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PSO is a simple and yet powerful metaheuristic search algorithm widely used to solve various optimization problems. Nevertheless, conventional PSO tends to lose its population diversity drastically and suffer with compromised performance when encountering the optimization problems with complex fitness landscapes. Extensive studies suggest the needs of preserving high population diversity for PSO to escape from the local optima in order to solve complex optimization problems effectively. Inspired by these ideas, a hovering swarm PSO (HSPSO) is proposed in this paper, where a computationally efficient diversity preservation scheme is first introduced to divide the population of HSPSO into a main swarm and a hovering swarm. An exemplar construction scheme is subsequently proposed in the main swarm of HSPSO to generate a universal exemplar by considering the promising directional information contributed by the other non-fittest particles. The proposed universal exemplar is envisioned to suppress the negative impacts of global best particle, while remain effective to guide all particles of main swarm converging towards the promising solution regions. While hovering around the main swarm, an intelligent scheme is introduced to dynamically adjust inertia weights of all hovering swarm members to achieve proper balancing of exploration and exploitation searches at swarm levels. Extensive performance analyses are conducted by using the proposed HSPSO to solve 30 benchmark functions of CEC 2014 and five real-world engineering applications. Simulation results reveal that the HSPSO is able outperform the state-of-art optimizers when solving most tested functions due to its excellent diversity preservation capability.

Ever since the deployment of the first-generation of mobile telecommunications, wireless communication technology has evolved at a dramatically fast pace over the past four decades. The upcoming fifth-generation (5G) holds a great promise in providing an ultra-fast data rate, a very low latency, and a significantly improved spectral efficiency by exploiting the millimeter-wave spectrum for the first time in mobile communication infrastructures. In the years beyond 2030, newly emerged data-hungry applications and the greatly expanded wireless network will call for the sixth-generation (6G) communication that represents a significant upgrade from the 5G network - covering almost the entire surface of the earth and the near outer space. In both the 5G and future 6G networks, millimeter-wave technologies will play an important role in accomplishing the envisioned network performance and communication tasks. In this paper, the relevant millimeter-wave enabling technologies are reviewed: they include the recent developments on the system architectures of active beamforming arrays, beamforming integrated circuits, antennas for base stations and user terminals, system measurement and calibration, and channel characterization. The requirements of each part for future 6G communications are also briefly discussed.

Automatic modulation recognition (AMR) has become increasingly important in the field of signal processing, especially with the advancements of intelligent communication systems. Deep Learning (DL) technologies have been incorporated into the AMR field and they have shown outstanding performances against conventional AMR methods. The robustness of DL-based AMR methods under varying noise regimes is one of major concerns for the widespread utilization of this technology. Furthermore, most existing works have neglected the contributions of hand-crafted features (HCFs) in boosting the classification performances of DL-based AMR methods. In order to address the aforementioned technical challenges, a novel and robust DL-AMR method is proposed by leveraging the benefits of both contextual features (CFs) and HCFs for a specific range of signal-to-noise ratio (SNR). A novel feature selection algorithm is also proposed to search for the optimal sets of HCFs in order to reduce the dimensions of feature vectors without losing any important and relevant features. Simulation studies are performed to investigate the feasibility of proposed method in classifying 11 types of modulation schemes. Extensive performance analyses revealed the superiority of proposed method over baseline method in terms of the classification performance as well as the excellent capability of proposed feature selection algorithm in determining an optimal subset of HCFs.

Abstract The excessive accumulation of extracellular matrix (ECM) is a key feature of liver fibrosis and the activated hepatic stellate cells (HSCs) are the major producer of ECM proteins. However, the precise mechanisms and target molecules that are involved in liver fibrosis remain unclear. In this study, we reported that activating transcription factor 3 (ATF3) was over-expressed in mice and human fibrotic livers, in activated HSCs and injured hepatocytes (HCs). Both in vivo and in vitro study have revealed that silencing ATF3 reduced the expression of pro-fibrotic genes and inhibited the activation of HSCs, thus alleviating the extent of liver fibrosis, indicating a potential protective role of ATF3 knockdown. However, ATF3 was not involved in either the apoptosis or proliferation of HCs. In addition, our data illustrated that increased nuclear localization of ATF3 promoted the transcription of fibrogenic genes and lnc-SCARNA10, which functioned as a novel positive regulator of TGF-β signaling in liver fibrogenesis by recruiting SMAD3 to the promoter of these genes. Interestingly, further study also demonstrated that lnc-SCARNA10 promoted the expression of ATF3 in a TGF-β/SMAD3-dependent manner, revealing a TGF-β/ATF3/lnc-SCARNA10 axis that contributed to liver fibrosis by activating HSCs. Taken together, our data provide a molecular mechanism implicating induced ATF3 in liver fibrosis, suggesting that ATF3 may represent a useful target in the development of therapeutic strategies for liver fibrosis.

Abstract The aim of this study is to provide evidence for the influencing factors of severe acute respiratory syndrome coronavirus 2 (SARS‐COV‐2) virus mutation by determining the impact of geographical and meteorological factors on SARS‐CoV‐2 transmission, and the different impacts of SARS‐CoV‐2 variant strains. From January 20 to March 10, 2020, we collected a number of daily confirmed new cases and meteorological factors in all cities and regions in China and Italy affected by the Alpha “variants of concern” (VOC). We also collected the daily confirmed cases of the Delta VOC infection in China and Italy from May 21 to November 30, 2021. The relationships between daily meteorological data and daily verified new cases of SARS‐CoV‐2 transmission were then investigated using a general additive model (GAM) with a log link function and Poisson family. The results revealed that latitude was substantially connected with daily confirmed new instances of the Alpha VOC, while there was no such correlation with Delta VOC transmission. When visibility is greater than 7 m, the propagation of the Alpha and Delta VOCs in Italy and China can be controlled. Furthermore, greater temperatures and increased wind speed reduce the transmission of the Alpha and Delta VOCs. In conclusion, geographical and meteorological factors play an important role in SARS‐CoV‐2 transmissibility and should be considered in virus mitigation strategies.

ABSTRACT Clostridioides difficile is a Gram-positive, spore-forming anaerobic bacteria that is one of the leading causes of antibiotic-associated diarrhea. The cell wall protein 66 gene (cwp66) encodes a cell wall protein, which is the second major cell surface antigen of C. difficile. Although immunological approaches, such as antibodies and purified recombinant proteins, have been implemented to study the role of Cwp66 in cell adhesion, no deletion mutant of the cwp66 gene has yet been characterized. We constructed a cwp66 gene deletion mutant using Clustered Regularly Interspaced Short Palindromic Repeats Cpf1 (CRISPR-Cpf1) system. The phenotypic and transcriptomic changes of the Δcwp66 mutant compared with the wild-type (WT) strain were studied. The deletion of the cwp66 gene led to the decrease of cell adhesive capacity, cell motility, and stresses tolerance (to Triton X-100, acidic environment, and oxidative stress). Interestingly, the Δcwp66 mutant is more sensitive than the WT strain to clindamycin, ampicillin, and erythromycin but more resistant than the latter to vancomycin and metronidazole. Moreover, mannitol utilization capability in the Δcwp66 mutant was lost. Comparative transcriptomic analyses indicated that (i) 22.90-fold upregulation of cwpV gene and unable to express gpr gene were prominent in the Δcwp66 mutant; (ii) the cwp66 gene was involved in vancomycin resistance of C. difficile by influencing the expression of d-Alanine-d-Alanine ligase; and (iii) the mannose/fructose/sorbose IIC and IID components were upregulated in Δcwp66 mutant. The present work deepens our understanding of the contribution of the cwp66 gene to cell adhesion, stress tolerance, antibiotic resistance, and mannitol transportation of C. difficile. IMPORTANCE The cell wall protein 66 gene (cwp66) encodes a cell wall protein, which is the second major cell surface antigen of C. difficile. Although immunological approaches, such as antibodies and purified recombinant proteins, have been implemented to study the role of Cwp66 in cell adhesion, no deletion mutant of the cwp66 gene has yet been characterized. The current study provides direct evidence that the cwp66 gene serves as a major adhesion in C. difficile, and also suggested that deletion of the cwp66 gene led to the decrease of cell adhesive capacity, cell motility, and stresses tolerance (to Triton X-100, acidic environment, and oxidative stress). Interestingly, the antibiotic resistance and carbon source utilization profiles of the Δcwp66 mutant were significantly changed. These phenotypes were detrimental to the survival and pathogenesis of C. difficile in the human gut and may shed light on preventing C. difficile infection.

Enterococcus faecalis is a frequent opportunistic pathogen of wounds, whose infections are associated with biofilm formation, persistence, and recalcitrance toward treatment. We have previously shown that E. faecalis wound infection persists for at least 7 days. Here we report that viable E. faecalis are present within both immune and non-immune cells at the wound site up to 5 days after infection, raising the prospect that intracellular persistence contributes to chronic E. faecalis infection. Using in vitro keratinocyte and macrophage infection models, we show that E. faecalis becomes internalized and a subpopulation of bacteria can survive and replicate intracellularly. E. faecalis are internalized into keratinocytes primarily via macropinocytosis into single membrane-bound compartments and can persist in late endosomes up to 24 h after infection in the absence of colocalization with the lysosomal protease Cathepsin D or apparent fusion with the lysosome, suggesting that E. faecalis blocks endosomal maturation. Indeed, intracellular E. faecalis infection results in heterotypic intracellular trafficking with partial or absent labelling of E. faecalis-containing compartments with Rab5 and Rab7, small GTPases required for the endosome-lysosome trafficking. In addition, E. faecalis infection results in marked reduction of Rab5 and Rab7 protein levels which may also contribute to attenuated Rab incorporation into E. faecalis-containing compartments. Finally, we demonstrate that intracellular E. faecalis derived from infected keratinocytes are significantly more efficient in reinfecting new keratinocytes. Together, these data suggest that intracellular proliferation of E. faecalis may contribute to its persistence in the face of a robust immune response, providing a primed reservoir of bacteria for subsequent reinfection.

Non-alcoholic fatty liver disease (NAFLD) is among the most prevalent primary liver diseases worldwide and can develop into various conditions, ranging from simple steatosis, through non-alcoholic steatohepatitis (NASH), to fibrosis, and eventually cirrhosis and hepatocellular carcinoma. Nevertheless, there is no effective treatment for NAFLD due to the complicated etiology. Recently, activation of the NLPR3 inflammasome has been demonstrated to be a contributing factor in the development of NAFLD, particularly as a modulator of progression from initial hepatic steatosis to NASH. NLRP3 inflammasome, as a caspase-1 activation platform, is critical for processing key pro-inflammatory cytokines and pyroptosis. Various stimuli involved in NAFLD can activate the NLRP3 inflammasome, depending on the diverse cellular stresses that they cause. NLRP3 inflammasome-related inhibitors and agents for NAFLD treatment have been tested and demonstrated positive effects in experimental models. Meanwhile, some drugs have been applied in clinical studies, supporting this therapeutic approach. In this review, we discuss the activation, biological functions, and treatment targeting the NLRP3 inflammasome in the context of NAFLD progression. Specifically, we focus on the different types of therapeutic agents that can inhibit the NLRP3 inflammasome and summarize their pharmacological effectiveness for NAFLD treatment.

Background and ObjectivesAccumulating evidence suggests that oxidative stress is involved in the development of chronic obstructive pulmonary disease (COPD) and its progression. Activity of extracellular superoxide dismutase (ecSOD), the only extracellular enzyme eliminating superoxide radicals, has been reported to decline in acute exacerbations of COPD (AECOPD). However, the association between serum ecSOD activity and 1-year all-cause mortality in AECOPD patients remains unclear. The objective of our study was to explore the usefulness of ecSOD activity on admission in AECOPD as an objective predictor for 1-year all-cause mortality.MethodsWe measured serum ecSOD activity in AECOPD patients on admission in a prospective cohort study. We also recorded their laboratory and clinical data. Multivariate Cox regression was used to analyze the association between ecSOD activity and the risk of 1-year all-cause mortality. Restricted cubic spline curves were used to visualize the relationship between ecSOD activity and the hazard ratio of 1-year all-cause mortality.ResultsA total of 367 patients were followed up for 1 year, and 29 patients died during a 1-year follow-up period. Compared with survivors, the non-survivors were older (79.52 ± 8.39 vs. 74.38 ± 9.34 years old, p = 0.004) and had increased levels of tobacco consumption (47.07 ± 41.67 vs. 33.83 ± 31.79 pack-years, p = 0.037). Having an ecSOD activity ≤ 98.8 U/ml was an independent risk factor of 1-year all-cause mortality after adjustment for baseline differences, clinical variables and comorbidities [hazard ratio = 5.51, 95% confidence interval (CI): 2.35–12.95, p < 0.001].ConclusionLower serum ecSOD activity was a strong and independent predictor of 1-year all-cause mortality in AECOPD patients.

Artificial robots often require multiple independently activated actuators to achieve multimodal locomotion. Here, the authors report a hydrogel-based, biomimetic soft robot capable of multimodal locomotion fueled and steered by light irradiation.

Swept Friction Stir Spot Welding is provoked and fascinated for its captive performance in building space frame structures, ship buildings and panels of automotive vehicles. The aim of the current research is to avoid the wastage in welding of 6061-T6 aluminium alloy and to improve the sustainabilty of the weld process. Al2O3 nanoparticles were added into the guide hole for improving the weld characteristics. The percentage of reinforcement was varied by changing the guide hole diameter as 1.5, 2.0, 2.5 and 3.0 mm. An improved NSTLBO algorithm was proposed and applied. The proposed algorithm predicted the optimum welding parameters as D = 2.8 mm, N = 1387 rpm and F = 17 mm/minute with the predicted wear, lap shear load and microhardness of 197 microns, 6134 N and 94.6 HV, respectively. The validation experiments were further done and the error within 0.5% was found between the actual and predicted results. The results of proposed algorithm was evaluated with other popular meta-heuristic algorithms for the effectiveness. The microscopic examinations on weld zones and fracturerd samples were also presented. Industries can use these best process parameters predicted by the proposed algorithm for earning the best weld characteristics from eco-friendly welding.

Abstract Background Statins are the most widely used drugs in elderly patients; the most common clinical application of statins is in aged hyperlipemia patients. There are few studies on the effects and mechanisms of statins on bone in elderly mice with hyperlipemia. The study is to examine the effects of atorvastatin on bone phenotypes and metabolism in aged apolipoprotein E-deficient (apoE–/–) mice, and the possible mechanisms involved in these changes. Methods Twenty-four 60-week-old apoE–/– mice were randomly allocated to two groups. Twelve mice were orally gavaged with atorvastatin (10 mg/kg body weight/day) for 12 weeks; the others served as the control group. Bone mass and skeletal microarchitecture were determined using micro-CT. Bone metabolism was assessed by serum analyses, qRT-PCR, and Western blot. Bone marrow-derived mesenchymal stem cells (BMSCs) from apoE–/– mice were differentiated into osteoblasts and treated with atorvastatin and silent information regulator 1 (Sirt1) inhibitor EX-527. Results The results showed that long-term administration of atorvastatin increases bone mass and improves bone microarchitecture in trabecular bone but not in cortical bone. Furthermore, the serum bone formation marker osteocalcin (OCN) was ameliorated by atorvastatin, whereas the bone resorption marker tartrate-resistant acid phosphatase 5b (Trap5b) did not appear obviously changes after the treatment of atorvastatin. The mRNA expression of Sirt1, runt-related transcription factor 2 (Runx2), alkaline phosphatase (ALP), and OCN in bone tissue were increased after atorvastatin administration. Western blot showed same trend in Sirt1 and Runx2. The in vitro study showed that when BMSCs from apoE–/– mice were pretreated with EX527, the higher expression of Runx2, ALP, and OCN activated by atorvastatin decreased significantly or showed no difference compared with the control. The protein expression of Runx2 showed same trend. Conclusions Accordingly, the current study validates the hypothesis that atorvastatin can increase bone mass and promote osteogenesis in aged apoE−/− mice by regulating the Sirt1–Runx2 axis.

Abstract Traffic-related air pollution particulate matter 2.5 (TRAPM2.5), is involved in chronic obstructive pulmonary disease (COPD), which is characterized by airway inflammation. Specifically, these harmful particles or gases can increase chronic airway inflammation. Some recent studies have shown that lncRNAs are closely related to COPD and participate in the regulation of airway inflammation. However, the precise mechanisms remain unknown. In the present study, we investigated the effect of TRAPM2.5 on airway inflammation in human bronchial epithelial cells (HBECs) and the underlying mechanisms mediated by a lncRNA. After exposure to TRAPM2.5, the novel lncRNA RP11-86H7.1 was markedly upregulated in HBECs. Functional assays indicated that the lncRNA RP11-86H7.1 was required for the TRAPM2.5-induced expression of inflammatory factors in HBECs. A mechanistic study demonstrated that lncRNA RP11-86H7.1 might participate in TRAPM2.5-induced inflammatory responses by activating the NF-κB signaling pathway. Moreover, the lncRNA RP11-86H7.1 can promote the inflammatory response by acting as a competing endogenous RNA of miR-9-5p, reversing the inhibitory effect of its target gene NFKB1, and sustaining NF-κB activation. In summary, our study elucidates the pro-inflammatory roles of the lncRNA RP11-86H7.1–miR-9-5p–NFKB1 regulatory network in airway inflammation induced by TRAPM2.5 and indicates that the components of this network might serve as novel diagnostic biomarkers and potential therapeutic targets.

Abstract Emerging evidence has revealed significant roles for small nucleolar RNAs (snoRNAs) in tumorigenesis. However, the genetic and pharmacogenomic landscape of snoRNAs has not been characterized. Using the genotype and snoRNA expression data from The Cancer Genome Atlas, we characterized the effects of genetic variants on snoRNAs across 29 cancer types and further linked related alleles with patient survival as well as genome-wide association study risk loci. Furthermore, we characterized the impact of snoRNA expression on drug response in patients to facilitate the clinical utility of snoRNAs in cancer. We also developed a user-friendly data resource, GPSno ( http://hanlab.uth.edu/GPSno ), with multiple modules for researchers to visualize, browse, and download multi-dimensional data. Our study provides a comprehensive genetic and pharmacogenomic landscape of snoRNAs, which will shed light on future clinical considerations for the development of snoRNA-based targeted therapies.

The Bacillus haemolytic enterotoxin haemolysin BL has been shown to activate the NLRP3 inflammasome. Here the authors show that a non-haemolytic enterotoxin (NHE) from B. cereus can also activate the NLRP3 inflammasome with a similar mechanism of lytic pore formation.

This paper describes a wideband, low-profile and efficiency-improved transmitarray antenna achieved by employing over-1-bit phase-shifting elements and incorporating optimized phase compensation scheme. Firstly, a wideband ultrathin 1-bit phase-shifting unit cell is presented based on the polarization twisting feature of the twisted stacking aperture structure. A minor variation in unit-cell geometry is then introduced to add more degrees of freedom in phase adjustment while maintaining nearly same low insertion loss within a wide frequency range. Moreover, the resultant performances of transmitarrays using different phase compensation schemes are compared. An optimized scheme that has a minimized average phase error and effectively enhances the aperture efficiency is adopted. Results of a 21.5% 1-dB gain bandwidth, 0.127-λ0 aperture thickness and 40% aperture efficiency are observed from the fabricated 14 × 14 transmitarray antenna.

This work presents a novel method for fast characterization of broadband and continuous dielectric properties of microwave substrates based on an ungrounded coplanar waveguide (UGCPW) structure containing two simple straight lines. The proposed method could, to some extent, alleviate the derivation error due to connector soldering and device fabrication. To verify this point, theoretical analysis and result comparisons are carried out. By considering both the conductor loss and radiation loss, the dielectric loss tangent can be retrieved with a high precision. The deviation of the measured dielectric constant and dielectric loss tangent are found to be within 0.03 (0.68%, 4.37 vs 4.40) and 0.0013 (6.5%, 0.0213 vs 0.02), respectively, in the range from 12 to 20 GHz, which is more accurate than the results reported in the literature, all while the proposed extraction approach is simpler than other methods such as the wave cascading matrix (WCM) algorithm. Due to the UGCPW configuration, this method is suitable for property evaluation of emerging synthesized dielectric materials, as a single round of electroplating process is required for device design, which can eliminate possible consistency error in conductor thickness and roughness caused by multiple electroplating process.

Convolutional neural networks (CNN) have a significant improvement in the accuracy of object detection. As networks become deeper, the precision of detection becomes obviously improved, and more floating-point calculations are also needed. Because of the great amount of calculation, it is inconvenient for mobile and embedded vision applications. Many researchers apply the knowledge distillation method to improve the precision of object detection by transferring knowledge from a deeper and larger teachers network to a small student one. Most methods of knowledge distillation are needed to design complex cost functions and mainly aim at the two-stage object detection algorithm. Therefore, we propose a clean and effective knowledge distillation method called Generative Adversarial Networks - Knowledge Distillation(GAN-KD) for the one-stage object detection. The feature maps generated by teacher network and student network are employed as true and fake samples respectively, and generating adversarial training for both of them to improve the performance of the student network in one-stage object detection. The experimental result shows that our approach achieves the performance gain of 5% mAP when compared with MobilenetV1 on COCO dataset.

Substrate integrated waveguide (SIW) elliptical cavity-backed slot antennas (CBSAs) with either penta- or hepta-resonance are characterized and designed for wideband performance in this paper. First, the resonant behavior of the elliptical cavity is explored. Then the SIW CBSA with penta-resonance is designed by introducing a cross-shaped slot and a pair of unbalanced shorting vias into the cavity to excite two additional odd- and even- half degenerate quasi-TM110 modes, besides other three modes of half quasi-TM010, and odd- and even- quasi-TM110. Further, by adding another pair of unbalanced shorting vias, two extra higher-order modes, i.e., odd- and even- quasi-TM210 modes are successfully introduced to design a hepta-resonance antenna. The corresponding mode analysis and design guidelines are discussed in detail. Two prototypes are fabricated and measured at X-band, exhibiting the measured bandwidths of 21.8% and 22.7%, respectively. Measured results agree well with simulations, thus validating the design concept.

In this paper, a 37-42.5GHz (N260 Band) 64 channel full-digital multi-beam array for 5G massive multiple input multiple output (MIMO) applications is developed. The multi-beam array is built on a time division duplexing (TDD) architecture in which the transmitter and receivers are independent and working separately to enable more flexible channel configuration and hardware distribution. The 64 antenna elements of the array are aligned in a way that 16 elements lie in the horizontal and 4 in the vertical direction to deliver higher beam resolution in the horizontal plane. By using cables of unequal lengths, the 16 × 4 antenna elements are connected to a cluster of 8 × 8 transmitters/receivers. The hardware design of the transmitters, receivers, antennas and other circuits is demonstrated, with excellent measured RF performance achieved. Furthermore, the calibration of the massive MIMO array is presented, and the influence of inequality of array feedlines on calibration accuracy in a wide bandwidth is analyzed and experimentally verified. Finally, experimental studies on single beam scanning, multiple concurrent beam generation and over-the-air (OTA) performance of the transmitting and receiving array have been done. Simulation and measurement results suggest that the array has an excellent beam-forming capability that supports beam steering and generation of multiple concurrent beams. The OTA test reveals that the array can provide high modulation and demodulation accuracy for communication.

In this paper, a novel two-transmission-line method based on optimized ABCD matrix for broadband and continuous substrate dielectric characterization is presented. The original single-line algorithm is firstly discussed and simulated, while the measurement shows that the extracted parameters are far from the actual values due to the presence of microwave connectors and transition mismatches. Therefore, a modified two-line algorithm based on the optimized ABCD matrix is proposed for ungrounded coplanar waveguide (UGCPW) configuration, which is very suitable for electroplating circuits with a consistent conductor layer on newly developed substrates. A comprehensive procedure to calculate the total line attenuation, phase number, characteristic impedance, substrate dielectric constant, and dielectric loss tangent is described. Since both conductor and radiation losses are taken into account, the extracted results show consistency within a single-digital percentage with the reference values. The analysis of the measurement uncertainty and the related uncertainty budgets for the derived dielectric results are also presented. The proposed method is expected to be applied to any transmission lines with arbitrary characteristic impedance, without a prior knowledge of substrate dielectric constant, and no additional calibrations are required other than the calibration kit for Vector Network Analyzer (VNA).

Despite of its simplicity, the conventional learning strategy of canonical particle swarm optimization (PSO) is inefficient to handle complex optimization problems due to its tendency of overemphasizing the fitness information of global best position without considering the diversity information of swarm. In this article, a modified particle swarm optimization with effective guides (MPSOEG) is proposed, aiming to improve the algorithm's search performances in handling the optimization problems with different characteristics. Depending on the search performance of algorithm, two types of exemplars can be generated by an optimal guide creation (OGC) module incorporated into MPSOEG by referring to the particles with valuable directional information. Particularly, a global exemplar is generated by OCG module to guide the swarm converging towards the promising solution regions of search space, whereas a unique local exemplar can be customized for each particle to enable it escaping from local or non-optimal solution regions. In contrary to global best particle, the exemplars generated by OGC module are able to guide all MPSOEG particles more effectively by considering both fitness and diversity information of swarm, hence can achieve better balancing of algorithm's exploration and exploitation searches. Another notable contribution of MPSOEG is the simplicity of its learning framework through the elimination of both inertia weight and acceleration coefficients parameters. Comprehensive simulation studies are conducted with 25 benchmark functions and the proposed MPSOEG is reported to outperform its six peer algorithms in terms of search accuracy, search reliability and search efficiency in most tested problems.

In the surface field integral equations (SIEs) from three-dimensional homogeneous dielectric objects, the equivalence electric and magnetic currents on the discontinuous interfaces between different homogeneous media are two independent sources. When the SIEs are iteratively solved, as indicated by the published literatures, the multilevel fast multipole algorithm (MLFMA) needs to be implemented respectively for the electric field integral equation (EFIE) and the magnetic field integral equation (MFIE) with these two currents, and hence a few MLFMA implementations are necessary for each homogeneous medium. In this paper, a concise and efficient scheme is proposed for reducing the implementations of the SIEs-MLFMA. First, the summation of the EFIE and MFIE-MLFMA implementations with the two currents can be simplified into one EFIE or MFIE-MLFMA implementation with integrating electric and magnetic currents at the lowest-level aggregation stage. Secondly, the common matrix frameworks consisting of the EFIE and MFIE-MLFMA implementations used in the SIEs can be simplified into one MLFMA implementation with two lowest-level diaggregations. The enhanced MLFMA scheme has excellent applicability to eight kinds of SIEs in wide use. In this way, the resulted SIE-MLFMA scheme performs only once for each homogeneous medium when transforming outgoing wave expansions of the two currents into incoming wave expansions for bottom cubes. Compared with the widely-used implementation approach of the MLFMA one by one for the two currents, it reduces the computation complexity by one half without sacrificing accuracy and adding a little memory requirement. Some examples are presented to validate the enhanced MLFMA scheme.

A large number of sinusoidal fractures exist in the open-pit slopes of mines, and the mechanical properties of shear failure are of great significance to the stability of the open-pit slope. Sandstone specimens containing sinusoidal fractures with different undulated heights were prefabricated by the CNC sand-wire-electrode cutting technology to explore the effect of sinusoidal fractures on the mechanical properties of shear failure of rock masses. The TFD-20H/50J rock shear testing machine was used for shear tests on sinusoidal-fracture sandstone with different undulated heights. In the shear loading process, the prefabricated-fracture sandstone specimens with different undulated heights have the fracture-compacting stage, linear-elastic changing stage, bottom-up stage, and residual strength stage. Before peak strength, the sinusoidal prefabricated-fracture rock masses with different undulated heights have the precursory characteristics of decreased stress, which can provide an early warning for the instability and failure of rock masses. The undulated height of sinusoidal fractures significantly affects the fracture initiation and propagation of specimens. Fractures occur and develop from the prefabricated fractures at low undulated height (≤10 mm) to multiple ways under the high undulated height (>10 mm); that is, fractures occur at the prefabricated fractures and the end of specimens simultaneously. With the increased undulated height, the fractures expand from parallel to the slope of the prefabricated fractures to perpendicular to the prefabricated fractures. The fracture propagation direction of sinusoidal-fracture rock masses with different undulated heights is mainly from the middle of the slope surface of prefabricated fractures to the end. It is the main direction of the shear failure of sinusoidal prefabricated fractures, and the monitoring of weak planes should be strengthened in the actual slope engineering.

BackgroundNeoantigens are presented on the cancer cell surface by peptide-restricted human leukocyte antigen (HLA) proteins and can subsequently activate cognate T cells. It has been hypothesized that the observed somatic mutations in tumors are shaped by immunosurveillance.MethodsWe investigated all somatic mutations identified in The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) samples. By applying a computational algorithm, we calculated the binding affinity of the resulting neo-peptides and their corresponding wild-type peptides with the major histocompatibility complex (MHC) Class I complex. We then examined the relationship between binding affinity alterations and mutation frequency.ResultsOur results show that neoantigens derived from recurrent mutations tend to have lower binding affinities with the MHC Class I complex compared to peptides from non-recurrent mutations. Tumor samples harboring recurrent SKCM mutations exhibited lower immune infiltration levels, indicating a relatively colder immune microenvironment.ConclusionsThese results suggested that the occurrences of somatic mutations in melanoma have been shaped by immunosurveillance. Mutations that lead to neoantigens with high MHC class I binding affinity are more likely to be eliminated and thus are less likely to be present in tumors.

Purpose. The goal of this study was to see if electroacupuncture was effective and safe in the management of cerebral infarction. PubMed, Embase, Cochrane Library, and Web of Science were used to conduct a comprehensive literature survey. Methods. Basic features of 7 studies were identified using the searching strategy. The investigation was found in PubMed, Embase, and Web of Science, with the most recent search being in March 2022. “Electroacupuncture,” “cerebral infarction,” and their permutations were among the MeSH terms and free words used. As literature, two reviewers independently used a standardized form to gather pertinent data from qualifying research. Results. 157 literatures were identified and evaluated. Electroacupuncture improved the BI score in individuals with cerebral infarction (mean difference=0.10, 95 percent CI: 0.00-0.20, p=0.04). Electroacupuncture enhanced BI score in individuals with cerebral infarction (mean difference=0.10, 95 percent CI: 0.00-0.20, p=0.04). The effects of electroacupuncture increased Fugl-Meyer index in patients with cerebral infarction (mean difference=25.92, 95% CI: 25.28-26.56, p

Wire cut EDM is a quite regularly used machining process in mechanical and electronic industries. This research has attempted to machine aluminum alloy for which experimental design was prepared using Box-Behnken design. Different combinational options of pulse-on time (P1), pulse-off time (P2), servo wire feed (WF), and current (I) were investigated and surface roughness after machining was observed. Collected 27 datasets were further used in Adaptive Neuro Fuzzy Inference System (ANFIS) to produce about 500 datasets. These 500 datasets are approximated data derived from experimental datasets, known as synthetic data. Data model was further developed and used in Gorilla Troops Optimizer (GTO) to locate the optimum machining parameters. With the excellent three search operators: move towards other gorillas, migrate towards unknown places, and migrate towards known places, GTO has produced the lowest surface roughness value of 0.500953 μm when the machining parameters of pulse-on time, pulse-off time, wire feed, and current values were set as 121 μs, 52 μs, 3 m/min, and 166A, respectively. To ensure the accuracy of the synthetic data-based model and optimality, verification and validation were conducted. Wilcoxon signed rank test was conducted for the pairwise comparison of GTO with each of its competing algorithms at the significance level of σ = 0.05. Friedman test was conducted to calculate the average ranking of each algorithm and to detect the global differences between all compared algorithms. Outperforming performance by GTO algorithm in machining of the selected material is found.

Recycled fine aggregate (RFA) generated from waste concrete, especially in harsh environment, can be considered as an alternative to natural sand. The yield rate, gradation and properties of RFA from natural aggregate concrete with the target strength of C40 as parent concrete (PC) every 200 freeze–thaw (FT) cycles are investigated. To more accurately evaluate the application potential of RFA, the mechanical properties and durability of recycled fine aggregate concrete (RFAC) is further studied. The results showed that as the FT cycles of PC increased, the yield rate of RFA decreases and the grading curve of RFA meets the requirements of Class II aggregate. The limit FT cycles of PC in Class II and III RFA are 148 and 450, respectively. For the compressive strength of RFAC that meets the design requirements, the FT cycles of PC are no more than 530. Based on 50 years of RFAC in Class D and Class E environments, the limit FT cycles of PC are 663 and 200, respectively. The limit FT cycles of PC are 221 based on 50 years of RFAC service in cold regions. Through the FT cycles of PC, the Class of RFA and the mechanical and durability of RFAC can be directly predicted. This provides a theoretical and data support for improving the utilization rate of waste concrete in FT environment.

Cosmology constraints serve as a crucial criterion in discriminating cosmological models. The traditional combined method to constrain the cosmological parameters designates the corresponding theoretical value and observational data as functions of redshift; however, sometimes the redshift cannot be measured directly, or the measurement error is large, or the definition of redshift is controversial. In this paper, we propose a novel joint method to constrain parameters that eliminates the redshift z and makes full use of the multiple observables $\left\{{{ \mathcal F }}_{1,\mathrm{obs}},{{ \mathcal F }}_{2,\mathrm{obs}},\cdots ,{{ \mathcal F }}_{M,\mathrm{obs}}\right\}$ spanning in M -dimensional joint observable space. Considering the generality of the mathematical form of the cosmological models and the guidance from low to high dimensions, we first validate our method in a 3D joint observable space spanned by H ( z ), f σ _8 ( z ), and D _A ( z ), where the three coordinates can be considered redshift-free measurements of the same celestial body (or shared-redshift data-reconstructed model independently). Our results are consistent with the traditional combined method but with lower errors, yielding H _0 = 68.7 ± 0.1 km s ^−1 Mpc ^−1 , Ω _m _0 = 0.289 ± 0.003, and σ _8 = 0.82 ± 0.01 and showing alleviated parametric degeneracies to some extent. In principle, our joint constraint method allows an extended form keeping the redshift information as an independent coordinate and can also be readily degraded to the form of a traditional combined method to constrain parameters.

Transport of fast electrons in overdense plasmas is of key importance in high energy density physics. However, it is challenging to diagnose the fast electron transport in experiments. In this article, we study coherent transition radiation (CTR) generated by fast electrons on the back surface of the target by using 2D and 3D first-principle particle-in-cell (PIC) simulations. In our simulations, aluminum targets of 2.7 g cc ^−1 are simulated in two different situations by using a newly developed high order implicit PIC code. Comparing realistic simulations containing collision and ionization effects, artificial simulations without taking collision and ionization effects into account significantly underestimate the energy loss of electron beams when transporting in the target, which fail to describe the complete characteristics of CTR produced by electron beams on the back surface of the target. Realistic simulations indicate the diameter of CTR increases when the thickness of the target is increased. This is attributed to synergetic energy losses of high flux fast electrons due to Ohm heating and colliding drags, which appear quite significant even when the thickness of the solid target only differs by micrometers. Especially, when the diagnosing position is fixed, we find that the intensity distribution of the CTR is also a function of time, with the diameter increased with time. As the diameter of CTR is related to the speed of electrons passing through the back surface of the target, our finding may be used as a new tool to diagnose the electron energy spectra near the surface of solid density plasmas.

Rap1 is a telomeric protein that is highly expressed in cancers. Here, the authors show that Rap1 interacts with several DNA repair proteins independent of its telomere function to enhance DNA repair and that its deficiency leads to accelerated tumorigenesis, but enhanced sensitivity to genotoxic stress.

Background: We compared the efficacy, safety, and immunogenicity of MIL60 with reference bevacizumab as first-line treatment in patients with advanced or recurrent non-squamous non-small cell lung cancer (NSCLC) in this phase 3, randomized, double-blind study. Methods: Patients with untreated advanced or recurrent NSCLC were randomized (1:1 ratio) to receive either MIL60 or bevacizumab in combination with paclitaxel/carboplatin. Patients with non-progressive disease continued maintenance single-agent MIL60 until disease progression, or intolerable toxicity. The primary endpoint was the 12-week objective response rates (ORR12) by independent review committee (IRC) using RECIST 1.1. Bioequivalence was established if the ORR ratio located between 0.75 and 1/0.75. The trial was registered with clinicaltrials.gov (NCT03196986). Findings: Between Aug 23, 2017, and May 8, 2019, 517 patients were randomly assigned to MIL60 group (n=257) and bevacizumab group (n=260). In the full analysis set (FAS) population including all randomized and evaluable patients who received at least one dose of MIL60 or bevacizumab, the ORR12 in MIL60 group and bevacizumab group were 48.6% and 43.1%, respectively. The ORR ratio of these two groups were 1.14 (90% CI 0.97-1.33), which fell within the pre-specified equivalence boundaries (0.75-1/0.75). The median DOR was 5.7 months (95% CI 4.5-6.2) for MIL60 and 5.6 months (95% CI 4.3-6.4) for bevacizumab. No significant difference was noted in median PFS (7.2 vs. 8.1 months; HR 1.01, 95% CI 0.78-1.30, p=0.9606) and OS (19.3 vs. 16.3 months; HR 0.81, 95% CI 0.64-1.02, p=0.0755). Safety and tolerability profiles were similar between the two groups. No patient detected positive for Anti-drug antibody (ADA). Interpretation: The efficacy, safety and immunogenicity of MIL60 were similar with bevacizumab, providing an alternative treatment option for advanced or recurrent non-squamous NSCLC. Funding: This study was sponsored by Betta Pharmaceutical Co., Ltd.

Abstract Anisotropic structures are ubiquitous in nature, affording fascinating morphing behaviors. Biomimetic morphing materials can be developed by spatially controlling the orientations of molecules or nanofillers that produce anisotropic responses and internal stresses under external stimuli. However, it remains a serious challenge to fabricate materials with sophisticated anisotropic architectures. Here, a facile strategy to fabricate morphing hydrogels with elaborately ordered structures of nanosheets, which are oriented under distributed electric field and immobilized by polymerization to form a poly(N‐isopropylacrylamide) matrix, is proposed. Diverse sophisticated anisotropic structures are obtained by engineering the electric field through the patterns and relative locations of the electrodes. Upon heating, the monolithic hydrogels with through‐thickness and/or in‐plane gradients in orientation of the nanosheets deform into various three‐dimensional configurations. After incorporating gold nanoparticles, the hydrogels become photoresponsive and capable of programmable motions, for example, dynamic twisting and flipping under spatiotemporal stimuli. Such a strategy of using patterned electrodes to generate distributed electric field should be applicable to systems of liquid crystals or charged particles/molecules to direct orientation or electrophoresis and form functional structures. The biomimetically architectured hydrogels would be ideal materials to develop artificial muscles, soft actuators/robots, and biomedical devices with versatile applications.

Background: The placenta is an important organ for fetal and maternal health during pregnancy and impacts offspring health late in life. Defects in placental vasculature and trophoblast have been identified in several pregnancy complications. Thus, the detailed molecular profile and heterogeneity of endothelial cells and trophoblasts in placentas will aid us in better understanding placental behaviors and improving pregnancy outcomes. Methods: Single-cell RNA sequencing (scRNA-seq) was performed to profile the transcriptomics of human placental villous tissues from eleven patients with normal pregnancies in the first and second trimesters (6–16 weeks of gestation). Results: The transcriptomic landscape of 52,179 single cells was obtained, and the cells were classified as trophoblasts, fibroblasts, endothelial cells, erythroid cells, Hofbauer cells, and macrophages. Our analysis further revealed the three subtypes of placental endothelial cells, with distinct metabolic signatures and transcription factor regulatory networks. We also determined the transcriptomic features of the trophoblast subpopulations and characterized two distinct populations of progenitor cells in cytotrophoblasts, which were capable of differentiating to extravillous trophoblasts and syncytiotrophoblasts, respectively. Conclusions: Our study provided a high-resolution molecular profile of the human placenta between 6 and 16 weeks of gestation. Our data revealed the placental cell complexity and demonstrated the transcriptional networks and signaling involved in placental endothelial and trophoblast differentiation during early pregnancy, which will be a resource for future studies of the human placental development.

One of the relevant factors in smart energy management is the ability to predict the consumption of energy in smart households and use the resulting data for planning and operating energy generation. For the utility to save money on energy generation, it must be able to forecast electrical demands and schedule generation resources to meet the demand. In this paper, we propose an optimized deep network model for predicting future consumption of energy in smart households based on the Dipper Throated Optimization (DTO) algorithm and Long Short-Term Memory (LSTM). The proposed deep network consists of three parts, the first part contains a single layer of bidirectional LSTM, the second part contains a set of stacked unidirectional LSTM, and the third part contains a single layer of fully connected neurons. The design of the proposed deep network targets represents the temporal dependencies of energy consumption for boosting prediction accuracy. The parameters of the proposed deep network are optimized using the DTO algorithm. The proposed model is validated using the publicly available UCI household energy dataset. In comparison to the other competing machine learning models, such as Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP), Sequence-to-Sequence (Seq2Seq), and standard LSTM, the performance of the proposed model shows promising effectiveness and superiority when evaluated using eight evaluation criteria including Root Mean Square Error (RMSE) and R2. Experimental results show that the proposed optimized deep model achieved an RMSE of (0.0047) and R2 of (0.998), which outperform those values achieved by the other models. In addition, a sensitivity analysis is performed to study the stability and significance of the proposed approach. The recorded results confirm the effectiveness, superiority, and stability of the proposed approach in predicting the future consumption of energy in smart households.

As a major public health problem, the prevalence of Acinetobacter baumannii (A. baumannii) infections in hospitals due to the pathogen’s multiple-antibiotic resistance has attracted extensive attention. We previously reported a series of 1,3-diamino-7H-pyrrolo[3,2-f]quinazoline (PQZ) compounds, which were designed by targeting Escherichia coli dihydrofolate reductase (ecDHFR), and exhibited potent antibacterial activities. In the current study, based on our molecular-modeling study, it was proposed that PQZ compounds may function as potent A. baumannii DHFR (abDHFR)-inhibitors as well, which inspired us to consider their anti-A. baumannii abilities. We further found that three PQZ compounds, OYYF-171, -172, and -175, showed significant antibacterial activities against A. baumannii, including multidrug-resistant (MDR) strains, which are significantly stronger than the typical DHFR-inhibitor, trimethoprim (TMP), and superior to, or comparable to, the other tested antibacterial agents belonging to β-lactam, aminoglycoside, and quinolone. The significant synergistic effect between the representative compound OYYF-171 and the dihydropteroate synthase (DHPS)-inhibitor sulfamethoxazole (SMZ) was observed in both the microdilution-checkerboard assay and time-killing assay, which indicated that using SMZ in combination with PQZ compounds could help to reduce the required dosage and forestall resistance. Our study shows that PQZ is a promising scaffold for the further development of folate-metabolism inhibitors against MDR A. baumannii.

The results of a commissioning experiment on the SILEX-Ⅱ laser facility (formerly known as CAEP-PW) are reported. SILEX-Ⅱ is a complete optical parametric chirped-pulse amplification laser facility. The peak power reached about 1 PW in a 30 fs pulse duration during the experiment. The laser contrast was better than 1010 at 20 ps ahead of the main pulse. In the basic laser foil target interaction, a set of experimental data were collected, including spatially resolved x-ray emission, the image of the coherent transition radiation, the harmonic spectra in the direction of reflection, the energy spectra and beam profile of accelerated protons, hot-electron spectra, and transmitted laser energy fraction and spatial distribution. The experimental results show that the laser intensity reached 5 × 1020 W/cm2 within a 5.8 µm focus (FWHM). Significant laser transmission did not occur when the thickness of the CH foil was equal to or greater than 50 nm. The maximum energy of the accelerated protons in the target normal direction was roughly unchanged when the target thickness varied between 50 nm and 15 µm. The maximum proton energy via the target normal sheath field acceleration mechanism was about 21 MeV. We expect the on-target laser intensity to reach 1022 W/cm2 in the near future, after optimization of the laser focus and upgrade of the laser power to 3 PW.

Staphylococcus aureus can produce a multilayered biofilm embedded in extracellular polymeric matrix. This biofilm is difficult to remove, insensitive to antibiotics, easy to develop drug-resistant strains and causes enormous problems to environments and health. Phage lysin which commonly consists of a catalytic domain (CD) and a cell-wall binding domain (CBD) is a powerful weapon against bacterial biofilm. However, the real-time interaction between lysin and S. aureus biofilm is still not fully understood. In this study, we monitored the interactions of three lysins (ClyF, ClyC, PlySs2) against culture-on-chip S. aureus biofilm, in real-time, based on surface plasmon resonance (SPR). A typical SPR response curve showed that the lysins bound to the biofilm rapidly and the biofilm destruction started at a longer time. By using 1:1 binding model analysis, affinity constants (KD) for ClyF, ClyC, and PlySs2 were found to be 3.18 ± 0.127 μM, 1.12 ± 0.026 μM, and 15.5 ± 0.514 μM, respectively. The fact that ClyF and PlySs2 shared the same CBD but showed different affinity to S. aureus biofilm suggested that, not only CBD, but also CD affects the binding activity of the entire lysin. The SPR platform can be applied to improve our understanding on the complex interactions between lysins and bacterial biofilm including association (adsorption) and disassociation (destruction).

ObjectiveHepatocellular carcinoma (HCC) is one of the most common and malignant tumors with an insidious onset, difficult early diagnosis, and limited therapy options, resulting in a poor prognosis. Cell division cycle associated 2 (CDCA2), also known as Repo-Man, plays an important role in regulating mitosis and DNA repair, but the involvement of CDCA2 in HCC remains unclear.MethodsThe differentially expressed genes that were significantly upregulated in multiple RNA sequencing datasets of HCC were screened. Receiver operating characteristic (ROC) curve analysis was performed to identify diagnostic markers for HCC. Least absolute shrinkage and selection operator Cox regression analysis was performed to screen the prognosis-related genes. The screening and analyses identified CDCA2 as the target gene in this study. The expression of CDCA2 was analyzed in public databases and clinical specimens, and CDCA2 involvement in HCC was explored by both bioinformatic analysis and in vitro experiments.ResultsThe level of CDCA2 was enhanced in HCC compared with healthy livers. Overexpression of CDCA2 positively correlated with the pathological grade and TNM stage of the diseases. Furthermore, CDCA2 was found to be an independent prognostic predictor. An excellent prognostic model of HCC was successfully constructed with CDCA2 in combination with TNM stage. Bioinformatic analysis revealed that CDCA2 was closely associated with the cell cycle, apoptosis, and p53 signaling pathway. Silencing CDCA2 in Huh7 cells resulted in significant upregulation of p53 and the downstream PUMA and NOXA and a subsequently increased apoptosis. Inhibition of p53 signaling and apoptosis was found after overexpression of CDCA2 in L02 cells. Strikingly, the proliferation of cells was not affected by CDCA2.ConclusionsCDCA2 was a novel diagnostic marker for HCC, and overexpression of this gene reflected poor pathological grade, stage, and clinical prognosis. CDCA2 promoted the pathogenesis of HCC by suppressing the p53-PUMA/NOXA signaling and the subsequent apoptosis.

Human skin diseases have become increasingly prevalent in recent decades, with millions of individuals in developed countries experiencing monkeypox. Such conditions often carry less obvious but no less devastating risks, including increased vulnerability to monkeypox, cancer, and low self-esteem. Due to the low visual resolution of monkeypox disease images, medical specialists with high-level tools are typically required for a proper diagnosis. The manual diagnosis of monkeypox disease is subjective, time-consuming, and labor-intensive. Therefore, it is necessary to create a computer-aided approach for the automated diagnosis of monkeypox disease. Most research articles on monkeypox disease relied on convolutional neural networks (CNNs) and using classical loss functions, allowing them to pick up discriminative elements in monkeypox images. To enhance this, a novel framework using Al-Biruni Earth radius (BER) optimization-based stochastic fractal search (BERSFS) is proposed to fine-tune the deep CNN layers for classifying monkeypox disease from images. As a first step in the proposed approach, we use deep CNN-based models to learn the embedding of input images in Euclidean space. In the second step, we use an optimized classification model based on the triplet loss function to calculate the distance between pairs of images in Euclidean space and learn features that may be used to distinguish between different cases, including monkeypox cases. The proposed approach uses images of human skin diseases obtained from an African hospital. The experimental results of the study demonstrate the proposed framework’s efficacy, as it outperforms numerous examples of prior research on skin disease problems. On the other hand, statistical experiments with Wilcoxon and analysis of variance (ANOVA) tests are conducted to evaluate the proposed approach in terms of effectiveness and stability. The recorded results confirm the superiority of the proposed method when compared with other optimization algorithms and machine learning models.

Convolutional neural networks (CNNs) have exhibited significant performance gains over conventional machine learning techniques in solving various real-life problems in computational intelligence fields, such as image classification. However, most existing CNN architectures were handcrafted from scratch and required significant amounts of problem domain knowledge from designers. A novel deep learning method abbreviated as TLBOCNN is proposed in this paper by leveraging the excellent global search ability of teaching–learning-based optimization (TLBO) to obtain an optimal design of network architecture for a CNN based on the given dataset with symmetrical distribution of each class of data samples. A variable-length encoding scheme is first introduced in TLBOCNN to represent each learner as a potential CNN architecture with different layer parameters. During the teacher phase, a new mainstream architecture computation scheme is designed to compute the mean parameter values of CNN architectures by considering the information encoded into the existing population members with variable lengths. The new mechanisms of determining the differences between two learners with variable lengths and updating their positions are also devised in both the teacher and learner phases to obtain new learners. Extensive simulation studies report that the proposed TLBOCNN achieves symmetrical performance in classifying the majority of MNIST-variant datasets, displays the highest accuracy, and produces CNN models with the lowest complexity levels compared to other state-of-the-art methods due to its promising search ability.

Aim Epithelial-mesenchymal transition (EMT) of retinal pigment epithelium (RPE) cells is the key of the development of diabetic retinopathy (DR), and lncRNA NEAT1 could accelerate EMT in diabetic nephropathy. Meanwhile, as a diabetes susceptibility gene, whether sex-determining region Y-related (SRY) high-mobility group box 4 (SOX4) has relationship with lncRNA NEAT1 in DR remains unclear. Methods Firstly, NEAT1, SOX4 and miR-204 were evaluated by qRT-PCR (quantitative reverse-transcriptase PCR) under high glucose condition. Then, cell viability, proliferation, migration and invasion were respectively detected by MTT, BrdU staining, wound healing and transwell assay after NEAT1 knockdown or miR-204 overexpression. Also, the EMT-related proteins were examined by western blot and cell immunofluorescence assay. In order to confirm the relationship between miR-204 and NEAT1 or SOX4, dual luciferase reporter gene assay was conducted. At the same time, the protein levels of SOX4 and EMT-related proteins were investigated by immunohistochemistry in vivo. Results High glucose upregulated NEAT1 and SOX4 and downregulated miR-204 in ARPE19 cells. NEAT1 knockdown or miR-204 overexpression inhibited the proliferation and EMT progression of ARPE19 cells induced by high glucose. NEAT1 was identified as a molecular sponge of miR-204 to increase the level of SOX4. The effect of NEAT1 knockdown on the progression of EMT under high glucose condition in ARPE19 cells could be reversed by miR-204 inhibitor. Also, NEAT1 knockdown inhibited retinal EMT in diabetic mice. Conclusion NEAT1 regulated the development of EMT in DR through miR-204/SOX4 pathway, which could provide reference for clinical prevention and treatment.

Abstract Chronic obstructive pulmonary disease is a complex condition with multiple etiologies, including inflammation. We identified a novel long noncoding RNA (lncRNA), interleukin 6 antisense RNA 1 (IL6‐AS1), which is upregulated in this disease and is associated with airway inflammation. We found that IL6‐AS1 promotes the expression of inflammatory factors, especially interleukin (IL) 6. Mechanistically, cytoplasmic IL6‐AS1 acts as an endogenous sponge by competitively binding to the microRNA miR‐149‐5p to stabilize IL‐6 mRNA. Nuclear IL6‐AS1 promotes IL‐6 transcription by recruiting early B‐cell factor 1 to the IL‐6 promoter, which increases the methylation of the H3K4 histone and acetylation of the H3K27 histone. We propose a model of lncRNA expression in both the nucleus and cytoplasm that exerts similar effects through differing mechanisms, and IL6‐AS1 probably increases inflammation via multiple pathways.

Optical nanoantennas can efficiently harvest electromagnetic energy from nanoscale space and boost the local radiation to the far field. The dielectric-metal nanogap is a novel design that can help to overcome the core issue of optical loss in all-metal nanostructures while enabling photon density of states larger than that in all-dielectric counterparts. This article reports that a crystalline spherical silicon nanoparticle on metal film (SiNPoM) nanoantenna can largely enhance the spontaneous emission intensity of quantum dots by an area-normalized factor of 69 and the decay rate by 42-fold compared with quantum dots on glass. A high total quantum efficiency of over 80%, including ~20% for far-field radiation and ~60% for surface plasmon polaritons, is obtained in simulation. Thanks to not only the low optical loss in dielectric nanoparticles but also the appropriate gap thickness which weakens the non-radiative decay due to the quenching from metal. Mie resonant modes additionally provide the flexible control of far-field emission patterns. Such a simple optical nanoantenna can be combined with various nanoscale optical emitters and easily extended to form large area metasurfaces functioning as active regions in light-emitting devices in applications such as advanced display, wireless optical communication, and quantum technology.

Abstract Background Sarcopenia and sarcopenic obesity (SO) have a greater impact on the elderly. This study aimed to explore whether there were sex differences in the prevalence and adverse outcomes of sarcopenia and SO in community-dwelling elderly individuals in East China. Methods This was a cross-sectional study that enrolled 213 males and 418 females aged > 65 years. Demographic characteristics, body composition, hand grip, gait speed, and indices of glucose and lipid metabolism were collected. Sarcopenia and SO were diagnosed using the Asian Working Group for Sarcopenia criteria. Results (1) The prevalence of sarcopenia was 19.2% in males and 8.6% in females. The prevalence of SO was 7.0% in males and 2.4% in females. (2) In males, the odds ratios (ORs) of osteoporosis and dyslipidemia in the SO group were 4.21-fold and 4.15-fold higher than those in the normal group, respectively. In females, the ORs of osteoporosis and hyperglycemia in the SO group were 1.12-fold and 4.21-fold higher than those in the normal group. Conclusions Males were more likely to be sarcopenic and to have SO than females using the AWGS criteria. Females with SO were more likely to have higher blood glucose, whereas males with SO were more likely to have osteoporosis and dyslipidemia.

Abstract Background Vomeronasal type 1 receptor genes (V1Rs) are expected to detect intraspecific pheromones. It is believed that rodents rely heavily on pheromonal communication mediated by V1Rs, but pheromonal signals are thought to be confined in subterranean rodents that live in underground burrows. Thus, subterranean rodents may show a contrasting mode of V1R evolution compared with their superterranean relatives. Results We examined the V1R evolution in subterranean rodents by analyzing currently available genomes of 24 rodents, including 19 superterranean and 5 subterranean species from three independent lineages. We identified a lower number of putatively functional V1R genes in each subterranean rodent (a range of 22–40) compared with superterranean species (a range of 63–221). After correcting phylogenetic inertia, the positive correlation remains significant between the small V1R repertoire size and the subterranean lifestyle. To test whether V1Rs have been relaxed from functional constraints in subterranean rodents, we sequenced 22 intact V1Rs in 29 individuals of one subterranean rodent (Spalax galili) from two soil populations, which have been proposed to undergo incipient speciation. We found 12 of the 22 V1Rs to show significant genetic differentiations between the two natural populations, indicative of diversifying selection. Conclusion Our study demonstrates convergent reduction of V1Rs in subterranean rodents from three independent lineages. Meanwhile, it is noteworthy that most V1Rs in the two Spalax populations are under diversifying selection rather than relaxed selection, suggesting that functional constraints on these genes may have retained in some subterranean species.

Abstract Background Alzheimer’s disease (AD) is responsible for 60–70% of all cases of dementia. On the other hand, the tap water consumed by hundreds of millions of people has been fluoridated to prevent tooth decay. However, little is known about the influence of fluoride on the expression of APP and subsequent changes in learning and memory and neuropathological injury. Our aim here was to determine whether exposure to fluoride aggravates the neuropathological lesions in mice carrying the amyloid precursor protein (APP)/presenilin1 (PS1) double mutation. Methods These transgenic or wide-type (WT) mice received 0.3 ml of a solution of fluoride (0.1 or 1 mg/ml, prepared with NaF) by intragastric administration once each day for 12 weeks. The learning and memory of these animals were assessed with the Morris water maze test. Senile plaques, ionized calcium binding adaptor molecule 1 (Iba-1), and complement component 3 (C3) expression were semi-quantified by immunohistochemical staining; the level of Aβ42 was detected by Aβ42 enzyme-linked immunosorbent assays (ELISAs); the levels of synaptic proteins and enzymes that cleave APP determined by Western blotting; and the malondialdehyde (MDA) content and activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) measured by biochemical procedures. Results The untreated APP mice exhibited a decline in learning and memory after 12 weeks of fluoride treatment, whereas treatment of these some animals with low or high levels of fluoride led to such declines after only 4 or 8 weeks, respectively. Exposure of APP mice to fluoride elevated the number of senile plaques and level of Aβ42, Iba-1, and BACE1, while reducing the level of ADAM10 in their brains. The lower levels of synaptic proteins and enhanced oxidative stress detected in the hippocampus of APP mice were aggravated to fluoride. Conclusions These findings indicate that exposure to fluoride, even at lower concentration, can aggravate the deficit in learning and memory and neuropathological lesions of the mice that express the high level of APP.

In this paper, a new class of shielded half-mode substrate integrated waveguide (SD-HMSIW) and shielded quarter-mode substrate integrated waveguide (SD-QMSIW) filtering power dividers (FPDs) have been presented. The proposed prototypes are capable of splitting/combining power and selecting frequency simultaneously. The SD-HMSIW and SD-QMSIW resonant cavities combine the features of compact size, high-quality factor, and low loss. To the best of author's knowledge, it is the first time employing the shielded SIW structure for FPD designs. The six prototype circuits with pure or hybrid SD-HMSIW/SD-QMSIW resonators are designed and fabricated to validate the proposed concept. Multilayered structures are implemented to minimize the dimensions of the FPDs further. Transmission zeros distributing near the operating passband are introduced by cross-coupling mechanism. Both measured and simulated results indicate that the proposed FPDs with the shielded SIW structures exhibit not only filtering performance, but also the good magnitude and phase imbalance characteristics in the operating frequency band.

Tomatoes (Solanum lycopersicum L.) are sensitive to chilling temperatures between 0 °C and 12 °C owing to their tropical origin. SlHSP17.7, a cytoplasmic heat shock protein, interacts with cation/calcium exchanger 1-like (SlCCX1-like) protein and promotes chilling tolerance in tomato fruits (Zhang, et al., Plant Sci., 2020, 298, 1–12). The overexpression of SlHSP17.7 can also promote cold tolerance in tomato plants, but its specific mechanism remains unclear. In this study, we show that the overexpression of SlHSP17.7 in tomato plants enhances chilling tolerance with better activity of photosystem II (PSII). Metabolic analyses revealed that SlHSP17.7 improved membrane fluidity by raising the levels of polyunsaturated fatty acids. Transcriptome analyses showed that SlHSP17.7 activated Ca2+ signaling and induced the expression of C-repeat binding factor (CBF) genes, which in turn inhibited the production of reactive oxygen species (ROS). The gene coexpression network analysis showed that SlHSP17.7 is coexpressed with SlMED26b. SlMED26b silencing significantly lowered OE-HSP17.7 plants’ chilling tolerance. Thus, SlHSP17.7 modulates tolerance to chilling via both membrane fluidity and Ca2+-mediated CBF pathway in tomato plants.