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Background Adenosine deaminase (ADA) is essential for the differentiation and maturation of lymphocytes, while lymphocytes infiltration in thyroid tissue is a vital pathological feature of Graves’ disease (GD). The aim of the present study was to compare the concentration of ADA between healthy controls (HC) and patients with GD, and evaluate the association between ADA and GD. Methods A total of 112 GD patients and 77 matched HC were enrolled in this study. Each participant was examined for thyroid hormones and autoantibodies, ADA concentration, and thyroid ultrasonography. Results Serum ADA levels in GD patients were significantly higher than that in HC subgroup (P < 0.001). In GD patients, serum ADA levels were positively associated with serum-free triiodothyronine (FT3), free thyroxine (FT4), thyroid peroxidase antibody (TPOAb), thyroid-stimulating hormone receptor antibody (TRAb) levels, and total thyroid gland volume (thyroid VolT) and negatively associated with serum thyroid-stimulating hormone receptor (TSH) levels (all P < 0.05). There were no similar correlations in the HC subgroup. Multiple linear regression analysis suggested that serum TSH, FT3, and ADA levels played an important role in serum TRAb levels. Conclusions Our results demonstrated that serum ADA levels were closely associated with GD.

The aim of the present study was to evaluate the association between adenosine deaminase (ADA) levels and diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D). In this study, patients with T2D who had been screened for DKD were recruited. Patients with an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 or a urinary albumin-to-creatinine ratio (UACR) ≥ 30 mg/g for 3 months were identified as having DKD. The prevalence of DKD was 13.3%, and the range of serum ADA levels was 4–37 U/L. Serum ADA levels were positively associated with cystatin C levels and UACR (r = 0.295 and r = 0.302, respectively, both P < 0.05) and negatively associated with eGFR (r = −0.342, P < 0.05). The proportion of participants with DKD increased significantly from 3.8% in the first tertile (T1) to 13.6% in the second tertile (T2) and 25.9% in the third tertile (T3) of ADA (P for trend < 0.001). After adjusting for clinical risk factors for DKD via multiple logistic regression, the corresponding odds ratios (ORs) of DKD for the participants in T2 and T3 vs those in T1 of ADA were 5.123 (1.282–20.474) and 10.098 (1.660–61.431), respectively. Receiver operating characteristic (ROC) analysis revealed that the optimal cutoff value of ADA to indicate DKD was 10 U/L. Its corresponding sensitivity and specificity were 75.5 and 56.4%, respectively. Our results demonstrated that serum ADA levels were closely associated with DKD and partly reflect the risk of DKD in patients with T2D.

Background Deterioration of sleep quality has been reported to contribute to the incidence of diabetes and may be responsible for glycemic status in diabetes. The present study explored the relationship between sleep quality and glycemic variability in patients with type 2 diabetes (T2D). Methods We recruited 111 patients with T2D for this cross-sectional study. Each patient underwent flash glucose monitoring for 14 days to obtain glycemic variability parameters, such as standard deviation of glucose (SD), coefficient of variation of glucose (CV), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), and time in glucose range of 3.9–10 mmol/L (TIR3.9–10). After 14 days of flash glucose monitoring, each patient received a questionnaire on the Pittsburgh Sleep Quality Index (PSQI) to evaluate subjective sleep quality. HbA1c was also collected to assess average glucose. Results HbA1c was comparable among the subgroups of PSQI score tertiles. Across ascending tertiles of PSQI scores, SD, CV and MAGE were increased, while TIR3.9–10 was decreased (p for trend p for trend = 0.090). Moreover, PSQI scores were positively correlated with SD, CV, MODD and MAGE (r = 0.322, 0.361, 0.308 and 0.354, respectively, p < 0.001) and were inversely correlated with TIR3.9–10 (r = − 0.386, p < 0.001). After adjusting for other relevant data by multivariate linear regression analyses, PSQI scores were independently responsible for SD (β = 0.251, t = 2.112, p = 0.041), CV (β = 0.286, t = 2.207, p = 0.033), MAGE (β = 0.323, t = 2.489, p = 0.018), and TIR3.9–10 (β = − 0.401, t = − 3.930, p < 0.001) but not for MODD (β = 0.188, t = 1.374, p = 0.177). Conclusions Increased glycemic variability assessed by flash glucose monitoring was closely associated with poor subjective sleep quality evaluated by the PSQI in patients with T2D.

Background Prolonged heart rate-corrected QT (QTc) interval may reflect poor prognosis of patients with type 2 diabetes (T2D). Serum adenosine deaminase (ADA) levels are related to hyperglycemia, insulin resistance (IR) and inflammation, which may participate in diabetic complications. We investigated the association of serum ADA levels with prolonged QTc interval in a large-scale sample of patients with T2D. Methods In this cross-sectional study, a total of 492 patients with T2D were recruited. Serum ADA levels were determined by venous blood during fasting. QTc interval was estimated from resting 12-lead ECGs, and prolonged QTc interval was defined as QTc > 440 ms. Results In this study, the prevalence of prolonged QTc interval was 22.8%. Serum ADA levels were positively associated with QTc interval ( r = 0.324, P < 0.0001). The proportion of participants with prolonged QTc interval increased significantly from 9.2% in the first tertile (T1) to 24.7% in the second tertile (T2) and 39.0% in the third tertile (T3) of ADA ( P for trend < 0.001). After adjusting for other possible risk factors by multiple linear regression analysis, serum ADA level was still significantly associated with QTc interval ( β = 0.217, t = 3.400, P < 0.01). Multivariate logistic regression analysis showed that female (OR 5.084, CI 2.379–10.864, P < 0.001), insulin-sensitizers treatment (OR 4.229, CI 1.290–13.860, P = 0.017) and ADA (OR 1.212, CI 1.094–1.343, P < 0.001) were independent contributors to prolonged QTc interval. Conclusions Serum ADA levels were independently associated with prolonged QTc interval in patients with T2D.

The aim of this study was to determine the relationship between glucose fluctuation and global registry of acute coronary events (GRACE) risk score in patients with acute coronary syndrome (ACS) and abnormal glucose metabolism using continuous glucose monitoring system (CGMS). A total of 76 patients with ACS admitted into coronary care unit (CCU) were divided into two groups based on their blood glucose level and were further divided into subgroups based on GRACE risk score. A CGMS was used to real-time monitor blood glucose for 72 h in all patients after admitted into CCU. Twenty-four-hour mean blood glucose (24-h MBG) and 24-h mean amplitude of glycemic excursion (24-h MAGE) were calculated. Among the 76 patients, 52 patients had abnormal glucose metabolism. Among the 52 patients, there were 8 patients in low-risk group, 19 patients in moderate-risk group, and 25 in high-risk group. Among the 24 patients with normal glucose metabolism, there were 6 patients in the low-risk group, 6 patients in the moderate-risk group, and 12 in the high-risk group based on GRACE score. For patients with abnormal glucose metabolism, the 24-h MBG and 24-h MAGE of moderate- and high-risk groups were significantly higher than that of the low-risk group, which were not found in patients with ACS and normal glucose metabolism. High prevalence of abnormal glucose metabolism was found in ACS patients admitted into CCU and larger blood glucose fluctuation is associated with moderate and high GRACE risk scores in patients with ACS and abnormal glucose metabolism.

To determine the clinical non-inferiority of recombinant glargine-Basalin vs glargine-Lantus, in treatment of type 2 diabetes mellitus (T2DM) using continuous glucose monitoring system (CGMS). One hundred patients with T2DM were recruited. They were either regularly taking Basalin (Basalin group) or Lantus (Lantus group) (n = 50 each). CGMS was employed to real-time monitor blood glucose profile for 4 days (from day 1 to day 5). To exclude the effect of patient background, the study design was to have a blinded crossover from glargine-Basalin to glargine-Lantus on day 3, and vice versa. 24-hour mean blood glucose (24hMBG), 24-hour standard deviation of blood glucose (24hSDBG), 24-hour mean amplitude of glycemic excursion (24hMAGE), and number of glycemic excursion (NGE) every 24 h (24hNGE) were calculated for each glargine from 100 patients. No significant difference of 24hMBG, 24hSDBG, 24hMAGE, and 24hNGE (p > 0.05 for all) was found between Basalin and Lantus treatments. The glucose area under the curve and time when blood glucose was below 3.9 mmol/L, between 3.9 and 10.0 mmol/L, or above 10.0 mmol/L were similar between Basalin and Lantus treatment. The frequency of hypoglycemic episodes was also similar. However, the mean cost of Basalin was only 72% of Lantus’s in one treatment course. Glargine-Basalin is non-inferior in clinical efficacy compared to glargine-Lantus. In view of the large difference in the cost of glargine-Basalin, it would be much more cost-effective for our patients.

Background and Aims.To evaluate the effect of adding acarbose on glycemic excursions measured by continuous glucose monitoring system (CGMS) in patients with type 2 diabetes mellitus (T2DM) already on insulin therapy.Materials and Methods.This was an opened and unblended study. 134 patients with T2DM were recruited. After initial rapidly corrected hyperglycaemia by continuous subcutaneous insulin infusion (CSII) for 7 d, a 4–6-day premixed insulin titration period subsequently followed. Patients were then randomized 1 : 1 to acarbose plus insulin group or insulin therapy group for 2 weeks. CGMS was used to measure glucose fluctuations for at least 3 days after therapy cessation.Results. Patients in acarbose plus insulin group achieved a significant improvement of MAGE compared to that of insulin therapy only group (5.56±2.16versus7.50±3.28 mmol/L,P=0.044), accompanied by a significant decrease in the incremental AUC of plasma glucose concentration above 10.0 mmol/L (0.5[0.03,0.9]versus 0.85[0.23,1.4] mmol/L per day,P=0.037).Conclusions. Add-on acarbose to insulin therapy further improves glucose fluctuation in patients with T2DM. This study was registered with ClinicalTrials.gov registration numberChiCTR-TRC-11001218.

This paper proposes an evolutionary fuzzy lead-lag control approach for coordinated control of flexible AC transmission system (FACTS) devices in a multi-machine power system. The FACTS devices used are a thyristor-controlled series capacitor (TCSC) and a static var compensator (SVC), both of which are equipped with a fuzzy lead-lag controller to improve power system dynamic stability. The fuzzy lead-lag controller uses a fuzzy controller (FC) to adaptively determine the parameters of two lead-lag controllers at each control step according to the deviations of generator rotor speeds. This paper proposes an Advanced Continuous Ant Colony Optimization (ACACO) algorithm to optimize all of the free parameters in the FC, which avoids the time-consuming task of parameter selection by human experts. The effectiveness and efficiency of the proposed evolutionary fuzzy lead-lag controller for oscillation damping control is verified through control of a multi-machine power system and comparisons with other lead-lag controllers and various population-based optimization algorithms.

This paper determined Hg and Cd contents through collecting the surface soil samples in Nanjing Liuhe Chemical Industry Park and its surrounding areas, analyzed the spatial distribution characteristics of Hg and Cd in the study area by means of ordinary Kriging, and carried out quantitative analysis for the impact of chemical industry park on the accumulation of soil heavy metals through introducing contribution rate. The results show that the chemical industry park is one of the important causes of the accumulation of Hg and Cd in the surrounding soils. In space, the closer the site is to the industrial park, the higher the accumulative content is. Wind direction has a significant effect on the diffusion of Hg, affected most greatly on the northwest, which is located downwind, with a contribution rate of 85.47%, while wind direction has no significant effect on the diffusion of Cd, affected most greatly on the north, with a contribution rate of 29.37%.

Image retake of radiological examinations not only increases the risk of radiation exposure of the patients, but also wastes the medical resource and degrades the quality of services of the hospitals. This study aimed at discovering factors affecting image retake of general digital radiography for setting guidelines to reduce the image retaking rate. A total of 98,503 general X-ray images retrieved from the picture archiving and communication system database of a medical center in central Taiwan were analyzed. The results showed that the total retaking rate was 4.89% with the position error (56.05%) was the main factor causing image retakes and chest examination showed the highest frequency (1544 cases). On the other hand, skull/face exhibited the highest retaking rate (9.81%) among various types of examinations. After discovering the factors affecting the image retaking rate, suitable guidelines were proposed and introduced. The image retake rate had been significantly reduced to 4.38% and 3.57% 1 month and 6 months, respectively, after the introduction of guidelines. In conclusion, image retake analysis is a quality indicator and is effective for quality assurance of digital radiology. Regular analysis of image retake can find factors inducing image retake and is useful for designing guidelines to reduce the image retake rate.

This paper proposes a Self-Evolving Interval Type-2 Fuzzy Neural Network (SEIT2FNN) for nonlinear systems identification. The SEIT2FNN has both on-line structure and parameter learning abilities. The antecedent parts in each fuzzy rule of the SEIT2FNN are interval type-2 fuzzy sets and the fuzzy rules are of the Takagi-Sugeno-Kang (TSK) type. An on-line clustering method is proposed to generate fuzzy rules which flexibly partition the input space. For parameter learning, the consequent part parameters are tuned by a rule-ordered Kalman filter algorithm for high accuracy learning performance. The antecedent part parameters are learned by gradient descent algorithms. Comparisons with identification using other type-1 and type-2 fuzzy systems verify the performance of the SEIT2FNN.

Indirect immunofluorescence technique applied on HEp-2 cell substrates provides the major screening method to detect ANA patterns in the diagnosis of autoimmune diseases. Currently, the ANA patterns are mostly inspected by experienced physicians to identify abnormal cell patterns. The objective of this study is to design a computer-assisted system to automatically detect cell patterns of IIF images for the diagnosis of autoimmune diseases in the clinical setting. The system simulates the functions of modern flow cytometer and provides the diagnostic reports generated by the system to the technicians and physicians through the radar graphs, box-plots, and tables. The experimental results show that, among the IIF images collected from 17 patients, 6 were classified as coarse-speckled, 3 as diffused, 2 as discrete-speckled, 1 as fine-speckled, 2 as nucleolar, and 3 as peripheral patterns, which were consistent with the patterns determined by the physicians. In addition to recognition of cell patterns, the system also provides the function to automatically generate the report for each patient. The time needed for the whole procedure is less than 30 min, which is more efficient than the manual operation of the physician after inspecting the ANA IIF images. Besides, the system can be easily deployed on many desktop and laptop computers. In conclusion, the designed system, containing functions for automatic detection of ANA cell pattern and generation of diagnostic report, is effective and efficient to assist physicians to diagnose patients with autoimmune diseases. The limitations of the current developed system include (1) only a unique cell pattern was considered for the IIF images collected from a patient, and (2) the cells during the process of mitosis were not adopted for cell classification.

Since a battery energy storage system (BES) can provide fast active power compensation, it also can be used to improve the performance of load-frequency control. In this paper a new incremental model of a BES is presented and merged into the load-frequency control of a power system. A comprehensive digital computer model of a two-area interconnected power system including governor deadband and generation rate constraint is employed for a realistic response. Computer simulations show that the BES is very effective in damping the oscillations caused by load disturbances. The BES model is suitable for charging mode and discharging mode operations. Optimization of controller gains is obtained by the second method of Lyapunov. >

This paper investigates the effect of a superconducting magnetic energy storage (SMES) unit on the repressing of torsional oscillations in a capacitor compensated power system. The IEEE Second Benchmark Model is employed. To increase the damping of torsional modes, an auxiliary controller, proportional-integral-derivative (PID) or lead-lag, is employed to control the power modulation of the SMES unit according to generator speed deviation. The gains of the proposed auxiliary controller are determined by a pole assignment method where the eigenvalues of the torsional modes are placed at a prespecified position. Eigenvalue analysis and computer simulations of the studied system show that the SMES unit provides adequate damping torque over a wide range of operating conditions. Stability investigation shows that the PID controller is better than the lead-lag controller. The SMES unit also ensures a stable system when one of the parallel lines is out of service.

This paper shows that a laser range finder and four artificial reflectors can be used to determine the position of a mobile robot in a three-dimensional (3D) working space provided that the four reflectors are not installed in the same plane. Moreover, a particle swarm optimization (PSO) algorithm is used to filter possible measuring errors. To show the feasibility and accuracy of the proposed method, experimental results are included for illustration.

Based on fuzzy control to adjust attractive factor and repulsive factor of potential function, a method is proposed to navigate a soccer robot from a given initial configuration to a ball and avoid an opponent robot. The potential field method has some problems that include oscillations in the presence of obstacles. Thus, this paper suggests use fuzzy control to adjust attractive factor and repulsive factor. By the attractive factor and repulsive factor of the potential function, the navigation path of the mobile robot is smooth and the shortest. To show the feasibility of the proposed method, the simulation results are included in the following illustrations.

This paper proposes the design of a Takagi-Sugeno-Kang (TSK)-type Recurrent Fuzzy Network (TRFN) using ant colony optimization in real space (ACO R ). The TRFN contains feedback loops in each rule. When the TRFN is applied to control a dynamic plant, no a priori knowledge of the plant order is necessary. Only the current state(s) and desired output(s) are fed as TRFN inputs. All of the free parameters in each recurrent rule are optimized using ACO R . The ACO R stores solutions in an archive and updates solutions using selection and Gaussian random sampling processes. The ACO R -designed TRFN is applied to control a dynamic plant for performance verification. Comparisons with other optimization algorithms verify the advantage of ACO R .

An evolutionary fuzzy system that automates the design of fuzzy systems by hybridizing multi-group genetic algorithm and particle swarm optimization, called F-MGAPSO, is proposed in this paper. By F-MGAPSO, we aim to simultaneously design the number of fuzzy rules and free parameters in a fuzzy system. In initial population, the number of rules encoded in each individual is randomly assigned, and the individuals with equal number of rules constitute the same group. Evolution of population consists of three major operations: group enhancement, variable-length individual crossover and mutation, where group enhancement is to enhance elites in each group by local version of particle swam optimization, respectively. To demonstrate the performance, F-MGAPSO is applied to fuzzy control of a nonlinear plant

This paper proposes a combination of on-line Clustering and Q-value based Genetic Algorithm learning scheme for Fuzzy network design (CQGAF) with reinforcements. The CQGAF fulfills GA based fuzzy network design under reinforcement learning environment where only weak reinforcement signals such as "success" and "failure" are available. In CQGAF, there are no fuzzy rules initially. They are generated automatically. The precondition part of a fuzzy network is online constructed by an aligned clustering-based approach. Simultaneously, the consequent part is designed by Q-value based genetic reinforcement learning. In CQGAF, evolution is performed immediately after the end of one trial in contrast to general GA where many trials are performed before evolution. The feasibility of CQGAF is demonstrated through simulations in cart-pole balancing problems with only binary reinforcement signals.

Power-system load-frequency control by fuzzy-PI (FPI) controller is proposed. During control, a fuzzy system is used to decide adaptively the proper proportional and integral gains of a PI controller according the area-control error and its change. To ease the design effort and improve the performance of the controller, design of the FPI controller by hybridising a genetic algorithm and particle-swarm optimisation, called FPI-HGAPSO, is proposed. FPI-HGAPSO is based on the hybrid of the genetic algorithm and particle-swarm optimisation. In FPI-HGAPSO, elites in the population of GAs are enhanced by particle-swarm optimisation and these enhanced elites are selected as parents for crossover and mutation operations. Simulations of the proposed evolutionary FPI-control approach on a multiarea interconnected power system with different kinds of perturbations are performed. The performance of the proposed approach is verified from simulations and comparisons.

A fuzzy-controller design by the hybrid of genetic algorithm and particle-swarm optimisation (F-HGAPSO) is employed for a thyristor-controlled series capacitor (TCSC) to improve the transient stability of flexible AC transmission systems (FACTS). According to the variation of rotation speed, a fuzzy controller decides an approximate series capacitance to achieve a better dynamic response of FACTS. To design the fuzzy controller, a new design approach, the F-HGAPSO, is proposed. F-HGAPSO introduces the concept of the maturing phenomenon in nature into the evolution of individuals originally modelled by a genetic algorithm. The maturing phenomenon is mimicked by particle-swarm optimisation, where individuals enhance themselves based on social interactions and their private cognition. Simulations and comparisons with other approaches have demonstrated the effectiveness and efficiency of the proposed F-HGAPSO.