As the most common examination tool in medical practice, chest radiography has important clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease based on chest radiography has become one of the hot topics in medical imaging research. Based on the clinical applications, the study conducts a comprehensive survey on computer-aided detection (CAD) systems, and especially focuses on the artificial intelligence technology applied in chest radiography. The paper presents several common chest X-ray datasets and briefly introduces general image preprocessing procedures, such as contrast enhancement and segmentation, and bone suppression techniques that are applied to chest radiography. Then, the CAD system in the detection of specific disease (pulmonary nodules, tuberculosis, and interstitial lung diseases) and multiple diseases is described, focusing on the basic principles of the algorithm, the data used in the study, the evaluation measures, and the results. Finally, the paper summarizes the CAD system in chest radiography based on artificial intelligence and discusses the existing problems and trends.

Background Adipose tissue-derived mesenchymal stem cells (ADSCs) are promising candidates for regenerative medicine. However, long-term in vitro passaging leads to stemness loss and cell senescence of ADSCs, resulting in failure of ADSC-based therapy. Methods In this study, ADSCs were treated with low dose of antioxidants (reduced glutathione and melatonin) with anti-aging and stem cell protection properties in the in vitro passaging, and the cell functions including stem cell senescence, cell migration, cell multidirectional differentiation potential, and ROS content were carefully analyzed. Results We found that GSH and melatonin could maintain ADSC cell functions through reducing cell senescence and promoting cell migration, as well as by preserving stemness and multidirectional differentiation potential, through inhibiting ROS generation during long-term expansion of ADSCs. Conclusions Our results suggested that antioxidant treatment could efficiently prevent the dysfunction and preserve cell functions of ADSCs after long-term passaging, providing a practical strategy to facilitate ADSC-based therapy.

Lung field segmentation in the posterior-anterior (PA) chest radiograph is important for pulmonary disease diagnosis and hemodialysis treatment. Due to high shape variation and boundary ambiguity, accurate lung field segmentation from chest radiograph is still a challenging task. To tackle these challenges, we propose a joint shape and appearance sparse learning method for robust and accurate lung field segmentation. The main contributions of this paper are: 1) a robust shape initialization method is designed to achieve an initial shape that is close to the lung boundary under segmentation; 2) a set of local sparse shape composition models are built based on local lung shape segments to overcome the high shape variations; 3) a set of local appearance models are similarly adopted by using sparse representation to capture the appearance characteristics in local lung boundary segments, thus effectively dealing with the lung boundary ambiguity; 4) a hierarchical deformable segmentation framework is proposed to integrate the scale-dependent shape and appearance information together for robust and accurate segmentation. Our method is evaluated on 247 PA chest radiographs in a public dataset. The experimental results show that the proposed local shape and appearance models outperform the conventional shape and appearance models. Compared with most of the state-of-the-art lung field segmentation methods under comparison, our method also shows a higher accuracy, which is comparable to the inter-observer annotation variation.

This paper presents a new deformable model using both populationbased and patient-specific shape statistics to segment lung fields from serial chest radiographs. First, a modified scale-invariant feature transform (SIFT) local descriptor is used to characterize the image features in the vicinity of each pixel, so that the deformable model deforms in a way that seeks for the region with similar SIFT local descriptors. Second, the deformable model is constrained by both population-based and patient-specified shape statistics. Initially, population-based shape statistics takes most of the rules when the number of serial images is small; gradually, patient-specific shape statistics takes more rules after a sufficient number of segmentation results on the same patient have been obtained. The proposed deformable model can adapt to the shape variability of different patients, and obtain more robust and accurate segmentation results.

Borneol, a natural product in the Asteraceae family, is widely used as an upper ushering drug for various brain diseases in many Chinese herbal formulae. The blood-brain barrier (BBB) plays an essential role in maintaining a stable homeostatic environment, while BBB destruction and the increasing BBB permeability are common pathological processes in many serious central nervous system (CNS) diseases, which is especially an essential pathological basis of cerebral ischemic injury. Here, we aimed to conduct a systematic review to assess preclinical evidence of borneol for experimental ischemic stroke as well as investigate in the possible neuroprotective mechanisms, which mainly focused on regulating the permeability of BBB. Seven databases were searched from their inception to July 2018. The studies of borneol for ischemic stroke in animal models were included. RevMan 5.3 was applied for data analysis. Fifteen studies investigated the effects of borneol in experimental ischemic stroke involving 308 animals were ultimately identified. The present study showed that the administration of borneol exerted a significant decrease of BBB permeability during cerebral ischemic injury according to brain Evans blue content and brain water content compared with controls (P<0.01). In addition, borneol could improve neurological function scores (NFS) and cerebral infarction area. Thus, borneol may be a promising neuroprotective agent for cerebral ischemic injury, largely through alleviating the BBB disruption, reducing oxidative reactions, inhibiting the occurrence of inflammation, inhibiting apoptosis, and improving the activity of lactate dehydrogenase (LDH) as well as P-glycoprotein (P-GP) and NO signaling pathway.

Background: Parkinson's disease (PD) is a debitlitating, chronic, progressive neurodegenerative disorder without modifying therapy. Here, we aimed to evaluate the available evidence of herbal medicine (HM) formulas for patients with PD according to randomized double-blind placebo-controlled clinical trials.Methods: HM formulas for PD were searched in eight main databases from their inception to February 2018. The methodological quality was assessed using Cochrane Collaboration risk of bias tool. Meta-analysis was performed using RevMan 5.3 software.Results: Fourteen trials with Seventeen comparisons comprising 1,311 patients were identified. Compared with placebo groups, HM paratherapy (n = 16 comparisons) showed significant better effects in the assessments of total Unified Parkinson's Disease Rating Scale (UPDRS) (WMD: −5.43, 95% CI:−8.01 to −2.86; P < 0.0001), UPDRS I (WMD: −0.30, 95% CI: −0.54 to −0.06; P = 0.02), UPDRS II (WMD: −2.21, 95% CI: −3.19 to −1.22; P < 0.0001), UPDRS III (WMD: −3.26, 95% CI:−4.36 to −2.16; P < 0.00001), Parkinson's Disease Quality of Life Questionnaire (p < 0.01) and Parkinson's Disease Questionnaire-39 (WMD: −7.65, 95% CI: −11.46 to −3.83; p < 0.0001), Non-motor Symptoms Questionnaire (p < 0.01) and Non-Motor Symptoms Scale (WMD: −9.19, 95% CI: −13.11 to −5.28; P < 0.00001), Parkinson's Disease Sleep Scale (WMD: 10.69, 95% CI: 8.86 to 12.53; P < 0.00001), and Hamilton depression rating scale (WMD: −5.87, 95% CI: −7.06 to −4.68; P < 0.00001). The efficiency of HM monotherapy (n = 1 comparison) was not superior to the placebo according to UPDRS II, UPDRS III and total UPDRS score in PD patients who never received levodopa treatment, all P > 0.05. HM formulas paratherapy were generally safe and well tolerated for PD patients (RR: 0.41, 95% CI: 0.21 to 0.80; P = 0.009).Conclusion: The findings of present study supported the complementary use of HM paratherapy for PD patients, whereas the question on the efficacy of HM monotherapy in alleviating PD symptoms is still open.

Background: Ischemia stroke is known as the major cause of morbidity and mortality. Buyang Huanwu Decoction (BHD), a classical traditional Chinese medicine (TCM) formula, has been used to prevent and treat stoke for hundreds of years. The purpose of present study is to investigate the effects of BHD on angiogenesis in rats after cerebral ischemia/reperfusion (I/R) injury targeting Silent information regulator 1 (SIRT1) / Vascular endothelial growth factor (VEGF) pathway.Methods: The cerebral I/R injury model was induced by middle cerebral artery occlusion (MCAO). Adult Sprag-Dawley (SD) rats were randomly divided into five groups: sham group, normal saline (NS) group, BHD group, BHD+EX527 (SIRT1 specific inhibitor) group, and NS+EX527 group. Each group was divided into the subgroups according to 1, 3, 7, or 14 days time-point after cerebral ischemia/reperfusion, respectively. Neurological function score (NFS) was evaluated by the Rogers scale; microvascular density (MVD) in brain tissue around infarction area was observed by immunofluorescence; and the expression of SIRT1 and VEGF was assessed by Western Blot and Quantitative Real-time-PCR.Results: BHD can significantly improve NFS (P < 0.05), increase the MVD in the boundary ischemic area (P < 0.01) and elevate the expression of protein and mRNA of SIRT1 and VEGF following I/R injury (P < 0.01). In contrast, treatment with EX527 reversed the BHD-induced improvements in NFS (P < 0.01) and decreased the MVD (P < 0.01) and the expression of SIRT1 and VEGF (P < 0.05).Conclusion: BHD exerts neuroprotection targeting angiogenesis through the up-regulation of SIRT1/VEGF pathway against cerebral ischemic injury in rats.

The purpose of this study was to analyze prognostic factors for ovarian metastases from primary gastric cancer, helping establish optimal strategy in ameliorating survival for this entity. Clinical data of 68 consecutive patients histologically diagnosed with ovarian metastases from primary gastric cancer were accrued from 1096 cases with female gastric cancer. Metachronous surgery was performed on 36 patients and 32 received synchronous surgery. There were 14 patients treated with surgery alone and 54 with combined modality therapy. After the median follow-up time of 9.1 months, the median survival time (MST) of 12.4 months was observed for all patients. Patients treated with synchronous surgery tended to have an inferior survival compared with those treated with metachronous surgery (MST: 10.9 vs 14.3 months; P = 0.100). Combined modality showed a significantly better MST compared with surgery alone (13.6 vs 7.9 months; P = 0.004). Chemotherapy cycles (more than four or less than or equal to four) were found to have an impact on survival (MST: 14.3 vs 9.4 months; P = 0.031). Peritoneal metastases, lymphovascular involvement, and unilateral ovarian metastasectomy were independent unfavorable prognostic factors. Combined modality therapy as primary therapy resulted in good outcome, and more aggressive chemotherapy (more than four cycles) was accompanied by an improvement in survival. Innovative systemic treatments need to be explored in treatment of peritoneal metastases and lymphovascular involvement. Bilateral oophorectomy was considered when ovarian metastases were histologically diagnosed.