Atrial functional mitral regurgitation (AFMR) is mitral regurgitation in patients with atrial fibrillation (AF), whose left atrium (LA) is enlarged, the left ventricle is not enlarged or only slightly enlarged, the left ventricular ejection fraction is preserved, and the mitral valve itself has no apparent lesion. At present, the etiology, pathophysiology and mechanism of this disease have not been completely clear yet. Existing studies have found that the causes of AFMR mainly include AF, enlargement of LA and mitral annulus, destruction of mitral annular shape, inability of mitral valve remodeling to compensate for mitral annular expansion, and hamstringing of the posterior mitral leaflet by atriogenic tethering. AFMR is demonstrated to be associated with an increased risk of mortality and readmission due to heart failure. Therefore, it serves as a primary therapeutic target for patients with heart failure and AF. However, the optimal treatment of AFMR still remains controversial. Therefore, this article will mainly expound the current definition, etiology, pathophysiological mechanism, treatment, and prognosis of AFMR.
This article reviews the development and progress in the field of limb salvage treatment, surgical techniques, and function reconstruction of pelvic malignant tumors in China in the past 30 years. Based on the surgical classification of pelvic tumor resection in different parts, the development of surgical techniques and bone defect repair and reconstruction methods were described in detail. In recent years, in view of the worldwide problem of biological reconstruction after pelvic tumor resection, Chinese researchers have systematically proposed the repair and reconstruction methods and prosthesis design for bone defects after resection of different parts for the first time in the world. In addition, a systematic surgical classification (Beijing classification) was first proposed for the difficult situation of pelvic tumors involving the sacrum, as well as the corresponding surgical plan and repair and reconstruction methods. Through unremitting efforts, the limb salvage rate of pelvic malignant tumors in China has reached more than 80%, which has preserved limbs and restored walking function for the majority of patients, greatly reduced surgical complications, and achieved internationally remarkable results.
The experimental models of chronic hepatic lesion of 40 rabbits were made by intra-abdominal injection of thioacetamide.The chronic hepatic lesion was confirmed by pathological examination and hepatectomies were performed in accordance with different measurements on each rabbit.The observations included indocyanine green retention rate,hepatic resection volume,and the outcomes of operations.The results showed that the mortality was correlative with the change of hepatic functions in the background of chronic hepatic lesion.The indocyanine green retention and the level of serum albumin are important parameters to indicate hepatic impairment.When the former was over 40% or the latter below 2.8g% the operative danger was high and the mortality was over 50%.In accordance with the classification of hepatic function,the preoperative functional state of liver were classified:grade A,B and C.the mortality of posthepatectomy were respectively 16.7%,3O%,and 72%.The multiple progressive regression equation is employed for calculating the postoperative outcome.The equation predicted the postoperative outcome with 88.9% accuracy.
The main shortcomings of using electrocortical stimulation (ECS) in identifying the motor functional area around the focus in neurosurgery are certainly time-consuming, possibly cerebral cortex injuring and perhaps triggering epilepsy. To solve these problems, we in our research presented an intraoperative motor cortex functional mapping based on electrocorticography (ECoG). At first, using power spectrum estimation, we analyzed the characteristic of ECoG which was related to move task, and selected Mu rhythm as the move-related feature. Then we extracted the feature from original ECoG by multi-resolution wavelet analysis. By calculating the sum value of feature in every channel and observing the distribution of these sum values, we obtained the correlation between the cortex area under the electrode and motor cortex functional area. The results showed that the distribution of the relationship between the cortex under the electrode and motor cortex functional area was almost consistent with those identified by ECS which was called as ‘the gold-standard’. It indicated that this method was basically feasible, and it just needed five minutes totally. In conclusion, ECoG-based and passive identification of motor cortical function may serve as a useful adjunct to ECS in the intraoperative mapping.
Although attention plays an important role in cognitive and perception, there is no simple way to measure one's attention abilities. We identified that the strength of brain functional network in sustained attention task can be used as the physiological indicator to predict behavioral performance. Behavioral and electroencephalogram (EEG) data from 14 subjects during three force control tasks were collected in this paper. The reciprocal of the product of force tolerance and variance were used to calculate the score of behavioral performance. EEG data were used to construct brain network connectivity by wavelet coherence method and then correlation analysis between each edge in connectivity matrices and behavioral score was performed. The linear regression model combined those with significantly correlated network connections into physiological indicator to predict participant's performance on three force control tasks, all of which had correlation coefficients greater than 0.7. These results indicate that brain functional network strength can provide a widely applicable biomarker for sustained attention tasks.
Objective To discuss the surgical procedures and curative effect of stiff 2-5 metacarpophalangeal (MP) joints after crash injury in hand. Methods Between January 2006 and June 2009, 7 cases of stiff 2-5 MP joints were treated by releasing the stiff MP joints and reconstructing the function of lumbrical muscle in one stage. There were 6 males and 1 female with an average age of 32 years (range, 18-56 years). All injuries were caused by crash. Six cases suffered from multiple metacarpal fracture or complex dislocation of MP joint and 1 case suffered from complete amputation at level of middle palm of hand. The interval from initial wound heal ing to hospital ization was 3 to 15 months. Before operation, the X-ray films showed fracture healed and the results of nipping paper test were positive. All hands were treated with physical therapy for 1 month. After the plaster external fixation for 6 weeks, the physical therapy and function training were given. Results All wounds healed by first intention. The patients had no joint instabil ity and extensor tendon side-sl ipping with normal finger function. Six patients were followed up from 6 months to 3 years. The extension and flexion of MP joint were 0° and 67-90°, respectively. The average grip strength of injured dominant hand reached 86.70% of normal side and non-dominant hand reached 66.70% of normal side. The average injured dominant tip pinch strength reached 83.52% of normal side and non-dominant tip pinch strength reached 61.30% of normal side. Based on total active motion (TAM) system of Chinese Medical Association for Hand Surgery, the results were excellent in 4 cases, good in 1 case, and fair in 1 case; the excellent and good rate was 83.33%. Conclusion In patients with stiff MP joint and lumbrical muscle defect, releasing stiff MP joint and reconstructing lumbrical function in one stage can recover the function of MP joint and achieve good outcome. Physical therapy plays an important role before operation.
New functional evaluation methods for coronary artery lesions have received widespread attention at home and abroad. As a new functional evaluation technique, the clinical value of quantitative flow ratio (QFR) in the accuracy and feasibility of diagnosing myocardial ischemia caused by coronary artery stenosis has been confirmed in many clinical trials. Compared with the traditional gold standard fractional flow reserve (FFR) for diagnosing coronary artery stenosis, QFR has the advantages of simple operation, time-saving and low cost. This article reviews the comparison of the diagnostic accuracy of FFR and QFR and the progress of clinical research, aiming to explore whether QFR may replace FFR as a functional evaluation method of coronary artery disease and guide clinical blood circulation reconstruction.
Flexible conductive fibers have been widely applied in wearable flexible sensing. However, exposed wearable flexible sensors based on liquid metal (LM) are prone to abrasion and significant conductivity degradation. This study presented a high-sensitivity LM conductive fiber with integration of strain sensing, electrical heating, and thermochromic capabilities, which was fabricated by coating eutectic gallium-indium (EGaIn) onto spandex fibers modified with waterborne polyurethane (WPU), followed by thermal curing to form a protective polyurethane sheath. This fiber, designated as Spandex/WPU/EGaIn/Polyurethane (SWEP), exhibits a four-layer coaxial structure: spandex core, WPU modification layer, LM conductive layer, and polyurethane protective sheath. The SWEP fiber had a diameter of (458.3 ± 10.4) μm, linear density of (2.37 ± 0.15) g/m, and uniform EGaIn coating. The fiber had excellent conductivity with an average value of (3 716.9 ± 594.2) S/m. The strain sensing performance was particularly noteworthy. A 5 cm × 5 cm woven fabric was fabricated using polyester warp yarns and SWEP weft yarns. The fabric exhibited satisfactory moisture permeability [(536.06 ± 33.15) g/(m2·h)] and maintained stable thermochromic performance after repeated heating cycles. This advanced conductive fiber development is expected to significantly promote LM applications in wearable electronics and smart textile systems.
How to extract high discriminative features that help classification from complex resting-state fMRI (rs-fMRI) data is the key to improving the accuracy of brain disease recognition such as schizophrenia. In this work, we use a weighted sparse model for brain network construction, and utilize the Kendall correlation coefficient (KCC) to extract the discriminative connectivity features for schizophrenia classification, which is conducted with the linear support vector machine. Experimental results based on the rs-fMRI of 57 schizophrenia patients and 64 healthy controls show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 81.82%) than other competing methods. Specifically, compared with the traditional network construction methods (Pearson’s correlation and sparse representation) and the commonly used feature selection methods (two-sample t-test and Least absolute shrinkage and selection operator (Lasso)), the algorithm proposed in this paper can more effectively extract the discriminative connectivity features between the schizophrenia patients and the healthy controls, and further improve the classification accuracy. At the same time, the discriminative connectivity features extracted in the work could be used as the potential clinical biomarkers to assist the identification of schizophrenia.
Brain functional network changes over time along with the process of brain development, disease, and aging. However, most of the available measurements for evaluation of the difference (or similarity) between the individual brain functional networks are for charactering static networks, which do not work with the dynamic characteristics of the brain networks that typically involve a long-span and large-scale evolution over the time. The current study proposes an index for measuring the similarity of dynamic brain networks, named as dynamic network similarity (DNS). It measures the similarity by combining the “evolutional” and “structural” properties of the dynamic network. Four sets of simulated dynamic networks with different evolutional and structural properties (varying amplitude of changes, trend of changes, distribution of connectivity strength, range of connectivity strength) were generated to validate the performance of DNS. In addition, real world imaging datasets, acquired from 13 stroke patients who were treated by transcranial direct current stimulation (tDCS), were used to further validate the proposed method and compared with the traditional similarity measurements that were developed for static network similarity. The results showed that DNS was significantly correlated with the varying amplitude of changes, trend of changes, distribution of connectivity strength and range of connectivity strength of the dynamic networks. DNS was able to appropriately measure the significant similarity of the dynamics of network changes over the time for the patients before and after the tDCS treatments. However, the traditional methods failed, which showed significantly differences between the data before and after the tDCS treatments. The experiment results demonstrate that DNS may robustly measure the similarity of evolutional and structural properties of dynamic networks. The new method appears to be superior to the traditional methods in that the new one is capable of assessing the temporal similarity of dynamic functional imaging data.