Protective effects of curcumin against osteoporosis and its molecular mechanisms: a recent review in preclinical trials

Osteoporosis (OP) is one of the most common metabolic skeletal disorders and is commonly seen in the elderly population and postmenopausal women. It is mainly associated with progressive loss of bone mineral density, persistent deterioration of bone microarchitecture, and increased fracture risk. To date, drug therapy is the primary method used to prevent and treat osteoporosis. However, long-term drug therapy inevitably leads to drug resistance and specific side effects. Therefore, researchers are constantly searching for new monomer compounds from natural plants. As a candidate for the treatment of osteoporosis, curcumin (CUR) is a natural phenolic compound with various pharmacological and biological activities, including antioxidant, anti-apoptotic, and anti-inflammatory. This compound has gained research attention for maintaining bone health in various osteoporosis models. We reviewed preclinical and clinical studies of curcumin in preventing and alleviating osteoporosis. These results suggest that if subjected to rigorous pharmacological and clinical trials, naturally-derived curcumin could be used as a complementary and alternative medicine for the treatment of osteoporosis by targeting osteoporosis-related mechanistic pathways. This review summarizes the mechanisms of action and potential therapeutic applications of curcumin in the prevention and mitigation of osteoporosis and provides reference for further research and development of curcumin

A Real-Time BLE/PDR Integrated System by Using an Improved Robust Filter for Indoor Position

Indoor position technologies have attracted the attention of many researchers. To provide a real-time indoor position system with high precision and stability is necessary under many circumstances. In a real-time position scenario, gross errors of the Bluetooth low energy (BLE) fingerprint method are more easily occurring and the heading angle of the pedestrian will drift without acceleration and magnetic field compensation. A real-time BLE/pedestrian dead-reckoning (PDR) integrated system by using an improved robust filter has been proposed. In the PDR method, the improved Mahony complementary filter based on the pedestrian motion states is adopted to estimate the heading angle reducing the drift error. Then, an improved robust filter is utilized to detect and restrain the gross error of the BLE fingerprint method. The robust filter detected the gross error at different granularity by constructing a robust vector changing the observation covariance matrix of the extended Kalman filter (EKF) adaptively when the application is running. Several experiments are conducted in the true position scenario. The mean position accuracy obtained by the proposed method in the experiment is 0.844 m and RMSE is 0.74 m. Compared with the classic EKF, these two values are increased by 38% and 18%, respectively. The results show that the improved filter can avoid the gross error in the BLE method and provide high precision and scalability in indoor position service

Fast Radio Map Construction by using Adaptive Path Loss Model Interpolation in Large-Scale Building

The radio map construction is usually time-consuming and labor-sensitive in indoor fingerprinting localization. We propose a fast construction method by using an adaptive path loss model interpolation. Received signal strength (RSS) fingerprints are collected at sparse reference points by using multiple smartphones based on crowdsourcing. Then, the path loss model of an access point (AP) can be built with several reference points by the least squares method in a small area. Afterwards, the RSS value can be calculated based on the constructed model and corresponding AP’s location. In the small area, all models of detectable APs can be built. The corresponding RSS values can be estimated at each interpolated point for forming the interpolated fingerprints considering RSS loss, RSS noise and RSS threshold. Through combining all interpolated and sparse reference fingerprints, the radio map of the whole area can be obtained. Experiments are conducted in corridors with a length of 211 m. To evaluate the performance of RSS estimation and positioning accuracy, inverse distance weighted and Kriging interpolation methods are introduced for comparing with the proposed method. Experimental results show that our proposed method can achieve the same positioning accuracy as complete manual radio map even with the interval of 9.6 m, reducing 85% efforts and time of construction

Evaluation of Five Satellite-Based Precipitation Products for Extreme Rainfall Estimations over the Qinghai-Tibet Plateau

The potential of satellite precipitation products (SPPs) in monitoring and mitigating hydrometeorological disasters caused by extreme rainfall events has been extensively demonstrated. However, there is a lack of comprehensive assessment regarding the performance of SPPs over the Qinghai-Tibet Plateau (QTP). Therefore, this research aimed to evaluate the effectiveness of five SPPs, including CMORPH, IMERG-Final, PERSIANN-CDR, TRMM-3B42V7, and TRMM-3B42RT, in identifying variations in the occurrence and distribution of intense precipitation occurrences across the QTP during the period from 2001 to 2015. To evaluate the effectiveness of the SPPs, a reference dataset was generated by utilizing rainfall measurements collected from 104 rainfall stations distributed across the QTP. Ten standard extreme precipitation indices (SEPIs) were the main focus of the evaluation, which encompassed parameters such as precipitation duration, amount, frequency, and intensity. The findings revealed the following: (1) Geographically, the SPPs exhibited better retrieval capability in the eastern and southern areas over the QTP, while displaying lower detection accuracy in high-altitude and arid areas. Among the five SPPs, IMERG-Final outperformed the others, demonstrating the smallest inversion error and the highest correlation. (2) In terms of capturing annual and seasonal time series, IMERG-Final performs better than other products, followed by TRMM-3B42V7. All products performed better during summer and autumn compared to spring and winter. (3) The statistical analysis revealed that IMERG-Final demonstrates exceptional performance, especially concerning indices related to precipitation amount and precipitation intensity. Moreover, it demonstrates a slight advantage in detecting the daily rainfall occurrences and occurrences of intense precipitation. On the whole, IMERG-Final’s ability to accurately detect extreme precipitation events on annual, seasonal, and daily scales is superior to other products for the QTP. It was also noted that all products overestimate precipitation events to some extent, with TRMM-3B42RT being the most overestimated

Simultaneous WiFi ranging compensation and localization for indoor NLoS environments

Smartphone-based WiFi ranging using fine time measurement (FTM) is severely impacted by Non-line-of-sight (NLoS) environments, which causes significant positioning errors. To address this problem, we propose a novel WiFi FTM positioning (WFP) approach based on the geomagnetism and enhanced genetic algorithm (EGA), which can simultaneously execute WiFi localization and ranging compensation. Based on the distribution of the ranging error in NLoS environments, a semiparametric error model-based ranging compensation method is proposed. To construct the EGA searching model, geomagnetism-based positioning is adopted and fed to the EGA together with the measured WiFi ranging data and the ranging compensation method. During online localization, the EGA model dynamically compensates for the erroneous ranging data until it finds the optimal position. Experimental results show that the ranging and localization accuracy of this EGA-based WFP are 1.33 m and 1.64 m, being an improvement of 30.7% and 56.5% compared to the uncompensated ranging data and the trilateration algorithm using the weighted least square (WLS) method, respectively

The incidence and risk factors of meningitis after major craniotomy in China: a retrospective cohort study.

BACKGROUND: Meningitis after neurosurgery can result in severe morbidity and high mortality. Incidence varies among regions and limited data are focused on meningitis after major craniotomy. AIM: This retrospective cohort study aimed to determine the incidence, risk factors and microbiological spectrum of postcraniotomy meningitis in a large clinical center of Neurosurgery in China. METHODS: Patients who underwent neurosurgeries at the Department of Neurosurgery in Huashan Hospital, the largest neurosurgery center in Asia and the Pacific, between 1st January and 31st December, 2008 were selected. Individuals with only shunts, burr holes, stereotactic surgery, transsphenoidal or spinal surgery were excluded. The complete medical records of each case were reviewed, and data on risk factors were extracted and evaluated for meningitis. RESULTS: A total of 65 meningitides were identified among 755 cases in the study, with an incidence of 8.60%. The risk of meningitis was increased by the presence of diabetes mellitus (odds ratio [OR], 6.27; P = 0.009), the use of external ventricular drainage (OR, 4.30; P = 0.003) and the use of lumbar drainage (OR, 17.23; P<0.001). The isolated microorganisms included Acinetobacter baumannii, Enterococcus sp, Streptococcus intermedius and Klebsiella pneumonia. CONCLUSIONS: Meningitis remains an important source of morbidity and mortality after major craniotomy. Diabetic patients or those with cerebral spinal fluid shunts carry significant high risk of infection. Thus, identification of the risk factors as soon as possible will help physicians to improve patient care

Effect of Arbuscular Mycorrhiza Fungus Diversispora eburnea Inoculation on Lolium perenne and Amorpha fruticosa Growth, Cadmium Uptake, and Soil Cadmium Speciation in Cadmium-Contaminated Soil

Cadmium (Cd) pollution has become aggravated during the past decades of industrialization, severely endangering human health through its entry into the food chain. While it is well understood that arbuscular mycorrhizal fungi (AMF) have a strong ability to regulate plant growth and Cd uptake, studies investigating how they affect soil Cd speciation and influence Cd uptake are limited. We designed a pot experiment comprising two AMF-inoculant groups (inoculation with Diversispora eburnea or no inoculation), three Cd concentration levels (0, 5, and 15 mg/kg), and two plant species (Lolium perenne and Amorpha fruticosa) to study the effect of AMF Diversispora eburnea on plant growth, Cd uptake, and Cd speciation in the soil. The results revealed that L. perenne exhibited higher productivity and greater Cd uptake than A. fruticosa, regardless of AMF D. eburnea inoculation. However, AMF D. eburnea significantly altered soil Cd speciation by increasing the proportion of exchangeable Cd and decreasing residual Cd, resulting in Cd enrichment in the plant root organs and the elimination of Cd from the polluted soils. Our experiments demonstrate that inoculating plants with AMF D. eburnea is an effective alternative strategy for remediating Cd-contaminated soil