This study aims to determine the salient brain regions with abnormal changes in white matter structures from diffusion tensor imaging (DTI) images of the patients with temporal lobe epilepsy (TLE), and to discriminate the patients with TLE from normal controls (NCs). Firstly, the DTI images from 50 subjects (28 NCs and 22 TLE) were acquired. Secondly, the four measures including the fractional anisotropy (FA), the mean diffusivity (MD), the axial diffusivity (AD) and the radial diffusivity (RD) were calculated. Thirdly, the tract-based spatial statistics (TBSS) was adopted to extract the measures in brain regions with significant differences between the two compared groups. Fourthly, the obtained measures were used as input features of the support vector machine (SVM) for classification, and the support vector machine-recursive feature elimination (SVM-RFE) was compared with the support vector machine-tract-based spatial statistics (SVM-TBSS) method. Finally, the essential brain regions and their spatial distribution were analyzed and discussed. The experimental results showed that the FA measures of the TLE group decreased significantly in the corpus callosum, superior longitudinal fasciculus, corona radiata, external capsule, internal capsule, inferior fronto-occipital fasciculus, fasciculus uncinatus and sagittal stratum, which were nearly bilaterally distributed, while the MD and RD increased significantly in most of these brain regions of the TLE group. Although the AD also increased, the differences were not statistically significant. The SVM-TBSS classifier obtained accuracies of 82%, 76% and 76% using the FA, MD and RD for classification, respectively, and 80% using combined measures. The SVM-RFE classifier obtained accuracies of 90%, 90% and 92% using the FA, MD and RD respectively, while the highest accuracy was 100% using combined measures. These results demonstrated that the SVM-RFE outperformed the SVM-TBSS, and the dominant characteristic influencing classification in brain regions were in associative and commissural fibers. These results illustrated that the measures of DTI images could reveal the abnormal changes in white matter structure of patients with TLE, providing effective information to clarify its pathological mechanism, localize the focus and diagnose automatically.
Objective To investigate the pathological mechanism of epileptic comorbid sleep disorder by analyzing the changes of cerebral white matter diffusion tensor in patients with sleep disorder with negative magnetic resonance imaging (MRI) epilepsy based on the method of tract-based spatial statistics (TBSS). Methods MRI negative epilepsy patients comorbid sleep disorder who were epileptic patients treated l in China-Japan Union Hospital of Jilin University from January 2020 to December 2022 completed the Epworth sleepiness scale (ESS) and Pittsburgh sleep quality index (PSQI) tests, and those who complained of sleep disorder and PSQI index ≥11 were monitored by nighttime polysomnography (PSG) and those with objective sleep disorder confirmed by PSG were included in the epilepsy comorbid sleep disorder group. Healthy volunteers with matching gender, age, education were included in the health control group. Diffusion tensor image ( DTI) was collected for all subjects by using a 3.0T magnetic resonance scanner. Diffusion parameters were compared between the two groups using TBSS. Results This study included 36 epilepsy patients comorbid sleep disorder and 35 healthy volunteers. epilepsy patients comorbid sleep disorder showed significantly lower fraction anisotropy (FA) (P<0.05) and significantly higher mean diffusivity (MD) (P<0.05) than the health control group . Brain regions with statistical differences in FA reduction included middle peduncle of cerebellum, genu of corpus callosum, body of corpus callosum, splenium of corpus callosum, anterior corona radiata, external capsule and right posterior thalamic radiation.Brain regions with statistical differences in MD degradation included genu of corpus callosum, body of corpus callosum, anterior limb of internal capsule, anterior corona radiata, superior corona radiata, external capsule and right posterior limb of internal capsul. Conclusion Patients with epilepsy comorbidities with sleep disorders have widespread and symmetric white matter damage.The white matter damage is concentrated in the front of the brain.
The phase-locking relationship between the firings of neuronal action potentials (i.e., spikes) and the oscillations of local field potentials (LFP) reflects important neural coding information. However, the present analysis methods can only determine whether there has phase-locking, but not the different strengths among various types of phase-locking. In the present paper, we used spike-triggered average (STA) signals and the percentage ratio (named φ) of the STA power to the power of original LFP as an index to evaluate the strengths of phase-locking. Experimental recordings obtained from rat hippocampal CA1 region as well as simulation data were used to evaluate the method. The results showed that the index φ changed monotonically as a function of the strength of phase-locking, and it could provide an effective critical value to divide phase-locking from non-phase-locking. Because the calculation of the index does not need pre-filtering, it can avoid the unwanted influences caused by intentionally limiting the frequencies of LFP oscillations such as in the traditional bin statistical method. Therefore, the index φ provides a novel method to investigate the mechanisms underlying neuronal coding in brain.
Objective To analyze the data of external fixation instruments (including Ilizarov instruments) used by QIN Sihe orthopaedic surgical team in the treatment of limb deformities in the past 30 years, and to explore the indications for the application of modern external fixation techniques in the correction of limb deformities and individual device configuration selection strategy. Methods According to QIN Sihe orthopaedic surgical team, the use of external fixator between January 1988 and December 2017 was analyzed retrospectively. The total use of external fixation and the proportion of different external fixators were analyzed in gender, different operation time, different age, different parts, and different diseases. Results External fixators were used in 8 113 patients, 69 of them were used simultaneously in both lower extremity surgery, so 8 182 external fixators were used. Among them, there were 4 725 (57.74%) combined external fixators, 3 388 (41.41%) Ilizarov circle fixators, 64 (0.78%) single arm external fixators (including Orthofix), 5 (0.06%) Taylor space external fixators. There were 4 487 males (55.31%) and 3 626 females (44.69%). According to the analysis of different time periods, the number of external fixators increased year by year, and the number of applications increased after 2000. The main age of the patients was 11-30 years old, of which 1 819 sets (22.23%) were used at the age of 21-25 years. The use of the external fixator covered almost all parts of the limbs, with the ankle and toe areas being the most common, reaching 4 664 sets (57.00%), and the upper extremities the least, with 152 sets (1.86%). The 8 113 cases covered more than a dozen disciplines and more than 150 kinds of diseases. The top 5 diseases were poliomyelitis sequelae, cerebral palsy, deformity of lower extremity after spina bifida, traumatic sequelae, and congenital equinovarus foot. Conclusion Ilizarov technique has been widely used in extremity deformity, disability, and complicated orthopedic diseases caused by vascular, lymphoid, nerve, skin, endocrine, and other diseases. The indication of operation is far beyond the scope of orthopedics. The domestic external fixator and its mounting tools can basically meet the requirements of various treatments. The technique of external fixation has entered a new era of tension tissue regeneration under stress control, natural repair of tissue trauma and deformity, and reconstruction of limb function.
Statistical analysis of clinical trials has traditionally relied on frequentist methods, but Bayesian statistics has attracted considerable attention from regulators and researchers in recent years due to its unique advantages, and its use in clinical trials is increasing. Despite the obvious advantages of Bayesian statistics, the complexity of its design, implementation and analysis poses a number of challenges to its practical application, which may lead to an increased risk of unregulated use. This study aims to comprehensively sort out the application scenarios, common methods, special considerations and key elements of reporting of Bayesian statistical methods in clinical trials, with the aim of providing researchers with references for conducting Bayesian clinical trials, and promoting the scientific and rational application of Bayesian statistical methods in clinical trials.
The key for performing meta-analysis using WinBUGS software is to construct a model of Bayesian statistics. The hand-written code model and Doodle model are two major methods for constructing it. The approach of hand-written code is flexible and convenient, but the language programming is fallibility. The Doodle is complicated, but it is benefit to understand the structure of hand-written code model and prevent error. This article briefly describes how to construct the Doodle model for binary and continuous data of head to head meta-analysis, indirect comparison and network meta-analysis, and ordinal variables meta-analysis.
The "bnma" package is a Bayesian network meta-analysis software package developed based on the R programming language. The network meta-analysis was performed utilizing JAGS software, which yielded relevant results and visual graphs. Moreover, this software package provides support for various data structures and types, while also providing the advantages of flexible utilization, user-friendly operation, and deliver of rich and accurate outcomes. In this paper, using a network meta-analysis example of different therapies for androgenetic alopecia, the operational process of conducting network meta-analysis using the "bnma" package is briefly introduced.
Machine learning-based diagnostic tests have certain differences of measurement indicators with traditional diagnostic tests. In this paper, we elaborate the definitions, calculation methods and statistical inferences of common measurement indicators of machine learning-based diagnosis models in detail. We hope that this paper will be helpful for clinical researchers to better evaluate machine learning diagnostic models.
There are so many biomechanical risk factors related with glaucoma and their relationship is much complex. This paper reviewed the state-of-the-art research works on glaucoma related mechanical effects. With regards to the development perspectives of studies on glaucoma biomechanics, a completely novel biomechanical evaluation factor -- Fractional Flow Reserve (FPR) for glaucoma was proposed, and developing clinical application oriented glaucoma risk assessment algorithm and application system by using the new techniques such as artificial intelligence and machine learning were suggested.
In 2025, the American Cancer Society published "Cancer statistics, 2025", which projected cancer data for the upcoming year based on incidence data collected by central cancer registries (through 2021) and mortality data obtained from the National Center for Health Statistics (through 2022). Similarly, the National Cancer Center of China released "Cancer incidence and mortality in China, 2022" in December 2024, analyzing data from 22 cancer registries across the country. This study provides a comparative analysis of cancer incidence and mortality trends in China and the United States during the same period, with a focus on sex- and age-specific distributions and long-term changes in cancer patterns. Long-term trends indicate that lung and liver cancer mortality rates in China have declined, primarily due to tobacco control measures and hepatitis B vaccination programs. However, the burden of gastric and esophageal cancers remains substantial. In the United States, mortality rates for colorectal and lung cancers have continued to decline, largely attributed to widespread screening programs and advances in immunotherapy. As economic growth and social development, China’s cancer profile is gradually shifting towards patterns observed in countries with high human development index. However, the prevention and control of upper gastrointestinal cancers remains a critical public health challenge that requires further attention.