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The long-term presence of antibiotics in the aquatic environment will affect ecology and human health. Techniques for determining antibiotics are often time-consuming, labor-intensive and costly, and it is desirable to seek new methods to achieve rapid prediction of antibiotics. Many scholars have shown the effectiveness of machine learning in water quality prediction, however, its effectiveness in predicting antibiotic concentrations in the aquatic environment remains inconclusive. Given that conventional water quality indicators directly or indirectly influence antibiotic concentrations, we explored the feasibility of predicting ciprofloxacin (CFX) concentrations based on conventional water quality indicators with the help of three commonly used machine learning algorithms and two parameter optimization algorithms. Then, we evaluated and determined the best model using four commonly used model performance evaluation metrics. The evaluation results showed that the generalized regression neural network (GRNN) model optimized by particle swarm optimization (PSO) had the best prediction among all the models under the conditions of six input variables, namely COD, NH4+-N, DO, WT, TN, and pH. The performance evaluations were R2= 0.936, NSE= 0.915, RMSE= 3.150 ng/L, and MAPE= 30.909 %. Overall, the CFX prediction models met the requirements for antibiotic concentration prediction accuracy, offering a potential indirect method for predicting antibiotic concentrations in water quality management.

As an important component of the automatic hydraulic quick coupling device (AHQCD) on rescue vehicles, the hydraulic quick couplings (HQCs) are used to rapidly dock hydraulic lines and transport fluid while changing and operating hydraulic working tools. However, during tool operation at rescue sites, pressure pulsations at multiple frequencies in the hydraulic lines can coincide with the natural frequencies of the HQCs, potentially causing resonance that severely affects the stability of fluid conveying and damages the connection of hydraulic lines accidentally. To investigate the natural frequencies of the HQCs with upstream and downstream lines, the characteristics of fluid–structure interaction were considered between the poppets and the fluid in this study, and an equivalent stiffness model of the fluid domain was derived based on the fluid compressibility. A dynamic model, along with 6-DOF equations for the system, was established, and the natural frequencies and mode vectors were determined by free vibration analysis. In addition, the effects of working pressure, air content, and stiffness of the springs on the natural frequency of the HQC system were analyzed. The results show the natural frequency increases with a higher working pressure and lower air content, while the effect of spring stiffness on natural frequencies varies with different modes. Furthermore, the proposed model is validated by experimental pressure signals, showing good agreement, with an average error of 2.7% for the first-order natural frequency. This paper presents a theoretical method for improving the stability of fluid transport when operating various hydraulic tools under complex rescue conditions.

Abstract Introduction Asthma is a common chronic condition in children. Several studies have explored the potential association between IL10 rs1800896 polymorphism and the risk of asthma in children, but the findings have been inconsistent. To address these discrepancies, we conducted a systematic review and meta‐analysis to assess the relationship between IL10 rs1800896 polymorphisms and the susceptibility to pediatric asthma. Methods A literature search was conducted in PubMed, Scopus, Web of Science, and CNKI databases to identify eligible studies through April 2022. Meta‐analysis was then performed using five genetic models: dominant, recessive, homozygous, heterozygous, and allele. Results A total of 12 studies comprising 1645 cases along with 1447 controls were included in this meta‐analysis. It was found that rs1800896 was not associated significantly with susceptibility to childhood asthma in all genetic models investigated. Subgroup analysis based on the ethnic background of the subjects revealed that rs1800896 was significantly linked to a lower risk of pediatric asthma among Asians in the homozygous model (OR = 0.311, 95% CI = 0.152–0.637, P = 0.001) and in the recessive model (OR = 0.585, 95% CI = 0.405–0.846, P = 0.004), whereas no significant relationship was observed in Egyptians (P > 0.05). Conclusion In conclusion, IL10 rs1800896 polymorphism may be useful as a predictive marker for childhood asthma in Asians, although further studies are needed to validate the study results.

The construction of new critical infrastructure, represented by high-speed full-time signal coverage, intelligent and fine-grained urban management, and deep space and deep sea scientific innovation experimental fields, has entered a new stage with the deep integration and development of new technologies such as 5G/6G, artificial intelligence, and blockchain in various fields.The security evaluation of cryptography applications, as a key technological resource for ensuring the security of national information, integration, and innovation infrastructure, has risen to the level of international law and national development strategy.It is urgent to construct a comprehensive, fine-grained, and self-evolving cryptography security evaluation system throughout the data lifecycle.The typical APT attacks and ransomware attacks faced by new critical infrastructure in industries such as energy, medicine, and transportation in recent years were considered.And then the growing demand for security evaluation of cryptography applications was analyzed in the face of new business requirements such as preventing endogenous data security risks, achieving differentiated privacy protection, and supporting authenticated attack traceability.The new challenges were also examined, which were brought by new information infrastructure (including big data, 5G communication, fundamental software, etc.), integration infrastructure (including intelligent connected vehicles, intelligent connected industrial control systems, etc.), and innovation infrastructure (including big data, artificial intelligence, blockchain, etc.) to the security evaluation of cryptography applications.Furthermore, the new requirements were revealed about domestically produced cryptography algorithms and protocols deployed on high-performance computing chips, ultra-high-speed communication modules, and large-capacity storage media for cryptography application security evaluation technology.Finally, the development of automated and intelligent cryptography application security evaluation technology was explored.

Studies have shown that a lot of traditional Chinese medicines could improve the immunity of the body. Dangdi oral liquid (DDO) was mainly composed of Angelica sinensis (Oliv.) Diels (Danggui), Rehmannia glutinosa Libosch. (Dihuang), Achyranthes bidentata Bl. (Niuxi), Glycyrrhiza uralensis Fisch. (Gancao). In this study, the rapid ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) method was used to identify the potentially effective compounds of DDO. Then the immune activity of DDO was measured by lymphocyte proliferation, macrophage phagocytic function, NK cell activity, delayed type hypersensitivity reaction, hemolytic plaque number, sIgA content and immune organ index. The results showed that a total of 51 compounds were identified. In addition, DDO could significantly promote the lymphocyte proliferation, improve macrophage phagocytic ability, NK cell activity, hemolytic plaque number, sIgA content and immune organ index compared with control group, and the medium dose possessed the best efficacy (P＜0.05). These results indicated that DDO could enhance the immunity of mice.

Threat analysis relies on knowledge bases that contain a large number of security entities.The scope and impact of security threats and risks are evaluated by modeling threat sources, attack capabilities, attack motivations, and threat paths, taking into consideration the vulnerability of assets in the system and the security measures implemented.However, the lack of entity relations between these knowledge bases hinders the security event tracking and attack path generation.To complement entity relations between CAPEC and ATT＆amp;CK techniques and enrich threat paths, an entity correlation prediction method called WGS was proposed, in which entity descriptions were analyzed based on word embedding and a graph convolution network.A Word2Vec model was trained in the proposed method for security domain to extract domain-specific semantic features and a GCN model to capture the co-occurrence between words and sentences in entity descriptions.The relationship between entities was predicted by a Siamese network that combines these two features.The inclusion of external semantic information helped address the few-shot learning problem caused by limited entity relations in the existing knowledge base.Additionally, dynamic negative sampling and regularization was applied in model training.Experiments conducted on CAPEC and ATT＆amp;CK database provided by MITRE demonstrate that WGS effectively separates related entity pairs from irrelevant ones in the sample space and accurately predicts new entity relations.The proposed method achieves higher prediction accuracy in few-shot learning and requires shorter training time and less computing resources compared to the Bert-based text similarity prediction models.It proves that word embedding and graph convolutional network based entity relation prediction method can extract new entity correlation relationships between attack patterns and techniques.This helps to abstract attack techniques and tactics from low-level vulnerabilities and weaknesses in security threat analysis.

Liver fibrosis is a result of chronic liver disease; without treatment, it can progress to cirrhosis and even liver cancer. The occurrence and development of liver fibrosis is closely related to the activation of hepatic stellate cells (HSCs). Many events, including induction of the hedgehog signal and angiogenesis, occur during HSCs activation. Transforming growth factor-β (TGF-β) acts as a critical regulator of HSCs activation. We found that Dendrobium officinale polysaccharide (DOP) markedly reduced the level of hepatic fibrosis in carbon tetrachloride (CCl4)-treated rats and TGF-β-stimulated HSC-T6 cells. DOP significantly inhibited smooth (SMO) protein expression and Gli1 transcription into the nucleus. Moreover, DOP inhibited the expression of angiogenesis-related proteins and angiogenesis markers. In conclusion, our results indicated that DOP might ameliorate CCl4-induced liver fibrosis and TGF-β-induced HSC-T6 cells activation by the SMO/Gli 1 pathway, suggesting that DOP could be used as a potential functional food.

Abstract Chimeric antigen receptor T-cell (CAR-T) therapy has demonstrated potent clinical efficacy in the treatment of hematopoietic malignancies. However, the application of CAR-T in solid tumors has been limited due in part to the expression of inhibitory molecules in the tumor microenvironment, leading to T-cell exhaustion. To overcome this limitation, we have developed a synthetic T-cell receptor (TCR) that targets programmed death-ligand 1 (PD-L1), a molecule that is widely expressed in various solid tumors and plays a pivotal role in T-cell exhaustion. Our novel TCR platform is based on antibody-based binding domain, which is typically a single-chain variable fragment (scFv), fused to the γδ TCRs (TCRγδ). We have utilized the T-cell receptor alpha constant (TRAC) locus editing approach to express cell surface scFv of anti-PD-L1, which is fused to the constant region of the TCRγ or TCRδ chain in activated T cells derived from peripheral blood mononuclear cells (PBMCs). Our results indicate that these reconfigured receptors, both γ-TCRγδ and δ-TCRγδ, have the capability to transduce signals, produce inflammatory cytokines, degranulate and exert tumor killing activity upon engagement with PD-L1 antigen in vitro. Additionally, we have also shown that γ-TCRγδ exerted superior efficacy than δ-TCRγδ in in vivo xenograft model.

Context Bushen Yiyuan recipe (BYR) is an effective Chinese prescription with antifatigue and antioxidation effects.Objective The effects of BYR on testosterone synthesis in rat Leydig cells with exercise-induced low serum testosterone levels (EILST) are assessed.Materials and methods Thirty-two Sprague-Dawley rats were chronically trained for 6 weeks to establish an EILST model. EILST rats were divided into model (physiological saline), EFE (700 mg/kg ethanol extract of Epimedii folium, the dried leaves of Epimedium brevicornu Maxim [Berberidaceae]), and BYR groups (350 and 700 mg/kg) for 6 weeks. Expression of HMG-CoA, LDL-R, SR-BI, STAR and CYP11A1 were quantified by RT qPCR and Western blots.Results Compared with the model group (115.52 ± 13.05 μg/dL; 67.83 ± 14.29; 0.32 ± 0.04; 0.33 ± 0.02; 0.38 ± 0.01), serum testosterone, testosterone/cortisol ratio, HMG-CoA, STAR and CYP11A1 relative protein expression significantly increased in low-dose BYR (210.60 ± 5.08 μg/dL; 119.38 ± 13.02; 0.47 ± 0.01; 0.46 ± 0.03; 0.46 ± 0.02), high-dose BYR (220.57 ± 14.71 μg/dL; 124.26 ± 14.79; 0.49 ± 0.02; 0.42 ± 0.03; 0.51 ± 0.02), and EFE groups (206.83 ± 5.54 μg/dL; 119.53 ± 25.04; 0.45 ± 0.02; 0.42 ± 0.02; 0.41 ± 0.02) (all p

In order to optimize the sulfite gold plating process and obtain gold - plated layer with uniform thickness and high density, the sulfite cyanide - free gold plating solution was used in vibration barrel plating. The effects of total content of plating solution, loading capacity, roller speed, vibration frequency, current density and other factors on the quality of gold - plated layer were studied, and the suitable process conditions were determined as follows: a gold content of 10～20 g/L, a loading capacity of 1/6～1/3 of the barrel volume, a barrel rotating rate of 15～20 r/min，a vibration frequency of once for every 5 min, and a current density of 0.1～0.4 A/dm2. Through a comparison between the properties of the gold - plated layers prepared by vibration barrel plating and hanging gold plating, it was found that the gold - plated layer prepared by vibration barrel plating had better compactness, better thickness uniformity (2～3 times higher), and had no obvious difference in appearance, roughness and gloss with that prepared by hanging gold plating.

Objective: Swertiamarin (STM) belongs to iridoid class of compounds, and the heat-transformed products (HTPS) are produced by STM in the process of drug processing. The purpose of this study was to explore the protective effect and mechanism of STM or HTPS on acetaminophen (APAP)-induced hepatotoxicity. Methods: Mice and L-O2 cells were given APAP to establish the hepatotoxicity model in vivo and in vitro. The effects of STM or HTPS on oxidative stress, inflammation, and apoptosis induced by APAP were evaluated, with N-acetylcysteine (NAC) as a positive control. Results: STM or HTPS reduced the APAP-induced apoptosis of L-O2 cells and significantly alleviated the liver injury index induced by APAP (p

More and more electronic devices are integrated into the modern vehicles with the development of intelligent vehicles.There are various design flaws and vulnerabilities hidden in a large number of hardware, firmware and software.Therefore, the vulnerabilities of intelligent vehicles have become the most important factor affecting the vehicle safety.The safety of vehicles is seriously affected by the disclosure of a large number of vulnerabilities, and the wide application of smart cars is also restricted.Vulnerability management is an effective method to reduce the risk of vulnerabilities and improve vehicle security.And vulnerability scoring is one the important step in vulnerability management procedure.However, current method have no capability assessing automotive vulnerabilities reasonably.In order to handle this problem, a vulnerability scoring model for intelligent vehicles was proposed, which was based on CVSS.The attack vector and attack complexity were optimized, and property security, privacy security, functional safety and life safety were added to characterize the possible impact of the vulnerabilities according to the characteristics of intelligent vehicles.With the machine learning method, the parameters in CVSS scoring formula were optimized to describe the characteristics of intelligent vehicle vulnerabilities and adapt to the adjusted and new added weights.It is found in case study and statistics that the diversity and distribution of the model are better than CVSS, which means the model can better score different vulnerabilities.And then AHP is used to evaluate the vulnerability of the whole vehicle based on the vulnerability score of the model, a score is given representing the risk level of whole vehicle.The proposed model can be used to evaluate the severity of information security vulnerabilities in intelligent vehicles and assess the security risks of the entire vehicle or part of the system reasonably, which can provide an evidence for fixing the vulnerabilities or reinforcing the entire vehicle.

Aiming at the problems of low calculation efficiency and conservative optimization design method of link in multi-arm mechanical arm system， taking the concrete pump truck as a typical engineering equipment component， the cylinder and link between the arm units are considered as one link group， the ANSYS APDL language is applied for the parametric modeling， and the optimization analysis is carried out under multiple working conditions， the optimal structure model of the link group is obtained. The feasibility of the calculation method is verified by the structural stress test. The results show that， the calculation efficiency of links is greatly improved with the methods of parametric modeling and optimal design， a feasible and effective method is provided for the design of links in the multi-arm manipulator system， and an important reference is provided for the design of components with similar structures.

Abstract Background Effective stem cell therapy is dependent on the stem cell quality that is determined by their differentiation potential, impairment of which leads to poor engraftment and survival into the target cells. However, limitations in our understanding and the lack of reliable markers that can predict their maturation efficacies have hindered the development of stem cells as an effective therapeutic strategy. Our previous study identified CD10, a pro-adipogenic, depot-specific prospective cell surface marker of human adipose-derived stem cells (ASCs). Here, we aim to determine if CD10 can be used as a prospective marker to predict mature adipocyte quality and play a direct role in adipocyte maturation. Methods We first generated 14 primary human subject-derived ASCs and stable immortalized CD10 knockdown and overexpression lines for 4 subjects by the lentiviral transduction system. To evaluate the role of CD10 in adipogenesis, the adipogenic potential of the human subject samples were scored against their respective CD10 transcript levels. Assessment of UCP1 expression levels was performed to correlate CD10 levels to the browning potential of mature ASCs. Quantitative polymerase chain reaction (qPCR) and Western blot analysis were performed to determine CD10-dependent regulation of various targets. Seahorse analysis of oxidative metabolism and lipolysis assay were studied. Lastly, as a proof-of-concept study, we used CD10 as a prospective marker for screening nuclear receptor ligands library. Results We identified intrinsic CD10 levels as a positive determinant of adipocyte maturation as well as browning potential of ASCs. Interestingly, CD10 regulates ASC’s adipogenic maturation non-canonically by modulating endogenous lipolysis without affecting the classical peroxisome proliferator-activated receptor gamma (PPARγ)-dependent adipogenic pathways. Furthermore, our CD10-mediated screening analysis identified dexamethasone and retinoic acid as stimulator and inhibitor of adipogenesis, respectively, indicating CD10 as a useful biomarker for pro-adipogenic drug screening. Conclusion Overall, we establish CD10 as a functionally relevant ASC biomarker, which may be a prerequisite to identify high-quality cell populations for improving metabolic diseases.

Abstract Background Prenatal anxiety has been a significant public health issue globally, leading to adverse health outcomes for mothers and children. The study aimed to evaluate the sociodemographic characteristics, knowledge, attitudes, and practices (KAP), and anxiety level of pregnant women during the coronavirus disease 2019 (COVID-19) epidemic in Wuhan and investigate the influencing factors for prenatal anxiety in this specific context. Methods Pregnant subjects’ KAP towards COVID-19 and their sociodemographics and pregnancy information were collected using questionnaires. The Zung Self-Rating Anxiety Scale (SAS) was used to assess anxiety status. Factors associated with the level of prenatal anxiety were analyzed by Pearson’s chi-square test and multivariable logistic regression analyses. Results The prenatal anxiety prevalence in this population was 20.8%. The mean score of knowledge was 13.2 ± 1.1 on a 0 ~ 14 scale. The attitudes and practices data showed that 580/ 817 (71.0%) were very concerned about the news of COVID-19, 455/817 (55.7%) considered the official media to be the most reliable information source for COVID-19, and 681/817 (83.4%) were anxious about the possibility of being infected by COVID-19. However, only 83/817 (10.2%) worried about contracting COVID-19 infection through the ultrasound transducer during a routing morphology scan. About two-thirds 528/817 (64.6%) delayed or canceled the antenatal visits. Approximately half of them 410/817 (50.2%) used two kinds of personal protection equipments (PPEs) during hospital visits. Logistic regression analysis revealed that the influential factors for prenatal anxiety included previous children in the family, knowledge score, media trust, worry of contracting the COVID-19 infection and worry about getting infected with COVID-19 from the ultrasound probe antenatal care (ANC) schedule. Conclusion Prenatal anxiety was prevalent among pregnant women in Wuhan during the outbreak of COVID-19. The current findings identified factors associated with the level of prenatal anxiety that could be targeted for psychological care.

Abstract Background The association of myocardial bridge (MB) with cardiovascular risk and the possible cardiovascular risk factors remain unclear. This study aimed to explore the clinical characteristics and related factors of coronary stenosis proximal to an MB. Methods This was a retrospective study of patients with symptoms of coronary atherosclerotic heart disease admitted between 10/2011 and 12/2014 to the Emergency and Cardiology Department of Bayannur Hospital, who underwent selective coronary angiography (SCAG). The patients were assigned to the non-stenosis and stenosis groups according to whether coronary stenosis was proximal to the MB. Results Among 244 patients with MB and cardiovascular symptoms, 91 (37.3%) had stenosis proximal to the MB. Compared with the non-stenosis group, there were more males (80.2% vs. 55.6%, P

With the development of automobile intelligence, the security of the Internet of Vehicles has become a key factor that affects the development of intelligent vehicles. However, existing security risk analysis methods for the IoV either focus only on certain levels, such as the component level, or perform only a static analysis. This paper proposes a dynamic attack graph generation method for the IoV to identify and visually display the security risks caused by the associated vulnerabilities in an IoV system. First, using the actual architecture of the IoV, this paper shows how to model the security elements and their relationships in the IoV system and proposes a network security ontology model for this system. Second, it shows how to construct a reasoning rule base according to the causal relationship between the vulnerabilities using the Semantic Web Rule Language Finally, in view of the rapid change in the network topology of the IoV, a dynamic attack graph generation algorithm based on an ontology reasoning engine is proposed, which can effectively reduce the overhead caused by the changes in the attack graph. The effectiveness of the algorithm is demonstrated through an actual security event scenario and a constructed scenario. The experimental results show that the algorithm can dynamically and accurately display the network attack graph of the IoV. The proposed method is helpful in globally analyzing the threat caused by the combined exploitation of the vulnerabilities in an IoV system and risk management.

Background We aimed to construct a novel epithelial-mesenchymal transition (EMT)-related gene pairs (ERGPs) signature to predict overall survival (OS) in skin cutaneous melanoma (CM) patients. Methods Expression data of the relevant genes, corresponding clinicopathological parameters, and follow-up data were obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis was utilized to identify ERGPs significantly associated with OS, and LASSO analysis was used to identify the genes used for the construction of the ERGPs signature. The optimal cutoff value determined by the receiver operating characteristic curve was used to classify patients into high-risk and low-risk groups. Survival curves were generated using the Kaplan–Meier method, and differences between the two groups were estimated using the log-rank test. The independent external datasets GSE65904 and GSE19234 were used to verify the performance of the ERGPs signature using the area under the curve (AUC) values. In addition, we also integrated clinicopathological parameters and risk scores to develop a nomogram that can individually predict the prognosis of patients with CM. Results A total of 104 ERGPs related to OS were obtained, of which 21 ERGPs were selected for the construction of the signature. All CM patients were stratified into high-and low-risk groups based on an optimal risk score cutoff value of 0.281. According to the Kaplan–Meier analysis, the mortality rate in the low-risk group was lower than that in the high-risk group in the TCGA cohort (P

Objective:To explore the clinical presentation and molecular genetic characteristics of a cohort of congenital hyperinsulinism (CHI) patients from southern China and also to explore the most appropriate therapeutic approaches.Methods:We retrospectively reviewed a cohort of 65 children with CHI. Mutational analysis was performed for KCNJ11 and ABCC8 genes. The GLUD1 gene was sequenced in patients with hyperammonaemia. GCK gene sequencing was performed in those patients with no mutation identified in the ABCC8, KCNJ11 or GLUD1 genes.Results:ABCC8 mutations were identified in 16 (25%) of the cohort, GLUD1 mutations were identified in five children, and no KCNJ11 or GCK mutations were identified. Moreover, some unique features of ABCC8 gene mutations in southern Chinese CHI patients were found in this study. The most common mutation was a deletion/insertion mutation p.Thr1042GlnfsX75 was found in five unrelated patients, which possibly represents a relatively common mutation in southern China. Five novel ABCC8 mutations were detected. The mutations were p.Phe5SerfsX72, p.Gln273ArgfsX85, p.Leu724del, p.Asp1447Gly and IVS 25-1G>T. Five compound heterozygous mutations of ABCC8 gene were identified in this study, and three of these patients were diazoxide-responsive. Forty patients were diazoxide-responsive, 13 patients were diazoxide-unresponsive and 12 patients received dietary treatment only. A pancreatectomy was performed in 10 patients who were unresponsive to medical treatment.Conclusion:To the best of our knowledge, this is the first study of CHI in south China. Mutations in ABCC8 are the most common causes of CHI in this cohort. Diazoxide and dietary treatment were effective in most patients. Multicentre studies are necessary to obtain the long-term follow-up characteristics of such patients at a national level.

ARIA is a Korean standard block cipher,which is flexible to provide security for software and hardware implementation.Since its introduction,some research of fault analysis is devoted to attacking the last two rounds of ARIA.It is an open problem to know whether provoking faults at some former rounds of ARIA allowed recovering the secret key.An answer was given to solve this problem by showing a novel integral differential fault analysis on two rounds earlier of ARIA.The mathematical analysis and simulating experiments show that the attack can successfully recover its secret key by fault injections.The results in this study describe that the integral fault analysis is a strong threaten to the security of ARIA.The results are beneficial to the analysis of the same type of other block ciphers.

The aim of the present study was to isolate phytochemicals from Mangifera indica L. leaves and to screen their bioactivities. Four benzophenone derivatives were isolated and characterized, two of which were new compounds, namely manindicins A and B. All the four compounds significantly inhibited the cellular ROS amount of H2O2-induced HepG2 cells. Stimulation index of spleen cells showed that manindicins A and B had a good and similar immunosuppressive activity, while mangiferin and norathyriol exhibited relatively weaker activity. Norathyriol showed the strongest inhibitory effect on α-glucosidase with an IC50 of 4.22 ± 0.19 μg/mL, which was lower than that of acarbose (16.28 ± 1.22 μg/mL). However, the manindicins A and B had weak inhibition of α-glucosidase. The present work suggests that M. indica leaves can be used potentially as functional-food supplement for improving human health.

Abstract The rapid development of wellness smart devices and apps, such as Fitbit Coach and FitnessGenes, has triggered a wave of interaction on social networks. People communicate with and follow each other based on their wellness activities. Though such IoT devices and data provide a good motivation, they also expose users to threats due to the privacy leakage of social networks. Anonymization techniques are widely adopted to protect users’ privacy during social data publishing and sharing. However, de-anonymization techniques are actively studied to identify weaknesses in current social network data-publishing mechanisms. In this paper, we conduct a comprehensive analysis on the typical structure-based social network de-anonymization algorithms. We aim to understand the de-anonymization approaches and disclose the impacts on their application performance caused by different factors, e.g., topology properties and anonymization methods adopted to sanitize original data. We design the analysis framework and define three experiment environments to evaluate a few factors’ impacts on the target algorithms. Based on our analysis architecture, we simulate three typical de-anonymization algorithms and evaluate their performance under different pre-configured environments.

Abstract Objective The correlation of serum fibroblast growth factor 23 (FGF-23) and Klotho protein levels with bone mineral density (BMD) in maintenance hemodialysis (MHD) patients was analyzed. Methods Between January 2015 and November 2015, 125 MHD patients in our hospital were enrolled. Dual-energy X-ray absorptiometry was used to examine the BMD in the femoral neck and lumbar spine of MHD patients. The patients were divided into three groups: a normal bone mass group, an osteopenia group, and an osteoporosis group. An ELISA was performed to measure serum FGF-23, Klotho protein, and 1,25(OH)2VitD3 levels. Other parameters, including calcium (Ca), phosphorus (P), and parathyroid hormone, were also measured. Results Of the 125 MHD patients, 82.40% of patients had femoral neck osteopenia, and 56.00% of patients had lumbar spinal osteopenia. The serum FGF-23 level was highest in the osteoporosis group. However, there was no significant difference in serum FGF-23 levels among the three groups, depending on femoral neck and lumbar spinal BMD (P > 0.05). Spearman’s correlation analysis also pointed to a lack of correlation between serum FGF-23 levels and BMD. Among the three groups, there were significant differences in serum Klotho protein levels and femoral neck BMD (P