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Abstract Objective To explore the association between the Oxidative Balance Score (OBS), which represents the balance of multiple oxidative stress-related dietary and lifestyle exposures, and the risk of metabolic syndrome (MetS). Methods A population-based cross-sectional study design was adopted and 16,850 participants in NHANES database were included in the statistics analysis stage. The OBS was constructed by combining information from 20 a priori selected pro- and antioxidant factors. Weighted logistic regression and restricted cubic splines (RCS) were used to estimate the association between OBS and MetS. Results Participants in the highest OBS quartile, indicating low oxidative stress (OS) levels, exhibited a significantly lower risk of MetS (odds Ratio [OR] = 0.55, 95% confidence Interval [CI]: 0.47–0.64) compared to the lowest quartile. Specifically, higher OBS was inversely associated with abdominal obesity (OR = 0.61, 95% CI: 0.54–0.69), hypertension (OR = 0.69, 95% CI: 0.58–0.83), elevated triglycerides (OR = 0.68, 95% CI: 0.57–0.82), low high-density lipoprotein cholesterol (HDL-C) levels (OR = 0.60, 95% CI: 0.50–0.70) and fasting blood glucose (FBG) levels (OR = 0.74, 95% CI: 0.62–0.88). The observed inverse association between OBS and hypertension or FBG levels appeared to primarily influenced by BMI. The association between dietary OBS intervals and elevated FBG levels was not statistically significant in men, whereas the risk was lower by 25% in women. Conclusions A higher OBS, representing a balance of multiple oxidative stress-related dietary and lifestyle exposures, is associated with a lower risk of MetS. Therefore, adhering to an antioxidant diet and lifestyle may help prevent the occurrence of metabolic disorders.

Quercetin is a flavonol that is widely distributed in plants. Although quercetin has good antioxidant activity, the exact mechanism is still unclear in intestinal cell model. In this study, a 3D Caco-2 cell model was constructed. An oxidative damage model was then established. Compared with 2D cell models, 3D cell models are more similar to the in vivo microenvironment and more sensitive to external stimuli. Quercetin and its nanoliposomes significantly increased intracellular SOD, GSH-Px and CAT activity and the T-AOC, and reduced ROS, IL-8 and MDA levels to exert antioxidant effects (P

The epicenter of the 2017 Qinghai Zeku MS4.9 earthquake was located near the SN-striking Riyueshan fault, while the focal mechanism solutions and the dominant arrangement of seismic sequence are inconsistent with the Riyueshan fault. In this paper, we have discovered EW- and NW-trending faults near the epicenter, by methods of remote sensing interpretation and field investigation. These faults are western terminal structures of Xiahe fault, in which the EW-trending faults are north-dipping and associated with kinematics including both left-lateral and vertical slip. Meanwhile, we use double differential positioning to relocate seismic sequences of Zeku MS4.9 earthquake. Results show that seismic arrangements consist of two segments striking NW and EW. The seismic profile crossing EW-striking segment indicates a north-dipping fault plane. Well consistence is found between Xiahe fault and seismic arrangements of Zeku MS4.9 earthquake, which leads us to the speculation that the seismogenic fault of Zeku earthquake is Xiahe fault. From a regional perspective, the Xiahe fault might be one strand of dissipating faults in the western end of the West Qinling fault, and the Zeku MS4.9 earthquake represents tectonic activity of the western end of the West Qinling fault. Besides，the northwestward turn of fault striking and reverse slipping of Xiahe fault might also be attributed to the right-lateral shearing effects of Riyueshan fault. Results of this paper highlight the significance of improving active fault traces, especially for the secondary or pre-existing faults in a tectonic active area.

Deep transfer learning has been widely used to improve the versatility of models. In the problem of cross-domain fault diagnosis in rolling bearings, most models require that the given data have a similar distribution, which limits the diagnostic effect and generalization of the model. This paper proposes a deep reconstruction transfer convolutional neural network (DRTCNN), which satisfies the domain adaptability of the model under cross-domain conditions. Firstly, the model uses a deep reconstruction convolutional automatic encoder for feature extraction and data reconstruction. Through sharing parameters and unsupervised training, the structural information of target domain samples is effectively used to extract domain-invariant features. Secondly, a new subdomain alignment loss function is introduced to align the subdomain distribution of the source domain and the target domain, which can improve the classification accuracy by reducing the intra-class distance and increasing the inter-class distance. In addition, a label smoothing algorithm considering the credibility of the sample is introduced to train the model classifier to avoid the impact of wrong labels on the training process. Three datasets are used to verify the versatility of the model, and the results show that the model has a high accuracy and stability.

PurposeIn this study, we aim to further evaluate the accuracy of ultrasound tracking for intra-fraction pancreatic tumor motion during radiotherapy by a phantom-based study.MethodsTwelve patients with pancreatic cancer who were treated with stereotactic body radiation therapy were enrolled in this study. The displacement points of the respiratory cycle were acquired from 4DCT and transferred to a motion platform to mimic realistic breathing movements in our phantom study. An ultrasound abdominal phantom was placed and fixed in the motion platform. The ground truth of phantom movement was recorded by tracking an optical tracker attached to this phantom. One tumor inside the phantom was the tracking target. In the evaluation of the results, the monitoring results from the ultrasound system were compared with the phantom motion results from the infrared camera. Differences between infrared monitoring motion and ultrasound tracking motion were analyzed by calculating the root-mean-square error.ResultsThe 82.2% ultrasound tracking motion was within a 0.5 mm difference value between ultrasound tracking displacement and infrared monitoring motion. 0.7% ultrasound tracking failed to track accurately (a difference value > 2.5 mm). These differences between ultrasound tracking motion and infrared monitored motion do not correlate with respiratory displacements, respiratory velocity, or respiratory acceleration by linear regression analysis.ConclusionsThe highly accurate monitoring results of this phantom study prove that the ultrasound tracking system may be a potential method for real-time monitoring targets, allowing more accurate delivery of radiation doses.

To better understand and control the crystallization of different polymorphs, a comprehensive crystal structure analysis was conducted by using fluralaner as a model compound, and the thermodynamic stability, phase transformation, and selective nucleation mechanisms were studied. Various analytical techniques such as powder X-ray diffraction, thermal analysis, and FT-IR spectra were used to comprehensively characterize Form I, Form Ⅱ, and Form III of fluralaner, and it was found that there is structural similarity between Form I and Form III, which was further confirmed by single crystal X-ray diffraction. However, it was found that Form Ⅱ had unique molecular conformation and packing pattern. The lattice energy was calculated by Materials Studio 7.0 and the thermodynamic stability of three forms was explored by phase transformation experiments, which suggested that the order of thermodynamic stability was Form Ⅱ > Form I > Form III. The selective nucleation of Form I and Form III with similar structure was studied through FT-IR spectra and molecular dynamics simulations. The results indicated that the addition of n-hexane may hinder the solute–solute interaction in the solution, thus resulting in the nucleation of different polymorphs.

PurposeWe proposed a Haar feature-based method for tracking endoscopic ultrasound (EUS) probe in diagnostic computed tomography (CT) and Magnetic Resonance Imaging (MRI) scans for guiding hydrogel injection without external tracking hardware. This study aimed to assess the feasibility of implementing our method with phantom and patient images.Materials and MethodsOur methods included the pre-simulation section and Haar features extraction steps. Firstly, the simulated EUS set was generated based on anatomic information of interpolated CT/MRI images. Secondly, the efficient Haar features were extracted from simulated EUS images to create a Haar feature dictionary. The relative EUS probe position was estimated by searching the best matched Haar feature vector of the dictionary with Haar feature vector of target EUS images. The utilization of this method was validated using EUS phantom and patient CT/MRI images.ResultsIn the phantom experiment, we showed that our Haar feature-based EUS probe tracking method can find the best matched simulated EUS image from a simulated EUS dictionary which includes 123 simulated images. The errors of all four target points between the real EUS image and the best matched EUS images were within 1 mm. In the patient CT/MRI scans, the best matched simulated EUS image was selected by our method accurately, thereby confirming the probe location. However, when applying our method in MRI images, our method is not always robust due to the low image resolution.ConclusionsOur Haar feature-based method is capable to find the best matched simulated EUS image from the dictionary. We demonstrated the feasibility of our method for tracking EUS probe without external tracking hardware, thereby guiding the hydrogel injection between the head of the pancreas and duodenum.

Abstract Background Neuroblastoma is an embryonal malignancy of the autonomic nervous system and is the most common extracranial tumor of early childhood. However, neuroblastoma in adults is rare with an overall incidence of 1 in 10 million adults/year. Adults with neuroblastoma have a significantly worse prognosis than children with neuroblastoma. Case presentation In this case report we describe a 75-year-old Han Chinese woman with bilateral lower extremities weakness, numbness, and fatigue for 1 week. She initially presented as primary hyperaldosteronism with hypertension, persistent hypokalemia, and an elevated aldosterone/plasma renin activity ratio. An abdominal computed tomography scan with intravenously administered contrast showed a solid mass arising from her left adrenal gland. She underwent retroperitoneal laparoscopic surgery that allowed the resection of the mass. Microscopic and immunohistochemical staining, which were positive for synaptophysin, CD56, and vimentin, confirmed the diagnosis of adrenal neuroblastoma. Surgical resection of the tumor was done and no chemotherapy or radiation therapy was done postoperatively. She died from lung and brain metastases 22 months after surgical resection. Conclusion Adrenal neuroblastoma in elderly adults is a very rare disease with sparse data available in the literature. Early stage disease could be managed by surgical resection alone. However, the prognosis is significantly worse than that observed in pediatric patients. Further research focusing on tumor biology and therapy for this rare malignancy in adults may help to improve disease outcome.

Abstract Epidemiological studies have a clear definition of the risk factors for breast cancer. However, it is unknown whether the distribution of these factors differs among breast cancer subtypes. We conducted a hospital‐based case‐only study consisting of 8067 breast cancer patients basing on the Tianjin Cohort of Breast Cancer Cases. Major breast cancer subtypes including luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)‐enriched and basal‐like were defined by estrogen receptor, progesterone receptor, HER2, and Ki‐67 status. Variables including demographic characteristics, reproductive factors, lifestyle habits, imaging examination, and clinicopathologic data were collected for patients. Chi‐square test and one‐way analysis of variance were used to compare the distributions of variables among the four breast cancer subtypes. Multivariate logistic regression was used to estimate the odds ratios and associated 95% confidence intervals where luminal A patients served as the reference group. Overall, more commonality rather than heterogeneity on the distributions of factors was found between the four molecular subtypes of breast cancer. The proportion of overweight and obesity were lower in HER2‐enriched subtype. Women with age at menarche ≤13 years were more likely to be found in basal‐like subtype. Postmenopausal women were more frequent in HER2‐enriched and basal‐like subtypes. Women with benign breast disease and higher breast density were more common in HER2‐enriched subtype. Risk factor scoring showed that total risk scores were similar among the four subtypes. HER2‐enriched and basal‐like subtypes were more frequently diagnosed with large tumors. Calcification was more likely to be found in luminal B and HER2‐enriched subtypes, whereas less distributed in basal‐like subtype. Most of the breast cancer risk factors were similarly distributed among the four major breast cancer subtypes; commonality is predominant.

We employ a nonparametric distribution dynamics approach to examine the long-run trend of particulate matter (PM2.5) air pollution in China. Analysis of the data from 288 Chinese prefectural and above (PAA) level cities over the 2001–2019 period shows evidence of convergence in the estimated long-run distribution of air pollution, which is consistent with Environmental Kuznets Curve hypothesis (EKC). However, presence of strong persistence suggests that convergence process takes considerable time. Conditioning analysis shows that China’s environment policy since 2013 has been successful in driving the air pollution in several cities to converge to a lower level. Furthermore, we uncover a poverty-environment trap in the estimated long-run distribution. Our analysis highlights the need for targeted environmental policies in heterogeneous city clusters in China. Lessons learned from China’s experience can also be useful to policy makers in other developing countries.

The transient pulses caused by local faults of rolling bearings are an important measurement information for fault diagnosis. However, extracting transient pulses from complex nonstationary vibration signals with a large amount of background noise is challenging, especially in the early stage. To improve the anti-noise ability and detect incipient faults, a novel signal de-noising method based on enhanced time-frequency manifold (ETFM) and kurtosis-wavelet dictionary is proposed. First, to mine the high-dimensional features, the C-C method and Cao’s method are combined to determine the embedding dimension and delay time of phase space reconstruction. Second, the input parameters of the liner local tangent space arrangement (LLTSA) algorithm are determined by the grid search method based on Renyi entropy, and the dimension is reduced by manifold learning to obtain the ETFM with the highest time-frequency aggregation. Finally, a kurtosis-wavelet dictionary is constructed for selecting the best atom and eliminating the noise and reconstruct the defective signal. Actual simulations showed that the proposed method is more effective in noise suppression than traditional algorithms and that it can accurately reproduce the amplitude and phase information of the raw signal.

We investigate the two-photon fluorescence (TPF) of conjugated polymer (CP) microspheres with diameters up to tens of micrometers. Two polymers, emitting in either the violet or red, were first synthesized and characterized in terms of their one-photon fluorescence and three-dimensional internal microstructure. Under femtosecond infrared excitation, both types of microspheres showed a strong TPF, which was investigated by the excitation intensity dependence, emission spectroscopy, time-resolved luminescence, and photobleaching dynamics. While the violet-fluorescent microspheres performed similarly compared to dye-doped polystyrene counterparts emitting at a similar wavelength, the red-fluorescent microspheres showed a two-orders-of-magnitude stronger TPF. This excellent performance is attributed to enhanced hyperpolarizability associated with intermolecular interactions in the polymer solid, indicating a route toward designed CP microspheres that could outperform currently-available microparticles for sensing or imaging applications involving two-photon fluorescence.

The data-driven intelligent fault diagnosis method of rolling bearings has strict requirements regarding the number and balance of fault samples. However, in practical engineering application scenarios, mechanical equipment is usually in a normal state, and small and imbalanced (S & I) fault samples are common, which seriously reduces the accuracy and stability of the fault diagnosis model. To solve this problem, an auxiliary classifier generative adversarial network with spectral normalization (ACGAN-SN) is proposed in this paper. First, a generation module based on a deconvolution layer is built to generate false data from Gaussian noise. Second, to enhance the training stability of the model, the data label information is used to make label constraints on the generated fake data under the basic GAN framework. Spectral normalization constraints are imposed on the output of each layer of the neural network of the discriminator to realize the Lipschitz continuity condition so as to avoid vanishing or exploding gradients. Finally, based on the generated data and the original S & I dataset, seven kinds of bearing fault datasets are made, and the prediction results of the Bi-directional Long Short-Term Memory (BiLSTM) model is verified. The results show that the data generated by ACGAN-SN can significantly promote the performance of the fault diagnosis model under the S & I fault samples.

Abstract Background The purpose of this work is to benchmark RapidPlan against clinical plans for liver Intensity-modulated radiotherapy (IMRT) treatment of patients with special anatomical characteristics, and to investigate the prediction capability of the general model (Model-G) versus our specific model (Model-S). Methods A library consisting of 60 liver cancer patients with IMRT planning was used to set up two models (Model-S, Model-G), using the RapidPlan knowledge-based planning system. Model-S consisted of 30 patients with special anatomical characteristics where the distance from planning target volume (PTV) to the right kidney was less than three centimeters and Model-G was configurated using all 60 patients in this library. Knowledge-based IMRT plans were created for the evaluation group formed of 13 patients similar to those included in Model-S by Model-G, Model-S and manually (M), named RPG-plans, RPS-plans and M-plans, respectively. The differences in the dose-volume histograms (DVHs) were compared, not only between RP-plans and their respective M-plans, but also between RPG-plans and RPS-plans. Results For all 13 patients, RapidPlan could automatically produce clinically acceptable plans. Comparing RP-plans to M-plans, RP-plans improved V95% of PTV and had greater dose sparing in the right kidney. For the normal liver, RPG-plans delivered similar doses, while RPS-plans delivered a higher dose than M-plans. With respect to RapidPlan models, RPS-plans had better conformity index (CI) values and delivered lower doses to the right kidney V20Gy and maximizing point doses to spinal cord, while delivering higher doses to the normal liver. Conclusion The study shows that RapidPlan can create high-quality plans, and our specific model can improve the CI of PTV, resulting in more sparing of OAR in IMRT for individual liver cancer patients.

Abstract Background For cervical carcinoma cases, this study aimed to evaluate the quality of intensity-modulated radiation therapy (IMRT) plans optimized by biological constraints. Furthermore, a new integrated strategy in biological planning module was proposed and verified. Methods Twenty patients of advanced stage cervical carcinoma were enrolled in this study. For each patient, dose volume optimization (DVO), biological model optimization (BMO) and integrated strategy optimization (ISO) plans were created using same treatment parameters. Different biological models were also used for organ at risk (OAR) in BMO plans, which include the LKB and Poisson models. Next, BMO plans were compared with their corresponding DVO plans, in order to evaluate BMO plan quality. ISO plans were also compared with DVO and BMO plans, in order to verify the performance of the integrated strategy. Results BMO plans produced slightly inhomogeneity and less coverage of planning target volume (PTV) (V95=96.79, HI = 0.10: p

Stimulated emission depletion nanoscopy and its derivatives based on saturation induced competition effects have become an indispensable tool for studying cellular events and their dynamics in living conditions. The successful implementation of these techniques heavily relies on the competition between excitation induced spontaneous emission and stimulated emission from fluorescent dyes. The use of two laser beams at different wavelengths perplexes the optical system and the high intensity saturation beam inevitably introduces detrimental photobleaching effects. Harnessing the emerging saturation scattering of plasmonic nanoparticles, here, we demonstrate a novel fluorescence-free single-wavelength super-resolution imaging technique using gold nanoparticles. A lateral resolution of 101.2 nm (

Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) has proven to be downregulated in podocytes challenged with high glucose (HG), and knockout of PTEN in podocytes aggravated the progression of diabetic kidney disease (DKD). However, whether podocyte-specific knockin of PTEN protects the kidney against hyperglycemia in vivo remains unknown. The inducible podocytespecific PTEN knockin (PPKI) mice were generated by crossing newly created transgenic loxP-stop-loxP-PTEN mice with podociniCreERT2 mice. Diabetes mellitus was induced in mice by intraperitoneal injection of streptozotocin at a dose of 150 mg/kg. In vitro, small interfering RNA and adenovirus interference were used to observe the role of PTEN in HG-treated podocytes. Our data demonstrated that PTEN was markedly reduced in the podocytes of patients with DKD and focal segmental glomerulosclerosis, as well as in those of db/db mice. Interestingly, podocyte-specific knockin of PTEN significantly alleviated albuminuria, mesangial matrix expansion, effacement of podocyte foot processes, and incrassation of glomerular basement membrane in diabetic PPKI mice compared with wild-type diabetic mice, whereas no alteration was observed in the level of blood glucose. The potential renal protection of overexpressed PTEN in podocytes was partly attributed with an improvement in autophagy and motility and the inhibition of apoptosis. Our results showed that podocyte-specific knockin of PTEN protected the kidney against hyperglycemia in vivo, suggesting that targeting PTEN might be a novel and promising therapeutic strategy against DKD. [ABSTRACT FROM AUTHOR]