[Veracity of using a visual chart with a testing distance of 2.5 meters for measurement of distance visual acuity in teenagers].

Objective: To compare the results of visual acuity testing for teenagers with visual acuity charts designed at 2.5-meter and 5-meter distances, and to investigate the accuracy of the 2.5-meter visual acuity chart. Methods: It was a self-control study. A total of 227 teenagers (454 eyes) with ametropia who came to the ophthalmic clinic of Peking Union Medical College Hospital from March 2019 to September 2019 were included. There were 123 males and 104 females aged (11.74±3.26) years. The vision examiners were trained in the same testing environment and passed the consistency test. Distance visual acuity of all participants was tested with charts designed at 2.5 meters and 5 meters in a 10-minute interval. According to the age (7-9, 10-12, 13-15 and 16-18 years old) and visual acuity (1.00-0.52, 0.40-0.30 and 0.22-0.10), the results of two kinds of visual acuity charts were compared. The testing order of the two visual charts was randomly determined. The visual acuity results were converted into logMAR values and compared. Paried t-student test was used to compare the difference between two charts, and Pearson correlation test was used to explore the correlation between the results of two charts. Results: The visual acuity of the right eye was 0.37±0.24 (logMAR) at 2.5 meters and 0.50±0.26 (logMAR) at 5 meters. The distance visual acuity measured with the 2.5-meter visual acuity chart was better (t=16.19, P<0.01). The visual acuity of the left eye was 0.36±0.23 (logMAR) at 2.5 meters and 0.45±0.23 (logMAR) at 5 meters (t=11.71, P<0.01). The differences between two charts were larger among teenagers with lower visual acuity (r=0.387,P<0.01). Conclusion: Under the same test conditions, the distance visual acuity measured with a 2.5-meter chart was significantly better than a 5-meter chart. The visual acuity chart designed at 2.5 meters was not an appropriate tool to measure distance vision in adolescents. (Chin J Ophthalmol, 2021, 57: 122-125).

A risk-adapted approach using US features and FNA results in the management of thyroid incidentalomas identified by 18F-FDG PET.

PURPOSE: To assess the risk of malignancy of thyroid incidentalomas found on 18F-FDG PET/CT by US features and cytologic results, and to evaluate the clinical usage of a combination of US features and cytology for post-FNA management of thyroid incidentalomas on 18F-FDG PET/CT. MATERIALS AND METHODS: From September 2006 to December 2008, 132 patients with 134 thyroid incidentalomas detected on 18F-FDG PET/CT who had undergone US and US-FNA were included in this study. We evaluated the malignancy rate of thyroid incidentalomas in different subgroups subdivided by US features and US-FNA cytology results. Several variables were compared between the benign and malignant group. RESULTS: The risk of malignancy was 58.2 % (78/132) in thyroid incidentalomas on 18F-FDG PET/CT. Age, gender, and tumor size were not significantly different between the malignant and benign group.  Malignancy rate of thyroid incidentalomas was significantly higher in the suspicious malignant (88.9 %) than in the probably benign group (11.3 %) on US (p < 0.001). Malignancy rates were high in thyroid nodules with "malignancy", "suspicious for malignancy", or "follicular neoplasm" on cytologic results, regardless of US features. However, malignancy rates of thyroid incidentalomas with "unsatisfactory" or "benign" results on cytology were higher in the suspicious malignant (75 %, 12.5 %, respectively) than in the probably benign (0 %) group on US.  CONCLUSIONS: This study demonstrated that the risk of malignancy was high in thyroid incidentalomas on 18F-FDG PET/CT even without suspicious US features. However, there was no malignancy in nodules with no suspicious US features and benign cytology. Based on these results, we concluded that US may not replace FNA in the diagnosis of PET incidentalomas, and that a follow-up may be considered of thyroid incidentalomas with benign cytology and no suspicious US features.

Modeling of brain D2 receptor occupancy-plasma concentration relationships with a novel antipsychotic, YKP1358, using serial PET scans in healthy volunteers.

YKP1358 is a novel serotonin (5-HT(2A)) and dopamine (D(2)) antagonist that, in preclinical studies, fits the general profile of an atypical antipsychotic. We conducted a D(2) receptor occupancy study with YKP1358 in healthy volunteers using positron emission tomography (PET) to measure the D(2) receptor occupancy of YKP1358 and to characterize its relationship to plasma drug concentrations. A single oral dose, parallel group, dose-escalation (100, 200, and 250 mg) study was performed in 10 healthy male volunteers with the PET radiotracer [(11)C]raclopride. The D(2) receptor occupancy of striatum was measured pre-dose, and at 2, 5, and 10 h after YKP1358 administration. Serial blood samples were taken for measurement of plasma YKP1358 concentrations. D(2) receptor occupancy by YKP1358 increased to 53-83% at 2 h, and then decreased afterwards, ranging from 40-64% at 5 h to 20-51% at 10 h. The YKP1358 dose-plasma concentration relationship exhibited extensive variability, but there was a good relationship between plasma concentrations and D(2) receptor occupancy that was well predicted by a sigmoid E(max) model using nonlinear mixed effects modeling. To our knowledge, this is the first study in which the relationship between plasma concentration and the biomarker of D(2) receptor occupancy was modeled using nonlinear mixed effects modeling. It is anticipated that these results will be useful in estimating for subsequent studies the initial doses of YKP1358 required to achieve a therapeutically effective range of D(2) receptor occupancy.

The effect of electrode arrangement on spectral distance measures for discrimination of EMG signals.

The proper electrode placement in applying cepstral coefficients for electromyogram (EMG) signature discrimination was investigated. We measured EMG signals of different motions with two electrode arrangements simultaneously. Electrode pairs were located separately on dominant muscles (S-type arrangement) and closely in the region between muscles (C-type arrangement). The application of the cepstral method to signals derived from a C-type arrangement did not achieve the same discrimination as with a S-type arrangement. We used a simplified model to elucidate the poor performance in C-type signals. The bandwidth of signals obtained from S-type placement is wider than that from C-type. Narrower bandwidth decreases the importance of the more discriminative parts for both autoregressive (AR) and cepstral methods. The cepstral method is more sensitive to such variation, so the degradation in performance is more serious for the cepstral method. Second, the amplitude of C-type signal is lower than the S-type; therefore, the C-type signal is more sensitive to the disturbance of noise, especially in the high-frequency band. As high-frequency noise increases, the spectral difference between different EMG signals is gradually dominated by the low-frequency part, which is more informative. Thus, the performances of both methods are improved with increasing high-frequency noise. The improving rate of the AR method is faster than the cepstral method; therefore, its discriminative efficiency may exceed the cepstral method with C-type arrangement.

[The structure correction of villosolside].

The crystal structure of villosolside was determined by X-ray diffraction, which led to some stereochemical amendment of the structure proposed in the article by Xu CJ et al. in Acta Pharm Sin 1985, 20:652.

Real-time implementation of electromyogram pattern recognition as a control command of man-machine interface.

The purpose of this study was to develop a real-time electromyogram (EMG) discrimination system to provide control commands for man-machine interface applications. A host computer with a plug-in data acquisition and processing board containing a TMS320 C31 floating-point digital signal processor was used to attain real-time EMG classification. Two-channel EMG signals were collected by two pairs of surface electrodes located bilaterally between the sternocleidomastoid and the upper trapezius. Five motions of the neck and shoulders were discriminated for each subject. The zero-crossing rate was employed to detect the onset of muscle contraction. The cepstral coefficients, derived from autoregressive coefficients and estimated by a recursive least square algorithm, were used as the recognition features. These features were then discriminated using a modified maximum likelihood distance classifier. The total response time of this EMG discrimination system was achieved about within 0.17 s. Four able bodied and two C5/6 quadriplegic subjects took part in the experiment, and achieved 95% mean recognition rate in discrimination between the five specific motions. The response time and the reliability of recognition indicate that this system has the potential to discriminate body motions for man-machine interface applications.

A comparative analysis of various EMG pattern recognition methods.

Identification of motions of the neck and shoulders using the electromyographic (EMG) signal was investigated in this study. Three discrimination methods, the Euclidean distance measure (EDM), the weighted distance measure (WDM) and the modified maximum likelihood method (MMLM), were used to compare the conventional autoregressive (AR) and cepstral coefficients with closely positioned (C-type) and separately located (S-type) electrode arrangements. Surface electrodes were bilaterally located on and between the sternocleidomastoid and the upper trapezius muscles. The EMG signals obtained during 20 repetitions of 10 motions were analyzed for each subject. Results from nine subjects showed that the mean recognition rate of the cepstral coefficients was at least 5% better than that of the AR coefficients for the S-type signals, while the improvement was less obvious for the C-type signals. The MMLM obtained the best discrimination results of the three discrimination methods. The S-type signals achieved higher recognition rates than the C-type signals in most cases. Among the various combinations of feature sets, classifiers and electrode arrangements proposed in this study, the combination of the cepstral coefficients and the MMLM with the S-type arrangement achieved the best discrimination efficiency. The proper choice of five of 10 motions raised the recognition rate to more than 97%.

The application of cepstral coefficients and maximum likelihood method in EMG pattern recognition.

A new technique for classifying patterns of movement via electromyographic (EMG) signals is presented. Two methods (conventional autoregressive (AR) coefficients and cepstral coefficients) for extracting features from EMG signals and three classification algorithms (Euclidean Distance Measure (EDM), Weighted Distance Measure (WDM), and Maximum Likelihood Method (MLM)) for discriminating signals representative of broad classes of movements are described and compared. These three classifiers are derived from Bayes classifier with some assumptions, the relationship among them is discussed. The conventional MLM is modified to avoid heavy matrix inversion. Six able-bodied subjects with two pairs of surface electrodes located on bilateral sternocleidomastoid and upper trapezius muscles were studied in the experiment. The EMG signals of 20 repetitions of 10 motions were analyzed for each subject. Experimental results showed that mean recognition rate of the cepstral coefficients was at least 5% superior to that of the AR coefficients. The improvement achieved by the cepstral method was statistically significant for all the three classifiers. Reasons for the superiority of cepstral features were investigated from the feature space and frequency domain, respectively. The cepstral coefficients owned better cluster separability in feature space and they emphasized the more informative part in the frequency domain. The discrimination rate of the MLM was the highest among three classifiers. Incorporation of the cepstral features with the MLM could reduce the misclassification rate by 10.6% when compared with the combination of AR coefficients and EDM. Proper choice of five of ten motions could further raise the recognition rate to more than 95%.