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Abstract Antibacterial bone cements (ABCs), such as antibiotic-loaded bone cements (ALBCs), have been widely utilized in clinical treatments. Currently, bone cements loaded with vancomycin, gentamicin, tobramycin, or clindamycin are approved by the US Food and Drug Administration. However, traditional ALBCs exhibit drawbacks like burst release and bacterial resistance. Therefore, there is a demand for the development of antibacterial bone cements containing novel agents to address these defects. In this review, we provide an overview and prospect of the new antibacterial agents that can be used or have the potential to be applied in bone cement, including metallic antibacterial agents, pH-switchable antibacterial agents, cationic polymers, N-halamines, non-leaching acrylic monomers, antimicrobial peptides and enzymes. Additionally, we have conducted a preliminary assessment of the feasibility of bone cement containing N-halamine, which has demonstrated good antibacterial activities. The conclusion of this review is that the research and utilization of bone cement containing novel antibacterial agents contribute to addressing the limitations of ALBCs. Therefore, it is necessary to continue expanding the research and use of bone cement incorporating novel antibacterial agents. This review offers a novel perspectives for designing ABCs and treating bone infections. Graphical abstract

Abstract Background Different approach ultrasound-guided superior laryngeal nerve block was used to aid awake intubation, but little is known which approach was superior. We aimed to compare the parasagittal and transverse approaches for ultrasound-guided superior laryngeal nerve block in adult patients undergoing awake intubation. Methods Fifty patients with awake orotracheal intubation were randomized to receive either a parasagittal or transverse ultrasound-guided superior laryngeal nerve block. The primary outcome was patient’s quality of airway anesthesia grade during insertion of the tube into the trachea. The patients’ tube tolerance score after intubation, total procedure time, mean arterial pressure, heart rate, Ramsay sedation score at each time point, incidence of sore throat both 1 h and 24 h after extubation, and hoarseness before intubation, 1 h and 24 h after extubation were documented. Results Patients’ quality of airway anesthesia was significantly better in the parasagittal group than in the transverse group (median grade[IQR], 0 [0–1] vs. 1 [0–1], P = 0.036). Patients in the parasagittal approach group had better tube tolerance scores (median score [IQR],1[1–1] vs. 1 [1–1.5], P = 0.042) and shorter total procedure time (median time [IQR], 113 s [98.5–125.5] vs. 188 s [149.5–260], P

Abstract Purpose To study the effect of miR-150-5p on the osteogenic differentiation of bone marrow-derived mesenchymal stem cells (BMSCs), and further explore the relationship between its regulatory mechanism and irisin. Methods We isolated mouse BMSCs, and induced osteogenic differentiation by osteogenic induction medium. Using qPCR to detect the expression of osteogenic differentiation-related genes, western blot to detect the expression of osteogenic differentiation-related proteins, and luciferase reporter system to verify that FNDC5 is the target of miR-150-5p. Irisin intraperitoneal injection to treat osteoporosis in mice constructed by subcutaneous injection of dexamethasone. Results Up-regulation of miR-150-5p inhibited the proliferation of BMSCs, and decreased the content of osteocalcin, ALP activity, calcium deposition, the expression of osteogenic differentiation genes (Runx2, OSX, OCN, OPN, ALP and BMP2) and protein (BMP2, OCN, and Runx2). And down-regulation of miR-150-5p plays the opposite role of up-regulation of miR-150-5p on osteogenic differentiation of BMSCs. Results of luciferase reporter gene assay showed that FNDC5 gene was the target gene of miR-150-5p, and miR-150-5p inhibited the expression of FNDC5 in mouse BMSCs. The expression of osteogenic differentiation genes and protein, the content of osteocalcin, ALP activity and calcium deposition in BMSCs co-overexpressed by miR-150-5p and FNDC5 was significantly higher than that of miR-150-5p overexpressed alone. In addition, the overexpression of FNDC5 reversed the blocked of p38/MAPK pathway by the overexpression of miR-150-5p in BMSCs. Irisin, a protein encoded by FNDC5 gene, improved symptoms in osteoporosis mice through intraperitoneal injection, while the inhibitor of p38/MAPK pathway weakened this function of irisin. Conclusion miR-150-5p inhibits the osteogenic differentiation of BMSCs by targeting irisin to regulate the/p38/MAPK signaling pathway, and miR-150-5p/irisin/p38 pathway is a potential target for treating osteoporosis.

BackgroundEpilepsy is a non-communicable chronic brain disease that affects all age groups. There are approximately 50 million epilepsy patients worldwide, which is one of the most common neurological disorder. This study reports the time trends in the burden of epilepsy from 1999 to 2019.MethodsWe evaluated the disease burden and its temporal trends of epilepsy using the prevalence and years lived with disability (YLDs), which was estimated based on the Global Burden of Disease (GBD) 2019 study. The age-period-cohort (APC) model was used to estimate the temporal trends of the epilepsy prevalence and YLDs rates, and to analyze the relative risks of age, periods and queues (age/period/queue effects).ResultsIn the past 30 years, the global age-standardized prevalence rate and age-standardized rate has increased by 29.61% and 27.02%, respectively. Globally, the APC model estimated the net drift of prevalence and YLDs were 0.88% (95% CI: 0.83–0.93) and 0.80% (95% CI: 0.75–0.85) per year. Among 204 countries and territories, the YLDs in 146 and prevalence 164 showed an increasing trend. And the risk of YLDs and prevalence increases with age, with the lowest risk among 0–4 years old and the highest risk among 75–79 years old. Unfavorable increasing period and cohort risks of YLDs and prevalence were observed.ConclusionOver the past 30 years, the YLDs and prevalence of epilepsy have gradually increased globally and unfavorable increasing period and cohort risks were observed. Emphasizing epilepsy prevention, strengthening epilepsy health education, optimizing older adults epilepsy diagnosis and treatment plans, and actively promoting epilepsy diagnosis and treatment plans can effectively reduce new cases of epilepsy and related disabilities.

Along with the development of 5G network and Internet of Things technologies, there has been an explosion in personalized healthcare systems. When the 5G and Artificial Intelligence (AI) is introduced into diabetes management architecture, it can increase the efficiency of existing systems and complications of diabetes can be handled more effectively by taking advantage of 5G. In this article, we propose a 5G-based Artificial Intelligence Diabetes Management architecture (AIDM), which can help physicians and patients to manage both acute complications and chronic complications. The AIDM contains five layers: the sensing layer, the transmission layer, the storage layer, the computing layer, and the application layer. We build a test bed for the transmission and application layers. Specifically, we apply a delay-aware RA optimization based on a double-queue model to improve access efficiency in smart hospital wards in the transmission layer. In application layer, we build a prediction model using a deep forest algorithm. Results on real-world data show that our AIDM can enhance the efficiency of diabetes management and improve the screening rate of diabetes as well.

Bladder cancer (BC), as one of the main urological cancers in the world, possesses the abilities of multiple-drug resistance and metastasis. However, there remains a significant gap in the understanding and advancement of prognosis and therapeutic strategies for BC. Ferroptosis, a novel type of iron-dependent regulated cell death, depends on lipid peroxidation, which has been proven to have a strong correlation with the development and treatment of BC. Its mechanism mainly includes three pathways, namely, lipid peroxidation, the antioxidant system, and the iron overload pathway. In this review, we reviewed the mechanism of ferroptosis, along with the related therapeutic targets and drugs for BC, as it might become a new anticancer treatment in the future.

The Doppler band compensated by the keystone transform (KT) is limited. Therefore, it needs to be used in conjunction with the Doppler ambiguity compensation function to correct the range migration (RM) caused by maneuvering targets with Doppler ambiguity. However, the KT implemented by sinc interpolation suffers from significant performance loss at boundaries of compensation Doppler bands. Additionally, in a multi-target scenario, KT implementation methods occupy high complexity when the Doppler range of targets spans over two compensation Doppler bands. To address the aforementioned issues, this study presents a variable Doppler starting point keystone transform (VDSPKT) method, where a new form of ambiguity compensation function is constructed, turning the Doppler starting point of the compensation band in KT variable. Firstly, the position of the compensation Doppler band is changed from fixed to adjustable as needed, enhancing the flexibility of KT. Crucially, the connection points of the compensation Doppler bands in sinc interpolation are reset, avoiding performance loss at their boundaries. Also, the compensation band is adjusted to cover the narrow Doppler frequency range caused by targets, significantly improving computational efficiency. Finally, the simulation and real data experiments demonstrate that the proposed approach effectively addresses the performance degradation and high computational complexity of KT in the aforementioned scenarios, resulting in a computational load reduced by approximately 50% compared to traditional methods.

Abstract Background High fasting plasma glucose (HFPG) is the fastest-growing risk factor for cancer deaths worldwide. We reported the cancer mortality attributable to HFPG at global, regional, and national levels over the past three decades and associations with age, period, and birth cohort. Methods Data for this study were retrieved from the Global Burden of Disease Study 2019, and we used age-period-cohort modelling to estimate age, cohort and period effects, as well as net drift (overall annual percentage change) and local drift (annual percentage change in each age group). Results Over the past 30 years, the global age-standardized mortality rate (ASMR) attributable to HFPG has increased by 27.8%. The ASMR in 2019 was highest in the male population in high sociodemographic index (SDI) areas (8.70; 95% CI, 2.23–18.04). The net drift for mortality was highest in the female population in low SDI areas (2.33; 95% CI, 2.12–2.55). Unfavourable period and cohort effects were found across all SDI quintiles. Cancer subtypes such as "trachea, bronchus, and lung cancers", "colon and rectal cancers", "breast cancer" and "pancreatic cancer" exhibited similar trends. Conclusions The cancer mortality attributable to HFPG has surged during the past three decades. Unfavourable age-period-cohort effects on mortality were observed across all SDI quintiles, and the cancer mortality attributable to HFPG is expected to continue to increase rapidly in the future, particularly in lower SDI locations. This is a grim global public health issue that requires immediate attention.

Abstract Background Isthmic spondylolisthesis (IS) is a common clinical disease with a high incidence rate. However, most current researches explain the clear pathogenesis from a single perspective. The aim of our study was to explore the relationships between multiple parameters in patients and find the potential risk factors of this disease. Methods Our study retrospectively included 115 patients who were diagnosed with isthmic spondylolisthesis and the same number of individuals without spondylolisthesis. The following parameters were measured or collected: age, pelvic incidence (PI), facet joint angle (FJA) and pedicle-facet angle (P-F angle). The radiographic files were imported into Mimics Medical 20.0 and all collected data were analyzed using SPSS, version 26.0, statistical software. Results The age was higher in IS group than in control group. PI was also higher in the IS group (50.99 ± 7.67) than in the control group (43.77 ± 9.30) significantly (P = 0.009). There was significant difference in cranial and average FJA tropism in L3-L4 level (P = 0.002, P = 0.006, respectively) and in L4-L5 level (P

Reference signal reconstruction serves as a crucial technique for suppressing multipath interference and noise in the reference channel of passive radar. Aiming at the challenge of detecting Low-Slow-Small (LSS) targets using Digital Terrestrial Multimedia Broadcasting (DTMB) signals, this article proposes a novel segmented sliding window reference signal reconstruction method based on Fuzzy C-Means (FCM). By partitioning the reference signals based on the structure of DTMB signal frames, this approach compensates for frequency offset and sample rate deviation individually for each segment. Additionally, FCM clustering is utilized for symbol mapping reconstruction. Both simulation and experimental results show that the proposed method significantly suppresses constellation diagram divergence and phase rotation, increases the adaptive cancellation gain and signal-to-noise ratio (SNR), and in the meantime reduces the computation cost.

Anthropogenic eutrophication has universally threatened river ecological health and has been a key issue in river conservation. Agricultural sewage, which leads to increased nutrient levels and results in the loss of ecological function and biodiversity, results from the growth of agricultural activity and human populations. Consequently, attention has increasingly been focused on developing a relevant tool to describe the relationship between the biotic communities and anthropogenic eutrophication. The benthic diatom community has been widely used as an effective tool for indicating the ecological status of river systems especially in the context of recent international Water Framework Directive policies (WFD). In this study, a statistical method consisting of trophic status index (TSI), Specific Polluosensitivity Index (IPS), Descy Index (DES), redundancy analysis (RDA), and the geographic information system (GIS) technique was conducted to explore the response of benthic diatom community to anthropogenic eutrophication. Initially, the TSI, IPS and DES were determined to differentiate the trophic gradient along a gradient in agricultural intensity. Subsequently, RDA was used to identify spatial distribution patterns of environmental parameters and benthic diatom communities. Finally, the RDA scores as calculated and spatially interpolated were applied to GIS technology to reveal the response of benthic diatom communities to anthropogenic impacts along the trophic gradient. Our results revealed that the studied basin mostly exceeded the eutrophic level. Two different patterns of diatom communities response to ecological gradient were identified based on RDA, one representing the agriculture eutrophication discharges in electrical conductivity (EC) and the other representing organic pollution as chemical oxygen demand (COD). The developed method in this study highlight that the EC was more effective than the nutrient indices in determining diatom distribution in a eutrophic agriculturally-influenced river system.

Abstract Background The β-cell function and insulin resistance required by existing methods of classifying type 2 diabetes are not routinely adopted in most medical institutions of developing countries and regions. This study aims to propose a novel, affordable classification approach and evaluate its predictive ability for several health and mortality outcomes, including cardiovascular health (CVH), retinopathy, chronic kidney disease (CKD), nonalcoholic fatty liver disease (NAFLD), advanced liver fibrosis, and mortality caused by all-cause, cardiovascular disease (CVD), cancer. Methods Based on 4060 participants with diabetes (aged ≥ 30 at the time of diagnosis) selected from the National Health and Nutrition Examination Survey III & 1999–2014, we proposed a novel, but simple classification approach based on the threshold of fasting plasma glucose (FPG), triglyceride-glucose (TyG) index and body mass index (BMI). We used logistic regression model to assess its predictability for diabetes complications, and Cox regression model to estimate the mortality risks. Results By utilizing this approach, we characterized the subjects into four subgroups: subgroup A (obesity-related), which accounts for 37% of the total, subgroup B (age-related), 38%, subgroup C (insulin resistance), 20%, and subgroup D (severe insulin deficiency), 5%. Subjects in subgroup D had a higher risk of retinopathy, in subgroup B had a lower risk of poor cardiovascular health, nonalcoholic fatty liver disease, and advanced liver fibrosis, in subgroup C had a higher risk of all-cause mortality. Conclusions This study proposes an affordable and practical method for classifying patients with type 2 diabetes into different subgroups, with a view to yield a high predictability of patient outcomes and to assist clinicians in providing better treatment.

Background/Aims Binge drinking leads to many disorders, including alcoholic hepatosteatosis, which is characterized by intrahepatic neutrophil infiltration and increases the risk of hepatocellular carcinoma (HCC). Molecular mechanisms may involve the migration of bacterial metabolites from the gut to the liver and the activation of neutrophil extracellular traps (NETs). Methods Serum samples from both binge drinking and alcohol-avoiding patients were analyzed. Mouse models of chronic plus binge alcohol-induced hepatosteatosis and HCC models were used. Results A marker of NETs formation, lipopolysaccharide (LPS), was significantly higher in alcoholic hepatosteatosis and HCC patients and mice than in controls. Intrahepatic inflammation markers and HCC-related cytokines were decreased in mice with reduced NET formation due to neutrophil elastase (NE) deletion, and liver-related symptoms of alcohol were also alleviated in NE knockout mice. Removal of intestinal bacteria with antibiotics led to decreases in markers of NETs formation and inflammatory cytokines upon chronic alcohol consumption, and development of alcoholic hepatosteatosis and HCC was also attenuated. These functions were restored upon supplementation with the bacterial product LPS. When mice lacking toll-like receptor 4 (TLR4) received chronic alcohol feeding, intrahepatic markers of NETs formation decreased, and hepatosteatosis and HCC were alleviated. Conclusions Formation of NETs following LPS stimulation of TLR4 upon chronic alcohol use leads to increased alcoholic steatosis and subsequent HCC.

Abstract Background Cognitive deficits are common in patients with sepsis. Previous studies in sepsis-associated encephalopathy (SAE) implicated the C-X-C chemokine receptor type (CXCR) 5. The present study used a mouse model of SAE to examine whether CXCR5 down-regulation could attenuate cognitive deficits. Methods Sepsis was induced in adult male C57BL/6 J and CXCR5 −/− mice by cecal ligation and puncture (CLP). At 14–18 days after surgery, animals were tested in a Morris water maze, followed by a fear conditioning test. Transmission electron microscopy of hippocampal sections was used to assess levels of autophagy. Primary microglial cultures challenged with lipopolysaccharide (LPS) were used to examine the effects of short interfering RNA targeting CXCR5, and to investigate the possible involvement of the p38MAPK/NF-κB/STAT3 signaling pathway. Results CLP impaired learning and memory and up-regulated CXCR5 in hippocampal microglia. CLP activated hippocampal autophagy, as reflected by increases in numbers of autophagic vacuoles, conversion of microtubule-associated protein 1 light chain 3 (LC3) from form I to form II, accumulation of beclin-1 and autophagy-related gene-5, and a decrease in p62 expression. CLP also shifted microglial polarization to the M1 phenotype, and increased levels of IL-1β, IL-6 and phosphorylated p38MAPK. CXCR5 knockout further enhanced autophagy but partially reversed all the other CLP-induced effects, including cognitive deficits. Similar effects on autophagy and cytokine expression were observed after knocking down CXCR5 in LPS-challenged primary microglial cultures; this knockdown also partially reversed LPS-induced up-regulation of phosphorylated NF-κB and STAT3. The p38MAPK agonist P79350 partially reversed the effects of CXCR5 knockdown in microglial cultures. Conclusions CXCR5 may act via p38MAPK/NF-κB/STAT3 signaling to inhibit hippocampal autophagy during sepsis and thereby contribute to cognitive dysfunction. Down-regulating CXCR5 can restore autophagy and mitigate the proinflammatory microenvironment in the hippocampus.

This paper addresses the problem of tracking multiple extended targets in three-dimensional space. We propose the Gaussian process Gaussian mixture probability hypothesis density (GP-PHD) filter, which is capable of tracking multiple extended targets with complex shapes in the presence of clutter. Our approach combines the Gaussian process regression measurement model with the probability hypothesis density filter to estimate both the kinematic state and the shape of the targets. The shape of the extended target is described by a 3D radial function and is estimated recursively using the Gaussian process regression model. Furthermore, we transform the recursive Gaussian process regression problem into a state estimation problem by deriving a state space model such that the estimation of the extent can be integrated into the kinematic part. We derive the predicted likelihood function of the PHD filter and provide a closed-form Gaussian mixture implementation. To evaluate the performance of the proposed filter, we simulate a typical extended target tracking scenario and compare the GP-PHD filter with the traditional Gamma Gaussian Inverse-Wishart PHD (GGIW-PHD) filter. Our results demonstrate that the proposed algorithm outperforms the GGIW-PHD filter in terms of estimating both kinematic states and shape. We also investigate the impact of the measurement rates on both filters; it is observed that the proposed filter exhibits robustness across various measurement rates, while the GGIW-PHD filter suffers under low-measurement-rate conditions.

ObjectiveWe investigated the association between cancer incidence and body mass index (BMI) variability calculated from the recall of weight at decades of age by participants in the USA Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.MethodsA total of 89,822 individuals' BMI were recorded as recalled the participant's aged 30, 40, 50, 60, 70 years, and baseline. BMI variability was assessed using four indices: SD, coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV). The multivariate Cox regression analysis was performed to calculate hazard ratios (HRs) of these measures for incident cancers and corresponding 95% CIs.ResultsDuring the median follow-up of 11.8 years, there were newly diagnosed 5,012 cases of prostate cancer, 792 cases of lung cancer, 994 cases of colon cancer, and 132 cases of ovarian cancer. Compared with the lowest quartile (Q1) group, the highest quartile (Q4) group of BMI variability indices was associated with increased lung cancer risk, including BMI_SD (HR, 1.58; 95% CI, 1.17–2.12), BMI_CV (HR, 1.46; 95% CI, 1.10–1.94), BMI_VIM (HR, 1.73; 95% CI, 1.33–2.25), and BMI_ARV (HR, 2.17; 95% CI, 1.62–2.91). Associations between BMI variability and prostate, colon, and ovarian cancer incidences were of limited significance.ConclusionThe findings imply that maintaining a stable weight across adulthood is associated with a decreased incidence of lung cancer.

Abstract Detection of weak manoeuvring targets has always been an important yet challenging task for radar signal processing. One primary reason is that target variable motions within a coherent processing interval generate energy migrations across multiple resolution bins, which severely deteriorate the parameter estimation performance. The problem is compounded by an increasingly complex surveillance environment, as well as more affordable and pervasive than ever small targets such as drones. In this work, a coarse‐to‐fine strategy for the detection of weak manoeuvring targets is designed. First, a coarse estimation of the chirp parameter in an extended unambiguous range using a novel coprime segmented discrete polynomial‐phase transform is coherently integrated and derived. Sparse fractional Fourier transform is then employed to refine the coarse estimation at a significantly reduced computational complexity. The proposed scheme achieves an efficient and reliable weak target detection, while requires no a priori knowledge on the motion parameters, which is verified by the simulation results.

Mucosal vaccination, which has the potential to induce both mucosal and systemic immune responses, is considered the most suitable method of preventing infectious diseases in farmed fish. Aeromonas veronii and Edwardsiella ictaluri are two pathogenic bacteria found in yellow catfish and often infect the fish through mucosal surfaces. Delivery of a bivalent inactivated vaccine by injection has been shown to induce a strong systemic immune response against both bacterial infections. However, mucosal immune responses and protective efficiency induced by this inactivated vaccine administrated via immersion are yet to be investigated. We developed a bivalent vaccine containing formalin-inactivated A. veronii and E. ictaluri and evaluated the immune response in yellow catfish after immersion vaccination using body fluids biochemistry indices, agglutinating antibody titers, and the expression level of immune-related genes in the skin, gills, spleen, and head kidney. The activities of innate immune-related enzymes and specific agglutination antibody titers in body fluids, as well as the expression of innate and adaptive immune-related genes in both the mucosal and systemic tissues of vaccinated fish, were significantly higher than that in control fish. Next, we assessed the protective efficacy by a challenge model of virulent strains of E. ictaluri and A. veronii. The relative survival percent of vaccinated fish was 80% and 87% after challenging fish with E. ictaluri and A. veronii, respectively, which was higher than unvaccinated control fish (43% and 57%). These results confirm that the bivalent inactivated vaccine administered via immersion induces a strong mucosal immune response and confers good protection against both E. ictaluri and A. veronii. Our results also reinforce the notion that immersion vaccination could stimulate both mucosal and systemic immunity contributing to protection against pathogens.

Objectives To verify whether a simplified method based on age, body mass index (BMI) and glycated haemoglobin (HbA1c) is feasible in classifying patients with type 2 diabetes (T2D), and evaluate the predictive ability of subgroups in several health and mortality outcomes.Design Retrospective cohort study.Setting The National Health and Nutrition Examination Survey 1999–2014 cycle.Participants A total of 1960 participants with diabetes and the age at diagnosis greater than 30.Primary and secondary outcome measures Participants with T2D were assigned to previously defined (by Ahlqvist) subgroups based on five variables: age, BMI, HbA1c, homoeostasis model assessment (HOMA) 2 estimates of β-cell function (HOMA2-B), and insulin resistance (HOMA2-IR), and on three variables: age, BMI and HbA1c. The classification performances of the three variables were evaluated based on 10-fold cross validation, with accuracy, precision and recall as evaluation criteria. Outcomes were assessed using logistic regression and Cox regression analysis.Results Without HOMA measurements, it is difficult to identify severe insulin-resistant diabetes, but other subgroups can be ideally identified. There is no significant difference between the five variables and the three variables in the ability to predict the prevalence of poor cardiovascular health (CVH), chronic kidney disease, non-alcoholic fatty liver disease and advanced liver fibrosis, and the risk of all-cause, cardiovascular disease and cancer-related mortality (p>0.05), except the prevalence of poor CVH in mild age-related diabetes (p

Fast and stable detection of dim and small infrared (IR) targets in complex backgrounds has important practical significance for IR search and tracking system. The existing small IR target detection methods usually fail or cause a high probability of false alarm in the highly heterogeneous and complex backgrounds. Continuous motion of a target relative to the background is important information regarding detection. In this article, a low-rank and sparse decomposition method based on greedy bilateral factorization is proposed for IR dim and small target detection. First, by analyzing the complex structure information of IR image sequences, the target is regarded as an independent sparse motion structure and an efficient optimization algorithm is designed. Second, the greedy bilateral factorization strategy is adopted to approximate the low-rank part of the algorithm, which significantly accelerates the efficiency of the algorithm. Extensive experiments demonstrate that the proposed method has better detection performance than the existing methods. The proposed method can still detect targets quickly and stably especially in complex scenes with weak signal-to-noise ratio.

Phytoplankton taxonomic α-diversity indices are useful tools to characterize the trophic states in freshwater ecosystems. However, the application of these indices to assess trophic states in large barrier lakes is rare, especially in China. To test the usefulness of phytoplankton taxonomic α-diversity indices in trophic state assessments, we investigated the taxonomic α-diversity-Comprehensive Trophic Level Index (TLI) relationships in the second largest alpine lava barrier lake (Jingpo Lake, China) in the rainy and dry season from 2017 to 2018. Based on a two-year dataset, we found that there was a significant difference in the phytoplankton community, α-diversity indices, and TLI dynamic between the rainy season and the dry season. First, there was significant variation in phytoplankton abundance, the Margalef index, and the Shannon-Wiener index in different hydrological periods (p < 0.05). Second, the mean TLI in the rainy season (44 ± 5) was higher than in the dry season (41 ± 5) (p < 0.05). Lastly, the response characteristics of the Margalef and Shannon-Wiener index with TLI were different in different hydrological periods, and the relationship between the Pielou evenness index and TLI was weak. This study highlights that phytoplankton taxonomic α-diversity indices are relevant tools in water quality assessments but selecting the fit index is necessary. The current study provides key information about phytoplankton community, α-diversity, and trophic states in the largest alpine lava barrier lake, and the results of the study will benefit water quality management and biodiversity conservation in barrier lakes.

PurposeTo extract texture features from magnetic resonance imaging (MRI) scans of patients with brain tumors and use them to train a classification model for supporting an early diagnosis.MethodsTwo groups of regions (control and tumor) were selected from MRI scans of 40 patients with meningioma or glioma. These regions were analyzed to obtain texture features. Statistical analysis was conducted using SPSS (version 20.0), including the Shapiro–Wilk test and Wilcoxon signed-rank test, which were used to test significant differences in each feature between the tumor and healthy regions. T-distributed stochastic neighbor embedding (t-SNE) was used to visualize the data distribution so as to avoid tumor selection bias. The Gini impurity index in random forests (RFs) was used to select the top five out of all features. Based on the five features, three classification models were built respectively with three machine learning classifiers: RF, support vector machine (SVM), and back propagation (BP) neural network.ResultsSixteen of the 25 features were significantly different between the tumor and healthy areas. Through the Gini impurity index in RFs, standard deviation, first-order moment, variance, third-order absolute moment, and third-order central moment were selected to build the classification model. The classification model trained using the SVM classifier achieved the best performance, with sensitivity, specificity, and area under the curve of 94.04%, 92.3%, and 0.932, respectively.ConclusionTexture analysis with an SVM classifier can help differentiate between brain tumor and healthy areas with high speed and accuracy, which would facilitate its clinical application.

PURPOSEWe aimed to assess the awareness of interventional radiology (IR) among medical students, and to evaluate an IR curriculum in China.METHODSBetween the academic years of 2008 and 2016, 517 third-year medical undergraduates, who successfully applied for an IR curriculum, received a survey related to IR before taking the course. Final exams were conducted after the IR course.RESULTSA total of 355 of the 517 medical students (68.67%) answered the survey; 81.97% of the respondents had heard of IR, 40.28% believed they understood what IR is, but no one was familiar with IR. The four most common pathways for medical students to acquire IR knowledge were via new media (e.g., internet, apps) (42.82%), a teacher/textbook (36.90%), a friend (32.68%), and traditional media (26.48%). The most familiar interventional procedures to respondents were percutaneous transluminal coronary angioplasty (PTCA, 78.59%) and transcatheter arterial chemoembolization (TACE, 44.51%). The results of the survey also indicated that 68.45% of the respondents wanted to learn about IR, but that only 47 male students (13.24%) considered a career in IR. The pass rate of the IR course final exam was 87.04%, i.e., 87.04% of the students successfully completed the course and final exam.CONCLUSIONThe IR knowledge of medical students in China is worse than that of European medical students. We suggest that providing medical students with general information about IR in the media, as well as via teaching and textbooks in medical school, requires prompt and significant attention. An IR curriculum is beneficial for increasing the IR knowledge of undergraduates.

Due to the short wavelength of the terahertz wave, airborne terahertz synthetic aperture radar (THz-SAR) suffers from echo phase errors caused by the high-frequency vibration of the platform. These errors will result in defocusing and the emergence of ghost targets, which will degrade the quality of the image. Therefore, it is necessary to compensate for phase errors in order to bring the image into focus. This paper proposes a multi-component high-frequency vibration parameter estimation method based on chirplet decomposition and least squares (LS) sequential estimators, which differs from other methods that can only be applied to simple harmonic vibrations. In particular, we first obtain the instantaneous chirp rate (ICR) of the signal by chirplet decomposition. Then, we employ the LS sequential estimators in conjunction with separable regression technique (SRT) to estimate vibration parameters. The estimated parameters are subsequently used to re-establish the ICR components for each vibration component and these parameters are further re-estimated to improve their accuracy. Based on the estimated parameters, phase compensation functions can be constructed to suppress the defocusing and ghost targets in airborne THz-SAR imaging. Simulated results on point targets and distributed imaging scenes demonstrate that the proposed method is accurate and reliable even at low signal-to-noise ratios (SNRs).

ObjectiveTo investigate structural and quantitative alterations of gut microbiota in an experimental model of small bowel obstruction.MethodA rat model of small bowel obstruction was established by using a polyvinyl chloride ring surgically placed surrounding the terminal ileum. The alterations of gut microbiota were studied after intestinal obstruction. Intraluminal fecal samples proximal to the obstruction were collected at different time points (24, 48 and 72 hours after obstruction) and analyzed by 16s rDNA high-throughput sequencing technology and quantitative PCR (qPCR) for target bacterial groups. Furthermore, intestinal claudin-1 mRNA expression was examined by real-time polymerase chain reaction analysis, and serum sIgA, IFABP and TFF3 levels were determined by enzyme-linked immunosorbent assay.ResultsSmall bowel obstruction led to significant bacterial overgrowth and profound alterations in gut microbiota composition and diversity. At the phylum level, the 16S rDNA sequences showed a marked decrease in the relative abundance of Firmicutes and increased abundance of Proteobacteria, Verrucomicrobia and Bacteroidetes. The qPCR analysis showed the absolute quantity of total bacteria increased significantly within 24 hours but did not change distinctly from 24 to 72 hours. Further indicators of intestinal mucosa damage and were observed as claudin-1 gene expression, sIgA and TFF3 levels decreased and IFABP level increased with prolonged obstruction.ConclusionSmall bowel obstruction can cause significant structural and quantitative alterations of gut microbiota and induce disruption of gut mucosa barrier.

Magnolol, a hydroxylated biphenyl extracted from Magnolia officinalis, has recently drawn attention due to its anticancer potential. The present study was aimed to explore the effects of Magnolol on restraining the proliferation, migration and invasion of pancreatic cancer in vivo and in vitro. Magnolol showed significant anti-growth effect in an orthotopic xenograft nude mouse model, and immunohistochemical staining of the xenografts revealed that Magnolol suppressed vimentin expression and facilitated E-cadherin expression. The cytoactive detection using CCK-8 assay showed Magnolol inhibited PANC-1 and AsPC-1 concentration-dependently. Scratch healing assay and the Transwell invasion assay proved the inhibiting effects of Magnolol on cellular migration and invasion at a non-cytotoxic concentration. Western blot and rt-PCR showed that Magnolol suppressed epithelial-mesenchymal-transition by increasing the expression level of E-cadherin and decreasing those of N-cadherin and vimentin. Magnolol suppressed the TGF-β/Smad pathway by negatively regulating phosphorylation of Smad2/3. Moreover, TGF-β1 impaired the antitumor effects of Magnolol in vivo. These results demonstrated that Magnolol can inhibit proliferation, migration and invasion in vivo and in vitro by suppressing the TGF-β signal pathway and EMT. Magnolol could be a hopeful therapeutic drug for pancreatic malignancy.

AIM: To describe a Chinese family affected by a severe form of Axenfeld-Rieger syndrome (ARS) and characterize the molecular defect in PITX2 in the family. METHODS: Patients presented with typical ARS from a Chinese family were investigated. We performed genome-wide linkage scan and exome sequencing to identify the pathogenic mutations. Candidate mutations were verified for co-segregation in the whole pedigree using Sanger sequencing. Real-time polymerase chain reaction (RT-PCR) and Western blotting were performed to verify the expression of the pathogenic gene. RESULTS: Genome-wide linkage and exome sequencing analyses showed PITX2 as the disease candidate gene. A>G substitution at position -11 of 3’ss of exon 5 (IVS5-11A>G) that co-segregated with the disease phenotype was discovered in the family. The PITX2 messenger ribonucleic acid and protein levels were about 50% lower in patients with ARS than in unaffected family members in the family. CONCLUSION: Our findings implicate the first intronic mutation of the PITX2 gene in the pathogenesis of a severe form of ARS in a Chinese family. This study highlights the importance of a systematic search for intronic mutation in ARS cases for which no mutations in the exons of PITX2 have been found.

Passive radar (PR) systems are attractive for various military and commercial applications, where illuminators of opportunity are used. Using the fact that most target scenes are very sparsely populated makes it possible to apply compressive sensing (CS) for PR. CS provides higher resolution than that obtained by using traditional ambiguous function, but suffers from increasing coherence associated with the finer grids whether for monostatic radar or multistatic radar. A novel incoherent CS dictionary construction method is presented here to deal with the case of finer grids. Experimental results demonstrate that the proposed CS-based processing scheme with incoherent dictionary can work well for high-resolution PRs.

Segmented discrete polynomial-phase transform (DPT) integrates input signals to enable detection and parameter estimation of weak linear frequency modulated (LFM) signals. However, conventional DPT approaches suffer from a low unambiguously detectable range of the chirp rates because the segmentation effectively reduces the sampling rate between adjacent segments. To enable unique detection of LFM signals with a high chirp rate estimation, the authors propose the use of multiple segmentation sets where the respective segment lengths are governed by a coprime relationship. As such, the ambiguity of the estimated chirp rates that arise from a single segmentation set is eliminated through the fusion of the multiple segmentation sets using the Chinese Remainder Theorem. The effectiveness of the proposed method for the estimation of LFM signals with a high chirp rate is validated by simulation results.

The GIS is widely used in the power system. However, the overheating of the device contacts may cause serious accidents. A method of online monitoring of contact temperature of GIS equipment is put forward based on infrared sensing technology in view of the structural characteristics of GIS device. The method realises continuous and automatic measurement of temperature. The selection and installation location of temperature sensor are analysed, and here, the characteristics of GIS contact temperature measurement are studied. The GIS temperature measurement system is set up on the basis of previous research. The system is used to carry out experiments, whether the shielding cover of the device contact is existing in the process of temperature measurement is studied, respectively. The artificial neural network algorithm is used to process the data. The experimental results verify the feasibility and stability of the GIS contact temperature-monitoring system. The potential economic benefit of this study is huge and its application prospect is very broad.

The utilization of Global Navigation Satellite System (GNSS) is becoming an attractive navigation approach for geostationary orbit (GEO) satellites. A high-sensitivity receiver compatible with Global Position System (GPS) developed by the United States and BeiDou Navigation Satellite System (BDS) developed by China has been used in a GEO satellite named TJS-5 to demonstrate feasibility of real-time navigation. According to inflight data, the GNSS signal characteristics including availability, position dilution of precision (PDOP), carrier-to-noise ratio (C/N0), observations quantity and accuracy are analyzed. The mean number of GPS and GPS + BDS satellites tracked are 7.4 and 11.7 and the mean PDOP of GPS and GPS + BDS are 10.24 and 3.91, respectively. The use of BDS significantly increases the number of available navigation satellites and improves the PDOP. The number of observations with respect to C/N0 is illustrated in detail. The standard deviation of the pseudorange noises are less than 4 m, and the corresponding carrier phase noises are mostly less than 8 mm. We present the navigation performance using only GPS observations and GPS + BDS observations combination at different weights through comparisons with the precision reference orbits. When GPS combined with BDS observations, the root mean square (RMS) of the single-epoch least square position accuracy can improve from 32.1 m to 16.5 m and the corresponding velocity accuracy can improve from 0.238 m/s to 0.165 m/s. The RMS of real-time orbit determination position accuracy is 5.55 m and the corresponding velocity accuracy is 0.697 mm/s when using GPS and BDS combinations. Especially, the position accuracy in x-axis direction reduced from 7.24 m to 4.09 m when combined GPS with BDS observations.

Hand and arm gesture recognition using radio frequency (RF) sensing modality proves valuable in man−machine interfaces and smart environments. In this paper, we use the time-series analysis method to accurately measure the similarity of the micro-Doppler (MD) signatures between the training and test data, thus providing improved gesture classification. We characterize the MD signatures by the maximum instantaneous Doppler frequencies depicted in the spectrograms. In particular, we apply two machine learning (ML) techniques, namely, the dynamic time warping (DTW) method and the long short-term memory (LSTM) network. Both methods take into account the values as well as the temporal evolution and characteristics of the time-series data. It is shown that the DTW method achieves high gesture classification rates and is robust to time misalignment.

AimsCancer development and progression is not only associated with the tumor cell proliferation but also depends on the interaction between tumor cells and the stromal microenvironment. A new understanding of the role of the tumor microenvironment suggests that the loss of stromal caveolin-1 (Cav-1) as a key regulator may become a potential therapy target. This study aims to elucidate whether stromal Cav-1 expression in pancreatic cancer can be a strong prognosis biomarker.MethodsTissue samples from 45 pancreatic cancer patients were studied. Parenchyma and stroma were separated and purified using laser capture microdissection. Stromal Cav-1 expression was measured from pancreatic cancer, paraneoplastic, and normal tissue using immunohistochemistry. We analyzed the correlation of stromal Cav-1 expression with clinicopathologic features and prognostic indicators, such as tumor marker HER-2/neu gene.ResultsSpecimens from six patients (13.3%) showed high levels of stromal Cav-1 staining, those from eight patients (17.8%) showed a lower, intermediate level of staining, whereas those from 31 patients (68.9%) showed an absence of staining. Cav-1 expression in cancer-associated fibroblasts was lower than that in paracancer-associated and in normal fibroblasts. Stromal Cav-1 loss was associated with TNM stage (P = 0.018), lymph node metastasis (P = 0.014), distant metastasis (P = 0.027), and HER-2/neu amplification (P = 0.007). The relationships of age, sex, histological grade, and tumor size with stromal Cav-1 expression were not significant (P>0.05). A negative correlation was found between circulating tumor cells and stromal Cav-1 expression (PConclusionThe loss of stromal Cav-1 in pancreatic cancer was an independent prognostic indicator, thus suggesting that stromal Cav-1 may be an effective therapeutic target for patients with pancreatic cancer.