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Trackers based on fully-convolutional Siamese networks regard tracking as a process of learning a similarity function. By utilizing shallow networks and off-line training, Siamese trackers can achieve high tracking speed and perform well in some simple scenes. However, due to the less semantic information and the invariant template, Siamese trackers still have a gap compared with the state-of-the-art methods in complex scenes and other challenging problems (Occlusion, Deformation, etc.). In this paper, we propose a Siamese tracking algorithm with deep features and robust feature fusion (SiamDF). The improved ResNet-18 network is utilized to replace the traditional shallow network and extract the deep features with more semantic information. For eliminating the negative effect of padding and making better use of the deep network, the proposed algorithm adopts the spatial aware sampling strategy to overcome the strict translation invariance. Meanwhile, a final response map with high quality can be obtained by using the multi-layer feature fusion. Thus, the tracker can significantly reduce the impact of the distractors in complex scenes. In addition, an adaptive feature information fusion is adopted to update the template, so that the algorithm can adapt to various changes of the target appearance. Objective evaluation on the OTB100 dataset shows that the precision and the overlap success can reach 0.852 and 0.658 respectively. Moreover, the EAO value evaluated on the VOT2016 database can reach 0.336. These results demonstrate that our algorithm can effectively improve the tracking performance and perform favorably in both robustness and accuracy.

Existing Siamese network based trackers are easily disturbed by large deformation, occlusion and distractor objects in the background. By comparing these trackers, we observe that the monotonous positive pairs usually have limited challenging factors (Occlusion, Deformation, etc.), which may make the learned features less robust. In addition, the foreground information of the substantial training data is utilized directly without deeper exploration. Thus, the trackers cannot effectively discriminate the foreground from the semantic backgrounds. In this paper, we focus on modifying the Siamese tracker by enriching the positive pairs and taking further advantage of the foreground information. During the offline training phase, a simple sampling strategy is adopted to enrich the challenging factors in positive pairs, which can effectively enhance the robustness of the tracker. At the same time, we highlight the foreground information by padding the background, and the information is utilized to generate a novel padding loss, which guides the tracker to pay less attention to the distractors in the background. Moreover, an improved feature information fusion is adopted to update the template, so that the tracker can adapt to the drastic appearance changes. Comprehensive experiments on the OTB and the VOT benchmarks demonstrate that our proposed tracker can achieve outstanding performance in both accuracy and robustness.

In this paper, we consider an IoT dedicated network corresponding to a non licensed LoRa Low Power Wide Area Network. The LoRa network operates in the unlicensed 868 MHz band within a total bandwidth of 1 MHz divided into 8 orthogonal channels of 125 kHz each. Despite the high level of interference, this network offers long range communications in the order of 2 to 5 km in urban areas and 10 to 30 km in rural areas. To efficiently mitigate this high level of interference, LoRa network essentially relies on a Chirp Spread Spectrum (CSS) modulation and on repetition diversity mechanisms. The LoRa CSS modulation spreads the signal within a band of 125 kHz using 6 possible spreading factors (from 7 to 12) to target data rates (starting from 5 kbps for the closest node to 300 bps for the furthest ones). The repetition diversity mechanisms enable the data recovery when the transmission is subject to bad channel conditions or/and high interference levels. Although the CSS modulation protects edge-cell's devices from the high level of interference induced by nodes in the proximity of the gateway, it fails to protect nodes at the edge of a given SF region and several trials are required to recover the packet. In this paper, we propose an adaptive multi-channels allocation policy that attributes multiple adjacent channels of 125 kHz for nodes situated at the edge of SF zones. We study the impact of this adaptive sub-band allocation on the gateways' intensities, the rate distribution and the power consumption. Our results are based on a statistical characterization of the interference in the network as well as the outage probability in a typical cell.

Travel time is inherently uncertain in urban networks due to volatile traffic flows, signal controls, bus stops and disturbances from pedestrians. An effective way to characterize such uncertainty is by estimating Travel Time Distribution (TTD). However, conventional TTD models are lack of considering the interactions between turning movements within the link. Whereas the phenomenon of the Channelization Section Spillover (CSS) is very common, leading to strong interactions between turning movements. In this study, by incorporating the correlation of turning movements in the TTD model, that is, considering CSS, copula-based link-level and path-level TTD models are built. First, based on the empirical data, the correlations of turning movements are analyzed, and then the applicability of the various copula models are examined. The marginal distribution of each turning movement is described using parametric and non-parametric regression analysis, respectively. Then, the best-fitting copula is determined based on correlation parameters and the goodness-of-fit tests. As a case study, the chosen model is applied in estimating link-level and path-level TTD in an arterial road in Hangzhou, China, and compared with the model that did not consider the CSS before. Both results indicate that the copula-based approach can precisely capture the positively correlated relationship between turning movements during peak hours. Furthermore, higher TTD estimation accuracy demonstrates the significance to consider CSS, particularly in peak hours.

Innate lymphoid cells (ILCs) are a group of lymphocytes without diversified antigen receptors encoded by gene rearrangement on T and B cells. ILCs, which are tissue-resident innate immune cells, expressed particularly in the mucosa or the barrier surface, contribute to the formation of lymphoid organs, the maintenance of tissue homeostasis, and the regulation of antimicrobial defenses. It has been recently reported that ILCs were enriched at the maternal–fetal interface. During a successful pregnancy, the maternal immune system must tolerate a fetus as an allograft. With the new defined of ILCs, a number of studies have shown that three types of ILCs are involved in embryonic development and pregnancy maintenance as well as the occurrence and development of pregnancy-related complications. This article reviews the types and roles of ILCs in normal pregnancy and pregnancy-related diseases.

Background and Aims. Mean platelet volume to platelet count ratio (MPV/PC) has been found to be an independent risk factor for mortality in various diseases, including cardiovascular disease, cancer, and hemodialysis. We aimed to evaluate the association between MPV/PC and all-cause and cardiovascular (CV) mortality in peritoneal dialysis (PD) patients. Methods and Results. We conducted a retrospective cohort study at a single center and enrolled 1473 PD patients who were catheterized at our PD center from January 1, 2006, to December 31, 2013. All patients were divided into four groups according to the quartiles of baseline MPV/PC levels and followed up until December 31, 2018. A total of 453 patients died, and 221 deaths were caused by cardiovascular disease during a median follow-up time of 48.0 (21.9-82.2) months. There was a significant interaction by age of association between MPV/PC level and all-cause mortality (P=0.009), and multivariate Cox regression analysis showed that higher MPV/PC level was related to a decreased risk of all-cause and CV mortality in PD patients aged

Objectives. The patient rehabilitation transfer device is a typical personnel transfer equipment, which is mainly composed of outriggers, support arm, lifting arms, hooks, handrails, hydraulic cylinders, and other components. The existing research on the device is mainly focused on the configuration design and transfer mode, and the research on its dynamic characteristics during the transfer process has not been thoroughly discussed. Methodology. Based on the existing research, a portable hydraulic rehabilitation patient transfer device has been developed. Then the multi-rigid body dynamic and finite element flexible body models were established. Next, the dynamic characteristic difference between the two models of the device was studied. Results. As shown in the results, the finite element multi-flexible body model has obvious flexible vibration in the lifting stage, and the amplitude reaches 16 mm in the motion startup stage due to the influence of rigid-flexible coupling. The tip acceleration of the flexible body model was also influenced by the vibration, and the maximum acceleration value reaches 0.06 m/s2. According to the test results, the maximum acceleration of the terminal reaches 0.05 m/s2, which is close to the finite-element multi-flexible model simulation results. The experimentally measured natural frequency of the device is 3.1 Hz, which is also close to 3.2 Hz calculated by the simulation. Because the flexible component in the flexible model is only the lift arm, the natural frequency is slightly larger than the experimental value. Conclusion. According to the stress value of the finite element multi-body model motion process, the maximum stress appears at the moment when the motion reaches the top end, and the instantaneous stress reaches 206 Mpa, which is in line with the allowable stress range of the material design. The data obtained in this study will provide help for the follow-up clinical rehabilitation and intelligent device research.

Morindae officinalis Radix (MOR) is a famous traditional Chinese medicine (TCM) and functional food material for invigorating kidneys and tonifying yang. Processed Morindae officinalis Radix (PMOR) is obtained by steaming MOR. Traditionally, the clinical effects are discrepant between processing and nonprocessing herbal medicines. MOR and PMOR are commonly used in both clinical practice and dietary supplements, and the effect of invigorating kidneys and tonifying yang of PMOR is stronger than MOR. To clarify the overall chemical composition and the difference of MOR and PMOR, a method was developed with an ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS). Among the 110 identified components shared by MOR and PMOR, 55 compounds showed significant differences in contents. Among them, the contents of 29 components, including fructooligosaccharides, monotropein, deacetylasperulosidic acid, geniposide, and anthraquinone glycosides, were higher in MOR than in PMOR; the contents of 26 components, including difructose anhydride sucrose, and iridoid glycoside derivatives, were higher in PMOR than in MOR. Difructose anhydrides and iridoid glycoside derivatives were first discovered in PMOR. These results provided a scientific basis for research on the therapeutic material basis of MOR. It would provide a method for the comparison of processing and nonprocessing in Chinese medicines.

Numerous studies have suggested that the titers of antibodies against SARS-CoV-2 are associated with the COVID-19 severity, however, the types of antibodies associated with the disease maximum severity and the timing at which the associations are best observed, especially within one week after symptom onset, remain controversial. We attempted to elucidate the antibody responses against SARS-CoV-2 that are associated with the maximum severity of COVID-19 in the early phase of the disease, and to investigate whether antibody testing might contribute to prediction of the disease maximum severity in COVID-19 patients. We classified the patients into four groups according to the disease maximum severity (severity group 1 (did not require oxygen supplementation), severity group 2a (required oxygen supplementation at low flow rates), severity group 2b (required oxygen supplementation at relatively high flow rates), and severity group 3 (required mechanical ventilatory support)), and serially measured the titers of IgM, IgG, and IgA against the nucleocapsid protein, spike protein, and receptor-binding domain of SARS-CoV-2 until day 12 after symptom onset. The titers of all the measured antibody responses were higher in severity group 2b and 3, especially severity group 2b, as early as at one week after symptom onset. Addition of data obtained from antibody testing improved the ability of analysis models constructed using a machine learning technique to distinguish severity group 2b and 3 from severity group 1 and 2a. These models constructed with non-vaccinated COVID-19 patients could not be applied to the cases of breakthrough infections. These results suggest that antibody testing might help physicians identify non-vaccinated COVID-19 patients who are likely to require admission to an intensive care unit.

Precious metal-based materials such as commercial Pt/C are available electrocatalysts for redox reactions in Zn-air batteries. However, their commercial use is still limited by slow kinetics and restricted stability. In this work, we highlight a facial urea-assisted sol-gel method to synthesize A-site vacancy in LaMnO3+δ oxide for boosting its catalytic activity and further explore the effect of the amount of urea on the A-site LaMnO3. The A-site vacancy in LMO was confirmed by XRD, TEM, and XPS, which revealed that the urea-assisted sol-gel method mitigated the A-site vacancy in LaMnO3+δ and increased its surface area, thus ultimately accelerating its redox reaction kinetics. The half-wave potential and current density of the resultant 3.0U-LMO electrocatalyst were 0.74 V and 5.74 mA cm−2, respectively. It is worth noting that the assembled Zn-air battery with the 3.0U-LMO catalyst presented a power output of 130.04 mW cm−2 at 0.51 V and a promising energy efficiency of 58.4% after 150 cycles. This protocol might offer an efficient approach for developing new defect-regulated perovskites for electrocatalysis.

Temperature control is needed in the construction process of massive concrete and it can avoid the concrete cracks. Prediction of temperature development based on a hydration kinetics model can reduce the need for adiabatic temperature rise tests for concrete. However, the existing hydration kinetics model cannot accurately describe the hydration process of cement, thereby limiting the ability to further accurately predict the temperature rise of concrete based on the hydration kinetics model. This paper aims to establish a new hydration kinetics model, which is based on nucleation and growth model, and to predict the temperature development of concrete with set-controlling admixture based on this model. In this paper, the nucleation and growth of hydration products and the diffusion of free water by the modified boundary of nucleation and growth (BNG) model and the modified Fuji and Kondo’s model are described. The relationship between nucleation rate and apparent activation energy and the relationship between effective diffusion coefficient and apparent activation energy are linear. However, the relationship between growth rate and apparent activation is exponential. Finally, the temperature development of concrete can be calculated by the hydration degree of the cement.

Abstract To improve the deficient tracking ability of fully-convolutional Siamese networks (SiamFC) in complex scenes, an object tracking framework with Siamese network and re-detection mechanism (Siam-RM) is proposed. The mechanism adopts the Siamese instance search tracker (SINT) as the re-detection network. When multiple peaks appear on the response map of SiamFC, a more accurate re-detection network can re-determine the location of the object. Meanwhile, for the sake of adapting to various changes in appearance of the object, this paper employs a generative model to construct the templates of SiamFC. Furthermore, a method of template updating with high confidence is also used to prevent the template from being contaminated. Objective evaluation on the popular online tracking benchmark (OTB) shows that the tracking accuracy and the success rate of the proposed framework can reach 79.8% and 63.8%, respectively. Compared to SiamFC, the results of several representative video sequences demonstrate that our framework has higher accuracy and robustness in scenes with fast motion, occlusion, background clutter, and illumination variations.

BackgroundEarly diagnosis and treatment of pediatric Inflammatory bowel disease (PIBD) is challenging due to the complexity of the disease and lack of disease specific biomarkers. The novel machine learning (ML) technique may be a useful tool to provide a new route for the identification of early biomarkers for the diagnosis of PIBD.MethodsIn total, 66 treatment naive PIBD patients and 27 healthy controls were enrolled as an exploration cohort. Fecal microbiome profiling using 16S rRNA gene sequencing was performed. The correlation between microbiota and inflammatory and nutritional markers was evaluated using Spearman’s correlation. A random forest model was used to set up an ML approach for the diagnosis of PIBD using 1902 markers. A validation cohort including 14 PIBD and 48 irritable bowel syndrome (IBS) was enrolled to further evaluate the sensitivity and accuracy of the model.ResultCompared with healthy subjects, PIBD patients showed a significantly lower diversity of the gut microbiome. The increased Escherichia-Shigella and Enterococcus were positively correlated with inflammatory markers and negatively correlated with nutrition markers, which indicated a more severe disease. A diagnostic ML model was successfully set up for differential diagnosis of PIBD integrating the top 11 OTUs. This diagnostic model showed outstanding performance at differentiating IBD from IBS in an independent validation cohort.ConclusionThe diagnosis penal based on the ML of the gut microbiome may be a favorable tool for the precise diagnosis and treatment of PIBD. A study of the relationship between disease status and the microbiome was an effective way to clarify the pathogenesis of PIBD.

Background: Several types of laboratory tests for COVID-19 have been established to date; however, the clinical significance of the serum SARS-CoV-2 nucleocapsid (N) antigen levels remains to be fully elucidated. In the present study, we attempted to elucidate the usefulness and clinical significance of the serum N antigen levels.Methods: We measured the serum N antigen levels in 391 serum samples collected from symptomatic patients with a confirmed diagnosis of COVID-19 and 96 serum samples collected from patients with non-COVID-19, using a fully automated chemiluminescence immunoassay analyzer.Results: Receiver operating characteristic analysis identified the optimal cutoff value of the serum N antigen level (cutoff index, based on Youden’s index) as 0.255, which yielded a sensitivity and specificity for the diagnosis of COVID-19 of 91.0 and 81.3%, respectively. The serum N antigen levels were significantly higher in the patient groups with moderate and severe COVID-19 than with mild disease. Moreover, a significant negative correlation was observed between the serum N antigen levels and the SARS-CoV-2 IgG antibody titers, especially in patients with severe COVID-19.Conclusion: Serum N antigen testing might be useful both for the diagnosis of COVID-19 and for obtaining a better understanding of the clinical features of the disease.

Background: Perturbation of energy metabolism exacerbates cardiac dysfunction, serving as a potential therapeutic target in congestive heart failure. Although circulating free fatty acids (FFAs) are linked to insulin resistance and risk of coronary heart disease, it still remains unclear whether circulating FFAs are associated with the prognosis of patients with acute heart failure (AHF).Methods: This single-center, observational cohort study enrolled 183 AHF patients (de novo heart failure or decompensated chronic heart failure) in the Second Affiliated Hospital, Zhejiang University School of Medicine. All-cause mortality and heart failure (HF) rehospitalization within 1 year after discharge were investigated. Serum FFAs were modeled as quartiles as well as a continuous variable (per SD of FFAs). The restricted cubic splines and cox proportional hazards models were applied to evaluate the association between the serum FFAs level and all-cause mortality or HF rehospitalization.Results: During a 1-year follow-up, a total of 71 (38.8%) patients had all-cause mortality or HF rehospitalization. The levels of serum FFAs positively contributed to the risk of death or HF rehospitalization, which was not associated with the status of insulin resistance. When modeled with restricted cubic splines, the serum FFAs increased linearly for the incidence of death or HF rehospitalization. In a multivariable analysis adjusting for sex, age, body-mass index, coronary artery disease, diabetes mellitus, hypertension, left ventricular ejection fraction and N-terminal pro-brain natriuretic peptid, each SD (303.07 μmol/L) higher FFAs were associated with 26% higher risk of death or HF rehospitalization (95% confidence interval, 2–55%). Each increasing quartile of FFAs was associated with differentially elevated hazard ratios for death or HF rehospitalization of 1 (reference), 1.71 (95% confidence interval, [0.81, 3.62]), 1.41 (95% confidence interval, [0.64, 3.09]), and 3.18 (95% confidence interval, [1.53, 6.63]), respectively.Conclusion: Serum FFA levels at admission among patients with AHF were associated with an increased risk of adverse outcomes. Additional studies are needed to determine the causal-effect relationship between FFAs and acute cardiac dysfunction and whether FFAs could be a potential target for AHF management.

Background: Transcatheter aortic valve implantation (TAVI) has achieved satisfactory outcomes in the selected patients with bicuspid aortic valve (BAV), predominately type 1 BAV (~90%). However, there are few reports about the safety and efficacy of TAVI in type 0 BAV. Therefore, in the current study, we aimed to compare procedural and 30-day outcomes after TAVI between type 0 and type 1 BAV.Methods: Studies comparing the outcomes of TAVI in Sievers type 0 vs. type 1 BAV were retrieved from PubMed, EMBASE, Cochrane Library, and Web of Science from inception to May 2021. The data were extracted regarding the study characteristics and outcomes. The odds ratios (ORs) with 95% CIs were pooled for procedural and 30-day outcomes.Results: Six observational studies were included with determined type 0 BAV in 226 patients and type 1 BAV in 902 patients. The patients with type 0 BAV were slightly younger, had larger supra-annular structure, and more frequently implanted self-expanding prosthesis compared with type 1 BAV. In the pooled analyses, the patients with type 0 BAV had a similar incidence of procedural death (OR = 2.6, 95% CI 0.7–10.3), device success (OR = 0.6; 95% CI 0.3–1.3), and ≥ mild (OR = 0.8; 95% CI 0.4–1.6) or moderate (OR = 0.9, 95% CI 0.4–1.8) paravalvular leak, whereas significantly higher mean aortic gradient (mean difference = 1.4 mmHg, 95% CI 0.03–2.7) and increased coronary compromise risk (OR = 7.2; 95% CI 1.5–34.9), compared with type 1 BAV. Meanwhile, the incidence of death (OR = 1.2; 95% CI 0.5–3.1), stroke (OR = 0.5; 95% CI 0.1–2.4), and new pacemaker (OR = 0.6; 95% CI 0.2–2.2) at 30 days were not significantly different between the BAV morphologies (p > 0.05). The treatment effect heterogeneity across the studies for the above outcomes were low.Conclusions: The patients with type 0 BAV appear to have similar short-term outcomes after TAVI compared with type 1 BAV. Whereas, TAVI for type 0 BAV aortic stenosis might lead to an elevated coronary obstruction risk and suboptimal aortic valvular hemodynamics.

The subsea production system is presently widely adopted in deepwater oil and gas development. The throttling valve is the key piece of equipment of the subsea production system, controlling the safety of oil and gas production. There are many valves with serious throttling effect in the subsea X-tree, so the hydrate formation risk is relatively high. In this work, a 3D cage-sleeve throttling valve model was established by the numerical simulation method. The temperature and pressure field of the subsea throttling valve was accurately characterized under different prefilling pressure, throttling valve opening degree, and fluid production. During the well startup period, the temperature of the subsea pipeline is low. If the pressure difference between the two ends of the pipeline is large, the throttling effect is obvious, and low temperature will lead to hydrate formation and affect the choice of throttling valve material. Based on the analysis of simulation results, this study recommends that the prefilling pressure of the subsea pipe is 7–8 MPa, which can effectively reduce the influence of the throttling effect so that the downstream temperature can be kept above 0°C. At the same time, in regular production, a suitable choke size is opened to match the production, preventing the serious throttling effect from a small choke size. According to the API temperature rating table, the negative impact of local low temperature caused by the throttling effect on the temperature resistance of the pipe was considered, and the appropriate subsea X-tree manifold material was selected to ensure production safety. The hydrate phase equilibrium curve is used to estimate the hydrate formation risk under thermodynamic conditions. Hydrate inhibitors are injected to ensure downstream flow safety.

We present a general theory for the coherence of Fano lasers based on a bound state in the continuum. We find that such lasers enable an orders-of-magnitude reduction in the quantum-limited linewidth and, by introducing mirror symmetry breaking, the linewidth can be further reduced. In contrast to ordinary macroscopic lasers, though, the linewidth may rebroaden due to optical nonlinearities enhanced by the strong light localization. This leads to the identification of optimal material systems. We also show that the coherence of this new type of microscopic laser can be understood intuitively using a simple, effective potential model. Based on this model, we examine the laser stability and deduce the dependence of the laser linewidth on the general Fano line shape. Our model facilitates the incorporation of other degrees of design freedom and can be applied to a general class of lasers with strongly dispersive mirrors.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. The AKT pathway is often activated in HCC cases, and a longer exposure to tyrosine kinase inhibitors such as sorafenib may lead to over-activation of the AKT pathway, leading to HCC resistance. Here, we studied the efficacy of a new generation of allosteric AKT inhibitor, vevorisertib, alone or in combination with sorafenib. To identify specific adverse effects related to the background of cirrhosis, we used a diethylnitrosamine (DEN)-induced cirrhotic rat model. Vevorisertib was tested in vitro on Hep3B, HepG2, HuH7 and PLC/PRF cell lines. Rats were treated weekly with intra-peritoneal injections of DEN for 14 weeks to obtain cirrhosis with fully developed HCC. After that, rats were randomized into four groups (n = 7/group): control, sorafenib, vevorisertib and the combination of vevorisertib + sorafenib, and treated for 6 weeks. Tumor progression was followed by MRI. We demonstrated that the vevorisertib is a highly potent treatment, blocking the phosphorylation of AKT. The tumor progression in the rat liver was significantly reduced by treatment with vevorisertib + sorafenib (49.4%) compared to the control group (158.8%, p < 0.0001). Tumor size, tumor number and tumor cell proliferation were significantly reduced in both the vevorisertib group and vevorisertib + sorafenib groups compared to the control group. Sirius red staining showed an improvement in liver fibrosis by vevorisertib and the combination treatment. Moreover, vevorisertib + sorafenib treatment was associated with a normalization in the liver vasculature. Altogether, vevorisertib as a single agent and its combination with sorafenib exerted a strong suppression of tumor progression and improved liver fibrosis. Thus, results provide a rationale for testing vevorisertib in clinical settings and confirm the importance of targeting AKT in HCC.

In this paper, the experimental modes of a large-scale photoelectric theodolite tracking frame are presented. On the basis of the experimental data and the gradient-less optimization approach, the modeling strategy and the parameterized equivalent dynamic finite element model are presented. Shafting, three-point leveling units, and other components are reasonably simplified during the modeling process. Influence factors such as contact stiffness are introduced as dynamic parameters in the model. The optimized parametric model obtained demonstrates that the linearization modeling strategy represents the dynamic response characteristics of this type of structure accurately. The maximum relative error of the first four-order natural frequencies between numerical simulation and experimental data is 4.45% when the consistency of mode shapes is taken into account. The research results in this paper can provide engineering guidance for the dynamic stiffness optimization design of the large-scale photoelectric theodolite tracking frame.

Craniomaxillofacial bone defects are characterized by an irregular shape, bacterial and inflammatory environment, aesthetic requirements, and the need for the functional recovery of oral–maxillofacial areas. Conventional clinical treatments are currently unable to achieve high-quality craniomaxillofacial bone regeneration. Hydrogels are a class of multifunctional platforms made of polymers cross-linked with high water content, good biocompatibility, and adjustable physicochemical properties for the intelligent delivery of goods. These characteristics make hydrogel systems a bright prospect for clinical applications in craniomaxillofacial bone. In this review, we briefly demonstrate the properties of hydrogel systems that can come into effect in the field of bone regeneration. In addition, we summarize the hydrogel systems that have been developed for craniomaxillofacial bone regeneration in recent years. Finally, we also discuss the prospects in the field of craniomaxillofacial bone tissue engineering; these discussions can serve as an inspiration for future hydrogel design.

Single crystals of Tb3+ single-doped and Tb3+/Pr3+ co-doped CaYAlO4 were produced by the Czochralski method. The room-temperature polarized absorption spectra, emission spectra, and decay curves were recorded and analyzed in detail. The absorption cross-section around 487 nm was found to be 1.53 × 10−22 cm2 for the π polarization in the Tb3+:CaYAlO4 crystal and increased to 5.23 × 10−22 cm2 in the Tb3+/Pr3+:CaYAlO4 crystal. The spectroscopic parameters were calculated through the Judd–Ofelt theory. For the Tb3+:CaYAlO4 crystal, the emission bands of green light at 546 nm and yellow light at 587 nm had fluorescence branching ratios of 64.7% and 6.65% with cross-sections of 8.82 × 10−22 cm2 (σ-polarization) and 0.44 × 10−22 cm2 (π-polarization), respectively. The decay lifetimes of 5D4 multiplets were measured to be 1.41 ms and 1.1 ms for Tb3+:CaYAlO4 and Tb3+/Pr3+:CaYAlO4 crystals, respectively. The energy transfer mechanisms of Tb3+ and Pr3+ and their emission spectral intensities at different temperatures were analyzed. As the temperature increased, the luminescence intensity of the Tb3+:CaYAlO4 and Tb3+/Pr3+:CaYAlO4 crystals decreased almost linearly with the CIE coordinate variation, from (0.370, 0.621) to (0.343, 0.636) and from (0.345, 0.638) to (0.246, 0.698), respectively. The results indicate the potential of Tb3+:CaYAlO4 and Tb3+/Pr3+:CaYAlO4 crystals as visible laser materials with a wide temperature range.

Concentric circular antenna arrays (CCAAs) can obtain better performance than other antenna arrays. However, high overhead and excessive sidelobes still make its application difficult. In this paper, we consider the sparse synthesis optimization of CCAAs. Specifically, we aim to turn off a specific number of antennas while reducing the sidelobe of CCAAs. First, we formulate an optimization problem and present the solution space. Then, we propose a novel evolutionary method for solving the optimization problem. Our proposed method introduces hybrid solution initialization, hybrid crossover method, and hybrid update methods. Simulation results show the effectiveness of the proposed algorithm and the proposed improvement factors.

Due to the increasing requirements for the imaging quality of optical systems, the design method for optical–mechanical structures has become a research hotspot in recent decades. To improve the imaging performance of the reflective system, it is often necessary to increase the aperture of the mirror. To meet the imaging quality and lightweightedness requirements of the mirror, the topology optimization method aiming at the minimization of wavefront aberration is proposed. The optical–mechanical coupling relationship is established by ray tracing of the deformed mirror surface fitted by orthogonal bases. The topology optimization model is established by the solid isotropic material with penalization model (SIMP). Additionally, the adjoint method is used to analyze the sensitivity of the objective and the constraints. To illustrate the rationality and effectiveness of the method, the mirrors of the Cassegrain system have been optimized under the action of gravity with the objective of the weighted sum of squares of wavefront aberration coefficients under the constraints of the mass of the design domain, the rigid body displacement of the mirror surface, and the residual of deformation fitting. The results show that the proposed method can effectively improve imaging performance under the condition of satisfying the constraints. In addition, the optimization method with wavefront aberration as the objective is a concrete application of the idea of opto-mechanical integration, which can improve optical performance more directly and effectively.

Soft robots, intelligent structures built up of smart soft materials, are capable of being programmed to perform delicate work. Recently, plenty of biomimetic soft robots with functionalities of grasping, sensing, searching, and transporting have been exploited by emulating activities of living creatures adapting to ecological environments. However, mass production of biomimetic soft robots has remained a grand challenge while maintaining stable pre‐engineered functionalities under distinct circumstances, which significantly constrains their practical applications. To this end, a facile and scalable approach that can be utilized for mass‐producing sandwich‐structured photoresponsive polyimide (PI)/Au/low‐density polyethylene (LDPE) nanocomposite films is reported. Attributed to the remote and precise‐driven mode, reversible and stable actuation behavior, and the ultrarobust mechanical properties of the sandwich‐structured PI/Au/LDPE nanocomposite films, it was possible to devise a variety of photoresponsive biomimetic soft robots such as artificial flytrap, directionally moveable caterpillar‐inspired walker, and dolphin‐like cruisable and loadable swimmer via simply tailoring them into predesigned geometries.

Summary: Garnet-type solid electrolytes have attracted extensive attention for solid-state lithium (Li) batteries. However, the high processing temperature of up to 1,200°C limits large-scale production. Here, we report a simple approach to reduce the sintering temperature by using a conformal nanoscale amorphous alumina coating. The ceramic sintered at 980°C shows a high room temperature ionic conductivity of 0.13 mS cm−1. It reveals that the second phases segregated at grain boundaries are ionically conductive but electronically blocking, which can block electronic conduction and improve mechanical property. The Li symmetry cells indicate a long-term 2,500-cycle life and a high critical current density of 0.52 mA cm−2. The garnet electrolyte enables the high-voltage cells using Li1.2Ni0.2Mn0.6O2 to deliver a high specific capacity of 248 mAh g−1 at 0.05 C. This work provides a new clue for lowering sintering temperature for garnet electrolytes, which can extend to other ceramics toward practical applications.

Mast cells (MCs) play important roles in multiple pathologies, including fibrosis; however, their behaviors in different extracellular matrix (ECM) environments have not been fully elucidated. Accordingly, in this study, the migration of MCs on substrates with different stiffnesses was investigated using time-lapse video microscopy. Our results showed that MCs could appear in round, spindle, and star-like shapes; spindle-shaped cells accounted for 80–90 % of the total observed cells. The migration speed of round cells was significantly lower than that of cells with other shapes. Interestingly, spindle-shaped MCs migrated in a jiggling and wiggling motion between protrusions. The persistence index of MC migration was slightly higher on stiffer substrates. Moreover, we found that there was an intermediate optimal stiffness at which the migration efficiency was the highest. These findings may help to improve our understanding of MC-induced pathologies and the roles of MC migration in the immune system.

An automatic colorization algorithm can convert a grayscale image to a colorful image using regression loss functions or classification loss functions. However, the regression loss function leads to brown results, while the classification loss function leads to the problem of color overflow and the computation of the color categories and balance weights of the ground truth required for the weighted classification loss is too large. In this paper, we propose a new method to compute color categories and balance the weights of color images. In this paper, we propose a new method to compute color categories and balance weights of color images. Furthermore, we propose a U-Net-based colorization network. First, we propose a category conversion module and a category balance module to obtain the color categories and to balance weights, which dramatically reduces the training time. Second, we construct a classification subnetwork to constrain the colorization network with category loss, which improves the colorization accuracy and saturation. Finally, we introduce an asymmetric feature fusion (AFF) module to fuse the multiscale features, which effectively prevents color overflow and improves the colorization effect. The experiments show that our colorization network has peak signal-to-noise ratio (PSNR) and structure similarity index measure (SSIM) metrics of 25.8803 and 0.9368, respectively, for the ImageNet dataset. As compared with existing algorithms, our algorithm produces colorful images with vivid colors, no significant color overflow, and higher saturation.

The synergistic effect of electrostatically enhanced fibrous filtration originates from the charging characteristics of aerosol particles and electret fibers in an electric field. Two electrostatically enhanced fibrous filter systems are designed in this study to investigate the mechanism of the effects of the charging characteristics of oily aerosol on the filtration efficiency. We investigate the charging characteristics and their effects on the filtration efficiency of dioctyl-phthalate (DOP) aerosol particles of various sizes by setting different filter systems and electric field intensities. The experimental results show that the charge of DOP particles increases with the strength of the electric field, and the average charge increases with the particle size. The maximum charge of DOP particles reaches 4760 eC/P, and the filtration efficiency of the coupled system improves when DOP particles are amply charged. For 0.25 μm DOP particles as the most penetrating particle size, the system had good long-term stability, and the filtration efficiency is approximately 72% higher than that of the fiber acting alone. Meanwhile, the problem of oily aerosol deposition reducing the electret filtration efficiency is solved, providing a basis for long-term filtration and oily aerosol purification by electret fiber.

The suspension system is a significant part of a vehicle because it transmits the torque and force between the wheels and the frame, meeting the requirements of ride comfort. In this paper, a novel interconnected air suspension was introduced and a cooperative control between interconnected mode activation (IMA) and outsourced mode activation (OMA) was designed. To improve ride comfort in a bus at a minimal energy consumption, this cooperative control based on model predictive control (MPC) for computing the best force and the rule was defined to distribute the best suspension force generated by IMA and OMA. The simulation and experimental results showed that the proposed control strategy significantly improved ride comfort in different conditions. Compared with traditional control in the test vehicle, the RMS of the front-left sprung mass and unsprung vertical acceleration decreased by 24.2% and 14.5%, respectively, under a straight condition; the RMS of the sprung (unsprung) mass vertical acceleration reduced by 22.38% and 15.43%, respectively, under a bump condition.

Highly accurate measurements of infrared systems cannot be achieved without precise radiometric calibrations. In order to correctly interpret and process infrared images and monitor the performance of infrared cameras, their radiometric calibration is also required periodically. In this paper, an equivalent calibration method is proposed based on an internal blackbody baffle. It is used for the replacement of a large surface-source blackbody covering the aperture for the field calibration of large-aperture equipment. Subsequently, the expressions of the equivalent calibration conversion function (ECCF) are derived based on the grayscale response of the camera and the calibration models of the two methods, and experimental measurements and fits are performed using a cooled mid-wave infrared camera. The results show that the measured functional form is consistent with the physical meaning. Moreover, in the target imaging experiments, the results of the inversion using the equivalent calibration conversion function and the results of the direct calibration of the external blackbody are largely consistent with the average error of 0.198% between the two, and the maximum error is within 1%. The maximum error between the inversion result of radiation brightness and the actual value of the target is 6.29%, and the accuracy fully meets the radiometric measurement requirements.

High-dose methotrexate (HD-MTX) is widely used in pediatric acute lymphoblastic leukemia (ALL) treatment regimens. In this study, we aimed to develop a population pharmacokinetic (PK) model of HD-MTX in Chinese pediatric patients with ALL for designing personalized dosage regimens. In total, 4,517 MTX serum concentration data for 311 pediatric patients with ALL, aged 0.75–15.2 years and under HD-MTX treatment, were retrospectively collected at a tertiary Children’s Hospital in China. The non-linear mixed-effect model was used to establish the population PK model, using NONMEM software. The potential covariate effects of age, body weight, and biochemical measurements (renal and liver function) on MTX PK disposition were investigated. The model was then evaluated using goodness-of-fit, visual predictive check. MTX PK disposition was described using a three-compartment model reasonable well. Body weight, implemented as a fixed allometric function on all clearance and volume of distribution parameters, showed a substantial improvement in model fit. The final population model demonstrated that the MTX clearance estimate in a typical child with body weight of 19 kg was 6.9 L/h and the central distribution of volume estimate was 20.7 L. The serum creatinine significantly affected the MTX clearance, with a 0.97% decrease in clearance per 1 μmol/L of serum creatinine. Other covariates (e.g., age, sex, bilirubin, albumin, aspartate transaminase, concomitant medication) did not significantly affect PK properties of MTX. The proposed population PK model could describe the MTX concentration data in Chinese pediatric patients with ALL. This population PK model combined with a maximum a posteriori Bayesian approach could be used to estimate individual PK parameters, and optimize personalized MTX therapy in target patients, thus aiming to reduce toxicity and improve treatment outcomes.

At present, lots of studies have tried to apply machine learning to different electroencephalography (EEG) measures for diagnosing schizophrenia (SZ) patients. However, most EEG measures previously used are either a univariate measure or a single type of brain connectivity, which may not fully capture the abnormal brain changes of SZ patients. In this paper, event-related potentials were collected from 45 SZ patients and 30 healthy controls (HCs) during a learning task, and then a combination of partial directed coherence (PDC) effective and phase lag index (PLI) functional connectivity were used as features to train a support vector machine classifier with leave-one-out cross-validation for classification of SZ from HCs. Our results indicated that an excellent classification performance (accuracy = 95.16%, specificity = 94.44%, and sensitivity = 96.15%) was obtained when the combination of functional and effective connectivity features was used, and the corresponding optimal feature number was 15, which included 12 PDC and three PLI connectivity features. The selected effective connectivity features were mainly located between the frontal/temporal/central and visual/parietal lobes, and the selected functional connectivity features were mainly located between the frontal/temporal and visual cortexes of the right hemisphere. In addition, most of the selected effective connectivity abnormally enhanced in SZ patients compared with HCs, whereas all the selected functional connectivity features decreased in SZ patients. The above results showed that our proposed method has great potential to become a tool for the auxiliary diagnosis of SZ.

Postpartum depression (PPD) is a serious health issue that can affect about 15% of the female population within after giving birth. It often conveys significant negative consequences to the offsprings. The symptoms and risk factors are somewhat similar to those found in non-postpartum depression. The main difference resides in the fact that PPD is triggered by postpartum specific factors, including especially biological changes in the hormone levels. Patients are usually diagnosed using a questionnaire onsite or in a clinic. Treatment of PPD often involves psychotherapy and antidepressant medications. In recent years, there have been more researches on the identification of biological markers for PPD. In this review, we will focus on the current research status of PPD, with an emphasis on the recent progress made on the identification of PPD biomarkers.

Non-Hodgkin lymphoma (NHL) are a diverse group of hematological malignancies comprised of over 60 subtypes. These subtypes range from indolent to aggressive. The PI3K/Akt/mTOR pathway has been shown to contribute to cell survival and proliferation and is constitutively active in most NHL. MK-7075 (miransertib) and MK-4440 are small molecules that effectively inhibit Akt and have entered clinical development. Using in vitro and in vivo models of NHL, we explored targeting the kinase Akt with miransertib and MK-4440 alone or in combination with the mTORC1 inhibitor, rapamycin (sirolimus). Both Akt inhibitors inhibited the pathway and NHL proliferation in a subtype-dependent manner. However, these compounds had a minimal effect on the viability of primary B-cells. Importantly, the combination of miransertib and sirolimus synergistically reduced cell proliferation in NHL, including in one indolent subtype, e.g., follicular lymphoma (FL), and two aggressive subtypes, e.g., diffuse large B-cell lymphoma (DLBCL) and primary effusion lymphoma (PEL). To establish in vivo efficacy, we used several xenograft models of FL, DLBCL, and PEL. The results obtained in vivo were consistent with the in vitro studies. The FL xenograft was highly sensitive to the inhibition of Akt alone; however, the tumor burden of PEL xenografts was only significantly reduced when both Akt and mTORC1 were targeted. These data suggest that targeting the PI3K/Akt/mTOR pathway with Akt inhibitors such as miransertib in combination with mTOR inhibitors serves as a broadly applicable therapeutic in NHL.

Radiotherapy is one of the standard treatments for cervical cancer and head and neck cancer. However, the clinical efficacy of this treatment is limited by radioresistance. The discovery of effective prognostic biomarkers and the identification of new therapeutic targets have helped to overcome the problem of radioresistance. In this study, we show that in the context of PIK3CA mutation or amplification, high expression of fascin actin-bundling protein 1 (FSCN1) (using the median as the cut-off value) is associated with poor prognosis and radiotherapy response in cancer patients. Silencing FSCN1 enhances radiosensitivity and promotes apoptosis in cancer cells with PIK3CA alterations, and this process may be associated with the downregulation of YWHAZ. These results reveal that FSCN1 may be a key regulator of radioresistance and could be a potential target for improving radiotherapy efficacy in cervical cancer and head and neck cancer patients with PIK3CA alterations.

Background: The purpose of this meta-analysis was to evaluate the controversy of angiotensin-converting enzyme inhibitor (ACEI) in combination with angiotensin-receptor blocker (ARB) in the treatment of chronic kidney disease (CKD) based on dose.Methods: PubMed, EMBASE, and Cochrane Library were searched to identify randomized controlled trials (RCTs) from inception to March 2020. The random effects model was used to calculate the effect sizes. Potential sources of heterogeneity were detected using sensitivity analysis and meta-regression.Results: This meta-analysis of 53 RCTs with 6,375 patients demonstrated that in patients with CKD, ACEI in combination with ARB was superior to low-dose ACEI or ARB in reducing urine albumin excretion (SMD, −0.43; 95% CI, −0.67 to −0.19; p = 0.001), urine protein excretion (SMD, −0.22; 95% CI, −0.33 to −0.11; p < 0.001), and blood pressure (BP), including systolic BP (WMD, −2.89; 95% CI, −3.88 to −1.89; p < 0.001) and diastolic BP (WMD, −3.02; 95% CI, −4.46 to −1.58; p < 0.001). However, it was associated with decreased glomerular filtration rate (GFR) (SMD, −0.13; 95% CI, −0.24 to −0.02; p = 0.02) and increased rates of hyperkalemia (RR, 2.07; 95% CI, 1.55 to 2.76; p < 0.001) and hypotension (RR, 2.19; 95% CI, 1.35 to 3.54; p = 0.001). ACEI in combination with ARB was more effective than high-dose ACEI or ARB in reducing urine albumin excretion (SMD, −0.84; 95% CI, −1.26 to −0.43; p < 0.001) and urine protein excretion (SMD, −0.24; 95% CI, −0.39 to −0.09; p = 0.002), without decrease in GFR (SMD, 0.02; 95% CI, −0.12 to 0.15; p = 0.78) and increase in rate of hyperkalemia (RR, 0.94; 95% CI, 0.65 to 1.37; p = 0.76). Nonetheless, the combination did not decrease the BP and increased the rate of hypotension (RR, 3.95; 95% CI, 1.13 to 13.84; p = 0.03) compared with high-dose ACEI or ARB.Conclusion: ACEI in combination with ARB is superior in reducing urine albumin excretion and urine protein excretion. The combination is more effective than high-dose ACEI or ARB without decreasing GFR and increasing the incidence of hyperkalemia. Despite the risk of hypotension, ACEI in combination with ARB is a better choice for CKD patients who need to increase the dose of ACEI or ARB (PROSPERO CRD42020179398).

Background: Monoclonal antibodies that target the PD-1 receptor are emerging as promising therapeutic candidates for the treatment of biliary tract cancers (BTCs). The purpose of the current study was to assess the combination of the camrelizumab with chemotherapy as a first-line treatment for metastatic BTCs. Methods: We conducted a prospective single-arm pilot study of PD-1 antibody (camrelizumab 3 mg/kg d1, Q2 W or Q3 W) combined with different chemotherapy regimens as first-line treatment for BTCs. Efficacy endpoints were objective response rate (ORR), disease control rate (DCR), progression free survival (PFS), and overall survival (OS). Treatment-related adverse events (TRAEs) were also evaluated. Results: Fourteen patients with histologically confirmed BTCs were evaluated. The ORR was 14.3% (95% CI: 1.8 to 42.8) and the DCR was 64.3% (95%CI: 41.7 to 86.9). The median PFS was 6.5 months (95% CI: 3.8 to 9.2), and the 6- and 12-month PFS rates were 61.6% and 12.3%, respectively. The median OS was 9.9 months (95% CI: 7.6 to 12.2), and the 6-and 12-month OS rates were 74.5% and 26.6%, respectively. All patients displayed at least 1 TRAE., and Grade 3 or 4 TRAEs occurred in 6 (42.86%) patients. Conclusions: Camrelizumab combined with chemotherapy as first-line treatment for metastatic BTCs demonstrated acceptable safety and efficacy in our pilot study. These findings warrant prospective controlled clinical trials comparing combinations of camrelizumab and chemotherapy to standard regimens.

Abstract Protein arginine methyltransferase 5 (PRMT5) is the type II arginine methyltransferase that catalyzes the mono‐ and symmetrical dimethylation of protein substrates at the arginine residues. Emerging evidence reveals that PRMT5 is involved in the regulation of tumor cell proliferation and cancer development. However, the exact role of PRMT5 in human lung cancer cell proliferation and the underlying molecular mechanism remain largely elusive. Here, it is shown that PRMT5 promotes lung cancer cell proliferation through the Smad7‐STAT3 axis. Depletion or inhibition of PRMT5 dramatically dampens STAT3 activation and thus suppresses the proliferation of human lung cancer cells. Furthermore, depletion of Smad7 blocks PRMT5‐mediated STAT3 activation. Mechanistically, PRMT5 binds to and methylates Smad7 on Arg‐57, enhances Smad7 binding to IL‐6 co‐receptor gp130, and consequently ensures robust STAT3 activation. The findings position PRMT5 as a critical regulator of STAT3 activation, and suggest it as a potential therapeutic target for the treatment of human lung cancer.

Introduction: This study aimed to identify factors associated with individual emergency preparedness behaviors which play an important role in effective emergency response.Methods: Data were drawn from a cross-sectional survey conducted in China's Heilongjiang, Guangdong and Sichuan provinces in 2017. Questionnaires were administered through face-to-face interviews, and 2,506 were valid for data analyses. A structural equation model was established to test the direct and indirect effects of the relevant factors on individual emergency preparedness behaviors.Results: Low levels of emergency preparedness were found: 28% of respondents reported being fully/partly prepared. The attitudes of the respondents toward emergency preparedness had the strongest association with emergency preparedness behaviors, with a total effect of 0.483. This was followed by self-efficacy (0.305) and training/exercise (0.295). Risk perception had the weakest effect (0.045) on emergency preparedness behaviors.Discussion: Improving attitudes of the public as well as their ability to prepare for emergency events is important for effective emergency management.

The power of a compound is enhanced by the direct connection of nitrogen atoms, and its stability can be improved through conjugated structure. So novel high energy density materials N14 (1,6-dihydro-1,2,3,3a,4,5,5a,6,7,8,8a,9,10,10a-tetradecazapyrene) and N18 (1,2,2a,3,4,4a,5,6,6a,7,8,8a,9,10,10a,11,12a-octadecazacoronene) were designed, and their structures, detonation performance, and stabilities were calculated employing density functional theory (DFT). The detonation performance includes detonation pressure (P), detonation velocity (D), and heat of detonation (Q). Furthermore, the stability involves frontier molecular orbitals and impact sensitivity. Calculations reveal that they have an excellent power, detonation performance of N14 (P = 43.6 GPa, D = 10040 m s-1, Q = 2214 cal g-1) and N18 (P = 37.4 GPa, D = 9400 m s-1, Q = 2114 cal g-1) are comparable to CL-20. Besides, their impact sensitivities are slightly better than CL-20, therefore they are promising candidates in energetic materials.

Summary: Insulin-induced AKT activation is dependent on phosphoinositide 3-kinase and opposed by tumor suppressor phosphatase and tensin homolog (PTEN). Our previous study demonstrates that myosin 1b (MYO1B) mediates arginase-II-induced activation of mechanistic target of rapamycin complex 1 that is regulated by AKT. However, the role of MYO1B in AKT activation is unknown. Here we show that silencing MYO1B in mouse embryonic fibroblasts (MEF) inhibits insulin-induced nuclear but not cytoplasmic AKT activation accompanied by elevated nuclear PTEN level. Co-immunoprecipitation, co-immunostaining, and proximity ligation assay show an interaction of MYO1B and PTEN resulting in reduced nuclear PTEN. Moreover, the elevated nuclear PTEN upon silencing MYO1B promotes apoptosis of MEFs and melanoma B16F10 cells. Taken together, we demonstrate that MYO1B, by interacting with PTEN, prevents nuclear localization of PTEN contributing to nuclear AKT activation and suppression of cell apoptosis. This may present a therapeutic approach for cancer treatment such as melanoma. : Biochemistry; Biological Sciences; Cell Biology; Molecular Biology Subject Areas: Biochemistry, Biological Sciences, Cell Biology, Molecular Biology

The structure of monometallic decahedral multiply twinned nanoparticles (MTPs) has been extensively studied, whereas less is known about intermetallic MTPs, especially the mechanism of formation of multiply twinned structures, which remains to be understood. Here, by using aberration-corrected scanning transmission electron microscopy, a detailed structural study of AuCu decahedral intermetallic MTPs is presented. Surface segregation has been revealed on the atomic level and the multiply twinned structure was studied systematically. Significantly different from Au and Cu, the intermetallic AuCu MTP adopts a solid-angle deficiency of −13.35°, which represents an overlap instead of a gap (+7.35° gap for Au and Cu). By analysing and summarizing the differences and similarities among AuCu and other existing monometallic/intermetallic MTPs, the formation mechanism has been investigated from both energetic and geometric perspectives. Finally, a general framework for decahedral MTPs has been proposed and unknown MTPs could be predicted on this basis.

Abstract Background Multidrug resistance is a growing global public health threat with far more serious consequences than generally anticipated. In this study, we investigated the antibiotic resistance and genomic traits of a clinical strain of Escherichia coli LCT-EC001. Results LCT-EC001 was resistant to 16 kinds of widely used antibiotics, including fourth-generation cephalosporins and carbapenems. In total, up to 68 determinants associated with antibiotic resistance were identified, including 8 beta-lactamase genes (notably producing ESBLs and KPCs), 31 multidrug efflux system genes, 6 outer membrane transport system genes, 4 aminoglycoside-modifying enzyme genes, 10 two-component regulatory system genes, and 9 other enzyme or transcriptional regulator genes, covering nearly all known drug-resistance mechanisms in E. coli. More than half of the resistance genes were located close to mobile genetic elements, such as plasmids, transposons, genomics islands, and insertion sequences. Phylogenetic analysis revealed that this strain may have evolved from E. coli K-12 but is a completely new MLST type. Conclusions Antibiotic resistance was extremely severe in E. coli LCT-EC001, mainly due to mobile genetic elements that allowed the gain of a large quantity of resistance genes. The antibiotic resistance genes of E. coli LCT-EC001 can probably be transferred to other bacteria. To the best of our knowledge, this is the first report of a strain of E. coli which has such a large amount of antibiotic resistance genes. Apart from providing an E. coli reference genome with an extremely high multidrug-resistant background for future analyses, this work also offers a strategy for investigating the complement and characteristics of genes contributing to drug resistance at the whole-genome level.

Abstract Background Meta-analysis is a useful tool for combining evidence from multiple studies to estimate a pooled treatment effect. An extension of meta-analysis, network meta-analysis, is becoming more commonly used as a way to simultaneously compare multiple treatments in a single analysis. Despite the variety of approaches available for presenting fitted models, ascertaining an intuitive understanding of these models is often difficult. This is especially challenging in large networks with many different treatments. Here we propose two visualisation methods, so that network meta-analysis models can be more easily interpreted. Methods Our methods can be used irrespective of the statistical model or the estimation method used and are grounded in network analysis. We define three types of distance measures between the treatments that contribute to the network. These three distance measures are based on 1) the estimated treatment effects, 2) their standard errors and 3) the corresponding p-values. Then, by using a suitable threshold, we categorise some treatment pairs as being “close” (short distances). Treatments that are close are regarded as “connected” in the network analysis theory. Finally, we group the treatments into communities using standard methods for network analysis. We are then able to identify which parts of the network are estimated to have similar (or different) treatment efficacy and which parts of the network are better identified. We also propose a second method using parametric bootstrapping, where a heat map is used in the visualisation. We use the software R and provide the code used. Results We illustrate our new methods using a challenging dataset containing 22 treatments, and a previously fitted model for this data. Two communities of treatments that appear to have similar efficacy are identified. Furthermore using our methods we can identify parts of the network that are better (and less well) identified. Conclusions Our new visualisation approaches may be used by network meta-analysts to gain an intuitive understanding of the implications of their fitted models. Our visualisation methods may be used informally, to identify the most salient features of the fitted models that can then be reported, or more formally by presenting the new visualisation devices within published reports.

While it is known that spermatogonial stem cells (SSCs) initiate the production of male germ cells, the mechanisms of SSC self-renewal, proliferation, and differentiation remain poorly understood. We have previously identified Strawberry Notch 1 (SBNO1), a vertebrate strawberry notch family protein, in the proteome profile for mouse SSC maturation and differentiation, revealing SBNO1 is associated with neonatal testicular development. To explore further the location and function of SBNO1 in the testes, we performed Sbno1 gene knockdown in mice to study the effects of SBNO1 on neonatal testicular and SSC development. Our results revealed that SBNO1 is required for neonatal testicular and SSC development in mice. Particularly, in vitro Sbno1 gene knockdown with morpholino oligonucleotides caused a reduction of SSCs and inactivation of the noncanonical Wnt pathway, through Jun N-terminal kinases. Our study suggests SBNO1 maintains SSCs by promoting the noncanonical Wnt pathway.

Objective: To investigate the spectrum of diseases in female children and adolescents hospitalized for obstetric and gynecological conditions. Methods: This retrospective study included patients (age ≤19 years) admitted to the Obstetrics and Gynecology Hospital of Fudan University, Shanghai, between January 2003 and December 2017. Their medical records – age, principal diagnosis, and treatment – were reviewed and analyzed. Diagnoses were divided into eight disease classifications. Comparison between groups was analyzed with Student's t-test. Results: This study enrolled 4,628 inpatients. The number of inpatients increased each year, especially in the groups of gynecologic tumors, pregnancy-related conditions, and disorders of the breast. The mean age was 16.33 ± 2.42 years (range: 2–19 years). Of all the inpatients, 41.9% (n = 1,939) were hospitalized for gynecologic tumors, and 85.5% (n = 1,657) of the tumors were benign. Altogether, ovarian cysts (28.66%, n = 1,325) were the most common disease observed in this group. In addition, 32.9% (n = 1,524) of the inpatients were hospitalized for pregnancy, childbirth, and puerperium; within this group, 21.9% (n = 1,014) were hospitalized for artificial abortions. Conclusions: The efforts of all stakeholders toward the implementation of government policies to promote sexual and reproductive health among children and adolescents in China have been effective.

In the field of humidity sensors, a major challenge is how to improve the sensing performance of existing materials. Based on our previous work on Na0.5Bi0.5TiO3, a facile strategy of tuning the Bi content in the material was proposed to improve its sensing performance. Na0.5BixTiO3 (x = 0.3, 0.35, 0.4, 0.45) nanocomposites were synthesized by a hydrothermal method. Humidity sensing properties of these nanocomposites were investigated in the relative humidity range of 11% to 95%. Our results show that, compared to the sensor based on nominally pure sample (Na0.5Bi0.5TiO3), the sensor based on Na0.5Bi0.35TiO3 exhibits boosted sensing performance of excellent linear humidity response in the humidity range of 11–75% relative humidity, lower hysteresis value, and faster response/recovery time. The improvement of the sensing performance was argued to be the reason that the proper reduction in Bi content leads to a minimum value of oxygen-vacancy concentrations, thereby weakening the chemical adsorption but enhancing the physical adsorption. These results indicate that the proper underdose of the Bi content in Na0.5Bi0.5TiO3 can greatly boost the sensing performance.

Multiple upwelling systems develop in the Indian Ocean during the summer monsoon. The Sri Lanka dome (SLD), which occurs in the open ocean off the east coast of Sri Lanka from June to September, is distinct from those near the coast. The SLD is characterized by uplifted thermocline and increased chlorophyll concentration. Mechanisms of the upwelling and its biogeochemical response are not well understood. Here, we explored the dynamics of the chlorophyll and sea-to-air CO2 flux in the SLD using ocean color and altimetry remote sensing data, together with other reanalysis products. We found that the occurrence of high chlorophyll concentration and sea-to-air CO2 flux happens along the pathway of the southwest monsoon current (SMC). The annual cycle of chlorophyll in the SLD has a one-month lag relative to that in the southern coast of Sri Lanka. The positive wind stress curl that forms in the SLD during the summer does not fully explain the seasonal chlorophyll maximum. Transport of the SMC, eddy activity, and associated frontal processes also play an important role in regulating the variability in chlorophyll. In the SLD, upwelled subsurface water has excess dissolved inorganic carbon (DIC) relative to the conventional Redfield ratio between DIC and nutrients; thus, upwelling and sub-mesoscale processes determine this region to be a net carbon source to the atmosphere.