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Glioblastoma (GBM), a highly malignant glioma of the central nervous system, is the most dread and common brain tumor with a high rate of therapeutic resistance and recurrence. Currently, the clinical treatment methods are surgery, radiotherapy, and chemotherapy. However, owning to the highly invasive nature of GBM, it is difficult to completely resect them due to the unclear boundary between the edges of GBM and normal brain tissue. Traditional radiotherapy and the combination of alkylating agents and radiotherapy have significant side effects, therapeutic drugs are difficult to penetrate the blood brain barrier. Patients receiving treatment have a high postoperative recurrence rate and a median survival of less than 2 years, Less than 5% of patients live longer than 5 years. Therefore, it is urgent to achieve precise treatment through the blood brain barrier and reduce toxic and side effects. Nanotechnology exhibit great potential in this area. This article summarizes the current treatment methods and shortcomings of GBM, and summarizes the research progress in the diagnosis and treatment of GBM using nanotechnology.
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BACKGROUND: Hemodialysis (HD) is the most important renal replacement therapy for patients with end-stage kidney disease (ESKD). Systemic inflammation is a risk factor of mortality in HD patients. Neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) are new inflammatory markers. However, previous studies have inconsistent conclusions about the predictive value of NLR, MLR and PLR on mortality of HD patients. The aim of this study was to establish an inflammation scoring system by including NLR, MLR and PLR, and evaluate the association between the inflammation score and all-cause and cardiovascular mortality in HD patients. METHODS: In this single center retrospective cohort study, 213 incident HD patients from January 1, 2015 to December 31, 2020 were included. Baseline demographic and clinical data and laboratory measurements were collected. According to the optimal cut-off values, NLR, MLR and PLR were assigned 0 or 1 point, respectively. Then, the inflammation score was obtained by adding the NLR, MLR and PLR scores. All patients were followed until July 31, 2021. The associations of the inflammation score with all-cause and cardiovascular mortality were assessed by multivariable-adjusted Cox models. RESULTS: Of 213 patients, the mean (± SD) age was 56.8 ± 14.4 years, 66.2% were men, and 32.9% with diabetes. The primary cause of ESKD was mainly chronic glomerulonephritis (46.5%) and diabetic nephropathy (28.6%). The median inflammation score was 2 (interquartile range = 1-3). During a median 30 months (interquartile range = 17-50 months) follow-up period, 53 patients had died, of which 33 deaths were caused by cardiovascular disease. After adjusting for demographics, primary diseases and other confounders in multivariable model, the inflammation score = 3 was associated with a hazard ratio for all-cause mortality of 4.562 (95% confidence interval, 1.342-15.504, P = 0.015) and a hazard ratio for cardiovascular mortality of 4.027 (95% confidence interval, 0.882-18.384, P = 0.072). CONCLUSION: In conclusion, an inflammation scoring system was established by including NLR, MLR and PLR, and the higher inflammation score was independently associated with all-cause mortality in HD patients.
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Doenças Cardiovasculares , Neutrófilos , Humanos , Adulto , Pessoa de Meia-Idade , Idoso , Monócitos , Prognóstico , Estudos Retrospectivos , LinfócitosRESUMO
Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting.
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Magnetic navigation is a promising positioning technique for scenarios where a global navigation satellite system (GNSS) is unavailable, such as for underwater submarines and aircraft in space. For ground scenarios, it faces more challenges, since the magnetic distribution suffers interference from surrounding objects such as buildings, bridges, and vehicles. It is natural to think how feasible it is to apply magnetic matching positioning to vehicles. In this paper, a theoretic distribution model is proposed to analyze the magnetic field around objects such as buildings, bridges, and vehicles. According to the experiments, it is shown that the proposed model matches the experimental data well. In addition, a comprehensive indicator metric is defined in this paper to describe the feasibility of the magnetic matching method based on the statistical characteristics of magnetic maps. The best length of matching window, anti-noise performance, and pre-comparison of positioning accuracy in different regions can be easily derived using the proposed comprehensive indicator metric. Finally, the metric is verified through a drive test using different building densities.
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The zero-velocity update (ZUPT)-aided extended Kalman filter (EKF) is commonly used in the traditional inertial navigation system (INS)-based foot-mounted pedestrian dead reckoning (PDR) system, which can effectively suppress the error growth of the inertial-based pedestrian navigation systems. However, in the realistic test, the system still often suffers from drift, which is commonly caused by two reasons: failed detection of the stationary phase in the dynamic pedestrian gait and heading drift, which is a poorly observable variable of the ZUPT method. In this paper, firstly, in order to improve the initial heading alignment accuracy, a novel method to calibrate the PDR system's initial absolute heading is proposed which is based on the geometric method. By using a calibration line rather than only using the heading of the starting point, the method can calibrate the initial heading of the PDR system more accurately. Secondly, for the problem of failed detection of the stationary phase in the dynamic pedestrian gait, a novel stationary phase detection method is proposed, which is based on foot motion periodicity rather than the threshold comparison principle in the traditional method. In an experiment, we found that the zero-speed state points always occur around the minimum value of the stationary detector in each gait cycle. By taking the minimum value in each gait cycle as the zero-speed state point, it can effectively reduce the failed detection of the zero-speed interval. At last, in order to reduce the heading drifts during walking over time, a new motion constraint method is exploited based on the range constraint principle. During pedestrian walking, the distance between the foot position estimates of the current moment and the previous stationary period is within the maximum stride length. Once the distance is greater than the maximum stride length, the constraint method is used to confine the current estimated foot position to the sphere of the maximum stride length relative to the previous stationary foot position. Finally, the effectiveness of all proposed methods is verified by the experiments.
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Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy.
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Indoor positioning has recently become an important field of interest because global navigation satellite systems (GNSS) are usually unavailable in indoor environments. Pedestrian dead reckoning (PDR) is a promising localization technique for indoor environments since it can be implemented on widely used smartphones equipped with low cost inertial sensors. However, the PDR localization severely suffers from the accumulation of positioning errors, and other external calibration sources should be used. In this paper, a context-recognition-aided PDR localization model is proposed to calibrate PDR. The context is detected by employing particular human actions or characteristic objects and it is matched to the context pre-stored offline in the database to get the pedestrian's location. The Hidden Markov Model (HMM) and Recursive Viterbi Algorithm are used to do the matching, which reduces the time complexity and saves the storage. In addition, the authors design the turn detection algorithm and take the context of corner as an example to illustrate and verify the proposed model. The experimental results show that the proposed localization method can fix the pedestrian's starting point quickly and improves the positioning accuracy of PDR by 40.56% at most with perfect stability and robustness at the same time.
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The effect of acupuncture induced weight reduction on menstrual activity is definitely not a negligible issue. By analyzing the existing materials about the mutual influence of neuroendocrine system and clinical trails, it is known that there exists a close interrelation between acupuncture-induced weight reduction and menstruation. Acupuncture treatment can achieve the effects of weight reduction and menstrual improvement via regulating activities of leptin, thyroid gland system and hypothalamus-pituitary-adrenal cortex axis. Clinical practice has demonstrated that acupuncture stimulation of some commonly-used acupoints for weight reduction also has a favorable regulation on menstrual activity in obesity women.
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Terapia por Acupuntura , Menstruação/fisiologia , Obesidade/terapia , Redução de Peso/fisiologia , Pontos de Acupuntura , Feminino , Humanos , Leptina/fisiologia , Obesidade/fisiopatologiaRESUMO
OBJECTIVE: To compare the effects of de-addiction with the therapy of acupuncture, acupuncture plus opium, opium plus buprenorphine and opium plus Han's instrument for de-addiction and to study the effects of the four therapeutic methods on the protracted withdrawal syndrome and craving. METHODS: The effects of de-addiction were assessed with the opiate withdrawal scale and the craving degree with visual analogue scale (VAS). RESULTS: The dominance of acupuncture treatment for withdrawal syndrome appeared to be after the 6th day, and the dominance for controlling craving showed after the 8th day, moreover, there were little side effects. CONCLUSION: Acupuncture treatment had the potentiality of preventing relapse and could be used for treating the protracted withdrawal syndrome and psychic dependence during the period between the stages of abstinence and rehabilitation.