OBJECTIVE: The association between neutrophil-to-lymphocyte ratio (NLR) with subclinical macrovascular and microvascular diseases has been less investigated. We sought to examine the association between NLR and new-onset subclinical macrovascular and microvascular abnormalities in the Chinese population. METHODS: From a community cohort, we included 6,430 adults aged ≥ 40 years without subclinical macrovascular and microvascular diseases at baseline. We measured subclinical macrovascular and microvascular abnormalities separately using the ankle-brachial index (ABI), brachial-ankle pulse wave velocity (baPWV), and albuminuria. RESULTS: During a mean follow-up of 4.3 years, 110 participants developed incident abnormal ABI, 746 participants developed incident elevated baPWV, and 503 participants developed incident albuminuria. Poisson regression analysis indicated that NLR was significantly associated with an increased risk of new-onset abnormal ABI, elevated baPWV, and albuminuria. Compared to overweight/obese participants, we found a much stronger association between NLR and subclinical vascular abnormalities in participants with normal weight. Furthermore, we found an interaction between the NLR and body mass index (BMI) on the risk of new-onset abnormal ABI ( P for interaction: 0.01). CONCLUSION NLR was associated with subclinical macrovascular and microvascular diseases in the Chinese population. Furthermore, in participants with normal weight, the association between NLR and subclinical vascular abnormalities was much stronger.
Adult ; Aged ; Ankle Brachial Index ; Body Mass Index ; China/epidemiology* ; Cohort Studies ; Female ; Humans ; Incidence ; Lymphocytes/cytology* ; Male ; Middle Aged ; Neutrophils/cytology* ; Poisson Distribution ; Prospective Studies ; Vascular Diseases/etiology*

Cryo-electron microscopy (cryo-EM) imaging has the unique potential to bridge the gap between cellular and molecular biology. Therefore, cryo-EM three-dimensional (3D) reconstruction has been rapidly developed in recent several years and applied widely in life science research to reveal the structures of large macromolecular assemblies and cellular complexes, which is critical to understanding their functions at all scales. Although the technical breakthrough in recent years, for example, the introduction of the direct detection device (DDD) camera and the development of cryo-EM software tools, made the three cryo-EM pioneers share the 2017 Nobel Prize, several bottleneck problems still exist that hamper the further increase of the resolution of single-particle reconstruction and hold back the application of in situ subnanometer structure determination by cryo-tomography. Radiation damage is still the key limiting factor in cryo-EM. In order to minimize the radiation damage and preserve as much resolution as possible, the imaging conditions of a low dose and weak contrast make cryo-EM images extremely noisy with very low signal-to-noise ratios (SNR), generally about 0.1. The high noise will obscure the fine details in cryo-EM images or reconstructed maps. Thus, a method to reduce the level of noise and improve the resolution has become an important issue. In this paper, we systematically reviewed and compared some robust filters in the cryo-EM field of two aspects, single-particle analysis (SPA) and cryo-electron tomography (cryo-ET), and especially studied their applications, such as, 3D reconstruction, visualization, structural analysis, and interpretation. Conventional approaches to noise reduction in cryo-EM imaging include the use of Gaussian, median, and bilateral filters, among other means. A Gaussian filter selects an appropriate filter kernel to conduct spatial convolution with a noisy image. Although noise with larger standard deviations in cryo-EM images can be suppressed and satisfactory performance is achieved in certain cases, this filter also blurs the images and over-smooths small-scale image features. This is especially detrimental when precise quantitative information needs to be extracted. Unlike a Gaussian filter, a median filter is based on the order statistics of the image and selects the median intensity in a window of the adjacent pixels to denoise the image. Although this filter is robust to outliers, it suffers from aliasing problems that possibly result in incorrect information for cryo-EM structure interpretation. A bilateral filter is a nonlinear filter that performs spatial weighted averaging and is more selective in the pixels allowing to contribute to the weighted sum, excluding the high frequency noise from the smoothing process. Thus, this filter can be used to smooth out noise while maintaining the edge details, which is similar to an anisotropic diffusion filter, and distinct from a Gaussian filter but its utility will be limited when the SNR of a cryo-EM image is very low. Generally, spatial filtering methods have the disadvantage of losing image resolution when reducing noise. A wavelet transform can exploit the wavelet's natural ability to separate a signal from noise at multiple image scales to allow for joint resolution in both the spatial and frequency domains, and thus has the potential to outperform existing methods. The modified wavelet shrinkage filter we developed can offer a remarkable improvement in image quality with a good compromise between detail preservation and noise smoothing. We expect that our review study on different filters can provide benefits to cryo-EM applications and the interpretation of biological structures.
Algorithms ; Cryoelectron Microscopy ; Image Processing, Computer-Assisted ; Normal Distribution ; Signal-To-Noise Ratio ; Tomography, X-Ray Computed

Vision is an important way for human beings to interact with the outside world and obtain information. In order to research human visual behavior under different conditions, this paper uses a Gaussian mixture-hidden Markov model (GMM-HMM) to model the scanpath, and proposes a new model optimization method, time-shifting segmentation (TSS). The TSS method can highlight the characteristics of the time dimension in the scanpath, improve the pattern recognition results, and enhance the stability of the model. In this paper, a linear discriminant analysis (LDA) method is used for multi-dimensional feature pattern recognition to evaluates the rationality and the accuracy of the proposed model. Four sets of comparative trials were carried out for the model evaluation. The first group applied the GMM-HMM to model the scanpath, and the average accuracy of the classification could reach 0.507, which is greater than the opportunity probability of three classification (0.333). The second set of trial applied TSS method, and the mean accuracy of classification was raised to 0.610. The third group combined GMM-HMM with TSS method, and the mean accuracy of classification reached 0.602, which was more stable than the second model. Finally, comparing the model analysis results with the saccade amplitude (SA) characteristics analysis results, the modeling analysis method is much better than the basic information analysis method. Via analyzing the characteristics of three types of tasks, the results show that the free viewing task have higher specificity value and a higher sensitivity to the cued object search task. In summary, the application of GMM-HMM model has a good performance in scanpath pattern recognition, and the introduction of TSS method can enhance the difference of scanpath characteristics. Especially for the recognition of the scanpath of search-type tasks, the model has better advantages. And it also provides a new solution for a single state eye movement sequence.
Algorithms ; Discriminant Analysis ; Eye Movements ; Humans ; Markov Chains ; Normal Distribution ; Probability

Climate change has been referred to as one of the greatest threats to human health, with reports citing likely increases in extreme meteorological events. In this study, we estimated the relationships between temperature and outpatients at a major hospital in Qingdao, China, during 2015-2017, and assessed the morbidity burden. The results showed that both low and high temperatures were associated with an increased risk of outpatient visits. High temperatures were responsible for more morbidity than low temperatures, with an attributed fraction (AF) of 16.86%. Most temperature-related burdens were attributed to moderate cold and hot temperatures, with AFs of 5.99% and 14.44%, respectively, with the young (0-17) and male showing greater susceptibility. The results suggest that governments should implement intervention measures to reduce the adverse effects of non-optimal temperatures on public health-especially in vulnerable groups.
Adolescent ; Adult ; Aged ; Aged, 80 and over ; Ambulatory Care/statistics & numerical data* ; Cardiovascular Diseases/therapy* ; Child ; Child, Preschool ; China/epidemiology* ; Cold Temperature/adverse effects* ; Cost of Illness ; Digestive System Diseases/therapy* ; Facilities and Services Utilization/statistics & numerical data* ; Female ; Hot Temperature/adverse effects* ; Humans ; Infant ; Infant, Newborn ; Male ; Middle Aged ; Poisson Distribution ; Respiratory Tract Diseases/therapy* ; Risk Factors ; Young Adult

Heart sound segmentation is a key step before heart sound classification. It refers to the processing of the acquired heart sound signal that separates the cardiac cycle into systolic and diastolic, etc. To solve the accuracy limitation of heart sound segmentation without relying on electrocardiogram, an algorithm based on the duration hidden Markov model (DHMM) was proposed. Firstly, the heart sound samples were positionally labeled. Then autocorrelation estimation method was used to estimate cardiac cycle duration, and Gaussian mixture distribution was used to model the duration of sample-state. Next, the hidden Markov model (HMM) was optimized in the training set and the DHMM was established. Finally, the Viterbi algorithm was used to track back the state of heart sounds to obtain S
Algorithms ; Electrocardiography ; Heart Sounds ; Markov Chains ; Normal Distribution

In clinic, intima and media thickness are the main indicators for evaluating the development of atherosclerosis. At present, these indicators are measured by professional doctors manually marking the boundaries of the inner and media on B-mode images, which is complicated, time-consuming and affected by many artificial factors. A grayscale threshold method based on Gaussian Mixture Model (GMM) clustering is therefore proposed to detect the intima and media thickness in carotid arteries from B-mode images in this paper. Firstly, the B-mode images are clustered based on the GMM, and the boundary between the intima and media of the vessel wall is then detected by the gray threshold method, and finally the thickness of the two is measured. Compared with the measurement technique using the gray threshold method directly, the clustering of B-mode images of carotid artery solves the problem of gray boundary blurring of inner and middle membrane, thereby improving the stability and detection accuracy of the gray threshold method. In the clinical trials of 120 healthy carotid arteries, means of 4 manual measurements obtained by two experts are used as reference values. Experimental results show that the normalized root mean square errors (NRMSEs) of the estimated intima and media thickness after GMM clustering were 0.104 7 ± 0.076 2 and 0.097 4 ± 0.068 3, respectively. Compared with the results of the direct gray threshold estimation, means of NRMSEs are reduced by 19.6% and 22.4%, respectively, which indicates that the proposed method has higher measurement accuracy. The standard deviations are reduced by 17.0% and 21.7%, respectively, which indicates that the proposed method has better stability. In summary, this method is helpful for early diagnosis and monitoring of vascular diseases, such as atherosclerosis.
Carotid Arteries/diagnostic imaging* ; Carotid Intima-Media Thickness ; Normal Distribution ; Ultrasonography

PURPOSE: Boarding is a common problem in the emergency department (ED) and is associated with poor health care and outcome. Imam Khomeini Hospital is the main healthcare center in Urmia, a metropolis in the northwest of Iran. Due to the overcrowding and high patient load, we aim to characterize the rate, cause and consequence of boarding in the ED of this center. METHODS: All medical records of patients who presented to the ED of Imam Khomeini Hospital from August 1, 2017 to August 1, 2018 were retrospectively analyzed. Patients with uncompleted records were excluded. Boarding was defined as the inability to transfer the admitted ED patients to a downstream ward in ≥2 h after the admission order. Demographic data, boarding rate, mortality and triage levels (1-5) assessed by emergency severity index were collected and analyzed. The first present time of patients was classified into 4 ranges as 0:00-5:59, 6:00-11:59, 12:00-17:59 and 18:00-23:59. Descriptive, parametric and non-parametric statistical tests were performed and the risk of boarding was determined by Pearson Chi-square test. RESULTS: Demographic data analysis showed that 941 (58.5%) male and 667 (41.5%) female, altogether 1608 patients were included in this study. Five patients (0.3%) died. The distribution of patients with the triage levels 1-5 was respectively 79 (4.9%), 1150 (71.5%), 374 (23.3%), 4 (0.2%) and 0 (0%). Most patients were of level 2. Only 75 (4.7%) patients required intensive care. The majority of patients (84.2%) were presented at weekdays. The maximum patient load was observed between 12:00-17:59. Of the 1608 patients, 340 (21.1%) experienced boarding within a mean admission time of 13.70 h. Among the 340-boarded patients, 20.1% belonged to surgery, 12.1% to orthopedics, 10.9% to neurosurgery and 10.3% to neurology. The boarding rate was higher in females, patients requiring intensive care and those with low triage levels. Compared with the non-boarded, the boarded patients had a higher mean age. CONCLUSION The boarding rate is higher in the older and female patients. Moreover, boarding is dependent on the downstream ward sections: patients requiring surgical management experience the maximum boarding rate.
Age Factors ; Chi-Square Distribution ; Cross-Sectional Studies ; Crowding ; Emergency Service, Hospital ; Female ; Hospital Mortality ; Hospitalization/statistics & numerical data* ; Humans ; Iran ; Length of Stay ; Male ; Patient Admission ; Retrospective Studies ; Risk Assessment/methods* ; Risk Factors ; Sex Factors ; Time Factors ; Triage

OBJECTIVES: Most of the studies on the effect of heat stress on preterm birth (PTB) are conducted in temperate climates. Evidence on this effect in hot and arid countries with low and middle income is limited. This paper describes the short-term effect of exposure to the hot and cold environment on a daily number of PTB in Iran. METHODS: The daily number of PTB was obtained from all hospitals of the city. Meteorological and air pollution data from 2011 to 2017 were obtained from a metrological station in the city. A semi-parametric generalized additive model following a quasi-Poisson distribution with the distributed lag non-linear model was selected as a modeling framework for time-series analysis to simultaneously model the short-term and lagged effect of heat stress on PTB in the Sabzevar city. RESULTS: The minimum and maximum daily temperature were - 11.2 and 45.4 °C respectively. The highest risk estimate at extreme cold temperature was found for apparent temperature (relative risk (RR) 1.83; 95% CI 1.61: 2.09). This pattern was seen for both models. For extreme hot temperatures, the model with mean temperature showed the highest risk increase for both the main model and air pollution adjusted model (RR 1.36; 95% CI 1.25: 1.49). The lowest risk estimate in extremely cold conditions was found in the model with mean temperature. However, for extremely hot temperature conditions, the lowest risk estimate was found for both maximum and apparent temperature. CONCLUSION Obstetricians working in semi-arid areas should be aware of the influence of environmental extreme temperature on the incidence of PTB.
Air Pollutants ; analysis ; Climate ; Cold Temperature ; adverse effects ; Environmental Exposure ; adverse effects ; Environmental Monitoring ; methods ; Female ; Hospital Records ; Hot Temperature ; adverse effects ; Humans ; Infant, Newborn ; Iran ; epidemiology ; Poisson Distribution ; Pregnancy ; Premature Birth ; etiology ; Risk Factors

Oral teeth image segmentation plays an important role in teeth orthodontic surgery and implant surgery. As the tooth roots are often surrounded by the alveolar, the molar's structure is complex and the inner pulp chamber usually exists in tooth, it is easy to over-segment or lead to inner edges in teeth segmentation process. In order to further improve the segmentation accuracy, a segmentation algorithm based on local Gaussian distribution fitting and edge detection is proposed to solve the above problems. This algorithm combines the local pixels' variance and mean values, which improves the algorithm's robustness by incorporating the gradient information. In the experiment, the root is segmented precisely in cone beam computed tomography (CBCT) teeth images. Segmentation results by the proposed algorithm are then compared with the classical algorithms' results. The comparison results show that the proposed method can distinguish the root and alveolar around the root. In addition, the split molars can be segmented accurately and there are no inner contours around the pulp chamber.
Algorithms ; Computers ; Cone-Beam Computed Tomography ; Humans ; Image Processing, Computer-Assisted ; Normal Distribution ; Tooth ; diagnostic imaging ; Tooth Root ; diagnostic imaging

In data analysis, given that various statistical methods assume that the distribution of the population data is normal distribution, it is essential to check and test whether or not the data satisfy the normality requirement. Although the analytical methods vary depending on whether or not the normality is satisfied, inconsistent results might be obtained depending on the analysis method used. In many clinical research papers, the results are presented and interpreted without checking or testing normality. According to the central limit theorem, the distribution of the sample mean satisfies the normal distribution when the number of samples is above 30. However, in many clinical studies, due to cost and time restrictions during data collection, the number of samples is frequently lower than 30. In this case, a proper statistical analysis method is required to determine whether or not the normality is satisfied by performing a normality test. In this regard, this paper discusses the normality check, several methods of normality test, and several statistical analysis methods with or without normality checks.
Data Collection ; Methods ; Normal Distribution ; Statistics as Topic