the progression of NAFLD and NASH on the genome level, and demonstrated that the DNA methylation variation in blood could mirror epigenetic signatures in target tissues of important biological function, i.e., liver and adipose tissue. Trialregistration International Standard Randomized Controlled Trial Number Register (ISRCTN42622771)

Mechanical ventilation is a life-sustaining therapy for patients with respiratory failure but can cause further lung damage known as ventilator-induced lung injury (VILI). However, the intrinsic molecular mechanisms underlying recovery of VILI remain unknown. Phagocytosis of apoptotic cells (also known as efferocytosis) is a key mechanism orchestrating successful resolution of inflammation. Here we show the positive regulation of macrophage Toll-like receptor (TLR) 4 in efferocytosis and resolution of VILI. Mice were depleted of alveolar macrophages and then subjected to injurious ventilation (tidal volume, 20 mL/kg) for 4 h. On day 1 after mechanical ventilation, Tlr4+/+ or Tlr4−/− bone marrow-derived macrophages (BMDMs) were intratracheally administered to alveolar macrophage-depleted mice. We observed that mice depleted of alveolar macrophages exhibited defective resolution of neutrophilic inflammation, exuded protein, lung edema, and lung tissue injury after ventilation, whereas these delayed responses were reversed by administration of Tlr4+/+ BMDMs. Importantly, these proresolving effects by Tlr4+/+ BMDMs were abolished in mice receiving Tlr4−/− BMDMs. The number of macrophages containing apoptotic cells or bodies in bronchoalveolar lavage fluid was much less in mice receiving Tlr4−/− BMDMs than that in those receiving Tlr4+/+ BMDMs. Macrophage TLR4 deletion facilitated a disintegrin and metalloprotease 17 maturation and enhanced Mer cleavage in response to mechanical ventilation. Heat shock protein 70 dramatically increased Mer tyrosine kinase surface expression, phagocytosis of apoptotic neutrophils, and rescued the inflammatory phenotype in alveolar macrophage-depleted mice receiving Tlr4+/+ BMDMs, but not Tlr4−/− BMDMs. Our results suggest that macrophage TLR4 promotes resolution of VILI via modulation of Mer-mediated efferocytosis.

An ultralight and high-strength SiCnw@SiC foam with highly efficient microwave absorption and heat insulation properties was successfully synthesized using the template sacrifice method and chemical vapor deposition process. The microstructure is a novel double network structure, which is formed by the coupling of the morphology-controlled SiCnw and the SiC skeleton. The introduction of SiCnw can not only provide more interface polarization and dielectric loss to the SiC foam, which greatly enhances the microwave absorption capacity of the composite foam, but also can enable it to act as an excellent radiation absorbent, which can effectively reduce the thermal conductivity of the foam, especially at high temperatures. In this study, a minimum reflection loss (RLmin) of -52.49 dB was achieved at 2.82 mm thickness with an effective absorption bandwidth of 5.6 GHz. As the length/diameter ratio of SiCnw decreases, the composite foam exhibits excellent high-temperature thermal insulation and mechanical properties. For the SiCnw@SiC foam, the thermal conductivity is only 0.304 W/mK at 1200 °C and the compressive strength reaches 1.53 MPa. This multifunctional SiCnw@SiC foam is an outstanding material, which has potential applications in microwave absorption and high-temperature heat insulation in harsh environments.

Background The number of multiple primary lung cancer (MPLC) patients has rapidly increased in recent years. However, information regarding the etiology of MPLC and responsiveness to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) is rare. The present study aims to describe the mutation signatures of EGFR in MPLC. Methods Polymerase chain reaction (PCR) and Sanger sequencing were used to screen EGFR mutations in 162 family probands comprising 366 tumor lesions and 162 paired noncancerous adjacent tissues (NATs). Sequencing data from 3,243 sporadic lung adenocarcinoma (LUAD) samples were analyzed as a control. Results Candidate germline mutations were observed in exons 19 (3, 1.85%), 20 (8, 4.94%) and 21 (5, 3.10%), with a total frequency of 9.88% in NATs (16/162). There were 63 probands harboring somatic mutations (63/162, 38.89%), 9 patients harbored the consistency mutations among lesions, and 8 patients carried 2 or more mutations. The overall rate of EGFR somatic mutations was lower in the MPLC probands, but those of exon 19 p.747-752del, 20 p.V769indelsVASV and 20 p.D770indelsDSVD were significantly higher in MPLC probands than in patients with sporadic LUAD. Conclusions There exists unique EGFR mutation signatures in a large cohort of MPLC probands, which might provide objective evidence of the etiology and effectiveness of clinical TKI treatment of high-risk MPLC patients.

Objective Major depressive disorder (MDD) is a heterogeneous psychiatric disorder and considered to be one of the most common mental diseases worldwide. The antidepressant venlafaxine, as a serotonin noradrenaline reuptake inhibitor, is applied to MDD relief. Solute carrier family 6 member 4 (SLC6A4) has been reported to promote the reuptake of serotonin and to be closely correlated to depression. The present study examined whether rs6354 and rs1487971 in SLC6A4 are associated with remission after venlafaxine treatment in MDD patients. Methods This study consisted of 195 Han Chinese patients with MDD, who accepted a 6-week treatment with venlafaxine. Two SLC6A4 single-nucleotide polymorphisms (SNPs) were selected from database of SNP and genotyped by matrix-assisted laser desorption/ionization time of flight mass spectrometer in MassARRAY Analyzer 4 platforms. The 17-item Hamilton Depression Scale was used to access the severity of major depression. Allele and genotype frequencies between patients in remission and nonremission were calculated with online software SHEsis. Results No significant differences in allele or genotype frequencies were observed in rs6354 and rs1487971. There were no significant associations between 2 SNPs and venlafaxine treatment outcome. Conclusions It suggested that rs6354 or rs1487971 within SLC6A4 appears not to be involved in the venlafaxine treatment outcome in Han Chinese patients with MDD.

Recently, web service recommender systems have attracted much attention due to the popularity of Service-Oriented Computing and Cloud Computing. Memory-based collaborative filtering approaches which mainly rely on the similarity calculation are widely studied to realize the recommendation. In these research works, the similarity between two users is computed based on the QoS data of their commonly-invoked services and the similarity between two services is computed based on the common users who invoked them. However, most approaches ignore that the similarity calculation is not always accurate under a sparse data condition. To address this problem, we propose a similarity propagation method to accurately evaluate the similarities between users or services. Similarity propagation means that "if A and B are similar, and B and C are similar, then A and C will be similar to some extent". Firstly, the similarity graph of users or services is constructed according to the QoS data. Then, the similarity propagation paths between two nodes on the similarity graph are discovered. Finally, the similarity along each propagation path is measured and the indirect similarity between two users or services is evaluated by aggregating the similarities of different paths connecting them. Comprehensive experiments on real-world datasets demonstrate that our similarity propagation method can outstandingly improve the QoS prediction accuracy of memory-based collaborative filtering approaches.

Installation time of ground support in many caverns excavation is mainly based on analytical and empirical method, instead of the robust numerical simulations. A novel graph method is proposed to determine the installation time of the support upon finite difference method (FDM) simulation. A three dimensional numerical model for the diversion tunnel of Guandi hydropower station is developed. The curve d-r between the convergence d and the excavation unloading rate r is built up upon one-step excavation simulation. Meanwhile, the curve d-l between d and the distance from the tunnel face l, is established via the step-by-step simulation. Using the dimensionless convergence λ instead of d in both curve d-r and curve d-l, curve λ-r and curve λ-l can be yielded to achieve the composite graph r-λ-l. When r = r0, l can be chose as l0 along the identical λ in the comprehensive graph r-λ-l, where r is the excavation unloading rate at the critical plastic state and l0 is the distance from the tunnel face to the support installation location. The proposed graph method is demonstrated to meet well with common sense upon the diversion tunnel of Guandi hydropower station and can be conveniently realized in other engineering practice.

We propose a modular architecture of Deep Neural Network (DNN) for multi-class classification task. The architecture consists of two parts, a router network and a set of expert networks. In this architecture, for a C-class classification problem, we have exactly C experts. The backbone network for these experts and the router are built with simple and identical DNN architecture. For each class, the modular network has a certain number $$\rho$$ ρ of expert networks specializing in that particular class, where $$\rho$$ ρ is called the redundancy rate in this study. We demonstrate that $$\rho$$ ρ plays a vital role in the performance of the network. Although these experts are light weight and weak learners alone, together they match the performance of more complex DNNs. We train the network in two phase wherein, first the router is trained on the whole set of training data followed by training each expert network enforced by a new stochastic objective function that facilitates alternative training on a small subset of expert data and the whole set of data. This alternative training provides an additional form of regularization and avoids over-fitting the expert network on subset data. During the testing phase, the router dynamically selects a fixed number of experts for further evaluation of the input datum. The modular nature and low parameter requirement of the network makes it very suitable in distributed and low computational environments. Extensive empirical study and theoretical analysis on CIFAR-10, CIFAR-100 and F-MNIST substantiate the effectiveness and efficiency of our proposed modular network.

Programmed death receptor-1 (PD-1) inhibitors have shown efficacy in first-line treatment of NSCLC; however, evidence of PD-1 inhibitor as neoadjuvant treatment is limited. This is a phase 1b study to evaluate the safety and outcome of PD-1 inhibitor in neoadjuvant setting.Treatment-naive patients with resectable NSCLC (stage IA-IIIB) received two cycles of sintilimab (200 mg, intravenously, day 1 out of 22). Operation was performed between day 29 and 43. Positron emission tomography-computed tomography scans were obtained at baseline and before the operation. The primary end point was safety. Efficacy end points included rate of major pathologic response (MPR) and objective response rate. Expression of programmed cell death ligand 1 was also evaluated (registration number: ChiCTR-OIC-17013726).A total of 40 patients enrolled, all of whom received two doses of sintilimab and 37 underwent radical resection. A total of 21 patients (52.5%) experienced neoadjuvant treatment-related adverse events (TRAEs). Four patients (10.0%) experienced grade 3 or higher neoadjuvant TRAEs, and one patient had grade 5 TRAE. Eight patients achieved radiological partial response, resulting in an objective response rate of 20.0%. Among 37 patients, 15 (40.5%) achieved MPR, including six (16.2%) with a pathologic complete response in primary tumor and three (8.1%) in lymph nodes as well. Squamous cell NSCLC exhibited superior response compared with adenocarcinoma (MPR: 48.4% versus 0%). Decrease of maximum standardized uptake values after sintilimab treatment correlated with pathologic remission (p0.00001). Baseline programmed cell death ligand 1 expression of stromal cells instead of tumor cells was correlated with pathologic regression (p = 0.0471).Neoadjuvant sintilimab was tolerable for patients with NSCLC, and 40.5% MPR rate is encouraging. The decrease of maximum standardized uptake values after sintilimab might predict pathologic response.

Objectives To compare the prevalence of sleep disturbances in older adults with traumatic brain injury (TBI) with that of age- and gender-matched controls and to determine the risk factors for post-TBI sleep disturbances and the effects of post-TBI disturbances on quality of life (QOL). Design Cross-sectional case-comparison study. Participants Eighty older adults (aged ≥65 years) with first-time TBI more than 3 months since injury and 80 older adults controls without TBI who completed sleep and health-related QOL questionnaires. Results Older adults with TBI showed a higher prevalence of obstructive sleep apnea (OSA), insomnia, and daytime sleepiness than older adult controls. Being male, having higher levels of depression and pain, and the presence of insomnia were significantly correlated with the risks of OSA, insomnia, and daytime sleepiness following TBI, respectively. Both OSA and insomnia were significantly correlated with low QOL in older adults with TBI. Conclusions Sleep disturbances are highly prevalent in older adults with TBI. Gender differences, depression severity, and pain level are correlated with the occurrence of post-TBI sleep disturbances. Both OSA and insomnia are regarded as major contributors to low QOL in older people with TBI. Interventions targeted at post-TBI sleep disturbances may improve QOL of older adults.

For high-volume manufacturing of 2-D transistors, area-selective chemical reaction deposition (CVD) growth is able to provide good-quality 2-D layers and may be more effective than exfoliation from bulk crystals or wet/dry transfer of large-area as-grown 2-D layers. We have successfully grown continuous and uniform WS2 film comprising around seven layers by area-selective CVD approach using patterned tungsten source/drain metals as the seeds. The growth mechanism is inferred and supported by the transmission electron microscope (TEM) images, as well. The first top-gate MOSFETs of CVD-WS2 channels on SiO x /Si substrates are demonstrated to have good short channel electrical characteristics: ON-/OFF-ratio of 106, a subthreshold swing of 97 mV/decade, and nearly zero drain-induced barrier lowering (DIBL).

Infarct healing is dependent on recruitment of inflammatory leukocytes and subsequent activation of myofibroblasts (MF) and neovessel formation, ultimately resulting in formation of a highly vascularized collagen-enriched scar. Though the heart has an abundant population of periendothelial pericytes, its role in wound healing upon myocardial infarction (MI) has not been studied. We hypothesized that in the infarcted myocardium, pericytes may become activated, contributing to inflammatory, fibrotic and angiogenic responses. We used pericyte/fibroblast reporter mice (NG2 DsRed ;PDGFRα GFP ), lineage tracing studies and in vitro approaches to study the fate and role of pericytes in the infarcted myocardium. In normal hearts, NG2+/PDGFRα- pericytes and PDGFRα+/NG2- fibroblasts had distinct transcriptomic profiles. Pericytes expressed mural genes like Acta2 , Pdgfrb and low amounts of extracellular matrix (ECM) genes, whereas fibroblasts synthesized collagens, Timp2/3 and matricellular genes. 7 days post-MI, expansion of the NG2+ population in the infarct zone was associated with emergence of non-mural NG2+/αSMA+ cells with MF characteristics. FACS-sorted NG2+/PDGFRα- cells from 7-day infarcts expressed higher levels of collagens when compared to NG2+/PDGFRα- cells from normal hearts. Infarct pericytes had high integrin and MMP14 expression, reflecting an activated migratory phenotype. Lineage tracing using NG2CreER TM ;Rosa tdTomato ;PDGFRα GFP mice showed that 5.7%±1.04 of PDGFRα+ fibroblasts and 10.49%±2.73 of infarct MFs were derived from NG2+ lineage. Pericyte-derived fibroblasts exhibited higher ECM gene synthesis, in comparison to fibroblasts from non-pericyte origin, while pericyte-derived mural cells showed accentuated inflammatory cytokine gene expression. Immunostaining showed pericytes actively contribute to vascular maturation, forming a mural cell coat enwrapping infarct neovessels. In vitro, TGFβ induced integrins, collagens and MMPs in human pericytes, similar to the changes observed in infarct pericytes. Taken together, our evidences show that after MI, pericytes become activated and contribute to repair by undergoing conversion to a subset of myofibroblasts and by coating infarct neovessels.

Dense Global Position System (GPS) arrays can be used to invert the terrestrial water-storage anomaly (TWSA) with higher accuracy. However, the uneven distribution of GPS stations greatly limits the application of GPS to derive the TWSA. Aiming to solve this problem, we grid the GPS array using regression to raise the reliability of TWSA inversion. First, the study uses the random forest (RF) model to simulate crustal deformation in unobserved grids. Meanwhile, the new Machine-Learning Loading-Inverted Method (MLLIM) is constructed based on the traditional GPS derived method to raise the truthfulness of TWSA inversion. Second, this research selects southwest China as the study region, the MLLIM and traditional GPS inversion methods are used to derive the TWSA, and the inverted results are contrasted with datasets of the Gravity Recovery and Climate Experiment (GRACE) Mascon and the Global Land Data Assimilation System (GLDAS) model. The comparison shows that values of Pearson Correlation Coefficient (PCC) between the MLLIM and GRACE and GRACE Follow-On (GRACE-FO) are equal to 0.91 and 0.88, respectively; and the values of R-squared (R2) are equal to 0.76 and 0.65, respectively; the values of PCC and R2 between MLLIM and GLDAS solutions are equal to 0.79 and 0.65. Compared with the traditional GPS inversion, the MLLIM improves PCC and R2 by 8.85% and 7.99% on average, which indicates that the MLLIM can improve the accuracy of TWSA inversion more than the traditional GPS method. Third, this study applies the MLLIM to invert the TWSA in each province of southwest China and combines the precipitation to analyze the change of TWSA in each province. The results are as follows: (1) The spatial distribution of TWSA and precipitation is coincident, which is highlighted in southwest Yunnan and southeast Guangxi; (2) this study compares TWSA of MLLIM with GRACE and GLDAS solutions in each province, which indicates that the maximum value of PCC is as high as 0.86 and 0.94, respectively, which indicates the MLLIM can be used to invert the TWSA in the regions with sparse GPS stations. The TWSA based on the MLLIM can be used to fill the vacancy between GRACE and GRACE-FO.

The letter to the editor suggested several questions regarding the methodology of the recent article by Lam et al who determined effect of multicomponent care bundle on the development of postoperative delirium. This article is published in Geriatric Orthopaedic Surgery & Rehabilitation . 2021; 12:21514593211004530. Our concerns included the incomplete preoperative assessment, possible influences of anaesthetic and intraoperative managements on the development of postoperative delirium, bias effect of postoperative analgesia on the primary and secondary findings, and real clinical value of multicomponent care bundle to decrease the risk of postoperative delirium. We believe that clarifying these issues would improve the transparency of this study and interpretation of findings.

Background Composed of mineral oil and mycobacteria pathogens, complete Freund’s adjuvant (CFA) is one of the most commonly used adjuvants for antibody production and scientific research due to its high efficiency. However, the dead mycobacteria in CFA can cause many allergic reactions. We propose here a new formulation based on the use of nanodiamonds (NDs) as biocompatible non-allergic additives in incomplete Freund’s adjuvant (IFA) to avoid these adverse effects. Methods Chicken egg ovalbumin (OVA) was used as the antigens and 100-nm NDs after purification by air oxidation and strong oxidative acid washes were used as the additives. Levels of OVA-specific IgG antibody in mouse sera were measured by using enzyme-linked immunosorbent assays (ELISA) after the second and third immunizations of healthy mice with OVA and OVA/ND in IFA or CFA. Abilities of the OVA/ND/IFA vaccination to inhibit the tumor growth of mice inoculated with EL4 cells or OVA-expressing E.G7 cells were examined over 1 month. Results The new formulation worked well as a potent vaccine adjuvant, which could boost the immune responses and reduce the consumption of antigens in producing antibodies of interest in model animals like mice. Additionally, the composites showed distinct therapeutic activities, as proven by the OVA/ND/IFA treatment that effectively inhibited the tumor progression of E.G7-inoculated mice, allowing the animals to survive over 35 days post tumor-cell challenges. About 0.2% of the injected ND particles were found in mouse spleens on day 24 after vaccination of the E.G7-inoculated mice with OVA/ND/IFA. Conclusions The multiple functionality of ND makes it useful as an active and trackable component of a vaccine adjuvant not only to enhance antibody production but also to suppress tumor growth in vivo. The ND-based new formulation can be developed into single-dose vaccines with promising potential for real-world applications.

We propose an optimization of Modular Selective Network or MS-Net by reducing the number of expert network evaluations. MS-Net is composed of a router and a set of expert networks. In our original proposal, MS-Net is constructed based on a Round-Robin dataset partition with controlled redundancy among the subsets of classes. In this paper, we propose a novel way for reducing the inference cost by performing Inter-Class-Correlation (ICC) analysis through calculating the joint-probability of appearance of top-2 classes in router’s prediction. Next, we construct subset of classes on the most frequently occurring class pairs and train experts on those subsets. We do not enforce redundancy in these subsets, thus during inference, only one expert is leveraged per sample. Our empirical results show that, with the ResNet-20 backbone, the optimized MS-Net reduces parameter utilization by over 70% yet performs with neck and neck score with the original MS-Net for CIFAR-10 and CIFAR-100 dataset.

Titanium dioxide nanotube arrays (TiO2 NTAs) has shown its promising properties for use as a photoelectrode material. However, the efficiency in this regard is restricted by the wide band gap of TiO2. In this study, a facile method was employed to prepare Ti3+ self-doped and sulfur-doped (S-doped) TiO2 NTAs (H-S-TiO2 NTAs). The Ti3+ and S co-doping greatly improved the photoelectrochemical performances of TiO2 NTAs. The optimized H-S-TiO2 NTAs showed obviously red-shifted compared with the optimized TiO2 NTAs. The saturation photocurrent density and the photoelectric conversion efficiency of the optimized H-S-TiO2 NTAs reached 1.97 mA/cm2 and 1.18%, which were 3.72 and 4.92 times higher than that of the optimized TiO2 NTAs, respectively. Furthermore, the optimized H-S-TiO2 NTAs exhibited the highest transient photocurrent density (1.08 mA/cm2) with excellent photoelectric response characteristics, indicating that the transfer efficiently of photogenerated carriers was increased in the optimized H-S-TiO2 NTAs. On the basis of research results, such enhanced performances could prove that the Ti3+ self-doping and S-doping had synergistic effects. The established S-doping as well as introduced Ti3+ self-doping of TiO2 NTAs resulted in enhanced visible-light absorption and rapid electron transfer rate.

Bifurcations are employed when two or more branch pipes are merged into one main pipe, which generally located upstream of the powerhouse and embedded in surrounding media. A three dimension (3D) numerical model for the symmetrical Y-shape steel bifurcation with crescent rib embedded in in-situ cast concrete anchor block is developed, in which the water head is as high as 652 m. Then, by means of the point-to-point contact element of CONTAC52 simulating the initial gap between steel pipe and concrete, the resulting distribution of stress, settlement of bedrock are revealed. Further, a novel method to calculate the load bearing ratio of the concrete anchor block is proposed to evaluate the load-bearing capability of the surrounding concrete. Further, this study also discusses the effects of the initial gap, the concrete elastic modulus and the deformation modulus of the bedrock. The results demonstrate adequate rebar should be arranged to ensure the integrity of the anchor block and to limit the crack widths. The design criteria of reinforced concrete penstock are suggested for the detailed design of embedded bifurcations to simplify the construction process, to reduce the steel thickness of the steel bifurcation and the amount of investment.

Most existing facial landmark detection algorithms regard the manually annotated landmarks as precise hard labels, therefore, the accurate annotated landmarks are essential to the training of these algorithms. However, in many cases, there exist deviations in manual annotations, and the landmarks marked for facial parts with occlusion and large poses are not always accurate, which means that the “ground truth” landmarks are usually not annotated precisely. In such case, it is more reasonable to use soft labels rather than explicit hard labels. Therefore, this paper proposes to associate a bivariate label distribution (BLD) to each landmark of an image. A BLD covers the neighboring pixels around the original manually annotated point, alleviating the problem of inaccurate landmarks. After generating a BLD for each landmark, the proposed method firstly learns the mappings from an image patch to the BLD of each landmark, and then the predicted BLDs are used in a deformable model fitting process to obtain the final facial shape for the image. Experimental results show that the proposed method performs better than the compared state-of-the-art facial landmark detection algorithms. Furthermore, the proposed method appears to be much more robust against the landmark noise in the training set than other compared baselines.

Based on the peripheral refractive theory, this study designed a contact lens which can change the peripheral refraction of the retina, and established a retinal image system that can analysis the refractive state of the eyeball. The Monte-Carlo ray trace modeling was used to analyze the retinal images under different refractive conditions. The calculation of the power vector of refractive state was optimized for judging the corrective effect. The purpose of this study is to control the development of myopia for suppress the change of axis oculi when the eyeball supported in relative peripheral myopia or emmetropia by using contact lens. The results show that the model of peripheral refractive lenses with fourth-order spherical aberration constructed in this study can be used to control myopia and can achieve excellent corrective effect.

The clinical treatment choices for multiple rib fractures and flail chest are controversial. For example, among conservative treatment and surgical treatment, different studies have different conclusions and recommendations. Furthermore, early clinical research was mainly focused on the treatment of flail chest due to its severity. Nowadays, the treatment for multiple rib fractures patients without a flail chest is drawing an increased clinical interest. However, we are facing many challenges for the treatment of rib fractures, such as insufficient understanding of the available treatment options, lack of clinical research, lack of the internationally recognized clinical indication for the surgical stabilization of rib fractures (SSRF), and the constant controversies and debates in terms of treatment options, surgery timing, and surgical techniques. All these challenges make it difficult to select the most appropriated clinical decisions for the proper treatment of a rib fracture, resulting in a seriously hindered development of novel rib fractures treatment choices. The concepts and ideas for traditional rib fractures treatment are relatively old, and even have some misunderstandings or errors. With the emergence of more and more research, the understandings of the rib fractures treatment has gradually improved; for example, the benefits provided to patients under the open reductions and internal fixation of fractures treatment. In this article, we outlined the new concepts in rib fractures treatment, which mainly included four parts, damage control, pain management, fixation selection, and quality of life. We hope these concepts help practitioners better manage rib fracture patients.

The ground support system has a significant impact on tunnel safety while the installation time of initial support is commonly designed by empirical method. The three dimensional numerical model, based on the engineering practice, is analyzed by FLAC3D. In this paper, an improved LDP (longitudinal displacement profile) equation is proposed, which is more accurate in describing the convergence of tunnel before excavation face reaching. Then, a methodology is presented to determine the installation location of initial support in a more efficient and effective way. By simulating the process of excavation load releasing, the appropriate time for installing initial support is when the evolution of surrounding rock displacement has a tendency to increase rapidly, namely that the stability of rock mass arrives at the critical state. The mathematical relationship between the convergence of tunnel and the relative location to tunnel face can be established by fitting monitoring data with the improved LDP equation. Substituting the critical tunnel convergence into the LDP relationship, the corresponding installation location of initial support will be calculated. Meanwhile, several schemes with diverse geological conditions are carried out to validate the improved LDP and the methodology.

Objective To compare the impact of minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) with open posterior lumbar interbody fusion (PLIF) on sagittal lumbar-pelvic radiographic parameters for degenerative spondylolisthesis (DS). Methods Of 48 patients with L4 single segmental DS, 25 underwent MIS-TLIF with Quadrant system and 23 underwent conventional open PLIF. Comparisons of data from the preoperative and final follow-up standing lateral lumbar x-rays, with the bilateral femoral heads, of the 2 groups were conducted using the following parameters: slip percentage (SP), lumbar lordosis (LL), pelvic incidence, pelvic tilt (PT), sacral slope, lumbosacral angle, slip angle (SA), and the L1 axis and S1 distance (LASD). Results The slip reduction rate (ΔSP) in the OPEN group was significantly higher than in the MIS group (67 ± 34% vs. 37 ± 51%, P = 0.018). The change of SA (ΔSA) in the OPEN group was significantly higher than in the MIS group (3 ± 7° vs. –3 ± 5°, P = 0.003). The change of LASD (ΔLASD) in the OPEN group was significantly lower than in the MIS group (–4 ± 15 mm vs. 4 ± 9 mm, P = 0.033). There were positive correlations between the preoperative SP and LASD, and ΔSA and the change of LL (ΔLL), and a negative correlation between ΔLL and the change of PT (ΔPT). Conclusions For low-grade DS, open PLIF has a higher rate of slip reduction compared to MIS-TLIF, and significantly reduces LASD, therefore, it is more conducive to improving lumbar sagittal balance.

Numerical simulation has been widely used for predicting rock mass convergence during tunnel excavation. Considering that tunnel construction is a three-dimensional (3D) process, the 3D numerical analysis, instead of the plane-strain models, are commonly employed in engineering practice. As the 3D numerical analyses require large numbers of computational resources, the geometric extents are often kept to a minimum to reduce simulation time. However, there is a lack of published information concerning appropriate the size of numerical model. The study investigates how the transverse range of tunnel section, including the upper boundary, the lower boundary and the lateral boundary, affects the tunnel convergence via the finite difference software package FLAC3D, respectively. Then, a comprehensive function to yield the minimum transverse section area within a given error is proposed. After several cases with different categories of rock are employed in the simulations, the universal model extents with the minimum transverse section area are proposed.

Everolimus, which inhibits mTOR kinase activity and is clinically used in graft rejection treatment, may have a two‐sided influence on metabolic syndrome; its role in obesity and hyperglycemic in animals and humans, however, has been explored insufficiently. This study further determined how continual everolimus treatment affects glucose homeostasis and body weight control in C57BL6/J mice with obesity. An obesity mouse model was developed by administering a high‐fat diet (HFD) to C57BL6/J mice over 12 weeks. The experimental group, while continuing their HFD consumption, were administered everolimus daily for 8 weeks. Metabolic parameters, glucose tolerance, fatty liver score, endocrine profile, insulin sensitivity index (ISI), insulin resistance (IR) index, and Akt phosphorylation, GLUT4, TNF‐α, and IL‐1 levels were measured in vivo. Compared with the control group, the everolimus group gained less body weight and had smaller adipocytes and lower fat pad weight; triglyceride (serum and hepatic), patatin‐like phospholipase domain‐containing 3, and fatty acid synthase levels; fatty liver scores; and glucose tolerance test values—all despite consuming more food. However, the everolimus group exhibited decreased ISI and muscle Akt phosphorylation and GLUT4 expression as well as impaired glucose tolerance and serum TNF‐α and IL‐1β levels—even when insulin levels were high. In conclusion, continual everolimus treatment may lead to diabetes with glucose intolerance and IR., Everolimus impaired glucose tolerance as indicated by the IPGTT data and enhanced hepatic gluconeogenic enzymes, PEPCK—even when higher insulin levels.

Study design A retrospective review of clinical and radiological parameters. Objective To evaluate the therapeutic efficacy of transpedicular impaction bone grafting (TIBG) with long segmental posterior instrumentation for the treatment of stage III Kummell disease. Summary of background data The optimal treatment for stage III Kummell disease remains controversial and unclear. Theoretically, transpedicular bone grafting can reconstruct anterior column support and reduce the failure of internal fixation, which is an intuitive method for the treatment of Kummell disease. However, the use of this technique has rarely been reported for the treatment of this disease. This study reported the clinical and radiological results of TIBG with long segmental posterior instrumentation for the treatment of stage III Kummell disease. Methods Between August 2011 and December 2017, we retrospectively analyzed 24 patients with stage III Kummell disease who underwent TIBG with long segmental posterior instrumentation. Anterior vertebral heights, kyphotic Cobb angle, visual analog scale (VAS), Oswestry disability index (ODI), and American Spinal Injury Association (ASIA) impairment scale were used to evaluate the effects of surgery. Results The mean time to follow-up was 38.1 ± 10.2 months. The average operative duration was 136 ± 16.5 minutes, and the average intraoperative blood loss was 293 ± 41.3 mL. The VAS, ODI, anterior vertebral heights, and kyphotic Cobb angles were improved significantly at 1 week after surgery compared the preoperative examinations, and were well maintained at the final follow-up evaluation. Fourteen patients (58%) had mild neurological impairments before surgery, with neurological function returning to normal at the final follow-up evaluation. There was no instance of instrumentation failure. Conclusion TIBG combined with long segmental posterior instrumentation is a safe and effective surgical option for stage III Kummell disease.Level of Evidence: 4.

Ventilator-induced lung injury is associated with an increase in mortality in patients with respiratory dysfunction, although mechanical ventilation is an essential intervention implemented in the intensive care unit. Intrinsic molecular mechanisms for minimizing lung inflammatory injury during mechanical ventilation remain poorly defined. We hypothesize that Yes-associated protein (YAP) expression in endothelial cells protects the lung against ventilator-induced injury. Wild-type and endothelial-specific YAP-deficient mice were subjected to a low (7 mL/kg) or high (21 mL/kg) tidal volume ( VT) ventilation for 4 h. Infiltration of inflammatory cells into the lung, vascular permeability, lung histopathology, and the levels of inflammatory cytokines were measured. Here, we showed that mechanical ventilation with high VT upregulated YAP protein expression in pulmonary endothelial cells. Endothelial-specific YAP knockout mice following high VT ventilation exhibited increased neutrophil counts and protein content in bronchoalveolar lavage fluid, Evans blue leakage, and histological lung injury compared with wild-type littermate controls. Deletion of YAP in endothelial cells exaggerated vascular endothelial (VE)-cadherin phosphorylation, downregulation of vascular endothelial protein tyrosine phosphatase (VE-PTP), and dissociation of VE-cadherin and catenins following mechanical ventilation. Importantly, exogenous expression of wild-type VE-PTP in the pulmonary vasculature rescued YAP ablation-induced increases in neutrophil counts and protein content in bronchoalveolar lavage fluid, vascular leakage, and histological lung injury as well as VE-cadherin phosphorylation and dissociation from catenins following ventilation. These data demonstrate that YAP expression in endothelial cells suppresses lung inflammatory response and edema formation by modulating VE-PTP-mediated VE-cadherin phosphorylation and thus plays a protective role in ventilator-induced lung injury.

BACKGROUND: Reports regarding prevalence of post-traumatic brain injury (TBI) cognitive deficits were inconsistent. We aimed to synthesize the prevalence of cognitive deficits after TBI in the acute, subacute, and chronic phases. METHODS: PubMed, EMBASE, and ProQuest Dissertations and Theses A&I databases were searched from the inception to April 27, 2020. Studies with prospective, retrospective, and cross-sectional designs reporting the prevalence of cognitive deficits after TBI in adults were included. RESULTS: A total of 15 articles were included for prevalence estimation. The pooled prevalence of memory and attention deficits after mild TBI was 31% and 20% in the acute phase and 26% and 18% in the subacute phase, respectively, and 49% and 54% in the subacute phase and 21% and 50% in the chronic phase after moderate-to-severe TBI. The overall prevalence of information processing speed deficits after mild TBI in the acute and subacute phases was 21% and 17%, respectively, and 57% in the chronic phase after moderate-to-severe TBI. The overall prevalence of executive dysfunction in the subacute and chronic phases was 48% and 38%, respectively, after moderate-to-severe TBI. CONCLUSION: Cognitive deficits are prevalent in the acute to chronic phases after TBI. Healthcare providers should design effective intervention targeting cognitive impairment after TBI as early as possible.

Natural disasters have caused substantial economic losses and numerous casualties. The demand analysis of relief supplies is the premise and basis for efficient relief operations after disasters. With the widespread use of social media, it has become a vital channel for people to report their demand for relief supplies and provides a way to obtain information on disaster areas. Therefore, we present a topic model-based framework and establish a demand dictionary and a gazetteer that aims to identify the spatial distribution of the demand for relief supplies by using social media data. Taking the 2013 Typhoon Haiyan (also called Yolanda) as a case study, we identify the potential topics of tweets with the biterm topic model, screen the tweets related to demands, and obtain the demand and location information from tweets to study the distribution of the relief supplies needs. The results show that, based on the demand dictionary, a gazetteer and the biterm topic model, the effective demand for relief supplies can be extracted from tweets. The proposed framework is feasible for the identification of accurate demand information and its distribution. Further, this framework can be applied to other types of disaster responses and can facilitate relief operations.

In this paper, we study real-time object detection based on cell-wise segmentation. Existing object detection methods usually focus on detecting interesting object's positions and sizes and demand expensive computing resources. This process makes it difficult to achieve high-speed and high-precision detection with low-cost devices. We propose a method called You Only Look at Interested Cells or in-short YOLIC to solve the problem by focusing on predefined interested cells (i.e., subregions) in an image. A key challenge here is how to predict the object types contained in all interested cells efficiently, all at once. Instead of using multiple predictors for all interested cells, we use only one deep learner to classify all interested cells. In other words, YOLIC applies the concept of multi-label classification for object detection. YOLIC can use exiting classification models without any structural change. The main point is to define a proper loss function for training. Using on-road risk detection as a test case, we confirmed that YOLIC is significantly faster and accurate than YOLO-v3 in terms of FPS and F1-score.

On-road risk detection and alert system is a crucial and important task in our day to day life. Deep Learning approaches have got much attention in solving this noble task. In this paper, we have performed a comparative study on two recent architectures that handle the on-road risk detection task, which are Block-Wise Detection and Modular Selective Network (MS-Net). In the Block-Wise Detection, we have used the VGG19, VGG19-BN, and ResNet family as the backbone network. On the other hand, for MS-Net we have used the ResNet-44 as the router and ResNet-101 as the expert network. In this experiment, we evaluate our model on an “on-road risk detection dataset”, which was created by our research group using an RGB-D sensor mounted on a senior car. On this dataset, we can achieve an accuracy of 89.40% for MS-Net. For the Block-Wise Detection model, we can achieve an accuracy of 90.51% if we use ResNet-50 as the backbone network. However, if we choose the network models used in MS-Net, we can double the inference speed. Thus, compared with Block-Wise Detection, we think the overall performance of MS-NET is better, and is potentially more useful for driving assistance of elderly drivers.

We propose a modular Deep Convolutional Neural Network (DCNN) architecture which has the property of block-like design and re-usage of parameters by certain blocks. We leverage networks from the ResNet family as the backbone for our proposed architecture. The proposed network architecture is composed of three primary blocks, i) common block ii) hidden blocks and iii) output block. The common block mainly focuses on learning low-level features which are afterward fed to ρ hidden blocks at a time, where ρ is the branching factor. The hidden blocks are placed in a row-wise manner and replicated ρ times depending on the computational availability. The output block takes features as an input from the common block and all the hidden blocks during both training and testing phases. In addition, each of the hidden blocks together with the common block is a stand-alone neural network, which implies that we have ρ neural networks coupled in a single framework. During the training phase, in every single epoch, each of the stand-alone neural networks (i.e. common block + hidden block) is trained in Round Robin fashion followed by fine-tuning the whole network graph. Inference can be performed using either the whole network graph or just any sub-graph of it. To substantiate the effectiveness of our proposed neural architecture we performed experiment on CIFAR-10 and CIFAR-100 datasets.

Double-gated monolayer two-dimensional (2D) material transistor is expected to offer ideal (~60 mV/dec) subthreshold swing (SS) for gate lengths well below 10 nm. However, the ideal 2D transistor assumes Ohmic contacts whereas a realistic metal/2D Schottky contact can degrade SS. Transport simulations including scattering is necessary to correctly describe carrier thermalization and predict the SS degradation. Scaled 2D transistors with a Schottky barrier height (SBH) smaller than 100 meV and doping concentration in the extension region larger than 2x1013 cm-2 are required to achieve high performance.

A HV energy harvesting circuit with ACC/CV mode and MPPT control is proposed for a 20 V/5 W solar panel. By considering the CC/CV charging process of the Liion battery and the changing maximum power point of the solar panel, the adaptive constant current (ACC) mode with PWM and MPPT control is utilized to improving the efficiency when the light source is not strong and the battery is not full. While the battery reaches full-charged, the constant voltage (CV) mode is used to prevent the damage to the Li-ion battery. The proposed design is implemented using TSMC 0.5 um UHV process. Based on the simulation results, the circuit achieves the tracking efficiency of 98% for the photocurrent from 0.1 A to 0.3 A.

On-road risk detection is one of the most important applications of Deep Neural Network (DNN). A good on-road risk detection system can accurately detect dangerous obstacles on the road and provides drivers with early warning information to avoid danger. However, current high-precision detection systems usually use a cumbersome DNN, which require a large number of computing resources. Due to the limitations of mobile devices such as limited computing power and power consumption problem, it is difficult to apply the high-precision detection model to such devices for running real-time applications. Therefore a fast and accurate model is needed to solve the on-road risk detection problem for low-cost mobile devices. In this paper, we propose a real-time on-road risk detection framework for the low computational platform. The proposed framework uses a tiny neural network model that improves accuracy by leveraging the knowledge distillation technique. By using the proposed method, we conduct our experiments in a Raspberry Pi using one Intel Neural Compute Stick-2 (NCS-2). The practical results show that our detection system can successfully detect the position and type of road obstacles in real-time while maintaining performance comparable to more complex DNN.

Background. High inspiratory oxygen fraction (FIO2) is associated with increased perioperative pulmonary morbidity and postoperative mortality. However, the use of pure oxygen is still currently recommended during the anesthesia induction.Methods, This open-label randomized non-inferiority trial was conducted in two metropolitan hospitals at Southern Taiwan. A total of 302 surgical patients (ASA PC≤III) who received endotracheal general anesthesia (ETGA) were randomized to receive 100% (FIO2 1.0) or 60% (FIO2 0.6) oxygen during induction. The primary endpoint was presence of hypoxemia (SpO2≤92%) during the induction of anesthesia. The secondary endpoint was the development of major complications immediately and within 3 days after surgery.Results. A total of 5 patients in the FIO2 0.6 group developed hypoxemia during induction (3.9% vs 0% for FIO2 0.6 vs FIO2 1.0, respectively; P=0.167 for non-inferiority), suggesting that FIO2 0.6 was inferior than FIO2 1.0 for anesthesia induction. The mean lowest SpO2 during induction was also significantly lower in FIO2 0.6 group. Four patients reached the primary endpoint had increased body mass indexes (BMI>30 kg/m2). However, the overall incidence of desaturation developed after removal of endotracheal tube was higher in FIO2 1.0 group (1.4% vs 5.8%, FIO2 0.6 vs FIO2 1.0; odd ratio 0.22, 95% confidence interval 0.05-1.05; P=0.064).Conclusions. High fractions of oxygen should be used for oxygenation during induction of ETGA in general population, especially in the obese patients. However, the supplement of high FIO2 during induction was associated with increased hypoxemic events after removal of endotracheal tube that might have a more significant impact on perioperative care.

A higher propensity of developing brain metastasis exists in triple-negative breast cancer (TNBC). Upon comparing the metastatic patterns of all breast cancer subtypes, patients with TNBC exhibited increased risks of the brain being the initial metastatic site, early brain metastasis development, and shortest brain metastasis-related survival. Notably, the development of brain metastasis differs from that at other sites owing to the brain-unique microvasculature (blood brain barrier (BBB)) and intracerebral microenvironment. Studies of brain metastases from TNBC have revealed the poorest treatment response, mostly because of the relatively backward strategies to target vast disease heterogeneity and poor brain efficacy. Moreover, TNBC is highly associated with the existence of cancer stem cells (CSCs), which contribute to circulating cancer cell survival before BBB extravasation, evasion from immune surveillance, and plasticity in adaptation to the brain-specific microenvironment. We summarized recent literature regarding molecules and pathways and reviewed the effects of CSC biology during the formation of brain metastasis in TNBC. Along with the concept of individualized cancer therapy, certain strategies, namely the patient-derived xenograft model to overcome the lack of treatment-relevant TNBC classification and techniques in BBB disruption to enhance brain efficacy has been proposed in the hope of achieving treatment success.

Dihydrotanshinone (DIH) is an extract of Salvia miltiorrhiza Bunge. It has been reported that DIH could regulate NF-κB signaling pathway. The aim of this study was to investigate whether DIH could protect mice from lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice. In this study, sixty mice were randomly divided into five groups, one group as blank control group, the second group as LPS control group, and the last three groups were pre-injected with different doses of DIH and then inhaled LPS for experimental comparison. After 12 h of LPS treatment, the wet-dry ratio, histopathlogical changes, and myeloperoxidase (MPO) activity of lungs were measured. In addition, ELISA kits were used to measure the levels of TNF-α and IL-1β inflammatory cytokines in bronchoalveolar lavage fluids (BALF), and western blot analysis was used to measure the activity of NF-κB signaling pathway. The results demonstrated that DIH could effectively reduce pulmonary edema, MPO activity, and improve the lung histopathlogical changes. Furthermore, DIH suppressed the levels of inflammatory cytokines in BALF, such as TNF-α and IL-1β. In addition, DIH could also downregulate the activity of NF-κB signaling pathway. We also found that DIH dose-dependently increased the expression of LXRα. In addition, DIH could inhibit LPS-induced IL-8 production and NF-κB activation in A549 cells. And the inhibitory effects were reversed by LXRα inhibitor geranylgeranyl pyrophosphate (GGPP). Therefore, we speculate that DIH regulates LPS-induced ALI in mice by increasing LXRα expression, which subsequently inhibiting NF-κB signaling pathway.

Traditional super-resolution algorithms are computationally intensive and the quality of generated images is not high. In recent years, due to the superiority of GAN in generating image details, it has begun to attract researchers’ attention. This paper proposes a new GAN-based image super-resolution algorithm, which solves the problems of the current GAN-based super-resolution algorithm that the generated image quality is not high and the multi-scale feature information is not processed enough. In the proposed algorithm, a densely connected dilated convolution network module with different dilation rate is added to enhance the network’s ability to generate image features at different scale levels; a channel attention mechanism is introduced in the network to adaptively select the generated image features, which improves the quality of the generated image on the network. After conducting experiments on classic test datasets, the proposed algorithm has improved PSNR and SSIM compared to ESRGAN.

Single phase multiferroic BiFeO3 nanocrystals and BiFeO3 doped magneto optical BiFeO3–PbO–Bi2O3–B2O3 glasses have been synthesized and characterized in this study. Through the X-ray diffraction, Scanning electron microscopy, differential scanning calorimetry, UV–Vis optical absorption, Vicker's hardness and Verdet constant measurement, the glass structure and spectral were found to be modified by BiFeO3 nanocrystal, and Faraday rotation, absorption edge and mechanical performance of glasses were improved by such modification due to the low band gap, high polarization, ferromagnetic & superparamagnetic property of nanocrystal BiFeO3. Glass of 5%BiFeO3–40%PbO–50%Bi2O3–5%B2O3 exhibits a Verdet constant of 0.1615 min/G·cm at 633 nm, thermal stability of 105 °C and a 510 nm cutoff wavelength which is very attractive to magneto optical glass devices.

Understanding the spatial distribution patterns (SDPs) of natural disasters plays an essential role in reducing and minimizing natural disaster risks. An integrated discussion on the SDPs of multiple global disasters is still lacking. In addition, due to their high quantity and complexity, natural disasters constitute high-dimensional data that represent a challenge for an analysis of SDPs. This paper analyzed the SDPs of global disasters from 1980 to 2016 through biclustering. The results indicate that the SDPs of fatality rates are more uneven than those of occurrence rates. Based on the occurrence rates, the selected countries were clustered into four classes. (1) The major disasters along the northern Pacific and in the Caribbean Sea and Madagascar are storms, followed by floods. (2) Most of Africa is mainly affected by floods, epidemics, and droughts. (3) The primary disaster types in the Alpine-Himalayan belt and the western Andes are floods and earthquakes. (4) Europe, America, Oceania, and South and Southeast Asia are predominantly influenced by floods. In addition, according to the fatality rates, the selected countries were clustered into eight classes. (1) Extreme high temperatures mostly result in high fatality rates (HFRs) in developed countries. (2) Epidemics lead to HFRs in parts of Africa. (3) Droughts produce HFRs in East Africa. (4) Earthquakes result in HFRs along the eastern Pacific coastline and the Alpine-Himalayan belt. (5) Tsunamis mainly cause HFRs in Thailand, Indonesia, and Japan. (6) Storms result in scattered but distinct HFRs along the coastal regions of the Pacific and Indian Oceans. (7) Floods cause concentrated HFRs in South Asia and northeastern South America. (8) Finally, volcanoes cause HFRs in Colombia, while extreme low temperatures cause HFRs in Ukraine and Poland.